From 890a4688ad30a40b2d9ddcdb86a05e4c77055a99 Mon Sep 17 00:00:00 2001
From: Francesco Murdaca <fmurdaca@redhat.com>
Date: Tue, 29 Sep 2020 15:48:21 +0200
Subject: [PATCH] Adjust scaling issues and saving

Signed-off-by: Francesco Murdaca <fmurdaca@redhat.com>
---
 Pipfile                                       |    3 +-
 Pipfile.lock                                  |  765 ++++--
 ...Detection-using-TF-and-Deep-Learning.ipynb | 2204 +++++++++++------
 3 files changed, 2105 insertions(+), 867 deletions(-)

diff --git a/Pipfile b/Pipfile
index 9944849..b8cdc46 100644
--- a/Pipfile
+++ b/Pipfile
@@ -4,12 +4,13 @@ verify_ssl = true
 name = "pypi"
 
 [packages]
-tensorflow = "==2.2.0"
+tensorflow = "==2.3.0"
 pandas = "*"
 matplotlib = "*"
 numpy = "*"
 scikit-learn = "*"
 seaborn = "*"
+jupyter = "*"
 
 [dev-packages]
 
diff --git a/Pipfile.lock b/Pipfile.lock
index 9ee38e5..4d7aa79 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "882c51fb4e2b98c6d5c302b38903acca334cef38a59e3bab5e93060b85b49ea2"
+            "sha256": "c2726b817711057d17090eed0eaab9b0b497f2273b46f21818f25e0c5b959b09"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -23,6 +23,27 @@
             ],
             "version": "==0.10.0"
         },
+        "argon2-cffi": {
+            "hashes": [
+                "sha256:05a8ac07c7026542377e38389638a8a1e9b78f1cd8439cd7493b39f08dd75fbf",
+                "sha256:0bf066bc049332489bb2d75f69216416329d9dc65deee127152caeb16e5ce7d5",
+                "sha256:18dee20e25e4be86680b178b35ccfc5d495ebd5792cd00781548d50880fee5c5",
+                "sha256:392c3c2ef91d12da510cfb6f9bae52512a4552573a9e27600bdb800e05905d2b",
+                "sha256:57358570592c46c420300ec94f2ff3b32cbccd10d38bdc12dc6979c4a8484fbc",
+                "sha256:6678bb047373f52bcff02db8afab0d2a77d83bde61cfecea7c5c62e2335cb203",
+                "sha256:6ea92c980586931a816d61e4faf6c192b4abce89aa767ff6581e6ddc985ed003",
+                "sha256:77e909cc756ef81d6abb60524d259d959bab384832f0c651ed7dcb6e5ccdbb78",
+                "sha256:7d455c802727710e9dfa69b74ccaab04568386ca17b0ad36350b622cd34606fe",
+                "sha256:9bee3212ba4f560af397b6d7146848c32a800652301843df06b9e8f68f0f7361",
+                "sha256:9dfd5197852530294ecb5795c97a823839258dfd5eb9420233c7cfedec2058f2",
+                "sha256:b160416adc0f012fb1f12588a5e6954889510f82f698e23ed4f4fa57f12a0647",
+                "sha256:ba7209b608945b889457f949cc04c8e762bed4fe3fec88ae9a6b7765ae82e496",
+                "sha256:cc0e028b209a5483b6846053d5fd7165f460a1f14774d79e632e75e7ae64b82b",
+                "sha256:d8029b2d3e4b4cea770e9e5a0104dd8fa185c1724a0f01528ae4826a6d25f97d",
+                "sha256:da7f0445b71db6d3a72462e04f36544b0de871289b0bc8a7cc87c0f5ec7079fa"
+            ],
+            "version": "==20.1.0"
+        },
         "astunparse": {
             "hashes": [
                 "sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872",
@@ -30,6 +51,37 @@
             ],
             "version": "==1.6.3"
         },
+        "async-generator": {
+            "hashes": [
+                "sha256:01c7bf666359b4967d2cda0000cc2e4af16a0ae098cbffcb8472fb9e8ad6585b",
+                "sha256:6ebb3d106c12920aaae42ccb6f787ef5eefdcdd166ea3d628fa8476abe712144"
+            ],
+            "markers": "python_version >= '3.5'",
+            "version": "==1.10"
+        },
+        "attrs": {
+            "hashes": [
+                "sha256:26b54ddbbb9ee1d34d5d3668dd37d6cf74990ab23c828c2888dccdceee395594",
+                "sha256:fce7fc47dfc976152e82d53ff92fa0407700c21acd20886a13777a0d20e655dc"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
+            "version": "==20.2.0"
+        },
+        "backcall": {
+            "hashes": [
+                "sha256:5cbdbf27be5e7cfadb448baf0aa95508f91f2bbc6c6437cd9cd06e2a4c215e1e",
+                "sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255"
+            ],
+            "version": "==0.2.0"
+        },
+        "bleach": {
+            "hashes": [
+                "sha256:52b5919b81842b1854196eaae5ca29679a2f2e378905c346d3ca8227c2c66080",
+                "sha256:9f8ccbeb6183c6e6cddea37592dfb0167485c1e3b13b3363bc325aa8bda3adbd"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
+            "version": "==3.2.1"
+        },
         "cachetools": {
             "hashes": [
                 "sha256:513d4ff98dd27f85743a8dc0e92f55ddb1b49e060c2d5961512855cda2c01a98",
@@ -45,6 +97,47 @@
             ],
             "version": "==2020.6.20"
         },
+        "cffi": {
+            "hashes": [
+                "sha256:005f2bfe11b6745d726dbb07ace4d53f057de66e336ff92d61b8c7e9c8f4777d",
+                "sha256:09e96138280241bd355cd585148dec04dbbedb4f46128f340d696eaafc82dd7b",
+                "sha256:0b1ad452cc824665ddc682400b62c9e4f5b64736a2ba99110712fdee5f2505c4",
+                "sha256:0ef488305fdce2580c8b2708f22d7785ae222d9825d3094ab073e22e93dfe51f",
+                "sha256:15f351bed09897fbda218e4db5a3d5c06328862f6198d4fb385f3e14e19decb3",
+                "sha256:22399ff4870fb4c7ef19fff6eeb20a8bbf15571913c181c78cb361024d574579",
+                "sha256:23e5d2040367322824605bc29ae8ee9175200b92cb5483ac7d466927a9b3d537",
+                "sha256:2791f68edc5749024b4722500e86303a10d342527e1e3bcac47f35fbd25b764e",
+                "sha256:2f9674623ca39c9ebe38afa3da402e9326c245f0f5ceff0623dccdac15023e05",
+                "sha256:3363e77a6176afb8823b6e06db78c46dbc4c7813b00a41300a4873b6ba63b171",
+                "sha256:33c6cdc071ba5cd6d96769c8969a0531be2d08c2628a0143a10a7dcffa9719ca",
+                "sha256:3b8eaf915ddc0709779889c472e553f0d3e8b7bdf62dab764c8921b09bf94522",
+                "sha256:3cb3e1b9ec43256c4e0f8d2837267a70b0e1ca8c4f456685508ae6106b1f504c",
+                "sha256:3eeeb0405fd145e714f7633a5173318bd88d8bbfc3dd0a5751f8c4f70ae629bc",
+                "sha256:44f60519595eaca110f248e5017363d751b12782a6f2bd6a7041cba275215f5d",
+                "sha256:4d7c26bfc1ea9f92084a1d75e11999e97b62d63128bcc90c3624d07813c52808",
+                "sha256:529c4ed2e10437c205f38f3691a68be66c39197d01062618c55f74294a4a4828",
+                "sha256:6642f15ad963b5092d65aed022d033c77763515fdc07095208f15d3563003869",
+                "sha256:85ba797e1de5b48aa5a8427b6ba62cf69607c18c5d4eb747604b7302f1ec382d",
+                "sha256:8f0f1e499e4000c4c347a124fa6a27d37608ced4fe9f7d45070563b7c4c370c9",
+                "sha256:a624fae282e81ad2e4871bdb767e2c914d0539708c0f078b5b355258293c98b0",
+                "sha256:b0358e6fefc74a16f745afa366acc89f979040e0cbc4eec55ab26ad1f6a9bfbc",
+                "sha256:bbd2f4dfee1079f76943767fce837ade3087b578aeb9f69aec7857d5bf25db15",
+                "sha256:bf39a9e19ce7298f1bd6a9758fa99707e9e5b1ebe5e90f2c3913a47bc548747c",
+                "sha256:c11579638288e53fc94ad60022ff1b67865363e730ee41ad5e6f0a17188b327a",
+                "sha256:c150eaa3dadbb2b5339675b88d4573c1be3cb6f2c33a6c83387e10cc0bf05bd3",
+                "sha256:c53af463f4a40de78c58b8b2710ade243c81cbca641e34debf3396a9640d6ec1",
+                "sha256:cb763ceceae04803adcc4e2d80d611ef201c73da32d8f2722e9d0ab0c7f10768",
+                "sha256:cc75f58cdaf043fe6a7a6c04b3b5a0e694c6a9e24050967747251fb80d7bce0d",
+                "sha256:d80998ed59176e8cba74028762fbd9b9153b9afc71ea118e63bbf5d4d0f9552b",
+                "sha256:de31b5164d44ef4943db155b3e8e17929707cac1e5bd2f363e67a56e3af4af6e",
+                "sha256:e66399cf0fc07de4dce4f588fc25bfe84a6d1285cc544e67987d22663393926d",
+                "sha256:f0620511387790860b249b9241c2f13c3a80e21a73e0b861a2df24e9d6f56730",
+                "sha256:f4eae045e6ab2bb54ca279733fe4eb85f1effda392666308250714e01907f394",
+                "sha256:f92cdecb618e5fa4658aeb97d5eb3d2f47aa94ac6477c6daf0f306c5a3b9e6b1",
+                "sha256:f92f789e4f9241cd262ad7a555ca2c648a98178a953af117ef7fad46aa1d5591"
+            ],
+            "version": "==1.14.3"
+        },
         "chardet": {
             "hashes": [
                 "sha256:84ab92ed1c4d4f16916e05906b6b75a6c0fb5db821cc65e70cbd64a3e2a5eaae",
@@ -59,6 +152,29 @@
             ],
             "version": "==0.10.0"
         },
+        "decorator": {
+            "hashes": [
+                "sha256:41fa54c2a0cc4ba648be4fd43cff00aedf5b9465c9bf18d64325bc225f08f760",
+                "sha256:e3a62f0520172440ca0dcc823749319382e377f37f140a0b99ef45fecb84bfe7"
+            ],
+            "version": "==4.4.2"
+        },
+        "defusedxml": {
+            "hashes": [
+                "sha256:6687150770438374ab581bb7a1b327a847dd9c5749e396102de3fad4e8a3ef93",
+                "sha256:f684034d135af4c6cbb949b8a4d2ed61634515257a67299e5f940fbaa34377f5"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
+            "version": "==0.6.0"
+        },
+        "entrypoints": {
+            "hashes": [
+                "sha256:589f874b313739ad35be6e0cd7efde2a4e9b6fea91edcc34e58ecbb8dbe56d19",
+                "sha256:c70dd71abe5a8c85e55e12c19bd91ccfeec11a6e99044204511f9ed547d48451"
+            ],
+            "markers": "python_version >= '2.7'",
+            "version": "==0.3"
+        },
         "gast": {
             "hashes": [
                 "sha256:8f46f5be57ae6889a4e16e2ca113b1703ef17f2b0abceb83793eaba9e1351a45",
@@ -69,11 +185,11 @@
         },
         "google-auth": {
             "hashes": [
-                "sha256:bcbd9f970e7144fe933908aa286d7a12c44b7deb6d78a76871f0377a29d09789",
-                "sha256:f4d5093f13b1b1c0a434ab1dc851cd26a983f86a4d75c95239974e33ed406a87"
+                "sha256:31941bf019fb242c04d0de32845da10180788bfddb0de87d78c4bdf55555dda1",
+                "sha256:873051a6317294b083795cffc467bcd05b6df483ef542bfe0069ddbfbac0a096"
             ],
             "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
-            "version": "==1.21.1"
+            "version": "==1.21.3"
         },
         "google-auth-oauthlib": {
             "hashes": [
@@ -92,47 +208,47 @@
         },
         "grpcio": {
             "hashes": [
-                "sha256:013287f99c99b201aa8a5f6bc7918f616739b9be031db132d9e3b8453e95e151",
-                "sha256:0397616355760cd8282ed5ea34d51830ae4cb6613b7e5f66bed3be5d041b8b9a",
-                "sha256:074871a184483d5cd0746fd01e7d214d3ee9d36e67e32a5786b0a21f29fb8304",
-                "sha256:08a9b648dbe8852ff94b73a1c96da126834c3057ba2301d13e8c4adff334c482",
-                "sha256:0fa86ac4452602c79774783aa68979a1a7625ebb7eaabee2b6550b975b9d61e6",
-                "sha256:220c46b1fc9c9a6fcca4caac398f08f0ed43cdd63c45b7458983c4a1575ef6df",
-                "sha256:259240aab2603891553e17ad5b2655693df79e02a9b887ff605bdeb2fcd3dcc9",
-                "sha256:292635f05b6ce33f87116951d0b3d8d330bdfc5cac74f739370d60981e8c256c",
-                "sha256:344b50865914cc8e6d023457bffee9a640abb18f75d0f2bb519041961c748da9",
-                "sha256:3c2aa6d7a5e5bf73fdb1715eee777efe06dd39df03383f1cc095b2fdb34883e6",
-                "sha256:43d44548ad6ee738b941abd9f09e3b83a5c13f3e1410321023c3c148ba50e796",
-                "sha256:5043440c45c0a031f387e7f48527541c65d672005fb24cf18ef6857483557d39",
-                "sha256:58d7121f48cb94535a4cedcce32921d0d0a78563c7372a143dedeec196d1c637",
-                "sha256:5d7faa89992e015d245750ca9ac916c161bbf72777b2c60abc61da3fae41339e",
-                "sha256:5fb0923b16590bac338e92d98c7d8effb3cfad1d2e18c71bf86bde32c49cd6dd",
-                "sha256:63ee8e02d04272c3d103f44b4bce5d43ea757dd288673cea212d2f7da27967d2",
-                "sha256:64077e3a9a7cf2f59e6c76d503c8de1f18a76428f41a5b000dc53c48a0b772ff",
-                "sha256:739a72abffbd36083ff7adbb862cf1afc1e311c35834bed9c0361d8e68b063e1",
-                "sha256:75e383053dccb610590aa53eed5278db5c09bf498d3b5105ce6c776478f59352",
-                "sha256:7a11b1ebb3210f34913b8be6995936bf9ebc541a65ab69e75db5ce1fe5047e8f",
-                "sha256:8002a89ea91c0078c15d3c0daf423fd4968946be78f08545e807ea9a5ff8054a",
-                "sha256:8b42f0ac76be07a5fa31117a3388d754ad35ef05e2e34be185ca9ccbcfac2069",
-                "sha256:8ca26b489b5dc1e3d31807d329c23d6cb06fe40fbae25b0649b718947936e26a",
-                "sha256:92e54ab65e782f227e751c7555918afaba8d1229601687e89b80c2b65d2f6642",
-                "sha256:a9a7ae74cb3108e6457cf15532d4c300324b48fbcf3ef290bcd2835745f20510",
-                "sha256:ba3e43cb984399064ffaa3c0997576e46a1e268f9da05f97cd9b272f0b59ee71",
-                "sha256:baaa036540d7ace433bdf38a3fe5e41cf9f84cdf10a88bac805f678a7ca8ddcc",
-                "sha256:bf00ab06ea4f89976288f4d6224d4aa120780e30c955d4f85c3214ada29b3ddf",
-                "sha256:bf39977282a79dc1b2765cc3402c0ada571c29a491caec6ed12c0993c1ec115e",
-                "sha256:c22b19abba63562a5a200e586b5bde39d26c8ec30c92e26d209d81182371693b",
-                "sha256:c9016ab1eaf4e054099303287195f3746bd4e69f2631d040f9dca43e910a5408",
-                "sha256:d2c5e05c257859febd03f5d81b5015e1946d6bcf475c7bf63ee99cea8ab0d590",
-                "sha256:e64bddd09842ef508d72ca354319b0eb126205d951e8ac3128fe9869bd563552",
-                "sha256:e8c3264b0fd728aadf3f0324471843f65bd3b38872bdab2a477e31ffb685dd5b",
-                "sha256:ea849210e7362559f326cbe603d5b8d8bb1e556e86a7393b5a8847057de5b084",
-                "sha256:ebb2ca09fa17537e35508a29dcb05575d4d9401138a68e83d1c605d65e8a1770",
-                "sha256:ef9fce98b6fe03874c2a6576b02aec1a0df25742cd67d1d7b75a49e30aa74225",
-                "sha256:f04c59d186af3157dc8811114130aaeae92e90a65283733f41de94eed484e1f7",
-                "sha256:f5b0870b733bcb7b6bf05a02035e7aaf20f599d3802b390282d4c2309f825f1d"
-            ],
-            "version": "==1.31.0"
+                "sha256:01d3046fe980be25796d368f8fc5ff34b7cf5e1444f3789a017a7fe794465639",
+                "sha256:07b430fa68e5eecd78e2ad529ab80f6a234b55fc1b675fe47335ccbf64c6c6c8",
+                "sha256:0e3edd8cdb71809d2455b9dbff66b4dd3d36c321e64bfa047da5afdfb0db332b",
+                "sha256:0f3f09269ffd3fded430cd89ba2397eabbf7e47be93983b25c187cdfebb302a7",
+                "sha256:1376a60f9bfce781b39973f100b5f67e657b5be479f2fd8a7d2a408fc61c085c",
+                "sha256:14c0f017bfebbc18139551111ac58ecbde11f4bc375b73a53af38927d60308b6",
+                "sha256:182c64ade34c341398bf71ec0975613970feb175090760ab4f51d1e9a5424f05",
+                "sha256:1ada89326a364a299527c7962e5c362dbae58c67b283fe8383c4d952b26565d5",
+                "sha256:1ce6f5ff4f4a548c502d5237a071fa617115df58ea4b7bd41dac77c1ab126e9c",
+                "sha256:1d384a61f96a1fc6d5d3e0b62b0a859abc8d4c3f6d16daba51ebf253a3e7df5d",
+                "sha256:25959a651420dd4a6fd7d3e8dee53f4f5fd8c56336a64963428e78b276389a59",
+                "sha256:28677f057e2ef11501860a7bc15de12091d40b95dd0fddab3c37ff1542e6b216",
+                "sha256:378fe80ec5d9353548eb2a8a43ea03747a80f2e387c4f177f2b3ff6c7d898753",
+                "sha256:3afb058b6929eba07dba9ae6c5b555aa1d88cb140187d78cc510bd72d0329f28",
+                "sha256:4396b1d0f388ae875eaf6dc05cdcb612c950fd9355bc34d38b90aaa0665a0d4b",
+                "sha256:4775bc35af9cd3b5033700388deac2e1d611fa45f4a8dcb93667d94cb25f0444",
+                "sha256:5bddf9d53c8df70061916c3bfd2f468ccf26c348bb0fb6211531d895ed5e4c72",
+                "sha256:6d869a3e8e62562b48214de95e9231c97c53caa7172802236cd5d60140d7cddd",
+                "sha256:6f7947dad606c509d067e5b91a92b250aa0530162ab99e4737090f6b17eb12c4",
+                "sha256:7cda998b7b551503beefc38db9be18c878cfb1596e1418647687575cdefa9273",
+                "sha256:99bac0e2c820bf446662365df65841f0c2a55b0e2c419db86eaf5d162ddae73e",
+                "sha256:9c0d8f2346c842088b8cbe3e14985b36e5191a34bf79279ba321a4bf69bd88b7",
+                "sha256:a8004b34f600a8a51785e46859cd88f3386ef67cccd1cfc7598e3d317608c643",
+                "sha256:ac7028d363d2395f3d755166d0161556a3f99500a5b44890421ccfaaf2aaeb08",
+                "sha256:be98e3198ec765d0a1e27f69d760f69374ded8a33b953dcfe790127731f7e690",
+                "sha256:c31e8a219650ddae1cd02f5a169e1bffe66a429a8255d3ab29e9363c73003b62",
+                "sha256:c4966d746dccb639ef93f13560acbe9630681c07f2b320b7ec03fe2c8f0a1f15",
+                "sha256:c58825a3d8634cd634d8f869afddd4d5742bdb59d594aea4cea17b8f39269a55",
+                "sha256:ce617e1c4a39131f8527964ac9e700eb199484937d7a0b3e52655a3ba50d5fb9",
+                "sha256:e28e4c0d4231beda5dee94808e3a224d85cbaba3cfad05f2192e6f4ec5318053",
+                "sha256:e467af6bb8f5843f5a441e124b43474715cfb3981264e7cd227343e826dcc3ce",
+                "sha256:e6786f6f7be0937614577edcab886ddce91b7c1ea972a07ef9972e9f9ecbbb78",
+                "sha256:e811ce5c387256609d56559d944a974cc6934a8eea8c76e7c86ec388dc06192d",
+                "sha256:ec10d5f680b8e95a06f1367d73c5ddcc0ed04a3f38d6e4c9346988fb0cea2ffa",
+                "sha256:ef9bd7fdfc0a063b4ed0efcab7906df5cae9bbcf79d05c583daa2eba56752b00",
+                "sha256:f03dfefa9075dd1c6c5cc27b1285c521434643b09338d8b29e1d6a27b386aa82",
+                "sha256:f12900be4c3fd2145ba94ab0d80b7c3d71c9e6414cfee2f31b1c20188b5c281f",
+                "sha256:f53f2dfc8ff9a58a993e414a016c8b21af333955ae83960454ad91798d467c7b",
+                "sha256:f7d508691301027033215d3662dab7e178f54d5cca2329f26a71ae175d94b83f"
+            ],
+            "version": "==1.32.0"
         },
         "h5py": {
             "hashes": [
@@ -178,11 +294,57 @@
         },
         "importlib-metadata": {
             "hashes": [
-                "sha256:90bb658cdbbf6d1735b6341ce708fc7024a3e14e99ffdc5783edea9f9b077f83",
-                "sha256:dc15b2969b4ce36305c51eebe62d418ac7791e9a157911d58bfb1f9ccd8e2070"
+                "sha256:77a540690e24b0305878c37ffd421785a6f7e53c8b5720d211b211de8d0e95da",
+                "sha256:cefa1a2f919b866c5beb7c9f7b0ebb4061f30a8a9bf16d609b000e2dfaceb9c3"
             ],
             "markers": "python_version < '3.8'",
-            "version": "==1.7.0"
+            "version": "==2.0.0"
+        },
+        "ipykernel": {
+            "hashes": [
+                "sha256:9b2652af1607986a1b231c62302d070bc0534f564c393a5d9d130db9abbbe89d",
+                "sha256:d6fbba26dba3cebd411382bc484f7bc2caa98427ae0ddb4ab37fe8bfeb5c7dd3"
+            ],
+            "markers": "python_version >= '3.5'",
+            "version": "==5.3.4"
+        },
+        "ipython": {
+            "hashes": [
+                "sha256:2dbcc8c27ca7d3cfe4fcdff7f45b27f9a8d3edfa70ff8024a71c7a8eb5f09d64",
+                "sha256:9f4fcb31d3b2c533333893b9172264e4821c1ac91839500f31bd43f2c59b3ccf"
+            ],
+            "markers": "python_version >= '3.3'",
+            "version": "==7.16.1"
+        },
+        "ipython-genutils": {
+            "hashes": [
+                "sha256:72dd37233799e619666c9f639a9da83c34013a73e8bbc79a7a6348d93c61fab8",
+                "sha256:eb2e116e75ecef9d4d228fdc66af54269afa26ab4463042e33785b887c628ba8"
+            ],
+            "version": "==0.2.0"
+        },
+        "ipywidgets": {
+            "hashes": [
+                "sha256:13ffeca438e0c0f91ae583dc22f50379b9d6b28390ac7be8b757140e9a771516",
+                "sha256:e945f6e02854a74994c596d9db83444a1850c01648f1574adf144fbbabe05c97"
+            ],
+            "version": "==7.5.1"
+        },
+        "jedi": {
+            "hashes": [
+                "sha256:86ed7d9b750603e4ba582ea8edc678657fb4007894a12bcf6f4bb97892f31d20",
+                "sha256:98cc583fa0f2f8304968199b01b6b4b94f469a1f4a74c1560506ca2a211378b5"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
+            "version": "==0.17.2"
+        },
+        "jinja2": {
+            "hashes": [
+                "sha256:89aab215427ef59c34ad58735269eb58b1a5808103067f7bb9d5836c651b3bb0",
+                "sha256:f0a4641d3cf955324a89c04f3d94663aa4d638abe8f733ecd3582848e1c37035"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
+            "version": "==2.11.2"
         },
         "joblib": {
             "hashes": [
@@ -192,6 +354,53 @@
             "markers": "python_version >= '3.6'",
             "version": "==0.16.0"
         },
+        "jsonschema": {
+            "hashes": [
+                "sha256:4e5b3cf8216f577bee9ce139cbe72eca3ea4f292ec60928ff24758ce626cd163",
+                "sha256:c8a85b28d377cc7737e46e2d9f2b4f44ee3c0e1deac6bf46ddefc7187d30797a"
+            ],
+            "version": "==3.2.0"
+        },
+        "jupyter": {
+            "hashes": [
+                "sha256:3e1f86076bbb7c8c207829390305a2b1fe836d471ed54be66a3b8c41e7f46cc7",
+                "sha256:5b290f93b98ffbc21c0c7e749f054b3267782166d72fa5e3ed1ed4eaf34a2b78",
+                "sha256:d9dc4b3318f310e34c82951ea5d6683f67bed7def4b259fafbfe4f1beb1d8e5f"
+            ],
+            "index": "pypi",
+            "version": "==1.0.0"
+        },
+        "jupyter-client": {
+            "hashes": [
+                "sha256:49e390b36fe4b4226724704ea28d9fb903f1a3601b6882ce3105221cd09377a1",
+                "sha256:c958d24d6eacb975c1acebb68ac9077da61b5f5c040f22f6849928ad7393b950"
+            ],
+            "markers": "python_version >= '3.5'",
+            "version": "==6.1.7"
+        },
+        "jupyter-console": {
+            "hashes": [
+                "sha256:1d80c06b2d85bfb10bd5cc731b3db18e9023bc81ab00491d3ac31f206490aee3",
+                "sha256:7f6194f4f4692d292da3f501c7f343ccd5e36c6a1becf7b7515e23e66d6bf1e9"
+            ],
+            "markers": "python_version >= '3.6'",
+            "version": "==6.2.0"
+        },
+        "jupyter-core": {
+            "hashes": [
+                "sha256:394fd5dd787e7c8861741880bdf8a00ce39f95de5d18e579c74b882522219e7e",
+                "sha256:a4ee613c060fe5697d913416fc9d553599c05e4492d58fac1192c9a6844abb21"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
+            "version": "==4.6.3"
+        },
+        "jupyterlab-pygments": {
+            "hashes": [
+                "sha256:19a0ccde7daddec638363cd3d60b63a4f6544c9181d65253317b2fb492a797b9",
+                "sha256:c9535e5999f29bff90bd0fa423717dcaf247b71fad505d66b17d3217e9021fc5"
+            ],
+            "version": "==0.1.1"
+        },
         "keras-preprocessing": {
             "hashes": [
                 "sha256:7b82029b130ff61cc99b55f3bd27427df4838576838c5b2f65940e4fcec99a7b",
@@ -232,70 +441,142 @@
             "markers": "python_version >= '3.5'",
             "version": "==3.2.2"
         },
+        "markupsafe": {
+            "hashes": [
+                "sha256:00bc623926325b26bb9605ae9eae8a215691f33cae5df11ca5424f06f2d1f473",
+                "sha256:09027a7803a62ca78792ad89403b1b7a73a01c8cb65909cd876f7fcebd79b161",
+                "sha256:09c4b7f37d6c648cb13f9230d847adf22f8171b1ccc4d5682398e77f40309235",
+                "sha256:1027c282dad077d0bae18be6794e6b6b8c91d58ed8a8d89a89d59693b9131db5",
+                "sha256:13d3144e1e340870b25e7b10b98d779608c02016d5184cfb9927a9f10c689f42",
+                "sha256:24982cc2533820871eba85ba648cd53d8623687ff11cbb805be4ff7b4c971aff",
+                "sha256:29872e92839765e546828bb7754a68c418d927cd064fd4708fab9fe9c8bb116b",
+                "sha256:43a55c2930bbc139570ac2452adf3d70cdbb3cfe5912c71cdce1c2c6bbd9c5d1",
+                "sha256:46c99d2de99945ec5cb54f23c8cd5689f6d7177305ebff350a58ce5f8de1669e",
+                "sha256:500d4957e52ddc3351cabf489e79c91c17f6e0899158447047588650b5e69183",
+                "sha256:535f6fc4d397c1563d08b88e485c3496cf5784e927af890fb3c3aac7f933ec66",
+                "sha256:596510de112c685489095da617b5bcbbac7dd6384aeebeda4df6025d0256a81b",
+                "sha256:62fe6c95e3ec8a7fad637b7f3d372c15ec1caa01ab47926cfdf7a75b40e0eac1",
+                "sha256:6788b695d50a51edb699cb55e35487e430fa21f1ed838122d722e0ff0ac5ba15",
+                "sha256:6dd73240d2af64df90aa7c4e7481e23825ea70af4b4922f8ede5b9e35f78a3b1",
+                "sha256:717ba8fe3ae9cc0006d7c451f0bb265ee07739daf76355d06366154ee68d221e",
+                "sha256:79855e1c5b8da654cf486b830bd42c06e8780cea587384cf6545b7d9ac013a0b",
+                "sha256:7c1699dfe0cf8ff607dbdcc1e9b9af1755371f92a68f706051cc8c37d447c905",
+                "sha256:88e5fcfb52ee7b911e8bb6d6aa2fd21fbecc674eadd44118a9cc3863f938e735",
+                "sha256:8defac2f2ccd6805ebf65f5eeb132adcf2ab57aa11fdf4c0dd5169a004710e7d",
+                "sha256:98c7086708b163d425c67c7a91bad6e466bb99d797aa64f965e9d25c12111a5e",
+                "sha256:9add70b36c5666a2ed02b43b335fe19002ee5235efd4b8a89bfcf9005bebac0d",
+                "sha256:9bf40443012702a1d2070043cb6291650a0841ece432556f784f004937f0f32c",
+                "sha256:ade5e387d2ad0d7ebf59146cc00c8044acbd863725f887353a10df825fc8ae21",
+                "sha256:b00c1de48212e4cc9603895652c5c410df699856a2853135b3967591e4beebc2",
+                "sha256:b1282f8c00509d99fef04d8ba936b156d419be841854fe901d8ae224c59f0be5",
+                "sha256:b2051432115498d3562c084a49bba65d97cf251f5a331c64a12ee7e04dacc51b",
+                "sha256:ba59edeaa2fc6114428f1637ffff42da1e311e29382d81b339c1817d37ec93c6",
+                "sha256:c8716a48d94b06bb3b2524c2b77e055fb313aeb4ea620c8dd03a105574ba704f",
+                "sha256:cd5df75523866410809ca100dc9681e301e3c27567cf498077e8551b6d20e42f",
+                "sha256:cdb132fc825c38e1aeec2c8aa9338310d29d337bebbd7baa06889d09a60a1fa2",
+                "sha256:e249096428b3ae81b08327a63a485ad0878de3fb939049038579ac0ef61e17e7",
+                "sha256:e8313f01ba26fbbe36c7be1966a7b7424942f670f38e666995b88d012765b9be"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
+            "version": "==1.1.1"
+        },
         "matplotlib": {
             "hashes": [
-                "sha256:0dc15e1ad84ec06bf0c315e6c4c2cced13a21ce4c2b4955bb75097064a4b1e92",
-                "sha256:1507c2a8e4662f6fa1d3ecc760782b158df8a3244ecc21c1d8dbb1cd0b3f872e",
-                "sha256:1f9cf2b8500b833714a193cb24281153f5072d55b2e486009f1e81f0b7da3410",
-                "sha256:233bef5e3b3494f3b7057595ca814f23ba0ce67a03632ddf677be5132128b3db",
-                "sha256:2375f039b8c6ad6c1d03f01bf31f086bbbf997bf25e246f3b67f69969cde3d98",
-                "sha256:24392ac1a382ed753505286f1a1483bcfd67ed0c72d51be10c4c2013e386d0b7",
-                "sha256:282f8a077a1217f9f2ac178596f27c1ae94abbc6e7b785e1b8f25e83918e9199",
-                "sha256:2c3619ec2a5ead430a4536ebf8c77ea55d8ce36418919f831d35bc657ed5f27e",
-                "sha256:5a42c84264a1acbbf01c073a7bd05a0e80d99f94f10020d613b1b0526af9dcc2",
-                "sha256:636c6330a7dcb18bac114dbeaff314fbbb0c11682f9a9601de69a50e331d18d7",
-                "sha256:6739b6cd9278d5cb337df0bd4400ad37bbd04c6dc7aa2c65e1e83a02bc4cc6fd",
-                "sha256:6d0f03079f655ca0a2d2e0bf49c28e1ec43d9d544c33d8da1a88765f23018ecc",
-                "sha256:73a493e340064e8fe03207d9333b68baca30d9f0da543ae4af6b6b4f13f0fe05",
-                "sha256:79f0c4730ad422ecb6bda814c9a9b375df36d6bd5a49eaa14e92e5f5e3e95ac3",
-                "sha256:83ae7261f4d5ab387be2caee29c4f499b1566f31c8ac97a0b8ab61afd9e3da92",
-                "sha256:87f53bcce90772f942c2db56736788b39332d552461a5cb13f05ff45c1680f0e",
-                "sha256:88c6ab4a32a7447dad236b8371612aaba5c967d632ff11999e0478dd687f2c58",
-                "sha256:96a5e667308dbf45670370d9dffb974e73b15bac0df0b5f3fb0b0ac7a572290e",
-                "sha256:9703bc00a94a94c4e94b2ea0fbfbc9d2bb21159733134639fd931b6606c5c47e",
-                "sha256:bc978374b43737f2bbc4a6ec48e52ae8c92be6278a80d0e2ce92f0eb0841f15c",
-                "sha256:bd8fceaa3494b531d43b6206966ba15705638137fc2dc5da5ee560cf9476867b",
-                "sha256:c4ffb25b9855bdb6cdaf21bbd4ab2c229be539248304ac5215b94c816ea6e32e",
-                "sha256:cc2d6b47c8fee89da982a312b54949ec0cd6a7976a8cafb5b62dea6c9883a14d",
-                "sha256:e4d6d3afc454b4afc0d9d0ed52a8fa40a1b0d8f33c8e143e49a5833a7e32266b",
-                "sha256:f62c0b9a5d38c26673a8862cbae4d26cffcda260848e4278246b4e00f5a95eaf",
-                "sha256:fab11637734eb14affb9c5e20d44d69429c18b49595d6e67c69295de24827fc4",
-                "sha256:ffbae66e2db70dc330cb3299525f97e1c0efdfc763e04e1a4e08f968c7ad21f0"
+                "sha256:06866c138d81a593b535d037b2727bec9b0818cadfe6a81f6ec5715b8dd38a89",
+                "sha256:16b241c3d17be786966495229714de37de04472da472277869b8d5b456a8df00",
+                "sha256:27f9de4784ae6fb97679556c5542cf36c0751dccb4d6407f7c62517fa2078868",
+                "sha256:2f5eefc17dc2a71318d5a3496313be5c351c0731e8c4c6182c9ac3782cfc4076",
+                "sha256:371518c769d84af8ec9b7dcb871ac44f7a67ef126dd3a15c88c25458e6b6d205",
+                "sha256:3d2edbf59367f03cd9daf42939ca06383a7d7803e3993eb5ff1bee8e8a3fbb6b",
+                "sha256:3fb0409754b26f48045bacd6818e44e38ca9338089f8ba689e2f9344ff2847c7",
+                "sha256:548cfe81476dbac44db96e9c0b074b6fb333b4d1f12b1ae68dbed47e45166384",
+                "sha256:57be9e21073fc367237b03ecac0d9e4b8ddbe38e86ec4a316857d8d93ac9286c",
+                "sha256:5ccecb5f78b51b885f0028b646786889f49c54883e554fca41a2a05998063f23",
+                "sha256:69cf76d673682140f46c6cb5e073332c1f1b2853c748dc1cb04f7d00023567f7",
+                "sha256:793e061054662aa27acaff9201cdd510a698541c6e8659eeceb31d66c16facc6",
+                "sha256:799c421bc245a0749c1515b6dea6dc02db0a8c1f42446a0f03b3b82a60a900dc",
+                "sha256:8bc1d3284dee001f41ec98f59675f4d723683e1cc082830b440b5f081d8e0ade",
+                "sha256:a522de31e07ed7d6f954cda3fbd5ca4b8edbfc592a821a7b00291be6f843292e",
+                "sha256:be2f0ec62e0939a9dcfd3638c140c5a74fc929ee3fd1f31408ab8633db6e1523",
+                "sha256:c5d0c2ae3e3ed4e9f46b7c03b40d443601012ffe8eb8dfbb2bd6b2d00509f797",
+                "sha256:f0268613073df055bcc6a490de733012f2cf4fe191c1adb74e41cec8add1a165"
             ],
             "index": "pypi",
-            "version": "==3.3.1"
+            "version": "==3.3.2"
+        },
+        "mistune": {
+            "hashes": [
+                "sha256:59a3429db53c50b5c6bcc8a07f8848cb00d7dc8bdb431a4ab41920d201d4756e",
+                "sha256:88a1051873018da288eee8538d476dffe1262495144b33ecb586c4ab266bb8d4"
+            ],
+            "version": "==0.8.4"
+        },
+        "nbclient": {
+            "hashes": [
+                "sha256:8a6e27ff581cee50895f44c41936ce02369674e85e2ad58643d8d4a6c36771b0",
+                "sha256:8ad52d27ba144fca1402db014857e53c5a864a2f407be66ca9d74c3a56d6591d"
+            ],
+            "markers": "python_version >= '3.6'",
+            "version": "==0.5.0"
+        },
+        "nbconvert": {
+            "hashes": [
+                "sha256:68335477288aab8a9b9ec03002dce59b4eb1ca967116741ec218a4e78c129efd",
+                "sha256:d8549f62e739a4d51f275c2932b1783ee5039dde07a2b71de70c0296a42c8394"
+            ],
+            "markers": "python_version >= '3.6'",
+            "version": "==6.0.6"
+        },
+        "nbformat": {
+            "hashes": [
+                "sha256:54d4d6354835a936bad7e8182dcd003ca3dc0cedfee5a306090e04854343b340",
+                "sha256:ea55c9b817855e2dfcd3f66d74857342612a60b1f09653440f4a5845e6e3523f"
+            ],
+            "markers": "python_version >= '3.5'",
+            "version": "==5.0.7"
+        },
+        "nest-asyncio": {
+            "hashes": [
+                "sha256:a4487c4f49f2d11a7bb89a512a6886b6a5045f47097f49815b2851aaa8599cf0",
+                "sha256:b86c3193abda5b2eeccf8c79894bc71c680369a178f4b068514ac00720b14e01"
+            ],
+            "markers": "python_version >= '3.5'",
+            "version": "==1.4.1"
+        },
+        "notebook": {
+            "hashes": [
+                "sha256:07b6e8b8a61aa2f780fe9a97430470485bc71262bc5cae8521f1441b910d2c88",
+                "sha256:687d01f963ea20360c0b904ee7a37c3d8cda553858c8d6e33fd0afd13e89de32"
+            ],
+            "markers": "python_version >= '3.5'",
+            "version": "==6.1.4"
         },
         "numpy": {
             "hashes": [
-                "sha256:082f8d4dd69b6b688f64f509b91d482362124986d98dc7dc5f5e9f9b9c3bb983",
-                "sha256:1bc0145999e8cb8aed9d4e65dd8b139adf1919e521177f198529687dbf613065",
-                "sha256:309cbcfaa103fc9a33ec16d2d62569d541b79f828c382556ff072442226d1968",
-                "sha256:3673c8b2b29077f1b7b3a848794f8e11f401ba0b71c49fbd26fb40b71788b132",
-                "sha256:480fdd4dbda4dd6b638d3863da3be82873bba6d32d1fc12ea1b8486ac7b8d129",
-                "sha256:56ef7f56470c24bb67fb43dae442e946a6ce172f97c69f8d067ff8550cf782ff",
-                "sha256:5a936fd51049541d86ccdeef2833cc89a18e4d3808fe58a8abeb802665c5af93",
-                "sha256:5b6885c12784a27e957294b60f97e8b5b4174c7504665333c5e94fbf41ae5d6a",
-                "sha256:667c07063940e934287993366ad5f56766bc009017b4a0fe91dbd07960d0aba7",
-                "sha256:7ed448ff4eaffeb01094959b19cbaf998ecdee9ef9932381420d514e446601cd",
-                "sha256:8343bf67c72e09cfabfab55ad4a43ce3f6bf6e6ced7acf70f45ded9ebb425055",
-                "sha256:92feb989b47f83ebef246adabc7ff3b9a59ac30601c3f6819f8913458610bdcc",
-                "sha256:935c27ae2760c21cd7354402546f6be21d3d0c806fffe967f745d5f2de5005a7",
-                "sha256:aaf42a04b472d12515debc621c31cf16c215e332242e7a9f56403d814c744624",
-                "sha256:b12e639378c741add21fbffd16ba5ad25c0a1a17cf2b6fe4288feeb65144f35b",
-                "sha256:b1cca51512299841bf69add3b75361779962f9cee7d9ee3bb446d5982e925b69",
-                "sha256:b8456987b637232602ceb4d663cb34106f7eb780e247d51a260b84760fd8f491",
-                "sha256:b9792b0ac0130b277536ab8944e7b754c69560dac0415dd4b2dbd16b902c8954",
-                "sha256:c9591886fc9cbe5532d5df85cb8e0cc3b44ba8ce4367bd4cf1b93dc19713da72",
-                "sha256:cf1347450c0b7644ea142712619533553f02ef23f92f781312f6a3553d031fc7",
-                "sha256:de8b4a9b56255797cbddb93281ed92acbc510fb7b15df3f01bd28f46ebc4edae",
-                "sha256:e1b1dc0372f530f26a03578ac75d5e51b3868b9b76cd2facba4c9ee0eb252ab1",
-                "sha256:e45f8e981a0ab47103181773cc0a54e650b2aef8c7b6cd07405d0fa8d869444a",
-                "sha256:e4f6d3c53911a9d103d8ec9518190e52a8b945bab021745af4939cfc7c0d4a9e",
-                "sha256:ed8a311493cf5480a2ebc597d1e177231984c818a86875126cfd004241a73c3e",
-                "sha256:ef71a1d4fd4858596ae80ad1ec76404ad29701f8ca7cdcebc50300178db14dfc"
+                "sha256:0172304e7d8d40e9e49553901903dc5f5a49a703363ed756796f5808a06fc233",
+                "sha256:34e96e9dae65c4839bd80012023aadd6ee2ccb73ce7fdf3074c62f301e63120b",
+                "sha256:3676abe3d621fc467c4c1469ee11e395c82b2d6b5463a9454e37fe9da07cd0d7",
+                "sha256:3dd6823d3e04b5f223e3e265b4a1eae15f104f4366edd409e5a5e413a98f911f",
+                "sha256:4064f53d4cce69e9ac613256dc2162e56f20a4e2d2086b1956dd2fcf77b7fac5",
+                "sha256:4674f7d27a6c1c52a4d1aa5f0881f1eff840d2206989bae6acb1c7668c02ebfb",
+                "sha256:7d42ab8cedd175b5ebcb39b5208b25ba104842489ed59fbb29356f671ac93583",
+                "sha256:965df25449305092b23d5145b9bdaeb0149b6e41a77a7d728b1644b3c99277c1",
+                "sha256:9c9d6531bc1886454f44aa8f809268bc481295cf9740827254f53c30104f074a",
+                "sha256:a78e438db8ec26d5d9d0e584b27ef25c7afa5a182d1bf4d05e313d2d6d515271",
+                "sha256:a7acefddf994af1aeba05bbbafe4ba983a187079f125146dc5859e6d817df824",
+                "sha256:a87f59508c2b7ceb8631c20630118cc546f1f815e034193dc72390db038a5cb3",
+                "sha256:ac792b385d81151bae2a5a8adb2b88261ceb4976dbfaaad9ce3a200e036753dc",
+                "sha256:b03b2c0badeb606d1232e5f78852c102c0a7989d3a534b3129e7856a52f3d161",
+                "sha256:b39321f1a74d1f9183bf1638a745b4fd6fe80efbb1f6b32b932a588b4bc7695f",
+                "sha256:cae14a01a159b1ed91a324722d746523ec757357260c6804d11d6147a9e53e3f",
+                "sha256:cd49930af1d1e49a812d987c2620ee63965b619257bd76eaaa95870ca08837cf",
+                "sha256:e15b382603c58f24265c9c931c9a45eebf44fe2e6b4eaedbb0d025ab3255228b",
+                "sha256:e91d31b34fc7c2c8f756b4e902f901f856ae53a93399368d9a0dc7be17ed2ca0",
+                "sha256:ef627986941b5edd1ed74ba89ca43196ed197f1a206a3f18cc9faf2fb84fd675",
+                "sha256:f718a7949d1c4f622ff548c572e0c03440b49b9531ff00e4ed5738b459f011e8"
             ],
             "index": "pypi",
-            "version": "==1.19.1"
+            "version": "==1.18.5"
         },
         "oauthlib": {
             "hashes": [
@@ -313,27 +594,64 @@
             "markers": "python_version >= '3.5'",
             "version": "==3.3.0"
         },
+        "packaging": {
+            "hashes": [
+                "sha256:4357f74f47b9c12db93624a82154e9b120fa8293699949152b22065d556079f8",
+                "sha256:998416ba6962ae7fbd6596850b80e17859a5753ba17c32284f67bfff33784181"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
+            "version": "==20.4"
+        },
         "pandas": {
             "hashes": [
-                "sha256:01b1e536eb960822c5e6b58357cad8c4b492a336f4a5630bf0b598566462a578",
-                "sha256:0246c67cbaaaac8d25fed8d4cf2d8897bd858f0e540e8528a75281cee9ac516d",
-                "sha256:0366150fe8ee37ef89a45d3093e05026b5f895e42bbce3902ce3b6427f1b8471",
-                "sha256:16ae070c47474008769fc443ac765ffd88c3506b4a82966e7a605592978896f9",
-                "sha256:1acc2bd7fc95e5408a4456897c2c2a1ae7c6acefe108d90479ab6d98d34fcc3d",
-                "sha256:391db82ebeb886143b96b9c6c6166686c9a272d00020e4e39ad63b792542d9e2",
-                "sha256:41675323d4fcdd15abde068607cad150dfe17f7d32290ee128e5fea98442bd09",
-                "sha256:53328284a7bb046e2e885fd1b8c078bd896d7fc4575b915d4936f54984a2ba67",
-                "sha256:57c5f6be49259cde8e6f71c2bf240a26b071569cabc04c751358495d09419e56",
-                "sha256:84c101d0f7bbf0d9f1be9a2f29f6fcc12415442558d067164e50a56edfb732b4",
-                "sha256:88930c74f69e97b17703600233c0eaf1f4f4dd10c14633d522724c5c1b963ec4",
-                "sha256:8c9ec12c480c4d915e23ee9c8a2d8eba8509986f35f307771045c1294a2e5b73",
-                "sha256:a81c4bf9c59010aa3efddbb6b9fc84a9b76dc0b4da2c2c2d50f06a9ef6ac0004",
-                "sha256:d9644ac996149b2a51325d48d77e25c911e01aa6d39dc1b64be679cd71f683ec",
-                "sha256:e4b6c98f45695799990da328e6fd7d6187be32752ed64c2f22326ad66762d179",
-                "sha256:fe6f1623376b616e03d51f0dd95afd862cf9a33c18cf55ce0ed4bbe1c4444391"
+                "sha256:026d764d0b86ee53183aa4c0b90774b6146123eeada4e24946d7d24290777be1",
+                "sha256:02ec9f5f0b7df7227931a884569ef0b6d32d76789c84bcac1a719dafd1f912e8",
+                "sha256:08783a33989a6747317766b75be30a594a9764b9f145bb4bcc06e337930d9807",
+                "sha256:0936991228241db937e87f82ec552a33888dd04a2e0d5a2fa3c689f92fab09e0",
+                "sha256:188cdfbf8399bc144fa95040536b5ce3429d2eda6c9c8b238c987af7df9f128c",
+                "sha256:1edf6c254d2d138188e9987159978ee70e23362fe9197f3f100844a197f7e1e4",
+                "sha256:474fa53e3b2f3a543cbca81f7457bd1f44e7eb1be7171067636307e21b624e9c",
+                "sha256:59df9f0276aa4854d8bff28c5e5aeb74d9c6bb4d9f55d272b7124a7df40e47d0",
+                "sha256:9e135ce9929cd0f0ba24f0545936af17ba935f844d4c3a2b979354a73c9440e0",
+                "sha256:ab6ea0f3116f408a8a59cd50158bfd19d2a024f4e221f14ab1bcd2da4f0c6fdf",
+                "sha256:b64ffd87a2cfd31b40acd4b92cb72ea9a52a48165aec4c140e78fd69c45d1444",
+                "sha256:b821f239514a9ce46dd1cd6c9298a03ed58d0235d414ea264aacc1b14916bbe4",
+                "sha256:c9235b37489168ed6b173551c816b50aa89f03c24a8549a8b4d47d8dc79bfb1e",
+                "sha256:eb0ac2fd04428f18b547716f70c699a7cc9c65a6947ed8c7e688d96eb91e3db8",
+                "sha256:eeb64c5b3d4f2ea072ca8afdeb2b946cd681a863382ca79734f1b520b8d2fa26",
+                "sha256:f7008ec22b92d771b145150978d930a28fab8da3a10131b01bbf39574acdad0b"
             ],
             "index": "pypi",
-            "version": "==1.1.1"
+            "version": "==1.1.2"
+        },
+        "pandocfilters": {
+            "hashes": [
+                "sha256:b3dd70e169bb5449e6bc6ff96aea89c5eea8c5f6ab5e207fc2f521a2cf4a0da9"
+            ],
+            "version": "==1.4.2"
+        },
+        "parso": {
+            "hashes": [
+                "sha256:97218d9159b2520ff45eb78028ba8b50d2bc61dcc062a9682666f2dc4bd331ea",
+                "sha256:caba44724b994a8a5e086460bb212abc5a8bc46951bf4a9a1210745953622eb9"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
+            "version": "==0.7.1"
+        },
+        "pexpect": {
+            "hashes": [
+                "sha256:0b48a55dcb3c05f3329815901ea4fc1537514d6ba867a152b581d69ae3710937",
+                "sha256:fc65a43959d153d0114afe13997d439c22823a27cefceb5ff35c2178c6784c0c"
+            ],
+            "markers": "sys_platform != 'win32'",
+            "version": "==4.8.0"
+        },
+        "pickleshare": {
+            "hashes": [
+                "sha256:87683d47965c1da65cdacaf31c8441d12b8044cdec9aca500cd78fc2c683afca",
+                "sha256:9649af414d74d4df115d5d718f82acb59c9d418196b7b4290ed47a12ce62df56"
+            ],
+            "version": "==0.7.5"
         },
         "pillow": {
             "hashes": [
@@ -369,6 +687,21 @@
             "markers": "python_version >= '3.5'",
             "version": "==7.2.0"
         },
+        "prometheus-client": {
+            "hashes": [
+                "sha256:983c7ac4b47478720db338f1491ef67a100b474e3bc7dafcbaefb7d0b8f9b01c",
+                "sha256:c6e6b706833a6bd1fd51711299edee907857be10ece535126a158f911ee80915"
+            ],
+            "version": "==0.8.0"
+        },
+        "prompt-toolkit": {
+            "hashes": [
+                "sha256:822f4605f28f7d2ba6b0b09a31e25e140871e96364d1d377667b547bb3bf4489",
+                "sha256:83074ee28ad4ba6af190593d4d4c607ff525272a504eb159199b6dd9f950c950"
+            ],
+            "markers": "python_full_version >= '3.6.1'",
+            "version": "==3.0.7"
+        },
         "protobuf": {
             "hashes": [
                 "sha256:0bba42f439bf45c0f600c3c5993666fcb88e8441d011fad80a11df6f324eef33",
@@ -392,6 +725,14 @@
             ],
             "version": "==3.13.0"
         },
+        "ptyprocess": {
+            "hashes": [
+                "sha256:923f299cc5ad920c68f2bc0bc98b75b9f838b93b599941a6b63ddbc2476394c0",
+                "sha256:d7cc528d76e76342423ca640335bd3633420dc1366f258cb31d05e865ef5ca1f"
+            ],
+            "markers": "os_name != 'nt'",
+            "version": "==0.6.0"
+        },
         "pyasn1": {
             "hashes": [
                 "sha256:014c0e9976956a08139dc0712ae195324a75e142284d5f87f1a87ee1b068a359",
@@ -428,6 +769,22 @@
             ],
             "version": "==0.2.8"
         },
+        "pycparser": {
+            "hashes": [
+                "sha256:2d475327684562c3a96cc71adf7dc8c4f0565175cf86b6d7a404ff4c771f15f0",
+                "sha256:7582ad22678f0fcd81102833f60ef8d0e57288b6b5fb00323d101be910e35705"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
+            "version": "==2.20"
+        },
+        "pygments": {
+            "hashes": [
+                "sha256:307543fe65c0947b126e83dd5a61bd8acbd84abec11f43caebaf5534cbc17998",
+                "sha256:926c3f319eda178d1bd90851e4317e6d8cdb5e292a3386aac9bd75eca29cf9c7"
+            ],
+            "markers": "python_version >= '3.5'",
+            "version": "==2.7.1"
+        },
         "pyparsing": {
             "hashes": [
                 "sha256:c203ec8783bf771a155b207279b9bccb8dea02d8f0c9e5f8ead507bc3246ecc1",
@@ -436,6 +793,13 @@
             "markers": "python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2, 3.3'",
             "version": "==2.4.7"
         },
+        "pyrsistent": {
+            "hashes": [
+                "sha256:2e636185d9eb976a18a8a8e96efce62f2905fea90041958d8cc2a189756ebf3e"
+            ],
+            "markers": "python_version >= '3.5'",
+            "version": "==0.17.3"
+        },
         "python-dateutil": {
             "hashes": [
                 "sha256:73ebfe9dbf22e832286dafa60473e4cd239f8592f699aa5adaf10050e6e1823c",
@@ -451,6 +815,54 @@
             ],
             "version": "==2020.1"
         },
+        "pyzmq": {
+            "hashes": [
+                "sha256:00dca814469436455399660247d74045172955459c0bd49b54a540ce4d652185",
+                "sha256:046b92e860914e39612e84fa760fc3f16054d268c11e0e25dcb011fb1bc6a075",
+                "sha256:09d24a80ccb8cbda1af6ed8eb26b005b6743e58e9290566d2a6841f4e31fa8e0",
+                "sha256:0a422fc290d03958899743db091f8154958410fc76ce7ee0ceb66150f72c2c97",
+                "sha256:276ad604bffd70992a386a84bea34883e696a6b22e7378053e5d3227321d9702",
+                "sha256:296540a065c8c21b26d63e3cea2d1d57902373b16e4256afe46422691903a438",
+                "sha256:29d51279060d0a70f551663bc592418bcad7f4be4eea7b324f6dd81de05cb4c1",
+                "sha256:36ab114021c0cab1a423fe6689355e8f813979f2c750968833b318c1fa10a0fd",
+                "sha256:3fa6debf4bf9412e59353defad1f8035a1e68b66095a94ead8f7a61ae90b2675",
+                "sha256:5120c64646e75f6db20cc16b9a94203926ead5d633de9feba4f137004241221d",
+                "sha256:59f1e54627483dcf61c663941d94c4af9bf4163aec334171686cdaee67974fe5",
+                "sha256:5d9fc809aa8d636e757e4ced2302569d6e60e9b9c26114a83f0d9d6519c40493",
+                "sha256:654d3e06a4edc566b416c10293064732516cf8871a4522e0a2ba00cc2a2e600c",
+                "sha256:720d2b6083498a9281eaee3f2927486e9fe02cd16d13a844f2e95217f243efea",
+                "sha256:73483a2caaa0264ac717af33d6fb3f143d8379e60a422730ee8d010526ce1913",
+                "sha256:8a6ada5a3f719bf46a04ba38595073df8d6b067316c011180102ba2a1925f5b5",
+                "sha256:8b66b94fe6243d2d1d89bca336b2424399aac57932858b9a30309803ffc28112",
+                "sha256:99cc0e339a731c6a34109e5c4072aaa06d8e32c0b93dc2c2d90345dd45fa196c",
+                "sha256:a7e7f930039ee0c4c26e4dfee015f20bd6919cd8b97c9cd7afbde2923a5167b6",
+                "sha256:ab0d01148d13854de716786ca73701012e07dff4dfbbd68c4e06d8888743526e",
+                "sha256:c1a31cd42905b405530e92bdb70a8a56f048c8a371728b8acf9d746ecd4482c0",
+                "sha256:c20dd60b9428f532bc59f2ef6d3b1029a28fc790d408af82f871a7db03e722ff",
+                "sha256:c36ffe1e5aa35a1af6a96640d723d0d211c5f48841735c2aa8d034204e87eb87",
+                "sha256:c40fbb2b9933369e994b837ee72193d6a4c35dfb9a7c573257ef7ff28961272c",
+                "sha256:d46fb17f5693244de83e434648b3dbb4f4b0fec88415d6cbab1c1452b6f2ae17",
+                "sha256:e36f12f503511d72d9bdfae11cadbadca22ff632ff67c1b5459f69756a029c19",
+                "sha256:f1a25a61495b6f7bb986accc5b597a3541d9bd3ef0016f50be16dbb32025b302",
+                "sha256:fa411b1d8f371d3a49d31b0789eb6da2537dadbb2aef74a43aa99a78195c3f76"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
+            "version": "==19.0.2"
+        },
+        "qtconsole": {
+            "hashes": [
+                "sha256:7a42af4b1c51d870b41e4a1b67e2e71296c0edd1b2f46c647ad67dff421c2726",
+                "sha256:f236ead8711dba0702507dd8fad473c7216a86eefa6098eff8ec4b54f57d7804"
+            ],
+            "version": "==4.7.7"
+        },
+        "qtpy": {
+            "hashes": [
+                "sha256:2db72c44b55d0fe1407be8fba35c838ad0d6d3bb81f23007886dc1fc0f459c8d",
+                "sha256:fa0b8363b363e89b2a6f49eddc162a04c0699ae95e109a6be3bb145a913190ea"
+            ],
+            "version": "==1.9.0"
+        },
         "requests": {
             "hashes": [
                 "sha256:b3559a131db72c33ee969480840fff4bb6dd111de7dd27c8ee1f820f4f00231b",
@@ -521,16 +933,23 @@
                 "sha256:dc60bb302f48acf6da8ca4444cfa17d52c63c5415302a9ee77b3b21618090521",
                 "sha256:dee1bbf3a6c8f73b6b218cb28eed8dd13347ea2f87d572ce19b289d6fd3fbc59"
             ],
-            "markers": "python_version >= '3'",
+            "markers": "python_version >= '3.5'",
             "version": "==1.4.1"
         },
         "seaborn": {
             "hashes": [
-                "sha256:2d1a0c9d6bd1bc3cadb0364b8f06540f51322a670cf8438d0fde1c1c7317adc0",
-                "sha256:c901ce494541fb4714cfa7db79d0232dc3f4c4dfd3f273bacf17816084df5b53"
+                "sha256:390f8437b14f5ce845062f2865ad51656464c306d09bb97d7764c6cba1dd607c",
+                "sha256:62439a38482decdb263a8339f54ecb9823995ad8716abc830e91ca0753201e70"
             ],
             "index": "pypi",
-            "version": "==0.10.1"
+            "version": "==0.11.0"
+        },
+        "send2trash": {
+            "hashes": [
+                "sha256:60001cc07d707fe247c94f74ca6ac0d3255aabcb930529690897ca2a39db28b2",
+                "sha256:f1691922577b6fa12821234aeb57599d887c4900b9ca537948d2dac34aea888b"
+            ],
+            "version": "==1.5.0"
         },
         "six": {
             "hashes": [
@@ -542,10 +961,10 @@
         },
         "tensorboard": {
             "hashes": [
-                "sha256:a3feb73e1221c0a512398ad2cd08570fb082d8a2ba364aa0562543ecbd3659ef"
+                "sha256:d34609ed83ff01dd5b49ef81031cfc9c166bba0dabd60197024f14df5e8eae5e"
             ],
             "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
-            "version": "==2.2.2"
+            "version": "==2.3.0"
         },
         "tensorboard-plugin-wit": {
             "hashes": [
@@ -555,27 +974,27 @@
         },
         "tensorflow": {
             "hashes": [
-                "sha256:267017724a49c367ca5df536e5f6d3d59643eaed946c82233d6b371e62b5ddc8",
-                "sha256:3ee8819732d8594913b7d22ded7b22e48a49aa015050d8dd8464eaa010ba2e41",
-                "sha256:572f69d2d0a3d3d83ebfb2c24e6d73d88b85a09f5da796974ef4a0ad83ff7cde",
-                "sha256:6735486ee9c3cb0807476e2b36ef7a4cd6c597cb24abf496e66b703360e1e54e",
-                "sha256:68ea22aee9c269a6a0c1061c141f1ec1cd1b1be7569390519c1bf4773f434a40",
-                "sha256:784ab8217e4b0eb4d121c28430c6cdc2ce56c02634a9720d84fb30598b338b8c",
-                "sha256:7ed67b47cdf6598a79583de5b57c595493eac2b8b6b3a828f912354716cb8149",
-                "sha256:8f364528f70d895b96a0de36c7c6002644bf4c5df1ee3fbfa775f5cee6571ad7",
-                "sha256:bbcfb04738099bd46822db91584db74703fdddacf4cd0a76acfc5e086956b5ba",
-                "sha256:c332c7fc5cfd54cb86d5da99787c9693e3a924848097c54df1b71ee595a39c93",
-                "sha256:dc5548562308acde7931f040e73d46ae31b398924cf675c3486fd3504e00a4af",
-                "sha256:f5f27528570fc0d7b90668be10c5dfd90d6ceb8fd2ed62d7d679554acb616bfe"
+                "sha256:0cfb0fbe875408cdbfc7677f12aa0b23656f3e6d8c5f568b3100450ec29262a7",
+                "sha256:2d9994157d6a222d9ffd956e99af4b5e46e47338428d2d197e325362283ec835",
+                "sha256:36a4ce9bbc9865385c1bb606fe34f0da96b0496ce3997e652d2b765a4382fe48",
+                "sha256:44c8d979b2d19ed56dbe6b03aef87616d6138a58fd80c43e7a758c90105e9adf",
+                "sha256:5c9f9a36d5b4d0ceb67b985486fe4cc6999a96e2bf89f3ba82ffd8317e5efadd",
+                "sha256:6f74ef59dc59cf8f2002738c65dffa591e2c332e9b1b4ced33ff8d39b6fb477c",
+                "sha256:797d6ca09d4f69570458180b7813dc12efe9166ba60454b0df7bed531bb5e4f4",
+                "sha256:92430b6e91f00f38a602c4f547bbbaca598a3a90376f90d5b2acd24bc18fa1d7",
+                "sha256:b1699903cf3a9f41c379d79ada2279a206a071b7e05671646d7b5e7fc37e2eae",
+                "sha256:bc9d761a857839344930eef86f0d6409840b1c9ada9cbe56b92287b2077ef752",
+                "sha256:c33a423eb1f39c4c6acc44c044a138979868f0d4c91e380c191bd8fddc7c2e9b",
+                "sha256:c6fad4e944e20199e963e158fe626352e349865ea4ca71655f5456193a6d3b9d"
             ],
             "index": "pypi",
-            "version": "==2.2.0"
+            "version": "==2.3.0"
         },
         "tensorflow-estimator": {
             "hashes": [
-                "sha256:d09dacdd127f2579cea8d5af21f4a918036b8ae246adc82f26b61f91cc247dc2"
+                "sha256:b75e034300ccb169403cf2695adf3368da68863aeb0c14c3760064c713d5c486"
             ],
-            "version": "==2.2.0"
+            "version": "==2.3.0"
         },
         "termcolor": {
             "hashes": [
@@ -583,6 +1002,21 @@
             ],
             "version": "==1.1.0"
         },
+        "terminado": {
+            "hashes": [
+                "sha256:3da72a155b807b01c9e8a5babd214e052a0a45a975751da3521a1c3381ce6d76",
+                "sha256:c55f025beb06c2e2669f7ba5a04f47bb3304c30c05842d4981d8f0fc9ab3b4e3"
+            ],
+            "markers": "python_version >= '3.6'",
+            "version": "==0.9.1"
+        },
+        "testpath": {
+            "hashes": [
+                "sha256:60e0a3261c149755f4399a1fff7d37523179a70fdc3abdf78de9fc2604aeec7e",
+                "sha256:bfcf9411ef4bf3db7579063e0546938b1edda3d69f4e1fb8756991f5951f85d4"
+            ],
+            "version": "==0.4.4"
+        },
         "threadpoolctl": {
             "hashes": [
                 "sha256:38b74ca20ff3bb42caca8b00055111d74159ee95c4370882bbff2b93d24da725",
@@ -591,6 +1025,28 @@
             "markers": "python_version >= '3.5'",
             "version": "==2.1.0"
         },
+        "tornado": {
+            "hashes": [
+                "sha256:0fe2d45ba43b00a41cd73f8be321a44936dc1aba233dee979f17a042b83eb6dc",
+                "sha256:22aed82c2ea340c3771e3babc5ef220272f6fd06b5108a53b4976d0d722bcd52",
+                "sha256:2c027eb2a393d964b22b5c154d1a23a5f8727db6fda837118a776b29e2b8ebc6",
+                "sha256:5217e601700f24e966ddab689f90b7ea4bd91ff3357c3600fa1045e26d68e55d",
+                "sha256:5618f72e947533832cbc3dec54e1dffc1747a5cb17d1fd91577ed14fa0dc081b",
+                "sha256:5f6a07e62e799be5d2330e68d808c8ac41d4a259b9cea61da4101b83cb5dc673",
+                "sha256:c58d56003daf1b616336781b26d184023ea4af13ae143d9dda65e31e534940b9",
+                "sha256:c952975c8ba74f546ae6de2e226ab3cc3cc11ae47baf607459a6728585bb542a",
+                "sha256:c98232a3ac391f5faea6821b53db8db461157baa788f5d6222a193e9456e1740"
+            ],
+            "markers": "python_version >= '3.5'",
+            "version": "==6.0.4"
+        },
+        "traitlets": {
+            "hashes": [
+                "sha256:70b4c6a1d9019d7b4f6846832288f86998aa3b9207c6821f3578a6a6a467fe44",
+                "sha256:d023ee369ddd2763310e4c3eae1ff649689440d4ae59d7485eb4cfbbe3e359f7"
+            ],
+            "version": "==4.3.3"
+        },
         "urllib3": {
             "hashes": [
                 "sha256:91056c15fa70756691db97756772bb1eb9678fa585d9184f24534b100dc60f4a",
@@ -599,6 +1055,20 @@
             "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4' and python_version < '4'",
             "version": "==1.25.10"
         },
+        "wcwidth": {
+            "hashes": [
+                "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784",
+                "sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83"
+            ],
+            "version": "==0.2.5"
+        },
+        "webencodings": {
+            "hashes": [
+                "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78",
+                "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"
+            ],
+            "version": "==0.5.1"
+        },
         "werkzeug": {
             "hashes": [
                 "sha256:2de2a5db0baeae7b2d2664949077c2ac63fbd16d98da0ff71837f7d1dea3fd43",
@@ -615,6 +1085,13 @@
             "markers": "python_version >= '3'",
             "version": "==0.35.1"
         },
+        "widgetsnbextension": {
+            "hashes": [
+                "sha256:079f87d87270bce047512400efd70238820751a11d2d8cb137a5a5bdbaf255c7",
+                "sha256:bd314f8ceb488571a5ffea6cc5b9fc6cba0adaf88a9d2386b93a489751938bcd"
+            ],
+            "version": "==3.5.1"
+        },
         "wrapt": {
             "hashes": [
                 "sha256:b62ffa81fb85f4332a4f609cab4ac40709470da05643a082ec1eb88e6d9b97d7"
@@ -623,11 +1100,11 @@
         },
         "zipp": {
             "hashes": [
-                "sha256:aa36550ff0c0b7ef7fa639055d797116ee891440eac1a56f378e2d3179e0320b",
-                "sha256:c599e4d75c98f6798c509911d08a22e6c021d074469042177c8c86fb92eefd96"
+                "sha256:43f4fa8d8bb313e65d8323a3952ef8756bf40f9a5c3ea7334be23ee4ec8278b6",
+                "sha256:b52f22895f4cfce194bc8172f3819ee8de7540aa6d873535a8668b730b8b411f"
             ],
             "markers": "python_version >= '3.6'",
-            "version": "==3.1.0"
+            "version": "==3.2.0"
         }
     },
     "develop": {}
diff --git a/ml-models/anomaly-detection/Anomaly Detection-using-TF-and-Deep-Learning.ipynb b/ml-models/anomaly-detection/Anomaly Detection-using-TF-and-Deep-Learning.ipynb
index ac6cf97..5df104f 100644
--- a/ml-models/anomaly-detection/Anomaly Detection-using-TF-and-Deep-Learning.ipynb	
+++ b/ml-models/anomaly-detection/Anomaly Detection-using-TF-and-Deep-Learning.ipynb	
@@ -48,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 674,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -90,17 +90,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 675,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Retrieve data\n",
-    "df = pd.read_csv('raw-data.csv')\n",
+    "df_initial = pd.read_csv('raw-data.csv')\n",
     "\n",
     "# Set time as index\n",
-    "df['time'] = pd.to_datetime(df['ts'],unit='ms')\n",
-    "df.set_index('time', inplace=True)\n",
-    "df.drop(columns=['ts'], inplace=True)"
+    "df_initial['time'] = pd.to_datetime(df_initial['ts'],unit='ms')\n",
+    "df_initial.set_index('time', inplace=True)\n",
+    "df_initial.drop(columns=['ts'], inplace=True)"
    ]
   },
   {
@@ -112,7 +112,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 676,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -297,18 +297,18 @@
        "2020-04-23 11:14:42.999  pump-2  18.245524      0"
       ]
      },
-     "execution_count": 676,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df.head(20)"
+    "df_initial.head(20)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 677,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -393,33 +393,41 @@
        "max      48.423213     1.000000"
       ]
      },
-     "execution_count": 677,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df.describe()"
+    "df_initial.describe()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 678,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib/python3.6/site-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
-       "<AxesSubplot:xlabel='value'>"
+       "<AxesSubplot:xlabel='value', ylabel='Density'>"
       ]
      },
-     "execution_count": 678,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -431,12 +439,12 @@
     }
    ],
    "source": [
-    "sns.distplot(df['value'].dropna())"
+    "sns.distplot(df_initial['value'].dropna())"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 679,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -501,14 +509,14 @@
     }
    ],
    "source": [
-    "printmd(f\"Data collected between **{min(df.index)}** and **{max(df.index)}**: **{df.shape[0]}** samples from 2 pumps.\")\n",
-    "total_time = max(df.index) - min(df.index)\n",
+    "printmd(f\"Data collected between **{min(df_initial.index)}** and **{max(df_initial.index)}**: **{df_initial.shape[0]}** samples from 2 pumps.\")\n",
+    "total_time = max(df_initial.index) - min(df_initial.index)\n",
     "printmd(f\"Total time: **{total_time}**\")\n",
     "\n",
-    "printmd(f\"Time between samples: **{(total_time.seconds/df.loc[(df['id'] == 'pump-1')].shape[0])}** s\")\n",
+    "printmd(f\"Time between samples: **{(total_time.seconds/df_initial.loc[(df_initial['id'] == 'pump-1')].shape[0])}** s\")\n",
     "\n",
-    "for pump in df['id'].unique():\n",
-    "    printmd(f\"There are **{df.loc[df['id'] == pump].shape[0]}** samples for **{pump}**\")"
+    "for pump in df_initial['id'].unique():\n",
+    "    printmd(f\"There are **{df_initial.loc[df_initial['id'] == pump].shape[0]}** samples for **{pump}**\")"
    ]
   },
   {
@@ -527,12 +535,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 680,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1440x720 with 1 Axes>"
       ]
@@ -546,8 +554,8 @@
    "source": [
     "fig= plt.figure(figsize=(20,10))\n",
     "\n",
-    "for pump in df['id'].unique():\n",
-    "    y = df.loc[(df['id'] == pump)]\n",
+    "for pump in df_initial['id'].unique():\n",
+    "    y = df_initial.loc[(df_initial['id'] == pump)]\n",
     "    df_time = [pd.to_datetime(t) for t in y.index]\n",
     "    plt.plot(df_time, y[\"value\"].values, label=pump)\n",
     "\n",
@@ -568,12 +576,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 681,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIAAAAFiCAYAAACOHKN0AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAAsTAAALEwEAmpwYAAD0cklEQVR4nOy9d5hk11nn/z2Vc+fu6Yk9SSNplCUnHHFcR1i8YFizsLDghSWsd5fdx/xIJi3LEgxeDIsBYzBeGzA2wUm2bAXLsmyNskaTNHl6pnN35Vz398etc+vcW+eGnhm5WzXfz/Po0UzNrapb9557znve9/u+rzAMA4QQQgghhBBCCCFkcAlt9AkQQgghhBBCCCGEkOcXOoAIIYQQQgghhBBCBhw6gAghhBBCCCGEEEIGHDqACCGEEEIIIYQQQgYcOoAIIYQQQgghhBBCBhw6gAghhBBCCCGEEEIGHDqACCGEEEIIIYQQQgYcOoAIIYQQsuEIIc4IIapCiJIQYl4I8VEhRGYTnNeHhRDHhBAdIcS/3+jzIYQQQgi5XOgAIoQQQshm4e2GYWQA3AHgLgC/uMHnAwBPAvhPAB7b6BMhhBBCCLkS6AAihBBCyKbCMIxZAF8AcJMQYkYIYQghIvLfhRD3CSF+rPvnfy+E+LoQ4gNCiDUhxCkhxHd0Xz8vhFgQQvyw8t6PCiH+rxDiy0KIohDifiHELo9z+ZBhGF8BUHsefzIhhBBCyPMOHUCEEEII2VQIIXYAeAuAxwO+5SUAngIwBuD/AfgkgBcB2AfgBwH8kSOd7N0Afh3AOIAnAHz8qpw4IYQQQsgmhg4gQgghhGwW/lEIsQbgQQD3A/ifAd932jCMvzQMow3gbwHsAPBrhmHUDcP4EoAGTGeQ5HOGYTxgGEYdwC8AeFnX6UQIIYQQMrBE/A8hhBBCCPm28N2GYdyjviCECPK+eeXPVQAwDMP5mqoAOi//YBhGSQixAmCr+johhBBCyKBBBRAhhBBCNjPl7v9TymtbrvAzLbVPNzVsFMDFK/xMQgghhJBNDR1AhBBCCNm0GIaxCGAWwA8KIcJCiB8FsPcKP/YtQohXCCFiMGsBPWwYhlb9I4SICSESAASAqBAiIYSg/UQIIYSQFxw0YAghhBCy2flxAP8dwDKAgwAeusLP+38AfgXACoA7YRaKduNLMFPIvgPAh7t/ftUVfj8hhBBCyLcdYRjGRp8DIYQQQsi3BSHERwFcMAzjFzf6XAghhBBCvp1QAUQIIYQQQgghhBAy4NABRAghhBBCCCGEEDLgMAWMEEIIIYQQQgghZMChAogQQgghhBBCCCFkwKEDiBBCCCGEEEIIIWTAoQOIEEIIIYQQQgghZMChA4gQQgghhBBCCCFkwKEDiBBCCCGEEEIIIWTAoQOIEEIIIYQQQgghZMChA4gQQgghhBBCCCFkwKEDiBBCCCGEEEIIIWTAoQOIEEIIIYQQQgghZMChA4gQQgghhBBCCCFkwKEDiBBCCCGEEEIIIWTAoQOIEEIIIYQQQgghZMChA4gQQgghhBBCCCFkwKEDiBBCCCGEEEIIIWTAoQOIEEIIIYQQQgghZMChA4gQQgghhBBCCCFkwKEDiBBCCCGEEEIIIWTAoQOIEEIIIYQQQgghZMChA4gQQgghhBBCCCFkwKEDiBBCCCGEEEIIIWTAoQOIEEIIIYQQQgghZMChA4gQQgghhBBCCCFkwIlsxJeOj48bMzMzG/HVhBBCCCGEEEIIIQPJo48+umQYxoTu3zbEATQzM4NDhw5txFcTQgghhBBCCCGEDCRCiLNu/8YUMEIIIYQQQgghhJABhw4gQgghhBBCCCGEkAGHDiBCCCGEEEIIIYSQAWdDagARQgghhBBCCCGEXCnNZhMXLlxArVbb6FP5tpJIJLB9+3ZEo9HA76EDiBBCCCGEEEIIIS9ILly4gGw2i5mZGQghNvp0vi0YhoHl5WVcuHABu3fvDvw+poARQgghhBBCCCHkBUmtVsPY2Ng14/wBACEExsbG1q16ogOIEEIIIYQQQgghL1iuJeeP5HJ+Mx1AhBBCCCGEEEIIId8GMpnMhn03HUCEEELIAHApX8WHHzgJwzA2+lQIIYQQQsgmhA4gQgghZAD48b8+hP/5+aM4t1LZ6FMhhBBCCLlmeN/73ocPfehD1t/f//734zd+4zfwute9DnfccQduvvlm/NM//VPf++677z687W1vs/7+0z/90/joRz8KAHj00Ufx6le/GnfeeSfe9KY34dKlS1flXNfVBUwIsR/A0wA+ZRjGDwohXgPgqwBUa/OnDMP4q6tydoQQQggJRKnWAgB0KAAihBBCyDXKr/7LYTx7sXBVP/PGrTn8ytsPuv77u971Lrz3ve/FT/3UTwEA/u7v/g533303fvZnfxa5XA5LS0t46Utfine84x2B6vY0m038zM/8DP7pn/4JExMT+Nu//Vv8wi/8Aj7ykY9c8W9Zbxv4DwF4xPHaRcMwtl/xmRBCCCGEEEIIIYS8gLj99tuxsLCAixcvYnFxESMjI9iyZQv+y3/5L3jggQcQCoUwOzuL+fl5bNmyxffzjh07hmeeeQZveMMbAADtdhvT09NX5VwDO4CEEN8PYA3AQwD2XZVvJ4QQQgghhBBCCLkKeCl1nk++93u/F5/61KcwNzeHd73rXfj4xz+OxcVFPProo4hGo5iZmelr2R6JRNDpdKy/y383DAMHDx7EN77xjat+noFqAAkhcgB+DcB/1fzzpBBiXghxWgjxASFE+qqeISGEEEIIIYQQQsgm5V3vehc++clP4lOf+hS+93u/F/l8HpOTk4hGo7j33ntx9uzZvvfs2rULzz77LOr1OtbW1vCVr3wFAHDgwAEsLi5aDqBms4nDhw9flfMMqgD6dQB/YRjGBUfO2lEAt3X/vwvAXwH4fQD/0fkBQoj3AHgPAOzcufPyz5gQQgghhBBCCCFkk3Dw4EEUi0Vs27YN09PTePe73423v/3tuPnmm3HXXXfh+uuv73vPjh078H3f93246aabsHv3btx+++0AgFgshk996lP42Z/9WeTzebRaLbz3ve/FwYNXrm4Sfu1ihRC3Afg4gNsNw2gIId4PYJ9hGD+oOfalAD5rGMa412feddddxqFDhy77pAkhhBBi5zW/cy/OLFdw78+9BrvHKcYlhBBCyLXBkSNHcMMNN2z0aWwIut8uhHjUMIy7dMcHUQC9BsAMgHNd9U8GQFgIcaNhGHc4jjXA1vKEEEIIIYQQQgghm4ogDqAPA/ik8vefg+kQ+kkhxHcCOAXgHIDtAP4XgP4G94QQQgghhBBCCCFkw/B1ABmGUQFQkX8XQpQA1AzDWBRC3A7gbwCMAFgG8BkAv/A8nSshhBBCCCGEEEIIuQwCt4GXGIbxfuXPvw+z6DMhhBBCCCGEEELItx3DMOBoWDXw+NVz1sF6PYQQQgghhBBCCHlBkkgksLy8fFkOkRcqhmFgeXkZiURiXe9btwKIEEIIIYQQQgghZDOwfft2XLhwAYuLixt9Kt9WEokEtm/fvq730AFECCGEEEIIIYSQFyTRaBS7d+/e6NN4QcAUMEIIIYQQQgghhJABhw4gQgghhBBCCCGEkAGHDiBCCCGEEEIIIYSQAYcOIEIIIYQQQgghhJABhw4gQgghhBBCCCGEkAGHDiBCCCFkgDAMY6NPgRBCCCGEbELoACKEEEIGCLp/CCGEEEKIDjqACCGEkAGCAiBCCCGEEKKDDiBCCCFkoKAHiBBCCCGE9EMHECGEEDJAUAFECCGEEEJ00AFECCGEDBD0/xBCCCGEEB10ABFCCCEDBBVAhBBCCCFEBx1AhBBCyABhUANECCGEEEI00AFECCGEDBBUABFCCCGEEB10ABFCCCEDBB1AhBBCCCFEBx1AhBBCyADBFDBCCCGEEKKDDiBCCCFkgKACiBBCCCGE6FiXA0gIsV8IURNC/I3y2r8VQpwVQpSFEP8ohBi9+qdJCCGEEEIuh/uPLyJfbW70aRBCCCFkg1mvAuhDAB6RfxFCHATwpwD+HYApABUAf3zVzo4QQggh64IKIKKyUm7ghz/yLfzExx7d6FMhhBBCyAYTCXqgEOL7AawBeAjAvu7L7wbwL4ZhPNA95pcAHBFCZA3DKF7lcyWEEEKID6wBRFTqrTYA4NRSaYPPhBBCCCEbTSAFkBAiB+DXAPxXxz8dBPCk/IthGCcBNABcd7VOkBBCCCHBoQKIEEIIIYToCJoC9usA/sIwjAuO1zMA8o7X8gCyzg8QQrxHCHFICHFocXFx/WdKCCGEEF/o/yEqAmKjT4EQQgghmwRfB5AQ4jYArwfwAc0/lwDkHK/lAPSlfxmG8WHDMO4yDOOuiYmJyzhVQgghhPhhUAJECCGEEEI0BKkB9BoAMwDOCSEAU/UTFkLcCOCLAG6VBwoh9gCIAzh+tU+UEEIIIf7Q/UNUWBOKEEIIIZIgDqAPA/ik8vefg+kQ+kkAkwC+IYR4JYDHYNYJ+jQLQBNCCCEbAwVARAdTwQghhBDi6wAyDKMCs707AEAIUQJQMwxjEcCiEOInAHwcwBiAewD8yPN0roQQQgjxhR4gQgghhBDST+A28BLDMN7v+Pv/A/D/rtYJEUIIIeTyoQKI6GAqGCGEEEKCdgEjhBBCyAsAbvMJIYQQQogOOoAIIYSQAYIKIKKDNYAIIYQQQgcQIYQQMkCwDTwhhBBCCNFBBxAhhBAyQND9Q1ToDySEEEKIhA4gQgghZIDghp+ocDgQQgghREIHECGEEDJAsNsTUel0OB4IIcExDAOPnVvd6NMghDxP0AFECCGEDBLc7xNCCLlMPvrQGXzPHz+E+48vbvSpEEKeB+gAIoQQQgYI+n+IClMCCSHr4fh8EQBwYbWywWdCCHk+oAOIEEIIGSC44ScqTAkkhBBCiIQOIEIIIWSA4IafqMgSQEJs7HkQQl4ocLIgZJChA4gQQggZIKgAIioGBwQhZF1wziBkkKEDiBBCCBkgaLoTFTke6AcihKwHQSUQIQMJHUCbgFa7g2qjvdGnQQghZACg4oOocDgQQgghREIH0CbgJ/7mMdzwy1/c6NMghBAyAHC/T1SkQ5A1gAghhBBCB9Am4J4j8xt9CoQQQgYFeoCIAocDIYQQQiR0ABFCCCEDBLuAERWmgBFCCCFEQgcQIYQQMkBww09U6BAkhBBCiIQOIEIIIWSAoAOIqHQ6G30GhJAXElxDCBls6AAihBBCBgja7kSFCiBCyOXAwvGEDCZ0ABGyiWl3aLgTQtYH28ATFQ4HQsjlwLmDkMEkkANICPE3QohLQoiCEOK4EOLHuq/PCCEMIURJ+e+Xnt9TJuTa4LmFIvb+f5/HF5+5tNGnQgh5AUGbnRBCCCGE6IgEPO63APwHwzDqQojrAdwnhHgcwHL334cNw2g9L2dIyDXKk+fzAIC7D8/jX900vcFnQwh5ocCoLVHheCCEXA5MASNkMAmkADIM47BhGHX51+5/e5+3syKEWHD9JYSsD+74SY9O1wPEtYQQQgghgWsACSH+WAhRAXAUwCUAn1f++awQ4oIQ4i+FEONX+yQJuZbhVo4Qsh6o+CAqhuP/hBDiBdcQQgabwA4gwzD+E4AsgFcC+DSAOoAlAC8CsAvAnd1//7ju/UKI9wghDgkhDi0uLl7peQ8kLNxJCCHkSuFKQlRoWxBCCCFEsq4uYIZhtA3DeBDAdgA/aRhGyTCMQ4ZhtAzDmAfw0wDeKITIat77YcMw7jIM466JiYmrc/YDBm00ooOyfULIeuBaQlQ4HAghhBAiudw28BHoawBJO4Pt5S8DGmlEheOBEHI5GJw9iILBGkCEkHXA4s+EDDa+jhohxKQQ4vuFEBkhRFgI8SYAPwDgK0KIlwghDgghQkKIMQAfBHCfYRj55/vEB5EOw7aEEEIuE9G12rmUEBWOB0LIeuCcQdx4ZjaPhWJto0+DXCFBlDoGgJ8EcAHAKoDfBfBewzD+GcAeAF8EUATwDMy6QD/w/Jzq4MMJlxBCyJXCpYSocDwQQi4HCoGIk7f9nwfxxg88sNGnQa6QiN8BhmEsAni1y799AsAnrvZJXatQtk+0cAUmhKwDFv0lKhwOhBBCrhZrleZGnwK5QlirZxNBI42ocBNHCCHkSmF6OSFkPTAgTchgQwfQJoI2GiGEkCuFawlR4XgghBBCiIQOoE0Eo3SEEEKuFEZviQrHAyFkPQjWHiBkoKEDaBNBE43o4EJMCFkPjCUQGxwPhJB1QKcxIYMNHUCbCNZ8ISocDYSQy4FLCVHpdMeDEAwmEEKCwymDkMGEDqBNRIdGOyGEkCuESwlRkdF8BpkIIYQQQgfQZoK2GSGEkCuEG32iwuFACLkcOHcQMpjQAbSJYBFoooMSXELIeuBKQlQ4HgghhBAioQNoE0EjjdjggCCEXA6cO4iCDC6xBhAhZD1wyiBkMKEDaBNBBRAhJAgr5Qby1eZGnwbZpLCDC7HB4UAIIYSQLpGNPgHSg/4fQkgQ7vj1LyMcEjj5P9+y0adCNiFcS4gKHYKEkPXANYSQwYYKoE0EjTSigwpcoqPNtoHEBY4MosLNHCHkchC0QIkCG0wMDnQAbSL4XBEVOgQJIZcD1xKiQl8xIeRyoB1KVGhbDA50AG0i+GARQgi5Umi0ExVGbQkhhFwpXEkGBzqANhEsAk0IIeRK4VJCVDgcCCGXA1PAiAr3qYMDHUCbCD5WhBBCrhSuJUSFNjshhJArhWvJ4EAH0Caiw0R9okEwAEMIWQ+00ogCU8AIIevBsP7PuYP0oAJocKADiBBCCBkgaKIRFY4HQsjlwP0+IYMJHUCbCE60hBBCrhSuJUSF44EQsh6k8JyJCUSFCqDBgQ6gTQQfLKLC4UAIuRyY8kNUmMZBCLkcOHcQFToEB4dADiAhxN8IIS4JIQpCiONCiB9T/u11QoijQoiKEOJeIcSu5+90Bxs+V0QHuzAQQtYD1xKiQqOdELIerBpAnDuIAoNLg0NQBdBvAZgxDCMH4B0AfkMIcacQYhzApwH8EoBRAIcA/O3zcqbXAFQAEUIIuVK4lBAVGu2EkMuBMwdRYTBhcIgEOcgwjMPqX7v/7QVwJ4DDhmH8PQAIId4PYEkIcb1hGEev8rkOPLTRCCGEXClcSgghhFwx3JgQFQ6HgSFwDSAhxB8LISoAjgK4BODzAA4CeFIeYxhGGcDJ7uvO979HCHFICHFocXHxik98MOGTRXpwNBBCLgcqPogKhwMh5HLg1EFUmKkyOAR2ABmG8Z8AZAG8EmbaVx1ABkDecWi+e5zz/R82DOMuwzDumpiYuPwzHmAorSM6BEsAEUIIuUxotBNCLocONyZEgaNhcFhXFzDDMNqGYTwIYDuAnwRQApBzHJYDULw6p3dtQRuNEELIlcK1hKhwPBBCLgdOHUSFwYTB4XLbwEdg1gA6DOBW+aIQIq28TtYJHyxCCCFXClv3EhWOBkLIepDbEW5LiArHw+Dg6wASQkwKIb5fCJERQoSFEG8C8AMAvgLgMwBuEkK8UwiRAPDLAJ5iAejLgw8WUeF4IIRcDpw7iAprQhFCLgfOHESFa8ngEEQBZMBM97oAYBXA7wJ4r2EY/2wYxiKAdwL4ze6/vQTA9z9P5zrwUAFEVBjFJ4RcDpw5iIo0LVhPjhCyHrjhJyosCTU4+LaB7zp5Xu3x7/cAuP5qnhQhhFF8QsjlwbmDqMhgAscFIWQ9cM4gKgxMDw6XWwOIPA9woiUqMvLCqC0hZD3QSCMqtC0IIZcD1xKiQgXQ4EAH0CaCKWBEhaOBEHI5cCkhKhwOhJDLgWsJUWFK4OBAB9Amgo8VUenQ1U4IIeQKYXCJEHI5cOYgKlxKBgc6gDYRNNKICkcDIeRyYJSOqLAINCFkPbBuGNHB8TA40AG0ieCDRVR6AiBa7YSQ4HAtISocDoSQy4E1gIgKhQqDAx1Amwo+WKQHo/iEkMuBMwexYTCaTwgJjugGHjlnEBUOh8GBDqBNBEu+EBUuvISQy4FzB1HhcCBufPTrp/Hrn312o0+DbDJ6KWCcPUgPKoAGBzqANhF8rogKpbeEkMuBcwdRkQ0FWAOIOHn/vzyLv3jw9EafBtmkcF9CVOgQHBzoANpE0LNKVDgcCCGXA+cOosLhQAi5HDh3EBXaFoMDHUCbCD5YREWmBDJqSwgJgozOcSkhKrQtCCHrojtncO4gKixVMjjQAbSJoLSOqDCNgxCyHqwZg2sJUeBoIIRcDrRDiQrHw+BAB9Amgo8VUeEejhCyHuScwamDqDC4RAi5HKj4ICqdzkafAbla0AG0iaCNRlRotBNC1kOvc8sGnwjZVHA8EELWA9WkRAcVQIMDHUCbCBaBJipWDaCNPQ1CyAuEngKIawnpwfFACFkPHdaTIxq4TR0c6ADaRPC5IiqcaAkh68FyAHHuIAocD4SQ9cC1hOjgeBgc6ADaRFABRFQ4HogOpgYSPzhCiAo7ShJC1oNh/Z+rCenBfcngQAfQZoLPFVEwHP8nBGBRRuKO1QaeY4QocBNHCFkPci2hvUFU6AAaHOgA2kTwwSIq3MwRHVQAETcYtSU6OGUQQtYDU8CIDg6HwYEOoE0EJ1qi0hsPHBikByNyxA2DskFCCCFXiNVRkosJUWAAcnDwdQAJIeJCiL8QQpwVQhSFEE8IId7c/bcZIYQhhCgp//3S83/agwkfK6IiFWGdzgafCNlU0CAjbvSMdkJ6dOg1JoSsAwYTiA76fwaHSMBjzgN4NYBzAN4C4O+EEDcrxwwbhtF6Hs7vmoIpYESF6RxEB6cJ4kZPts9BQnpwNBBC1gPbwBMdjCUMDr4KIMMwyoZhvN8wjDOGYXQMw/gsgNMA7nz+T+/agjY7UemwBhDRwPFA3LCcxhwjRIHjgRCyHhhMIDo4HgaHddcAEkJMAbgOwGHl5bNCiAtCiL8UQoxftbO7xuCDRWwYtv8RAoCKMOKOwTmDaOCcQQhZD3LGoOKDqHA8DA7rcgAJIaIAPg7grwzDOApgCcCLAOyCqQjKdv9d9973CCEOCSEOLS4uXtlZDyh8roiKVQOIjkGiwAWYuEPVIOmHcwYhZD2wCy3RwWDC4BDYASSECAH4GIAGgJ8GAMMwSoZhHDIMo2UYxnz39TcKIbLO9xuG8WHDMO4yDOOuiYmJq3T6gwUnWqLCInxEB5WCxI2eAohjhChwM0cIWQdcS4gOriGDQ5Ai0BBCCAB/AWAKwFsMw2i6HCqHBtvLXwZUehCVDtM5iAZG84kbrAFEdHBcEELWA+cMooP71MEhkAMIwJ8AuAHA6w3DqMoXhRAvAbAG4ASAEQAfBHCfYRj5q3ye1wR8rIiK1dKZEy5R4XAgLnCuIDpY0JUQsh640Sc6OCwGB1+ljhBiF4D/COA2AHNCiFL3v3cD2APgiwCKAJ4BUAfwA8/f6Q42NM6IihwOVHwQFRpmxI1e1JZjhPRgS2dCyHro2Z+cNUgPjofBwVcBZBjGWQDC45BPXL3Tubbhc0VUDBrtRAPHA3GDXcCIDqZzEELWA+cMooPDYXBgrZ5NBD2rRKVD2T7RwPFA3GDnFqKDBV0JIeuhF4DknEF60P4cHOgA2kTwuSIqVg2gDT4PsrlQUwK5GBOVXuNAjgvSo1dPboNPhBDygqBXN2xjz4NsLjgeBgc6gDYRfK6ICgt3Eh3q5p5Dg9ig0U40sJ4cIWQ9MABJdHANGRzoANpEMAWMqHS4mSMa1PHAOYOoGI7/EwKoQQSODEKIP1QAER0MSA8OdABtJvhcERuU7ZN+1PHAoUFUWAOI6OBmjhCyHqzOgZw0iAIVQIMDHUCbCEbziUqnY/6f9TyIijpPcM4gKobmT4RQ/0MIWQ90GhMddAgODnQAbSL4WBEV6fihx52oqMOBazFRodFOdDCaT/zg2CAqbChAdHA0DA50AG0iGM0nKqwBRHR0FI8gxwZRYbcnoqPXBp4QPZwziArTiYkO7lMHBzqANhF8rohKbzxwYBA9jM4Rld5Gn+OC9NOhnJS4wI0dUaHTmOjgNDE40AG0ieBzRVQYgSE67F3ANu48yObDku1zXBAFay3Z4PMgmxeuJUSFawnRQUfx4EAH0CaCOdhERY4GTrhEhUWgiSuM2hIN1uaeA4O4QNUgUWHdMEIGGzqANhGcZ4lKh1FbooFFoIkbrAFEdFjjYoPPg2xeOGcQFaaAER0MOg4OdABtIvhgERV29CE61HmC0TmiwhpAREdvLeG4IHo4NIhKLwWMA4P04HAYHOgA2kTwwSIqVAARHeo8wTmDaOG4IArMACN+MABJbND+JBpYK2xwoANoE8HniqgwAkN0GKwBRFzgRp/okHMG5wviBscGUelYqsGNPQ+yueA8MTjQAbSJ4EafqLALGNFhuPyZkN6cwZFBejCdmPjBoUFUZBoxN/zEBofDwEAH0CaC8yxRYT0PosPeBp5jg/SgAojoYEFX4ofR2egzIJsJzhlEB23OwYEOoA2G6RzEjQ4VQESDvQj0Bp4I2XRQ6UF0WEEEjgviAgNNRKXDaALRYO9Cy8HxQoYOoA3GVtB1406DbELk2KBjkKiwCDTxg8OCqFj1PDgyiAss7kpUrHRizhlEoWMTLWzgiZArhg6gDUZ9frjRJyoswkd0dKgaJBoMmzKM44L0oDKM+ME5g+jgsCAq9gAkB8cLGV8HkBAiLoT4CyHEWSFEUQjxhBDizcq/v04IcVQIURFC3CuE2PX8nvJgYTCdg7jCNpzEG44NIqGalLjBgq7ED0bziQpLEBAdBhVAA0MQBVAEwHkArwYwBOAXAfydEGJGCDEO4NMAfgnAKIBDAP72eTrXgYTPD3GDOdhEh00BxBWYdDFc/0KueVgCiPjAaD5RYQkCosPehZZj44VMxO8AwzDKAN6vvPRZIcRpAHcCGANw2DCMvwcAIcT7ASwJIa43DOPo1T/dwcPW0YebOaIgDTIuwESFw4HosKlJaZgRBUbziR8cGkSF8UeiQ92ncj15YbPuGkBCiCkA1wE4DOAggCflv3WdRSe7r5MA2Dr6bOB5kM0HF2CigzWAiA57d44NOw2yCeFwIDrYhZa4Qacx0UE7Y3BYlwNICBEF8HEAf9VV+GQA5B2H5QFkNe99jxDikBDi0OLi4uWe70DDBZio9IpAc1yQHvbC8Rt2GmSTwe5wxA0W7iQ6OpwziBtG3x8Isc8ZHBsvaAI7gIQQIQAfA9AA8NPdl0sAco5DcwCKzvcbhvFhwzDuMgzjromJics83cGDRjtxo9eGk5Ae3MwRHaoxRsOMqDBqS3RQTUrcsBToHBZEgY2LBodADiAhhADwFwCmALzTMIxm958OA7hVOS4NYG/3dRIAu9FOSI9eEb6NPQ+yuWAXBqKDwQTiBlN9iI4ON3PEBdagJDpsdWs5Nl7QBFUA/QmAGwC83TCMqvL6ZwDcJIR4pxAiAeCXATzFAtDBYTSfuGE5BzkuiILh8TdCAI4KYsdmZ2zcaZBNBp3GxA2rBMHGngbZZLBu7eDg6wASQuwC8B8B3AZgTghR6v73bsMwFgG8E8BvAlgF8BIA3/88nu/AwQgMcaPTMf/PYUFU1C4MVAARCTdzxA2b0phjg3RhChhxQ84ZHBZExZZO3Nmw0yBXgSBt4M8CEB7/fg+A66/mSV1L2Au6XpszbbXRRscwkI77Dsdrimt5AT61WEK12cbBrUMbfSqbDtbzIDrsdX84MEgPuwKIY4OYUBlG3JBjg+OCqNgVQBwdL2TW3QaeXF24AANv/6MHcfBX7t7o09h0SHXHtegYfO3v3Y+3fvDBjT6NTQmjts8fL+Q0XCqAiBscG0QH1xLihuUA4rggClxLBgc6gDYaFtTCcwslAMBCobbBZ7LJYAkgokMzZ+SrTcy873P4pydmN+ikNgeX8lW86QMP4PRSed3v/cfHZ7H75z+Pv3rozNU/scug3mrjNz/3LPKVpv/BAPU/xJVr1bYg3gxqG/gzlzH/E5NKowXDMOj4IVrYUGBwoAPoCji1WMLj51av6DNsErpr/Fm67/jiRp/CpkJOrtf4sCAOdEb7xTWzNv8f3nNiA85o8/DVows4Nl/EH9xzfN3vPTJXAAB88Zm5q31al8W/PHkJf/a10/i9Lx8LdLy9PevVmzVqzTbWKo2r9nnk2w9TzYmO52vO2Eg+//QlvOZ378O9xxY2+lRecBiGgTt//R68+8+/ac0ZnC9eGBy5VMCpxdLz/j3MWhkc6AC6An7ts8/iFz7zzBV9hrqZ+4fHZlFttK/wrF54jKVjAIDzK5UNPpPNhRwag2KYXQ6tNqvMOdEVdK00WgCAUr21Eae0aUjHzDpiT1/Ir/u9hap57VY3ibOj0TLHfr0Z7Bl4vhRA7/7zb+K2X/vyVfxEk07HQLEWTN20mXghzkmU7RMdqv05KA0FnrywBgB49mJhY0/kBUi91UG12cZDJ5dxKW8q8q/WfPGt0yu8J88j/+NTT+EX//HK9qNBsM8ZAzJpXKPQAXQF7JvI4NRSydaVZ72om/ulUh0/8tFvXY1Te0FR7m5eF4v1DT6TzYWlAPo2z7HfOLmMj3/z7Lf3S1241h0aOnQFXfNVcyN9rV8v6VA4tVRe97xc6F7DlfLmcADJeytcWzA4jn+eNvmPnl3tfubVnYj+9IFTuPn9X8Jy6YUz7//Doxew7xe+gLn8Cy1dma17ST+DWNBVuPesIT4UNA75qzXtf9+ffgNv+eDXrs6HkT4Wi3UcnSuu+33PzObx8KnlwMd31ikBqjba3xZlElk/dABdAXsnM6g1O7iYr172Zzifn4dPrVxTio9mu4NaN8K9dJU2AqV6CxdW16cm+rV/eRb/6wtHfY/7nbuP4j1/fejbEgXudWH49o6HH/izh69Y2XYlqBt3qcoIgmEYl6X8eKFhL9xp/n+tWyemMoAKwnbHwMz7PocPfNk/ratQ642X08vrqwMhnWirlcZlzcFrlQb+6Ksn0L5KofRWe30OoOc7m3g9z2IQPv/0JQCms+6FwpefnQeATZNecv/xRRw6s+J7nD1t9NqxL4g3trXkhSds84TjfP0Ua/1z/KA4BgcZwzCwUmlgpdxY9z7qbf/nQXz/hx8O/l0uf3bj5/7+Sbz29+5HrTl4tukLHTqAroC9ExkAvSLGl4NujSpfhU2cYRj4rS8cwfH59XuEv52oC87VUgD94J9/E6/47XvX9Z6PfP00/u/9J303bx+69yS+9Ow8/uGxC1dyioEwNkgBJLlaG9n1Umr0xoQuIuXGY+fW8PY/ejDQhujbxXMLRSs9Kyinl8qexqu9Dbz5tzWlUPALMUXFC6nI+eBX/esbqfPJep2Bcqw128ZlKanuPjyH3/3ScSsF4UqRDqmg2FMDr/6zu1y+ukqdkW7q79nlF07q79bhJADgoZPBI6bPJz/8kW/h3/zfb/geZ6v14nNstdHGn3/tlOc88jcPn8X3f9j/e58vjs0V8aYPPIDnFja3fbPp0ahJr4SHTi5t+D2RG02dM2Mz02h1Ahf8lxybK17V0glaBxD9P5ueSqNtpYw/33u+9RaBfvC5JQBXtk/+dpCvNq+5Eix0AF0BeyfSAICTi5cfwdQZ6qtXIQVhrlDDn95/Cm/8wANX/FnPJ6XLcAD9zcNn8Qufedr13584vwZgfc4DyWM+Rb23dTcAJ+af38nsIw+expPdDeyVrL/NK3AGFAJsQBeLddz561/GU1dp0wvYjZAg5yCRXeQ2y0LT7hh4/e8/gO/+0NcDv+fYXBHf+bv34V//8UM46SKbNTQKINVZ8IdfGaxC0AtF874GEcKU6k0MJaNIREN4ap0OIPUarpbXP3csFMz569QVrAcqcuwHVXU934b61U6Ny8bNek0vJHn4WtW8BqeXrv45F2vNy3bc+b3P7jT2/qz7jy/iNz53xDLcdTx1YQ2PnFndMJXF104s4th8ET/18cc35PsHhSBdwI7PF/GVI/OBPu/f/tk38frf31ibU1VyvpD4H596Erf+2pfWFcB50x88gFf+7/UFO70oPU8OoPX8pgeOL+Leo8EVloZhKoR/P4BC+Pni809fwqceXV9Q+ORi6arVwFPH+vHLSAMDEDhlfr2p5qPdQM+xyzyvbxe3/uqX8F0fenCjT+PbCh1AV8BYJo6RVNR1o6by3EJJn1+rOXbNIwpQbbTxb//sYasugxtyM2L+efPWK5DXZM9EGkulYKkXn3/6kpU+4MXsarDUPHXie+LcmuexcqK9krS/IPzaZ5+1/ny5hdYqjRZu+pW78Tt3+6e26VgJYEA9enYFy+UGfu9LV2/xVRfF9aggpOPo3CYpJi5rmxyfLwXePMtuXk+cX3M1aOwLcK8GUDYRwZsOTuFvHj4byOA6s1R+QchyF7qOYREgF6pYa2E4FcXBrUN4enZtXd+TrzaxfcR08AYZ+04WS9IBdHWcA3LsB3WCrmeTP7tWtSKGQVm+yg4gOfdfLYfZeslXm3j7/3kQJ9YRMZVrs9carfJ3j5wP5JA+MV/Eze//Er43gJpHoio0l0re90Y3Z7ghx5uXgq5QbaHduTylnI7Hzq3iHX/0oK9dI5HBouMLxcsK9ATl8MX8usZHUDodI/CmuFBr4ic+9qi1NlwJDxxfxMz7PmeliXQCRPPf+IEH8B/+6tAVf7dKpdHCG37/fjzyPKh1pY22chlO/I3kC93uk4cCPgNBg3uffeoidv/851AO8KzqHBJXQxm2HjXWD33kW/iRjz4S+PjZ7nPxwasY+Gq1O/jdu4/hXEB16kcePI0/ue+5wJ9vGAZe93v34wf/4urUfFUDVsfXEQBV1xC/e/TcQgn3PDsfaM5QSUbDAIBjmzgbpaeeeuEEo64GdABdIXsnMjgZ4IF7/e/fj3f9aX+epe758YpcnFku46GTy3jnnzzk+X0Liprm0lUsWFlrtq9qsWY56ewZT6PR7gTa8J9eKmO10nQ1oCIhc6MY1AFUVBZGL2O91mxb0fjZteDX9MilAl70m/fgcR91kSuXuf4emyui3urgQ/eeDOxIUTcHwZRo5rU+H7Dm0jv/5CH88Ee8Fz2bAmgdxr089nzA+75ePvGtc/jkt84FPv6i8tx97cRioPdIR9GO0aSrtNsWte3+f63SwHAqinfcug2rlabvRqrV7uA1v3sffurjjwU6r9/+4lHc8ev+naCKtSaOXLq6nT7kfBNEAVSstZBNRHDztiE8M1sInMbY6RgoVJuYGTNVnZejwpTnGSQgEATLARTQeLan+bj/7karg5f/r6/iv3/qSd/PVJ3jV1sBJJ0olwIGKEr1Fj7y4OnAkcoLqxXPTc+DJ5bw9Gwev/ulY4E+D+itzUEcQO2Ogf/xD0/h9b/vX/9A1kE6dHY18O9bU+yEEz5pN7Zivz4fL+fRp2Y9HEDdY9zWlWNzRfzp/Se9v0jhvqMLeOpC3hb48EKuN4YBPHL6+Uv5fesHH8QbAqqoDcMInI7zno89in2/8IVAx/79oQv44uE5fPiBU67H3HdsAd/1Rw/6OpX+5mGzuYNMYVzPuPBzHKpj3O88js+XcGKhhPf/82HvL70MVi0n7frmqw98+Tj+7tD5QMdeXKsGWlsePrWMmfd9LpDz7tYdwwCALwQIbgLBU2d/+Z8OwzDMrAA/nq8UMNWO87puagpOUHWMTHnKdBWlV4Pj8yX80b3P4VW/c2+g+Xi+WMPFtVpgRaTcczzZzVbw4k0feAC/9fkjnsfIgFU8ElqXw1rda/op5n72E4/jx/76kE0ZGuTnys/99GMXrooYIV9p4oNfuXq1FgFzX30tQgfQFbJ3IuNr8MuFUbcx0hnqXg+iatB6GeQybcL8czCHzcz7Pof//UVvtch//NijeNFv3uM70XU6Br5xctn3gZeT/N5Js57SfMH7XCuNluXQWnUxwrMJcyEIqtJRI+xehrQaAQ/qXAKArx5dwGKxjv/2d/4bLh3OK71YrGPmfZ/DV496y7LVXOCghmlVMeKCRPzltQsaKXn07CruP+7tDFFlyF9/LnitjfUqgH77i0fx0a+fDnRsvdXGz3/6abzv0+6ph04uKUbfQwF/h3z2b90+jAsuY8yWAtbpKYCGklG8bO8YAOBpj80b0LtWXwkotf6T+05ipdzwrVHwM594HG/+w68FVhY9fSHve6zlAArgASrWmsjGo7hl+xCqzTaOzgVzRpUbLXQM4LqpLABcVmRazrNBFC2/+bln8V0+qYHSaL7aCiD5uf/85EXfzyw3gq03To7NFX0L8fecKcE+93fvPoZf++yzgcZsp2PgFb99L/7VH7pv3uMR0/ypNoMroaTjp1Rv+Ubg1XnMzymqOhyDRsvV++E3v9u7PXkjHY6eCiAfB9D3/ek38FtfOBq4poJ0lq8ErDN1fqWKF+8eRSQkfNO2nZTqLTx9Ie9rw9Rb61NH/sWDp/HK/31voBo493RTqoJsGOU18drg/tzfP4UnL+R9bT1Zw0quTerX+0Xzaz7PiWq3uq1dzu+qr0OFeM+z84EcKXI+mS8G32y22h384VdO4H986infY5dLdbzmd+/DPwRI+flY1+EWpMuS3ND+w2OzgZwf6r7DK1Am54kg84p0TGzJJazX3EbFarmBH//rQ4FsS/W7dWlmkmcv9eacoC3jj82Z12E4FfU87vxKJXDx/kWlkPKiT1FlwzCwUKij2mwHDrQuBdyTGYaBY/NF/KmH8xforR937BzBsbliYEeUWjDaS/Xc6Rg43Q1SrCe1vtMxsFis4/U3TGKp1MCnPGqnPjObx8984nFfe/BXP3sYv//l47jP514eny8Gti3Ukh7rVUa/kKED6ArZO2mmLnkNNK9ooe459TpenUi9nBBqClgQxY586P74Pu+ondy8+zlqfvvuo/iBP3sYv+IT4ZG/50B34+XntDmz1Fts3IqSRsPmsA7qpJGT9pZcAicWSq6T50pXZn/ztiEsleqBN7nSIz9XCB4hUHG+R6a2fPQh71btcmEE/BcxibqpCKKCkDUxWh0DZ6+SF10aM7vGUvjnJy8G3sTLsRTU2fUn953E+//l2UAb2wdPuNfDcEM6Kl88M4qvnwz2/pVyA+GQwA3TOayUG1oFg04BtFJpYjgZw3AyipDwVyhcbtrEcZ/NzaNnzM1YkIjKueUK3v5HD/p235NO5Gbb8N1QFmstZBIRvGLfONKxcKDOfkBvDrh+SxZvv3Ur/vxrp9edHifn2bPLFd8I+J997bRv9C/f7boVXL2n/7MT6VAKMhWp3/2Mj1NR5U1/8IBvIX45RoOqreQGM0htDyk3P79Sdb3O0tldW0fhx5Vyw3JErucZ87uHqvEdtNi2mvblt7kr1Xu/MWgK2Fyh5hrAkR3h3BzCcgMbtCONXKuXisHGwoXVCvZNZjCeidtsnSD8wZeP4+1/9CB+525v5dd6a8l95cjCut8XpLPeuRXz2lQ95qNo2ByUfmuZdHqe6QZs1uMY9BvDahqK3zWQ4zWok63WbOPH/voQvuN/fTXAeZjX4PxKFZ8IqNhdT3rKU7N5NFodPBtA6RrtqtGDbCrz1SZGUlGU6i1885R/AEJ1Kl9yUaSrz3qQdUQ+tzIV2vkZKo+cWcGXn53HD/kougF7EMPL9lDbmD8T0AEkg7Z+Dso3fuAB/MhfBkstU/dMfk7HQrVlOTJnA6Zp+qXsSoKmXcs18SV7RlGotQIH/dXf6bWHPbVU0s4/fk7jtWoTrY6Bl+8bxw3TOdx/zD34+6F7n8O/PHnRt7yHnDP9nqk3fuAB3yCbRHWmzm/ikilXGzqArpB9XeWKVyFoL4NV9wB5Ha9Onl4R1sVS3SqyGcQBFGSiUTdEXgv8armBv/z6GQD+6WeHzq4gEQ3hlu3D5vE+qVWnlZbBKy6TqDQugqaqSUP+5u1DKNZarnUNpGF+07YcAGAuYGrd4e5CVmm0L6tmglPp2GiZL0jjwo0TC0UrKhL0WqhGXJA6KOom6F8CKAqCIA36P/z+2wEAT50PtvGUxstKueF7nVXHypcOz/l+9tcUB1BQo/VSvop4JIS33jKNC6vVQI6p1UoDI6kYdo6mALil1vXnYM/lq5geSiAUEhhOxXw3yZfb0tuvkJ/s7HRywd8BdLJbSNeva4VqzCz4RHVlCthkLoF3vWgnvhkwPUQax7lkFC/ZPYpGu7OuAuSGYWChWMNwKopGu+MZAVfnDa+xJL9/rdoMJHdW1aRexwdNKQN612XvRBpfeGYukBMoSG2KRquDUr2FcEigUGsFqocSCZnmynIA4/lbyn13U9/ItdRrY63S7hgo1JrY3U0TzFe9z0N1ygTdtALBlVYr61ANqYoCv5GkfpZbtNdPARTpBmGCBh7kxqnabPvWKmm0OlitNLEll8BYJrbu1ESZ/uQ3l11u0dLzK8HVwYslfxvi2YvmPfBaw8NdW8DvekuFhwwi2YtA+zgGfYIGa8rz4KfKknNbPaD6TrUzvJRprXYHhVoLP/mavRjPxH1VApInFCex38bycHcODBLwCnW9xX4BU8C8JnfuGgUQLKX+C0/37Ba3wKlq1wdZz4q1FtKxsFW4F3CfL+Q8cTpALUF17HiNI+kAHk3HrOvsh9ywL5frnuuInOeDrDXqs+Zn56s2ycWApSHk5yei3lvwoEHspVId4ZDAi2bM8RO0E5jq3PKqmfVc156TDmSJXxDpUndcTmYTeM2BCTx6dtV1fh9KmnuVLz7jbY8HUYJL+ydomqT9Hj6/9V03E3QAXSGyFbxXGpi6GXNKO50PUDYRCawA8tpkLBTq2DaSxHAqGsjIcHOmqBxWPPJev/fIXAGNVgej6Zin4VtrtvFPT1zE22/ZipmxFELC/+FTu68saQy/RqtjTfRBu0DIc9wxYm663YxpaWjetG0IQLCJolxv4eRiCTNj5mcHMQSchpgzTVA6N6TSyY3TS2W8uLsgBHUALSnR5yAbrbVqE2PpGA5MZfG4TwHtoNLK2bUqsvEIbtk2hEw8gmcuBnUA9e6bn7NFjdT4pUsB9g1l0IjzXKGOLUMJvHyfmZb1dY+uOpLVchOj6agVgbug2UzYhodhXteFYt2S9w+noljzMfbUecgvxz2o41d+d5DjAOBC9x5NZOOexy0U69bn+jl08tUmcgnz2LFMDI1WJ5CSp+cAiiDXNUTWo5I6s1xBrdnBa66bAGBGzNxQZe5e82Oh2sTWoQQarQ7uPx5gI6PcRq9zX49jSzoK3/2SXQCCGVTqvOim2JLRxj3jpjPFb7wCZoc3INjm6OhcASOpKGLhkC1ooCLni0ojmEMsX23CMIAZec4+CqD1FLNfviwHUG8e8ncA9f49SA0guR4/fr5/I28YhjWG3H5XrLs2BUl16HQMXMpXrXnATzUkv3MkFcVoOqa1A9wo1pqWotTPPlA3X0FS2WSAyOvZd+IXqT+1WLKCi17O72jA6y3HwTOzBRy+aE+D042L9ShI5POQjIZt66UOOT8FTQFTnUteKXbSuT2VjeO2HUOBN4BnlDnCz6572nIA+X+2nNeC2Ir5ahN7JtJIRsO+aexnlso4Nl/Ee161B4B7oxf1ngVRAJW6CtqxTG9NdjMPVKWin5pVDTp4BZ9WynXkEhHcvmM4sN0nbVvDCBbIDhKEtTkEfB1Aar3V4A4bAIhHwp7HBXVGLBTqGM/EcP0WM5MiqPP6yQt5y6HipcS11uvuflfiF0yQc9feyTRevHsUrY6BJ106BsvrGFRB6dUd1SvNUMdyqWGpKIPOGYMAHUBXyPaRFGKRkGchaNVQ9MuN3jOexj8+Mes6kfQ2/8JbAVSsYSIbx0QmHlAB5H/MQ8oG1ssBJB+g23cMexqzS6U6Ko02XjQzikg4hKlcwjcF7NRSGamYOWmuaAxF1egOsqkwjzPPUW663YxpaRDesXPE/HuAyfnJ82voGMC/umkaQLCObM6JzWmYye5S0Yj741tvtXFxrYrrp3PIxiOBHUDSEEpGw4Hek682MZSKYttI0nehVDelXs6g2bUqtg4nEQoJ3Lg1Fzj1pFhvWhEVPwNKPjvxSMhXalyqt3BkroDbdw4DCFZMETAXzZFUDHsnMkjHwoFk5ivd9+zwUACpBlnHMCNghgFs6zqARlIx39xn9V74GU1qBMxv0yQ3SqqTww1pHMguEW4sFut41f4JbB1K4J5n3eteleumem8yZxqvMqIUxPCVRulQMopct4bYepQysk3yj73SNMi9jBg10uaWQtPuGCjWW/ieO7ZjJBXF557yV6kFNfbX49iSnyOVrosB6mqcUQwot3VC1m/bbTlT/A136Tz3W0MBU2I/lUtg11jK1QHUc2IEu8/yeKnOc6tBJ7EpgHyOXS03rKh7UAfQsfkiUrEwJrJx35ohxVoT6e66GSQFbDKXwF0zo/iy5nkrN9rWHOSuADKN6SCpDkulOpptAzd3Ayv+DiDzM4dSMYxn4oHrBgFmZLxjAKlY2N+Bp9Zb9Bmf7Y5hjXu/DYzqcPRbY2U6xB07hz2PlY0v/K53sda0xu+9Rxf61hInalqNn+NYrg1vuXkaj59fwyGPOmpyvg2qplXv1XMBgq3DqRh2jaVxZrkcKO1evW5+tsMzs6a9cH7VP9VXOhL87Npas416q4OhZLTbAML7eKnweO31kwDc1/D1qBDlMblEFFuHejWA3DzG6nf6dS5Tx47XXLVcbmAsE8fBbUN4bqEUyPG6WKxjsus8DtLwJkgtpMViHTNjKcQjIcz53Ds1ZShoCph8liM+Kv6gn7dQrGMym8BYJo6xdMxW08aLx8+t4RX7xhGLhDznXbnWyYCNxC8F7MR8ESFhrvN37DD3TY+5jBXp7JpdqwZ6Zr3G0XpLHCyXGrhtxzAS0ZAtDXHQoQPoCgmHBPaMpwMrgM44jFHnOP/lt9+ItUoTj51d035WsdZEOCSwbzKLsx4LlZwQpnKJQAZzoDoozy3h4NYc9k9mPI2Rs8sVRMPm5r1Qc09fUNMuAGB6KBEoBeyW7UMICf05q5u2oK165XE9B5D+faeXypgeSmDPhDkJBpF7Sin0mw5OAQhWkNv5u/ocQN1/9zI+zq9U0TGAmbEUJrLxwFL85xZKyCYiuGlbzjfdBjA3NsPJqHnvfBbKoEbA7GoV27r3YvtIMpBqyvzMFq7fYqbn+SmAZNHqt9w8jSOXCp4btItrVRgG8PK94wCCp/6Z6VxRCCEwlIwGMjxWyqYDaCwdQzIa1j67hiMFTC6c08Om0TacjNpS+XSoUTi/36Mar0E3AfcdW/TdlMqNedEjIidTq6Zycdw1M4ojHvWgpCEmC1iuzwHUtN6T7SqIgipl8pUm/vLrZ3Bwaw43bRvCtuEknvRIW1SdHW5OavndY5kYdo6lAz2/n33qEoQA3nbLtOfcp957vw2YWo8rHBKBzuOckhrh5nxZdUQU/ZwpQM95HiQqKh0qM+NpdwdQ97ctl+sB62OY121XV83p57Qq1tdTA6iJfd1rESSKbRgGvnpkAS/fN45hn7ml2e6g1uxY62yQFLBcIoq33jyN4/OlvuunPhdu41dubNaTfi6j135ODDm2h5JRjKVjgZSqEvnZ101lfZ3Z6vzlV6dqrdJAo9VBIhrC4+fWvANfSp0jv+vzuafncMfOYdyyfdjTdpBKmmWf57NUa2H7SBKZeAQr5aa9oYBm07UeBYm8L+978/UYz8Twfz26wMlnr9bsBFIGy8+ORUKeDrY1ywEUxcxYCrVmJ5DNtVSqY7rr9PBSGK6WG5hdq+KmbTk02wa+ftK7uLNUCx+fL3raa/J65BIR7BhJ+RbQl10Db5jOIRkNuyr4g9bekayUGxjLxDA9rNQAcju21MCWXALbR5K+KUfq/OT13K105+0942l0DH/HmUwHfcU+0zYL0oE0yHVY7O6ftg4nfZ0wcnyNZ+KBU8Cks8VLxQLYledeqdWLxbqloLx5+xC+cWrZ14nSaHVwfL6IW7cPY0su4RnYXKs0EIuEsEV1DMJfTXpivoSZsTTikTCGUlHsmUi7Ku7l99dbnUCBA68AnTpXBVGAL5XN+31gKotj81e3i+1mhg6gq8CeibRnDSBb9MKxeMnN3PfdtR33/txrMD3k7YSQNS5u2JJ1nexk5fXJXBwv2T2KwxcLvps81WBxmziOXDJVECNp77z7s8tl7BhNYSwdg2G4Gw55ZdMFmKkgfkqkU4tl7J3IYCSll37LBW/bcDJwBfilUh2ZeMSaQN2M6ZNLZeyZMCeziWw80Ebk8MUCdo+nsb9b5DpIgTHnBsB5P6TB67WQyfz0XWNpjGeDqcAAc3zun8xgMpsIZDitVRsYTsWwdTiJtUrTM2KTtzmA3Cfv2bWqpWYZDVDPRv3M7SNJZBMRzyjeYrGOD371OWwbTuI9r9qDRquDv3jQvcuCNOJu3m5GqIMWiVstNzGSMqP62UTU1yHytROLeG6hhOunsxBCYPuIvhW8swi0NJJ6KWDrUwD5Rdzl2JkeSnguup2OgdVKEy/bM4Z6q4O7D3t3qZMOQ6+xUKy3UGt2MJGNmymlHo4C6SicugwHkDoXDSXXpwD6k/tP4lK+it/47psAAHfNjOCRMyuu86g6nt0cNb0NQRTDyajv/TQMA595fBYv32sWW6w2266Gj0395WNoyfl0OBXDeCYWaB55WClg6nbePUm56Uz3C0B0OoY1HwWZ1+VGYsdIytWAl44wwwhW5F1eN5kC5jc/ynEdi4R81air5Qa2DifMzVwAB9BHvn4GF/M1vOGGKWQTEZuzye08ZGpkkBSwXCJiOWScdSiCFLcud4tOBykCLX/vge73+Y0x+cwMJ6MYzcRQabQDdxuT37V3IoN8temZ/loIuGlV//1HXr4brY7hWcdCTbP2+q3nVyo4cqmAt9w8jbF0DMVay9VZIp+Jp2e9u5sVay1k4hGMpKNYrTQcNYD6j1fvr59D/OxyGcOpKCaycbxoZtRT8ap+VpC0Gan6esW+cTx1Ie/quJaBj5GuAggI1pVxsVjHjdM5xMIhT9tBlkH4b288gOmhBH7n7qOu96TTMbBcbuC6qQzmC3V8wWNMyLkolzTTv/1qv5xaLGE8E8NQ0kyDdJszbLV3AqyDS+U6xtJxmwLIbTgtd51FU7mEb1p8odZEPBKCEN6BUzlvSzWkn+NVzi93zowgm4gESucPGogbTcdw245hfO3EkqcTYb5QQzoWxv7JTOCULfncV5ttV8fO+ZUKvvTsvJX+7mXHLCgqqLfcPI1zKxU86dOta7lcR7tjYNtI0nQAeewRZTBzxNFpzc/JdHKxZHV4BoCJTFwb7Kk22lirNC2VvZcDVM71Xva0eo8D7blK5lg+sCWLo5eCd1F7oUMH0FVg93ga51cqrg/yWqWBRDSEbcPJPvmqXIC/Y+84do+nrRbmbpt76QA6uG0I84W6VqWxWmmg1TEwmY3jzTebqUdfPuK9GVMXEF2ObLNbXG88E/fdlJ9eKmPXaMoqCOu6ODkcQMPJmGfkOl9pIl9tYmYsbRZ/1GxeZLTy+i1ZXwNPslAwJ08r8q+59oZh4NRiyUpZCBIZAEw58a6xFDLxCFKxcCCninPyc/4C6STzyqWWjoOdoylMZuOB206eXCxh32TGVA35LOqr5QbOLlUwnolZ0TOviE0+QDQqXzXvsVQAjaRNAz+IF79YayKbiGLbcNJzIf7Lr5/GSrmBP//hu3DDdA4vnhnF1zzq88gF5LqpLOKRUGAHkEyPA8zaXn6Gx98duoCJbBw/8eq9AIAdoym9AsgRtf3mqRXEIyElBSzqq6hQjUE/VYc0VvZOZDyNyGKthXbHwOtumMTO0RT+8fFZz8+VDhuvz5SG5WQ2gVwyimK95aoolPelzwEUQF2SrzYREmarZblR9nPYLRbr+PlPP4UPP3ASb7l5Grd3U0Pv2jWChWLddX5Q742bM0N1SI2kor5qxkfPruLcSgXfc8c263e7XVf1dT+DNV9tQgggG49gMpvw3Zwvl+r40rNz+MGX7rT9DidOSbmXghYASo0WWh3DdKZUmr4G2nK5gbF0DKPpKCqNtnbDWKg1ceN0DkPJaKAaS/K6bcklsHUoEbjT0faRpI/xXsOF1QpmxtMYTcd8Nz3Ndgd/cM9xvOq6CXzPHduQTUQ9ax7IcZzrOjadNeWcFKpN5JJRa+5ynrtfWkmt2bbq8AVJl5UBj+umsohFvDfgQE91NJyKYjwd737G+rpc7pkwFQZeQRRZEBfwV6jJtM7v2DuGRDRkq1XYd6xit3ilTUuVx207hjHctaXWNIXHzeLk5j355ukVT+eTXCNHU6bTwNYFzFcB5K3U/Ppzy3jJbrPm4IGpLM6vVF0LvqrOtSA1N+T1/67btqLSaOPQGX0aibRLR1K9eihBuogulRqYzMWxfSSprbsnkXVpbt8xjF95+414ZraAv31E32ms3DDXqnfesR3ZRMSzLpKqhh/PxFGstzzVmacWy9gzbm6sR9Mx1xRFaSNm4pFAgRC5EbYrgNxTwEbTMUxm475q8UK1hbHusV52c2/eDpYOK9ejqWwCN28bci0XoI7tIA6gQq2JXDKC771zO4q1Fu496r4+LBTrmMyZaqFLgbuA9eYrt7lb7mXedou5h3OzAVrtDpbLPQfQdx4w0wLdUq2sc+gqEcfSMUwNJTzt2tWKGcwcTsVsr/vtrubyNcsuBUx7RmeXyHXirl3+5TXknO21/1Hndb+0wEarg3y1ibF0HHfsHMFyuRGow98gQAfQVWBmLI1Wx3BNtVouNTCaimHvZKYvN1NOTLIQVzoWQUi4T1LFWhPZeBQ3bTVTXQ7P9g9U6WSYzCawdyKNbDyC53wkmupEq5to5Guj6VhXAaSfjBqtDk4ulnBgS86aLHw3OV1DczhtFq91M+6lNHfHaBKj6ZjW6HvkzAqy8QhesmcUHSPYZL/QrZcka3/o3pOvNlGstTDTjSpN+0gmrXNeqVjFpc3aLP6LsDSAf/Tlu5GMhjU1gPwVQJcKNUTDAmPpmOnMCeAAqrfaWCo1sGMkhcmcaYR4RVb/+htnUW608CMv320p17xSr1Sjz+2+yOJ1B7qKKSsS5BOBbbQ6WC43MJmNY9twErMuUaaPPXwWf3zfSbxk9yhumDafoQNbsnhuvuQ67nrPUxxbhhKYC5CSJrsc9RRA/g6gJ8+v4a5dI0h0a+JsH0ni9FLZM220WGvhM4/P4nvu2Ga9byQd81SAAOa9iFp1OvwdQPFICFuHE55jThqho+kY3nLzNB466R45qzXb1vPv5WhZVK79cDIKw3A/vucAuowaQDVz0yuEUFLAvO/XF5+5hE986zxec2ASv/S2G63XpfPSTca8VmlYakNfdWQqGqir27e69TbecOOUFTF0TS9Trp/f5qtQbSIbjyAUEoFSST/z+CyabQP/7qUzSERDrr9Prjc3TOfwopkRfODLxz3TV6QTb2YshVbHQNljXmq2TYNuJB3DUPf5051HodrEaDqGg1tzOBGg8KSlykpGsW8q65v2UKg1EYuEMJGJe47Bzzw2i44BvPXmaQynor7j9ZHTKyjWWnj3S3YiEg75zi3rUQDJ2lO5RATDSb3TQRrw0bDQGvPqayeC1D3r3veJbBx7xtO+jjUrzScZs1SPQdpmA+bamYqFrYCFl2OnWGtatdjyPs+fHM+jAdZbeX+3DSc9I91yPpvMJqzIu85+kNf7p77TDBx4OdCKdTOAOJKOdRVA3m3gVXWO1xx0fqWK2bUqXt5Nxbmu63xxe64K1aY1T3uVMpCsVZqIhgVef8MUIiHh2lDBUoelTSXSWDqGZ31q/LU7BlbKdYxn4tg+mvK8fk/P5rF9JInhVAz/6qZpTA8l8IiLM0raO8OpqG9al5z7xtIxqwCzm/Oj0zFwdK5oKea8FEBqW3e/eUXOm2PpuPV8AB4KoJJ5zUwHkJ8a0lxftw27q5sMw7BSd/2CxxL5nE1k45gZT7sGNNSgtl9gxzzGTIO9sbvP8nIiLBbM9KttwwlczNfW3WXMbe6Wz9uM1XVSf97L5QYMA5joBr7GMzHEwiHM+zjlpBJxPBvHllwcc4Waqw28VmlgOBW1bAuJ11pSrrdQrLesgBxgrp263yHnmTu7DiCvUiDyevk57yV+Kmd5nccyMbzx4BZEQgL/8qR3K/pBgQ6gq4BUhTg3apLTy2XsGktj52iyTyHhfH5CIYFM3N2gkwogWTtBl69sbVhzcQghsHMs5bvIqg+lbqGXE/FIyoyqrlUa2sni5GIJzbaBG7fmMJrynsTVXH7ANOjMrj3ukkjALLw9lolrayUcOrOKO3aNYKwbGdRFzJxID37Wivz3X3v5XePdxXkyF/ct6JyvNlGotbBjtNedya91MGD+zvFMDL/89hvxXbdt7YvAyN/kpZyYz9cwlUtYGzc/Zw7Q27BOZOOYzJqTtldk58xyGdNDSdwwncONW3PIJSL40L3PuS6wQeTkMlp3/bRp3Iz4jCHJpbxZp2fbSBJbPRRAckPyu997q/XadVMZFOstV4feQrGGTDyCdDyCqWwC8wFqAMl7NGIpgLxTwJZLdZxbqeC2HcPWa+960Q5EwgL/++6jtmPV8fDcfBH1VgevvX7Kes3P8WEYBp6ezWMql0AqFrbVpNAh88vN6I37RlNuWCayceybzKBjuBtO0gAKh4TrXGcYBv7+0HkA5n31+11zXSm2fI7XmwImj09EQ+bm1sdQvJSvIRIS+PMfustu5PjUEFotm4VYQ8I9qmdFhBOm0VX0aZW+0t3YZhPR3sbd5bOLtRa2DiUQEv6tjFUV20Qm7luP65+fvIhbdwzjwJYshpPuXSDXKg3EIyGk4xH81zccQLNteMr35efsHE1b73dD/u6xdAzDHiqwQnct3TWWDqRCsNI0EhHsn8zguYWSqxoNkJuIiNmVz+V8n1so4re/eBQv3zeG/VPZQB38vnFqGeGQsOpeZBMRz3RF1XEFeBfulJ3ORtMx1+dHft62Yf2mUjoJ909mcHal4ttlbaXcgBDmXL9/KosTHl2eAPO5EsL83d+xdww3bct51ptRWa10N5gp/8BCsdayHEx+6aCrivN7PBP3rGEhr9mNW3OeqT6Lih3ntQ5KVfnN24YRDQvX8dPpGCh1nXtSAaQOBd24OHKpiGhYYM9E2tOB8dyiec9kh1Sp7HObX/LVJvZPmoracwHaqeerDQwlY0jHI9g/lXVt3LBWbSAcEsjGIxDCrEPpVTcOgJUKN56JY+do0rMG0OHZvFWsHABu3T7s2tVIzv/ZRLews8e9npdKllzCCnq5bVxPLZVQqrdwSzcl3asOVqFbM3T7SNJ/IyydmJkYEtEwfua1+zCWjmmLg3c6hqmcz8UxmUugWGv5BJyayCYi2DaSclWJF2qmynM0HevtHXwcrwuKA8hMldYHkIOWHwBMR1il0UY2YdYDFMK7ocx80bS1t3edxe/92yc8P98wDCyW6tYz4mZnyHXMr1GCGiQDACFEd3/ivVbLrICJTBxTuQRqzY6nYnckFbMKyEu81pIFa0z3Osq5KoC6duL+qSxi4ZAtTdaJtKO97qP6HX7qUHn9xjNmmYFX7B/Hvzx58ZpIAwvkABJC/LQQ4pAQoi6E+Kjy+owQwhBClJT/ful5O9tNinxA7z3WLxM0U4fM2jFy8KtpSXKMCdGrBp9N6B8SwDQAZFoAoF8kFqzIkfng7RpL+Rq46sOkMzLka2Nd46nVjRQ6kdGWG6dzGMuYk7hb1DhfNRcnKbPuRa71E11PAZRyXfTOr1awbzJjfZafdNswDCsFLBENIRIS2o26WlwQMK9twWfRk84GqQAaDpDKYRgGDl8sWJFHIfq7c8jPKNRarpPUXKFmFcOdyARrr6tGU+TY8YrszOVrVlG4oWQU73/HQTxyZhX/6wtHtcerUQ+3hebIpSKGU1Hr3Hu54N7XTRrS27sOoHy1qU1lzFfNzfcOZSGT9ZmOu3ROkOMDAKaGgim/5IZzSFEAeW0iZKRUqpIA4ODWIbxy/3hfBFO95dKxKwvTAr2NnpvD6Z4jC3j07Cq2DiUxnvGvu7XQdQDlElFUm23XmgcXrHuQsmS/bhsc6SzaN5FxXcg/+9QlfPrxWfzUd+7FrrF0b35weYYWCvW+aBOwfgeQEAK5ADWb5go1TGbjCDk6eXg5kgGZTx/DaNpdOq92JRsO8Dtk8XBAmUc1BuO55Qq+emQB+6ay2Dqc9A0MFGot67rs6xb/93LGXlyr4cau83Yo6T7fSYMSgBVlPewRqZdGsjRAvebRnhoj7qmGWirVMZaJYWYshZVyw3ecFGum4yEdi2DPRBr1VsdzLjCDNVHsn8ziuYWSVuH01IU8Ogbwq+84CECmQXtvek4tlrFzNIV03FSs+jmX5TiUqjOv1ttWoCcdQyIaQizcr+KSY3PHaEp7Hx7tph58713bYRjw7UizXG5gOBk1m1tMZHBhteoZrFjrPquhkEAoJPDimbFA3X/kd42lYz37wGMsF2tNjGdiiIbdndQSNUDm13nVcgBN57BQrLvaEPOFGnKJCBLRsOczfd+xBYRDAi/bO4Yhj/EjnXu5ZFdV2JcC1v+eZy8VsG8yi/2TGVt3PyeyqYK0dfxquEjbwezSF0wBJK/Bwa05PHtRX+totduUQtrT101lcWK+5FkKQNpF45m4VctQ57Qs1Jo4s1yxnFwAcOuOYZxdrmivuaq8295VALnZa4uFGkJCKoC8g16ywcCt3WCRZw2gqunw2xLAbpFOy/HuvftvbzyAO3aNaM95vlhDo93BjpGUNa94ORykombrcAIX16pax7laEiIZCyMZDfumw6qb96Fk1FUdancAec/zMiUrl4wgHDJtATcFoLp/ePstW7Ell/BVnOWrTTTbhlX/zk8BJPeXbvdY2hDyPgCmI9GvVIG832OZmGXHu40RUwEUwy3bh/Gr7zhoNczx8pE4U/IB896WG/11j+T8PT2UwFjGu7C/XH+8AnS2Gpc+6rQzXQe0tC3efstWzK5V8fj5Nc/3DQJBFUAXAfwGgI+4/PuwYRiZ7n+/fnVO7YXDaDqGt90yjb/+xtk+FdBy17DcO5HBUDKKjmHWM+jRTQFTXnHbLNaabZxaKuO6qSwi4RCGU1HtpKCmgAFmIeALqxWfaGXT07i2cqvV6Jnmu08vla22f1O5hFlUz8VwkJsuuVjLjY6bcX9+pdot0hrFWDrenUh7E0mr67nPJaKKhNSnK0a9hWqzjclsvJv+oVdfqcUFgd61dTP0DMPAf/7kEwB6xS2HkzHf6O6HHziFpy7krUkfELZJttXuWJHldsdwvVbzhTqmupP6RABnjvpbZMFdwFt5M684mQDge+7YjoNbc64S6vMrFSWly80BVMD1W7LWmBhNm2PCLxJkOR+GU1YKji4fW93oS26YziEk3HOmF4t1jHevoZ9UViJ/n1MB5PY+eZ3VRRwADkzl+qLo6mMs5xtpeJvf5V3EWMpt//AHbsN4JhbIMTiRifs6lmSEeOtwwjIQZtf0Y0EqSfZNZlwLIX7m8VnsGkvhv77hAAB/Rc9coWYzNmQkeL0OIKA7B/ukgM0XatYzppJLetdxW6s0MZqOYv9kxjVFwlYDyKr/4aEg6xbklO9RP0Pla88tolhv4RffegNmxtK+BVJlW2AAOLjNdNR41VmQ9WPkeXgpgOSGbqhb+NTLcJabg14HLvdrIcehGRXWq6HqLbPo5FQ2YRV19lNDFWotKx1OKkG9NihrFTNY89ZbptExgC8e7q/NIts9b+8+v0MBggQnlVp0gFmfqd5y76akNkYAvB2JqpJFCIGcJmIr/759JKX9rIeeW8a24STedHALAPgWZpUFV83PTMIwvAt3rnU3+ZLRdBQln5opgLl2PnVhDaPpmJWy7FWDRzrwghTwXy2bCrxENIzxbNxzTs1Xm13lmXnP3dSqpsLCnF96iqX+8/jKkQXcuXPECgy6BUukUmjvZAajaXMjpqqtddH8o5cKuGE6i5nxNM4tu9uQ51erSEbDGHfMQbrzbbY7mC/WsHU4iZu2DeGxc6u+tRrVe35waw5LpYbWnlHnFcBMGa23vDuBWbVQMmb3TUAfWJXz08GtvSDNjHUP+8eRfE5yyQh2jCRRa7p3N5ovmOlUkXCodw4utuvJxRLCIYG93SwAmfKtc5oWujWftuQSWKs0PQOW8vtkChpg35eoyHlrR7fGJAAsltyfJakA2j+ZRbNtaNM8nU1hzDIPPg6gUg0jqShikZBnsWT1uvs5c+W6LQM5Ix6qzOVyA9VmG1O5OJKxMF53w6SvvSHnBjmH6wKVgDnmc4lecxpXB5BVJ1F1AMV9HX7LpTpSsTBSsYhlx+sKQRuGuc+QtuwPf8eMlfLupQBypuQDcC2zMZevYSgZRSoWMYOSLvNnrdlGo2srejl2ZP22sbS+WZCKtKFnxs1n+Q0Hp3DTtpxnXb1BIZADyDCMTxuG8Y8AvHseXqMIIfB9d+0A0K+ykAa2VAABdjm6XPdCigIol9QbHMfmimh3DGsBkjJeJ4vFOrLxCJJdZc2u0RSabcOz4Gex1rIcQDpZ9LKiAPJyDsiuUOGQQDgksGM06ao+cm66hnwi/OdWKlY61Wim3wklJ9JsImJtBP1SFpydg9yMPbW4IABM5KRTxSXFpWQWgf3Rl++20vWCGPdfPDyH0XQMP//mGwDI2lC9SVZu6mX054xm02IYBubyNUzn7A4gvzpA63EAGYbRt+EGzEXbbYE9t1LBdVMZxCMh7RjrdAwcmytardwBeDobVS6sVSEEsGUooRSk1htlTgfQUDKKg1vN1pk6CrWe8TmVS6DR6vgWAHeOl1wygmbbcI2+qzUkVA5sycIwgIeVc1OdSGeWK5jIxq1nHegtsm4qQjn/mPn7CZxeLLumF8n7PJGNK44N/f2dXa1iMhtHPBLGVC4BIeBai0k+N7JDhO5c1ypmPapwV2HjV9tmvlCzGRuA+ZwG6TIzl69Zm3rAHBN+dXfm8nYHqCTrUUS60zG6G944DmzJ4vicvuNEvmrWvEhEQ9Z49VKGqJtoL0NYzj87R1O4Y9cInrmY91UrDFkbLzPyLQuhOqk1O2i0O9bxQx71bJZKPYcVYDoCdXOZeh4AsFM6gDxSab90eB6ZeAS37hhyVU5YRnMujr3dSOwTPhE/1bkVxEEuO6dcvyWLbCKiVcKcW6lgSy5h1e8aTnrXwet0DJxZLtsdQN3n3W0j8ciZFWTiEVzXVTp6pQ6rShZAr1ot1JrWZr9Q62+0cPhSHrfvHLYaEHgVvwVk4dm49X2At5Nqrdq0lJXme7xTHiUf/OpzWKs0sXU4iclsHLFICBdcghUtKw0kEqh+20qlp8Abz8SxUmm4zqnymZJOKLfuOwvF3nzmlrL23EIRR+eKePPNW6zj3OYtOf72T2Ysp7K60XIOuWqjjYViHXsnMpgZS6PR7rjOpedXKtg+krQCN5FwqKsA7D+X+UINhgFsHUrglfvHsRKg6OpatacAksEO3XVTO28CwM5u/RSvuj6qAmg07b7Zlo5vOQ8Cim2l2bDKznzZRBTbuufsdv1kGhEAq3yBmwpirWpuxuW6KB1GuiBZsdZCLqnaw+5OgSe785+0sQHT/tRNRbIcw46RZCAFUKHaQi4ZtYr8HjrbPyf0HGZdx0s6GkgBJL/fa51UA/N+6Zw95ZY5rw6lYq4BS1kc+mV7xq1zyHvM30AvECv3BW7O5dVKAyPpGDLxCGKRkIcCqGe3S4J0ZpMKWHk8oB8fxbqZmqc+V26OQZVeCquiAHKZ3y/la5bdPpaJuTpKpXNuNB3DXKHm2nhJrtWmmsj7OpxeqmAqF0cqZt7vXCKKz/7MK/Gq6yb8fuILnqtVA+isEOKCEOIvhRDjugOEEO/pppEdWlxcvEpfu3mQk5Yz6iu7m5gKoP6ClL0UMOWzXBRAh60IhLkAuRVCXijWLAcFAKsdplcaWKHbQlsI/WZbvjacUuTTmol2VZHqyu92SzPIKwY1ACta61Yn5/xqr6CyXPTUiUJtpSnTnvxkkHIjKr3nbsaeWlxQPd5tkpUL5Cuv6z0Ow0mzBpDb4lCsNfHUhTz+7Yt3WpN5yLEAy8VNdhw6rak7Veyqmqb6HEDe10JO2GNpfwdQsd5CpdHGliH7hjuXiLoqH86tVLBrNO2avnd2pYJqs40blTSo4VQM2XgEn3l81jXCDZhR/y25BGKRkLWR10385piL9L3+sr1jeOLcmvY71I3f62+YQiwSwu9/6bjruQA9J8uwogAC3FUhvefL7py6a2YEqVgY7/uHp61xo44HmdKm4peCtFZtIhULIxoO4btv34qL+Ro++5S+6N1coYZ8tYnrprK+3aUurFYt5U8sEsJUNuGRAlZHNCywr+sA0kX61PQjQEnp0sw7UortdEjum8gEKip7KV+zlHqAqW7wKmguf4Pz+wAgHQsjJPRFpFcqDTTaHUwPJXDdVBblRlvrTCzUeurIXv0P7427fGYzcVO6ri/mb3akTETDePNNW2AYwD0uHSJl5C+n1FSazMZx2kU1pNYtksfrxophGDi5ULIi2IA5n/qpJgAzmGH+Dv21+OIzc/jbQ+fxxhunEI+EXQ1Oe6OEDA5uzeFj3zjrabib7dFlVNi/hozcjMp7qDv2/ErF9vyOpGJod2u16Jgr1FBrdhwOIHeHY6vdwZeencfrb5j0LTwO9DuidSouczMXwZAsyu4417VKE+MZU1H7kj1j+ObpZc/rejFftdpOB6nbla80HAqgYI0CjlwqIBoWeN+br0eoWxfFrd5LL5gU7doEHjVACjU8eGLJUlhNZOMwDPe1UzqARtLeaepz+RqmukrjZCyMeLcDnspHHzqDkDALiAPeaebH54tIx8LYNpy0ahupjhFnrUHprJgeSlh2l1ujk/Or1b51aCQVxYrmXKRaZutwEi/ZPQYAePycd8eifKVh2c89JapGqd1NVZHIc/JS98l5ZyLjbfc8M5vHllzCttG2aiVq7Ey1ZphV18dlTJhrSbz7+yKIhIT7+KnYg1jWOTtsKsMwcHy+iKlsopfi4+JsNAwDf//oBbxsz5jlmAQAAaHtAnZ+tQIhzNp8vXqR7mr4Ynfu3DWWwngmZqWJqli1ypQ5Vjd+VBZsDiD3gv9nlstIxcLYM5H2dICr5yHn1eGkewrYV48uYOtQAjd11bFeaWgSaWfLGkDuKWBNDHfXjzEPNdRCsYbhVBTxSC8IOJVLoFRveaZJnV2pYDqXtI4HgLm8RlVXttuyQE+w4CWEXyzWEYuEkI337G23+f3iWrXnAEq7K4DktbpxOmfWmHQJMMqUQ/OzfBRAy2Wr0Pa1xpU6gJYAvAjALgB3AsgC+LjuQMMwPmwYxl2GYdw1MTF4nrVe1N3+MJ9aLFktmnUbKEObAqZXoRy+mEc2EempYNIxrdxXrVkC9GTzZ1fcF8Fid8NhRr77P3Ol3EC264n2WoDzDnn2ztEUzi6XtQagU43hVeOj0+2yJmu3SANcjQT3Ju5I1xEQ83UAqYUWAbgW4F6tNBDpppQA3h5zoOdsU42i4VQUzbaBisvicOSSqfC6a2bEek1A2GSWUv1w87YhhENC6wBaUXJ7AXNCFcK9K5FEldMmomGkYmFXI0QWQnZugN0caNVGG4vFOnaOpTCaiWlT845csheABsw0nt9658144vwa/ubhs67nPrtatQxw+bt1E3++2upTAAGmo6DR7ugjIN1isQAwM57GO+/YjrsPz7lGH4DeZkQao14d5gDTMMzGI7ZFHDCjkj/56r1YKNatTYnTIHMuXjkfB5Cq6njTwS1IxcJ46oJe1fFMt8vgTdtyveLGbilgaxUrlQUwnyk3GftCoYbJbMLTkep01vUifDqFXhONdqffATSZwdnliue9OtrtPHe94gCaGU/h/GrV9X3legslR4cLiewkppvDpQG+ZShhbeJ1KbKqc1zeX6+uUyvd2iby+4eSUa1KRq29c/2WLLLxCI66RN8/+tAZLJXquEF5HkdS7oWdnRL+oaReOn8pX0Ox3rIUKYC5aV4qNVxTQQrVFsIhYW1c3dRQ//DYBeQSEfzCW00FZdbFGbao1E0QQuBtt2zFiYWSq+NFnoOcB/xqnMhzlM//SEq/rp5frWC7EnH3U8HKOU0dd1mPuWWl3MBapYk7d434Kvjk8YCPA6i7mctp7Jl2x0BRcdy+av845gt1PHZuTft97Y6pVpX3NYgDSFWDAMEbBZxdLuM1Byatjd2OkZSVyuJE3bxn41FPBdCXn53HQrGOn3/L9QCgpPD4OIA8nIjFWhMX8zVLISl/p7qmLRRq+Pg3z+HfvXSXLVXMTR13crGEPRMZCGHWWgKAY8qc0nFMdb26HElfZdZisW6L9APm2qd7TqUSXSqxAPdrJVHveS/FWa9wHFHGxrbhJELCWwG0WKojFg4hl4x43rvTyxXsn8rYXvNUACmOhDEXJw1gOkgu5avW9RNCmMFdF3vN6eSy7B3HWvvYuVVcWK3izTdP91J8XOzVk4slnF2u4B23bbW9Hgr116AETLt3LG2qfcfSpuLfTQ1fbrTRMcz7JoTAzFha64jqBXDN+zuWjgVTAGUcXT81c+fZ5Qp2jaU9nw/nechx5lWYf3ativ1TvZIFQRSMcs+x26oB5J4mLceyV52nxaJ9vweYKj+g11XXSaPVweGLBauQeCxiph7qxoeaFiyRggWvFLDVitn9Wq1v69YgY3atatmO41kzbcttzwj06ga6OfBlyuGYT4kDwzC68yIdQOvGMIySYRiHDMNoGYYxD+CnAbxRCJH1e++g4a4AMuXaoZDQGjduCiCdwXH4YgEHt+asB2oso/cKLxTrllcegKWMcFMANVod1FsdZGV3CM2ivVjqedq9utzoIjCVRltr/DpTwKRBpPtNi6U6Gq0Odow4DEXlc+U1kxP3VC7hGvGQyI3nRLaXAqYzLKSyybr23S4px1w2ZWeXzQiJVEQAUNrqukT8upOvdGQAXQmucoz8vRPZOHaMJLU1PJzpR+GQwHAyGqgavpoG47XoWB3DMg4FkEv6ohpNHE3HtZ/76NlVxCIh28YQAN52y1a8eGYUn/jWOddzNxcQ87pJR6Wuk4Bs9+1E1g1yRjh7bZF773n1dRMoN9p43GVTA5jjJRruFTiX73fvstCwZPlOpHNSvtdpkDmNUi8DWX6OWvDYqxD0o2dXERJmnaTehq9/bmp3DFxaq9nGu1lHR38OZuc9tdi4Pl1Pve7xSBjZeEQ7P+gKDgKmA6jVMVw7NAK92g5qAe6ZsTTaXaezDnkvRlL9YwkwjVjdRlstdui1IVed40OpKHaPp/GUS7eZaqONarNtpS8AsDqiOJF1aQDz3m8bSbqmM3716AIOTGXxQy+bsV7zquvjdAANJ6OoaAo+yuivqriayMTR7hiuKg6zFpFZEHc8E3Ndy04vlfHSPWNWSpF0hjk/t9ehJNH9vyyU7745WCr35kdTnQXXCHWj1UG50bbGx4hmM1NrtjFXqNmDBD4OkKIS5JBkPJ53ObZyyahvdzrAXstG/k6tA0gpTq6Os4JjDLz55mmkYmH8xYOntAb9YrGOVsdYnwPIRQHh1Sig0zHMTaByrXeMJl0dA3JDP56N+6aAyfsqNyV+Skk5/3oVdpYNCQ4oa+FN23K479iCVcdlvlCHYQCv3N8LqA53HY26a31RWSO3DSeRjIZtTmXnO+S84Ba8VDEVHnZlrc5+6HQMfPKRc1ZQVKaKeW306602Ko22Nd56Dk+9/amuo7FIyCx276F+Xyqa6ahCCKUAs8aho0kfT8bMNUmXRluotcxC6pGQVbJAZ/fMrlWxVmnaAhBe9W+cTi43R6K0T157/aTlXHJTrH/txBIAWJ0FJQJCX2y73LTqM5o10WKun+1M7XJ7npzdCkc87E/AVHirdbK8nC9nlsqYGUu5rosqclyp65h7M4OG7V4ESddeKjUQC4cwkTHTUP2aRQDd8eDiyFBVUBJZqNytXt+RSwU0Wh3ctnPYem3LkL5wtDOYCfT2q16Vu1bKzT5Fu25+L9aayFeblg0+no6j0epomwypCiAAriptuUZtySVwKV9zrV22UKxjrdK0zbPXEle7Dby8ytdce3lr0+WYfE4t9qTuOjm69KA6u4A5C8a22h0cuVSw5R9LWbm9q5iBhWLN5hEOhYSlxNGhRircWtaqhXC9isyq3RoAsyAsoC90aBpCPaMhGTO7XejypKWhJhVAusneKSE1K+H7dTiqIR4JWcaLm/NN3TgB5v26bcewqxPg/GoF07mETdEh77+bsWN1b1M2sQKOFLBu9GI4GcWBLVlLNaPSm7DtRrJfhHSp1LAtJF5GiEzTUxcFwHS+1Jr9BUnlOY1l4q5y1m+eXsbtO4atzYfK/qmM6/m32h1cytesBUQIgfF0rK+9ea3bwUp1KkjkBsQ5TkvKBkrysr1jEAL4xkn3kmj5bi2sXjFrb8XAStndAeSUNjvtsX0TdgdQKhbutld32YA4NlBuXReeWyjiz752Cq85MIlULOKpAJov1NDqGNY9ANDtpKU3buYLZnqDHOtOA7rWbKPe6vQ56yaycW20VVdwEDBTJSMhgV/8x2e05wEAn33qIvZOpG1zplTnuDmOnMaqE1M1oFMAmeNry1BCUWppNu4O59ct24dca9RIx5CajulWf0dVAAHm5s7NyfXcQgk3TGdtXc5yHg4g5+Zft96tVRr42U8+DiHgUAB1x4FHx0i1FpGuDXS7Y+DsctmKrEp0c99isY6Q6D2XQeqkLRXrVpFb6VR3e56trpFpqQDqTwGbXavCMJwqUe96NgVHkAPwVvypDqNE1Ewj8qwBpGw6gK4DyFkDqNtZSGfMyz/LtScTj+AnXr0Xn396DvcfX+z7PtXJAPh37ut0DFtNNgBWKpVXo4CFYh31Vge7lNS56SGzW6SueK6lEMvEfYtAr1QayCjqzd486a3AjEfCSMfC2uCYdMyoTtIf/o4ZLJcbeKB7HXVz0HAqhkarg6qj2K+pMqlZ6T2hkJl+q3a+dEbzZXrF1FDc877UW20rgKiiS0c7s1zGw6dW8N/eeJ1Vt2407Z3q4xxTbgp0uWY4nTS7xlKe3Q6XSj3HbiYeQSwccklJ7ncAAebcoUt/kmlPgGkXRcNC+7lSfXvr9mHrtTEXlTQgx4+iAHKpGbRWMbvsjqSiZvF64R4UOnRmFdtHkrbuqAAAod/kr1UbVkATMFPh3FLA5Hk5G2LofldIAJluLZbRVMyzuPsffuUEAOB77tgGwL1GYKvdwfnVCmbG04HqcDrn2KGUWetM50RYKzdtNrBXGppksbuOmN1G3bvDrikOFK8UMLOphN3umczGMZ6Ju3bW/MzjswgJ4M5dvWyDLS4B815A2b7/AbwVQGuOtQTQO4DkGiCd0+NZdwW/HL/7pzJIRsO458i81kEpG+Xsn8qg3upYjSGcSIXUAaXu6LVE0DbwESFEAkAYQFgIkei+9hIhxAEhREgIMQbggwDuMwzDu+3DABKPhJGIhmwPc7tj4Pxq1UrB8lQAKZ+VTUTQMWDLIz27UkG91bFFqce6UVN1wivVW6g1O5ZqQLJzNIVzLnJnVTnjllamygwT0TBikZB2MclXm7aFweq24dhYG4bRV+MDALYOJbV1Q05263jIdAjL027zJPfabgKmA2h2zT2NAzANQ7NgrbCugWtkyTGZ3b5zGMfmi1rn1lqlaeumAMAyMtyksnP5GhLRkC2SJoQ9AiMXr6FkFDdtHcKppXLf+cr7p0o2xzL+ubCqISTf77bBkUar08Pv1ilKfvdoyuwi5/zcaqONZy8W8JLdo9rvkzJcfUvSOtodw5Z+NKZRtTgVCioy/9iphihoIu5DySj2TWTwpIsiA5D1P+xOFsC9sKOawuPEOW84F919k3YHkFc3O/k5NgdQWl9/5ZnZAtodA/9fN7XBUqxojBu1BbzEqx7UfKGGyVwc6W67V6fx6OZgGc/qWyy7FdHePZ7Gj7x8BofOrmrHzvH5Ih47t4bvf9FOmxNeXlO34qS9FBEPBZBGKXUpX0MkJDCejnum7jjv0b6JDOYLdW2Nqj994BTGM3Gr6xLgrQCSG2YArgqgUr2FS/la39ga9ijsrEsBM7+zd/yzlwowDOD9bz9o+31+Dpjlct26tzdty+HEfLGvo83satVsr6ts8gFgPBPr+1yzE1OvkKqc99zk4vVWG4VayzY/jrioZYH+LoC6zbAzqCGPA9yLXBcdQQ5AKQKtdQD1atkA3g48oD8teygZRbHesm1+it3oqtbBp5ljf+TlMwD06QhqOhAAy0nlroBqwTBgLwKd9E/HkxuAHYqDWqq/dOuxmhoeRAGkPlNe8yRgf7aHNWshYNo7iWjIpgbeP2k6g6RKTe0yJZHjzelUylebqDTaVkDO/LyMbT5xzo8X16oYz8Qt5aUQ+t9U1ARJzHPpd3rKv6vOX7Nzmfu9kw5Iec8zse65OO6JU/ks2TmadlUKGIbR/Z299NnRdExbT0cWMnYyno1rN86y25vtczVOnacu5BENC1vq+2g67rHht3c6c6sZtFZtINdNuwqFzLRkrw6azhpOQHdfotnjr1Wa1vMPmA4HNwfQ6W7gWdYidVUAdedkGXCwul+6OGzOLFdww3TWahqSjIYRDfen+15cq6HZNroKIPcUZut8l8xnT86ZeyfSMAzgbkcXx2bbVKk4Hebyt7ihZlNkE1Ft2rHzs8cypo2m28sUa80+56sQAjduzWkDxNVGG3/z8Fl83107bPWeptwUQI4OyEBvv+pVA2i10uizx3SZMhccnTClQ1O3FstxM5qO4T+/fj/uObKg7TIpx9K+7pzpVgdS52i/lgiq1PlFAFUA7wPwg90//yKAPQC+CKAI4BkAdQA/cPVP84VBLmEverlcNjemsgBbuhuZ101AtjxJzSZaGkqqAaNr3WdFS5L2B28ql3AtAqwaiaPpmDYKu+iQGeqUMo1WB6V6y7bxne4aHJccC2Spa1Q6N+PbRpLalppPzeaRU1qnmkVs7dfSKY9/w41mS8ZPPnJe+7uB7kZU+V1yQnYaQ2uVZp/a5a03TyMdi+B/fOqpvs8taIoNy9pNbhH3+WIdWxRnFNDfhWG13EBImGNEyjyd7ZN1ks2xIAogZwqYS5c5oLcoO40tN3WYlUeciWEsE+u2oG3b/r1j9DYCToaT7sVRpXNQNZZ1qhYvB5CZWhLvcz46VWWS23YM48nza67FTVcr9giZtai5RPVWyo0+Z5rEme7o/Ma+qB2806+czoXxjP4+y5TELV0jIRkNIxISWqeO3GA5U8B0hl6taW6mpeN1MtdvPKo1OFQmfBxAY45IGNBzlDuj4gDwiW+dQzQsrCiiZDgVw96JtLZYJaBPxVHJJfQ1eOYL5jwaCglk4sEdQG6OVcCUeb/2+gmri4U8f933O+exbcNJFGutvjVJPlNOB9B6UsB0AQ9piKnOKqDnAHJzwKgFt2+cHkKr099K+MSCacztcSjiJrKJvs9V63oF+X5rfKkOIM1GUWLNd1YNIDOarW64ZQcqXQqY26bHmeZs/tl9bDiPH0q6O2WBXoFniXND02x3MF8wnXFBFEDy/LKJiDZQcnKx1J8qnepXHUlUBawkFgkhm4h4dnuRDhF1fuiln+rtnZAwj88lIig1Wq71qVYrTes+A95pbJYK1Upz0XcbXCr15gmJs/mGbm2Sz7bToaIWXpbsc6QOO5eyU0sly5ka6tY/1P0m3ZgETPu00mjbFOW6zaSfOnnNsml7KUeZWH+grvfZ/QqglXJD+3z8/aMXcGKhZOv4M5bpt4Flh0Odw/+2HcN46sJa3+dfytcs29/8nfrU97l8FdNDSZtafMxlbnGmlgLm3kGXLpWvthzqFH1RfqA33pwIIbQKIDPQqziAcnEsFGpae8hqs911AGVcU8Dsc49VN8m1GLa93ISZ7tvv4JHdJWfG0hhOmfa9W1C41e7gi8/M4bXXT1rBgbfePI09E2n8508+jseUYuVWGrji/PWr4QaYdvaEkk3h3XXY/Lzv2DuGWrODe561N2ywHJOacblvIoOTi6W+eUum3arqH8B8XpfLjT7F1VqlASHsDt7eHsVLAdSfAibFA+o9upiXQYBeFzBA38RFjt9sIorvvXM7AFiKSIkUF+SSEas8wu/cfUyrJJtdqyITj/Q5qq4VgraBf79hGMLx3/sNw/iEYRi7DcNIG4YxbRjGDxmGMef/iYNJzmFcWa1ms/Z6BEEUQIB9Y6AW5JPIxUX12soNcsaxGE/lzCKbbh5kwJS/7hxNYbFYR1nZaFcaZsFTta5QNtG/mOiMv/F0HNGwsB5y57F9DqDhZFcab59Ynrqwhlu2D1sTj1Xo1FZ/wG6IfOeBSdy0LYfPPHah7zcD5mR/Yr5k20Dr1FdAf941AOyfyuJtt0xr6wCpHWMkE5k44pGQuwOoUOsrpGh2Yeix1O32Ew4JHOzWHHB6+aX0V908e6VzAWZUoNxoW/JLoDueXQyGtWqjWyzaPoW4bUbkd4+mYtpOG17OGcB7Yf2zr53CaDqGO5QFbTzT30lAtiN2bmolW4cTfUXwetFN+/N0y/YhLJcbrkUVnYtfMmYW1dYpgDodA4tFfUcpQJPu6Hg2wiHhfItn4dK8o4jqWNcB5DQU5vI1ZOIRy1EhhOiOif7PlY4z1QmXc6kBI1unyvswmY33OaflPOocD5MeDqBwSGg7vHkpbe4/vohX7Z/oU+sBwItmRnHozIp24+eXAnb9liyeWyj1GaOy2D5gtkpORsN9z4pqwEjc6gWV6y0sFOtWdFWiS90xDFMtqhruMhL/0a+fsR0rVUE7R/s/t9Joa5VI0nmiOhsAezT0uYUSsvFIX6qeXCOdgQLJfKHXJlk6TJzz6CNnVhENC9ykpEkDegWQGTVV0ohSMYSEuwJJppNKpQBgrr/OdU0i52RZ+2NEo+w5t1JBLBKy1VHrzXP6ubqgrNUSr/GtpncDpkPVqyCu0/HonHuens2j2mzjrl2jWkeHPO8hRwDKXNf77+3j59Zw3WQWaUenGDcn45qL8tRLgaCel/o+qZLWRb0XinWMZeIIhwSGUjEYhnuhYmfdQ3lv3BTSQO/ZGHFpMb1cbvSldSSiplpS/har656tjqLe+aTW4JNIRZFEneYMw8CJhZLNSTSUimrTVawxFrffk72T5tyhOmp1Kp0Rj0AToL/nZoDD2X1On5a+y+oE1j/uHz+3itF0DP/+O2as17YNJ/uclb35vn99ed31k2i2DauOjkRtTAG4p/GsamzLsXQMRU36k5w/hhy/cTTV/9nOsgW5pN6BB9iLKauYXWg1qU8O++bgVtMe0ilmzyyVsSWXsFL+cokoGu1O329zpj2P+DiAnMXgAWAoGenrIixLX+weT/sWaf7sU5ewVGrgu27rBYQi4RD+6kdejGbbsDkbdONNrq1etraqAHJrOtMb8+Znv+bAJMYz8T4VUr3VdUxqxuW+yQxqzU6fwlcGIccd93uLS52o1W7JANXOlH908YlbtoYzQAz0OyKdweQJS43bfw2LtRZCwhRTjGXiOLg11/fcVZtttDuG2aggEcX1W7I4OlfEJ77ZX0PUud5da1xztXqeT3KORaknI+4tun0OINkFTNnDWS2jlePUfGyJ1dpRMWDcojHSeaMzcGWr+olsDLvHzQX/jFIvSL7HTwGU1yxOoZDAlqFEX7s+LweQ2b7Qnkp3bK6Ig9vseZrmtexNEsWa2d46EjaHtRACr71+Ck+cX9Ma1N84tYzlcgNvvHHKek1ee6ec3q1I75YhM7rs3BDpvPKy6KpOjlxrtnFmqdznBBCOBVhV6Uxkzejkc4v2SPhKtzCdqiQay8SxWmm4FkOTmzd1UfCKfK6VzY2k+h3yPfL3286p1EAyGkYyFvZ0ALltqN2Koy6V6vjaiSX88MtmbJsis66A/Z5/9qmL2DORthVbVNFFIi2ZveNeSqehW5vztWp/yqCpSup//pbLDbQ6hrUAO+lPAev9m5sCRVf4FjBTWarNdl8KWKtbW0PF3HQ7inwnItqNjayDodZvcktN+fg3z2HXWAqvv8F87sxuMXpnsq4GUKneQqWheT4dHSd65+GukFgpN1xVZ3fNjKJQa/U9X4C7Qknyyusm0DGAh56zGydO5YlOJVVutPvUkW71guSmxtkJbri7WbOl7nRVl+q4fM2BCbz2+kl87OEztvdb80HWPobdDOhSvYVPPnIeL90zas2/bgqgvZOZvvuUjkcwkopqn6dqo41irWWtP1Itohq2s2tVfOwbZ3DL9mFroyGZyMZRbrRttV4KjvsQDgmMpuNayTygGM3KGrh33EwtcW5kPv/0JfzWF47iJbtHcV13k91TZvSuhUyrVlUe8YjpKPZSAKlrHABEw6Yj3qtopvytW4YSeGa2gL966Iz2852BC2eq9cOnzLpnL9kz2ku5UDtxuqzrWzWb6k7HwBPn13DHrmHb60PJKJ7tFil1Iu95vwPIvQYJoKRO29JW3Avjqhvi23aY5/fImRXtZ6+U7akOkXAImbg+BVTnANLZJmYHnf61UE0lLFR7myGJtFGcc790wqjBrv2OQIjaXXK52z1OrS/n5phzszn3TfSnX1hBQkU1IddqNzXtbFddqgYgdc0mrLTLtP26TXfnd52j71K+hq3DdtX1thGzDIF6Pm52AGDWmQOAE0o9pXqrjYViHduG1bR0fa29tUqj36GT0Rc2l079YcfzpUvXdwZ63O5fud5CpdG2zW0Sgf5Nfq1p2hCq4+Ntt0wjFg7hn5+42PcZZ5bLmBm3B1mBfof1qsNhpbMTVdYcHYcBc551/sbTSxUko2FMZOOenUQB4CNfP40bpnN4ww1Tttd3jKawbThpqwm4qrkX6XgEu8fdlcP1VhvLpV6THlcFUNnuKA2HBHaNpfqUaV7jUqpfnPbLsqNLsGRKs580f2e/LSvg3QZe2h46Vbtzn1ysNbtribmmyTlMp8YtdAM38nm9dcdwX3fUnhDA/O7P/+wrcduOYfz1N/q7CLuldV4r0AF0FXEqgOSCo6YYOXPw5eQashWB7p8g5wpmnrIqE53Mmu291aip3Gypm2GgVxxVZyR9/JvncON0DnsnMkrx056TYkHjANJ1y3LWPZBsHUr2FXZ22+BZTi3lN61WGmi2DWwdsm/UnAtavtqvunnV/nF0jJ76Q+WR0ysQAvjO6yeV39XfYaLaMIsL6iaz6aEEDKO/joBZhb5/c7hjJKVVAP3l189goVjvS0UJOYrwLZXq1sQthFnIUTU8AHv7YclY2oxiukWW5cKiRoGyiSgMAyg1NBGKqj5lSRrYZ1fKttdXlHzgy1EAuRVHlYWYX31gwvZ6LmEWo5abs4VCDd88vYK33bJV6ySQ5+U0NmQUwjmurKLRGsWCYRhW1ziVMZe8frcOVpJUzEy96hWB7o2IH335bu173Drc6K6zHE/OgulzBbuEHXBXhTkdG4BaDLXfsXTjdM6KKGk7DbkYNnJ8Oh3ZyyX3GkryvPKODVm7YyBf7Y++Su7qKsp0Gz9Viqzjth3DiEdCfYZgsW5XnmQTERTreueXeo96QQH7b7Dk7YqBDegdpmvl/ki6EAIv2zOGpVLDNvaXinUIAVtqi3pOzvv15WfnsFJu4L+98UDvHKxntve5C8W6rQ6JynaXuVHOrVNKt5d0LGylHc7la3jH/3kQ5UYbb7hxqu/9uvo+skikyraRJO45soD7ji30fcZSd7yNK6qMvZMZdIx+ZcHfHTqPeCSED737Dsu5o5O1510ipMNJ97bDunoPAJBxUfwVa00IpbDq//zXN+PW7UP4lX8+jM883q+MNVOX+x1A8n6fWjSj+eOZuJVyoYvm9juA+tVS51cryFebtuK3APDGG7fg3EoFn3zEHrHtdAz85ueOIBYJ9aW9Tubi2g2+dV5VUyGYVeyikVQU0bDQ2kSySyEA3Lp9CJl4pC/SLFkt64ud6jbb/Q6gqFYBtFLqVwAB3ZpB0gHUrcWkrmfyuXd+5tdOLOG6qYwtwOO8hupGXzr6VLVszqWGjFNlJtk2kkQ8EupTADnvw2g6ZqU26Xj8/BqmcnFbMELnOHerAWSp7zTX+dJazaaqB8x5qNxo29XlHorPWCSEbDxic7rJgKfaFGEio6+1t6ZZg9zqoKw61BKSUU0at7Nbnpn+2T9HWAFejQLITAGz7/J169NwKoZdYymtzbFYsqub3RxACw4VtJcDqN0NWDkdZ86sAMB0gOyZSEMIYa1JTpWQdQ6FOm7elrM55SUz4ymcUeZ6p5NG8h17x/D155a0z8q55Qo6Bqy247mEvlafrsbmWLrfgahrCiCRztuTjlRpWYfKqXrWlRQB9Klc8vK4lkBwuTZA/9zotB2j4RBGUlGts7ToUEbvGElhtdK07deKDrVeKCTwqv3jOLNc7guAm6ozfRDvWoAOoKuIswaQznHilL8Zmhww3cbJmU8MmA/KeCaOeeWBLbgsxnJidRpJtWYbR+eK+Fc3bYEQwtpInFK8xhetTh1qBKZ/AbZkiw75txn9czhIXDb8lqGs1Epx81g7lQO6Tbcs7nVCUwRsresw0qkW1IXSzbAAevVRVCdcs91BpdHWeuVnxlI4tVhCy5EWc3y+iO0jSXzngUnb60IIW9HfpVLDZsTtm8xYCi7JSrnRZ1DIxdRNmmptcDJ2IwvQpxasamoiAaas/ODWHP7oq8/ZFgc1Snp5DqD+FArA3Jxn4hHctNWuDnN2Cvni4TkYBvD2W6a1nw/010mqNFr4rc8fAaCJKnafxUuauhYX8zU0Wp0+A3s8E9PKWuWC63y+JVa6o0MB9MX3vhLvff1+7Xt2j2ewVOqve2A9d8q9k7WknI6O+XwNW3J249gs7KzfaPY5gJJ6p4VOZeDmAHKOBzk+neN41VHc2H7O+rbBhWoThtGfMiDZNZbCeCaOR8/0R/OK9V6LXx3RcEjbfaZfAdS/cZdRXvUa9VLA7L9BGtzOFLAJjeLTbR6TkcITSiRtqdzAaCpmU5qY5yEdAvbrf/cz85jKxXHnzl4aZk7jeDM3JfrrvX0kqe3WIR2TcgNota/vOosefG4Jy+UGPvHjL8VPvHpv3/snNLVenClgAPBHP3A7AH3ByMfPryEVC9sUuLK756lFpwO+idt2DNvm0klNlzNdCgNgPpteCiCd0zHnEkku1FrIxCLWhmY4FcNv/5tbzN/71edsx7ba5iZcpwCSz+eaQwk75EgryVdNFa7zuZgeSmKt0rTVfet1YLErMn/8VXuQjUf6AhvzxRpm16p47+v329QgQC8FzG1DItUC9vp6ApNZfeFTVQEUCYdw564RPKnpwldvmanTo465J+uilMw7HGRSsaDaA4ZhYLnc6LN3AFncvVcE2mljWE5XZX6sNdv41pkVW7t4oD91WF67Ur2F/+/TT+PAVBYvmuk1ZXBzallqSEfAS6oWVKfAquY+SCeJW8fFx86t4o6dI/2dcgM4zgFFfacJfl3KV21pcUAvjVlVGPopPocdtZyc3e0Acx6qNNq28gqAuVl2KlkmuspLZ0qsLpUR0KeXOev0uDnwpJNJWwMI/SoPt/qPXgoxdZxm4v1qVsMwzJbuyjnIc9c5gOTa7bRzhzXncHKhZDkyZQ3VLz6jr1TilRK0ayxty4zQddsFgLfcPI16q4P/+rdP9H3GqaVeOpr5mSksFOt9tS3lfVbn2jGNA9HLMTmSjmEsHeubR6UN6gyYbXHZI+oUQHK/6pYCJgt/69TVznEiHdkquiYuAHB6qWyb+2Vd1fNKgyNdbbSJbBwdA9rGMEwBI1eFXNLe0m++UMNIKmpvBd6XAmaiLsU5jRNiLl/TpohsHUrgqGK4u6eAdY1gx8MtH3a5CKZiEUxk4zivGOIyKqs+zNl4vxLAbUKcHjJrq6jeV7fF2trgKRvlZU16EtA/2evaDmYTUWzJJfq84PIcnN+vSxfRtUFUfxtgX6jdumIAwB27RlBumE43FWcxaolzAXZ26to/mcVSqWGT/y47nERAb7J360IlFwU15cMrdSavkd8CptH3PXdsx6V8zXZv5gs95dKYxhnV62iin4zdpLtLpTq2DCX6N6qONMoT8yUMp6LYP+Ve7X8kHUO12UsVObNUQbHewntfv79v05VNmK1VdTVLjs2ZaSTOVLPJXAIXNfWtrGLLLgogwN7WW757eijpqmba3XXkqko+QB+h3zOexvaRpK1Nc6djYKFYt7UWB2R3KzcFUP8myPw3p+PFHsUZ1tSVcVMSWI5AhzG/XG5oC0Cb52F3BlrfoalZpiKEwIEtGZvR1/sN/ZsvJ7vG0lb9AUmx1uqr3+J0qM13FS9qJ0fneJbM5WvIKnWaJNJZosq53eZn+UyoTnJnQXjJ3m6K8OPn1myvP35+FS/fN26LnMpUGFW5lndRDgKmIuHCav/zIa+hGh1W1UJnlsoIhwTumrEXtZSMW22S7Qog5xq5fSSJWCTUpwhptTu4u1sYVF3LZ6Ra1qEAMlMv7OuQ5YRSVHb5Sr/hC8h1TT9P684bMOcuXWqx7vjrt+TwAy/eqalP1b+Rd3b6ctYrcdozzhpT6nHq5wC98aarybZzLGWzQQAzeg6gr8YTYDrYGq2ONu0K6O9aJNk9nu5z+HU6Rl9R3Ou3ZPGcJnDjrNUhcVNK6hRA6uuAWcOi3upoA04j6V4gwFknDDDVKM7W8meWy2i0Ori1m8rmhnzsPvP4LAq1Fn7rnTfb0ildHUAuQUfAnLfUedfZwQoAbux2tnU2swDMWlrnV6p4saM76EgqZtXlkqyWzTRzNaAHwGqB7rQdyt1SA/0KINmsozf+/Gq+OWs5yWdRLW6uc0SbSpZW3/g5uHUIiWgIXzuxaHtd12VPfn++2rTq7ekUMm5FoOVzpnMAxaMh1JrOMa9fR3TjwzCMPtWGLrCYrzbRaHds5TIi4RCGU1GtA8ht7c45at+V6y3MrlUtNcyeiQz+zZ3b8VcPne1LI2+0Oqg29YFbwKwltVZpWmPhuYUSYpFQX+Du5fvG8fobJnF8ob826GlZELu7dsgafCccaUy6bArZrEPdR3mlgAGmSlWXApaO9T8nuWQEsUioT12tUwDJ79OlxwPAo2dWEQ4J3Lqjf652Zsro1qjJbBxPz+ZtztKFYg1PXljDq5WC7Tu6ncPUtUKmTQbpMqpzPl1L0AF0FZEKIGnArpQbfTK7oWTEJu+2BECO6AZg3zi5ycW/+/ZtePL8mhW9l55k5wM15lJYS6c+MCOx9voKo+mYrcvMULctt1ofJq+RLQJmDna7W+hWcuRSEYloqG/R6TkqescuWg6gfiMrb1MA6VUA+6f6J0HAzQHUvzi5GXlA77rd/cycdd917Vkld3UjaoccaouFYr0vqgkAUFLAKg0zV1uNDErjWf19apqYRN5/t3xqGVlQN9FuCiDDMDBXqGkL5wI9Z6O837VmGyfmi5ahl+u2X1ZbohaqZqpCNq6PsPUcQM4aPf2pHEB/0Vw1Bc2NnmPKPK+5gvkMqB1CVKaHE9oW2kcumYv5dQ4H0A3TOeSrTduzVW+18ZdfP42Q6B/fKqrxJseZi+8HAKxaXs50Fp3jVQiBl+wewxNKhHupXNfWJXJPA3BPAVOdZDojS9dO2k1JIOdAZ22ElbK7Asir5oD6mTrcOrcEMRxmxlI4u1yx5kjTGLYrT3KJKEoOB5nsDiWNG6Bf0SaZy9es3H0VneKzV6TfodAcSiAdC9sVQJo5BDA35jdM5/AFJYIq53Znii5g3xSYBcH7Oz9KdowkUW91+lIR7z48hy25hK0eidq57vRyGdtHklYNASc9p2Hv+SnV+8erqQiJ9wVJ7j22iOVyA2+/davt9Uw8gmQ0bKknJWuV/oh+LtE1rp0KIJ0DSNMyXqJTLgHAm2/agicv5PtqGJXq+uNHut+hOtvyms1ErwOhea3Nluf2TaU9CKN/LnQOoOPzRWwdSmjPz2mDAD21m65dtVXQ2aXTqa4mGwDcMJ3FsfmizbGzWjFrsqkBmeumsmi0On2KPjkGnWvLcDKKOU1XpD4HkFWzp3ddll0i9IBUPbsrgKxjFAfiqUVz0yk7erkhlcZfPTKPPRNp3O5wGHml/wL9ZQcAc+5V1Q2r5X47dtdYGsloWFtA+K+/cQbJaBjfc/t22+vbR5KYL9Zs9bd0xZQBMwVE1xWx11ilX00G2G1l3bOh4qzldHqpjFgkZAua6jahVicpTbekV+ybwFeP2tdvVwVQxp4iX6yZChlnJ8l6q2NT4VUbbXz062ewdSjRVxMKMMs3LJXqtve4OaF06VeVbj07Z9qzPEfJvKNhjsStQ5wVzHCoSYdTURTrLet5lup41cn8jlu3otHu4BGHstdqPOESoJD2rgy2PjNbwA1bstp1Z9twUuuMPrNUxngmZo2jngOov4xDLGI2ibC+Px1Dx1HGQdq3Q5q9BmD+7kfPrtrq3y2X61rbXQiB0VSsTymnUwAd3JrDLduH8Ov/8mxfYWoAePTsKm6cztn2jJJ+BVB/8PAnX7MXF1ar+POvnbZee/jUCgwDeK1SskOq7NXgh1XwXslYcXMAUQFErhq5ZBQtpd2wbnANd3Pme46T7mZOOSYRDSEaFn0ecp1h9Y6uUfrMbB6AOamGQ8I2cQCmMiOb6O8CoFMfyE5ckguObgaAWXS00bJXmF+rNhBR2htLtnYXWLUGwEMnl/CimVFbRBUwjZeQsKtDegaRQwHkmOx1rdoBUyVzfL7Y5/HX3Z+pXALhkMBhJRrltVHMJaL4sVfsxueevmR1A3NrHQ6Y13brUAKHHLVBFgo1W8RfEhI9D5C8Ds4UMKC3gLTaHaxWmn3R+17alUuXm1IdQ8mobcMtO8k5i/ieX6kiX23i5m393n2gf7I9fDGPVsewimmGQgIjjsiOrN+ky70GTIMoHQv3yZzdNkTODkSr3ZQWL2TNBXlec3nz/N2UOdOa2laAGRnaOpTou/+3dK+XfFYB4GvHl3BysYw7d430qZicv6e3gTVf8/D/YPd4GtuGk/jgV0/YZMNuyruZMbP7nzQU5vMy7aZfHr9Yqvc54nT3Yfd4GjtGk/iNzz1rPaNFTSTVrZ20bmEe0cj5G60O1jRjXuKmZHMzplXcOre4OR5Vdo2lUW91rDm23uqg2Tb6ikA7axOdX60iFgnZfk86FkZIaOopFfXKUDmXqM6MXl6+/fcKIbBvKmtTAC2X+1WEkpfvHcMzs3lrc7tcrqNjQDt/Dad6qRHOds5ObuwqO568sGa9Vm+1cf/xRbz1lmnb3GAqC8zPO7NU7iuCreIsjKvblEh03aT+/tB5TOXieJ1ieErGszHb89Xp1pVyjinpXJJzoqmG0qeADafcawCtaJxLAPDWbmqrM43TtBv6x+lwyrRVyrbC2P1zQzwSRiLaa9u7Wmn0KYDsnThd0tq0DqCSqyLTrJVXsTlQzq9UEBL6tALZEfOeI/N9/waYjgfddbt+Sw6NVsfe9MJKiek9VzJN7bhDuetW6+I1ByZxdrnSt847ax/K96nzqZtTCZApYM1up0C9A2gkbb8npx1pJ27IS/3spQJuVTquSoY0DgTAHBO5RETbjTKTiNocQAvFWp9jORwSuG5LFic0iolnZgu4a2akb1O+YzQFw4CttICu9qFkWFNradkl9UnXiW+xWEdI6FXggKzlpDjdlsqYGUvZromuEUtPldl/3i+aGcGF1Wqfg1VnYzvT6pc0QdOcwyYCgF/4zNN48kIeP/mavVr7Y4fVcbG3wXYL9OochLqMBDlm1d/lrPNm/a5UTJsKZHUb1KiQgJ5jRNbtul1JTX7RzChi4RDuP2ZXV/mpaeS9X+0+f89czFvp805kkXJnAxVnnaMdoynEI6G+sS/nWWcjF8C+N3KrvyWRQdf/9PFHe+dQqLsGG50Ot3qrjUqjrbUZfuff3IpGu4MvHbbPuc12B0+cX+trMy+RwUw5txer/eUDXrl/Ai/dPYZ/fGLWOk4+N2pgbCQVRTIatgUZZ9dqiIaFrV7fRKb/2ZOlOugAIleFnkzfnHycObiAOfg7SmFdGeVSjW0hhK3NutdAdUaGS90UA11qiE6iaRWgVaIg20bMjh1y8ppdrfQ5gHQV5mUNHud3S4mtLIy3Vmng+HwJL9s71neOZjcWe62U5XIdkZDQRhwAc7LvtR3sv0ZvOjiFWrODzz9t91TrNplDyShefd0E/umJWev3uxW3lryt64S70M1D7eXE64+/c2YUj5xZsSa2WrONQq3lmgImI3M6R9S24SQS0V6hRTl5Oz388tx1NWjM1/sXhV4qon3MPNHdoN2y3ccB1DVCnr5gOjxuUyKKzoUmiCd+Mtff6cWUweul5/JzAfO6uBmHvXOKWscCpnNUCL00GjALmzq72wHmAj2h2ZQf2JJFLBzC+z79tLUQPXMxDyGAv/rRF3uem5ruKMdDyEMCFIuE8KvvOIhm27A2AIBap8t+zXaO2Q09yzHsiI6+ePcoDAN90TOdoiIZC+M/vHw3VitNyyAr6NJMNJvDNZfxkE30y/mlgahV0KHnPOlTAJX1tQxURtMxFGutvo5ExQAKIDlnSuOk5xju/fadYyksORxq51cq2D6StDk8nGuCZD6vdxzHI2GMpKI2NY2cx3TX9brJDI4rUUi3FDDA7IRVb5lrEtBLa9Jd/3GlboHbxkFycGsO0bDAY+d6Y2s+X0ezbfTVickmoig32mi1Ozi7XPHc3KZjZreqVSs67l44c0ozx5xZLuO2HcPaDZL5+xSDvN5Cx9Bf44ls3NrolLod2ZwRbADYkjOj7s55t9Xu4NJazZZWop4H0K+MWyjUbWkVEvm9auqw27o1nDRrErU75hqrOtKHUzGbCnet2tD+pp6SyDy23TFwcrGE66b6VQeAqfCoNTu2a3tupYLpoaS27ta+ySxevm8MH3/4nLYO0HK5ro3s3yDTjy71NmDWeM7ZAy1CwArySOSYcjprvvv2rQiHhFaBmY33nCU9h3bvGsqggq4m3EgqhlbHVLA5U2klTjvv5GIJW3IJpDUKnZSS4tUxDKyUG5gv1HHDdL9jTudAALrtzpVNmYra5ajV7uDcSsVSp6pMZuPa9PQLqxWt4kvWcrHXF3JXgaq1k9Tjgf75SNeJby5fw3gm7hqkGU7FrCL7gOl0c85JvcCY6rRynxP3aGqMybphTht71KFe1s3JPXu5a0d0DHz12ALeevM0/t3LZrS/S1djRSqpnPbUUDJqdZqU6IKhU7kEhDA36pL1KoC+cmQBsXBI2/0S6DmIvnR4DrftGLY9S8lYGK+7YRJ//+j5vqAToFfuq793rdLo1ldsaVVT8vd2DKDsCDovOzoGhkMCE5qxb6rZ7NdX18ygV5tKP+6//0U7sHcibVMunloqWSloTpzX2yv74cCWLG6YzvWtU0cuFVBttl0dQPLaSMdwodbfMRkA3nzzFpxeKlsig9VywxIySIQQmMzZgzZmXS+7/SRLWyzarl2/PXatQQfQVcRZqNNZhR/oN4Semc0jFglZDhWJ2uXArSAqYBYbTUbD1iLrViMAMCfHPgVQvo5kNGxLvdk+kkKzbVgP1UKh3meM6CrM5zW/F+gZUnLikhuiXaP6SWg8E7elgC2XzEnTqQ5RJ3vZdlC3mXvx7lFM5eJ9+dTOjieS77x+EpfyNev3y3PRtYEHYHW1kROVlwIIMCM784W65fyTzgCdoa4IgKzJXr3GoZDAnvFeIeheNy/7uUa6lfVdU8CK/RF/t9opT55fQzwS6tuUSZwKoLlCHbGwPd1vIhu3bU7XXCLVzs9ddKSHFDTRA0AxVpVn0Vmo04n8/fK+z3eNPrfUkumhJJbLjb6IqFtngUQ0jP/yhuuQrzbxVNeJ9sxsAXsnMlqprIpq1Ft1w7wkQAB2dztNqPJYt+57lpTW6QByjMlbdwwjFgnhW6eXba8722pLeg5q83t1UbaeA8jfIRgKyYLYvWOlsevmqBPCjJj2tw0OkgKmLyCqky27vVc+cz3HQ+99N1uqsJ7i8PxqxRblkuQcBXetOk0uCrWpXMJWAyjffVZ0m5jrprJYKtWxWm6g2jAL2zpbwLv9rt781X/9J7JxK0VK3jO3ItCJaBg3bh2yFduVqlFnepmcKy7layjVW30BChXZ/UVuCryippPZeF9h99VK0zV9dNxRmDPvYTCrCiBdW3LJHbuGYRjAE446S3OFGlodo6+4PGDaAbmEvRORYRi4lK9hWucA0qRdrrhsiKV6Qlc0fSqXQLHesq6p23PrdPKe7dalcVMAyZbU6u8xuwnpn3EA+K5bt2F2rWql4ErOr1QwX6jjoKZ20N7JNCIhgaNK+pGuK1IiGsbMWLqv5fCKNYfYf3MqFsGopmtPvmqvRSSvteqIk3aBztGnpjO6KYCczUgurFS1ThTAbksY6NXhkY4x3bFOG9Kcr/TPXzbes2MvrFbRbBtWByQVmZKoUqq3sFppase7LvXDTQFufn5/YXU35508XnXK6TpiOo8v1ltotjtodwycW+53dA0no4iEhG0TKseaztkur9PJRTWA09A+X845WV9HThblN3/Xsfki1ipNW0qNk+0j/Qqg1a4KKR2zq/edqmtAnWt7tkEsEsJ0LmGlOgNmR95MPGJL2wHM1DanzVpvtfGpRy/gX9++TZN62XOorpYbePJCXvv7fvQVu1GstfCNk73Ofr10KhcnovLsyd/lNt6cJQgkq+X+UgSj6Zg1j0h0tbLk+FNTYwu1JqJhgURUb6NGwiG8cv+EZTeX6i3MF+pWAwMnI2n7uPezkcyW7vbnSgYH3WryOeeRYk1vL8tnXNrjK11VlHMf6EzbvrjWX9g9FTPrJNpq8FXd1+BrBTqAriLOQp06B0POMfifns3jhulc3yZTlbj7eaaziYjlHCjWW9pcbEDKte0TzUKxhqlc3BZR2G51Qaig2e6gWG/1TUaywrxaQNFsDa6XLQO9yUQnT1UZy9jTLi66RLnViUQaULrvF0JgSy5hm9ikBF832ctuZzISt1wyJ2M3R8B4Oo5YJGR1S/OqAQTAMkSl7FOqsPQKIGFFNN3GwdbhhOKs6k8Tk7hFUwDTuHZuoN1qpzx5fg03bRtyvR7ZeARxpZjcSrmOkbQ9aiUl/pKjl4rYo4kMqkwqEXRAKTDoYgQDptPMMAxz8fCpAbR9JIVENISj3Q3EXKHWt5CoyH9zts0s1NzVTO+8YxuAXme9I5cKlkzXi6Fu4bxOx7Ck+l4KIKCnQFGjd84ItERuEGSh1fl8DeGQ6FOSJaJh7JvI2NKF6i2zgLPuPjjbl+uKafZas9pTSdyuodM4txwQLg4gwBz7S46xv1I2U1bdHObyfUB/8fQg7UMt51GfA6j3PlnQ9uluWqBhGDizVMGusf5Nz3AyZksNWip16zS5jNGJrN05oe3m0UVuNk4vl3vzs0tRbWcRd/lM6q6/eQ4Nc771UQABZqFNNa1Dl88P9MaV7CTltTkDYHN+y//rFJ17JzMoN9r40L1mhyzDMMwuPS7XzekAsqLjrgqgrhrKIx3u9p0jCIn+OnFejgGgf34vVFuoNtvaa9OLZvfG06ym2QMgC8w2epsBxZEuz0UGP3QFQ4F+o1+qza5zcQDpip4vu7RGl7zm+gkA/Wlg93WL27/6uvG+98QjYeybzNhqJ8nNs3M9vG4q09e8wcvucI4NQNbW6n2uMz0RMO9zJh7Rzn/yexZLdbPTqIv6VV2zl8t1V2euOmcbhoGvn1xCJCS0BaN1imDDMHB+pWo5CpxkExHUWx00Wh2cWjLv+V6NA2hYU3tEV0hZMpVLIBISjhIEegW4/HynA6g3D+gVa6qtPF/Qp9pK5DOxWmng4loVjXbHasQgCYUExjNx2yZU1y1MsnM0hUhI2BVAGmWI+v7TXWfRgkZR03PQmGPj4VNmEOcle+wFtlUmMnHEIyGcVppJyGdclyIIONZxl4YoahH/VruDu5+dw+tumOwrCTHadUioqVTH50qotzra2ozTiu3+zW6Q6uX7+jMNpHJoQVOPyavOk/n7G551rwC9Mwywd8NVP9dpl+sUQDu76WJqGmqx6wR2awYCmE7AYr2FaqNtjQ/dMwgAo44gcU8lrb8mOYfa0DAM/MOjF3BgKttXXF19D2COw3rLLHivs8GkA17ad6tlvf0ymU3YnKoX12ra52n7SNKmGJSqKJkedi1CB9BVRFUdtDsGivWWplq/3Rny3EIJN2iUFKoCyK9FdjYRsVpi6toxS4aTsb7ozapmY9zrglC1JjCdobplKGHLqVwp6xfgSDiEbCJiLcDWBsNlwzaWtiuATi6UtB5rGUleqzY9O3UB9uKJgNlpw60gqWx9LTf2y+W6tiCjJBQS2DqUCKwAkoohudFZsDaw/RNRNBxCxzDTAN3GwYQSWbaKOWscQGNpfWtFQJ/ykYyGEQ4Jm3Ki1e7gmYt53Lp9WPs5gOlwUzc7K+Vmn+G+YzSFpVID5XoLF9eqmCvUcMdO988EuhO9Mt7qrQ4abf3iIetoFWpNq8OUXw2gcEjghukcDl80N+NqK2AdcqN00VEHyJTm6++9qSgSmF0zC4TOF2pWG1wvcskoDMN0InQ0KQ46EtEwJrNxezeTqr4bzlg6hkQ0ZI3hi/kqJrNxbV2H3eNpW8teL2PIuWmwOg1pC83aax14ReLUZ1mOMzcFENDtMOUo4HphtYqtw0nXulNAf2QVQK/+hk8KmKx1sWw5gPqVJyPpGCazccvIn12rolRvadV1zg3+t7oOAl20Hug3zuby/fU3JHIMXlyrKvOznwLInm6gu/7jmTgabbM7k1/XNcDsXrZQ7BXPlXOk0xErn3nZacXfAdTbAM4X3Wt7/cCLd2L3eBpf6ToRSvUWWh3Dde5wdmax0oU1asOJTAJrlSbqrba1XunGeCYewYt3j+LvH71gK3LbcwDpN9tm9LY3Pi51i9jrDPFhhx0CmAGfoWS07zmWCiBdvRKrRshKFbVu9yqtU0KjAAKgVYOox6vOhpVyw3MdnswmcNeuEfzzkxdtjTj+4MvHcWAq6xr1vn5L1qYaOrtUwXgm3pcydWAqizNLZZvic6XcQDYe0aaljWdifSnXy6UGxpXfkI6FEQuHbA5tWXNRt6mT9o10juic0M4W9LpNp0Qdfx0DuPfoAl40M6q1XXQb/JVyA9Vm20oVciLHUqnespwIuhSw4ZRZX0gtVnteUwxfIlNn5NzT6Rjd4utuc1YUS6W6LT3QrWsYYO+2BnS78HrMMVbR/XxdafXd/zsnsnHbZnV2tYpkNKydE6Nhs4i0zcnl4mDNJqLYO5G26qctFOtIxcK2Z9l5/x4+tYwdo0nX+QQwbdsbt+ZsdQvzLoFerQPIJc1m+2jSpjZeqzTx0j39jprRdNzqaCZ5pmuf3bStf92TG/8Lq1V86/QqktEwbtHYqqPpGMIhYXPGeWVaqL9htdJ0bbbTO7bfAVRvtVGqt/rWEl1gVlfPKhwS2D+VsaWhFqruGR8Sua9YKNYsJ+weDwVQvtpU6qo2rNfdfqfqbP7m6RU8e6mAH3n5jOv5yAB2vtrUqqJ75213AK2U9UFcNTPAMMyGFLpsir2TvUwJALjn2XmkYmFXpdK1AB1AVxFrs1NtuU4mcmAuFOrodMyca51aQ13E/aSJZsEx6SxquUrsnRsCQN+VYZviAHLrHAPYo+rLpTqOzxdd04JGlAiPbN/pVmNiLNOTTlcbbcyuVV0cQL1JdtVnonIW6fNyqjlbu+vSo5xsG+kt1IVqC+GQsOXXq0xmzULT0sEk5Ys6lZOcLEu1lrZIJ2Bex5VyHe2OoSiA+q/D9HACZx0ti+X3F+utPpm4EALbhpP45ulevaJnLxVQa3a07R1VxpRFbUXjQNuppBzJmh93uOQMSyZzcZQbbas1pFdrViGEFcWzIn0+CiDArEPy7MUCOh0Dqz6dw6xxstavAHJz/oVCAtNDZo2tQs3cXHptaiQ6lYxfChhgbtDUqMfsWlX7fWaR2p6S7NyyvvYCAMyMp7pyflnY2d0YchZg1qnj5LypGtxuBXKB7lyi1FvwktFLdoym+jr4nF+tuKopJM7OcECvmLNfG/hULIJENGQ5StzqHJjPrzlGpaLles08OuZIKfnKkQWMpKK4Y6e71Fpe71a7g6dn81YhcieWM3Otam1aXednq6169/muNLqqv/75rlcPrNZLe/JwnE3lEqg1O9aaN5evYSgZ7UuRlNdeFr/3is4D9vWnN9/qHe637xy25mY5ztzG4ngmjo7RcxDKVCJnwwLz+3rXza1Wm+THX7kHl/I1PHSyl2r55Pk1hEPCCiA4GXVEkuW8pFcAddMZlGduVtPswTzWdJ4dmzOv9W6l7obaMjvv4eBzNqFYqTQQC4dcuz6qthTQVWJVGhj16JQIAN9zx3Y8t1CyHDqPn1vFcrmBX3nHja5R8hftHsVcoYZvnTYdqqeXytqOWdtHU+gYsG0a1zyUpWYBeXvAxezA0zteCIGxTMzWMfOJ86uu85K8tnIdd3O2mR33Or26TS7KKVk8HDDniKNzRbwoYOoG4K1gAcwi0IA5/6+U6wh3G0A40RX3l2uRm+NFVQSbgRH353TLkNlh0J7e4p7aOZzszRfVhlmj0VmgWEWulWdXyjjd3WTq6pKpwTrAnG+3jeidfUB/63YzBUx/zrfuGMYT5/NWYGkya1f2q05YwzDwrdMreMnufqeLk9t2DOPp2by92YpWndY/p7ht8LePpDBXqKHR6ljH6NYFp9oUMJuKZOMRrWMwm4hiKBnFhdWKdW11SvVwSGAsHbMpyuV65hbYiXTTbE3HhfkbM24OIM2zItcS5xxm2jP2ANOaS0e7A1M5fO3EkmUnBAlESXtjoVjH0bkiIiHh2jRBPg/yHvbqn7qnuqnj86NfP4ORVBTfffs21/NR5xEv23w0HYMQigKoom/koiqcKo02Gu2OXt07kcH5lYrlwP/6c0t4+b5xrQP4WoEOoKuIGrVyM4bUh7FQa6Jj6Ad/NhHtUwC5bTiyiWivyKpH6oSsI6JGQXS5pqlYBCOpKGbXqq4tHwG5yTejKr/yz4fR7hh4681btd89onRhWCqZNWHcUijGM+YDXWu2FdmwPmpk/oamtWlxU2w4i/R5GfbDqSjikZBVP2Op7F4QVTKlqFMK3ZxWt0U9HDI7wkjlyELRLHKtm9zUOjz5qpnv6+zwNpE1NyHL5bp5bSMhrRrjlu3DZm0jR5tjGVG5WVPU+cdftQePnl3Fk91Czp969AJikRBetb9ffquiKq50EUiZ4nJuuYLHzq4hEQ25Khkk8tn5z598AoBaAE8/jraNpHB+pWptPL1qvUj2T2ZRrLewXG54Rk4Bc9OciIbwuacv2Qp6N1odz3pGW4cTuLhW9ez24kRdNAu1JmLhEGIeXcMkM2Npq8NNsdbEo2dX8VJN8XXAvL4yHfHMcsXVSNg1lkarY1gpI141Vaxc+KpZo+sTj5xHMhq23YtIdyMo57l6q41q0707g1PNt1CsYSQV1UbhrXMeTWGt0rQZZOdXqlojUmV6OIlwSNjatPqleKqYqjvzXKUSS1fnQB4jU0x0tVHM43qbhyfOr+Elu8e0Ki1A1gIxUyCPzhVRabRdnay5RBTZRAQX12qW+tJtzpMGrBy/3oo389iFYh35qjlunfOXirNQqlnQsX/jZSmAutFQr80ZYEb05fozX6ghGQ27zhvTQwnMF02HutwEuj2jUvlwdrmMVruD/3v/Sbxi37g2hW9CqTG25OGoB3oRWrkx+L0vHcPHHj6Ld96xTetoM3+jfSMhN+e66yeVEqrSdra7Yeo7tqu4e/zcKkZSUdtvG0vHkIyGcWG16uvgUzezZjt599QF5waqUGuh2XZXYklkYwmpWLjYdeS5qX8A4Htu347hVBSf/NY5AGYHJ+3mXRZhVZ7BpZK7A2g8E7eCXYCpUlku9QeTtg73ukn+8X0nsVRq4BX7+9PVgF4gwHIAadOfe6nbq5UGDEPfUh4Afuhlu/DF974SgNKS3EctpCo1rYCTi/pSTSOXagUvZVPQIB1gdmlTN4fm57jUaZSdaBU1zarG9pUMp6LW7zwyZzp1vToNSiXcuZUKTi+VkY1HtM/2pMMBNLumd7pKnHXfvNLcbtsxjKVS3apf6XRwq6qUhWIdq5UmbnVp5OH83GqzbaV9u6mQpBNMrQuqU/wCZo1KwzBTZt2OAfQK3ONzJVy3Jeuq3N02nMTsatVMffRwGE/m1JpsDXz0odO4dfsQ4h52hFRZFjzOWX1drQFk2XuOMTqWiaHcaFuOiWJXdaoby//mzu0AgA9+5YT5+VX3YKNErqkLhTqOzRWxdyLjaivJ75Tn6lYoXf2dauHvQ2dX8MYbt3g6VXrXpumZvh8Jh7pOul4mgVYBpKSKeamM906k0TF6c+d8oY5dLkHOawU6gK4iVuehStPVcZKOR5COhbFQrClF6LzzuAOlgHWPcSsSB5gPRbPda1MP6HNNgV6OrlwEtWkjmThWSmahtc8+dQnfeWBC2z3C/O7epm2x23HKzfgbUyZ9aeDvnexffNVNcS/1yb0IoCzSB3jXrRBCYHooYSmATKPN2/BUCz66FZdWmR5K9BRARbP+jm5BU1NoZKt053VTJ8DFkpm2pLu2t3VVO08oRVYBswCtEPpUklfsMw3RE9378IVn5vDGG6d81TRqK2Nn5wPArjh47Nwqbtk27FpTSPKq6yZwcGsO9xyZx1MX1nxT7faMp3F6qaztvuSG3EieXiqj3up4/s5ENIyfee1+fPXogrWo+LUSBczfbjqAzDG7XgfQSrcoulfet2TvZBrzhTqKtSYePrWCVsfAdx7QF32U3RRK9RaWSnXsGtcvjjI6Lp2z1sZBM0eoTvEzy2U8eX4N//1NB/oMBFWd6Dffqc5kwFTqbXHJN5fsdBQNrTbaWCrVXVMXJJl4BLfvGMYDSgH5gofDq+9c072c+tnVKqZycW2dA+nYuefIPK7fknUxhuOoNTuoNEynzuxa1fP8h5JRNNod1Jod/POTFwGYLXDd2NZNN/CbS9OxMGKRUM8B5BGFVJ+nfLWBIU3tCN3xUi11ca2mbfstx8aJ+RLGMzFP5x/QW3/M6Hi9r+6dypahJNodA0ululIYWX8t9k+a692JhRLOrVSwWmniu27bqv1sqQBaLNaxXDKd/m7zhFNt8bf/f3vnHSfZUd373+kcZnp6ctic865WWu0q7K4SQQghkACbYAQWIIKF38OAjUywsLGNwRhjG9sE+xmcSA94YJBAAmRkJILSSlqFzWE2TE49oXtCvT/q1u2a2b63qmdndmbunu/nM5+Z6b7dXX3PvXWqTvz1SWQSEdz9sg2e33FqMdEDbQOoiEdKRkfFIiE0ZRJufTAhhGcEULXTMv7nhzqxfWn1pO/m6sr+ETetyyulpEZbzHutOxRTUyhsjeVLa1JIRsOuIfVM7zAiTu0VL5IxWeC5w+m81pnLuwX0ddwuPNoG/mjnoOcmorYijuHRcQwVihGrYxPinKgvpQ8AWYR5RV0av331ipLvqSIv1DxWal2md+synTcicqPV/LoE6u/bN1zc1LoGUg9ZqgivgZExt15Jye9VoiZV75B3ihaASd1/StWn0mme0pFRvcbrvFSnZL01IQR+8lw7wiEqWUtGUeEYfE52D+FkzzCW1KRKzgGqLtv4hMC9T5/B06f6PCNtAVX7T55v1ZLbazOu0vL3nexFuxMBpBOLSON73/CoGxVcqsD2VJThS6WgytqZpSIxEqivjLsORUBGf8cjoXOKFOt1YEoVilaUqsF3uCPnNqEpxeLqJFp7ZCSr332vRzz/aH8beoZG8bFXbvbVT9mkXHvkfKKe5fdTjq/J6ZL6d1JUT7n2e32c01euqsVly6rdWnN+TX8UygFwqncIz5/px3qPPRowee8lx+R/Dyo55kbG3IwWv0L9QHHO6h8uGoC80vfrKqSRzo0ALXF/17lRxsVuqqX0tao399yZfgwVZH08rwjciwU2AM0gsUgILVUJHGjP+W5iGjMJtPfn3Zus1MVamYi4rWL7hvxDEzNOBNDo+AQGfRSEGouaaEZGpae91MZtUTY5Oazbo/PAYGEcR52N4Ptfus5z8tRTsDpzBU+PEVAMi+/KFfCroz2oTETchbZONBxCTTqGZ0/3oytXQCoW9uympBYG6vuoMG4vz3FDZQLtTohq3/CocaLQF3tebQ11mrNJdzHSVkJZKyo1a7lX0Wo1eXbmCujKFTw3bqr49LNawcu+4VF847GTWNdYWTJqaFE2iRBJz9ZwYRwdA3ljpA5QDGsdHZchvlOVnvoenbkC9p/uw/ZlWeN71lXE8dU7r0AkRLjvmbOucdJLAa6sS+NU77CrZGw27EpZPussYkwe562OB01FzvilpSkWZ5M42z/iXoOl0kWmogyQB9oG0DXoLeOprHJbyQ7irONl9vKGN1Qm0NGfdzdyKzw8nmublCKVmyw/z39FLAIiqeyVci5V96MqWfS4uumzXh1d0jEMjxY9Zl4bVx0VUaGKvapoHJsF8J419XiqtU8ryu8feaZTk467URmtHuOsTUtD+vGuQTxxohe3XVo6fLpWWwx35goojE34fm8lj7P9I/iXnx/DbZcuKmlMUaiNaGeugMpE6ZQuwKnxVVGMFvMriL2yLo3VDRX4z1+d8Ewd0CkagEbcsftFABXGJ6wMqMqIIbugjJRM/1K0aCnAvYYIoEXZJJLRMA60DbjdelZ7tAbWuyN6dbZU6ClQExMCXYMF/NYVy3wN0tWpmGsgBKQxYUOzt6d8aW0KJ7rlmDtyeQwWxrHco/g4IKNpSqVGyUiXvBsh4FVgdOviKjxxogdj4xOeBT0VarOq5lPXWG6Y98Ihcoo1y/v8TN8IGjMJzyg5RcbZaB9z67eU+J5OTSwVvTUyOo7TfcOedYzUnK2igLyivlqqEjjdN4KJCYHWniHP8wcUoyWPO3LzK7w/MDLmbpz90ozVks0UwRUNh5CKhc/pCAV4R96oseTyY56dIoHSNam81juKhkqZOjs6PuHbrhrQ72mpA+W5Lp0ODchaZOMT0lj88OFObF+S9XxvxZKaFI53DaHXx7CkorW7Bwv47I8PorkqgbuuX+35nnpHt6IztvR7r2+uRDRMeLK1F+0D+ZJrW9VMQhkQ/YxPCrfZRb+szdaZy3t2VN2yqAr7tY6WZ/qkAX/qvkB3DPX7GIBqp0Sb9gwW0DVYKOkQVjRmZFHgUnUtdfRorPv2n8Xi6qQxIirjRDEq5/zUOmGKyoSMSD6p3SvKYTZVB6tzqb6jyjzwuqf0jrB+5QYU2VQMLVUJ/PJIN073jXgW3ge0ovRuBJB3xBkw2UHdOywzWkz6uCIWQYjk/d3uUXBf0ZhJoLVnyLfLs16c250HSswbaxoqkIiGsK+1tzgvWq6jgwobgGaY7Uur8fjxHl8DUL2Tu9zr4z1Rk2FuZAxPtfZhcXXS2wqbkC2OzZ7zyZOpX32ftU2y4KGKbCjd5UI+piZ8r6rv6vXKsi29E94LcHVTdg7m8csjXdi5vMZzAfe6y5fgh8+exZMne30n+6Lxy6kDYZh4sqnopBxV00ThFnzNFZwIIINVPiPTgFTRsnqP8zE5hLq0p13fWHTmvJVeIhpGXUV8UteqB19ox8nuYXzk5o0lXxOLyEKEJ7qHcKpXXgumuilA0XOlogmmKoVoOIR0LIwjnTmMjgvf8GodlePdOzzqGrK8DBrKi6s6LJk8JUCx3oAybpginVyvcE7dU2bjQEs2iQlRNEaYNjWA3JBctqwaX3roCLpyeatNL1A8N4c7cq4n0es81FfK1EsVdedlHMkkolhSk3TH70Y7llgohEKyBXv/yJjWUeLcsav7DTBHAOmpnyoSxnRNrmmoQDYVxS+dOh9qYeZXAFOhomyUjAcsjHwKWQfEiQDqLd0tR4WAq85I2z1q+uhFpd3aGz7jV3PQC2cHUBifcKP5vNBTE011qZbUFDtq9I94p4AREV65rQXPnOrH6d5h3wLQwOQU6ZHRcXQPFkoagHRjtWkBDEyOMGgfyPt2jGvS0kW6DV1QQk5hzoNtObcj5ioPA5Ay9LYPjDi1YLzHEHHmx75hubAenxDGNGQ93XJiQqb9+RnrlzkbVgA43C4NCqWKg+oyKyXnukp5jR9uz6G5KuFpaN+1ohaDhXHsP92PbkN9NfV9VJpvp4UhQ7GxpQpPtfahx7lPvGom6ago6qOOAaiUoUvJT+m0Y12DEKK0sQjQ6j06a41Oj9TKlmwShbEJeV/3eHfUUmTTUTdCrtQ6Q9+UuVEHPjpGdZPsG/YuTK64eWszvvl4qxsR3DNYQIi8dYp6r56hgm8EkFoDT66v5F0HDtAdX3ljCphqvqCKyj90qBMdA3m8aGNjyeOV3jzUnsPJHm8jn05TJoHOnExD8Wotrda9N3z6QTx/dgBv27PSN31Vj4xVetZrLopHwljbWInHjvVgqDBeco5TxoMT3UMgglUDitqKuFOzUtYEzY9NeI55x/JqvNA24NZ1PNtXunuaHuHnVwi4uGeR14UyongZ2dV37B0axUB+zDdyf2V92qmL049nT/dj14paY1S16s6cy48iGQ17Rq2HQ4Sdy2vw80PFNvOPHutBYyZ+zlpFrf2VcfJvf3IQmUQE2z2aomS0rs8y/dq8rt22JIufvtAOwNwtFYAbSVqqGPWksWiRql0+DWh0QiGSZUucCKBE1LsW3KVL5fWkmmSU0hnF9NFRX0NwJBzCZkc3qDWZjT4JMmwAmmG2L83iVO8wDjkKspQiaMgk0KZFAJVSWurG6h0u4JEjXb6Ld9VqU1mzvRR4nbaBAPzzpnevrsOEkJZxoPSGVhUW3H+6H7FIyNdSrFKwCmMTOG1YlKn2w8+d6ceRzkHfNpXXr2+AEMBjx3t8J/tikUFVByKPbCrqaVSTdQ9GtVQx/0Wkfm5trPLNWVmUsHuw4HQjKv3+eqFrLwNQXcVkA5DfpNaSTbh1EYBiWK+XsgFkvZ7jXTK0GbAzAKlrQS2oS42pKhl168h4tdMsheqQ9+TJXqyoS3saaZRRqRwDUJ2z2FF5/16eLv14oLi4t4kAUh6gZ047n2FRm4iIcOOmJpzuG8GJ7iFrxbVUq03QPzKKWCTkHVLvLAz2neybNM5SbGiSxbIBuBGK3t0zpNfRb75RRj3A7Il2PT7DMhc/lx8zRgCFQoRdK2rc1rfqujelgAHntmo25f/rqA4f+bFxnPZI2VKLGhV94LlJco472zfipoz4zaPq/KnOF6Y5rCWbRM/QqCy8bLgml9WkcaJbFb337jwJFDefrT3DngVMFel4BBXxCNr6R9wIyVKOhYhWQNjGEFejOT+6fIzkALCyTtZIePx4D3qH5AbXT9ZLalI43TuMwx05NFTGPY+NRULIpqJuBJcprVh5601dMxV6wfWfH+5ELj9mnNfbB/IYLoxr3WHO3ejqi+lS64DatExrOdie892YXeK0Fn/uTL8scmqYW9W8AQD/9dQZpGNhLPcwtui85arlGCqM4cuPHHO6N1l0WXSiqI90DIJIRkdNJRYJoSoZdeWhCrF6OSCU4VLpWxV1MbWosZpnnz/bjwGLuax6kjwMKWCGFC0AUL41tTbyu5/u3LsKQhTrBvYMyUguryizYtRU3rdjUX1lHMtqU3jwQDHV1hwBVGyo4uf5B+T8v6w27UaGPfhCO5LRMF7sYQBa3ViMGO3M5X11oULVXPOLdLxmbf2ktK5dK7zXtoCcA/JjExgZHde+o7cs6yribpeoUkaaTDKC411D+PLDx9CUSXhGeeqEQ4TGyjjO9uVdw6OXAej2K5cjm4ri3x45DkBGAJUy4FcpY/XImG8TiUQ0jHQs7O5ZlJPEr6aXfs34zfO/sWMJUrEwvvzwcXTk8miqMkdiq7XnwMiYZwFoxZ41dTjQlkN7/wiePd2PHzx9BjuW15xjZHJT6jtkHblfHOnC63cu9TSkKCPe6PgEhkfHrdYhWxdn4ZTp8TXouJF4egSQzzytznXXYKFopLdwaKrvoMpfeBnedq+phRDAD54+A6C0QzarRwANqzVm6TFvbMngwNkBa2NV0GED0AyjvLc/fUEqslIKbE1DBU72DLntIkvdYGqh9eTJXgyMjGGnj6JQn6E8st4GIJVa5eRN+3g3ty/NIhEN4bkz/aiMRxApYelWG5L9p/t8ayoAcPNCj3TKSAS/aCE1gaibvlR7SIXuIfK7mYu5xKojzwgafTZE2VQMvcMFY45q8f2L57Z/2JwCpkKSHzooF+qlWlUCkyOAvMIx9bpSXYb0uqZMwk0FAqTXIZs6t8uOztKaFFp7hlxjjU3UhJqUVVpEqYk7k4y6kQw2xhlFZSKKhw914v5n29xNRSmUoUp15rExMqkC3Sq6xVQ4uiYdQ4iKBiBVH8LvdWox+fSpPiSjYSQ9usVNJat5Ory6ukwlFgm5UV+m61JdN0+f6kPcYNDdsbwaRzoHcaxzEL1Do0jFwp6LyYyT3uUuYEvMd3pYs1/aqf54z+Coe03aeDK3Ls6itWcYg/kxnOweQjwS8iwar+Maj51F0fefOo2I04bYRE06hiEn6mFsQmBd07kRGcqYd9RJvfPy6K1qqEBNOoY/v/c5t8bJ4qx//QigWL+rVJdBHbXxfO5MvzG9bWltCp25PAbzY0aDtzJMdA1616fTaXDaO59RRYw9jFxqTrGZO5SO7RjIo79ESqpOMhbGrhU1ePBAB7oHpQfUa4MLyBpsHQN5tPWXrlekU5OSdXq6SnRGnIry/qs5xWQwqkwUN1VffvgYGjNx3LSl2fP4pY6B/ET3EI50DCIRDaGlhF7W54FSXvq6ijh6h0ZltI2PXte9y71D/ilggErLkh13vv/Uabx+51Krzc66pkosr03jYFtOtgS2uE9VFPXRzkEsrk56zmW1FTF05vIYHZ/AJ+97AUtqkljTWHozqgw9St8+e6YfyWj4nGhXZcT9tROdaHKwqHsoGi7daVQZcLqHCkXjvM9cTpDXdq/BkA9IgzlRsZCqKUonFZNrk84BGQHkFR1GRLhxcxMePtTpGv1sUsAAGS3YO1QAkb/x6upVtfjlkW7kx8bR2jOMpTUpTznXV8SRSUTw0KFOCAHf61pRmYigd9j/2k7GwnjTFcvc/00RkVMLepteo3cE9ooAev7sAHqGRnHVKv+IUJ3GqgTO9g+7qblendkq4hEsrUmhe6iAiQnZjazUsXoEkMkxVVNR7G7o1wHM/Y7a+fEzAGVTMaxuqMBTrb0YnxDGRgKAZgDKm2vvbHE6bh7qyOFvfnwQYxMCt2uyV1SnY6hJx3CkM4czfSMYHRe+EWdSxsWMDxv9pzue/K6feCSMinjEjXztGfSPANrYkkEkRHjkcFcxW8JibapqhJ7uHfZ1TG1ZlAUAN3K7lCE7k4ggHCL0aClgXvNATVoGIrS55Rc4AoiZQTYvyiAWDuHpU31IREMlFcyeNXUQAvjePrmRKLUxVYryiLOB9ppwgeJCWHmQvZS9m1rlbFZV4dFSm/NoOOROiN5dLuTj/SNjaM4YirA6HrVfOG1t/TzXqVgY0TDhmVP9qIhHsNEnjF2fnPwWyHqXBgBoG8j7boiqklGMjE64XjvTIlKvzyGLovpPykqe//WUNHJd6uGprdCKKPp1paqvjONwx6CxrXhLNjmpbfnp3hFfYxxQbFN9snsIsbDdplkpGRW6WWpMmWTU9RrY1OdRVCYirkfozr0rPY+rSkbd9KNULFzSiFmKxkwCo+PSXWLapIRDhBrHAw5Ig1c0TFjis4hX136H4/2wRb/Wy8ldbsnKguam61Ittg+cHSiZt69zy7ZFIAK+9cQp2bLdL+KpKoFTvcPoGSogEqKS4b5VqWKHQlMEkO7xOeVGwpgX6G7nue4hnOyWaWM2hbRrtOjBM33D+OH+Nrz7utVWxgx13T/izHsbSrR3V8arx4/LsHm/ziLvvGYljncN4W9+fBB719b7buxcA1C7igDyv9bUORzIjxm/mzqXx7oGkct7p4ABkxeopg0PoIq7jri1ELzmJ6WXykkBO+o6XfzvnytX1eKQU9jZzxAKFFMnOwbyxvMmmwXk0d5vvvdVvYkOZ24xzbsZLQLoRPcQLlmS9fXwq+LFx7sGcaJ7CEtrUiUNXVWTDED+dTr8NiOpWBiREOFk97DsfmqYW6tTUXQOyEYQE8LfETSV5mwCRzoHMTw6bpUuq6KoD7QN+KYjN1bKubS1ZxineofxnuvWeBu+E1L/qLSj/U5Npqnp7Mrw+oTTnKHRZ60HFM9bdap0I4DmTAK16Rh+fbQbfcOjnutQBTlq0TTvAnKD2JxJ4IRjAOo21HICnNbnubyTKup9fVyzth5jEwKPHZPzYN+wv3FJrd9UQ5WqZNS31tOeNfUYHh3H2778qKzH5qOjiQjL69L41VE5b3sZoXUyzprRrx09MPn8muYLPcWmz01v8TEAafdfqTpn+lz5x6/c5PvZOqopipqT/ZynypnzP4c6MTYhSkYA6TWABkbGfB0ONem4a1x45lQ/NrZkfA3y+jk1zbHVqZjrTLExFFcmohgeHUfPYMG4Zl2iNZ440zeMPWvqsMtjDltZl8bhjkG3Y+synzmoKhnFhIC7jrdZO+uGMFMdPtkxs5gl4l8DKIqdK2rwk+fb3P2kzdq0riKOB1/owK+P9eBqj660ANzMElWWoNRcTkRucW5T0Wp1rlQNNa4BxMwo8UgYmxZJg4XX5L51cRaV8Qhae4Y9u/moiVpNCH6LGLVBUcd6fW5FPIJYJOQWwDJ1AlCf6fXZ+uOmRYua0H5xRFpy/YwOROR+h9UNFb4bd/27+lmSq5JR1KRjOOYsXExpAErJqs2TbQ2g1p4hp1OD//Fqs/XAc23IJCKedQRULYiuQdmdySuUu74y7rbf9PvspqoEBvLFzgune4exyLC4qU7FMCHkArYlm/BVvgo1BrWpLXUN6bKzKairUJuMXStqfGtcEJHrTS0nwkjlrMedlA0TdRUxdDiFPg+1yw2E3zWbikVcpVpqceTFpGi3MjwXTZkEzvQNOx0jzAvTgfxYybz9Se9ZlcDu1XX41uOt6Bkq+KYMLalJ4WT3kNN2t/R8V5WMojAmO1Ypz5aXUUFFc/QMjeKUU8vHlDYBTE6HO9kzZFUAGihGLPUMFnDUMcibQveLY5Xn5eHDnYiFQyXv8w1NGdSm5UI0HCrt1XffTzvPb9i51PezlQ452J5z01f80I1opmPV+T7YloMQ/vev/pxp8QlIA6yeIu3d2VG+l00NBHXeVKqTKe1S3ZeH2nNWG1xAOmtM6WjVjpzzYxNuBI4XaiNVLB5sMgBNdRb4H68bRDs8isYCk1NOvCKA/J5XEBGyqairp0w6dWV9BY52DrqpputKGE+9aMoUa5TZzJVKbi+0DfhG4KxuqMChtpzrGFpWIlVs0jicbp9CCDx3Wm5ep1KVjCIZDWOfYwAyGfrUde8V8RwKEa5ZV+9EsI36pgwBgJqNe4f9IzEUS2tTOO58/56hglWdvLb+EeTy/vpn+5JqRMPkevt7h/wjgOoq4iCSjpQei4iy69c3YNuSLP7nUCdau4eMkVaqqDrgv15V6POc37j150xRybqhRKW32NRkAUpHfKrnIwY9M5VltWmc7B5yU6f9nKeqcPUffXc/AGDzonMLK8cjIcTCIacLmP910ZSJ40jHIEbHJ/D82X63mYkX+vk1OYZq0zG3hblfYwCFkvHDh7uw1ifdFZA6JBIinOgewtn+0rWQFKsbKnCgbcB1UPgZoZVeV3UMbdaouiHMz2kESN3YpYqrD5ujzbcuzuJo5yDO9o2AyGzYB4rGtkiI8O7rvIugA/I+V/eh11wjS3YU0GOISFTyO9yeQ9qnadDFgpUBiIjuIqJHiShPRP8y5bkbiOh5Ihoiop8S0bkxbhcZalPqpXjDIXK9D16RPUo5qUWB34JV3RSqCKXXDUhEqEvH3AXlia4h1FXEPJWQ+kyvyBplUALMG9mmTAKxcAi/UB4Vw/FKUZm8d3oRNr8oKUDVspETrCm8WMnuYHsO2VTUmCudikUQj4TwrFM82FR4sq4ijohjSFlel/aNRKhMRF3DlVcxx/rKuFU6ldoEq2vldO+wcXGjFupPtfZapX8B0rucjIaxr1XWCii1aNHPf3kRQPJY04YIKN5H5dQYUtdRc1XCKkKkvjKODqdW1KH2nGdKgI4yiNpErih0T4zJ4KqjvHd+3ZqAyfKw8Xi++tLFaO0ZxoMvdPhu7JfUpDBYGMfhjkFPb5K6Lj/+/WfR59SU8fLmFut5yQigeCRkTI8BZN0aQM577QN5o5FLURmPIOKEGKs0LZtaJEBx8/l0ax8WVSdLGgZDIcKeNTIcvyrp3ybdNuIRKM6hhbEJNPjk2SsaK+PuOTcZgFSYt0oF8Y8AKj5nFQFUKTeMXYMFRMOlI8YAIOHMyTYRQPK86imp/q9Rc8uZvhGjMV9t2AvjE0ZDdm065kZalOq4paM2Um39I4iFzQY8dZ5V8wKT4SObiiGTkDVBOgbynoYHpePlZ5z7/eortZo0BmNcJhn1rVGis7axEoXxCfxwfxsq4hGr2nMKfX1hMlAAxe8lhP+41jZVYiA/hkcdx8ZigxFZzr3DaO0ZxkB+DBubz928EhFasgm3LozJMKaM7X5z7g3rG9E7NIr/PtBuvG5UEejxCWEV1biiLo0DbQPoGx41RggAUj8W65t5Xx/JWBibF1Xh18dkmtbw6LjveKLhEGpSMScFzH/jB8h59hVbmyEErGot6e9n46jR50BbI41N0WFApkr1DI0iEiKkfQw36nivwrrqfFYmIlZrG8WG5gxGxwUePtTpWzsTUKmrYzjbN4I3XbGsZFMDInJTPE015G5Y34hTvcP4l58fw8johG85DGCy7jLNgfrcYBsBpPgdg+EiEpYNVI52DqJjIO+7P9m1sga9Q6O49+mziEdCvmNR14+p5IeOvla2iVLtGSygM5eHEDCuk6qSUYyOC3zxoSO43Kdhj44ytjVmEkaDsxp7zHGGl0J2HTY3eFDy29fa5xtldbFgGwF0GsDHAfyz/iAR1QH4FoCPAKgB8CiAr83kABciKrTab35Vk4HXxVqdjqFWi1jxUyjKSPLEiV5UxCO+CrmuMu6G6h3vGvJtA2mKACIid4I1LebCIcLimqS7+DVt3tUkZbNhUJgmquW1aRzrHML4hJBhp34GIOdzD7XnrBSDeo3yOpqMKuFQMTrFL58ZkOfiaKd3KhUw2Wvop0yvWFmLEMkaVYNOa1aTEUJtuPtHzIsm9zXpGD588wb3/1JKYZInbBoRQDabfmWw8mrXWQp1b9oUlwWANQ2VeP7sAAbzYzjRPYTVPgUKFWrzZzJa6ugFdE3XjE5zNomBkTGc6Rv2/U6TPGcWHs/LlsmF3diE8L1PVTrc0619nsbpmzY3Y01DBR4/0Ws0ziaiYTRlEnjoYAdO9crW6jaL2aqU7CB3rGtQtqG2jKKSkQsx9AwVcKxzEPFICM2WxiM1d/Ybwtz9Itl09PNsMo6HtXQ7m1TDSDikRdWYw8QBuAZ1v++mz0c2tasaMwnkxyZwtGPQM80FAMJhct7ffJ+GQ4RMQos+MYxDf95UCF4/tzYRQApT50NVLPaFswNY3VBhjLxU5/lkzxAmhF14+7LaNI51yQ1KvaFGlBrTVPRzZZJFVqv1ZdLX65x2xf9zqBMrDE6Sqejzqk0EUGW8OG6/cakx/eT5NkSc4rh+NDst3vc7UUylIoCAoiMgZeGVVvdoJOyT7rS2DpEQoTNnrruln9ZGi2vgDTuXYTA/hi/87DA6cwVjcXnZ9dbpWma4PnauqMFTrb1ubTfTOrHeqRdmEwEETF5Hm+rGqfOWioWt1g8ZS0O3zYa9eKz8XNVlqbbCez4EigbYxkxp55Wan0Jl3EsA3DIMjx7v8U3/UmPozOUxPDru22Qhk4zgVM+wUxvK+/y+dFMTwiHCX91/ANEwYfca/9pF+rk3zZm6DrXRkfo4bZxAS2tSePx4LyYMhuXdq+sBAI8c6UJ9Zdx33ErGygBks0fS9bPJma3WOqpbsKk4trqeR8cF/tcNa4xjAYr73kTUbIJQtSmr097OMTXm9v4R30gude46BvJWnf2CjpUBSAjxLSHEdwB0TXnqNgD7hRDfEEKMALgHwDYiWj+jo1xgKKNKv7PQKYVaZPhdrKqdbKUWaVMKNQGMTQjjQqk2HXPrlRzvGvS1gla7BiBzcWUbD4lSHNEwGW98pUxtlLr7/oYF5aJsEmf6hl252ITpdg8WrOu0VKdibhSOzflY7xSEXWzoRFRfGcdJp+OOlyz0hZLfIqsmHcP2pdV46GCH23bSFK2kK8lyvLCmmg36OP28WlNJOh4Dmw286oKjFpQ2qHvTdsNx2bJq5Mcm8P2nzmBCeLeB1lEbJZsOYApd0ZcjB7W5aOvP+14b0XDIDQu3iQBqqkq4mwc/I6lKtRoeHfcMPw6FCFsWVeFUzxCePNlr3LS9bc8K/OJIN352oNOqALQ75kxCdtsw1MqaSk06ip7BURztHMKy2tK1Ukqhb479jJwqlUTl3ntRXYYBCCgu+G2/q9ogmTYpFU5UlOoG5Df36kYBG1ltcwq737f/rO93jDoy8NONOhubM27tMGMEkBbVYpsCBpg3uPr9bo6CjSCXH8P+031Yb5H+lIqFEQ4Rjnc60aIWMl9el8a+k70ojE9Y1XYrtVHTmw6YUm0npWwbjA2rGoprk3IcQUD5EUC64c4vunKtE935zKl+NGcTxrpyzVVJdOby2NfaixDBU47KsWJjtFPnws/TnklEcakTeWEySurGgHfsXWX8/C2Lq7C4OoUnTqjiuf5y1OeG1Ybo2J3LazA6LnD/s20AzJtyaVwa8e28paMfY7r/1LE29xEwJQLI0tFi+579I2PoyhWMhms1/3jp43I+W2dFXdpds5vuW9uyDLXpGP77QAceP9HrO29WpaJY11iJ4dFx7FxRY4zmLuc7KtnGI/51shTlRKoD8tpXdZP8DMv1lXG3MYxJ36jshKdaewHYOSrLMZ6rQteq4LfJwKufbxsDsnxPJ6rH4pwrR6/fPrQhI6OGTRFA+nW20sJRG3TOtwbQJgD71D9CiEEAh53HL1rUhqfPxwCkJh6/hfkaZyNZqmuOjqrcDpit0tlUDH3DsrPGmf4RtwVhKaKOhynpE6Kn8tBtKugr62tlwj/NAShahm2VrxyDWTFNCLhGGt8UMG3BabMwnvp+NudDbTJMCkuf0PyKQCtMi/BlNSl0DORxyikiZ+xcoxuALNpmK0webv0cl6OgRsdlPrApdBQAdq2QRii18bNBnUvbEV26LAsA+PqjJwHAtxWyIhWXYx8XwnpcerqjzXdX6FF+phQVdS3aGDCj4ZC7efAzetVZRqdVJmTB7qOdg7jren9PkuqwYdMCXiebirpt0cuZW7JO96ZjXYPG61onkyymsulRBlNRhnjT5aBHgdmkPtmm0iqUgckcNUCoTsfctrxeNcyAycZdG1ldvrwGVzmFIf3GHQ7J+2Fiwu4e+r2XrHX/Nnb30543GRB0HW5KgVLntToVNRoP1LGduQLWN5sNQESyoYSqBWiTIru2ocJNPbJxdJTafKVjYVdfm65JPQXFFOmSikXctYfNta6jR9rYGNl1uflt1LKpmKu3bKIwm6sSEAL40f6zWNNQ6Tlvb3Lms+HCuPE91XkzRXGoa6acCKBr19UbPx+Q8lP1EU1rnWvWFt9zS4l6MDrKaPXj59sBmK/JLYuq8FRrH071DhtTNYHJaw7jxjZVNA7YoF9DfvXlTDVYJr2nlgLWNVgwGgjVfO/lWC6n1qJOOESu3jNF7un3qt9m/C9evdX927RmVWus69Y1mIbqu1+ZitIvtvUAlYxt6yfp8jJFexcjXfxlvLaxAhuaM3jmlIwqnK5Rz4tMIopcfkyLALI3ANl2p1WvsXHexBw96dUoB5B7mp4hmfrsNx/p1+YqjgA6bwNQBYC+KY/1AThntUJEdzp1hB7t6Og4z4+d36iOVwVno1oKtSnwU+Eqd9YmekHdSCsMdQWUdffxE70QopjGUQq1GfFbZ9SWEQGkL/5MqM8ux/Nn2uSoz2/tMefO6gsPm+JwQHGstemY1QZ9q9Pi0HTu9LF4poBNMgD5nzPVXeaMZQcl/byurrcvxBkOETY0Z/CqS1pKPu8VDm+iMCbvK5uFWVNVArFIaFLrVRNKaduOrymTQDwSwqPHe0AErLLwLNy5ZyVevqUZv7ljifW4pssy3QBkWCwUDUB2RhVVQNEv7U2/3/02cnqEzB5jmLeWu295fwJy46/SEcoxANWkZPemE11DvsaOqRCRa2ywqc1lQp+zbKKQ1ILfdmGmzuuEhWFSGYuyqajv5ks37tqkbQLSCAT4L+ZVGqWtjrh8eQ3+7NYteOUlLZOMqaXQjTMmx4J+rMlQoaJL/uBGc5C0LmubOQWQ15gqJGpzfa/XUg9t0wSnIlPB4+7n+6GuE9v6W1nLlMSp6POXzQZJn79MY1OGn7WNZl3Y7OjWwx2DuGKld+2SHc46TNVn9EM496bJAKQcEfkxf6MSaatQ2wiHTCKKDmceNRmANjl6tKEybrzvsqko0rEwnnZqB5quyfe+eK07D5lqEQHldYhSUTyRkKUBSDt3fuu/cjbsiWgY8UjIMQDljZGcar6f6QggoBilapL35Cg/72OX16ahVJjpurt6lUxpvGFDo3GcRIR3XLMSX75jp/HYsHMP2Tp1lFxt1w66vEznTR1ruo4j4RDesLO4brSJXAKA379xHd77orXG4yoTEYxPCBztlB1tTQZ0Xd42UXgAsMIxvrzlKvO6XJ23W7aV3kcAk7um+elrXT/ZOGqDzvmWwM4BmLpLygAYmHqgEOILAL4AADt27LB3ey9AMoko7ty7Ei/e6D1ZFY0h3jfMDeultdvGwZnLSy/eHs3b4jW2/uFR/OJIF8IhwiU+VlW1+PZbhNc7hUNtFo9KQdoYgNQGxNTBAgA+8NJ1uP/ZNnNBPcd6r9KpTO1Ok9EwhkfHrSOA1EbPNiXltTsWo6kqYdzsTqrg7zHmciKAMokIBvJjaO0ZRohgrGOgL2Y2LyrPaHPv/9rj+ZzJG+hFhbuptVPCL/zJjWVFGK1vyuArd+w0FhtUEBHqKmQR7sXVSSvjX21FHJ9746XWY1Lcsq2lrM5hwOQNsumcq+vLpgaQjl8EUCIaRiwSQmFswhABZLeABqbfEU33rpVjAKpOy0Ls4xOi7OKBKu3WLwVM1ZhQ6U9e2KY7KVSdEFMdG8UrtrXg/mfbrIxcar4r1yBmg6qJpNKVS/Gua1dhTWOFr56dyht2LcUbdvl3T5vKizc2GY9RHbtMhoq9a+rwk/ddYxV+rm8obaJ5AHkPtVrWTwEmpyT5bYLesGspvvPEKc/n65wmBCYDWDquUkzt5pdsKoYzfSNWnd6m8qINDXjguXYrQ2kkHMI33nklvrfvtNGgqJx3Nml5+lx9pU+7Y2VMstGvu1bUoqEyjruu9y9Cq+SpDDVeWGazTkKXh2ljS0R45O7rXU++6dimqoRbrN2U8hQNh1BfGZfdfyzmcz36xqRjlC6MRuxOkDreFOVYTro7ALdYcneu4Nn5TT8W8JaJ+v5llgACoDffsDcI+KWLhUKEdDzidAHzv79v3NyEh+++3hi1pbj7ZRvMBwG4anUtXnVJC/7gZXZVS5bWpPDyLc1417XmVEmguMaIhsm4TlHztU3Zi+kUMH73tf7zhULJ+WB7Dg2V5q6/5TqlABl9d+wTL7c69k1XLsOVq2p96yTq3Rj9rhH9OlvTYO/MDirnawDaD+DN6h8iSgNY5Tx+UfOHN/lPQG+6chkK4xO43ccCWp2O4c69K62Kyn7p9h0YHZ9wPadeZJIRTAjgHx48jD1r6nzDsO/YvQK5/Bh+yyd64i1XLccVK2uMnh2gOFHYhGgqo5fNhud3rlttrMgPFBfUttXzo2HC8KidZxQoKlfbiYWIsNdgsAOKXpSadMxzglVjTERDRllkklEIARxsH0BjxlzHAAA+evNGbGjOlGVIMZGwMDCW4q7r1qAmHcfNW709AjrTGbONXHTqKmT9J9Vparb4m9dvL/s1+ve36aCRioWtN1xv37MCX3zoqLFQeiREKMA/QkIpZ5s1xOSw4zIMOWXW0Cm+rtgudnmdfQFu/XNMXs5ffegGpGe4Lakas20E0C3bWnDNmnqrNAVltFpZN/OeNLW5Lox7ez8i4RBu3Nw845+t+MRtWxANh6w6CNZWxNzudX4QkXXtAV0GNrVhAOD69fVIx8J4zWWLrfTWomwSe9fW46bNTb6RoH926xb82a1bPJ+vS5uj3ACZwvHEiV58yLA+UiSd1LLpRC78429dhjHL9EBARoiZ1k8AMDIqI2psDJ+6AWj3Gm+dEg4RfvK+a6zmpOp0DL/60IuMxykPt1+UNzA9/ajmMiK7qD7biFJ1rOoYabP+UxvmciOATKhr2TYCKB2P4DO/uQ1XrfJ36BER7nnFRuywuNYA6bBr689jsDBuvD5aqpLYurjKU8+Xm0qpo9KeRn3mZGBKd1fD3KmMqaZxEZG18accUrEI/vp19muqaDhUluNOzdvlGFJsIlrLSUMvF7X2O9Ses6o1OdMpaFOJhkPGJhm6Acgvskff65TrTAsiVqtNIoo4x4YBhIkoAWAMwLcBfIqIXg3g+wA+CuApIcTzszTewBCPhK0ssiZDksJ2w6pPtH/6Ku8FHSAV2t2Gz2/JJq1bWSvvhE3Zk2wZxiJb1Oef7LGrnq8MKbZdwFQotV/ng+mgJli/ybgYgm9RF8Q55unWPutuUnfsXmF1XLk8+dEXl/2aZCyMt87SeKaL8t6YCmrPFR+9eSN6hwpGr+fly6Ux13ZT8KGXb8Qf3rTBeLx61m+DqDbaNgtu/XuUFQGkeddM3mWv15UT8QIANc4i0LQYtl3grqhLW+evFw1A9os02xoVqpbSrdsXGY994Pf2WoeqA3JB957rV+MVPmHfs83rdtpHCm1uqcKRjkFELTeLNui62vZa/cBLy+u/EQoRvmKRKmFCzX8mA9CO5TX4j7dfYf2+Ks1pOhvXSDiEMi45a+65ZRP+6P/tx5bF5gjWykQUr7lsMW7c1GQ0JM50UdKWbBI/+8B1xoL+al9azryWcaNB4lYOpHJQNUdsHW/KKDJmMEwA9ukyQNEwpqLWbLh1+2Kr495ytf36pSoZxbFOVdfLX9clY2F8967dvu8FAC/fUr7h/PYrl+G7+07jxs3+EZEbWzL4/RvX4dbti4zrAnV/22QFLESU48Wm26u6jyIWHrDZXGeqPUT7QN5oPAbK6+A7W6RiEbzzmlXYsazaqp7TGk7/AmAfAfRhAH+k/f9bAD4mhLjHMf78HYB/A/BLAK+b2SEyM4luILjQm1WlfGzqS/zRKzZhbVOlWwx0Jj//pGUEkEqfqLNciKh0BduFiy1qsvKLcopFZAtnG0WqLPyn+0bKjnSZaWwKNy4ElHHR1hh6obE14L1978qy39vGWETuQs/7nlObCr/uNqWosYyOACangCXLCMVXr0tEQ8Y2uFOptYyOsOWn77/W+lgVAXE+nl8v7rllE374zFlcvdo8R68uM9yaiPC+l6yb7tAuOH922xbsXlNXdoqsH7p+KudanQu2L83iubP9M24McA1As+xlLocrVtbih+/da338X7522yyOxp+lhpqQgLzX/uPtu9yupDaouazcdGQblKFso8Hrr7hj9wrc+8xZq82qwqb99KVLs3jTFcvwjmvK14kzSSYZxeMnegGcf+RHOh7Brz50Q1ndRxWrGyrx5EdfYjwuGg5ZpxvZ1gBaqCjdb1PzTE2dPqVjXWZ6ntXRC4XbNLMpd702W3zQMo3vsQ+/yNiA4GLB6iwIIe6BbPFe6rkHAFzUbd8XEnpqx2xOIn6fbROUXZWK4p3X2OXZWn++o2QOdwwim4oaoyFetX0RPv/fR6wjgG6/chl+/FxbWTUpbGjJJnH0z28ybrTrK+NIWkxsk1shciX8mUAVfC+3ds7Fgk0EUDHkvkwD0DRSwFrK3Lio1y2vTVvnuRdfa5cCNhuoyJHZMCBct67BqivLxUBFPILfmOGC7tOpezNXvG7n0rIipmxRKm+63YsYO0xpS1NRBrnZSP9QNXTesMuuccPly2us64kAwI/eu9eqWG0kHMKfvGqz9fvOFqp20su3NGPXyvN3iM5GKtV0ITfCL5j3t1qb2BhSVDR+U5XdfuP+9+5FyiI9uVz0dYrNuAHgxRsbscuyZuZcY6qjdTERzLuO8WQ2PMG2qImljM7XM4oeqmiT6//7L12Pt+1eaR2lsnVxFk9YeEimg02UxTVr693WyH7o3tQVs1C/42JEdSZLz4JCDgSup88nBcx5LhyenoHFBpX3ffXq8jY8KgJoOh5YVQdgLkKlP/marfj+U6etvenM/GEm058XKioCyLYOC3NhUOmss5G68+arlmPP2rqyIpLKwaZ723ziyZO9AIDXz4KBda4JegRQKhbGO69ZZUybA4Df2LEE1ekYXmzR6QwA1szSdawb42yNUV+8fcesjIWZXVirXmTMZSi1ChUUc2QB0kMVr7DwpNh2N5svfOjlG63CIHUj4NpGNgDNBKpWyXQ7mwWdYgSQXxFo1Xa3PAOQTQF6xVWr6vCRmzfinls2lfUZysi0vMz6P0AxCmcuvJw16RjedOXyGS3ezlwYWGZF/bSQoqEuBvJOxKtNgfRyiUVCs2b8WYi8w4mE37VyYURYlEPQawARET74svW4xNDdE5D12F66qansCOOZRt8j2kYAMQuTYN51jCdzOdGqEMfbLrUrlDeb3LTFbJEPKvpiejrtJJlzuWVbC27c1MSdBTywCfVWm4ndltE5b75yGX5+uKuscYRDNK0C4s1VCaxvqsSeNeVFDgHAdevrcffL1mPr4mzZr2UubnYur8H2pdm5HsaccfdNG3DNunq+d+YZKjqNI4hnn7fuXjHvml7MFKvqK3Cmb8TtMMbMPfFICEtrUhgZHccGNsQGGpqLaIwdO3aIRx999IJ/LiNTVdZ++F5sX5rFt9999QX//PzYOGJldBmaae5/tg21FTFcutS+YGDQGJ8QWPWHP8ArtrXgb6fRVpxhyuXP730On//vI3j+T270rb11oG0AS2tSxvpcDMMwzNwwPiHwfx9vxW3bF13wWpJMcOgdKuAXR7pw4+byu5Ixs4eyC3AU6sKHiB4TQpTM0WMD0EXIr491Y21DpXW7XyZ4dA8WUJWMzpsK/kywmZgQGB4d5xpJDMMwDMMwDDPL+BmAeDV+EWJTAJkJNuV0TmKY8yUUIjb+MAzDMAzDMMwcw7GbDMMwDMMwDMMwDMMwAYcNQAzDMAzDMAzDMAzDMAGHDUAMwzAMwzAMwzAMwzABhw1ADMMwDMMwDMMwDMMwAYcNQAzDMAzDMAzDMAzDMAGHDUAMwzAMwzAMwzAMwzABhw1ADMMwDMMwDMMwDMMwAYcNQAzDMAzDMAzDMAzDMAGHDUAMwzAMwzAMwzAMwzABh4QQF/5DiToAHL/gHzx31AHonOtBMLMKyzj4sIyDD8s4+LCMgw/LONiwfIMPyzj4sIxnn2VCiPpST8yJAehig4geFULsmOtxMLMHyzj4sIyDD8s4+LCMgw/LONiwfIMPyzj4sIznFk4BYxiGYRiGYRiGYRiGCThsAGIYhmEYhmEYhmEYhgk4bAC6MHxhrgfAzDos4+DDMg4+LOPgwzIOPizjYMPyDT4s4+DDMp5DuAYQwzAMwzAMwzAMwzBMwOEIIIZhGIZhGIZhGIZhmIDDBqAZgohorsfAMAzDMBc7rI8ZhmEYZu5hfTw/YQPQeUJEbyaiRYJz6QILEdUSEd8rAYaIbiOi+rkeBzN7EFFqrsfAzC6sj4MP6+Pgw/o4+LA+Dj6sj+c3rESnCRHtIaJ9AD4GIMMWzuBBRFcS0bMAvgrga0S0aq7HxMwszn28H8BHAVTM9XiYmYeIriaiJwH8OxF9kReewYP1cfBhfRx8WB8HH9bHwYf18cKADUBlQkQxIvocgB8B+GchxHIhxHNs4QwWRLQIwD8C+BKAdwCoAvDnRHTjnA6MmRGIKE5E/w7gewC+JIS4RAhxdK7HxcwsRLQWwJcBfAXAJwFcCeCzRLRjTgfGzAisjy8OWB8HG9bHFwesj4MN6+OFBRuAykQIUQCwFsDnhRCfBQAiupmI1hJReG5Hx8wgqwH0QS5GjgB4O4BWAO9hj8XCRwiRh1x8fEYI8RkAIKLriKhpbkfGzASax+lSAAeEEH8lhHgEwOsApAC8hYjiczZAZkZgfXzRwPo4wLA+Djasjy8OWB8vLNgAZAERRZzfaoL6JIAtRPQPRHQMwO8DuBfAl4ho09yMkjkfiGgnETUTUcJ5qArAGiFEPwAIIY4D+L8ABOTik1lgOHUFtmkPfRDArUR0DxEdAfBxAD8jok8TUc3cjJI5H4joUiKqRVG3pQBsUc8LIZ4B8F8AFgG45cKPkDlfWB8HH9bHwYf1cfBhfRx8WB8vXNgA5AMRbXLyGL/uPDQGAEKI+wEcBLALwDuFEHsBvB5AFsBvsEdq4eAoqF8B+CcAfwfg0wAghPgugHEi+h3t8H0AfgXgUiKquuCDZaYNEV0N4JsA/lU9JoT4OoCzAN4I4E4AewG8G8BLALyKC40uHIhoNRE9DeBrAL4N4FPOU98BMEREb9AOvx9AD4Ct7HVcOLA+Dj6sjy8OWB8HG9bHwYf18cKHJ1QPiOgSAP8H8kK+mYiuFkKMax6pjwJ4sxDiPiKKCCF+BeAhANcKIYbmZtRMORDRayAV0veEEFsgFdHlWj7yJwG8j4iiACCEyAE4CWAFgNyFHzFTLlrocTekrJcQ0V3aIXcAeK0Q4gEA5Py+D8BrhBATF3SwzLRwZPy7AB4QQqwB8LcA9hLR54QQ3ZALlLcSUQwAhBCdAA4BuMpJPWDmOayPgw/r4+DD+jj4sD4OPqyPgwEbgLzpBvA5AG91fn8JAIQQI0REQoh2IcTTU17TDqCg3QTM/OYEgOuFEH/i/H8ZgBZILxQgC9V1wpG9w0HI+4ZlvADQis9dAulluh3AJ5SnSQhxWgjx5JSXdQDIqdBWZt4TBnAFgBcAQAjxDchCse8koqsgF5xhyJQCxfMA8moRysx7WB8HH9bHAYf18UUB6+Pgw/o4ALABaAqah+IUgP8UQvQB+GMAdUT0Tue5sHZ8QggxRkQ3A/gIgK8JIUYu6KCZstBCiR8TQhwiokYnXHUPpHK6hYg+JITohVyg3EhEXyOiu53nfwiArdgLi4MACgAecP7+BAAQUYXzO6Ldx78N4JtCiLG5GixTFmkAh4HivS2EeAzAFwF8ylmIfBzAXUT0WSL6Xcj0knudooXMPIX1cfBhfXxRwvo4uLA+Diisj4MFcXe2Io7lUuj/A9JrQUTvAPBJIUSV9nwYwG4AnwVQC+D9QoivXeBhM2UwVcbOYxUAVivPExFthQxXvE0I8WMnX30bgBsgFyL/eYGHzZSBh4zfDuBFQojfJFmI7ikAv4ZclHwTwA7IPPVGAP/b8Vox85QSc/XnANRByu6M81g95ObiJiHEw0T0CsguJHsB/JMQ4j/mYOiMJayPgw/r4+DD+jj4sD4OPqyPg8dFGwFERBEiWqY/5lzIESK6Q3/M+fNLAI4S0d84r88IIcYBPAHgL4QQS/jinl+UIeOcEOJJkkQAHIAsMHmt8/zPhRB/L4R4NS825xe2MgbwHIAniSgJ4G0ABgEsFUL8k+PFOAHgr4UQi3ixOb8goigRvUKXsyPjKBHd6Tz0achNw4u0EOMCZJHYdc5rvieE+JgQ4gZebM4vDDJmfRwAypAx6+MFiq2Mwfp4weLI8nYiumyKEYD1cUAwyJj1cUC4KA1ARHQ7ZP7xh4ioyXlMhbbdAOAmx3qpjifnYn4LgHcR0WcAtBHRbiFEPy9C5h+2MtYeAwA4YcZx5+eHF3DITJmUeR9fBuC9AJ6ELBr6agBNjhcKQoiDQoivXMDhMxaQ7PpzCsAHAHyPiP7BeTwE4HoALyGimBDiCGRRwjfBaSfrbCSqIBchzDzFQsasjxc4tjJmfbxwKfM+Zn28ACGZrnUKwGsA/CNkly+17mJ9HAAsZMz6OCgIIS6qHwA3A/gpZKjpTwG8csrz5PPaWwFMAHgYwDVz/V34Z+ZkDNmisA7ATQCehZz0quf6u/DPzMjYke0DAG7RHnsbgE1z/V34p6R8Q5CtgB8DcLnz2BXO/LvR+T8y5TVhAB+D7CjyLwCOAvgBgBq/eZ1/Fo6Mp7ye9fE8/5mujFkfL5yfac7VrI8X2A+A90Ma7K5w/r8ZskD3Iuf/8JTjWR8vsJ9yZTzltayPF9jPRVMDiIjCQrapy0LmoP4HEf0zAALwcSHE4SnHx4UQeSIKCSEmiOh6SIX1LiHE5y/8N2BMTFfGzt8bAdwN4GoAnxBCfOECD5+x4DxlfE4tAmb+oUUBvARAUgjxHSKKCiFGiehHAP5ZCPFV7XhdxlHIDjNXAegWQvzrBR4+Y8F0Zcz6eOFwnvcx6+MFwHnKmPXxAkCbc5sBjAkhOohoOYCvQhZ8vkMI8Wvt+IRwCv2yPl4YTFfGrI8XNoE3ABHRLUKI7zp/q4tV/d4Embv4JQD/Knwq0KuN5wUaNlMGMyjj7UIIDk+dh8ygjENCiIkLNGymDHQZO/9XCRk2rv6PQXoTXyuE+OVcjJE5P2ZKxqyP5y8zKGPWx/OUGZQx6+N5ylQZa49vAvAggO8BuA/SSHsI0tg3eEEHyZwXMyVj1scLk8DWACKiG4noOIB/JaI36s85m8awEGI/gB9B5qhum/L6NBHtI6Lfdl7DF/c8YwZl/FbnNbzYnGfMwn3Mi815RikZOxuDPudvcnLOV0KGI7dSsXU0iKhClzEz/5hpGbM+nn/MoIxZH89TZuE+Zn08z/CSsXreWW9tEELcIYT4OoDvAngPgE3OsZVE9CTr4/nLTMuY9fHCJJARQES0BMDvARgDkANwJYDXCCFyRDLsVIseqAHwbQDfEUJ8hohWAWhzjl0khDg1d9+E8YJlHHxYxsHHUsbq920A7hRC3KheK4Q4SUQEoIVlPD9hGQcflnHwYRkHnzJlHINsBDVKRG0APiyE+CLLeH7DMmYUQY0AOg3g6wD+FDJ8bRTA7+oHOJvGqBCiG8BfAXgdEb0A4FEADc4xfHHPX1jGwYdlHHxsZKy8FC8C8C2S3YLuA/AwEdUICct4/sIyDj4s4+DDMg4+1jIWQhQcw8AOAM8BeEg9zzKe17CMGQABNQA54Wi/EEL0AtgH4F4ALyOitY5VM+wcN+q85FoAlzvHNQrZwpCZx7CMgw/LOPjYypiIkpCyfTeALgAnAKxyDH/MPIZlHHxYxsGHZRx8LGQcAQAiaiSi7UT0F5Dp9w8CeGGOhs2UAcuYUSxoAxDJCvPq70nfRQtjGwHwE8gWhO9znhvXXvceANsh8x3/t/ApIMtceFjGwYdlHHxmQMYEoBJAO2Sr4TtZxvMLlnHwYRkHH5Zx8DkPGY85h9VCRo1sA3CVEOIeLfqLmQewjBkTC7IGEBFtgwxfOw7gjBDi44bjQwB+E8CdAN4LoA/ANiFbVka0C56ZJ7CMgw/LOPjMgIz7AawXQvyAiFYJIQ7P9piZ8mAZBx+WcfBhGQefGZZxvRCiY7bHzJQHy5ixZUFFABFRhIg+B2mxfMz5/WEierPzPJV4DQnZaeCrkOFrvwRwAEDaOYSrl88jWMbBh2UcfGZQxi8AqAEA3lDML1jGwYdlHHxYxsFnhmVcDQBsGJhfsIyZconM9QDKZBGKXv9WIqoA8ASKSueccCbtsY9AWjg/D+APhBD9Xq9h5hSWcfBhGQefGZcxM+9gGQcflnHwYRkHH5Zx8GEZM2Ux7yOAiKhKy188DeDjzsV9G4DDADYByBPRtT7vsRxABsCVQoh38cU9v2AZBx+WcfBhGQcflnHwYRkHH5Zx8GEZBx+WMXM+zNsaQES0BsDfQbaoKwD4PSHEMe359wHoAfBvANZAhry9Xgjx7Qs/WmY6sIyDD8s4+LCMgw/LOPiwjIMPyzj4sIyDD8uYmQnmpQGIiN4K4B4A/w7gKwD+HsApAHcB6HNyFtWxESHEGBF9CsBuIcSVczBkpkxYxsGHZRx8WMbBh2UcfFjGwYdlHHxYxsGHZczMFPM1BWwFgD8WQnxQCPEsgDcCuBVAdsrFTZAtJwEgB6CDiOIXfLTMdGAZBx+WcfBhGQcflnHwYRkHH5Zx8GEZBx+WMTMjzNci0P8IIA8AzgU7DOB5AFX6QU4Bq1Ei2g3gtQA+JYTIX+CxMtODZRx8WMbBh2UcfFjGwYdlHHxYxsGHZRx8WMbMjDAvDUBCiFbAbVGXJ6KNkGPdr44hokYA1wB4B4AtAO4WQnx5LsbLlA/LOPiwjIMPyzj4sIyDD8s4+LCMgw/LOPiwjJmZYl4agBSiWKDoWgAHhBCj2nNtRNQN4FtCiBvmYnzM+cMyDj4s4+DDMg4+LOPgwzIOPizj4MMyDj4sY+Z8mdcGICIKCyHGAewEcJ/z2LsArAPwMSHEAwAemMMhMucJyzj4sIyDD8s4+LCMgw/LOPiwjIMPyzj4sIyZ82VeG4CEEONEFAFQA6CBiH4GYDmAO4QQPXM6OGZGYBkHH5Zx8GEZBx+WcfBhGQcflnHwYRkHH5Yxc77MyzbwOkS0BcA+AG0APi2E+Ms5HhIzw7CMgw/LOPiwjIMPyzj4sIyDD8s4+LCMgw/LmDkfFoIBKAbgLgB/L4QYmevxMDMPyzj4sIyDD8s4+LCMgw/LOPiwjIMPyzj4sIyZ82HeG4AYhmEYhmEYhmEYhmGY8yM01wNgGIZhGIZhGIZhGIZhZhc2ADEMwzAMwzAMwzAMwwQcNgAxDMMwDMMwDMMwDMMEHDYAMQzDMAzDMAzDMAzDBBw2ADEMwzAMwzAMwzAMwwQcNgAxDMMwDMMwDMMwDMMEHDYAMQzDMAxz0UFEWSJ6t/N3CxF9c67HxDAMwzAMM5uQEGKux8AwDMMwDHNBIaLlAP5LCLF5rsfCMAzDMAxzIYjM9QAYhmEYhmHmgE8AWEVETwI4CGCDEGIzEb0FwKsApAGsAfCXAGIA3gQgD+AmIUQ3Ea0C8DkA9QCGALxdCPH8hf4SDMMwDMMwtnAKGMMwDMMwFyMfBHBYCHEJgA9MeW4zgNsAXA7gTwEMCSG2A3gEwO3OMV8A8B4hxGUA3g/g7y/EoBmGYRiGYaYLRwAxDMMwDMNM5qdCiAEAA0TUB+B7zuNPA9hKRBUArgLwDSJSr4lf+GEyDMMwDMPYwwYghmEYhmGYyeS1vye0/ycg104hAL1O9BDDMAzDMMyCgFPAGIZhGIa5GBkAUDmdFwoh+gEcJaLXAgBJts3k4BiGYRiGYWYaNgAxDMMwDHPRIYToAvBzInoGwKem8RZvBPBWItoHYD+AV87k+BiGYRiGYWYabgPPMAzDMAzDMAzDMAwTcDgCiGEYhmEYhmEYhmEYJuCwAYhhGIZhGIZhGIZhGCbgsAGIYRiGYRiGYRiGYRgm4LABiGEYhmEYhmEYhmEYJuCwAYhhGIZhGIZhGIZhGCbgsAGIYRiGYRiGYRiGYRgm4LABiGEYhmEYhmEYhmEYJuCwAYhhGIZhGIZhGIZhGCbg/H8CNjPRYxnfugAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1440x360 with 1 Axes>"
       ]
@@ -585,7 +593,7 @@
     }
    ],
    "source": [
-    "df1 = df.loc[df['id'] == 'pump-1']\n",
+    "df1 = df_initial.loc[df_initial['id'] == 'pump-1']\n",
     "df1 = df1.drop(columns=['id','label'])\n",
     "df1.plot(figsize=(20,5),  fontsize=12,subplots=True,  title = \"Pump 1\")\n",
     "plt.show()"
@@ -600,12 +608,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 682,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1440x360 with 1 Axes>"
       ]
@@ -617,7 +625,7 @@
     }
    ],
    "source": [
-    "df2 = df.loc[df['id'] == 'pump-2']\n",
+    "df2 = df_initial.loc[df_initial['id'] == 'pump-2']\n",
     "df2 = df2.drop(columns=['id','label'])\n",
     "df2.plot(figsize=(20,5),  fontsize=12,subplots=True,  title = \"Pump 2\")\n",
     "plt.show()"
@@ -641,12 +649,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 683,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1440x720 with 2 Axes>"
       ]
@@ -658,7 +666,7 @@
     }
    ],
    "source": [
-    "df1 = df.loc[df['id'] == 'pump-1']\n",
+    "df1 = df_initial.loc[df_initial['id'] == 'pump-1']\n",
     "df1 = df1.drop(columns=['id'])\n",
     "df1.plot(figsize=(20,10),  fontsize=12,subplots=True,  title = \"Pump 1\")\n",
     "plt.show()"
@@ -675,12 +683,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 684,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1440x720 with 2 Axes>"
       ]
@@ -692,7 +700,7 @@
     }
    ],
    "source": [
-    "df2 = df.loc[df['id'] == 'pump-2']\n",
+    "df2 = df_initial.loc[df_initial['id'] == 'pump-2']\n",
     "df2 = df2.drop(columns=['id'])\n",
     "df2.plot(figsize=(20,10),  fontsize=12,subplots=True, title = \"Pump 2\")\n",
     "plt.show()"
@@ -708,12 +716,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 685,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIQAAAJ7CAYAAACSxkrAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAAsTAAALEwEAmpwYAAC2AUlEQVR4nOzdd3zV1f3H8ffJvNkJWRAChA0CskHcVq2jtq66967aarXDDtv6q3ZvW0ddxV231lnrnqiAsodsQgIJkHsz70ju+f1x7w0BsnOTe5P7ej4ePEjuyoHkm3u+7+/nfI6x1goAAAAAAACxIy7SAwAAAAAAAEDfIhACAAAAAACIMQRCAAAAAAAAMYZACAAAAAAAIMYQCAEAAAAAAMQYAiEAAAAAAIAYQyAEAAAQQcYYa4wZE+lxAACA2EIgBABADDLGbDLGNBhjao0xO4wx840x6REe0zhjzAvGmEpjzG5jzH+NMeN78HpDjDH/McaUBUOXkn3uTzbGPGCMqTbGbDfG3LjP/UcbY1YbY+qNMW8bY0a08XVeM8b8spXbTw6+bkJ3/w0AAAC9hUAIAIDY9XVrbbqkGZJmSbo5wuPJlvQfSeMlFUr6VNILPXg9v6TXJJ3exv23SBoraYSkoyT90BhzvCQZY/IkPSvpZ5IGSVoo6Yk2XudBSecbY8w+t18g6VFrbWMP/g0AAAC9gkAIAIAYZ63dJulVSZONMSXBaprmqhZjzDvGmMuDH19sjPnQGPMXY4zTGLPBGHNw8PatxpgKY8xFLZ473xhztzHmf8aYGmPMu21V2lhrP7XW3m+t3W2t9Un6i6Txxpjcbv67dlhr75T0WRsPuUjSrdbaKmvtKkn3Sro4eN9pklZYa5+y1roVCI+mGmMmtPI6z0vKlXRY6AZjTI6kkyQ9ZIyZY4z5OPj/VW6M+YcxJqm1AbX8vw5+frEx5oMWn08I/l/uNsasMcac2eK+E40xK4P/z9uMMd/v4L8IAADEMAIhAABinDFmmKQTJX3eyafMlbRUgRDkMUn/ljRb0hhJ50v6xz7Lz86TdKukPElfSHq0k1/ncEnbrbW7Ovn4TgsGNkMkLWlx8xJJk4IfT2p5n7W2TtL6FverxX0Nkp6UdGGLm8+UtNpau0RSk6QbFPj3z5N0tKRrujHmNEn/U+D/vEDS2ZLuNMYcEHzI/ZKustZmSJos6a2ufg0AABA7CIQAAIhdzxtjnJI+kPSupF938nkbrbX/stY2KbCMapikX1prPdba1yV5FQiHQl621r5nrfVI+qmkecEQqk3GmGJJd0i6sb3H9UAosHK1uM0lKaPF/S7treX9+3pQ0jeNMY7g5xcGb5O1dpG1doG1ttFau0nSPyUd0Y0xnyRpU/D/vtFa+7mkZySdEbzfJ+kAY0xmsOppcTe+BgAAiBEEQgAAxK5TrLXZ1toR1tprgpUunbGjxccNUmB51j63tawQ2hr6wFpbK2m3pKK2XtwYky/pdUl3Wmsfb+Mxw4MNsWuNMbWdHHdLoedktrgtU1JNi/sztbeW9+/FWvuBpJ2STjHGjJY0R4FKnlCz7JeCDaarFQje8rox5hGS5gaXnjmDYd55kgYH7z9dgUqvzcGlefO68TUAAECMIBACAAAt1QX/Tm1x2+DWHtgFzdVAwaVkgySVtfbA4FKu1yX9x1r7q7Ze0Fq7xVqbHvrT1QFZa6sklUua2uLmqZJWBD9e0fK+4HKt0S3ub81DClQGnS/pvy1CsrskrZY01lqbKeknkvZtQB1Sp7b/77dKejcY4oX+pFtrrw7+mz6z1p6swHKy5xVYxgYAANAqAiEAANDMWlspaZsCu2bFG2MuVSAI6YkTjTGHBhsp3yppgbV2674PMsZkSvqvpA+ttT/q4dcMvaZDUnLw0+QWS7qkQIBzszEmJ9gs+gpJ84P3PadAk+3Tg8/5uaSl1trV7Xy5hyQdE3ydB1vcniGpWlJt8Otc3c5rfCHpNGNMqjFmjKTLWtz3kqRxxpgLjDGJwT+zjTETjTFJxpjzjDFZwYbc1QrssgYAANAqAiEAALCvKyT9QNIuBZoof9TD13tM0i8UWCo2U4EKmtacqkBz6ktaLgczxgzvwddu0J7lYauDn4f8QoFG0ZsV6KH0B2vta1JzMHa6pF9JqlKgkfbZ7X2hYH+gjySlSfpPi7u+L+lcBZab3au2t6+XAjureRVYlvegWjTgttbWSPpqcBxlkrZL+p32BF4XSNoUXJb2LQWWkwEAALTKWGsjPQYAADBAGWPmSyq11t4c6bEAAABgDyqEAAAAAAAAYgyBEAAAAAAAQIxhyRgAAAAAAECMoUIIAAAAAAAgxhAIAQAAAAAAxBgCIQAAAAAAgBhDIAQAAAAAABBjCIQAAAAAAABiDIEQAAAAAABAjCEQAgAAAAAAiDEEQgAAAAAAADGGQAgAAAAAACDGEAgBAAAAAADEGAIhAAAAAACAGEMgBAAAAAAAEGMIhAAAAAAAAGIMgRAAAAAAAECMIRACAAAAAACIMQRCAAAAAAAAMYZACAAAAAAAIMYQCAEAAAAAAMQYAiEAAAAAAIAYQyAEAAAAAAAQYwiEAAAAAAAAYgyBEAAAAAAAQIwhEAIAAAAAAIgxBEIAAAAAAAAxhkAIAAAAAAAgxhAIAQAAAAAAxBgCIQAAAAAAgBhDIAQAAAAAABBjCIQAAAAAAABiDIEQAAAAAABAjCEQAgAAAAAAiDEEQgAAAAAAADGGQAgAAAAAACDGEAgBAAAAAADEGAIhAAAAAACAGEMgBAAAAAAAEGMIhAAAAAAAAGIMgRAAAAAAAECMIRACAAAAAACIMQRCAAAAAAAAMYZACAAAAAAAIMYQCAEAAAAAAMQYAiEAAAAAAIAYQyAEAAAAAAAQYwiEAAAAAAAAYgyBEAAAAAAAQIwhEAIAAAAAAIgxBEIAAAAAAAAxhkAIAAAAAAAgxhAIAQAAAAAAxBgCIQAAAAAAgBhDIAQAAAAAABBjCIQAAAAAAABiDIEQAAAAAABAjCEQAgAAAAAAiDEEQgAAAAAAADGGQAgAAAAAACDGEAgBAAAAAADEmIRID0CS8vLybElJSaSHAQAAAAAAMGAsWrRop7U2v7X7oiIQKikp0cKFCyM9DAAAAAAAgAHDGLO5rftYMgYAAAAAABBjCIQAAAAAAABiDIEQAAAAAABAjImKHkIAAAAAAAA95fP5VFpaKrfbHemh9CmHw6Hi4mIlJiZ2+jkEQgAAAAAAYEAoLS1VRkaGSkpKZIyJ9HD6hLVWu3btUmlpqUaOHNnp57FkDAAAAAAADAhut1u5ubkxEwZJkjFGubm5Xa6KIhACAAAAAAADRiyFQSHd+TcTCCHqvL26QktLnZEeBgAAAAAAvSo9PT1iX5tACFHnlhdX6B9vrYv0MAAAAAAAGLAIhBB1dtd55WzwRXoYAAAAAAB0yY9+9CPdcccdzZ/fcsstuu2223T00UdrxowZmjJlil544YX9nvfOO+/opJNOav7829/+tubPny9JWrRokY444gjNnDlTxx13nMrLy8MyVgIhRJXGJr9q3I2qJhACAAAAAPQzZ511lp588snmz5988klddNFFeu6557R48WK9/fbb+t73vidrbadez+fz6Tvf+Y6efvppLVq0SJdeeql++tOfhmWsbDuPqFLtbpQkOesJhAAAAAAA3fd/L67QyrLqsL7mAUWZ+sXXJ7V5//Tp01VRUaGysjJVVlYqJydHgwcP1g033KD33ntPcXFx2rZtm3bs2KHBgwd3+PXWrFmj5cuX69hjj5UkNTU1aciQIWH5t/QoEDLGjJW0TNLT1trzjTFHSnpLUn2Lh11rrX2wJ18HscNZ7w383eCN8EgAAAAAAOi6M844Q08//bS2b9+us846S48++qgqKyu1aNEiJSYmqqSkZL8t4hMSEuT3+5s/D91vrdWkSZP08ccfh32cPa0QukPSZ/vcVmatLe7h6yJGhXoHuX1+uX1NciTGR3hEAAAAAID+qL1Knt501lln6YorrtDOnTv17rvv6sknn1RBQYESExP19ttva/Pmzfs9Z8SIEVq5cqU8Ho8aGhr05ptv6tBDD9X48eNVWVmpjz/+WPPmzZPP59PatWs1aVLP/23dDoSMMWdLckr6SNKYHo8E0J4KIUmqbvARCAEAAAAA+pVJkyappqZGQ4cO1ZAhQ3Teeefp61//uqZMmaJZs2ZpwoQJ+z1n2LBhOvPMMzV58mSNHDlS06dPlyQlJSXp6aef1nXXXSeXy6XGxkZ997vfjVwgZIzJlPRLSV+RdPk+dxcYY3YosGzseUk3W2vrejJIxI6WvYNcDT4VZDoiOBoAAAAAALpu2bJlzR/n5eW1ueSrtra2+ePf//73+v3vf7/fY6ZNm6b33nsv7GPs7i5jt0q631pbus/tqyVNkzREgbBopqQ/t/YCxpgrjTELjTELKysruzkMDDQtAyG2ngcAAAAAoHd0ORAyxkyTdIykv+x7n7V2u7V2pbXWb63dKOmHkk5v7XWstfdYa2dZa2fl5+d3dRgYoFqGQOw0BgAAAABA7+jOkrEjJZVI2mKMkaR0SfHGmAOstTP2eaxV96uQEINcLXoIuagQAgAAAACgV3QnrLlH0mgFloZNk3S3pJclHWeMOcoYM8IEDJP0W0kvhGmsiAFV9T7lpCZK2rvBNAAAAAAAnWGtjfQQ+lx3/s1dDoSstfXBpWHbrbXbJdVKcltrKyVNV2DXsbrg38skXdflUSFmORt8GjYoVcZQIQQAAAAA6BqHw6Fdu3bFVChkrdWuXbvkcHRtU6Zubzvf4gvf0uLjP6uNJtJAZ7jqvcpJTVJWSiKBEAAAAACgS4qLi1VaWqpY27zK4XCouLi4S8/pcSAEhJOzwaeSvDRlpSTSVBoAAAAA0CWJiYkaOXJkpIfRL9DwGVHFWe9TTmqSsqkQAgAAAACg1xAIIWo0+a2q3T5lpSQqMyVxry3oAQAAAABA+BAIIWpUN/hkrZSdmqjs1KS9tqAHAAAAAADhQyCEqBGqCMpOTWTJGAAAAAAAvYhACFHDGawIyk7Zs8uY3x87WwUCAAAAANBXCIQQNUIVQlmpicpOTZTfSrXexgiPCgAAAACAgYdACFHDFdxmPic1SZkpiXvdBgAAAAAAwodACFGjqnnJWKCHkBTYhh4AAAAAAIQXgRCiRij8yUwJ7DImicbSAAAAAAD0AgIhRA1Xg0+ZjgTFxxllhSqEGth6HgAAAACAcCMQQtRw1nubK4OyU1kyBgAAAABAbyEQQtRwNviUEwyCQhVCLBkDAAAAACD8CIQQNarqfcoKVgg5EuOVnBBHIAQAAAAAQC8gEELUcNV7m3cXkwLLxth2HgAAAACA8CMQQtRwNviaewdJgWVjNJUGAAAAACD8CIQQFfx+K1eDb+8KoZQkmkoDAAAAANALehQIGWPGGmPcxphHWtx2rjFmszGmzhjzvDFmUM+HiYGuxt0oa9W8y5gkZaUm0kMIAAAAAIBe0NMKoTskfRb6xBgzSdI/JV0gqVBSvaQ7e/g1EAOq6gNLw/ZdMkYgBAAAAABA+CV094nGmLMlOSV9JGlM8ObzJL1orX0v+JifSVpljMmw1tb0cKwYwJzB4KdlIJRNIAQAAAAAQK/oVoWQMSZT0i8l3bjPXZMkLQl9Yq1dL8kraVwrr3GlMWahMWZhZWVld4aBAcQZrBDKSmmxZCwlUfXeJnkamyI1LAAAAAAABqTuLhm7VdL91trSfW5Pl+Ta5zaXpIx9X8Bae4+1dpa1dlZ+fn43h4GBwtVahVDwY6qEAAAAAAAIry4vGTPGTJN0jKTprdxdKylzn9syJbFcDO0K7SaWs1dT6cDH1Q0+FWQ4IjIuAAAAAAAGou70EDpSUomkLcYYKVAVFG+MOUDSa5Kmhh5ojBklKVnS2p4OFANbqKl0pmPPj2RWcAt6tp4HAAAAACC8uhMI3SPp3y0+/74CAdHVkgokfWyMOUzSYgX6DD1LQ2l0xFnvU4YjQQnxe1YxZhMIAQAAAADQK7ocCFlr6xXYTl6SZIypleS21lZKqjTGfEvSo5JyJb0h6ZIwjRUDmKvBt1f/IGlPhRA9hAAAAAAACK9ubzsfYq29ZZ/PH5P0WE9fF7HFWe9VdosdxqQ9TaWdBEIAAAAAAIRVd3cZA8LK2UqFUIYjUcZQIQQAAAAAQLgRCCEqOOt9yk7du0IoPs4oIzlBrmDDaQAAAAAAEB4EQogKgSVjifvdnp2axJIxAAAAAADCjEAIEef321abSkuBPkIsGQMAAAAAILwIhBBxNZ5G+e2eXcVaykpJZNt5AAAAAADCjEAIEecKBj45+/QQkgKBUDUVQgAAAAAAhBWBECKuKtg0urUlY1kpifQQAgAAAAAgzAiEEHGhwKe9HkLW2r4eFgAAAAAAAxaBECLOGawQykrZf8lYdkqSmvxWtZ7Gvh4WAAAAAAADFoEQIs7VToVQqNE0jaUBAAAAAAgfAiFEXCjsyW5tl7FgSMTW8wAAAAAAhA+BECKuqt6rjOQEJcTv/+MYqhAiEAIAAAAAIHwIhBBxrnpfcyXQvkLLyFgyBgAAAABA+BAIIeKcDb5W+wdJgabSEhVCAAAAAACEE4EQIs5Z720OfvbV3FS6wduXQwIAAAAAYEAjEELEtVch5EiMU1JCnFwsGQMAAAAAIGy6FQgZYx4xxpQbY6qNMWuNMZcHby8xxlhjTG2LPz8L75Ax0Djr2w6EjDHKTklkyRgAAAAAAGGU0M3n/UbSZdZajzFmgqR3jDGfS9oVvD/bWtsYlhFiQPP7bbtLxqTAsjGaSgMAAAAAED7dqhCy1q6w1npCnwb/jA7bqBAzar2N8lu1WSEkBe6jQggAAAAAgPDpdg8hY8ydxph6SasllUt6pcXdm40xpcaYfxlj8no6SAxcod5AoebRrclKSZSTQAgAAAAAgLDpdiBkrb1GUoakwyQ9K8kjaaek2ZJGSJoZvP/R1p5vjLnSGLPQGLOwsrKyu8NAPxdaCpaT2t6SsSS56tllDAAAAACAcOnRLmPW2iZr7QeSiiVdba2ttdYutNY2Wmt3SPq2pK8aYzJaee491tpZ1tpZ+fn5PRkG+rGqYNDDkjEAAAAAAPpOuLadT1DrPYRsmL8OBpjQUrD2AqGslETVeZvkbfT31bAAAAAAABjQuhzUGGMKjDFnG2PSjTHxxpjjJJ0j6U1jzFxjzHhjTJwxJlfS7ZLesda6wj1wDAyhpWBZ7ewyFgqLqBICAAAAACA8ulO5YyVdLalUUpWkP0r6rrX2P5JGSXpNUo2k5Qr0FTonPEPFQOTsZFNpiUAIAAAAAIBwSejqE6y1lZKOaOO+xyU93tNBIXY4G3xKT05QUkLb2eSeQIjG0gAAAAAAhAO9fRBRVfXedquDJCk7uAMZFUIAAAAAAIQHgRAiylXva7ehtLSnQii0vAwAAAAAAPQMgRAiytnQcSCUTSAEAAAAAEBYEQghopz1XmW3s8OYJGXSVBoAAAAAgLAiEEJEuTpRIRQfZ5ThSCAQAgAAAAAgTAiEEDHWWjk70UNIkrJTEwmEAAAAAAAIEwIhREytp1GNftvhkjEp0FjaWc+28wAAAAAAhAOBECIm1CQ6qzMVQilJclIhBAAAAABAWBAIIWJCS8BCu4i1J4slYwAAAAAAhA2BECImVCGUk9a5JWMutp0HAAAAACAsCIQQMVXBnkCdqRDKTkmUs8Ena21vDwsAAAAAgAGPQAgRE+oJ1JkeQlkpiWryW9V5m3p7WAAAAAAADHgEQogYV7BCKKszFULB0IidxgAAAAAA6DkCIUSMs96n1KR4JSfEd/jYrODW9DSWBgAAAACg5wiEEDHOBp9yUjtuKC3tqSKisTQAAAAAAD1HIISIcdZ7O7VcTGqxZIwKIQAAAAAAeqxbgZAx5hFjTLkxptoYs9YYc3mL+442xqw2xtQbY942xowI33AxkDjrfc1BT0eaK4QIhAAAAAAA6LHuVgj9RlKJtTZT0jck3WaMmWmMyZP0rKSfSRokaaGkJ8IyUgw4zobOB0J7mkoTCAH7enFJmZZsdUZ6GAAAAAD6kW4FQtbaFdZaT+jT4J/Rkk6TtMJa+5S11i3pFklTjTETwjFYDCzOel9zs+iOpCTGKyk+jgohoBU/e2G57nl/Q6SHAQAAAKAf6XYPIWPMncaYekmrJZVLekXSJElLQo+x1tZJWh+8HWhmrZWrwaucTlYIGWOUmZIoVwPbzgMt1Xsb5az3qaLaHemhAAAAAOhHuh0IWWuvkZQh6TAFlol5JKVLcu3zUFfwcXsxxlxpjFlojFlYWVnZ3WGgn6rzNsnXZDu9ZEwKLBtjyRiwtzJnIAjaUe3p4JEAAAAAsEePdhmz1jZZaz+QVCzpakm1kjL3eVimpJpWnnuPtXaWtXZWfn5+T4aBfshZH6j0ye7kkrHAYxNZMgbso8zZIEnaUe2WtTbCowEAAADQX4Rr2/kEBXoIrZA0NXSjMSatxe1As1ClT1YXKoSyUqgQAvZV7goEQp5Gv6obGiM8GgAAAAD9RZcDIWNMgTHmbGNMujEm3hhznKRzJL0p6TlJk40xpxtjHJJ+LmmptXZ1eIeN/i5U6ZOd0oVAKJUKIWBfoSVjklRRQx8hAAAAAJ3TnQohq8DysFJJVZL+KOm71tr/WGsrJZ0u6VfB++ZKOjtMY8UAEqr0yUnr/JKxLJaMAfsJLRmT6CMEAAAAoPMSuvqEYOhzRDv3vyGJbebRrqrmHkJdaCqdkqRaT6N8TX4lxodrtSPQv5W73MpJTVRVvU872GkMAAAAQCdxVo2ICFX6ZHYlEAr2G6qmSghoVuZq0LRh2ZKkHSwZAwAAANBJBEKICGe9VymJ8XIkxnf6OVnB8MhJIARIkqy1KnM2aHR+ujIcCapgyRgAAACATiIQQkQ4633NFT+dFdqRjJ3GgABnvU9un19DslNUmOlgyRgAAACATiMQQkQ4G3zKTu18Q2lpT4UQS8aAgG3BhtJFWQ4VZiYTCAEAAADoNAIhRISz3tulhtLSngbUzgZvbwwJ6HfKXYEAqCg7RYUZDnYZAwAAANBpBEKIiO4sGQtVFLlYMgZIkspdgQqhIdkOFWQ6VFHjlrU2wqMCAAAA0B8QCCEiAkvGuhYIZToSmp8LILBkLCk+TnlpySrMTJavyaqKwBQAACCiXlu+naX86BcIhNDnrLVy1fuUldK1HkIJ8XHKSE6gqTQQVO50a3CWQ3FxRoWZDkli8gEAABBB9d5GXf3oIj340aZIDwXoEIEQ+lyDr0neJr9yulghJEmZKYk0lQaCyl0NGpIVCIIKM5MlEQgBnbF1d71q3LyXAADCb7vLLWul0qqGSA8F6BCBEPpcqMKnq0vGQs9hyRgQUOZ0a2h2iiSpICMQDFXQWBro0Ol3faS/vvFlpIcBABiAQpt+lDkJhBD9CITQ56rqA7uEdXXJmBQIhFwEQoCa/Fbbq90akh0IggqoEAI6pdbTqIoaj9buqIn0UAAAA1AoENpGIIR+gEAIfc7VgwqhrJREOevZdh6orPGoyW81JCtQIZScEK+c1ETtqCEQAtpTHpygb95VH+GRAAAGou3BXWB3VLvla/JHeDRA+wiE0OdCS766FwglUSEEaM9Vp9CSMUkqzHRoB0vGgHaVtbhy28hEHQAQZqH3Gb8N9BMCohmBEPpcqIdQTmr3l4xZa8M9LKBfKQ9efQotGZOkgkyHKlgyBrQrVCHU5Lcqc3K8AADCq2UIRB8hRDsCIfQ5Z0Ooh1D3loz5mqzqvU3hHhbQr5QHT2RDS8YkqTAjmQohoANlLSbqm3fXRXAkAICBqNzl1qi8NElSmYtACNGNQAh9zlnvkyMxTo7E+C4/NzsYIrHTGGLdNmeD0pMTlOlIaL6tMNOhytpAbyEArSt3NigpPjD9oY8QACDcyl0NmjEiR5K0ja3nEeUIhNDnnPVeZXdjhzFpT1VRqDE1EKvKXQ0akuWQMab5toLMZDX5rXbVUSUEtKXc5daEIRlKSojT1t0EQgCA8GnwNslZ79PIvDTlpSdpG0uTEeW6HAgZY5KNMfcbYzYbY2qMMV8YY04I3ldijLHGmNoWf34W/mGjP3PW+7rVUFqSslJDFULsNIbYVu5ya0iLhtKSVJAR6CdUwbIxoE1lrgYNzU7RsJwUKoQAAGG1PdjLcXCmQ0XZKWw9j6iX0PFDWn3OVklHSNoi6URJTxpjprR4TLa1tjEM48MA5GzofiAUqiyqZskYYlyZs0GTijL3uq0wM1lSYJvTyUOzIjEsIKpZa1XudOvIcQXyNPq1mQohAEAYtdz0Y2h2ir6sqI3wiID2dblCyFpbZ629xVq7yVrrt9a+JGmjpJnhHx4GIle9r/tLxkIVQiwZQwxz+5q0s9a7V0NpKdBDSBKNpYE2uBp8avA1qSjboeGDUrVlVx27VgIAwqblph9F2SnaVtXA+wyiWo97CBljCiWNk7Sixc2bjTGlxph/GWPyevo1MLBU1Xt7UCFEU2kgtJ3pkCzHXrfnZwQqhCpqWK8OtKasxUR9+KBU1XmbtKuOJcgAgPBouWRsaHaKGnxNXMhGVOtRIGSMSZT0qKQHrbWrJe2UNFvSCAUqhjKC97f23CuNMQuNMQsrKyt7Mgz0I9ZaORt8zZU+XZWaFK+EOCMXgRBiWGgL06H79BBKjI9TXnoSFUJAG1qW8o/ITZUkbWHZGAAgTMpdDcpJTVRKUryKgvM0+gghmnU7EDLGxEl6WJJX0rclyVpba61daK1ttNbuCN7+VWNMxr7Pt9beY62dZa2dlZ+f391hoJ9x+/zyNvq7vWTMGKPs1ESSdsS05nLkfQIhKdBYuqKaCiGgNeXB6rqirJQ9gRCNpQEAYVLudGtwcEl/cQ6BEKJfd5pKywT2Ob5fUqGkE621bZ2dhxZMsr09JO3ZHay7S8akwNbzNJVGLCsLTiz2XTImBRpL72DJGNCqcleDEuKM8jOSm9+H2GkMABAu5S538/ysuUKoikAI0au7Qc1dkiZK+rq1tvkn3Bgz1xgz3hgTZ4zJlXS7pHesta4wjBUDQKiyJ6eHgRDbziOWlbncyk1LkiMxfr/7CjMdLBkD2lDudKsw06H4OCNHYrwGZzq0eXddpIcFABggtlfvCYRyUhPlSIxrvpAHRKMuB0LGmBGSrpI0TdJ2Y0xt8M95kkZJek1SjaTlkjySzgnfcNHfVdUHgpysbi4Zk6Ts1CSWjCGmlbsaNCR7/+ogSSrIdGhnrUeNTf4+HhUQ/cpcDXtV1g3PTWXJGAAgLNy+Ju2u8za/zxhjNDQ7hSVjiGpdXjJmrd0sybTzkMe7PxwMdK5gkNOTJWPZKYlau6MmXEMC+p0yZ4NG5Ka1el9hZrKslXbWejW4lSVlQCwrd7l1YHF28+cjBqXq3bVsbAEA6LnQLrChHkJSYNkYFUKIZvT2QZ8KbRffk0AoMyWxOVgCYlG5073fDmMhhRmBEGgHjaWBvVhrVe5yq6hFUDoiN1UVNR41eJsiODIAwEAQ2rigZSVqcQ4VQohuBELoU6GlXt3dZUwKhEk1nkaWxCAmVbt9qvE0ttpQWgr0EJIIhIB97arzytvo32fJWKDSjq3ngfa56n3yMe8C2rW9ev9NP4qyUrSz1iu3jwsPiE4EQuhTzgavkhPilJK0fzPczspKCVQXVbsbwzUsoN8IbTlf1FaFUGayJGlHDY2lgZZCx86QFsfO8EGBrec376KxNNAWv9/qmL+8q7veWR/poQBRrcwZWjK2JxAaGtx6PlQ9BEQbAiH0KWedr0fLxaQ9y82c9ew0hthT5gpcfSpqo6l0bnqy4oxUQYUQsJfmY6dFb4cRwUCICiGgbeXVblXWeLRkqzPSQwGi2naXW1kpiUpN2tOml63nEe0IhNCnnA3eHi0Xk/YsN3M10EcIsae5yiGr9Qqh+Dij/IxklowB+ygP9nBouUNfdmqiMhwJBEJAO9ZX1Ab+rqyN8EiA6Fbucu+3pD/U85HG0ohWBELoU856n7J6WCGUGVwy5iQQQgwqczYoPs6oICO5zccUZjq0o5olY0BL5S63khLilJu256KEMUYjclO1ma3ngTZtCAZBW3bX0wcFaEe5q2G/QGhwlkNxRiolEEKUIhBCn3I1+JSdEp4lY+w0hlhU5mpQYUayEuLb/vVdkOGgQgjYR1nwyq0xZq/bhw9KpUIIaMf6ykCPLb8V4SnQju0u915bzktSYnycCjMdVAghahEIoU85633KSe3ZkrFQU2mWjCEWlTkb9mqK25rCzGRV0FQa2Eu5c/8rt5I0fFCaSqvq1eS3ERgVEP027KxVWnAzkHUVLBsDWuP2NWlXnVdFrbzPFGWn0EMIUYtACH2qqt7b46bSoUDISYUQYlC5y93mDmMhhZkO7a7zytNIaT8QUu5y79VQOmREbqp8TVblLibrQGs2VNbp8HH5kugjBLQlVJk9uJVAaGh2SvPGBkC0IRBCn3H7muRp9Pe4h1BifJzSkxOoEELM8ftt8KS29R3GQkJbz1dSJQRIkpr8Vtur3Xs1lA5p3mmMpTDAfuo8jSp3uTWpKFNDs1OoEALaENpWvrVNP4qyU1TudMtPJSqiEIEQ+kyooqenu4xJgSohZwPbziO27Krzytvob3XZS0sFmYH7aSwNBFTWeNTkt61O1IfnBgKhzfQRAvazcWegf9Co/HSNKUinQghow/ZQINTKhYeh2Q55m/zaWcu8DNGHQAh9JhTg9HTJmBQIhGgqjVgTWtLS4ZKxjMBkpILG0oAkNZfqF7UyUR+SlaLEeEOzXKAVoQBodH66RucHAiGqHID9hSqEBme2EgjlBOZt7DSGaEQghD7TXCEUhkAoOzWRJWOIOWXOwGSj4x5CgSVj7DQGBJQ72y7lj48zKs5J1ZbddX09LCDqra+skzGBXltjCtLl9vnphQK0otzVoExHgtKSE/a7LzRvY6cxRCMCIfQZZ32wQihsS8YIhBBbQhOJjpaM5aQmKTHeaAc9hABJLarrWgmEJLaeB9qyobJWxTkpciTGa3R+miR2GgNaU+5yt3rRQQo0lZbETmOISgRC6DPhrhBilzHEmnJXg5IT4jQorf1QNS7OqCDDQYUQEFTmdCs1KV6ZKftfuZUC1Q+bd9XLWpbCAC1tqKzT6Px0SdKYgsDf6yuppgP2td3V+sYFkpThSFSGI4EKIUQlAiH0mVBFTzgCocyURFU3+Ji8I6aUBbecN8Z0+NiCzGRV0FQakBQIU4dkOdo8doYPSlWNu5ELDUALfr/Vhp21GpUXCIIGpSUpOzWRCiGgFaH3mbYMzU7RNgIhRKEuB0LGmGRjzP3GmM3GmBpjzBfGmBNa3H+0MWa1MabeGPO2MWZEeIeM/spZ71NSfJxSEuN7/FrZKUnyNvnV4GsKw8iA/qHM2f5ko6XCDIcqaqgQAqQ9YWpbhg9ipzFgX+XVbrl9fo0uCCwVM8ZoTD47jQH78jQ2aWetV4Mz236fCQRCzMsQfbpTIZQgaaukIyRlSbpZ0pPGmBJjTJ6kZyX9TNIgSQslPRGmsaKfczV4lZ2a2Knqho6EqoxoLI1YUu5s/6S2pYLMZLadB4LKOwhTR+QGTng372IpDBCyPlgJFKoQkgK7ja2nQgjYS6giu60lY1JgpzGWjCEadTkQstbWWWtvsdZustb6rbUvSdooaaak0yStsNY+Za11S7pF0lRjzISwjhr9UlWdLyzLxaRAU2lJlPcjZvia/KqocauosxVCmQ65GnxyU0WHGOdt9Kuy1tNms09pT4XQViqEgGYbmrecT2u+bUxBunbVeVVV543UsICo05lNP4qyU+Rq8KnW09hXwwI6pcc9hIwxhZLGSVohaZKkJaH7rLV1ktYHb0eMczZ4w7LDmCRlEwghxuyodstvpSGdrRDKCGw9Tx8hxLod1W5ZKxW1c+U2JSleBRnJ2ryLQAgI2bCzThnJCcoPvp9Ial4+xrIxYI/twU08OuohJLH1PKJPjwIhY0yipEclPWitXS0pXZJrn4e5JGW08twrjTELjTELKysrezIM9BPOep+ywlQhlJnCkjHElnJXYLLR2SVjhZmBSckO+gghxoWOnfYqhKTgTmNUCAHN1lfWalR+2l5L/cfkZzTfByAg9D4zuJ33mSK2nkeU6nYgZIyJk/SwJK+kbwdvrpWUuc9DMyXV7Pt8a+091tpZ1tpZ+fn53R0G+hFXg6+5sqen9vQQomQZsSF0RakrS8YksfU8Yl65K3jstFMhJEnDBqVqCxVCQLMNlXUalZ++121Dc1KUlBDHTmNAC9tdbmU4EpSenNDmY4pzgoEQFUKIMm3/1LbDBC4V3C+pUNKJ1tpQmcYKSRe1eFyapNHB2zEAvfDFNt3x9jrlpSerJC9NI3PTNDIvTSV5aRo+KFVJCXsyR2e9TzlpYVoylhp4HSqEECvKgjtTdHbJWGFmoMSfxtKIdc3HTkcVQoPS9Gz1Nrl9TXKEYTdMoD+r8zSq3OXeq3+QJMXHGY3KS9P6ShqwAyGd2QU2Pz1ZifGGQAhRp1uBkKS7JE2UdIy1tuVP9XOS/mCMOV3Sy5J+LmlpcDkZBhC/3+qvb6zV7W+t08QhmWrwNenVZeWqatHTJ85IxTmpKslLU0luqhp8Tc3NoHsqLSle8XGGHkKIGeWuBmV2cPWppayURCUlxKmCCiHEuNCxk9bBsTMiN9BYurSqXmMK9lvpDsSUjTsDgc++FUKSNLogXctK9+0QAcSu7dXuDi86xMUZDc5y0EMIUafLgZAxZoSkqyR5JG1vsa74Kmvto8Ew6B+SHpH0iaSzwzRWRAm3r0nfe2qJXl5arjNnFeu2U6Y0VwI5673auLNOG3fWadPOOm3YWadNu+q0eHOVJGlUXlp7L91pxhhlpyTKSYUQYkSZs6HT/YOkwDFSmJnMkjHEvDKnu1PHzvBgILR5F4EQEOoRNCp//3nbmPx0vbKsnGo6IKjc5dYBQ/btmrK/odkp9BBC1OlyIGSt3SzJtHP/G5LYZn6Aqqh264qHF2lpqVM/OXGCrjhs1F7NBrNTkzR9eJKmD8/Z63nWWtV6GpXhCE+FkBSogGDJGGJFZ09qWyrMcLBkDDGv3NVxKb+0Z+t5dhqLnKo6r8pcDZpUlBXpocS8DZV1MkYqyd0/EBpdkC5rA1VEEztxEgwMZN5Gv3bWejS4E+8zRdkpWrB+Vx+MCui87i4ZQwxaUebS5Q8ulLPep3+eP1NfnTS40881xoQ1DJKkrNREuVgyhhhR7mrQ9OHZXXpOYaZDq7ZX986AgH6i3OXW1GHZHT4uNy1JaUnx2sJOY31uR7Vb972/QY9+skX13iadOn2obj1lcqeXyCL81lfWqjgnpdUKoDHBZWTrK2sJhBDzdlS7ZW37W86HFGenaHu1W74mvxLje7TZNxA2vNOiU/63coeu//fnykpJ1FPfmqfJQyN/9S47JVGVtVQ/YOBr8Dapqt7X5QqhgsxkvbuWYwSxy+1r0u46b6d25zPGaHhumjbvolluX9myq153v7deTy8sVZO1+sbUIg3Jcujud9dr8ZYq/f2c6TqwODvSw4xJGyrrNCpv//5BkoJb0YudxgAF+gdJHW9cIAUqhPw2ECIV56T29tCwj0837tZf/rdWm3fV6crDR+ncuSP22gApVhEIoV3WWt33/kb9+tVVOnBolu69cJYKMju37XVvy0pJ1KryGjU2+ZVAyo5e8tmm3Rqc6dCwQZF74y7r5LbZ+yrMdKjW06haTyNX2sPEWqt/fbhJ5a4G/eC4CUwkoly5q/MTdUkaMShVX1bU9OaQIGntjhrd9c56/WdJmeKN0TdnFetbh49u7uN01IQCXf/45zrtzo/0w+PH6/JDRykurs1uBQgzv99q4846HTQqt9X7HYnxKs5JYacxQGpuEt2ZCqGhoa3nqxoIhPrQos1V+usba/X+lzsDO2PnpuqWF1fqXx9t0g+OG6+vTRmyVwuUWMMZAtrkbfTr5y8s178/26oTpwzWn86YppSk6GkeeNCoXD3/RZkufXCh/nHudGWGeUkaYltljUe/fGmlXlxSppzURM2/ZE6nlp30hvJObpu9r9DW8xXVbqW3slMMusbT2KQfP7NMz36+TZK0qrxGd50/I+zLYRE+5aGJeifD1BG5qXprTYX8fksA0QuWljp1x9vr9N8VO5SSGK9LDi7RFYePUuE+F5pmlwzSK9cfppueWapfv7JaH6zbpT+dMVX5GckRGnlsKa92q8HX1GpD6ZDR+elUCEVQY5Nfi7c49eaqHSqtatC80bk6akKBhnaxkhg9tz144aGzPYSkPRf60LuWbHXqL2+s1TtrKpWblqSfnjhR5x80Qo7EOL2ztlK/fWW1vv3Y57p32Eb95IQJmttGCD7QEQihVTtrPfrOY5/r4w279J2vjNENx4yLusnx2XOGS5Jufn65TrvzI91/0SyNaKX5IdAV1lo9tbBUv3pllRq8Tbr6yNF6aWmZzr13ge69cJYOHpPX52MKXX0q6moglBGYnOyo9rS6dTA6b2etR1c9vEiLNlfpxmPHaUiWQz96dpnO+ucCzb9kdtRUTmJvZcGJemePnWGDUuVt9Gt7ddebuKNtn2+p0p//F7g6m+lI0HVHj9UlB5coJy2pzedkpybp7vNn6tFPtujWl1bqhL+9pz+fOU2Hj8vvw5HHpg3BHcZGt/O+MSY/XR+v30V42oeq3T69t7ZSb66q0NtrKuSs9ykx3ig3LVkvLyuXJE0YnKEjxxfoKxMKNGN4NhX0faDc5VZGckKnLg6FAjt2Gutdy7e59Nc31uqNVRXKTk3UTcdP0IXzRiitRbX8UeMLdPjYfD2zuFR/fn2tzrpngY6ZWKCbjp+gsYWxtdMogRCaNfmt3v+yUk8tLNX/Vu6QJP3lrKk6dXpxhEfWtrPnDNeI3DRd/eginXzHh7r7/JltljgDHdlQWaufPLdMCzbs1pySQfr1aZM1piBDFx9cogvu/0QX/+sz/f3c6TquCw3Vw6HM1SBjpMKsrl0dD4UUFTVsPd8Tq8qrdfmDC7WrzqM7z5uhE6cMkSTlZyTrmkcX69Q7P9KDl87RmAJCt2gTqhDqzJVbKVAhJAV2GiMQ6rk6T6P++Poazf9ok3LTkvSjEybovLnDO11VZ4zR+QeN0OySQfrO44t14QOf6qrDR+l7Xx3Pcs1etL4iFAi1UyFUkC5Po1/bnA0RXVI90G3eVac3VlXordU79MmG3Wr0W+WkJuor4wt09MRCHT4uT+nJCVpfWau3VlfordUVuu/9Dbr73fXKSknU4ePy9ZUJ+TpiXIEGtRPAovu2u9ydfo9xJMYrNy1J25zMy3rDqvJq/fWNtfrvih3KdCTo+18dp4sOLmnzPSc+zujMWcP09QOL9MCHG3X3O+t13F/f01mzh+m7x4zbr3p1oCIQgjbtrNNTi7bqmUXbtL3arZzURJ1/0AidO3eYxhREf0I6b3Sunr/mEF324Gc6/75P9KtTJ+us2cMjPSz0I95Gv+55b71uf2udkhPi9JvTpuisWcOar3oWZjr05FXzdMn8z3T1I4v029MP1JmzhvXZ+MqdbuWlJys5oWtLNkNLxnZUM/HorjeCDfXTHQl68qp5ezW4PXJ8gZ64cp4umf+pvnl3oEpx5ohBkRss9lPmcis3LanVnZJaM2JQ4AR46+56zRvNxYWeeG9tpX787DJtczboonkj9IPjJ3S7l9n4wRl64dpDddvLK/XP9zZowYZduv2c6VQF95INO+uUnpzQ7hK9UAC+rrKWQCjMfE1+zf9wk55YuLV5Wd6YgnRddthIHTOxUDOG5yh+n6qsMQUZGlOQoSsPH61qt08ffLlTb62u0DtrKvTikjIZI80YnqOfnXSApkVo+ftAVe5q6HQgJAX6CIUqvxHQ5LfaVedRRbVHlTWBPxU1blUEP/Y0+tXkt/Jbqya/3ftjG+h75mvya/X2GmUkJ+i7x4zVpYeO7HQ7kZSkeF171BidM2e4/v7Wl3pkwWY9/3mZrjhspK48YvSA78M5sP91aFO9t1GvLNuuJxdu1acbdyvOSEeMy9cvvn6Ajp5Y2O+uvJXkpem5aw/Rtx/7XDc9s0xrd9TqJydO3O8NE9jX4i1V+vEzy7RmR42+NmWIfvH1A1pd/pOdmqRHLpurbz2ySD98eqmqG3y6/LBRfTLGMldDp3ZJ2ld6coJSk+K1o5qdxrrKWqt739+g37y6WpOLAg31W5vwTSnO0rNXH6KL/vWpzr33E91+Tt9XkKFt5a6GTvcPkgKN2xPijDbvplludznrvbrt5VV6elGpRuWn6alvzdPskp4HpSlJ8frVqVN06Jg83fTMUp3wt/d18OhcTR6apclFWZpSnKWCjOSYbgwaLhsq6zQ6P63d/8vQcrL1FbU6anxBXw1twFtW6tJNzyzVyvJqzRk5SD8/6QAdPbGgS+FnpiNRJ04ZohOnDJHfb7Vsm0tvra7QUwu36oy7P9JPT5yoiw4u4VgJk3KXWxMGZ3b68UVZKVpXOTD7b/ma/FpdXqMaj091nibVewMbm9R5GlXnaQr87Q18XOP2qbI2EALtqvOqyW/3e71MRyCYTkmKV7wxioszzX8nxMUpOSF0W6Da56uTBuvSQ0qUndq9arhBaUn6xdcn6eKDS/SH/67R7W+t06Fj8zVn5MC+2EcgFGOWb3PpkQWb9dLSctV6GjUyL00/PH68Tpte3KV0OxplOhL1wEWzdNvLq3T/Bxu1obJWt58znYavaFWtp1F/eG21HlqwWYMzHbrvwlk65oDCdp+Tlpyg+y6apRue+EK3vbxKznqfvvfVcb0+qSpzNmhcN9YzG2NUmOmgQqiLvI1+/fS5ZXpqUam+NmWI/njG1HYb6g/PTdXT35qnyx5cqKsfWaT/O3myLjhoRB+OGG0pd7qbd67qjIT4OA3NSdHmXfW9OKqB69Vl5frZCytUVe/VtUeN1ne+MrbT1VmddcKUITpwWLb++r+1+nyrU2+urpANnkfkpSdrytDMQEgU/FOU5eDEt4vWV9Z2uPx+UFqSBqUlaf0APbHtaw3eJv3ljbW67/0Nyk1P1t3nz9Dxk4f0+HXj4oymDsvW1GHZuuSQEn3vySW65cWV+mxTlX57+hTmyD3ka/KrstbT5Qqh976slLV2QP1uKq2q19WPLNayba42H5OSGK+05ASlJccrPTlBeenJmjg4UwWZySrIcKggI7n54/yM5LC/f3TWiNw0/ePcGbrx2NqY6MFJIBQjKqrd+t1ra/TM4lKlJsXra1OG6MzZwzRrRM6A+mWUEB+nW74xSWML0/WLF1bo9Ls+0n0Xzu7SCQEGvuXbXLryoYUqr3bronkl+v5x4ztdDpqcEK+/nzNDmY5l+sfb6+Rs8OqX35jca001rbUqd7l1xLjuXYEtyEhWBRVCnbar1qOrH1msTzft1vVHj9X1R4/t1Pc2Nz1Zj19xkL7z+GL97Pnl2u5q0Pe/On5A/X7tj8pcDTpoVNeu7A0flKotuwmEuqKixq1fvLBCry7frklFmXrw0tmaVJTVa19vaHaK/nDGVEmBPkWryqu1fJtLy7ZVa0WZS+99ubP5avOgtCR9/cAh+vZXxrJLWSfUextV7nJrVF7HFSmj89PYaSwMPvhyp37y3DJt2V2vc+YM049OmKislPAHNdmpSbr3wlm65/0N+sN/12hFmUt3njdTBxR1vroFe9tR7Za1ndtyPqQoO0X13iY5633tNtbvT95dW6nr//25mpqsfnPaFJXkpiktORj+JAUCoNSkhH63ciMWwiCJQGjA8zQ26YEPNukfb30pX5PVt44YrWuPGj3grwicN3eERuam6epHF+uUOwPNpgd6uR86563VO/Ttxz5XTmqSnrn6YM0YntPl14iPM/rNaVOUlZqof767Qa6GRv3pjKm9stTS1eBTvbdJRV1Y9tJSYaZDS0qd4R3UALV2R40ue/Az7aj26PZzpusbU4u69PyUpHjdff5M/eyFFbrj7fUqd7n1u9MPVCK7vEREradRNe5GDelic+jhg1L10tLyXhrVwGKt1dOLSnXrSyvlbvTrpuMn6PLDRvbpz3xacoJmlQzSrBbL0hq8TVq9PRASLdxcpUc+2aKnFpXq0kNG6sojRnW6r0Qs2lAZWC45uhNN8scUpOu/K3b09pAGLGe9V796eZWeWlSqkXlpevyKg3q9d1lcnNG3jhitGcNz9J3HA3PkX35jks6aPYwLGN0Q2nK+K+8zQ4PzuW3Ohn4fCPn9Vn9/a53++uZajS/M0F3nz9TIToTJiC4EQgOUtVZvrqrQbS+v1KZd9TpmYqFu/tpElcTQQXrwmDw9f+0humz+ZzrvvgW6/uix+tYRo9mCM4Y9/PEm/eI/KzSpKEv3XzxLBRndXyZpjNGPT5io7JQk/e611apx+3TXeTPbXVrUHWXBnSi6u+NRYWZy8ArWwCpNDrcXl5TpR88sVWpygp648iBN70ZQKAWqFH996mQNyXLoz/9bq8oaj+44bwYnoBEQ2mGsK1dupcBOY64Gn1z1PmWl8n1rTZPfNu9m9MnGwK6Mvzl9SrvblPellKR4TR+eo+nDc3TBvBJ995hx+vP/1uofb6/TI59s1jVHjtaF80oithwhmoWWgI1qZ4exkNH56dpdt1W767zsYNUF1lq9vKxct/xnharqfbrmyNG67ujwL69sz5yRg/TydYfpu//+Qj96dpk+3bhbt506WalJnBp2RXkoEOrKkrHswKqFbc4GTR7ae5WUvc1Z79UNT3yht9dU6tTpQ/Urfn76Lb5rA9C6ihr934sr9f6XOzWmIF0PXTpHh4/Lj/SwImJkXpqeu+YQ3fzCcv3x9bV6feUO/fGMqd3qx4L+y++3+vUrq3TfBxt1zMQC3X7O9LC9aV195GhlpybqJ88t05n//Fi3nTJZU8O4g0e5q3sntSGFmQ65fX5Vuxt7pQS9v/M0NunXL6/Sgx9v1swROfrHudM1JKtn240bY3Td0WM1OMuhnzy7TKfd+ZHuu3BWTAXy0aDM1b0wdXhwp7Etu+s1JbX/TtZ7Q2WNR08u3KrHPtmibc4GFWYm69ZTJuu8OcN7bdlsOIzMS9Pfz5muqw4fpT/8d41+/cpqPfDBJl1/zFidMbOYC0UtbKiskzFSSSeaGIeqiNZX1mpQGlXYnVHuatDPnl+uN1ZVaMrQLD146ZxeXV7Znrz0ZD146Rz9/a0v9bc3v9SybS7ded4MjWWO3GmhOVpXegiFKr77805jy7e59K1HFmlHtVu3njxJ5x80gouO/RiB0ADiavDpr2+s1UMfb1ZqUrx+ftIBumDeiJhfrpCVmqi/nzNdJ0werJufX66Tbv9ANxw7TlccNpJJYAxo8Dbphie+0Gsrtuvig0v0s5MOCPsa5nPmDNegtCT99LnlOvmOD/XNmcX64fHje1SBFBKaMHS3Qii0Y1pljZtAaB+lVfW69tHFWlLq0uWHjtRNJ0wI6+/LM2cN07CcVF396CKdcueHuvO8GTp4dF7YXh/t626F0PDgFtqbd9dpSjGBkLVWCzdX6eGPN+vV5eXyNVkdMiZXPztpoo6ZWNiv3kcnB0/AF2zYpd+/tlo/fnaZ7n1vg2786jidOHlIVIdafWXDzjoV56R0qlplTLAibF1FbVh2khtorLUqrWrQos1VWrh5txZuqtKaHTVKTojTT0+cqEsOKYn48RMfZ/TdY8Zp1ohBuv7fn+sb//hQvz5tsk6dXhzRcfUX5S630pLildGFbckHpSXJkRinbVX9MxB68rOtuvmF5cpNS9ITV83rVusFRBcCoQFgR7Vbry3frr+9+aWq6r06Z85wfe/YccpNp3liSydOGaI5IwfpZ88v1+9eW63/rtiuP54xVWM6sU4e/VNljUeXP7RQS0ud+vlJB+jSQ0f22tc6btJgHTw6V/94e50e+GCjXl1Wru8cPVaXHFKi5ITul4GXudxKjDfK7+bxXBhsorqj2qMxBVz1C3lr9Q7d8MQS+f02bLu5tGbe6Fy9cO0huvzBhbrw/k/1fydP0nlz2YGsL5S53DImUCXXFaFNCGJ9p7FaT6Oe/3ybHlmwWau31yjDkaDzDxqh8+aO6PfvmweNytUzVx+sN1ZV6I//XaNvP/a5Jg9dr7NmDVO6I0EpifFyJMYrJTHQCDUlKa7585SkeDkS4gdseLS+olaj8jr3/R2anaLkhDitp7G0pMCOUyvLqrVwc5UWbd6tRZurtCO4qUN6coKmD8/WcZMG6/QZxVG32cmhY/P0yvWH6TuPf64bnliid9dU6uaTDlAe5xLt2u5ya0h2SpeqY4wxKspOUZmrfwVCbl+TbvnPCv37s606ZEyubj97OueaAwSBUD/kqvfp4w079dH6Xfpw3U6tDzYAnDNykH7x9QMiVnraH+SlJ+vO82boxaXl+vkLy3Xi7e/rB18dr0sPHdnvOt+jfesqanTxvz7TzlqP/nn+TH110uBe/5oZjkT9+ISJOnv2cP3q5ZX67aur9finW3Tz1w7QMRMLulVOW+ZsUGGmo9snH6GTYbaeD2hs8uvP/1urO99ZrwOGZOrO82b0+lKuEblpevaag3Xd45/rp88t19rtNfrZSQdE/MrwQFfubFBBRnKXq74CW+EmaUsMBULWWlXWerShsk4bd9ZpaalLLy4pU62nUZOKMvXb06boG9OKBlR/CGOMjj2gUF+ZUKAXvtimP/9vrX72wopOPTc0lxhom1X4/VYbd9Z1uOV8SFyc0aj8dK2L4a3nrbV6Z22l7nt/gxZvdqrB1yQpEJbNHZmrWSU5mjkiRxMGZ0b9PLMw06HHLp+rv7+1Tne+s07vrK3UT0+cqG/OLGY5UBvKXe5uLekfmp3SryqEtu6u1zWPBraUv/ao0brx2PFR//OMzuvyO7sx5tuSLpY0RdLj1tqLg7eXSNooqa7Fw39nrb21x6OMcQ3eJn22abc+XL9TH63bpeVlLlkrpSTGa87IQTpr9jAdPDpPk4oy+YXdCcYYfWNqkQ4aNUg/fW65fvXKKr22Yrv+8M0DY2Z7wYHu4/W7dNXDC5WUEK8nrpwX1p4+nTEyL033XTRb766t1K0vrdQVDy3UYWPz9POTDujy2vxyp1tFPehpU5C5p0Io1lXUuHXd459rwYbdOmfOMP3i65P6rIlnhiNR9100W799dZXufX+j1lfW6Y5zZ9C0uBcFJurdO3YG6tbzNW6fNu2s14adtc3hT+hPraex+XGOxDidOHmIzp83QtOHZQ/ouUV8nNFpM4r1jalF2lnrldvXpHpvkxp8TXL7mtQQ/Ljl508s3Krz7/tEfzjjQJ08bWik/wlhU17tVoOvqVMNpUPGFKTri61VvTiq6PX5lir99tXV+mTjbhXnpOis2cOaA6Ce9qKLlIT4ON1w7DiddOAQ/fjZZfrB00v17OJt+tWpk5kjt6Lc1aCxBV3v0zo0O0Wrymt6YUTht3ybSxf/61N5Gv2698JZOvaAwkgPCWHWnUs9ZZJuk3ScpNZ+22VbaxtbuR1dtLTUqV+/skqLNlfJ12SVGG80fViOrj96rA4Zk6epxdm9ss11rCjIcOieC2bq+S+26RcvrAhUCx03QRfNG8GV+37s2cWluumZpSrJTdMDF8/WsEGRK8s+Yly+Dr7+MD388Wb95Y21Ov5v7+uCg0bohmPGdToIKHM1aNaI7q/PTk1KUIYjIeYrhBZs2KXvPP65atw+/emMqTp9Zt/3R4iPM/rp1wKh4E+fW6ZT7vxQ9144q98vv4lWZa4GTRjcvWWSI3LT9OnG3WEeUe+q9TRqu6tBZU63trvcKne5tb26IfB38HNXg6/58cZIxTkpGpmXrpkjcjQyL00j89I0Kj9NRVkpA3ZJVFsS4uM63Rj2rNnDdNXDi3T9v7/Q1t31uvaoMQMiNNvQhR3GQkbnp+mlpWVy+5piZte2dRW1+uN/1+i1FduVl56k//vGJJ0zZ/iAmpOPLczQk1fN0+OfbdFvX12t4//2vq77yhhdefjoAfXv7Alfk18VNZ4ubTkfMjQ7RTtrPVF/3HyyYZcuf3ChMhwJ+veV85ivDFBdDoSstc9KkjFmliQ6jvWS/ywp0w+eWqKc1CRdeshIHTwmT7NLcgZUuXY0MMbo1OnFOnh0nn787DLd+tJK3fXOOn19apFOm16syUOpuuovtu6u159eX6PnvyjTwaNzddf5M6OiiXJifJwuPXSkTp5WpD//b60e+niTXlxSpvsvnq1pHVQuNflt8/r0nijISFZFTWwGQrWeRs3/cKP+/L+1KslL0yOXzdX4boYE4XLmrGEalZemqx5epFPv/FD/OHeGjojRnSB7i7VW5U63jhpf0K3nDxuUque/2CZPY1OPeoD1NrevSb94YYVeWVauGs/+1+Ly0pM0OMuhYYNSNWfkIA3JSmkOfYYPSo3qE5Folp2apIcum6MfPbNMf3x9rbbsrtevTp3S7zfx2BBsQTCmC5UgYwrSZW3guQcUZfbW0KLCdpdbf31jrZ5cuFUpifG64ZhxuvywkUrrQkPh/iQuzui8uSN07MRC/d+LK/XH19fqP0vK9JvTpmjmiIG1XLI7Kms8srZ7u8CGNgopd7k1Mkp3IH1j5Q5d+9hiFeek6OHL5nZ7cxNEv974DbbZGGMl/U/SD6y1O3vhawxYfr/VX95Yq7+/tU6zS3J09/kzadjVBwozHbr/oll6c1WFnllcqkcXbNG/Ptyk0flpOnX6UJ08bWhEK03QNme9V3e8vU4PfrRZxkjXHDla3z1mXNRdwcpNT9avTp2ic+cO19WPLNZ59y7Q/RfPbrdXw85ajxr9VkXd3HI+pDDTEVNLxjyNTXp3TaVeWFKmN1ftkNvn10kHDtFvTz9Q6VEycZ9VMkjPX3uIrnhooS7516f66dcO0PkHDY/q8KE/cTX41OBr6tZEXZJGDEqVtVJpVYNGR+kyie0ut658eKGWlrr0zZnFGlOQriFZDg3JStGQLIcKMpP5eepFyQnx+vOZUzUsJ0W3v7VO5S637jhvhjIdkb8Q0V3rK2uVnpyg/IzOzztDx8e6ytoBGwi56n266931+teHG+W3VhfOK9G3vzImZhouF2Q6dMd5M3Taqh362fPL9c27P9Z5c4frh8dP6Nc/7z3VnS3nQ4bmBMKVbVUNURkIPbu4VD94eqkmFWVq/iVzNCgtKdJDQi8K58x4p6TZkr6QlCvpDkmPKrC0bD/GmCslXSlJw4cPD+Mw+q96b6NufGKJXluxXWfOKtZtp0yJupPagcwYo2MOKNQxBxTKVe/Tq8vL9ezn2/TH19fqj6+v1eySHJ06vVhfmzKEvh9RwO1r0oMfbdIdb69TjadR35xRrBuOHRf1VzAmFWXpqW/N03n3faKLHvhU/7xgpo5so4qhp1vOhxRmOvTZpv61/KWrmvxWn2zYpRe+KNOry8tV7W5UblqSzpw1TCdPK9KM4TlRV+03bFCqnrn6YH33iS9060srdetLK1WYmaxhOakqzknRsEGpe308OMvR7ysQ+kqZM1AR191jZ0RwB6Atu+qjMhD6YqtTVz60UHWeRt1zQd80zcf+jDG68avjNWxQqn787DKdcdfHeuCS2Roa5e9DbdlQWadR+Wld+l05Mi9NxmhA7jQWmmfc+c56Vbt9OmXaUN147LiYvUB49MRCHTQqV396fa3mf7RRr6/Yod+cNkVHT4zNnjLlruD7TDf6RYV+R4TmedHkgQ826pcvrdTBo3N1z4WzouZCGnpP2L7D1tpaSQuDn+4INp8uN8ZkWGv365plrb1H0j2SNGvWLBuucfRX25wNuvzBhVqzvVo/O+kAXXpISdSdvMSSrNREnT1nuM6eM1ylVfV64YsyPff5Nv3kuWW65T8rdNSEfF195JgOl/wg/Px+q+e/2KY/vb5W25wNOmp8vm46YYImDO4/VyYLMx164sqDdOEDn+qKhxbq9rOn64Qp+297Hjqp7WlzyoLMZFVUe2StHVC/V6y1Wlrq0n+WlOnFJWWqqPEoLSlex00erG9MLdIhY/KiPkBJS07QP8+fqddWbNeXO2q1tapepVX1+mxTlf6zpEz+Fu+O8XFGgzMdOunAIbr+mLEsIW5H6MptdyuEQltCR2Nj6ec+L9VNzyxTYWayHrrs4H71u2+gOmPWMBVlp+hbDy/SKXd8qH9dPFuTh/a/HV83VNZqbid3GAtxJMZrWE7qgNtpbMuuel396CKtKKvWkePz9cPjJgzYCqiuSEtO0M+/foBOmV6km55ZpssfWqhbT56s8w8aEemh9bntwUCoOxVCg7McMiZw/hctrLX6y//W6va31um4SYX629nTWVYcI3pzNhmaxkb3bDwKLNq8W1c9vEgen18PXDy7zWoBREZxTqquPWqMrjlytFaUVev5z7fp+S+26Zx7FuiBi2dr3uiuTZ7Qfe+trdRvXl2tVeXVmjI0S3/45oE6eExepIfVLbnpyXrsioN06fzPdO1ji/WHb+7f6Dh0UtvTq82FGQ55m/xy1vuUM0DKft9eU6FfvrhSG3fWKSk+TkeOz9fJ04bqKxMKlJLUvyYwcXFGJ04ZEti7swVfk1/bXe5ASLS7QVur6rVme43++d4GvbysXL8+dYoOp/dQq8pcPQtT89OTlZIYr81RtPV8k9/q96+t1j/f26CDRg3SnefNpIw/ihwyJk/PXHOwLvnXZzrznx/r7+dM71eVE/XeRpW53BrVjeUrYwrSB1SF0Bsrd+jGJ7+QJN134Swdw65K+zmwOFvPXn2wrn1ssW5+frl21np0/dFjB9RFp46UOd1KTYpXpqPrp9OJ8XEqzHBETSDk91v94j8r9PCCzTpr1jD96tTJbLATQ7qz7XxC8HnxkuKNMQ5JjZJmSnJK+lJSjqTbJb1jrXWFbbQD0FMLt+qnzy1XUbZD/75ylsYURLbZKdpmjNHkoVmaPDRLVx0xWufeu0CXzP9UD1w8WweP7p+hRH+xfJtLv3tttd7/cqeGDUrR7edM10lThvT7XXCyUhL18GVzdMVDC/W9p5ao3tuoC+aVNN/fPNlI6Vl2X5gZuHq1o8bd7wMha63u/2Cjfv3KKo0pSNfvTp+i4ycNzGWcifFxgWVjg1Kl0Xtu/2TDLv34uWW68IFPder0obr5axPpNbePcmeDEuJMl3qhtGSMCW49XxfmkXVPtdun6x//XG+vqdT5Bw3XL74+Keqr32LRuMIMPXfNwbrswYW64qGFuuUbk3Rhi9/p0SzUULo7W4uPzk/TB+t2qslvFd+P35eb/FZ//t8a3fH2ek0qytTd58+M2eVhnZGSFK9/XjBTP3pmmf76xpfaVevVLd+Y1K9/Brpie3WDhmQ5uh2CFWU7omLJmLfRr+89tUQvLinTVUeM0o+OnxBTwR66V71zs6QGST+SdH7w45sljZL0mqQaScsleSSdE55hDjxNfqtfv7JKP3h6qWaV5Oj5aw8hDOpH8jMC1R3DclJ16fzP9NF6eqf3hg2Vtbr2scU66e8faNk2l35+0gF648Yj9I2pRf0+DApJTUrQ/RfN1jETC/WzF1bo7nfXN99X5uzZZCOkMDNwUtzfG0t7G/266Zmluu3lVTr2gEI9f+0hOmv28AEZBrVn7qhcvXLdYbruK2P00tIyHfPnd/Xs4lJZG/Orr5uVu9wqzHT06MRkeG5qVFQIbdpZp9Pu/Ejvf7lTt54yWbed0v93sxrICjIdeuKqg/SVCQX6+QsrdMMTX8jV4Iv0sDq0YWcgEBpd0L0KIW+jX9uqIn9y2107az268IFPdMfb63X27GF65uqDCYM6ITE+Tn8840BddfgoPbxgs657/HN5GpsiPaw+Ue5y92hJ/9Cc1IhXCNV7G3X5Qwv14pIy/eiECfrxCRMJg2JQd7adv0XSLW3c/XhPBhMrqt0+ffffX+it1RW64KAR+vnXD2By1w/lZyTr8SsP0rn3LtCl8z/TAxfN7rfLl6JNmbNBt7/5pZ5aVKrkhDhd95UxuvzwUQN2NwtHYrzuOn+GbnxyiX776mrVeRp147HjVO5qCEuT7OYKoer+u/X8rlqPrn5ksT7dtFvf+coY3XDMuAETCnaHIzFeN351vE6aWqQfPbNUNz65RM99vk2/OmVKc/+bWFbuauh2/6CQEYNS9d7ayoj23vrgy5269rHFijPSQ5fNoRq1n0hNStA/L5il29/8Uv94e50+2bBLfzxzalR//9ZX1MoYqSS364FQqPH6+srafvn7Z9HmKl376GJV1Xv1+9MP1Jmzh0V6SP2KMUY/PnGictOT9OtXVsvZ4NU/Lxj4zYjLnW4dOrb7x3RRtkP/Xe6W3297fT7jbQwsQS911mtbVYO2ORu0rapBi7dUaePOOv3u9Ck6azabPMWqgX2kRpkmv9Uzi0r1h9fXaHedV7eePGmv5SHof/KCfWDOu/cTXfrgZ7r/otk6hFCo23bXeXXn2+v00ILNkpUunDdC1x4VG1u7JsbH6a9nTVNaUrz+/tY61Xoatc3pDkvD2NCymYp+Ggit2V6jyx78TBU1Hv3t7Gk6edrQSA8paowrzNDT3zpYj36yWb97bY2++td3deOx43TpISNjev1/ucutA4uze/QaI3JT5Wn0q6LG0xyq9rYmv1WZs0EbdtZp4abduvOd9RqTn657L5zVL0+0Y1l8nNENx47TURMKdMMTX+jcez/R5YeO1PePGx+VjVo37KxTcU5Kt8bWvPV8Ra2OmtB/+mBaa/XgR5t028urVJSdomeuPrhfNgOPFlcePlq5acn64TNLdfY9H2v+JXMG7Pytscmvihp3jy48FGenyNvk185ajwrC+B6z3eXWY59s1qZd9c3Bz44at/YtIi7ISFZxToruPp+dKmMdgVAf+Xj9Lt360kqtLK/WjOHZuvfCWexQNUAEQqG5OvfeTwKVQhcTCnVVradR972/Qfe9v1H13kadPqNY1x8zVsU5sXUCFB9n9JvTpigtOUH3f7BRkjQku+eTBEdivLJTE/vlkrE3V+3QdY9/rtTkBD151Tx+b7YiLs7ognklOuaAQv38hRX69Sur9cIXZfr1qVM0NQb/v6y1Kne5dfyknh07w4OVEpt31Yc9EKqq82rDzlptqKzThp112lhZpw07a7VpV728jf7mxx03qVB/OnPagL/SPpBNG5atl687VL95ZbXu+2Cj3vuyUn85a5omFUVX8LChslaj8rreP0iSctKSlJuWpPX9aKexOk+jfvTsMr24pEzHTCzQn86YFnPLj3vD6TOLlZOWqGseXaxv3vWRHr5s7oBceldZ65Hf9mwX2FAF+DZnQ1gCIbevSfe8t0F3vbNe3ia/irIdGpqdokPG5GloToqKs1M0NCdFQ7NTNCTboeSE6AumERnMMHrZpp11+vUrq/T6yh0amh1ohvv1A4ewPnOAyQ2GQufdFwiF7r9odo/KSGOF29ekRxZs1p3vrNfuOq+OnzRY3z9uXEz30zLG6OavTVRacoJuf/NLjezGji+tKcxw9KslY9Za3fv+Bv3m1dWaVJSpey+c1aOJVywYkpWiey6YqdeWb9fP/7NCJ9/xoY4cn69vHzVGs0oGRXp4fWZXnVfeRn+Pl4wND57EbN5VpzkjO/7/q/M0aletV5W1Hu2q9WhnrVe7aj3aVbf3bZU1nr16yiTGBxpYj8xL15HjCzQqL00j89I0Kj+9202xEV1SkxJ06ymTdfTEAv3g6aU65Y4PdeOx43Xl4aOiogGv32+1obJzP+dtGV2QrnUR3mmszNmgnbUeNfmt/Naqya8WH1s1WSu/38rT6Nef/7dWGypr9cPjx+tbh4+O6SXI4faVCYV69PK5unT+Qp1210d66NI5mjik59XO0aS8eSfL7r/PDM3ZEwhNH57T7dex1uqlpeX67aurtc3ZoBOnDNaPT5g4IIM49A4CoV7iavDp729+qQc/3qSk+Dj94LjxuuzQkVFZJozwyE1P1qOXB0Khyx78TPddNEuHjWVL6LbsqHbr3HsXaH1lnQ4bm6fvf3V8TFYztMYYoxuPHacTJg/WmILuXbHdV0FmsnbU9I8KIU9jk3763HI9vahUJ04ZrD+dMa3fbSUfKcYYnTBliA4Zm6eHP96s+z/YqG/e/bHmjhykb39ljA4dkzfgL0iUO4MT9R723xqanaI4I23ZvX9j6TpPo5Zvc2lJqVNLSl1astWp0jYa6mY6EpSXnqy89GSNLUjXvFG5GpGbqlH5aRqVl67inJSYXt4XS44cX6DXv3u4fvr8Mv3utdV6a/UO/fnMaRE/cdte7VaDr6l56Vd3jM5P12vLy8M4qs5pbPLrjVUVemTBZn2wrvMbfOSmJemRy+bS+7GXzBwxSE99a54uvP9TnfnPj/X3c6ZrVskgpSXFD4j3oND7zOAeBEKhCqGe7DS2rNSlX760Qp9tqtIBQzL1pzOn6qBRud1+PcQmAqEwa2zy6/FPt+jP/1srZ4NPZ84cpu8dN04FGX3TfwCRlRvsKXTuvQt0+YMLde+Fs3T4OEKhfe2oduucexZoR7Vb/7pkto4a3396DvSlcF5RK8x0aF1F9O+Gt7PWo6sfWaTPNlXpuqPH6rtHj+XKbTdkOhJ17VFjdMkhJXr80626970NuuD+TzW1OEvXHjVGx0wsHLD/r2WuwOS6qIcVZUkJcSrKTtGGyjot3+bSF1udWlrq1JKtLn1ZUSN/sB9DcU6KphZn65w5w1WQkay8jGTlpSUrLyNJg9KSKMvHXnLSknTHuTP0/Bfb9PPnV+j4v76nX3x9ks6YVRyxE+XQUq9R+d2vSB1TkK6qep921XqU2wd9Yyqq3fr3Z1v12CdbtL3araIsh7537DgdUJSpuDijOGMUb4zi4qR4YxQfZxQXZ5o/Hp6bOmA3qogW4woz9Mw1B+uC+z/Rxf/6TJLkSIxrDsjzM4J/pycFfm8Gb89KSVSGI0GZKYlRGyCVh+F9JtMR+Hd2Z3e+ihq3/vDaGj29uFSDUpP0m9Om6MxZw6Ki4hD9D4FQGL2zpkK/enmVvqyo1bxRubr5pIlRt0YcvW9QWlKg0fR9n+jyhxbq7vNn6CsTCiM9rKix3eXWOfcuUEW1Ww9eOiemlrJEUmFmsipqPH2ym0V3bdpZpwsf+FQ7qt36+znT9fWpRZEeUr+XmpSgyw4dqfMPGq5nF2/TXe+s15UPL9L4wgxdc9RofW3KkAFXnVIevNoajv5bI3JT9fKycr28LFD5MCgtSQcWZ+n4yYM1dViWDizOHrBNU9F7jDE6dXqx5ozM1fee/EI/fGapHl6wWWfOHqZvTC1SVkrfBhUbKoNbzveoQigQJq2vrOu1QMhaqwUbduuRBZv13xXb1ei3Onxcvn558iR9ZULBgPtdNhAMzU7Rc9ccojdX7VBljUc7az3Bv73aurten2+p0q46734Nj0PijJQRDE4yHYnKTElQhiNRWSmJOn1GseaNjkw1zHaXWymJ8cpM6dmp9NDsFG1zdn45v6exSQ98sEn/eOtLeZv8uuKwUfr2V8YQbqJHCITCpMlv9auXV8nX5Nc9F8zUsQcURmWijb4xKC2pefnYpfMXavrwbF04b4ROnDIkpq8Wl7sadM49C7Sz1quHLpujmSMIg/pKYaZDTX6rXXXeqOxLsmSrU5fO/0x+a/XvKw/q0Xp67C85IV7nzBmuM2YW66Wl5brj7XW6/t9f6M//W6sLDhqhvPRkJcbHKSkhTonxRkkJcUpq/jzwd1pSggozk6P+va3c5VZSQpxy05J6/FrXHjlGk4uyNHlolqYNy1ZxTkrU//vRfwzNTtFjlx+kf3+2VQ99vEk/e365bntppU6cMkRnzhqmg0YN6pOftw2VtUpPTlBBD94bQsub11XU9qgXUWuq3T49u6hUj3yyResqapWVkqhLDinReXNHqCRMffbQe7JSEnXajOI2729s8mt3vVc7a7zaVedRdUOjqt0+1bh9qm5oDPztbmz+fOvuen1W7dYzi0t11eGjdeOx45SU0LdhYLkrsMNYT4/PQCDUuQqh99ZW6ubnl2vL7nodM7FAP/3aAWHrM4nYRiAUJvFxRvdfNFuDsxx9/ksJ0WlQWpKe+tY8PfnZVj2yYLNueGKJbntplc6aPUznHTRCQ3vY36K/KXc16Ox7FmhXrVcPXjpHM0dwwt+XQstWd1S7oy4QemdNha55dLEGpSXpoUvnaFQPrlKjfQnxcTpl+lB9Y2qRXl+5Q3e8vU63vbyq08+fNypX3z9ufFQfv2VhmqhL0sFj8ugxgl4VF2d07tzhOmfOMC3fVq0nFm7RC1+U6bnPt2lEbqrOnDVMp88o7lGvko6sr6zTqPy0Hh0zRVkpSkmMD+tOYzVun+55b4Pu/2Cj6r1NmjosW388Y6pOOnAIPTkHkIT4OBVkOLrUXqPe26hbX1qpu99drw/X7dTfzp7Wp3OHcldDWKpQi7JTtHBzVbuPcfua9NtXV2v+R5s0Oj9ND182hx6lCCsCoTAanks3d+wtPTlBlx46UhcfXKIP1+/UQx9v1t3vrtfd767X0RMLddG8Eh0yJnfAX3EuczbonHsJgyKpMDMQAlXUuCVFz1LWZxaV6qZnlmpcYYbmXzI7LFuvomNxcUbHTx6s4yYVqtzlltvXJF+TlbfRL2+TX95Gv3wt/27ya5uzQQ98sFGn3/WRjplYoO99dXxU7hxT7mzo8Q5jQF8zxmhKcZamFE/RT088QK+tKNcTn23VH/67Rn96fY2OHF+gM2cV67Cx+UpJjA/r0t8NlT2v6omLMxqVnxaWncY8jU16ZMEW/eOtL1VV79PXDhyiqw4fpQOLs3v82hgYUpMS9JvTDtQR4/J10zPLdNLfP9AtfdiLa7vLrXmje36xYGhOilwNPtV6GpWevP9p+aryan33319ozY4aXXxwiX50wgTCUIQdgRDQB+LijA4bm6/DxuartKpej36yRU98tlX/W7lDo/LTdMFBI3T6zOIBuQa4zBmoDKqqCywTm8FSoIgozAxVCEXHTmPWWt317nr9/rU1OmRMru4+f6YyBuDPf7QzxjTvdNIZF80r0fyPNunud9frhL+9r29MLdINx46LqrL1cpdbc8O8ZAXoSylJ8Tp1erFOnV6szbvq9NTCUj29qFTfemRx82OS4uOUnBCn5MR4JSfEyZEYp+SE+Oa/i7JT9P3jxmlIB01v672NKnO5e9Q/KGR0froWb2m/2qE9TX6rF77Ypj+9vlbbnA06dEyebjp+gqYUR89FDESX4ycP0dRh2brxiSX64TNL9c7aCv3m1AOVldp784kmv9WOGk9YLjy03GlsXGFG8+1+v9UDH27U719bo8yURM2/ZLaOZAMW9BICIaCPFeek6qbjJ+j6o8fqlWXleujjzfq/F1fqz6+v1d0XzNQhA2h5wjZnoGdQKAyiL0zkhJaJVURBINTkt7r1pZWa/9EmfWNqkf54xlSW2vYTackJuvaoMTp/7gj98731+teHm/TysnKdMbNY1x09tkvhUm9o8lttr3aHpZQfiAYjctP0/ePG64Zjx+m9Lyu1ZnuNPD6/3I1Ncvua5Gn0N//t8TXJ7fPL09ikV5aV641VO/SrUyfrpAPbbtAfaigdjuU2YwrS9eLSMjV4m5SS1PkqBmut3llTqd+9tlqrt9do8tBM/fb0KSyLQacMyUrRI5fP1T3vbdCfXl+jL7a8p7+cNU1ze2n79coaj5r8NizvM0ODr7GtRSC0o9qt7z25RB+s26ljJhbqd6dP6ZOd+xC7CISACHEkxuu0GcU6bUaxlpY69YOnluqS+Z/prvNm6OiJ/X9Xsm3OBp19z8dy1vkIg6JAYnyc8tKTtKOm87tZ9Aa3r0k3PvmFXlm2XVccNlI/PmFi1O56hrZlpSbqh8dP0MWHlOjOt9frsU+26NnF23T+QSN0zVGjI7bzVvNEvYdbzgPRJj7O6KjxBTqqk1UCGyprdcMTX+jbj32ut1ZV6JaTJ7VahbxhZygQ6nmV3+j8dFkrbdhZ2+lddj/fUqXfvrpan2zcrRG5qfr7OdP1tSlDeF9Al8THGV195GgdPDpX1//7c5197wJde+QYXX/MWCWGefe50Jbz4agQGpodaDcS2nr+teXl+tGzy+Tx+fXrU6fonDnDBnxbCUQegRAQBQ4szta/rzxIF/3rU1318CL99exp7V7Ri3alVfU6594Fctb79PDlczVtWHakhwQFGktXVEcuEHI1+HTlQwv1ycbduvlrE3X5YaMiNhaER0GGQ7d8Y5IuP2ykbn/zS83/aKP+/dkWHTQqV/npySrITFZ+RrLy0wN/F2Q4lJ+R3KXqga4oC07Ui6gQQowblZ+up68+WH9/a53+8daX+mTjbv3lrGn79QraUFkrYxSWZZ8tdxprKxCy1mqbs0HLt1Xr+c+36bUV25WXnqRfnjxJZ88eTrUoemTqsGy9fN1h+r8XV+gfb6/TB+t26q9nTQvrbnTbXYF51ODMnl94yM9IVkKc0bqKWv3w6SV6cmGpDizO0l/P6tsm2YhtBEJAlMgJblV/6fzPdN3jn6ve26QzZw2L9LC6bFuwgbSz3qdHLpurqYRBUaMwM1nrK+tUWePp853Gtrvcuvhfn2p9Za3+dvY0nTxtaJ9+ffSu4pxU/f6bU3Xl4aN15zvrtGZ7jZZtc2lXrUd+u//j05MTlJ+RrGGDUjWtOEtTh2Vr6rDsHlcWlTsDE3UqhIBAZeiNx47TEePydeOTX+isez7Wt44YrRuO2bNN9/rKOg3NTglLo9qSvFTFmcBrSoE+KFt212t5mUvLt1Vr+TaXlpe55Kz3SZLSkuJ1wzHjdPlhI5XWSkNdoDvSkhP0+29O1eHj8vXjZ5fpuL++p+uOHqsrDhsVlsCxzBV6n+n5hYf4OKMh2Q7N/2iTjJGuPWq0vnvMuLBXNQHt4bcvEEUyHIl68NI5uurhRfrh00tV72nUxYeMjPSwOq0stEyMMCgqzR2Vq7fXVGreb97UVycV6tw5I3Tw6NxeL83fvKtO5977iVwNPs2/ZM6A6pOFvY0pSNefz5zW/HmT32p3nVeVNR5V1npUUe1WZa1HlTUeVdR4tKGyTv94e11zaFSck6Kpw7I1rTgQEE0ZmtWlaqJQKX8RgRDQbOaIHL1y3WG69aWVuuud9XpvbaX+etY0jS3M0IbK2rA0lJak5IR4DR+UqheXlOnTjbu0oqxaNe5GSVJivNH4wRk6ftJgTRqapclFmZo4JJMdk9BrTjqwSDNH5OiXL67UH/67Rs8uLtVtp0zRvNE96y203dUgR2KcssPUuPrA4mz5/Wq1gg/oCwRCQJRJTUrQfRfN0nce+1y3vLhSdd4mXXvUmEgPq0PlrmBlUF1gmRhhUPT51hGjdczEQv370y16enGpXlm2XSNyU3XOnOH65sziXun7sq6iVufdt0DeRr/+feVBmjyU3WJiSXycCSwZa6cird7bqOXbqrVkq1NflDr1xRanXl5a3vz8cYUZml2SowvnlTQvSWlLmdOt1KR4ZaYwvQFaSktO0G9PP1BfmVCgHz0b2Kb7xydM0IbKurCehM4dmavnv9imrJREnTytSJOLsjR5aJbGFqYrOYHwB31rSFaK7jp/pt5eXaGf/2e5zrl3gU6bPlQ/+drEbs95yl1uDclKCVtvn7+dNU1xxtA3CxFjrG2llruPzZo1yy5cuDDSwwCiiq/Jr+8/tUQvfFGma44crR8cNz5qG8ttd7l19j0fa2etVw/TQLpfcPua9Nry7Xrsky36dNNuJcYbfXXSYJ03Z7jmjc4Ny8/a6u3VOv++TyQZPXbF3L22VAXaU1nj0dJSp5ZsderzrU59unG3vE1+HXfAYF195Og2A+erH1mktTtq9Ob3juzT8QL9SUWNWzc9vVRvr6mUJN16ymRdcNCIsLy2tVZ+GwhzgWjS4G3SP97+Uve8t0EpifG66YQJOmf28C4HMaff9ZGS4uP0+JUH9dJIgfAzxiyy1s5q9b6uBkLGmG9LuljSFEmPW2svbnHf0ZLukDRc0ieSLrbWbu7oNQmEgNY1+a1ufn6ZHv90qy4+uEQ/P+mAqLuCsKParXPuWaAd1W49dNlczRxBGNTffLmjRo9/ulXPLC6Vq8GnkXlpOm/ucJ1/0Ihul/MvK3Xpggc+kSMhXo9dMZfmiOiRXbUezf9okx78aJOq3Y06ZEyurjlyjA7eJ7w8+Y4PlelI0MOXzY3gaIHoZ63VI59s0f3vb9B9F83usPoOGCjWVdTo5ueXa8GG3Zo2LFu/OnVyp3fFk6RDfvuW5o4atNfyaCDahTsQOk2SX9JxklJCgZAxJk/SekmXS3pR0q2SDrPWdhifEggBbbPW6raXV+n+DzbqjJnF+u3pB0bNlbeKarfOvneBdrjcevDSOZpVwtrn/szta9Iry8r12CdbtHBzlUpyU3XrKZN12Nj8Lr3Oos1VuviBT5WVmqjHLj9Iw3NTe2nEiDU1bp8e/3SL7nt/oypqPJpanKWrjxytrx4wWHFxRnN+9YaOHJ+v339zaqSHCgCIUtZaPff5Nv3q5VWqqvfq4oNH6savjlN6B83Nm/xW429+VVcdMUo/OG5CH40W6Ln2AqEuL7K31j4bfNFZkopb3HWapBXW2qeC998iaacxZoK1dnWXRw1AkmSM0c1fm6i05ATd/uaXqvc16S9nTov41qyVNR6dc+8CbScMGjAcifE6bUaxTptRrPe/rNTPX1ihC+7/VF87cIh+ftIBKszseEeNBRt26dL5n6kw06FHL5+romya+yJ8MhyJuvLw0bpwXomeXbxN/3xvvb71yGKNyk/TVYePUmWthx3GAADtMsbotBnFOnpCoX7339X610cb9finW1Sck6Ih2SkakunQkGyHirJSNDjLoaJsh4ZkpajW06hGv9Vg3mcwgISz6+IkSUtCn1hr64wx64O3EwgBPWCM0Y3HjlN6crx+/cpqeXx+3XHe9Ig1aNxZ69G59y5QmdOt+ZfM1mzCoAHnsLH5evX6w/TPdzfojnfW6d01lbrx2HG6cN4IJbSxHep7ayt15cMLNSwnVY9ePlcFnQiQgO5wJMbr3LnDddbsYXplWbnufGe9bnpmmSSpKJufOwBAx7JSE/XrU6fojJnFeuGLMpW7GlTucmtlWbV21nr2e3xqcNfLojBsOQ9Ei3AGQumSKve5zSWp1S6ixpgrJV0pScOHDw/jMICB68rDR8uRGK+fv7BCVz28SHefP7PPt2zdFQyDSqsa9K9LZmvuqJ5t34no5UiM1/XHjNXJ04r08/+s0C9fWqmnF5XqtlMna8Y+jcPfWLlD1zy6WGMK0vXwZXOU2ws7lgH7io8z+vrUIp104BC9u7ZSLy8t11HjCyI9LABAPzJ9eM5+G6J4GptUUe1RmTMQEpW5GlTudKve26TZbA+PAaTbu4wZY26TVNyih9DfJCVaa69p8Zhlkm6x1j7T3mvRQwjomsc/3aKfPLdMh4zO070XzlJKUt+EQrvrvDr33gXatKtOD1w8WwePzuuTr4vIs9bq1eXb9X8vrlBFjUdnzx6um44fr+zUJL2yrFzXPf65Jg3N0kOXzFFWamKkhwsAAABAYe4h1I4Vki5q8UXTJI0O3g4gjM6ZM1wJcUY/fGapLpn/qe6/aLbSOmiE11Oryqt1wxNfaONOwqBYZIzRiVOG6PBx+frL/9Zq/keb9PqK7Tpl+lD968ONmjkiRw9cPFsZDsIgAAAAoD/ocldaY0yCMcYhKV5SvDHGYYxJkPScpMnGmNOD9/9c0lIaSgO944xZw/TXs6bps01VuuiBT1Xj9oX9a7jqfXr44036+t8/0Al/e1+bd9Xr/otm65AxhEGxKj05QT876QC9+O1DNSI3Vfd/sFEHjcrVg5fOIQwCAAAA+pHubDt/i6Rf7HPz/1lrbzHGHCPpH5JGSPpE0sXW2k0dvSZLxoDue3lpua7/9+eaPDRLD146R1kpPTspb/JbfbR+p55cWKr/rtgub6NfE4dk6sxZxTp52lANSksK08jR3/n9Vp9t2q2pw7L7vJcVAAAAgI61t2Ss2z2EwolACOiZ11ds17WPLdb4wRl65LK5yk7temizZVe9nl60VU8vKlWZy62slESdMq1IZ8wapslDs3ph1AAAAACA3kQgBMSAt1dX6KpHFmlUXpoevXxuh7s8+Zr8WllWrcVbqvTfFdu1YMNuGRPYbvzMWcU6ZmIhVR8AAAAA0I8RCAEx4r21lbrioYUaPihVj14xVwUZjub7dtZ6tHhzlRZtqdLnm51aUuqUp9EvSSrJTdU3ZxbrtBnFKspOidTwAQAAAABhRCAExJCP1u/UZfMXaki2QxfNK9EXW51avKVKm3fVS5IS440mFWVpxvAczRyRoxkjsjUkixAIAAAAAAYaAiEgxny2abcufuBT1XmblJ+RrBnDswPhz/AcTR6axVIwAAAAAIgB7QVCCX09GAC9b3bJIL1/01dU52lUcU6KjDGRHhIAAAAAIIoQCAED1KC0JLaIBwAAAAC0Ki7SAwAAAAAAAEDfIhACAAAAAACIMQRCAAAAAAAAMYZACAAAAAAAIMYQCAEAAAAAAMQYAiEAAAAAAIAYQyAEAAAAAAAQYwiEAAAAAAAAYoyx1kZ6DDLGVEraHOlxdFGWJFcnHpcnaWcvjwXRob99rzv7M4z99bfv9UDVFz/DfK9jRyS+1/wejgyO6/CK5p9jvtexoyff62j+Gcb+OK7319HP8AhrbX5rd0RFINQfGWPusdZe2YnHLbTWzuqLMSGy+tv3urM/w9hff/teD1R98TPM9zp2ROJ7ze/hyOC4Dq9o/jnmex07evK9juafYeyP43p/PfkZZslY970Y6QEAPcTPMPo7fobR3/EzjIGAn2P0d/wMo7/r9s8wgVA3WWv5xYF+jZ9h9Hf8DKO/42cYAwE/x+jv+BlGf9eTn2ECod53T6QHgD7D9zp28L2OHXyvYwff69jB9zp28L2OHXyvYwff6zCihxAAAAAAAECMoUIIAAAAAAAgxhAIAQAAAAAAxBgCIQAAAAAAgBhDIAQAAAAAABBjCIQAAAAAAABiDIEQAAAAAABAjCEQAgAAAAAAiDEEQgAAAAAAADGGQAgAAAAAACDGEAgBAAAAAADEGAIhAAAAAACAGEMgBAAAAAAAEGMIhAAAAAAAAGIMgRAAAAAAAECMIRACAAAAAACIMQRCAAAAAAAAMYZACAAAAAAAIMYQCAEAAAAAAMQYAiEAAAAAAIAYQyAEAAAAAAAQYwiEAAAAAAAAYgyBEAAAAAAAQIwhEAIAAAAAAIgxBEIAAAAAAAAxhkAIAAAAAAAgxhAIAQAAAAAAxBgCIQAAAAAAgBhDIAQAAAAAABBjCIQAAAAAAABiDIEQAAAAAABAjCEQAgAAAAAAiDEEQgAAAAAAADGGQAgAAAAAACDGEAgBAAAAAADEGAIhAAAAAACAGEMgBAAAAAAAEGMIhAAAAAAAAGIMgRAAAAAAAECMSYj0ACQpLy/PlpSURHoYAAAAAAAAA8aiRYt2WmvzW7svKgKhkpISLVy4MNLDAAAAAAAAGDCMMZvbuo8lYwAAAAAAADGGQAgAAAAAACDGEAgBAAAAAADEmKjoIQQAAAAAABBOPp9PpaWlcrvdkR5Kr3M4HCouLlZiYmKnn9OpQMgY821JF0uaIulxa+3F7Tz2Bkk3SUqV9LSkq621nk6PCAAAAAAAoIdKS0uVkZGhkpISGWMiPZxeY63Vrl27VFpaqpEjR3b6eZ1dMlYm6TZJD7T3IGPMcZJ+JOloSSMkjZL0f50eDQAAAAAAQBi43W7l5uYO6DBIkowxys3N7XIlVKcCIWvts9ba5yXt6uChF0m631q7wlpbJelWBSqLAAAAAAAA+tRAD4NCuvPvDHdT6UmSlrT4fImkQmNMbpi/DgayTR9IO1ZGehRA/7H+bWnnl5EeBdB/fPmGtHtDpEcB9B9rXpOcWyI9CqD/WPWiVF0e6VEgSqSnp7d7/6ZNmzR58uQuvebFF1+sp59+uifDkhT+QChdkqvF56GPM/Z9oDHmSmPMQmPMwsrKyjAPA/3ai9dL7/4u0qMA+o8XrpU++EukRwH0H89cJn18R6RHAfQP1kpPXih9ek+kRwL0D41e6YkLpEXzIz0SoEPhDoRqJWW2+Dz0cc2+D7TW3mOtnWWtnZWfnx/mYaBfc7sCfwB0DscM0HnWSp5qjhmgsxo9UpOHYwboLG+tJMsxg/3U1tbq6KOP1owZMzRlyhS98MILzfc1NjbqvPPO08SJE/XNb35T9fX1kqRFixbpiCOO0MyZM3XcccepvDy8lWfhDoRWSJra4vOpknZYazvqPQTs4akN/iIF0CG/P3C8ePbL3QG0xlcvWX/gvQZAx0JzMo4ZoHNCczIvczPszeFw6LnnntPixYv19ttv63vf+56stZKkNWvW6JprrtGqVauUmZmpO++8Uz6fT9/5znf09NNPa9GiRbr00kv105/+NKxj6uy28wnBx8ZLijfGOCQ1Wmsb93noQ5LmG2MeVWBnspslzQ/fcDHgNTVKjQ1MOoDO8tUF/iZEBTon9P7CMQN0TvPJLccM0CmEqNHr1R9J25eF9zUHT5FO+G2nHmqt1U9+8hO99957iouL07Zt27Rjxw5J0rBhw3TIIYdIks4//3zdfvvtOv7447V8+XIde+yxkqSmpiYNGTIkrMPvVCCkQLDzixafny/p/4wxD0haKekAa+0Wa+1rxpjfS3pbUoqkZ/Z5HtA+LxN1oEs8TDqALmmeqHPlFugUTm6BruHCA9rw6KOPqrKyUosWLVJiYqJKSkqat4nfd4cwY4ystZo0aZI+/vjjXhtTpwIha+0tkm5p4+69WmZba/8s6c89GhViFxN1oGsIUYGuodoB6Jrmk1vmZkCnhI4VQtTo08lKnt7icrlUUFCgxMREvf3229q8eXPzfVu2bNHHH3+sefPm6bHHHtOhhx6q8ePHq7Kysvl2n8+ntWvXatKkSWEbU7h7CAE90zJRD66nBNAOD5MOoEuodgC6hmMG6BoqhNCG8847TwsXLtSUKVP00EMPacKECc33jR8/XnfccYcmTpyoqqoqXX311UpKStLTTz+tm266SVOnTtW0adP00UcfhXVMnV0yBvSN0C9Of2NgV4tER2THA0Q7b4srt9ZK+5SbAtgHE3Wga6iqA7qGFQ/YR21t4GciLy+vzeVfq1evbvX2adOm6b333tvv9vnz54dlbFQIIbq0/MXJxAPoWOjk1volX0NkxwL0By2XWfr9kR0L0B9QIQR0DRce0I8QCCG6tPzFSaoOdKzlMcPEA+hYy/eW0C59ANoWOrltbAjsBgugffQQQj9CIITo4uHkFuiSlie3hKhAx/a68MD7DNChlscMISrQsdB7S5NHavJFdixABwiEEF2YqANdQ4UQ0DVceAC6Zq8LDxwzQIdY8RB1bIxsVtSdfyeBEKLLXie3XIUCOtTyOGGiDnSMEBXoGo4ZoGtazs04n4k4h8OhXbt2DfhQyFqrXbt2yeHo2qZM7DKG6LLXlVsSdaBDVDsAXUMlKtA1Ho4ZoEvYJCeqFBcXq7S0VJWVlZEeSq9zOBwqLi7u0nMIhBBdmKgDXeNl0gF0CSEq0DV7VTtwsQ7oEOczUSUxMVEjR46M9DCiFkvGEF08tVJiauBjJupAx1oeM0w6gI55OWaALvHWcMwAXbHX+QwhKqIbgRCii7dGyhgc+JhJB9Axb62UMWTPxwDa52l5zDBRBzrk4X0G6JKWczPOZxDlCIQQXTy1UkqOFJ/MRB3oDE8tISrQFd4aJupAV+x1csvcDOgQISr6EQIhRBdvrZSULiWnM1EHOsNbIyVnBkqTCVGBjnlqpfSCwMdM1IGOtbzwwDEDdIwVD+hHCIQQXTy1UnJGIBRi0gF0zFMbCFCTCFGBTvG2eJ/hmAE65q2V0vIlE8cxA3TE2n1CVC7WIboRCCG6eGuCFUIZTDqAzmhZVUeICnRsrwsPTNSBdlkbDFHTpaQM3meAjjS6JdskpeZKcQmczyDqEQghurSsdmCiDnSs+ZhJY9IBdMTvl3x1LE0GOstXL1l/4JjhfQboWOgYYcUD+gkCIUQXb21gwsGkA+hYU6PU2BCcqHPlFuhQ6BgJvc9wzADt87Q4ZpK5WAd0KHSMJKWxNBn9AoEQokejV2ryBk5sWf4CdKz55DZU7cBEHWhX6JgJLX9hog60z7tPtQPHDNA+zz5zM0JURDkCIUQPJupA1+x1zBCiAh1qnqhnMFEHOiN0oYFedUDn7Ds343wGUY5ACNGDSQfQNftehWLSAbQvFAAxUQc6h4t1QNfsd+GBYwbRjUAI0aO1agdrIzsmIJrtVcpPDyGgQ/uV8nPMAO2iqg7oGi48oJ8hEEL02HfSYf2B3S0AtK61qjq/P7JjAqIZpfxA13DMAF2z14UHLtYh+hEIIXrsm6hLTDyA9uw7UZcCW2oDaN1eFx4yArv0NTVGdkxANGM5P9A1+4WoVNUhuhEIIXrsm6hLTDyA9uy7/KXlbQD219qFB95ngLbt20OoyRvYFRZA61rrIUQLDEQxAiFEj9aqHUjVgbbt20Oo5W0A9tdaiMoxA7SNYwboGm+NlOCQ4hMCx42/UWr0RHpUQJsIhBA99k3UJSYdQHv2LeVveRuA/XlrJRkpKY2lyUBneGulxFQpLp6LdUBneGr3HCuseEA/QCCE6LFXKX/wFygTdaBt3lrJxEmJKSx/ATojNFE3hok60BmemhYnt7zPAB3y1u45VghR0Q8QCCF6eGqluEQpIZlJB9AZntpAeGoMPYSAzvDWMFEHumKvk1su1gEdCs3NJM5n0C8QCCF6kKgDXdPaRJ1JB9C2vUr5magDHWr1mGFuBrSp1fMZ3mcQvQiEED1I1IGuaa2UnxAVaBsTdaBrvLV7lldyzAAd22tuxsU6RD8CIUQPJupA17R2zDDpANpGs0+ga1rtIVQXufEA0Y4VD+hnOhUIGWMGGWOeM8bUGWM2G2PObeNxycaYu40xO4wxu40xLxpjhoZ3yBiwWk464uIDu1owUQfa1vLkNilNkiFEBdrTarUDE3WgTSxNBrqGpcnoZzpbIXSHJK+kQknnSbrLGDOplcddL2mepAMlFUmqkvT3MIwTsaDlpEMK/DJlog60reXJrTGBY4ZJB9C2lhceElMCu/RxzABta+3klrkZ0DaWWaKf6TAQMsakSTpd0s+stbXW2g8k/UfSBa08fKSk/1prd1hr3ZKekNRacATsr+WkQwpMPJioA21r7Zhhog60reWFB2MCFQ9M1IG2tTy5TUgO7AbL3Axond8fOD5Ymox+pDMVQuMkNVpr17a4bYlaD3rul3SIMabIGJOqQDXRqz0fJmJCy0mHFKwQ4hco0KaWW2hLVAgBHeHCA9B5/ibJV9/KhQeOGaBVvmB/rdDcLD5Rik/mYh2iWkInHpMuqXqf21ySMlp57JeStkraJqlJ0jJJ327tRY0xV0q6UpKGDx/eyeFiQPPuO1HPoHEh0B5vHRN1oLOafFKTZ/8LDwRCQOtCx8ZeFx4yOGaAtoTOW/a78MD5DKJXZyqEaiVl7nNbpqTWos47JCVLypWUJulZtVEhZK29x1o7y1o7Kz8/v/MjxsBkbeBEdr9qBxJ1oFWNXqnJS4UQ0FmhY4MQFegcT1vHDHMzoFWhY4YLD+hHOhMIrZWUYIwZ2+K2qZJWtPLYaZLmW2t3W2s9CjSUnmOMyevxSDGwNbol28REHeis5pPbFpOOZPqhAG3ytFbtwEQdaJOXk1ugS0IXsvdd8cDcDFGsw0DIWlunQKXPL40xacaYQySdLOnhVh7+maQLjTFZxphESddIKrPW7gznoDEAkagDXRO6QktVHdA5rVYIMVEH2tRmhRDHDNCqNi88MDdD9OrstvPXSEqRVCHpcUlXW2tXGGMOM8a0fFf4viS3Ar2EKiWdKOnUMI4XAxWJOtA1LH8BuqbNCw9M1IFWedu68MD7DNAq5mbohzrTVFrW2t2STmnl9vcVaDod+nyXAjuLAV3TVqLuqwts4RjX2ewSiBEsfwG6ptULD0zUgTa1WiHExTqgTW1deHBuicx4gE7gLBvRoa1EveV9APZoPrndp4dQo1tqaozMmIBoRogKdE2bPYSoqgNaxYUH9EMEQogObSXqEpN1oDWtntymBf5msg7sr60LD03ewK59APbmaeXkNikt8P5jbWTGBESzVudmGZzLIKoRCCE6tNVDSCJVB1rT2sltc4ha1/fjAaJdqxcegh8zWQf2F3ovSd4nRLVNgWpUAHsLvZckpu25LTlYiUqIiihFIITo0FYpv0S1A9Ca1k5uQ8cPISqwv7ZK+aU9lRAA9vDWSiZOSkzdc1sSF+uANnlqA+8xLXufJqVL1i/56iM3LqAdBEKIDu31EGLSAeyvtZNbqh2AtnlqpbgEKSF5z20sTQbaFjq5NWbPbclcrAPa5K3Ze14mcT6DqEcghOjQ2k4WTNSBtnlqpfgkKSFpz21UOwBt87ZzcstEHdhfaye3SRwzQJs8tXuvdpC4WIeoRyCE6OCtkRJSpPiEPbfRQwhoW+jktiVCVKBtntq9l1hKLSbqhKjAflo7uWUHWKBtrc3NuFiHKEcghOjgqd2zQ1IIOyYBbfO0N+lgog7sx1vT9vsMxwywP29rczMu1gFtam1u1nw+wzGD6EQghOjgba3EkpNboE2tHjOUJQNtai9E5ZgB9tfuMcPFOmA/3pq252aczyBKEQghOnhq9/zCDElKk2SYqAOt8bTXuJCJOrCf9kJUJurA/rytLbPkYh3QJi48oB8iEEJ0aG2ibkzglyqTDmB/rR0zCQ7JxDPpAFpDtQPQNe1deOB9BthfuyseeJ9BdCIQQnRobdIhBX6pMlEH9tfaya0xgWOGEBXYX2vVDgnJ+v/27j5c1rss7P33Xq9J1t4JDUQ8IJxwYbAYMCgR5CWY1qO1aguKtJdQQKUgUO0LFEVbWqVYq9bj0VNAKUet1AutFBREFHvUI1ioBjVKeIlHMBUwJMdAsmcnmVkv9/njmVlr9t5rr/U8M8+aeWZ+38915drZM88Mv3DPb+b+3b+Xh5V1+4x0GFfVSc24QkgLyIKQuuGwpANcISRdzGGDW6iSdZMO6UJHTjzYZ6QLHDa4XV2rVqM6WSeda3cHdu5zm6UWjgUhdcNhSQeYqEsXc1SfcVmydK7MIyYeTpuoS+fb3Ybd/kUmHpysky4wGq+cn5utrML6ZY5n1FkWhNQNF13tYNIhXSDz8DtZQNVnTDqkc+30YW/HiQeprtHEgn1GqmfUJy6648HJOnWTBSHN395e9SV6aNLh9hfpAtv3Qe4dsULIPiOdYz9Rv9jEg4m6dI4jB7enYXB2tu2Ruq5/kRVCYBFVnWZBSPO3PUwqrKhL9Rw3uDXpkM7lagepmeMGt+Zm0rmOnXjwd0bdZEFI82dFXWrmyMGt56FIFzh2Kb99RjqHEw9SM8flZvYZdZQFIc2fFXWpmeMGt979RTrXkRMPJurSBY5bVWduJp3LM4S0oCwIaf6Oq6jv9qu7XUiqHLuU30RdOocTD1Izx0482Gekc7jjQQvKgpDm77ikA6yqS+OOG9zubVd3VZJUOfYMoTPV3fskVY5bVWcRVTqXEw9aUBaENH/HVdTBqro07rhVdWDiIY07buIh96q790mq1DlDyCKqdMAzhLSgLAhp/o5LOsDBrTSuzqo6zxGSDhy32gFM1qVxx62qI731vDRu0INYgfVLL3xu4xRs3wt7u7Nvl3QMC0KavzqrHUzUpQN1VtVZRJUO1Jp4sIgq7Rv0YGUN1jYvfG7D1dvSBfo92DgNERc+544HdZgFIc3faIbpyNUOfoFK+0Z95rCCkH1GutCgB6ubsLp+4XP7ibqrHaR9/V71e3Lo4NatydIFBmcPH8vAWG7m74y6x4KQ5m80cF3fuvA5VztIFxqcgbVLYXXtwudM1KUL9Xs1EnX7jLRv0Dt8RR24NVk6zODM4RN1YG6mTrMgpPkbzUKtHPJxNFGXLlRrcGuiLu0b9EzUpSb6Rw1unayTLmBupgVlQUjzZ0VdaubIwa2JunSBvqsdpEYGrqqTGjE304KyIKT5s6IuNeP2F6mZIyceTNSlC/SPGNx6B1jpQrUmHuwz6h4LQpq/oyrqa5vVXS5MOqQDg+GdLA5joi5dyCKq1MxRK4Q2nayTLuCOBy2oWgWhiLgyIt4WEWcj4raIePYR135JRPxORPQi4tMR8U/aa66W0lEV9Yjqy9VEXTrQP3PxRH1tA1Y3TNSlcUdNPFhElS7Ud+JBasQdD1pQdVcIvRYYAA8GngO8PiKuPf+iiHgQ8GvATwIPBD4feHc7TdXSOqqiDlWxyKRDOnDU4Baq5+wz0oGjEvXVtequfSbq0oHBERMPrqqTLuQZQlpQxxaEImILeCbwqszsZeZ7gbcDzz3k8pcBv56ZP5eZ/cw8k5kfbrfJWjpHJeowXCFkoi7tO67PbLqqTjrHUdssoeozJupSJfPoM4RWVmB9yz4jjewMYHdw8dxs/TKIFXMzdVKdFUKPAnYy89axx24GLlghBHwZcFdE/PeIuCMi3hERD2+joVpix612MFGXznXc4HbDVXXSvsyjz0MBtyZL43buh9ytMfHgZJ0EHPx+XCw3Gx2BYW6mDqpTEDoF3HPeY3cDh33iPw94PvBPgIcDHwfefNibRsSLIuKmiLjpzjvvrN9iLZ9aK4T8ApUA2Ns7fnBroi4d2L4Xcs+JB6mu/jGDW3BwK43rD3MudzxoAdUpCPWAy8977HLgsE/0fcDbMvP3M/N+4PuAJ0fEFedfmJlvyMzrM/P6q666qmm7tSx2d2DnPpfyS3Vtn63+9AwhqZ5RXzgyUT/txIM0MqgxuHVrsnRgf4WQEw9aPHUKQrcCaxFxzdhj1wG3HHLtHwM59vc85BrpwMBEXWqkzuB28xQMzs6mPVLXHbeUH4aJujO3EnDw+3HkxINbk6V9tSYeLKKqm44tCGXmWeCtwKsjYisingI8HXjTIZf/NPD1EfG4iFgHXgW8NzPvbrPRWiK1K+om6hJQb3BrEVU6UHspv31GAhpMPJibScBBX3DHgxZQ3dvOvxS4FLiD6kygl2TmLRFxQ0Tsf7Iz8zeB7wHeObz284Fnt9tkLZUmFfV0wZlUa3Br0iEdcCm/1EytiQf7jLTPrclaYGt1LsrMu4BnHPL4e6gOnR5/7PXA69tonApQJ1Hf2IK9Hdjpw/ols2mX1FX7fWbr4teMDi7MrO5sIZWsX+d3xhVC0r7RxMNRvzOeISQdqJWbbbnjQZ1Ud4WQdDL2k46jZm6HM1QmHlK9we3mqequStv3zaZNUpfVOqtuOLjd25tNm6Quq9tnXCEkVercmc8iqjrKgpDmq27SAVbVJRjrM8cs5R+/VipZrYmH4XPbHsYu1Zt4OF3dJXZvdzZtkrqszp35LKKqoywIab7qrnYAB7cSNFtVZxFVajjx4O+M5MSD1FC/ByvrsLZ58Ws2T8NuH3a3Z9cuqQYLQpqvJkmHibrUbHBroi7VX+0A9hkJqsmE1U1YXb/4NZvmZtK+Qe/ovAzc8aDOsiCk+fIMIamZUfK9fsxhn+PXSiUb9GD9MlhZvfg1JurSgSaDW3Mzqcq3jjo/CNzxoM6yIKT5GvQgVmD90otfY6IuHRj0qj6xcsTX94ZFVGlf/8zRkw5goi6N6/dq9JnTB9dKpWu0Qsg+o26xIKT5GlXUj7o1tom6dKDJ4NYiqmSiLjU16B29lR/GVgj5OyPVy82crFM3WRDSfJmoS824lF9qpslqB/uM1HDiwT4jeYaQFpkFIc2XFXWpmVqDWxN1aV+T1Q4m6pITD1JTTXIz+4w6xoKQ5qtO0rG6Xt3twkRdariU36RD8gwhqaFGZwiZm0nNJh78nVG3WBDSfNVJOqBK1k3UpXp9ZmW1uquSibpUb+JhdNc+E3XJFUJSU25N1gKzIKT5qlNRh+pL1kRdqg7wPC5Rh6rPmHRINYuoK/YZaaTOLbTXL63uEmtuptJl1svN3JqsjrIgpPmqvULotIm6BM1W1ZmoSw0nHkzUVbjMeiuEIqqikbmZSrd9H+Te8bnZ2iasrNln1DkWhDRfdZIOMFGXRgZnXSEk1bW3C9v3ujVZqmtwFkgnHqS6BmerP4+beIhwx4M6yYKQ5mvQ5AyhsyffHqnLdndg577jl/JDlZiYdKh0+4l63SKqvzMq3KgoWrvPOFmnwo36QO0dD/7OqFssCGl+dgawO3C1g1SXibrUzKjP1E3ULaKqdKM+UGviwdUO0n4fMDfTgrIgpPkZmHRIjTQZ3G5s2Wek/US95hlCJuoq3agP1BrcbjlZJzWaeHA8o+6xIKT56TdJOjy4UGo0C+V5KFLDpfwm6tLBCqGauZl9RqVrPPFgn1G3WBDS/DStqA961d0vpFI1WVVnoi5NsJTfPqPCNdmavOmqOsmJBy06C0Kan6aJeu5Vd4uRStVkVd3mKdg+C3t7J9smqctcyi810+QMIe+YJDUcz7jjQd1jQUjzs19Rr3mGEJh4qGyNzhA6de5rpBI1Wsp/urqL3+7OybZJ6rImZwi5NVmaYOLBVXXqFgtCmp+mFXUw8VDZmp4hBPYZla3pUn6wz6hsTc8Q2h1Ud42VStWoz3gEhrrHgpDmp2lFHayqq2xNzxACV9WpbE23JoMFIZVtktzMPqOSDc7A2qWwunb8tZunYG8Hdvon3y6pJgtCmp+mp/KDSYfK1vQMIfDAT5Vt0INYgfXLjr/WrclS9flf34KVGkOEDSfrJPq9enkZuONBnWRBSPMzyVJ+E3WVbNCDWIW1S46/dsM+I9HvVX0h4vhrTdSlKjerO7h1hZBUff7rjGXAHQ/qJAtCmp9+D1Y3YG3j+GtN1KWDWag6g1sTdaka3JqoS/X1Gwxu3ZosNVwhZG6m7rEgpPmxoi41M+jVOz8ITNQlMFGXmho06DNOPEjNcjN3PKiDLAhpfkzUpWb6kyzlt4iqgk008eDvjArWbzLxYG4mNcrN3PGgDrIgpPlptNrBRF1qNLi1z0ge9ik1NckZQv7OqGTueNCCsyCk+WlSUV9Zqe56YaKukjUa3G4BYZ9R2SZaym+iroJNcoaQvzMqmTsetOAsCGl+mlTUofqyNVFXyZr0mYjqWmduVbImEw9rl1R38TNRV8kmOUPI3Ewl8wwhLbhaBaGIuDIi3hYRZyPitoh49jHXb0TEhyPiE+00U0up3xuuYqhpwxVCKlyTmVuoEg/7jEo2aPA7YxFVgsHZ+r8za5uwsu7vjMq1t9fsd8YVQuqgtZrXvRYYAA8GHge8MyJuzsxbLnL9K4A7gZrlUhVp0IPNBh8RE3WVrsnZDlD1GZMOlcwiqlTf3i5s3zvB6m37jAq1fbb6s25utroOq5uuqlOnHLtCKCK2gGcCr8rMXma+F3g78NyLXP8I4B8AP9BmQ7WEGifqp03UVbZJBrcm6irV7jbs9ieYeDBRV6FGOVajiQdzMxVslGM58aAFVmfL2KOAncy8deyxm4FrL3L9/wl8D3DflG3TMsucbLWDibpKtdOHvW1XCEl1jX4vTNSleiYd3JqbqVT7RVR3PGhx1SkInQLuOe+xuzlkO1hEfD2wmplvO+5NI+JFEXFTRNx055131mqslsj2fZB7JupSXfuJeoOkY/O0SYfKNdFqBxN1FWzSwa25mUo10cSDq+rULXUKQj3g8vMeuxw4ZzpguLXsh4B/XOd/ODPfkJnXZ+b1V111VZ2XaJlYUZeaGQy/chuvEHLmVoWaaLWDiboKNvEKIfuMCjXxxIO5mbqjTkHoVmAtIq4Ze+w64PwDpa8BrgbeExG3A28F/peIuD0irm6hrVomVtSlZkzUpWaceJCamXjiwT6jQnmGkJbAsQWhzDxLVdx5dURsRcRTgKcDbzrv0g8CD6O6C9njgH8IfHr473/RWou1HCatqG/fW90FQyrNpH3GpEOlmvgMIWduVahJV9VZRFWpnHjQEqizQgjgpcClwB3Am4GXZOYtEXFDRPQAMnMnM28f/QPcBewN/+4IXueatKIODnBVpknPENq5H3Z3TqZNUpd5hpDUzMRnCFlEVaG8eYGWwFqdizLzLuAZhzz+HqpDpw97zW8DnzdF27TMJk06oErWL7mi/TZJXTbpUv7Ray/9a+23SeqySSce9raru/qtbZ5Mu6SumnRw2+9Vd4+NOJl2SV010cSDq+rULXVXCEntmvQMIbCqrjJNs6rOxEMlmmjiYXitfUYlmnRVXe5Wq1Gl0ox+K9a36r9mtEIo82TaJDVkQUjzMWnSASbqKtM0q+osoqpEk652ALfAqEz9HsQKrF9W/zWbFlFVsEGv+o1ZaTCk3jgFJAzOnlizpCYsCGk+Rl+CniEk1TOYYIWQRVSVbHAWVtaabf3aL6KaqKtAo8Ftk61fG8OVERZRVaJRn2li098ZdYsFIc3HJNtfXO2gkvV7sLoBaxv1X+NqB5VsksGt2yxVsv4Eg1snHlSyfq/Zbgc42JrseEYdYUFI8zE4A2uXwmqtc80rLktWySaZhTJRV8n6vWZbLGEsUbeIqgINzjQf3Lp6WyWbZoVQ398ZdYMFIc3HRBV1VzuoYJP0GRN1lWxwZopE3T6jAk20QsjJOhVsookHczN1iwUhzcdUFXW/QFWgQe8g8a7LRF0lm2riwT6jAg2mmXhwsk4FcuJBS8CCkOZjkkR9/bLq7hcm6ipRf5ql/CbqKtBEEw8WUVWw/iQTDw5uVTDPENISsCCk+ZhktUNElXiYdKhEkwxu1y6BWLXPqExuTZaa8QwhqRnPENISsCCk+ZhktQNUX7om6irRJIPbiOo1Juoq0SQTD2sb1d38LKKqRJ4hJDXj1mQtAQtCmo9JKupQfemadKhEkwxuoXqNfUYlmmriwT6jAk1yhtDqWrUa1ck6lWZ3B3buc5ulFp4FIc3HJBV1MFFXuSbtM5uuqlOBMp14kJrYGcDuYMKJh1MwONt+m6QuG41HmuZmKyuwvuV4Rp1hQUjzMelqBxN1lShzsjtZgOduqUw7fdjbmXDi4bSJusoz6eB29Bp/Z1SaUZ+ZeOLByTp1gwUhzd7e3mTLksFEXWXavg9yb4oVQvYZFWY/UZ904sFEXYUZfeYnmngwN1OB+lMUUd3xoA6xIKTZ2x4uK7aiLtUzzSyUK4RUotHvhIm6VM/UK4TMzVSYqSce/J1RN1gQ0uxZUZea2R/cTpJ0OHOrAk29lN8+o8L0pxjcmpupRFNNPJibqTssCGn2rKhLzUy9QsiZWxVmqokHE3UVaDDF4NbcTCXyDCEtCQtCmr1pK+q7fdjdbrdNUpdNM7gdnSGU2W6bpC5z4kFqpj/lxINFVJXGHQ9aEhaENHvTVtTBqrrKMs3gduNUdbelnX67bZK6bOozhM5YRFVZpjpD6LRFVJXHiQctCQtCmr1pK+pgVV1lmWZwOzp3yD6jkkw78ZB71d39pFK0cYaQRVSVxJsXaElYENLsTVtRB6vqKsu0ZwiBq+pUFicepGamPUOIhMHZVpskddqgB7EKa5c0f+3madi+F/Z222+X1JAFIc3etGcIgYm6yjLtGUJgn1FZplohNPydsYiqkvR7sLIOa5vNX2sRVSXq96ocK6L5a+0z6hALQpq9/UR9q/lrR68xUVdJRn1mfZI+46o6Fah/BlY3YXW9+WtHvzMm6irJoDdZXgZjRVT7jAoy6E026QBj4xn7jObPgpBmrz/F4NbVDipR/wysXQqra81f6xlCKtGgN9mKOrCIqjL1ewe/F03tr3Zwsk4F6Z+ZvCBkbqYOsSCk2RtV1Fcm+PiZqKtEbQxuTTpUkv4UM7cm6irRNKsdPN9RJXLiQUvCgpBmz4q61MxUg1uTDhVo0MJqB7cmqyROPEjNtJGbuapOHWBBSLPXSkXdL1AVxERdamaqiQf7jArUxqo6Jx5UklYmHuwzmj8LQpq9aZKOtU1YWTNRV1n6vYM77DVloq4SuZRfaqaViQcn61QQtyZrSVgQ0uxNU1GPqL58TdRVksGZyRP11fXqbksm6irJNIm6q+pUoqkmHiyiqkDT5GbueFCHWBDS7E2TqENVTDJRV0mm7TMbWybqKss0qx1W16q7+pmoqyTTDG5Hd401N1NJWjlDyD6j+atVEIqIKyPibRFxNiJui4hnX+S6V0TEByPiTER8PCJe0W5ztRSmSTpguELIRF0FmWZwC9VrTTpUkmlWO4B9RmXJnG5wu7JSFYWceFApdvqwtz1FEfUyiBX7jDphreZ1rwUGwIOBxwHvjIibM/OW864L4HnAHwOPBN4dEX+RmT/fUnu1DKZeIWSirsJMO7jdOG3SoXJkTl9EdWuySrJzP+RuCxMPTtapEKPfh0lzs9ERGI5n1AHHrhCKiC3gmcCrMrOXme8F3g489/xrM/OHMvMPMnMnMz8K/DLwlLYbrQU3ODt9oj442157pC7b24PtKfuMibpKsn0vkC1MPPg7o0JMO7gFi6gqy6iQM/V4xj6j+auzZexRwE5m3jr22M3AtUe9KCICuAE4fxWRSra7Azv3Tb+U36RDpdgeDkqnOkPIPqOC9NtI1D2rTgUZTRi4NVmqZ/RZn3biwdxMHVCnIHQKuOe8x+4GjhvRf+/w/X/6sCcj4kURcVNE3HTnnXfWaIaWQisVdRN1FaSNwa2JukoyaGG1w6Zn1akg/RYGt25NVklamXgwN1M31CkI9YDLz3vscuCimVJEfDvVWUJfm5n9w67JzDdk5vWZef1VV11Vt71adK1V1E3UVYg2Brcm6ipJv4XVDibqKkkbk3VuTVZJRp91dzxoCdQpCN0KrEXENWOPXcdFtoJFxLcCrwS+IjM/MX0TtVTarKhnttMmqcvaGNy6QkglcSm/1IxnCEnNuDVZS+TYglBmngXeCrw6IrYi4inA04E3nX9tRDwH+LfAV2bmx9purJZAW0v593aqWz5Ky66Nwa1FVJXERF1qprUzhDyIXYVwx4OWSJ0VQgAvBS4F7gDeDLwkM2+JiBsiYjxjeg3wQOD3I6I3/Ocn2m2yFlorS/mHxSSTdZWgrTOEcm949yVpybU18TDoVXf5k5ZdK2cIuRJVBdnPzaZcVWefUQes1bkoM+8CnnHI4++hOnR69PdHtNYyLae2KupQFZe2HjR9m6Qua+UMoVGf6cHG1vRtkrqsrTOEoLrL3zQJv7QIWjlD6HQ16bC3Cyur7bRL6qr9M4TcmqzFV3eFkNSOts4QAqvqKkMrZwi5qk4FaXXiwT6jArR1hhD4O6My9HuwugFrG5O/x8Zp2O3D7nZ77ZImYEFIs9XWUn4wUVcZ2jpDCNyrrjK0dQttcHCrMgzOwNolsFpr48DhzM1UkkFvut8YOHfHgzRHFoQ0W54hJDXT7wEx3VavTWduVZBBD9a3YGWKFMdEXSXptzC4dYWQStLvTTeWAfuMOsOCkGZr0INYrWaiJmWirpKMZqEiJn+PURHVmVuVoH/GRF1qYtDC4HbT3xkVZNCbbrcDuKpOnWFBSLM1qqhPNbg1UVdB2hjcukJIJWl1Kb99RgXotzC43c/NnKxTAVqZeHDHg7rBgpBmy4q61Ewbg1vPEFJJWlnKb6KugrSyQsjcTAXxDCEtEQtCmi0r6lIzbQxuXSGkkrQ68WCirgL0z3iGkNSEZwhpiVgQ0my1UVFfXavOIDJRVwlaXSFk0qECeIaQ1EyrZwiZm6kA7njQErEgpNlqo6IOVbJuoq4S9HsHifakVlZh/TL7jMrQShF1CwgTdZXBu4xJzbg1WUvEgpBmq41EHaovYRN1lWDQwlJ+qN7DmVuVoI1EPcKJB5Vj0MLEw/qlECvmZlp+me3kZm5NVkdYENJstbHaAaqquom6StDWqrpNB7cqRKsTDybqWnJ7e+30mQhzM5Vh+z7Ivelzs7VNWFm3z2juLAhpttpa7WCirlK0NbjdcFWdCrC3C9v3tjTxYBFVBdg+W/3Z1sSDvzNadqPfBXc8aElYENJseYaQVN/uDuzc387gdtOZWxXARF1qpt9in9k4VU38SctsNCHtjgctCQtCmp2dPuxtm6hLdY0Sa88QkuoZ/S448SDVM/qMtzLxYG6mArQ+8WBupvmyIKTZaXUWastEXctvv89sTf9eniGkErSZqLvNUiUYDUbb+J2xiKoStJmbOZ5RB1gQ0uyMVju0MnN72kRdy2/Q8moH+4yWXZsTD5tuf1EBWl3tYG6mArS5qs7cTB1gQUiz03qi3qtu/Sgtq/0+4xlCUi2tTjyYqKsArW+ztIiqJddvcTu/q7fVARaENDttr3YgYXB2+veSuqrVwe1Wdfelvd3p30vqqpOYeJCW2aDFiYeNLYuoWn6tjmdcVaf5syCk2Wl1tcPwS9hkXcus7bu/gH1Gy63Vpfynq7v87e5M/15SV/VbnHiwiKoSuDVZS8aCkGan7TOEwKq6llubs1D7RVRX1WmJtb2UH0zWtdxGvwmtTDycht0B7Aymfy+pq07i5gUegaE5siCk2Wm7og4m6lpuba6qs4iqErS+NRn7jJZb27fQHn9PaRn1z8DapbC6Nv17bZ6C3K1Wo0pzYkFIszOahWrrVP7x95SW0YmsELKIqiU2OAuxAuuXTf9erqpTCfo9WN+ClRaGBPtFVH9ntMQGZ9vJy+Bgss7fGc2RBSHNzuAElvI7c6tlNuhBrMLaJdO/l6sdVIJ+r/qsR0z/XvuJun1GS2xwpr3BrSuEVIJBr52xDIyNZyyian4sCGl2+j1Y3YC1jenfy0RdJej3qmShjcGtibpKMDhjoi410W9xcOtqB5VglJu1wRt+qAMsCGl2rKhLzQx67ZwfBJ4hpDKYqEvNDFrsM+ZmKkGbuZk7HtQBFoQ0OybqUjP9k1jKb6KuJXYiEw/+zmiJ9duceDA3UwHazM3c8aAOsCCk2Wl1tYOJugrQ5uDWPqMStDrxYKKuApzEGUL+zmiZueNBS8aCkGanzYr6ykp1VwwTdS2zVge3W0DYZ7TcTmQpv4m6ltiJnCHk74yWmDsetGQsCGl22qyoQ/VlbKKuZdZmn4mo3suZWy2zNice1i6p7vJnoq5l5hlCUjOeIaQlY0FIs9NmRR2qwa2JupZZvwebLSUdUPU/zxDSMmu7iLppEVVLrs0VQmubsLJubqbltbfXbhHVVXXqAAtCmp02K+pgoq7l1+YttMEVQlp+rU88nDZR1/La3YGd+9qfePB3Rstq+2z1Z1u52epatRrVVXWao1oFoYi4MiLeFhFnI+K2iHj2Ra6LiPjBiPir4T8/GBHRbpO1sEzUpWba7jObrqrTEtvdht3+CUw8mKhrSY1+D1qdeDA30xIbFTvd8aAlslbzutcCA+DBwOOAd0bEzZl5y3nXvQh4BnAdkMBvAB8HfqKNxmqBZba/2mHzFNzzqfbeT+qSnT7sbbtCSKprVLgxUZfqGZzA4NYiqpbZfhHVVXVaHscWhCJiC3gm8JjM7AHvjYi3A88FXnne5c8HfiQzPzF87Y8AL6SUgtAdH4ad++fdim7aGUDutZ+o33sXfOoP23tPqSvuv6f6s9Wl/Kfhzo/aZ7ScendUf7Y98dC7wz6j5fSZ26o/2554OHO7fUbL6c5bqz/b3vFwz6fsM131wGvajXcH1Vkh9ChgJzNvHXvsZuDLD7n22uFz49ddO3nzFsxbvhXu+NC8W9Ftlz2ovffaugru+QS84cb23lPqmsse2N57bT0IPvqr9hktt62Wf2c+9tv2GS23tvvMR99pn9Fya3U88yD42G/ZZ7rqBb8BD3vCvFtxoiIzj74g4gbgFzPzc8ceeyHwnMy88bxrd4FrM/Mjw79fA9wKrOR5/0MR8SKqLWY8/OEPf/xtt902/X/NvH38PS4tP8rKOjzihuouFG2477PwP99PtTtRWkKrG/CIp8Hqejvvd+9d8Bf/o533krpobROuflp1UGcbenfCJ29q572kLlq/DK6+AVZaus/MmU/Dp/6gnfeSumjjFFz91OpOlG24+5Nw+x+3815q38OeCJddOe9WTC0iPpCZ1x/6XI2C0BcDv5uZl4099nLgxsz8O+ddezfwlZn5e8O/Px747cw8cs/D9ddfnzfdZMIlSZIkSZLUlqMKQnWmA24F1oarfUauA84/UJrhY9fVuE6SJEmSJElzcmxBKDPPAm8FXh0RWxHxFODpwJsOufxngZdFxEMj4iHAy4GfabG9kiRJkiRJmlLdDcMvBS4F7gDeDLwkM2+JiBsiYvzQnJ8E3gH8CfBB4J3DxyRJkiRJktQRtU5dzMy7gGcc8vh7gFNjf0/gO4f/SJIkSZIkqYNauqWAJEmSJEmSFoUFIUmSJEmSpMJYEJIkSZIkSSqMBSFJkiRJkqTCRHUO9JwbEXEncNu829HQFcDdNa57EPD/nXBb1A2LFuu6n2FdaNFivaxm8Rk21uWYR6z9Hp4P+3W7uvw5NtblmCbWXf4M60L26wsd9xn+XzPzqsOe6ERBaBFFxBsy80U1rrspM6+fRZs0X4sW67qfYV1o0WK9rGbxGTbW5ZhHrP0eng/7dbu6/Dk21uWYJtZd/gzrQvbrC03zGXbL2OTeMe8GSFPyM6xF52dYi87PsJaBn2MtOj/DWnQTf4YtCE0oM/3i0ELzM6xF52dYi87PsJaBn2MtOj/DWnTTfIYtCJ28N8y7AZoZY10OY10OY10OY10OY10OY10OY10OY90izxCSJEmSJEkqjCuEJEmSJEmSCmNBSGogImLebZAkSZIkaVoWhKYQEU+JiCuG/26hYIlFxPMj4qHpHsulFxHPjYhnRMTmvNuikxUR3xQRPx0RD5l3W3SyIuK6iNiadzt08iLiCnOyMkTEAyPCsUxB7NvLLyJOzbsNpfFLdEIR8WrgPcC3AFgoWE4RcUNE3Ax8H3C5P0TLKyL++jDWrwZ2gUvm3CSdkGG//iDwn4CvA+6ec5N0QiLiy4ax/lngVyLihfNuk05GRDx5+B3+ZuDNEfGwebdJJyMinhQRHwJ+HviFiHjkvNukkzH8Dn9zRDxr3m3RyRrmZu8HfiYifjYirpx3m0phQaihsYLAA4B3A0+MiC867zktuIjYiIjXUsX4pzLz6sz8sIW/pfZ84Fcz8xGZ+Y7MtEiwRKKyFRG/C/wi8LrM3AB6wONH18yzjWpXRFwD/Efg9Zl5HfA+4Ksi4tHzbZnaFhFfCLyRKt4vB64Gfjwi/sY826X2RcRDgZ+give3AVcAPxARXz3XhqlVEbESEd9MVfR7LPC1EfGgzEx/q5dLRKxFxL8Gfo6qoP/vgC8GvjsiNubauEJYEJrcLnAb8FfAPwBXCS2TzBwAjwJ+MjN/DCAivi4iHhURq/Ntndo23B72VcCvD//+8oh4WUR8aUSszbd1akNWzgLvBR6Wma+LiM8BPgp8weiaebZRrXsMcCdVkglVonkN8Jdza5FOyo3ABzLzP2Tmh4FvBh4O/CO3/y6dz6da1fnGzPwY8ELgE8B3RMRlc22ZWpOZe1Tj1H8GfA+wBTx7+Jy/1cslgIcCL8jMH8vMm6ji/vz5NqscFoSOMRoMjooAw8r0BrBONUPxh8C1EfHE+bVSbRiL9Sh5/CHgsRHx+oj4c+A7gXcBb4yIa+fTSrXh/H4NPIgqwdyIiPcBfwv4MuDHge+eSyPVivP7dWZ+V2ZuR0Rk5h3A5cCVw2ss9i6wsVivDx/aoUoynzz8+5OGj/0tf7MX2yGxBnji8LGVzPwI1cTdlwJ/b/YtVFsi4tERcXpsVcjlwDWZeQ9AZt4G/FcgqYpDWlBjsR6NT38F+OXhn38CPG2Uf3t21GIbj3VmbgP/B/DfhyvDVqkmc/6cYX6mk2VnuoiIuHa4F/2/DB/K4eMxXD3yuVSzFG8BbgFeGRHviIiHz6XBmtghsd4ByMzfAP6UKsl8cWY+Dfgmqu2Cf8+ZqMVzsX6dmZ8ELgO+F3hvZn4V1cq/7weeHRGfP4fmagqHxHp77Lng4Pfv14CvAcjM3Zk2Uq04JNZ7AJn5DuDHgGcOi/qvoVot9HeA17t1bPFcLNbAL1EV9P81sBYRXwLcDvwm8NfPKxxpAUTE4yLi94D/DLwd+C7Y79d7EfGPxi6/Gfg94EtieLMXLY5DYv2dAJl5R2buDVcLvQu4H3jO8Lm9i72fuuu8WL+Dg1h/aLiKO4a52GOAM5l5+/xaWw4LQoeIiMcBP01VDPi6iHhKZu5FxOpwhdA61WqC3xqeM3I98JXASmb+T6vWi+Misd6NiNGBwv8KeH5m/lpErGXm71EdJn5jZt47n1ZrEkf061Gs/wXVqqC/FhHrw8Lvh4A7gC+cR5s1mSNivQb728dGxZ87gc8Ot49pwRzxHT5aEfY64KeADwCfl5k/SpWA3gX8b/NptSZxRKxXMvNTwEupBou/PvznjcD/Czx2tCpwTk1XQxHxdVRnx7ydapXX24Evj4jRaq8fBF4+KvRlZg/4C+ARVOfCaUEcEetnDZ8PgMz8feD9VLsy/sbwuUvn0mhN5JBY/zJjsYZzJuZuAH5/7LWOrU+Q/+ce7i7gtcALhn++EaoP6djStlPAOyPiz4DPUN3BJCPiIVatF8rFYn3/aEtJZv7Jea+5AxiMFRK0GI6L9f9NtSz5C6nOGYHqjLAN4IOzb66mcLFY74wuGBsc/inwBKrvcS2ei8W6P3bN04GHDIu8APdQnUfx/hm2U9O7WKz3hrnZr1IV9V8BPDIz3w7cB3x6Tu3V5K4EfiAzXzPMqX+GagvgaKXnf6GK6xvHXvOnVOMac7PFcrFYj1brjx8i/S6qOD8rIn4UeG1EPHAObdZkjow1VFv3h4XeR1Ot/CQivpfqgOmtWTe4FBaExox94XwSePNw9c+rgQdFxIuHz60MZ5k/RDWAeHFmPpPqrjXvA/qo82rGenXs+ksyc2dY3X4V8AuZef9MG62J1Iz1aDvBt1J9L/5MRPww8EdUff12Z5e7r06sx1cJDa99PzCguv28FkTNWI/Og/u/gCdExL8aPvdHVIfQ3jrbVmsSTX6vM/Mu4A8z857hapIXMxxUeBBt942tAngXB4PB1cz8DPBgqvODGG4jeR7w1RHxCxHx3VRFol8HXL29AGrE+vTo2lHfzcw/ozq24cVUB8n/aGb+1cwarYk0jPUu8DlU3+lfFhEfAb4BeOtwS5lOQPj7WBmuEMjxv8N+ZfrbgB/KzCvGnn8wcMfoNee/Xt01QaxXgadSnUXxQOCfZ+YvzLjZmkCTWA+3BO5ExCOpbnd5I/AeY70YJujXMXzukVRbiP73zPzozBuuxhr265XhCpJnA48HrgP+o/16MTTt18Nrrga+j+rOkf/UWC+Gw/Lose/phwC/DTwtM28fe/xJVL/XXwG8JTPfPPuWq6kmsR49R3XO478BXkR1lMN/nXGzNYGmsR4+//VUB8V/BPj+zPw5dKKKLAgNZ4gfmtWdCc5//HmZ+VPjH+BhQeADwO9k5j+OiMtzeHcDC0Hd1lasI+Jy4GtNNrqrhVhfMZx5Vse1+R2ubmsh1g/IzM/OvOFqrOXc7EmZ+b5Z/zeongli/XjgxzPzKaPrcmwLsLqrhVivDleNEBFPyOosT3VQW/16uOji72fmj8/6v6FUxW0Zi4jnUW31+hcR8bnDx0bLkb8C+JoYu/Xw8IO7C3wz8JKo9qzeHhFPAZcgd1lLsf50RDw1M++xGNRdLcX6L0f9Wt3V9ne4uqulWH/KWHdfi/36BgCLQd3VNNZDT2N4wGxEvBz4QER80YyarAm1FOs/iOpAeSwGdVeLsb4uMz9tMWi2iioIRXX+y7dQnXB+DdXtxMeLOu/OzG/MzN3RY2PPPYJqP+MTgb+dmb8708arkRZj/dWZ+d6ZNl6N2K/LYazLYazL0XKs3zPTxquRSWI99DeBh0TEzVRFwBdn5h/PruVqquVY/9HMGq7GWoz1t2XmzbNruUaKKAiNVSTfS3V2wAuBjwPPiOr8CODggxvDgyhjeAhWRPxNqr2ML8nMJ2fm/zPL9qs+Y10OY10OY10OY10OY12OaWIdEQ+guuPQE6m2lzzWFWDdZazLYayXx1KfIRQRfzer246OHyw5+vNaqttVvhF4Ux7cjvaw99nfv6puMtblMNblMNblMNblMNblaDHW35iZb5lRszUBY10OY718lnKFUER8dUTcBrwpIp4z/tzww7qambcA7wb+LtVdR8ZfvxURN0fEtwxfY8LRUca6HMa6HMa6HMa6HMa6HC3G+h8OX+OgsaOMdTmM9fJauhVCEfEw4GXADtADngR8Y2b2IvZvczeqYl4JvA34pcz80eHytk8Pr31oZn5yfv8lOo6xLoexLoexLoexLoexLoexLoexLoexXm7LWBBaBZ4AfBj4AuBfAu/LzH87+sAOr1vPzO2IeDrwPcADgM8BHp+ZH5tP69WEsS6HsS6HsS6HsS6HsS6HsS6HsS6HsV5uS7dlbLiE+P2Z+VngZuBdwN+OiEcNq5erw+u2hy+5EfjS4XUP9sO6OIx1OYx1OYx1OYx1OYx1OYx1OYx1OYz1clvYglBErI/9+zn/HcMPZmTm/cBvUp14/vLhc7tjr/sO4IuBR2fmP80jDr7S/BjrchjrchjrchjrchjrchjrchjrchjrMi3clrGIuA74fuA24C8z8zXHXL8C/H3gRcA/A+4GrsvMX4qItczcOek2azLGuhzGuhzGuhzGuhzGuhzGuhzGuhzGumwLs0IoItYi4rVUFckPDP/8lxHx/OHzcchrIjP3gJ8HPgr8D+BWYGt4iXeo6CBjXQ5jXQ5jXQ5jXQ5jXQ5jXQ5jXQ5jLYC1eTeggYdyUH38REScAv4QuBKqZWznv2DssVdRVTB/EviuzLznYq9RJxjrchjrchjrchjrchjrchjrchjrchhrdXuFUERcMbZ/8VPAa4Yf1m8A/gy4FuhHxI1HvMfVwOXAkzLzJaMPq7rFWJfDWJfDWJfDWJfDWJfDWJfDWJfDWOt8nTxDKCKuAf4DsA0MgJdl5p+PPf9y4DPAfwauoVri9k2Z+bbZt1bTMNblMNblMNblMNblMNblMNblMNblMNa6mM4VhCLiBcD3Aj8H/CzwOuCTwLcDd2e1Z3F07Vpm7kTEDwNPzcwnzaHJmpCxLoexLoexLoexLoexLoexLoexLoex1lG6uGXsEcCrM/OVmfkh4DnA1wMPOO/DGsDooKsecGdEbM68tZqGsS6HsS6HsS6HsS6HsS6HsS6HsS6HsdZFdfFQ6Z8A+gDDD+B9wEeAK8YvGh5YtR0RTwWeBfxwZvZn3FZNx1iXw1iXw1iXw1iXw1iXw1iXw1iXw1jrojpXEMrMT8D+Le36EfGFVO28ZXRNRDwY+HLg24DHAt+dmf9pHu3V5Ix1OYx1OYx1OYx1OYx1OYx1OYx1OYy1jtK5gtBIHhxudCNwa2Zujz336Yi4C3hrZn7FPNqn9hjrchjrchjrchjrchjrchjrchjrchhrHaazBaGIWM3MXeAJwK8NH3sJ8AXA92XmfwP+2xybqJYY63IY63IY63IY63IY63IY63IY63IYax2mswWhzNyNiDXgSuBzIuJ3gKuBb83Mz8y1cWqVsS6HsS6HsS6HsS6HsS6HsS6HsS6HsdZhOnfb+XER8VjgZuDTwI9k5r+fc5N0Qox1OYx1OYx1OYx1OYx1OYx1OYx1OYy1ztf1gtAG8O3A6zLz/nm3RyfHWJfDWJfDWJfDWJfDWJfDWJfDWJfDWOt8nS4ISZIkSZIkqX0r826AJEmSJEmSZsuCkCRJkiRJUmEsCEmSJEmSJBXGgpAkSZIkSVJhLAhJkiRJkiQVxoKQJEmSJElSYSwISZKk4kXEAyLipcN/f0hEvGXebZIkSTpJkZnzboMkSdJcRcTVwK9k5mPm3RZJkqRZWJt3AyRJkjrg3wGPjIg/Av4UeHRmPiYivhl4BrAFXAP8e2ADeC7QB74mM++KiEcCrwWuAu4FXpiZH5n1f4QkSVJdbhmTJEmCVwJ/lpmPA15x3nOPAb4B+FLg+4F7M/OLgfcBzxte8wbgOzLz8cA/B143i0ZLkiRNyhVCkiRJR/utzDwDnImIu4F3DB//E+CLIuIU8GTgFyNi9JrN2TdTkiSpPgtCkiRJR+uP/fve2N/3qHKpFeCzw9VFkiRJC8EtY5IkSXAGOD3JCzPzHuDjEfEsgKhc12bjJEmS2mZBSJIkFS8z/wr43Yj4IPDDE7zFc4AXRMTNwC3A09tsnyRJUtu87bwkSZIkSVJhXCEkSZIkSZJUGAtCkiRJkiRJhbEgJEmSJEmSVBgLQpIkSZIkSYWxICRJkiRJklQYC0KSJEmSJEmFsSAkSZIkSZJUGAtCkiRJkiRJhfn/AeJXVE59E3F3AAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1440x720 with 2 Axes>"
       ]
@@ -746,7 +754,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 686,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -814,7 +822,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 687,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -831,10 +839,10 @@
     "\n",
     "df_epis = create_empty_df(length)\n",
     "\n",
-    "for id in df.id.unique():\n",
+    "for id in df_initial.id.unique():\n",
     "    print(\"Convert data for: \", id)\n",
     "    \n",
-    "    df2 = df.loc[df['id'] == id]\n",
+    "    df2 = df_initial.loc[df_initial['id'] == id]\n",
     "\n",
     "    epi = []\n",
     "    for index, row in df2.iterrows():\n",
@@ -843,8 +851,7 @@
     "        if len(epi) == length :\n",
     "            df_row = create_df(epi,row['label'] )\n",
     "            df_epis = df_epis.append(df_row, ignore_index=True)\n",
-    "            del(epi[0])\n",
-    "\n"
+    "            del(epi[0])"
    ]
   },
   {
@@ -856,7 +863,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 688,
+   "execution_count": 15,
    "metadata": {
     "scrolled": true
    },
@@ -1099,7 +1106,7 @@
        "19  14.035776  12.314211  11.173016  10.768019   9.691997  0"
       ]
      },
-     "execution_count": 688,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1110,7 +1117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 689,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -1241,7 +1248,7 @@
        "max       1.000000  "
       ]
      },
-     "execution_count": 689,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1252,7 +1259,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 690,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -1300,15 +1307,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 691,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
     "factor = 5 # Number of copies\n",
     "dfr = df_epis.copy()\n",
+    "\n",
+    "increase_factor = 4.5\n",
+    "\n",
     "for i in range(1,factor):\n",
     "\n",
-    "    f = 0.5 + ((i - 1 ) * 0.5 / (factor-1)) # vary the anomaly by a factor \n",
+    "    f = increase_factor + ((i - 1 ) * 0.5 / (factor-1)) # vary the anomaly by a factor \n",
     "    #print(i,f)\n",
     "    \n",
     "    dfi = df_epis.copy()\n",
@@ -1320,7 +1330,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 692,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -1368,7 +1378,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 693,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1399,7 +1409,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 694,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -1457,7 +1467,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 695,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -1543,7 +1553,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 784,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1609,7 +1619,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 799,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -1620,39 +1630,39 @@
       "DecisionTreeClassifier: \n",
       "\n",
       "Training a DecisionTreeClassifier using a training set size of 10096. . .\n",
-      "Trained model in 0.0345 seconds\n",
-      "Made predictions in 0.0023 seconds.\n",
+      "Trained model in 0.0071 seconds\n",
+      "Made predictions in 0.0014 seconds.\n",
       "F1 score for training set: 1.0000.\n",
-      "Made predictions in 0.0019 seconds.\n",
-      "F1 score for test set: 0.9783.\n",
+      "Made predictions in 0.0014 seconds.\n",
+      "F1 score for test set: 1.0000.\n",
       "\n",
       "SVC: \n",
       "\n",
       "Training a SVC using a training set size of 10096. . .\n",
-      "Trained model in 0.0486 seconds\n",
-      "Made predictions in 0.0227 seconds.\n",
-      "F1 score for training set: 0.9472.\n",
-      "Made predictions in 0.0106 seconds.\n",
-      "F1 score for test set: 0.9278.\n",
+      "Trained model in 0.0186 seconds\n",
+      "Made predictions in 0.0075 seconds.\n",
+      "F1 score for training set: 1.0000.\n",
+      "Made predictions in 0.0044 seconds.\n",
+      "F1 score for test set: 1.0000.\n",
       "\n",
       "GaussianNB: \n",
       "\n",
       "Training a GaussianNB using a training set size of 10096. . .\n",
-      "Trained model in 0.0027 seconds\n",
-      "Made predictions in 0.0017 seconds.\n",
-      "F1 score for training set: 0.8423.\n",
+      "Trained model in 0.0028 seconds\n",
+      "Made predictions in 0.0018 seconds.\n",
+      "F1 score for training set: 0.9928.\n",
       "Made predictions in 0.0015 seconds.\n",
-      "F1 score for test set: 0.7845.\n",
+      "F1 score for test set: 0.9929.\n",
       "\n",
       "Report for DecisionTreeClassifier:\n",
       "\n",
       "              precision    recall  f1-score   support\n",
       "\n",
       "           0       1.00      1.00      1.00      4833\n",
-      "           1       1.00      0.96      0.98       141\n",
+      "           1       1.00      1.00      1.00       141\n",
       "\n",
       "    accuracy                           1.00      4974\n",
-      "   macro avg       1.00      0.98      0.99      4974\n",
+      "   macro avg       1.00      1.00      1.00      4974\n",
       "weighted avg       1.00      1.00      1.00      4974\n",
       "\n",
       "----------------------------------------------------\n",
@@ -1662,10 +1672,10 @@
       "              precision    recall  f1-score   support\n",
       "\n",
       "           0       1.00      1.00      1.00      4833\n",
-      "           1       1.00      0.87      0.93       141\n",
+      "           1       1.00      1.00      1.00       141\n",
       "\n",
       "    accuracy                           1.00      4974\n",
-      "   macro avg       1.00      0.93      0.96      4974\n",
+      "   macro avg       1.00      1.00      1.00      4974\n",
       "weighted avg       1.00      1.00      1.00      4974\n",
       "\n",
       "----------------------------------------------------\n",
@@ -1674,12 +1684,12 @@
       "\n",
       "              precision    recall  f1-score   support\n",
       "\n",
-      "           0       0.99      1.00      0.99      4833\n",
-      "           1       1.00      0.65      0.78       141\n",
+      "           0       1.00      1.00      1.00      4833\n",
+      "           1       1.00      0.99      0.99       141\n",
       "\n",
-      "    accuracy                           0.99      4974\n",
-      "   macro avg       0.99      0.82      0.89      4974\n",
-      "weighted avg       0.99      0.99      0.99      4974\n",
+      "    accuracy                           1.00      4974\n",
+      "   macro avg       1.00      0.99      1.00      4974\n",
+      "weighted avg       1.00      1.00      1.00      4974\n",
       "\n",
       "----------------------------------------------------\n"
      ]
@@ -1736,10 +1746,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 698,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
+    "import os\n",
     "# Create Keras callbacks\n",
     "losses = []\n",
     "\n",
@@ -1762,10 +1773,6 @@
     "        keys = list(logs.keys())\n",
     "        print(\"Start epoch {} of training; got log keys: {}\".format(epoch + 1, keys))\n",
     "\n",
-    "    def on_epoch_end(self, epoch, logs=None):\n",
-    "        keys = list(logs.keys())\n",
-    "        print(\"End epoch {} of training; got log keys: {}\".format(epoch + 1, keys))\n",
-    "\n",
     "    def on_test_begin(self, logs=None):\n",
     "        keys = list(logs.keys())\n",
     "        print(\"Start testing; got log keys: {}\".format(keys))\n",
@@ -1780,12 +1787,39 @@
     "\n",
     "    def on_predict_end(self, logs=None):\n",
     "        keys = list(logs.keys())\n",
-    "        print(\"Stop predicting; got log keys: {}\".format(keys))"
+    "        print(\"Stop predicting; got log keys: {}\".format(keys))\n",
+    "        \n",
+    "\n",
+    "class SaveCallback(keras.callbacks.Callback):\n",
+    "    def __init__(self, model_name, model):\n",
+    "        super().__init__()\n",
+    "        self.best_loss = np.inf\n",
+    "        self.filedir = f\"{model_name}_models/\"\n",
+    "        self.model_ = model\n",
+    "\n",
+    "    def on_epoch_end(self, epoch, logs=None):\n",
+    "        keys = list(logs.keys())\n",
+    "        if 'val_loss' in keys:\n",
+    "            if logs['val_loss'] < self.best_loss:\n",
+    "                savepath = self.filedir + 'epoch' + str(epoch + 1)\n",
+    "                print('\\n' + 'Val_loss improved from ' + str(self.best_loss) + ' to ' + str(logs['val_loss']) + '. Saving model to ' + savepath + '/' + 'ckpt...')\n",
+    "                self.best_loss = logs['val_loss']\n",
+    "                if not os.path.exists(savepath):\n",
+    "                    os.makedirs(savepath)\n",
+    "                self.model_.save_weights(savepath + '/' + 'epoch' + str(epoch + 1) + 'ckpt')\n",
+    "            else:\n",
+    "                print('\\n' + 'Val_loss did not improve from ' + str(self.best_loss))\n",
+    "                savepath = self.filedir + 'epoch' + str(epoch + 1)\n",
+    "                print('\\n' + 'Val_loss improved from ' + str(self.best_loss) + ' to ' + str(logs['val_loss']) + '. Saving model to ' + savepath + '/' + 'ckpt...')\n",
+    "                self.best_loss = logs['val_loss']\n",
+    "                if not os.path.exists(savepath):\n",
+    "                    os.makedirs(savepath)\n",
+    "                self.model_.save_weights(savepath + '/' + 'epoch' + str(epoch + 1) + 'n' + 'ckpt')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 699,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1793,39 +1827,39 @@
     "\n",
     "def get_model(X):\n",
     "    \"\"\"Get model.\"\"\"\n",
-    "    model = keras.Sequential()\n",
+    "    new_model = keras.Sequential()\n",
     "\n",
-    "    model.add(keras.layers.LSTM(units=16,\n",
+    "    new_model.add(keras.layers.LSTM(units=16,\n",
     "                                input_shape=(X.shape[1],X.shape[2]),\n",
     "                                activation='relu', return_sequences=True))\n",
-    "    model.add(keras.layers.LSTM(units=4, activation='relu'))\n",
-    "    model.add(keras.layers.RepeatVector(n=X.shape[1]))\n",
-    "    model.add(keras.layers.LSTM(units=4, activation='relu', return_sequences=True))\n",
-    "    model.add(keras.layers.LSTM(units=16, activation='relu', return_sequences=True))\n",
-    "    model.add(\n",
+    "    new_model.add(keras.layers.LSTM(units=4, activation='relu'))\n",
+    "    new_model.add(keras.layers.RepeatVector(n=X.shape[1]))\n",
+    "    new_model.add(keras.layers.LSTM(units=4, activation='relu', return_sequences=True))\n",
+    "    new_model.add(keras.layers.LSTM(units=16, activation='relu', return_sequences=True))\n",
+    "    new_model.add(\n",
     "      keras.layers.TimeDistributed(\n",
     "        keras.layers.Dense(units=X.shape[2])\n",
     "      )\n",
     "    )\n",
-    "\n",
-    "    model.compile(loss='mae', optimizer='adam')\n",
     "    \n",
-    "    model.summary()\n",
+    "    new_model.summary()\n",
     "\n",
-    "    return model"
+    "    return new_model"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 700,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Create helper functions\n",
     "def train(x_train_data, tot_epochs, selected_batch_size):\n",
     "    \"\"\"Train model.\"\"\"\n",
-    "    model = get_model(X=x_train_data)\n",
-    "    history = model.fit(\n",
+    "    new_model_ = get_model(X=x_train_data)\n",
+    "\n",
+    "    new_model_.compile(loss='mae', optimizer='adam')\n",
+    "    history = new_model_.fit(\n",
     "        x_train_data,\n",
     "        x_train_data,\n",
     "        epochs=tot_epochs,\n",
@@ -1833,19 +1867,34 @@
     "        validation_split=0.05,\n",
     "        verbose=1,\n",
     "        shuffle=False,\n",
-    "        callbacks=[CustomCallback()]\n",
+    "        callbacks=[CustomCallback(), SaveCallback(model_name=\"lstm_autoencoder\", model=new_model_)]\n",
     "    )\n",
     "    \n",
-    "    return history, model\n",
+    "    return history, new_model_\n",
     "\n",
-    "def predict(model, data):\n",
+    "def predict_results(newmodel, data):\n",
     "    \"\"\"Predict value.\"\"\"\n",
-    "    predicted_value =  model.predict(data)\n"
+    "    predicted_value =  newmodel.predict(data)\n",
+    "    return predicted_value"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Deep Learning Model: LSTM Autoencoder"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Separate data in healthy and anomalies"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 701,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -1858,26 +1907,20 @@
     }
    ],
    "source": [
-    "healthy_data = df.loc[(df['label'] == 0)]\n",
-    "anomalies_data = df.loc[(df['label'] == 1)]\n",
+    "healthy_data = df_initial.loc[(df_initial['label'] == 0)]\n",
+    "anomalies_data = df_initial.loc[(df_initial['label'] == 1)]\n",
     "\n",
     "print(f\"Total number of healthy samples is {healthy_data.shape[0]}\")\n",
-    "percentage_anomalies = anomalies_data.shape[0]/df.shape[0]*100\n",
+    "percentage_anomalies = anomalies_data.shape[0]/df_initial.shape[0]*100\n",
     "print(f\"Total number of samples with anomalies is {anomalies_data.shape[0]} -> {percentage_anomalies:.2f}%\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 702,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# X_all_healthy = pd.DataFrame(healthy_data['value'].values)\n",
-    "# y_all_healthy = pd.DataFrame(healthy_data['label'].values)\n",
-    "\n",
-    "# X_all_anomalies = pd.DataFrame(anomalies_data['value'].values)\n",
-    "# y_all_anomalies = pd.DataFrame(anomalies_data['label'].values)\n",
-    "\n",
     "df_epis_healthy = df_epis[df_epis['L'] == 0]\n",
     "df_epis_anomalies = df_epis[df_epis['L'] == 1]\n",
     "\n",
@@ -1888,16 +1931,9 @@
     "y_all_anomalies = df_epis_anomalies[target_col]"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Deep Learning Model: LSTM Autoencoder"
-   ]
-  },
   {
    "cell_type": "code",
-   "execution_count": 703,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -1926,7 +1962,7 @@
     }
    ],
    "source": [
-    "X_train_healthy, X_test_healthy, y_train_healthy, y_test_healthy = train_test_split( X_all_healthy, y_all_healthy, test_size=0.15, random_state=42)\n",
+    "X_train_healthy, X_test_healthy, y_train_healthy, y_test_healthy = train_test_split(X_all_healthy, y_all_healthy, test_size=0.15, random_state=42)\n",
     "\n",
     "# Show the results of the split\n",
     "printmd(\"**Training healthy** set has **{}** samples.\".format(X_train_healthy.shape[0]))\n",
@@ -1944,40 +1980,75 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 704,
-   "metadata": {
-    "scrolled": true
-   },
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "my_scaler = MinMaxScaler(feature_range=(0, 1))\n",
+    "\n",
+    "# Fit scaling with train and the transform test and validation\n",
+    "my_scaler.fit(X_train_healthy)\n",
+    "\n",
+    "X_train_healthy_scaled = pd.DataFrame(my_scaler.transform(X_train_healthy))\n",
+    "X_test_healthy_scaled = pd.DataFrame(my_scaler.transform(X_test_healthy))\n",
+    "X_all_anomalies_scaled = pd.DataFrame(my_scaler.transform(X_all_anomalies))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Store set used to fit scaling to be reused in production\n",
+    "X_train_healthy.to_csv('sensor-training-data-for-scaling.csv', index = False, header=True, float_format='%.2f')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
+     "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Using normalized/scaled data!\n"
+      "/home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib/python3.6/site-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n",
+      "/home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib/python3.6/site-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
      ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Scaled data')"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "def scaleData(data, use_normalized):\n",
-    "    # normalize features\n",
-    "    if use_normalized:\n",
-    "        scaler = MinMaxScaler(feature_range=(0, 1))\n",
-    "        return pd.DataFrame(scaler.fit_transform(data))\n",
-    "    \n",
-    "    return data\n",
-    "\n",
-    "use_normalized = True\n",
-    "\n",
-    "if use_normalized:\n",
-    "    print (\"Using normalized/scaled data!\")\n",
-    "\n",
-    "X_train_scaled = scaleData(X_train, use_normalized=use_normalized)\n",
-    "X_test_scaled = scaleData(X_test, use_normalized=use_normalized)\n",
-    "\n",
-    "X_train_healthy_scaled = scaleData(X_train_healthy, use_normalized=use_normalized)\n",
-    "X_test_healthy_scaled = scaleData(X_test_healthy, use_normalized=use_normalized)\n",
-    "\n",
-    "X_all_anomalies_scaled = scaleData(X_all_anomalies, use_normalized=use_normalized)"
+    "# plot both together to compare\n",
+    "fig, ax=plt.subplots(1,2)\n",
+    "sns.distplot(X_train_healthy, ax=ax[0])\n",
+    "ax[0].set_title(\"Original Data\")\n",
+    "sns.distplot(X_train_healthy_scaled, ax=ax[1])\n",
+    "ax[1].set_title(\"Scaled data\")"
    ]
   },
   {
@@ -1989,7 +2060,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 705,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -2013,6 +2084,71 @@
     "print (\"Set anomalies shape: {}\".format(x_all_anomalies.shape))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "limit = 100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "count = 0\n",
+    "for index, row in X_train_healthy_scaled.iterrows():\n",
+    "    row.plot()\n",
+    "    count += 1\n",
+    "    if count == limit:\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD4CAYAAADiry33AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAABcYklEQVR4nO3dd3hU15n48e+Zrt57BUmIIiSBRMcUUw24xrFje93ikrK/bMo6dbPZ3WSTTdt4k9hp7r3QDDZgwHSM6VUghArqvY7K9Ht+f2gkBAgbgwrg83meeWbm3DP3vOdK886dc+/cI6SUKIqiKDcu3XAHoCiKogwulegVRVFucCrRK4qi3OBUolcURbnBqUSvKIpygzMMdwD9CQ8Pl8nJycMdhqIoynXj0KFDjVLKiP6WfWaiF0K8CCwD6qWUGd6yd4B0b5VgoFVKmd3Pa0uBdsADuKWUuZcTcHJyMgcPHrycqoqiKAoghCi71LLL2aN/GXgGeLWnQEp5b5+V/y/Q9imvnyulbLyMdhRFUZRB8JmJXkq5UwiR3N8yIYQA7gFuHuC4FEVRlAFytQdjbwLqpJSFl1gugU1CiENCiCevsi1FURTlClztwdj7gLc+ZflMKWWVECIS2CyEOC2l3NlfRe8HwZMAiYmJVxmWoiiK0uOK9+iFEAbgLuCdS9WRUlZ57+uB1cDkT6n7DyllrpQyNyKi3wPHiqIoyhW4mqGb+cBpKWVlfwuFEH5CiICex8BCIO8q2lMURVGuwGcmeiHEW8AnQLoQolII8Zh30Ve4YNhGCBErhFjvfRoF7BZCHAP2A+uklB8OXOiKoijK5bics27uu0T5I/2UVQNLvI9LgKyrjE9RFOULYWflTiraK7hn1D0Y9cYBXbe6BIKiKMo14KW8l3gz/00MuoG/YIFK9IqiKMOstK2Ug3UHuTPtTrp/njSwVKJXFEUZZquKVqFDh7HAiNvtHvD1q0SvKIoyjFyaizVFa0h0JeJscWIwqKEbRVGUG8rOip0025uJbYolJydnUNpQiV5RFGUYrSxcSYAIIMGTQEZGxqC0oRK9oijKMKntrOXj6o9JaE0ga3wWJpNpUNpRiV5RFGWYvFf0HprUSLQmDtqwDahEryiKMiw0qbG6cDXxnnhSwlOIjY0dtLZUolcURRkGe2v2Ut1ZPagHYXuoRK8oijIMVhWuwkf4kORMYvz48YPalkr0iqIoQ6zF3sKW8i0kWBPIHJeJxWIZ1PZUolcURRli7xe/j1tzk9g2uAdhe6hEryiKMoSklKwsXEm0Fk1qcCrx8fGD3qZK9IqiKEPoWMMxStpKeg/CDsZFzC6kEr2iKMoQWlm4EpMwkWRPIjMzc0jaVIleURRliHQ4O/jw7IckdCSQNSYLX1/fIWlXJXpFUZQhsqF0A3aPncTWoTkI20MlekVRlCGy6swqwmU4qQGpJCUlDVm7KtEriqIMgYLmAvKa8ohrjiNn4tAchO2hEr2iKMoQWFW4CgMGkruSycrKGtK2PzPRCyFeFELUCyHy+pT9pxCiSghx1HtbconXLhZCFAghioQQPxrIwBVFUa4Xdred90veJ94WT+aoTPz9/Ye0/cvZo38ZWNxP+dNSymzvbf2FC4UQeuBZ4BZgLHCfEGLs1QSrKIpyPdpSvoV2ZzsJrQlMnDhxyNv/zEQvpdwJNF/BuicDRVLKEimlE3gbuP0K1qMoinJdW1m4kiCCSLOkMXLkyCFv/2rG6P+fEOK4d2gnpJ/lcUBFn+eV3rJ+CSGeFEIcFEIcbGhouIqwFEVRrh1l1jIO1B4gvjmenIk56HRDf2j0Slv8K5ACZAM1wP9ebSBSyn9IKXOllLkRERFXuzpFUZRrwurC1QgEyZ3JZGdnD0sMV5TopZR1UkqPlFIDnqN7mOZCVUBCn+fx3jJFUZQvBJfmYk3RGuIccWSlZBEYGHjJuhWVr5F38jt4PI4Bj+OKEr0QIqbP0zuBvH6qHQDShBAjhBAm4CvA2itpT1EU5Xq0q3IXjfbGzzwIq2luysufw26vQa83D3gchs+qIIR4C5gDhAshKoH/AOYIIbIBCZQCX/PWjQWel1IukVK6hRD/D9gI6IEXpZQnB7wHiqIo16hVhavwx580fRqpqamXrNfQsBG7vYpRaf8+KHF8ZqKXUt7XT/ELl6hbDSzp83w9cNGpl4qiKDe6us46dlXuIq01jZwJOej1+n7rSSkpL38eH59kwsPnDUos6pexiqIog2BN8Ro0NJLbkz912Ka19QDW9uMkJj6GEIOTklWiVxRFGWCa1FhVuIoYZwzZydkEBwdfsm55xQsYjaHERN85aPGoRK8oijLA9tfup6qj6jMPwnZ2ltDY+BHxcQ+g1/sMWjwq0SuKogywlWdWYsFCGmmkp6dfsl55xQvodCbi4/9pUONRiV5RFGUAtdhb2FK+hXhrPDnZlz4I63Q2Ulu7mujouzCZwgc1JpXoFUVRBtAHJR/g0lwkWz/9IGxl5RtomoPEhK8Oekwq0SuKogwQKSUrz6wkwh1BVlwWYWFh/dbzeOxUVr1OePg8/PxSBj0ulegVRVEGyPHG4xS3FZPQmvCpc8LW1K7C5WomMeHx3rI9xY28e6ACt0cb8Lg+8wdTiqIoyuVZVbgKI0bSPGmMGTOm3zpSapSXv0BAwHiCgyd5yyS//bCAxg4Hd0685EV+r5jao1cURRkAna5ONpRsIL49ntzMXAyG/vejGxu3YLOVkpT4eO+8sR8XNXG0opVvzEnBqB/4tKwSvaIoygD48OyH2Dw2ktqTPnXYprz8BSyWOCIizk3c98y2QqICzdydEz8osalEryiKMgBWFq4kxBNCVmQWl5pTo63tKK1tB0hIeBSdrnuP/2BpM3tLmnlyVgpmQ/+nYl4tlegVRVGu0pmWM5xoPEFCawK5ObmXrFde8QIGQwCxMV/uLXtmWxGhfiZuS4/C1uEclPhUolcURblKqwpXoUdPqiuVsWPH9lvHZqugvv5D4mLvx2DwB+BEZRvbCxp4bOYITmwo483/3Ifb6Rnw+FSiVxRFuQoOj4P3i94ntjOWyRmTMZlM/dYrr3gJIXTEJzzUW/bMtkICLQbuHBVFwd5a0iZFYTAN/PCNSvSKoihXYUvZFqwuK0nWSx+EdbnaqKlZTlTUrVjM0QCcqWtn48k6HpmeTMHWSoROMHFh0qDEqBK9oijKVVhZuJIALYDs0Gyio6P7rVNV9RYeTxeJied+IPXstiJ8TXruHhPD6U9qGTszFv+QgZ9GEFSiVxRFuWIV1gr21+4noe3SB2E1zUFF5SuEhswkwH80AKWNnbx/rJoHpyZRvKMadJA9Pw4p5aDEqRK9oijKFVpdtBqBINWWSkZGRr91auvex+msP29v/q/bizHoddw7LobTe2oYNyOWUzve5+2f/QCX0zHgcapEryiKcgXcmpvVhauJscUwZdwUzOaLh12654N9AX+/dEJDZwJQ1Wpj5eFK7puUQNnuWtDBuJvC2PHRRjwh4RhNAz9885mJXgjxohCiXgiR16fsd0KI00KI40KI1UKI4Eu8tlQIcUIIcVQIcXAA41YURRlWu6t202hv/NSDsM3Nu+jsPOOdD7b7cgd/31GMEPBAVjyn99Qwdnos+bvX89H4GfwqZzG2Qbio2eXs0b8MLL6gbDOQIaXMBM4AP/6U18+VUmZLKS/9KwJFUZTrzMrClfhKXzIDMomNje23Tnn585hNUURF3QpAfbudtw9UcNeEeKr31AEwZnowm3fv5uToidwdG47PcFzrRkq5E2i+oGyTlNLtfboXGJwLNCiKolyD6rvq2Vm5k4S2BCbnTO7dW++rvT2f5paPiU94GJ2u+9z653edxe3ReGhCPPkfVzNmRiwnd6xlR9ZMzDod30qKHJR4B+Kj46vAhkssk8AmIcQhIcSTn7YSIcSTQoiDQoiDDQ0NAxCWoijK4FhbvBZNaqTYUhg/fny/dcornkev9yUu9isAtHQ6eX1vGbdlxdK4rzvHpU/xZ9OhQ5xOzeRr0f5EuNoGJd6rSvRCiH8D3MAbl6gyU0o5EbgF+GchxKxLrUtK+Q8pZa6UMvdSFwRSFEUZbprUWFGwgkhHJFPTp+Lj43NRHbu9hrq6D4iNuQejMQiAlz4+S5fTwyMTEzi1p5rR02PI27qaXRPnEqgTfOP0M/DsFHB2DXjMV5zohRCPAMuAB+QlTv6UUlZ57+uB1cDkK21PURTlWnCg9gBVnVUktSVdck7YyspXkVIjIeFRAKx2Fy/tKWXxuGish5pAg7RcCxtP5lOUlM7/CxcEHX0Zsu8Dk++Ax3xFiV4IsRj4AXCblLLfjx8hhJ8QIqDnMbAQyOuvrqIoyvViZeFKzNJMpk8miYmJFy13u9uprHqTyMjF+Ph0H7587ZMy2u1uHs1N4OTH3XvzJz5axa5J8wkz6Hjs+G/BHAgzvzcoMV/O6ZVvAZ8A6UKISiHEY8AzQACw2Xvq5N+8dWOFEOu9L40CdgshjgH7gXVSyg8HpReKoihDoNXeykelHxFvjWdKzpR+D8JWVy/H4+kgKfEJALqcbl7YfZY56RE4jrWCBiOz9XxYUk5Z7Ai+G2jDr+B9uOm74Bs6KHF/5pyxUsr7+il+4RJ1q4El3sclQNZVRacoinINWXd2HS7pIqUrhczMzIuWa5qbioqXCA6eTGBg9/I395XT3OnksdwkTv49n9HTojm2eSW7piwgxqjnwQM/g4BYmPL1QYtb/TJWURTlMkgpWVGwgjBnGNNSp+Hn53dRnfqGDdgd1SQmPAaA3eXhuV0lTB0ZijzVhtQkSRmSDTWNVEfE8X2fBsyVe2Huj8F48UHdgaISvaIoymXIa8yjqK2IRGtivwdhuy938Dy+viMID78ZgBWHKqmzOnhicjKndlWTPjWaI5uW8/HUhYwwG7hnz48gPB2y7qe+YSPFJX/A41HXulEURRkWKwtXYpAGxhvGk5ycfNHy1tb9tLfnkZjwGELocHk0/rq9mAmJwRgLrGiaJD7dwQarg/qQSH6oK8LQVADzfoYHD4WF/0Nj45beuWQHkkr0iqIon6HL1cX6kvXEdcQxdeJUdLqLU2d5+fMYjaFER98JwJqj1VS12nh8chKndteQPjWaw5uXs2fKAsb4GLlt948gfjKMXkpl5SvY7RWkJPwQIdQMU4qiKENuY+lGbB4bIztHkp2dfdHyzs4iGpu2Eh//IHq9BY8m+cu2IsbEBBJY3IXmkcSObGeDy0BzQAg/dhxE11EDC/4Lp6uZs6XPEuiajPNFM5qaM1ZRFGXoLT+znCB3ENOTphMQEHDR8vKKF9HpzMTHPQDA+hM1lDR28sTUJE7urmbUpEj2b17B3snzmOBrZMGef4dRt0DSdM6e/TMej43QA3fgmxmOTs0ZqyiKMrQKWwo50XiCxLbEfi9H7HA2Ulu7mpjouzCZwtA0ybPbikiJ8CO83I7mkUQmtbDRGESbbyD/1rYZ4WyHeT+js7OIquo3CWtdgI+WSOC8i3+ANRBUolcURfkUqwpXoUNHhi6DlJSUi5ZXVr6GprlISPgqAFtO13O6tp0npiaTv7OatEkR7P9oNfty5jLDT8/Mfb+ErPshaixFRb9Bh4XgI0sIXJCEztc4KH1QiV5RFOUSnB4na4vWEtMRw/Ts6RcdhPV4bFRVvUF4+Dz8/EYipeSZrYUkhPoQW+3E49YIj6lnY2A0nRZfflK7AhAw98c0N39MY9NWwipuxxISjd/kmEHrh0r0iqIol7C1fCtWl5URHSOYMGHCRctralbhcrX0zge7u6iRY5VtPDalZ28+kk+2reHAhFks8Iecw3+EKV9DBsZQWPQ/mIgm6PQcgpeNROgvvpzCQFGJXlEU5RJWnFmBn8ePGXEzCAoKOm+ZlB7KK14gMDCL4KDuCfT+vLWI6EALyfVuPG6N4IhKNkWOwG4y8+OS58ASCDO/S03NKjo68gk/9SV8R0VjGRUyqP1QiV5RFKUfle2V7KvdR5I1idzci2dCbWzcgs1WRmLi4wgh2H+2mf1nm3l0ShIFu6pJzQnn453rOJw5gzt8XYzNfx1mfg+3yUxxyR/wc4/Gv3oSQUtHAOCqqcFZWjoofVGJXlEUpR+ri1YjEIyT40hLS7toeVn581gsCUSELwTgmW1FhPmZGNWs4XFpBISeZXP8GDwGA9/P/733wmVfo7z8OZzOesIO303AtFiMEd3Xn6/9719Seu9X0LquoYlHFEVRblRuzc3qM6uJ6opiRuYM9Przz21vaztCW9shEhMeQaczcKyilZ1nGnh4ciJndlUzckIoOz/+iKMZU7jX0kFK6Ycw98fYtTbKyp8jqH0mfs7RvadTtm/dRseWLYQ9+QQ632tk4hFFUZQb2Z7qPTTYG0huT+73Ambl5S9gMAQSE/NlAJ7dVkSgxcA4K7hdGn4BZ9iSkoVOp+N7x37ee+GykuL/RWoeQo/e3ns6pWazUffLX2LLGEfnzTcPSn9UolcURbnAioIVWDQL06OmExJy/oHSrq4y6hs2Ehf3AAaDH6drrWw6VceDkxIp2l3LyOxgdhzYSd7oiTxsbCC+dj/M/w+sXaepqV1FaO1ifAOSek+nbPz733FWVXF41izeevddnE7ngPdHJXpFUZQ+Groa2FG5g0RrIpNzL57muqLyJYTQkxD/IADPbivGz6Qnu0uP2+nBx+cUW0ZPwiR0fPvgTyFhCnLULRQW/goDQYScuqX3dEpHyVmaXniRurvuorK5mQULFmAymQa8TyrRK4qi9LGmeA0aGmPcY0hPTz9vmcvVSnX1CqKjbsNsjqKkoYN1x6u5LyeBs7trGJEZwJajezmdmsmTopSI1gKY/180Nm2htXUfYYV34Jcaj2VUCFJKan/xc1wBAewPDCAxMbHfC6YNBJXoFUVRvHpmkQq3hzNr/CwMhvOvDV9V9SaaZiMxsXsGqb9uL8ao15HrMOByejCZTrAtYwb+Ovjm/h9B+hK0hBwKi36N2ZNAUPlsgpZ0n05pXb+erk/2kn/3l3A4nSxbtqzfyx8PBJXoFUVRvA7WHaSqs6rfg7Ca5qCi8hVCQ2/C3z+dypYuVh+p4p4J8ZTvqSU5w5fNp45RNGIM/+zKI9hWB/N+RlXVm9hspYQf/xIBU+MxRvriaW+n7te/pnXyJPKtVqZPn05kZOSg9euyEr0Q4kUhRL0QIq9PWagQYrMQotB73+9Pu4QQD3vrFAohHh6owBVFUQbaijMrMEkT08KmER4eft6y2tq1OJ2NJCU+AcDfd5QgBEz1GHHZPeh1R9mePYtQneSJ/T+B7PtxhcRScvbP+HdlEtCZ03s6ZcOf/4yzuYWDWVkEBwcza9asQe3X5e7RvwwsvqDsR8AWKWUasMX7/DxCiFDgP4ApwGTgPy71gaAoijKc2hxtbC7dTHx7PFNzpp63TEpJecUL+PuPISRkOnVWO+8crOCOzFiq9tSROM7MxpIzlMWn8J3OPfhJJ8z5MaWlz+J2txF29G6CFiSj8zViz8+n5fU3KPvy3TS1t7NkyZJBOQDb12UleinlTqD5guLbgVe8j18B7ujnpYuAzVLKZillC7CZiz8wFEVRht26knW4pIt0Rzpjxow5b1lT8w46Owu988EKnttZgkeT3CQsuOwehDzEjpy5ROs0HjrwXzDla3QZPVRUvkpw4xz8fUfjNzkGqWnU/tfP6YqJ4Yhez9ixYxk1atSg9+1qxuijpJQ13se1QFQ/deKAij7PK71lFxFCPCmEOCiEONjQ0HAVYSmKonw+UkqWFywnxBHC3HFzMRrPvy58efnzmM3RREUtpbnTyRv7ylk6Lpq6PXUkjDawobqS6qgEnmregMVsgZnfpaj4twhpICzv9t7TKdtWraLr6FGOL7kFnV7P4sXn9nvzO2xsbbIOSv8G5GCslFIC8irX8Q8pZa6UMjciImIgwlIURbksp5pOUdRW1O9B2Pb2k7S0fEJC/MPodCZe3H0Wu9vDbIMPTrsHj3s/O3NvJknn5t7j/ws3/SutjmIaGj4k9OwS/EeOxDIqBHdLC/W/+z11c2ZT1t7OvHnzCAwMBMClSf62o4jtH5yhw+Ue8P5dTaKvE0LEAHjv6/upUwUk9Hke7y1TFEW5Zqw4swK91DMlaApRUecPTpSXv4Be70ds7Fdos7l4ZU8pC0dH0by3gbh0WN/STENYND+sfhtjQDRy0uMUFv4SoxZOyNlFvadTNvzhD9gcDg4mJxMTE8OkSZN62/hrUTX/dKCNh2o9+DHw16W/mkS/Fug5i+ZhYE0/dTYCC4UQId6DsAu9ZYqiKNeELlcX60rWEd8Rz/Sc6ects9urqav/gNjYezEaA3ntk1LaHW5uNvnitLlx2vfy8aR5pOvs3FHwPMz5MXXNH2FtP07YqTsJnJKMMdKXriNHaF2+gsK7v0SXw8Gtt97ae878yQ4buk0VRNklDaF+eAahj5d7euVbwCdAuhCiUgjxGPBrYIEQohCY732OECJXCPE8gJSyGfgFcMB7+7m3TFEU5ZqwsXQjNo+NNEca48aNO29ZRWX3+SYJ8Y/Q6XDzwu6zzEkLx7q/kZgUF+ttdpqDwvjx2efQRaTjybiTouLf4WMfSXDrTQTOS0S63dT+189pTUsjz+1m8uTJxMbGAuDUNJ7bVsgdlS7OuiXVLXZ0+oH/eZPhs6uAlPK+Syya10/dg8DjfZ6/CLx4RdEpiqIMshUFKwhwBXDzqJvPO83R7W6nquptIiNuwccnjud3ldDS5WK+rz9ttk5s9n3smTSPbNHBotIV8JW3qKh+FYejhoQTPyRowQh0vkaaX30VW0EBR776KAE6HXPnzu1t4y9nqnnwoJUOveBMl4cvPzwWne7aGrpRFEW5rhW3FnO86TjJ1mRycnLOW1ZV/Q4eTweJiY9hd3n4+84Spo4IxX6giegRNtajw+ofxE8K/g+RMBXHiEmUlv2NgNZcAo05+E2OwVVXT8Mf/0T5okXUd3ayePFiLBYLACfauzBvriDCITnU6mLqXakERw38tehBJXpFUb7AVhWuQid1TPKb1DucAqBpLioqXiY4eAqBgZksP1hBQ7uDRf4BOLrcWLv2sjdnLtNkEzfVbIYF/0XJ2f9D89gJz7u793TK+t/8hk6DniPhYaSlpTF27Fige8jmha2F3FrlpsSl4Z8WTMasfs88HxAq0SuK8oXk9Dh5r/A9YrpiuCnnpvOW1ddvwOGoISnxcVwejb/tKGFCfDDuQ01EJrazwRJAp48fPzn5a0T6UjpCQ6iufpfgyvkEJozBMiqEzj17sK5fT97tt6MBS5YsQYjuYZlnC6p5+FA77TpBsSa4+aExiEEYsumhEr2iKF9I2yq2YXVZSe1KJSMjo7dcSkl5+fP4+qYQFjaH1UeqqGq1cUtwII5ONy2dn7B/4izmeaqY1HwQ5v2MwqL/QS99CSu6jaClI9GcTmp//gvqsjIpcTqZPXt27wQmx9q78NtcQZhTcqjNyYx70wgItQxqX1WiVxTlC2lFwQp83b7MS53XO24O0NK6l/aOkyQmPoYmBX/dXszY6ADE4WYi4lvYEBKF3WThx8d/AdkP0KSvo7l5F6FnbiVoUhrGSF+aX3yJrooKDk2YQEREBNOnd5+26dA0XtlSyJJqN4VOjdCMcNKnRA96X1WiVxTlC6eqo4p9tftIak8iNyf3vGXl5c9jNIYRHXUH607UcLaxkyWhwTg63TR07edQ1gxudRSS0XUWbfb3KSz6H0yuaMIaFxE4LxFnZSWNf/0rhbcuo91uZ9myZb2Tiz+TX8XDh9uxCijT6ZjzwOje4ZzBpBK9oihfOO8VvYeUkhxzDvHx8b3lHZ2FNDVtJyH+QYQw8ezWIlLC/TAfayEsto4NUUm49UZ+eOznMOXr1HTuobOzkPCTdxM0LwWdr5G6X/6K1uBg8nx9mTBhAklJSQAcsXYRvLmSEKfkUJuL2Q+k4xs4uFet7KESvaIoXygezcOK0yuIskUxe8Ls8/aoK8pfRKezEBf3AJvz6yioa2dZRDCODhfVnYc4ljGFe7qOkSrbcE99nOKSp/FtH00wN+E3JYb2rVtp37aNo4sWYbFYWLBgAQB2j8brH51hUa2bM3YP0ZOiSJkweBONXEglekVRvlA+rv6YRkcjKV0pZGZm9pY7HA3U1L5HTMyXMBpDeHZbEQkhPvgftxISWc3GpNGg0/GvJ34FN/0rpfXv4HI1EX7yHkKWpSAdNur++5eUT5tKrdPBwoUL8fXtPi/+T/lVPHykgzagymJg1r2Df2nivlSiVxTlC2VFwQrMHjPzkuf1JmKAyspXkdJFYsKj7Cxs5HhlG8siQ3B0OCm3HyVvdA4PtX1MgtmALXMZ5eUvEFg3nZCYHCyjQmj8299pb2riSGoqycnJZGVlAXCorZPIzZUEuSSHrC7mPjQGs6/xUuENCpXoFUX5wmi0NbKzcieJ7YlMzpncW+7xdFFZ9SYREQvw9R3Bs1uLiA60EJLXTnB4KZtSMzEJyXdO/QHm/oTi8mdAg/AzXyJo6UgcxcU0vfQSJ2+7FZfHw9KlSxFCYPNovPVRIfPr3BTYPSTNjCNxbNiQ91slekVRvjDWFq/Fg4cJhnMHSQGqa1bidreSmPAY+0qa2F/azNKoEJwddopdpzidlsXjjRuJDI6ibcRY6urWEnJ2ESETxmOI8KH257+gPj6eIr2emTNn0jOnxp9OVvDI0XZagXp/E9PuShmWfqtEryjKF4KUknfz3yXcHs7N2Tf3HoSV0kNF+YsEBk4gKCiHZ7YVEeZnIvJ0B4GhJWwenYsfbv75zF+Q835GYfGvMbiDCa+7jcD5iVg/WEf7gQMcmTmDkJAQbrqp+1e2B1o7iP2omgAXHG53cfMjYzFZLus6kgNOJXpFUb4QDtUdoqqrihEdI8jOzu4tb2j4CJu9nKTExzlW2cauwkaWRofisto4rRVRNGIs36heRUhsBg0hgra2Q4QV3EHI3NFIj5263/yGwjmzaXW5WLZsGUajkS6PxrubC5lb7+a0zUPqzYnEpgZ/anxSSjRtMK5GrxK9oihfECsKVmDUjMyLn4efn19veXn5c/hYEomIWMAzW4sI8jESc6YT/6ACtoybSohm52tnX0Kb91MKi3+D2ZZAmGsRflOiafjjn2h1OMiLjiYjI4OUlO6hmT/mVfDosQ5aJDSHWph824jPjO/QuvdY9T//ictuH/C+q0SvKMoNz+q0sqlsEwkdCUzNndpb3tp2iDbrERISH+V0bScf5ddxS3QIHmsneaKSsoRUvl3+Ov5p86gUBdjtFUScupeQpanYT+fT/OabHFu6BIPRyKJFiwDY29JO0kdV+LrhSKeb+Y+Ow2DUf2p8ZcePsvP1lzBZfDCYBv5HVCrRK4pyw1tfsh6XdDGe8YwYcW7vurz8BQyGIGJj7ubZbUX4mfUkFNnw9T/F1uwZRHs6eLhyOa7Z3+Hs2Wfwa84kLPwmzGnB1P7851SMGUMVMH/+fAICAuj0eFi9uYhZDR7ybR7G3JJMRGLAp8bWWlfLB3/8DaFx8Sz+5ncQuoFPyyrRK4pyQ5NS8k7+OwQ7glmYtbB3rtaurlIaGjYRH3c/pc0a607UsDgmFNnWzlFzI9XRSXyv5Dl8su6hpH0DbncHEQX3ErR0JK0rVmA9lc+xCdnExcX1Tlryx+MVPHKsgyZN0hHlS87ipE8LDafdxprf/zdSatzx/X/H5KMmHlEURfncTjWfoshaxIiOEUyYMKG3vLziJYQwEh//EH/ZVozZoCO5xI7ZL4/tE2aR6G7lvobNdE59gKrKNwiqmkXY+EkIg536//0Dp+bPx+bxsGzZMnQ6HXua2xm5pRofDxyzacx7dNynzv8qpWTjX/6Ppopyln37hwRHxwzaNlCJXlGUG9qKghXopZ650XMJCOgeRnG5WqipWUF09O3Ud/rz3tEqFsSEIlrbOOjfTn14DD8ofBbj5Ccoqn0RoRmJrPoygfMTqf/f/6XebKYgKJCpU6cSExNDp9vD2k2FzGz0cKrLQ+btIwmN8fvUuPa/t5wz+z7mpgceITlr4qBugytO9EKIdCHE0T43qxDiOxfUmSOEaOtT52dXHbGiKMpl6nJ1sa5kHXEdcczIndFbXln5BppmJzHhq/xtRzE6AamlDoy+x9k1cTajnHXcaT1I8/iZNDZuIbR4KaGzM7GfPkHLqtUcmT+PwMBA5syZA8DTxyt49EQnjR6JIzGArJsTPjWuksMH2P3Oa4yeMZvcZXcO5iYA4IrP3pdSFgDZAEIIPVAFrO6n6i4p5bIrbUdRFOVKbS7bjM1jY5w2jtTUVAA8HgcVla8SFjabDk8iyw9u4+boEPQn6tgb66I5OILf5/0U3czvUFj+J4yOcCK6bsc3J5zSL3+DotxcmjWNe2+5BbPZzO5mK+lbqjF7YL9LcvsjYz91WsDm6krW/el3RCaNZOHXvnVdXY9+HlAspSwboPUpiqJctXfz38Xf6c/ijMW9B2Hr6tbgcjWRmPA4z+0qwSMl6ZUudJZjfDxxNlm2Mm5xnaU2OYqOjlOEF9xN6JLRtLz1Js2VlZxISyU9PZ0xY8bQ4fawbmMh05o8nOzykHN3GoHhPpeMx9HVyXu/+2/0BgO3P/VvGM2DO4Vgj4FK9F8B3rrEsmlCiGNCiA1CiHGXWoEQ4kkhxEEhxMGGhoYBCktRlC+qkrYSjjcfJ7kjmYkTu8fApdQoK38Bf/+xaMaJvLGvjFnRwRibG9gTqccaEMKPC/+ENucpis7+EYt1JBFBi9EHu2j40585tnABQq/nlltuAeDpY+U8eqKLBreGTAtmzIxLH1CVmsb6P/+e1tpqbv3ejwmMuI6uRy+EMAG3Acv7WXwYSJJSZgF/Bt671HqklP+QUuZKKXN7LgikKIpypVYWrERIwZzwOQQHBwPQ1LSDrq4ikhIf56U9pTjcGmOrXGA5yicT5jCt4zSzDZ2UBVtxuuqJKLiP4KUp1P3611RGRlJhsTBnTvf6djRZydhSg1GDk5pg7oNjPnUYZs/yNyg5fIC5Dz9BwtjxQ7MRvAZij/4W4LCUsu7CBVJKq5Syw/t4PWAUQoQPQJuKoiiX5PK4eK/wPWK6YpiVO6u3vLz8eczmaMwBC3hlTxnTI4OwNNexKzaATl9/flz4Z5xzv0NZ2T/wr8slcsxsHGeO0Lz5I45On0ZUVBRTp06l3e1h04eFTGr2cLLLzZT70vELNl8ynjP7PmbvqnfImLuA7EVDf8hyIBL9fVxi2EYIES28H3FCiMne9poGoE1FUZRL2l65HavbyhjXGEaN6p7NyWo9QUvrXhISHuW1vVV0ONyMr9NwW46yf8JNzGs9xOTgQIo5gtTcRJbfh/+saOp+8Qvyp0+nQ9N6J/p++kgpj5zsot6tYcwIJ21S1CVjaSgv5cNnnyYmNZ15X/3GkBx8vdBVJXohhB+wAFjVp+zrQoive5/eDeQJIY4BfwK+IqWUV9OmoijKZ3nn1Dv4uH1YMnYJen33dWbKK15Ar/cnOOxuXvz4LJMjAvFrrGJnYgR2sw8/Kv4r7bMepaZ2JcFl84mYOYnWt16lrq2N07Ex5OTkkJCQwLbGNrK21GLQ4LROx+z7R18yDltHO2t+/9+YfHy47V9/MijXsbkcV3VxZCllJxB2Qdnf+jx+BnjmatpQFEX5PKo7qtlfv5/R7aPJzckFwG6vpr5+PQnxj/DOoSZau1xkdZmxW45xKOtObm3cRUb8KI5Y16J3+xPVfg/GODfl3/w7R25dhq+fH/Pnz6fN5Wbrh0V8rVXjSJeb6U+Mx+Lf/7SAmsfDuj/+lvbGRu79z//BP3ToZ5bqoX4ZqyjKDWV14WqklMwMmUloaCgAFRUvA4KI6If4x86zZIf5E9hYzo7UeNwGIz84+xxNk26hpfUTwgpvI3RRBnX/8ytKUkbSYDCwaNEifHx8ePpwGY+c6qLWpeGXG0Xy+Esfctz11iuUHT/CvMe+QeyoMUPT+UtQiV5RlBuGR/Ow4vQKIm2R3JxzMwBudztV1e8QGbmEtXluGjscZDVJ2n1OcDRjKl+u20TK6Js4U/cKpq5oon3vwl15hMZ9+zmelcXIkSMZP348HzW0MWlrLUKDIpOBmV8edck48ndv5+D7q8hauJTMeYuGqvuXpBK9oig3jE9qPqHR2Ui6I53Ro7vHzquq38bj6SAm7qv8bXsxY0P8CG04y470VBDwr5VvUjV2DDb7WSLO3EvgzQnU/vJXHJ89C49Ox9KlS2lze9i1oYisNo0TnW5mPjIWk0//I991JUVs+tufiBs9jrkPPz6U3b8klegVRblhvJv/LiaPiaWjl2IwGNA0JxUVLxMSMo2PCoOobrMzoUXS5nuKE2NyeLBmLTETllFS9RK+zWOISl1C24qXqZQapd75X8PCwnj6UCkP53dR49IInRlLfHpIv+13tbWy5ve/xBIYyG3f+zF6Q//j90NNJXpFUW4ITbYmdlTtIKkjick5kwGoq1+Pw1FLbNxX+ev2YlIDfYisL2J7xjhMePhO3VpK40243W1Elj6AZaSbulde5fDs2YSFhTFz5kw21bcybWsdaJKzfiam3Znab/set5v3n/41Nmsbdzz1U3yDgoew959OJXpFUW4Ia4vXoqExzX8aERERSCkpL38BP7809laNorSpixyroDHwDPlpmTxWuYLAKXdTUf02gdUziJx6E/W/+RWnM8fTLgTLli2jXcInG4rIsGqcsHmY/eg4DKb+pwXc/urzVObnseBr3yJqZP8fBsNFJXpFUa57UkreOfUOYfYwFuYsBKClZQ8dHaeIj3+MZ7cVk+RvIbb+NNvHZ+Ov2fnn1h0UBVSDR0d0ywN4Gg9RW3Ca/NRUMjMzGTFiBE8fKOXB0zaqnRrR8xKJGhHYb/sntm3i6MYPyFl6B2NvmjuUXb8sKtErinLdO1J/hCpbFWn2NMaOHQt0X+7AZArnRPNUCus7yO0UVAefpXDkOL5e8Ta66XdS37SR0NLFhMxIp+53v+Pw7NmYLBYWLlzIhroWbtpWh9QklSEWcpeO6Lft6jOn2fL8X0gcn82sBx4dym5fNpXoFUW57r2b/y4GzcDS1KUYjUY6Ogpoat5JXNxDPLu9lFhfM/G1J9mRnUuIq50nHMc5o+3D4Agmxng/HetepTgwkDo/PxYsWIDDZOHg+iLGtGuccGjM/uo49IaL02VHcxNr//Ar/EPDWPbtH6DT9z+sM9xUolcU5bpmdVrZVL6JhI4EpuZMBaC84kV0Oh/O2m4hr8rKJJugIryK0oRR/Ev5q3RNXUB753HCi76Eb4qgduVKjk+ZTEJCAhMmTOD/9pfwYIGdKqdG4i0jCIvzv6hdt8vF2j/8CkdXJ7d//9/xCeh/WOdaoBK9oijXtfUl63FJF5N9JhMdHY3DUU9t7Rpiou/mLztqibAYSaw9zs4JU4lyNvGgoYai9g8xWxOJSbiTxj/9huOTJ+PU6Vi2bBnr69qYu70Bj5TURvqRvSDxojallGx54a/UFBZwyze/S0Ri8tB3/HNQiV5RlOva2yffJsgRxOLsxQBUVr6KlG5qtS9zqKyFyQ5BaVQjlTHJfK/0ZRonZONwVRNZ+gDSeoSK2hpK4mKZNm0a+pAwjm0oYlSHRp5TY/ZXx6LrZ1rAY5vWk7dtE1PuvJdRU2cOdZc/N5XoFUW5bp1qOkVxRzGptlTGjx+P291JZdWbREQs4vk9HYSYDYyoOcaunOkk2mv4UrCL0ua1+NVnE5U+lbq//JnDN91EUFAQs2fP5o/7SvinM3YqnRojb08lONL3ojYrT+Wx7ZV/MHLiJGbc88Aw9PrzU4leUZTr1vL85eg1PUuSl2A2m6mpWYHb3Uab/kF2FzUyyamjMM5KbXgc3y99icpREXg0OzGND9O54w3y4+NoNZlYunQpHza1M397PS5N0hgfQMasuIvaszbWs/bp/yEoKoYl33oKobs+Uuj1EaWiKMoFbG4b686uI64rjhm5M5DSQ3nFSwQFTeTl/XoCjHpSag+zJ3cGozpLWRjvT1XLhwRXzCEw1p+qzZs5lZHBmDFjCEkewal1xaR0Sk56YPYjYxEXDNm4HHbW/P6XeFwubn/q3zD7+g1Tzz8/legVRbkubS7djE2zMdE4kdjYWOobNmG3V2C3PMaW0/VMcgsKEuw0BEfxw/LXKIm0o3NbiPH8E80v/R9HZkxHbzSyePFi/vhJCfcVOahwaqR/OY2AUMt5bUkp2fyPZ6gvLWHJt54iLC5hmHp9ZVSiVxTluvT2ybfxc/mxLKt7Dtby8ufx8UnkzaMR+Bp0pNQd4pPcmWS2n2bKqHCaO/cRVnIrhs58iu02qkNDuXnePLZ3uFm0vQGnJrGODCZ9SvRFbR1a9x75u7cz48sPkOK9js71RCV6RVGuO6VtpZxoPUFKZwpZWVm0tR3Caj2K5vcEG/JqyXULTo+QtASE8aPqtymylGDsiiDGdwl1r7/I0alTiY6OJjlrAmfWFzPCJjklBTc9NOaiOV1Ljx9h5+svkTZlOlPuuneYenx1VKJXFOW6s/z0coQULIpfhMViobz8eYzGEFbmp2PS6UhpOMS+iTOZ2nqMUWOi6HSWEFH2Fez73uV4+ii69HqWLVvGn/ed5d5iB2UOjfH3j8Y38Pw5XVvraln3f78hLD6Bxd/87rBM7D0QVKJXFOW64vK4eK/oPWK6YpgzaQ5dXWdpaPwIEfAwa4/VMdEDp1INWH2D+H7jGkrkYSwtqYTpEyk/fJDClBQmT57Mfiws3d6IQ5M4xoUxckLEee047TbW/O4XANz+1E8xWXyGo7sD4qoTvRCiVAhxQghxVAhxsJ/lQgjxJyFEkRDiuBBi4tW2qSjKF9eOyh1Y3VaydFkkJCRQXvESQhj5oGgqOiC18RAHJ8xgbvM+oscG49Kaia55gNaVf+PQjBn4+/uTMeMmzq4rIdEuydfpmHF/+nltSCn58C9P01RZwdJv/4Dg6Jjh6ewA6X8urM9vrpSy8RLLbgHSvLcpwF+994qiKJ/bm3lv4uP24bbM23C5mqmpWYEh4B5Wf9RIliY5le5Lp9mf79V9RJkjj4Caqfg21bPfYqHZ34+7Fy/m74eq+NpZB6UOjewnMjD7nj8T1L7V71K4bw+z/umrJGdd//umQzF0czvwquy2FwgWQlzfH4+KogyL2s5aDjYeJLkzmYnZE6msehNNc7CpfBFuTSO15TCHsqaztGE7Pql60CTRTbdRs245eRMnkJqaSn5QFLfuaMSuSbSJkSSODTuvjeJD+/n43dcZPWM2ucvuHKaeDqyBSPQS2CSEOCSEeLKf5XFARZ/nld6y8wghnhRCHBRCHGxoaBiAsBRFudGsLFiJRLIgegFms57KylfR+y1ixZE2MqUkf0wQToORf5b7qHMcILhsAfLgJo5kZyMNBibNX0DVB8XEOyRnjHqm3TPqvPU3VVWw/s+/JzJpJAu/9q3r9uDrhQYi0c+UUk6ke4jmn4UQs65kJVLKf0gpc6WUuREREZ/9AkVRvlA8moflp5cTaYtk/qT51NauxuVqZkfNl3C4NFLajnIkYypfqtuMFtOG3hlAZEMmRRVnqYiNYdbs2byS18yXylycdXjIeXQcRvO568c7ujpZ8/tfojcauf37/4bRbPmUaK4vV53opZRV3vt6YDVw4a8JqoC+PyOL95YpiqJctn01+2hyNZEhM0hKSqS84gWEeQLLj7gYh0ZBRihSCB71PU6bu4Dwkttp3/gWR6ZOITw8nOqEUdy5s4kuj8QwPZaY1ODedUtNY/2ff09bXQ23fvdHBIZHDl9HB8FVJXohhJ8QIqDnMbAQyLug2lrgIe/ZN1OBNillzdW0qyjKF8+beW9i8pi4I+MOmpq309VVwicND9Ph8JDceZwjoydzX+16bIFlmDpiCSzUOBYRQYfZzNSFi2lYX0qMU1LkY2TSHSnnrXvP8jcoOXyAOQ8/QcLY8cPUw8FztXv0UcBuIcQxYD+wTkr5oRDi60KIr3vrrAdKgCLgOeCbV9mmoihfMM32ZnbX7iapM4lJEyZRXv4CUp/Mu8dMpEsPReMjMUoP94YUYJe1RBbdQtW+rRSMGU12djary5zcWeGixKEx+fEMDMZzQzZn9n3M3lXvkDF3AdkLlw5jLwfPVZ1eKaUsAbL6Kf9bn8cS+OeraUdRlC+2NYVr8ODh5vCb0bQSWlv3cbD9l7TZ3Ex1nGRt6iKerFlFe/RJfBvHod99jMO5uVh8fGgfPZG73iijwyPxnRtPRGJA73obykv58NmniUlLZ95j37xhDr5eSP0yVlGUa5qUkrdPvU2oPZTFkxZTVv48HoJZfjyUFOmmJCsGP4+NJZEFeOgk4uRETts7aAgNYdLN8+jYXE2kU1IaaGbi0hG967V1tLPm9/+NydeX2773EwxG46dEcX1TiV5RlGva0YajVNurGeseS0yMiYaGDznW/nWaOl0kuAs4kZzNVxvfp1N3nKCK6XRt3cbxnIkkJibyUZOFW6tclLglU57IQKfvTnmax8O6P/6WjqZGbvveT/APDfuMKK5vKtErinJNezPvTQyagTvH3klV9au4NQMrTyaRKF2UTYgjxNXGnIg88BgI3uvP4ZQRuI1GxITp3PNxKx0eSfCiZEKiz00UsvPNlyk7foR5j32T2FGjh7F3Q0MlekVRrlntzna2Vm4loTOB3KxxVFe/S177V6m1uogXxeTHjeOrrR9g0+UTemYGlfknKU1OZvyUqbh3thDmkpSH+ZA5P7F3nfm7tnHog9VkL1rK+JsXDmPvho5K9IqiXLPWF6/HKZ3MCp5Fe/sHOF02Vp0eT4x0UT4hkShHI1NCD2CwhWL5sJbDkycTHBTEQVcUt9S4KXHD1MczeqcFrCspYtPf/0z8mAzmPPTEMPdu6KhEryjKNeutk28R5Ahiac4iKipe4WT7vVS2uok3llAUmcajtvW4dBWEHc4kz2zE6ueHT+5M7v3ESrtHEnHbSALDuy8v3NXWyprf/xKfwCBu/e6P0BsG6pqO1z6V6BVFuSadbj5NcWcxo12jCQwswOaoZ23hdCKki4oJI0mw15AZsBNzSyJdmwvJz8ggefQYjAfchLglNTH+jJnVfVktj9vN+0//Gpu1jduf+jd8g4KHt3NDTCV6RVGuSW/lvYVO03HbqNuorHqJU22LOdssSfAtozQ0mYfdHyJ1LYRsi+TQuHEYTCYKTSNYWO+mWIMpj43rPS9++6vPUZmfx8KvfYuokanD3LOhpxK9oijXHLvbzobSDcR1xZE1ykh7+2nWnV1EiHRRnp1KalcpY3w241eRTsWZVuqiovDLnsJ9hxxYPZK4u9PwCzIDcGLrJo5uXEfOsjsZc9PcYe7Z8FCJXlGUa87m0s3YpI3pAdNpbnmH/NZpnGnQkRRUQWVgHA+ITYAbn7UOjubmEBYZRdApHwLdkvqkQNKmdE95UX3mNFte+AtJmROYdf8jw9qn4aQSvaIo15w3TryBn8uPpZlZNDXt4sPyOwnAxdnMUYzrPEOqeTOBeWkct8TgMJmoCxnHvCaNEgRTHxkHQEdzE2v/8Cv8w8JZ+u0foNPrP6PVG5dK9IqiXFNK20o5aT3JKMcojMYdFLZlcLLOwoiwKur8orjHsAGDy4xjQwfFqSn4jx7P/ScEbR5J8n2jsfgbcbtcrP3Dr3B2dXH7Uz/Fxz/gsxseZk1VFeTv2jYo6/7inF+kKMp14Z1T7yCk4LaUOdTX/5aNFf+Bn/BQnDGGiZ15pPjuJHBLMrvGZuLr50d0WQT+HklFWgjjsiOQUrLlhb9QU1jArd/7MRGJycPdpU9VX1rCvveWc2bvbiz+AaROmY7RZB7QNlSiVxTlmuHSXKwpXkN0VzTp8ZXsOZPA0ZpAMmPK2W+Zxndcf8NkDaHilC+tWUFoEeOZXSAo1gmmPTgGgKOb1pG3bTNT7ryXUVNmDHOPLq2mqIC9q96h5NB+TD4+jJs3lZCkiAFP8qASvaIo15Ad5Tto97Qz328Wzc2r2Vz5L1h0HgpGj2Nq12FG+hzCtCGavIxsLDEJ3H7Gj1a3JOWxcZh8DFScOsH2V55j5MRJzLjngeHuTr8qT+Wxd/U7lB0/gtnPnzE359LeKTidl0b76SKyburC4uM7oG2qRK8oyjXjjeNvYHFbWDTOj4LaQA5WR5KZUMF+UyK36VZhrgznhGc00mgkvjkZPw2qM8LIGBOKtbGe95/+NUFRMSz51lMI3bVzCFJKSdnxI+xd9Q5Vp0/iExjEqFnjaWv15/jJBIqCVnMsYwV6Df7V9XVQiV5RlBtRbWcth1oOMc4+FunZzKaKr2AyeDg5KpNZtr0kWfKxb46nKiUBGTGGOWUmig06Ztw/GpfDzprf/RKPy8Ud3/8pZl+/z25wCEgpKT60n32r3qa2uBC/kGBGTh9Na1McB4vgdPha8ic2otNgZkEkUysScd3vGvA4VKJXFOWasDx/ORLJrSNGcLapgn1ViYwfWc0BfTzLxLtYjofxcexUjP5B3FUeSatHI/2JTPRGHev//Gfqy0q44/v/Tmhs/HB3BU3zULhvD/tWvUNDeSkB4aEk5KbR0jSKTyrLOBHzFpUpNgK6BPd/nMiUfCNRjWdwGZuoq2khKCBqQONRiV5RlGGnSY2VBSuJsEWQHHKCvxy6A7PJw/GRmcxz7iZeV0XliXF0JfiQYh+FryZomBhJdEoQB99fxemPdzDj3gdJyZk8rP3wuN2c/ngH+95bTkt1JYGRocRkplDfMp5jzR9zNPFvWP00RtSa+d4HI8ksasbXVkKX2cyHE8NYnT2VlcEhAx6XSvSKogy7fdX7aHI3cavvJMqaTvJx5RjGj6rhsC6Opaa30e8M4HT8eERQEnPrAikx65nx5VGUHjvMzjdeJm3KdKbcec+wxe92uTi1Ywv71yynrb6OoOhQIkenUtExio9dGzk+ZisuA8w9EcjCY6EkV5ail2coiwzi/ZkpbJjwZUxBMUw4fQiLr/+Ax3fFiV4IkQC8CkQBEviHlPKPF9SZA6wBznqLVkkpf36lbSqKcmN67dhrmDwm5qW081reEnwtTo4kZTPftY1oRysnWmajizBxZ10SzR7J2CfG095Yx7o//paw+AQWf/O7wzKxt8th58TWTRxYu5KO5iaCYkIISU2nxBFGvmUTZ0Zuwc8G9+2KYHq+JLStFpehnX2jQ3hrQganx97BiLZ6bj+2l5nHjpLqacHyrW8OeJxXs0fvBv5VSnlYCBEAHBJCbJZSnrqg3i4p5bKraEdRlBtYi72FPQ17SHcl0NxZwq7Khxg7toHjxLHU+C62baE0hkSRrKUTIA20ToslMMLAWz/9bwBuf+qnmCw+Qxqz09bF0U3rObTuPbraWgmKCcEveTwnpYMTkTupC7aTWqXnR6uiyShuwuSuoSkwkLdmJrIi5xacUePJKjzCD9/5C+Ory0mNM2O5aTH4J2EKCBzweK840Uspa4Aa7+N2IUQ+EAdcmOgVRVEuadXpVXjwcEucmY1lCwj0sXMoLoulng1ENHbxsX4+Okso81ojKfU1Mv32kaz7469pqqzgrp/8F8HRMUMWq72jgyMfvs/h9Wuwd3YQGB2MCJrAQXMpR+PXYzN7mHfUh8VHwkmor0UT1eQnhfPuhHHsGf8l4l1O5h//hLnvLmes0UbI+Gloo+/F7YrH5tKo7soj1GFHN8AfXAMyRi+ESAYmAPv6WTxNCHEMqAaeklKevMQ6ngSeBEhMTOyviqIoNxgpJe/mv0uYI5ggQxk7Kh4ibXwLbdLBUv0Kqo+n4TabWdY2ihYPZHwtkwNrllO4bw+z/+mrJGdOGJI4u9paObTuPY5uWofTZsM/KhhbWDZHAo6QF3+MAJvk/p2BTD/lws/eQadFsjEnntcmTqc5eSbjy/J5as1rTKopIyU9Bd2Mh3C603Gip1aU8X7kcrYFHaJN385O230EXWuJXgjhD6wEviOltF6w+DCQJKXsEEIsAd4D0vpbj5TyH8A/AHJzc+XVxqUoyrXvWMMxqp3VLAtIYGNpLqF+HRyOzuJLnuUEFGkcNWcTxwjCNF865yTQXHWSj999nTEz55Cz7M5Bj6+juYkD76/i+EcbcLuc+IQH0xCZwM7wA5REHmV8qeCn7wQyprwVnWyhLCqSl2YnsW7iHYQZ/Jhy/BMWfPBzsqMC8BsxC9eIr+HGh3bZxMbQzWwOPkC5qQYE+Dl9yahPwekZ+B96XVWiF0IY6U7yb0gpV124vG/il1KuF0L8RQgRLqVsvJp2FUW5Mbx29DX0mp6Jwc38e95skrM6adbaWcxaTlVPQ6e3sKAricpAM2Oy9Lz5098TmTySBV/71qAefG2rr+PA2hXkbduM5vGgCw/mbEAoJ2OP0mE+yqLDBp5a6Ut4WztOQyf7R8fxWu5YikctZmz1Wb618QPmWpuJT8vCPfUpNBlKp7CxO+AwHwYf4IRPIVInsbjMjKsbSVptCvGtBsIMBYT4mwa8P1dz1o0AXgDypZR/uESdaKBOSimFEJPpvixy05W2qSjKjaPD2cG2mm2MlkHsqhhPVGAbRyOy+Ir2KrqTvjSJWObbR9Om6Rj9SAprfv9T9EYjtz/1b4Ny4S+A5uoq9r+3nPzd25BSwxkRwplgG3nxxwi3aty/3czkAoHJ7aAxyJ93ZqbzVs58TEGJTMvbz/de/BMTkuLRJy3DLZOw4+G4z0k2hKxmr99xnHoXRreRtKZERtWMJKVVR6r5IKP9DhOVaMXlNgzKpRuuZo9+BvAgcEIIcdRb9hMgEUBK+TfgbuAbQgg3YAO+IqVUwzKKovB+4fu4cHFThItn9s0lbqKbEE8zC50bOWpdSoSMIt4TimNhIrtef5a2uhq+/NNfEhgeOeCxNJSXsm/1u5z5ZBfoBC3RgZwJq6cw6jCTz0j+800LI2q78OicnE6MYXlOInvHLSWtpYkn9+5mqdxPSPQkXFk/QKKn2FTK+qB32RF0kDZDB3qPnsS2aEbXjCCjWZJmPkK63yFCE7oAsLcYqGvwp9wvnBw58N9Uruasm93Ap0YkpXwGeOZK21AU5cb19sm3CfH4UFyfQXJwM0dCJvGwfA7rmQTcngAWONKoDvVBa9xJyeEDzPvqN4gfmzGgMdQWF7J39TsUH9gLBkFVoi+noyroMpWw+BA8tVyPv91Jh4+RTRPTeGXSZGxRE5h++iAvv7+G0TGpeGLuB3yoNzSyMWgTW4L2U2muQ6fpiGuPYEpNBhOb3Yw1HCE14DAB8Q6khK4mI+UdQZSmhmPPdaP37cTjcuHQXPiirkevKMp1rqC5gBJbCYv9/fnwxM2E5hqJ0OqZa93Ovra7mOJKpUszETCpk01/f5eMuQvJWrhkwNqvOn2KvaveovTYEVwWKEk1cDqmlPhGF/+0RU/WWQ0hoTw6lteyolg7cTFJNjePHznGLUW7MQdMQUu6mU7RxY7Ag3wUfICTPsUARHWEMb88h+mNDjL0xxgReARLjBvpgY5WM4UynIrRQWgzOxB6D5rLTlf9aOqLxlPeOZ65c6+hMXpFUZQr9frR19FJgaczjbTQJvYEzuBJ+QxlpdkEaCGku2OxTvdl28u/JiYtnXmPfeOqD75KKSnPO8belW9SmX+K9kCNwrEeKsKqmZav8YuP9ES2aTiMFg6MHsFruaMpHzGTRWcKeHdPHvFBY9FC7sSDm73+J9kctIp9/idwCTdhthDmlmQwt9FGpi6PhKCjGKM1NLegrcNMYUAU9el6COkeqnFYfbCW5FJhzUY0+xKnFeBnrCNN1OHWbsM4EBu5D5XoFUUZUg6Pg42VG0nXm9lZNB/jpGBitSomNxziYOtt3OkcTU24iVNb/orJ15fbvvcTDMYrT31SSs4eOcieFa9RW1xMfYSbMxO6kLSw8LDGzJMCk0ejMTiK5TOjeT13JnG6EJ48VcqM5gp0xkkQoqPAUsKmoLfZGXgIq76TYEcgN5WncEtdO+P1BUQHH0cfKXE7BU0ePypjQmhNcYLZg+bW6GxIo/5kJm1NyUTYqjEY6rEYztBkDqYAMyYZSrStFoPmAgZ2r14lekVRhtSHxR9ikzZCZQr68Ba2+WXyL/L3FFRNZ5w7CU3zp7LzAzqam7jnP36Nf2jYFbUjNY3CA5+wZ/kr1FdVURrnoGRyKyk1Nh77EFJrNdw6I4WJI1iZnciBsXO5v7SJlQV2QszhYImn3tDA5qANbA3eT7WxAX+nH1OqI7ij2sRY01kigvIQkeB06qk2hFA7wkJ7nAMpBM4OX9oqp1DbMg5Lixtf0X2dmy5RRqmPDoMMJNTRgm9bPRVaCCcCUmg3jud+hNqjVxTl+vbG8TcIwkBe6S3YJyWSpJWQVl1OsfUWstwjKInMp2L/MRZ+/V+IHTX6c69f83jI/3gHn6x8hbrmes4k2WjJbmb6KTePfgT+dkm7bxhbJsbz8qQJjDCn8lhpM78+aUCI0XT6dLIucD9bg/ZzyqcEH7cPs+qC+HmVD+nmMoKD8iEKulxGzgaG0zACOoIlUjPQ1TiSulPjcTSF4OdowWZ0YBUttJr16KQfwa4WjB0tlHtCyfNLo0oXjgwSSAEy2IQI1uPQJJYB3uYq0SuKMmTKreXkd+aTQRSmyA42+sTwlOeXFFVNYpYrnWo/Kyf3v0/2oqWMn7vwc63b43ZxcsdH7Fn5GpWORgqSOvD3b2PhYUl2iQQhqIpM4a1ZcezJmMNDtfBWjQEfXSRuXSif+J9gS9C7HPA/ifAIFtf68eNqQapvKf7+DogEq/ThTEQ4TUluunwNuLqCaakbT3PhSExWF259F006A25ho8lsItDdha6znVIZzilLCrWEgK9A6kALMiFDTISGNJMSkM8oXT4psoAA308GfLurRK8oypB5/djrCAkNNfOon5hFmjxNRIUNT+cIfNyBHDjzF+LHZDDnoScue50up4PjH73PJ6vfptjcQkVMG6OrbPy/dZLINonN7M+R0SksnziW1IAJ3Fvn5Lsl4Qh0nPIrYkvQVnYGHsIpHdxZbeS7+TaS/Ruw+LqREdBi8iM/1oemKIHdZKCzKYW6ogxksw8ezUmL3ohLaGDS469JXF02ionitCGeRhkEZroTe7AZEaInKqSWUQF5ZOpPMU53Bh/suDRBU0coTdZYNE1Dp9MP6HZXiV5RlCHh1tx8UPoBMSKA+FA9eaZwHnc8S1VFNrc6R3GwbSW+gUHc+t0foTd8dmpy2m0cWv8Oe9e9R35wM87INqaddvHoNonRAw0hiayZnkjBuDnc1h7In7r80HcZqTHW83rQOrYG7ceqa+LeCsEbhZ0kBDZjNGt4IgRN/n4Uxwqawo10uQOpr5pA1+EoNDu06Q04hBF0YMGOzeGmQIRTpIulxeMPepB6gRZswhgsiQ2pYHzgMSYa8kmkFJ300GILpL4hnu1t8zhpTeGMNRmPNKDXSb5xLf1gSlEU5fPYXraddq2dgKab+Xj8ZDLkUcxlFtIcYyiz52HtrOMrP/8tvkHBn7oee2cHe9e8xJ5tGykIbybS18odBz2MqAOHwUhp3Gj2ZmYQGz6Ju1qN+DaYadd1sD54D1uD91GjP8t9VR5eKOskLsiK3iBxRehoDLXQGKWnMcREU+MYmqtTcReYsQoDdtF9FoxBb6fNo+MMEZwlCqu7+yqTUted2H1CHCSHlJIbeJRx+lNEUUu7w4f65jjOto5gnXUB+W0jcXi8o/AmgSfIjBxpRAs0EqzrQjcIl/BRiV5RlCHx6tFX8cFAYlAsxwzB/HPnGhzV0wi1Wdhdu5Ul33qKqJGpl3x9V1sru1c9y459O6kLamZsVyf/sl7i64DmwDAOZo6lduxNzHbH8E23GVebi70Bx9kStJ9y4wnurbHzx9MdRAd2odOBI9JATYSZhnATVYYo6iqzcJwOpkMz0+VN7AgXzZgpJIZyTxidru5frEq9QIYYCQzpYFRIMbmBhxmty8fktlFvjaGiLIm11sXkt6ZgdQZ1r8ukwxNkQiYbkQHdST3JUU86drJCgpicOoa0kRMv69vM56USvaIog66us46j1iNEdWawddRMcuU+tOIwpjnSOVD7Frm33sWYmXP6fa21qY5tbz/N9tP70NHClLNOxpdJ3DpBTVQ6J9NziIiawlyHD9ghz6eQ5eH7OWvexx11rfzqbCcR/g6EgK5IAxURFmqC/Clsz6KjLp6OGj86RXcCd0poMPhQIiOpcoVgd3Wf6CgNAoINhIc2MybkDJMCDjGCItrag6lsSyK/MoXVLQtpsIUDAmnSoQUZkQkmhL+eSDoY6W5kjEmSExPL5PRRREdGDdn0hyrRK4oy6N468RYSiAnIJE/nw0LrZqIaFlLe+AlR49K46b6HL3pNc+1ZPnzjt+wtO05sm5W7T7oJ7QCrny+loybiSp9Dhj6eseio0Gp5JXwTpZYdLGiq54d1NsLNDgDaowwUh/pTpE+ktCmTzqpg2qu6h1w6MVBr9qNUC6fOGYTTqQdHd2LXhwhiQxsYF3Kayf778bdZqW5L4HRNCitP3UJVRyweqT+X1GNNGHx1xGJllGghw9/EpKRUJqWl4+s7tFMdXkglekVRBpUmNVYXLSfIncCO5JuZxi44k0Rsu4ECn0Ye+PbT6PTnzjKpLTvGyld/S0XVGUZXd/JkoUQvoToqjuoxs4iJn0mcNGLVdbA+cDtVPpuZ0lbGN612QjqcSKA13Mhxv2hOOjKosY6gvcIPDUGL3kKNJZAKLYRGhz9uhw7sII06zCFukkNqyArNI8OYh83qQ2HbSAoKRrDL+g3sHsu5pB5pwpIoSRHtjDG2kRUWwpS0ZMbFx6HXD+wZMwNBJXpFUQbVJ1Wf0Oyxkup3GyXCwOz6fYxtXsbJ1g3c/Ytf4OMfAEDZ6W28+vL/YqipJLfIwc1N0GXWU5uSSfiIZaT7JeDEzV7fQ1T7fchYWwEP2bsItLvRBDQE+vGxYSQnO7OoaY/GY9VRawyk1hxItSmQ5i4/tC6gC6RR4BfiJCW0nPGBJ4nVqqlui+ZMUzLbzk5hjXPBuaQeaiIgysM4fQcZfg5y40OYlj6W+KCBn8R7sKhEryjKoHrl0HPoRCQHIm9mtraNgMLxNNUfZt43v0FYQhJ5B95k1ct/J7qmmWWFbiwuqAsPpGXiXBLiFhChN3LGVMCRgF+R5D7JHc52fK0abp2g0jeMPZ5RHHeMp73djwqfUGp8/Kk1BdLW4QMd3ukvTIKAkC6SgysY6VOKxd5BaWsCZ8uSWWFbgjTp0QKNEGgkNMxNjtHGhFCNySkJTBkxgiDTwF9RciipRK8oyqBptbeyr/UwMb6P0oxkSmUeiY1TMM+PoaR2M2sf+TapFZ18uVri1ENN8giS4+8iNSSdBl0VR/z/RIQ4wiynFVOnxK4zcNaQwAnXOPK0NAr1MdT5+FJvDKLdakK0did2YYaQECvxATVE6utwtgvKrEmcqk/huHE0WqARnb+BiEAXN1mcTIn1YerocYyPDMM8CDM8DTeV6BVFGTRvn3gdtz6SY2GzWeDZSFLRFApte9CvOkFmiYMlXdAYZKR64mRSo+/CYrHRZFqO0/hzMl1tTHBCh87CMZnBId1YdoWOo0IXRp0tCHubAdGgAaAzS8JDW4nwaSTAY6XV6k9FQwLHm0ejBY7H4KcnOsrFvFSNmSnRTEsfRYq/D7ohOutluKlEryjKoJBS8k7+G0T7PkQHDiYVV+OoambavsMYpUZpUggyaQlJISPoMH2EZvgm6VoLAI2uILabJ/FR0ER26DKp7wzF1SoQld2JXW/RCA9uIdBoRW9zUtceQWNzCPWBkVh8BbFhbhanGrg5cySTk+KJMhmG7FTGa5FK9MoXgpQSCUhAk6Ahe++lBA3QpEQD7/OLyzXvdMdCCATdM90LAQLR+xhAh/CWd9903vqiT/3u8p46os9jbpiEdKTuMJ2eEMrDprHE8QHJBaPwO/U8pZmppMdMYVTAaYJ0LxJJEwAV+kjeDJrHauMsDtrGoLV6EG3d29xgcRMa1IlF2HG0G2jSwqjXIukUkcSFeFg2yodFE0czISaUIKNKaxe6obbImmUzEVJDAgiQQnS/uUX3G1zqzj0H76VBe+tJpPfd2V1fIIX0LutTt8+6NdGzLtAuXAfeOt7hvp7Xat7lmrfuuRjOj0P2WYdEInXn2uxu7/x4NNGdlKSup2+yuw6c3wbn6vW2cV58dPfb22etb1nPdqGnjkTTdcd3Xlve1+AtR3gTqDi3LZDd5d3td7+Zu/si+3nufR0SKc7NLd9bU/R5hehTjvS2eUE90bvUG0/PfW+r3v71Xce5euel4Yumuhe9C8SnTal8wes+LbWLi9q49OsuuR7Zd1k//bjS9V6wrO9jh14QHPw9fGUHM0/Z6bAWkjY/kRzjEYLYjobgpE8yL5sXsto1i+q2YER7d2wmix1fvy6kB9ocATj9fHCaLURZJNPTg7glJ52MyCB89DfeePpguKpEL4RYDPwR0APPSyl/fcFyM/AqkAM0AfdKKUuvps1PY+mwYXR73xhSIqRE572hgZDd80AKqXWXSdBpoJPdr/HmJHTeW/eblfPelJ/nDaBcTOuTceSF99D7QdtfeX+vubC8p+z818jz6/Z53Fu/z/Nz6xbn1+lTt3eHoU/7Pc/7LpMX9qfng8i7e3/xDsSnPL6grX7L+vanZwdACO/Og8CjE94dBgHeHRFN6Lo/1IWu+yqLeO+FrncHSRPi3D2i+wNeeO85t07ZZ302n2jeTM7mto4PiD1rY3HCeziFgT3mDD6Q09nSmUVLS/eplWazk1CfNqxuXzxmH8y+BhJ8LMxMCGdJ1kjGRgejv0G+6QyHK070Qgg98CywAKgEDggh1kopT/Wp9hjQIqVMFUJ8BfgNcO/VBPxp1j/yIB7vB3zfBC363CTnEnq/9Xq+nnv3XPvuTQnpTfzeNXW/trtmb7nssyfnrS96d2Evbu/CGHvaOZdZZO+HUHe9c8t6Yu15d4tzT7qHB7RzwZ/rh0Tnfb30rq/nWwZSounOfZPo7t6F3zA479sRF5aLnm8h5x5r3gB6yru/0YiL63L+N5meby+9iUn2fLsQfep7X9/zDaQn7p7kQ08b516jXfAc6FPmTWQ96+9T1r2+7r+U7LscupOmd5mG8G6Xc8u7t2ef1/eNq8+tZ9v01kF3Ud1z67l4HecvG/693SDZwuzDOmyRp/mG49vsdGfSafPBx+zA1+TAaJH4+OhICbAwKzGRZVkjSI0OuWGGr64VV7NHPxkoklKWAAgh3gZuB/om+tuB//Q+XgE8I4QQUkrJIFidOBWnGOi5WZRrhZCaN51p6HpTW3eZrk9a7FvW87jnprvgee9NXrjevjfN2zbnLe9Nw5KLXgPnl/VbR7uwrDtNd/f1wvWcW6aTPR9t9N53x9jzvGcH49Jx4O0L57XjrSvPj6O37nn96Fl2br06765DdyzdOzdx9Rb+3j6BZt9RBJps+PtopARpLBgZy21ZqSTFhQ/Gv4pygatJ9HFARZ/nlcCUS9WRUrqFEG1AGNB44cqEEE8CTwIkJiZeUUCPFe9HQ0NH9xi16N53RYq+o6XefW/R/bj7wJoEoaN7RFr0LuupLnr2oEXf/flz+9D0rgt6x2a9O95Cdo9363p30IV3ned/1nV/e+gZB+9+8/SOGZ+34671tEB3Te99n68H3e30fFWQ3jZ7xsO7+6v1Joi+324kOtH95td5+9fzLUbXW787KSJE7zCXQCJET4LwJlRvXtAJEBqAhs775hfdL+9Nnr3JxfsNRKd1/x2Q3X9LtJ6ELZCaQNO8Y/6ARwo0DaQUSNl9r/Xc93wLkN50JGV3uXfzyJ5y+jzu+RvIPqlVeo9r9Gz13q96wruZRe//hBTd4yY9x4EEAq3PGM/5abV7j7t7s/Rs5XMfJX3/X3tey3njTn3+/3rbOBej4Px2z/vmSc831gvr9yzpObjUswpd9/+kpPd9de5/DO//TE985/4Xj/s4WDrRhwdm5hCfGI0yPK6Zg7FSyn8A/wDIzc29oj3+/3jiXwY0JkVRlBvB1QziVQEJfZ7He8v6rSOEMABB4D2XSlEURRkSV5PoDwBpQogRQggT8BVg7QV11gIPex/fDWwdrPF5RVEUpX9XPHTjHXP/f8BGuk+vfFFKeVII8XPgoJRyLfAC8JoQoghopvvDQFEURRlCVzVGL6VcD6y/oOxnfR7bgS9fTRuKoijK1Rn+E20VRVGUQaUSvaIoyg1OJXpFUZQbnEr0iqIoNzhxLZ7tKIRoAMqu8OXh9PPL22uAiuvzUXF9Piquz+dGjCtJShnR34JrMtFfDSHEQSll7nDHcSEV1+ej4vp8VFyfzxctLjV0oyiKcoNTiV5RFOUGdyMm+n8MdwCXoOL6fFRcn4+K6/P5QsV1w43RK4qiKOe7EffoFUVRlD5UolcURbnBXbeJXgixWAhRIIQoEkL8qJ/lZiHEO97l+4QQyddIXI8IIRqEEEe9t8eHIKYXhRD1Qoi8SywXQog/eWM+LoSYONgxXWZcc4QQbX221c/6qzcIcSUIIbYJIU4JIU4KIb7dT50h32aXGdeQbzMhhEUIsV8Iccwb13/1U2fI34+XGdeQvx/7tK0XQhwRQnzQz7KB3V7d06tdXze6L4tcDIwETMAxYOwFdb4J/M37+CvAO9dIXI8Azwzx9poFTATyLrF8CbCB7knhpgL7rpG45gAfDMP/Vwww0fs4ADjTz99xyLfZZcY15NvMuw38vY+NwD5g6gV1huP9eDlxDfn7sU/b3wPe7O/vNdDb63rdo++dmFxK6QR6Jibv63bgFe/jFcA8MfhTy19OXENOSrmT7vkALuV24FXZbS8QLISIuQbiGhZSyhop5WHv43Ygn+75j/sa8m12mXENOe826PA+NXpvF57lMeTvx8uMa1gIIeKBpcDzl6gyoNvrek30/U1MfuE//HkTkwM9E5MPd1wAX/J+3V8hhEjoZ/lQu9y4h8M071fvDUKIcUPduPcr8wS69wb7GtZt9ilxwTBsM+8wxFGgHtgspbzk9hrC9+PlxAXD8378P+AHdM87358B3V7Xa6K/nr0PJEspM4HNnPvUVi52mO7rd2QBfwbeG8rGhRD+wErgO1JK61C2/Wk+I65h2WZSSo+UMpvuuaMnCyEyhqLdz3IZcQ35+1EIsQyol1IeGuy2elyvif5anZj8M+OSUjZJKR3ep88DOYMc0+W4nO055KSU1p6v3rJ7NjOjECJ8KNoWQhjpTqZvSClX9VNlWLbZZ8U1nNvM22YrsA1YfMGi4Xg/fmZcw/R+nAHcJoQopXt492YhxOsX1BnQ7XW9JvprdWLyz4zrgnHc2+geZx1ua4GHvGeSTAXapJQ1wx2UECK6Z1xSCDGZ7v/XQU8O3jZfAPKllH+4RLUh32aXE9dwbDMhRIQQItj72AdYAJy+oNqQvx8vJ67heD9KKX8spYyXUibTnSO2Sin/6YJqA7q9rmrO2OEir9GJyS8zrn8RQtwGuL1xPTLYcQkh3qL7bIxwIUQl8B90H5hCSvk3uuf9XQIUAV3Ao4Md02XGdTfwDSGEG7ABXxmCD2vo3uN6EDjhHd8F+AmQ2Ce24dhmlxPXcGyzGOAVIYSe7g+Wd6WUHwz3+/Ey4xry9+OlDOb2UpdAUBRFucFdr0M3iqIoymVSiV5RFOUGpxK9oijKDU4lekVRlBucSvSKoig3OJXoFUVRbnAq0SuKotzg/j/Z1uvsu6EctwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "count = 0\n",
+    "for index, row in X_all_anomalies_scaled.iterrows():\n",
+    "    row.plot()\n",
+    "    count += 1\n",
+    "    if count == limit:\n",
+    "        break"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -2022,7 +2158,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 706,
+   "execution_count": 38,
    "metadata": {
     "scrolled": true
    },
@@ -2031,21 +2167,21 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Model: \"sequential_16\"\n",
+      "Model: \"sequential\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
-      "lstm_69 (LSTM)               (None, 1, 16)             1408      \n",
+      "lstm (LSTM)                  (None, 1, 16)             1408      \n",
       "_________________________________________________________________\n",
-      "lstm_70 (LSTM)               (None, 4)                 336       \n",
+      "lstm_1 (LSTM)                (None, 4)                 336       \n",
       "_________________________________________________________________\n",
-      "repeat_vector_15 (RepeatVect (None, 1, 4)              0         \n",
+      "repeat_vector (RepeatVector) (None, 1, 4)              0         \n",
       "_________________________________________________________________\n",
-      "lstm_71 (LSTM)               (None, 1, 4)              144       \n",
+      "lstm_2 (LSTM)                (None, 1, 4)              144       \n",
       "_________________________________________________________________\n",
-      "lstm_72 (LSTM)               (None, 1, 16)             1344      \n",
+      "lstm_3 (LSTM)                (None, 1, 16)             1344      \n",
       "_________________________________________________________________\n",
-      "time_distributed_15 (TimeDis (None, 1, 5)              85        \n",
+      "time_distributed (TimeDistri (None, 1, 5)              85        \n",
       "=================================================================\n",
       "Total params: 3,317\n",
       "Trainable params: 3,317\n",
@@ -2054,638 +2190,831 @@
       "Starting training; got log keys: []\n",
       "Start epoch 1 of training; got log keys: []\n",
       "Epoch 1/100\n",
-      "11820/11829 [============================>.] - ETA: 0s - loss: 0.0417Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 1 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0417 - val_loss: 0.0226\n",
+      "11828/11829 [============================>.] - ETA: 0s - loss: 0.0493Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from inf to 0.02421671338379383. Saving model to lstm_autoencoder_models/epoch1/ckpt...\n",
+      "11829/11829 [==============================] - 16s 1ms/step - loss: 0.0493 - val_loss: 0.0242\n",
       "Start epoch 2 of training; got log keys: []\n",
       "Epoch 2/100\n",
       "11820/11829 [============================>.] - ETA: 0s - loss: 0.0241Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 2 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0241 - val_loss: 0.0223\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.02421671338379383 to 0.022082993760704994. Saving model to lstm_autoencoder_models/epoch2/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0241 - val_loss: 0.0221\n",
       "Start epoch 3 of training; got log keys: []\n",
       "Epoch 3/100\n",
-      "11802/11829 [============================>.] - ETA: 0s - loss: 0.0233Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 3 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0232 - val_loss: 0.0220\n",
+      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0230Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.022082993760704994\n",
+      "\n",
+      "Val_loss improved from 0.022082993760704994 to 0.02211032435297966. Saving model to lstm_autoencoder_models/epoch3/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0229 - val_loss: 0.0221\n",
       "Start epoch 4 of training; got log keys: []\n",
       "Epoch 4/100\n",
-      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0210Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 4 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0210 - val_loss: 0.0195\n",
+      "11792/11829 [============================>.] - ETA: 0s - loss: 0.0226Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.02211032435297966 to 0.02202053926885128. Saving model to lstm_autoencoder_models/epoch4/ckpt...\n",
+      "11829/11829 [==============================] - 18s 2ms/step - loss: 0.0225 - val_loss: 0.0220\n",
       "Start epoch 5 of training; got log keys: []\n",
       "Epoch 5/100\n",
-      "11812/11829 [============================>.] - ETA: 0s - loss: 0.0202Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 5 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0202 - val_loss: 0.0189\n",
+      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0223Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.02202053926885128 to 0.021334586665034294. Saving model to lstm_autoencoder_models/epoch5/ckpt...\n",
+      "11829/11829 [==============================] - 20s 2ms/step - loss: 0.0223 - val_loss: 0.0213\n",
       "Start epoch 6 of training; got log keys: []\n",
       "Epoch 6/100\n",
-      "11819/11829 [============================>.] - ETA: 0s - loss: 0.0200Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 6 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0200 - val_loss: 0.0187\n",
+      "11816/11829 [============================>.] - ETA: 0s - loss: 0.0221Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.021334586665034294 to 0.021065501496195793. Saving model to lstm_autoencoder_models/epoch6/ckpt...\n",
+      "11829/11829 [==============================] - 20s 2ms/step - loss: 0.0221 - val_loss: 0.0211\n",
       "Start epoch 7 of training; got log keys: []\n",
       "Epoch 7/100\n",
-      "11816/11829 [============================>.] - ETA: 0s - loss: 0.0198Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 7 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0198 - val_loss: 0.0180\n",
+      "11798/11829 [============================>.] - ETA: 0s - loss: 0.0220Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.021065501496195793\n",
+      "\n",
+      "Val_loss improved from 0.021065501496195793 to 0.021560853347182274. Saving model to lstm_autoencoder_models/epoch7/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0219 - val_loss: 0.0216\n",
       "Start epoch 8 of training; got log keys: []\n",
       "Epoch 8/100\n",
-      "11819/11829 [============================>.] - ETA: 0s - loss: 0.0195Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 8 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0195 - val_loss: 0.0186\n",
+      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0218Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.021560853347182274 to 0.02060971036553383. Saving model to lstm_autoencoder_models/epoch8/ckpt...\n",
+      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0218 - val_loss: 0.0206\n",
       "Start epoch 9 of training; got log keys: []\n",
       "Epoch 9/100\n",
-      "11823/11829 [============================>.] - ETA: 0s - loss: 0.0194Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 9 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0194 - val_loss: 0.0174\n",
+      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0217Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.02060971036553383 to 0.02034945972263813. Saving model to lstm_autoencoder_models/epoch9/ckpt...\n",
+      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0217 - val_loss: 0.0203\n",
       "Start epoch 10 of training; got log keys: []\n",
       "Epoch 10/100\n",
-      "11819/11829 [============================>.] - ETA: 0s - loss: 0.0194Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 10 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0194 - val_loss: 0.0180\n",
+      "11811/11829 [============================>.] - ETA: 0s - loss: 0.0216Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.02034945972263813\n",
+      "\n",
+      "Val_loss improved from 0.02034945972263813 to 0.021263886243104935. Saving model to lstm_autoencoder_models/epoch10/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0216 - val_loss: 0.0213\n",
       "Start epoch 11 of training; got log keys: []\n",
       "Epoch 11/100\n",
-      "11829/11829 [==============================] - ETA: 0s - loss: 0.0193Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 11 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0193 - val_loss: 0.0180\n",
+      "11807/11829 [============================>.] - ETA: 0s - loss: 0.0216Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.021263886243104935 to 0.020675359293818474. Saving model to lstm_autoencoder_models/epoch11/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0215 - val_loss: 0.0207\n",
       "Start epoch 12 of training; got log keys: []\n",
       "Epoch 12/100\n",
-      "11805/11829 [============================>.] - ETA: 0s - loss: 0.0193Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 12 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0192 - val_loss: 0.0181\n",
+      "11808/11829 [============================>.] - ETA: 0s - loss: 0.0215Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.020675359293818474 to 0.020428098738193512. Saving model to lstm_autoencoder_models/epoch12/ckpt...\n",
+      "11829/11829 [==============================] - 18s 2ms/step - loss: 0.0215 - val_loss: 0.0204\n",
       "Start epoch 13 of training; got log keys: []\n",
       "Epoch 13/100\n",
-      "11813/11829 [============================>.] - ETA: 0s - loss: 0.0193Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 13 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0193 - val_loss: 0.0183\n",
+      "11823/11829 [============================>.] - ETA: 0s - loss: 0.0214Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.020428098738193512\n",
+      "\n",
+      "Val_loss improved from 0.020428098738193512 to 0.020739659667015076. Saving model to lstm_autoencoder_models/epoch13/ckpt...\n",
+      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0214 - val_loss: 0.0207\n",
       "Start epoch 14 of training; got log keys: []\n",
       "Epoch 14/100\n",
-      "11828/11829 [============================>.] - ETA: 0s - loss: 0.0192Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 14 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0192 - val_loss: 0.0176\n",
+      "11817/11829 [============================>.] - ETA: 0s - loss: 0.0214Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.020739659667015076 to 0.020261360332369804. Saving model to lstm_autoencoder_models/epoch14/ckpt...\n",
+      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0214 - val_loss: 0.0203\n",
       "Start epoch 15 of training; got log keys: []\n",
       "Epoch 15/100\n",
-      "11810/11829 [============================>.] - ETA: 0s - loss: 0.0191Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 15 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0191 - val_loss: 0.0179\n",
+      "11806/11829 [============================>.] - ETA: 0s - loss: 0.0213Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.020261360332369804 to 0.01969141513109207. Saving model to lstm_autoencoder_models/epoch15/ckpt...\n",
+      "11829/11829 [==============================] - 20s 2ms/step - loss: 0.0213 - val_loss: 0.0197\n",
       "Start epoch 16 of training; got log keys: []\n",
       "Epoch 16/100\n",
-      "11828/11829 [============================>.] - ETA: 0s - loss: 0.0191Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 16 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0191 - val_loss: 0.0175\n",
+      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0211Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01969141513109207 to 0.01952601969242096. Saving model to lstm_autoencoder_models/epoch16/ckpt...\n",
+      "11829/11829 [==============================] - 20s 2ms/step - loss: 0.0211 - val_loss: 0.0195\n",
       "Start epoch 17 of training; got log keys: []\n",
       "Epoch 17/100\n",
-      "11829/11829 [==============================] - ETA: 0s - loss: 0.0190Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 17 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0190 - val_loss: 0.0177\n",
+      "11820/11829 [============================>.] - ETA: 0s - loss: 0.0202Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01952601969242096 to 0.019481578841805458. Saving model to lstm_autoencoder_models/epoch17/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0202 - val_loss: 0.0195\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "Start epoch 18 of training; got log keys: []\n",
       "Epoch 18/100\n",
-      "11816/11829 [============================>.] - ETA: 0s - loss: 0.0190Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 18 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0190 - val_loss: 0.0170\n",
+      "11806/11829 [============================>.] - ETA: 0s - loss: 0.0197Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.019481578841805458\n",
+      "\n",
+      "Val_loss improved from 0.019481578841805458 to 0.019737521186470985. Saving model to lstm_autoencoder_models/epoch18/ckpt...\n",
+      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0197 - val_loss: 0.0197\n",
       "Start epoch 19 of training; got log keys: []\n",
       "Epoch 19/100\n",
-      "11811/11829 [============================>.] - ETA: 0s - loss: 0.0189Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 19 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0189 - val_loss: 0.0174\n",
+      "11824/11829 [============================>.] - ETA: 0s - loss: 0.0195Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.019737521186470985 to 0.019115794450044632. Saving model to lstm_autoencoder_models/epoch19/ckpt...\n",
+      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0194 - val_loss: 0.0191\n",
       "Start epoch 20 of training; got log keys: []\n",
       "Epoch 20/100\n",
-      "11809/11829 [============================>.] - ETA: 0s - loss: 0.0189Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 20 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0188 - val_loss: 0.0179\n",
+      "11820/11829 [============================>.] - ETA: 0s - loss: 0.0193Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.019115794450044632 to 0.017812732607126236. Saving model to lstm_autoencoder_models/epoch20/ckpt...\n",
+      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0193 - val_loss: 0.0178\n",
       "Start epoch 21 of training; got log keys: []\n",
       "Epoch 21/100\n",
-      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0188Start testing; got log keys: []\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Stop testing; got log keys: []\n",
-      "End epoch 21 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 29s 2ms/step - loss: 0.0188 - val_loss: 0.0170\n",
+      "11822/11829 [============================>.] - ETA: 0s - loss: 0.0191Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.017812732607126236\n",
+      "\n",
+      "Val_loss improved from 0.017812732607126236 to 0.018614426255226135. Saving model to lstm_autoencoder_models/epoch21/ckpt...\n",
+      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0191 - val_loss: 0.0186\n",
       "Start epoch 22 of training; got log keys: []\n",
       "Epoch 22/100\n",
-      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0188Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 22 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0188 - val_loss: 0.0169\n",
+      "11829/11829 [==============================] - ETA: 0s - loss: 0.0191Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.018614426255226135 to 0.01791161671280861. Saving model to lstm_autoencoder_models/epoch22/ckpt...\n",
+      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0191 - val_loss: 0.0179\n",
       "Start epoch 23 of training; got log keys: []\n",
       "Epoch 23/100\n",
-      "11823/11829 [============================>.] - ETA: 0s - loss: 0.0187Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 23 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0187 - val_loss: 0.0170\n",
+      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0190Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01791161671280861\n",
+      "\n",
+      "Val_loss improved from 0.01791161671280861 to 0.01848003827035427. Saving model to lstm_autoencoder_models/epoch23/ckpt...\n",
+      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0190 - val_loss: 0.0185\n",
       "Start epoch 24 of training; got log keys: []\n",
       "Epoch 24/100\n",
-      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0188Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 24 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0187 - val_loss: 0.0180\n",
+      "11817/11829 [============================>.] - ETA: 0s - loss: 0.0189Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01848003827035427 to 0.017717035487294197. Saving model to lstm_autoencoder_models/epoch24/ckpt...\n",
+      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0189 - val_loss: 0.0177\n",
       "Start epoch 25 of training; got log keys: []\n",
       "Epoch 25/100\n",
-      "11823/11829 [============================>.] - ETA: 0s - loss: 0.0187Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 25 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0187 - val_loss: 0.0172\n",
+      "11809/11829 [============================>.] - ETA: 0s - loss: 0.0188Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.017717035487294197\n",
+      "\n",
+      "Val_loss improved from 0.017717035487294197 to 0.018744952976703644. Saving model to lstm_autoencoder_models/epoch25/ckpt...\n",
+      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0188 - val_loss: 0.0187\n",
       "Start epoch 26 of training; got log keys: []\n",
       "Epoch 26/100\n",
-      "11817/11829 [============================>.] - ETA: 0s - loss: 0.0187Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 26 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0187 - val_loss: 0.0179\n",
+      "11824/11829 [============================>.] - ETA: 0s - loss: 0.0188Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.018744952976703644 to 0.01823248714208603. Saving model to lstm_autoencoder_models/epoch26/ckpt...\n",
+      "11829/11829 [==============================] - 21s 2ms/step - loss: 0.0188 - val_loss: 0.0182\n",
       "Start epoch 27 of training; got log keys: []\n",
       "Epoch 27/100\n",
-      "11808/11829 [============================>.] - ETA: 0s - loss: 0.0186Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 27 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0186 - val_loss: 0.0179\n",
+      "11820/11829 [============================>.] - ETA: 0s - loss: 0.0187Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01823248714208603 to 0.017900099977850914. Saving model to lstm_autoencoder_models/epoch27/ckpt...\n",
+      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0187 - val_loss: 0.0179\n",
       "Start epoch 28 of training; got log keys: []\n",
       "Epoch 28/100\n",
-      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0186Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 28 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0186 - val_loss: 0.0182\n",
+      "11813/11829 [============================>.] - ETA: 0s - loss: 0.0187Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.017900099977850914\n",
+      "\n",
+      "Val_loss improved from 0.017900099977850914 to 0.01814698800444603. Saving model to lstm_autoencoder_models/epoch28/ckpt...\n",
+      "11829/11829 [==============================] - 21s 2ms/step - loss: 0.0187 - val_loss: 0.0181\n",
       "Start epoch 29 of training; got log keys: []\n",
       "Epoch 29/100\n",
-      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0186Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 29 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 30s 3ms/step - loss: 0.0186 - val_loss: 0.0182\n",
+      "11806/11829 [============================>.] - ETA: 0s - loss: 0.0187Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01814698800444603 to 0.017594940960407257. Saving model to lstm_autoencoder_models/epoch29/ckpt...\n",
+      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0187 - val_loss: 0.0176\n",
       "Start epoch 30 of training; got log keys: []\n",
       "Epoch 30/100\n",
       "11812/11829 [============================>.] - ETA: 0s - loss: 0.0186Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 30 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 30s 3ms/step - loss: 0.0186 - val_loss: 0.0175\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017594940960407257 to 0.017346585169434547. Saving model to lstm_autoencoder_models/epoch30/ckpt...\n",
+      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0186 - val_loss: 0.0173\n",
       "Start epoch 31 of training; got log keys: []\n",
       "Epoch 31/100\n",
-      "11812/11829 [============================>.] - ETA: 0s - loss: 0.0185Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 31 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0185 - val_loss: 0.0171\n",
+      "11824/11829 [============================>.] - ETA: 0s - loss: 0.0186Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.017346585169434547\n",
+      "\n",
+      "Val_loss improved from 0.017346585169434547 to 0.017511915415525436. Saving model to lstm_autoencoder_models/epoch31/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0186 - val_loss: 0.0175\n",
       "Start epoch 32 of training; got log keys: []\n",
       "Epoch 32/100\n",
-      "11806/11829 [============================>.] - ETA: 0s - loss: 0.0185Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 32 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0185 - val_loss: 0.0171\n",
+      "11799/11829 [============================>.] - ETA: 0s - loss: 0.0186Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.017511915415525436\n",
+      "\n",
+      "Val_loss improved from 0.017511915415525436 to 0.019037645310163498. Saving model to lstm_autoencoder_models/epoch32/ckpt...\n",
+      "11829/11829 [==============================] - 20s 2ms/step - loss: 0.0186 - val_loss: 0.0190\n",
       "Start epoch 33 of training; got log keys: []\n",
       "Epoch 33/100\n",
-      "11820/11829 [============================>.] - ETA: 0s - loss: 0.0185Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 33 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0185 - val_loss: 0.0173\n",
+      "11807/11829 [============================>.] - ETA: 0s - loss: 0.0186Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.019037645310163498 to 0.01732838898897171. Saving model to lstm_autoencoder_models/epoch33/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0186 - val_loss: 0.0173\n",
       "Start epoch 34 of training; got log keys: []\n",
       "Epoch 34/100\n",
-      "11827/11829 [============================>.] - ETA: 0s - loss: 0.0185Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 34 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0185 - val_loss: 0.0175\n",
+      "11810/11829 [============================>.] - ETA: 0s - loss: 0.0185Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01732838898897171\n",
+      "\n",
+      "Val_loss improved from 0.01732838898897171 to 0.017366938292980194. Saving model to lstm_autoencoder_models/epoch34/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0185 - val_loss: 0.0174\n",
       "Start epoch 35 of training; got log keys: []\n",
       "Epoch 35/100\n",
-      "11811/11829 [============================>.] - ETA: 0s - loss: 0.0185Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 35 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0184 - val_loss: 0.0169\n",
+      "11806/11829 [============================>.] - ETA: 0s - loss: 0.0185Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.017366938292980194\n",
+      "\n",
+      "Val_loss improved from 0.017366938292980194 to 0.017969714477658272. Saving model to lstm_autoencoder_models/epoch35/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0185 - val_loss: 0.0180\n",
       "Start epoch 36 of training; got log keys: []\n",
       "Epoch 36/100\n",
-      "11818/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 36 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0184 - val_loss: 0.0171\n",
+      "11822/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017969714477658272 to 0.017544521018862724. Saving model to lstm_autoencoder_models/epoch36/ckpt...\n",
+      "11829/11829 [==============================] - 20s 2ms/step - loss: 0.0184 - val_loss: 0.0175\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "Start epoch 37 of training; got log keys: []\n",
       "Epoch 37/100\n",
-      "11808/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 37 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0184 - val_loss: 0.0171\n",
+      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017544521018862724 to 0.016994567587971687. Saving model to lstm_autoencoder_models/epoch37/ckpt...\n",
+      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0184 - val_loss: 0.0170\n",
       "Start epoch 38 of training; got log keys: []\n",
       "Epoch 38/100\n",
-      "11822/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 38 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0184 - val_loss: 0.0171\n",
+      "11820/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016994567587971687 to 0.016888383775949478. Saving model to lstm_autoencoder_models/epoch38/ckpt...\n",
+      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0184 - val_loss: 0.0169\n",
       "Start epoch 39 of training; got log keys: []\n",
       "Epoch 39/100\n",
-      "11817/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 39 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0184 - val_loss: 0.0169\n",
+      "11802/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016888383775949478 to 0.01681835763156414. Saving model to lstm_autoencoder_models/epoch39/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0183 - val_loss: 0.0168\n",
       "Start epoch 40 of training; got log keys: []\n",
       "Epoch 40/100\n",
-      "11829/11829 [==============================] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 40 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 29s 2ms/step - loss: 0.0184 - val_loss: 0.0171\n",
+      "11810/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01681835763156414\n",
+      "\n",
+      "Val_loss improved from 0.01681835763156414 to 0.0170427355915308. Saving model to lstm_autoencoder_models/epoch40/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0183 - val_loss: 0.0170\n",
       "Start epoch 41 of training; got log keys: []\n",
       "Epoch 41/100\n",
-      "11818/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 41 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0184 - val_loss: 0.0168\n",
+      "11803/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.0170427355915308\n",
+      "\n",
+      "Val_loss improved from 0.0170427355915308 to 0.017071200534701347. Saving model to lstm_autoencoder_models/epoch41/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0183 - val_loss: 0.0171\n",
       "Start epoch 42 of training; got log keys: []\n",
       "Epoch 42/100\n",
-      "11813/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 42 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 30s 3ms/step - loss: 0.0183 - val_loss: 0.0171\n",
+      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.017071200534701347\n",
+      "\n",
+      "Val_loss improved from 0.017071200534701347 to 0.017888473346829414. Saving model to lstm_autoencoder_models/epoch42/ckpt...\n",
+      "11829/11829 [==============================] - 18s 2ms/step - loss: 0.0183 - val_loss: 0.0179\n",
       "Start epoch 43 of training; got log keys: []\n",
       "Epoch 43/100\n",
-      "11822/11829 [============================>.] - ETA: 0s - loss: 0.0184Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 43 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0184 - val_loss: 0.0169\n",
+      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017888473346829414 to 0.01693646050989628. Saving model to lstm_autoencoder_models/epoch43/ckpt...\n",
+      "11829/11829 [==============================] - 18s 2ms/step - loss: 0.0183 - val_loss: 0.0169\n",
       "Start epoch 44 of training; got log keys: []\n",
       "Epoch 44/100\n",
-      "11807/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 44 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0183 - val_loss: 0.0173\n",
+      "11801/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01693646050989628\n",
+      "\n",
+      "Val_loss improved from 0.01693646050989628 to 0.01731625571846962. Saving model to lstm_autoencoder_models/epoch44/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0182 - val_loss: 0.0173\n",
       "Start epoch 45 of training; got log keys: []\n",
-      "Epoch 45/100\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 45 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0183 - val_loss: 0.0171\n",
+      "Epoch 45/100\n",
+      "11812/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01731625571846962 to 0.01690022647380829. Saving model to lstm_autoencoder_models/epoch45/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0182 - val_loss: 0.0169\n",
       "Start epoch 46 of training; got log keys: []\n",
       "Epoch 46/100\n",
-      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 46 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0183 - val_loss: 0.0169\n",
+      "11798/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01690022647380829 to 0.016762780025601387. Saving model to lstm_autoencoder_models/epoch46/ckpt...\n",
+      "11829/11829 [==============================] - 18s 2ms/step - loss: 0.0182 - val_loss: 0.0168\n",
       "Start epoch 47 of training; got log keys: []\n",
       "Epoch 47/100\n",
-      "11805/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 47 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0183 - val_loss: 0.0177\n",
+      "11817/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016762780025601387\n",
+      "\n",
+      "Val_loss improved from 0.016762780025601387 to 0.017068488523364067. Saving model to lstm_autoencoder_models/epoch47/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0182 - val_loss: 0.0171\n",
       "Start epoch 48 of training; got log keys: []\n",
       "Epoch 48/100\n",
-      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 48 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0183 - val_loss: 0.0169\n",
+      "11827/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017068488523364067 to 0.016707269474864006. Saving model to lstm_autoencoder_models/epoch48/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0181 - val_loss: 0.0167\n",
       "Start epoch 49 of training; got log keys: []\n",
       "Epoch 49/100\n",
-      "11808/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 49 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0183 - val_loss: 0.0174\n",
+      "11808/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016707269474864006\n",
+      "\n",
+      "Val_loss improved from 0.016707269474864006 to 0.017999764531850815. Saving model to lstm_autoencoder_models/epoch49/ckpt...\n",
+      "11829/11829 [==============================] - 18s 2ms/step - loss: 0.0181 - val_loss: 0.0180\n",
       "Start epoch 50 of training; got log keys: []\n",
       "Epoch 50/100\n",
-      "11809/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 50 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0183 - val_loss: 0.0167\n",
+      "11829/11829 [==============================] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017999764531850815 to 0.01727534644305706. Saving model to lstm_autoencoder_models/epoch50/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0181 - val_loss: 0.0173\n",
       "Start epoch 51 of training; got log keys: []\n",
       "Epoch 51/100\n",
-      "11811/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 51 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 36s 3ms/step - loss: 0.0183 - val_loss: 0.0175\n",
+      "11805/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01727534644305706 to 0.01663380302488804. Saving model to lstm_autoencoder_models/epoch51/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0181 - val_loss: 0.0166\n",
       "Start epoch 52 of training; got log keys: []\n",
       "Epoch 52/100\n",
-      "11820/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 52 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 33s 3ms/step - loss: 0.0183 - val_loss: 0.0168\n",
+      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01663380302488804\n",
+      "\n",
+      "Val_loss improved from 0.01663380302488804 to 0.016700366511940956. Saving model to lstm_autoencoder_models/epoch52/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0181 - val_loss: 0.0167\n",
       "Start epoch 53 of training; got log keys: []\n",
       "Epoch 53/100\n",
-      "11809/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 53 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 32s 3ms/step - loss: 0.0182 - val_loss: 0.0172\n",
+      "11828/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016700366511940956\n",
+      "\n",
+      "Val_loss improved from 0.016700366511940956 to 0.01683039963245392. Saving model to lstm_autoencoder_models/epoch53/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0181 - val_loss: 0.0168\n",
       "Start epoch 54 of training; got log keys: []\n",
       "Epoch 54/100\n",
-      "11804/11829 [============================>.] - ETA: 0s - loss: 0.0183Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 54 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0182 - val_loss: 0.0169\n",
+      "11806/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01683039963245392 to 0.016651000827550888. Saving model to lstm_autoencoder_models/epoch54/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0180 - val_loss: 0.0167\n",
       "Start epoch 55 of training; got log keys: []\n",
       "Epoch 55/100\n",
-      "11807/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 55 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0182 - val_loss: 0.0170\n",
+      "11825/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016651000827550888 to 0.016631711274385452. Saving model to lstm_autoencoder_models/epoch55/ckpt...\n",
+      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0180 - val_loss: 0.0166\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "Start epoch 56 of training; got log keys: []\n",
       "Epoch 56/100\n",
-      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 56 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0182 - val_loss: 0.0171\n",
+      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016631711274385452 to 0.016589757055044174. Saving model to lstm_autoencoder_models/epoch56/ckpt...\n",
+      "11829/11829 [==============================] - 21s 2ms/step - loss: 0.0180 - val_loss: 0.0166\n",
       "Start epoch 57 of training; got log keys: []\n",
       "Epoch 57/100\n",
-      "11816/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 57 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0182 - val_loss: 0.0168\n",
-      "Start epoch 58 of training; got log keys: []\n",
+      "11809/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016589757055044174\n",
+      "\n",
+      "Val_loss improved from 0.016589757055044174 to 0.017587164416909218. Saving model to lstm_autoencoder_models/epoch57/ckpt...\n",
+      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0180 - val_loss: 0.0176\n",
+      "Start epoch 58 of training; got log keys: []\n",
       "Epoch 58/100\n",
-      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 58 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 33s 3ms/step - loss: 0.0182 - val_loss: 0.0165\n",
+      "11818/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017587164416909218 to 0.01724269799888134. Saving model to lstm_autoencoder_models/epoch58/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0180 - val_loss: 0.0172\n",
       "Start epoch 59 of training; got log keys: []\n",
       "Epoch 59/100\n",
-      "11816/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 59 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 29s 2ms/step - loss: 0.0182 - val_loss: 0.0173\n",
+      "11822/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01724269799888134 to 0.016623767092823982. Saving model to lstm_autoencoder_models/epoch59/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0180 - val_loss: 0.0166\n",
       "Start epoch 60 of training; got log keys: []\n",
       "Epoch 60/100\n",
-      "11812/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 60 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0182 - val_loss: 0.0170\n",
+      "11810/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016623767092823982 to 0.016575925052165985. Saving model to lstm_autoencoder_models/epoch60/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0179 - val_loss: 0.0166\n",
       "Start epoch 61 of training; got log keys: []\n",
       "Epoch 61/100\n",
-      "11829/11829 [==============================] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 61 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0182 - val_loss: 0.0170\n",
+      "11807/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016575925052165985 to 0.01655130833387375. Saving model to lstm_autoencoder_models/epoch61/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0180 - val_loss: 0.0166\n",
       "Start epoch 62 of training; got log keys: []\n",
       "Epoch 62/100\n",
-      "11810/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 62 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0182 - val_loss: 0.0173\n",
+      "11819/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01655130833387375\n",
+      "\n",
+      "Val_loss improved from 0.01655130833387375 to 0.017422642558813095. Saving model to lstm_autoencoder_models/epoch62/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0180 - val_loss: 0.0174\n",
       "Start epoch 63 of training; got log keys: []\n",
       "Epoch 63/100\n",
-      "11810/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 63 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0182 - val_loss: 0.0166\n",
+      "11811/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017422642558813095 to 0.01710696332156658. Saving model to lstm_autoencoder_models/epoch63/ckpt...\n",
+      "11829/11829 [==============================] - 21s 2ms/step - loss: 0.0179 - val_loss: 0.0171\n",
       "Start epoch 64 of training; got log keys: []\n",
       "Epoch 64/100\n",
-      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 64 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0182 - val_loss: 0.0168\n",
+      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01710696332156658 to 0.016519803553819656. Saving model to lstm_autoencoder_models/epoch64/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0179 - val_loss: 0.0165\n",
       "Start epoch 65 of training; got log keys: []\n",
       "Epoch 65/100\n",
-      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 65 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0182 - val_loss: 0.0170\n",
+      "11805/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016519803553819656\n",
+      "\n",
+      "Val_loss improved from 0.016519803553819656 to 0.017281226813793182. Saving model to lstm_autoencoder_models/epoch65/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0179 - val_loss: 0.0173\n",
       "Start epoch 66 of training; got log keys: []\n",
       "Epoch 66/100\n",
-      "11813/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 66 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0182 - val_loss: 0.0171\n",
+      "11828/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017281226813793182 to 0.016663815826177597. Saving model to lstm_autoencoder_models/epoch66/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0179 - val_loss: 0.0167\n",
       "Start epoch 67 of training; got log keys: []\n",
       "Epoch 67/100\n",
-      "11813/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 67 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0182 - val_loss: 0.0172\n",
+      "11800/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016663815826177597 to 0.01645437814295292. Saving model to lstm_autoencoder_models/epoch67/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0179 - val_loss: 0.0165\n",
       "Start epoch 68 of training; got log keys: []\n",
       "Epoch 68/100\n",
-      "11828/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 68 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0182 - val_loss: 0.0167\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "11824/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01645437814295292\n",
+      "\n",
+      "Val_loss improved from 0.01645437814295292 to 0.0170237235724926. Saving model to lstm_autoencoder_models/epoch68/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0179 - val_loss: 0.0170\n",
       "Start epoch 69 of training; got log keys: []\n",
       "Epoch 69/100\n",
-      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 69 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0181 - val_loss: 0.0167\n",
+      "11797/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.0170237235724926 to 0.01673063449561596. Saving model to lstm_autoencoder_models/epoch69/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0179 - val_loss: 0.0167\n",
       "Start epoch 70 of training; got log keys: []\n",
       "Epoch 70/100\n",
-      "11823/11829 [============================>.] - ETA: 0s - loss: 0.0182Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 70 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0181 - val_loss: 0.0167\n",
+      "11803/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01673063449561596\n",
+      "\n",
+      "Val_loss improved from 0.01673063449561596 to 0.017014453187584877. Saving model to lstm_autoencoder_models/epoch70/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0179 - val_loss: 0.0170\n",
       "Start epoch 71 of training; got log keys: []\n",
       "Epoch 71/100\n",
-      "11811/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 71 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0181 - val_loss: 0.0166\n",
+      "11803/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017014453187584877 to 0.01634257659316063. Saving model to lstm_autoencoder_models/epoch71/ckpt...\n",
+      "11829/11829 [==============================] - 19s 2ms/step - loss: 0.0179 - val_loss: 0.0163\n",
       "Start epoch 72 of training; got log keys: []\n",
       "Epoch 72/100\n",
-      "11816/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 72 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0181 - val_loss: 0.0168\n",
+      "11818/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01634257659316063\n",
+      "\n",
+      "Val_loss improved from 0.01634257659316063 to 0.017760466784238815. Saving model to lstm_autoencoder_models/epoch72/ckpt...\n",
+      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0178 - val_loss: 0.0178\n",
       "Start epoch 73 of training; got log keys: []\n",
       "Epoch 73/100\n",
-      "11825/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 73 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0181 - val_loss: 0.0168\n",
+      "11824/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017760466784238815 to 0.017020009458065033. Saving model to lstm_autoencoder_models/epoch73/ckpt...\n",
+      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0178 - val_loss: 0.0170\n",
       "Start epoch 74 of training; got log keys: []\n",
       "Epoch 74/100\n",
-      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 74 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0181 - val_loss: 0.0176\n",
+      "11819/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.017020009458065033\n",
+      "\n",
+      "Val_loss improved from 0.017020009458065033 to 0.017456064000725746. Saving model to lstm_autoencoder_models/epoch74/ckpt...\n",
+      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0179 - val_loss: 0.0175\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "Start epoch 75 of training; got log keys: []\n",
       "Epoch 75/100\n",
-      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 75 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0181 - val_loss: 0.0167\n",
+      "11812/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017456064000725746 to 0.01633012294769287. Saving model to lstm_autoencoder_models/epoch75/ckpt...\n",
+      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0179 - val_loss: 0.0163\n",
       "Start epoch 76 of training; got log keys: []\n",
       "Epoch 76/100\n",
-      "11820/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 76 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0181 - val_loss: 0.0172\n",
+      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01633012294769287\n",
+      "\n",
+      "Val_loss improved from 0.01633012294769287 to 0.017236266285181046. Saving model to lstm_autoencoder_models/epoch76/ckpt...\n",
+      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0178 - val_loss: 0.0172\n",
       "Start epoch 77 of training; got log keys: []\n",
       "Epoch 77/100\n",
-      "11808/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 77 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0181 - val_loss: 0.0167\n",
+      "11808/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017236266285181046 to 0.016524748876690865. Saving model to lstm_autoencoder_models/epoch77/ckpt...\n",
+      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0178 - val_loss: 0.0165\n",
       "Start epoch 78 of training; got log keys: []\n",
       "Epoch 78/100\n",
-      "11829/11829 [==============================] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 78 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0181 - val_loss: 0.0168\n",
+      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016524748876690865\n",
+      "\n",
+      "Val_loss improved from 0.016524748876690865 to 0.016610639169812202. Saving model to lstm_autoencoder_models/epoch78/ckpt...\n",
+      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0178 - val_loss: 0.0166\n",
       "Start epoch 79 of training; got log keys: []\n",
       "Epoch 79/100\n",
-      "11816/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 79 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 38s 3ms/step - loss: 0.0181 - val_loss: 0.0166\n",
+      "11800/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016610639169812202\n",
+      "\n",
+      "Val_loss improved from 0.016610639169812202 to 0.016977529972791672. Saving model to lstm_autoencoder_models/epoch79/ckpt...\n",
+      "11829/11829 [==============================] - 29s 2ms/step - loss: 0.0178 - val_loss: 0.0170\n",
       "Start epoch 80 of training; got log keys: []\n",
       "Epoch 80/100\n",
-      "11817/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 80 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 33s 3ms/step - loss: 0.0181 - val_loss: 0.0173\n",
+      "11819/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016977529972791672 to 0.016668355092406273. Saving model to lstm_autoencoder_models/epoch80/ckpt...\n",
+      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0178 - val_loss: 0.0167\n",
       "Start epoch 81 of training; got log keys: []\n",
       "Epoch 81/100\n",
-      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 81 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 32s 3ms/step - loss: 0.0181 - val_loss: 0.0167\n",
+      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0179Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016668355092406273 to 0.01654655672609806. Saving model to lstm_autoencoder_models/epoch81/ckpt...\n",
+      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0178 - val_loss: 0.0165\n",
       "Start epoch 82 of training; got log keys: []\n",
       "Epoch 82/100\n",
-      "11811/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 82 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 33s 3ms/step - loss: 0.0180 - val_loss: 0.0171\n",
+      "11823/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01654655672609806\n",
+      "\n",
+      "Val_loss improved from 0.01654655672609806 to 0.016577215865254402. Saving model to lstm_autoencoder_models/epoch82/ckpt...\n",
+      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0178 - val_loss: 0.0166\n",
       "Start epoch 83 of training; got log keys: []\n",
       "Epoch 83/100\n",
-      "11820/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 83 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 34s 3ms/step - loss: 0.0181 - val_loss: 0.0171\n",
+      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016577215865254402 to 0.016444455832242966. Saving model to lstm_autoencoder_models/epoch83/ckpt...\n",
+      "11829/11829 [==============================] - 21s 2ms/step - loss: 0.0178 - val_loss: 0.0164\n",
       "Start epoch 84 of training; got log keys: []\n",
       "Epoch 84/100\n",
-      "11823/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 84 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 30s 3ms/step - loss: 0.0181 - val_loss: 0.0164\n",
+      "11824/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016444455832242966\n",
+      "\n",
+      "Val_loss improved from 0.016444455832242966 to 0.017008185386657715. Saving model to lstm_autoencoder_models/epoch84/ckpt...\n",
+      "11829/11829 [==============================] - 29s 2ms/step - loss: 0.0178 - val_loss: 0.0170\n",
       "Start epoch 85 of training; got log keys: []\n",
       "Epoch 85/100\n",
-      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 85 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0181 - val_loss: 0.0171\n",
+      "11805/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.017008185386657715 to 0.016670383512973785. Saving model to lstm_autoencoder_models/epoch85/ckpt...\n",
+      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0178 - val_loss: 0.0167\n",
       "Start epoch 86 of training; got log keys: []\n",
       "Epoch 86/100\n",
-      "11803/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 86 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0180 - val_loss: 0.0170\n",
+      "11815/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016670383512973785\n",
+      "\n",
+      "Val_loss improved from 0.016670383512973785 to 0.01704159751534462. Saving model to lstm_autoencoder_models/epoch86/ckpt...\n",
+      "11829/11829 [==============================] - 24s 2ms/step - loss: 0.0178 - val_loss: 0.0170\n",
       "Start epoch 87 of training; got log keys: []\n",
       "Epoch 87/100\n",
-      "11819/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 87 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0180 - val_loss: 0.0173\n",
+      "11798/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01704159751534462 to 0.01633460633456707. Saving model to lstm_autoencoder_models/epoch87/ckpt...\n",
+      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0178 - val_loss: 0.0163\n",
       "Start epoch 88 of training; got log keys: []\n",
       "Epoch 88/100\n",
-      "11819/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 88 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0180 - val_loss: 0.0165\n",
+      "11824/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01633460633456707\n",
+      "\n",
+      "Val_loss improved from 0.01633460633456707 to 0.01676095649600029. Saving model to lstm_autoencoder_models/epoch88/ckpt...\n",
+      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0178 - val_loss: 0.0168\n",
       "Start epoch 89 of training; got log keys: []\n",
       "Epoch 89/100\n",
-      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 89 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0180 - val_loss: 0.0165\n",
+      "11823/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01676095649600029\n",
+      "\n",
+      "Val_loss improved from 0.01676095649600029 to 0.01677265390753746. Saving model to lstm_autoencoder_models/epoch89/ckpt...\n",
+      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0178 - val_loss: 0.0168\n",
       "Start epoch 90 of training; got log keys: []\n",
       "Epoch 90/100\n",
-      "11827/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 90 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 31s 3ms/step - loss: 0.0180 - val_loss: 0.0171\n",
+      "11800/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01677265390753746\n",
+      "\n",
+      "Val_loss improved from 0.01677265390753746 to 0.016860900446772575. Saving model to lstm_autoencoder_models/epoch90/ckpt...\n",
+      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0178 - val_loss: 0.0169\n",
       "Start epoch 91 of training; got log keys: []\n",
       "Epoch 91/100\n",
-      "11818/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 91 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0180 - val_loss: 0.0165\n",
+      "11807/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016860900446772575 to 0.01667620800435543. Saving model to lstm_autoencoder_models/epoch91/ckpt...\n",
+      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0178 - val_loss: 0.0167\n",
       "Start epoch 92 of training; got log keys: []\n",
       "Epoch 92/100\n",
-      "11810/11829 [============================>.] - ETA: 0s - loss: 0.0181Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 92 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0180 - val_loss: 0.0168\n"
+      "11823/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01667620800435543 to 0.016661861911416054. Saving model to lstm_autoencoder_models/epoch92/ckpt...\n",
+      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0178 - val_loss: 0.0167\n",
+      "Start epoch 93 of training; got log keys: []\n",
+      "Epoch 93/100\n",
+      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016661861911416054\n",
+      "\n",
+      "Val_loss improved from 0.016661861911416054 to 0.01683807000517845. Saving model to lstm_autoencoder_models/epoch93/ckpt...\n",
+      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0178 - val_loss: 0.0168\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Start epoch 93 of training; got log keys: []\n",
-      "Epoch 93/100\n",
-      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 93 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0180 - val_loss: 0.0164\n",
       "Start epoch 94 of training; got log keys: []\n",
       "Epoch 94/100\n",
-      "11819/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 94 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 35s 3ms/step - loss: 0.0180 - val_loss: 0.0174\n",
+      "11826/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.01683807000517845 to 0.016545960679650307. Saving model to lstm_autoencoder_models/epoch94/ckpt...\n",
+      "11829/11829 [==============================] - 27s 2ms/step - loss: 0.0178 - val_loss: 0.0165\n",
       "Start epoch 95 of training; got log keys: []\n",
       "Epoch 95/100\n",
-      "11816/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 95 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0180 - val_loss: 0.0166\n",
+      "11799/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016545960679650307 to 0.016485299915075302. Saving model to lstm_autoencoder_models/epoch95/ckpt...\n",
+      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0178 - val_loss: 0.0165\n",
       "Start epoch 96 of training; got log keys: []\n",
       "Epoch 96/100\n",
-      "11825/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 96 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0180 - val_loss: 0.0172\n",
+      "11808/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016485299915075302 to 0.01647641509771347. Saving model to lstm_autoencoder_models/epoch96/ckpt...\n",
+      "11829/11829 [==============================] - 22s 2ms/step - loss: 0.0178 - val_loss: 0.0165\n",
       "Start epoch 97 of training; got log keys: []\n",
       "Epoch 97/100\n",
-      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 97 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 25s 2ms/step - loss: 0.0180 - val_loss: 0.0166\n",
+      "11813/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01647641509771347\n",
+      "\n",
+      "Val_loss improved from 0.01647641509771347 to 0.016712285578250885. Saving model to lstm_autoencoder_models/epoch97/ckpt...\n",
+      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0177 - val_loss: 0.0167\n",
       "Start epoch 98 of training; got log keys: []\n",
       "Epoch 98/100\n",
-      "11806/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 98 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 32s 3ms/step - loss: 0.0180 - val_loss: 0.0166\n",
+      "11829/11829 [==============================] - ETA: 0s - loss: 0.0177Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss improved from 0.016712285578250885 to 0.01637931726872921. Saving model to lstm_autoencoder_models/epoch98/ckpt...\n",
+      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0177 - val_loss: 0.0164\n",
       "Start epoch 99 of training; got log keys: []\n",
       "Epoch 99/100\n",
-      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 99 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 26s 2ms/step - loss: 0.0180 - val_loss: 0.0165\n",
+      "11821/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.01637931726872921\n",
+      "\n",
+      "Val_loss improved from 0.01637931726872921 to 0.016686936840415. Saving model to lstm_autoencoder_models/epoch99/ckpt...\n",
+      "11829/11829 [==============================] - 23s 2ms/step - loss: 0.0178 - val_loss: 0.0167\n",
       "Start epoch 100 of training; got log keys: []\n",
       "Epoch 100/100\n",
-      "11814/11829 [============================>.] - ETA: 0s - loss: 0.0180Start testing; got log keys: []\n",
-      "Stop testing; got log keys: []\n",
-      "End epoch 100 of training; got log keys: ['loss', 'val_loss']\n",
-      "11829/11829 [==============================] - 28s 2ms/step - loss: 0.0180 - val_loss: 0.0164\n",
-      "Stop training; got log keys: []\n"
+      "11822/11829 [============================>.] - ETA: 0s - loss: 0.0178Start testing; got log keys: []\n",
+      "Stop testing; got log keys: ['loss']\n",
+      "\n",
+      "Val_loss did not improve from 0.016686936840415\n",
+      "\n",
+      "Val_loss improved from 0.016686936840415 to 0.016705887392163277. Saving model to lstm_autoencoder_models/epoch100/ckpt...\n",
+      "11829/11829 [==============================] - 29s 2ms/step - loss: 0.0178 - val_loss: 0.0167\n",
+      "Stop training; got log keys: ['loss', 'val_loss']\n"
      ]
     }
    ],
    "source": [
+    "from pathlib import Path\n",
+    "import datetime\n",
+    "now = datetime.datetime.utcnow()\n",
+    "current_path = Path().cwd()\n",
+    "\n",
     "tot_epochs = 100\n",
     "selected_batch_size = 1\n",
     "\n",
-    "history, lstm_autoencoder = train_model(\n",
-    "    x_train=x_train_healthy,\n",
+    "history, lstm_autoencoder = train(\n",
+    "    x_train_data=x_train_healthy,\n",
     "    tot_epochs=tot_epochs,\n",
     "    selected_batch_size=selected_batch_size\n",
     ")"
@@ -2700,12 +3029,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 720,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -2738,9 +3067,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 721,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib/python3.6/site-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -2752,7 +3089,7 @@
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1280x720 with 1 Axes>"
       ]
@@ -2764,7 +3101,7 @@
     }
    ],
    "source": [
-    "x_train_pred = lstm_autoencoder.predict(x_train_healthy)\n",
+    "x_train_pred = predict_results(lstm_autoencoder, x_train_healthy)\n",
     "x_train_pred_ = x_train_pred.reshape(x_train_pred.shape[0], x_train_pred.shape[2])\n",
     "x_train_healthy_ = x_train_healthy.reshape(x_train_healthy.shape[0], x_train_healthy.shape[2])\n",
     "train_mae_loss = np.mean(np.abs(x_train_pred_ - x_train_healthy_), axis=1)\n",
@@ -2793,18 +3130,204 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 792,
+   "execution_count": 41,
+   "metadata": {
+    "scrolled": false
+   },
+   "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>threshold</th>\n",
+       "      <th>percentage_anomalies_test</th>\n",
+       "      <th>percentage_anomalies_val</th>\n",
+       "      <th>f1_score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.001420</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.018913</td>\n",
+       "      <td>8.644222</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.036406</td>\n",
+       "      <td>7.825296</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.053899</td>\n",
+       "      <td>7.825296</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.071392</td>\n",
+       "      <td>7.643312</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0.088886</td>\n",
+       "      <td>6.778890</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>0.106379</td>\n",
+       "      <td>4.458599</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0.123872</td>\n",
+       "      <td>2.820746</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>0.141365</td>\n",
+       "      <td>0.591447</td>\n",
+       "      <td>99.761905</td>\n",
+       "      <td>0.998808</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   threshold  percentage_anomalies_test  percentage_anomalies_val  f1_score\n",
+       "0   0.001420                 100.000000                100.000000  1.000000\n",
+       "1   0.018913                   8.644222                100.000000  1.000000\n",
+       "2   0.036406                   7.825296                100.000000  1.000000\n",
+       "3   0.053899                   7.825296                100.000000  1.000000\n",
+       "4   0.071392                   7.643312                100.000000  1.000000\n",
+       "5   0.088886                   6.778890                100.000000  1.000000\n",
+       "6   0.106379                   4.458599                100.000000  1.000000\n",
+       "7   0.123872                   2.820746                100.000000  1.000000\n",
+       "8   0.141365                   0.591447                 99.761905  0.998808"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results_summary = []\n",
+    "from numpy import arange, mean\n",
+    "\n",
+    "for threshold_ in arange(min(train_mae_loss), max(train_mae_loss), mean(train_mae_loss)):\n",
+    "    x_test_pred = predict_results(lstm_autoencoder, x_test_healthy)\n",
+    "\n",
+    "    x_test_pred_ = x_test_pred.reshape(x_test_pred.shape[0], x_test_pred.shape[2])\n",
+    "    x_test_healthy_ = x_test_healthy.reshape(x_test_healthy.shape[0], x_test_healthy.shape[2])\n",
+    "\n",
+    "    test_mae_loss = np.mean(np.abs(x_test_pred_ - x_test_healthy_), axis=1)\n",
+    "\n",
+    "    scored_test = {}\n",
+    "    scored_test['Loss_mae'] = test_mae_loss\n",
+    "    scored_test['Threshold'] = threshold_\n",
+    "    scored_t = pd.DataFrame(scored_test)\n",
+    "    scored_t['Healthy_pred'] = scored_t['Loss_mae'] < scored_t['Threshold']\n",
+    "    scored_t['Healthy_pred_int'] = scored_t['Healthy_pred'].astype(int)\n",
+    "\n",
+    "    scored_t['Target'] = y_test_healthy.values\n",
+    "    no_anomalies = scored_t[scored_t['Healthy_pred_int'] == 0]\n",
+    "    percentage_identified = no_anomalies.shape[0]/scored_t.shape[0]\n",
+    "    \n",
+    "    start = time()\n",
+    "    x_all_pred = predict_results(lstm_autoencoder, x_all_anomalies)\n",
+    "    end = time()\n",
+    "\n",
+    "    x_all_pred_ = x_all_pred.reshape(x_all_pred.shape[0], x_all_pred.shape[2])\n",
+    "    x_all_anomalies_ = x_all_anomalies.reshape(x_all_anomalies.shape[0], x_all_anomalies.shape[2])\n",
+    "\n",
+    "    all_mae_loss = np.mean(np.abs(x_all_pred_ - x_all_anomalies_), axis=1)\n",
+    "\n",
+    "    scored_test = {}\n",
+    "    scored_test['Loss_mae'] = all_mae_loss\n",
+    "    scored_test['Threshold'] = threshold_\n",
+    "    scored_a = pd.DataFrame(scored_test)\n",
+    "    scored_a['Anomaly_pred'] = scored_a['Loss_mae'] > scored_a['Threshold']\n",
+    "    scored_a['Anomaly_pred_int'] = scored_a['Anomaly_pred'].astype(int)\n",
+    "\n",
+    "    scored_a['Target'] = y_all_anomalies.values\n",
+    "\n",
+    "    with_anomalies = scored_a[scored_a['Anomaly_pred_int'] == 1]\n",
+    "    percentage_identified_val_set = with_anomalies.shape[0]/scored_a.shape[0]\n",
+    "\n",
+    "    f1_score_ = f1_score(scored_a['Target'], scored_a['Anomaly_pred_int'])\n",
+    "\n",
+    "    result_summary = {\n",
+    "        \"threshold\": threshold_,\n",
+    "        \"percentage_anomalies_test\": percentage_identified*100,\n",
+    "        \"percentage_anomalies_val\": percentage_identified_val_set*100,\n",
+    "        \"f1_score\": f1_score_\n",
+    "    }\n",
+    "    \n",
+    "    results_summary.append(result_summary)\n",
+    "\n",
+    "pd.DataFrame(results_summary)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
-    "threshold = 0.030"
+    "threshold = 0.136306"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 793,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib/python3.6/site-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -2816,7 +3339,7 @@
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1280x720 with 1 Axes>"
       ]
@@ -2828,7 +3351,7 @@
     }
    ],
    "source": [
-    "x_test_pred = lstm_autoencoder.predict(x_test_healthy)\n",
+    "x_test_pred = predict_results(lstm_autoencoder, x_test_healthy)\n",
     "\n",
     "x_test_pred_ = x_test_pred.reshape(x_test_pred.shape[0], x_test_pred.shape[2])\n",
     "x_test_healthy_ = x_test_healthy.reshape(x_test_healthy.shape[0], x_test_healthy.shape[2])\n",
@@ -2858,14 +3381,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 794,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Percentage of anomalies in healthy data identified: 7.87%\n"
+      "Percentage of anomalies in healthy data identified: 1.09%\n"
      ]
     }
    ],
@@ -2875,16 +3398,23 @@
     "print(f\"Percentage of anomalies in healthy data identified: {percentage_identified*100:.2f}%\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Predict anomalies"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 795,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Made predictions in 0.0407 seconds.\n"
+      "Made predictions in 0.0602 seconds.\n"
      ]
     },
     {
@@ -2918,40 +3448,40 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>0.103365</td>\n",
-       "      <td>0.03</td>\n",
+       "      <td>0.484086</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>True</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>0.339458</td>\n",
-       "      <td>0.03</td>\n",
+       "      <td>0.455965</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>True</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>0.084965</td>\n",
-       "      <td>0.03</td>\n",
+       "      <td>0.397048</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>True</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>0.276226</td>\n",
-       "      <td>0.03</td>\n",
+       "      <td>0.705545</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>True</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>0.273821</td>\n",
-       "      <td>0.03</td>\n",
+       "      <td>0.577181</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>True</td>\n",
        "      <td>1</td>\n",
        "      <td>1</td>\n",
@@ -2962,21 +3492,21 @@
       ],
       "text/plain": [
        "   Loss_mae  Threshold  Anomaly_pred  Anomaly_pred_int  Target\n",
-       "0  0.103365       0.03          True                 1       1\n",
-       "1  0.339458       0.03          True                 1       1\n",
-       "2  0.084965       0.03          True                 1       1\n",
-       "3  0.276226       0.03          True                 1       1\n",
-       "4  0.273821       0.03          True                 1       1"
+       "0  0.484086   0.136306          True                 1       1\n",
+       "1  0.455965   0.136306          True                 1       1\n",
+       "2  0.397048   0.136306          True                 1       1\n",
+       "3  0.705545   0.136306          True                 1       1\n",
+       "4  0.577181   0.136306          True                 1       1"
       ]
      },
-     "execution_count": 795,
+     "execution_count": 45,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "start = time()\n",
-    "x_all_pred = lstm_autoencoder.predict(x_all_anomalies)\n",
+    "x_all_pred = predict_results(lstm_autoencoder, x_all_anomalies)\n",
     "end = time()\n",
     "\n",
     "# Print and return results\n",
@@ -3000,7 +3530,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 796,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
@@ -3034,56 +3564,56 @@
        "    <tr>\n",
        "      <th>count</th>\n",
        "      <td>420.000000</td>\n",
-       "      <td>4.200000e+02</td>\n",
+       "      <td>420.000000</td>\n",
        "      <td>420.000000</td>\n",
        "      <td>420.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
-       "      <td>0.263620</td>\n",
-       "      <td>3.000000e-02</td>\n",
-       "      <td>0.978571</td>\n",
+       "      <td>2.234482</td>\n",
+       "      <td>0.136306</td>\n",
+       "      <td>0.997619</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
-       "      <td>0.129270</td>\n",
-       "      <td>1.042075e-17</td>\n",
-       "      <td>0.144981</td>\n",
+       "      <td>1.047440</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.048795</td>\n",
        "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
-       "      <td>0.015536</td>\n",
-       "      <td>3.000000e-02</td>\n",
+       "      <td>0.136188</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
-       "      <td>0.149017</td>\n",
-       "      <td>3.000000e-02</td>\n",
+       "      <td>1.768499</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
-       "      <td>0.278706</td>\n",
-       "      <td>3.000000e-02</td>\n",
+       "      <td>2.384155</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
-       "      <td>0.371289</td>\n",
-       "      <td>3.000000e-02</td>\n",
+       "      <td>3.152145</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
-       "      <td>0.499539</td>\n",
-       "      <td>3.000000e-02</td>\n",
+       "      <td>3.906270</td>\n",
+       "      <td>0.136306</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
@@ -3092,18 +3622,18 @@
        "</div>"
       ],
       "text/plain": [
-       "         Loss_mae     Threshold  Anomaly_pred_int  Target\n",
-       "count  420.000000  4.200000e+02        420.000000   420.0\n",
-       "mean     0.263620  3.000000e-02          0.978571     1.0\n",
-       "std      0.129270  1.042075e-17          0.144981     0.0\n",
-       "min      0.015536  3.000000e-02          0.000000     1.0\n",
-       "25%      0.149017  3.000000e-02          1.000000     1.0\n",
-       "50%      0.278706  3.000000e-02          1.000000     1.0\n",
-       "75%      0.371289  3.000000e-02          1.000000     1.0\n",
-       "max      0.499539  3.000000e-02          1.000000     1.0"
+       "         Loss_mae   Threshold  Anomaly_pred_int  Target\n",
+       "count  420.000000  420.000000        420.000000   420.0\n",
+       "mean     2.234482    0.136306          0.997619     1.0\n",
+       "std      1.047440    0.000000          0.048795     0.0\n",
+       "min      0.136188    0.136306          0.000000     1.0\n",
+       "25%      1.768499    0.136306          1.000000     1.0\n",
+       "50%      2.384155    0.136306          1.000000     1.0\n",
+       "75%      3.152145    0.136306          1.000000     1.0\n",
+       "max      3.906270    0.136306          1.000000     1.0"
       ]
      },
-     "execution_count": 796,
+     "execution_count": 46,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3114,9 +3644,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 797,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib/python3.6/site-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+      "  warnings.warn(msg, FutureWarning)\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -3128,7 +3666,7 @@
     },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAABAkAAAJWCAYAAAA6D96ZAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAAxOAAAMTgF/d4wjAABpd0lEQVR4nO3dd5jU1cH28e9ZehdBBcXeY6HZFbuCDWOJ3cQkiiUajcmTmGae9JgnGmsUNPaWKPaGsfdKsTcMIiIqiqB02PP+cWZfVqTswuyeKd/Pdc01zOzszL37Y3dn7jklxBiRJEmSJEmqyR1AkiRJkiSVBksCSZIkSZIEWBJIkiRJkqQCSwJJkiRJkgRYEkiSJEmSpAJLAkmSJEmSBFgSSJIkSZKkAksCSZKWQwhhrRBCDCH8bzM+5iMhhHELXTcuhPBIc2UoPOb/Fr72tZrzcQUhhGMK3/ud613n8ZAkLTdLAklSkwgh7Fx4wXJa7iwNFUK4spC57jQzhPBhCOHhEMKvQwirFfnx/jeE8M1i3mexhRD6FHKulTvL0oQQ/lk4bo/kziJJUrmyJJAk6euOB44GTgLOBaYCZwJvhhCOWui27wHtgD8sw+P8BvjmMnzensCGy/B5y6IPKedai/jYH0hf+3vNlGWxQggdgEOAscCOIYR1MkfKoWSOhySpfLXMHUCSpBL07xjj5/WvCCF8A7gXuDKE8F6M8XGAGGMEZjVHqBBCxxjjlzHGOc3xeEsTY5wHzMudo+BgoCOwO/AIcAyp2KkaJXY8JEllypEEkqTsQgg7hRAeCCFMCyHMCCE8H0I4fBG32yGEMCKE8HEIYVYIYUII4Y4Qwmb1brNmYdrA+BDC7BDCRyGEx0MIBy1Pxhjja6QXni2A39Z7vK+tSRBCqAkh/DiE8HII4csQwtQQwushhAvrf07h5t+pN71h3ML3GUI4MoQwOoQwi8JohUWtSVDvsbcMITwaQphe+D5dFELouNBtFvn59aaIHFO4/L/AFYUPP1wv5//WfXxRc+BDCL1DCLeHED4rHKeXQwinhBDConKEEFYLIfy78H36IoRwawhh1UUficX6LvBcjPFZ4A7S9/Vrz3Ma+5ghhLVDCNcW/h/NDiG8FUL4TQih9UK3q5uq0j2EcE3ha58aQrguhNC58H/i1yGE9wrfk6dCCJsudB+dQgh/CCE8F0L4tHC7N0IIvwwhLPWNnSUcj9VCCMMKPy9zCj8bfw8hdFrodk3ysyNJKi+OJJAkZRVC2A+4FZgI/B8wHTgKuD6E0CvG+H+F220E3A+8DfwVmAL0BHYBNgJeLryQuh9YAbiENOy6G9AX2BYYvjxZY4wPF15cDwghdIgxTl/MTX9FKhKuAS4ilfLrAoMKH/+ENJ3hGuBxYFjh+i8Xup8DgNWAfxTu55OlROxF+vr/VTgNIE2Z2CiEsHth1ENj3EL6Hg8B/gS8Xrj+pcV9QghhC+BRYHa9zAcA55OO0w8W+pQOhds/DvwM2BQ4EegM7NaQkCGEdYEdgVMKV11FmnqwG/CfRXxKgx4zhLAm8CzQiXQM3iWNVPhfYMsQwn6L+J7eR5ry8EvS/7vjgNbAx0A/4BygC/BT4NYQwkYxxvmFz10N+D5wM3A16f/NQFI5tDZwbEO+H/UVCoOngQBcBowHNil8vduGEAbEGOc29c+OJKl8WBJIkrIJIbQALgSmAVvFGCcVrv8H8BTwhxDCtTHGD0nz8NsBe8QYP653N/XXAvgGsAFwaIzx300U+yXS/Px1gJcXc5tvAvfGGL+90PU/BiiUC9eGEK4B3o0xXruY+9kY2DTG+FYDs60LnBJjvLBw+R8hhInA6aTh+Dc18H4o5HwphPA0qST4T4zxkQZ82nmkF8VbxRhfBQhpBMUdwEkhhCtijC/Uu3134M8xxnPqrghplMXJhRfQbzTgMY8B5gI3Fi6PACaRRhcsqiRo6GP+CVgJGBhjvL9w3UUhhIuBE4AD+fqL58djjD+qd79dgYNIZcOAwpQAQgifkv7v70EqFiCVEKvX3abg/BDCVcB3QwhnxhgnNuD7Ud8FhfM+dT9fhcd/ELidVMhdQfP87EiSyoDTDSRJOfUH1gAuq/8CJsY4Czib9GJzn8LVUwvnBy1h6HXdbfYKIXRpgrwAXxTOOy/hNlOBTUK9aRDL6K5GFASQypZhC133f4Xzby5nlqUKIawMbAfcWlcQAMQYa4E/LybHfNKIg/oeLpyv14DHrAG+A9wTY/y08HjzgeuBA0IIKyzi05b6mIX7HQw8X68gqFNXTB2wiPu+cKHLT5Lexb90oRf/TxbO16+7IsY4p16J0CqEsGIIoTup6KgBtljE4y1W4WvfG7gNmFeYCtG9cJ9PkUbt7FG4eXP87EiSyoAlgSQpp7UL568u4mN119WtUn8j8ABp2PdnIYR7QwinhhBWqfuEGON7wB9JLxo/Kcz7/t3Cc7+XU9087mlLuM0vSKMeXgohvBvS1nwHLGqO/FK808jbv7vwooaF8uVzFnwfm1JjjmedD2OMsxe67rPCebcGPOZuwOrAIyGE9epOwBNAW+CwRXxOQx5zJdJCiF/7WmKMH5BeVC/qezpuocufF84X3nGg7voV618Z0toNr5IWw/yUNF3jmsKHV1jE4y3JBqTneicU7mfhUwdgFWi2nx1JUhmwJJAklYUY4+wY4x7ANiwYZfA34K0Qws71bvcr0ruzPwE+BE4FxoQQflKkKJuTVpB/dwlZnya9gDyYNJR8B9L8/qdCCO0a8VgzliPnkixubYIWTfR4SzJ/CR8LS/hYne8Vzs8lrVdRd7ploY8X8zEXq976Ag19zP//eCGEH5PWbniPtJbBPqR3+n9WuEljn7fV3f6qwv0s6vTTetmb+mdHklQGXJNAkpRT3QvtbyziY99Y6DYAFFavfxYghLA+MIq0kNzO9W4zlvRi6/yQVvZ/FPhTCOH85dk+MISwC2k9goeWsGhhXYYvSfPVhxc+9+ekOe6HAlcua4alWCeE0Lr+1xhC6EF6B7r+9/Ez0iJ6X/v8RVzXmMUO/1s4b/DxXB6F4fTfBO5m0d/T3YATQgib1J/+0ECfkKaWfO1rCWkXhC4U8WspOIr0Pdy3MEWj7vHWXcb7e4d0/FrGGB9oyCc01c+OJKl8OJJAkpTTSNJq698LIaxUd2UIoQ1psb05pBeAFOZRL+xd0rDvboXbdAkhtKp/g8KL9beBViyYKtBoIYRvkF6Izgd+s5TbLirrqMJ5/SH0XwJdlzXTInQmLTJY3/8Uzm+vd93bQOcQQv+6K0La0u+kRdxn3Y4LS81ZWFDyKdJaABvWu+8a4IzCxVuXdj+NcDhpSsE/Yow3L3wi7YIBaQHDRim8SL8T2KpQDtX3i8J5Mb8WWDDaoP7ognbAD5flzmKMk0kjWQ4JIXytFAohtAwhrFj4d5P97EiSyosjCSRJTW2PwjuSC/tvjPG6EMLJpBdbz4cQLiUNsT+K9E73Tws7GwD8KoSwJ+mF239Jf8MOBFYlragPaTvEoSGE4cCbhfvalrQd3r11C9s1wCEhhBmFx6hbjG8f0rZ+x8QYn1jK579e2BXgOdLWjr1IW85N56svLJ8Fdg8h/A/wPjA9xnhnAzMuyljg94V55GNI2wIeRno3+OZ6txtG2mnhthDCeaR3m48ilTILewGoBX5eWKl/BvBKjPGVxWQ4tfB4TxZ2qajbAnEX0ov5F5fj61vYd0kl0SLfJY8x/jeEMBo4KoRwxkILBzbEL0hD8u8OIVxE+n+3O+nruZsFUxqK5RbSugD3hBBuIa1XcAwLFstcFieS1md4KoRwJen/RRvSAo0Hkr7GKynez44kqcxZEkiSmtrehdPCHgSuizHeGULYHfg16d3mlsArwJExxuvr3f52UiFwGOmF+wzSi5mj620hOIa0kvsuwNGkd2TfA84k7U/fUEML53OAKcAbwO+BfxYWrVuas0mlwqmkd/c/Iq2e/8cYY/0h6j8gLcR4JmmRvPdIJciymkB6d/1vpK9/BmnP+5/WH74eY3w3hHAQ6QXpn0jzz4eSSouvvOCOMb4XQjiONC9+KOn4/JZ0jL4mxvhCCGF74HfAKUB70rvRp7JgO77lFkLYBNgSuH4pw+BvKWTZh6+Opliqwte+NWk3g2NIUwzeI01v+XOMsTFTMRriLNK6EN8lDfl/n7Q94bMseivHpSp8Df1IZcDgwn1/Sfo6rib9HELxfnYkSWUuFP/vmyRJkiRJKkeuSSBJkiRJkgBLAkmSJEmSVGBJIEmSJEmSAEsCSZIkSZJUYEkgSZIkSZIASwJJkiRJklTQMneAOm3atIkrrbRS7hiNMnv2bNq0aZM7hpqZx706edyrk8e9Onncq5PHvTp53KuTxx0++OCDOTHGRX4TSqYkWGmllZgwYULuGI0yYsQIBg4cmDuGmpnHvTp53KuTx706edyrk8e9Onncq5PHHUIInyzuY043kCRJkiRJgCWBJEmSJEkqsCSQJEmSJEmAJYEkSZIkSSqwJJAkSZIkSYAlgSRJkiRJKrAkkCRJkiRJgCWBJEmSJEkqsCSQJEmSJEmAJYEkSZIkSSqwJJAkSZIkSYAlgSRJkiRJKrAkkCRJkiRJgCWBJEmSJEkqsCSQJEmSJEmAJYEkSZIkSSqwJJAkSZIkSYAlgSRJkiRJKrAkkCRJkiRJgCWBJEmSJEkqsCSQJEmSJEmAJYEkSZIkSSqwJJAkSZIkSYAlgSRJkiRJKmiZO4AkSZK0KMOGNd9jde/+1ccbMqT5HluSSokjCSRJkiRJEmBJIEmSJEmSCiwJJEmSJEkSYEkgSZIkSZIKLAkkSZIkSRJgSSBJkiRJkgosCSRJkiRJEmBJIEmSJEmSCiwJJEmSJEkSYEkgSZIkSZIKLAkkSZIkSRJgSSBJkiRJkgosCSRJkiRJEmBJIEmSJEmSCiwJJEmSJEkSAC1zB5AkSdLSDRuWO4EkqRo4kkCSJEmSJAGWBJIkSZIkqcCSQJIkSZIkAY0oCUII94cQXgohjA4hPB5C6LuY230/hPB2CGFsCOHSEEKr4sWVJEmSJElNpTEjCQ6JMW4eY+wDnANcufANQghrA78HBgDrAasAQ5Y/piRJkiRJamoNLglijJ/Xu9gFiIu42cHAHTHGSTHGCFwCHL5cCSVJkiRJUrNo1BaIIYSrgV0KF/dexE3WAN6rd3lc4TpJkiRJklTiQnrDv5GfFMJ3gENjjHsvdP0FwMQY458Ll78B3Bdj/FpREEI4HTi97nKHDh1WGz58eKOz5DRr1izatm2bO4aamce9Onncq5PHvTqV6nGfPj13gspWUzOL2toFx71Dh4xh1GxK9eddTcvjDoMGDfogxthrUR9bppIAIIQwE+gVY/y03nX/A6wbYzyhcHlv4Bcxxh2Wdn+9evWKEyZMWKYsuYwYMYKBAwfmjqFm5nGvTh736uRxr06letyHDcudoLJ17z6CyZMXHPchrqpVFUr1511Ny+MOIYTFlgQNWpMghLBCCGHVepe/CXwKfLbQTYcDg0MIPUIIATgBuHGZUkuSJEmSpGbV0DUJugA3hRDaAbXAJ8C+McYYQriMtFjhHTHGd0MIvwGeLHzeI8DQYoeWJEmSJEnF16CSIMb4HrDVYj527EKXLwUuXf5okiRJkiSpOTV4C0RJkiRJklTZLAkkSZIkSRJgSSBJkiRJkgosCSRJkiRJEmBJIEmSJEmSCiwJJEmSJEkSYEkgSZIkSZIKLAkkSZIkSRJgSSBJkiRJkgosCSRJkiRJEmBJIEmSJEmSCiwJJEmSJEkSYEkgSZIkSZIKLAkkSZIkSRJgSSBJkiRJkgosCSRJkiRJEmBJIEmSJEmSCiwJJEmSJEkSYEkgSZIkSZIKLAkkSZIkSRIALXMHkCRJUvmZPx+mT4cvvoAvv4QZM6B7d+jZE1r6DFOSypa/wiVJkrRIc+bAa6/B66/D1KmpEKhfCsT49c9p0SIVBauvDr16LTjv0KH580uSGs+SQJIkSf/fzJnw8sswahS88koqCgBCSC/0O3WCVVdN5506QceO6bxdO/j4Y3j//XR6+umv3m+3bqkw2GIL6N8fapz0KkklyZJAkiSpyk2bBi+9lIqB119PUwlCgHXXhb59oXfv9CK/MS/sv/wylQUTJiwoDl56CUaPhjvvhEGDYOut08gDSVLpsCSQJEmqQjGmF+wPPQRvv50u19TARhstKAa6dFn2++/YETbeOJ3qfPklPPhgesyrroK77oKBA2G77aBVq+X+kiRJRWBJIEmSVEVihFdfhdtvh/Hj04vz3r1TMbDZZk27dkDHjrD//rDHHvDII/DAA3D99XDPPem6HXeE1q2b7vElSUtnSSBJklQl3nwzlQNjx6YdCHbbLQ3779y5eXO0bw977w277gqPPw733w833QT33Qe77w477wxt2zZvJklSYkkgSZJU4d59N5UDb7yRphTsuGN6kd61a95cbdumEQQ77QRPPgkjRsCtt6Z/n3hiWiBRktS8LAkkSZIq1PjxcMcdabeCEGCbbWDffWGllXIn+6rWrWGXXWDAAHj4YbjlFvjLX+CYY6Bfv9zpJKm6WBJIkiRVmJkz0/D9J59Ml/v3h/32g5498+ZampYt08iCNdeEYcNg6FDYay8YPNgtEyWpuVgSSJIkVZBXX4VrroEpU9JOBQcfDKuvnjtV42ywAfziF6kkuPfeNCLi+99v2kUVJUmJnawkSVIFmDkzlQPnnw8zZsCRR8Jpp5VfQVBnxRXhJz9J2yO++ir8+c/wwQe5U0lS5XMkgSRJUpl77TW4+uo0emDjjeHoo6Fbt9ypll+rVvDtb6fpB//6F5x1FnznO2n6hCSpaVgSSJIklamZM2H48LSNYJs2afTAgAFpkcJKEULaErFXrzT9YNiwtG3j/vu7ToEkNQVLAkmSpDL0+utp9MBnn8GGG6Z33Lt3z52q6ay33oJ1Cu67DyZNgiFDoEWL3MkkqbLYv0qSJJWRefPS0Ptzz4Xp0+GII9LaA5VcENTp2hV+/GPYcksYPRquvx5izJ1KkiqLIwkkSZLKxJQpabj9u++md9a/+93qKAfqa9Uqfd3Tp8MTT8AKK6TtHSVJxeFIAkmSpDLwxhvwxz+mgmDPPeH006uvIKjTogUcfzyssQbcdVdak0GSVByWBJIkSSWsthb+8pc0vWDu3PTi+KCDnIvfti2cckoqSq67Dl56KXciSaoMlgSSJEkl6vPP4YAD4Oc/h54908J9/frlTlU6OneGH/4QOnRYMA1DkrR8LAkkSZJK0JgxsMUWcMcdaWvDM86AVVbJnar0rLIKnHxy2irxwgvTrgeSpGVnSSBJklRirroKttkGxo+Hiy6Ca66BNm1ypypda6+dtkOcORPOPx+mTs2dSJLKlyWBJElSiZg7F046CY45Js21f/zxdDmE3MlK32abwVFHwaefwgUXpMJAktR4lgSSJEkl4LPPYNAguPhi2HVXGDkStt46d6rysv32MHgwvP8+DB0K8+blTiRJ5ceSQJIkKbM330zTCx56KI0cuO8+WGml3KnK0957w4AB8PrrcO21udNIUvmxJJAkScrogQdSQfDuu2nhvYsuglatcqcqXyHA4YfDppvC00/Dc8/lTiRJ5cWSQJIkKZOLL05TDGKEe+6BH/wgd6LK0KJFWtehc2e44QaYMiV3IkkqH5YEkiRJzWzePDjllDS1YK214JlnYM89c6eqLJ06wdFHw4wZcOWVUFubO5EklQdLAkmSpGb0+eewzz5pasHOO8Ozz8JGG+VOVZk23xx22AHeeAMeeSR3GkkqD5YEkiRJzeSdd2DbbeH+++G442DECOjWLXeqyvatb6XtJG+5BT78MHcaSSp9lgSSJEnN4PHH05aGb70F556btuhr3Tp3qsrXti1897tpisfll8P8+bkTSVJpsySQJElqYtdfD7vvDnPmwJ13wqmnplX41TzWWw8GDoTx4+Huu3OnkaTSZkkgSZLURGKE3/8ejjwSVloJnngC9t47d6rqtN9+sPrqcO+9abtJSdKiWRJIkiQ1gTlz0jD3M8+EPn3SAoW9e+dOVb1atoTvfQ9qauCKK2D27NyJJKk0WRJIkiQV2ZQpaXj7VVelnQwefxxWWy13Kq26KhxwAHz8MQwfnjuNJJUmSwJJkqQievfdtIPBI4/AySfDbbdBx465U6nOrrvChhvCo4/CK6/kTiNJpceSQJIkqUiefnrBDgbnnQcXXJCGuat01NTAMcekXQ+uugq+/DJ3IkkqLZYEkiRJRfDvf8Muu8CMGWn0wA9/mDuRFmfFFeHww2HaNLjuutxpJKm0WBJIkiQthxjhz3+GQw+Frl3hscdg8ODcqbQ0W28NffvCyJHw2mu500hS6bAkkCRJWkZz5sD3vw+/+AVstlnawaB//9yp1BAhwCGHQKtWcNNNMH9+yB1JkkqCJYEkSdIymDIFBg1K2+kNGgRPPAFrrJE7lRpjxRVhzz1h4kR44AG3n5AksCSQJElqtHffhe22g4cfhpNOgjvvhM6dc6fSsthzT+jSBW68cX1mzMidRpLysySQJElqhKeeSvPZ33wT/v53uPBCdzAoZ23bwgEHwLRprbnnntxpJCk/SwJJkqQGuuEG2HXXBTsYnHZamtuu8rb11rDuulN56CH4+OPcaSQpL0sCSZKkpYgR/vAHOOII6NYNHn/cHQwqSU0NHHPMG8yfD8OH504jSXk5OE6SJGkJZs+G44+Hq66C3r3hrrugV6/cqVRs3/jG5/TvDy++mKaSSFK1ciSBJEnSYnzyCey+eyoI9tknjSCwIKhcBx6Y1pf4979h/vzcaSQpD0sCSZKkRXjlFdhqq7S14Y9+BLffDp065U6lptS9eyqFJkxIW1tKUjVyuoFUpYYNy/fYQ4bke2xJxZXrd0lT/x65+2447DCYNQsuvRSOPbZpH0+lY9CgtIPFj38M06dDu3bN+/j+jZSUmyMJJEmSCmKE4cPXZL/9oHVr+M9/LAiqTbt2sP/+MG0a3Hdf7jSS1PwsCSRJkoA5c1IhcOmlG7HRRvDcc7DzzrlTKYfttktrTzzwAEyenDuNJDUvSwJJklT1Jk+GPfaAyy+H/v0n8/TTsO66uVMpl5oaOOQQmDcPbrkldxpJal6WBJIkqaq9+mpaoPCxx+DUU+F3vxtJly65Uym3DTeEPn3Slohvv507jSQ1nwaVBCGEtiGE20IIb4UQxoQQ/hNCWG8Rt1srhDA/hDC63skeXpIklaS77oJtt4X334dLLoFzz4UWLWLuWCoRBx0ELVqkLRFra3OnkaTm0ZiRBMOADWOMvYHbgcsWc7svYox96p3GLndKSZKkIooR/vQnGDwYWrWCESPg+ONzp1KpWXll2GUXGD8exozJnUaSmkeDSoIY46wY4z0xxrpq/RlgrSZLJUmS1ESmT0/bG/7yl7DppvD887DrrrlTqVQNHJiKpLvvTuWSJFW6ZV2T4FTSaIJF6RBCeD6EMDKEcGYIocUyPoYkSVJRjRsH22+fho8fdBA89RSss07uVCplnTvDgAFpSsorr+ROI0lNL8RGVqIhhF8A+wG7xRhnLPSxNkCXGOPHIYQVgX8B/4kx/nUR93M6cHrd5Q4dOqw2fPjwZfgS8pk1axZt27bNHUPNrFKO+/Tp+R67Q4d8j72sKuW4q3E87kuX63fJsvweeemlrvzxj32YOrU1Rx/9Nocf/i41i3i7pFSPe87f29WgpmYWtbWLPu6fftqGk07akXXWmcaf/vQsITRdjnL8G1nOSvXnXU3L4w6DBg36IMbYa1Efa1RJEEL4CXAYsHuM8fMG3P5w4IgY435Lu22vXr3ihAkTGpylFIwYMYKBAwfmjqFmVinHfdiwfI89ZEi+x15WlXLc1Tge96XL9bukMb9HYoSLL047F7RtC9deC/vvv/jbl+pxz/l7uxp07z6CyZMXf9yvuy7tgHHaabDxxk2Xoxz/RpazUv15V9PyuEMIYbElQYOnGxTe+T8c2GNxBUEIYeUQQqvCv9sABwKjGp1YkiSpCGbPTi+6fvADWHNNeOaZJRcE0uIMHAg1NXDPPbmTSFLTaugWiL2As4EVgIcLWxs+W/jY70IIJxRuugMwKoQwBhgJTAL+WPTUkiRJSzFpUlqQ8LLLYI894LnnYJNNcqdSuereHbbeGt56C955J3caSWo6LRtyoxjjBGCRs69ijGfW+/ctwC3FiSZJkrRsnnkmLUw4cSKcfjqcdRa0bNCzHmnx9tor/d+6++40fUWSKtGy7m4gSZJUki67DHbaCaZMSesPnH22BYGKY5VVYIst4LXX0k4ZklSJLAkkSVJFmDMHTjwRjjsOevaEJ5+EI4/MnUqVZq+90rlrE0iqVPbqkiSp7H34IRx8MDz1FOy2G9x4Y5pD3hTcZaC6rbYa9OkDo0fD++/D6qvnTiRJxeVIAkmSVNaefhr6908FwU9+Avfd13QFgQSw997p/N578+aQpKZgSSBJksrWsGFp/YHPP4cbboD/+z/XH1DTW3NN2HRTGDkyjWKRpEpiSSBJksrO7NkwZAgcfzz06pVGExx2WO5UqiZ77w0xppErklRJLAkkSVJZ+fxz2GUXuPRS2GMPeP556N07dypVm3XXhQ03hOeeg08+yZ1GkorHkkCSJJWNsWPhT39KIwd++tM0J7xbt9ypVK322Qdqax1NIKmyWBJIkqSy8MQTcPbZMGNGWn/grLOgRYvcqVTNNtggjSh4+mn47LPcaSSpOCwJJElSSZs3D667Dq65BlZYAX72M9cfUGkIIa1NMH8+jBiRO40kFYfr/0qSpJI1dSoMHZqmGWy0ERx3HHTsmDuVtMAmm6TdDp54IhUGXbrkTiRJy8eRBJIkqST9979p/YGxY9MChT/8oQWBSk8IMGhQGvHy2GO500jS8rMkkCRJJefJJ+Fvf4Pp0+H734eDD3b9AZWu3r1hxRVTSTBvXu40krR8LAkkSVLJmD8fbrwRrr4aOndOOxhstVXuVNKStWgBO+0E06bByJG500jS8rEkkCRJJWH6dLjgAnj44bRq/C9+AWuskTuV1DA77ACtWsFDD+VOIknLx4ULJUlSdpMmwUUXwccfw4ABafeClj5LURnp2DGNennyybSextpr504kScvGkQSSJCmr116Dv/wFJk9O5cCRR1oQqDztsks6f/jhvDkkaXlYEkiSpCxiTEOzzz8/rRB/yinpRVYIuZNJy2b11WH99eGFF9L2nZJUjuzpJUkqc8OG5U7QePPmwQ03pL3lV1kFfvCDdC6Vu113hbffhscfh333zZ1GkhrPkQSSJKlZffklnHtuKgi+8Q044wwLAlWO3r2ha1e3Q5RUviwJJElSs5k4Ef785/RO6667wsknQ/v2uVNJxdOiBey8c5pu4HaIksqRJYEkSWoWb7wBZ50Fn30GRx0Fhx6aXlBJlWaHHdLimy5gKKkcWRJIkqQm98wzCxYoPPXUtM2hVKk6doStt4Z334Vx43KnkaTGsSSQJElNJka4+2644gro3Bl++lPYaKPcqaSm53aIksqVJYEkSWoS8+fDNdfAHXekreHOOANWXTV3Kql5rL46rLde2g5x2rTcaSSp4SwJJElS0c2cCRdeCE8+CZtsAj/5CaywQu5UUvPadde0w8Hjj+dOIkkNZ0kgSZKKasoU+Nvf4LXX0gJuP/gBtG2bO5XU/Pr0WbAd4vz5udNIUsNYEkiSpKL54IO0g8GECbD//mkXA3cwULVq0QJ23BE+/9ztECWVD0sCSZJUFK+/Dn/9a5p//d3vwt57p90MpGo2YIDbIUoqL5YEkiRpuY0cmdYgqNvicJttcieSSkOnTrDlljB2LIwfnzuNJC2dJYEkSVouTz4Jw4ZB+/ZpgcINN8ydSCotu+6azh96KG8OSWoISwJJkrTMHngArr4aVlwR/ud/oFev3Imk0rPGGrDuuvD88/DFF7nTSNKSWRJIkqRGixHuuANuugl69kwFwcor504lla5ddknbIT71VO4kkrRklgSSJKlRamvhX/+Cu++GNddMUwy6ds2dSiptffpAhw5pek6MudNI0uK1zB1AkiSVj/nz0/SCZ56BDTaAk06Cdu2aP8ewYU133927N+39qzq1apUW9HzwwbSI4Xrr5U4kSYvmSAJJktQgc+fC0KGpINh8czjllDwFgVSutt8+nT/5ZN4ckrQklgSSJGmpZs2CCy6AMWNg663hhBOgdevcqaTystpqsNZa8OKL6WdKkkqRJYEkSVqiGTPg73+HN9+EnXeGY46BFi1yp5LK0/bbw+zZ8MILuZNI0qJZEkiSpMWaMQPOOw/GjYNBg+Cww6DGZw/SMttyyzQK54kncieRpEXzz7wkSVqk6dPh3HNTQbDPPvDNb0IImUNJZa5dO+jfH/77X5g4MXcaSfo6SwJJkvQ1dQXBe+/BvvvC4MEWBFKxuIChpFJmSSBJkr6iriAYPz4VBPvtlzuRVFnWWw9WWQWefRbmzcudRpK+ypJAkiT9f9Onp0UKx49P5YAFgVR8IcB228EXX8BLL+VOI0lfZUkgSZIA+PLLVBC8/36aXrDvvrkTSZVr223TIqBOOZBUaiwJJEnS1wqCffbJnUiqbF26wGabwauvwpQpudNI0gKWBJIkVbm6gmDCBNh/fwsCqblsvz3ECE8/nTuJJC1gSSBJUhWrW4NgwoS0xeHee+dOJFWPTTeFzp3TlIPa2txpJCmxJJAkqUrNnAnnnbegINhrr9yJpOrSokVam2DyZHj77dxpJCmxJJAkqQrNng0XXADvvZemF1gQSHlsv306f+KJvDkkqY4lgSRJVWbuXLj4Yhg7FvbYw20OpZxWWQXWWw9GjYIZM3KnkSRLAkmSqsq8eTB0KLz+Ouy0Exx0UNqzXVI+O+yQyrvnnsudRJIsCSRJqhrz58M//wkvv5zmQR92mAWBVAr69YO2bdMChpKUmyWBJElVoLYWrr4aRo6E/v3h6KOhxmcBUklo0wa22ALGj4fRo3OnkVTtfHogSVKFixFuuAGeeQY23xy+//20qrqk0rHDDun8n//Mm0OSLAkkSapgMcJNN8Fjj8HGG8OQIRYEUilaay1YdVW47jqYNSt3GknVzJJAkqQKdscd8OCDafX0E0+EVq1yJ5K0KCGk7RCnTIHbbsudRlI1sySQJKlCjRgB99yT3qE8+eQ071lS6dp66zTS59prcyeRVM0sCSRJqkCPPw633JKGL//wh9CuXe5EkpamUycYNAjuuw8++SR3GknVypJAkqQK88ILaV5z9+5w2mnQoUPuRJIa6sgj03al//pX7iSSqpUlgSRJFeSVV+Dyy6FLF/jRj9K5pPKx//7QsWMq+iQpB0sCSZIqxNtvwyWXQNu2cOqpaSSBpPLSvj0ccEDasvSdd3KnkVSNLAkkSaoA48fDhRdCTU1ag2DVVXMnkrSsjjoqnV9/fd4ckqqTJYEkSWVu0iQ4/3yYNw9+8IO0m4Gk8rXrrrDKKmmXgxhzp5FUbSwJJEkqY+PHw7nnwvTpMGQIbLhh7kSSllfLlnD44WkK0Qsv5E4jqdpYEkiSVKY++gj22AOmTIHvfAd6986dSFKxHHlkOr/22rw5JFUfSwJJksrQ55+n/dTfegsOOwy22SZ3IknF1L9/Ghl0441pKpEkNZeWuQNIUjUYNix3guY3ZEjuBM2vuY7zrFlw3nnw7rtpu7Rddmmex5XUfEJIownOPBMeeCCVgpLUHBxJIElSGZk7N21z+O67sOeesNdeuRNJaip1Uw6uuy5vDknVxZJAkqQyMX8+XHopvP467LgjHHhgerdRUmVaZx3Ydlu45Rb48svcaSRVC0sCSZLKQG0tXHkljBkDW2+dVj63IJAq31FHwYwZcPvtuZNIqhaWBJIklbgY4YYb4LnnoE+ftJNBjX/BpapwyCFpS0SnHEhqLj7FkCSphMWYhho/9hhsvDEceyy0aJE7laTm0r17WrTw/vvh449zp5FUDSwJJEkqYffem14crLsunHgitGqVO5Gk5nbkkWlNkn/9K3cSSdWgQSVBCKFtCOG2EMJbIYQxIYT/hBDWW8xt9w0hvBFCeDuEcEsIoXNxI0uSVB0eeijNQ159dTj5ZGjTJnciSTkMHgwdO8K11+ZOIqkaNGYkwTBgwxhjb+B24LKFbxBC6Aj8E/hmjHF9YCLw62IElSSpmjz1VHrXsEcPOPVUaN8+dyJJubRvn3Yzee45ePvt3GkkVboGlQQxxlkxxntijLFw1TPAWou46V7AqBjjG4XL/wAOX+6UkiRVkeefh6uvhm7d4LTToFOn3Ikk5XbUUencBQwlNbVlXZPgVNJogoWtAbxX7/I4oGcIoeUyPo4kSVXlhRfg8suhSxf40Y+ga9fciSSVgl13TSOLrrsuLWgqSU0lxEb+lgkh/ALYD9gtxjhjoY/9GNggxnh84XJ74AugTYxx3kK3PR04ve5yhw4dVhs+fPgyfRG5zJo1i7Zt2+aOoWZWKcd9+vR8j92hQ77HXlbLe9xzfr9zKcfjvLDGHvflPc5PPbUKf//75qywwhx++9vnWXXVGUv/JBVdTc0samvL//e8GqdUjvuSfncOHboht966Fuee+wwbbTS1+UJVsEp5XqfG8bjDoEGDPogx9lrUxxr1Dn8I4SfAgcDuCxcEBeOBPepdXgv4cOGCACDGeA5wTt3lXr16xYEDBzYmTnYjRoyg3DJr+VXKcR82LN9jH3hgvsdeVst73HN+v3Mpx+O8sMYe9+U5zi++CJddlqYWnHZaW1q3HsDkyct+f1p23buPYPLk8v89r8YpleO+pN+d3bvDrbfC2LHbcOqpzZepklXK8zo1jsd9yRo83aDwzv/hwB4xxs8Xc7P7gH4hhI0Kl08CblyuhJIkVbiRIxcUBKefDquskjuRpFLUrx9stBHceCPMnZs7jaRK1dAtEHsBZwMrAA+HEEaHEJ4tfOx3IYQTAGKMXwDHAreFEN4BegG/b4rgkiRVglGj4NJL0/Zmp5+e5hxL0qKEAEceCZ98Av/5T+40kipVg6YbxBgnAGExHztzoct3AHcsfzRJkirb6NFpikLHjvDjH1sQSFq6I46AX/8abrgB9t47dxpJlWhZdzeQJEnLYfRoGDo0LVLmCAJJDbXOOrDVVnD77TBrVu40kiqRJYEkSc1szJg0gqCuIOjZM3ciSeXkkEPgiy/gvvtyJ5FUiSwJJElqRqNGpREE7dungmDVVXMnklRuvvWtdP7vf+fNIakyNWoLREmStOweewyuv75um0MLAknLZo01YNtt4Y47YMaMVDpKUrE4kkCSpCYWI9x9N1x3HXTrBj/9Kay2Wu5UksrZIYfA9Olw7725k0iqNJYEkiQ1odratKf5HXfA6qvDz34GK62UO5Wkclc35eBf/8qbQ1LlcbqBJElNZO5cuOIKePFF2HBDOPFEaNcudypJlWC11WCHHeCuu9KIgg4dcieSVCkcSSBJUhOYNQsuvDAVBP36wSmnWBBIKq5DD4WZM1NRIEnFYkkgSVKRTZsGZ58Nb7wBO+4Ixx0HrVrlTiWp0hx0EITgLgeSisvpBpIkFdHkyXDeefDxx7DvvukUQu5UkipRz56w005wzz3wxRdp5xRJWl6OJJAkqUjGj4ezzoJPPoEjjoD99rMgkNS0DjkkTW+6887cSSRVCksCSZKK4J//TAXBjBlpesFOO+VOJKkaHHQQ1NS4y4Gk4nG6gSRJy2HmTDj5ZLj8cujWDYYMgbXWyp1KUrVYeWXYZRe47z6YOhW6dMmdSFK5cySBJEnL6N13YbvtUkEwaBD84hcWBJKa36GHwpw5cMcduZNIqgSWBJIkLYM770xbG44ZA7/9Ldx9N3TsmDuVpGp0wAHQooVTDiQVhyWBJEmNMG9eGjEweHB6Un7vvXDmmWlOsCTl0L077L473H8/TJmSO42kcudTGkmSGujjj2HgQPjzn2GrrWDUqHRZknI75BCYOxduuy13EknlzoULJUlqgIcfhqOOgokT4aST4JxzoE2b3KkkVZphw5bt86ZPT6Obzj47lQXLYsiQZfs8SZXFkQSSJC3Bhx/CkUfCrrvC55/DNdfARRdZEEgqLR06wMYbw+uvw5df5k4jqZxZEkiStAjz5sGtt67JhhvC9dfDPvvAyy+n0QSSVIq22AJqa2H06NxJJJUzSwJJkhbyxBNp54KhQzdixRXh9tvhrrtgnXVyJ5OkxevdG1q2hBdeyJ1EUjmzJJAkqeCjj+A734EBA+DNN+Hww8fy2mtpJwNJKnXt28M3vgFvvAFffJE7jaRyZUkgSap68+fDhRfChhvC1VfDnnvCK6/Ad77zDu3b504nSQ23xRYQI4wcmTuJpHLl7gaSVKZqa9M7RV9+mf69uFOMUFMDnTqlU4cOaQVspf3Er7wSLr4Y3n4bevWCf/4TDjwQQoB3382dUJIaZ/PN05SDF1+EnXbKnUZSObIkkKQSVVsLU6fCp59+/fTZZ+l83rzG328IqSioKw3qTl26wCqrQI8esPLK0KpV8b+mUjFmTNqh4LrrYMYMWHFF+OUv4YwzoGPH3Okkadm1awebbpp+z02dmn63S1JjWBJIUomYNQv++9/07vU776R/z5z59du1bg3dusFGG6Xzjh3TyICamsWf5s9Pow4WPn3wQdpbe2EhpPvu0WNBcVB33rlz+ni5mTMHhg9P5cCTT6brttgCfvADOPTQ9MRakirBFlukHQ5GjoRddsmdRlK5sSSQpEw++wzGjk2FwNixMGFCmhoAaajommvC6qtD9+7pne5u3dK/O3Qo7ov0+fPTlIUpU2DSpLR436RJ6fTGG2lufn2dOsGqq6ah+autls579kzlRamJMX1vr74ahg1LX1ubNvDtb6dyYKutcieUpOLbbLM0GuzFFy0JJDWeJYEkNZPa2vSCddSoNAx08uQFH+vUKW1dte666bTGGs033L9FizQctUsXWGutr2f+9NMFxcGHH6bRB+PGpdX/64SQpijUFQc9esBLL8F669GsC//Nm5e+t088kU5PPpkyQypd/vIX+P73U9kiSZWqbVvYZJP0+3DatDQCTJIaypJAkprQ7Nnw4INwzTXpyVrdllQrrpi22Vt33fRCunv30hzCX1MDK62UTptuuuD6uvJgwoR0+uCDdBo5Mr1zBemde0iFxwYbpJ0DNthgwWmVVVKBsKxf97x5afRD/VLgmWcWTJ8IIb2bdsABMGgQ7L23CzZKqh79+6cpB6NHw4475k4jqZxYEkhSkX3xBdxzD9x6azqvKwZWXTUVA337pmkEpVgKNFT98qBv3wXXz54NEyemkQe9eqXRBm+9BU89BQ888PX7adUKVlgBunb9+mmFFdL9TZmy6NPCe4C3awdbbw3bbw877ADbbuuCXZKq12abpalrI0daEkhqHEsCSSqC2lp49FG4/HK4+ea0CCHANtukd7Jnz07vnFe6Nm1g7bXTaciQBdfHmMqDt95KxcHbb6fpFvVf9L//fpqisKjFGkNYUCastFIaiVBXJmywQSpf+vQpzXURJCmHdu1g443h1VfTujPu3CKpoSwJJGk5jB8PV10FV1yRdiOA9E72EUfAN7+ZRg/AgqH31SqEtFbBaqstfRGt2bPh889TcdCmTSoCOndOoxckSQ3Xrx+8/HKalrX99rnTSCoXlgSS1EizZ8Ptt8M//wn/+U96l7xHD/jZz+C7301z77Xs2rRJoy6qYeSFJDWl3r1TwTpqlCWBpIazJJBUNZbn3fzu3eF3v0tTCp59Ni2OV1OTnoBtv31aRbpFi/TxRx8tXmZJkpZVhw6w0Ubw2mtpKle7drkTSSoHlgSStAS1tenJ1RNP9GPUqHRdz56w115pkTy3lZIklbK+fdPfsZdeSn+3JGlpLAkkaRFmzUrb6T38MEyaBDU13enXL82nX3/98t6ZQJJUPfr0geuvT7scWBJIaghLAkmqZ/JkeOQReOKJNDSzfXvYc0844IDHqKnZKXc8SZIapXPnVG6/+moqwNu2zZ1IUqmzJJAk0s4EI0bA6NFpIcKePdPWhdtskxbS6959FpMn504pSVLj9euXtqB99VXo3z93GkmlzpJAUtWKMT1puvdeeP31dN2mm8Juu6W9pZ1SIEmqBH36wI03wosvWhJIWjpLAklVJ0Z45ZVUDowdm8qArbZKixGuumrudJIkFVfXrrDuuulv35w50Lp17kSSSpklgaSqUVubphPccw+8/37asnCHHWDQIFhppdzpJElqOn37pmL8tdfSyAJJWhxLAkkVb948uOEG+N3v4MMPoVUr2HVX2GMPWHHF3OkkSWp6ffvCzTenXQ4sCSQtiSWBpIoVI9x1F5xxRnrnpG3bNGpgt93Sas+SJFWL7t1hzTXhpZdg7txUmEvSolgSSKpIzz4LP/0pPPYYtGsHv/wldOsGHTrkTiZJUh79+sGtt8Ibb8Bmm+VOI6lU1eQOIEnF9M47cMghaevCJ56A445L1/3hDxYEkqTq1rdvOh81Km8OSaXNkkBSRfj4YzjllLR14U03weDB8PLLMGyYOxZIkgSwyirQq1daxHf+/NxpJJUqSwJJZW3GjDRKYN114cIL0/7Pjz0Gt98O3/hG7nSSJJWWvn1h+nR4663cSSSVKksCSWXroYdg883h17+Gnj3Tqs1PPw0DBuROJklSaerXL52PHJk3h6TSZUkgqexMmQLf/37apeDDD+Hss+HVV+GggyCE3OkkSSpdq64KPXqkKQe1tbnTSCpFlgSSykaMabTAxhvD5ZfDHnvAK6/A6ae7lZMkSQ3Vty9Mm5YW9pWkhVkSSCoLEyfCgQfCt74Fc+bAlVfCiBGw9tq5k0mSVF7690/n7nIgaVEsCSSVtNratEPBxhvDbbfBoYfC66/Dd77j1AJJkpZFr17QvXsqCZxyIGlhlgSSSta778Kuu8Lxx0OnTmnHghtvTFs4SZKkZRNCWsBwyhQYNy53GkmlxpJAUkm65540HPLRR+HEE9PChIMH504lSVJlcJcDSYtjSSCppNTWwu9/D/vum97puO8++Mc/oEuX3MkkSaoca60FXbumKQcx5k4jqZRYEkgqGVOnwgEHwJlnwuabw4svwsCBuVNJklR5Qki7HEyeDBMm5E4jqZRYEkgqCa+9BlttBXfcAUceCU895c4FkiQ1pb5907m7HEiqz5JAUnY335wKgrFj4dxz4ZproH373KkkSaps662XFga2JJBUnyWBpGzmz4czzoBvfQs6dIAHH4RTT3VrQ0mSmkNNDfTuDRMnwqRJudNIKhWWBJKy+PRT2GsvOOss2HrrtP7ATjvlTiVJUnWpm3IwenTWGJJKiCWBpGY3aRLssAP85z9w3HFpm8NevXKnkiSp+my0EbRt65QDSQtYEkhqVlOnwi67wBtvwNlnw7Bh0KZN7lSSJFWnli3TjkLjxsH48bnTSCoFlgSSms3UqakYeOONtEDh6afnTiRJkuqmHNx2W9YYkkqEJYGkZlFXEHz0EZx3XlqgUJIk5bfJJtCqFdxyS+4kkkqBJYGkJvf55wsKgkMPhR/+MHciSZJUp02bVBQ8/jh8/HHuNJJya5k7gFTNhg3LnaDpff45nHNOKggOOyytRyBJkkpL375ph4M77oBjj82dRlJOjiSQ1GSmTFkwgsCCQJKk0rX55mkRQ6ccSLIkkNQkpkxJIwg+/hgOP9yCQJKkUta+Pey2GzzwQFpHSFL1siSQVHT1C4IjjoCdd86dSJIkLc2BB8LcuXDXXbmTSMrJkkBSUc2cmXYvqCsIdtopdyJJktQQ++8PITjlQKp2lgSSiqa2Fq64Aj78ML0bYUEgSVL5WGUV2GEHuPdemDEjdxpJuVgSSCqae+6BMWNgq61gzz1zp5EkSY114IFpVOCIEbmTSMrFkkBSUYwZA3feCauvDkcfnYYrSpKk8nLAAencKQdS9bIkkLTcJk2Cyy+HDh3ghBOgdevciSRJ0rJYc03o3z8V/3Pm5E4jKYcGlQQhhPNDCONCCDGE0Gcxt9k5hDAzhDC63qldUdNKKjkzZ8LFF8Ps2XDccdC9e+5EkiRpeRx4YNoG8eGHcyeRlENDRxLcDOwAvLeU270ZY+xT7zRz+eJJKmV1CxVOmgQHHQQbb5w7kSRJWl4HHpjOnXIgVacGlQQxxsdijBOaOoyk8lJ/ocLdd8+dRpIkFcNGG6Xi/7bbYP783GkkNbdir0mwbghhZAjh+RDCSUW+b0klxIUKJUmqXAceCB9/DE89lTuJpOYWYowNv3EI44BvxhhHL+JjnQv3NzWE0Au4B/hDjPHfi7mv04HT6y536NBhteHDhzcufWazZs2ibdu2uWOomRXzuE+fXpS7aXYffNCeM87YhhYtIn/969OsvPKsRn1+hw5NFGwpluf7XVMzi9paf94bI9dxLqbG/ryX68+0vsqf9+rkcf/q7+133unEySdvxwEHjOP449/MF6qJ+Xy+OnncYdCgQR/EGHst6mNFKwkWcdufA6vGGE9pyH336tUrTphQXjMaRowYwcCBA3PHUDMr5nEfNqwod9OsZs6Ev/wFPvoITj112dYhGDKk+LkaYnm+3927j2DyZH/eGyPXcS6mxv68l+PPtL7On/fq5HH/6u/tGGGdddL6Q+PGVe6IQZ/PVyePO4QQFlsSFG26QQihZwihpvDvTsC+wKhi3b+k/GKEK690oUJJkipdCGnKwfjxMHJk7jSSmlNDt0AcGkKYAPQCRoQQ3ilcf1kIYXDhZgcBL4cQxgDPAP8BrmiCzJIyefZZGD067Z/sQoWSJFU2dzmQqlPLhtwoxnj8Yq4/tt6/LwQuLFIuSSVm2jT497+hUyc44ojKHXao8lfMIf/duzuFQFL12nZb6NEDhg+HP/zBv/1StSj27gaSKtSNN6ZF2Q4/HDp2zJ1GkiQ1tZoa+OY34c034fXXc6eR1FwsCSQt1ejR8OKL0KcP9OuXO40kSWouTjmQqo8lgaQlmj4drrsO2rd3moEkSdVm552ha9c05UBSdbAkkLREw4en9QgOPhi6dMmdRpIkNadWrWDw4DSq8N13c6eR1BwsCSQt1muvwZNPwje+AdttlzuNJEnKoW7Kwa235s0hqXlYEkhapFmz4NproU0bOPJIpxlIklSt9twTOnRwyoFULSwJJC3S7bfDp5+mVY27d8+dRpIk5dK2LeyzDzz9NEycmDuNpKZmSSDpa955Bx5+GNZdNy1YJEmSqlvdlIPbbssaQ1IzsCSQ9BVz58I110CLFvDtb6c9kiVJUnXbe+80BdEpB1Ll8+m/pK+4+26YNAn22w969MidRpIklYJOndLaBI8+CpMn504jqSlZEkj6/8aPhxEjYPXVYY89cqeRJEml5KCDYP58uPPO3EkkNSVLAkkA1NbC1Venf3/nO2m6gSRJUp399kvPD265JXcSSU3JkkASkFYsfv/9NIJg9dVzp5EkSaVmxRVhl13g/vth2rTcaSQ1FUsCScyZA3fcAR07wl575U4jSZJK1UEHpecN99yTO4mkpmJJIIkHHoDPP4d994V27XKnkSRJpWr//SEEpxxIlaxl7gCS8po2LS1WuPLKMGBA7jSqJMOG5U4gSWqMhv7eXmedNALxwguhdevlf9whQ5b/PiQVjyMJpCp3990waxYccAC0tDaUJElL0a8fzJ4Nr72WO4mkpmBJIFWxjz6Cxx6DtdeGvn1zp5EkSeWgT590PmpU1hiSmoglgVTFbrstbX148MFpfqEkSdLSdO8Oa6wBL70E8+blTiOp2CwJpCr17rswcmR6N2C99XKnkSRJ5aRvX5gxA956K3cSScVmSSBVoRjh5puhpiatRSBJktQY/fqlc6ccSJXHkkCqQmPGwNixsMMO0KNH7jSSJKnc9OgBPXumkqC2NncaScVkSSBVmfnz097GbdrAvvvmTiNJkspV377wxRfpjQdJlcOSQKoyTzyRdjXYc0/o0iV3GkmSVK7qdkZyyoFUWSwJpCoyaxbceSd07gy77547jSRJKmerr552Ohg1Kq13JKkyWBJIVeT++9OwwP32g7Ztc6eRJEnlLIQ0muCzz+C993KnkVQslgRSlZg6Ff7zn7TQ0Pbb504jSZIqgVMOpMpjSSBViTvvhDlz4MADoUWL3GkkSVIlWHvttMaRUw6kymFJIFWBjz5KCxautx5svnnuNJIkqVLU1KTRBB99BBMn5k4jqRgsCaQqMGJEavf33z/NH5QkSSqWfv3S+Ysv5s0hqTgsCaQK99ln8PTTaRTBBhvkTiNJkirN+utDp04wcmTuJJKKwZJAqnD33w+1tbDXXrmTSJKkSlQ35eDDD51yIFUCSwKpgk2bltYiWGMN2GST3GkkSVKlqpty4GgCqfxZEkgV7MEHYe7cNIrAtQgkSVJT2WAD6NjRkkCqBJYEUoWaMQMeeQR69IA+fXKnkSRJlaxFi/R844MPYNKk3GkkLQ9LAqlCPfIIzJoFgwaluYKSJElNqX//dO5oAqm8+dJBqkCzZ8MDD0C3brDVVrnTSJKkarDhhtChg1shSuXOkkCqQI8/DtOnw8CBafifJElSU6ubcjBhAnz0Ue40kpaVJYFUYebOhf/8Bzp3hu22y51GkiRVk7pdDkaNyptD0rKzJJAqzDPPwOefwx57QKtWudNIkqRqstFG0L69Uw6kcmZJIFWQ+fPhvvvSH+cdd8ydRpIkVZuWLaF3bxg/Hj75JHcaScvCkkCqIC++CJMnw667Qtu2udNIkqRqVDflwF0OpPJkSSBViNpauPdeaNMmlQSSJEk5bLxxerPCkkAqT5YEUoV46SWYOBF22iltPyRJkpRDq1ZpysG4cfDpp7nTSGosSwKpAsSYRhG0bAm77547jSRJqnZOOZDKlyWBVAHeeCO19dtvD1265E4jSZKq3Te+kaZAusuBVH4sCaQKcO+9UFMDe+6ZO4kkSRK0bg2bbw7//S989lnuNJIaw5JAKnP//S+8+SZsvTV07547jSRJUuKUA6k8WRJIZe7BB9P5HnvkzSFJklTfppumEQWWBFJ5sSSQytiUKWmu38Ybw2qr5U4jSZK0QOvWsNlmMHZses4iqTxYEkhl7JFHoLYWdt01dxJJkqSv698/nY8alTeHpIazJJDK1Jw58PjjsPLKaTifJElSqdlkE2jVyikHUjmxJJDK1LPPwvTpsMsuaWcDSZKkUtO2bXoz4513YOrU3GkkNYQvLaQyFCM89FD6w7vddrnTSJIkLV7//um5i1MOpPJgSSCVoTfegIkTYfvtU1EgSZJUqjbbDFq2dMqBVC4sCaQy9OCDEIILFkqSpNLXtm1am+Ctt2DatNxpJC2NJYFUZj76CF5+GXr3hu7dc6eRJElaui22SFMOXnwxdxJJS2NJIJWZhx9O57vtljeHJElSQ22+edrl4IUXcieRtDSWBFIZmTkTnnoKevWC9dfPnUaSJKlh2rZNRcE778Bnn+VOI2lJLAmkMvLkkzB7dlqLIITcaSRJkhpuyy3TuVMOpNJmSSCVidraNNWgUyfYaqvcaSRJkhpn003TiILnn8+dRNKSWBJIZeKll2DyZNhxxzSnT5IkqZy0agV9+8J776WFmCWVJksCqUw8+CC0aAE77ZQ7iSRJ0rLZYot07gKGUulqmTuApKV7//20t/DWW0OXLrnTLL9hw3InkCRJOWy8MXTokEqCffbJnUbSojiSQCoDDz2Uzt32UJIklbMWLaB/f5g4ET74IHcaSYtiSSCVuGnT4LnnYN11Yc01c6eRJElaPnVTDlzAUCpNlgRSiXv8cZg3z1EEkiSpMqy/fpo++cILEGPuNJIWZkkglbB58+CRR2DFFaFPn9xpJEmSll9NTRpN8MknaacDSaXFkkAqYSNHpukGO++c5vBJkiRVgi23TOfuciCVHksCqYQ98kjaU3j77XMnkSRJKp611oJu3VJJUFubO42k+iwJpBL1/vswdmwajtexY+40kiRJxRNCGk0wZQo8+WTuNJLqsySQStRjj6XznXfOGkOSJKlJ1O1ycOONeXNI+ipLAqkEzZwJzz4La6yRhuNJkiRVml69oEcPuOmmtFizpNLQoJIghHB+CGFcCCGGEPos4XbfDyG8HUIYG0K4NITQqmhJpSryzDMwe7ajCCRJUuUKYcEuBw8/nDuNpDoNHUlwM7ADsNhNSkIIawO/BwYA6wGrAEOWN6BUbWKERx+F9u0XrPwrSZJUieqe6zjlQCodDSoJYoyPxRgnLOVmBwN3xBgnxRgjcAlw+PIGlKrN22/Dhx/CtttC69a500iSJDWdHj2gb1+45ZY0ilJSfsVck2ANvjrSYFzhOkmN8Oij6XzHHfPmkCRJag6HHQaffw733587iSSAlrkeOIRwOnB63eUOHTowYsSIXHGWyaxZs8ous5ZfMY979+5fvTxlSmtGjdqJzTf/jE03fbEoj6HiqKmZRffu/rxXG497dfK4VyePez5t2rQFduLvf59I69YvN+tj+3y+Onncl6yYJcF4YN16l9cqXLdIMcZzgHPqLvfq1SsOHDiwiHGa3ogRIyi3zFp+xTzuw4Z99fI998D8+bDttt2ZPNn/W6Wke/cRHpMq5HGvTh736uRxz2fIEBg6FJ57blUGDFiV9u2b77F9Pl+dPO5LVszpBsOBwSGEHiGEAJwAuASJ1EDz58Njj8EKK0Dv3rnTSJIkNZ/DDoPp0+Guu3InkdTQLRCHhhAmAL2AESGEdwrXXxZCGAwQY3wX+A3wJPAO8AkwtElSSxXo5ZdhyhQYMABatMidRpIkqfl861tQU+MuB1IpaNB0gxjj8Yu5/tiFLl8KXFqEXFLVefTR9Mdxhx1yJ5EkSWpePXvCzjunqZdTp0KXLrkTSdWrmNMNJC2jjz+G116DPn3SdANJkqRqc/jhaRvE4cNzJ5GqmyWBVAIeeyyd77xz1hiSJEnZHHwwtGkDV1+dO4lU3SwJpMzmzIGnnoIePWCDDXKnkSRJymOFFWD//dMUzHHjcqeRqpclgZTZiy+m1Xx32glCyJ1GkiQpn29/O51fe23eHFI1sySQMnvkEWjdGrbZJncSSZKkvPbcE1ZeOU05iDF3Gqk6WRJIGb33XhpOt9VW0L597jSSJEl5tWoFRx4Jb78Nzz6bO41UnSwJpIwefTSd77RT3hySJEmlom7KgQsYSnlYEkiZTJkCzz0Ha68Na6yRO40kSVJp6N0bNtsMbrwxbYkoqXlZEkiZXH01zJ3rKAJJkqT6QkijCaZMgbvvzp1Gqj6WBFIGMcIll0CHDtC/f+40kiRJpeWII6CmxikHUg6WBFIGjz4Kb7wB222XdjaQJEnSAquuCnvskUYSfPJJ7jRSdbEkkDK4+OJ0PmBA3hySJEml6tvfhnnz0toEkpqPJYHUzD76CG65BXbbDVZZJXcaSZKk0vTNb0LHjk45kJqbJYHUzC6/PLXiJ56YO4kkSVLpat8evvUteOEFeO213Gmk6mFJIDWj+fNh6FDo2RMGD86dRpIkqbR9+9vp/Jpr8uaQqoklgdSMRoyA996DY4+FVq1yp5EkSSptO+4Ia6wB116b3myR1PQsCaRmdPHFaTufY4/NnUSSJKn01dTA0UfDhAnwyCO500jVwZJAaibvvZe28dlnn9SIS5IkaemOPjqdu4Ch1DwsCaRmctllEKMLFkqSJDXGhhvC1lvD8OHw5Ze500iVz5JAagZz56aSYK21YM89c6eRJEkqL9/+NkyfDrfemjuJVPksCaRmcPvtMGkSDBkCLVrkTiNJklReDj00LfrslAOp6VkSSM3gkkvSH7bvfS93EkmSpPLTrRvsuy88+GBaxFBS07EkkJrYW2+lP2gHHgirrJI7jSRJUnn69rfT+k7XXZc7iVTZLAmkJjZ0aDp3wUJJkqRlt/feaUTB1VenskBS07AkkJrQzJlwxRWw0Uaw446500iSJJWv1q3h8MPhtdfgxRdzp5EqlyWB1IRuugmmTIETToAQcqeRJEkqb8cck84vvTRrDKmiWRJITeiSS6BduzSHTpIkScunf3/o1w+uvx6++CJ3GqkyWRJITWTMGHj6aTjsMOjaNXcaSZKkyjBkCHz5JdxwQ+4kUmWyJJCayCWXpPMTTsibQ5IkqZIccQR06ADDhuVOIlUmSwKpCXzxBVx7bRoOt+WWudNIkiRVjk6dUlHw4osuYCg1BUsCqQlcd10aBueChZIkScV3/PHp3NEEUvFZEkhFFiNcdBF07py26ZEkSVJxuYCh1HQsCaQie/xxeOWVtEVPx46500iSJFWmugUMb7wxdxKpslgSSEV20UXp/KST8uaQJEmqZHULGA4dmjuJVFksCaQimjgRbrkF9tgDNtwwdxpJkqTK5QKGUtOwJJCKaNgwmDcPfvCD3EkkSZIqnwsYSsVnSSAVyZw5abjbGmvAvvvmTiNJklT5XMBQKj5LAqlIbr0VJk1K2x62aJE7jSRJUnVwAUOpuCwJpCK56CJo3RqOPTZ3EkmSpOrhAoZScVkSSEXw0ktp68NDD4WVVsqdRpIkqXq4gKFUXJYEUhHUbXvogoWSJEnNr24Bw0svzZtDqgSWBNJy+vxzuPZa2GIL2Gqr3GkkSZKqT90Chtdd5wKG0vKyJJCW01VXwYwZaRRBCLnTSJIkVScXMJSKw5JAWg61tWmqwYorpvUIJEmSlIcLGErFYUkgLYcHHoC33047GrRrlzuNJElS9XIBQ6k4LAmk5XDRRWmKwQkn5E4iSZIkFzCUlp8lgbSMxo2DO++EffaBtdfOnUaSJEkuYCgtP0sCaRldcgnE6LaHkiRJpaRuAcPrrsudRCpPlgTSMpg1Cy67DNZbD/bcM3caSZIk1TnySFhhBTjvvLTItKTGsSSQlsG//gWffgonnQQ1/hRJkiSVjI4d02iCN96A++7LnUYqP768kZbBRRel3QyOOSZ3EkmSJC3slFOgZUs455zcSaTyY0kgNdKbb3bh+efhqKOga9fcaSRJkrSwXr3gkEPgwQdhzJjcaaTyYkkgNdIdd6wOuGChJElSKfvRj9L53/+eN4dUbiwJpEaYOBEefbQnO+4IvXvnTiNJkqTF2WILGDAArr8ePvwwdxqpfFgSSI1w4YUwb14NP/5x7iSSJElamtNPh7lz4R//yJ1EKh+WBFIDTZ8Ol1wCq602nX33zZ1GkiRJS7PffrDuunDxxTBjRu40UnmwJJAa6IorYMoUOOCA99z2UJIkqQy0aAGnnZa2rr7mmtxppPLgSx2pAebPh3PPhW7dYPfdP8gdR5IkSQ10zDGwwgppAcPa2txppNJnSSA1wB13wNixcOKJ0Latf10kSZLKRceOMGQIvPkm3Htv7jRS6bMkkBrg7LOhdWu3PZQkSSpHp5wCLVu6HaLUEJYE0lI8+yw8+SQceST06JE7jSRJkhqrVy845BB48EEYMyZ3Gqm0WRJIS3HOOen89NPz5pAkSdKy+9GP0rmjCaQla5k7gFTKxo2Dm2+GgQNh001zp5EkSao8w4Y132Otvz5cey1ssgl06QJrrtl8jy2VC0cSSEtw3nlpFVxHEUiSJJW/3XdPu1Y9/HDuJFLpsiSQFmPqVLjsMthsM9hjj9xpJEmStLw23xxWWgkeewzmzMmdRipNlgTSYlx6KXz5ZRpFEELuNJIkSVpeNTWw224wfTo8/XTuNFJpsiSQFmHu3DTVoEcPOPzw3GkkSZJULNtuC+3bp50Oamtzp5FKjyWBtAg33QQTJsDJJ0ObNrnTSJIkqVjatoUBA+Cjj+D551fKHUcqOZYE0kJihLPPhnbt4IQTcqeRJElSse2yC7RoATfcsA4x5k4jlRZLAmkhjz0GI0fCd78L3brlTiNJkqRi69oVdtgB3nhjBe67L3caqbRYEkgLOfvstFDhaaflTiJJkqSmstde0KpVLb/5DY4mkOqxJJDqeestuPNOGDwY1l8/dxpJkiQ1la5dYdCgCTz/PNxzT+40UumwJJDq+fvf0/mPf5w3hyRJkpreoYe+S5s2OJpAqqfBJUEIYf0QwlMhhLdCCM+HEDZZxG12DiHMDCGMrndqV9zIUtP44AO4/HLYaqs0R02SJEmVrXv32Rx/PLz4YhpNKqlxIwmGAsNijBsAZwFXLuZ2b8YY+9Q7zVzekFJzOOssmDMHzjwzrUkgSZKkynfGGWlbxP/9X0cTSNDAkiCEsDKwBXBt4arhwOohhPWaKpjUnCZOhGHDYIstYO+9c6eRJElSc+nZM217PWoU3H577jRSfg0dSbA68GGMcR5AjDEC44E1FnHbdUMIIwtTEk4qUk6pSZ11FsyeneajOYpAkiSpuvzsZ9CuXXouWFubO42UV4gNGFMTQugPXB9j3LDedc8BZ8QYH6p3XefCfU4NIfQC7gH+EGP89yLu83Tg9LrLHTp0WG348OHL9cU0t1mzZtG2bdvcMbScPv20DcccM4C11vqS889/ZqklQTGP+/TpRbkbNYOamlnU1vrzXm087tXJ416dPO7VqUWLBc/rLr10A4YPX5tf/Wo0O+zwUeZkakq+joNBgwZ9EGPstaiPNbQkWBl4B1gxxjgvhBCAD4EdYozvLOHzfg6sGmM8ZWmP0atXrzhhwoSlZiklI0aMYODAgbljaDmddhqcdx7ccQfst9/Sb1/M4z5sWFHuRs2ge/cRTJ7sz3u18bhXJ497dfK4V6c111zwvO7jj2HttWGddWDMGKhxH7iK5es4CCEstiRo0H/9GOPHwEjgqMJVBwETFi4IQgg9Qwg1hX93AvYFRi1rcKmpffghDB0K/frBvvvmTiNJkqRcVl4ZTj4ZXnkFymyAs1RUjenHjgeODyG8BZwBfBcghHBZCGFw4TYHAS+HEMYAzwD/Aa4oYl6pqP76V5g1y7UIJEmSBP/zP9ChQ9rpYP783GmkPFo29IYxxjeBbRdx/bH1/n0hcGFxoklNa9IkuOQS6Nu3YdMMJEmSVNm6d4dTToG//AVuugkOOyx3Iqn5OdNGVctRBJIkSVrYT34CHTvCb3/raAJVJ0sCVaW6UQR9+sDgwUu9uSRJkqpEt25w6qnwxhvwr3/lTiM1P0sCVaX/+z+YOdNRBJIkSfq600+Hzp3TaIJ583KnkZqXJYGqzkcfwcUXQ+/esP/+udNIkiSp1Ky4YhpN8NZbcP31udNIzcuSQFXnb39zFIEkSZKW7Ec/ghVWgF/9CqZPz51Gaj6WBKoqH38MF10Em2/uKAJJkiQtXteu8Lvfwfvvw1ln5U4jNR9LAlWV+qMIavzfL0mSpCU48UTYZJO0K9Z//5s7jdQ8fJmkqlE3imCzzeCb38ydRpIkSaWuZUs4/3yYPTttjShVA0sCVY2zz4YZM+DMMx1FIEmSpIbZdVc4+GC45RZ44IHcaaSm50slVYX334cLLoBNN4UDD8ydRpIkSeXkb3+Dtm3Tjgdz5+ZOIzUtSwJVhTPOSGsR/N//OYpAkiRJjbPmmun55GuvwT/+kTuN1LR8uaSK9/TTaX/bvfeGQYNyp5EkSVI5+ulPU1nwm9+kta6kSmVJoIpWW5uGhbVsCeeckzuNJEmSylW7dmmNq6lT4Ze/zJ1GajqWBKpo114Lzz8PJ58MG26YO40kSZLK2YEHwi67wD//CS+8kDuN1DQsCVSxvvwyzR3r1i3taCBJkiQtjxDgvPPSGlc//GEatSpVGksCVay//AU+/BB+/3vo2jV3GkmSJFWCzTaDk05K615dd13uNFLxWRKoIo0bl7aq2XRTOO643GkkSZJUSX772zRa9ac/hS++yJ1GKi5LAlWkn/4UZs+Gc89NixZKkiRJxdK1K/zpTzBpEvzhD7nTSMVlSaCK89hjcNNNsP/+sNtuudNIkiSpEn3/+9C3L/z97/DWW7nTSMVjSaCKMn8+nHYatGqVphtIkiRJTaFFC7jgApg7F37wA4gxdyKpOCwJVFGuvBJGjUpFwXrr5U4jSZKkSrb99mlEwQMPwD/+kTuNVByWBKoY06bBL34BK68Mv/pV7jSSJEmqBn//O6y9NvzP/8Abb+ROIy0/SwJVjD/+ET7+OC0e07lz7jSSJEmqBp06wdVXw6xZcPTRafqBVM4sCVQRxo5NOxn07g3f+17uNJIkSaomO+wAP/sZvPCCux2o/FkSqCL85CcwZw6cd15aREaSJElqTr/9bXrD6o9/hGefzZ1GWnaWBCp7N98Mt90GBx8MO+2UO40kSZKqUevWcO216Q2ro4+G6dNzJ5KWjSWBytqkSXDCCdCtW9qCRpIkScpl003hz3+Gt99OCxlK5ciSQGUrRjjuOPj0Uxg6FHr0yJ1IkiRJ1e6002CXXeDii+Hee3OnkRrPkkBl6/LL4a674Kij4KCDcqeRJEmSoKYGrrwy7bb1ve/B5Mm5E0mNY0mgsvTf/6aWdrXVnGYgSZKk0rLGGnDhhQumxsaYO5HUcJYEKju1tXDMMfDll3DFFbDCCrkTSZIkSV911FFpYe3hw9OChlK5sCRQ2Tn3XHjsMTj5ZNhjj9xpJEmSpK8LAS65BHr2TM9b33svdyKpYSwJVFZefRV+8QtYf30466zcaSRJkqTF69YtraM1bVoaWTBnTu5E0tJZEqhszJ0L3/52Or/6amjfPnciSZIkackGDYIf/QieeAJOPNH1CVT6LAlUNv7wBxg5En7+c9hmm9xpJEmSpIb5619TWXD55fC3v+VOIy2ZJYHKwnPPwR//CH36wJln5k4jSZIkNVzLlnDjjbDJJvCzn8Htt+dOJC2eJYFK3owZaZpBixZwzTXQunXuRJIkSVLjdOkCd96Z1ik44ggYPTp3ImnRLAlU8n7+c3jzzTSSYNNNc6eRJEmSls3aa8Ntt8G8ebDffvDhh7kTSV9nSaCSdtNNcP75MGBAWvBFkiRJKmfbbw///CdMmAD7759GzUqlxJJAJevZZ9M0gx494Lrr0nQDSZIkqdwddRT88pfw/PNwzDFQW5s7kbRAy9wBpEUZNw4GD4YQ0tyt1VfPnUiSJEkqnt/9Lk2pvekm2GijdFkqBY4kUMmZOhX23Rc++SSNINhii9yJJEmSpOKqqYGrrkrPdX//+/S8VyoFlgQqKfPmwSGHwKuvwllnwQEH5E4kSZIkNY327dN2iKutBt/7Hjz1VO5EkiWBSkiMcMopcP/9cOyx8JOf5E4kSZIkNa1VV03Ta1u2TNNtR43KnUjVzpJAJeO88+CSS2DXXeEf/0jrEUiSJEmVrm9fuPlm+PJL2GUXePrp3IlUzSwJVBLuuANOPz0t2nLzzdCqVe5EkiRJUvPZay+4+26YOxf22AMeeSR3IlUrSwJlN3IkHH44dOuWfjF27Zo7kSRJktT8dtstTb1t0SKVBvfdlzuRqpElgbL64APYbz+YPz8t2rLOOrkTSZIkSflsvz089FBa1HDwYLj11tyJVG0sCZTN1KmpIJg4Ea64ArbbLnciSZIkKb/+/eHRR2HFFeFb34Lrr8+dSNXEkkBZTJoEO+2UVm/97W/TdANJkiRJyaabwmOPQc+ecNRRcNlluROpWlgSqNmNHZuGUY0ZA3/8I/z617kTSZIkSaVngw3g8cdh7bXhuOPSbmBSU7MkULMaPToVBOPGwbBh8ItfuNWhJEmStDhrrZVGFGy0EZx2WnqTLcbcqVTJLAnUbB59NE0xmDIFbroptaGSJEmSlmy11dJz6d694Ve/gkMPTet7SU3BkkDN4tZbYeDA1Hredx8ceGDuRJIkSVL5WHnlVBQcdFB6w61//7S+l1RslgRqcpddBgcfDF26pF9su+ySO5EkSZJUfrp0SQXBBRfA+PGwzTZw8cVOP1BxWRKoycQIf/5zmlaw5prw5JPQt2/uVJIkSVL5CgFOPhmeeipNQzjppLRT2LRpuZOpUlgSqEnU1sLpp6eFCTffPBUE662XO5UkSZJUGbbYAkaOhAMOgH/9K10eMyZ3KlUCSwIV3bhxsNtucO65sOOOaYpBz565U0mSJEmVZYUVYPjw9Lx73DjYeuu0g5jTD7Q8LAlUNDHC5ZenkQOPPJKGPt13X/rlJUmSJKn4QoBTT4UnnkhvzB1/PBx5JHzySe5kKleWBCqKSZNg//3h+9+Hzp1hxAi46CJo1y53MkmSJKnybbVVmn7wzW/CDTfA+uunEQZz5+ZOpnJjSaDlNnw4bLop3Hlnai1ffhn23DN3KkmSJKm6dO0Kt9yS1ijo0gV+9KM0yve++3InUzmxJNAymzIFjjoqbW8IaTuWa69Nv5wkSZIkNb8Q4JBD4I034He/g/feg732gn32gTffzJ1O5cCSQMvk/vths83guutgv/3glVcWlAWSJEmS8mrXDn7961QMHHEE3HNPGv374x/D55/nTqdSZkmgRnn5ZfjWt2DgwLQX6z//CbffDj165E4mSZIkaWGrr57e2HvySejTB845J61XMHQozJmTO51KkSWBGmTMGDjooDSn6eab0+iBl16C730vDWmSJEmSVLq22w6efRauuAJatIATToC11oLf/x4+/jh3OpUSSwIt0ejRcOCBqXW85RYYPBheeAHuuCP9UpEkSZJUHmpq4Jhj4O234c9/hpYt4cwz02iDY46BUaNyJ1QpsCTQIo0albZP6dsXbr01/XvkyDS1oH//3OkkSZIkLatOneCMM+Ddd+Hf/07bJ151FfTrBwMGpJHD8+blTqlcLAn0/82fDw8+CPvvn35B3H47HHBAKgxuvTUVBpIkSZIqQ8uWab2xxx9Po4W/8x147rl03TrrwFlnwfvv506p5mZJUOVihGeegVNPhV69YPfd01SCAw9MUw1uuSVNNZAkSZJUufr3hyuvhPHj4be/hblz02iDNdaALbeEP/4RXnstvX5QZbMkqFKvvAK//CWstx5suy2cf34adnTmmWlP1eHDoXfv3CklSZIkNadVVkmvCd57L007OPLItIbBr34Fm2wCG24IP/sZPP001NbmTqum0DJ3ADWP2lp49VW46y64/vpUEgCsthqcfnraO7VfP3cqkCRJkgStW6fdzQ46KI0qePTRNAX5ttvgr39Npx490lTlXXdNbzyuvnru1CoGS4IKNXt2mlf0xBNpjtGTT8Lnn6ePrbgiDBmSioEBA9Iqp5IkSZK0KK1apWnJu+8OF1yQXmfcdlsqDYYOTSdIb0Buu+2CU79+0KZN1uhaBpYEFSBGmDw5/bA+/ngqBp57LhUFkH6o+/dPhcAuu8Buu6VmUJIkSZIao6Ym7Yaw1Vbwpz/BO++kNySfeipNQRg+PE1TgPSao18/2GabNJV5o43SdIWuXfN+DVqyBpcEIYT1gauA7sBU4JgY46uLuN33gTNI6x08BJwUY5xbnLjVbc4cGDsW3nwzrRvw5psL/j1lyoLbdeoEO+8MO+yQioEtt4T27bPFliRJklSh1lsvnb7znXR52rT0huXTT6fTM8+kU30rrbSgMKg7bbQRrLmmb2aWgsaMJBgKDIsxXhlCOBi4Etiy/g1CCGsDvwf6AR8BtwNDgIuKkraCzZwJH3749dOkSel87Ni0j+n8+V/9vJVWgk03TT9Ym22WSoHNNkvbmUiSJElSc+rcecHUBEhro739dtoZof6bna+8kkZBL2yllWDVVdNptdUW/LvutPLKaSRChw6up9ZUGvRSMoSwMrAFsGfhquHAhSGE9WKM79S76cHAHTHGSYXPuwT4BRVYEtTWwqxZNXz6aXqBP3MmzJq14N91p2nT0loAU6cuONW//Pnn8PHH6d+L07YtrLUW7LffgpatrnFbccXm+XolSZIkqbFqaha8dqmvbsp0/eJg/HiYODGdHnpowfTpRWnVKpUFizp16ZJKhPbt03n9U/v28O67nXj77TRqoU2br563bGn50ND3m1cHPowxzgOIMcYQwnhgDaB+SbAG8F69y+MK11WUp5+G7bYD2GOZ76Nz5/Sft0uXNE+nZ89Fn3r0SLep9v+okiRJkipHCGnUwEorpWnSC4sxTameOBE++GDB+SefpOvrn8aPhzFj0pu0DbPdEnMtXBq0bAktWiz4d/1TixZpO/mtt16mb0NJyjYoPYRwOnB6vavmhxAm5cqzjDoCXy7LJ06blk7vv1/kRGoOy3zcVdY87tXJ416dPO7VyeNenTzu1Wmxxz3GNIJhSaMYFrbNNkVK1bxWWtwHGloSvA/0DCG0jDHOCyEE0giB8Qvdbjywbr3Lay3iNgDEGM8Bzmng45ekEMKEGGOv3DnUvDzu1cnjXp087tXJ416dPO7VyeNenTzuS1bTkBvFGD8GRgJHFa46CJiw0HoEkNYqGBxC6FEoEk4AbixWWEmSJEmS1HQaVBIUHA8cH0J4i7TF4XcBQgiXhRAGA8QY3wV+AzxJWqvgE9KuCJIkSZIkqcQ1eE2CGOObwLaLuP7YhS5fCly6/NHKQllPl9Ay87hXJ497dfK4VyePe3XyuFcnj3t18rgvQYgx5s4gSZIkSZJKQGOmG0iSJEmSpApmSSBJkiRJkgBLgkYJIdSEEC4IIYwNIbwTQjh5Cbc9P4QwLoQQQwh9mjGmiiCEsH4I4akQwlshhOdDCJss5nbfDyG8Xfg/cWkIoVVzZ1XxNOS4hxDWCiE8EkKYGkIYnSGmiqyBx33XEMJzIYTXQgivhhD+GkLwb2gZa+Bx3zaEMLpwejWEMDSE0CZHXhVHQ/++F24bQggPhRA+b8aIagIN/HnfOYQws97P/OgQQrsceVUcjXg+v1nhud3rhdOBzZ211PgEp3GOAr4BbABsBfzPEv643AzsALzXTNlUXEOBYTHGDYCzgCsXvkEIYW3g98AAYD1gFWBIM2ZU8S31uAPTgF8BRzRjLjWthhz3KcBhMcZvAP2B7YBvN1tCNYWGHPcxwJYxxj7AZsDKwEnNFVBNoiHHvc6PgLHNEUpNrqHH/c0YY596p5nNllBNoSHP59sDtwO/ijFuDGwKPN6cIUuRJUHjHApcGmOcH2P8DPgXcPiibhhjfCzGOKFZ06koQggrA1sA1xauGg6sHkJYb6GbHgzcEWOcFNMKoJewmP8PKn0NPe4xxs9ijE8A05s5oppAI477qMI2v8QYZwGjgbWaL6mKqRHHfUaMcW7hYmugHeCKz2WqEX/fKbwJ9E3gL80WUE2iMcddlaMRx/0I4JnCczsKr/M+ab6kpcmSoHHW4KsjA8YVrlNlWR34MMY4D6BQAIzn68fa/w+VpaHHXZWl0cc9hNCDVBLe1SwJ1RQafNwLU4zGAJOBqcA/mjOoiqpBx70wdfBS4HhgfnOHVNE15vf8uiGEkYWh6Y4aKm8NPe7fAGaHEO4qTDG5OoSwUjNnLTmWBPWEEJ4OIUxezGn13PkkSXmFEDoDdwJ/jTG+kDuPml6McVyMsTfQA2gDVP1c1SrwG+CWGOPruYOoWY0EesUY+wEHACeEEA7JnElNryWwO6kU7At8AFycNVEJsCSoJ8a4bYyx+2JO75PapzXrfcpahetUWd4HeoYQWkJauIjUOi58rP3/UFkaetxVWRp83EMInYD7gNtjjOc0a0oVW6N/3mOMXwI3Akc2S0I1hYYe952AU0II44AngM4hLUZd9e8ulqkGHfcY47QY49TCvycAN5DWnVJ5aszz+YdjjB8URhtcC2zTrElLkCVB49wEHBdCaBFCWJG0RsG/MmdSkcUYPya1yUcVrjoImBBjfGehmw4HBocQehR+8ZxAegKpMtSI464K0tDjHkLoSCoI7osx/qF5U6rYGnHc1ysMPSeE0Jr07uJLzZlVxdPQ4x5jHBBjXDPGuBZpEeppMca1nKdcnhrx896zbteaQim8LzCqObOqeBrxvO7fwJaFkYIAe5MWra1qIRUmaogQQgvgfGAv0sJF58cYzyt8bDAwOMZ4bOHyUGAf0vDET4EvYowukFImQggbklZA7UZazf67McaXQwiXkRYrvKNwu+OAMwqf9ghwQr1FrlRmGnLcC6vgvkUadtwF+Bi4Jsb480yxtZwaeNx/Cfwv8Gq9T70pxvjH5s6r4mjgcR8C/JA0L70l8CDw08LilSpDDf37Xu/2awGjY4wrNHNUFVEDf95PBk4E5pF+3m8Cfht9sVS2GvF8/mjgZ0AtabrBkMIo8qplSSBJkiRJkgCnG0iSJEmSpAJLAkmSJEmSBFgSSJIkSZKkAksCSZIkSZIEWBJIkiRJkqQCSwJJkiRJkgRYEkiSJEmSpAJLAkmSJEmSBFgSSJIkSZKkgv8H3PsKdvvyz6YAAAAASUVORK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1280x720 with 1 Axes>"
       ]
@@ -3147,19 +3685,18 @@
     "sns.distplot(all_mae_loss,\n",
     "             bins = 20, \n",
     "             kde= True,\n",
-    "            color = 'blue');\n",
-    "# plt.xlim([0.0,.5])"
+    "            color = 'blue');"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 800,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/markdown": [
-       "Percentage of anomalies identified in anomalies set: **97.86%**"
+       "Percentage of anomalies identified in anomalies set: **99.76%**"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -3168,15 +3705,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2020-09-03 11:22:22,272 [1305416] WARNING  py.warnings:99: [JupyterRequire] /home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib64/python3.6/site-packages/sklearn/metrics/_classification.py:1221: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
-      "  _warn_prf(average, modifier, msg_start, len(result))\n",
-      "\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -3184,18 +3712,26 @@
       "              precision    recall  f1-score   support\n",
       "\n",
       "           0       0.00      0.00      0.00         0\n",
-      "           1       1.00      0.98      0.99       420\n",
+      "           1       1.00      1.00      1.00       420\n",
       "\n",
-      "    accuracy                           0.98       420\n",
-      "   macro avg       0.50      0.49      0.49       420\n",
-      "weighted avg       1.00      0.98      0.99       420\n",
+      "    accuracy                           1.00       420\n",
+      "   macro avg       0.50      0.50      0.50       420\n",
+      "weighted avg       1.00      1.00      1.00       420\n",
       "\n"
      ]
     },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib64/python3.6/site-packages/sklearn/metrics/_classification.py:1221: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
+      "  _warn_prf(average, modifier, msg_start, len(result))\n"
+     ]
+    },
     {
      "data": {
       "text/markdown": [
-       "F1 score for anomalies set: **0.9892**."
+       "F1 score for anomalies set: **0.9988**."
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -3228,7 +3764,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 801,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [
     {
@@ -3259,28 +3795,28 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>LSTM Autoencoder</td>\n",
-       "      <td>Deep Learning model</td>\n",
-       "      <td>0.989170</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>DecisionTreeClassifier</td>\n",
        "      <td>Statistical model</td>\n",
-       "      <td>0.978261</td>\n",
+       "      <td>1.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>SVC</td>\n",
        "      <td>Statistical model</td>\n",
-       "      <td>0.927757</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>LSTM Autoencoder</td>\n",
+       "      <td>Deep Learning model</td>\n",
+       "      <td>0.998808</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>GaussianNB</td>\n",
        "      <td>Statistical model</td>\n",
-       "      <td>0.784483</td>\n",
+       "      <td>0.992857</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -3288,13 +3824,13 @@
       ],
       "text/plain": [
        "                    Model           Model type  F1 score\n",
-       "3        LSTM Autoencoder  Deep Learning model  0.989170\n",
-       "0  DecisionTreeClassifier    Statistical model  0.978261\n",
-       "1                     SVC    Statistical model  0.927757\n",
-       "2              GaussianNB    Statistical model  0.784483"
+       "0  DecisionTreeClassifier    Statistical model  1.000000\n",
+       "1                     SVC    Statistical model  1.000000\n",
+       "3        LSTM Autoencoder  Deep Learning model  0.998808\n",
+       "2              GaussianNB    Statistical model  0.992857"
       ]
      },
-     "execution_count": 801,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3319,59 +3855,295 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 803,
+   "execution_count": 50,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# from joblib import dump, load\n",
+    "\n",
+    "# tf.keras.models.save_model(\n",
+    "#     lstm_autoencoder, \"file_name\", overwrite=True, include_optimizer=True, save_format=None,\n",
+    "#     signatures=None, options=None\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2020-09-03 11:22:50,162 [1305416] WARNING  py.warnings:99: [JupyterRequire] /home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib64/python3.6/site-packages/sklearn/metrics/_classification.py:1221: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
-      "  _warn_prf(average, modifier, msg_start, len(result))\n",
-      "\n"
+      "/home/fmurdaca/work/manuela-dev/ml-models/anomaly-detection\n",
+      "Model: \"sequential_1\"\n",
+      "_________________________________________________________________\n",
+      "Layer (type)                 Output Shape              Param #   \n",
+      "=================================================================\n",
+      "lstm_4 (LSTM)                (None, 1, 16)             1408      \n",
+      "_________________________________________________________________\n",
+      "lstm_5 (LSTM)                (None, 4)                 336       \n",
+      "_________________________________________________________________\n",
+      "repeat_vector_1 (RepeatVecto (None, 1, 4)              0         \n",
+      "_________________________________________________________________\n",
+      "lstm_6 (LSTM)                (None, 1, 4)              144       \n",
+      "_________________________________________________________________\n",
+      "lstm_7 (LSTM)                (None, 1, 16)             1344      \n",
+      "_________________________________________________________________\n",
+      "time_distributed_1 (TimeDist (None, 1, 5)              85        \n",
+      "=================================================================\n",
+      "Total params: 3,317\n",
+      "Trainable params: 3,317\n",
+      "Non-trainable params: 0\n",
+      "_________________________________________________________________\n",
+      "/home/fmurdaca/work/manuela-dev/ml-models/anomaly-detection/lstm_autoencoder_models/epoch100/epoch100ckpt\n"
      ]
     },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.training.tracking.util.CheckpointLoadStatus at 0x7fd2042c0208>"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Validate that the model can be loaded\n",
+    "\n",
+    "# load the model from disk\n",
+    "# loaded_model = tf.keras.models.load_model(file_name)\n",
+    "\n",
+    "from pathlib import Path\n",
+    "\n",
+    "current_path = Path.cwd()\n",
+    "print(current_path)\n",
+    "# Create a new model instance\n",
+    "loaded_model = get_model(X=x_train_healthy)\n",
+    "# Restore the weights\n",
+    "epoch_selected = \"epoch100\"\n",
+    "checkpoint_selected = \"epoch100ckpt\"\n",
+    "path_to_weights = current_path.joinpath(\"lstm_autoencoder_models\", epoch_selected, checkpoint_selected)\n",
+    "print(path_to_weights)\n",
+    "loaded_model.load_weights(current_path.joinpath(\"lstm_autoencoder_models\", epoch_selected, checkpoint_selected))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "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>threshold</th>\n",
+       "      <th>percentage_anomalies_test</th>\n",
+       "      <th>percentage_anomalies_val</th>\n",
+       "      <th>f1_score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.001420</td>\n",
+       "      <td>98.680619</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.018913</td>\n",
+       "      <td>4.868062</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.036406</td>\n",
+       "      <td>2.957234</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.053899</td>\n",
+       "      <td>2.957234</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.071392</td>\n",
+       "      <td>2.820746</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0.088886</td>\n",
+       "      <td>2.365787</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>0.106379</td>\n",
+       "      <td>1.728844</td>\n",
+       "      <td>99.761905</td>\n",
+       "      <td>0.998808</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0.123872</td>\n",
+       "      <td>1.228389</td>\n",
+       "      <td>99.761905</td>\n",
+       "      <td>0.998808</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>0.141365</td>\n",
+       "      <td>0.227480</td>\n",
+       "      <td>99.761905</td>\n",
+       "      <td>0.998808</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   threshold  percentage_anomalies_test  percentage_anomalies_val  f1_score\n",
+       "0   0.001420                  98.680619                100.000000  1.000000\n",
+       "1   0.018913                   4.868062                100.000000  1.000000\n",
+       "2   0.036406                   2.957234                100.000000  1.000000\n",
+       "3   0.053899                   2.957234                100.000000  1.000000\n",
+       "4   0.071392                   2.820746                100.000000  1.000000\n",
+       "5   0.088886                   2.365787                100.000000  1.000000\n",
+       "6   0.106379                   1.728844                 99.761905  0.998808\n",
+       "7   0.123872                   1.228389                 99.761905  0.998808\n",
+       "8   0.141365                   0.227480                 99.761905  0.998808"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results_summary = []\n",
+    "from numpy import arange\n",
+    "\n",
+    "for threshold_ in arange(min(train_mae_loss), max(train_mae_loss), mean(train_mae_loss)):\n",
+    "    x_test_pred = predict_results(loaded_model, x_test_healthy)\n",
+    "\n",
+    "    x_test_pred_ = x_test_pred.reshape(x_test_pred.shape[0], x_test_pred.shape[2])\n",
+    "    x_test_healthy_ = x_test_healthy.reshape(x_test_healthy.shape[0], x_test_healthy.shape[2])\n",
+    "\n",
+    "    test_mae_loss = np.mean(np.abs(x_test_pred_ - x_test_healthy_), axis=1)\n",
+    "\n",
+    "    scored_test = {}\n",
+    "    scored_test['Loss_mae'] = test_mae_loss\n",
+    "    scored_test['Threshold'] = threshold_\n",
+    "    scored_tt = pd.DataFrame(scored_test)\n",
+    "    scored_tt['Healthy_pred'] = scored_tt['Loss_mae'] < scored_tt['Threshold']\n",
+    "    scored_tt['Healthy_pred_int'] = scored_tt['Healthy_pred'].astype(int)\n",
+    "\n",
+    "    scored_tt['Target'] = y_test_healthy.values\n",
+    "    no_anomalies = scored_tt[scored_tt['Healthy_pred_int'] == 0]\n",
+    "    percentage_identified = no_anomalies.shape[0]/scored_t.shape[0]\n",
+    "\n",
+    "    \n",
+    "    x_all_pred = predict_results(loaded_model, x_all_anomalies)\n",
+    "    all_mae_loss = np.mean(np.abs(x_all_pred - x_all_anomalies), axis=1)\n",
+    "\n",
+    "    scored_test_aa = {}\n",
+    "    scored_test_aa['Loss_mae'] = all_mae_loss[:, 0]\n",
+    "    scored_test_aa['Threshold'] = threshold_\n",
+    "\n",
+    "    scored_aa = pd.DataFrame(scored_test_aa)\n",
+    "    scored_aa['Anomaly_pred'] = scored_aa['Loss_mae'] > scored_aa['Threshold']\n",
+    "    scored_aa['Anomaly_pred_int'] = scored_aa['Anomaly_pred'].astype(int)\n",
+    "\n",
+    "    scored_aa['Target'] = y_all_anomalies.values\n",
+    "\n",
+    "    with_anomalies = scored_aa[scored_aa['Anomaly_pred_int'] == 1]\n",
+    "    percentage_identified_val_set = with_anomalies.shape[0]/scored_aa.shape[0]\n",
+    "\n",
+    "    f1_score_ = f1_score(scored_aa['Target'], scored_aa['Anomaly_pred_int'])\n",
+    "\n",
+    "    result_summary = {\n",
+    "        \"threshold\": threshold_,\n",
+    "        \"percentage_anomalies_test\": percentage_identified*100,\n",
+    "        \"percentage_anomalies_val\": percentage_identified_val_set*100,\n",
+    "        \"f1_score\": f1_score_\n",
+    "    }\n",
+    "    \n",
+    "    results_summary.append(result_summary)\n",
+    "\n",
+    "pd.DataFrame(results_summary)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Percentage of anomalies identified: 96.19%\n",
+      "Percentage of anomalies identified: 99.76%\n",
       "              precision    recall  f1-score   support\n",
       "\n",
       "           0       0.00      0.00      0.00         0\n",
-      "           1       1.00      0.96      0.98       420\n",
+      "           1       1.00      1.00      1.00       420\n",
       "\n",
-      "    accuracy                           0.96       420\n",
-      "   macro avg       0.50      0.48      0.49       420\n",
-      "weighted avg       1.00      0.96      0.98       420\n",
+      "    accuracy                           1.00       420\n",
+      "   macro avg       0.50      0.50      0.50       420\n",
+      "weighted avg       1.00      1.00      1.00       420\n",
       "\n",
-      "Score is: 0.9806.\n"
+      "Score is: 0.9988.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/fmurdaca/.local/share/virtualenvs/manuela-dev-SY9YZsQk/lib64/python3.6/site-packages/sklearn/metrics/_classification.py:1221: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
+      "  _warn_prf(average, modifier, msg_start, len(result))\n"
      ]
     }
    ],
    "source": [
-    "from joblib import dump, load\n",
-    "from pathlib import Path\n",
-    "\n",
-    "current_path = Path().cwd()\n",
-    "\n",
-    "filepath = current_path.joinpath('ml-models/anomaly-detection/lstm_autoencoder_model')\n",
-    "\n",
-    "tf.keras.models.save_model(\n",
-    "    lstm_autoencoder, filepath, overwrite=True, include_optimizer=True, save_format=None,\n",
-    "    signatures=None, options=None\n",
-    ")\n",
-    "\n",
-    "# Validate that the model can be loaded\n",
-    "\n",
-    "# load the model from disk\n",
-    "loaded_model = tf.keras.models.load_model(filepath)\n",
-    "x_all_pred = loaded_model.predict(x_all_anomalies)\n",
+    "x_all_pred = predict_results(loaded_model, x_all_anomalies)\n",
     "all_mae_loss = np.mean(np.abs(x_all_pred - x_all_anomalies), axis=1)\n",
     "\n",
     "scored_test = {}\n",
     "scored_test['Loss_mae'] = all_mae_loss[:, 0]\n",
     "scored_test['Threshold'] = threshold\n",
+    "\n",
     "scored_a = pd.DataFrame(scored_test)\n",
     "scored_a['Anomaly_pred'] = scored_a['Loss_mae'] > scored_a['Threshold']\n",
     "scored_a['Anomaly_pred_int'] = scored_a['Anomaly_pred'].astype(int)\n",
@@ -3398,7 +4170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 718,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3423,21 +4195,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 719,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Initializing...\n",
-      "Load modelfile: model.joblib\n",
-      "Features types:  <class 'numpy.ndarray'> <class 'numpy.float32'>\n",
-      "Predict features:  [[16.1  15.4  15.32 13.47 17.7 ]]\n",
-      "Prediction:  [1]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "p = AnomalyDetection()\n",
     "    \n",