diff --git a/data/.ipynb_checkpoints/beers-checkpoint.csv b/data/.ipynb_checkpoints/beers-checkpoint.csv
deleted file mode 100644
index b041f48..0000000
--- a/data/.ipynb_checkpoints/beers-checkpoint.csv
+++ /dev/null
@@ -1,2408 +0,0 @@
-,abv,ibu,id,name,style,brewery_id,ounces
-0,0.05,,1436,Pub Beer,American Pale Lager,408,12.0
-1,0.066,,2265,Devil's Cup,American Pale Ale (APA),177,12.0
-2,0.071,,2264,Rise of the Phoenix,American IPA,177,12.0
-3,0.09,,2263,Sinister,American Double / Imperial IPA,177,12.0
-4,0.075,,2262,Sex and Candy,American IPA,177,12.0
-5,0.077,,2261,Black Exodus,Oatmeal Stout,177,12.0
-6,0.045,,2260,Lake Street Express,American Pale Ale (APA),177,12.0
-7,0.065,,2259,Foreman,American Porter,177,12.0
-8,0.055,,2258,Jade,American Pale Ale (APA),177,12.0
-9,0.086,,2131,Cone Crusher,American Double / Imperial IPA,177,12.0
-10,0.07200000000000001,,2099,Sophomoric Saison,Saison / Farmhouse Ale,177,12.0
-11,0.073,,2098,Regional Ring Of Fire,Saison / Farmhouse Ale,177,12.0
-12,0.069,,2097,Garce Selé,Saison / Farmhouse Ale,177,12.0
-13,0.085,,1980,Troll Destroyer,Belgian IPA,177,12.0
-14,0.061,60.0,1979,Bitter Bitch,American Pale Ale (APA),177,12.0
-15,0.06,,2318,Ginja Ninja,Cider,154,12.0
-16,0.06,,2170,Cherried Away,Cider,154,12.0
-17,0.06,,2169,Rhubarbarian,Cider,154,12.0
-18,0.06,,1502,BrightCider,Cider,154,12.0
-19,0.08199999999999999,,1593,He Said Baltic-Style Porter,Baltic Porter,368,12.0
-20,0.08199999999999999,,1592,He Said Belgian-Style Tripel,Tripel,368,12.0
-21,0.099,92.0,1036,Lower De Boom,American Barleywine,368,8.4
-22,0.079,45.0,1024,Fireside Chat,Winter Warmer,368,12.0
-23,0.079,,976,Marooned On Hog Island,American Stout,368,12.0
-24,0.044000000000000004,42.0,876,Bitter American,American Pale Ale (APA),368,12.0
-25,0.049,17.0,802,Hell or High Watermelon Wheat (2009),Fruit / Vegetable Beer,368,12.0
-26,0.049,17.0,801,Hell or High Watermelon Wheat (2009),Fruit / Vegetable Beer,368,12.0
-27,0.049,17.0,800,21st Amendment Watermelon Wheat Beer (2006),Fruit / Vegetable Beer,368,12.0
-28,0.07,70.0,799,21st Amendment IPA (2006),American IPA,368,12.0
-29,0.07,70.0,797,Brew Free! or Die IPA (2008),American IPA,368,12.0
-30,0.07,70.0,796,Brew Free! or Die IPA (2009),American IPA,368,12.0
-31,0.085,52.0,531,Special Edition: Allies Win The War!,English Strong Ale,368,12.0
-32,0.09699999999999999,94.0,432,Hop Crisis,American Double / Imperial IPA,368,12.0
-33,0.044000000000000004,42.0,353,Bitter American (2011),American Pale Ale (APA),368,12.0
-34,0.079,45.0,321,Fireside Chat (2010),Winter Warmer,368,12.0
-35,0.068,65.0,173,Back in Black,American Black Ale,368,12.0
-36,0.083,35.0,11,Monk's Blood,Belgian Dark Ale,368,12.0
-37,0.07,65.0,10,Brew Free! or Die IPA,American IPA,368,12.0
-38,0.049,17.0,9,Hell or High Watermelon Wheat,Fruit / Vegetable Beer,368,12.0
-39,0.07,82.0,2519,Bimini Twist,American IPA,67,12.0
-40,0.05,,2518,Beach Blonde,American Blonde Ale,67,12.0
-41,0.059000000000000004,,2517,Rod Bender Red,American Amber / Red Ale,67,12.0
-42,0.035,11.0,2545,Passion Fruit Prussia,Berliner Weissbier,60,12.0
-43,0.045,18.0,2544,Send Help,American Blonde Ale,60,12.0
-44,0.055,,2324,Cast Iron Oatmeal Brown,American Brown Ale,60,12.0
-45,0.06,,2288,Reprise Centennial Red,American Amber / Red Ale,60,12.0
-46,0.055,,2287,Alter Ego,American Black Ale,60,12.0
-47,0.065,,2286,Divided Sky,American IPA,60,12.0
-48,0.065,,2285,Resurrected,American IPA,60,12.0
-49,0.05,28.0,1870,Contact High,American Pale Wheat Ale,60,12.0
-50,0.065,,2603,Galaxyfest,American IPA,27,16.0
-51,0.05,45.0,2602,Citrafest,American IPA,27,16.0
-52,0.09,,2220,Barn Yeti,Belgian Strong Dark Ale,27,16.0
-53,0.069,65.0,2219,Scarecrow,American IPA,27,16.0
-54,0.09,50.0,2218,Ironman,English Strong Ale,27,16.0
-55,0.046,15.0,2217,Honey Kolsch,Kölsch,27,16.0
-56,0.052000000000000005,18.0,2216,Copperhead Amber,Belgian Dark Ale,27,16.0
-57,0.059000000000000004,75.0,972,Rude Parrot IPA,American IPA,481,16.0
-58,0.054000000000000006,30.0,866,British Pale Ale (2010),English Pale Ale,481,16.0
-59,0.054000000000000006,30.0,48,British Pale Ale,English Pale Ale,481,16.0
-60,0.084,82.0,47,Ballz Deep Double IPA,American Double / Imperial IPA,481,16.0
-61,0.038,,1583,Wolfman's Berliner,Berliner Weissbier,373,12.0
-62,0.055,26.0,1165,Colorado Native,American Amber / Red Lager,462,12.0
-63,0.055,26.0,431,Colorado Native (2011),American Amber / Red Lager,462,12.0
-64,0.065,52.0,516,Jockamo IPA,American IPA,533,12.0
-65,0.042,13.0,515,Purple Haze,Fruit / Vegetable Beer,533,12.0
-66,0.045,17.0,514,Abita Amber,American Amber / Red Lager,533,12.0
-67,0.08199999999999999,68.0,2540,Citra Ass Down,American IPA,62,16.0
-68,0.05,20.0,2539,The Brown Note,American Brown Ale,62,16.0
-69,0.08,68.0,2686,Citra Ass Down,American Double / Imperial IPA,1,16.0
-70,0.125,80.0,2685,London Balling,English Barleywine,1,16.0
-71,0.077,25.0,2684,35 K,Milk / Sweet Stout,1,16.0
-72,0.042,42.0,2683,A Beer,American Pale Ale (APA),1,16.0
-73,0.05,25.0,2682,Rules are Rules,German Pilsener,1,16.0
-74,0.066,21.0,2681,Flesh Gourd'n,Pumpkin Ale,1,16.0
-75,0.04,13.0,2680,Sho'nuff,Belgian Pale Ale,1,16.0
-76,0.055,17.0,2679,Bloody Show,American Pilsner,1,16.0
-77,0.076,68.0,2678,Rico Sauvin,American Double / Imperial IPA,1,16.0
-78,0.051,38.0,2677,Coq de la Marche,Saison / Farmhouse Ale,1,16.0
-79,0.065,,2676,Kamen Knuddeln,American Wild Ale,1,16.0
-80,0.06,65.0,2675,Pile of Face,American IPA,1,16.0
-81,0.05,20.0,2674,The Brown Note,English Brown Ale,1,16.0
-82,0.053,35.0,1594,Maylani's Coconut Stout,American Stout,367,16.0
-83,0.05,35.0,1162,Oatmeal PSA,American Pale Ale (APA),367,16.0
-84,0.052000000000000005,33.0,1137,Pre Flight Pilsner,American Pilsner,367,16.0
-85,0.04,20.0,2403,P-Town Pilsner,American Pilsner,117,12.0
-86,0.053,36.0,2402,Klickitat Pale Ale,American Pale Ale (APA),117,12.0
-87,0.08199999999999999,103.0,2401,Yellow Wolf Imperial IPA,American Double / Imperial IPA,117,12.0
-88,0.053,40.0,1921,Freeride APA,American Pale Ale (APA),270,12.0
-89,0.053,18.0,1920,Alaskan Amber,Altbier,270,12.0
-90,0.057,,2501,Hopalicious,American Pale Ale (APA),73,12.0
-91,0.043,,1535,Kentucky Kölsch,Kölsch,388,16.0
-92,0.065,,1149,Kentucky IPA,American IPA,388,16.0
-93,0.054000000000000006,,1474,Dusty Trail Pale Ale,American Pale Ale (APA),401,16.0
-94,0.062,,1473,Damnesia,American IPA,401,16.0
-95,0.062,43.0,837,Desolation IPA,American IPA,401,16.0
-96,0.059000000000000004,,2592,Liberty Ale,American IPA,35,12.0
-97,0.065,,2578,IPA,American IPA,35,12.0
-98,0.045,,2577,Summer Wheat,American Pale Wheat Ale,35,12.0
-99,0.049,,2103,California Lager,American Amber / Red Lager,35,12.0
-100,0.055999999999999994,,2102,Brotherhood Steam,California Common / Steam Beer,35,12.0
-101,0.042,,2291,Blood Orange Gose,Gose,171,12.0
-102,0.042,,1818,Keebarlin' Pale Ale,American Pale Ale (APA),171,12.0
-103,0.048,,1738,"the Kimmie, the Yink and the Holy Gose",Gose,171,12.0
-104,0.06,,1563,Fall Hornin',Pumpkin Ale,171,12.0
-105,0.057,13.0,1520,Barney Flats Oatmeal Stout,Oatmeal Stout,171,12.0
-106,0.055999999999999994,4.0,1350,Summer Solstice,Cream Ale,171,12.0
-107,0.07,80.0,1327,Hop Ottin' IPA,American IPA,171,12.0
-108,0.057999999999999996,15.0,1326,Boont Amber Ale,American Amber / Red Ale,171,12.0
-109,0.057,13.0,1221,Barney Flats Oatmeal Stout,Oatmeal Stout,171,12.0
-110,0.055,25.0,1217,El Steinber Dark Lager,Vienna Lager,171,16.0
-111,0.057999999999999996,15.0,811,Boont Amber Ale (2010),American Amber / Red Ale,171,12.0
-112,0.055999999999999994,4.0,753,Summer Solstice Cerveza Crema (2009),Cream Ale,171,12.0
-113,0.057,13.0,572,Barney Flats Oatmeal Stout (2012),Oatmeal Stout,171,12.0
-114,0.069,6.0,523,Winter Solstice,Winter Warmer,171,12.0
-115,0.07,80.0,367,Hop Ottin' IPA (2011),American IPA,171,12.0
-116,0.057999999999999996,15.0,78,Boont Amber Ale (2011),American Amber / Red Ale,171,12.0
-117,0.055999999999999994,4.0,77,Summer Solstice (2011),Cream Ale,171,12.0
-118,0.055,28.0,76,Poleeko Gold Pale Ale (2009),American Pale Ale (APA),171,12.0
-119,0.06,,2337,Charlie's Rye IPA,American IPA,146,16.0
-120,0.054000000000000006,,410,River Pig Pale Ale,American Pale Ale (APA),542,16.0
-121,0.047,,409,Oaky's Oatmeal Stout,Oatmeal Stout,542,16.0
-122,0.05,,1294,Angry Orchard Apple Ginger,Cider,434,16.0
-123,0.05,,1293,Angry Orchard Crisp Apple,Cider,434,16.0
-124,0.05,,1292,Angry Orchard Crisp Apple,Cider,434,12.0
-125,0.068,,2207,Golden One,Belgian Pale Ale,193,12.0
-126,0.06,,2040,Arjuna,Witbier,193,12.0
-127,0.085,,2039,Uroboros,American Stout,193,12.0
-128,0.071,75.0,2511,Long Leaf,American IPA,69,16.0
-129,0.047,19.0,2510,Honey Badger Blonde,American Blonde Ale,69,16.0
-130,0.06,23.0,2509,Porter (a/k/a Black Gold Porter),American Porter,69,16.0
-131,0.06,55.0,413,Sky High Rye,American Pale Ale (APA),541,12.0
-132,0.062,17.0,390,Whitsun,American Pale Wheat Ale,541,12.0
-133,0.052000000000000005,,735,On-On Ale (2008),American Pale Ale (APA),513,12.0
-134,0.092,50.0,1333,Quakertown Stout,American Double / Imperial Stout,426,12.0
-135,0.051,20.0,1332,Greenbelt Farmhouse Ale,Saison / Farmhouse Ale,426,12.0
-136,0.052000000000000005,10.0,1172,Mo's Gose,Gose,461,16.0
-137,0.07,45.0,1322,Green Bullet Organic India Pale Ale,American IPA,429,16.0
-138,0.032,27.0,550,Rocket Girl,Kölsch,528,12.0
-139,0.053,26.0,429,Ninja Porter,American Porter,528,12.0
-140,0.06,69.0,428,Shiva IPA,American IPA,528,12.0
-141,0.048,,1640,Aslan Kölsch,Kölsch,353,16.0
-142,0.077,,1639,Aslan IPA,American IPA,353,16.0
-143,0.077,,1638,Aslan Amber,American Amber / Red Ale,353,16.0
-144,0.055999999999999994,27.0,597,This Season's Blonde,American Blonde Ale,523,12.0
-145,0.07,67.0,596,Independence Pass Ale,American IPA,523,12.0
-146,0.057,40.0,1580,Trolley Stop Stout,American Stout,374,12.0
-147,0.08199999999999999,138.0,980,Bitter Bitch Imperial IPA,American Double / Imperial IPA,374,12.0
-148,0.062,35.0,979,Poop Deck Porter,American Porter,374,12.0
-149,0.06,35.0,978,Old Red Beard Amber Ale,American Amber / Red Ale,374,12.0
-150,0.075,115.0,2503,Hop A-Peel,American Double / Imperial IPA,72,16.0
-151,0.055,12.0,2502,Vanilla Java Porter,American Porter,72,16.0
-152,0.052000000000000005,,2495,Michelada,Fruit / Vegetable Beer,72,16.0
-153,0.045,8.0,534,Dirty Blonde Ale,American Blonde Ale,72,12.0
-154,0.05,62.0,528,Grand Circus IPA,American IPA,72,12.0
-155,0.05,12.0,527,Atwater's Lager,Munich Helles Lager,72,12.0
-156,0.07,,1409,Heavy Machinery IPA Series #1: Heavy Fist,American Black Ale,413,16.0
-157,0.062,,343,Fire Eagle IPA,American IPA,413,12.0
-158,0.051,,342,Peacemaker,American Pale Ale (APA),413,12.0
-159,0.053,,341,Pearl-Snap,German Pilsener,413,12.0
-160,0.052000000000000005,,340,Black Thunder,Schwarzbier,413,12.0
-161,0.08,,2589,Raja,American Double / Imperial IPA,37,12.0
-162,0.064,,2546,Perzik Saison,Saison / Farmhouse Ale,37,12.0
-163,0.047,42.0,146,Avery Joe’s Premium American Pilsner,German Pilsener,37,12.0
-164,0.055999999999999994,10.0,108,White Rascal,Witbier,37,12.0
-165,0.063,69.0,107,Avery India Pale Ale,American IPA,37,12.0
-166,0.055,17.0,106,Ellie’s Brown Ale,American Brown Ale,37,12.0
-167,0.062,17.0,1620,Pumpkin Beast,Pumpkin Ale,360,12.0
-168,0.07200000000000001,22.0,1579,OktoberBeast,Märzen / Oktoberfest,360,12.0
-169,0.048,23.0,1228,Mad Beach,American Pale Wheat Ale,360,12.0
-170,0.067,,705,Hog Wild India Pale Ale,American IPA,360,12.0
-171,0.092,5.0,704,Devils Tramping Ground Tripel,Tripel,360,12.0
-172,0.061,41.0,702,Hot Rod Red,American Amber / Red Ale,360,12.0
-173,0.086,,2058,Palate Mallet,American Double / Imperial IPA,235,12.0
-174,0.06,,1483,Back East Porter,American Porter,235,12.0
-175,0.049,,1426,Back East Golden Ale,American Blonde Ale,235,12.0
-176,0.07,,1132,Misty Mountain IPA,American IPA,235,12.0
-177,0.05,,1131,Back East Ale,American Amber / Red Ale,235,12.0
-178,0.06,,1876,Truck Stop Honey Brown Ale,English Brown Ale,286,12.0
-179,0.06,43.0,1875,Naked Pig Pale Ale,American Pale Ale (APA),286,12.0
-180,0.068,70.0,966,Topcutter India Pale Ale,American IPA,483,12.0
-181,0.044000000000000004,38.0,965,Field 41 Pale Ale,American Pale Ale (APA),483,12.0
-182,0.07,,2593,Grapefruit Sculpin,American IPA,34,12.0
-183,0.038,40.0,2105,Even Keel,American IPA,34,12.0
-184,0.052000000000000005,23.0,1401,Ballast Point Pale Ale,Kölsch,34,12.0
-185,0.07,75.0,1400,Big Eye India Pale Ale,American IPA,34,12.0
-186,0.046,,1019,Longfin Lager,Munich Helles Lager,34,12.0
-187,0.07,70.0,1018,Sculpin IPA,American IPA,34,12.0
-188,0.045,,1776,All Nighter Ale,Extra Special / Strong Bitter (ESB),318,12.0
-189,0.045,20.0,1644,Banner American Rye,Rye Beer,318,12.0
-190,0.035,45.0,1643,Banner American Ale,American Amber / Red Ale,318,12.0
-191,0.07,46.0,2618,Thai.p.a,American IPA,20,16.0
-192,0.06,60.0,2005,Barrio Blanco,American IPA,251,12.0
-193,0.045,,1343,Barrio Tucson Blonde,American Blonde Ale,251,12.0
-194,0.049,22.0,2404,Hop in the ‘Pool Helles,American Pilsner,116,12.0
-195,0.067,60.0,2323,Ultra Gnar Gnar IPA,American IPA,116,12.0
-196,0.068,62.0,2189,In-Tents India Pale Lager,American Pale Lager,116,12.0
-197,0.05,20.0,2188,Lost Meridian Wit,Witbier,116,12.0
-198,0.051,45.0,2187,Celestial Meridian Cascadian Dark Lager,Euro Dark Lager,116,12.0
-199,0.054000000000000006,55.0,1966,Wagon Party,California Common / Steam Beer,258,12.0
-200,0.067,70.0,1965,Sky-Five,American IPA,258,12.0
-201,0.05,28.0,1964,Stargrazer,Schwarzbier,258,12.0
-202,0.054000000000000006,48.0,1963,Wonderstuff,German Pilsener,258,12.0
-203,0.053,,1855,Tarnation California-Style Lager,California Common / Steam Beer,292,12.0
-204,0.07,42.0,1778,On the Count of 3 (2015),Hefeweizen,292,16.0
-205,0.047,,1209,Summer Swelter,American Pale Wheat Ale,292,12.0
-206,0.068,,954,Phantom Punch Winter Stout,Foreign / Export Stout,292,12.0
-207,0.066,,910,Hayride Autumn Ale,Rye Beer,292,12.0
-208,0.047,,707,Celsius Summer Ale (2012),American Pale Wheat Ale,292,12.0
-209,0.055,35.0,533,Amber Road,American Amber / Red Ale,292,12.0
-210,0.049,28.0,183,Pamola Xtra Pale Ale,American Pale Ale (APA),292,12.0
-211,0.069,69.0,182,Stowaway IPA,American IPA,292,12.0
-212,0.08800000000000001,108.0,1806,Hoptopus Double IPA,American Double / Imperial IPA,306,16.0
-213,0.05,10.0,2435,Watermelon Ale,Fruit / Vegetable Beer,103,12.0
-214,0.057999999999999996,45.0,2423,Fenway American Pale Ale,American Pale Ale (APA),103,12.0
-215,0.068,85.0,2420,Back Bay IPA,American IPA,103,12.0
-216,0.048,16.0,2419,Bunker Hill Blueberry Ale ,Other,103,12.0
-217,0.057999999999999996,,2494,Oberon,American Pale Wheat Ale,76,12.0
-218,0.06,,2325,Smitten,Rye Beer,76,16.0
-219,0.05,,2022,Winter White,Witbier,76,16.0
-220,0.057999999999999996,,1989,Oberon,American Pale Wheat Ale,76,16.0
-221,0.07,,1988,Two Hearted,American IPA,76,16.0
-222,0.057999999999999996,,1955,Best Brown,American Brown Ale,76,16.0
-223,0.044000000000000004,44.0,2558,Moar,English India Pale Ale (IPA),53,12.0
-224,0.083,,2557,Uber Lupin Schwarz IPA,American Double / Imperial IPA,53,16.0
-225,0.057,27.0,2556,Nordic Blonde,American Blonde Ale,53,12.0
-226,0.06,,2496,Cold Press,American Black Ale,75,12.0
-227,0.07200000000000001,87.0,2410,Harness the Winter,American IPA,75,12.0
-228,0.055999999999999994,32.0,1902,14° ESB ,Extra Special / Strong Bitter (ESB),75,12.0
-229,0.062,68.0,1901,Bent Hop Golden IPA,American IPA,75,12.0
-230,0.06,34.0,1261,Bent Paddle Black Ale,American Black Ale,75,12.0
-231,0.05,38.0,1253,Venture Pils,German Pilsener,75,12.0
-232,0.055,40.0,1900,Lost Sailor IPA,English India Pale Ale (IPA),278,12.0
-233,0.053,20.0,1317,Steel Rail Extra Pale Ale,American Pale Ale (APA),278,12.0
-234,0.078,,1158,La Frontera Premium IPA,American IPA,463,12.0
-235,0.047,,1157,Tejas Lager,Czech Pilsener,463,12.0
-236,0.064,,1156,Number 22 Porter,American Porter,463,12.0
-237,0.055999999999999994,,1155,Big Bend Hefeweizen,Hefeweizen,463,12.0
-238,0.06,,1154,Terlingua Gold,American Blonde Ale,463,12.0
-239,0.081,17.0,2104,Aprè Shred,American Strong Ale,220,16.0
-240,0.095,104.0,1762,Hemlock Double IPA,American Double / Imperial IPA,220,12.0
-241,0.040999999999999995,,1422,West Portal Colorado Common Summer Ale,California Common / Steam Beer,220,16.0
-242,0.067,85.0,1067,Disconnected Red,American Amber / Red Ale,220,16.0
-243,0.07,,1003,Big Elm IPA,American IPA,477,12.0
-244,0.065,,1002,Gerry Dog Stout,American Stout,477,12.0
-245,0.06,,1001,413 Farmhouse Ale,Saison / Farmhouse Ale,477,12.0
-246,0.08,54.0,2639,Dark Star,American Stout,8,16.0
-247,0.062,,2469,Ryecoe,American IPA,8,16.0
-248,0.06,,2586,Blueberry Blonde,Fruit / Vegetable Beer,40,12.0
-249,0.075,60.0,2585,Galaxy IPA,American IPA,40,16.0
-250,0.05,32.0,643,Big River Pilsner,Czech Pilsener,519,12.0
-251,0.06,55.0,632,House Brand IPA,American IPA,519,12.0
-252,0.062,65.0,1714,Big Sky IPA,American IPA,336,12.0
-253,0.05,40.0,1713,Scape Goat Pale Ale,English Pale Ale,336,12.0
-254,0.05,35.0,1712,Montana Trout Slayer Ale,American Pale Wheat Ale,336,12.0
-255,0.051,26.0,1711,Moose Drool Brown Ale,American Brown Ale,336,12.0
-256,0.07200000000000001,60.0,1456,Powder Hound Winter Ale,English Strong Ale,336,12.0
-257,0.051,26.0,767,Moose Drool Brown Ale (2011),American Brown Ale,336,12.0
-258,0.05,35.0,766,Montana Trout Slayer Ale (2012),American Pale Wheat Ale,336,12.0
-259,0.062,65.0,579,Big Sky IPA (2012),American IPA,336,12.0
-260,0.047,,168,Summer Honey,American Blonde Ale,336,12.0
-261,0.05,40.0,159,Scape Goat Pale Ale (2010),English Pale Ale,336,12.0
-262,0.05,35.0,35,Montana Trout Slayer Ale (2009),American Pale Wheat Ale,336,12.0
-263,0.051,26.0,34,Moose Drool Brown Ale (2009),American Brown Ale,336,12.0
-264,0.069,81.0,2096,Arcus IPA,American IPA,221,12.0
-265,0.057999999999999996,38.0,2095,Wavemaker,American Amber / Red Ale,221,12.0
-266,0.053,43.0,1257,Jack Pine Savage,American Pale Ale (APA),444,16.0
-267,0.099,85.0,1256,Forest Fire Imperial Smoked Rye,Rye Beer,444,16.0
-268,0.098,76.0,1255,Bad Axe Imperial IPA,American Double / Imperial IPA,444,16.0
-269,0.055,35.0,986,Morning Wood,Oatmeal Stout,444,16.0
-270,0.066,50.0,985,Bark Bite IPA,American IPA,444,16.0
-271,0.055,45.0,2508,Jalapeno Pale Ale,American Pale Ale (APA),70,16.0
-272,0.052000000000000005,,1441,Blown Out Brown,American Brown Ale,407,12.0
-273,0.063,,1413,Single Hop Ale,American Pale Ale (APA),407,12.0
-274,0.054000000000000006,,1411,Sawtooth Ale,American Blonde Ale,407,12.0
-275,0.07200000000000001,75.0,2620,Saucy Intruder,Rye Beer,18,16.0
-276,0.045,16.0,2412,Deception,American Blonde Ale,112,12.0
-277,0.075,35.0,1898,Blackmarket Rye IPA,American IPA,112,12.0
-278,0.05,8.0,1897,Black Market Hefeweizen,Hefeweizen,112,12.0
-279,0.057999999999999996,44.0,1896,Aftermath Pale Ale,American Pale Ale (APA),112,12.0
-280,0.071,83.0,1850,American India Red Ale,American Strong Ale,294,12.0
-281,0.071,45.0,1849,American Red Porter,American Porter,294,12.0
-282,0.078,34.0,1848,American Red Saison,Saison / Farmhouse Ale,294,12.0
-283,0.066,44.0,1847,Colorado Red Ale,American Amber / Red Ale,294,12.0
-284,0.048,16.0,2485,Saddle Bronc Brown Ale,American Brown Ale,79,12.0
-285,0.046,20.0,2484,Bomber Mountain Amber Ale,American Amber / Red Ale,79,12.0
-286,0.073,,2449,Flying Sailor,Rye Beer,95,12.0
-287,0.048,47.0,2634,Nordskye ,American IPA,12,12.0
-288,0.06,30.0,2153,North Third Stout,Foreign / Export Stout,12,12.0
-289,0.052000000000000005,,1953,Honey Lav,American Pale Wheat Ale,12,12.0
-290,0.068,,1496,Coconut Brown Ale,American Brown Ale,12,12.0
-291,0.07,51.0,1481,51K IPA,American IPA,12,12.0
-292,0.055,,1480,Grand Rabbits,Cream Ale,12,12.0
-293,0.05,,1564,1800 Big Log Wheat (2012),American Pale Wheat Ale,380,12.0
-294,,,1541,Double Play Pilsner,American Pilsner,380,12.0
-295,0.055,,1321,Brewerhood Brown Ale,American Brown Ale,380,12.0
-296,0.08,,1320,Last Call Imperial Amber Ale,American Amber / Red Ale,380,12.0
-297,0.096,,1319,Pernicious Double IPA,American Double / Imperial IPA,380,12.0
-298,0.052000000000000005,,1303,6-4-3 Double Play Pilsner,German Pilsener,380,12.0
-299,,,1025,N Street Drive-In 50th Anniversary IPA,American Double / Imperial IPA,380,12.0
-300,0.05,,1012,467 Ethan's Stout,American Stout,380,12.0
-301,0.064,,942,1335 Wicked Snout,Saison / Farmhouse Ale,380,12.0
-302,0.045,,937,543 Skull Creek Fresh Hopped Pale Ale,American Pale Ale (APA),380,12.0
-303,0.055999999999999994,37.0,888,1327 Pod's ESB,Extra Special / Strong Bitter (ESB),380,12.0
-304,0.055999999999999994,37.0,886,1327 Pod's ESB,Extra Special / Strong Bitter (ESB),380,12.0
-305,0.055999999999999994,37.0,612,1327 Pod's ESB,Extra Special / Strong Bitter (ESB),380,12.0
-306,0.046,35.0,611,834 Happy As Ale,American Pale Ale (APA),380,12.0
-307,0.059000000000000004,,1372,Yellow Collar,Mead,422,12.0
-308,0.059000000000000004,,1371,Green Collar,Mead,422,12.0
-309,0.08,80.0,1812,Quarter Mile Double IPA,American Double / Imperial IPA,304,12.0
-310,0.059000000000000004,60.0,1547,Full Nelson Pale Ale,American Pale Ale (APA),382,12.0
-311,0.065,30.0,1546,Steel Wheels ESB,Extra Special / Strong Bitter (ESB),382,12.0
-312,0.053,22.0,1545,Blue Mountain Classic Lager,Euro Pale Lager,382,12.0
-313,0.059000000000000004,60.0,119,Full Nelson Pale Ale (2010),American Pale Ale (APA),382,12.0
-314,0.049,16.0,1408,Kölsch 151,Kölsch,414,12.0
-315,,,2490,Professor Black,American Stout,77,12.0
-316,,,2489,Little Boss,American Pale Wheat Ale,77,12.0
-317,,,2488,Van Dayum!,American Amber / Red Ale,77,12.0
-318,,,2487,Spirit Animal,American Pale Ale (APA),77,12.0
-319,0.07,,939,Toxic Sludge,American Black Ale,489,16.0
-320,0.06,40.0,692,Blue Point White IPA,American White IPA,489,12.0
-321,0.044000000000000004,16.0,667,Blue Point Summer Ale,American Blonde Ale,489,12.0
-322,0.055,28.0,665,Toasted Lager,Vienna Lager,489,12.0
-323,0.06,,1607,Bohemian Export Lager,Dortmunder / Export Lager,364,12.0
-324,0.053,,1597,Altus Bohemes Altbier,Altbier,364,12.0
-325,0.04,,344,Cherny Bock,Schwarzbier,364,12.0
-326,0.05,,89,Czech Pilsner,Czech Pilsener,364,12.0
-327,0.05,,88,Viennese Lager,Vienna Lager,364,12.0
-328,0.065,,1569,Mad Manatee IPA,American IPA,378,12.0
-329,0.055,,1568,Killer Whale Cream Ale,Cream Ale,378,12.0
-330,0.06,,1188,Duke's Cold Nose Brown Ale,American Brown Ale,378,12.0
-331,0.042,30.0,1891,Longhop IPA,American IPA,281,16.0
-332,0.04,34.0,1890,Lucky Buck,Irish Dry Stout,281,16.0
-333,0.051,,577,Bomb Lager (New Recipe),Munich Helles Lager,525,12.0
-334,0.045,27.0,513,Bomb Lager (Old Recipe),Munich Helles Lager,525,12.0
-335,0.066,72.0,2422,Firestarter India Pale Ale,American IPA,107,12.0
-336,0.075,22.0,1727,Kilt Dropper Scotch Ale,Scotch Ale / Wee Heavy,107,16.0
-337,0.048,30.0,1614,Wood Splitter Pilsner,Czech Pilsener,107,16.0
-338,0.055999999999999994,26.0,1613,Gyptoberfest,Märzen / Oktoberfest,107,12.0
-339,0.07,94.0,1549,Farmer Wirtz India Pale Ale,English India Pale Ale (IPA),107,16.0
-340,0.047,,1548,Slow & Steady Golden Ale,American Blonde Ale,107,12.0
-341,0.068,,1517,Pink-I Raspberry IPA,American IPA,107,16.0
-342,0.047,,1500,Moe's Original Bar B Que 'Bama Brew Golden Ale,American Blonde Ale,107,12.0
-343,0.047,,1421,Live Local Golden Ale,American Blonde Ale,107,12.0
-344,0.048,38.0,1360,Screaming Eagle Special Ale ESB,Extra Special / Strong Bitter (ESB),107,12.0
-345,0.049,,1184,Dirtbag Dunkel,Munich Dunkel Lager,107,16.0
-346,0.053,45.0,1183,Kindler Pale Ale,American Pale Ale (APA),107,12.0
-347,0.064,,1023,Mistress Winter Wheat,Winter Warmer,107,12.0
-348,0.061,,998,Tent Pole Vanilla Porter,American Porter,107,16.0
-349,0.057999999999999996,,997,Awry Rye Pale Ale,American Pale Ale (APA),107,12.0
-350,0.057999999999999996,,996,Demshitz Brown Ale,American Brown Ale,107,12.0
-351,0.048,,931,Wood Splitter Pilsner (2012),Czech Pilsener,107,12.0
-352,0.048,,798,Brush Creek Blonde,American Blonde Ale,107,16.0
-353,0.066,72.0,633,Firestarter India Pale Ale,American IPA,107,16.0
-354,0.071,16.0,2062,Noche Dulce,American Porter,231,16.0
-355,0.045,8.0,1830,Porch Rocker,Radler,300,12.0
-356,0.065,45.0,1629,Rebel IPA,American IPA,300,16.0
-357,0.055,,1601,Cold Snap,Witbier,300,12.0
-358,0.055999999999999994,,1427,Samuel Adams Winter Lager,Bock,300,12.0
-359,0.049,30.0,1349,Boston Lager,Vienna Lager,300,16.0
-360,0.049,30.0,1310,Boston Lager,Vienna Lager,300,12.0
-361,0.053,15.0,1281,Samuel Adams Octoberfest,Märzen / Oktoberfest,300,12.0
-362,0.053,7.0,1144,Samuel Adams Summer Ale,American Pale Wheat Ale,300,12.0
-363,0.049,30.0,1143,Boston Lager,Vienna Lager,300,12.0
-364,0.049,35.0,1395,Hazed & Infused,American Pale Ale (APA),417,12.0
-365,0.057,35.0,808,Hoopla Pale Ale,American Pale Ale (APA),417,12.0
-366,0.049,35.0,81,Hazed & Infused (2010),American Pale Ale (APA),417,12.0
-367,0.062,80.0,2596,Heavy Lifting,American IPA,31,12.0
-368,0.065,,2300,1492,American Pale Ale (APA),167,12.0
-369,0.057999999999999996,,2299,Mango Ginger,American IPA,167,12.0
-370,0.047,,2298,Passenger,English Dark Mild Ale,167,12.0
-371,0.06,52.0,2107,Plum St. Porter,American Porter,219,12.0
-372,0.057,52.0,1573,Plum St. Porter,American Porter,219,12.0
-373,0.07,80.0,1289,Bozone HopZone IPA,American IPA,219,12.0
-374,0.06,25.0,1288,Bozone Hefe Weizen,Hefeweizen,219,12.0
-375,0.055,,470,Bozone Select Amber Ale,American Amber / Red Ale,219,12.0
-376,0.052000000000000005,40.0,2167,Evil Owl,American Amber / Red Ale,207,12.0
-377,0.05,,2204,Post Time Kölsch,Kölsch,195,16.0
-378,0.042,9.0,1522,Agave Wheat,American Pale Wheat Ale,391,12.0
-379,0.045,15.0,397,SummerBright Ale,American Pale Wheat Ale,391,12.0
-380,0.062,68.0,193,Lucky U IPA,American IPA,391,12.0
-381,0.054000000000000006,19.0,83,Avalanche Ale,American Amber / Red Ale,391,12.0
-382,0.05,,1802,"You're My Boy, Blue",Fruit / Vegetable Beer,308,12.0
-383,0.07200000000000001,60.0,1801,Last Stop IPA,American IPA,308,12.0
-384,0.05,21.0,1800,Rollin Dirty Red Ale,Irish Red Ale,308,12.0
-385,0.055,28.0,1799,Are Wheat There Yet?,American Pale Wheat Ale,308,12.0
-386,0.057999999999999996,,2619,Insert Hop Reference,American Pale Ale (APA),19,16.0
-387,0.053,,2468,Manitou Amber,American Amber / Red Ale,85,16.0
-388,0.067,,2637,Belfort,Saison / Farmhouse Ale,10,16.0
-389,0.06,,2636,Star Runner,Belgian Pale Ale,10,16.0
-390,0.098,,2598,Tart Side of the Barrel,American Double / Imperial Stout,10,16.0
-391,0.06,,2597,Linnaeus Mango IPA,American IPA,10,16.0
-392,0.07,,2548,Beasts A'Burnin',Rauchbier,10,16.0
-393,0.077,,2542,Verdun,Bière de Garde,10,16.0
-394,0.065,,2541,Barrel Aged Triomphe,Belgian IPA,10,16.0
-395,0.065,,2504,Cherry Doppelbock,Doppelbock,10,16.0
-396,0.065,,2500,Tropical Saison,Saison / Farmhouse Ale,10,16.0
-397,0.065,,2499,Beach Patrol,Witbier,10,16.0
-398,0.05,,2498,Nuit Serpent,Belgian IPA,10,16.0
-399,0.09,,2481,Paris,Saison / Farmhouse Ale,10,16.0
-400,0.055,,2476,The Grand Army,Belgian IPA,10,16.0
-401,0.059000000000000004,,2467,Acidulated Trip,Saison / Farmhouse Ale,10,16.0
-402,0.066,,2466,Root Stock,Rye Beer,10,16.0
-403,0.040999999999999995,,2465,Mind Games,Dunkelweizen,10,16.0
-404,0.08199999999999999,,2433,Sous Chef,Belgian Strong Pale Ale,10,16.0
-405,0.065,,2418,Dubbelicious,Dubbel,10,16.0
-406,0.062,,2416,Psychopomp,Belgian Dark Ale,10,16.0
-407,,,2382,Fat Paczki,Belgian Dark Ale,10,16.0
-408,,,2381,Earth-Like Planets,Belgian Pale Ale,10,16.0
-409,0.061,,2290,Ski Patrol,Witbier,10,16.0
-410,0.063,,2241,Viking Ice Hole,Oatmeal Stout,10,16.0
-411,0.055999999999999994,,2240,Rye Porter,American Porter,10,16.0
-412,0.099,,2137,Wizard Burial Ground,Quadrupel (Quad),10,16.0
-413,0.051,,2101,Smoky Wheat,Rauchbier,10,16.0
-414,0.062,,2092,BRIPA,Belgian IPA,10,16.0
-415,0.062,,2091,Mela,Belgian Dark Ale,10,16.0
-416,0.053,,2086,W.I.P.A Snappa,Belgian IPA,10,16.0
-417,0.063,,2023,Pepper in the Rye,Rye Beer,10,16.0
-418,0.064,,2006,Moe Lasses',American Stout,10,16.0
-419,0.07,,1997,Pumpkin Tart,Fruit / Vegetable Beer,10,16.0
-420,0.067,,1977,Undertaker,Belgian Dark Ale,10,16.0
-421,0.067,,1976,Undertaker (2014),Belgian Dark Ale,10,16.0
-422,0.05,,1974,Coq D'Or,Belgian Pale Ale,10,16.0
-423,0.06,,1973,North French,Bière de Garde,10,16.0
-424,0.065,,1959,Agent a Deux,Belgian Dark Ale,10,16.0
-425,0.045,,1958,Belgian Wit,Witbier,10,16.0
-426,0.063,,1949,Pothole Stout,American Stout,10,16.0
-427,0.09300000000000001,,1947,Tree Bucket,Belgian IPA,10,16.0
-428,0.073,,1785,Le Flaneur Ale,American Wild Ale,10,16.0
-429,0.055999999999999994,,1651,Maize & Blueberry,Fruit / Vegetable Beer,10,16.0
-430,0.09300000000000001,,1443,Trebuchet Double IPA,American Double / Imperial IPA,10,16.0
-431,0.065,,1352,Contemplation,Bière de Garde,10,16.0
-432,0.05,,1267,Black Rabbit,American Black Ale,10,16.0
-433,0.09,,1266,Zaison,Saison / Farmhouse Ale,10,16.0
-434,0.08199999999999999,,1178,Vivant Tripel,Tripel,10,16.0
-435,0.098,,1136,Tart Side of the Moon,Belgian Dark Ale,10,16.0
-436,0.06,,1044,Big Red Coq,American Amber / Red Ale,10,16.0
-437,0.099,,1033,Hubris Quadrupel Anniversary Ale,Quadrupel (Quad),10,16.0
-438,0.095,,1031,Plow Horse Belgian Style Imperial Stout,American Double / Imperial Stout,10,16.0
-439,0.092,,909,Escoffier Bretta Ale,American Wild Ale,10,16.0
-440,0.065,,873,Contemplation (2012),Bière de Garde,10,16.0
-441,0.099,,860,Vivant Belgian Style Imperial Stout (2012),Russian Imperial Stout,10,16.0
-442,0.062,,677,Big Red Coq (2012),American Amber / Red Ale,10,16.0
-443,0.09,,671,Zaison (2012),Saison / Farmhouse Ale,10,16.0
-444,0.092,,670,Vivant Tripel (2012),Tripel,10,16.0
-445,0.09699999999999999,,669,Trebuchet Double IPA (2012),Belgian IPA,10,16.0
-446,0.085,,627,Kludde,Belgian Strong Dark Ale,10,16.0
-447,0.055,,387,Farm Hand,Saison / Farmhouse Ale,10,16.0
-448,0.06,,385,Solitude,Belgian Pale Ale,10,16.0
-449,0.065,,384,Triomphe,Belgian IPA,10,16.0
-450,,,1096,Tampa Pale Ale,American Pale Ale (APA),467,12.0
-451,,,1095,Orange Grove Wheat Ale,American Pale Wheat Ale,467,12.0
-452,0.061,,2456,Broad Brook Ale,American Amber / Red Ale,89,16.0
-453,0.05,15.0,921,Northern Lights Amber Ale,American Amber / Red Ale,493,12.0
-454,0.052000000000000005,17.0,920,Polar Pale Ale,American Pale Ale (APA),493,12.0
-455,0.048,,919,Chugach Session Ale,Cream Ale,493,12.0
-456,0.061,64.0,648,Fairweather IPA,American IPA,493,12.0
-457,0.068,47.0,1279,East India Pale Ale,English India Pale Ale (IPA),437,16.0
-458,0.045,,756,Brooklyn Summer Ale,English Pale Mild Ale,437,12.0
-459,0.068,47.0,566,East India Pale Ale,English India Pale Ale (IPA),437,12.0
-460,0.045,,328,Brooklyn Summer Ale (2011),English Pale Mild Ale,437,12.0
-461,0.052000000000000005,,66,Brooklyn Lager (16 oz.),American Amber / Red Lager,437,16.0
-462,0.052000000000000005,,65,Brooklyn Lager (12 oz.),American Amber / Red Lager,437,12.0
-463,0.08,,538,Tour de Nez Belgian IPA (Current),Belgian IPA,530,16.0
-464,,,504,Roler Bock (Current),Maibock / Helles Bock,530,16.0
-465,0.073,85.0,383,Black Adder IBA (Current),American Black Ale,530,16.0
-466,0.099,,29,Very Noddy Lager (Current),Schwarzbier,530,16.0
-467,0.062,42.0,28,Tule Duck Red Ale (Current),American Amber / Red Ale,530,16.0
-468,0.057999999999999996,35.0,27,Original Orange Blossom Ale (Current),Herbed / Spiced Beer,530,16.0
-469,0.052000000000000005,40.0,26,Black Noddy Lager (Current),Schwarzbier,530,16.0
-470,0.053,,1627,Cleveland Beer Week 2013,Munich Helles Lager,357,16.0
-471,0.045,,2552,Painted Turtle,American Pale Ale (APA),56,12.0
-472,0.06,40.0,2125,1836,American Blonde Ale,214,12.0
-473,0.06,20.0,2124,Summer's Wit,Witbier,214,12.0
-474,0.09,118.0,2123,More Cowbell,American Double / Imperial IPA,214,16.0
-475,0.065,,2608,Wrath of Pele,American Brown Ale,24,16.0
-476,0.068,,2607,Black Beer'd,American Black Ale,24,16.0
-477,0.078,,2606,Mr. Tea,Fruit / Vegetable Beer,24,24.0
-478,0.055,40.0,2478,Pale Alement,American Pale Ale (APA),24,12.0
-479,0.099,115.0,2471,Hopkick Dropkick,American Double / Imperial IPA,24,12.0
-480,0.06,,2470,Kreamed Corn,Cream Ale,24,12.0
-481,0.065,,2464,Coconoats,American Pale Wheat Ale,24,16.0
-482,0.068,16.0,2160,Joey Wheat,American Pale Wheat Ale,24,16.0
-483,0.07200000000000001,86.0,2158,3:33 Black IPA,American IPA,24,16.0
-484,0.068,,2072,MCA,American IPA,24,16.0
-485,0.055,40.0,2054,Pale Alement,American Pale Ale (APA),24,16.0
-486,0.05,14.0,2196,Couch Select Lager,American Pale Lager,197,12.0
-487,0.055999999999999994,36.0,668,Mucho Aloha Hawaiian Pale Ale,American Pale Ale (APA),517,12.0
-488,0.049,,52,Heinnieweisse Weissebier,Hefeweizen,556,12.0
-489,0.068,,51,Snapperhead IPA,American IPA,556,12.0
-490,0.049,,50,Moo Thunder Stout,Milk / Sweet Stout,556,12.0
-491,0.043,,49,Porkslap Pale Ale,American Pale Ale (APA),556,12.0
-492,0.09300000000000001,,2657,Blackbeard,American Double / Imperial Stout,5,12.0
-493,0.062,,2656,Rye Knot,American Brown Ale,5,12.0
-494,0.06,,2655,Dead Arm,American Pale Ale (APA),5,12.0
-495,0.048,,2654,32°/50° Kölsch ,Kölsch,5,16.0
-496,0.077,,2653,HopArt,American IPA,5,16.0
-497,0.09699999999999999,,2652,Boy King,American Double / Imperial IPA,5,16.0
-498,0.052000000000000005,,2252,Gran Sport,American Porter,182,16.0
-499,0.053,25.0,2214,Horny Toad Cerveza,American Blonde Ale,182,16.0
-500,0.063,35.0,2213,Native Amber,American Amber / Red Ale,182,16.0
-501,0.068,100.0,1442,F5 IPA,American IPA,182,16.0
-502,0.063,35.0,170,Native Amber (2013),American Amber / Red Ale,182,16.0
-503,0.053,25.0,169,Horny Toad Cerveza (2013),American Blonde Ale,182,16.0
-504,0.068,100.0,2315,Hopportunity Knocks IPA,American IPA,155,12.0
-505,0.06,,1808,Pilot Rock Porter,American Porter,155,12.0
-506,0.055999999999999994,55.0,1419,Caldera Pale Ale,American Pale Ale (APA),155,12.0
-507,0.039,16.0,878,Lawnmower Lager,American Adjunct Lager,155,12.0
-508,0.054000000000000006,24.0,794,Ashland Amber Ale (2009),American Amber / Red Ale,155,12.0
-509,0.061,94.0,793,Caldera IPA (2009),American IPA,155,12.0
-510,0.061,94.0,792,Caldera IPA (2007),American IPA,155,12.0
-511,0.055999999999999994,55.0,791,Caldera Pale Ale (2010),American Pale Ale (APA),155,12.0
-512,0.055999999999999994,55.0,790,Caldera Pale Ale (2009),American Pale Ale (APA),155,12.0
-513,0.055999999999999994,55.0,789,Caldera Pale Ale (2005),American Pale Ale (APA),155,12.0
-514,0.055999999999999994,55.0,788,Caldera Pale Ale (2007),American Pale Ale (APA),155,12.0
-515,0.055999999999999994,55.0,38,Caldera Pale Ale (2011),American Pale Ale (APA),155,12.0
-516,0.054000000000000006,24.0,37,Ashland Amber Ale,American Amber / Red Ale,155,12.0
-517,0.061,94.0,36,Caldera IPA,American IPA,155,12.0
-518,0.05,,2257,Remain in Light,American Pilsner,178,12.0
-519,0.065,,2256,Flower Child (2014),American IPA,178,12.0
-520,,,870,THP White (2006),Witbier,497,12.0
-521,,,869,THP Amber (2006),American Amber / Red Ale,497,12.0
-522,,,868,THP Light (2006),American Blonde Ale,497,12.0
-523,,,867,THP Dark (2006),English Dark Mild Ale,497,12.0
-524,0.099,43.0,2068,Imperial Pumpkin Stout,Pumpkin Ale,230,16.0
-525,0.09,130.0,2067,Dead-Eye DIPA,American Double / Imperial IPA,230,16.0
-526,0.055,64.0,2066,Fisherman's IPA,American IPA,230,12.0
-527,0.054000000000000006,35.0,2065,Fisherman's Pils,German Pilsener,230,12.0
-528,0.055,30.0,2064,Fisherman's Brew,American Amber / Red Ale,230,12.0
-529,0.055,35.0,1928,Cape Cod Red,American Amber / Red Ale,267,16.0
-530,0.049,10.0,1927,Beach Blonde,American Blonde Ale,267,16.0
-531,0.065,80.0,2227,Dark Voyage Black IPA (2013),American Black Ale,192,12.0
-532,0.052000000000000005,28.0,2226,Wisconsin Amber,Vienna Lager,192,12.0
-533,0.046,18.0,2225,Lake House,Munich Helles Lager,192,12.0
-534,0.055999999999999994,55.0,1954,Ghost Ship White IPA,American IPA,192,12.0
-535,0.046,18.0,1910,Lake House,Munich Helles Lager,192,16.0
-536,0.062,70.0,1177,Mutiny IPA,American IPA,192,12.0
-537,0.052000000000000005,,840,Wisconsin Amber (1998),Vienna Lager,192,12.0
-538,0.042,,180,Island Wheat,American Pale Wheat Ale,192,12.0
-539,0.052000000000000005,,63,Wisconsin Amber (2013),Vienna Lager,192,12.0
-540,0.05,,62,U.S. Pale Ale,American Pale Ale (APA),192,12.0
-541,,,61,Supper Club Lager,American Pale Lager,192,12.0
-542,0.04,,784,Carolina Lighthouse (2007),American Blonde Ale,504,12.0
-543,0.05,,783,Carolina Blonde (2006),American Blonde Ale,504,12.0
-544,0.035,,782,Carolina Blonde Light (2005),American Blonde Ale,504,12.0
-545,0.059000000000000004,22.0,2255,Santa's Secret,Winter Warmer,179,16.0
-546,0.057,,530,Flagship IPA,English India Pale Ale (IPA),179,12.0
-547,0.051,,427,Sky Blue Golden Ale,Kölsch,179,12.0
-548,0.099,100.0,2094,Epitome,American Black Ale,222,16.0
-549,0.039,9.0,1941,Monkey Chased the Weasel,Berliner Weissbier,222,16.0
-550,0.078,80.0,1940,077XX,American Double / Imperial IPA,222,16.0
-551,0.042,35.0,1439,Boat Beer,American IPA,222,12.0
-552,0.069,,1465,Granny Smith Hard Apple Cider,Cider,404,16.0
-553,0.069,,1464,Dry Hard Apple Cider,Cider,404,16.0
-554,0.055999999999999994,,1744,Farmer Ted's Cream Ale,Cream Ale,331,12.0
-555,0.052000000000000005,,1743,Firewater India Pale Ale,American IPA,331,12.0
-556,0.047,,1742,White Zombie Ale,Witbier,331,12.0
-557,0.07,,1719,King Winterbolt Winter Ale,Winter Warmer,331,12.0
-558,0.047,,638,White Zombie Ale,Witbier,331,12.0
-559,0.052000000000000005,,507,Firewater India Pale Ale,American IPA,331,12.0
-560,0.055999999999999994,,480,Farmer Ted's Farmhouse Cream Ale,Cream Ale,331,12.0
-561,0.048,16.0,1882,Whitecap Wit,Witbier,285,16.0
-562,0.078,16.0,1881,Seiche Scottish Ale,Scottish Ale,285,16.0
-563,0.057999999999999996,,2446,Peanut Butter Jelly Time,American Brown Ale,96,12.0
-564,0.054000000000000006,,2106,King Coconut,American Porter,96,12.0
-565,0.085,90.0,2600,Gone A-Rye,American Double / Imperial IPA,29,16.0
-567,0.068,70.0,2052,Dankosaurus,American IPA,29,16.0
-568,0.051,35.0,1584,Scruffy's Smoked Alt,Smoked Beer,29,16.0
-569,0.051,36.0,1182,Elliott's Phoned Home Pale Ale,American Pale Ale (APA),29,16.0
-570,0.05,18.0,1050,The Lawn Ranger,Cream Ale,29,16.0
-571,0.05,,1219,All American Blonde Ale,American Blonde Ale,452,12.0
-572,0.05,,1218,All American Red Ale,American Amber / Red Ale,452,12.0
-573,0.05,40.0,2377,Main St. Virginia Ale,Altbier,122,12.0
-574,0.045,24.0,1839,Chin Music Amber Lager,American Amber / Red Lager,122,12.0
-575,0.05,40.0,1248,Main St. Virginia Ale,Altbier,122,12.0
-576,0.052000000000000005,42.0,1247,Ray Ray’s Pale Ale,American Pale Ale (APA),122,12.0
-577,0.051,15.0,1649,Chai Ale,Herbed / Spiced Beer,350,16.0
-578,0.07200000000000001,85.0,1648,Lucky Day IPA,American IPA,350,16.0
-579,0.095,99.0,1647,Terrace Hill Double IPA,American Double / Imperial IPA,350,16.0
-580,0.075,77.0,1646,Catch 23,American Black Ale,350,16.0
-581,0.07,,2057,Stickin' In My Rye,Rye Beer,236,24.0
-582,0.06,45.0,2056,Black Me Stout,American Stout,236,12.0
-583,0.05,22.0,2055,Killer Kolsch,Kölsch,236,12.0
-584,0.07,65.0,1933,Missile IPA,American IPA,236,12.0
-585,0.045,,2019,Enlighten,Kölsch,250,16.0
-586,0.065,8.0,2018,Ale Cider,Fruit / Vegetable Beer,250,16.0
-587,0.055,30.0,2017,Pail Ale,American Pale Ale (APA),250,16.0
-588,0.045,,2016,Englishman,English Brown Ale,250,16.0
-589,0.08,69.0,2080,8 Barrel,American Strong Ale,226,16.0
-590,0.055,40.0,2079,Oktoberfest,Märzen / Oktoberfest,226,16.0
-591,0.057,58.0,2380,IPA #11,American IPA,121,16.0
-592,0.057,10.0,2379,Blood Orange Honey,Fruit / Vegetable Beer,121,16.0
-593,0.052000000000000005,,2354,Lighthouse Amber,Altbier,121,16.0
-594,0.08900000000000001,126.0,2440,Bay of Bengal Double IPA (2014),American Double / Imperial IPA,99,12.0
-595,0.049,29.0,567,Churchkey Pilsner Style Beer,American Pilsner,526,12.0
-596,0.05,,1342,First Press,Cider,425,12.0
-597,0.05,,1341,Magic Apple,Cider,425,12.0
-598,0.055,25.0,2349,Cubano Espresso,Bock,141,12.0
-599,0.062,65.0,2014,Operation Homefront,American IPA,141,12.0
-600,0.08199999999999999,65.0,2013,Wandering Pelican,American Black Ale,141,12.0
-601,0.055,,2012,Sugar Plum,American Brown Ale,141,12.0
-602,0.055,,2011,Oktoberfest,Märzen / Oktoberfest,141,12.0
-603,0.06,,2010,Puppy's Breath Porter,American Porter,141,12.0
-604,0.045,,2009,Happening Now,American IPA,141,12.0
-605,0.07,60.0,1726,Hopped on the High Seas (Hop #529),American IPA,141,12.0
-606,0.07,60.0,1725,Hopped on the High Seas (Calypso),American IPA,141,12.0
-607,0.063,,1695,Wiregrass Post-Prohibition Ale,American Pale Ale (APA),141,12.0
-608,0.07,60.0,1694,Dry-Hopped On The High Seas Caribbean-Style IPA,American IPA,141,12.0
-609,0.07,60.0,1693,Hopped on the High Seas (Citra),American IPA,141,12.0
-610,0.07,60.0,1692,Hopped on the High Seas (Ahtanum),American IPA,141,12.0
-611,0.055,,1369,Gwar Beer,American Pale Ale (APA),141,12.0
-612,0.052000000000000005,,1243,Tropical Heatwave,American Pale Wheat Ale,141,16.0
-613,0.075,70.0,1142,Humidor Series India Pale Ale,American IPA,141,12.0
-614,0.075,70.0,1141,Jai Alai IPA Aged on White Oak,American IPA,141,12.0
-615,0.08,65.0,1140,José Martí American Porter,American Porter,141,12.0
-616,0.05,,1139,Invasion Pale Ale,American Pale Ale (APA),141,12.0
-617,0.055,25.0,1138,Maduro Brown Ale,English Brown Ale,141,12.0
-618,0.055,25.0,571,Maduro Brown Ale,American Brown Ale,141,12.0
-619,0.05,,570,Hotter Than Helles Lager,Munich Helles Lager,141,12.0
-620,0.07200000000000001,75.0,569,Tocobaga Red Ale,American Amber / Red Ale,141,12.0
-621,0.075,70.0,546,Jai Alai IPA,American IPA,141,12.0
-622,0.05,18.0,545,Florida Cracker Belgian Wit,Witbier,141,12.0
-623,0.048,,2338,Shark Tracker Light lager,Light Lager,145,12.0
-624,0.06,,1365,Pumple Drumkin,Pumpkin Ale,145,12.0
-625,0.045,,1094,Grey Lady,Witbier,145,12.0
-626,0.062,,657,Summer of Lager,Munich Helles Lager,145,12.0
-627,0.065,,656,Indie Pale Ale,American IPA,145,12.0
-628,0.038,,359,Sankaty Light Lager,Light Lager,145,12.0
-629,0.055999999999999994,,56,Whale's Tale Pale Ale,English Pale Ale,145,12.0
-630,0.067,60.0,1772,Jacaranada Rye IPA,American IPA,320,16.0
-631,0.06,75.0,1393,Cascadian Dark Ale,American Black Ale,418,12.0
-632,0.044000000000000004,13.0,893,Wheat the People,American Pale Wheat Ale,418,16.0
-633,0.047,17.0,1407,Tybee Island Blonde,American Blonde Ale,415,12.0
-634,0.062,55.0,1406,Savannah Brown Ale,American Brown Ale,415,12.0
-635,0.046,11.0,2438,Rhode Island Blueberry,Kölsch,101,12.0
-636,0.065,75.0,2437,Newport Storm IPA,American IPA,101,12.0
-637,0.052000000000000005,24.0,751,Hurricane Amber Ale (2004),American Amber / Red Ale,101,12.0
-638,0.052000000000000005,24.0,120,Hurricane Amber Ale,American Amber / Red Ale,101,12.0
-639,0.057999999999999996,,2061,Big Blue Van,Fruit / Vegetable Beer,232,16.0
-640,0.068,75.0,970,Des Moines IPA,American IPA,482,16.0
-641,0.048,22.0,969,Capital Gold Golden Lager,German Pilsener,482,16.0
-642,0.055999999999999994,21.0,968,Farmer John's Multi-Grain Ale,American Blonde Ale,482,16.0
-643,0.05,,2351,Behemoth,American Pilsner,139,12.0
-644,0.052000000000000005,,1650,Arkansas Red,American Amber / Red Ale,139,12.0
-645,0.057,,1337,Core Oatmeal Stout,Oatmeal Stout,139,12.0
-646,0.061,,1336,Core ESB,Extra Special / Strong Bitter (ESB),139,12.0
-647,0.038,,737,Chester's Beer (2005),American Pale Lager,512,12.0
-648,0.05,,129,Heiner Brau Kölsch,Kölsch,553,12.0
-649,0.048,,716,Trigger Blonde Ale,American Blonde Ale,515,16.0
-650,0.075,29.0,659,Crabtree Oatmeal Stout,Oatmeal Stout,515,16.0
-651,0.077,71.0,556,Eclipse Black IPA,American Black Ale,515,16.0
-652,0.06,46.0,2538,Neomexicanus Native,American Pale Ale (APA),63,12.0
-653,0.075,25.0,2355,Old Soul,Belgian Strong Pale Ale,63,12.0
-654,0.059000000000000004,,1689,Snowcat Coffee Stout,American Stout,63,12.0
-655,,,1163,WinterWonderGrass Festival Ale,American Amber / Red Ale,63,12.0
-656,,,940,Boohai Red Ale,American Amber / Red Ale,63,12.0
-657,0.052000000000000005,15.0,685,Lava Lake Wit,Witbier,63,12.0
-658,0.06,,613,Mountain Livin' Pale Ale,American Pale Ale (APA),63,12.0
-659,0.052000000000000005,25.0,356,Crazy Mountain Amber Ale,American Amber / Red Ale,63,12.0
-660,0.065,65.0,2029,Tropicalia,American IPA,247,12.0
-661,0.045,,2028,Athena,Berliner Weissbier,247,12.0
-662,0.049,25.0,2293,Aviator Raspberry Blonde,American Blonde Ale,169,12.0
-663,0.055,,1105,3 Picket Porter,American Porter,169,12.0
-664,0.055999999999999994,,1104,Rusty Nail Pale Ale,American Pale Ale (APA),169,12.0
-665,0.065,,2145,Red Water Irish Style Red,American Amber / Red Ale,212,12.0
-666,0.066,,1804,Mjöllnir,Herbed / Spiced Beer,212,12.0
-667,0.055,,1602,Bear Butte Nut Brown Ale,American Brown Ale,212,12.0
-668,0.045,,1301,Easy Livin' Summer Ale,American Blonde Ale,212,12.0
-669,0.055,,542,Canyon Cream Ale,Cream Ale,212,12.0
-670,0.069,,272,Pile O'Dirt Porter,American Porter,212,12.0
-671,0.06,,271,11th Hour IPA,American IPA,212,12.0
-672,0.06,31.0,1057,South Ridge Amber Ale,American Amber / Red Ale,472,16.0
-673,0.052000000000000005,23.0,681,Summertime Ale,Kölsch,472,16.0
-674,0.049,,1789,Lost River Blonde Ale,American Blonde Ale,315,16.0
-675,0.054000000000000006,,1788,Monon Wheat,Witbier,315,16.0
-676,0.08,,1787,Floyd's Folly,Scottish Ale,315,16.0
-677,0.063,,1786,Half Court IPA,American IPA,315,16.0
-678,0.045,,1763,Geary's Pale Ale,English Pale Ale,323,12.0
-679,0.06,,1311,Geary's Summer Ale,Kölsch,323,12.0
-680,0.08,,2078,Stone of Arbroath,Scotch Ale / Wee Heavy,227,12.0
-681,0.05,15.0,1809,The Tradition,American Blonde Ale,227,12.0
-682,0.053,11.0,1263,El Hefe Speaks,Hefeweizen,227,12.0
-683,0.055,,1092,Penn Quarter Porter,American Porter,227,12.0
-684,0.092,115.0,851,On the Wings of Armageddon,American Double / Imperial IPA,227,12.0
-685,0.065,80.0,186,The Corruption,American IPA,227,12.0
-686,0.07,,185,The Citizen,Belgian Pale Ale,227,12.0
-687,0.06,,184,The Public,American Pale Ale (APA),227,12.0
-688,0.065,,1224,Dank IPA,American IPA,451,16.0
-689,0.065,,964,Dank IPA (2012),American IPA,451,16.0
-690,0.07200000000000001,,1623,Lift Off IPA,American IPA,358,16.0
-691,0.055,,110,BrewFarm Select Golden Lager,American Pale Lager,554,12.0
-692,0.05,,1735,Sprocket Blonde Ale (2006),American Blonde Ale,333,12.0
-693,0.05,,1734,Sprocket Pale Ale (2006),American Pale Ale (APA),333,12.0
-694,0.063,37.0,1746,Dead Armadillo Amber Ale,American Amber / Red Ale,330,12.0
-695,0.06,,2371,Neato Bandito,Euro Pale Lager,127,12.0
-696,0.075,33.0,2251,Oak Cliff Coffee Ale,American Brown Ale,127,12.0
-697,0.085,100.0,2166,Dream Crusher Double IPA,American Double / Imperial IPA,127,12.0
-698,0.06,,1827,Deep Ellum Pale Ale,American Pale Ale (APA),127,12.0
-699,0.07,,1203,Double Brown Stout,Baltic Porter,127,12.0
-700,0.048,25.0,1202,Farmhouse Wit,Saison / Farmhouse Ale,127,16.0
-701,0.046,,1161,Rye Pils Session Lager,German Pilsener,127,12.0
-702,0.052000000000000005,23.0,946,Dallas Blonde,American Blonde Ale,127,12.0
-703,0.07,70.0,943,Deep Ellum IPA,American IPA,127,12.0
-704,0.045,44.0,1886,Thrasher Session India Pale Ale,American IPA,283,12.0
-705,0.05,16.0,1885,Gutch English Style Mild Ale,English Pale Mild Ale,283,12.0
-706,0.059000000000000004,55.0,1213,Chuli Stout,Irish Dry Stout,453,12.0
-707,0.055999999999999994,46.0,1159,Mother Ale,American Blonde Ale,453,12.0
-708,0.065,71.0,947,Twister Creek India Pale Ale,American IPA,453,12.0
-709,0.057999999999999996,46.0,929,Single Engine Red,Irish Red Ale,453,12.0
-710,0.07,,1944,Incredible Pedal IPA,American IPA,263,12.0
-711,0.05,,1943,Graham Cracker Porter,American Porter,263,12.0
-712,0.05,40.0,1210,Mirror Pond Pale Ale,American Pale Ale (APA),454,12.0
-713,0.052000000000000005,16.0,2550,Weissenheimer,Hefeweizen,57,12.0
-714,0.049,22.0,2505,Abbey's Single (2015- ),Abbey Single Ale,57,12.0
-715,0.063,76.0,2025,Vertex IPA,American IPA,57,12.0
-716,0.05,12.0,2021,Here Gose Nothin',Gose,57,12.0
-717,0.05,,2015,Strawberry Blonde,Fruit / Vegetable Beer,57,12.0
-718,0.096,85.0,1888,Hoperation Overload,American Double / Imperial IPA,57,12.0
-719,0.049,22.0,1887,Abbey's Single Ale (Current),Abbey Single Ale,57,12.0
-720,0.044000000000000004,45.0,2051,Bravo Four Point,American Pale Ale (APA),237,12.0
-721,0.052000000000000005,26.0,1201,Striped Bass Pale Ale,American Pale Ale (APA),237,12.0
-722,0.054000000000000006,27.0,924,Deadicated Amber,American Amber / Red Ale,491,16.0
-723,,,731,Kaleidoscope Collaboration 2012,American Black Ale,491,16.0
-724,0.071,85.0,730,California Sunshine Rye IPA,American IPA,491,16.0
-725,0.07400000000000001,12.0,647,Full Boar Scotch Ale,Scotch Ale / Wee Heavy,491,16.0
-726,0.045,,1773,12 Man Pale Ale,American Pale Ale (APA),319,12.0
-727,0.065,72.0,1795,Filthy Hoppin' IPA,American IPA,311,16.0
-728,,,944,Dock Street Amber Beer (1992),American Amber / Red Ale,488,12.0
-729,,,524,Dolores River Hefeweizen,Hefeweizen,531,16.0
-730,,,450,Dolores River ESB,Extra Special / Strong Bitter (ESB),531,16.0
-731,,,449,Snaggletooth Double Pale Ale,American Double / Imperial IPA,531,16.0
-732,,,448,Dolores River Pale Ale,American Pale Ale (APA),531,16.0
-733,,,447,Dolores River Dry Stout,Irish Dry Stout,531,16.0
-734,,,446,Dolores River Mild,English Dark Mild Ale,531,16.0
-735,0.049,,1246,Cranberry Blend,Cider,446,12.0
-736,0.051,,977,Orignal Blend,Cider,446,12.0
-737,0.066,100.0,881,Hop Abomination,American IPA,496,12.0
-738,0.051,17.0,880,Apricot Blonde,Fruit / Vegetable Beer,496,12.0
-739,0.043,12.0,872,Dry Dock Hefeweizen,Hefeweizen,496,12.0
-740,0.057999999999999996,49.0,871,Dry Dock Amber Ale,American Amber / Red Ale,496,12.0
-741,0.061,64.0,1685,Category 3 IPA,American IPA,340,12.0
-742,0.045,18.0,457,Dundee Summer Wheat Beer,American Pale Wheat Ale,538,12.0
-743,0.05,,1590,Pumpkin Patch Ale,Pumpkin Ale,369,16.0
-744,0.078,74.0,1382,Crank Yanker IPA,American IPA,369,16.0
-745,0.06,,1110,River Runners Pale Ale,American Pale Ale (APA),369,16.0
-746,0.05,,1014,Pumpkin Patch Ale (2012),Pumpkin Ale,369,16.0
-747,0.055,,911,Mountain Fairy Raspberry Wheat,Fruit / Vegetable Beer,369,16.0
-748,0.045,,680,Boater Beer,German Pilsener,369,16.0
-749,0.078,74.0,395,Crank Yanker IPA (2011),American IPA,369,16.0
-750,0.057,,1642,Bleeding Buckeye Red Ale,Extra Special / Strong Bitter (ESB),352,16.0
-751,0.049,25.0,673,Dottie Seattle Lager,American Amber / Red Lager,516,16.0
-752,0.07,,1107,Nut Sack Imperial Brown Ale,American Brown Ale,465,12.0
-753,0.05,,1039,Underachiever,American Adjunct Lager,473,16.0
-754,0.052000000000000005,,2477,Lil' Brainless Raspberries,Fruit / Vegetable Beer,81,12.0
-755,0.052000000000000005,,2008,Element 29,American Pale Ale (APA),81,12.0
-756,0.05,,2004,Hop Syndrome,American Pale Lager,81,12.0
-757,0.062,,2003,Escape to Colorado,American IPA,81,12.0
-758,0.043,60.0,2292,Little Sister India Style Session Ale,American IPA,170,12.0
-759,0.062,80.0,1504,Country Boy IPA,American IPA,170,12.0
-760,0.049,23.0,2604,Blonde Czich,American Blonde Ale,26,16.0
-761,0.07,61.0,2432,White Reaper,Belgian IPA,26,16.0
-762,0.051,,2431,Bobblehead,American Pale Wheat Ale,26,16.0
-763,0.052000000000000005,,2430,Lucky Dog,American Pale Ale (APA),26,16.0
-764,0.048,,2429,Voodoo,American Porter,26,16.0
-765,0.054000000000000006,48.0,1967,General George Patton Pilsner,Czech Pilsener,26,16.0
-766,0.04,,2283,Nomader Weiss,Berliner Weissbier,173,12.0
-767,0.085,,2248,Molotov Lite,American Double / Imperial IPA,173,16.0
-768,0.055,,1287,Hipster Ale (Two Roads Brewing),American Pale Ale (APA),173,12.0
-769,0.027000000000000003,,1286,Bikini Beer,American IPA,173,12.0
-770,0.055,,640,Hipster Ale (Westbrook Brewing),American Pale Ale (APA),173,12.0
-771,0.05,32.0,1722,Iron Horse Pale Ale,American Pale Ale (APA),335,12.0
-772,0.045,19.0,1435,Stone's Throw IPA,Scottish Ale,335,12.0
-773,0.067,70.0,1434,Wood Chipper India Pale Ale,American IPA,335,12.0
-774,0.063,55.0,2089,Trail Head,American Pale Ale (APA),224,12.0
-775,0.07,80.0,2088,Hop Stalker Fresh Hop IPA,American IPA,224,16.0
-776,0.07,58.0,1455,Sudice American Stout,American Stout,405,16.0
-777,0.05,20.0,1454,Parcae Belgian Style Pale Ale,Belgian Pale Ale,405,16.0
-778,0.05,20.0,1453,Norns Roggenbier,Roggenbier,405,16.0
-779,0.05,20.0,1452,Laimas Kölsch Style Ale,Kölsch,405,16.0
-780,0.07,70.0,1451,Moirai India Pale Ale,American IPA,405,16.0
-781,0.075,53.0,2191,Loki Red Ale,American Amber / Red Ale,201,16.0
-782,0.046,,1731,Peaches & Cream,Fruit / Vegetable Beer,201,16.0
-783,0.051,,1022,Quaff India Style Session Ale,American IPA,201,16.0
-784,0.075,53.0,895,Loki Red Ale (2013),American Amber / Red Ale,201,16.0
-785,0.069,,682,Mjolnir Imperial IPA,American Double / Imperial IPA,201,16.0
-786,0.05,,112,Fearless Scottish Ale,Scottish Ale,201,16.0
-787,0.081,,2289,Mastermind,American Double / Imperial IPA,172,12.0
-788,0.08199999999999999,,2027,Hyzer Flip,American Double / Imperial IPA,172,16.0
-789,0.08199999999999999,80.0,1929,Second Fiddle,American Double / Imperial IPA,172,16.0
-790,0.055,30.0,1858,Hodad Porter,American Porter,172,16.0
-791,0.045,,2591,Weiss Weiss Baby,Kristalweizen,36,12.0
-792,0.055,45.0,2590,Czech Yo Self,Czech Pilsener,36,12.0
-793,0.048,20.0,1968,FMB 101,Kölsch,36,12.0
-794,0.09,,1981,Hardcore Chimera,American Double / Imperial IPA,256,16.0
-795,0.08,80.0,1664,Sobek & Set,American Black Ale,256,16.0
-796,0.086,,1663,Nuclear Winter,Belgian Strong Dark Ale,256,16.0
-797,0.05,22.0,1662,Wet Hot American Wheat Ale,American Pale Wheat Ale,256,16.0
-798,0.053,,941,Secret Stache Stout,American Stout,256,16.0
-799,0.08,72.0,935,Fascist Pig Ale,American Amber / Red Ale,256,16.0
-800,0.055,,809,Cut Throat Pale Ale,American Pale Ale (APA),256,16.0
-801,0.075,,481,Threadless IPA,American IPA,256,16.0
-802,0.055,,351,Cut Throat Pale Ale (2011),American Pale Ale (APA),256,16.0
-803,0.047,,350,Golden Wing Blonde Ale,American Blonde Ale,256,16.0
-804,0.045,47.0,2569,Easy Jack,American IPA,48,12.0
-805,0.075,75.0,2463,Union Jack,American IPA,48,12.0
-806,0.053,,2462,Pivo Pils,German Pilsener,48,12.0
-807,0.047,,1957,805 Blonde Ale,American Blonde Ale,48,12.0
-808,0.047,20.0,1733,805,American Blonde Ale,48,12.0
-809,0.065,,2624,Deflator,Doppelbock,16,16.0
-810,0.05,27.0,2284,Hinchtown Hammer Down,American Blonde Ale,16,16.0
-811,0.06,104.0,1610,Half Cycle IPA,American IPA,16,16.0
-812,,,520,Inclined Plane Ale,American IPA,532,12.0
-813,0.055,,2554,Moped Traveler,American Pale Ale (APA),54,16.0
-814,0.071,60.0,608,Snake Dog IPA,American IPA,521,12.0
-815,0.047,28.0,607,Underdog Atlantic Lager,American Pale Lager,521,12.0
-816,0.04,,2567,Flying Mouse 8,American Porter,50,12.0
-817,0.07,70.0,2566,Flying Mouse 4,American IPA,50,12.0
-818,0.078,,1899,La Ferme Urbaine Farmhouse Ale,Saison / Farmhouse Ale,279,12.0
-819,0.06,,983,Backyahd IPA,American IPA,279,12.0
-820,0.065,,982,Raincloud Robust Porter,American Porter,279,12.0
-821,0.045,,981,Barstool American Golden Ale,American Blonde Ale,279,12.0
-822,0.05,18.0,2111,What the Butler Saw,Witbier,217,12.0
-823,0.069,65.0,2110,1916 Shore Shiver,American IPA,217,12.0
-824,0.052000000000000005,,2172,Quick WIT,Belgian Pale Ale,206,12.0
-825,0.062,,2171,The Optimist,American IPA,206,12.0
-826,0.045,,1911,Suicide Squeeze IPA,American IPA,206,16.0
-827,0.065,,1803,Java the Hop,American IPA,206,16.0
-828,0.062,,1566,Next Adventure Black IPA,American Black Ale,206,16.0
-829,0.067,,1515,3-Way IPA (2013),American IPA,206,16.0
-830,0.057999999999999996,,1214,Tender Loving Empire NWPA,American Pale Ale (APA),206,16.0
-831,0.052000000000000005,,674,Quick Wit Belgianesque Ale,Witbier,206,16.0
-832,0.055,,562,Sunrise Oatmeal Pale Ale,American Pale Ale (APA),206,16.0
-833,0.08800000000000001,,552,Cavatica Stout,American Double / Imperial Stout,206,16.0
-834,0.051,,319,1811 Lager,American Amber / Red Lager,206,16.0
-835,0.07400000000000001,97.0,318,Vortex IPA,American IPA,206,16.0
-836,,,2322,Fort Pitt Ale,American Amber / Red Ale,151,12.0
-837,0.047,19.0,2661,Park,American Pale Wheat Ale,4,12.0
-838,0.055999999999999994,16.0,2660,Westfalia,American Amber / Red Ale,4,12.0
-839,0.046,17.0,2659,KSA,Kölsch,4,12.0
-840,0.063,42.0,2658,Villager,American IPA,4,12.0
-841,0.085,50.0,2625,Dirty Bastard,Scotch Ale / Wee Heavy,15,12.0
-842,0.07200000000000001,65.0,1565,Centennial IPA,American IPA,15,12.0
-843,0.047,42.0,1223,All Day IPA,American IPA,15,12.0
-844,0.076,73.0,1874,El Chingon IPA,American IPA,287,12.0
-845,0.057,40.0,1873,Block Party Robust Porter,American Porter,287,12.0
-846,0.052000000000000005,20.0,1872,Local Buzz,American Blonde Ale,287,12.0
-847,0.055,,2613,Feel Like Maplin' Love,Oatmeal Stout,22,16.0
-848,0.05,,2612,Father's Beer,Belgian Pale Ale,22,16.0
-849,0.06,,2611,The 26th,American IPA,22,16.0
-850,0.064,90.0,2610,The Gadget,American IPA,22,16.0
-851,0.04,,1657,Leprechaun Lager,American Pale Lager,348,12.0
-852,0.052000000000000005,17.0,2309,Sunbru Kölsch,Kölsch,160,12.0
-853,0.06,21.0,1635,Kilt Lifter Scottish-Style Ale,Scottish Ale,160,12.0
-854,0.051,,1616,Pumpkin Porter,American Porter,160,12.0
-855,0.042,9.0,1585,Four Peaks Peach Ale,Fruit / Vegetable Beer,160,12.0
-856,0.067,47.0,358,Hop Knot IPA,American IPA,160,12.0
-857,0.06,21.0,179,Kilt Lifter Scottish-Style Ale (2009),Scottish Ale,160,12.0
-858,0.052000000000000005,,178,Sunbru Kölsch,Kölsch,160,12.0
-859,0.06,,2428,Four String Vanilla Porter,American Porter,105,12.0
-860,0.05,28.0,2427,Suncaster Summer Wheat,American Pale Wheat Ale,105,12.0
-861,0.057,36.0,2425,Brass Knuckle Pale Ale,American Pale Ale (APA),105,12.0
-862,0.07,70.0,2424,Big Star White IPA,American White IPA,105,12.0
-863,0.055999999999999994,,1998,Old Detroit,American Amber / Red Ale,253,12.0
-864,0.069,69.0,1556,Batch 69 IPA,American IPA,253,12.0
-865,0.055,18.0,1208,Twisted Helles Summer Lager,Munich Helles Lager,253,12.0
-866,0.053,27.0,2527,OktoberFiesta,Märzen / Oktoberfest,66,12.0
-867,0.065,33.0,2526,Texicali ,American Brown Ale,66,12.0
-868,0.06,,2525,Pinata Protest,Witbier,66,12.0
-869,0.042,20.0,2524,Bat Outta Helles,Munich Helles Lager,66,12.0
-870,0.068,,2523,Original,American Amber / Red Ale,66,12.0
-871,0.042,10.0,2522,Rye Wit,Witbier,66,12.0
-872,0.059000000000000004,70.0,2521,Soul Doubt,American IPA,66,12.0
-873,0.044000000000000004,5.0,2520,Yo Soy Un Berliner,Berliner Weissbier,66,12.0
-874,0.04,,1174,77 Fremont Select Spring Session IPA,American IPA,460,12.0
-875,0.045,,1116,Fremont Organic Pale Ale,American Pale Ale (APA),460,12.0
-876,0.08,,994,Abominable Ale,English Strong Ale,460,12.0
-877,0.065,35.0,901,Harvest Ale,Saison / Farmhouse Ale,460,12.0
-878,0.065,45.0,875,Fremont Summer Ale,American Pale Ale (APA),460,12.0
-879,0.055999999999999994,30.0,858,Universale Pale Ale,American Pale Ale (APA),460,12.0
-880,0.065,80.0,857,Interurban IPA,American IPA,460,12.0
-881,0.053,32.0,1300,Gateway Kolsch Style Ale,Kölsch,433,12.0
-882,0.07,24.0,1260,Wee-Heavy-Er Scotch Ale,Scotch Ale / Wee Heavy,433,12.0
-883,0.052000000000000005,42.0,1259,13 Rebels ESB,Extra Special / Strong Bitter (ESB),433,12.0
-884,0.07,73.0,2254,Salamander Slam,American IPA,180,16.0
-885,0.05,,1658,Cack-A-Lacky,American Pale Ale (APA),347,12.0
-886,0.07200000000000001,50.0,2077,No Wake IPA,American IPA,228,12.0
-887,0.049,15.0,2076,Boathouse Blonde,American Blonde Ale,228,12.0
-888,0.05,26.0,2075,Cedar Point,American Amber / Red Ale,228,12.0
-889,0.067,70.0,2426,Clean Shave IPA,American IPA,106,12.0
-890,0.07200000000000001,75.0,2045,Might As Well IPL,American Pale Lager,240,16.0
-891,0.057999999999999996,35.0,1960,Saison Pamplemousse,Saison / Farmhouse Ale,240,12.0
-892,0.07400000000000001,74.0,1777,2020 IPA,American IPA,240,16.0
-893,0.08,70.0,1698,Wolf Among Weeds IPA,American IPA,240,16.0
-894,0.094,92.0,1641,Better Weather IPA,American IPA,240,16.0
-895,0.059000000000000004,60.0,1490,Point the Way IPA,American IPA,240,16.0
-896,0.046,15.0,1489,Golden Road Hefeweizen,Hefeweizen,240,16.0
-897,0.068,65.0,1399,Heal the Bay IPA,American IPA,240,16.0
-898,0.059000000000000004,60.0,1296,Point the Way IPA,American IPA,240,12.0
-899,0.05,,1034,Cabrillo Kölsch,Kölsch,240,16.0
-900,0.055,20.0,991,Get Up Offa That Brown,American Brown Ale,240,16.0
-901,0.08,70.0,750,Burning Bush Smoked IPA,American IPA,240,16.0
-902,0.08,70.0,749,Wolf Among Weeds IPA (2012),American IPA,240,16.0
-903,0.059000000000000004,60.0,549,Point the Way IPA (2012),American IPA,240,16.0
-904,0.046,15.0,548,Golden Road Hefeweizen (2012),Hefeweizen,240,16.0
-905,0.07,11.0,2587,Vanilla Porter,American Porter,39,16.0
-906,0.07,70.0,1109,Descender IPA,American IPA,464,12.0
-907,0.06,18.0,1108,Sweet As Pacific Ale,American Pale Wheat Ale,464,12.0
-908,0.055999999999999994,36.0,1000,Good People Pale Ale,American Pale Ale (APA),478,12.0
-909,0.09300000000000001,103.0,312,Snake Handler Double IPA,American Double / Imperial IPA,478,12.0
-910,0.06,54.0,311,Coffee Oatmeal Stout,Oatmeal Stout,478,12.0
-911,0.06,64.0,309,Good People IPA,American IPA,478,12.0
-912,0.057999999999999996,36.0,308,Good People American Brown Ale,American Brown Ale,478,12.0
-913,0.055,40.0,2205,Mountain Rescue Pale Ale,American Pale Ale (APA),194,12.0
-914,0.059000000000000004,55.0,2198,Goose Island India Pale Ale,American IPA,196,12.0
-915,0.054000000000000006,30.0,2457,312 Urban Pale Ale,American Pale Ale (APA),88,16.0
-916,0.054000000000000006,30.0,2202,312 Urban Pale Ale,American Pale Ale (APA),88,12.0
-917,0.042,18.0,2201,312 Urban Wheat Ale,American Pale Wheat Ale,88,16.0
-918,0.042,18.0,1829,312 Urban Wheat Ale,American Pale Wheat Ale,88,12.0
-919,0.042,20.0,581,312 Urban Wheat Ale (2012),American Pale Wheat Ale,88,12.0
-920,0.052000000000000005,19.0,1383,Beaver Logger,American Pale Lager,420,12.0
-921,0.05,,477,White Water Wheat,American Pale Wheat Ale,536,12.0
-922,0.052000000000000005,,476,Grand Canyon American Pilsner,American Pilsner,536,12.0
-923,0.054000000000000006,,143,Grand Canyon Sunset Amber Ale,American Amber / Red Ale,536,12.0
-924,,,142,Black Iron India Pale Ale,American IPA,536,12.0
-925,0.043,21.0,2129,Monarch Classic American Wheat,American Pale Wheat Ale,213,12.0
-926,0.049,21.0,2127,Sir William's English Brown Ale,English Brown Ale,213,12.0
-927,0.055,35.0,2126,Lakefire Rye Pale Ale,American Pale Ale (APA),213,12.0
-928,0.053,22.0,2303,Beer Agent Re-Ignition,American Blonde Ale,165,16.0
-929,0.057,18.0,1990,Cherry Ale,Fruit / Vegetable Beer,165,16.0
-930,0.055999999999999994,33.0,1702,Bourbon Barrel Aged Coconut Porter,American Porter,165,16.0
-931,0.062,60.0,1701,Great Crescent IPA,American IPA,165,16.0
-932,0.057,27.0,1700,Aurora Lager,Dortmunder / Export Lager,165,16.0
-933,0.053,22.0,1699,Great Crescent Blonde Ale,American Blonde Ale,165,16.0
-934,0.055999999999999994,33.0,1269,Great Crescent Coconut Porter,American Porter,165,16.0
-935,0.057,25.0,930,Great Crescent Oktoberfest Lager,Märzen / Oktoberfest,165,16.0
-936,0.045,36.0,649,Great Crescent Brown Ale,American Brown Ale,165,16.0
-937,0.057,18.0,639,Cherry Ale (1),Fruit / Vegetable Beer,165,16.0
-938,0.057,27.0,626,Aurora Lager (2011),Dortmunder / Export Lager,165,16.0
-939,0.06,25.0,615,Frosted Fields Winter Wheat,American Dark Wheat Ale,165,16.0
-940,0.051,13.0,478,Great Crescent Belgian Style Wit,Witbier,165,16.0
-941,0.075,65.0,455,Bourbon's Barrel Stout,American Stout,165,16.0
-942,0.08,66.0,442,Great Crescent Stout,English Stout,165,16.0
-943,0.055999999999999994,33.0,441,Great Crescent Coconut Porter (2012),American Porter,165,16.0
-944,0.057,23.0,440,Great Crescent Dark Lager,Euro Dark Lager,165,16.0
-945,0.042,26.0,439,Great Crescent Mild Ale,English Dark Mild Ale,165,16.0
-946,0.062,60.0,436,Great Crescent IPA (2011),American IPA,165,16.0
-947,0.053,22.0,389,Great Crescent Blonde Ale (2011),American Blonde Ale,165,16.0
-948,0.05,,2650,Denver Pale Ale (Artist Series No. 1),American Pale Ale (APA),6,12.0
-949,0.087,,2649,Hibernation Ale,Old Ale,6,12.0
-950,0.061,,2648,Whitewater,American Pale Wheat Ale,6,12.0
-951,0.071,,2647,Rumble,American IPA,6,12.0
-952,0.083,,2646,Orabelle,Tripel,6,12.0
-953,0.05,,2645,Lasso,American IPA,6,12.0
-954,0.095,75.0,2644,Yeti  Imperial Stout,Russian Imperial Stout,6,12.0
-955,0.073,,2643,Colette,Saison / Farmhouse Ale,6,12.0
-956,0.071,,2642,Titan IPA,American IPA,6,12.0
-957,0.045,15.0,404,Black Star Double Hopped Golden Lager (24 oz.),American Pale Lager,543,24.0
-958,0.045,15.0,164,Black Star Double Hopped Golden Lager (12 oz.),American Pale Lager,543,12.0
-959,0.052000000000000005,49.0,1923,Commotion APA,American Pale Ale (APA),269,12.0
-960,0.052000000000000005,,1922,Southern Drawl Pale Lager,American Pale Lager,269,12.0
-961,0.05,5.0,1604,Chickawawa Lemonale,Fruit / Vegetable Beer,365,12.0
-962,0.07,22.0,1574,Barrel Aged Farmer,American Brown Ale,365,16.0
-963,0.048,,1446,Great River Golden Ale,American Blonde Ale,365,12.0
-964,0.048,,1275,Dirty Blonde Chocolate Ale,American Blonde Ale,365,12.0
-965,0.048,20.0,1244,Dos Pistolas,Vienna Lager,365,12.0
-966,0.05,30.0,1064,Owney Irish Style Red Ale,Irish Red Ale,365,16.0
-967,0.06,,1028,Aaah Bock Lager,Vienna Lager,365,16.0
-968,0.055,10.0,865,Widespread Wit,Witbier,365,16.0
-969,0.054000000000000006,30.0,864,Roller Dam Red Ale,Irish Red Ale,365,16.0
-970,0.053,48.0,863,483 Pale Ale,American Pale Ale (APA),365,16.0
-971,0.09,99.0,672,Hop A Potamus Double Dark Rye Pale Ale,Rye Beer,365,16.0
-972,0.07,22.0,655,Farmer Brown Ale,American Brown Ale,365,16.0
-973,0.07,70.0,540,Big Cock IPA,American IPA,365,16.0
-974,0.059000000000000004,25.0,539,Oktoberfest,Märzen / Oktoberfest,365,16.0
-975,0.048,25.0,517,40th Annual Bix Street Fest Copper Ale (Current),American Amber / Red Ale,365,16.0
-976,0.06,36.0,371,Redband Stout,American Stout,365,16.0
-977,0.053,48.0,190,483 Pale Ale (2010),American Pale Ale (APA),365,16.0
-978,0.054000000000000006,30.0,189,Roller Dam Red Ale (2010),Irish Red Ale,365,16.0
-979,0.05,30.0,1106,Pablo Beach Pale Ale,American Pale Ale (APA),466,12.0
-980,0.057,44.0,2314,Wild Trail Pale Ale,American Pale Ale (APA),156,12.0
-981,0.067,71.0,2313,Mothman Black IPA,American Black Ale,156,12.0
-982,0.057999999999999996,,2461,Autumn Winds Fest Beer,Märzen / Oktoberfest,86,16.0
-983,0.085,69.0,2044,Captain's Daughter,American Double / Imperial IPA,86,12.0
-984,0.057999999999999996,,1567,Autumn Winds,Märzen / Oktoberfest,379,16.0
-985,0.06,54.0,1505,Flying Jenny Extra Pale Ale,American Pale Ale (APA),379,12.0
-986,0.04,20.0,1186,Hazy Day Belgian-Style Wit,Witbier,379,16.0
-987,0.055,,1185,Bring Back the Beach Blonde Ale,American Blonde Ale,379,16.0
-988,0.06,34.0,984,Leaning Chimney Smoked Porter,American Porter,379,16.0
-989,0.06,54.0,693,Flying Jenny Extra Pale Ale (2012),American Pale Ale (APA),379,12.0
-990,0.049,22.0,631,Flagship Ale,Cream Ale,379,12.0
-991,0.045,6.0,2375,Mr. Blue Sky,American Pale Wheat Ale,124,16.0
-992,0.065,,2143,3 Scrooges,Winter Warmer,124,16.0
-993,0.05,25.0,2142,Screamin’ Pumpkin,Pumpkin Ale,124,16.0
-994,0.05,35.0,2141,Grand Trunk Bohemian Pils,Czech Pilsener,124,16.0
-995,0.065,25.0,2140,El Rojo,American Amber / Red Ale,124,16.0
-996,0.075,,2139,Norm's Raggedy Ass IPA,American IPA,124,16.0
-997,0.05,35.0,2138,Grind Line,American Pale Ale (APA),124,16.0
-998,0.04,55.0,2007,Norm's Gateway IPA,American IPA,124,12.0
-999,0.09,,1570,Lemon Shandy Tripel,Tripel,124,16.0
-1000,0.063,43.0,2339,Little Red Cap,Altbier,144,12.0
-1001,0.069,67.0,1857,Supergoose IPA,American IPA,290,12.0
-1002,0.047,,1440,Hale's Pale American Ale,American Pale Ale (APA),290,12.0
-1003,0.07,,1753,Heyoka IPA,American IPA,327,16.0
-1004,0.08,,1448,Guest Lager,American Double / Imperial Pilsner,327,16.0
-1005,0.057,,1134,Pony Pilsner,German Pilsener,327,16.0
-1006,0.055,,1066,Akari Shogun American Wheat Ale,American Pale Wheat Ale,327,16.0
-1007,0.06,,849,Meat Wave,English India Pale Ale (IPA),327,16.0
-1008,0.06,,352,Over Ale,American Brown Ale,327,16.0
-1009,0.042,,149,Gossamer Golden Ale,American Blonde Ale,327,16.0
-1010,0.052000000000000005,,148,Daisy Cutter Pale Ale,American Pale Ale (APA),327,16.0
-1011,0.07,40.0,2026,Pursuit,American IPA,248,12.0
-1012,0.052000000000000005,18.0,1361,Half Full Bright Ale,American Blonde Ale,248,12.0
-1013,0.046,17.0,1016,Orange Wheat,Fruit / Vegetable Beer,476,12.0
-1014,0.043,14.0,1015,Hangar 24 Helles Lager,Munich Helles Lager,476,12.0
-1015,0.075,70.0,1677,The Great Return,American IPA,343,16.0
-1016,0.044000000000000004,18.0,1331,Hardywood Cream Ale,Cream Ale,343,12.0
-1017,0.055999999999999994,55.0,1270,Capital Trail Pale Ale,American Pale Ale (APA),343,12.0
-1018,0.052000000000000005,15.0,2059,UFO Gingerland,Herbed / Spiced Beer,234,12.0
-1019,0.062,45.0,1653,The Long Thaw White IPA,American White IPA,234,12.0
-1020,0.048,,1558,Honey Cider,Cider,234,12.0
-1021,0.05,28.0,1380,Harpoon Summer Beer,Kölsch,234,12.0
-1022,0.059000000000000004,42.0,1379,Harpoon IPA,American IPA,234,12.0
-1023,0.059000000000000004,20.0,1340,UFO Pumpkin,Pumpkin Ale,234,12.0
-1024,0.055,30.0,1313,Harpoon Octoberfest,Märzen / Oktoberfest,234,12.0
-1025,0.059000000000000004,42.0,770,Harpoon IPA (2012),American IPA,234,12.0
-1026,0.05,28.0,769,Harpoon Summer Beer (2012),Kölsch,234,12.0
-1027,0.048,10.0,610,UFO White,American Pale Wheat Ale,234,12.0
-1028,0.05,28.0,192,Harpoon Summer Beer (2010),Kölsch,234,12.0
-1029,0.059000000000000004,42.0,126,Harpoon IPA (2010),American IPA,234,12.0
-1030,,,506,Great Falls Select Pale Ale,American Blonde Ale,535,12.0
-1031,0.048,,181,Beltian White,Witbier,535,12.0
-1032,0.049,,2183,Kaua'i Golden Ale,American Blonde Ale,204,12.0
-1033,0.054000000000000006,,2182,Sunset Amber,American Pale Ale (APA),204,12.0
-1034,0.064,,2181,Hapa Brown Ale,American Brown Ale,204,19.2
-1035,0.064,,2180,Hapa Brown Ale,American Brown Ale,204,12.0
-1036,0.083,,2179,Southern Cross,Flanders Red Ale,204,19.2
-1037,0.076,65.0,1895,Groupe G,Belgian IPA,280,16.0
-1038,0.062,40.0,1894,Pt. Bonita Rustic Lager,American Pale Lager,280,16.0
-1039,0.08800000000000001,77.0,1893,Hill 88 Double IPA,American Double / Imperial IPA,280,16.0
-1040,0.07200000000000001,45.0,990,Loose Cannon,American IPA,479,12.0
-1041,0.06,30.0,989,AARGHtoberfest!,Märzen / Oktoberfest,479,12.0
-1042,0.06,,988,Davy Jones Lager,Cream Ale,479,12.0
-1043,0.063,30.0,1351,Grazias,Cream Ale,423,16.0
-1044,0.08,86.0,1346,Habitus IPA,American IPA,423,16.0
-1045,0.099,85.0,904,Ex Umbris Rye Imperial Stout,American Double / Imperial Stout,423,16.0
-1046,0.063,21.0,2295,The Golden One,American Pilsner,168,12.0
-1047,0.07,68.0,2294,The Power of Zeus,American Pale Ale (APA),168,12.0
-1048,0.044000000000000004,22.0,824,Tonganoxie Honey Wheat,American Pale Wheat Ale,500,12.0
-1049,0.045,,616,Oregon Trail Unfiltered Raspberry Wheat,Fruit / Vegetable Beer,500,12.0
-1050,0.055,,96,Annie's Amber Ale,American Amber / Red Ale,500,12.0
-1051,0.045,32.0,1615,The 12th Can™,American Pale Ale (APA),362,16.0
-1052,0.055,34.0,889,Hilliard's Pils,Czech Pilsener,362,16.0
-1053,0.049,20.0,724,Hilliard's Blonde,American Blonde Ale,362,16.0
-1054,0.055,60.0,497,Hilliard's Amber Ale,American Amber / Red Ale,362,16.0
-1055,0.066,30.0,496,Hilliard's Saison,Saison / Farmhouse Ale,362,16.0
-1056,0.042,,1652,White Cap White IPA,American White IPA,349,16.0
-1057,0.042,25.0,1835,Provision,Saison / Farmhouse Ale,297,12.0
-1058,0.047,28.0,1834,One Nut Brown,American Brown Ale,297,12.0
-1059,0.057999999999999996,45.0,1833,Hop Farm IPA,American IPA,297,12.0
-1060,0.049,20.0,2195,Double D Blonde,American Blonde Ale,198,12.0
-1061,0.078,60.0,1605,Festeroo Winter Ale,American Strong Ale,198,12.0
-1062,0.063,70.0,1543,Proxima IPA,American IPA,198,12.0
-1063,0.049,20.0,1390,Double D Blonde (2013),American Blonde Ale,198,12.0
-1064,0.048,13.0,1354,541 American Lager,American Pale Lager,198,12.0
-1065,0.065,90.0,1353,Alphadelic IPA,American IPA,198,12.0
-1066,0.065,90.0,499,Alphadelic IPA (2011),American IPA,198,12.0
-1067,0.049,20.0,498,Double D Blonde (2011),American Blonde Ale,198,12.0
-1068,0.07,,1501,Green House India Pale Ale,American IPA,395,12.0
-1069,0.051,,1004,The One They Call Zoe,American Pale Lager,395,12.0
-1070,0.051,40.0,502,Alteration,Altbier,395,12.0
-1071,0.06,50.0,501,Pale Dog,American Pale Ale (APA),395,12.0
-1072,0.065,,2357,Porter Culture,American Porter,136,12.0
-1073,0.068,,2483,Hard Cider,Cider,80,16.0
-1074,0.027000000000000003,21.0,2482,Totally Radler,Radler,80,16.0
-1075,0.039,20.0,2400,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1076,0.039,20.0,2399,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1077,0.039,20.0,2398,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1078,0.039,20.0,2397,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1079,0.039,20.0,2396,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1080,0.039,20.0,2395,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1081,0.039,20.0,2394,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1082,0.039,20.0,2393,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1083,0.039,20.0,2392,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1084,0.039,20.0,2391,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1085,0.039,20.0,2390,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1086,0.039,20.0,2389,Nonstop Hef Hop,American Pale Wheat Ale,80,16.0
-1087,0.057999999999999996,60.0,2388,Rise Up Red,American Amber / Red Ale,80,16.0
-1088,0.057999999999999996,35.0,2200,Survival Stout,American Stout,80,16.0
-1089,0.066,75.0,2199,Hopworks IPA,American IPA,80,16.0
-1090,0.073,70.0,2193,Abominable Winter Ale,American Strong Ale,80,16.0
-1091,0.06,60.0,1398,Pigwar White India Pale Ale,American White IPA,80,16.0
-1092,0.057999999999999996,60.0,1085,Rise-Up Red (2014),American Amber / Red Ale,80,16.0
-1093,0.073,70.0,916,Abominable Winter Ale (2012),American Strong Ale,80,16.0
-1094,0.051,32.0,658,HUB Lager,Czech Pilsener,80,16.0
-1095,0.066,75.0,653,Hopworks IPA (2012),American IPA,80,16.0
-1096,0.055999999999999994,,2385,Watermelon Wheat,American Pale Wheat Ale,120,12.0
-1097,0.051,17.0,2384,Laka Laka Pineapple,Hefeweizen,120,12.0
-1098,0.06,,2383,Oktoberfest,Märzen / Oktoberfest,120,16.0
-1099,0.065,,1251,Trail Maker Pale Ale,American Pale Ale (APA),445,12.0
-1100,0.055,,1250,Action Man Lager,Vienna Lager,445,12.0
-1101,0.068,90.0,1903,Let It Ride IPA,American IPA,277,12.0
-1102,0.065,22.0,1691,Stir Crazy Winter Ale,Winter Warmer,277,12.0
-1103,0.05,10.0,1555,Sweet Yamma Jamma Ale,Fruit / Vegetable Beer,277,12.0
-1104,0.046,27.0,1115,Shenanigans Summer Ale,American Pale Wheat Ale,277,12.0
-1105,0.065,80.0,729,Midnight Ryder,American Black Ale,277,12.0
-1106,0.054000000000000006,45.0,728,Day Tripper Pale Ale,American Pale Ale (APA),277,12.0
-1107,0.048,32.0,2350,Oklahoma Suks,American Amber / Red Ale,140,12.0
-1108,0.055,42.0,2301,Power & Light,American Pale Ale (APA),140,12.0
-1109,0.059000000000000004,27.0,1904,White Rabbit ,Witbier,140,12.0
-1110,0.057999999999999996,58.0,2609,Tribute,American Pale Ale (APA),23,12.0
-1111,0.07,75.0,2038,Infamous IPA,American IPA,242,12.0
-1112,0.055,20.0,1774,Hijack,Cream Ale,242,12.0
-1113,0.045,20.0,559,Jon Boat Coastal Ale,American Blonde Ale,527,12.0
-1114,0.068,55.0,558,I-10 IPA,American IPA,527,12.0
-1115,0.053,28.0,553,People's Pale Ale,American Pale Ale (APA),527,12.0
-1116,0.049,,2376,Summer Ale,American Blonde Ale,123,12.0
-1117,,,1784,Appreciation Ale,American IPA,316,16.0
-1118,0.052000000000000005,18.0,2673,House Lager,Keller Bier / Zwickel Bier,2,16.0
-1119,0.048,15.0,2672,Leisure Time,American Pale Lager,2,12.0
-1120,0.07200000000000001,80.0,2671,Excess IPL,American India Pale Lager,2,16.0
-1121,0.067,65.0,2670,Hoponius Union,American India Pale Lager,2,12.0
-1122,0.049,45.0,2669,Calyptra,American India Pale Lager,2,12.0
-1123,0.05,,1405,Helen's Blend,Cider,416,12.0
-1124,0.051,,823,Jack's Hard Cider,Cider,416,12.0
-1125,0.055,37.0,1793,Thunder Ann,American Pale Ale (APA),312,12.0
-1126,0.055,,2453,Razz Wheat,Fruit / Vegetable Beer,92,12.0
-1127,0.065,,2363,Hop Ryot,American IPA,92,12.0
-1128,0.07,,689,Mystic Mama IPA,American IPA,92,12.0
-1129,0.05,,688,Firefly Amber Ale,American Amber / Red Ale,92,12.0
-1130,0.067,,687,Chomolungma Honey Nut Brown Ale,English Brown Ale,92,12.0
-1131,0.069,,2408,Welcome to Scoville,American IPA,114,12.0
-1132,,,2595,Bastian,American Strong Ale,32,12.0
-1133,0.045,,2480,Healani,Hefeweizen,32,12.0
-1134,0.055,,1525,Yabba Dhaba Chai Tea Porter,American Porter,32,12.0
-1135,0.055,,1524,A Capella Gluten Free Pale Ale,American Pale Ale (APA),32,12.0
-1136,0.06,,1523,Casper White Stout,American Blonde Ale,32,12.0
-1137,0.06,,1254,JP's Ould Sod Irish Red IPA,American IPA,32,12.0
-1138,0.05,15.0,2060,Weize Guy,Hefeweizen,233,12.0
-1139,0.05,50.0,469,Fox Tail Gluten Free Ale,American Pale Ale (APA),233,12.0
-1140,0.09300000000000001,90.0,468,Hop Box Imperial IPA,American Double / Imperial IPA,233,12.0
-1141,0.052000000000000005,15.0,467,Joseph James American Lager,American Adjunct Lager,233,12.0
-1142,0.071,,2163,Sucha Much IPA,American IPA,208,12.0
-1143,0.075,24.0,2162,Lewbricator Wheat Dopplebock ,Doppelbock,208,12.0
-1144,0.052000000000000005,16.0,2374,Weisse Versa (2012),Hefeweizen,125,12.0
-1145,0.057999999999999996,25.0,1560,Mother in Lager,Munich Dunkel Lager,125,12.0
-1146,0.055,40.0,1557,Weekend Warrior Pale Ale,American Pale Ale (APA),125,12.0
-1147,0.055,25.0,1458,Karbachtoberfest,Märzen / Oktoberfest,125,12.0
-1148,0.047,20.0,1235,Love Street Summer Seasonal (2014),Kölsch,125,12.0
-1149,0.066,20.0,1068,Barn Burner Saison,Saison / Farmhouse Ale,125,12.0
-1150,0.095,85.0,666,Rodeo Clown Double IPA,American Double / Imperial IPA,125,12.0
-1151,0.049,45.0,465,Sympathy for the Lager,American Amber / Red Lager,125,12.0
-1152,0.052000000000000005,15.0,464,Weisse Versa,Hefeweizen,125,12.0
-1153,0.066,70.0,463,Hopadillo India Pale Ale,American IPA,125,12.0
-1154,0.057,19.0,1678,KelSo Nut Brown Lager,Euro Dark Lager,342,12.0
-1155,0.06,64.0,1572,KelSo India Pale Ale,American IPA,342,12.0
-1156,0.055,23.0,1348,KelSo Pilsner,Czech Pilsener,342,12.0
-1157,0.057999999999999996,,1193,Skilak Scottish Ale,Scottish Ale,458,12.0
-1158,0.05,15.0,1187,Peninsula Brewers Reserve (PBR),American Blonde Ale,458,12.0
-1159,0.068,,349,Sunken Island IPA,American IPA,458,12.0
-1160,0.057999999999999996,,348,Skilak Scottish Ale (2011),Scottish Ale,458,12.0
-1161,0.065,11.0,760,Cold Smoke Scotch Ale (2007),Scotch Ale / Wee Heavy,510,16.0
-1162,0.065,65.0,759,Double Haul IPA (2009),American IPA,510,16.0
-1163,0.065,65.0,758,Double Haul IPA (2006),American IPA,510,16.0
-1164,0.055,50.0,87,Eddy Out Pale Ale,American Pale Ale (APA),510,16.0
-1165,0.065,65.0,86,Double Haul IPA,American IPA,510,16.0
-1166,0.065,11.0,85,Cold Smoke Scotch Ale,Scotch Ale / Wee Heavy,510,16.0
-1167,,,2472,U. P. Witbier,Witbier,84,12.0
-1168,,,779,November Gale Pale Ale,American Pale Ale (APA),84,12.0
-1169,,,364,Olde Ore Dock Scottish Ale,Scottish Ale,84,12.0
-1170,,,60,Widow Maker Black Ale,American Brown Ale,84,12.0
-1171,,,59,Lift Bridge Brown Ale,American Brown Ale,84,12.0
-1172,,,58,Pick Axe Blonde Ale,American Blonde Ale,84,12.0
-1173,,,57,Red Jacket Amber Ale,American Amber / Red Ale,84,12.0
-1174,0.051,,2436,Amber Ale,American Amber / Red Ale,102,12.0
-1175,0.055,,1706,King Street Pilsner,Czech Pilsener,102,12.0
-1176,0.06,70.0,1667,King Street IPA,American IPA,102,12.0
-1177,0.057,10.0,1666,King Street Hefeweizen,Hefeweizen,102,12.0
-1178,0.049,,1665,King Street Blonde Ale,American Blonde Ale,102,12.0
-1179,0.063,65.0,2460,India Pale Ale,American IPA,87,16.0
-1180,0.048,11.0,2459,Blackberry Wheat,American Pale Wheat Ale,87,16.0
-1181,0.046,18.0,1274,Longboard Island Lager,American Amber / Red Lager,439,24.0
-1182,0.046,18.0,1220,Longboard Island Lager,American Amber / Red Lager,439,16.0
-1183,0.046,18.0,1070,Longboard Island Lager,American Amber / Red Lager,439,12.0
-1184,0.046,18.0,590,Longboard Island Lager,American Amber / Red Lager,439,12.0
-1185,0.04,9.0,781,Choc Beer (2003),American Dark Wheat Ale,505,12.0
-1186,0.08,,1637,Bellingham Beer Week 2013 Collaboration,Belgian Strong Dark Ale,354,16.0
-1187,0.054000000000000006,15.0,1741,A Slice of Hefen,Hefeweizen,332,16.0
-1188,0.07200000000000001,100.0,664,Elevated IPA,American IPA,332,16.0
-1189,0.066,30.0,392,Rumspringa Golden Bock,Maibock / Helles Bock,545,12.0
-1190,0.048,28.0,195,Lancaster German Style Kölsch,Kölsch,545,12.0
-1191,0.045,,2547,Beach Cruiser,Hefeweizen,59,12.0
-1192,0.068,,2493,I.P. Eh!,American IPA,59,12.0
-1193,0.05,,2492,Schoolhouse Honey,American Amber / Red Ale,59,12.0
-1194,0.055,,2491,10 Degrees of Separation,English Brown Ale,59,12.0
-1195,0.05,12.0,2108,Laughing Dog Cream Ale,Cream Ale,218,12.0
-1196,0.048,9.0,1397,Two-One Niner,American Pilsner,218,12.0
-1197,0.064,66.0,1396,Laughing Dog IPA,American IPA,218,12.0
-1198,0.064,95.0,1675,Madra Allta,American IPA,345,12.0
-1199,0.055999999999999994,70.0,1249,Duluchan India Pale Ale,American IPA,345,12.0
-1200,0.05,,1445,Lazy Monk Bohemian Pilsner,Czech Pilsener,406,16.0
-1201,0.051,,475,Yellowstone Golden Ale,Kölsch,537,12.0
-1202,0.057,,474,Tumbleweed IPA,American IPA,537,12.0
-1203,0.05,,473,Lewis & Clark Amber Ale,American Amber / Red Ale,537,12.0
-1204,0.05,,472,Miner's Gold Hefeweizen,Hefeweizen,537,12.0
-1205,0.057,,471,Back Country Scottish Ale,Scottish Ale,537,12.0
-1206,0.052000000000000005,30.0,2036,Getaway,German Pilsener,244,16.0
-1207,0.06,30.0,1168,Farm Girl Saison,Saison / Farmhouse Ale,244,16.0
-1208,0.057999999999999996,40.0,1832,Adam's Stout,American Stout,298,12.0
-1209,0.057,42.0,1688,American Hero,American Amber / Red Ale,298,12.0
-1210,0.052000000000000005,20.0,1687,Schweet Ale,Fruit / Vegetable Beer,298,12.0
-1211,0.065,75.0,1686,Irregardless IPA,American IPA,298,12.0
-1212,0.057,40.0,2434,Peach Pale Ale,American Pale Ale (APA),104,12.0
-1213,0.06,,2332,Deadeye Jack,American Porter,149,12.0
-1214,0.075,,2330,Pistols at Dawn,American Stout,149,16.0
-1215,0.057,47.0,2329,Peacemaker Pale Ale,American Pale Ale (APA),149,12.0
-1216,0.057999999999999996,11.0,2327,Shotgun Betty,Hefeweizen,149,12.0
-1217,0.061,30.0,2326,Sweet Josie,American Brown Ale,149,12.0
-1218,0.059000000000000004,42.0,1926,Long Trail IPA,English India Pale Ale (IPA),268,12.0
-1219,0.046,30.0,1924,Long Trail Ale,American Amber / Red Ale,268,12.0
-1220,0.07200000000000001,33.0,1090,Double Bag,Altbier,268,16.0
-1221,0.04,8.0,574,Blackbeary Wheat,Fruit / Vegetable Beer,268,12.0
-1222,0.046,30.0,573,Long Trail Ale (1),Altbier,268,12.0
-1223,0.046,8.0,2584,Gose,Gose,41,16.0
-1224,0.048,20.0,2583,Vermont Pilsner,German Pilsener,41,16.0
-1225,0.055,,2582,Mosaic Single Hop IPA,American IPA,41,16.0
-1226,0.045,,2581,Lost Galaxy,American IPA,41,16.0
-1227,0.062,65.0,1309,Face Plant IPA,American IPA,430,12.0
-1228,0.055999999999999994,55.0,1308,Rhino Chasers Pilsner,Czech Pilsener,430,12.0
-1229,0.052000000000000005,29.0,1571,Slow Hand Stout,American Stout,377,16.0
-1230,0.062,,1204,Hips Don't Lie,Hefeweizen,456,16.0
-1231,0.052000000000000005,,1122,Ride Again Pale Ale,American Pale Ale (APA),456,16.0
-1232,0.048,,700,The Farmer's Daughter,American Blonde Ale,456,16.0
-1233,0.038,18.0,2033,Pub Ale,English Dark Mild Ale,245,12.0
-1234,0.051,31.0,2032,Ballistic Blonde,Belgian Pale Ale,245,12.0
-1235,0.054000000000000006,,2311,Knotty Pine,American Pale Ale (APA),158,12.0
-1236,0.053,20.0,1153,Lumberyard Pilsner,American Pilsner,158,12.0
-1237,0.061,,355,Lumberyard IPA,American IPA,158,12.0
-1238,0.057999999999999996,,125,Lumberyard Red Ale,American Amber / Red Ale,158,12.0
-1239,0.05,,962,Mac's Highlander Pale Ale (2000),American Pale Ale (APA),485,12.0
-1240,0.051,32.0,961,Mac's Scottish Style Amber Ale (2000),American Amber / Red Ale,485,12.0
-1241,0.05,,1475,Macon Progress Ale,American Pale Ale (APA),400,12.0
-1242,0.055,,1008,Macon History Ale,American Brown Ale,400,12.0
-1243,0.099,,2454,Galaxy High,American Double / Imperial IPA,91,12.0
-1244,0.043,18.0,2209,Sol Drifter,American Blonde Ale,91,12.0
-1245,0.085,,2133,Thunder Snow,Winter Warmer,91,12.0
-1246,0.079,18.0,1994,The Great Pumpcan,Fruit / Vegetable Beer,91,16.0
-1247,0.047,11.0,1816,LIFT,Kölsch,91,12.0
-1248,0.05,40.0,1815,SPRYE,American Pale Ale (APA),91,12.0
-1249,0.069,70.0,1126,Psychopathy,American IPA,91,12.0
-1250,0.07,32.0,1125,Gnarly Brown,American Brown Ale,91,12.0
-1251,0.06,30.0,1124,Happy Amber,American Amber / Red Ale,91,12.0
-1252,0.051,20.0,1813,#9,Fruit / Vegetable Beer,303,16.0
-1253,0.055,13.0,1113,Elder Betty,Hefeweizen,303,12.0
-1254,0.051,20.0,360,#9,Fruit / Vegetable Beer,303,12.0
-1255,0.042,,511,High Country Pilsner (Current),German Pilsener,534,12.0
-1256,0.065,,75,Epic IPA,American IPA,534,12.0
-1257,0.042,,74,Golden Trout Pilsner,German Pilsener,534,12.0
-1258,0.045,,73,Real McCoy Amber Ale (Current),American Amber / Red Ale,534,12.0
-1259,0.07200000000000001,,1628,Festivus (1),Winter Warmer,356,12.0
-1260,0.067,,1626,Manayunk Oktoberfest,Märzen / Oktoberfest,356,12.0
-1261,0.045,21.0,1625,Belgian Style Session Ale,Belgian Pale Ale,356,12.0
-1262,0.055,,1624,Manayunk IPA,American IPA,356,12.0
-1263,0.055,,1600,Yunkin' Punkin',Pumpkin Ale,356,12.0
-1264,0.05,18.0,1484,Summer Paradise,American Pale Wheat Ale,356,12.0
-1265,0.09,30.0,1356,Monk from the 'Yunk,Tripel,356,12.0
-1266,0.06,14.0,1355,Schuylkill Punch,Fruit / Vegetable Beer,356,12.0
-1267,0.085,85.0,1334,Dreamin' Double IPA,American Double / Imperial IPA,356,12.0
-1268,0.099,93.0,1674,Chaotic Double IPA,American Double / Imperial IPA,346,12.0
-1269,0.08,88.0,1673,Manzanita IPA,American IPA,346,12.0
-1270,0.06,25.0,1672,Riverwalk Blonde Ale,American Blonde Ale,346,12.0
-1271,0.095,49.0,1671,Gillespie Brown Ale,American Brown Ale,346,12.0
-1272,0.066,44.0,1670,Manzanita Pale Ale,American Pale Ale (APA),346,12.0
-1273,0.047,,1262,Marble Pilsner,German Pilsener,443,12.0
-1274,0.062,,845,Marble India Pale Ale,American IPA,443,12.0
-1275,0.07200000000000001,,1783,Toughcats IPA,American IPA,317,16.0
-1276,0.05,,1717,Tug Pale Ale,American Pale Ale (APA),317,16.0
-1277,0.099,,1716,Sexy Chaos,Russian Imperial Stout,317,16.0
-1278,0.063,,1516,Ace Hole American Pale Ale,American Pale Ale (APA),317,16.0
-1279,0.09699999999999999,,725,Cant Dog Imperial Pale Ale,American Double / Imperial IPA,317,16.0
-1280,0.05,20.0,2308,River House,Saison / Farmhouse Ale,161,16.0
-1281,0.065,47.0,2268,Pretzel Stout,American Stout,161,16.0
-1282,0.05,35.0,2197,Rubberneck Red,American Amber / Red Ale,161,16.0
-1283,0.08,,2120,The Imperial Texan,American Double / Imperial IPA,161,16.0
-1284,0.08,,1234,The Imperial Texan,American Double / Imperial IPA,161,12.0
-1285,0.05,,1233,Day Break 4-Grain Breakfast Beer,Rye Beer,161,16.0
-1286,0.05,,1232,River House Saison,Saison / Farmhouse Ale,161,12.0
-1287,0.065,,1231,There Will Be Stout,American Stout,161,12.0
-1288,0.065,60.0,1831,Our Legacy IPA,American IPA,299,12.0
-1289,0.042,,1359,Saranac Shandy,Shandy,299,12.0
-1290,0.065,60.0,1135,Our Legacy IPA,American IPA,299,16.0
-1291,0.051,,960,Saranac Golden Pilsener (2003),German Pilsener,299,12.0
-1292,0.045,,959,Saranac Adirondack Light (2002),Light Lager,299,12.0
-1293,0.045,,958,DAX Light (1998),Light Lager,299,12.0
-1294,0.048,,957,Saranac Traditional Lager (2000),American Pale Lager,299,12.0
-1295,0.047,,956,Pomegranate Wheat (2008),Fruit / Vegetable Beer,299,12.0
-1296,0.05,12.0,773,Blueberry Blonde Ale,American Blonde Ale,299,12.0
-1297,0.06,,686,Saranac White IPA,American IPA,299,12.0
-1298,0.047,,453,Saranac Summer Ale (2011),American Pale Wheat Ale,299,12.0
-1299,0.055,,150,Saranac Pale Ale (12 oz.),English Pale Ale,299,12.0
-1300,0.055,,133,Saranac Pale Ale (16 oz.),English Pale Ale,299,16.0
-1301,0.051,20.0,1578,Lahaina Town Brown,American Brown Ale,375,12.0
-1302,0.055,,1429,Pau Hana Pilsner,Czech Pilsener,375,12.0
-1303,0.05,,1271,Lemongrass Saison,Saison / Farmhouse Ale,375,12.0
-1304,0.07,,713,Aloha B’ak’tun,Belgian Strong Dark Ale,375,12.0
-1305,0.08199999999999999,,712,Liquid Breadfruit,Fruit / Vegetable Beer,375,12.0
-1306,0.06,24.0,690,Sobrehumano Palena'ole,American Amber / Red Ale,375,12.0
-1307,0.05,12.0,547,La Perouse White,Witbier,375,12.0
-1308,0.068,68.0,435,Flyin' HI.P.Hay,American IPA,375,12.0
-1309,0.055,15.0,313,Mana Wheat,American Pale Wheat Ale,375,12.0
-1310,0.045,18.0,33,Bikini Blonde Lager,Munich Helles Lager,375,12.0
-1311,0.057,30.0,32,CoCoNut Porter,American Porter,375,12.0
-1312,0.062,65.0,31,Big Swell IPA,American IPA,375,12.0
-1313,0.037000000000000005,34.0,1237,Pit Stop Chocolate Porter,American Porter,448,12.0
-1314,0.037000000000000005,21.0,1236,Pace Setter Belgian Style Wit,Witbier,448,12.0
-1315,0.037000000000000005,53.0,1047,Back in the Saddle Rye Pale Ale,American Pale Ale (APA),448,12.0
-1316,0.069,,1986,Bushwhacker Cider,Cider,254,16.0
-1317,0.069,,1985,Weim-R-Iner,Cider,254,16.0
-1318,0.069,,1984,Cherry Bomb,Cider,254,16.0
-1319,0.07200000000000001,75.0,2186,Tsunami IPA,American IPA,203,19.2
-1320,0.07200000000000001,75.0,2185,Tsunami IPA,American IPA,203,12.0
-1321,0.042,22.0,2184,Humpback Blonde Ale,American Blonde Ale,203,12.0
-1322,0.052000000000000005,27.0,2178,Hawaiian Crow Porter,American Porter,203,12.0
-1323,0.052000000000000005,23.0,2177,Volcano Red Ale,American Amber / Red Ale,203,12.0
-1324,0.054000000000000006,42.0,2176,Mauna Kea Pale Ale,American Pale Ale (APA),203,12.0
-1325,0.053,11.0,1508,Shark Bait,Fruit / Vegetable Beer,393,12.0
-1326,0.053,30.0,1507,Gator Tail Brown Ale,American Brown Ale,393,12.0
-1327,0.071,62.0,1506,Miami Vice IPA,American IPA,393,12.0
-1328,0.053,16.0,1325,Big Rod Coconut Ale,American Blonde Ale,393,12.0
-1329,0.055999999999999994,,174,Mickey Finn's Amber Ale,American Amber / Red Ale,552,12.0
-1330,0.063,61.0,2093,Pleasure Town,American IPA,223,12.0
-1331,0.063,61.0,1814,Pleasure Town IPA,American IPA,223,12.0
-1332,0.048,12.0,587,Snowshoe White Ale,Witbier,223,12.0
-1333,0.05,24.0,586,Kodiak Brown Ale,American Brown Ale,223,12.0
-1334,0.057,70.0,434,Sockeye Red IPA,American IPA,223,12.0
-1335,0.08,100.0,2668,Habitus (2014),American Double / Imperial IPA,3,16.0
-1336,0.075,85.0,2667,Solis,American IPA,3,16.0
-1337,0.06,24.0,2666,Jucundus,Wheat Ale,3,16.0
-1338,0.08,100.0,2664,Habitus,American Double / Imperial IPA,3,16.0
-1339,0.063,30.0,2663,Grazias,Cream Ale,3,16.0
-1340,0.057999999999999996,28.0,2662,Claritas,Kölsch,3,16.0
-1341,0.083,,2535,Vinyl Frontier,American Double / Imperial IPA,65,24.0
-1342,0.08,,2534,Disco Superfly,American IPA,65,24.0
-1343,0.075,,2533,Misty Mountain Hop,American IPA,65,24.0
-1344,0.075,,2532,One-Hit Wonderful,Belgian IPA,65,24.0
-1345,0.065,,2531,En Parfaite Harmonie,Saison / Farmhouse Ale,65,24.0
-1346,0.043,8.0,2530,Daft Funk,Berliner Weissbier,65,24.0
-1347,0.075,,2529,Love In An Ellavator,American IPA,65,24.0
-1348,0.053,,2528,Spin Doctor,American Pale Ale (APA),65,24.0
-1349,0.05,,1612,Keeper (Current),American Pilsner,363,12.0
-1350,0.068,,1611,Better Half,American IPA,363,12.0
-1351,0.048,,1273,SNO White Ale,Witbier,440,16.0
-1352,0.048,,365,BRIK Irish Red Ale,Irish Red Ale,440,16.0
-1353,,,273,AXL Pale Ale,American Pale Ale (APA),440,16.0
-1354,0.087,80.0,1884,Hop Freak,American Double / Imperial IPA,284,16.0
-1355,0.051,24.0,1272,Louie's Demise Amber Ale,American Amber / Red Ale,284,16.0
-1356,0.075,51.0,1080,Hop Happy,American IPA,284,16.0
-1357,0.065,20.0,932,Booyah Farmhouse Ale,Saison / Farmhouse Ale,284,16.0
-1358,0.092,,776,O-Gii,Witbier,284,16.0
-1359,0.048,18.0,172,Flaming Damsel Lager (2010),Vienna Lager,284,16.0
-1360,0.051,24.0,171,Louie’s Demise Immort-Ale (2010),American Amber / Red Ale,284,16.0
-1361,0.099,,2361,Axe Head Malt Liquor,American Malt Liquor,134,24.0
-1362,0.054000000000000006,,2359,Huber Bock (2014),Bock,134,16.0
-1363,0.04,,2358,Minhas Light (2012),Light Lager,134,12.0
-1364,0.05,,2282,Huber,American Pale Lager,134,12.0
-1365,0.062,,2281,Clear Creek Ice,American Pale Lager,134,16.0
-1366,0.062,,2280,Clear Creek Ice,American Pale Lager,134,12.0
-1367,0.055,,2279,Mountain Crest,American Pale Lager,134,16.0
-1368,0.055,,2278,Mountain Crest,American Pale Lager,134,12.0
-1369,0.055,,2277,Mountain Creek (2013),American Pale Lager,134,12.0
-1370,0.05,,2276,Boxer,American Adjunct Lager,134,24.0
-1371,0.042,,2275,Boxer Light,Light Lager,134,12.0
-1372,0.055,,2274,Boxer Ice,American Adjunct Lager,134,12.0
-1373,0.05,,2273,Boxer,American Adjunct Lager,134,12.0
-1374,0.05,,2442,Cortez Gold,Belgian Pale Ale,98,32.0
-1375,0.068,66.0,2441,Mission IPA,American IPA,98,32.0
-1376,0.048,44.0,1460,El Conquistador Extra Pale Ale,American Pale Ale (APA),98,32.0
-1377,0.092,75.0,1459,Shipwrecked Double IPA,American Double / Imperial IPA,98,32.0
-1378,0.04,,1476,Squeaky Bike Nut Brown Ale,American Brown Ale,399,16.0
-1379,0.04,,902,Dead Horse Amber,American Pale Wheat Ale,399,16.0
-1380,0.04,,645,Rocket Bike American Lager,California Common / Steam Beer,399,16.0
-1381,0.04,,644,Johnny's American IPA,American IPA,399,16.0
-1382,0.055,,337,Boneshaker Brown Ale,English Brown Ale,547,24.0
-1383,0.055999999999999994,,336,Iron Mike Pale Ale,American Pale Ale (APA),547,24.0
-1384,0.042,,2236,Monkadelic,American Pale Ale (APA),189,12.0
-1385,0.075,85.0,2159,City of the Sun,American IPA,209,16.0
-1386,0.068,75.0,2157,Booming Rollers,American IPA,209,16.0
-1387,0.052000000000000005,50.0,2156,Oneida,American Pale Ale (APA),209,16.0
-1388,0.067,75.0,2154,Aurora ,American Amber / Red Ale,209,16.0
-1389,0.055,30.0,1495,Lomaland,Saison / Farmhouse Ale,209,16.0
-1390,0.047,46.0,1494,Fortunate Islands,American Pale Wheat Ale,209,16.0
-1391,0.057999999999999996,40.0,1493,Black House,American Stout,209,16.0
-1392,0.065,115.0,1492,Blazing World,American Amber / Red Ale,209,16.0
-1393,0.05,,327,Wapiti Amber Ale,American Amber / Red Ale,549,12.0
-1394,0.054000000000000006,,719,Sweet Georgia Brown,American Brown Ale,514,16.0
-1395,0.087,,718,Rich Man's IIPA,American Double / Imperial IPA,514,16.0
-1396,0.057999999999999996,,717,Monkey Paw Oatmeal Pale Ale,American Pale Ale (APA),514,16.0
-1397,0.055999999999999994,28.0,1907,Montauk Summer Ale,American Blonde Ale,276,12.0
-1398,0.06,49.0,1906,Driftwood Ale,Extra Special / Strong Bitter (ESB),276,12.0
-1399,0.055999999999999994,18.0,1756,When Helles Freezes Over,Munich Helles Lager,326,12.0
-1400,0.049,24.0,1617,Morgan Street Oktoberfest,Märzen / Oktoberfest,326,12.0
-1401,0.047,14.0,1052,Honey Wheat,American Pale Wheat Ale,326,12.0
-1402,0.046,24.0,1051,Black Bear Dark Lager,Schwarzbier,326,12.0
-1403,0.05,35.0,1046,Golden Pilsner,German Pilsener,326,12.0
-1404,0.052000000000000005,21.0,2413,Cali Creamin',Cream Ale,111,12.0
-1405,0.05,,419,Second Wind Pale Ale,American Pale Ale (APA),540,12.0
-1406,0.05,,408,Sunny Haze,Hefeweizen,540,12.0
-1407,0.052000000000000005,21.0,2237,Towhead,American Blonde Ale,188,12.0
-1408,0.07,70.0,2208,Lil' Helper,American IPA,188,12.0
-1409,0.08199999999999999,,1952,Train Wreck,American Amber / Red Ale,260,16.0
-1410,0.085,,768,Full Moon Belgian White Ale,Witbier,507,12.0
-1411,0.07200000000000001,,625,Desert Magic IPA,American IPA,507,12.0
-1412,0.042,,326,Up River Light,Light Lager,507,12.0
-1413,0.085,,132,Full Moon Belgian White Ale (2007),Witbier,507,12.0
-1414,0.055,,131,Dry Heat Hefeweizen (2006),Hefeweizen,507,12.0
-1415,0.05,,1598,Mustang Sixty-Six,American Amber / Red Lager,366,12.0
-1416,0.04,,862,Mustang '33,American Pale Lager,366,12.0
-1417,0.04,,699,Session '33 (2011),American Pale Lager,366,12.0
-1418,0.053,10.0,421,Mustang Golden Ale,American Blonde Ale,366,12.0
-1419,0.053,14.0,420,Washita Wheat,American Pale Wheat Ale,366,12.0
-1420,0.037000000000000005,10.0,2345,Gansett Light,Light Lager,143,16.0
-1421,0.052000000000000005,30.0,2224,Bohemian Pils,American Pilsner,143,16.0
-1422,0.053,30.0,1775,Autocrat Coffee Milk Stout,Milk / Sweet Stout,143,16.0
-1423,0.086,35.0,1291,Narragansett Bohemian Pilsner,German Pilsener,143,16.0
-1424,0.042,24.0,1093,Narragansett Summer Ale,American Pale Wheat Ale,143,12.0
-1425,0.05,22.0,580,Narragansett Cream Ale,Cream Ale,143,16.0
-1426,0.042,24.0,403,Narragansett Summer Ale,American Pale Wheat Ale,143,16.0
-1427,0.07,22.0,316,Narragansett Porter,American Porter,143,16.0
-1428,0.065,32.0,315,Narragansett Bock,Bock,143,16.0
-1429,0.055,15.0,314,Narragansett Fest Lager,Märzen / Oktoberfest,143,16.0
-1430,0.053,,1537,Undun Blonde Ale,American Blonde Ale,387,16.0
-1431,0.07400000000000001,,1536,CuDa Cascadian Dark Ale,American Black Ale,387,16.0
-1432,0.085,86.0,1265,Old Grogham Imperial India Pale Ale,American Double / Imperial IPA,387,16.0
-1433,0.085,86.0,747,Old Grogham Imperial India Pale Ale (2012),American Double / Imperial IPA,387,16.0
-1434,0.07400000000000001,,746,CuDa Cascadian Dark Ale (2012),American Black Ale,387,16.0
-1435,0.053,,654,Undun Blonde Ale (2012),American Blonde Ale,387,16.0
-1436,0.061,11.0,1705,Wick For Brains,Pumpkin Ale,337,12.0
-1437,0.065,65.0,1148,Nebraska India Pale Ale,American IPA,337,12.0
-1438,0.048,10.0,1147,EOS Hefeweizen,Hefeweizen,337,12.0
-1439,0.048,15.0,1146,Brunette Nut Brown Ale,English Brown Ale,337,12.0
-1440,0.057,29.0,1145,Cardinal Pale Ale,American Pale Ale (APA),337,12.0
-1441,0.066,,1758,County Line IPA,American IPA,325,12.0
-1442,0.048,,1757,Trauger Pilsner,German Pilsener,325,12.0
-1443,0.045,40.0,2475,Slow Ride,American IPA,82,12.0
-1444,0.065,70.0,2230,Ranger IPA,American IPA,82,12.0
-1445,0.05,29.0,1987,Shift,American Pale Lager,82,12.0
-1446,0.055999999999999994,21.0,1978,1554 Black Lager,Euro Dark Lager,82,12.0
-1447,0.048,,1975,Blue Paddle,Czech Pilsener,82,12.0
-1448,0.055,,1737,California Route,American Amber / Red Lager,82,12.0
-1449,0.052000000000000005,,1707,Snapshot,American Pale Wheat Ale,82,16.0
-1450,0.048,,1690,Sunshine Wheat Beer,American Pale Wheat Ale,82,12.0
-1451,0.052000000000000005,18.0,1586,Fat Tire Amber Ale,American Amber / Red Ale,82,12.0
-1452,0.05,29.0,952,Shift (1),American Pale Lager,82,12.0
-1453,0.052000000000000005,18.0,748,Fat Tire Amber Ale (2011),American Amber / Red Ale,82,12.0
-1454,0.05,29.0,578,Shift,American Pale Lager,82,16.0
-1455,0.065,70.0,564,Ranger IPA,American IPA,82,16.0
-1456,0.052000000000000005,18.0,563,Fat Tire Amber Ale,American Amber / Red Ale,82,16.0
-1457,0.065,70.0,115,Ranger IPA (Current),American IPA,82,12.0
-1458,0.048,,72,Sunshine Wheat Beer (2009),American Pale Wheat Ale,82,12.0
-1459,0.052000000000000005,18.0,71,Fat Tire Amber Ale (2008),American Amber / Red Ale,82,12.0
-1460,0.034,6.0,1417,Weiss Trash Culture,Berliner Weissbier,410,12.0
-1461,0.062,,885,Sea Hag IPA,American IPA,410,12.0
-1462,0.05,,884,Elm City Pilsner,American Pilsner,410,12.0
-1463,0.05,,757,Atlantic Amber Ale (2004),American Amber / Red Ale,410,12.0
-1464,0.09,,568,668 Neighbor of the Beast12 oz.,Belgian Pale Ale,410,12.0
-1465,0.08800000000000001,85.0,320,Gandhi-Bot Double IPA (12 oz.),American Double / Imperial IPA,410,12.0
-1466,0.09,,43,668 Neighbor of the Beast (16 oz.) (2010),Belgian Pale Ale,410,16.0
-1467,0.08800000000000001,85.0,42,Gandhi-Bot Double IPA (16 oz.) (2010),American Double / Imperial IPA,410,16.0
-1468,0.05,,41,Elm City Lager (2007),American Pilsner,410,12.0
-1469,0.05,,40,Atlantic Amber Ale (2007),American Amber / Red Ale,410,12.0
-1470,0.062,,39,Sea Hag IPA (Current),American IPA,410,12.0
-1471,0.05,,2272,Rebirth Pale Ale,American Pale Ale (APA),174,12.0
-1472,0.068,,1582,Irish Channel Stout,American Stout,174,16.0
-1473,0.08800000000000001,,1114,MechaHopzilla,American Double / Imperial IPA,174,16.0
-1474,0.065,,486,Hopitoulas IPA,American IPA,174,16.0
-1475,0.039,,485,NOLA Brown Ale,English Dark Mild Ale,174,12.0
-1476,0.049,,484,NOLA Blonde Ale,American Blonde Ale,174,12.0
-1477,0.055999999999999994,20.0,2043,Skylight,Dunkelweizen,241,12.0
-1478,0.055999999999999994,30.0,2042,Kadigan,American Blonde Ale,241,12.0
-1479,0.052000000000000005,50.0,2041,Dammit Jim!,American Amber / Red Ale,241,12.0
-1480,0.054000000000000006,,646,Nut Brown Ale,English Brown Ale,518,12.0
-1481,0.046,,165,White Ale,Witbier,518,12.0
-1482,0.042,35.0,2050,Cream Ale,Cream Ale,238,12.0
-1483,0.07200000000000001,,915,Green Head IPA,American IPA,495,12.0
-1484,0.054000000000000006,,914,Plum Island Belgian White,Witbier,495,12.0
-1485,0.055,,913,Newburyport Pale Ale,American Pale Ale (APA),495,12.0
-1486,0.055,,1811,Marblehead,American Amber / Red Ale,305,16.0
-1487,0.051,31.0,1622,Jam Session,American Pale Ale (APA),359,16.0
-1488,0.07200000000000001,80.0,1621,Hop Drop 'N Roll IPA,American IPA,359,16.0
-1489,0.06,,1307,Paleo IPA,English India Pale Ale (IPA),431,12.0
-1490,0.061,,1306,Buck Snort Stout,American Stout,431,12.0
-1491,0.055,,1305,Station 33 Firehouse Red,Irish Red Ale,431,12.0
-1492,0.045,,1304,Slimy Pebble Pils,German Pilsener,431,12.0
-1493,0.045,50.0,2692,Get Together,American IPA,0,16.0
-1494,0.049,26.0,2691,Maggie's Leap,Milk / Sweet Stout,0,16.0
-1495,0.048,19.0,2690,Wall's End,English Brown Ale,0,16.0
-1496,0.06,38.0,2689,Pumpion,Pumpkin Ale,0,16.0
-1497,0.06,25.0,2688,Stronghold,American Porter,0,16.0
-1498,0.055999999999999994,47.0,2687,Parapet ESB,Extra Special / Strong Bitter (ESB),0,16.0
-1499,0.069,,1854,Blue Boots IPA,American IPA,293,16.0
-1500,0.063,,1227,Hoppy Bitch IPA,American IPA,450,16.0
-1501,0.063,42.0,1226,Three Skulls Ale Pale Ale,American Pale Ale (APA),450,16.0
-1502,0.045,,541,Walter's Premium Pilsener Beer,German Pilsener,529,12.0
-1503,0.045,,109,Floppin' Crappie,American Pale Wheat Ale,529,12.0
-1504,0.043,,1917,Left of the Dial IPA,American IPA,271,12.0
-1505,0.04,,1190,Notch Session Pils,Czech Pilsener,271,12.0
-1506,0.055,,1264,O'Fallon Pumpkin Beer,Pumpkin Ale,442,12.0
-1507,0.061,66.0,1258,5 Day IPA,American IPA,442,12.0
-1508,0.051,7.0,128,O'Fallon Wheach,Fruit / Vegetable Beer,442,12.0
-1509,0.067,70.0,2331,Watershed IPA,American IPA,150,12.0
-1510,0.054000000000000006,24.0,1669,Oakshire Amber Ale,American Amber / Red Ale,150,12.0
-1511,0.057999999999999996,27.0,1668,Overcast Espresso Stout,American Stout,150,12.0
-1512,0.067,70.0,999,Watershed IPA (2013),American IPA,150,12.0
-1513,0.08199999999999999,25.0,2247,Lake Monster,Baltic Porter,184,16.0
-1514,0.049,27.0,2071,London Homesick Ale,English Bitter,184,12.0
-1515,0.048,35.0,2070,Luchesa Lager,Keller Bier / Zwickel Bier,184,12.0
-1516,0.048,35.0,2069,Slow Ride,American Pale Ale (APA),184,12.0
-1517,0.047,,2192,Occidental Hefeweizen,American Pale Wheat Ale,200,16.0
-1518,0.051,,1130,Occidental Dunkel,Dunkelweizen,200,16.0
-1519,0.05,,1129,Occidental Altbier,Altbier,200,16.0
-1520,0.045,,1081,Occidental Kölsch,Kölsch,200,16.0
-1521,0.092,72.0,2335,Perpetual Darkness,Belgian Strong Dark Ale,148,12.0
-1522,0.087,29.0,2334,Clan Warrior,Scotch Ale / Wee Heavy,148,12.0
-1523,0.054000000000000006,36.0,2333,Psycho Penguin Vanilla Porter,American Porter,148,12.0
-1524,0.047,,1721,Heliocentric Hefeweizen,Hefeweizen,148,12.0
-1525,0.051,,1720,Ghose Drifter Pale Ale,American Pale Ale (APA),148,12.0
-1526,0.051,,1431,Ghost Rider Pale Ale (2013),American Pale Ale (APA),148,12.0
-1527,0.047,,1430,Helios Hefeweizen (2013),Hefeweizen,148,12.0
-1528,0.095,19.0,1059,The Hole in Hadrian's Wall,Scottish Ale,471,16.0
-1529,0.065,26.0,1058,33 Select Brown Ale,American Brown Ale,471,16.0
-1530,0.06,29.0,603,Midwest Charm Farmhouse Ale,Saison / Farmhouse Ale,471,16.0
-1531,0.05,45.0,602,Boji Blue Pale Ale,American Pale Ale (APA),471,16.0
-1532,0.057,26.0,601,Winter Games Select #32 Stout,American Stout,471,16.0
-1533,0.05,23.0,600,Boji Beach Golden Rye Ale,Rye Beer,471,16.0
-1534,0.06,,1828,Hopsmith Pale Lager,American Pale Lager,301,16.0
-1535,0.065,65.0,1487,Falling Down Brown Ale,American Brown Ale,301,16.0
-1536,0.068,,1486,Resolution Rye Stout,American Stout,301,16.0
-1537,0.055,,1485,Plowshare Porter,American Porter,301,16.0
-1538,0.046,20.0,1394,Old Forge Pumpkin Ale,Pumpkin Ale,301,16.0
-1539,0.045,,1381,Endless Sun Ale,American Pale Wheat Ale,301,16.0
-1540,0.065,,900,Celestial Blonde Ale,American Blonde Ale,301,16.0
-1541,0.075,,891,Overbite IPA,American IPA,301,16.0
-1542,0.055,,509,T-Rail Pale Ale,American Pale Ale (APA),301,16.0
-1543,0.048,,508,Endless Summer Ale (2011),American Pale Wheat Ale,301,16.0
-1544,0.053,,1530,Clem's Gold,American Pale Lager,390,16.0
-1545,0.055,,1529,Lizzy's Red,American Amber / Red Lager,390,16.0
-1546,0.067,,1528,Orlison India Pale Lager,American Pale Lager,390,16.0
-1547,0.042,,1527,Brünette,Euro Dark Lager,390,16.0
-1548,0.040999999999999995,,1526,Havanüther,Light Lager,390,16.0
-1549,0.065,,2113,Lyric Ale,Saison / Farmhouse Ale,216,12.0
-1550,0.053,,2112,Atalanta,Saison / Farmhouse Ale,216,12.0
-1551,0.049,35.0,2302,Pinner Throwback IPA,American IPA,166,12.0
-1552,0.052000000000000005,,1883,Centennial State Pale Ale,American Pale Ale (APA),166,19.2
-1553,0.08,,1859,Old Chub NITRO,Scotch Ale / Wee Heavy,166,16.0
-1556,,,1752,Icey.P.A.,American IPA,166,16.0
-1557,0.05,,1751,One Nut Brown,English Brown Ale,166,12.0
-1558,,,1750,Birth IPA,American IPA,166,12.0
-1559,0.065,65.0,1444,Dale's Pale Ale,American Pale Ale (APA),166,12.0
-1560,0.065,65.0,1252,Dale's Pale Ale,American Pale Ale (APA),166,12.0
-1561,0.053,35.0,1167,Mama's Little Yella Pils,Czech Pilsener,166,19.2
-1562,0.085,,993,oSKAr the G'Rauch,American IPA,166,19.2
-1563,0.085,,992,oSKAr the G'Rauch,American IPA,166,16.0
-1564,0.065,65.0,955,Dale's Pale Ale,American Pale Ale (APA),166,19.2
-1565,0.07,,933,The Deuce,American Brown Ale,166,16.0
-1566,0.065,65.0,892,Dale's Pale Ale (10 Year Anniversary),American Pale Ale (APA),166,12.0
-1567,0.065,65.0,828,Dale's Pale Ale (2012),American Pale Ale (APA),166,12.0
-1568,0.087,85.0,806,Gordon Imperial Red (2010),American Double / Imperial IPA,166,12.0
-1569,0.065,65.0,755,Dale's Pale Ale (2011),American Pale Ale (APA),166,12.0
-1570,0.065,65.0,754,Dale's Pale Ale (2010),American Pale Ale (APA),166,12.0
-1571,0.087,85.0,726,G'KNIGHT (16 oz.),American Double / Imperial IPA,166,16.0
-1572,0.09,,720,15th Anniversary Abbey Ale (2012),Belgian Dark Ale,166,16.0
-1573,0.08,,661,Chaka,Belgian Strong Pale Ale,166,16.0
-1574,0.08,70.0,585,HGH (Home Grown Hops): Part Duh,American Strong Ale,166,12.0
-1575,0.08,,565,Deviant Dale's IPA,American Double / Imperial IPA,166,16.0
-1576,0.09,60.0,391,One Hit Wonder,American Double / Imperial IPA,166,12.0
-1577,0.087,85.0,388,G'KNIGHT (12 oz.),American Double / Imperial IPA,166,12.0
-1578,0.099,98.0,8,Ten Fidy Imperial Stout,Russian Imperial Stout,166,12.0
-1579,0.053,35.0,7,Mama's Little Yella Pils,Czech Pilsener,166,12.0
-1580,0.099,100.0,6,GUBNA Imperial IPA,American Double / Imperial IPA,166,12.0
-1581,0.08,35.0,5,Old Chub,Scottish Ale,166,12.0
-1582,0.087,85.0,4,Gordon Ale (2009),American Double / Imperial IPA,166,12.0
-1583,0.065,65.0,1,Dale's Pale Ale,American Pale Ale (APA),166,12.0
-1584,0.092,85.0,805,Gordon (2005),American Double / Imperial IPA,503,12.0
-1585,0.095,98.0,804,Ten Fidy Imperial Stout (2008),Russian Imperial Stout,503,12.0
-1586,0.099,98.0,803,Ten Fidy Imperial Stout (2007),Russian Imperial Stout,503,12.0
-1587,0.08,35.0,787,Old Chub (2008),Scottish Ale,503,12.0
-1588,0.08,35.0,786,Old Chub (2004),Scottish Ale,503,12.0
-1589,0.08,35.0,785,Old Chub (2003),Scottish Ale,503,12.0
-1590,0.065,65.0,745,Dale's Pale Ale (2008),American Pale Ale (APA),503,12.0
-1591,0.065,65.0,744,Dale's Pale Ale (2006),American Pale Ale (APA),503,12.0
-1592,0.065,65.0,743,Dale's Pale Ale (2004),American Pale Ale (APA),503,12.0
-1593,0.065,65.0,742,Dale's Pale Ale (2003),American Pale Ale (APA),503,12.0
-1594,0.065,65.0,741,Dale's Pale Ale (2002),American Pale Ale (APA),503,12.0
-1595,0.052000000000000005,,734,Leroy (2005),American Brown Ale,503,12.0
-1596,0.087,60.0,733,Gordon Beer (2006),American Double / Imperial IPA,503,12.0
-1597,0.087,85.0,1533,G'KNIGHT,American Double / Imperial IPA,389,12.0
-1598,0.099,98.0,1532,Ten Fidy,Russian Imperial Stout,389,12.0
-1599,0.08,85.0,1328,Deviant Dale's IPA,American Double / Imperial IPA,389,16.0
-1600,0.08,35.0,1175,Old Chub,Scottish Ale,389,12.0
-1601,0.065,65.0,1166,Dale's Pale Ale,American Pale Ale (APA),389,19.2
-1602,0.065,65.0,1065,Dale's Pale Ale,American Pale Ale (APA),389,12.0
-1603,0.055,45.0,1908,Fresh Slice White IPA,American White IPA,275,12.0
-1604,0.055,55.0,1946,Overgrown American Pale Ale,American Pale Ale (APA),261,12.0
-1605,0.04,39.0,1961,Ozark American Pale Ale,American Pale Ale (APA),259,12.0
-1606,0.048,,1684,Hula Hoppie Session IPA,American IPA,341,12.0
-1607,0.053,,927,Dirty Hippie Dark Wheat,American Dark Wheat Ale,341,12.0
-1608,0.052000000000000005,23.0,1268,Rustic Red,Irish Red Ale,441,16.0
-1609,0.053,48.0,697,Stimulator Pale Ale,American Pale Ale (APA),441,16.0
-1610,0.045,22.0,696,Old Town Ale,Kölsch,441,16.0
-1611,0.044000000000000004,28.0,695,Car 21,English Bitter,441,16.0
-1612,0.05,24.0,694,Cache La Porter,American Porter,441,16.0
-1613,0.042,35.0,1805,Rodeo Rye Pale Ale,American Pale Ale (APA),307,12.0
-1614,0.062,65.0,1048,Outlaw IPA,American IPA,307,12.0
-1615,0.044000000000000004,,1043,North Fork Lager,American Pale Lager,307,12.0
-1616,0.048,35.0,890,Payette Pale Ale,American Pale Ale (APA),307,12.0
-1617,0.055,25.0,775,Mutton Buster,American Brown Ale,307,12.0
-1618,0.05,,1087,Side Kick Kölsch,Kölsch,468,12.0
-1619,0.046,,1931,Fresh Cut Pilsner,American Pilsner,266,12.0
-1620,0.05,61.0,1930,Summer Session Ale,American Pale Wheat Ale,266,12.0
-1621,0.04,12.0,2238,Lobo Lito,Light Lager,187,12.0
-1622,0.05,17.0,2144,Robert Earl Keen Honey Pils,American Pilsner,187,12.0
-1623,0.065,77.0,2175,Mound Builder IPA,American IPA,205,12.0
-1624,0.062,62.0,2168,Amazon Princess IPA,American IPA,205,12.0
-1625,0.042,,1956,Farmer's Daughter Wheat,American Pale Wheat Ale,205,12.0
-1626,0.045,,1794,People's Pilsner,German Pilsener,205,12.0
-1627,0.055,10.0,2633,Hotbox Brown,American Brown Ale,13,12.0
-1628,0.048,15.0,2632,Gold,American Blonde Ale,13,12.0
-1629,0.057999999999999996,,2631,Black,American Black Ale,13,12.0
-1630,0.065,65.0,2630,98 Problems (Cuz A Hop Ain't One),American IPA,13,12.0
-1631,0.05,40.0,2629,Veteran’s Pale Ale (VPA),American Pale Ale (APA),13,12.0
-1632,0.05,35.0,2628,Grapefruit IPA,American IPA,13,12.0
-1633,0.051,,1062,Pete's ESP Lager (1998),American Pale Lager,470,12.0
-1634,0.047,,1061,Pete's Wicked Summer Brew (1995),American Pale Wheat Ale,470,12.0
-1635,0.049,,1060,Pete's Wicked Bohemian Pilsner (1997),Czech Pilsener,470,12.0
-1636,,,1056,Pete's Wicked Pale Ale (1997),American Pale Ale (APA),470,12.0
-1637,0.047,,1055,Pete's Wicked Summer Brew (2002),American Pale Wheat Ale,470,12.0
-1638,0.047,,1054,Pete's Wicked Summer Brew (1997),American Pale Wheat Ale,470,12.0
-1639,0.047,,1053,Pete's Wicked Summer Brew (1996),American Pale Wheat Ale,470,12.0
-1640,0.040999999999999995,12.0,2635,Sparkle,American Pale Lager,11,16.0
-1641,0.059000000000000004,25.0,1404,North 45 Amber Ale,American Amber / Red Ale,11,16.0
-1642,0.069,20.0,1403,Horny Monk,Dubbel,11,16.0
-1643,0.067,74.0,1402,Mind's Eye PA,American IPA,11,16.0
-1644,0.061,60.0,2312,Camelback,American IPA,157,12.0
-1645,0.055999999999999994,,1636,Local 5 Pale Ale,American Pale Ale (APA),355,16.0
-1646,0.073,,1518,Devils Head Red Ale,American Amber / Red Ale,355,16.0
-1647,0.07,75.0,1384,Elephant Rock IPA,American IPA,355,12.0
-1648,0.05,,1797,Black Bay Milk Stout,Milk / Sweet Stout,310,12.0
-1649,0.05,,1437,Atom Splitter Pale Ale,American Pale Ale (APA),310,12.0
-1650,0.06,20.0,1791,Hot Date Ale,Chile Beer,314,16.0
-1651,0.07,,1540,Masked Bandit IPA,American Black Ale,314,16.0
-1652,0.06,24.0,1491,Sweet Potato Ale,Fruit / Vegetable Beer,314,16.0
-1653,0.045,18.0,1335,Float Trip Ale,American Blonde Ale,314,16.0
-1654,0.055,25.0,847,Old Tom Porter,American Porter,314,16.0
-1655,0.045,18.0,846,Black Walnut Wheat,American Dark Wheat Ale,314,16.0
-1656,0.055,20.0,521,McKinney Eddy Amber Ale,American Amber / Red Ale,314,16.0
-1657,0.07,70.0,479,Missouri Mule India Pale Ale,American IPA,314,16.0
-1658,0.065,,2559,Blood of the Unicorn,American Amber / Red Ale,52,16.0
-1659,0.069,51.0,1760,GreyBeard™ IPA,American IPA,324,12.0
-1660,0.057,31.0,1759,Pisgah Pale Ale,American Pale Ale (APA),324,12.0
-1661,0.045,,1589,PONTO S.I.P.A.,American IPA,370,16.0
-1662,0.049,,1457,Chronic Ale,American Amber / Red Ale,370,16.0
-1663,0.068,,1191,Swami's India Pale Ale,American IPA,370,16.0
-1664,0.05,,2336,New Cleveland Palesner,American Pilsner,147,12.0
-1665,0.054000000000000006,45.0,2553,Mazzie,American Pale Ale (APA),55,12.0
-1666,0.099,,1909,Big Chuck Barleywine,American Barleywine,274,12.0
-1667,,,335,Ponderosa IPA,American IPA,548,12.0
-1668,,,64,Liquid Amber Ale,American Amber / Red Ale,548,12.0
-1669,0.059000000000000004,14.0,2360,Morning Wood Wheat (Current),American Pale Wheat Ale,135,12.0
-1670,0.069,17.0,1463,Hideout Helles,Munich Helles Lager,135,12.0
-1671,0.06,15.0,1462,Dead Eye Dunkel,Munich Dunkel Lager,135,12.0
-1672,0.057999999999999996,21.0,1461,Peacemaker Pilsner,Czech Pilsener,135,12.0
-1673,0.057,68.0,711,Over the Rail Pale Ale,American Pale Ale (APA),135,12.0
-1674,0.057999999999999996,21.0,188,Pallavicini Pilsner (2009),Czech Pilsener,135,12.0
-1675,0.059000000000000004,14.0,130,Morning Wood Wheat (Current),American Pale Wheat Ale,135,12.0
-1676,0.052000000000000005,18.0,399,Pyramid Hefeweizen (2011),Hefeweizen,544,12.0
-1677,0.052000000000000005,18.0,82,Haywire Hefeweizen (2010),Hefeweizen,544,16.0
-1678,0.045,35.0,2031,Golden Fleece,Belgian Pale Ale,246,12.0
-1679,0.055,30.0,2030,Smoking Mirror,American Porter,246,12.0
-1680,0.046,,2269,Rahr's Blonde,Munich Helles Lager,176,12.0
-1681,0.057999999999999996,60.0,2229,Pride of Texas Pale Ale,American Pale Ale (APA),176,12.0
-1682,0.044000000000000004,5.0,2370,18th Anniversary Gose,Gose,128,12.0
-1683,0.046,25.0,2211,White (2015),Witbier,128,12.0
-1684,0.099,85.0,1861,BLAKKR,American Black Ale,128,12.0
-1685,0.051,21.0,1718,Firemans #4 Blonde Ale (2013),American Blonde Ale,128,12.0
-1686,0.059000000000000004,,1290,The Sword Iron Swan Ale,English Pale Ale,128,12.0
-1687,0.053,52.0,1091,Hans' Pils (2015),German Pilsener,128,12.0
-1688,0.06,50.0,1086,Four Squared (2015),American Blonde Ale,128,12.0
-1689,0.051,21.0,830,Firemans #4 Blonde Ale (2015),American Blonde Ale,128,12.0
-1690,0.07200000000000001,55.0,1021,Watership Brown Ale,American Brown Ale,475,12.0
-1691,0.062,55.0,938,Gangway IPA,American IPA,475,12.0
-1692,0.049,,715,Long Day Lager,Czech Pilsener,475,12.0
-1693,0.051,17.0,2516,Farmer's Daughter Blonde,American Blonde Ale,68,16.0
-1694,0.055,45.0,2515,Pump House IPA,American IPA,68,16.0
-1695,0.07,,2514,Suicide Blonde IPA,Belgian IPA,68,16.0
-1696,0.047,25.0,2513,Vanilla Porter,American Porter,68,16.0
-1697,0.057999999999999996,18.0,2512,Honey Rye,Rye Beer,68,16.0
-1698,0.055,,1467,Happy Cider,Cider,403,16.0
-1699,0.065,44.0,945,Long Hammer IPA,American IPA,487,16.0
-1700,0.065,44.0,583,Long Hammer IPA,American IPA,487,12.0
-1701,0.057999999999999996,27.0,339,Copper Hook (2011),American Amber / Red Ale,487,12.0
-1702,0.08,,1375,Nectar of the Hops,Mead,421,16.0
-1703,0.08,,1374,Sunshine Nectar,Mead,421,16.0
-1704,0.08,,1373,Black Raspberry Nectar,Mead,421,16.0
-1705,0.05,16.0,2087,Blood Orange Wit,Witbier,225,16.0
-1706,0.05,40.0,2414,Consilium,American Pale Ale (APA),110,12.0
-1707,0.09,60.0,1581,Hammer & Sickle,Russian Imperial Stout,110,12.0
-1708,0.07,100.0,1176,Redacted Rye IPA,American IPA,110,16.0
-1709,0.099,100.0,1006,Elevation Triple India Pale Ale,American Double / Imperial IPA,110,12.0
-1710,0.05,25.0,1005,5:00 O'Clock Afternoon Ale,American Blonde Ale,110,16.0
-1711,0.07,100.0,636,Ryeteous Rye IPA (2012),American IPA,110,16.0
-1712,0.064,,1538,Stout Ol' Friend,American Stout,386,16.0
-1713,0.064,,1075,Stout Ol' Friend (2012),American Stout,386,16.0
-1714,,,710,Rye Porter,American Porter,386,16.0
-1715,0.05,,709,Miner's Gold,American Blonde Ale,386,16.0
-1716,0.046,,708,Vienna Lager,Vienna Lager,386,16.0
-1717,0.055999999999999994,,706,Jessie's Garage,American Pale Ale (APA),386,16.0
-1718,0.062,,220,Colorado Red Ale,American Amber / Red Ale,386,12.0
-1719,,,219,Miner's Gold,American Blonde Ale,386,12.0
-1720,0.055,40.0,2576,Fist City,American Pale Ale (APA),44,12.0
-1721,0.068,,1133,A Little Crazy,Belgian Pale Ale,44,12.0
-1722,0.057999999999999996,15.0,609,Rosa Hibiscus Ale,Herbed / Spiced Beer,44,12.0
-1723,0.061,31.0,418,Fistmas Ale,Herbed / Spiced Beer,44,12.0
-1724,0.057,25.0,417,Oktoberfest Revolution,Märzen / Oktoberfest,44,12.0
-1725,0.068,28.0,416,Eugene Porter,American Porter,44,12.0
-1726,0.065,70.0,415,Anti-Hero IPA,American IPA,44,12.0
-1727,0.05,14.0,414,Bottom Up Belgian Wit,Witbier,44,12.0
-1728,0.057,42.0,2452,Hustle,American Amber / Red Ale,93,12.0
-1729,0.055,42.0,2451,Pure Fury,American Pale Ale (APA),93,12.0
-1730,0.06,60.0,2132,Dad,American Amber / Red Ale,93,12.0
-1731,0.057999999999999996,35.0,1993,Panther,American Porter,93,12.0
-1732,0.052000000000000005,21.0,1992,Franz,Märzen / Oktoberfest,93,12.0
-1733,0.043,45.0,1935,Zen,American Pale Ale (APA),93,12.0
-1734,0.07200000000000001,75.0,1852,Truth,American IPA,93,12.0
-1735,0.048,25.0,1851,Cougar,American Blonde Ale,93,12.0
-1736,0.038,,2307,Smooth Operator,Cream Ale,162,16.0
-1737,0.035,,2580,Gose,Gose,42,16.0
-1738,0.043,,1807,Maine Island Trail Ale,American Pale Ale (APA),42,16.0
-1739,0.05,,1180,River North White Ale,Witbier,459,16.0
-1740,0.05,,1179,River North Ale,American Amber / Red Ale,459,16.0
-1741,0.05,55.0,1771,Lil SIPA,American IPA,321,16.0
-1742,0.055,60.0,1654,Hop Bomber Rye Pale Ale,American Pale Ale (APA),321,16.0
-1743,0.05,100.0,2579,Jah Mon,American IPA,43,12.0
-1744,0.062,,2373,Oktoberfest,Märzen / Oktoberfest,43,12.0
-1745,0.08,,2049,Headless Wylie,Pumpkin Ale,43,12.0
-1746,0.05,,2048,Dayman IPA,American IPA,43,12.0
-1747,0.071,,1880,All Aboard! Anniversary Stout,Oatmeal Stout,43,12.0
-1748,0.062,,1879,Hop Lace,American White IPA,43,12.0
-1749,0.048,,1878,OH-PA Session Pale Ale,American Pale Ale (APA),43,12.0
-1750,0.08,,1877,Patrick's Poison,American Amber / Red Ale,43,12.0
-1751,0.081,,1764,Rudolph's Red,American Amber / Red Ale,43,12.0
-1752,0.053,,1103,Babbling Blonde,American Blonde Ale,43,12.0
-1753,0.051,,1102,Maxwell's Scottish Ale,Scottish Ale,43,12.0
-1754,0.061,,1101,Grateful White,Witbier,43,12.0
-1755,0.055,,1100,RT Lager,American Amber / Red Lager,43,12.0
-1756,0.062,,1099,Old Wylie's IPA,American IPA,43,12.0
-1757,0.048,,1098,Hala Kahiki Pineapple Beer,Fruit / Vegetable Beer,43,12.0
-1758,0.045,,1330,Track 1 Amber Lager,American Amber / Red Lager,427,16.0
-1759,0.053,,2074,Pine Knob Pilsner,Czech Pilsener,229,16.0
-1760,,,1724,Cal and Co. Black Cherry Porter,American Porter,229,16.0
-1761,0.055,,1280,Lazy Daze Lager,American Adjunct Lager,229,16.0
-1762,0.059000000000000004,,899,Rochester Red Ale,American Amber / Red Ale,229,16.0
-1763,0.05,,363,Milkshake Stout,Milk / Sweet Stout,229,16.0
-1764,0.07,,158,Cornerstone IPA,American IPA,229,16.0
-1765,0.055,,97,Lazy Daze Lager,American Adjunct Lager,229,12.0
-1766,0.051,,1860,Rogue American Amber Ale,American Amber / Red Ale,289,16.0
-1767,0.076,78.0,1577,12th Round,American Strong Ale,376,16.0
-1768,0.07,80.0,1576,RoughTail IPA,American IPA,376,16.0
-1769,0.08,,1575,Polar Night Stout,American Stout,376,16.0
-1770,0.071,36.0,2304,Sundown,Saison / Farmhouse Ale,164,12.0
-1771,0.099,,2249,Sanctified,Belgian Strong Pale Ale,164,12.0
-1772,0.051,,2053,Fear of a Brett Planet,American Pale Ale (APA),164,12.0
-1773,0.055999999999999994,40.0,1842,Original Slacker Ale,English Brown Ale,164,12.0
-1774,0.07200000000000001,,1841,Alpha Blackback,American Black Ale,164,12.0
-1775,0.063,,1782,Kiss Off IPA,American IPA,164,12.0
-1776,0.045,28.0,1552,Dog Days Summer Ale,Kölsch,164,12.0
-1777,0.055999999999999994,35.0,1479,1881 California Red,American Amber / Red Ale,397,12.0
-1778,0.073,55.0,1478,CAPT Black IPA,American Black Ale,397,12.0
-1779,0.048,42.0,1370,Ruhstaller's Gilt Edge Lager Beer,American Amber / Red Lager,397,12.0
-1780,0.073,55.0,883,CAPT Black IPA,American Black Ale,397,16.0
-1781,0.055999999999999994,35.0,882,1881 California Red Ale,American Amber / Red Ale,397,16.0
-1782,0.05,15.0,1868,Saint Archer White Ale,Witbier,288,12.0
-1783,0.068,66.0,1867,Saint Archer IPA,American IPA,288,12.0
-1784,0.052000000000000005,40.0,1865,Saint Archer Pale Ale,American Pale Ale (APA),288,12.0
-1785,0.048,22.0,1864,Saint Archer Blonde,Kölsch,288,12.0
-1786,0.069,20.0,2599,Sex Panther,American Porter,30,12.0
-1787,0.095,25.0,2073,Winter Warmer (Vault Series),Winter Warmer,30,16.0
-1788,0.091,99.0,2063,Count Hopula (Vault Series),American Double / Imperial IPA,30,16.0
-1789,0.055,,1995,Oktoberfest,Märzen / Oktoberfest,30,12.0
-1790,0.05,15.0,1934,SunSpot Golden Ale,American Blonde Ale,30,12.0
-1791,0.06,,1329,I.W.A. (2011),American Pale Wheat Ale,30,12.0
-1792,0.065,,1299,Supermonk I.P.A.,Belgian IPA,30,12.0
-1793,0.055,20.0,1073,Epicenter Amber Ale,American Amber / Red Ale,30,12.0
-1794,0.05,15.0,1072,SanTan HefeWeizen,Hefeweizen,30,12.0
-1795,0.07,85.0,1071,Hop Shock IPA,American IPA,30,12.0
-1796,0.069,20.0,852,Sex Panther (2014),American Porter,30,12.0
-1797,0.055,45.0,850,Devil’s Ale,American Pale Ale (APA),30,12.0
-1798,0.081,,839,Rail Slide Imperial Spiced Ale,Herbed / Spiced Beer,30,12.0
-1799,0.05,20.0,777,Mr. Pineapple,Fruit / Vegetable Beer,30,12.0
-1800,0.055,45.0,764,American Idiot Ale (2012),American Pale Ale (APA),30,12.0
-1801,0.07,85.0,317,Hop Shock IPA (2010),American IPA,30,12.0
-1802,0.05,15.0,286,SanTan HefeWeizen (2010),Hefeweizen,30,12.0
-1803,0.055,45.0,285,Devil’s Ale (2010),American Pale Ale (APA),30,12.0
-1804,0.055,20.0,124,Epicenter Amber Ale (2010),American Amber / Red Ale,30,12.0
-1805,0.057999999999999996,20.0,1392,Sanitas Saison Ale,Saison / Farmhouse Ale,419,12.0
-1806,0.068,65.0,1391,Sanitas Black IPA,American Black Ale,419,12.0
-1807,0.08900000000000001,88.0,2002,Giant DIPA,American Double / Imperial IPA,252,16.0
-1808,0.054000000000000006,,1683,Dread Brown Ale,American Brown Ale,252,12.0
-1809,0.07,,1362,Casinos IPA,English India Pale Ale (IPA),252,16.0
-1810,0.055,30.0,1519,Saison 88,Saison / Farmhouse Ale,392,12.0
-1811,0.071,95.0,967,Black IPA,American Black Ale,392,12.0
-1812,0.045,,599,Santa Fe Irish Red Ale,Irish Red Ale,392,12.0
-1813,,,307,Santa Fe Oktoberfest,Märzen / Oktoberfest,392,12.0
-1814,0.08,,305,Imperial Java Stout,Russian Imperial Stout,392,12.0
-1815,0.055,,304,Freestyle Pilsner,German Pilsener,392,12.0
-1816,0.066,,217,Happy Camper IPA,American IPA,392,12.0
-1817,0.05,11.0,1477,Oval Beach Blonde Ale,American Blonde Ale,398,16.0
-1818,0.065,,1503,Oak Aged Cider,Cider,394,12.0
-1819,0.065,,1466,Ginger Cider,Cider,394,12.0
-1820,0.065,,1245,Schilling Hard Cider,Cider,394,12.0
-1821,0.05,45.0,1324,Schlafly Yakima Wheat Ale,American Pale Wheat Ale,428,12.0
-1822,0.05,,1323,Schlafly Black Lager,Schwarzbier,428,12.0
-1823,0.045,30.0,1078,Schlafly IPA,American IPA,428,12.0
-1824,0.05,30.0,1077,Schlafly American Brown Ale,American Brown Ale,428,12.0
-1825,0.040999999999999995,16.0,588,Schlafly Hefeweizen,Hefeweizen,428,12.0
-1826,0.045,17.0,53,Schlafly Summer Lager,Munich Helles Lager,428,12.0
-1827,0.047,,815,Sea Dog Wild Blueberry Wheat Ale,Fruit / Vegetable Beer,502,12.0
-1828,0.07400000000000001,60.0,1302,Blur India Pale Ale,American IPA,432,12.0
-1829,0.065,,1416,Dry Cider,Cider,411,16.0
-1830,0.065,,1415,Dry Hard Cider,Cider,411,16.0
-1831,0.07,105.0,918,Frankenlou's IPA,American IPA,494,16.0
-1832,0.07,55.0,917,Becky's Black Cat Porter,American Porter,494,16.0
-1833,0.077,40.0,2250,Seventh Son of a Seventh Son,American Strong Ale,183,16.0
-1834,0.053,20.0,1768,Stone Fort Brown Ale,English Brown Ale,183,16.0
-1835,0.077,40.0,1767,Seventh Son Hopped Red Ale,American Amber / Red Ale,183,16.0
-1836,0.06,53.0,1766,Humulus Nimbus Super Pale Ale,American Pale Ale (APA),183,16.0
-1837,0.07,68.0,1765,Golden Ratio IPA,American IPA,183,16.0
-1838,0.068,,2368,Black Hop IPA,American Black Ale,130,12.0
-1839,0.05,,738,Archer's Ale (2004),English Pale Ale,511,12.0
-1840,0.069,65.0,1539,Monkey Fist IPA,American IPA,385,12.0
-1841,0.051,,975,Shipyard Summer Ale,American Pale Wheat Ale,385,12.0
-1842,0.047,,814,Pumpkinhead Ale,Pumpkin Ale,385,12.0
-1843,0.051,,727,Shipyard Export,American Blonde Ale,385,12.0
-1844,0.052000000000000005,,2474,Nooner,German Pilsener,83,12.0
-1845,0.07200000000000001,65.0,2239,Torpedo,American IPA,83,12.0
-1846,0.06,,1919,Yonder Bock,Maibock / Helles Bock,83,12.0
-1847,0.06,,1918,CANfusion Rye Bock,Rye Beer,83,12.0
-1848,0.055999999999999994,37.0,1905,Sierra Nevada Pale Ale,American Pale Ale (APA),83,16.0
-1849,0.048,26.0,1338,Old Chico Crystal Wheat,American Pale Wheat Ale,83,12.0
-1850,0.05,28.0,1295,Summerfest,Czech Pilsener,83,12.0
-1851,0.07200000000000001,65.0,426,Torpedo,American IPA,83,16.0
-1852,0.055999999999999994,37.0,400,Sierra Nevada Pale Ale,American Pale Ale (APA),83,12.0
-1853,0.069,,2353,Sietsema Red Label,Cider,137,16.0
-1854,0.042,,212,Bear Ass Brown,American Brown Ale,551,12.0
-1855,0.06,,161,Red Mountain Ale,American Amber / Red Ale,551,12.0
-1856,0.068,,160,Ice Pick Ale,American IPA,551,12.0
-1857,0.1,52.0,2574,4Beans,Baltic Porter,46,12.0
-1858,0.042,16.0,2479,Jammer,Gose,46,12.0
-1859,0.08,,2443,Abigale,Belgian Pale Ale,46,12.0
-1860,0.032,7.0,2266,Rad,Fruit / Vegetable Beer,46,16.0
-1861,0.065,62.0,2090,Bengali,American IPA,46,24.0
-1862,0.047,50.0,1962,Sensi Harvest,American Pale Ale (APA),46,12.0
-1863,0.099,111.0,1696,Hi-Res,American Double / Imperial IPA,46,12.0
-1864,0.07,70.0,1608,Global Warmer,American Strong Ale,46,12.0
-1865,0.067,74.0,1591,Autumnation (2013),American IPA,46,16.0
-1866,0.054000000000000006,42.0,1388,The Crisp,German Pilsener,46,16.0
-1867,0.052000000000000005,34.0,1387,Sweet Action,Cream Ale,46,16.0
-1868,0.063,57.0,1386,Righteous Ale,Rye Beer,46,16.0
-1869,0.064,62.0,1385,Bengali Tiger,American IPA,46,16.0
-1870,0.099,85.0,1020,3Beans,Baltic Porter,46,12.0
-1871,0.059000000000000004,47.0,778,Brownstone,American Brown Ale,46,16.0
-1872,0.052000000000000005,11.0,630,Apollo,American Pale Wheat Ale,46,16.0
-1873,0.049,35.0,629,Harbinger,Saison / Farmhouse Ale,46,16.0
-1874,0.091,103.0,628,Resin,American Double / Imperial IPA,46,12.0
-1875,0.063,69.0,525,Diesel,American Stout,46,16.0
-1876,0.06,48.0,512,Autumnation (2011-12) (2011),Pumpkin Ale,46,16.0
-1877,0.054000000000000006,42.0,425,The Crisp (2011),German Pilsener,46,16.0
-1878,0.052000000000000005,34.0,424,Sweet Action (2011),Cream Ale,46,16.0
-1879,0.063,57.0,423,Righteous Ale (2011),Rye Beer,46,16.0
-1880,0.064,62.0,422,Bengali Tiger (2011),American IPA,46,16.0
-1881,0.045,,1942,Rudie Session IPA,American IPA,264,12.0
-1882,0.07400000000000001,,1708,Taster's Choice,Doppelbock,264,12.0
-1883,0.068,65.0,1521,Modus Hoperandi,American IPA,264,12.0
-1884,0.057999999999999996,15.0,1297,Estival Cream Stout,American Stout,264,12.0
-1885,0.057999999999999996,,1192,Vernal Minthe Stout,American Stout,264,12.0
-1886,0.08,,1013,Hibernal Vinifera Stout,Foreign / Export Stout,264,12.0
-1887,,,774,Autumnal Molé Stout,American Stout,264,12.0
-1888,0.042,18.0,386,Mexican Logger,American Pale Lager,264,12.0
-1889,0.053,,70,True Blonde Ale,American Blonde Ale,264,12.0
-1890,0.061,,69,Euphoria Pale Ale,American Pale Ale (APA),264,12.0
-1891,0.057,58.0,68,ESB Special Ale,Extra Special / Strong Bitter (ESB),264,12.0
-1892,0.068,65.0,67,Modus Hoperandi,American IPA,264,12.0
-1893,0.057999999999999996,39.0,1792,Iron Butt Red Ale,American Amber / Red Ale,313,12.0
-1894,0.071,92.0,1609,Initial Point India Pale Ale,American IPA,313,12.0
-1895,0.085,,2537,Monkey Dancing On A Razor Blade,Belgian IPA,64,24.0
-1896,0.08199999999999999,,2536,Tripel Deke,Tripel,64,24.0
-1897,0.049,,30,Urban Wilderness Pale Ale,English Pale Ale,557,12.0
-1898,0.06,70.0,2305,Homefront IPA,American IPA,163,12.0
-1899,0.055,16.0,1588,Sly Fox Christmas Ale 2013,Winter Warmer,371,12.0
-1900,0.055999999999999994,25.0,1363,Grisette,Grisette,371,12.0
-1901,0.062,,1211,360° India Pale Ale,American IPA,371,12.0
-1902,0.049,18.0,1123,Helles Golden Lager,Munich Helles Lager,371,12.0
-1903,0.055,16.0,926,Sly Fox Christmas Ale 2012 (2012),Winter Warmer,371,12.0
-1904,0.084,90.0,894,Odyssey Imperial IPA,American Double / Imperial IPA,371,12.0
-1905,0.057999999999999996,25.0,166,Oktoberfest Lager,Märzen / Oktoberfest,371,12.0
-1906,0.07,113.0,24,113 IPA,American IPA,371,12.0
-1907,0.053,21.0,23,Dunkel Lager,Munich Dunkel Lager,371,12.0
-1908,0.055999999999999994,11.0,22,Royal Weisse Ale,Hefeweizen,371,12.0
-1909,0.049,44.0,21,Pikeland Pils,German Pilsener,371,12.0
-1910,0.051,40.0,20,Phoenix Pale Ale,American Pale Ale (APA),371,12.0
-1911,0.07,88.0,2407,Rule G IPA,American IPA,115,12.0
-1912,0.057999999999999996,35.0,2406,Murphy's Law,American Amber / Red Ale,115,12.0
-1913,0.062,33.0,2405,Alter Ego ,Saison / Farmhouse Ale,115,12.0
-1914,0.05,,2234,Monarch Pilsner,American Pilsner,191,12.0
-1915,0.06,55.0,1606,Snow King Pale Ale,American Pale Ale (APA),191,12.0
-1916,0.054000000000000006,36.0,617,Zonker Stout,Foreign / Export Stout,191,12.0
-1917,0.05,22.0,407,OB-1 Organic Ale,English Brown Ale,191,12.0
-1918,0.05,18.0,406,Snake River Lager,Vienna Lager,191,12.0
-1919,0.052000000000000005,32.0,402,Snake River Pale Ale,American Pale Ale (APA),191,12.0
-1920,0.068,60.0,393,Pako’s EyePA,American IPA,191,12.0
-1921,0.05,,1798,Thanksgiving Ale,Kölsch,309,12.0
-1922,0.092,,1655,Double Dagger Imperial IPA,American Double / Imperial IPA,309,12.0
-1923,0.063,100.0,1596,Dagger Falls IPA,American IPA,309,12.0
-1924,0.063,100.0,1595,Dagger Falls IPA,American IPA,309,12.0
-1925,0.06,,1482,Socktoberfest,Märzen / Oktoberfest,309,16.0
-1926,0.079,,1447,Hopnoxious Imperial IPA,American Double / Imperial IPA,309,12.0
-1927,0.099,,1425,Barrel Aged Seven Devils Imperial Stout,American Double / Imperial Stout,309,12.0
-1928,0.055,,1424,Boise Co-Op Two Score Ale,Saison / Farmhouse Ale,309,16.0
-1929,0.05,,1298,Sockeye Belgian Style Summer Ale,Witbier,309,16.0
-1930,0.064,,1181,Sockeye Maibock,Maibock / Helles Bock,309,12.0
-1931,0.099,100.0,1160,Old Devil's Tooth,American Barleywine,309,12.0
-1932,0.043,,1152,Galena Golden,American Blonde Ale,309,12.0
-1933,0.052000000000000005,32.0,1151,Hell-Diver Pale Ale,American Pale Ale (APA),309,12.0
-1934,0.046,12.0,1150,Woolybugger Wheat,American Pale Wheat Ale,309,12.0
-1935,0.057,,1076,Power House Porter,American Porter,309,12.0
-1936,0.084,90.0,995,Winterfest,American Strong Ale,309,16.0
-1937,0.063,100.0,879,Dagger Falls IPA,American IPA,309,12.0
-1938,0.07,18.0,1972,LuckenBock,Bock,257,16.0
-1939,0.055,40.0,1971,Texas Pale Ale (TPA),American IPA,257,16.0
-1940,0.08,,1970,6 String Saison,Saison / Farmhouse Ale,257,16.0
-1941,0.05,22.0,1969,Kol' Beer,Kölsch,257,16.0
-1942,0.035,,2024,Montauk Light,Light Lager,249,12.0
-1943,0.048,32.0,1283,Na Zdraví Pilsner,Czech Pilsener,436,16.0
-1944,0.055,65.0,1282,Nice Rack IPA,American IPA,436,16.0
-1945,0.075,72.0,2362,2014 IPA Cicada Series,American IPA,133,16.0
-1946,0.077,65.0,2346,Sinister Minister Black IPA,American IPA,133,16.0
-1947,0.053,45.0,2320,Jack the Sipper,Extra Special / Strong Bitter (ESB),133,12.0
-1948,0.057999999999999996,60.0,2297,Devil's Harvest Extra Pale Ale,American Pale Ale (APA),133,12.0
-1949,0.05,20.0,2296,Suzy B Dirty Blonde Ale,American Blonde Ale,133,12.0
-1950,0.08,80.0,1745,Mississippi Fire Ant,American Amber / Red Ale,133,16.0
-1951,0.057999999999999996,40.0,1120,Hipster Breakfast,Oatmeal Stout,133,16.0
-1952,0.05,20.0,1118,Suzy B Dirty Blonde Ale,American Blonde Ale,133,16.0
-1953,0.057999999999999996,60.0,1117,Devil's Harvest Extra Pale Ale,American Pale Ale (APA),133,16.0
-1954,0.065,45.0,2387,Pine Belt Pale Ale,American Pale Ale (APA),118,12.0
-1955,0.055,,2267,Walloon,Saison / Farmhouse Ale,118,12.0
-1956,0.069,23.0,1740,Le Mort Vivant,Bière de Garde,118,12.0
-1957,0.085,110.0,1728,Red Cockaded Ale,American Double / Imperial IPA,118,12.0
-1958,0.092,100.0,1497,Valkyrie Double IPA,American Double / Imperial IPA,118,12.0
-1959,0.085,110.0,1011,Red Cockaded Ale (2013),American Double / Imperial IPA,118,12.0
-1960,0.07200000000000001,40.0,1010,Old Potentate,Old Ale,118,12.0
-1961,0.05,20.0,856,Bombshell Blonde,American Blonde Ale,118,16.0
-1962,0.099,100.0,853,PRO-AM (2012) (2012),American Double / Imperial IPA,118,12.0
-1963,0.055,,691,Walloon (2014),Saison / Farmhouse Ale,118,12.0
-1964,0.069,23.0,555,Le Mort Vivant (2011),Bière de Garde,118,12.0
-1965,0.083,50.0,46,Buried Hatchet Stout,Foreign / Export Stout,118,12.0
-1966,0.065,45.0,45,Pine Belt Pale Ale,American Pale Ale (APA),118,16.0
-1967,0.05,20.0,44,Bombshell Blonde,American Blonde Ale,118,12.0
-1968,0.047,35.0,2486,Baby Daddy Session IPA,American IPA,78,12.0
-1969,,,763,Hopluia (2004),English India Pale Ale (IPA),508,16.0
-1970,0.057999999999999996,,2271,Ball & Chain (2014),American Pale Ale (APA),175,16.0
-1971,0.096,,2206,Bitter Biker Double IPA,American Double / Imperial IPA,175,16.0
-1972,0.08199999999999999,,2136,God Damn Pigeon Porter,American Porter,175,16.0
-1973,0.079,,2135,Working for the Weekend,American Double / Imperial IPA,175,16.0
-1974,0.06,,2134,Angry Adam,American Amber / Red Ale,175,16.0
-1975,0.055,,2109,Freedom Fries,American Stout,175,16.0
-1976,0.096,,1821,Bitter Biker Double IPA,American Double / Imperial IPA,175,12.0
-1977,0.073,,1820,Ghost Bike Pale Ale,American Pale Ale (APA),175,16.0
-1978,0.062,,1819,Spiteful IPA,American IPA,175,12.0
-1979,0.06,,1634,Alley Time,American Pale Ale (APA),175,12.0
-1980,0.057999999999999996,,1633,Fat Badger,Irish Red Ale,175,12.0
-1981,0.055,,1632,In the Weeds,American Pale Wheat Ale,175,12.0
-1982,0.05,22.0,855,Special Amber,Vienna Lager,498,12.0
-1983,0.05,22.0,445,Special Amber,Vienna Lager,498,12.0
-1984,0.055999999999999994,,1587,Seven Gates Pale Ale,American Pale Ale (APA),372,12.0
-1985,0.052000000000000005,,2242,Gunga Din,Cider,186,16.0
-1986,0.042,20.0,1544,Starr Pils,German Pilsener,383,12.0
-1987,0.065,52.0,1205,Northern Lights India Pale Ale,American IPA,383,16.0
-1988,0.048,12.0,369,Festie,Märzen / Oktoberfest,383,12.0
-1989,0.065,52.0,368,Northern Lights India Pale Ale,American IPA,383,12.0
-1990,0.065,65.0,2386,Third Eye Enlightened Pale Ale,American Pale Ale (APA),119,12.0
-1991,0.049,17.0,92,Colorado Kölsch,Kölsch,119,12.0
-1992,0.057,25.0,91,Steam Engine Lager,American Amber / Red Lager,119,12.0
-1993,0.065,65.0,90,Third Eye Pale Ale,American IPA,119,12.0
-1994,0.047,9.0,2366,Point Special (Current),American Adjunct Lager,131,12.0
-1995,0.047,9.0,2365,Point Special,American Adjunct Lager,131,12.0
-1996,0.054000000000000006,33.0,2270,Point Cascade Pale Ale (2013),American Pale Ale (APA),131,12.0
-1997,0.047,9.0,2228,Point Special,American Adjunct Lager,131,12.0
-1998,0.052000000000000005,9.0,2151,Onyx Black Ale,American Black Ale,131,12.0
-1999,0.063,64.0,2150,Beyond The Pale IPA,American IPA,131,12.0
-2000,0.047,9.0,2122,Point Special (2013),American Adjunct Lager,131,12.0
-2001,0.047,9.0,2121,Point Special (2012),American Adjunct Lager,131,12.0
-2002,0.047,9.0,2115,Point Special Lager,American Adjunct Lager,131,16.0
-2003,0.062,,1450,St. Benedict's Winter Ale,Winter Warmer,131,12.0
-2004,0.057,15.0,1357,Point Oktoberfest,Märzen / Oktoberfest,131,16.0
-2005,0.052000000000000005,7.0,1225,Point Nude Beach Summer Wheat,American Pale Wheat Ale,131,16.0
-2006,0.05,7.0,816,Point Nude Beach Summer Wheat,American Pale Wheat Ale,131,12.0
-2007,0.05,7.0,772,Point Nude Beach Summer Wheat (2011),American Pale Wheat Ale,131,12.0
-2008,0.035,,684,Drop Dead Blonde,American Blonde Ale,131,12.0
-2009,0.049,13.0,650,Three Kings Ale,Kölsch,131,12.0
-2010,0.057,15.0,456,Point Oktoberfest,Märzen / Oktoberfest,131,12.0
-2011,0.054000000000000006,32.0,357,2012 Black Ale,American Brown Ale,131,12.0
-2012,0.05,7.0,141,Point Nude Beach Summer Wheat (2010),American Pale Wheat Ale,131,12.0
-2013,0.054000000000000006,33.0,140,Point Cascade Pale Ale,American Pale Ale (APA),131,12.0
-2014,0.047,14.0,139,Point Amber Classic,American Amber / Red Lager,131,12.0
-2015,0.047,9.0,138,Point Special Lager,American Adjunct Lager,131,12.0
-2016,0.051,31.0,953,Wisco Disco,American Amber / Red Ale,486,16.0
-2017,0.05,,1983,Brontide,American Black Ale,255,12.0
-2018,0.05,,1631,Brontide,American Black Ale,255,12.0
-2019,0.045,,1344,Classique,Saison / Farmhouse Ale,255,12.0
-2020,0.045,,922,Sunsplash Golden Ale (2004),American Blonde Ale,492,12.0
-2021,0.051,25.0,1410,Sand Island Lighthouse,Kölsch,412,12.0
-2022,0.05,30.0,925,Lily Flagg Milk Stout,Milk / Sweet Stout,412,12.0
-2023,0.07200000000000001,70.0,637,Monkeynaut IPA,American IPA,412,12.0
-2024,0.05,,2369,Straub Beer (Current),American Adjunct Lager,129,12.0
-2025,0.040999999999999995,8.0,2233,American Lager,American Adjunct Lager,129,12.0
-2026,0.040999999999999995,8.0,2232,American Amber,American Amber / Red Lager,129,12.0
-2027,0.032,13.0,2231,American Light,Light Lager,129,12.0
-2028,0.053,49.0,2352,Extra Pale Ale,American Pale Ale (APA),138,12.0
-2029,0.053,40.0,2549,Make It So,Extra Special / Strong Bitter (ESB),58,12.0
-2030,0.047,55.0,2473,Hopvale Organic Ale,American Pale Ale (APA),58,16.0
-2031,0.083,100.0,2415,Unchained #18 Hop Silo,American Double / Imperial IPA,58,16.0
-2032,0.052000000000000005,29.0,2605,Tip Off,Altbier,25,16.0
-2033,0.054000000000000006,,2215,Java Mac,Scottish Ale,25,16.0
-2034,0.054000000000000006,23.0,2164,Cowbell,American Porter,25,16.0
-2035,0.057999999999999996,20.0,2085,Hop Up Offa That Brett (2014),Belgian Pale Ale,25,16.0
-2036,0.083,23.0,2084,PV Muckle (2013),Scotch Ale / Wee Heavy,25,16.0
-2037,0.099,36.0,2083,Bourbon Barrel Batch 666: Sympathy for the Devil,Belgian Dark Ale,25,16.0
-2038,0.09,30.0,2082,Whip Fight,Scotch Ale / Wee Heavy,25,16.0
-2039,0.053,23.0,2081,Port Barrel Wee Mac ,Scotch Ale / Wee Heavy,25,16.0
-2040,0.064,75.0,2001,Fistful Of Hops Red,American IPA,25,16.0
-2041,0.063,75.0,2000,Fistful of Hops Orange,American IPA,25,16.0
-2042,0.064,75.0,1999,Fistful Of Hops Blue,American IPA,25,16.0
-2043,0.064,75.0,1996,Fistful of Hops Green,American IPA,25,16.0
-2044,,,1948,30 Min Coma,Belgian IPA,25,16.0
-2045,0.09,30.0,1656,Wee Muckle,Scotch Ale / Wee Heavy,25,16.0
-2046,0.065,55.0,1599,Royal Brat,Extra Special / Strong Bitter (ESB),25,16.0
-2047,0.075,77.0,1420,Grapefruit Jungle (GFJ),American IPA,25,16.0
-2048,0.055999999999999994,50.0,1389,Osiris Pale Ale,American Pale Ale (APA),25,16.0
-2049,0.099,75.0,1367,Bourbon Barrel Aged Timmie,Russian Imperial Stout,25,16.0
-2050,0.063,23.0,1366,Stupid Sexy Flanders,Flanders Oud Bruin,25,16.0
-2051,,,1347,Bourbon Barrel Cowbell,American Porter,25,16.0
-2052,0.054000000000000006,,1314,Popcorn Pilsner,German Pilsener,25,16.0
-2053,0.071,27.0,1128,Ring of Dingle,Irish Dry Stout,25,16.0
-2054,0.054000000000000006,23.0,1127,Bourbon Barrel Wee Mac,Scottish Ale,25,16.0
-2055,0.099,60.0,1049,Bourbon Barrel Johan,English Barleywine,25,16.0
-2056,0.07,,934,The Deuce,American Brown Ale,25,16.0
-2057,0.09,24.0,923,The Velvet Fog,Quadrupel (Quad),25,16.0
-2058,0.055,23.0,874,Sun King Oktoberfest,Märzen / Oktoberfest,25,16.0
-2059,0.052000000000000005,24.0,739,Indianapolis Indians Lager,Dortmunder / Export Lager,25,16.0
-2060,0.052000000000000005,24.0,698,Indians Victory Lager (2012),Dortmunder / Export Lager,25,16.0
-2061,0.08,,660,Chaka,Belgian Strong Pale Ale,25,16.0
-2062,0.091,91.0,651,Isis,American Double / Imperial IPA,25,16.0
-2063,0.09,30.0,584,Wee Muckle (2011),Scotch Ale / Wee Heavy,25,16.0
-2064,0.075,77.0,532,Grapefruit Jungle (GFJ) (2011),American IPA,25,16.0
-2065,0.055,23.0,526,Sun King Oktoberfest (2011),Märzen / Oktoberfest,25,16.0
-2066,0.099,60.0,394,Johan the Barleywine,English Barleywine,25,16.0
-2067,0.054000000000000006,23.0,213,Wee Mac Scottish-Style Ale,Scottish Ale,25,16.0
-2068,0.053,20.0,55,Sunlight Cream Ale,Cream Ale,25,16.0
-2069,0.055999999999999994,50.0,54,Osiris Pale Ale (2010),American Pale Ale (APA),25,16.0
-2070,0.045,,1207,Dam Lager,American Amber / Red Lager,455,12.0
-2071,0.07,,1206,Red Clay IPA,American IPA,455,12.0
-2072,0.07200000000000001,,2543,Todd the Axe Man,American IPA,61,16.0
-2073,0.057,,2409,Doomtree,Extra Special / Strong Bitter (ESB),61,16.0
-2074,0.099,85.0,1739,BLAKKR,American Black Ale,61,16.0
-2075,0.073,69.0,1112,Overrated! West Coast Style IPA,American IPA,61,16.0
-2076,0.075,90.0,329,WET,American IPA,61,16.0
-2077,0.04,37.0,19,Bitter Brewer,English Bitter,61,16.0
-2078,0.055,34.0,18,SurlyFest,Rye Beer,61,16.0
-2079,0.051,45.0,17,Coffee Bender,American Brown Ale,61,16.0
-2080,0.051,45.0,16,Bender,American Brown Ale,61,16.0
-2081,0.09699999999999999,120.0,15,Abrasive Ale,American Double / Imperial IPA,61,16.0
-2082,0.051,20.0,14,Hell,Keller Bier / Zwickel Bier,61,16.0
-2083,0.067,33.0,13,CynicAle,Saison / Farmhouse Ale,61,16.0
-2084,0.062,99.0,12,Furious,American IPA,61,16.0
-2085,0.073,50.0,1242,Big Nose,American IPA,447,12.0
-2086,0.05,10.0,1241,Cotton Mouth,Witbier,447,12.0
-2087,0.055999999999999994,35.0,1240,Stump Knocker Pale Ale,American Pale Ale (APA),447,12.0
-2088,0.05,38.0,1239,Midnight Oil,Oatmeal Stout,447,12.0
-2089,0.059000000000000004,18.0,1238,Wild Night,Cream Ale,447,12.0
-2090,0.045,,1554,Bermuda Triangle Ginger Beer,Herbed / Spiced Beer,381,12.0
-2091,0.055,35.0,2568,Take Two Pils,German Pilsener,49,12.0
-2092,0.057,,2551,Waterkeeper,Hefeweizen,49,12.0
-2093,0.064,,1710,SweetWater IPA,American IPA,49,12.0
-2094,0.054000000000000006,,1709,420 Extra Pale Ale,American Pale Ale (APA),49,12.0
-2095,0.08,95.0,1229,Dodgy Knight Imperial IPA,American Double / Imperial IPA,449,12.0
-2096,0.05,,1164,TailGate Saison,Saison / Farmhouse Ale,449,12.0
-2097,0.05,44.0,663,TailGate IPA,American IPA,449,24.0
-2098,0.05,44.0,662,TailGate IPA,American IPA,449,12.0
-2099,0.049,28.0,623,TailGate Hefeweizen,Hefeweizen,449,24.0
-2100,0.05,19.0,622,Blacktop Blonde,American Blonde Ale,449,24.0
-2101,0.05,19.0,362,Blacktop Blonde,American Blonde Ale,449,12.0
-2102,0.049,28.0,361,TailGate Hefeweizen,Hefeweizen,449,12.0
-2103,0.085,34.0,2575,Wooden Rooster,Tripel,45,16.9
-2104,0.048,20.0,2555,Ginger Peach Saison,Saison / Farmhouse Ale,45,16.0
-2105,0.062,35.0,1736,Zombie Monkie,American Porter,45,16.0
-2106,0.055999999999999994,20.0,1196,Wild Plum Farmhouse Ale,Saison / Farmhouse Ale,45,16.0
-2107,0.05,20.0,1063,Vanilla Bean Buffalo Sweat,Oatmeal Stout,45,16.0
-2108,0.068,110.0,1017,Ethos IPA,American IPA,45,16.0
-2109,0.044000000000000004,12.0,1009,Tallgrass Pub Ale,American Brown Ale,45,16.0
-2110,0.07200000000000001,93.0,912,Oasis,Extra Special / Strong Bitter (ESB),45,16.0
-2111,0.05,20.0,765,Buffalo Sweat,Milk / Sweet Stout,45,16.0
-2112,0.05,20.0,676,Halcyon Unfiltered Wheat,American Pale Wheat Ale,45,16.0
-2113,0.052000000000000005,,595,8-Bit Pale Ale,American Pale Ale (APA),45,16.0
-2114,0.085,,537,Velvet Rooster,Tripel,45,16.0
-2115,0.05,20.0,412,Halcyon Unfiltered Wheat,American Pale Wheat Ale,45,12.0
-2116,0.05,16.0,105,Köld Lager (2010),German Pilsener,45,16.0
-2117,0.07200000000000001,93.0,104,Oasis (2010),American Double / Imperial IPA,45,16.0
-2118,0.044000000000000004,22.0,103,Tallgrass Ale,American Brown Ale,45,16.0
-2119,0.05,20.0,102,Buffalo Sweat (2010),Milk / Sweet Stout,45,16.0
-2120,0.063,60.0,101,Tallgrass IPA,American IPA,45,16.0
-2121,0.068,,1433,Hat Trick Hop IPA,American IPA,409,16.0
-2122,0.055999999999999994,,1432,Yard Sale Amber Ale,American Amber / Red Ale,409,16.0
-2123,0.055,,936,Loafin Bräu,Altbier,490,16.0
-2124,0.07,80.0,544,Old Elephant Foot IPA,American IPA,490,16.0
-2125,0.065,35.0,2640,Peck's Porter,American Porter,7,16.0
-2126,0.07,,2448,Reactor,American IPA,7,16.0
-2127,0.057,,2447,Mr. Orange,Witbier,7,16.0
-2128,0.08,22.0,2601,Deduction,Dubbel,28,12.0
-2129,0.057,,973,Face Down Brown Ale,American Brown Ale,480,12.0
-2130,0.064,,827,Tempter IPA,American IPA,480,12.0
-2131,0.055,,589,Bridal Veil Rye Pale Ale,American Pale Ale (APA),480,12.0
-2132,0.048,,2155,Smittytown,Extra Special / Strong Bitter (ESB),210,12.0
-2133,0.04,,1982,Greenwood Beach,Fruit / Vegetable Beer,210,12.0
-2134,0.066,,1939,Gatecrasher,English India Pale Ale (IPA),210,12.0
-2135,0.047,42.0,1082,RecreationAle,American Pale Ale (APA),469,12.0
-2136,0.055,35.0,2119,First Stand,Saison / Farmhouse Ale,215,12.0
-2137,0.063,23.0,2118,Battle LIne,American Brown Ale,215,12.0
-2138,0.055999999999999994,12.0,2117,Broken Bridge,Dunkelweizen,215,12.0
-2139,0.071,69.0,2116,Brutus,English India Pale Ale (IPA),215,12.0
-2140,0.06,,1916,Petit Mutant,American Wild Ale,272,16.0
-2141,0.096,,1915,The Crusher,American Double / Imperial IPA,272,16.0
-2142,0.08,,1914,Beelzebub,American Double / Imperial Stout,272,16.0
-2143,0.07,,1810,Focal Banger,American IPA,272,16.0
-2144,0.08,120.0,1111,Heady Topper,American Double / Imperial IPA,272,16.0
-2145,0.08,120.0,379,Heady Topper,American Double / Imperial IPA,272,16.0
-2146,0.046,20.0,1200,Bomber Mountain Amber Ale (2013),American Amber / Red Ale,457,12.0
-2147,0.07,75.0,1199,Indian Paintbrush IPA,American IPA,457,12.0
-2148,0.048,16.0,1198,Saddle Bronc Brown Ale (2013),English Brown Ale,457,12.0
-2149,0.059000000000000004,15.0,1197,Wagon Box Wheat Beer,American Pale Wheat Ale,457,12.0
-2150,0.05,,1945,Birdhouse Pale Ale,Belgian Pale Ale,262,12.0
-2151,0.073,,1079,Ozzy,Belgian Pale Ale,262,12.0
-2152,0.07,,94,Resurrection,Dubbel,262,12.0
-2153,0.052000000000000005,16.0,1748,Bronx Summer Pale Ale,American Pale Ale (APA),329,16.0
-2154,0.057,46.0,1747,Bronx Black Pale Ale,American Black Ale,329,16.0
-2155,0.063,50.0,1037,Bronx Pale Ale,American Pale Ale (APA),329,16.0
-2156,0.052000000000000005,35.0,2594,Surfrider,American Pale Ale (APA),33,16.0
-2157,0.055,,2035,Kolschtal Eddy,Kölsch,33,16.0
-2158,0.05,,2034,South Bay Session IPA,American IPA,33,16.0
-2159,0.069,34.0,1562,Grandma's Pecan,English Brown Ale,33,16.0
-2160,0.099,101.0,1561,Double Trunk,American Double / Imperial IPA,33,16.0
-2161,0.046,45.0,1749,Just IPA,American IPA,328,12.0
-2162,0.045,,2455,Lionshead,American Pilsner,90,12.0
-2163,,,963,Manhattan Gold Lager (1990),American Amber / Red Lager,484,12.0
-2164,0.052000000000000005,,2638,G. B. Russo’s Italian Pistachio Pale Ale,American Pale Ale (APA),9,16.0
-2165,0.057999999999999996,,1278,Northern Hawk Owl Amber,American Amber / Red Ale,438,12.0
-2166,0.059000000000000004,,1277,CEO Stout,American Stout,438,16.0
-2167,0.047,,1276,Will Power Pale Ale,American Pale Ale (APA),438,16.0
-2168,0.044000000000000004,,1732,Curious Traveler Shandy,Shandy,334,12.0
-2169,0.048,18.0,2347,Hunny Do Wheat,American Pale Wheat Ale,142,12.0
-2170,0.052000000000000005,,1781,Three Way Pale Ale,American Pale Ale (APA),142,12.0
-2171,0.040999999999999995,,1780,Rise to the Top,Cream Ale,142,12.0
-2172,0.049,,1779,Lost Trout Brown Ale,American Brown Ale,142,12.0
-2173,0.051,11.0,2421,Watermelon Ale,Fruit / Vegetable Beer,108,12.0
-2174,0.04,18.0,2319,Knotty Blonde Ale,American Blonde Ale,153,12.0
-2175,0.062,40.0,2317,Fivepine Chocolate Porter,American Porter,153,12.0
-2176,0.062,82.0,2316,Hoodoo Voodoo IPA,American IPA,153,12.0
-2177,0.053,22.0,1913,Hydraulion Red,Irish Red Ale,273,12.0
-2178,0.06,50.0,1912,40 Mile IPA,American IPA,273,12.0
-2179,0.055,64.0,2617,Citra Faced,American Pale Wheat Ale,21,16.0
-2180,0.055,31.0,2616,Pole Barn Stout,Oatmeal Stout,21,16.0
-2181,0.054000000000000006,37.0,2615,Pale,American Pale Ale (APA),21,16.0
-2182,0.053,27.0,2614,Yoshi's Nectar,California Common / Steam Beer,21,16.0
-2183,0.052000000000000005,,1889,Leatherhead Red,American Amber / Red Ale,282,12.0
-2184,0.065,,1222,Cropduster Mid-American IPA,American IPA,282,12.0
-2185,0.075,,122,Golden Frau Honey Wheat,Braggot,282,12.0
-2186,,,121,Cornstalker Dark Wheat,American Dark Wheat Ale,282,12.0
-2187,0.057999999999999996,20.0,2623,Cafe Leche,American Porter,17,16.0
-2188,0.052000000000000005,12.0,2622,Damascene Apricot Sour,Fruit / Vegetable Beer,17,16.0
-2189,0.12,90.0,2621,Csar,Russian Imperial Stout,17,16.0
-2190,0.055,,1817,Klingon Warnog Roggen Dunkel,Roggenbier,17,16.0
-2191,0.085,115.0,1449,Overlord Imperial IPA,American Double / Imperial IPA,17,16.0
-2192,0.057999999999999996,36.0,951,Alloy,American IPA,17,16.0
-2193,0.051,22.0,950,Rivet Irish Red Ale,Irish Red Ale,17,16.0
-2194,0.052000000000000005,50.0,949,3 Gear Robust Porter,American Porter,17,16.0
-2195,0.045,35.0,948,Circuit Bohemian Pilsner,Czech Pilsener,17,16.0
-2196,0.055,,2321,Turnrow Harvest Ale,American Blonde Ale,152,12.0
-2197,0.07,60.0,1755,Juke Joint IPA,American IPA,152,12.0
-2198,0.07,35.0,1754,Parade Ground Coffee Porter,American Porter,152,12.0
-2199,0.05,21.0,1428,Tin Roof Watermelon Wheat,Fruit / Vegetable Beer,152,12.0
-2200,0.045,18.0,529,Tin Roof Blonde Ale,American Blonde Ale,152,12.0
-2201,0.055,37.0,495,Voodoo Bengal Pale Ale,American Pale Ale (APA),152,12.0
-2202,0.045,28.0,494,Perfect Tin Amber,American Amber / Red Ale,152,12.0
-2203,0.073,87.0,1856,IPA & a Half,American IPA,291,12.0
-2204,0.055,33.0,736,Ornery Amber Lager (2003),Vienna Lager,291,12.0
-2205,0.05,,1027,Big Island Shandy,Shandy,474,16.0
-2206,0.068,,1026,Preservation IPA,American IPA,474,16.0
-2207,0.062,72.0,1938,Almanac IPA,American IPA,265,12.0
-2208,0.065,,1937,Milk Mustachio Stout,Milk / Sweet Stout,265,12.0
-2209,0.06,30.0,1936,Farmer's Tan Red Ale,American Amber / Red Ale,265,12.0
-2210,0.057,,594,Triangle India Pale Ale,American IPA,524,12.0
-2211,0.05,,114,Triangle White Ale,Witbier,524,12.0
-2212,0.08,,113,Triangle Belgian Golden Ale,Belgian Strong Pale Ale,524,12.0
-2213,0.08199999999999999,,2445,Troegenator,Doppelbock,97,16.0
-2214,0.075,93.0,2444,Nugget Nectar,American Amber / Red Ale,97,16.0
-2215,0.045,45.0,2203,Sunshine Pils,American Pilsner,97,12.0
-2216,0.08199999999999999,25.0,1510,Troegenator Doublebock,Doppelbock,97,16.0
-2217,0.075,85.0,1509,Perpetual IPA,American IPA,97,12.0
-2218,0.055,52.0,433,Greenville Pale Ale,American Pale Ale (APA),539,12.0
-2219,0.062,65.0,641,Hoppy Boy,American IPA,520,16.0
-2220,0.054000000000000006,26.0,2588,Cow Creek,American Amber / Red Lager,38,12.0
-2221,0.075,63.0,2458,Chupahopra,American IPA,38,12.0
-2222,0.051,19.0,2212,Twisted X,American Adjunct Lager,38,12.0
-2223,0.040999999999999995,41.0,2235,Day Hike Session,American IPA,190,12.0
-2224,0.048,48.0,1661,Trailhead ISA,American IPA,190,12.0
-2225,0.052000000000000005,27.0,1660,Immersion Amber,American Amber / Red Ale,190,12.0
-2226,0.062,70.0,1659,Evo IPA,American IPA,190,12.0
-2227,0.048,,1438,Presidential Pils,Czech Pilsener,190,12.0
-2228,0.062,70.0,1173,Evolutionary IPA (2012),American IPA,190,12.0
-2229,0.057,36.0,560,Persnickety Pale,American Pale Ale (APA),190,12.0
-2230,0.054000000000000006,20.0,519,SoDo Brown Ale,American Brown Ale,190,12.0
-2231,0.052000000000000005,27.0,518,Immersion Amber Ale (2011),American Amber / Red Ale,190,12.0
-2232,0.062,70.0,505,Evolutionary IPA (2011),American IPA,190,12.0
-2233,0.048,48.0,482,Trailhead India Style Session Ale (2011),American IPA,190,12.0
-2234,0.046,,451,Panorama Wheat Ale,American Pale Wheat Ale,190,12.0
-2235,0.063,69.0,2497,Wobble,American IPA,74,16.0
-2236,0.057999999999999996,43.0,2246,Night Cat,American Dark Wheat Ale,74,12.0
-2237,0.057999999999999996,43.0,1630,Night Cat (2014),American Dark Wheat Ale,74,12.0
-2238,0.051,17.0,1284,Dog Days Lager,Dortmunder / Export Lager,74,12.0
-2239,0.051,36.0,1121,Sidekick Extra Pale Ale,American Pale Ale (APA),74,12.0
-2240,0.077,23.0,1042,Atom Smasher,Märzen / Oktoberfest,74,12.0
-2241,0.045,,1041,Testudo,Bière de Garde,74,12.0
-2242,0.065,,1040,Hobnob B & B Pale Ale,American Pale Ale (APA),74,12.0
-2243,0.07,68.0,861,Cane and Ebel,American Strong Ale,74,12.0
-2244,0.065,,642,Outlaw IPA (2015),American IPA,74,12.0
-2245,0.045,,2037,The Gilded Age,Munich Helles Lager,243,12.0
-2246,0.05,,1285,No Limits Hefeweizen,Hefeweizen,435,16.0
-2247,0.06,,1189,Honeyspot Road White IPA,American White IPA,435,12.0
-2248,0.07200000000000001,,1171,Road 2 Ruin Double IPA,American Double / Imperial IPA,435,12.0
-2249,0.048,,1170,Workers Comp Saison,Saison / Farmhouse Ale,435,12.0
-2250,0.05,,1169,Ol' Factory Pils,German Pilsener,435,12.0
-2251,0.05,10.0,2310,PUNK'N,Pumpkin Ale,159,12.0
-2252,0.04,22.0,2100,Yard Sale Winter Lager,American Amber / Red Lager,159,12.0
-2253,0.04,42.0,1925,Trader Session IPA,American IPA,159,12.0
-2254,0.073,83.0,1723,Hop Nosh IPA,American IPA,159,12.0
-2255,0.04,17.0,1212,SUM'R,American Blonde Ale,159,12.0
-2256,0.04,32.0,1097,Organic Baba Black Lager,Schwarzbier,159,12.0
-2257,0.073,82.0,1089,Hop Notch IPA (2013),American IPA,159,12.0
-2258,0.04,34.0,1088,Cutthroat Pale Ale,American Pale Ale (APA),159,12.0
-2259,0.04,29.0,974,WYLD Extra Pale Ale,American Pale Ale (APA),159,12.0
-2260,0.055,,98,Pilsner Ukiah,German Pilsener,555,12.0
-2261,0.06,75.0,2372,The Green Room,American IPA,126,16.0
-2262,0.047,25.0,2367,Humbucker Helles,Maibock / Helles Bock,126,16.0
-2263,0.065,,1704,Uncle John's Apple Cherry Cider,Cider,338,16.0
-2264,0.065,,1703,Uncle John's Apricot Apple Cider,Cider,338,16.0
-2265,0.065,,877,Draught Hard Apple Cider,Cider,338,16.0
-2266,0.001,,606,Scotty K NA,Low Alcohol Beer,522,16.0
-2267,0.068,,543,Bacon Brown Ale,American Brown Ale,522,16.0
-2268,0.064,,347,Golden State Ale,Belgian Pale Ale,522,16.0
-2269,0.078,,346,Baltic Porter,Baltic Porter,522,16.0
-2270,0.085,,25,Siamese twin,Dubbel,522,16.0
-2271,0.085,90.0,2507,Double Duckpin,American Double / Imperial IPA,71,12.0
-2272,0.042,10.0,2506,Old Pro,Gose,71,12.0
-2273,0.055,,829,Duckpin Pale Ale,American Pale Ale (APA),71,12.0
-2274,0.06,,582,Balt Altbier,Altbier,71,12.0
-2275,0.045,50.0,2190,Campside Session IPA,American IPA,202,16.0
-2276,0.045,15.0,1951,Upland Wheat Ale,Witbier,202,16.0
-2277,0.06,,1950,Dragonfly IPA,American IPA,202,16.0
-2278,0.128,,2565,Lee Hill Series Vol. 5 - Belgian Style Quadrupel Ale,Quadrupel (Quad),51,19.2
-2279,0.10400000000000001,,2564,Lee Hill Series Vol. 4 - Manhattan Style Rye Ale,Rye Beer,51,19.2
-2280,0.068,24.0,2563,Lee Hill Series Vol. 2 - Wild Saison,American Wild Ale,51,19.2
-2281,0.099,51.0,2562,Lee Hill Series Vol. 3 - Barrel Aged Imperial Stout,American Double / Imperial Stout,51,19.2
-2282,0.076,,2561,Lee Hill Series Vol. 1 - Barrel Aged Brown Ale,American Brown Ale,51,19.2
-2283,0.06,,2560,Blood Orange Saison,Saison / Farmhouse Ale,51,12.0
-2284,0.065,33.0,1932,Thai Style White IPA,American White IPA,51,12.0
-2285,0.075,30.0,1853,Ferus Fluxus Wild Belgian Pale Ale,American Wild Ale,51,19.2
-2286,0.099,90.0,1315,Upslope Imperial India Pale Ale,American Double / Imperial IPA,51,19.2
-2287,0.08199999999999999,,907,Upslope Christmas Ale,Winter Warmer,51,16.0
-2288,0.077,,906,Upslope Pumpkin Ale,Pumpkin Ale,51,16.0
-2289,0.075,30.0,683,Upslope Belgian Style Pale Ale,Belgian Pale Ale,51,12.0
-2290,0.069,,614,Upslope Foreign Style Stout,Foreign / Export Stout,51,12.0
-2291,0.048,15.0,466,Top Rope Mexican-style Craft Lager,Vienna Lager,51,12.0
-2292,0.048,22.0,444,Upslope Craft Lager,Vienna Lager,51,12.0
-2293,0.067,,345,Upslope Brown Ale,English Brown Ale,51,12.0
-2294,0.057999999999999996,,80,Upslope Pale Ale,American Pale Ale (APA),51,12.0
-2295,0.07200000000000001,,79,Upslope India Pale Ale,American IPA,51,12.0
-2296,0.053,22.0,382,Common Sense Kentucky Common Ale,American Brown Ale,546,16.0
-2297,0.065,70.0,381,Upstate I.P.W.,American IPA,546,12.0
-2298,0.04,,1826,Squatters Full Suspension Pale Ale,American Pale Ale (APA),302,12.0
-2299,0.09,75.0,1825,Squatters Hop Rising Double IPA,American Double / Imperial IPA,302,12.0
-2300,0.08,,1824,Devastator Double Bock,Doppelbock,302,12.0
-2301,0.06,,1823,Wasatch Ghostrider White IPA,American White IPA,302,12.0
-2302,0.06,,1682,Wasatch Ghostrider White IPA (2014),American White IPA,302,12.0
-2303,0.04,,1681,Wasatch Apricot Hefeweizen,Fruit / Vegetable Beer,302,12.0
-2304,0.09,75.0,1680,Squatters Hop Rising Double IPA (2014),American Double / Imperial IPA,302,12.0
-2305,0.04,,1679,Squatters Full Suspension Pale Ale,American Pale Ale (APA),302,12.0
-2306,0.068,,2245,Nunica Pine,Cider,185,16.0
-2307,0.069,,2244,Ginger Peach,Cider,185,16.0
-2308,0.068,,1378,Totally Roasted,Cider,185,16.0
-2309,0.068,,1377,Blue Gold,Cider,185,16.0
-2310,0.068,,1376,Hard Apple,Cider,185,16.0
-2311,0.052000000000000005,,2411,Nitro Can Coffee Stout,American Stout,113,12.0
-2312,0.092,25.0,1770,Voodoo Love Child,Tripel,322,12.0
-2313,0.079,23.0,1769,White Magick of the Sun,Witbier,322,12.0
-2314,0.075,31.0,1730,Wynona's Big Brown Ale,American Brown Ale,322,12.0
-2315,0.092,25.0,1729,Gran Met,Belgian Strong Pale Ale,322,12.0
-2316,0.073,85.0,1603,Good Vibes IPA,American IPA,322,12.0
-2317,0.075,85.0,1488,Pilzilla,American Double / Imperial Pilsner,322,12.0
-2318,0.04,37.0,1846,Wachusett Light IPA,American IPA,295,12.0
-2319,0.06,55.0,1845,Green Monsta IPA,American IPA,295,12.0
-2320,0.055999999999999994,50.0,1844,Wachusett IPA,American IPA,295,12.0
-2321,0.047,,1843,Strawberry White,Witbier,295,12.0
-2322,0.085,85.0,1418,Larry Imperial IPA,American Double / Imperial IPA,295,12.0
-2323,0.047,,1038,Wachusett Summer,American Pale Wheat Ale,295,12.0
-2324,0.051,17.0,1030,Country Pale Ale,English Pale Ale,295,12.0
-2325,0.04,37.0,1029,Wachusett Light IPA (2013),American IPA,295,12.0
-2326,0.052000000000000005,20.0,908,Pumpkan,Pumpkin Ale,295,12.0
-2327,0.045,10.0,619,Wachusett Blueberry Ale,Fruit / Vegetable Beer,295,12.0
-2328,0.06,55.0,618,Green Monsta IPA,American IPA,295,12.0
-2329,0.047,,780,T-6 Red Ale (2004),American Amber / Red Ale,506,12.0
-2330,0.052000000000000005,67.0,2450,Self Starter,American IPA,94,16.0
-2331,0.054000000000000006,20.0,2223,Ermal's,Cream Ale,94,16.0
-2332,0.07,,2222,10 Ton,Oatmeal Stout,94,16.0
-2333,0.07,,2221,Flyin' Rye,American IPA,94,16.0
-2334,0.09,,2439,Christmas Ale,Herbed / Spiced Beer,100,12.0
-2335,0.07,,2356,Pay It Forward Cocoa Porter,American Porter,100,12.0
-2336,0.055,,1069,West Sixth Amber Ale,American Amber / Red Ale,100,12.0
-2337,,,652,West Sixth IPA,American IPA,100,12.0
-2338,0.055,,1542,One Claw,American Pale Ale (APA),384,12.0
-2339,0.04,5.0,1312,Westbrook Gose,Gose,384,12.0
-2340,0.05,16.0,576,White Thai,Witbier,384,12.0
-2341,0.068,65.0,575,Westbrook IPA,American IPA,384,12.0
-2342,0.057,22.0,1645,Westfield Octoberfest,Märzen / Oktoberfest,351,12.0
-2343,0.052000000000000005,,1551,Pop's Old Fashioned Lager,American Amber / Red Lager,351,12.0
-2344,0.057999999999999996,55.0,1550,Charlie in the Rye,American IPA,351,12.0
-2345,,,2364,Royal Lager,American Pale Lager,132,16.0
-2346,0.08,,2348,Rip Van Winkle (Current),Bock,132,12.0
-2347,,,2344,O’Malley’s Stout,English Stout,132,12.0
-2348,0.075,89.0,2343,O’Malley’s IPA,American IPA,132,12.0
-2349,,,2342,O’Malley’s Irish Style Cream Ale,Cream Ale,132,12.0
-2350,0.049,28.0,2341,L'il Lucy's Hot Pepper Ale,Chile Beer,132,12.0
-2351,0.052000000000000005,,2340,Drop Kick Ale,American Amber / Red Ale,132,12.0
-2352,0.055,,2573,Raspberry Berliner Weisse,Berliner Weissbier,47,12.0
-2353,0.05,,2572,Hop Session,American IPA,47,12.0
-2354,0.055,,2571,Blueberry Berliner Weisse,Berliner Weissbier,47,12.0
-2355,0.055,,2570,Berliner Weisse,Berliner Weissbier,47,12.0
-2356,0.06,,1498,Super G IPA,American IPA,396,16.0
-2357,0.049,30.0,1838,Hefe Lemon,Radler,296,12.0
-2358,0.049,30.0,1837,Hefe Black,Hefeweizen,296,12.0
-2359,0.049,30.0,1836,Widmer Brothers Hefeweizen,Hefeweizen,296,12.0
-2360,0.08199999999999999,100.0,1619,Hop Slayer Double IPA,American Double / Imperial IPA,361,12.0
-2361,0.045,,1618,Pumpkin Ale,Pumpkin Ale,361,12.0
-2362,0.05,,1364,Big Bowl Blonde Ale,American Brown Ale,361,12.0
-2363,0.052000000000000005,27.0,971,Phat Chance,American Blonde Ale,361,12.0
-2364,0.08199999999999999,100.0,740,Hop Slayer Double IPA (2011),American Double / Imperial IPA,361,12.0
-2365,0.08199999999999999,100.0,430,Hop Slayer Double IPA (2011),American Double / Imperial IPA,361,12.0
-2366,0.042,13.0,398,Wild Onion Summer Wit,Witbier,361,12.0
-2367,0.06,23.0,366,Jack Stout,Oatmeal Stout,361,12.0
-2368,0.045,,334,Wild Onion Pumpkin Ale (2010),Pumpkin Ale,361,12.0
-2369,0.055999999999999994,41.0,162,Paddy Pale Ale,American Pale Ale (APA),361,12.0
-2370,0.068,21.0,2253,Blonde Hunny,Belgian Pale Ale,181,12.0
-2371,0.057,20.0,1318,Wild Wolf Wee Heavy Scottish Style Ale,Scotch Ale / Wee Heavy,181,12.0
-2372,0.045,25.0,1195,Wild Wolf American Pilsner,American Pilsner,181,12.0
-2373,0.051,45.0,1194,Alpha Ale,American Pale Ale (APA),181,12.0
-2374,0.054000000000000006,,826,Mystical Stout,Irish Dry Stout,499,16.0
-2375,0.075,,825,Bodacious Bock,Bock,499,16.0
-2376,0.05,,813,Ambitious Lager,Munich Helles Lager,499,16.0
-2377,0.07200000000000001,,324,Wyoming Pale Ale,American Pale Ale (APA),550,16.0
-2378,0.05,,323,Wind River Blonde Ale,American Blonde Ale,550,16.0
-2379,0.07400000000000001,83.0,762,Ace IPA,American IPA,509,16.0
-2380,0.08,31.0,761,P-51 Porter,American Porter,509,16.0
-2381,0.055,,2149,#001 Golden Amber Lager,American Amber / Red Lager,211,12.0
-2382,0.071,60.0,2148,#002 American I.P.A.,American IPA,211,12.0
-2383,0.052000000000000005,,2147,#003 Brown & Robust Porter,American Porter,211,12.0
-2384,0.048,38.0,2146,#004 Session I.P.A.,American IPA,211,12.0
-2385,0.059000000000000004,,2047,Tarasque,Saison / Farmhouse Ale,239,12.0
-2386,0.062,61.0,1470,Ananda India Pale Ale,American IPA,239,12.0
-2387,0.045,23.0,1469,Tiny Bomb,American Pilsner,239,12.0
-2388,0.057999999999999996,72.0,2627,Train Hopper,American IPA,14,12.0
-2389,0.045,,2626,Edward’s Portly Brown,American Brown Ale,14,12.0
-2390,0.059000000000000004,135.0,1676,Troopers Alley IPA,American IPA,344,12.0
-2391,0.047,15.0,1468,Wolverine Premium Lager,American Pale Lager,402,12.0
-2392,0.05,,822,Woodchuck Amber Hard Cider,Cider,501,12.0
-2393,0.065,82.0,2417,4000 Footer IPA,American IPA,109,12.0
-2394,0.027999999999999997,15.0,2306,Summer Brew,American Pilsner,109,12.0
-2395,0.065,69.0,1697,Be Hoppy IPA,American IPA,339,16.0
-2396,0.069,69.0,2194,Worthy IPA,American IPA,199,12.0
-2397,0.045,25.0,1514,Easy Day Kolsch,Kölsch,199,12.0
-2398,0.077,30.0,1513,Lights Out Vanilla Cream Extra Stout,American Double / Imperial IPA,199,12.0
-2399,0.069,69.0,1512,Worthy IPA (2013),American IPA,199,12.0
-2400,0.06,50.0,1511,Worthy Pale,American Pale Ale (APA),199,12.0
-2401,0.042,,1345,Patty's Chile Beer,Chile Beer,424,12.0
-2402,0.08199999999999999,,1316,Colorojo Imperial Red Ale,American Strong Ale,424,12.0
-2403,0.055,,1045,Wynkoop Pumpkin Ale,Pumpkin Ale,424,12.0
-2404,0.075,,1035,Rocky Mountain Oyster Stout,American Stout,424,12.0
-2405,0.067,45.0,928,Belgorado,Belgian IPA,424,12.0
-2406,0.052000000000000005,,807,Rail Yard Ale,American Amber / Red Ale,424,12.0
-2407,0.055,,620,B3K Black Lager,Schwarzbier,424,12.0
-2408,0.055,40.0,145,Silverback Pale Ale,American Pale Ale (APA),424,12.0
-2409,0.052000000000000005,,84,Rail Yard Ale (2009),American Amber / Red Ale,424,12.0
diff --git a/data/.ipynb_checkpoints/experiment-checkpoint.csv b/data/.ipynb_checkpoints/experiment-checkpoint.csv
deleted file mode 100644
index 11e2115..0000000
--- a/data/.ipynb_checkpoints/experiment-checkpoint.csv
+++ /dev/null
@@ -1,101 +0,0 @@
-h,p1,p2,p3
-0.049932,0.196199,0.187707,0.192456
-0.141180,0.560334,0.530930,0.577945
-0.913031,3.547039,3.874131,3.566819
-1.093637,4.670684,3.950131,4.645236
-1.661272,6.277652,7.273146,7.171237
-3.624861,15.775701,14.068987,15.426168
-4.032482,16.767783,16.947008,17.658178
-4.250714,18.042570,17.118080,16.678498
-4.875576,18.136630,19.329691,18.401925
-6.088597,24.744785,22.746466,22.445222
-9.602248,37.417542,35.088121,34.748649
-10.035888,39.297119,41.240388,40.338300
-10.452520,39.626886,44.377888,40.713840
-10.481946,39.795751,39.427448,42.345483
-10.822528,44.939463,45.371759,41.828790
-11.569609,48.602001,49.421002,42.908949
-12.334063,53.390793,47.746862,46.949651
-12.959138,47.845502,54.245413,54.064298
-14.422266,56.994099,59.480047,60.958941
-17.492100,69.014920,74.581125,68.034573
-17.981319,78.336610,68.189151,75.391291
-18.755133,78.381981,69.517353,78.555133
-19.047697,72.103361,77.393672,81.748728
-20.366922,76.840793,84.787783,86.341778
-23.067483,95.663609,99.634741,87.847719
-23.240658,99.171921,92.543822,101.103875
-24.655419,95.109064,93.691074,100.208127
-25.043780,108.285545,94.775678,90.218298
-26.374133,98.941293,100.845653,100.237459
-26.769737,111.373057,99.324055,109.743478
-26.772322,99.746607,100.613252,98.530511
-27.067196,109.890066,119.048087,116.510935
-28.247690,114.368918,119.289241,102.304873
-28.642185,124.212106,116.537663,113.620222
-31.496408,120.900830,131.293339,116.107435
-31.982666,127.879163,130.572299,131.147564
-33.111762,121.279171,120.113602,131.114341
-34.355644,125.286768,136.671883,144.349496
-34.790331,126.059745,147.824782,132.356239
-35.785156,140.373228,151.040668,131.705751
-37.458429,160.217563,151.163621,160.654964
-37.928632,156.627204,147.679349,150.296704
-39.721063,173.782204,171.659043,172.123590
-41.643937,179.195933,172.347010,181.489268
-42.300531,156.605007,165.630186,178.604017
-43.430193,170.765540,158.619790,157.279655
-47.398594,186.404993,200.238183,206.501188
-47.724599,203.733090,185.366594,179.715886
-47.817127,204.484496,202.495723,172.331808
-48.027619,192.412101,206.279699,201.373067
-48.826644,177.512226,190.514951,201.130324
-49.299424,211.827328,203.276358,187.960828
-52.104066,210.758777,218.292594,191.446215
-52.142947,213.806118,218.867125,202.662066
-53.212175,197.239640,215.992361,221.640417
-54.504915,224.322887,220.146996,227.662649
-55.278452,238.696786,226.316743,234.092386
-55.305488,225.883993,224.599702,205.332899
-56.091869,207.254009,215.746382,202.673678
-56.167207,204.729897,216.242605,223.984548
-56.348567,232.585118,240.237360,246.246572
-56.379584,220.521441,228.468731,231.747763
-57.392164,230.836225,207.971598,209.124592
-60.277349,226.054012,258.425060,255.061088
-61.931665,242.885050,265.902696,226.184565
-63.205597,248.028617,237.769008,229.041938
-63.652389,277.614744,236.659121,271.875765
-66.299178,282.031280,289.222494,267.309998
-67.249607,289.398388,266.576907,251.954574
-67.298164,263.458986,246.531934,258.722055
-69.744554,298.690795,294.848200,273.055922
-69.760584,273.324355,299.990792,296.395633
-71.668698,279.904239,260.280781,276.410599
-71.686355,291.423302,301.449044,290.537597
-75.690269,288.668723,293.882926,309.836905
-79.459812,314.371188,333.854133,347.408133
-79.629445,308.280816,314.401765,321.353537
-80.010133,335.289807,347.881948,348.799072
-80.410612,324.765207,328.408955,320.749797
-81.834847,341.517372,358.659400,295.042067
-83.037712,362.599102,344.889181,301.405945
-84.658452,341.689789,306.863638,318.253142
-85.709400,329.388281,370.191938,329.439166
-85.970707,350.996065,315.850234,371.911395
-87.153608,369.587232,322.949477,382.816501
-88.351375,340.660590,379.037444,369.511053
-89.467319,384.559285,348.019397,357.951639
-90.523925,358.760503,347.363928,386.906841
-92.629099,355.066098,357.572391,363.760323
-93.740193,407.631276,345.691189,408.661460
-94.468092,381.967904,410.552443,340.129353
-96.145283,415.519141,409.792458,418.384232
-96.573020,354.554374,378.851115,364.829722
-97.089370,404.316874,413.689272,355.404488
-97.169532,362.355950,393.974083,422.498388
-97.252983,417.474419,387.274184,418.045115
-97.960874,395.805214,382.839222,374.246981
-98.476252,375.103335,406.672300,369.685730
-98.915110,392.460265,358.656764,414.427542
-99.267371,404.420831,402.143805,418.501915
diff --git a/data/.ipynb_checkpoints/land_global_temperature_anomaly-1880-2016-checkpoint.csv b/data/.ipynb_checkpoints/land_global_temperature_anomaly-1880-2016-checkpoint.csv
deleted file mode 100644
index 749296e..0000000
--- a/data/.ipynb_checkpoints/land_global_temperature_anomaly-1880-2016-checkpoint.csv
+++ /dev/null
@@ -1,142 +0,0 @@
-Global Land Temperature Anomalies, January-December
-Units: Degrees Celsius
-Base Period: 1901-2000
-Missing: -999.0000
-Year,Value
-1880,-0.47
-1881,-0.45
-1882,-0.41
-1883,-0.60
-1884,-0.60
-1885,-0.52
-1886,-0.48
-1887,-0.47
-1888,-0.46
-1889,-0.31
-1890,-0.49
-1891,-0.55
-1892,-0.52
-1893,-0.56
-1894,-0.35
-1895,-0.40
-1896,-0.27
-1897,-0.29
-1898,-0.37
-1899,-0.18
-1900,-0.13
-1901,-0.09
-1902,-0.33
-1903,-0.39
-1904,-0.46
-1905,-0.42
-1906,-0.20
-1907,-0.60
-1908,-0.49
-1909,-0.39
-1910,-0.33
-1911,-0.44
-1912,-0.51
-1913,-0.34
-1914,-0.07
-1915,-0.07
-1916,-0.36
-1917,-0.51
-1918,-0.37
-1919,-0.32
-1920,-0.28
-1921,-0.06
-1922,-0.24
-1923,-0.21
-1924,-0.26
-1925,-0.10
-1926,0.01
-1927,-0.15
-1928,-0.10
-1929,-0.40
-1930,-0.08
-1931,-0.03
-1932,-0.02
-1933,-0.34
-1934,-0.02
-1935,-0.14
-1936,-0.12
-1937,-0.03
-1938,0.17
-1939,0.09
-1940,0.04
-1941,0.11
-1942,0.07
-1943,0.09
-1944,0.21
-1945,-0.08
-1946,-0.01
-1947,0.06
-1948,0.06
-1949,-0.05
-1950,-0.33
-1951,-0.07
-1952,-0.08
-1953,0.17
-1954,-0.16
-1955,-0.13
-1956,-0.42
-1957,-0.05
-1958,0.13
-1959,0.05
-1960,-0.04
-1961,0.10
-1962,0.16
-1963,0.21
-1964,-0.24
-1965,-0.13
-1966,-0.07
-1967,-0.00
-1968,-0.11
-1969,-0.10
-1970,0.02
-1971,-0.04
-1972,-0.18
-1973,0.29
-1974,-0.21
-1975,0.12
-1976,-0.25
-1977,0.21
-1978,0.08
-1979,0.15
-1980,0.27
-1981,0.49
-1982,0.09
-1983,0.49
-1984,0.05
-1985,0.07
-1986,0.28
-1987,0.41
-1988,0.55
-1989,0.39
-1990,0.59
-1991,0.53
-1992,0.26
-1993,0.35
-1994,0.45
-1995,0.77
-1996,0.35
-1997,0.68
-1998,0.96
-1999,0.80
-2000,0.64
-2001,0.83
-2002,0.94
-2003,0.89
-2004,0.81
-2005,1.05
-2006,0.92
-2007,1.10
-2008,0.87
-2009,0.88
-2010,1.09
-2011,0.91
-2012,0.92
-2013,1.01
-2014,1.02
-2015,1.35
-2016,1.45
diff --git a/data/.ipynb_checkpoints/primary-energy-consumption-by-region-checkpoint.csv b/data/.ipynb_checkpoints/primary-energy-consumption-by-region-checkpoint.csv
deleted file mode 100644
index facd19c..0000000
--- a/data/.ipynb_checkpoints/primary-energy-consumption-by-region-checkpoint.csv
+++ /dev/null
@@ -1,5066 +0,0 @@
-Entity,Code,Year,Primary Energy Consumption (terawatt-hours)
-Africa,,1965,710.9496218370446
-Africa,,1966,742.3557894211085
-Africa,,1967,750.4345544205105
-Africa,,1968,791.0998844157018
-Africa,,1969,807.9623052554762
-Africa,,1970,875.8575993480164
-Africa,,1971,951.3538360556091
-Africa,,1972,1011.5591171299385
-Africa,,1973,1087.611638468385
-Africa,,1974,1142.4470925130538
-Africa,,1975,1209.361200720239
-Africa,,1976,1316.082352326862
-Africa,,1977,1384.1726687059763
-Africa,,1978,1437.690751907023
-Africa,,1979,1567.8167111229407
-Africa,,1980,1688.4608236158724
-Africa,,1981,1882.3847187089277
-Africa,,1982,2010.4197830152507
-Africa,,1983,2065.874518832706
-Africa,,1984,2136.94122794506
-Africa,,1985,2217.8016016972447
-Africa,,1986,2269.3208429987676
-Africa,,1987,2340.164150562731
-Africa,,1988,2508.9537976665138
-Africa,,1989,2516.310250001407
-Africa,,1990,2597.4525020354927
-Africa,,1991,2594.732004911744
-Africa,,1992,2638.661744244721
-Africa,,1993,2649.1260676244697
-Africa,,1994,2727.1853143504954
-Africa,,1995,2837.7403384537865
-Africa,,1996,2914.1053605107545
-Africa,,1997,2969.5663494548953
-Africa,,1998,3015.0363850147273
-Africa,,1999,3106.265531917238
-Africa,,2000,3179.78678924349
-Africa,,2001,3306.5696263568316
-Africa,,2002,3344.0058205715295
-Africa,,2003,3504.9254473059495
-Africa,,2004,3757.6515298153213
-Africa,,2005,3786.0332515163486
-Africa,,2006,3855.000009214428
-Africa,,2007,3994.037595619741
-Africa,,2008,4249.897933458425
-Africa,,2009,4326.0884858189065
-Africa,,2010,4464.043502961286
-Africa,,2011,4481.371714602618
-Africa,,2012,4643.128590988004
-Africa,,2013,4765.0683798958
-Africa,,2014,4914.695261020759
-Africa,,2015,5001.8845992674505
-Africa,,2016,5110.664038390359
-Africa,,2017,5217.289746039103
-Africa,,2018,5367.396523588756
-Algeria,DZA,1965,24.684921944444447
-Algeria,DZA,1966,29.736455277777825
-Algeria,DZA,1967,28.10500111111115
-Algeria,DZA,1968,30.145581388888942
-Algeria,DZA,1969,33.425377499999996
-Algeria,DZA,1970,36.57900583333339
-Algeria,DZA,1971,39.617660277777766
-Algeria,DZA,1972,44.49832916666663
-Algeria,DZA,1973,53.01575250000003
-Algeria,DZA,1974,58.753500833333355
-Algeria,DZA,1975,70.26040750000004
-Algeria,DZA,1976,81.96365250000001
-Algeria,DZA,1977,90.12660361111114
-Algeria,DZA,1978,113.29676472222219
-Algeria,DZA,1979,148.44730722222283
-Algeria,DZA,1980,177.05753999999953
-Algeria,DZA,1981,215.05758277777784
-Algeria,DZA,1982,247.95175777777746
-Algeria,DZA,1983,270.8881611111113
-Algeria,DZA,1984,260.05752638888856
-Algeria,DZA,1985,262.08636305555564
-Algeria,DZA,1986,277.40919890350864
-Algeria,DZA,1987,285.00572178362546
-Algeria,DZA,1988,305.36227755848006
-Algeria,DZA,1989,296.99472795321674
-Algeria,DZA,1990,314.92979899122815
-Algeria,DZA,1991,311.99973874268983
-Algeria,DZA,1992,320.1621297660822
-Algeria,DZA,1993,297.88011403508824
-Algeria,DZA,1994,301.8670879385967
-Algeria,DZA,1995,313.08202751461937
-Algeria,DZA,1996,309.8808028801176
-Algeria,DZA,1997,297.8353478654977
-Algeria,DZA,1998,308.2790275292403
-Algeria,DZA,1999,311.36811635964966
-Algeria,DZA,2000,299.9280724853802
-Algeria,DZA,2001,310.7918378362579
-Algeria,DZA,2002,321.9341547222222
-Algeria,DZA,2003,336.8509539766079
-Algeria,DZA,2004,349.71503409356706
-Algeria,DZA,2005,366.14279568947325
-Algeria,DZA,2006,379.17351232894794
-Algeria,DZA,2007,399.5954578470893
-Algeria,DZA,2008,423.5064182373826
-Algeria,DZA,2009,448.8042344444447
-Algeria,DZA,2010,437.40561552631607
-Algeria,DZA,2011,464.43794581871373
-Algeria,DZA,2012,507.6259857085637
-Algeria,DZA,2013,536.9648394736848
-Algeria,DZA,2014,585.59359383041
-Algeria,DZA,2015,617.5044838040936
-Algeria,DZA,2016,616.8577568181724
-Algeria,DZA,2017,617.8796480716378
-Algeria,DZA,2018,659.5842167982457
-Argentina,ARG,1965,313.01496299896394
-Argentina,ARG,1966,323.4269603163651
-Argentina,ARG,1967,333.0293933353713
-Argentina,ARG,1968,344.52213755060313
-Argentina,ARG,1969,356.3979989293926
-Argentina,ARG,1970,336.54109831353884
-Argentina,ARG,1971,357.59899969629384
-Argentina,ARG,1972,364.0100019653057
-Argentina,ARG,1973,379.4433612945737
-Argentina,ARG,1974,395.4679586146552
-Argentina,ARG,1975,384.6591402250331
-Argentina,ARG,1976,405.72852087430164
-Argentina,ARG,1977,424.5512826046247
-Argentina,ARG,1978,432.563602482013
-Argentina,ARG,1979,458.3900799019945
-Argentina,ARG,1980,457.2440729921701
-Argentina,ARG,1981,440.661998142562
-Argentina,ARG,1982,451.3141576524524
-Argentina,ARG,1983,470.90888597572246
-Argentina,ARG,1984,469.5989507919085
-Argentina,ARG,1985,458.60820974669116
-Argentina,ARG,1986,506.52557818621466
-Argentina,ARG,1987,529.2651176665332
-Argentina,ARG,1988,538.938859470584
-Argentina,ARG,1989,515.97354409023
-Argentina,ARG,1990,509.5785992202937
-Argentina,ARG,1991,515.5174180442012
-Argentina,ARG,1992,554.4296666921838
-Argentina,ARG,1993,571.780050744056
-Argentina,ARG,1994,581.7401100449149
-Argentina,ARG,1995,605.5834418661485
-Argentina,ARG,1996,649.2325236711686
-Argentina,ARG,1997,644.4973381871645
-Argentina,ARG,1998,668.4856838458692
-Argentina,ARG,1999,654.4723212369857
-Argentina,ARG,2000,680.1464031073946
-Argentina,ARG,2001,672.1997575838614
-Argentina,ARG,2002,640.7068305958256
-Argentina,ARG,2003,688.6550791353284
-Argentina,ARG,2004,726.7201435437893
-Argentina,ARG,2005,775.7798291472524
-Argentina,ARG,2006,815.8156553211016
-Argentina,ARG,2007,852.9581254886125
-Argentina,ARG,2008,868.2759225062638
-Argentina,ARG,2009,852.3020688601055
-Argentina,ARG,2010,897.632885972413
-Argentina,ARG,2011,915.5681227302288
-Argentina,ARG,2012,942.2604514311959
-Argentina,ARG,2013,982.6040098322283
-Argentina,ARG,2014,978.4022981521706
-Argentina,ARG,2015,1001.3302034887311
-Argentina,ARG,2016,999.2181065296804
-Argentina,ARG,2017,1001.3857253097067
-Argentina,ARG,2018,989.1598669446079
-Asia Pacific,,1965,5135.237611123247
-Asia Pacific,,1966,5615.9561930005175
-Asia Pacific,,1967,5885.708835984587
-Asia Pacific,,1968,6327.74005936363
-Asia Pacific,,1969,7208.321129955075
-Asia Pacific,,1970,8197.82993761301
-Asia Pacific,,1971,8971.673288008604
-Asia Pacific,,1972,9512.956347692863
-Asia Pacific,,1973,10293.739388263812
-Asia Pacific,,1974,10492.027434247144
-Asia Pacific,,1975,10885.766862062637
-Asia Pacific,,1976,11435.314403207325
-Asia Pacific,,1977,12063.522072120442
-Asia Pacific,,1978,12865.552992497078
-Asia Pacific,,1979,13462.980033905915
-Asia Pacific,,1980,13584.492010882585
-Asia Pacific,,1981,13665.634540948055
-Asia Pacific,,1982,13802.453601851526
-Asia Pacific,,1983,14428.214034161843
-Asia Pacific,,1984,15429.01462438926
-Asia Pacific,,1985,16233.678880555452
-Asia Pacific,,1986,16929.323097351637
-Asia Pacific,,1987,17883.154329458797
-Asia Pacific,,1988,19186.860997557258
-Asia Pacific,,1989,20232.268375288753
-Asia Pacific,,1990,21068.683227376583
-Asia Pacific,,1991,22050.251168867693
-Asia Pacific,,1992,23070.765742916952
-Asia Pacific,,1993,24287.226124183893
-Asia Pacific,,1994,25629.83661682342
-Asia Pacific,,1995,26815.562505780734
-Asia Pacific,,1996,28063.274272156727
-Asia Pacific,,1997,28926.13341439491
-Asia Pacific,,1998,28853.823401517922
-Asia Pacific,,1999,30020.041731266392
-Asia Pacific,,2000,31113.842695311683
-Asia Pacific,,2001,32137.063623390717
-Asia Pacific,,2002,33796.87585845572
-Asia Pacific,,2003,36633.17648037434
-Asia Pacific,,2004,40130.70734848111
-Asia Pacific,,2005,43369.73939462064
-Asia Pacific,,2006,45937.13277422703
-Asia Pacific,,2007,48849.62466112426
-Asia Pacific,,2008,50197.43811765898
-Asia Pacific,,2009,51388.901659926516
-Asia Pacific,,2010,54678.99138665818
-Asia Pacific,,2011,57620.864304346745
-Asia Pacific,,2012,59564.68647930671
-Asia Pacific,,2013,61341.002858802836
-Asia Pacific,,2014,62681.384756379775
-Asia Pacific,,2015,63682.05659089313
-Asia Pacific,,2016,64976.325083947915
-Asia Pacific,,2017,66849.68780629005
-Asia Pacific,,2018,69615.32381130465
-Australia,AUS,1965,404.18988403508786
-Australia,AUS,1966,443.55216925438623
-Australia,AUS,1967,470.45545456140405
-Australia,AUS,1968,498.94848248538057
-Australia,AUS,1969,519.4448253508773
-Australia,AUS,1970,566.6456486258483
-Australia,AUS,1971,594.9155380013505
-Australia,AUS,1972,622.1784750277434
-Australia,AUS,1973,665.1684946804619
-Australia,AUS,1974,707.1458616619885
-Australia,AUS,1975,718.7814240665318
-Australia,AUS,1976,744.211050388576
-Australia,AUS,1977,781.3206722945035
-Australia,AUS,1978,800.5856379382421
-Australia,AUS,1979,832.3140349254406
-Australia,AUS,1980,838.0664375920799
-Australia,AUS,1981,844.9801408354093
-Australia,AUS,1982,844.6022310607432
-Australia,AUS,1983,846.4926323535063
-Australia,AUS,1984,883.3886700358529
-Australia,AUS,1985,890.0499014105027
-Australia,AUS,1986,920.2190229875002
-Australia,AUS,1987,944.9230590070846
-Australia,AUS,1988,988.8308342894527
-Australia,AUS,1989,1036.6497927934327
-Australia,AUS,1990,1054.887549222008
-Australia,AUS,1991,1048.0126908611594
-Australia,AUS,1992,1058.6286546616063
-Australia,AUS,1993,1088.7986048901844
-Australia,AUS,1994,1132.365856903358
-Australia,AUS,1995,1162.524552947921
-Australia,AUS,1996,1191.8377881175572
-Australia,AUS,1997,1222.0023680410543
-Australia,AUS,1998,1250.5693214796543
-Australia,AUS,1999,1305.306180870178
-Australia,AUS,2000,1310.941737996227
-Australia,AUS,2001,1323.3788124058483
-Australia,AUS,2002,1343.2900607535892
-Australia,AUS,2003,1363.8118525643285
-Australia,AUS,2004,1409.4186713153786
-Australia,AUS,2005,1405.7260394606017
-Australia,AUS,2006,1489.9859885349738
-Australia,AUS,2007,1510.4798947573152
-Australia,AUS,2008,1538.3304902012983
-Australia,AUS,2009,1527.8442325717697
-Australia,AUS,2010,1534.1029636243104
-Australia,AUS,2011,1585.8081676820823
-Australia,AUS,2012,1565.6027545844947
-Australia,AUS,2013,1573.5473710456451
-Australia,AUS,2014,1598.6109661483608
-Australia,AUS,2015,1619.2295892568532
-Australia,AUS,2016,1653.0123656870128
-Australia,AUS,2017,1634.0995887188105
-Australia,AUS,2018,1678.5216783644187
-Austria,AUT,1965,184.26470558555454
-Austria,AUT,1966,192.68538368589222
-Austria,AUT,1967,194.60438173184707
-Austria,AUT,1968,208.32398470244428
-Austria,AUT,1969,216.4862862842099
-Austria,AUT,1970,247.221341493147
-Austria,AUT,1971,247.61070498572187
-Austria,AUT,1972,256.2001997358727
-Austria,AUT,1973,275.25925870277274
-Austria,AUT,1974,275.57137406586224
-Austria,AUT,1975,273.3203797592352
-Austria,AUT,1976,284.20144344044274
-Austria,AUT,1977,283.48820874199816
-Austria,AUT,1978,296.0738418974789
-Austria,AUT,1979,313.07418562991086
-Austria,AUT,1980,311.40114760658315
-Austria,AUT,1981,301.48208899283486
-Austria,AUT,1982,291.26766437950624
-Austria,AUT,1983,290.53557187260543
-Austria,AUT,1984,288.731489856568
-Austria,AUT,1985,302.77975503858397
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-Austria,AUT,1987,321.9955860932325
-Austria,AUT,1988,317.05754248493054
-Austria,AUT,1989,318.9387122910032
-Austria,AUT,1990,324.7771530429641
-Austria,AUT,1991,341.15957327807547
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-Austria,AUT,1993,339.9943112892047
-Austria,AUT,1994,338.1912951284402
-Austria,AUT,1995,354.51748702835175
-Austria,AUT,1996,356.06712881623355
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-Austria,AUT,1998,368.7275547066838
-Austria,AUT,1999,376.35103765204354
-Austria,AUT,2000,377.37849566745973
-Austria,AUT,2001,392.60805102441816
-Austria,AUT,2002,394.27700044478337
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-Austria,AUT,2005,415.61009258325055
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-Austria,AUT,2007,403.1952774140121
-Austria,AUT,2008,412.16756107432354
-Austria,AUT,2009,399.3929250165941
-Austria,AUT,2010,413.5406345743519
-Austria,AUT,2011,386.94648631665393
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-Austria,AUT,2014,387.780423025891
-Austria,AUT,2015,388.73357131081985
-Austria,AUT,2016,401.96892575875705
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-Austria,AUT,2018,407.0015428771737
-Azerbaijan,AZE,1985,234.30933747653486
-Azerbaijan,AZE,1986,252.33484620205385
-Azerbaijan,AZE,1987,244.52614642874866
-Azerbaijan,AZE,1988,244.74513137425663
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-Azerbaijan,AZE,1993,185.05423505429906
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-Azerbaijan,AZE,1996,131.14806528711676
-Azerbaijan,AZE,1997,125.5094601815615
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-Azerbaijan,AZE,2002,124.7272766467425
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-Azerbaijan,AZE,2011,144.88177414190224
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-Azerbaijan,AZE,2017,166.37837289701721
-Azerbaijan,AZE,2018,167.43452350295271
-Bangladesh,BGD,1971,8.135291666666673
-Bangladesh,BGD,1972,15.862670413567232
-Bangladesh,BGD,1973,19.574157651578947
-Bangladesh,BGD,1974,20.241851298654993
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-Bangladesh,BGD,1976,26.335063667777813
-Bangladesh,BGD,1977,27.046376241111076
-Bangladesh,BGD,1978,29.142202096257346
-Bangladesh,BGD,1979,32.27539645877189
-Bangladesh,BGD,1980,36.38836300409356
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-Bangladesh,BGD,1982,40.47115710298066
-Bangladesh,BGD,1983,39.9747705143801
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-Bangladesh,BGD,1989,69.31486952222478
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-Bangladesh,BGD,1991,70.98191547847806
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-Bangladesh,BGD,1998,125.27770154893153
-Bangladesh,BGD,1999,126.7143010805749
-Bangladesh,BGD,2000,135.87709770390524
-Bangladesh,BGD,2001,155.2809235709591
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-Bangladesh,BGD,2003,169.91727084912523
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-Bangladesh,BGD,2005,186.82833421377728
-Bangladesh,BGD,2006,198.2275683076827
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-Bangladesh,BGD,2008,219.0422604351003
-Bangladesh,BGD,2009,239.98236912244283
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-Bangladesh,BGD,2012,291.20121866214816
-Bangladesh,BGD,2013,296.9778933490554
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-Bangladesh,BGD,2015,363.5425430294553
-Bangladesh,BGD,2016,369.3937845083417
-Bangladesh,BGD,2017,383.4701689206792
-Bangladesh,BGD,2018,416.2945268606732
-Belarus,BLR,1985,408.037199970314
-Belarus,BLR,1986,465.83185347326037
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-Belgium,BEL,1965,412.85270352362915
-Belgium,BEL,1966,397.76044266779144
-Belgium,BEL,1967,417.5580761736155
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-Belgium,BEL,2018,723.2607195112448
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-Bulgaria,BGR,1965,119.2800672222225
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-Bulgaria,BGR,1980,333.51243083333384
-Bulgaria,BGR,1981,327.97831861111143
-Bulgaria,BGR,1982,335.91224499999964
-Bulgaria,BGR,1983,337.8003397222224
-Bulgaria,BGR,1984,335.7621872222223
-Bulgaria,BGR,1985,333.44197527777783
-Bulgaria,BGR,1986,340.39818833333356
-Bulgaria,BGR,1987,342.9078944444442
-Bulgaria,BGR,1988,350.2272772222226
-Bulgaria,BGR,1989,347.40305944444447
-Bulgaria,BGR,1990,320.3711162236235
-Bulgaria,BGR,1991,259.82891158714517
-Bulgaria,BGR,1992,244.02604693923504
-Bulgaria,BGR,1993,259.16669909368426
-Bulgaria,BGR,1994,249.18662922488764
-Bulgaria,BGR,1995,267.26183609022
-Bulgaria,BGR,1996,266.9610319021535
-Bulgaria,BGR,1997,252.34085534402334
-Bulgaria,BGR,1998,242.11820892538026
-Bulgaria,BGR,1999,211.74649750462927
-Bulgaria,BGR,2000,212.68176826670978
-Bulgaria,BGR,2001,222.15051066827633
-Bulgaria,BGR,2002,216.04645015149833
-Bulgaria,BGR,2003,223.16354070273252
-Bulgaria,BGR,2004,216.55160473504188
-Bulgaria,BGR,2005,234.3406412940347
-Bulgaria,BGR,2006,240.41774627834582
-Bulgaria,BGR,2007,233.40858291742364
-Bulgaria,BGR,2008,229.91188171325518
-Bulgaria,BGR,2009,202.05253152213854
-Bulgaria,BGR,2010,210.46564307858873
-Bulgaria,BGR,2011,224.1610367864634
-Bulgaria,BGR,2012,213.42368090166207
-Bulgaria,BGR,2013,197.76656927446714
-Bulgaria,BGR,2014,210.87488117817227
-Bulgaria,BGR,2015,224.73845166286068
-Bulgaria,BGR,2016,213.1092028447886
-Bulgaria,BGR,2017,217.9627580507302
-Bulgaria,BGR,2018,216.01844259993587
-CIS,,1965,6900.2211236797875
-CIS,,1966,7337.457098910874
-CIS,,1967,7712.827002860533
-CIS,,1968,7998.801732830085
-CIS,,1969,8361.934967824714
-CIS,,1970,8778.396558836379
-CIS,,1971,9209.745801496534
-CIS,,1972,9680.010832686523
-CIS,,1973,10177.22135540317
-CIS,,1974,10737.970806439833
-CIS,,1975,11269.304362428395
-CIS,,1976,11705.678169876024
-CIS,,1977,12227.220069669815
-CIS,,1978,12724.987091396535
-CIS,,1979,13108.235679323503
-CIS,,1980,13375.669192556437
-CIS,,1981,13659.171705131965
-CIS,,1982,14002.626645411206
-CIS,,1983,14293.511008493257
-CIS,,1984,14823.698121847994
-CIS,,1985,11944.863797017435
-CIS,,1986,12220.178071910548
-CIS,,1987,12579.382770283022
-CIS,,1988,12845.823456809194
-CIS,,1989,12858.238524180191
-CIS,,1990,12636.670927815228
-CIS,,1991,12428.012184721496
-CIS,,1992,11800.65187170192
-CIS,,1993,10976.753402953495
-CIS,,1994,10008.706932546427
-CIS,,1995,9408.11381988839
-CIS,,1996,9102.138395339045
-CIS,,1997,8583.938487518293
-CIS,,1998,8569.008675261504
-CIS,,1999,8672.775460342833
-CIS,,2000,8750.42222019891
-CIS,,2001,8939.395951283499
-CIS,,2002,8921.651760936671
-CIS,,2003,9140.673878902773
-CIS,,2004,9312.232596502265
-CIS,,2005,9341.10737260246
-CIS,,2006,9685.650232652717
-CIS,,2007,9821.11247972684
-CIS,,2008,9823.513781421707
-CIS,,2009,9422.139992300696
-CIS,,2010,9806.723760104664
-CIS,,2011,10211.674294331591
-CIS,,2012,10312.542687371966
-CIS,,2013,10142.767991279588
-CIS,,2014,10237.615544461001
-CIS,,2015,10093.401649075637
-CIS,,2016,10251.522558849783
-CIS,,2017,10365.16120241614
-CIS,,2018,10822.08825091469
-Canada,CAN,1965,1348.043170994157
-Canada,CAN,1966,1430.3929718567285
-Canada,CAN,1967,1500.5786688011642
-Canada,CAN,1968,1601.3981697514644
-Canada,CAN,1969,1689.8741524853785
-Canada,CAN,1970,1809.48834709064
-Canada,CAN,1971,1858.4046527777814
-Canada,CAN,1972,1985.220533888891
-Canada,CAN,1973,2107.8347291666723
-Canada,CAN,1974,2181.284614166671
-Canada,CAN,1975,2157.006520277774
-Canada,CAN,1976,2280.773381593568
-Canada,CAN,1977,2390.4098278947395
-Canada,CAN,1978,2432.4370357017547
-Canada,CAN,1979,2461.247513128656
-Canada,CAN,1980,2520.0166006871405
-Canada,CAN,1981,2450.176331286554
-Canada,CAN,1982,2481.8902076461986
-Canada,CAN,1983,2462.0009687719266
-Canada,CAN,1984,2621.471183888894
-Canada,CAN,1985,2702.529752997078
-Canada,CAN,1986,2706.9277948099475
-Canada,CAN,1987,2800.185833464912
-Canada,CAN,1988,2917.285548947374
-Canada,CAN,1989,2949.7079414612067
-Canada,CAN,1990,2895.3974790842517
-Canada,CAN,1991,2897.9259504578304
-Canada,CAN,1992,2970.9928271682675
-Canada,CAN,1993,3035.4867620154987
-Canada,CAN,1994,3147.3368235080566
-Canada,CAN,1995,3216.175210272886
-Canada,CAN,1996,3304.784668732433
-Canada,CAN,1997,3333.0247059764406
-Canada,CAN,1998,3290.2481468419724
-Canada,CAN,1999,3394.62660495875
-Canada,CAN,2000,3493.812749150524
-Canada,CAN,2001,3417.9234290078975
-Canada,CAN,2002,3530.276415110186
-Canada,CAN,2003,3555.054151083193
-Canada,CAN,2004,3603.5847876988378
-Canada,CAN,2005,3646.97084080329
-Canada,CAN,2006,3609.884124687282
-Canada,CAN,2007,3745.5474805396225
-Canada,CAN,2008,3739.518659739619
-Canada,CAN,2009,3545.817586317525
-Canada,CAN,2010,3628.1428301336123
-Canada,CAN,2011,3805.378810097547
-Canada,CAN,2012,3776.551554692874
-Canada,CAN,2013,3919.5404566545235
-Canada,CAN,2014,3975.2952274734203
-Canada,CAN,2015,3943.070620536991
-Canada,CAN,2016,3933.5391132316045
-Canada,CAN,2017,3997.1930792746493
-Canada,CAN,2018,4005.6529471730537
-Central America,,1965,50.1307920453292
-Central America,,1966,50.921257095351514
-Central America,,1967,53.92517067763239
-Central America,,1968,55.2046321934029
-Central America,,1969,58.988199653913185
-Central America,,1970,61.51682463720886
-Central America,,1971,64.76266275301941
-Central America,,1972,70.24893912006165
-Central America,,1973,73.77818184606231
-Central America,,1974,75.73044128956067
-Central America,,1975,83.19231428299842
-Central America,,1976,86.49689589276808
-Central America,,1977,88.14420483234098
-Central America,,1978,92.00838031497051
-Central America,,1979,93.59081937865494
-Central America,,1980,90.59678660586108
-Central America,,1981,91.72087105824862
-Central America,,1982,91.54077529229423
-Central America,,1983,92.2028833030254
-Central America,,1984,93.23923252753657
-Central America,,1985,95.37411403724015
-Central America,,1986,98.65892148459473
-Central America,,1987,105.11243707224901
-Central America,,1988,104.21577261882268
-Central America,,1989,110.75166136057
-Central America,,1990,114.62824264579469
-Central America,,1991,121.51274388980161
-Central America,,1992,133.3868024510761
-Central America,,1993,143.19517035589877
-Central America,,1994,152.12007689851848
-Central America,,1995,164.33343850792113
-Central America,,1996,166.62998453563935
-Central America,,1997,175.95109187220805
-Central America,,1998,195.56507802126288
-Central America,,1999,201.77512267709096
-Central America,,2000,210.7314467063103
-Central America,,2001,218.5799644813857
-Central America,,2002,221.96820187134279
-Central America,,2003,232.30357805616876
-Central America,,2004,239.32716259722574
-Central America,,2005,241.84086278154018
-Central America,,2006,255.00876497541717
-Central America,,2007,267.60879459558015
-Central America,,2008,274.66594046040683
-Central America,,2009,269.8881560948143
-Central America,,2010,280.93804168293804
-Central America,,2011,295.69703977278874
-Central America,,2012,306.30799529986916
-Central America,,2013,309.4423543108085
-Central America,,2014,319.69295047122296
-Central America,,2015,348.15909454216046
-Central America,,2016,364.05534583229803
-Central America,,2017,373.71259590544815
-Central America,,2018,391.54985600634427
-Chile,CHL,1965,71.74195762971097
-Chile,CHL,1966,76.91124830588326
-Chile,CHL,1967,78.42455336897528
-Chile,CHL,1968,78.34606145265221
-Chile,CHL,1969,84.33722260880837
-Chile,CHL,1970,88.9932722539104
-Chile,CHL,1971,95.09389587719295
-Chile,CHL,1972,97.85985666666674
-Chile,CHL,1973,94.64475858187132
-Chile,CHL,1974,93.38378818713451
-Chile,CHL,1975,84.0978121929825
-Chile,CHL,1976,88.16961387426902
-Chile,CHL,1977,91.17974964912287
-Chile,CHL,1978,96.74526035087725
-Chile,CHL,1979,99.8043595321637
-Chile,CHL,1980,103.00522745614035
-Chile,CHL,1981,105.64603451754382
-Chile,CHL,1982,96.58909770467841
-Chile,CHL,1983,98.59920314327479
-Chile,CHL,1984,103.37846459064326
-Chile,CHL,1985,106.38922906432742
-Chile,CHL,1986,111.10760105263154
-Chile,CHL,1987,116.51286945906388
-Chile,CHL,1988,130.34012307017522
-Chile,CHL,1989,144.28977812865523
-Chile,CHL,1990,152.23109082163774
-Chile,CHL,1991,170.1105996900585
-Chile,CHL,1992,187.7693884766076
-Chile,CHL,1993,198.64430043207702
-Chile,CHL,1994,208.9527299707598
-Chile,CHL,1995,225.1901198479526
-Chile,CHL,1996,239.37982290397622
-Chile,CHL,1997,273.917238490058
-Chile,CHL,1998,275.63879595029175
-Chile,CHL,1999,287.8842225643275
-Chile,CHL,2000,303.70482650292365
-Chile,CHL,2001,305.76062438888914
-Chile,CHL,2002,316.80235921052616
-Chile,CHL,2003,315.46768181578904
-Chile,CHL,2004,332.156366410029
-Chile,CHL,2005,345.35860908829005
-Chile,CHL,2006,369.25425227510163
-Chile,CHL,2007,377.8982604747691
-Chile,CHL,2008,374.18477984536366
-Chile,CHL,2009,366.8952917444191
-Chile,CHL,2010,368.8495662643175
-Chile,CHL,2011,401.26402163280613
-Chile,CHL,2012,410.71511645845857
-Chile,CHL,2013,415.23175642777045
-Chile,CHL,2014,407.9148437146516
-Chile,CHL,2015,417.68823759853814
-Chile,CHL,2016,438.0693707781038
-Chile,CHL,2017,445.52743717217083
-Chile,CHL,2018,466.3308833239992
-China,CHN,1965,1529.0036653957704
-China,CHN,1966,1661.9907588962687
-China,CHN,1967,1494.7608728687312
-China,CHN,1968,1509.2536533824978
-China,CHN,1969,1837.6173492354965
-China,CHN,1970,2353.8764803785607
-China,CHN,1971,2790.6628000122882
-China,CHN,1972,3008.113956796953
-China,CHN,1973,3174.9092337020666
-China,CHN,1974,3273.2002484390355
-China,CHN,1975,3666.250184913959
-China,CHN,1976,3860.4453888864277
-China,CHN,1977,4210.139776497045
-China,CHN,1978,4617.966547109139
-China,CHN,1979,4756.025128485739
-China,CHN,1980,4847.776402951134
-China,CHN,1981,4781.406686645237
-China,CHN,1982,4991.821064334859
-China,CHN,1983,5311.389161962301
-China,CHN,1984,5699.800239165316
-China,CHN,1985,6164.965980173284
-China,CHN,1986,6461.492551096853
-China,CHN,1987,6968.511809871976
-China,CHN,1988,7484.8323002399575
-China,CHN,1989,7853.3489854894415
-China,CHN,1990,7953.984521296604
-China,CHN,1991,8357.540454548287
-China,CHN,1992,8801.081973802606
-China,CHN,1993,9474.6884945488
-China,CHN,1994,10054.439064588985
-China,CHN,1995,10360.687129821961
-China,CHN,1996,10902.323546245718
-China,CHN,1997,10964.571439562
-China,CHN,1998,10979.25961402515
-China,CHN,1999,11365.4160436996
-China,CHN,2000,11757.131164599345
-China,CHN,2001,12417.892187629963
-China,CHN,2002,13533.031574637238
-China,CHN,2003,15766.562426930066
-China,CHN,2004,18448.787100887243
-China,CHN,2005,20966.89843534381
-China,CHN,2006,22993.818864764424
-China,CHN,2007,25000.357048089147
-China,CHN,2008,25939.73477852968
-China,CHN,2009,27099.593206744343
-China,CHN,2010,28977.748561833254
-China,CHN,2011,31290.67441082402
-China,CHN,2012,32558.223499705215
-China,CHN,2013,33814.393499852195
-China,CHN,2014,34595.64895008942
-China,CHN,2015,35001.97848552344
-China,CHN,2016,35437.84338213813
-China,CHN,2017,36506.93409416597
-China,CHN,2018,38070.39795085376
-Colombia,COL,1965,87.74424500022185
-Colombia,COL,1966,95.59766124415552
-Colombia,COL,1967,101.74233546812714
-Colombia,COL,1968,107.14650837852034
-Colombia,COL,1969,108.92763084257344
-Colombia,COL,1970,118.81909661540301
-Colombia,COL,1971,116.71254618832424
-Colombia,COL,1972,131.11380987890527
-Colombia,COL,1973,130.8316020608283
-Colombia,COL,1974,146.59161540447786
-Colombia,COL,1975,149.4731026112317
-Colombia,COL,1976,155.69765066093808
-Colombia,COL,1977,159.2360235248635
-Colombia,COL,1978,170.20218733522356
-Colombia,COL,1979,180.7437327428065
-Colombia,COL,1980,183.69124257053406
-Colombia,COL,1981,188.13443594990062
-Colombia,COL,1982,196.68345394674478
-Colombia,COL,1983,206.81452603554936
-Colombia,COL,1984,212.12134099716164
-Colombia,COL,1985,220.4331012960315
-Colombia,COL,1986,227.2895955710615
-Colombia,COL,1987,247.12226381582695
-Colombia,COL,1988,247.1133616662714
-Colombia,COL,1989,259.87360228377753
-Colombia,COL,1990,242.66750569762382
-Colombia,COL,1991,252.1673611722019
-Colombia,COL,1992,264.72959868333044
-Colombia,COL,1993,290.97077083277617
-Colombia,COL,1994,312.0852292328772
-Colombia,COL,1995,317.0072824396621
-Colombia,COL,1996,324.7771248777511
-Colombia,COL,1997,334.9864687541524
-Colombia,COL,1998,337.0596345066491
-Colombia,COL,1999,311.011044460626
-Colombia,COL,2000,303.37026278003214
-Colombia,COL,2001,298.8824790018371
-Colombia,COL,2002,298.07285975555084
-Colombia,COL,2003,309.1104348099541
-Colombia,COL,2004,315.09513222643375
-Colombia,COL,2005,316.3542579305035
-Colombia,COL,2006,355.49018646672346
-Colombia,COL,2007,357.42428141908124
-Colombia,COL,2008,386.8747873025133
-Colombia,COL,2009,369.73846771305864
-Colombia,COL,2010,396.3990972009803
-Colombia,COL,2011,415.46968177164473
-Colombia,COL,2012,445.19624832902747
-Colombia,COL,2013,451.84044230334337
-Colombia,COL,2014,476.96303585987425
-Colombia,COL,2015,480.3972457520065
-Colombia,COL,2016,514.5463281471378
-Colombia,COL,2017,529.2868378211598
-Colombia,COL,2018,546.0092198286926
-Croatia,HRV,1990,99.2149488758479
-Croatia,HRV,1991,82.89568397836246
-Croatia,HRV,1992,79.10460494467826
-Croatia,HRV,1993,82.51533743608178
-Croatia,HRV,1994,83.09161904152039
-Croatia,HRV,1995,85.98536037152037
-Croatia,HRV,1996,91.68080371707586
-Croatia,HRV,1997,91.45494770350867
-Croatia,HRV,1998,96.75791964023377
-Croatia,HRV,1999,99.70612226304084
-Croatia,HRV,2000,94.4496812852046
-Croatia,HRV,2001,99.31882687105256
-Croatia,HRV,2002,99.94021325660812
-Croatia,HRV,2003,104.85446513140342
-Croatia,HRV,2004,108.63217191192975
-Croatia,HRV,2005,107.64498461842103
-Croatia,HRV,2006,106.5246892642689
-Croatia,HRV,2007,107.52882415508763
-Croatia,HRV,2008,106.82362746163744
-Croatia,HRV,2009,105.31963381643261
-Croatia,HRV,2010,106.91032148116953
-Croatia,HRV,2011,93.75822551672508
-Croatia,HRV,2012,86.97272409660815
-Croatia,HRV,2013,95.14286551871338
-Croatia,HRV,2014,95.16215125777771
-Croatia,HRV,2015,90.42819541140338
-Croatia,HRV,2016,94.13001691134491
-Croatia,HRV,2017,94.29306123578941
-Croatia,HRV,2018,100.46296928331114
-Cyprus,CYP,1965,4.680250555555556
-Cyprus,CYP,1966,5.338632500000006
-Cyprus,CYP,1967,5.787254722222228
-Cyprus,CYP,1968,6.427251666666663
-Cyprus,CYP,1969,7.589793611111107
-Cyprus,CYP,1970,8.004829166666665
-Cyprus,CYP,1971,9.54851444444445
-Cyprus,CYP,1972,10.737023888888894
-Cyprus,CYP,1973,11.519170277777773
-Cyprus,CYP,1974,10.213084166666672
-Cyprus,CYP,1975,8.530229999999996
-Cyprus,CYP,1976,8.673059444444446
-Cyprus,CYP,1977,9.796983611111113
-Cyprus,CYP,1978,10.044485277777781
-Cyprus,CYP,1979,10.192833333333331
-Cyprus,CYP,1980,10.278665000000004
-Cyprus,CYP,1981,9.856193611111113
-Cyprus,CYP,1982,11.81379194444447
-Cyprus,CYP,1983,12.430679722222182
-Cyprus,CYP,1984,12.612488888888903
-Cyprus,CYP,1985,13.565379722222193
-Cyprus,CYP,1986,14.143438333333325
-Cyprus,CYP,1987,17.280825277777723
-Cyprus,CYP,1988,17.845005833333307
-Cyprus,CYP,1989,18.312032499999948
-Cyprus,CYP,1990,19.27453583333336
-Cyprus,CYP,1991,19.512156666666645
-Cyprus,CYP,1992,22.79668000000003
-Cyprus,CYP,1993,23.690177777777773
-Cyprus,CYP,1994,23.73236027777782
-Cyprus,CYP,1995,25.230673055555524
-Cyprus,CYP,1996,25.604817777777743
-Cyprus,CYP,1997,25.851622777777816
-Cyprus,CYP,1998,27.4466055555556
-Cyprus,CYP,1999,28.880678888888944
-Cyprus,CYP,2000,30.2611052777778
-Cyprus,CYP,2001,30.60965277777783
-Cyprus,CYP,2002,30.185936388888887
-Cyprus,CYP,2003,32.08830055555559
-Cyprus,CYP,2004,31.228174897660807
-Cyprus,CYP,2005,34.99257257309936
-Cyprus,CYP,2006,34.41155459202506
-Cyprus,CYP,2007,34.98717750136215
-Cyprus,CYP,2008,35.876319226473036
-Cyprus,CYP,2009,35.01785282288957
-Cyprus,CYP,2010,34.059295907704524
-Cyprus,CYP,2011,33.67997669712318
-Cyprus,CYP,2012,31.55409143391814
-Cyprus,CYP,2013,28.224896404678336
-Cyprus,CYP,2014,28.245348216389946
-Cyprus,CYP,2015,29.134354845725298
-Cyprus,CYP,2016,31.690833871988268
-Cyprus,CYP,2017,32.55528090862158
-Cyprus,CYP,2018,32.378477635266286
-Czech Republic,CZE,1965,468.0519172222227
-Czech Republic,CZE,1966,471.599968333333
-Czech Republic,CZE,1967,464.3232108333332
-Czech Republic,CZE,1968,484.41472916666646
-Czech Republic,CZE,1969,505.14327305555577
-Czech Republic,CZE,1970,526.3149638888885
-Czech Republic,CZE,1971,553.2226794444448
-Czech Republic,CZE,1972,556.4107016666668
-Czech Republic,CZE,1973,559.8174469444441
-Czech Republic,CZE,1974,565.3516666666666
-Czech Republic,CZE,1975,588.7155350000006
-Czech Republic,CZE,1976,605.2442419444448
-Czech Republic,CZE,1977,625.0074638888887
-Czech Republic,CZE,1978,633.794500555555
-Czech Republic,CZE,1979,640.3533347222219
-Czech Republic,CZE,1980,620.0453725000001
-Czech Republic,CZE,1981,615.5504899999999
-Czech Republic,CZE,1982,608.4741538888888
-Czech Republic,CZE,1983,608.8657899999998
-Czech Republic,CZE,1984,626.3791222222223
-Czech Republic,CZE,1985,630.4784130555561
-Czech Republic,CZE,1986,636.6666122222223
-Czech Republic,CZE,1987,650.259283055556
-Czech Republic,CZE,1988,653.024909166667
-Czech Republic,CZE,1989,632.9004886111111
-Czech Republic,CZE,1990,543.7783515723387
-Czech Republic,CZE,1991,494.7959469403504
-Czech Republic,CZE,1992,480.01704335421095
-Czech Republic,CZE,1993,475.9680087907605
-Czech Republic,CZE,1994,463.1773067201168
-Czech Republic,CZE,1995,482.85621814742666
-Czech Republic,CZE,1996,499.5194635900004
-Czech Republic,CZE,1997,478.9807875438012
-Czech Republic,CZE,1998,464.84493156152047
-Czech Republic,CZE,1999,445.42194335713407
-Czech Republic,CZE,2000,470.94895047192927
-Czech Republic,CZE,2001,481.65227494549634
-Czech Republic,CZE,2002,482.68541926918124
-Czech Republic,CZE,2003,510.1063153347366
-Czech Republic,CZE,2004,523.1120090683628
-Czech Republic,CZE,2005,515.5789924628066
-Czech Republic,CZE,2006,525.8392568709936
-Czech Republic,CZE,2007,520.4497892216366
-Czech Republic,CZE,2008,511.11431952824495
-Czech Republic,CZE,2009,490.78499853543866
-Czech Republic,CZE,2010,511.76489034795264
-Czech Republic,CZE,2011,500.55858590652446
-Czech Republic,CZE,2012,498.1012861784756
-Czech Republic,CZE,2013,489.12539899788555
-Czech Republic,CZE,2014,478.8425021618853
-Czech Republic,CZE,2015,470.93532852303133
-Czech Republic,CZE,2016,463.97841911960666
-Czech Republic,CZE,2017,485.7048211096713
-Czech Republic,CZE,2018,489.83957808922395
-Denmark,DNK,1965,166.19249883333373
-Denmark,DNK,1966,189.0406739999998
-Denmark,DNK,1967,190.1077036666673
-Denmark,DNK,1968,198.6629109999996
-Denmark,DNK,1969,228.03969261111135
-Denmark,DNK,1970,242.97660583333294
-Denmark,DNK,1971,229.62233722222172
-Denmark,DNK,1972,242.3294566111112
-Denmark,DNK,1973,234.45674477777743
-Denmark,DNK,1974,213.30108566666672
-Denmark,DNK,1975,210.2326429356725
-Denmark,DNK,1976,231.43699438888902
-Denmark,DNK,1977,236.18080683040898
-Denmark,DNK,1978,239.60882481286546
-Denmark,DNK,1979,239.12723881871383
-Denmark,DNK,1980,232.9463888654969
-Denmark,DNK,1981,209.23240263157902
-Denmark,DNK,1982,199.97849433040977
-Denmark,DNK,1983,190.0753730672509
-Denmark,DNK,1984,193.2535599883036
-Denmark,DNK,1985,217.76914222807042
-Denmark,DNK,1986,222.5647291111115
-Denmark,DNK,1987,214.54040721345066
-Denmark,DNK,1988,212.15579640643313
-Denmark,DNK,1989,195.59703385964949
-Denmark,DNK,1990,201.6355658654973
-Denmark,DNK,1991,232.40559046414873
-Denmark,DNK,1992,217.53781491793666
-Denmark,DNK,1993,230.55011445754394
-Denmark,DNK,1994,247.35386862639834
-Denmark,DNK,1995,242.86406921762017
-Denmark,DNK,1996,289.0167833011415
-Denmark,DNK,1997,261.81522206782637
-Denmark,DNK,1998,252.16024482638903
-Denmark,DNK,1999,244.31359338008423
-Denmark,DNK,2000,234.4004599525601
-Denmark,DNK,2001,235.04171671955632
-Denmark,DNK,2002,234.29153478322326
-Denmark,DNK,2003,252.33530080138678
-Denmark,DNK,2004,238.36656476700963
-Denmark,DNK,2005,230.02639748754538
-Denmark,DNK,2006,253.83308631727056
-Denmark,DNK,2007,240.61252464339884
-Denmark,DNK,2008,231.6397261555746
-Denmark,DNK,2009,217.91260196686568
-Denmark,DNK,2010,229.17319135900323
-Denmark,DNK,2011,216.79594831023522
-Denmark,DNK,2012,200.97904417572693
-Denmark,DNK,2013,210.16819873209297
-Denmark,DNK,2014,203.52611124340763
-Denmark,DNK,2015,196.7666075284923
-Denmark,DNK,2016,198.71517809766428
-Denmark,DNK,2017,199.96855182591594
-Denmark,DNK,2018,197.3507684509082
-Eastern Africa,,1965,111.6068478747138
-Eastern Africa,,1966,118.46435512586135
-Eastern Africa,,1967,124.11684275612483
-Eastern Africa,,1968,129.57590015400086
-Eastern Africa,,1969,133.75742253736593
-Eastern Africa,,1970,146.50253676842294
-Eastern Africa,,1971,156.32043647658932
-Eastern Africa,,1972,166.38247146170633
-Eastern Africa,,1973,172.81186393448124
-Eastern Africa,,1974,179.48777992406258
-Eastern Africa,,1975,176.61564705521562
-Eastern Africa,,1976,182.5841485757598
-Eastern Africa,,1977,185.58262493116945
-Eastern Africa,,1978,179.67780121675946
-Eastern Africa,,1979,183.58090298799752
-Eastern Africa,,1980,186.35400830519194
-Eastern Africa,,1981,183.52449341692764
-Eastern Africa,,1982,182.26097079005183
-Eastern Africa,,1983,178.33202083804719
-Eastern Africa,,1984,179.13107043333977
-Eastern Africa,,1985,186.3439960416344
-Eastern Africa,,1986,196.24173123120124
-Eastern Africa,,1987,197.26798745779942
-Eastern Africa,,1988,213.42856514907072
-Eastern Africa,,1989,216.32532460324714
-Eastern Africa,,1990,243.33811075689454
-Eastern Africa,,1991,231.5208790743406
-Eastern Africa,,1992,227.49110100961752
-Eastern Africa,,1993,242.43442575155723
-Eastern Africa,,1994,243.97599999846042
-Eastern Africa,,1995,248.50260818743595
-Eastern Africa,,1996,249.86350976010468
-Eastern Africa,,1997,259.65858920140994
-Eastern Africa,,1998,275.74562711897164
-Eastern Africa,,1999,281.4265931626468
-Eastern Africa,,2000,284.9423792713391
-Eastern Africa,,2001,306.9656397344554
-Eastern Africa,,2002,314.9317290935945
-Eastern Africa,,2003,311.5809016135721
-Eastern Africa,,2004,337.5903059249893
-Eastern Africa,,2005,349.87579191426136
-Eastern Africa,,2006,362.8434064369178
-Eastern Africa,,2007,380.0265484493778
-Eastern Africa,,2008,377.7146055895042
-Eastern Africa,,2009,398.6336669761924
-Eastern Africa,,2010,433.4146225702026
-Eastern Africa,,2011,456.8645342058124
-Eastern Africa,,2012,465.0880786241501
-Eastern Africa,,2013,506.03311207735874
-Eastern Africa,,2014,559.45297569285
-Eastern Africa,,2015,584.880380844766
-Eastern Africa,,2016,576.1773141796415
-Eastern Africa,,2017,605.0603323873368
-Eastern Africa,,2018,629.1256565759878
-Ecuador,ECU,1965,8.827777499999996
-Ecuador,ECU,1966,9.304819444444444
-Ecuador,ECU,1967,10.082515277777784
-Ecuador,ECU,1968,11.870032222222262
-Ecuador,ECU,1969,12.630500833333329
-Ecuador,ECU,1970,15.04082472222219
-Ecuador,ECU,1971,16.53522027777772
-Ecuador,ECU,1972,18.469451388888867
-Ecuador,ECU,1973,18.389198611111144
-Ecuador,ECU,1974,21.232815555555582
-Ecuador,ECU,1975,21.19462277777781
-Ecuador,ECU,1976,23.498849166666638
-Ecuador,ECU,1977,28.94387555555558
-Ecuador,ECU,1978,29.89433222222225
-Ecuador,ECU,1979,31.071763611111155
-Ecuador,ECU,1980,39.26167666666666
-Ecuador,ECU,1981,43.51862333333338
-Ecuador,ECU,1982,47.77021388888885
-Ecuador,ECU,1983,47.27327027777775
-Ecuador,ECU,1984,53.08167722222224
-Ecuador,ECU,1985,59.88875459064326
-Ecuador,ECU,1986,62.550256681286484
-Ecuador,ECU,1987,64.37828134502921
-Ecuador,ECU,1988,63.57714583333329
-Ecuador,ECU,1989,65.19382960526309
-Ecuador,ECU,1990,66.13750986842106
-Ecuador,ECU,1991,73.5233401754386
-Ecuador,ECU,1992,71.51066551169585
-Ecuador,ECU,1993,76.68322891812858
-Ecuador,ECU,1994,83.47287466374263
-Ecuador,ECU,1995,77.75419399122801
-Ecuador,ECU,1996,88.42049374269004
-Ecuador,ECU,1997,98.50996261695896
-Ecuador,ECU,1998,99.977559239766
-Ecuador,ECU,1999,94.07927922001743
-Ecuador,ECU,2000,100.12601082737862
-Ecuador,ECU,2001,101.31818421318475
-Ecuador,ECU,2002,99.90198725728015
-Ecuador,ECU,2003,101.58569634238613
-Ecuador,ECU,2004,112.17966797023531
-Ecuador,ECU,2005,119.04698357485955
-Ecuador,ECU,2006,126.01662568541602
-Ecuador,ECU,2007,132.33282391252146
-Ecuador,ECU,2008,140.86265202750383
-Ecuador,ECU,2009,138.12748173733075
-Ecuador,ECU,2010,153.71951746908422
-Ecuador,ECU,2011,162.9775950860208
-Ecuador,ECU,2012,172.30397808254557
-Ecuador,ECU,2013,178.173456906333
-Ecuador,ECU,2014,187.3367175089564
-Ecuador,ECU,2015,186.90956427804701
-Ecuador,ECU,2016,186.39292702638124
-Ecuador,ECU,2017,193.76648721487572
-Ecuador,ECU,2018,204.99919173270902
-Egypt,EGY,1965,91.11126722222227
-Egypt,EGY,1966,95.86880388888895
-Egypt,EGY,1967,81.94484611111109
-Egypt,EGY,1968,88.14109833333329
-Egypt,EGY,1969,72.07654888888894
-Egypt,EGY,1970,89.90578611111107
-Egypt,EGY,1971,92.34805252333334
-Egypt,EGY,1972,102.6102891266667
-Egypt,EGY,1973,96.89589294888889
-Egypt,EGY,1974,110.18552725666669
-Egypt,EGY,1975,122.0778356200004
-Egypt,EGY,1976,145.85794683333302
-Egypt,EGY,1977,158.0649004711107
-Egypt,EGY,1978,167.12235692222242
-Egypt,EGY,1979,182.95523598555505
-Egypt,EGY,1980,208.82948573333363
-Egypt,EGY,1981,237.77184412444439
-Egypt,EGY,1982,265.5845228966664
-Egypt,EGY,1983,288.4257367333337
-Egypt,EGY,1984,313.97868683333274
-Egypt,EGY,1985,325.87259017163706
-Egypt,EGY,1986,333.77051933801107
-Egypt,EGY,1987,349.67689958508737
-Egypt,EGY,1988,360.32816104520447
-Egypt,EGY,1989,380.61423021368466
-Egypt,EGY,1990,393.2307160620461
-Egypt,EGY,1991,398.34344488321597
-Egypt,EGY,1992,397.8378767419885
-Egypt,EGY,1993,402.0223320952048
-Egypt,EGY,1994,409.72445707292354
-Egypt,EGY,1995,434.16657097116996
-Egypt,EGY,1996,457.5357694649127
-Egypt,EGY,1997,476.6699774372516
-Egypt,EGY,1998,496.36834655619936
-Egypt,EGY,1999,531.414729310585
-Egypt,EGY,2000,563.3528366479532
-Egypt,EGY,2001,593.757336952748
-Egypt,EGY,2002,603.1571157119884
-Egypt,EGY,2003,639.9878109301173
-Egypt,EGY,2004,670.1930273062736
-Egypt,EGY,2005,703.5859343521901
-Egypt,EGY,2006,738.6924546550155
-Egypt,EGY,2007,782.3884893150693
-Egypt,EGY,2008,833.8446316785423
-Egypt,EGY,2009,867.1074905268323
-Egypt,EGY,2010,912.20127343712
-Egypt,EGY,2011,926.5947788247171
-Egypt,EGY,2012,974.05618923292
-Egypt,EGY,2013,967.1968604425679
-Egypt,EGY,2014,964.9701345722011
-Egypt,EGY,2015,991.8807551982165
-Egypt,EGY,2016,1045.9911631403218
-Egypt,EGY,2017,1077.1767312649874
-Egypt,EGY,2018,1099.4382378338594
-Estonia,EST,1985,118.45261205190006
-Estonia,EST,1986,117.882853020886
-Estonia,EST,1987,119.6663498067
-Estonia,EST,1988,117.63286485314885
-Estonia,EST,1989,121.22505717199202
-Estonia,EST,1990,120.41714569817276
-Estonia,EST,1991,108.65108604159956
-Estonia,EST,1992,78.74392711999995
-Estonia,EST,1993,62.46318975000001
-Estonia,EST,1994,63.097360692222225
-Estonia,EST,1995,58.900524783684254
-Estonia,EST,1996,62.101068631403585
-Estonia,EST,1997,61.41402712491227
-Estonia,EST,1998,57.46405559736836
-Estonia,EST,1999,52.69280610426898
-Estonia,EST,2000,54.21076392883036
-Estonia,EST,2001,56.043659753274895
-Estonia,EST,2002,55.410277938011724
-Estonia,EST,2003,60.52196355163745
-Estonia,EST,2004,63.28019559754391
-Estonia,EST,2005,62.29225575959064
-Estonia,EST,2006,61.340332093391794
-Estonia,EST,2007,69.5468526298246
-Estonia,EST,2008,66.4607877283041
-Estonia,EST,2009,58.98453185067113
-Estonia,EST,2010,71.42736923754272
-Estonia,EST,2011,73.58394983575057
-Estonia,EST,2012,74.32398537396648
-Estonia,EST,2013,76.92463275645743
-Estonia,EST,2014,75.1298461884665
-Estonia,EST,2015,70.0848846323606
-Estonia,EST,2016,70.6543875775189
-Estonia,EST,2017,77.08570195450467
-Estonia,EST,2018,80.3017131644243
-Europe,,1965,12310.926523398723
-Europe,,1966,12679.435420607215
-Europe,,1967,13056.049452039284
-Europe,,1968,13928.488438425597
-Europe,,1969,14947.71854336528
-Europe,,1970,15917.563472453103
-Europe,,1971,16351.063356974331
-Europe,,1972,17123.215621941235
-Europe,,1973,18111.628430656714
-Europe,,1974,17849.298108672312
-Europe,,1975,17661.574689108285
-Europe,,1976,18677.720726135532
-Europe,,1977,18975.435827072724
-Europe,,1978,19701.52934955674
-Europe,,1979,20434.855928299592
-Europe,,1980,19924.44165938226
-Europe,,1981,19393.02883508112
-Europe,,1982,19021.73446693542
-Europe,,1983,19184.762071688016
-Europe,,1984,19659.604984303864
-Europe,,1985,23420.808997235577
-Europe,,1986,23819.962811568766
-Europe,,1987,24297.838380413446
-Europe,,1988,24541.71937515404
-Europe,,1989,24464.72972962895
-Europe,,1990,24682.728669336902
-Europe,,1991,24277.591027880073
-Europe,,1992,23582.605673888083
-Europe,,1993,23102.18164691593
-Europe,,1994,22639.22119684086
-Europe,,1995,23039.763235195795
-Europe,,1996,23719.761556241185
-Europe,,1997,23661.49460013229
-Europe,,1998,23867.633678955634
-Europe,,1999,23776.78602204416
-Europe,,2000,24051.76092898297
-Europe,,2001,24382.721362478533
-Europe,,2002,24300.0166836734
-Europe,,2003,24776.081126499885
-Europe,,2004,25172.203789606017
-Europe,,2005,25300.780128405717
-Europe,,2006,25552.681922767504
-Europe,,2007,25324.400832588224
-Europe,,2008,25275.06551869153
-Europe,,2009,23823.35912415268
-Europe,,2010,24709.308908306783
-Europe,,2011,24163.74879067206
-Europe,,2012,24101.24489485302
-Europe,,2013,23895.956427342622
-Europe,,2014,23007.946491736486
-Europe,,2015,23222.441856001795
-Europe,,2016,23579.27775129843
-Europe,,2017,23841.770900567517
-Europe,,2018,23849.822682945185
-Europe (other),,1965,182.2286398314534
-Europe (other),,1966,191.66197307434516
-Europe (other),,1967,194.23408895448316
-Europe (other),,1968,213.73132268534872
-Europe (other),,1969,227.71355633345908
-Europe (other),,1970,251.48631320475184
-Europe (other),,1971,294.2179078033437
-Europe (other),,1972,306.35587152693677
-Europe (other),,1973,321.7405136568661
-Europe (other),,1974,356.1483655967875
-Europe (other),,1975,359.3204525074744
-Europe (other),,1976,382.8373652806917
-Europe (other),,1977,410.1432724717724
-Europe (other),,1978,446.52397522582686
-Europe (other),,1979,484.2290446770118
-Europe (other),,1980,469.70515265708883
-Europe (other),,1981,468.6458588895209
-Europe (other),,1982,487.9858741844575
-Europe (other),,1983,526.5349639674469
-Europe (other),,1984,549.5804452646016
-Europe (other),,1985,701.5006583272587
-Europe (other),,1986,735.5733814787324
-Europe (other),,1987,744.5572634457029
-Europe (other),,1988,767.6805558309411
-Europe (other),,1989,745.6056660658007
-Europe (other),,1990,527.2498400623746
-Europe (other),,1991,463.6087731986804
-Europe (other),,1992,405.4784259664222
-Europe (other),,1993,349.6283484690639
-Europe (other),,1994,297.87587006920376
-Europe (other),,1995,305.5412807375734
-Europe (other),,1996,333.4324180780786
-Europe (other),,1997,359.6899726038086
-Europe (other),,1998,365.294631237473
-Europe (other),,1999,331.47502692736447
-Europe (other),,2000,356.6869438919862
-Europe (other),,2001,373.1481546937461
-Europe (other),,2002,391.75599478777406
-Europe (other),,2003,414.6158597256562
-Europe (other),,2004,450.6281359895972
-Europe (other),,2005,444.9084799906067
-Europe (other),,2006,456.8086442553458
-Europe (other),,2007,444.19645672737767
-Europe (other),,2008,455.1751376433717
-Europe (other),,2009,462.3616541276145
-Europe (other),,2010,494.4369430306088
-Europe (other),,2011,485.83729918197344
-Europe (other),,2012,455.93664919001304
-Europe (other),,2013,482.85265569166404
-Europe (other),,2014,443.8097223738383
-Europe (other),,2015,473.6014052423464
-Europe (other),,2016,503.6877515485082
-Europe (other),,2017,497.2654703152644
-Europe (other),,2018,520.3034705406511
-Finland,FIN,1965,112.35986974982966
-Finland,FIN,1966,127.98711803879323
-Finland,FIN,1967,134.4678929355074
-Finland,FIN,1968,146.61766337906366
-Finland,FIN,1969,162.07461579587425
-Finland,FIN,1970,178.60923640882442
-Finland,FIN,1971,183.1057346863366
-Finland,FIN,1972,193.332962563795
-Finland,FIN,1973,213.33576751993616
-Finland,FIN,1974,203.80562322434798
-Finland,FIN,1975,207.27833771398133
-Finland,FIN,1976,220.95439783226988
-Finland,FIN,1977,232.43390346631148
-Finland,FIN,1978,242.06505556290034
-Finland,FIN,1979,260.93017934658235
-Finland,FIN,1980,259.90184982435113
-Finland,FIN,1981,259.7879310215035
-Finland,FIN,1982,256.2035787911664
-Finland,FIN,1983,253.3233220247485
-Finland,FIN,1984,264.1708286814124
-Finland,FIN,1985,277.8298043609228
-Finland,FIN,1986,281.09330274273185
-Finland,FIN,1987,295.7927926086346
-Finland,FIN,1988,293.96145894596964
-Finland,FIN,1989,295.4693275304989
-Finland,FIN,1990,314.7105303251643
-Finland,FIN,1991,320.8562093619579
-Finland,FIN,1992,318.6555047016509
-Finland,FIN,1993,322.5850280809632
-Finland,FIN,1994,339.7037186778668
-Finland,FIN,1995,323.42047461303355
-Finland,FIN,1996,339.4754721744191
-Finland,FIN,1997,342.3289999055009
-Finland,FIN,1998,353.5948596673297
-Finland,FIN,1999,347.2573492377914
-Finland,FIN,2000,349.4859944843581
-Finland,FIN,2001,358.531288828359
-Finland,FIN,2002,363.1956856757376
-Finland,FIN,2003,390.6389047575383
-Finland,FIN,2004,387.2165385165774
-Finland,FIN,2005,352.5421323368635
-Finland,FIN,2006,378.52277645007325
-Finland,FIN,2007,378.24284050567155
-Finland,FIN,2008,365.6907845924764
-Finland,FIN,2009,340.2016745252233
-Finland,FIN,2010,370.68513287929073
-Finland,FIN,2011,345.5164320092009
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-Indonesia,IDN,2013,2072.136524797509
-Indonesia,IDN,2014,1944.4667287744933
-Indonesia,IDN,2015,1926.992226623864
-Indonesia,IDN,2016,1979.00131516515
-Indonesia,IDN,2017,2056.9560598631724
-Indonesia,IDN,2018,2157.7135639898665
-Iran,IRN,1965,98.93851704304113
-Iran,IRN,1966,107.70246851882247
-Iran,IRN,1967,118.3322771240147
-Iran,IRN,1968,129.9456964780402
-Iran,IRN,1969,142.46213595390594
-Iran,IRN,1970,167.75677721649944
-Iran,IRN,1971,183.60362635401847
-Iran,IRN,1972,207.7915750337637
-Iran,IRN,1973,248.65441451471654
-Iran,IRN,1974,281.40811132718835
-Iran,IRN,1975,327.67009933543795
-Iran,IRN,1976,368.3132874222552
-Iran,IRN,1977,417.47901864898137
-Iran,IRN,1978,407.6032597811487
-Iran,IRN,1979,440.06887859664226
-Iran,IRN,1980,406.8961618370235
-Iran,IRN,1981,407.6190239088508
-Iran,IRN,1982,460.05566210501036
-Iran,IRN,1983,546.4655312842448
-Iran,IRN,1984,590.6608926051351
-Iran,IRN,1985,644.7124579065908
-Iran,IRN,1986,603.3685702151561
-Iran,IRN,1987,647.0076417207977
-Iran,IRN,1988,683.4911090004239
-Iran,IRN,1989,748.2581603895701
-Iran,IRN,1990,842.0969823607139
-Iran,IRN,1991,914.4932291205388
-Iran,IRN,1992,1003.0892140328647
-Iran,IRN,1993,925.3996441643937
-Iran,IRN,1994,1040.074730546294
-Iran,IRN,1995,1101.6728369301063
-Iran,IRN,1996,1191.231160753085
-Iran,IRN,1997,1232.3819848777646
-Iran,IRN,1998,1274.2081132018006
-Iran,IRN,1999,1360.3793117326848
-Iran,IRN,2000,1429.5233290701867
-Iran,IRN,2001,1508.2740112058734
-Iran,IRN,2002,1639.5206758714562
-Iran,IRN,2003,1675.2875311685748
-Iran,IRN,2004,1837.0027840311448
-Iran,IRN,2005,1970.267326839984
-Iran,IRN,2006,2153.066614856045
-Iran,IRN,2007,2304.8928612504596
-Iran,IRN,2008,2393.023767458324
-Iran,IRN,2009,2473.720581911133
-Iran,IRN,2010,2481.984431974258
-Iran,IRN,2011,2616.1183868275666
-Iran,IRN,2012,2630.9302038733294
-Iran,IRN,2013,2767.2041865574865
-Iran,IRN,2014,2895.3333042144586
-Iran,IRN,2015,2898.5200627414933
-Iran,IRN,2016,2990.711950647721
-Iran,IRN,2017,3163.5334995877824
-Iran,IRN,2018,3322.9064854738817
-Iraq,IRQ,1965,20.34517113333432
-Iraq,IRQ,1966,22.705020996065283
-Iraq,IRQ,1967,22.949337985930992
-Iraq,IRQ,1968,24.532959075821033
-Iraq,IRQ,1969,28.784638021634233
-Iraq,IRQ,1970,36.49548554866888
-Iraq,IRQ,1971,40.00563536647956
-Iraq,IRQ,1972,47.42097939664713
-Iraq,IRQ,1973,46.27611055688886
-Iraq,IRQ,1974,45.612977404405505
-Iraq,IRQ,1975,50.13877045651464
-Iraq,IRQ,1976,64.0674312972944
-Iraq,IRQ,1977,66.03989719409746
-Iraq,IRQ,1978,63.54644796076286
-Iraq,IRQ,1979,79.71990607891304
-Iraq,IRQ,1980,94.956847643555
-Iraq,IRQ,1981,94.2673265199121
-Iraq,IRQ,1982,98.5015815439786
-Iraq,IRQ,1983,108.99430403746801
-Iraq,IRQ,1984,119.57040341806047
-Iraq,IRQ,1985,141.43276309250984
-Iraq,IRQ,1986,156.94185850679176
-Iraq,IRQ,1987,188.1774926503038
-Iraq,IRQ,1988,219.44467398738757
-Iraq,IRQ,1989,245.96413913568472
-Iraq,IRQ,1990,227.51957659787536
-Iraq,IRQ,1991,153.05734059298322
-Iraq,IRQ,1992,240.65412256807542
-Iraq,IRQ,1993,326.64970607359396
-Iraq,IRQ,1994,374.11741913895816
-Iraq,IRQ,1995,367.27865620874815
-Iraq,IRQ,1996,381.15159232533296
-Iraq,IRQ,1997,446.64780858655166
-Iraq,IRQ,1998,313.18928146316733
-Iraq,IRQ,1999,235.22164652763848
-Iraq,IRQ,2000,299.6873109849408
-Iraq,IRQ,2001,337.20549330273883
-Iraq,IRQ,2002,318.59640806820033
-Iraq,IRQ,2003,294.87355530468034
-Iraq,IRQ,2004,314.7748855204612
-Iraq,IRQ,2005,301.9090055363773
-Iraq,IRQ,2006,308.4766382395411
-Iraq,IRQ,2007,327.23124399757603
-Iraq,IRQ,2008,339.40914130488335
-Iraq,IRQ,2009,378.9432821021187
-Iraq,IRQ,2010,403.8416646590956
-Iraq,IRQ,2011,426.828899510442
-Iraq,IRQ,2012,453.94276600495317
-Iraq,IRQ,2013,489.01280535750675
-Iraq,IRQ,2014,467.835796418272
-Iraq,IRQ,2015,466.24405521150516
-Iraq,IRQ,2016,537.8685010593771
-Iraq,IRQ,2017,547.7119598472697
-Iraq,IRQ,2018,625.0964740479629
-Ireland,IRL,1965,67.35657020467835
-Ireland,IRL,1966,75.5301650438597
-Ireland,IRL,1967,81.90841426900585
-Ireland,IRL,1968,95.5824943128655
-Ireland,IRL,1969,95.9603681578947
-Ireland,IRL,1970,75.54264176900593
-Ireland,IRL,1971,78.58215580409355
-Ireland,IRL,1972,82.90348497076023
-Ireland,IRL,1973,87.16129530701754
-Ireland,IRL,1974,88.64314289473685
-Ireland,IRL,1975,82.97501461988307
-Ireland,IRL,1976,84.68422314327483
-Ireland,IRL,1977,90.22116684210523
-Ireland,IRL,1978,93.88465912280707
-Ireland,IRL,1979,103.51764229532166
-Ireland,IRL,1980,100.15193839181286
-Ireland,IRL,1981,97.71093891812875
-Ireland,IRL,1982,97.02648399122809
-Ireland,IRL,1983,95.62378985380117
-Ireland,IRL,1984,94.63376330409356
-Ireland,IRL,1985,99.26536394736841
-Ireland,IRL,1986,107.20378078947365
-Ireland,IRL,1987,108.49592247076018
-Ireland,IRL,1988,107.9151141812866
-Ireland,IRL,1989,111.2454102339181
-Ireland,IRL,1990,116.80488679746934
-Ireland,IRL,1991,121.00459344190187
-Ireland,IRL,1992,121.82738615224652
-Ireland,IRL,1993,124.46751507033512
-Ireland,IRL,1994,129.38869518432185
-Ireland,IRL,1995,131.98127775364046
-Ireland,IRL,1996,139.4662476745615
-Ireland,IRL,1997,145.62920017449682
-Ireland,IRL,1998,156.60219304621089
-Ireland,IRL,1999,165.68754890549718
-Ireland,IRL,2000,171.5233654593572
-Ireland,IRL,2001,182.7274825412862
-Ireland,IRL,2002,181.44129616865524
-Ireland,IRL,2003,176.68163707602352
-Ireland,IRL,2004,179.14558740247978
-Ireland,IRL,2005,186.9773748300113
-Ireland,IRL,2006,190.89543295839758
-Ireland,IRL,2007,196.89311416278724
-Ireland,IRL,2008,196.18559295807597
-Ireland,IRL,2009,179.23219939772625
-Ireland,IRL,2010,178.8926654165655
-Ireland,IRL,2011,168.8945439657829
-Ireland,IRL,2012,166.92028469239492
-Ireland,IRL,2013,163.89589248331413
-Ireland,IRL,2014,163.760282456543
-Ireland,IRL,2015,173.75147276034832
-Ireland,IRL,2016,181.14481115936957
-Ireland,IRL,2017,182.2882521130725
-Ireland,IRL,2018,187.22601432654068
-Israel,ISR,1965,46.47141230362245
-Israel,ISR,1966,48.658479633814125
-Israel,ISR,1967,50.79462031501603
-Israel,ISR,1968,53.22445291270539
-Israel,ISR,1969,55.488019611668555
-Israel,ISR,1970,57.670440311030696
-Israel,ISR,1971,60.008409170821
-Israel,ISR,1972,62.61393995615591
-Israel,ISR,1973,65.5135206092849
-Israel,ISR,1974,66.92459302358151
-Israel,ISR,1975,68.94644706643724
-Israel,ISR,1976,72.79051584923691
-Israel,ISR,1977,76.07279055377764
-Israel,ISR,1978,81.0816809148767
-Israel,ISR,1979,88.7297527783014
-Israel,ISR,1980,94.54403821214612
-Israel,ISR,1981,96.19610340539583
-Israel,ISR,1982,100.00993736807767
-Israel,ISR,1983,100.80486624897087
-Israel,ISR,1984,102.25437406013594
-Israel,ISR,1985,99.39835028989116
-Israel,ISR,1986,104.52813349187325
-Israel,ISR,1987,115.7174592395523
-Israel,ISR,1988,123.8661187622314
-Israel,ISR,1989,128.31971081561665
-Israel,ISR,1990,133.04656915858064
-Israel,ISR,1991,138.03668373131123
-Israel,ISR,1992,150.4070783607868
-Israel,ISR,1993,159.31721930687283
-Israel,ISR,1994,174.40630935374435
-Israel,ISR,1995,194.6197163708772
-Israel,ISR,1996,204.87073592514233
-Israel,ISR,1997,201.03129689977808
-Israel,ISR,1998,214.88902439047612
-Israel,ISR,1999,223.38610046719094
-Israel,ISR,2000,233.7002078872329
-Israel,ISR,2001,232.6157657643001
-Israel,ISR,2002,235.9641922353675
-Israel,ISR,2003,242.5420498360828
-Israel,ISR,2004,245.48430078825058
-Israel,ISR,2005,253.44871062741535
-Israel,ISR,2006,253.20702444173932
-Israel,ISR,2007,267.15869779061245
-Israel,ISR,2008,271.3894798259971
-Israel,ISR,2009,259.89264182380583
-Israel,ISR,2010,275.47884530787974
-Israel,ISR,2011,281.9719099095415
-Israel,ISR,2012,294.4670473265593
-Israel,ISR,2013,273.54993702753507
-Israel,ISR,2014,269.043084527525
-Israel,ISR,2015,283.8058254511087
-Israel,ISR,2016,288.77846023311884
-Israel,ISR,2017,297.52317680993997
-Israel,ISR,2018,298.2089169057165
-Italy,ITA,1965,913.4511737719291
-Italy,ITA,1966,992.5104167982456
-Italy,ITA,1967,1076.6618416959059
-Italy,ITA,1968,1164.611598567245
-Italy,ITA,1969,1255.2176345614075
-Italy,ITA,1970,1387.0834906871394
-Italy,ITA,1971,1461.5892305847924
-Italy,ITA,1972,1533.3262834795328
-Italy,ITA,1973,1601.433751505853
-Italy,ITA,1974,1600.4366531140358
-Italy,ITA,1975,1564.6369789619823
-Italy,ITA,1976,1654.1057277339141
-Italy,ITA,1977,1655.7816210964882
-Italy,ITA,1978,1698.557299707607
-Italy,ITA,1979,1757.7448993128653
-Italy,ITA,1980,1714.4066385818755
-Italy,ITA,1981,1678.6415163450242
-Italy,ITA,1982,1644.6319047660836
-Italy,ITA,1983,1610.1714373976588
-Italy,ITA,1984,1627.8446727192977
-Italy,ITA,1985,1622.1884039619888
-Italy,ITA,1986,1666.3691038157888
-Italy,ITA,1987,1718.6033951461998
-Italy,ITA,1988,1760.902320570177
-Italy,ITA,1989,1812.7562471398228
-Italy,ITA,1990,1821.1689209560416
-Italy,ITA,1991,1860.9283328816105
-Italy,ITA,1992,1859.6488376946925
-Italy,ITA,1993,1829.864373342266
-Italy,ITA,1994,1826.0441126883231
-Italy,ITA,1995,1902.4222835566397
-Italy,ITA,1996,1904.3340995933854
-Italy,ITA,1997,1931.1523035476575
-Italy,ITA,1998,1982.6521498046193
-Italy,ITA,1999,2044.689317133096
-Italy,ITA,2000,2073.8647400787754
-Italy,ITA,2001,2085.033863610406
-Italy,ITA,2002,2069.9036541099426
-Italy,ITA,2003,2138.853507632922
-Italy,ITA,2004,2178.511625550351
-Italy,ITA,2005,2181.9247044904732
-Italy,ITA,2006,2172.418808005553
-Italy,ITA,2007,2132.60316941782
-Italy,ITA,2008,2105.0271680380943
-Italy,ITA,2009,1967.2191199411493
-Italy,ITA,2010,2028.5332609154668
-Italy,ITA,2011,1982.8771343648193
-Italy,ITA,2012,1927.753084356411
-Italy,ITA,2013,1839.600423888473
-Italy,ITA,2014,1741.233859301769
-Italy,ITA,2015,1780.0218999759795
-Italy,ITA,2016,1798.6734670300216
-Italy,ITA,2017,1817.3046648964091
-Italy,ITA,2018,1796.6773401949704
-Japan,JPN,1965,1782.9521738362575
-Japan,JPN,1966,1988.576436462573
-Japan,JPN,1967,2284.370324388309
-Japan,JPN,1968,2533.5607962491235
-Japan,JPN,1969,2905.236462028421
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-Japan,JPN,1972,3614.8173843132295
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-Japan,JPN,1974,4024.649244352909
-Japan,JPN,1975,3838.1030723374543
-Japan,JPN,1976,4001.171623955868
-Japan,JPN,1977,3993.692977875024
-Japan,JPN,1978,4139.35312501461
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-Japan,JPN,1980,4174.106644035572
-Japan,JPN,1981,4106.955604365523
-Japan,JPN,1982,3968.8192956110606
-Japan,JPN,1983,4010.1551052503382
-Japan,JPN,1984,4337.335509785952
-Japan,JPN,1985,4385.401269030519
-Japan,JPN,1986,4390.533561747312
-Japan,JPN,1987,4474.844248536365
-Japan,JPN,1988,4761.360695271244
-Japan,JPN,1989,4923.228478793787
-Japan,JPN,1990,5132.065364981251
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-Japan,JPN,1992,5323.094463096938
-Japan,JPN,1993,5393.549097802692
-Japan,JPN,1994,5605.010393060399
-Japan,JPN,1995,5821.64364685166
-Japan,JPN,1996,5931.983492821544
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-Japan,JPN,1998,5902.524418345417
-Japan,JPN,1999,6007.425552221155
-Japan,JPN,2000,6074.773601296689
-Japan,JPN,2001,6022.423236172708
-Japan,JPN,2002,6010.258355534742
-Japan,JPN,2003,5998.041890282436
-Japan,JPN,2004,6072.871123038999
-Japan,JPN,2005,6174.323976074262
-Japan,JPN,2006,6163.023029452268
-Japan,JPN,2007,6108.776690561208
-Japan,JPN,2008,6021.5452956655545
-Japan,JPN,2009,5502.5327463388185
-Japan,JPN,2010,5869.744758917834
-Japan,JPN,2011,5572.214068236492
-Japan,JPN,2012,5532.129712904391
-Japan,JPN,2013,5492.926050216078
-Japan,JPN,2014,5353.511820335408
-Japan,JPN,2015,5272.180919605133
-Japan,JPN,2016,5242.730863621088
-Japan,JPN,2017,5294.092862799763
-Japan,JPN,2018,5281.663479999475
-Kazakhstan,KAZ,1985,794.3318231052455
-Kazakhstan,KAZ,1986,812.6945322196182
-Kazakhstan,KAZ,1987,830.7295840479923
-Kazakhstan,KAZ,1988,860.6823170803942
-Kazakhstan,KAZ,1989,847.10219806645
-Kazakhstan,KAZ,1990,857.0198271911748
-Kazakhstan,KAZ,1991,856.0813299645538
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-Kazakhstan,KAZ,1993,745.5762629011115
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-Kazakhstan,KAZ,2005,528.0817076880251
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-Kazakhstan,KAZ,2015,740.2884524971539
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-Kuwait,KWT,1966,84.94587082416932
-Kuwait,KWT,1967,86.62526694077138
-Kuwait,KWT,1968,91.24988199247362
-Kuwait,KWT,1969,93.62173290407637
-Kuwait,KWT,1970,76.31032076728007
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-Kuwait,KWT,1976,86.19494499999999
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-Kuwait,KWT,1978,96.23138972222223
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-Kuwait,KWT,1980,88.10697722222223
-Kuwait,KWT,1981,111.58926305555553
-Kuwait,KWT,1982,111.61166027777779
-Kuwait,KWT,1983,123.18041666666696
-Kuwait,KWT,1984,131.30873611111144
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-Kuwait,KWT,1986,145.22731444444463
-Kuwait,KWT,1987,135.21986916666702
-Kuwait,KWT,1988,153.5171572222218
-Kuwait,KWT,1989,166.9518716666666
-Kuwait,KWT,1990,79.17798166666671
-Kuwait,KWT,1991,45.13820194444441
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-Kuwait,KWT,1993,111.00268527777781
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-Kuwait,KWT,1998,213.34964207220608
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-Kuwait,KWT,2004,312.83098122909365
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-Latvia,LVA,1999,37.69645735223776
-Latvia,LVA,2000,36.83521235867312
-Latvia,LVA,2001,39.794358357543025
-Latvia,LVA,2002,40.30586892282412
-Latvia,LVA,2003,39.73478429477867
-Latvia,LVA,2004,44.78189402958785
-Latvia,LVA,2005,46.13263413714588
-Latvia,LVA,2006,43.94710958242544
-Latvia,LVA,2007,45.22189193591181
-Latvia,LVA,2008,45.64896922309694
-Latvia,LVA,2009,43.153765486922275
-Latvia,LVA,2010,49.13569215098145
-Latvia,LVA,2011,43.914209995856424
-Latvia,LVA,2012,45.357488419432116
-Latvia,LVA,2013,43.69898245181678
-Latvia,LVA,2014,40.21173424636828
-Latvia,LVA,2015,41.17893144790604
-Latvia,LVA,2016,43.909156938037384
-Latvia,LVA,2017,48.20708314834994
-Latvia,LVA,2018,42.795251540675366
-Lithuania,LTU,1985,178.6129505608561
-Lithuania,LTU,1986,164.56887559930217
-Lithuania,LTU,1987,172.65890151227012
-Lithuania,LTU,1988,180.55607718565957
-Lithuania,LTU,1989,195.0180862003358
-Lithuania,LTU,1990,198.24517126866982
-Lithuania,LTU,1991,209.81786584934494
-Lithuania,LTU,1992,127.61723340311997
-Lithuania,LTU,1993,99.58308291066409
-Lithuania,LTU,1994,86.50802911345657
-Lithuania,LTU,1995,96.03703207405815
-Lithuania,LTU,1996,104.31006459253693
-Lithuania,LTU,1997,96.37212455263145
-Lithuania,LTU,1998,103.23055341812854
-Lithuania,LTU,1999,86.11006715204668
-Lithuania,LTU,2000,76.19018672807013
-Lithuania,LTU,2001,89.01248016081863
-Lithuania,LTU,2002,94.88088030701742
-Lithuania,LTU,2003,99.67708145614019
-Lithuania,LTU,2004,100.85045691959053
-Lithuania,LTU,2005,92.18102060818703
-Lithuania,LTU,2006,88.63375375584786
-Lithuania,LTU,2007,97.19619466520456
-Lithuania,LTU,2008,96.5381891856724
-Lithuania,LTU,2009,88.72402379532156
-Lithuania,LTU,2010,65.53977200438597
-Lithuania,LTU,2011,68.04156812280705
-Lithuania,LTU,2012,68.33005530994149
-Lithuania,LTU,2013,63.045383694444396
-Lithuania,LTU,2014,60.82967606286544
-Lithuania,LTU,2015,63.55586201900583
-Lithuania,LTU,2016,64.72135048391809
-Lithuania,LTU,2017,68.38020304532168
-Lithuania,LTU,2018,67.9979407721522
-Luxembourg,LUX,1965,41.775936611111156
-Luxembourg,LUX,1966,40.031913725146225
-Luxembourg,LUX,1967,39.422882362573056
-Luxembourg,LUX,1968,42.63966112865503
-Luxembourg,LUX,1969,45.89454509649126
-Luxembourg,LUX,1970,47.65317728070173
-Luxembourg,LUX,1971,45.82867811988301
-Luxembourg,LUX,1972,47.25600990058479
-Luxembourg,LUX,1973,50.09929117251463
-Luxembourg,LUX,1974,50.86954183918126
-Luxembourg,LUX,1975,42.25505430116963
-Luxembourg,LUX,1976,42.32959168713453
-Luxembourg,LUX,1977,39.489149198830404
-Luxembourg,LUX,1978,41.08481944736845
-Luxembourg,LUX,1979,42.22882641812868
-Luxembourg,LUX,1980,38.92473426023394
-Luxembourg,LUX,1981,33.28254992982461
-Luxembourg,LUX,1982,31.183622122807026
-Luxembourg,LUX,1983,29.149076160818733
-Luxembourg,LUX,1984,31.40542129532168
-Luxembourg,LUX,1985,32.25536848538012
-Luxembourg,LUX,1986,31.52657316081867
-Luxembourg,LUX,1987,29.786514900584802
-Luxembourg,LUX,1988,30.52907374269006
-Luxembourg,LUX,1989,35.08353439181289
-Luxembourg,LUX,1990,37.121465260899804
-Luxembourg,LUX,1991,39.89356749846913
-Luxembourg,LUX,1992,40.01345100460892
-Luxembourg,LUX,1993,40.538802847324014
-Luxembourg,LUX,1994,38.97384849795362
-Luxembourg,LUX,1995,33.89503870843033
-Luxembourg,LUX,1996,34.87109628726885
-Luxembourg,LUX,1997,34.12111192254018
-Luxembourg,LUX,1998,32.93717168168668
-Luxembourg,LUX,1999,34.815567393936625
-Luxembourg,LUX,2000,37.14341503736678
-Luxembourg,LUX,2001,39.8087612636991
-Luxembourg,LUX,2002,43.531307772540494
-Luxembourg,LUX,2003,45.65602424493431
-Luxembourg,LUX,2004,51.71773574743833
-Luxembourg,LUX,2005,52.48932637727131
-Luxembourg,LUX,2006,51.55496772017162
-Luxembourg,LUX,2007,50.05177954260768
-Luxembourg,LUX,2008,49.684336078008236
-Luxembourg,LUX,2009,47.51904540719249
-Luxembourg,LUX,2010,50.042550475761594
-Luxembourg,LUX,2011,48.75372141672244
-Luxembourg,LUX,2012,47.87144226552906
-Luxembourg,LUX,2013,45.609471008495845
-Luxembourg,LUX,2014,44.185796806264236
-Luxembourg,LUX,2015,42.953448936883056
-Luxembourg,LUX,2016,42.396296979496874
-Luxembourg,LUX,2017,44.238365545839905
-Luxembourg,LUX,2018,46.37452962364919
-Macedonia,MKD,1990,29.499792333224303
-Macedonia,MKD,1991,29.171477204289964
-Macedonia,MKD,1992,29.960999439338217
-Macedonia,MKD,1993,30.10960690962455
-Macedonia,MKD,1994,28.21565314498416
-Macedonia,MKD,1995,28.39048204072591
-Macedonia,MKD,1996,33.00371929703541
-Macedonia,MKD,1997,29.72075121520854
-Macedonia,MKD,1998,33.57156976166213
-Macedonia,MKD,1999,32.05196899169684
-Macedonia,MKD,2000,30.46698617964638
-Macedonia,MKD,2001,28.832879559033568
-Macedonia,MKD,2002,28.144042697570946
-Macedonia,MKD,2003,31.606624531222845
-Macedonia,MKD,2004,31.20646641521417
-Macedonia,MKD,2005,32.20094540719113
-Macedonia,MKD,2006,32.73651696195275
-Macedonia,MKD,2007,32.642620239328224
-Macedonia,MKD,2008,31.58118874680562
-Macedonia,MKD,2009,31.05549981401511
-Macedonia,MKD,2010,33.54062807056507
-Macedonia,MKD,2011,33.625340491814846
-Macedonia,MKD,2012,31.255142042995246
-Macedonia,MKD,2013,29.973642748411606
-Macedonia,MKD,2014,27.864222870128625
-Macedonia,MKD,2015,29.348505042391153
-Macedonia,MKD,2016,30.477574345740027
-Macedonia,MKD,2017,29.434250920355122
-Macedonia,MKD,2018,30.771172812656104
-Malaysia,MYS,1965,28.862792764416643
-Malaysia,MYS,1966,33.68862531063892
-Malaysia,MYS,1967,34.04625538655559
-Malaysia,MYS,1968,34.69531059394441
-Malaysia,MYS,1969,36.32006723611108
-Malaysia,MYS,1970,40.59018792555945
-Malaysia,MYS,1971,45.163013976082276
-Malaysia,MYS,1972,50.52907517978705
-Malaysia,MYS,1973,54.62254246660874
-Malaysia,MYS,1974,55.67450202020593
-Malaysia,MYS,1975,57.798909520208554
-Malaysia,MYS,1976,64.01057242756126
-Malaysia,MYS,1977,71.05672762607452
-Malaysia,MYS,1978,97.1387363178295
-Malaysia,MYS,1979,118.77162599483258
-Malaysia,MYS,1980,127.86659753875969
-Malaysia,MYS,1981,131.17310458656326
-Malaysia,MYS,1982,141.3343394250648
-Malaysia,MYS,1983,162.39697420542683
-Malaysia,MYS,1984,175.12017760335877
-Malaysia,MYS,1985,173.32591039269627
-Malaysia,MYS,1986,194.33983176832587
-Malaysia,MYS,1987,200.30663841833308
-Malaysia,MYS,1988,212.53144014517932
-Malaysia,MYS,1989,237.51883216034275
-Malaysia,MYS,1990,256.6939615605875
-Malaysia,MYS,1991,310.90723965116257
-Malaysia,MYS,1992,336.29143100537163
-Malaysia,MYS,1993,350.662295318917
-Malaysia,MYS,1994,382.6091271426624
-Malaysia,MYS,1995,398.8024485839119
-Malaysia,MYS,1996,445.56367814429507
-Malaysia,MYS,1997,518.5980843903851
-Malaysia,MYS,1998,482.15469546919655
-Malaysia,MYS,1999,545.5129566911469
-Malaysia,MYS,2000,607.1999922664223
-Malaysia,MYS,2001,611.6920861699305
-Malaysia,MYS,2002,655.0230435012915
-Malaysia,MYS,2003,712.6396689222082
-Malaysia,MYS,2004,759.4088336773345
-Malaysia,MYS,2005,810.3648299660173
-Malaysia,MYS,2006,842.2156532966138
-Malaysia,MYS,2007,897.9963204847741
-Malaysia,MYS,2008,929.8794932686718
-Malaysia,MYS,2009,903.8923465821782
-Malaysia,MYS,2010,931.4359840046412
-Malaysia,MYS,2011,963.9932235668257
-Malaysia,MYS,2012,1035.1011339844063
-Malaysia,MYS,2013,1082.4110992877754
-Malaysia,MYS,2014,1089.0104203438173
-Malaysia,MYS,2015,1106.317906558808
-Malaysia,MYS,2016,1123.1014731811208
-Malaysia,MYS,2017,1124.9293269297432
-Malaysia,MYS,2018,1154.850234383959
-Mexico,MEX,1965,290.4355701705385
-Mexico,MEX,1966,307.41332887674497
-Mexico,MEX,1967,313.1054467467597
-Mexico,MEX,1968,340.65580595855266
-Mexico,MEX,1969,374.44350626811297
-Mexico,MEX,1970,399.14609191798235
-Mexico,MEX,1971,419.78162184762084
-Mexico,MEX,1972,464.23150254614137
-Mexico,MEX,1973,500.84938070782795
-Mexico,MEX,1974,552.3392530852819
-Mexico,MEX,1975,590.5203443229158
-Mexico,MEX,1976,628.1318341060734
-Mexico,MEX,1977,662.3619838272543
-Mexico,MEX,1978,747.0919993271067
-Mexico,MEX,1979,825.9854796390056
-Mexico,MEX,1980,900.663750873957
-Mexico,MEX,1981,993.8785816123067
-Mexico,MEX,1982,1036.5280683763121
-Mexico,MEX,1983,1025.663333156251
-Mexico,MEX,1984,1072.866603659469
-Mexico,MEX,1985,1124.8076437961722
-Mexico,MEX,1986,1093.0450077680205
-Mexico,MEX,1987,1129.7138755775431
-Mexico,MEX,1988,1137.4049917581306
-Mexico,MEX,1989,1200.5375408940263
-Mexico,MEX,1990,1263.0642091390553
-Mexico,MEX,1991,1312.2814881076956
-Mexico,MEX,1992,1334.4386333860602
-Mexico,MEX,1993,1341.115738368181
-Mexico,MEX,1994,1419.729949287179
-Mexico,MEX,1995,1395.5166237384856
-Mexico,MEX,1996,1439.235915025888
-Mexico,MEX,1997,1464.465419605726
-Mexico,MEX,1998,1530.3521170529218
-Mexico,MEX,1999,1548.4250748707427
-Mexico,MEX,2000,1621.2166351400456
-Mexico,MEX,2001,1602.6966226562274
-Mexico,MEX,2002,1655.147249889814
-Mexico,MEX,2003,1670.05298635881
-Mexico,MEX,2004,1760.5618220507297
-Mexico,MEX,2005,1874.1794489925887
-Mexico,MEX,2006,1934.2899369937925
-Mexico,MEX,2007,1945.290340190903
-Mexico,MEX,2008,1986.8254189796837
-Mexico,MEX,2009,1971.7857960385757
-Mexico,MEX,2010,2030.3438329458265
-Mexico,MEX,2011,2128.925878492728
-Mexico,MEX,2012,2142.0360154622135
-Mexico,MEX,2013,2151.944519176614
-Mexico,MEX,2014,2141.568717637382
-Mexico,MEX,2015,2139.575795967157
-Mexico,MEX,2016,2167.347883580739
-Mexico,MEX,2017,2201.566076383148
-Mexico,MEX,2018,2173.807726627447
-Middle Africa,,1965,33.790227759222404
-Middle Africa,,1966,34.93225668977215
-Middle Africa,,1967,36.53054884543308
-Middle Africa,,1968,38.75861356202762
-Middle Africa,,1969,40.64730999384807
-Middle Africa,,1970,42.48835133881569
-Middle Africa,,1971,49.103223222381686
-Middle Africa,,1972,50.959357468582255
-Middle Africa,,1973,56.86375282726559
-Middle Africa,,1974,58.909051198040885
-Middle Africa,,1975,55.25487055031554
-Middle Africa,,1976,54.63627221543679
-Middle Africa,,1977,57.63519134487213
-Middle Africa,,1978,64.20950996162577
-Middle Africa,,1979,65.1744561626046
-Middle Africa,,1980,67.80875566685862
-Middle Africa,,1981,72.1070998627927
-Middle Africa,,1982,69.68877989123042
-Middle Africa,,1983,77.16380690070415
-Middle Africa,,1984,73.05504431759216
-Middle Africa,,1985,81.88093240029055
-Middle Africa,,1986,81.39081430031207
-Middle Africa,,1987,83.26875457956315
-Middle Africa,,1988,87.53381262820005
-Middle Africa,,1989,91.85944917844951
-Middle Africa,,1990,85.0418490752833
-Middle Africa,,1991,79.88120662492939
-Middle Africa,,1992,81.80592570943818
-Middle Africa,,1993,81.89321653015354
-Middle Africa,,1994,79.58075236012911
-Middle Africa,,1995,81.69136750454848
-Middle Africa,,1996,82.18224221856343
-Middle Africa,,1997,82.02290730711694
-Middle Africa,,1998,79.00580957848379
-Middle Africa,,1999,82.50644566336852
-Middle Africa,,2000,90.05890712488984
-Middle Africa,,2001,101.52126294652004
-Middle Africa,,2002,107.59237027090636
-Middle Africa,,2003,117.07960821899908
-Middle Africa,,2004,131.4342790427874
-Middle Africa,,2005,131.92797973833703
-Middle Africa,,2006,145.3938256187248
-Middle Africa,,2007,149.1697090400252
-Middle Africa,,2008,169.01424774833723
-Middle Africa,,2009,179.6430088240256
-Middle Africa,,2010,193.55408764521977
-Middle Africa,,2011,210.39465044919658
-Middle Africa,,2012,214.59404169763084
-Middle Africa,,2013,228.9487855432747
-Middle Africa,,2014,240.82475422147698
-Middle Africa,,2015,234.47001329047058
-Middle Africa,,2016,244.84730364292847
-Middle Africa,,2017,254.17568254966983
-Middle Africa,,2018,266.2348522785487
-Middle East,,1965,561.4094753361031
-Middle East,,1966,585.3364189259314
-Middle East,,1967,612.4623033901796
-Middle East,,1968,646.450219491899
-Middle East,,1969,680.0805547768631
-Middle East,,1970,714.978789822836
-Middle East,,1971,757.0964813800279
-Middle East,,1972,823.5227715107023
-Middle East,,1973,902.4664005286799
-Middle East,,1974,961.0591368334901
-Middle East,,1975,959.0271123362097
-Middle East,,1976,1085.1335366143264
-Middle East,,1977,1233.7959964641839
-Middle East,,1978,1293.2584952353407
-Middle East,,1979,1518.9456521825502
-Middle East,,1980,1469.7778320185669
-Middle East,,1981,1601.1805385576204
-Middle East,,1982,1773.6107063121424
-Middle East,,1983,1940.440666330837
-Middle East,,1984,2192.492620350803
-Middle East,,1985,2331.5712581869857
-Middle East,,1986,2435.5800171494147
-Middle East,,1987,2605.496637827771
-Middle East,,1988,2767.9652147348124
-Middle East,,1989,2917.693649152668
-Middle East,,1990,3014.4537823019145
-Middle East,,1991,3148.9934558451077
-Middle East,,1992,3433.7478927027887
-Middle East,,1993,3536.005252344063
-Middle East,,1994,3947.067109223678
-Middle East,,1995,4084.6679654680456
-Middle East,,1996,4215.5973808406725
-Middle East,,1997,4417.01265299148
-Middle East,,1998,4489.485602990267
-Middle East,,1999,4570.561476078293
-Middle East,,2000,4801.8999492805215
-Middle East,,2001,5035.957261668717
-Middle East,,2002,5312.897354669109
-Middle East,,2003,5546.521126299047
-Middle East,,2004,5976.944614139297
-Middle East,,2005,6387.858689541813
-Middle East,,2006,6713.692583636376
-Middle East,,2007,7091.871787080568
-Middle East,,2008,7602.660559885327
-Middle East,,2009,7836.487404295822
-Middle East,,2010,8255.216254636349
-Middle East,,2011,8587.724653378496
-Middle East,,2012,8924.21372776715
-Middle East,,2013,9216.91672070288
-Middle East,,2014,9503.66488902628
-Middle East,,2015,9811.90528801844
-Middle East,,2016,10058.873425512096
-Middle East,,2017,10250.507226853251
-Middle East,,2018,10493.619931743013
-Morocco,MAR,1965,17.957445137686413
-Morocco,MAR,1966,22.62252289383678
-Morocco,MAR,1967,24.04677351243769
-Morocco,MAR,1968,26.261629954859128
-Morocco,MAR,1969,28.835760213381178
-Morocco,MAR,1970,29.923720998863743
-Morocco,MAR,1971,31.83256782333327
-Morocco,MAR,1972,34.46996039333333
-Morocco,MAR,1973,38.425873614152
-Morocco,MAR,1974,41.04761629040932
-Morocco,MAR,1975,42.03476286052636
-Morocco,MAR,1976,45.48806896836251
-Morocco,MAR,1977,51.10455708315787
-Morocco,MAR,1978,54.40436018725141
-Morocco,MAR,1979,59.400129681403534
-Morocco,MAR,1980,60.25999619304096
-Morocco,MAR,1981,58.73599557877193
-Morocco,MAR,1982,60.005169381228114
-Morocco,MAR,1983,62.07001819590639
-Morocco,MAR,1984,63.77012949251458
-Morocco,MAR,1985,65.14462286175443
-Morocco,MAR,1986,67.32590904760227
-Morocco,MAR,1987,69.29659430824559
-Morocco,MAR,1988,73.18225631362576
-Morocco,MAR,1989,80.47056559543856
-Morocco,MAR,1990,82.3587607346784
-Morocco,MAR,1991,83.40485619725148
-Morocco,MAR,1992,93.46561942081874
-Morocco,MAR,1993,94.6217378603509
-Morocco,MAR,1994,104.18108164356721
-Morocco,MAR,1995,102.25300851573101
-Morocco,MAR,1996,106.47673592222226
-Morocco,MAR,1997,110.67596227625727
-Morocco,MAR,1998,113.63344277169587
-Morocco,MAR,1999,118.22355533046846
-Morocco,MAR,2000,117.2089010679538
-Morocco,MAR,2001,126.57838743146156
-Morocco,MAR,2002,129.7637491143006
-Morocco,MAR,2003,129.97915365974092
-Morocco,MAR,2004,148.07765633374558
-Morocco,MAR,2005,160.81603978008985
-Morocco,MAR,2006,164.10974999778085
-Morocco,MAR,2007,162.57379965666948
-Morocco,MAR,2008,179.47305925260463
-Morocco,MAR,2009,174.83820455028652
-Morocco,MAR,2010,193.86873708955483
-Morocco,MAR,2011,203.79267807759905
-Morocco,MAR,2012,207.37692279593276
-Morocco,MAR,2013,212.84003230037646
-Morocco,MAR,2014,216.00568215897917
-Morocco,MAR,2015,219.82534236450002
-Morocco,MAR,2016,222.2724897871349
-Morocco,MAR,2017,232.82498091120502
-Morocco,MAR,2018,244.18719264091908
-Netherlands,NLD,1965,413.9600936111114
-Netherlands,NLD,1966,443.3774338888891
-Netherlands,NLD,1967,468.8000280555557
-Netherlands,NLD,1968,524.3718247222222
-Netherlands,NLD,1969,584.7302955555562
-Netherlands,NLD,1970,659.742096666667
-Netherlands,NLD,1971,695.7157786111109
-Netherlands,NLD,1972,808.0853933333335
-Netherlands,NLD,1973,859.4568991666672
-Netherlands,NLD,1974,814.6718530555555
-Netherlands,NLD,1975,821.09644872807
-Netherlands,NLD,1976,895.4260657309949
-Netherlands,NLD,1977,880.0585811695906
-Netherlands,NLD,1978,896.3202823657658
-Netherlands,NLD,1979,926.8887576249512
-Netherlands,NLD,1980,869.9844546159737
-Netherlands,NLD,1981,825.1718659389552
-Netherlands,NLD,1982,762.7461183503299
-Netherlands,NLD,1983,766.5225215962098
-Netherlands,NLD,1984,795.9240555176867
-Netherlands,NLD,1985,821.7862835483805
-Netherlands,NLD,1986,862.4530561862507
-Netherlands,NLD,1987,880.2974413814818
-Netherlands,NLD,1988,883.139387104297
-Netherlands,NLD,1989,887.1087630407333
-Netherlands,NLD,1990,909.5920298005944
-Netherlands,NLD,1991,926.8947869794921
-Netherlands,NLD,1992,937.8260547150554
-Netherlands,NLD,1993,945.5824242898933
-Netherlands,NLD,1994,935.3554542211506
-Netherlands,NLD,1995,973.4321176857287
-Netherlands,NLD,1996,1015.3472964592738
-Netherlands,NLD,1997,997.3492917715522
-Netherlands,NLD,1998,1004.0202074300104
-Netherlands,NLD,1999,991.7449041785895
-Netherlands,NLD,2000,1004.5650916514284
-Netherlands,NLD,2001,1043.1978210086538
-Netherlands,NLD,2002,1043.4607252663445
-Netherlands,NLD,2003,1050.6582681483953
-Netherlands,NLD,2004,1085.8703402323886
-Netherlands,NLD,2005,1108.3119029379357
-Netherlands,NLD,2006,1085.7179820212089
-Netherlands,NLD,2007,1104.2764813093365
-Netherlands,NLD,2008,1090.5515648650455
-Netherlands,NLD,2009,1074.9872943725181
-Netherlands,NLD,2010,1137.983017611443
-Netherlands,NLD,2011,1089.5114335110518
-Netherlands,NLD,2012,1054.1184275573546
-Netherlands,NLD,2013,1022.8494110669366
-Netherlands,NLD,2014,966.4267227609052
-Netherlands,NLD,2015,978.6599893847855
-Netherlands,NLD,2016,996.3340068845852
-Netherlands,NLD,2017,982.7806657443687
-Netherlands,NLD,2018,986.0880219385213
-New Zealand,NZL,1965,81.6801067543859
-New Zealand,NZL,1966,86.75314634502928
-New Zealand,NZL,1967,87.4560188596491
-New Zealand,NZL,1968,89.37743723684216
-New Zealand,NZL,1969,91.01730387426896
-New Zealand,NZL,1970,101.42340472222214
-New Zealand,NZL,1971,105.85871260233921
-New Zealand,NZL,1972,113.01244695906438
-New Zealand,NZL,1973,117.80760040935715
-New Zealand,NZL,1974,118.24964573937245
-New Zealand,NZL,1975,119.26908461599288
-New Zealand,NZL,1976,123.85148766051404
-New Zealand,NZL,1977,126.91877444591739
-New Zealand,NZL,1978,124.99185386159483
-New Zealand,NZL,1979,125.92940736958407
-New Zealand,NZL,1980,126.37513974628786
-New Zealand,NZL,1981,126.71436651753282
-New Zealand,NZL,1982,131.37930761018936
-New Zealand,NZL,1983,136.32389808318348
-New Zealand,NZL,1984,143.94292030458655
-New Zealand,NZL,1985,145.64772133170163
-New Zealand,NZL,1986,152.33767077175295
-New Zealand,NZL,1987,156.9769735375028
-New Zealand,NZL,1988,160.99128588016558
-New Zealand,NZL,1989,164.80481876242487
-New Zealand,NZL,1990,171.21474143104368
-New Zealand,NZL,1991,176.83992854295172
-New Zealand,NZL,1992,178.06717217652232
-New Zealand,NZL,1993,183.4141998276277
-New Zealand,NZL,1994,194.84495237163193
-New Zealand,NZL,1995,201.1000650841631
-New Zealand,NZL,1996,206.67980073814968
-New Zealand,NZL,1997,208.6874181340691
-New Zealand,NZL,1998,208.46733006315753
-New Zealand,NZL,1999,210.66135167770486
-New Zealand,NZL,2000,219.85435785092557
-New Zealand,NZL,2001,219.02409964683858
-New Zealand,NZL,2002,226.98107801958827
-New Zealand,NZL,2003,220.41750365145145
-New Zealand,NZL,2004,228.0788157104949
-New Zealand,NZL,2005,221.2624763145691
-New Zealand,NZL,2006,223.87016286123526
-New Zealand,NZL,2007,223.6653218874445
-New Zealand,NZL,2008,224.7211211171855
-New Zealand,NZL,2009,223.80972223171128
-New Zealand,NZL,2010,231.21717282797204
-New Zealand,NZL,2011,229.66897799727707
-New Zealand,NZL,2012,232.34783238220453
-New Zealand,NZL,2013,235.07851912340848
-New Zealand,NZL,2014,246.54853562733615
-New Zealand,NZL,2015,248.3235525069312
-New Zealand,NZL,2016,250.76116376577716
-New Zealand,NZL,2017,257.80862996936906
-New Zealand,NZL,2018,252.82263129953392
-North America,,1965,16171.820137905172
-North America,,1966,17089.84765381383
-North America,,1967,17697.166772199103
-North America,,1968,18793.134462156027
-North America,,1969,19813.92978079766
-North America,,1970,20559.041491230822
-North America,,1971,21005.634290985683
-North America,,1972,22137.74157152797
-North America,,1973,23103.594598187672
-North America,,1974,22701.772223877928
-North America,,1975,22218.213705152404
-North America,,1976,23443.196883157714
-North America,,1977,24128.849572941657
-North America,,1978,24338.487390029084
-North America,,1979,24699.941461076938
-North America,,1980,24054.38704846231
-North America,,1981,23468.93998842471
-North America,,1982,22696.473668779883
-North America,,1983,22574.869186512005
-North America,,1984,23797.656316393164
-North America,,1985,23877.679354744065
-North America,,1986,23966.241563561936
-North America,,1987,24781.550577697064
-North America,,1988,25859.028995304376
-North America,,1989,26468.39718578985
-North America,,1990,26516.228994800884
-North America,,1991,26531.2317765977
-North America,,1992,26966.84520908619
-North America,,1993,27510.936253056283
-North America,,1994,28133.04487597688
-North America,,1995,28675.043928329622
-North America,,1996,29614.752411788944
-North America,,1997,29864.136533743233
-North America,,1998,30051.03736476611
-North America,,1999,30615.017665030256
-North America,,2000,31375.938859108104
-North America,,2001,30684.4794707478
-North America,,2002,31234.67918099587
-North America,,2003,31377.478792113838
-North America,,2004,32052.04391386819
-North America,,2005,32240.452576358286
-North America,,2006,32065.669940409127
-North America,,2007,32604.651650203537
-North America,,2008,31994.260700870298
-North America,,2009,30506.749864037854
-North America,,2010,31515.213161112883
-North America,,2011,31568.552927292316
-North America,,2012,30905.102744064276
-North America,,2013,31750.8202889215
-North America,,2014,32085.85645773006
-North America,,2015,31822.278028924884
-North America,,2016,31834.14723837123
-North America,,2017,32046.209621687736
-North America,,2018,32935.90731321991
-Norway,NOR,1965,199.10104350777783
-Norway,NOR,1966,204.3975330777774
-Norway,NOR,1967,219.3991582411114
-Norway,NOR,1968,245.63467979666697
-Norway,NOR,1969,246.95988048222208
-Norway,NOR,1970,259.212358175555
-Norway,NOR,1971,273.6116725688885
-Norway,NOR,1972,290.013375638889
-Norway,NOR,1973,306.9035789088893
-Norway,NOR,1974,306.7773764866671
-Norway,NOR,1975,311.5040987422223
-Norway,NOR,1976,333.46135581222177
-Norway,NOR,1977,308.4265118422227
-Norway,NOR,1978,346.03209941333375
-Norway,NOR,1979,370.1233946800003
-Norway,NOR,1980,352.6639100022217
-Norway,NOR,1981,371.14839029555606
-Norway,NOR,1982,366.4330825622218
-Norway,NOR,1983,401.36573559555586
-Norway,NOR,1984,406.9502880400006
-Norway,NOR,1985,402.1257656809345
-Norway,NOR,1986,393.5235154384198
-Norway,NOR,1987,412.7327468772501
-Norway,NOR,1988,424.6586813241512
-Norway,NOR,1989,451.64293560011623
-Norway,NOR,1990,455.8564492532515
-Norway,NOR,1991,420.83581370274703
-Norway,NOR,1992,442.9710760932576
-Norway,NOR,1993,457.4949924435046
-Norway,NOR,1994,442.9942428416684
-Norway,NOR,1995,469.0815064154271
-Norway,NOR,1996,432.74288868653474
-Norway,NOR,1997,454.7943567504043
-Norway,NOR,1998,472.4635223518637
-Norway,NOR,1999,484.1186567332834
-Norway,NOR,2000,534.2051965135344
-Norway,NOR,2001,487.961097330873
-Norway,NOR,2002,508.8442802409884
-Norway,NOR,2003,453.4604904205348
-Norway,NOR,2004,463.4798195627405
-Norway,NOR,2005,529.0139161638015
-Norway,NOR,2006,487.41674381874907
-Norway,NOR,2007,524.7253246566137
-Norway,NOR,2008,539.4345480742497
-Norway,NOR,2009,500.709409408148
-Norway,NOR,2010,483.2746864413113
-Norway,NOR,2011,492.9949293540692
-Norway,NOR,2012,549.8535535804514
-Norway,NOR,2013,515.348866714301
-Norway,NOR,2014,531.6483842264718
-Norway,NOR,2015,541.1740171729516
-Norway,NOR,2016,549.2282559471997
-Norway,NOR,2017,553.9895192407646
-Norway,NOR,2018,551.0421487509285
-Oman,OMN,1965,5.291939166666668
-Oman,OMN,1966,5.5202780555555515
-Oman,OMN,1967,5.759781666666671
-Oman,OMN,1968,6.022882500000005
-Oman,OMN,1969,6.273933333333329
-Oman,OMN,1970,6.561514722222218
-Oman,OMN,1971,15.471502777777827
-Oman,OMN,1972,17.677216666666723
-Oman,OMN,1973,15.375913888888883
-Oman,OMN,1974,14.127883333333378
-Oman,OMN,1975,12.904697222222245
-Oman,OMN,1976,14.856397222222265
-Oman,OMN,1977,14.312168888888948
-Oman,OMN,1978,16.64237638888893
-Oman,OMN,1979,19.17322694444448
-Oman,OMN,1980,17.058377777777796
-Oman,OMN,1981,18.02799749999998
-Oman,OMN,1982,23.881949444444444
-Oman,OMN,1983,22.350086388888922
-Oman,OMN,1984,32.493594722222234
-Oman,OMN,1985,33.571021111111065
-Oman,OMN,1986,31.459568611111095
-Oman,OMN,1987,35.43523500000001
-Oman,OMN,1988,34.38907666666665
-Oman,OMN,1989,39.01986250000003
-Oman,OMN,1990,48.86399166666672
-Oman,OMN,1991,64.8682466666667
-Oman,OMN,1992,62.49089861111113
-Oman,OMN,1993,59.8380080555556
-Oman,OMN,1994,56.84055124294433
-Oman,OMN,1995,65.89965408803272
-Oman,OMN,1996,67.78353564329402
-Oman,OMN,1997,69.71264101147702
-Oman,OMN,1998,71.64712888664364
-Oman,OMN,1999,82.48155384588505
-Oman,OMN,2000,114.5245906918614
-Oman,OMN,2001,126.48572001099987
-Oman,OMN,2002,137.64600530157867
-Oman,OMN,2003,142.57997596349733
-Oman,OMN,2004,132.4522922100182
-Oman,OMN,2005,159.32631457482643
-Oman,OMN,2006,174.04108614090063
-Oman,OMN,2007,173.57794460405268
-Oman,OMN,2008,203.93386142209616
-Oman,OMN,2009,204.33816844106354
-Oman,OMN,2010,240.05752498042315
-Oman,OMN,2011,262.2162777782752
-Oman,OMN,2012,285.0694841427613
-Oman,OMN,2013,318.43206949563324
-Oman,OMN,2014,317.11862984619177
-Oman,OMN,2015,334.98185126917673
-Oman,OMN,2016,336.89659542485634
-Oman,OMN,2017,341.14854042153496
-Oman,OMN,2018,356.9154646492128
-Other Asia & Pacific,,1965,189.65560049091442
-Other Asia & Pacific,,1966,201.37595585646952
-Other Asia & Pacific,,1967,219.0271624127035
-Other Asia & Pacific,,1968,235.77727495706478
-Other Asia & Pacific,,1969,250.31298698420736
-Other Asia & Pacific,,1970,266.9858778409897
-Other Asia & Pacific,,1971,292.71679539165433
-Other Asia & Pacific,,1972,303.64218754906204
-Other Asia & Pacific,,1973,314.4226221561983
-Other Asia & Pacific,,1974,336.21620585199133
-Other Asia & Pacific,,1975,345.40419068170957
-Other Asia & Pacific,,1976,363.3750439774996
-Other Asia & Pacific,,1977,383.96716173056785
-Other Asia & Pacific,,1978,405.64026608648606
-Other Asia & Pacific,,1979,437.24820958676816
-Other Asia & Pacific,,1980,468.78926721806863
-Other Asia & Pacific,,1981,481.3380428565706
-Other Asia & Pacific,,1982,502.10748443663806
-Other Asia & Pacific,,1983,522.142047995243
-Other Asia & Pacific,,1984,531.1286827253125
-Other Asia & Pacific,,1985,566.7546925045198
-Other Asia & Pacific,,1986,572.7170693312663
-Other Asia & Pacific,,1987,557.1205766939619
-Other Asia & Pacific,,1988,565.2513997494997
-Other Asia & Pacific,,1989,558.852138883567
-Other Asia & Pacific,,1990,546.2839804402416
-Other Asia & Pacific,,1991,537.9321534034708
-Other Asia & Pacific,,1992,487.9751851632183
-Other Asia & Pacific,,1993,467.13742763130074
-Other Asia & Pacific,,1994,448.3002103880559
-Other Asia & Pacific,,1995,443.0440141433426
-Other Asia & Pacific,,1996,409.74834171887795
-Other Asia & Pacific,,1997,406.12339773103946
-Other Asia & Pacific,,1998,390.3157871027124
-Other Asia & Pacific,,1999,411.27522757080976
-Other Asia & Pacific,,2000,438.4082159082215
-Other Asia & Pacific,,2001,455.2166495005974
-Other Asia & Pacific,,2002,448.38792013365486
-Other Asia & Pacific,,2003,472.70454205201366
-Other Asia & Pacific,,2004,479.92215337775076
-Other Asia & Pacific,,2005,504.80631647906773
-Other Asia & Pacific,,2006,523.5724886533841
-Other Asia & Pacific,,2007,512.6124021761541
-Other Asia & Pacific,,2008,536.8284504636149
-Other Asia & Pacific,,2009,490.92214143546335
-Other Asia & Pacific,,2010,527.761178859239
-Other Asia & Pacific,,2011,526.1304463994712
-Other Asia & Pacific,,2012,561.4522195345568
-Other Asia & Pacific,,2013,567.137483816757
-Other Asia & Pacific,,2014,613.1754122385938
-Other Asia & Pacific,,2015,627.3375126310706
-Other Asia & Pacific,,2016,704.1099874184868
-Other Asia & Pacific,,2017,725.3637294597162
-Other Asia & Pacific,,2018,760.40987591313
-Other CIS,,1985,385.2375784561139
-Other CIS,,1986,367.76880343078767
-Other CIS,,1987,378.339014421497
-Other CIS,,1988,417.44445062205057
-Other CIS,,1989,400.49582949962917
-Other CIS,,1990,400.6403081877884
-Other CIS,,1991,335.4694223791902
-Other CIS,,1992,282.99198109671664
-Other CIS,,1993,223.82496733989038
-Other CIS,,1994,186.2302125770409
-Other CIS,,1995,162.72859092426006
-Other CIS,,1996,175.1036657634392
-Other CIS,,1997,165.89044600243798
-Other CIS,,1998,165.13590500028872
-Other CIS,,1999,157.38625498457006
-Other CIS,,2000,151.7752372668114
-Other CIS,,2001,149.5869698270477
-Other CIS,,2002,149.9821358231864
-Other CIS,,2003,158.0506996124266
-Other CIS,,2004,171.16261193450555
-Other CIS,,2005,177.91907744688
-Other CIS,,2006,179.43241183646205
-Other CIS,,2007,194.61445470283346
-Other CIS,,2008,188.35049694863014
-Other CIS,,2009,181.27925038791636
-Other CIS,,2010,184.9036243194829
-Other CIS,,2011,197.59388272702566
-Other CIS,,2012,208.76547570221672
-Other CIS,,2013,198.83692828948503
-Other CIS,,2014,203.9076700994507
-Other CIS,,2015,202.88833369076886
-Other CIS,,2016,204.05905314774196
-Other CIS,,2017,209.02108785631597
-Other CIS,,2018,221.358680276232
-Other Caribbean,,1965,174.78273780820115
-Other Caribbean,,1966,182.8118200283623
-Other Caribbean,,1967,190.37164727381054
-Other Caribbean,,1968,195.81217162738665
-Other Caribbean,,1969,207.8317221419787
-Other Caribbean,,1970,224.76100659738105
-Other Caribbean,,1971,321.9597700757386
-Other Caribbean,,1972,332.07845026976054
-Other Caribbean,,1973,361.6224053664168
-Other Caribbean,,1974,359.90317345260956
-Other Caribbean,,1975,347.6347710679376
-Other Caribbean,,1976,361.24300351258046
-Other Caribbean,,1977,372.56884728772457
-Other Caribbean,,1978,385.1228006650773
-Other Caribbean,,1979,405.5341225763542
-Other Caribbean,,1980,448.0614600971784
-Other Caribbean,,1981,454.05952803548274
-Other Caribbean,,1982,411.2543873759835
-Other Caribbean,,1983,407.69619359391174
-Other Caribbean,,1984,412.97796334190383
-Other Caribbean,,1985,384.59958153480983
-Other Caribbean,,1986,383.50839601131486
-Other Caribbean,,1987,395.67039454609886
-Other Caribbean,,1988,396.49246553635027
-Other Caribbean,,1989,411.6457642351271
-Other Caribbean,,1990,411.24634871956255
-Other Caribbean,,1991,399.81818842116115
-Other Caribbean,,1992,379.0731455220565
-Other Caribbean,,1993,377.512725539307
-Other Caribbean,,1994,395.25252971989323
-Other Caribbean,,1995,397.67640476215826
-Other Caribbean,,1996,412.6834163940832
-Other Caribbean,,1997,448.4834658717484
-Other Caribbean,,1998,465.67340569539425
-Other Caribbean,,1999,446.84874662901456
-Other Caribbean,,2000,495.3950693089652
-Other Caribbean,,2001,504.3058654253304
-Other Caribbean,,2002,512.7008029304377
-Other Caribbean,,2003,524.5774402870933
-Other Caribbean,,2004,530.6073697447844
-Other Caribbean,,2005,532.6671888213943
-Other Caribbean,,2006,545.1137263464536
-Other Caribbean,,2007,530.6495080387995
-Other Caribbean,,2008,506.5529505013749
-Other Caribbean,,2009,479.4761296639808
-Other Caribbean,,2010,478.3555936942854
-Other Caribbean,,2011,485.5109394410783
-Other Caribbean,,2012,471.5027219926814
-Other Caribbean,,2013,458.119628909192
-Other Caribbean,,2014,459.56183612965515
-Other Caribbean,,2015,468.3665797248601
-Other Caribbean,,2016,483.7653612148162
-Other Caribbean,,2017,484.63584166553954
-Other Caribbean,,2018,493.24398091148635
-Other Middle East,,1965,71.85889595505549
-Other Middle East,,1966,75.1344438269019
-Other Middle East,,1967,78.77254032977035
-Other Middle East,,1968,82.54602232520618
-Other Middle East,,1969,86.67432620155724
-Other Middle East,,1970,86.18015072640581
-Other Middle East,,1971,92.33321735394959
-Other Middle East,,1972,92.66646372333746
-Other Middle East,,1973,102.68200307415543
-Other Middle East,,1974,114.33771486725584
-Other Middle East,,1975,125.74206078241266
-Other Middle East,,1976,140.86627841641078
-Other Middle East,,1977,155.61312453658897
-Other Middle East,,1978,165.37813876793155
-Other Middle East,,1979,189.8827640497265
-Other Middle East,,1980,182.40141666962916
-Other Middle East,,1981,191.6301996468435
-Other Middle East,,1982,225.15526489379573
-Other Middle East,,1983,240.47320069564455
-Other Middle East,,1984,259.3347079750229
-Other Middle East,,1985,272.4894249571401
-Other Middle East,,1986,276.7917929066761
-Other Middle East,,1987,291.1998977710073
-Other Middle East,,1988,299.9876565897481
-Other Middle East,,1989,305.9102411439141
-Other Middle East,,1990,322.08505330050014
-Other Middle East,,1991,340.66488610247745
-Other Middle East,,1992,354.47954433110004
-Other Middle East,,1993,366.23480336143643
-Other Middle East,,1994,378.24962401790026
-Other Middle East,,1995,406.1777383705827
-Other Middle East,,1996,411.0477494484644
-Other Middle East,,1997,448.9024678022901
-Other Middle East,,1998,475.9120838192482
-Other Middle East,,1999,479.52570078095516
-Other Middle East,,2000,486.6537440464917
-Other Middle East,,2001,499.9978361789408
-Other Middle East,,2002,518.8729808158157
-Other Middle East,,2003,541.5997492065741
-Other Middle East,,2004,558.0941232192957
-Other Middle East,,2005,609.4227944104629
-Other Middle East,,2006,632.2802522662064
-Other Middle East,,2007,654.9117797164843
-Other Middle East,,2008,677.6749511774474
-Other Middle East,,2009,680.1982890419774
-Other Middle East,,2010,677.1531861097455
-Other Middle East,,2011,636.6319395206988
-Other Middle East,,2012,594.4343210704194
-Other Middle East,,2013,584.5051914063176
-Other Middle East,,2014,582.189656841593
-Other Middle East,,2015,562.453819001195
-Other Middle East,,2016,557.7991071437206
-Other Middle East,,2017,558.3064935393877
-Other Middle East,,2018,556.9315343789482
-Other Northern Africa,,1965,17.52508856223459
-Other Northern Africa,,1966,19.19670840500067
-Other Northern Africa,,1967,20.445144929460685
-Other Northern Africa,,1968,23.315377282860506
-Other Northern Africa,,1969,25.994050932137572
-Other Northern Africa,,1970,30.81143310962559
-Other Northern Africa,,1971,28.474137620539047
-Other Northern Africa,,1972,36.067692626828276
-Other Northern Africa,,1973,49.04354032146429
-Other Northern Africa,,1974,53.89957027579855
-Other Northern Africa,,1975,60.192831583046676
-Other Northern Africa,,1976,70.56340968234282
-Other Northern Africa,,1977,80.07725094713565
-Other Northern Africa,,1978,89.16209554033085
-Other Northern Africa,,1979,116.09863267199886
-Other Northern Africa,,1980,120.73186703719423
-Other Northern Africa,,1981,128.71391033232615
-Other Northern Africa,,1982,131.82913162516482
-Other Northern Africa,,1983,138.79324606960878
-Other Northern Africa,,1984,137.5357245961311
-Other Northern Africa,,1985,154.79124701397754
-Other Northern Africa,,1986,158.52014819220196
-Other Northern Africa,,1987,175.55713819581044
-Other Northern Africa,,1988,178.42607841368832
-Other Northern Africa,,1989,192.2446538771723
-Other Northern Africa,,1990,187.9342373293598
-Other Northern Africa,,1991,186.40498301718998
-Other Northern Africa,,1992,186.77345839819301
-Other Northern Africa,,1993,198.25764146737143
-Other Northern Africa,,1994,215.72434690596816
-Other Northern Africa,,1995,227.4880880729179
-Other Northern Africa,,1996,233.19386140018884
-Other Northern Africa,,1997,243.0175773565438
-Other Northern Africa,,1998,253.03127981268406
-Other Northern Africa,,1999,250.2574812996915
-Other Northern Africa,,2000,269.4186178231078
-Other Northern Africa,,2001,275.3139725668877
-Other Northern Africa,,2002,272.6566324353091
-Other Northern Africa,,2003,281.79324611951904
-Other Northern Africa,,2004,304.20521359701655
-Other Northern Africa,,2005,312.29824484991343
-Other Northern Africa,,2006,313.19025536769095
-Other Northern Africa,,2007,304.23793209403266
-Other Northern Africa,,2008,319.09355704596277
-Other Northern Africa,,2009,339.5943014838559
-Other Northern Africa,,2010,348.1911268649572
-Other Northern Africa,,2011,251.06134452075872
-Other Northern Africa,,2012,299.5037873907529
-Other Northern Africa,,2013,323.6818590629265
-Other Northern Africa,,2014,318.5356825956313
-Other Northern Africa,,2015,279.1054036235332
-Other Northern Africa,,2016,268.7972896745987
-Other Northern Africa,,2017,284.35081398743034
-Other Northern Africa,,2018,295.93588485562
-Other South America,,1965,30.776313201852314
-Other South America,,1966,34.95816974089913
-Other South America,,1967,37.25547127561004
-Other South America,,1968,38.65972315658486
-Other South America,,1969,41.21441454467098
-Other South America,,1970,43.7575904737845
-Other South America,,1971,48.2298730352148
-Other South America,,1972,53.91031326952279
-Other South America,,1973,55.71849468412672
-Other South America,,1974,50.802129624658036
-Other South America,,1975,56.75488900471012
-Other South America,,1976,57.59399602419227
-Other South America,,1977,61.400976070602255
-Other South America,,1978,68.10682673955849
-Other South America,,1979,71.24198810831693
-Other South America,,1980,75.27514539709442
-Other South America,,1981,71.21202581960708
-Other South America,,1982,68.92780569790176
-Other South America,,1983,66.1130348909097
-Other South America,,1984,66.88378118258265
-Other South America,,1985,77.17712871266735
-Other South America,,1986,100.34448290849494
-Other South America,,1987,118.04486817829854
-Other South America,,1988,125.4566261511615
-Other South America,,1989,137.41034287027392
-Other South America,,1990,148.20091253980476
-Other South America,,1991,156.5048514860845
-Other South America,,1992,158.75715737565284
-Other South America,,1993,171.7890008635691
-Other South America,,1994,192.23786448071718
-Other South America,,1995,215.78625796434267
-Other South America,,1996,225.797811972918
-Other South America,,1997,244.81898338999451
-Other South America,,1998,254.53446274922177
-Other South America,,1999,254.82511860540453
-Other South America,,2000,249.71100889011845
-Other South America,,2001,232.28031866297331
-Other South America,,2002,241.12185669765992
-Other South America,,2003,253.5424883998591
-Other South America,,2004,250.55225981802917
-Other South America,,2005,253.95914089148027
-Other South America,,2006,254.86443417845615
-Other South America,,2007,275.23061720539033
-Other South America,,2008,284.0454022722826
-Other South America,,2009,292.7662724393725
-Other South America,,2010,308.4551515926872
-Other South America,,2011,318.6458859386119
-Other South America,,2012,328.3297858247919
-Other South America,,2013,338.50617970648125
-Other South America,,2014,333.86128248044935
-Other South America,,2015,340.2577568763926
-Other South America,,2016,369.0155369608513
-Other South America,,2017,363.9987553967819
-Other South America,,2018,368.7916307830972
-Other Southern Africa,,1965,4.368125637560205
-Other Southern Africa,,1966,4.893960434366463
-Other Southern Africa,,1967,5.181055682466851
-Other Southern Africa,,1968,5.766111653954747
-Other Southern Africa,,1969,5.949465211135069
-Other Southern Africa,,1970,6.3601406412973
-Other Southern Africa,,1971,6.56710496497595
-Other Southern Africa,,1972,7.062212809755694
-Other Southern Africa,,1973,7.25614631686588
-Other Southern Africa,,1974,7.632523261771835
-Other Southern Africa,,1975,7.798623815038955
-Other Southern Africa,,1976,8.457215039164968
-Other Southern Africa,,1977,8.199357640156457
-Other Southern Africa,,1978,8.46699200777131
-Other Southern Africa,,1979,8.563322066480566
-Other Southern Africa,,1980,9.125240772629702
-Other Southern Africa,,1981,10.830063195755676
-Other Southern Africa,,1982,10.99136498259778
-Other Southern Africa,,1983,10.433658623542234
-Other Southern Africa,,1984,10.802150162235105
-Other Southern Africa,,1985,12.28367012161679
-Other Southern Africa,,1986,12.817631352700808
-Other Southern Africa,,1987,13.251287403578898
-Other Southern Africa,,1988,14.32614654071802
-Other Southern Africa,,1989,15.410181750834072
-Other Southern Africa,,1990,20.25459562973814
-Other Southern Africa,,1991,24.736556475887795
-Other Southern Africa,,1992,26.565917418378675
-Other Southern Africa,,1993,26.930455111708653
-Other Southern Africa,,1994,27.638063087158834
-Other Southern Africa,,1995,29.904716430840978
-Other Southern Africa,,1996,28.84678621129746
-Other Southern Africa,,1997,29.603615498708734
-Other Southern Africa,,1998,32.815362198013325
-Other Southern Africa,,1999,35.00839405506917
-Other Southern Africa,,2000,36.23226932871573
-Other Southern Africa,,2001,37.21287600301907
-Other Southern Africa,,2002,37.16648128470967
-Other Southern Africa,,2003,37.179727407697946
-Other Southern Africa,,2004,37.37436406444525
-Other Southern Africa,,2005,40.155721824409014
-Other Southern Africa,,2006,39.59362959495739
-Other Southern Africa,,2007,41.206113985741354
-Other Southern Africa,,2008,42.914170768679
-Other Southern Africa,,2009,44.2906637446784
-Other Southern Africa,,2010,40.54692395182359
-Other Southern Africa,,2011,43.64555300007127
-Other Southern Africa,,2012,48.486861392841924
-Other Southern Africa,,2013,50.4407600183525
-Other Southern Africa,,2014,54.63140495736441
-Other Southern Africa,,2015,55.93716340492369
-Other Southern Africa,,2016,56.69334881954999
-Other Southern Africa,,2017,60.05946960684948
-Other Southern Africa,,2018,58.45864391200311
-Pakistan,PAK,1965,81.50971138888889
-Pakistan,PAK,1966,82.12597250000005
-Pakistan,PAK,1967,90.87251166666667
-Pakistan,PAK,1968,103.11285027777782
-Pakistan,PAK,1969,103.55751333333332
-Pakistan,PAK,1970,102.00093777777776
-Pakistan,PAK,1971,98.91317416666668
-Pakistan,PAK,1972,87.0857538888889
-Pakistan,PAK,1973,92.88082083333335
-Pakistan,PAK,1974,99.37520777777773
-Pakistan,PAK,1975,107.0604188888889
-Pakistan,PAK,1976,108.62916444444441
-Pakistan,PAK,1977,117.42874027777727
-Pakistan,PAK,1978,125.42269638888946
-Pakistan,PAK,1979,136.77495916666678
-Pakistan,PAK,1980,151.8402319444444
-Pakistan,PAK,1981,163.32450472222212
-Pakistan,PAK,1982,180.0507463888894
-Pakistan,PAK,1983,192.16013083333343
-Pakistan,PAK,1984,203.44179888888942
-Pakistan,PAK,1985,213.84556444444482
-Pakistan,PAK,1986,227.07887222222212
-Pakistan,PAK,1987,253.995507222222
-Pakistan,PAK,1988,269.9352233333332
-Pakistan,PAK,1989,286.5440113888891
-Pakistan,PAK,1990,299.85172583333275
-Pakistan,PAK,1991,317.6647211111107
-Pakistan,PAK,1992,333.4245966666664
-Pakistan,PAK,1993,369.0924908333334
-Pakistan,PAK,1994,382.25578972222274
-Pakistan,PAK,1995,403.17014583333355
-Pakistan,PAK,1996,429.28986694444404
-Pakistan,PAK,1997,416.788996111111
-Pakistan,PAK,1998,445.92294055555504
-Pakistan,PAK,1999,466.70780805555586
-Pakistan,PAK,2000,477.32636476608207
-Pakistan,PAK,2001,488.6689483333336
-Pakistan,PAK,2002,507.3845904970757
-Pakistan,PAK,2003,552.0908177758171
-Pakistan,PAK,2004,615.2535032141433
-Pakistan,PAK,2005,641.4896436343477
-Pakistan,PAK,2006,677.4650598557517
-Pakistan,PAK,2007,721.2290148484326
-Pakistan,PAK,2008,725.8460326523204
-Pakistan,PAK,2009,734.5198691571189
-Pakistan,PAK,2010,737.8021424161349
-Pakistan,PAK,2011,739.0478083074825
-Pakistan,PAK,2012,745.9788321538374
-Pakistan,PAK,2013,754.394666551063
-Pakistan,PAK,2014,777.4800861684739
-Pakistan,PAK,2015,818.5028169652619
-Pakistan,PAK,2016,891.3705949334167
-Pakistan,PAK,2017,941.8986698253368
-Pakistan,PAK,2018,988.9306144800513
-Peru,PER,1965,55.64911037379443
-Peru,PER,1966,67.74417456268738
-Peru,PER,1967,68.89841367126908
-Peru,PER,1968,70.12456241890801
-Peru,PER,1969,70.59141273556679
-Peru,PER,1970,73.66181898992001
-Peru,PER,1971,76.02742258771934
-Peru,PER,1972,68.03415786549706
-Peru,PER,1973,78.17805621345026
-Peru,PER,1974,90.66974027777783
-Peru,PER,1975,93.33479333333334
-Peru,PER,1976,94.81543517543867
-Peru,PER,1977,95.3300612719298
-Peru,PER,1978,94.84345391812865
-Peru,PER,1979,98.63031709064335
-Peru,PER,1980,105.43572893274857
-Peru,PER,1981,110.61801361111114
-Peru,PER,1982,110.42992036549703
-Peru,PER,1983,97.53522755847952
-Peru,PER,1984,102.41490282163747
-Peru,PER,1985,101.7848035818713
-Peru,PER,1986,108.93302320175434
-Peru,PER,1987,117.05238608187182
-Peru,PER,1988,114.27108321637415
-Peru,PER,1989,104.78937311403494
-Peru,PER,1990,103.64565918128646
-Peru,PER,1991,102.5584216520467
-Peru,PER,1992,100.36182925438588
-Peru,PER,1993,109.05330293859643
-Peru,PER,1994,118.68581445906385
-Peru,PER,1995,129.59051722222173
-Peru,PER,1996,134.01868587719324
-Peru,PER,1997,135.2160021052631
-Peru,PER,1998,135.60758409356743
-Peru,PER,1999,139.4869469298243
-Peru,PER,2000,143.4020381140346
-Peru,PER,2001,141.65097627192958
-Peru,PER,2002,145.45171478070216
-Peru,PER,2003,143.59144682748476
-Peru,PER,2004,153.4863157249328
-Peru,PER,2005,160.81911336455408
-Peru,PER,2006,162.392392007789
-Peru,PER,2007,178.47878130835556
-Peru,PER,2008,192.98584073963582
-Peru,PER,2009,198.24617337987087
-Peru,PER,2010,218.14695688041422
-Peru,PER,2011,243.51379020485535
-Peru,PER,2012,248.11340920873334
-Peru,PER,2013,255.16648623712337
-Peru,PER,2014,262.5408741145902
-Peru,PER,2015,281.5746577965368
-Peru,PER,2016,296.63026889337954
-Peru,PER,2017,295.39458372350236
-Peru,PER,2018,314.0540634993502
-Philippines,PHL,1965,52.202767454444434
-Philippines,PHL,1966,56.78875327555559
-Philippines,PHL,1967,64.33969767111117
-Philippines,PHL,1968,71.83840763377775
-Philippines,PHL,1969,77.1553287693334
-Philippines,PHL,1970,89.36354876933338
-Philippines,PHL,1971,103.44811610022217
-Philippines,PHL,1972,100.88745148666663
-Philippines,PHL,1973,118.79554231999984
-Philippines,PHL,1974,112.47292641466673
-Philippines,PHL,1975,121.11309125911173
-Philippines,PHL,1976,125.45400075244456
-Philippines,PHL,1977,135.47402306139196
-Philippines,PHL,1978,141.6660809890649
-Philippines,PHL,1979,147.30162167007072
-Philippines,PHL,1980,144.50163744385966
-Philippines,PHL,1981,143.56752755766078
-Philippines,PHL,1982,139.66858574526313
-Philippines,PHL,1983,148.0339263883511
-Philippines,PHL,1984,136.47978332898262
-Philippines,PHL,1985,131.67699336709978
-Philippines,PHL,1986,133.71368769257344
-Philippines,PHL,1987,145.53066455023338
-Philippines,PHL,1988,160.38955545498274
-Philippines,PHL,1989,173.58099868962518
-Philippines,PHL,1990,180.451155687462
-Philippines,PHL,1991,174.9526822218241
-Philippines,PHL,1992,203.40394374075996
-Philippines,PHL,1993,210.3197168146663
-Philippines,PHL,1994,223.23669130673207
-Philippines,PHL,1995,248.85938418579076
-Philippines,PHL,1996,267.5454176579391
-Philippines,PHL,1997,288.16050076300695
-Philippines,PHL,1998,292.53392530026997
-Philippines,PHL,1999,297.36536976965914
-Philippines,PHL,2000,296.49226878466754
-Philippines,PHL,2001,292.6770447552891
-Philippines,PHL,2002,291.09556181854714
-Philippines,PHL,2003,301.7916291469074
-Philippines,PHL,2004,312.10520668917223
-Philippines,PHL,2005,311.1657462704264
-Philippines,PHL,2006,301.9606246421186
-Philippines,PHL,2007,314.6128348178494
-Philippines,PHL,2008,325.40431165427924
-Philippines,PHL,2009,329.70667464927476
-Philippines,PHL,2010,340.2437875873777
-Philippines,PHL,2011,347.27000800670976
-Philippines,PHL,2012,359.18271986025144
-Philippines,PHL,2013,385.51481372041206
-Philippines,PHL,2014,405.8598027285071
-Philippines,PHL,2015,445.21539173019744
-Philippines,PHL,2016,486.50578306129114
-Philippines,PHL,2017,531.574890258251
-Philippines,PHL,2018,546.9703627670884
-Poland,POL,1965,775.7649199122814
-Poland,POL,1966,790.8742598830413
-Poland,POL,1967,813.9547182456138
-Poland,POL,1968,876.0247563450295
-Poland,POL,1969,935.7557877777782
-Poland,POL,1970,987.3066814327483
-Poland,POL,1971,1018.5762063742687
-Poland,POL,1972,1074.3169619298246
-Poland,POL,1973,1094.4629182309939
-Poland,POL,1974,1130.4312702339187
-Poland,POL,1975,1219.4970078362603
-Poland,POL,1976,1284.871762441526
-Poland,POL,1977,1339.63471679824
-Poland,POL,1978,1406.5731228216428
-Poland,POL,1979,1427.521900935678
-Poland,POL,1980,1494.7284434795267
-Poland,POL,1981,1347.621556213445
-Poland,POL,1982,1372.4031160964926
-Poland,POL,1983,1378.6397531725192
-Poland,POL,1984,1433.2585368859668
-Poland,POL,1985,1465.6225046783586
-Poland,POL,1986,1507.0944150000012
-Poland,POL,1987,1555.9960274122823
-Poland,POL,1988,1526.2596941812824
-Poland,POL,1989,1468.9459230994103
-Poland,POL,1990,1209.837816988309
-Poland,POL,1991,1183.6537266637392
-Poland,POL,1992,1131.843997236842
-Poland,POL,1993,1131.3291238450288
-Poland,POL,1994,1082.587481230994
-Poland,POL,1995,1108.070615675439
-Poland,POL,1996,1163.2469668319948
-Poland,POL,1997,1151.8071260208164
-Poland,POL,1998,1103.3234384315194
-Poland,POL,1999,1081.9110303399002
-Poland,POL,2000,1016.7137011938241
-Poland,POL,2001,1009.491272205594
-Poland,POL,2002,998.6676904291696
-Poland,POL,2003,1033.688926905748
-Poland,POL,2004,1040.29042426566
-Poland,POL,2005,1063.2520857512036
-Poland,POL,2006,1115.871463446458
-Poland,POL,2007,1112.4265526771599
-Poland,POL,2008,1132.3579670048073
-Poland,POL,2009,1092.3501021891482
-Poland,POL,2010,1163.0304893675054
-Poland,POL,2011,1169.105519542944
-Poland,POL,2012,1134.15189913931
-Poland,POL,2013,1137.5935669844696
-Poland,POL,2014,1095.8020384318374
-Poland,POL,2015,1107.6892180955808
-Poland,POL,2016,1156.2003750311228
-Poland,POL,2017,1202.7127334795305
-Poland,POL,2018,1222.9049117756313
-Portugal,PRT,1965,48.419736491228036
-Portugal,PRT,1966,52.7275796491228
-Portugal,PRT,1967,56.44267931286541
-Portugal,PRT,1968,57.581289078947364
-Portugal,PRT,1969,62.14465489766073
-Portugal,PRT,1970,74.88947074529233
-Portugal,PRT,1971,82.56312567529235
-Portugal,PRT,1972,89.65790087849412
-Portugal,PRT,1973,99.2277917858917
-Portugal,PRT,1974,103.83400000997065
-Portugal,PRT,1975,103.60893457921043
-Portugal,PRT,1976,103.0435678620029
-Portugal,PRT,1977,115.34856361593559
-Portugal,PRT,1978,121.38978875690027
-Portugal,PRT,1979,128.8149829269295
-Portugal,PRT,1980,126.01749224964858
-Portugal,PRT,1981,124.65449994864088
-Portugal,PRT,1982,134.40946107454667
-Portugal,PRT,1983,138.87781998693004
-Portugal,PRT,1984,144.2408471986985
-Portugal,PRT,1985,146.84850886820155
-Portugal,PRT,1986,156.32569990361128
-Portugal,PRT,1987,159.8398091670025
-Portugal,PRT,1988,176.69478951495623
-Portugal,PRT,1989,193.20713323316954
-Portugal,PRT,1990,195.09703745278046
-Portugal,PRT,1991,202.5556766861365
-Portugal,PRT,1992,206.11341403094818
-Portugal,PRT,1993,210.8808690690359
-Portugal,PRT,1994,217.91310308412147
-Portugal,PRT,1995,239.9243258720427
-Portugal,PRT,1996,245.43158024745293
-Portugal,PRT,1997,249.53315544944076
-Portugal,PRT,1998,272.6728259069618
-Portugal,PRT,1999,280.74961658062466
-Portugal,PRT,2000,288.8393543261958
-Portugal,PRT,2001,292.5147520298675
-Portugal,PRT,2002,292.2268388289855
-Portugal,PRT,2003,298.21400557190225
-Portugal,PRT,2004,293.97316102715934
-Portugal,PRT,2005,294.5152052069608
-Portugal,PRT,2006,290.86257976531897
-Portugal,PRT,2007,293.23496538587807
-Portugal,PRT,2008,283.4491483082075
-Portugal,PRT,2009,285.46623092296903
-Portugal,PRT,2010,299.9375947248062
-Portugal,PRT,2011,286.72756370045914
-Portugal,PRT,2012,262.3290422625283
-Portugal,PRT,2013,287.62673854780945
-Portugal,PRT,2014,290.14829730531824
-Portugal,PRT,2015,288.2480972026796
-Portugal,PRT,2016,304.589599676552
-Portugal,PRT,2017,299.55875577927867
-Portugal,PRT,2018,302.03474131233224
-Qatar,QAT,1965,1.4110830555555556
-Qatar,QAT,1966,1.4206977777777807
-Qatar,QAT,1967,2.0353772222222277
-Qatar,QAT,1968,6.4395641666666705
-Qatar,QAT,1969,10.118639999999996
-Qatar,QAT,1970,11.52568722222222
-Qatar,QAT,1971,11.481247222222223
-Qatar,QAT,1972,12.70093583333339
-Qatar,QAT,1973,18.021015833333355
-Qatar,QAT,1974,15.712179444444446
-Qatar,QAT,1975,23.44534777777779
-Qatar,QAT,1976,15.060140277777759
-Qatar,QAT,1977,20.983208611111163
-Qatar,QAT,1978,20.128460555555595
-Qatar,QAT,1979,50.366066111111174
-Qatar,QAT,1980,57.59345305555562
-Qatar,QAT,1981,54.04643805555555
-Qatar,QAT,1982,65.34616944444446
-Qatar,QAT,1983,68.47765166666663
-Qatar,QAT,1984,77.44816999999996
-Qatar,QAT,1985,78.76559666666662
-Qatar,QAT,1986,86.18324833333331
-Qatar,QAT,1987,85.93523611111118
-Qatar,QAT,1988,79.16833500000001
-Qatar,QAT,1989,84.59311638888884
-Qatar,QAT,1990,86.29591250000004
-Qatar,QAT,1991,97.28904805555551
-Qatar,QAT,1992,149.68493166666707
-Qatar,QAT,1993,159.1087041666662
-Qatar,QAT,1994,160.40702777777787
-Qatar,QAT,1995,161.397269444444
-Qatar,QAT,1996,120.00891049955447
-Qatar,QAT,1997,128.0749964300569
-Qatar,QAT,1998,136.9990861156409
-Qatar,QAT,1999,153.0242333628694
-Qatar,QAT,2000,134.40784610513356
-Qatar,QAT,2001,130.99409289135008
-Qatar,QAT,2002,147.97374870333346
-Qatar,QAT,2003,166.32390047730556
-Qatar,QAT,2004,194.9699380430714
-Qatar,QAT,2005,224.38952329276776
-Qatar,QAT,2006,236.40234471971297
-Qatar,QAT,2007,258.51683059136155
-Qatar,QAT,2008,285.8869930084897
-Qatar,QAT,2009,288.84139558367457
-Qatar,QAT,2010,336.2061845909785
-Qatar,QAT,2011,388.8741522460516
-Qatar,QAT,2012,441.3505057592387
-Qatar,QAT,2013,474.94342199671075
-Qatar,QAT,2014,510.1648662815231
-Qatar,QAT,2015,560.9858985699799
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-Qatar,QAT,2018,561.2283498485921
-Romania,ROU,1965,278.37751221973326
-Romania,ROU,1966,296.93081184458305
-Romania,ROU,1967,331.25340764004983
-Romania,ROU,1968,352.4663252044331
-Romania,ROU,1969,405.10609735853524
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-Romania,ROU,1988,763.2865441111114
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-Romania,ROU,2009,392.5586151862246
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-Romania,ROU,2018,388.41059585273365
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-Saudi Arabia,SAU,1965,235.13954944444387
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-Slovakia,SVK,1965,106.11284396353824
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-South & Central America,,1965,1279.7271009268313
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-South & Central America,,2018,8164.427125066203
-South Africa,ZAF,1965,354.1191002777781
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-South Africa,ZAF,2018,1413.2006437960856
-South Korea,KOR,1965,74.58588945906426
-South Korea,KOR,1966,90.44770513157893
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-South Korea,KOR,1995,1742.096823307021
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-South Korea,KOR,1997,2114.287416131576
-South Korea,KOR,1998,1948.6998621725156
-South Korea,KOR,1999,2121.7919692309947
-South Korea,KOR,2000,2250.5891694795287
-South Korea,KOR,2001,2303.974427417831
-South Korea,KOR,2002,2412.371252201751
-South Korea,KOR,2003,2491.5472859871297
-South Korea,KOR,2004,2539.6827563967972
-South Korea,KOR,2005,2622.410391496292
-South Korea,KOR,2006,2667.567088417482
-South Korea,KOR,2007,2754.386833963878
-South Korea,KOR,2008,2807.999292179777
-South Korea,KOR,2009,2821.274024512864
-South Korea,KOR,2010,3038.6196506050155
-South Korea,KOR,2011,3179.7044888530163
-South Korea,KOR,2012,3213.602521472998
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-South Korea,KOR,2014,3250.91395551793
-South Korea,KOR,2015,3317.514921253245
-South Korea,KOR,2016,3398.790004175518
-South Korea,KOR,2017,3455.4880061924287
-South Korea,KOR,2018,3500.882556620662
-Spain,ESP,1965,331.9111558333337
-Spain,ESP,1966,374.2080717543865
-Spain,ESP,1967,405.2286703508776
-Spain,ESP,1968,426.1915873976605
-Spain,ESP,1969,481.54221133040875
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-Spain,ESP,1975,726.7123025730999
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-Spain,ESP,1984,914.3013579678365
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-Spain,ESP,1986,925.0857547953219
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-Spain,ESP,1989,1050.250815571504
-Spain,ESP,1990,1049.1435284447884
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-Spain,ESP,1995,1200.6912937487455
-Spain,ESP,1996,1243.5081663124413
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-Spain,ESP,1999,1423.2617010123022
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-Spain,ESP,2001,1572.8057575422968
-Spain,ESP,2002,1596.1325010748774
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-Spain,ESP,2014,1553.1131828203756
-Spain,ESP,2015,1574.7866971812025
-Spain,ESP,2016,1592.66319573843
-Spain,ESP,2017,1614.2450000259842
-Spain,ESP,2018,1643.9903646863836
-Sri Lanka,LKA,1965,6.444912959828844
-Sri Lanka,LKA,1966,6.666719102852222
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-Sri Lanka,LKA,1997,38.59882776900577
-Sri Lanka,LKA,1998,41.83763788622215
-Sri Lanka,LKA,1999,45.414854850374255
-Sri Lanka,LKA,2000,49.204552605163684
-Sri Lanka,LKA,2001,48.278018021046705
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-Sri Lanka,LKA,2003,51.39618828282457
-Sri Lanka,LKA,2004,49.749424922964856
-Sri Lanka,LKA,2005,57.192657653999916
-Sri Lanka,LKA,2006,62.19658141680404
-Sri Lanka,LKA,2007,63.43179509946482
-Sri Lanka,LKA,2008,59.310650810286496
-Sri Lanka,LKA,2009,61.27915251909064
-Sri Lanka,LKA,2010,65.75653072100138
-Sri Lanka,LKA,2011,69.11883894517045
-Sri Lanka,LKA,2012,69.65344334884576
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-Sri Lanka,LKA,2014,63.99787140711844
-Sri Lanka,LKA,2015,81.46134805135017
-Sri Lanka,LKA,2016,86.64604956589253
-Sri Lanka,LKA,2017,91.27854777835996
-Sri Lanka,LKA,2018,94.26677639746917
-Sweden,SWE,1965,377.91974683041354
-Sweden,SWE,1966,404.34891266591893
-Sweden,SWE,1967,413.23263275310387
-Sweden,SWE,1968,442.60619598704216
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-Sweden,SWE,1974,480.39051804560125
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-Sweden,SWE,1982,579.8406647596735
-Sweden,SWE,1983,572.8587315537983
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-Sweden,SWE,1985,655.7647170491053
-Sweden,SWE,1986,681.9574577882508
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-Sweden,SWE,1998,670.1602113304598
-Sweden,SWE,1999,650.6046897045998
-Sweden,SWE,2000,600.5894375812852
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-Sweden,SWE,2003,588.9647270762136
-Sweden,SWE,2004,633.9334718030173
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-Sweden,SWE,2009,566.0047426102143
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-Sweden,SWE,2011,597.9484593988275
-Sweden,SWE,2012,636.192095812711
-Sweden,SWE,2013,599.1411130989887
-Sweden,SWE,2014,598.8164910171449
-Sweden,SWE,2015,619.3669397328397
-Sweden,SWE,2016,611.2853737218267
-Sweden,SWE,2017,632.4463129746255
-Sweden,SWE,2018,623.4503771084262
-Switzerland,CHE,1965,174.62680250000054
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-Switzerland,CHE,1968,210.38237738304107
-Switzerland,CHE,1969,218.25464815789513
-Switzerland,CHE,1970,241.1208745760238
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-Switzerland,CHE,1978,274.89388055555514
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-Taiwan,TWN,1965,72.37542833333337
-Taiwan,TWN,1966,77.54421194444446
-Taiwan,TWN,1967,83.93414527777777
-Taiwan,TWN,1968,96.85181416666666
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-Taiwan,TWN,1987,474.0482626334722
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-Taiwan,TWN,1997,865.5435186578187
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-Taiwan,TWN,2005,1225.8938999940685
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-Taiwan,TWN,2011,1271.3528903297577
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-Taiwan,TWN,2017,1361.1787852404482
-Taiwan,TWN,2018,1377.2109363312381
-Thailand,THA,1965,31.10393972222221
-Thailand,THA,1966,36.796854999999944
-Thailand,THA,1967,42.21545194444447
-Thailand,THA,1968,53.469035833333386
-Thailand,THA,1969,56.486598055555575
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-Thailand,THA,1974,100.3353860833333
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-Thailand,THA,1976,113.88008929444447
-Thailand,THA,1977,125.79274529333274
-Thailand,THA,1978,137.8032276833329
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-Thailand,THA,1980,146.45013967333387
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-Thailand,THA,1982,150.41879322333375
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-Thailand,THA,1984,184.06604817999994
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-Thailand,THA,1986,205.49161370210376
-Thailand,THA,1987,236.11232134900013
-Thailand,THA,1988,264.6552951319808
-Thailand,THA,1989,304.03447146521853
-Thailand,THA,1990,359.9651555960608
-Thailand,THA,1991,397.6519872818865
-Thailand,THA,1992,439.0356419016045
-Thailand,THA,1993,500.10805882830414
-Thailand,THA,1994,560.6388285503566
-Thailand,THA,1995,614.3886110627328
-Thailand,THA,1996,694.674562101187
-Thailand,THA,1997,732.2589330734825
-Thailand,THA,1998,678.519878937449
-Thailand,THA,1999,725.5313333101228
-Thailand,THA,2000,741.9738468022564
-Thailand,THA,2001,781.9540745029093
-Thailand,THA,2002,859.7331476510608
-Thailand,THA,2003,931.2313554627605
-Thailand,THA,2004,997.598418634358
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-Thailand,THA,2006,1033.2407020584792
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-Thailand,THA,2010,1218.6103024712513
-Thailand,THA,2011,1266.467837238018
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-Thailand,THA,2013,1376.2144435712057
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-Thailand,THA,2015,1450.6447927181287
-Thailand,THA,2016,1480.8888108781794
-Thailand,THA,2017,1514.1208435017254
-Thailand,THA,2018,1546.4419471160816
-Trinidad and Tobago,TTO,1965,34.432663786830844
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-Trinidad and Tobago,TTO,1990,69.5825728362573
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-Trinidad and Tobago,TTO,1992,73.42962831079637
-Trinidad and Tobago,TTO,1993,77.40183427524853
-Trinidad and Tobago,TTO,1994,82.02533671828249
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-Trinidad and Tobago,TTO,2001,124.87479187699716
-Trinidad and Tobago,TTO,2002,134.44520385040707
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-Trinidad and Tobago,TTO,2004,155.7403892608923
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-Trinidad and Tobago,TTO,2006,179.53401356191037
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-Trinidad and Tobago,TTO,2008,184.52342709455442
-Trinidad and Tobago,TTO,2009,186.57911888055207
-Trinidad and Tobago,TTO,2010,203.54977423739277
-Trinidad and Tobago,TTO,2011,204.53121808974197
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-Trinidad and Tobago,TTO,2015,196.88343797245503
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-Trinidad and Tobago,TTO,2017,177.29634671489669
-Trinidad and Tobago,TTO,2018,177.48809398554621
-Turkey,TUR,1965,90.66821286549705
-Turkey,TUR,1966,104.08697875730991
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-Turkey,TUR,1982,324.0712611403512
-Turkey,TUR,1983,336.0213869152042
-Turkey,TUR,1984,353.33030020467794
-Turkey,TUR,1985,382.1717922368417
-Turkey,TUR,1986,416.83041494152036
-Turkey,TUR,1987,473.52319755847935
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-Turkey,TUR,2001,778.1394040058476
-Turkey,TUR,2002,849.8527403801173
-Turkey,TUR,2003,900.7267305555549
-Turkey,TUR,2004,963.1854627777772
-Turkey,TUR,2005,987.5364868421053
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-Turkey,TUR,2008,1172.2326980116961
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-Turkey,TUR,2010,1251.7463901023414
-Turkey,TUR,2011,1338.5759503731394
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-Turkey,TUR,2014,1458.2839030116934
-Turkey,TUR,2015,1595.5374228740898
-Turkey,TUR,2016,1681.5051976927841
-Turkey,TUR,2017,1776.0132139016812
-Turkey,TUR,2018,1785.673547929368
-Turkmenistan,TKM,1985,144.68851076071007
-Turkmenistan,TKM,1986,178.37765740865387
-Turkmenistan,TKM,1987,179.29100880982347
-Turkmenistan,TKM,1988,181.00252738878143
-Turkmenistan,TKM,1989,183.56072227329355
-Turkmenistan,TKM,1990,153.72036641917356
-Turkmenistan,TKM,1991,157.81951905769589
-Turkmenistan,TKM,1992,60.67867631578946
-Turkmenistan,TKM,1993,122.29147933278975
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-Turkmenistan,TKM,1998,149.1335350292402
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-Turkmenistan,TKM,2001,151.23569223684225
-Turkmenistan,TKM,2002,127.5640214035082
-Turkmenistan,TKM,2003,176.11756890350873
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-Turkmenistan,TKM,2005,176.5994800146197
-Turkmenistan,TKM,2006,178.46175001461975
-Turkmenistan,TKM,2007,173.17142862573135
-Turkmenistan,TKM,2008,142.05468751461953
-Turkmenistan,TKM,2009,231.60031918128647
-Turkmenistan,TKM,2010,249.56539828190847
-Turkmenistan,TKM,2011,276.9895773290709
-Turkmenistan,TKM,2012,301.9568132657501
-Turkmenistan,TKM,2013,268.2365938198523
-Turkmenistan,TKM,2014,278.0297032652082
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-Turkmenistan,TKM,2016,319.4448284695503
-Turkmenistan,TKM,2017,333.64617909222613
-Turkmenistan,TKM,2018,366.3974046494184
-USSR,OWID_USS,1965,6900.2211236797875
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-USSR,OWID_USS,1968,7998.801732830085
-USSR,OWID_USS,1969,8361.934967824714
-USSR,OWID_USS,1970,8778.396558836379
-USSR,OWID_USS,1971,9209.745801496534
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-USSR,OWID_USS,1975,11269.304362428395
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-USSR,OWID_USS,1979,13108.235679323503
-USSR,OWID_USS,1980,13375.669192556437
-USSR,OWID_USS,1981,13659.171705131965
-USSR,OWID_USS,1982,14002.626645411206
-USSR,OWID_USS,1983,14293.511008493257
-USSR,OWID_USS,1984,14823.698121847994
-Ukraine,UKR,1985,2673.6673415578534
-Ukraine,UKR,1986,2689.349751282574
-Ukraine,UKR,1987,2748.406640684055
-Ukraine,UKR,1988,2751.3983550221637
-Ukraine,UKR,1989,2637.6187119425904
-Ukraine,UKR,1990,3066.205070347672
-Ukraine,UKR,1991,2792.562158527828
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-Ukraine,UKR,1994,1761.473194795905
-Ukraine,UKR,1995,1653.400477292913
-Ukraine,UKR,1996,1628.822844158086
-Ukraine,UKR,1997,1599.502323450533
-Ukraine,UKR,1998,1540.1271722265237
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-Ukraine,UKR,2002,1552.7775449606781
-Ukraine,UKR,2003,1595.29792285952
-Ukraine,UKR,2004,1606.544749177449
-Ukraine,UKR,2005,1589.5801951229575
-Ukraine,UKR,2006,1607.0661111205584
-Ukraine,UKR,2007,1568.7704602919068
-Ukraine,UKR,2008,1552.6225760056236
-Ukraine,UKR,2009,1319.352538140513
-Ukraine,UKR,2010,1413.0171636791663
-Ukraine,UKR,2011,1469.2054287433452
-Ukraine,UKR,2012,1432.002677393057
-Ukraine,UKR,2013,1364.4749981032994
-Ukraine,UKR,2014,1200.1818741549534
-Ukraine,UKR,2015,996.1977018758467
-Ukraine,UKR,2016,1044.665111126826
-Ukraine,UKR,2017,969.441886505495
-Ukraine,UKR,2018,976.9823728796677
-United Arab Emirates,ARE,1965,0.8656089502471281
-United Arab Emirates,ARE,1966,0.9275648483811441
-United Arab Emirates,ARE,1967,5.4282123613432995
-United Arab Emirates,ARE,1968,6.970712540986252
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-United Arab Emirates,ARE,1998,536.7142563888889
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-United Arab Emirates,ARE,2000,538.8712133333335
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-United Kingdom,GBR,1965,2311.6108198830416
-United Kingdom,GBR,1966,2321.8650584941515
-United Kingdom,GBR,1967,2321.8309292690083
-United Kingdom,GBR,1968,2404.829681564327
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-United Kingdom,GBR,2018,2236.2720248148394
-United States,USA,1965,14533.341396740547
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-Venezuela,VEN,1965,191.11174294006616
-Venezuela,VEN,1966,192.94984803931803
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-Venezuela,VEN,2018,751.768822937406
-Vietnam,VNM,1965,29.34432467521292
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-Vietnam,VNM,2000,207.51762641188728
-Vietnam,VNM,2001,234.41929421513467
-Vietnam,VNM,2002,257.2863949894552
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-Vietnam,VNM,2004,341.06649775770154
-Vietnam,VNM,2005,360.4638193818291
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-Vietnam,VNM,2007,360.08026575327995
-Vietnam,VNM,2008,447.4733056833459
-Vietnam,VNM,2009,457.77153818724514
-Vietnam,VNM,2010,518.3489512160959
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-Vietnam,VNM,2012,620.5130876269938
-Vietnam,VNM,2013,665.3426374871724
-Vietnam,VNM,2014,727.7399462035125
-Vietnam,VNM,2015,803.547362602424
-Vietnam,VNM,2016,859.8073419043309
-Vietnam,VNM,2017,881.9921085647925
-Vietnam,VNM,2018,997.7041834395584
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-Western Africa,,1967,58.98637091680998
-Western Africa,,1968,57.498604585776505
-Western Africa,,1969,64.0236969231645
-Western Africa,,1970,71.88266121321314
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-Western Africa,,1973,111.10654420105156
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-Western Africa,,1975,122.11125713836664
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-Western Africa,,1977,162.25326361233826
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-Western Africa,,1981,224.2554329771512
-Western Africa,,1982,233.7232129043756
-Western Africa,,1983,220.5083352717158
-Western Africa,,1984,204.07979581336497
-Western Africa,,1985,216.13963948892538
-Western Africa,,1986,212.48476175097116
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-World,OWID_WRL,1991,94998.44136208357
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-World,OWID_WRL,1998,104270.79783871827
-World,OWID_WRL,1999,106165.3834994446
-World,OWID_WRL,2000,108822.05880317488
-World,OWID_WRL,2001,110048.80353779378
-World,OWID_WRL,2002,112538.20870713833
-World,OWID_WRL,2003,116667.06992825895
-World,OWID_WRL,2004,122395.7885558709
-World,OWID_WRL,2005,126626.721059885
-World,OWID_WRL,2006,130323.33164710835
-World,OWID_WRL,2007,134465.27049606023
-World,OWID_WRL,2008,136130.34057453115
-World,OWID_WRL,2009,134213.75563207068
-World,OWID_WRL,2010,140722.29377284617
-World,OWID_WRL,2011,144255.09090983882
-World,OWID_WRL,2012,146252.98273359356
-World,OWID_WRL,2013,149089.9298026643
-World,OWID_WRL,2014,150489.50214668777
-World,OWID_WRL,2015,151720.06315733574
-World,OWID_WRL,2016,153848.43335585727
-World,OWID_WRL,2017,156709.6232435849
-World,OWID_WRL,2018,161248.58563878245
\ No newline at end of file
diff --git a/notebooks/.ipynb_checkpoints/01_Cheers_Stats_Beers-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/01_Cheers_Stats_Beers-checkpoint.ipynb
deleted file mode 100644
index 8d868a6..0000000
--- a/notebooks/.ipynb_checkpoints/01_Cheers_Stats_Beers-checkpoint.ipynb
+++ /dev/null
@@ -1,1447 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "###### Content modified under Creative Commons Attribution license CC-BY 4.0, code under BSD 3-Clause License © 2020 Ryan C. Cooper"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Cheers!  Stats with Beers\n",
-    "\n",
-    "\n",
-    "Welcome to the second module in _Computational Mechanics_, our series in computational thinking for undergraduate engineering students. This module explores practical data and statistical analysis with Python.\n",
-    "\n",
-    "This first lesson explores how we can answer questions using data combined with practical methods from statistics.\n",
-    "\n",
-    "We'll need some fun data to work with. We found a neat data set of canned craft beers in the US, scraped from the web and cleaned up by Jean-Nicholas Hould ([@NicholasHould](https://twitter.com/NicholasHould?lang=en) on Twitter)—who we want to thank for having a permissive license on his GitHub repository so we can reuse his [work](https://github.com/nickhould/craft-beers-dataset)!\n",
-    "\n",
-    "The data source ([@craftcans](https://twitter.com/craftcans) on Twitter) doesn't say that the set includes *all* the canned beers brewed in the country. So we have to asume that the data is a sample and may contain biases.\n",
-    "\n",
-    "We'll process the data using **numpy**—the array library for Python that we learned about in [Module 1, lesson 2: Getting Started](../../CompMech01-Getting-started/notebooks/02-Getting-started.ipynb). But we'll also learn about a new Python library for data analysis called **pandas**. \n",
-    "\n",
-    "[`pandas`](http://pandas.pydata.org/) is an open-source library providing high-performance, easy-to-use data structures and data-analysis tools.  Even though `pandas` is great for data analysis, we won't exploit all its power in this lesson. But we'll learn more about it later on!\n",
-    "\n",
-    "We'll use `pandas` to read the data file (in `csv` format, for comma-separated values), display it in a nice table, and extract the columns that we need—which we'll convert to `numpy` arrays to work with.\n",
-    "\n",
-    "Let's start by importing the two Python libraries that we need."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Step 1: Read the data file\n",
-    "\n",
-    "Below, we'll take a peek into the data file, `beers.csv,` using the system command `head` (which we can use with a bang, thanks to IPython).\n",
-    "\n",
-    "But first, we will download the data using a Python library for opening a URL on the Internet. We created a short URL for the data file in the public repository with our course materials.\n",
-    "\n",
-    "The cell below should download the data in your current working directory. The next cell shows you the first few lines of the data."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      ",abv,ibu,id,name,style,brewery_id,ounces\n",
-      "0,0.05,,1436,Pub Beer,American Pale Lager,408,12.0\n",
-      "1,0.066,,2265,Devil's Cup,American Pale Ale (APA),177,12.0\n",
-      "2,0.071,,2264,Rise of the Phoenix,American IPA,177,12.0\n",
-      "3,0.09,,2263,Sinister,American Double / Imperial IPA,177,12.0\n",
-      "4,0.075,,2262,Sex and Candy,American IPA,177,12.0\n",
-      "5,0.077,,2261,Black Exodus,Oatmeal Stout,177,12.0\n",
-      "6,0.045,,2260,Lake Street Express,American Pale Ale (APA),177,12.0\n",
-      "7,0.065,,2259,Foreman,American Porter,177,12.0\n",
-      "8,0.055,,2258,Jade,American Pale Ale (APA),177,12.0\n"
-     ]
-    }
-   ],
-   "source": [
-    "!head \"../data/beers.csv\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can use `pandas` to read the data from the `csv` file, and save it into a new variable called `beers`. Let's then check the type of this new variable—rememeber that we can use the function `type()` to do this."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "beers = pd.read_csv('../data/beers.csv')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "pandas.core.frame.DataFrame"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type(beers)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This is a new data type for us: a `pandas DataFrame`. From the `pandas` documentation: \"A `DataFrame`  is a 2-dimensional labeled data structure with columns of potentially different types\" [4]. You can think of it as the contens of a spreadsheet, saved into one handy Python variable. If you print it out, you get a nicely laid-out table: "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "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>Unnamed: 0</th>\n",
-       "      <th>abv</th>\n",
-       "      <th>ibu</th>\n",
-       "      <th>id</th>\n",
-       "      <th>name</th>\n",
-       "      <th>style</th>\n",
-       "      <th>brewery_id</th>\n",
-       "      <th>ounces</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0</td>\n",
-       "      <td>0.050</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>1436</td>\n",
-       "      <td>Pub Beer</td>\n",
-       "      <td>American Pale Lager</td>\n",
-       "      <td>408</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1</td>\n",
-       "      <td>0.066</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2265</td>\n",
-       "      <td>Devil's Cup</td>\n",
-       "      <td>American Pale Ale (APA)</td>\n",
-       "      <td>177</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>2</td>\n",
-       "      <td>0.071</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2264</td>\n",
-       "      <td>Rise of the Phoenix</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>177</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>3</td>\n",
-       "      <td>0.090</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2263</td>\n",
-       "      <td>Sinister</td>\n",
-       "      <td>American Double / Imperial IPA</td>\n",
-       "      <td>177</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>4</td>\n",
-       "      <td>0.075</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2262</td>\n",
-       "      <td>Sex and Candy</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>177</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2402</th>\n",
-       "      <td>2405</td>\n",
-       "      <td>0.067</td>\n",
-       "      <td>45.0</td>\n",
-       "      <td>928</td>\n",
-       "      <td>Belgorado</td>\n",
-       "      <td>Belgian IPA</td>\n",
-       "      <td>424</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2403</th>\n",
-       "      <td>2406</td>\n",
-       "      <td>0.052</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>807</td>\n",
-       "      <td>Rail Yard Ale</td>\n",
-       "      <td>American Amber / Red Ale</td>\n",
-       "      <td>424</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2404</th>\n",
-       "      <td>2407</td>\n",
-       "      <td>0.055</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>620</td>\n",
-       "      <td>B3K Black Lager</td>\n",
-       "      <td>Schwarzbier</td>\n",
-       "      <td>424</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2405</th>\n",
-       "      <td>2408</td>\n",
-       "      <td>0.055</td>\n",
-       "      <td>40.0</td>\n",
-       "      <td>145</td>\n",
-       "      <td>Silverback Pale Ale</td>\n",
-       "      <td>American Pale Ale (APA)</td>\n",
-       "      <td>424</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2406</th>\n",
-       "      <td>2409</td>\n",
-       "      <td>0.052</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>84</td>\n",
-       "      <td>Rail Yard Ale (2009)</td>\n",
-       "      <td>American Amber / Red Ale</td>\n",
-       "      <td>424</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>2407 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      Unnamed: 0    abv   ibu    id                  name  \\\n",
-       "0              0  0.050   NaN  1436              Pub Beer   \n",
-       "1              1  0.066   NaN  2265           Devil's Cup   \n",
-       "2              2  0.071   NaN  2264   Rise of the Phoenix   \n",
-       "3              3  0.090   NaN  2263              Sinister   \n",
-       "4              4  0.075   NaN  2262         Sex and Candy   \n",
-       "...          ...    ...   ...   ...                   ...   \n",
-       "2402        2405  0.067  45.0   928             Belgorado   \n",
-       "2403        2406  0.052   NaN   807         Rail Yard Ale   \n",
-       "2404        2407  0.055   NaN   620       B3K Black Lager   \n",
-       "2405        2408  0.055  40.0   145   Silverback Pale Ale   \n",
-       "2406        2409  0.052   NaN    84  Rail Yard Ale (2009)   \n",
-       "\n",
-       "                               style  brewery_id  ounces  \n",
-       "0                American Pale Lager         408    12.0  \n",
-       "1            American Pale Ale (APA)         177    12.0  \n",
-       "2                       American IPA         177    12.0  \n",
-       "3     American Double / Imperial IPA         177    12.0  \n",
-       "4                       American IPA         177    12.0  \n",
-       "...                              ...         ...     ...  \n",
-       "2402                     Belgian IPA         424    12.0  \n",
-       "2403        American Amber / Red Ale         424    12.0  \n",
-       "2404                     Schwarzbier         424    12.0  \n",
-       "2405         American Pale Ale (APA)         424    12.0  \n",
-       "2406        American Amber / Red Ale         424    12.0  \n",
-       "\n",
-       "[2407 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "beers"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Inspect the table above. The first column is a numbering scheme for the beers. The other columns contain the following data:\n",
-    "\n",
-    "- `abv`: Alcohol-by-volume of the beer.\n",
-    "- `ibu`: International Bittering Units of the beer.\n",
-    "- `id`: Unique identifier of the beer.\n",
-    "- `name`: Name of the beer.\n",
-    "- `style`: Style of the beer.\n",
-    "- `brewery_id`: Unique identifier of the brewery.\n",
-    "- `ounces`: Ounces of beer in the can."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Step 2: Explore the data\n",
-    "\n",
-    "In the field of statistics, [Exploratory Data Analysis](https://en.wikipedia.org/wiki/Exploratory_data_analysis) (EDA) has the goal of summarizing the main features of our data, and seeing what the data can tell us without formal modeling or hypothesis-testing. [2]\n",
-    "\n",
-    "Let's start by extracting the columns with the `abv` and `ibu` values, and converting them to numpy arrays. One of the advantages of data frames in `pandas` is that we can access a column simply using its header, like this:\n",
-    "\n",
-    "```python\n",
-    "data_frame['name_of_column']\n",
-    "```\n",
-    "\n",
-    "The output of this action is a `pandas Series`. From the documentation: \"a `Series` is a 1-dimensional labeled array capable of holding any data type.\" [4]\n",
-    "\n",
-    "Check the type of a column extracted by header:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "pandas.core.series.Series"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type(beers['abv'])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Of course, you can index and slice a data series like you know how to do with strings, lists and arrays. Here, we display the first ten elements of the `abv` series:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0    0.050\n",
-       "1    0.066\n",
-       "2    0.071\n",
-       "3    0.090\n",
-       "4    0.075\n",
-       "5    0.077\n",
-       "6    0.045\n",
-       "7    0.065\n",
-       "8    0.055\n",
-       "9    0.086\n",
-       "Name: abv, dtype: float64"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "beers['abv'][:10]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Inspect the data in the table again: you'll notice that there are `NaN` (not-a-number) elements in both the `abv` and `ibu` columns. Those values mean that there was no data reported for that beer. A typical task when cleaning up data is to deal with these pesky `NaN`s.\n",
-    "\n",
-    "Let's extract the two series corresponding to the `abv` and `ibu` columns, clean the data by removing all `NaN` values, and then access the values of each series and assign them to a numpy array. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "abv_series = beers['abv']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2407"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "len(abv_series)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Another advantage of `pandas` is that it has the ability to handle missing data. The  data-frame method `dropna()` returns a new data frame with only the good values of the original: all the null values are thrown out. This is super useful!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "abv_clean = abv_series.dropna()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Check out the length of the cleaned-up `abv` data; you'll see that it's shorter than the original. `NaN`s gone!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2348"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "len(abv_clean)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Remember that a a `pandas` _Series_ consists of a column of values, and their labels. You can extract the values via the [`series.values`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.values.html) attribute, which returns a `numpy.ndarray` (multidimensional array). In the case of the `abv_clean` series, you get a one-dimensional array. We save it into the variable name `abv`. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "abv = abv_clean.values"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[0.05  0.066 0.071 ... 0.055 0.055 0.052]\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(abv)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "numpy.ndarray"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type(abv)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now we repeat the whole process for the `ibu` column: extract the column into a series, clean it up removing `NaN`s, extract the series values as an array, check how many values we lost."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2407"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ibu_series = beers['ibu']\n",
-    "\n",
-    "len(ibu_series)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1405"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ibu_clean = ibu_series.dropna()\n",
-    "\n",
-    "ibu = ibu_clean.values\n",
-    "\n",
-    "len(ibu)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "##### Exercise\n",
-    "\n",
-    "Write a Python function that calculates the percentage of missing values for a certain data series. Use the function to calculate the percentage of missing values for the `abv` and `ibu` data sets. \n",
-    "\n",
-    "For the original series, before cleaning, remember that you can access the values with `series.values` (e.g., `abv_series.values`)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "##### Important:\n",
-    "\n",
-    "Notice that in the case of the variable `ibu` we are missing almost 42% of the values. This is important, because it will affect our analysis. When we do descriptive statistics, we will ignore these missing values, and having 42% missing will very likely cause bias."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Step 3: Ready, stats, go!\n",
-    "\n",
-    "\n",
-    "Now that we have numpy arrays with clean data, let's see how we can process them to get some useful information. \n",
-    "\n",
-    "Focusing on the numerical variables `abv` and `ibu`, we'll walk through some \"descriptive statistics,\" below. In other words, we aim to generate statistics that summarize the data concisely."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Maximum and minimum \n",
-    "\n",
-    "The maximum and minimum values of a dataset are helpful as they tell us the _range_ of our sample: the range gives some indication of the _variability_ in the data.\n",
-    "We can obtain them for our `abv` and `ibu` arrays with the `min()` and `max()` functions from numpy."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**abv**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "abv_min = np.min(abv)\n",
-    "abv_max = np.max(abv)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The minimum value for abv is:  0.001\n",
-      "The maximum value for abv is:  0.128\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('The minimum value for abv is: ', abv_min)\n",
-    "print('The maximum value for abv is: ', abv_max)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**ibu**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ibu_min = np.min(ibu)\n",
-    "ibu_max = np.max(ibu)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The minimum value for ibu is:  4.0\n",
-      "The maximum value for ibu is:  138.0\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('The minimum value for ibu is: ', ibu_min)\n",
-    "print('The maximum value for ibu is: ', ibu_max)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Mean value\n",
-    "\n",
-    "The **mean** value is one of the main measures to describe the central tendency of the data: an indication of where's the \"center\" of the data. If we have a sample of $N$ values, $x_i$, the mean, $\\bar{x}$, is calculated by:\n",
-    "\n",
-    "\\begin{equation*}\n",
-    "    \\bar{x} = \\frac{1}{N}\\sum_{i} x_i\n",
-    "\\end{equation*}\n",
-    "\n",
-    "In words, that is the sum of the data values divided by the number of values, $N$. \n",
-    "\n",
-    "You've already learned how to write a function to compute the mean in [Module 1 Lesson 5](http://go.gwu.edu/engcomp1lesson5), but you also learned that numpy has a built-in `mean()` function. We'll use this to get the mean of the `abv` and `ibu` values."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "abv_mean = np.mean(abv)\n",
-    "ibu_mean = np.mean(ibu)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Next, we'll print these two variables, but we'll use some fancy new way of printing with Python's string formatter, `string.format()`. There's a sweet site dedicated to Python's string formatter, called [PyFormat](https://pyformat.info), where you can learn lots of tricks!\n",
-    "\n",
-    "The basic trick is to use curly brackets `{}` as placeholder for a variable value that you want to print in the middle of a string (say, a sentence that explains what you are printing), and to pass the variable name as argument to `.format()`, preceded by the string.\n",
-    "\n",
-    "Let's try something out…"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The mean value for abv is 0.059773424190800686 and for ibu 42.71316725978647\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('The mean value for abv is {} and for ibu {}'.format(abv_mean, ibu_mean))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Ugh! That doesn't look very good, does it? Here's where Python's string formatting gets fancy. We can print fewer decimal digits, so the sentence is more readable. For example, if we want to have four decimal digits, we specify it this way:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The mean value for abv is 0.0598 and for ibu 42.7132\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('The mean value for abv is {:.4f} and for ibu {:.4f}'.format(abv_mean, ibu_mean))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Inside the curly brackets—the placeholders for the values we want to print—the `f` is for `float` and the `.4` is for four digits after the decimal dot. The colon here marks the beginning of the format specification (as there are options that can be passed before). There are so many tricks to Python's string formatter that you'll usually look up just what you need.\n",
-    "Another useful resource for string formatting is the [Python String Format Cookbook](https://mkaz.blog/code/python-string-format-cookbook/). Check it out!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Variance and standard deviation\n",
-    "\n",
-    "While the mean indicates where's the center of your data, the **variance** and **standard deviation** describe the *spread* or variability of the data. We already mentioned that the _range_ (difference between largest and smallest data values) is also an indication of variability. But the standard deviation is the most common measure of variability.\n",
-    "\n",
-    "We really like the way [Prof. Kristin Sainani](https://profiles.stanford.edu/kristin-sainani), of Stanford University, presents this in her online course on [Statistics in Medicine](https://lagunita.stanford.edu/courses/Medicine/MedStats-SP/SelfPaced/about). In her lecture \"Describing Quantitative Data: What is the variability in the data?\", available [on YouTube](https://youtu.be/hlFeEQF5tDc), she asks: _What if someone were to ask you to devise a statistic that gives the avarage distance from the mean?_ Think about this a little bit.\n",
-    "\n",
-    "The distance from the mean, for any data value, is $x_i - \\bar{x}$. So what is the average of the distances from the mean? If we try to simply compute the average of all the values $x_i - \\bar{x}$, some of which are negative, you'll just get zero! It doesn't work.\n",
-    "\n",
-    "Since the problem is the negative distances from the mean, you might suggest using absolute values. But this is just mathematically inconvenient. Another way to get rid of negative values is to take the squares. And that's how we get to the expression for the _variance_: it is the average of the squares of the deviations from the mean. For a set of $N$ values,\n",
-    "\n",
-    "\\begin{equation*}\n",
-    "     \\text{var} = \\frac{1}{N}\\sum_{i} (x_i - \\bar{x})^2\n",
-    "\\end{equation*}\n",
-    "\n",
-    "\n",
-    "The variance itself is hard to interpret. The problem with it is that the units are strange (they are the square of the original units). The **standard deviation**, the square root of the variance, is more meaningful because it has the same units as the original variable. Often, the symbol $\\sigma$ is used for it:\n",
-    "\n",
-    "\\begin{equation*} \n",
-    "    \\sigma = \\sqrt{\\text{var}} = \\sqrt{\\frac{1}{N}\\sum_{i} (x_i - \\bar{x})^2}\n",
-    "\\end{equation*}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Sample vs. population\n",
-    "\n",
-    "The above definitions are used when $N$ (the number of values) represents the entire population. But if we have a _sample_ of that population, the formulas have to be adjusted: instead of dividing by $N$ we divide by $N-1$. This is important, especially when we work with real data since usually we have samples of populations. \n",
-    "\n",
-    "The **standard deviation** of a sample is denoted by $s$, and the formula is:\n",
-    "\n",
-    "\\begin{equation*}     \n",
-    "     s = \\sqrt{\\frac{1}{N-1}\\sum_{i} (x_i - \\bar{x})^2}\n",
-    "\\end{equation*}\n",
-    "\n",
-    "Why? This gets a little technical, but the reason is that if you have a _sample_ of the population, you don't know the _real_ value of the mean, and $\\bar{x}$ is actually an _estimate_ of the mean. That's why you'll often find the symbol $\\mu$ used to denote the population mean, and distinguish it with the sample mean, $\\bar{x}$. Using $\\bar{x}$ to compute the standard deviation introduces a small bias: $\\bar{x}$ is computed _from the sample values_, and the data are on average (slightly) closer to $\\bar{x}$ than the population is to $\\mu$. Dividing by $N-1$ instead of $N$ corrects this bias!\n",
-    "\n",
-    "Prof. Sainani explains it by saying that we lost one degree of freedom when we estimated the mean using $\\bar{x}$.  For example, say we have 100 people and I give you their mean age, and the actual age for 99 people from the sample: you'll be able to calculate the age of that 100th person. Once we calculated the mean, we only have 99 degrees of freedom left because that 100th person's age is fixed. \n",
-    "\n",
-    "Below is a graphical distinction between the _sample_ and the _population_ from [@allison_horst on twitter](https://twitter.com/allison_horst)\n",
-    "\n",
-    "![Sample vs Population from @allison_horst](https://pbs.twimg.com/media/EOM8s3fVUAAglHu?format=jpg&name=small)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Let's code!\n",
-    "\n",
-    "Now that we have the math sorted out, we can program functions to compute the variance and the standard deviation. In our case, we are working with samples of the population of craft beers, so we need to use the formulas with $N-1$ in the denominator. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def sample_var(array):\n",
-    "    \"\"\" Calculates the variance of an array that contains values of a sample of a \n",
-    "    population. \n",
-    "    \n",
-    "    Arguments\n",
-    "    ---------\n",
-    "    array : array, contains sample of values. \n",
-    "    \n",
-    "    Returns\n",
-    "    -------\n",
-    "    var   : float, variance of the array .\n",
-    "    \"\"\"\n",
-    "    \n",
-    "    sum_sqr = 0 \n",
-    "    mean = np.mean(array)\n",
-    "    \n",
-    "    for element in array:\n",
-    "        sum_sqr += (element - mean)**2\n",
-    "    \n",
-    "    N = len(array)\n",
-    "    var = sum_sqr / (N - 1)\n",
-    "    \n",
-    "    return var\n",
-    "    "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Notice that we used `np.mean()` in our function: do you think we can make this function even more Pythonic? \n",
-    "\n",
-    "*Hint:* Yes!, we totally can.\n",
-    "\n",
-    "##### Exercise:\n",
-    "\n",
-    "Re-write the function `sample_var()` using `np.sum()` to replace the `for`-loop. Name the function `var_pythonic`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We have the sample variance, so we take its square root to get the standard deviation. We can make it a function, even though it's just one line of Python, to make our code more readable:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def sample_std(array):\n",
-    "    \"\"\" Computes the standard deviation of an array that contains values\n",
-    "    of a sample of a population.\n",
-    "    \n",
-    "    Arguments\n",
-    "    ---------\n",
-    "    array : array, contains sample of values. \n",
-    "    \n",
-    "    Returns\n",
-    "    -------\n",
-    "    std   : float, standard deviation of the array.\n",
-    "    \"\"\"\n",
-    "    \n",
-    "    std = np.sqrt(sample_var(array))\n",
-    "    \n",
-    "    return std"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's call our brand new functions and assign the output values to new variables:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "abv_std = sample_std(abv)\n",
-    "ibu_std = sample_std(ibu)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "If we print these values using the string formatter, only printing 4 decimal digits, we can display our descriptive statistics in a pleasant, human-readable way."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The standard deviation for abv is 0.0135 and for ibu 25.9541\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('The standard deviation for abv is {:.4f} and for ibu {:.4f}'.format(abv_std, ibu_std))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "These numbers tell us that the `abv` values are quite concentrated around the mean value, while the `ibu` values are quite spread out from their mean. How could we check these descriptions of the data? A good way of doing so is using graphics: various types of plots can tell us things about the data. \n",
-    "\n",
-    "We'll learn about _histograms_ in this lesson, and in the following lesson we'll explore _box plots_. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Step 4: Distribution plots \n",
-    "\n",
-    "Every time that we work with data, visualizing it is very useful. Visualizations give us a better idea of how our data behaves. One way of visualizing data is with a frequency-distribution plot known as **histogram**: a graphical representation of how the data is distributed. To make a histogram, first we need to \"bin\" the range of values (divide the range into intervals) and then we count how many data values fall into each interval. The intervals are usually consecutive (not always), of equal size and non-overlapping. \n",
-    "\n",
-    "Thanks to Python and Matplotlib, making histograms is easy. We recommend that you always read the documentation, in this case about [histograms](https://matplotlib.org/devdocs/api/_as_gen/matplotlib.pyplot.hist.html). We'll show you here an example using the `hist()` function from `pyplot`, but this is just a starting point. \n",
-    "\n",
-    "Let's first load the **Matplotlib** module called `pyplot`, for making 2D plots. Remember that to get the plots inside the notebook, we use a special \"magic\" command, `%matplotlib inline`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from matplotlib import pyplot\n",
-    "%matplotlib inline\n",
-    "\n",
-    "#Import rcParams to set font styles\n",
-    "from matplotlib import rcParams"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(array([  1.,   0.,  38., 699., 857., 486., 159., 104.,   1.,   3.]),\n",
-       " array([0.001 , 0.0137, 0.0264, 0.0391, 0.0518, 0.0645, 0.0772, 0.0899,\n",
-       "        0.1026, 0.1153, 0.128 ]),\n",
-       " <a list of 10 Patch objects>)"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "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": [
-    "pyplot.hist(abv)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now we have a line plot, but if you see this plot without any information you would not be able to figure out what kind of data it is! We need labels on the axes, a title and why not a better color, font and size of the ticks. \n",
-    "**Publication quality** plots should always be your standard for plotting. \n",
-    "How you present your data will allow others (and probably you in the future) to better understand your work. \n",
-    "\n",
-    "We can customize the style of our plots using parameters for the lines, text, font and other plot options. We set some style options that apply for all the plots in the current session with [`plt.rc()`](https://matplotlib.org/api/_as_gen/matplotlib.plt.rc.html)\n",
-    "Here, we'll make the font of a specific type and size (sans-serif and 18 points). You can also customize other parameters like line width, color, and so on (check out the documentation)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Set font style and size \n",
-    "rcParams['font.family'] = 'sans'\n",
-    "rcParams['lines.linewidth'] = 3\n",
-    "rcParams['font.size'] = 18"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We'll redo the same plot, but now we'll add a few things to make it prettier and **publication quality**. We'll add a title, label the axes and, show a background grid. Study the commands below and look at the result!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x360 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "#You can set the size of the figure by doing:\n",
-    "pyplot.figure(figsize=(10,5))\n",
-    "\n",
-    "#Plotting\n",
-    "pyplot.hist(abv, bins=20, color='b', histtype='bar', edgecolor='white') \n",
-    "#The \\n is to leave a blank line between the title and the plot\n",
-    "pyplot.title('abv \\n')\n",
-    "pyplot.xlabel('Alcohol by Volume (abv) ')\n",
-    "pyplot.ylabel('Frequency');"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x360 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "#You can set the size of the figure by doing:\n",
-    "pyplot.figure(figsize=(10,5))\n",
-    "\n",
-    "#Plotting\n",
-    "pyplot.hist(ibu, bins=20, color=(0.9, 0.5, 0, 0.9), histtype='bar', edgecolor='white') \n",
-    "#The \\n is to leave a blanck line between the title and the plot\n",
-    "pyplot.title('ibu \\n')\n",
-    "pyplot.xlabel('International Bittering Units (ibu)')\n",
-    "pyplot.ylabel('Frequency');"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In the previous two plots we set the colors in two ways:\n",
-    "\n",
-    "1. A string 'b', which specifies blue. We could also choose from: a string representation \n",
-    "one of \n",
-    "\n",
-    "    {'b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'} = \n",
-    "    {**b**lue, **g**reen, **r**ed, **c**yan, **m**agenta, **y**ellow, blac**k**, **w**hite}\n",
-    "    \n",
-    "2. A RGB or RGBA (red, green, blue, alpha) tuple of float values in [0, 1] (e.g., (0.1, 0.2, 0.5) or (0.1, 0.2, 0.5, 0.3));\n",
-    "\n",
-    "Check out the other formatting options use can use in [Matplotlib colors](https://matplotlib.org/3.1.1/tutorials/colors/colors.html) and [Matplotlib hist command](https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.hist.html?highlight=hist#matplotlib.pyplot.hist)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Exploratory exercise:\n",
-    "\n",
-    "Play around with the plots, change the values of the bins, colors, etc."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Comparing with a normal distribution\n",
-    "\n",
-    "A **normal** (or Gaussian) distribution is a special type of distrubution that behaves as shown in the figure: 68% of the values are within one standard deviation $\\sigma$ from the mean; 95% lie within $2\\sigma$; and at a distance of $\\pm3\\sigma$ from the mean, we cover 99.7% of the values. This fact is known as the $3$-$\\sigma$ rule, or 68-95-99.7 (empirical) rule.\n",
-    "\n",
-    "<img src=\"../images/std_bell_curve.png\" style=\"width: 800px;\"/> \n",
-    "\n",
-    "####  Standard deviation and coverage in a normal distribution. Modified figure based on original from [Wikimedia Commons](https://commons.wikimedia.org/wiki/File:Standard_deviation_diagram.svg), the free media repository.\n",
-    "\n",
-    "\n",
-    "Notice that our histograms don't follow the shape of a normal distribution, known as *Bell Curve*. Our histograms are not centered in the mean value, and they are not symetric with respect to it. They are what we call **skewed** to the right (yes, to the _right_). A right (or positive) skewed distribution  looks like it's been pushed to the left: the right tail is longer and most of the values are concentrated on the left of the figure. Imagine that \"right-skewed\" means that a force from the right pushes on the curve."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Discussion point\n",
-    "\n",
-    "* How do you think that skewness will affect the percentages of coverage by standard deviation compared to the Bell Curve?\n",
-    "\n",
-    "* Can we calculate those percentages? \n",
-    "\n",
-    "## Exercise\n",
-    "\n",
-    "We can calculate skewness and standard deviation in a few lines of Python. But before doing that, we want you to explain in your own words how the following piece of code works. \n",
-    "\n",
-    "*Hints:* \n",
-    "\n",
-    "1. Check what the logical operation `np.logical_and(1<x, x<4)` returns.\n",
-    "2. Check what happens if you sum booleans. For example, `True + True`, `True + False` and so on.\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2\n"
-     ]
-    }
-   ],
-   "source": [
-    "x = np.array([1,2,3,4])\n",
-    "num_ele = np.logical_and(1<x, x<4).sum()\n",
-    "print(num_ele)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now, using the same idea, we will calculate the number of elements in each interval of width $(1\\sigma, 2\\sigma, 3\\sigma)$, and get the corresponding percentage. \n",
-    "\n",
-    "Since we want to compute this for both of our variables, `abv` and `ibu`, we'll write a function to do so. Study carefully the code below. Better yet, explain it to your neighbor."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def std_percentages(x, x_mean, x_std):\n",
-    "    \"\"\" Computes the percentage of coverage at 1std, 2std and 3std from the\n",
-    "    mean value of a certain variable x.\n",
-    "    \n",
-    "    Arguments\n",
-    "    ---------\n",
-    "    x      : array, data we want to compute on. \n",
-    "    x_mean : float, mean value of x array.\n",
-    "    x_std  : float, standard deviation of x array.\n",
-    "    \n",
-    "    Returns\n",
-    "    -------\n",
-    "    \n",
-    "    per_std_1 : float, percentage of values within 1 standard deviation.\n",
-    "    per_std_2 : float, percentage of values within 2 standard deviations.\n",
-    "    per_std_3 : float, percentage of values within 3 standard deviations.    \n",
-    "    \"\"\"\n",
-    "    \n",
-    "    std_1 = x_std\n",
-    "    std_2 = 2 * x_std\n",
-    "    std_3 = 3 * x_std\n",
-    "    \n",
-    "    elem_std_1 = np.logical_and((x_mean - std_1) < x, x < (x_mean + std_1)).sum()\n",
-    "    per_std_1 = elem_std_1 * 100 / len(x) \n",
-    "    \n",
-    "    elem_std_2 = np.logical_and((x_mean - std_2) < x, x < (x_mean + std_2)).sum()\n",
-    "    per_std_2 = elem_std_2 * 100 / len(x) \n",
-    "    \n",
-    "    elem_std_3 = np.logical_and((x_mean - std_3) < x, x < (x_mean + std_3)).sum()\n",
-    "    per_std_3 = elem_std_3 * 100 / len(x) \n",
-    "    \n",
-    "    return per_std_1, per_std_2, per_std_3\n",
-    "    "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's compute the percentages next. Notice that the function above returns three values. If we want to assign each value to a different variable, we need to follow a specific syntax. In our example this would be:"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**abv**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "abv_std1_per, abv_std2_per, abv_std3_per = std_percentages(abv, abv_mean, abv_std)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's pretty-print the values of our variables so we can inspect them:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The percentage of coverage at 1 std of the abv_mean is : 74.06 %\n",
-      "The percentage of coverage at 2 std of the abv_mean is : 94.34 %\n",
-      "The percentage of coverage at 3 std of the abv_mean is : 99.79 %\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('The percentage of coverage at 1 std of the abv_mean is : {:.2f} %'.format(abv_std1_per))\n",
-    "print('The percentage of coverage at 2 std of the abv_mean is : {:.2f} %'.format(abv_std2_per))\n",
-    "print('The percentage of coverage at 3 std of the abv_mean is : {:.2f} %'.format(abv_std3_per))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**ibu**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ibu_std1_per, ibu_std2_per, ibu_std3_per = std_percentages(ibu, ibu_mean, ibu_std)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The percentage of coverage at 1 std of the ibu_mean is : 68.11 %\n",
-      "The percentage of coverage at 2 std of the ibu_mean is : 95.66 %\n",
-      "The percentage of coverage at 3 std of the ibu_mean is : 99.72 %\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('The percentage of coverage at 1 std of the ibu_mean is : {:.2f} %'.format(ibu_std1_per))\n",
-    "print('The percentage of coverage at 2 std of the ibu_mean is : {:.2f} %'.format(ibu_std2_per))\n",
-    "print('The percentage of coverage at 3 std of the ibu_mean is : {:.2f} %'.format(ibu_std3_per))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Notice that in both cases the percentages are not that far from the values for normal distribution (68%, 95%, 99.7%), especially for $2\\sigma$ and $3\\sigma$. So usually you can use these values as a rule of thumb. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## What we've learned\n",
-    "\n",
-    "* Read data from a `csv` file using `pandas`.\n",
-    "* The concepts of Data Frame and Series in `pandas`.\n",
-    "* Clean null (NaN) values from a Series using `pandas`.\n",
-    "* Convert a `panda`s Series into a `numpy` array.\n",
-    "* Compute maximum and minimum, and range.\n",
-    "* Revise concept of mean value.\n",
-    "* Compute the variance and standard deviation.\n",
-    "* Use the mean and standard deviation to understand how the data is distributed.\n",
-    "* Plot frequency distribution diagrams (histograms).\n",
-    "* Normal distribution and 3-sigma rule.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## References\n",
-    "\n",
-    "1. [Craft beer datatset](https://github.com/nickhould/craft-beers-dataset) by Jean-Nicholas Hould.\n",
-    "2. [Exploratory Data Analysis](https://en.wikipedia.org/wiki/Exploratory_data_analysis), Wikipedia article.\n",
-    "3. _Think Python: How to Think Like a Computer Scientist_ (2012). Allen Downey. Green Tea Press.  [PDF available](http://greenteapress.com/thinkpython/thinkpython.pdf)\n",
-    "4. [Intro to data Structures](https://pandas.pydata.org/pandas-docs/stable/dsintro.html), `pandas` documentation.\n",
-    "5. _Think Stats: Probability and Statistics for Programmers_ version 1.6.0 (2011). Allen Downey. Green Tea Press.  [PDF available](http://greenteapress.com/thinkstats/thinkstats.pdf)\n",
-    "\n",
-    "### Recommended viewing\n",
-    "\n",
-    "From [\"Statistics in Medicine,\"](https://lagunita.stanford.edu/courses/Medicine/MedStats-SP/SelfPaced/about), a free course in Stanford Online by Prof. Kristin Sainani, we highly recommend that you watch these three lectures: \n",
-    "* [Describing Quantitative Data: Where is the center?](https://youtu.be/tQ5slNYRcC4)\n",
-    "* [Describing Quantitative Data: What is the variability in the data?](https://youtu.be/hlFeEQF5tDc)\n",
-    "* [Variability in the data, continued: examples, bell curve](https://youtu.be/qeG0uNI3DBQ)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "widgets": {
-   "state": {},
-   "version": "1.1.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/.ipynb_checkpoints/02_Seeing_Stats-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/02_Seeing_Stats-checkpoint.ipynb
deleted file mode 100644
index a25d3aa..0000000
--- a/notebooks/.ipynb_checkpoints/02_Seeing_Stats-checkpoint.ipynb
+++ /dev/null
@@ -1,1641 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "###### Content modified under Creative Commons Attribution license CC-BY 4.0, code under BSD 3-Clause License © 2020 R.C. Cooper"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Seeing stats in a new light\n",
-    "\n",
-    "Welcome to the second lesson in \"Analyze Data,\" Module 2 of our series in _Computational Mechanics_. In the previous lesson, [Cheers! Stats with Beers](./01_Cheers_Stats_Beers.ipynb), we did some exploratory data analysis with a data set of canned craft beers in the US [1]. We'll continue using that same data set here, but with a new focus on _visualizing statistics_.\n",
-    "\n",
-    "In her lecture [\"Looking at Data\"](https://youtu.be/QYDuAo9r1xE), Prof. Kristin Sainani says that you should always plot your data. Immediately, several things can come to light: are there outliers in your data? (Outliers are data points that look abnormally far from other values in the sample.) Are there data points that don't make sense? (Errors in data entry can be spotted this way.) And especially, you want to get a _visual_ representation of how data are distributed in your sample.\n",
-    "\n",
-    "In this lesson, we'll play around with different ways of visualizing data. We have so many ways to play! Have a look at the gallery of [The Data Viz Project](http://datavizproject.com) by _ferdio_ (a data viz agency in Copenhagen). Aren't those gorgeous? Wouldn't you like to be able to make some pretty pics like that? Python can help!\n",
-    "\n",
-    "Let's begin. We'll import our favorite Python libraries, and set some font parameters for our plots to look nicer. Then we'll load our data set for craft beers and begin!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "import matplotlib.pyplot as plt\n",
-    "%matplotlib inline\n",
-    "\n",
-    "#Import rcParams to set font styles\n",
-    "from matplotlib import rcParams\n",
-    "\n",
-    "#Set font style and size \n",
-    "rcParams['font.family'] = 'sans'\n",
-    "rcParams['font.size'] = 16\n",
-    "rcParams['lines.linewidth'] = 3"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Read the data\n",
-    "\n",
-    "Like in the previous lesson, we will load the data from a `.csv` file. You may have the file in your working directory if you downloaded it when working through the previous lesson. In that case, you could load it like this:\n",
-    "\n",
-    "```Python\n",
-    "beers = pd.read_csv(\"beers.csv\")\n",
-    "```\n",
-    "\n",
-    "If you downloaded the full set of lesson files from our public repository, you can find the file in the `/data` folder, and you can load it with the full path:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Load the beers data set using pandas, and assign it to a dataframe\n",
-    "beers = pd.read_csv(\"../data/beers.csv\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "##### Note:\n",
-    "\n",
-    "If you don't have the data file locally, download it by adding a code cell, and executing the following code in it:\n",
-    "\n",
-    "```Python\n",
-    "from urllib.request import urlretrieve\n",
-    "URL = 'http://go.gwu.edu/engcomp2data1?accessType=DOWNLOAD'\n",
-    "urlretrieve(URL, 'beers.csv')\n",
-    "```\n",
-    "The data file will be downloaded to your working directory, and you will load it like described above."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "OK. Let's have a look at the first few rows of the `pandas` dataframe we just created from the file, and confirm that it's a dataframe using the `type()` function. We only display the first 10 rows to save some space."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "pandas.core.frame.DataFrame"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type(beers)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "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>Unnamed: 0</th>\n",
-       "      <th>abv</th>\n",
-       "      <th>ibu</th>\n",
-       "      <th>id</th>\n",
-       "      <th>name</th>\n",
-       "      <th>style</th>\n",
-       "      <th>brewery_id</th>\n",
-       "      <th>ounces</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>2</td>\n",
-       "      <td>0.071</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2264</td>\n",
-       "      <td>Rise of the Phoenix</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>177</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>4</td>\n",
-       "      <td>0.075</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2262</td>\n",
-       "      <td>Sex and Candy</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>177</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>28</td>\n",
-       "      <td>0.070</td>\n",
-       "      <td>70.0</td>\n",
-       "      <td>799</td>\n",
-       "      <td>21st Amendment IPA (2006)</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>368</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>29</td>\n",
-       "      <td>0.070</td>\n",
-       "      <td>70.0</td>\n",
-       "      <td>797</td>\n",
-       "      <td>Brew Free! or Die IPA (2008)</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>368</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>30</th>\n",
-       "      <td>30</td>\n",
-       "      <td>0.070</td>\n",
-       "      <td>70.0</td>\n",
-       "      <td>796</td>\n",
-       "      <td>Brew Free! or Die IPA (2009)</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>368</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2387</th>\n",
-       "      <td>2390</td>\n",
-       "      <td>0.059</td>\n",
-       "      <td>135.0</td>\n",
-       "      <td>1676</td>\n",
-       "      <td>Troopers Alley IPA</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>344</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2390</th>\n",
-       "      <td>2393</td>\n",
-       "      <td>0.065</td>\n",
-       "      <td>82.0</td>\n",
-       "      <td>2417</td>\n",
-       "      <td>4000 Footer IPA</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>109</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2392</th>\n",
-       "      <td>2395</td>\n",
-       "      <td>0.065</td>\n",
-       "      <td>69.0</td>\n",
-       "      <td>1697</td>\n",
-       "      <td>Be Hoppy IPA</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>339</td>\n",
-       "      <td>16.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2393</th>\n",
-       "      <td>2396</td>\n",
-       "      <td>0.069</td>\n",
-       "      <td>69.0</td>\n",
-       "      <td>2194</td>\n",
-       "      <td>Worthy IPA</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>199</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2396</th>\n",
-       "      <td>2399</td>\n",
-       "      <td>0.069</td>\n",
-       "      <td>69.0</td>\n",
-       "      <td>1512</td>\n",
-       "      <td>Worthy IPA (2013)</td>\n",
-       "      <td>American IPA</td>\n",
-       "      <td>199</td>\n",
-       "      <td>12.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>424 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      Unnamed: 0    abv    ibu    id                          name  \\\n",
-       "2              2  0.071    NaN  2264           Rise of the Phoenix   \n",
-       "4              4  0.075    NaN  2262                 Sex and Candy   \n",
-       "28            28  0.070   70.0   799     21st Amendment IPA (2006)   \n",
-       "29            29  0.070   70.0   797  Brew Free! or Die IPA (2008)   \n",
-       "30            30  0.070   70.0   796  Brew Free! or Die IPA (2009)   \n",
-       "...          ...    ...    ...   ...                           ...   \n",
-       "2387        2390  0.059  135.0  1676            Troopers Alley IPA   \n",
-       "2390        2393  0.065   82.0  2417               4000 Footer IPA   \n",
-       "2392        2395  0.065   69.0  1697                  Be Hoppy IPA   \n",
-       "2393        2396  0.069   69.0  2194                    Worthy IPA   \n",
-       "2396        2399  0.069   69.0  1512             Worthy IPA (2013)   \n",
-       "\n",
-       "             style  brewery_id  ounces  \n",
-       "2     American IPA         177    12.0  \n",
-       "4     American IPA         177    12.0  \n",
-       "28    American IPA         368    12.0  \n",
-       "29    American IPA         368    12.0  \n",
-       "30    American IPA         368    12.0  \n",
-       "...            ...         ...     ...  \n",
-       "2387  American IPA         344    12.0  \n",
-       "2390  American IPA         109    12.0  \n",
-       "2392  American IPA         339    16.0  \n",
-       "2393  American IPA         199    12.0  \n",
-       "2396  American IPA         199    12.0  \n",
-       "\n",
-       "[424 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "beers[beers['style']=='American IPA']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index(['Unnamed: 0', 'abv', 'ibu', 'id', 'name', 'style', 'brewery_id',\n",
-       "       'ounces'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "beers.columns"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Quantitative vs. categorical data\n",
-    "\n",
-    "As you can see in the nice table that `pandas` printed for the dataframe, we have several features for each beer: the label `abv` corresponds to the acohol-by-volume fraction, label `ibu` refers to the international bitterness unit (IBU), then we have the `name` of the beer and the `style`, the brewery ID number, and the liquid volume of the beer can, in ounces.\n",
-    "\n",
-    "Alcohol-by-volume is a numeric feature: a volume fraction, with possible values from 0 to 1 (sometimes also given as a percentage). In the first 10 rows of our dataframe, the `ibu` value is missing (all those `NaN`s), but we saw in the previous lesson that `ibu` is also a numeric feature, with values that go from a minimum of 4 to a maximum of 138 (in our data set). IBU is pretty mysterious: how do you measure the bitterness of beer? It turns out that bitterness is measured as parts per million of _isohumulone_, the acid found in hops [2]. \n",
-    "\n",
-    "For these numeric features, we learned that we can get an idea of the _central tendency_ in the data using the **mean value**, and we get ideas of _spread_ of the data with the **standard deviation** (and also with the range, but standard deviation is the most common).\n",
-    "\n",
-    "Notice that the beer data also has a feature named `style`: it can be \"American IPA\" or \"American Porter\" or a bunch of other styles of beer. If we want to study the beers according to style, we'll have to come up with some new ideas, because you can't take the mean or standard deviation of this feature!\n",
-    "\n",
-    "**Quantitative data** have meaning through a numeric feature, either on a continuous scale (like a fraction from 0 to 1), or a discrete count. \n",
-    "**Categorical data**, in contrast, have meaning through a qualitative feature (like the style of beer). Data in this form can be collected in groups (categories), and then we can count the number of data items in that group. For example, we could ask how many beers (in our set) are of the style \"American IPA,\" or ask how many beers we have in each style.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Visualizing quantitative data\n",
-    "\n",
-    "In the previous lesson, we played around a bit with the `abv` and `ibu` columns of the dataframe `beers`. For each of these columns, we extracted it from the dataframe and saved it into a `pandas` series, then we used the `dropna()` method to get rid of null values. This \"clean\" data was our starting point for some exploratory data analysis, and for plotting the data distributions using **histograms**. Here, we will add a few more ingredients to our recipes for data exploration, and we'll learn about a new type of visualization: the **box plot**.\n",
-    "\n",
-    "Let's repeat here the process for extracting and cleaning the two series, and getting the values into NumPy arrays:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Repeat cleaning values abv\n",
-    "abv_series = beers['abv']\n",
-    "abv_clean = abv_series.dropna()\n",
-    "abv = abv_clean.values"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Repeat cleaning values ibu\n",
-    "ibu_series = beers['ibu']\n",
-    "ibu_clean = ibu_series.dropna()\n",
-    "ibu = ibu_clean.values"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's also repeat a histogram plot for the `abv` variable, but this time choose to plot just 10 bins (you'll see why in a moment)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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K4gA2rrLiZmbWnI5eKywi7pC0HXAx8Olc/DzwqYiYml+PAeaVzD63bnrt+YlYel9eMW4pkg4GDgYYN25cK00wM7N+dHrwfiPgIlKvYmfgPcAPgR9K2qcWBpTtXS7u5W42bikRcUZETIyIiWPHjm22+mZm1oROX934eFIPZaeIeD6XXSNpdeBUSb8g9TjKuhGj8/PcuufRklTotRTjzMysgzo9xrIpcGtdUqn5M7A6sCapNzNB0kqFmI2BRbw8pjITWBF4bUkcwF+rqrSZmTWv04nlEWBzSSML5VsCC0m9jGmk81x2r03Mhxt/FLgyIp7Lxb8lJZp9llwU+wJ3RMTs6qtvZmb96fSusNOAXwKXSvoB6bDjycBewMkRsQi4RdL5wCmSRgCzgUOACdQlkYh4VNLJwBGSngZuJiWfHYAPdbBNZmZWp9NHhV2Yz4r/CnAmMAr4B/AZ4Ed1oQcAxwHHAqsBtwLvj4ibC4s8EpgPfA5YG7gL2CMiLm1nO8zMrLGOnnm/LPKZ99YMn3lvtqRl6cx7MzMb4pxYzMysUk4sZmZWKScWMzOrlBOLmZlVyonFzMwq5cRiZmaVcmIxM7NKObGYmVmlnFjMzKxSTixmZlYpJxYzM6uUE4uZmVXKicXMzCrlxGJmZpVyYjEzs0o5sZiZWaWcWKwnLFzY7RqYWbM6es97s4EaNao7twcG3yLYrFXusZiZWaWcWMzMrFJOLGZmViknFjMzq5QTi5mZVcqJxczMKuXEYmZmlXJiMTOzSjmxmJlZpZxYzMysUk4sZmZWKScWMzOrlBOLmZlVyonFzMwq5cRiZmaVcmIxM7NKObGYmVmlupJYJH1Q0nWS5kt6StIMSTvUTR8t6UxJj0l6RtLVkjYtWc4oSSdJeljSAknXS9qms60xM7N6HU8skj4JXALcBHwY2B34JbBSni5gGvB+4FBgV2AEcK2kVxcWdxZwEHA0sBPwMHCFpM3b3xIzMyvT0j3vJa0cEfMHujJJ44FTgC9FxCl1k66o+3sysDWwQ0Rcm+e7HpgNfBk4LJdtBuwNHBgRZ+ey3wMzgW/m5ZiZWYe12mN5RNKPJL15gOs7EHgR+GEfMZOBh2pJBSAingQuBT5UiHseOL8ubjEwFZgkacUB1tHMzAah1cRyCmmX0wxJN0o6UNJKLcy/NXAnsKekf0haLGmWpM/UxWwC3FEy70xgnKSV6+JmR8SzJXEjgQ1bqJeZmVWkpcQSEUcB40jjInOBHwMPSfpvSf/WxCLWBTYCTgK+DbwPuAo4TdLncswYYF7JvHPz8+gm48Y0qoSkg/MBAzPmzJnTRLXNzKxZLQ/eR8QLEfGriJhEShKnkxLNrZL+KGlfSSP6WN8qwCcj4scR8buIOAT4LXBEHrgXECXzquR1M3FlbTgjIiZGxMSxY8f2F25mZi0Y7FFhjwMPkXoJAtYGfgrMkvT2BvGQein1rgTWAtbJyyrrbdR6KrVeSn9xc0ummZlZmw0osUjaUtJPgAeB44H/BbaIiA2BTYH7gTNKZp3ZaJH5+cUcs0lJzMbA/XVHpc0EJpSM8WwMLAJmNdkcMzOrUEuJRdIhkm4B/gS8HTgSeHVEHBQRtwBExF+BrwFvLFnExfl5UqF8EvBARDxCOodlPUnb1q13VWDnPK1mGun8lt3r4oYDHwWujIjnWmmbmZlVo6XzWIBTSYf9fiEirukj7u/ACSXllwPXAj+StAZwD7AbaRD/gBwzDbgemCLpS6RdX0eQejUn1hYUEbdIOh84JY/pzAYOASYA+7TYLjMzq0iriWV8RDzUX1BEPEjqtRTLQ9IupKTzDdJ4yJ3APhHx8xzzoqSdgO8CPwBGkRLN9hHxz8IiDwCOA44FVgNuBd4fETe32C4zM6uIIsoOrGoQLG0IrB0RfyyZ9k7gkYj4R4X1a7uJEyfGjBkzul0Na4L6Pd6vPSK6s+4W/jXNOk7STRExsWxaq4P3pwIfaTDtw8DJLS7PzMyGmFYTy1uB6Q2mTQe2HExlzMys97WaWFYFFjaYtgh41eCqY2Zmva7VxHIPsH2DadsD9w2uOmZm1utaTSxTgMMlfbJ22RZJI/I9Vv4D+FnVFTQzs97S6uHG3wHeRro+2GmS5gBr5OX8mnRhSTMzW461lFgi4gVgF0nvA94LrA48RjrT/eo21M/MzHpMqz0WACLiStKFI83MzJYwoMQCIGkM6az4JTRzZr6ZmQ1drd7zfhXge8CeQKM7Rw4bbKXMzKx3tdpjOQ3YAzgHuB3wFYTNzGwJrSaWDwBfjoj/bkdlzMys97V6HssKwN/aUREzMxsaWk0sFwA7tqMiZmY2NLS6K+x/gO9LeiXppl1L3Vc+Iq6romJmZtabBpJYADYAPgHU3zFC+bWPCjMzW461mlje25ZamJnZkNHqJV36us+9mZnZwM68lzSadFOv1YHLI2KepBER8XyltTMzs57T6lFhSDoBeIg0eP8zYEKedJmkoyqsm9lybWGjW+oN8XVb72spsUj6Cum+KycA7yQN2Ndcig9FNqvMqFEgdecxaqmrAJo1r9VdYQcD34qI4yQVj/76O7BhNdUyM7Ne1equsFcDf2owbRGw8uCqY2Zmva7VxPIQsEmDaZsC9w6qNmZm1vNaTSwXAkdL2rKuLCS9FvgicH5lNTMzs57UamI5BphF2h1WuxjlVOAOYDZpUN/MzJZjrZ4g+YykbYD9gEnAA8DjwInAz3wei5mZtXyCZEQsBs7ODzMzsyW0fIKkmZlZX1q95/3fWfKKxkUREa8fXJXMzKyXtbor7P9YOrGsDmwFPAX4XixmZsu5Vgfv9y0rlzQG+C1wWRWVMjOz3lXJGEtEzCUdGfb1KpZnZma9q8rB+2eBcRUuz8zMetCA7sdST9IKwMbA0bx80qSZmS2nWr1s/vOSFtU/SBefvBV4I+mS+i2R9FtJIenYQvloSWdKekzSM5KulrRpyfyjJJ0k6WFJCyRdn0/iNDOzLmi1x/Idlj4qbCFwH3BZRMxrZWGS9gI2KykXMI10E7FDgXnAEcC1kjaPiAfqws8i3QfmS8A9wGeAKyS9PSJuaaU+ZmY2eK0eFVbZHSIlrQacTOrl/LwweTKwNbBDRFyb468nXY/sy8BhuWwzYG/gwIg4O5f9HpgJfDMvx8zMOqibZ96fCMyMiF+UTJsMPFRLKgAR8STpLpUfKsQ9T91VlfMlZ6YCkySt2I6Km5lZY62eeX9GC+EREZ9ssJytgY9Rshss24R0xeSimcDHJK0cEfNz3OyIeLYkbiTpjpYzW6izmZkNUqtjLB8AVgFWBV4kjX2MJvV8ngKerostvfSLpBHAj4DvRsRdDdYzhvKbhs3Nz6OB+TmubFynFjemQR0OJt1mmXHjfIS0mVmVWt0VtgcpgewLvCIixgKvIF1G/ylg94h4TX40+sb+Sp7nuD7WI8oTkwYYt4SIOCMiJkbExLFjx/YVamZmLWq1x3IycGJEvDTYnu/Bcl6+rMupwJaNZpY0DjgS+ASwYmEMZMU8oP80qcdR1tsYnZ9rvZS5lJ+UObpuupmZdVCrPZbNgEa7r+4i3fe+LxsAo4AppORQe0C6tfG8vIyZpPGToo2B+/P4CjlugqSVSuIWke52aWZmHdRqYvkXsFuDabsDj/Yz/y3A9iUPSMlme1IymAasJ2nb2oySVgV2ztNqpgEj8rprccOBjwJXRsRzTbXKzMwq0+qusFOB/5K0NvBLUqJZizT2siPwhb5mjogngOnF8nQ+JPdFxPT8ehpwPTBF0pd4+QRJkQ5Tri3vFknnA6fkgwJmA4eQTqzcp8W2mZlZBVo9QfJkSc8CXyP1HmoeAg6JiFYOR+5rPS9K2gn4LvAD0u6z64HtI+KfhfADSAcCHAusRrq8zPsj4uYq6mJmZq1RRF83hGwwU7rw5PrAOsDDpN7GixXXrSMmTpwYM2bM6HY1rAnq81i/9onozrq7td7aus36IummiJhYNm1AVzfOSWR2fpiZmb2k5Uu6SHqTpAskPZKvcLxFLj9W0vuqr6KZmfWSVi+b/w7Sfe83A34FDCss61PVVc3MzHpRqz2W7wDXkO69chhLnuE+A3hLRfUyM7Me1eoYy1uAXfNRW8VhxcdIhx6bmdlyrNUey3Ok63yVWRt4cnDVMTOzXtdqYvkjcFg+3LimdmDigcC1S89iZmbLk1Z3hR1NSi5/IZ15H8C+kk4EtgLeVm31zMys17TUY4mIvwDbAU8Ax5AG7z9POjN++4j4W8X1MzOzHtPyCZIRcSOwbb6i8BrAvIh4up/ZzMxsOdF0j0XSSEmPStoZICKejYj7nVTMzKxe04klIhaRdn0tbF91zMys17V6VNg0YNd2VMTMzIaGVsdYpgGnSZoK/Jp0ZeMlroMaEddVVDczM+tBrSaWi/PzHvlRn1SUXw8rzmRmZsuPVhPLe9tSCzMzGzL6TSySdgD+HBHzI+KaDtTJzMx6WDOD91cBG9deSFpB0nWSNmpftczMrFc1k1iKVzEWsDWwSvXVMTOzXtfyHSTNzMz64sRiZmaVavaosPUkbZD/HlZX9kQxMCLuqaRmZmbWk5pNLBeWlP26QazPYzEzW441k1gOaHstzMxsyOg3sUTETztRETMzGxo8eG9mZpVyYjEzs0o5sZiZWaWcWMzMrFJOLGZmViknFjMzq5QTi5mZVcqJxczMKuXEYmZmlXJiMTOzSnU0sUjaTdJFku6TtEDSXZJOkLRKIW60pDMlPSbpGUlXS9q0ZHmjJJ0k6eG8vOslbdO5FpmZWVGneyxfBF4A/hN4P3A6cAhwlaQVACQJmJanHwrsCowArpX06sLyzgIOAo4GdgIeBq6QtHn7m2JmZmWavWx+VXaOiDl1r38vaS7wU2A74HfAZNKtj3eIiGsBJF0PzAa+DByWyzYD9gYOjIizc9nvgZnAN/NyzMyswzraYykklZob8/N6+Xky8FAtqeT5ngQuBT5UN99k4Hng/Lq4xcBUYJKkFSusupmZNWlZGLzfNj//LT9vAtxREjcTGCdp5bq42RHxbEncSGDDqitqZmb962pikbQeabfV1RExIxePAeaVhM/Nz6ObjBvTx3oPljRD0ow5c8o6UWZmNlBdSyy553EJsJgl71IpIMpmKXndTNxSIuKMiJgYERPHjh3bZI3NzKwZXUkskkaRjvzaAJgUEQ/UTZ5LeW+j1lOZ12Tc3JJpZmbWZh1PLJJGABcBbwM+GBG3F0JmksZPijYG7o+I+XVxEyStVBK3CJhVXa3NzKxZnT5BcgXgPODdwIci4oaSsGnAepK2rZtvVWDnPK0+bgSwe13ccOCjwJUR8Vz1LTAzs/50+jyW/0dKBMcBz0jaqm7aA3mX2DTgemCKpC+Rdn0dQRo7ObEWHBG3SDofOCX3gmaTTracAOzTicaYmdnSOr0r7AP5+UhS8qh/fAIgIl4knUV/FfAD4GLS2frbR8Q/C8s7ADgbOBa4DHgN8P6IuLm9zTAzs0YUUXZg1fJj4sSJMWPGjP4DrevU7/F+7RHRnXV3a721dZv1RdJNETGxbNqycIKkmZkNIU4sZmZWKScWM1vKwoXL13qtWp0+KszMesCoUd0bV7Le5x6LmZlVyonFzMwq5cRiZmaVcmIxM7NKObGYmVmlnFjMzKxSTixmZlYpJxYzM6uUE4uZmVXKicXMzCrlxGJmZpVyYjEzs0o5sZjZMsNXVR4afHVjM1tm+KrKQ4N7LGZmViknFjMzq5QTi5mZVcqJxczMKuXEYmZmlXJiMTOzSjmxmJlZpZxYzMysUk4sZmZWKScWMzOrlBOLmZlVyonFzMwq5cRiZmaVcmIxM7NKObFYS3zfCjPrj+/HYi3x/TLMrD/usZiZWaWcWMzMrFJDIrFIeo2kCyU9KekpSb+SNK7b9TIzWx71fGKRtBLwO+ANwMeB/YCNgGslvbKbdTMzWx4NhcH7g4ANgNdHxCwASbcBfwc+CXyvi3UzM1vu9HyPBZgM3FBLKgARMRv4X+BDXauVmdlyaigklk2AO0rKZwIbd7guZmYt6da5Ye1c71DYFTYGmFdSPhcYXTaDpIOBg/PL+ZLuanGdawCPtThPr1om2trBc2eWam83ztvp4HpLt+8QbvMy1XqX2moAAAoLSURBVN4OaOf/7/qNJgyFxAJQdvpcw49KRJwBnDHQlUmaERETBzp/L1me2gpu71Dn9nbGUNgVNo/UaykaTXlPxszM2mgoJJaZpHGWoo2Bv3a4LmZmy72hkFimAVtJ2qBWIGk88M48rR0GvButBy1PbQW3d6hzeztA0eNX98snQd4KLACOIo23fAtYBXhTRMzvYvXMzJY7Pd9jiYhngB2Au4FzgfOA2cAOTipmZp3X8z0WMzNbtvR8j6U/g7lApaRRkk6S9LCkBZKul7RNSdwKko6QdK+khZJulbRrg2UeJOlOSc9JukvSpwbbxsLy29peSa+TdKqk2yTNz7HTJG1WsrzpkqLk8fleaW+Ou7dBO3YpiW3b9u3Att2/QTtrj7XrYpf1bXu8pCslPZ7rtX8fsU1tM0m7SPpL/h+/T9JRkoYNsHlly29reyWtI+kESTPyOuZIuqbBZ/6cBtv3lKYaExFD9gGsRLpm2B3ALqRLvNwO/AN4ZRPznwc8Qboe2buBX5HGcjYvxB0HPAd8Edge+BHwIvDBQtxBufy4HHdsfn1Ir7QX+CxwG/CF3IYPA9cDC4G3FJY3nTT+tVXhsXavtDfH3Qv8tqQdozu1fTu0bceWtPHtpBPs/txj2/Zp4A/AT0njrvs3iGtqmwGTgBdIg+HbA4fnz/x3eqW9wE7APcDXgPcCOwKX5fbuVIg9B3i0ZPuu31R7qnhTltUH8Ln8YdiwrmwCsBg4vJ95N8sb6IC6suHAXcC0urI1SUnlG4X5rwFuK8z7KPDTQtxP8j/uiB5p7xrkXah1Za8inTP0s0L5dOCPvbx9c/m9wJR+ltfW7duptpbM+64872d6Zdvm2BXy84Y0/qJtepsBfwF+X4g7GlhEBcm0Q+1dDRhe8h7cBVxXKD8HeGCg7Rnqu8IGc4HKycDzwPl18y4GpgKTJK2YiycBI4EphfmnAJtKmpBfv530i7AYdy6wOrB1k23qr85tbW9EPBb5k1cX9yTp4In1KmhDKzqxfZvV7u3brbZ+nPTlOXWA9R6oQV1cNiJebGIdTW0zSa8BNm8QNwL4QBPr6k/b2xsRT+TtXl+2GLiFiv93h3piGcwFKjcBZkfEsyXzjiT9MqjFPQfMKomjbj21kziL9SnGDUYn2rsUSWOAfwP+VjL5zXl/7vN5XObf+6lHKzrZ3p0lPZv3w99QMr7S7u3b8W0r6RXA7sD/RMTjJSHL6rZtZR2UrKep/938xf9sRfXpysV0JY0kJdiy/901JT0mabGkuyV9pdkxpaFyrbBGWr5AZZPz1qbXnp8o/opvEEfJMotxg9GJ9pb5b9K12YoDe9eR9u3fTeqGfww4U9I6EXFsP/VpRqfaeylwI+kw9rVI40wXS9ovIqYU4tu1fbuxbXcBViXtty9alrdtK+ugZD3N/u/Wyrr9vzsYxwCvBvYplN8C3ERKbKNIY6knkG6i+In+FjrUEwu0eIHKQkwz87YS16g+VWp3e5ecKB0B7A38e303HiAiji6EXyLpYuBISadENecZtb29EXHoEgGpDTeQ/tGmFOZr5/bt6LYl7QabA1y+VEWW7W3brGa3WV9xVdan3ctfcsHS3sBXgW9FxB+WqEhE8Ufi5ZLmA5+X9J2I+Htfyx7qu8IGc4HKuX3MW5teex4tLXXh7bI4SpY5pjB9MDrR3pfkwzKPB46KiJ80WcdfkH4BbdpkfF862t6aiHgB+CXwaknrFOLbtX07vW3XAd4DnFfcL9+HZWXbNqvZbdZXz241uv+/2zJJO5MG6M+KiK83Odsv8nO/V0se6ollMBeonAlMkLRSybyLeHlMZSawIvDakjjq1lPbb1usTzFuMDrRXgAk7Qf8APiviDiuhTpW+cu+Y+0tUWxHu7dvp9u6LzCM8t1gjSwr27aVdVCynqb+d5WuSbhSRfXp2MV0Jb2b9MPoYtLt25ueNT/3v30He5jcsvwAPk86XG+DurLxpCNkvtDPvJvnN/DjdWXDSYNcl9aV1Q43/nph/quB2+tejyDtVji7EHcm8Dgwshfam8s/nNdzxgDqeAlpwLPfY/OXlfaWzDscmAHc16nt2+m2ks6huLUXt21hOX0dftv0NiONOVxbiDuK6g43bnt78/S3A/NJ56+0dAg8cCrpnJfX9hs72DdkWX4AryT9GruddMjeZNJJXfcAK9fFrZ836tGF+aeSuqGfIJ1UdiHppKgtCnHfzuWHA9sBp+cNsHMh7lO5/Ngc9838+jO90l5gm1x2M/AOljx56s11ce/KH95/z8v6SP7iCeArPdTevXLcx0gnxu1JOhEtgD07tX079VnOsVvk9pWeP9Ej23ZbYDfSgRYBnJZf7zaQbQZ8MJf/KMf9R37/TuqV9gJvIO22uze3YYmTHwvruA74NPA+YGfSuT0vAqc31Z4q3pRl+QGMAy4CniKdnfprYHwhZnzeGMcUyl8BfA94JH+I/g/YrmQdw0i/Xu4j9V5uK36A62I/STqS5jnSmbaf7qX2ko4iiQaPe+viNgR+AzyY2zof+BOwV4+1dyvgd8C/SL8enyT1Rid1evt24rOcY0/NbV2rwfRe2LbTG31OB7rNSAn01hx3P+kEyWG90l5g/0Yxhbgxed335c/KAtIPyc+ST8Ts7+GLUJqZWaWG+uC9mZl1mBOLmZlVyonFzMwq5cRiZmaVcmIxM7NKObGYmVmlnFjMlhH5drAPdLseZoPlxGJmZpVyYjEzs0o5sZi1maQNJZ0rabakBZLukXS6pNIbOEl6h6QbJS2UdK+kQ+umvU1S5MueF+c7XdIcSSPa2R6z/jixmLXfusADpCvYTiJd6PDdlNxAi3THxvNJl6vfhXQNqO9L2h8gIv4M3AXsVz9TvsXsHsDUiHi+HY0wa5avFWbWYZKGky5u+QfS1YX/ksvPId21ca+ImFoXfxXwOtIFCUPSkaSLnq4dEU/mmF1I99fYMicfs65xj8WszSSNlPSfku6UtIB05eDarWBfXwh/gXSF23pTSVe+XS+/nkK6udzudTH7AXc5qdiywInFrP1OIN1uYAqwI/A20iXYId3Kt968kl1Z/8rP6wFExH2k+2XsByBptbzcc6uuuNlADO92BcyWA3sCP4uIY2sFklZuEDta0ohCclkrPz9YV3Yu8GNJ65PGbUYC51VYZ7MBc4/FrP1WIu3+qndAg9hhwK6Fsj1JN5aqTyy/JN2EaR9Sz+W6iLh30DU1q4B7LGbt91vg45JuJ91+9iOk2zqXeRo4UdIapLsZ7gW8h3QP85eOtImIpyRNAz4DrAMc1Mb6m7XEicWs/Q4FBByXX19OShhlA+1PkXoopwKbksZXPhcRPy2JPRf4KKnncmHFdTYbMB9ubGZmlfIYi5mZVcqJxczMKuXEYmZmlXJiMTOzSjmxmJlZpZxYzMysUk4sZmZWKScWMzOr1P8HA++jFTzPzO4AAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.figure(figsize=(6,4))\n",
-    "plt.hist(abv, bins=10, color='b', histtype='bar', edgecolor='w') \n",
-    "plt.title('Alcohol by Volume (abv) \\n')\n",
-    "plt.xlabel('abv')\n",
-    "plt.ylabel('Frequency');"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "You can tell that the most frequent values of `abv` fall in the bin just above 0.05 (5% alcohol), and the bin below. The mean value of our data is 0.06, which happens to be within the top-frequency bin, but data is not always so neat (sometimes, extreme values weigh heavily on the mean). Note also that we have a _right skewed_ distribution, with higher-frequency bins occuring in the lower end of the range than in the higher end.\n",
-    "\n",
-    "If you played around with the bin sizes in the previous lesson, you might have noticed that with a lot of bins, it becomes harder to visually pick out the patterns in the data. But if you use too few bins, the plot is also unhelpful. What number of bins is just right? Well, it depends on your data, so you'll just have to experiment and use your best judgement."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's learn a new trick. It turns out that `pandas` has built-in methods to make histograms directly from columns of a dataframe! (It uses Matplotlib internally for that.) The syntax is short and sweet:\n",
-    "\n",
-    "```\n",
-    "dataframe.hist(column='label')\n",
-    "```\n",
-    "\n",
-    "And `pandas` plots a pretty nice histogram without help. You can add optional parameters to set these to your liking; see the [documentation](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.hist.html). Check it out, and compare with our previous plot."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "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": [
-    "beers.hist(column='abv', edgecolor='white')\n",
-    "plt.title('Alcohol by Volume (abv) \\n');"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Which one do you like better? Well, the `pandas` histogram took fewer lines of code to create.  And it doesn't look bad at all. But we do have more fine-grained control with Matplotlib. Which method you choose in a real situation will just depend on the situation and your preference."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Exploring quantitative data (continued)\n",
-    "\n",
-    "In the [previous lesson](./01_Cheers_Stats_Beers.ipynb), you learned how to compute the mean of the data using `np.mean()`. How easy is that? But then we wrote our own custom functions to compute variance or standard deviation. There are some standard numpy libraries that we can use instead. \n",
-    "\n",
-    "\n",
-    "##### Exercise:\n",
-    "\n",
-    "* Go to the documentation of [`np.var()`](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.var.html) and analyze if this function is computing the _sample variance_. \n",
-    "__Hint__: Check what it says about the \"data degrees of freedom.\"\n",
-    "\n",
-    "If you did the reading, you might have noticed that, by default, the argument `ddof` in `np.var()` is set to zero. If we use the default option, then we are not really calculating the sample variance. Recall from the previous lesson that the **sample variance** is:\n",
-    "\n",
-    "$$\n",
-    "\\begin{equation*}     \n",
-    "     \\text{var}_{sample} = \\frac{1}{N-1}\\sum_{i} (x_i - \\bar{x})^2\n",
-    "\\end{equation*}\n",
-    "$$\n",
-    "\n",
-    "Therefore, we need to be explicit about the division by $N-1$ when calling `np.var()`. How do we do that? We explicitly set `ddof` to `1`.  \n",
-    "\n",
-    "For example, to compute the sample variance for our `abv` variable, we do:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.00018337855205347506\n"
-     ]
-    }
-   ],
-   "source": [
-    "var_abv = np.var(abv, ddof=1)\n",
-    "print(var_abv)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now we can compute the standard deviation by taking the square root of `var_abv`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.013541733716680264\n"
-     ]
-    }
-   ],
-   "source": [
-    "std_abv = np.sqrt(var_abv)\n",
-    "print(std_abv)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "You might be wondering if there is a built-in function for the standard deviation in NumPy. Go on and search online and try to find something.\n",
-    "\n",
-    "**Spoiler alert!**\n",
-    "You will. \n",
-    "\n",
-    "##### Exercise:\n",
-    "\n",
-    "1. Read the documentation about the NumPy standard deviation function, compute the standard deviation for `abv` using this function, and check that you obtained the same value than if you take the square root of the variance computed with NumPy.\n",
-    "\n",
-    "2. Compute the variance and standard deviation for the variable `ibu`."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Median value\n",
-    "\n",
-    "So far, we've learned to characterize quantitative data using the mean, variance and standard deviation.\n",
-    "\n",
-    "If you watched Prof. Sainani's lecture [Describing Quantitative Data: Where is the center?](https://youtu.be/tQ5slNYRcC4) (recommended in our previous lesson), you'll recall that she also introduced the **median**: the middle value in the data, the value that separates your data set in half. (If there's an even number of data values, you take the average between the two middle values.)\n",
-    "\n",
-    "As you may anticipate, NumPy has a built-in function that computes the median, helpfully named [`numpy.median()`](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.median.html). \n",
-    "\n",
-    "##### Exercise:\n",
-    "\n",
-    "Using NumPy, compute the median for our variables `abv` and `ibu`. Compare the median with the mean, and look at the histogram to locate where the values fall on the x-axis."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Box plots\n",
-    "\n",
-    "Another handy way to visualize the distribution of quantitative data is using **box plots**. By \"distribution\" of the data, we mean some idea of the dataset's \"shape\": where is the center, what is the range, what is the variation in the data. \n",
-    "Histograms are the most popular type of plots in exploratory data analysis. But check out box plots: they are easy to make with `pyplot`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "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": [
-    "plt.boxplot(abv, labels=['Alcohol by volume']);"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "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": [
-    "plt.boxplot(ibu, labels=['International bitterness unit']);"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "What is going on here? Obviously, there is a _box_: it represents 50% of the data in the middle of the data range, with the line across it (here, in orange) indicating the _median_. \n",
-    "\n",
-    "The bottom of the box is at the 25th _percentile_, while the top of the box is at the 75th percentile. In other words, the bottom 25% of the data falls below the box, and the top 25% of the data falls above the box. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "_Confused by percentiles?_\n",
-    "The Nth percentile is the value below which N% of the observations fall. \n",
-    "\n",
-    "Recall the bell curve from our previous lesson: we said that 95% of the data falls at a distance $\\pm 2 \\sigma$ from the mean. This implies that 5% of the data (the rest) falls in the (symmetrical) tails, which in turn implies that the 2.5 percentile is at $-2\\sigma$ from the mean, and the 97.5 percentile is at $+2\\sigma$ from the mean.\n",
-    "\n",
-    "The percentiles 25, 50, and 75 are also named _quartiles_, since they divide the data into quarters. They are named first (Q1), second (Q2 or median) and third quartile (Q3), respectively. \n",
-    "\n",
-    "Fortunately, NumPy has a function to compute percentiles and we can do it in just one line. Let's use [`np.percentile()`](https://docs.scipy.org/doc/numpy-dev/reference/generated/np.percentile.html) to compute the `abv` and `ibu`  quartiles. \n",
-    "\n",
-    "** abv quartiles **"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The first quartile for abv is 0.05\n",
-      "The second quartile for abv is 0.056\n",
-      "The third quartile for abv is 0.067\n"
-     ]
-    }
-   ],
-   "source": [
-    "Q1_abv = np.percentile(abv, q=25)\n",
-    "Q2_abv = np.percentile(abv, q=50)\n",
-    "Q3_abv = np.percentile(abv, q=75)\n",
-    "\n",
-    "print('The first quartile for abv is {}'.format(Q1_abv))\n",
-    "print('The second quartile for abv is {}'.format(Q2_abv))\n",
-    "print('The third quartile for abv is {}'.format(Q3_abv))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "** ibu quartiles **\n",
-    "\n",
-    "You can also pass a list of percentiles to `np.percentile()` and calculate several of them in one go. For example, to compute the quartiles of `ibu`, we do:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The first quartile for ibu is 21.0\n",
-      "The second quartile for ibu is 35.0\n",
-      "The third quartile for ibu is 64.0\n"
-     ]
-    }
-   ],
-   "source": [
-    "quartiles_ibu = np.percentile(ibu, q=[25, 50, 75])\n",
-    "\n",
-    "print('The first quartile for ibu is {}'.format(quartiles_ibu[0]))\n",
-    "print('The second quartile for ibu is {}'.format(quartiles_ibu[1]))\n",
-    "print('The third quartile for ibu is {}'.format(quartiles_ibu[2]))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "OK, back to box plots. The height of the box—between the 25th and 75th percentile—is called the _interquartile range_ (IQR). Outside the box, you have two vertical lines—the so-called \"whiskers\" of the box plot—which used to be called \"box and whiskers plot\" [3]. \n",
-    "\n",
-    "The whiskers extend to the upper and lower extremes (short horizontal lines). The extremes follow the following rules: \n",
-    "\n",
-    "* Top whisker: lower value between the **maximum** and `Q3 + 1.5 x IQR`. \n",
-    "* Bottom whisker: higher value between the **minimum** and `Q1 - 1.5 x IQR`\n",
-    "\n",
-    "Any data values beyond the upper and lower extremes are shown with a marker (here, small circles) and are an indication of outliers in the data.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "##### Exercise:\n",
-    "\n",
-    "Calculate the end-points of the top and bottom whiskers for both the `abv` and `ibu` variables, and compare the results with the whisker end-points you see in the plot. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "##### A bit of history:\n",
-    "\n",
-    "\"Box-and-whiskers\" plots were invented by John Tukey over 45 years ago. Tukey was a famous mathematician/statistician who is credited with coining the words _software_ and _bit_ [4]. He was active in the efforts to break the _Enigma_ code during WWII, and worked at Bell Labs in the first surface-to-air guided missile (\"Nike\"). A classic 1947 work on early design of the electonic computer acknowledged Tukey: he designed the electronic circuit for computing addition. Tukey was also a long-time advisor for the US Census Bureau, and a consultant for the Educational Testing Service (ETS), among many other contributions [5].\n",
-    "\n",
-    "##### Note:\n",
-    "\n",
-    "Box plots are also drawn horizontally. Often, several box plots are drawn side-by-side with the purpose of comparing distributions."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Visualizing categorical data\n",
-    "\n",
-    "The typical method of visualizing categorical data is using **bar plots**. These show visually the frequency of appearance of items in each category, or the proportion of data in each category. Suppose we wanted to know how many beers of the same style are in our data set. Remember: the _style_ of the beer is an example of _categorical data_. Let's extract the column with the style information from the `beers` dataframe, assign it to a variable named `style_series`, check the type of this variable, and view the first 10 elements."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "style_series = beers['style']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "pandas.core.series.Series"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type(style_series)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['American Pale Lager', 'American Pale Ale (APA)', 'American IPA',\n",
-       "       'American Double / Imperial IPA', 'Oatmeal Stout',\n",
-       "       'American Porter', 'Saison / Farmhouse Ale', 'Belgian IPA',\n",
-       "       'Cider', 'Baltic Porter', 'Tripel', 'American Barleywine',\n",
-       "       'Winter Warmer', 'American Stout', 'Fruit / Vegetable Beer',\n",
-       "       'English Strong Ale', 'American Black Ale', 'Belgian Dark Ale',\n",
-       "       'American Blonde Ale', 'American Amber / Red Ale',\n",
-       "       'Berliner Weissbier', 'American Brown Ale',\n",
-       "       'American Pale Wheat Ale', 'Belgian Strong Dark Ale', 'Kölsch',\n",
-       "       'English Pale Ale', 'American Amber / Red Lager',\n",
-       "       'English Barleywine', 'Milk / Sweet Stout', 'German Pilsener',\n",
-       "       'Pumpkin Ale', 'Belgian Pale Ale', 'American Pilsner',\n",
-       "       'American Wild Ale', 'English Brown Ale', 'Altbier',\n",
-       "       'California Common / Steam Beer', 'Gose', 'Cream Ale',\n",
-       "       'Vienna Lager', 'Witbier', 'American Double / Imperial Stout',\n",
-       "       'Munich Helles Lager', 'Schwarzbier', 'Märzen / Oktoberfest',\n",
-       "       'Extra Special / Strong Bitter (ESB)', 'Rye Beer',\n",
-       "       'Euro Dark Lager', 'Hefeweizen', 'Foreign / Export Stout', 'Other',\n",
-       "       'English India Pale Ale (IPA)', 'Czech Pilsener',\n",
-       "       'American Strong Ale', 'Mead', 'Euro Pale Lager',\n",
-       "       'American White IPA', 'Dortmunder / Export Lager',\n",
-       "       'Irish Dry Stout', 'Scotch Ale / Wee Heavy', 'Munich Dunkel Lager',\n",
-       "       'Radler', 'Bock', 'English Dark Mild Ale', 'Irish Red Ale',\n",
-       "       'Rauchbier', 'Bière de Garde', 'Doppelbock', 'Dunkelweizen',\n",
-       "       'Belgian Strong Pale Ale', 'Dubbel', 'Quadrupel (Quad)',\n",
-       "       'Russian Imperial Stout', 'English Pale Mild Ale',\n",
-       "       'Maibock / Helles Bock', 'Herbed / Spiced Beer',\n",
-       "       'American Adjunct Lager', 'Scottish Ale', 'Smoked Beer',\n",
-       "       'Light Lager', 'Abbey Single Ale', 'Roggenbier', 'Kristalweizen',\n",
-       "       'American Dark Wheat Ale', 'English Stout', 'Old Ale',\n",
-       "       'American Double / Imperial Pilsner', 'Flanders Red Ale',\n",
-       "       'Keller Bier / Zwickel Bier', 'American India Pale Lager',\n",
-       "       'Shandy', 'Wheat Ale', 'American Malt Liquor', 'English Bitter',\n",
-       "       'Chile Beer', 'Grisette', 'Flanders Oud Bruin', 'Braggot',\n",
-       "       'Low Alcohol Beer'], dtype=object)"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "style_series.unique()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Already in the first 10 elements we see that we have two beers of the style \"American IPA,\" two beers of the style \"American Pale Ale (APA),\" but only one beer of the style \"Oatmeal Stout.\" The question is: how many beers of each style are contained in the whole series? "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Luckily, `pandas` has a built-in function to answer that question: [`series.value_counts()`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.value_counts.html) (where `series` is the variable name of the `pandas` series you want the counts for). Let's try it on our `style_series`, and save the result in a new variable named `style_counts`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Herbed / Spiced Beer                  9\n",
-      "Schwarzbier                           9\n",
-      "American Double / Imperial Stout      9\n",
-      "Belgian Strong Pale Ale               7\n",
-      "American Dark Wheat Ale               7\n",
-      "Bière de Garde                        7\n",
-      "Doppelbock                            7\n",
-      "Bock                                  7\n",
-      "Belgian Strong Dark Ale               6\n",
-      "California Common / Steam Beer        6\n",
-      "American Wild Ale                     6\n",
-      "Baltic Porter                         6\n",
-      "Foreign / Export Stout                6\n",
-      "English Dark Mild Ale                 6\n",
-      "Dortmunder / Export Lager             6\n",
-      "Euro Dark Lager                       5\n",
-      "Mead                                  5\n",
-      "Irish Dry Stout                       5\n",
-      "Dubbel                                5\n",
-      "Maibock / Helles Bock                 5\n",
-      "English Strong Ale                    4\n",
-      "Quadrupel (Quad)                      4\n",
-      "Munich Dunkel Lager                   4\n",
-      "Dunkelweizen                          4\n",
-      "American India Pale Lager             3\n",
-      "Keller Bier / Zwickel Bier            3\n",
-      "English Barleywine                    3\n",
-      "Chile Beer                            3\n",
-      "English Bitter                        3\n",
-      "American Barleywine                   3\n",
-      "Radler                                3\n",
-      "English Pale Mild Ale                 3\n",
-      "Shandy                                3\n",
-      "Rauchbier                             2\n",
-      "Abbey Single Ale                      2\n",
-      "English Stout                         2\n",
-      "Euro Pale Lager                       2\n",
-      "Old Ale                               2\n",
-      "Roggenbier                            2\n",
-      "American Double / Imperial Pilsner    2\n",
-      "Grisette                              1\n",
-      "American Malt Liquor                  1\n",
-      "Low Alcohol Beer                      1\n",
-      "Braggot                               1\n",
-      "Flanders Red Ale                      1\n",
-      "Wheat Ale                             1\n",
-      "Flanders Oud Bruin                    1\n",
-      "Kristalweizen                         1\n",
-      "Smoked Beer                           1\n",
-      "Other                                 1\n",
-      "Name: style, dtype: int64\n"
-     ]
-    }
-   ],
-   "source": [
-    "style_counts = style_series.value_counts()\n",
-    "print(style_counts[-50:])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "pandas.core.series.Series"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type(style_counts)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "99"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "len(style_counts)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The `len()` function tells us that `style_counts` has 99 elements. That is, there are a total of 99 styles of beer in our data set. Wow, that's a lot!\n",
-    "\n",
-    "Notice that `value_counts()` returned the counts sorted in decreasing order: the most popular beer in our data set is \"American IPA\" with 424 entries in our data. The next-most popular beer is \"American Pale Ale (APA)\" with a lot fewer entries (245), and the counts decrease sharply after that. Naturally, we'd like to know how much more popular are the top-2 beers from the rest. Bar plot to the rescue! "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Below, we'll draw a horizontal bar plot directly with `pandas` (which uses Matplotlib internally) using the [`plot.barh()`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.plot.barh.html) method for series. We'll only show the first 20 beers, because otherwise we'll get a huge plot. This plot gives us a clear visualization of the popularity ranking of beer styles in the US!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "style_counts[0:20].plot.barh(figsize=(10,8), color='#008367', edgecolor='gray');"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Visualizing multiple data\n",
-    "\n",
-    "These visualizations are really addictive! We're now getting ambitious: what if we wanted to show more than one feature, together on the same plot? What if we wanted to get insights about the relationship between two features through a multi-variable plot? \n",
-    "\n",
-    "For example, we can explore the relationship between bitterness of beers and the alcohol-by-volume fraction."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Scatter plots\n",
-    "\n",
-    "Maybe we can do this: imagine a plot that has the alcohol-by-volume on the absissa, and the IBU value on the ordinate. For each beer, we can place a dot on this plot with its `abv` and `ibu` values as $(x, y)$ coordinates. This is called a **scatter plot**.\n",
-    "\n",
-    "We run into a bit of a problem, though. The way we handled the beer data above, we extracted the column for `abv` into a series, dropped the null entries, and saved the values into a NumPy array. We then repeated this process for the `ibu` column. Because a lot more `ibu` values are missing, we ended up with two arrays of different length: 2348 entries for the `abv` series, and 1405 entries for the `ibu` series. If we want to make a scatter plot with these two features, we'll need series (or arrays) of the same length.\n",
-    "\n",
-    "Let's instead clean the whole `beers` dataframe (which will completely remove any row that has a null entry), and _then_ extract the values of the two series into NumPy arrays."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "beers_clean = beers.dropna()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1405"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ibu = beers_clean['ibu'].values\n",
-    "len(ibu)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1405"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "abv = beers_clean['abv'].values\n",
-    "len(abv)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Notice that both arrays now have 1403 entries—not 1405 (the length of the clean `ibu` data), because two rows that had a non-null `ibu` value _did_ have a null `abv` value and were dropped."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "With the two arrays of the same length, we can now call the [`pyplot.scatter()`](https://matplotlib.org/devdocs/api/_as_gen/matplotlib.pyplot.scatter.html) function."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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P/3c0tO0i8/ItPCtm+7r5Fev/5f8a7ftyNV7Tyrrw36u/33K8po8RvL/HylKfguZ4I94Y3p/i1Y4fw2vrPRGvlrsfr50M8N7I/aQcVwM/MLPr8WrU8/C+YfwX8MfOuQkz+we8D74fmNkNeOGrN+F9a3lBTFluAt4KXGNmX8eLVHzXeePDf+qX7W1m9hR+ZzHn3Dp/37f7+3/NzDbjfaMZx8t7cAreB2ueTkZ5PIYXCbnHzDZxKE9B0DM5q13uQ3jfPteZl/DoHrw8BWfgdXB6b2T7m/A65X3VzG7Di97c4JxLq9VfhXcv34R3/zdxKE/BAHBOQvt8Ls65R/1nfwZwp9+GuhCv1/w38Pqi5LEW7xvwJ81LxnML3giNF+JVkJ7tn+9mM/t7vHvzY//ch+HlEZgHfMhNz0NRxF/j3av3+N+Kb8WrgJ6N9zfwrhzPNY97gHv9NusgT8FzgI865+L6gHwVr4K9ELjPOfe9Gs/7Zbxha3+B994aFwbfa2bvwfvbvtvMvoj3zf+NeL33/5OMSoHvM/65bjezL+H1g1iDV6laWmP5Mznn/svMPolXKd1qZt8AfoH3wb4M7z3t7XgV9zw24FVkLg39HvUBvEjXjXgjWA7iRcpOxHsN3Rna9iq8v/tXE99htogFkQ6mc/xjvwjvvfGvItt/HG9ek3cDrzSzb+ONOFuC9zfbhzca6QmqrJFDG/QzORTlBXgfUt/C+3DfjxcJ+CleB8MXJOy3Ei/By268D+9H/N9PCm1zGF4Slq3+cR/C+wM7jJghMnjfZP6Pf6xxpg93eiVeDXjEX+ci+z8b+CResp5RvG89D+B9u3ptZNvUITop92u7//NsvKFtu/1z/Teh4VGh7W+OltNfPg/vjfNhvM55O/DeNBbHbDvkX8MOvDcdB5yXo6wz8IaQ3uff/yfxPrBfFbPtadH7neP4s/A+AH7uH/8+4I/wmhaShp5tjznOkf5ze9B/Lf0PXnKnP4lsZ3hvanf7r9ER//XwWzHHvNQvw2l51/nX8wn/9fqMX47/AI7P+1xT7tWV/jmPBf4S729tDG/o79qMff/O3/dP8p4v4ThBTohRYChlu9P818mToef658CMvK8ZvC8DD/n3cSvesNGir4tj4rb3152X9HcArMYbvfG4f/5f4lU2/wyYU/Ce3eOf5xFihs3i5Ua4Cu/9cgQvAncv3nvqr0S2vTnpNZnxmskzJHG/X4bPEDMk099vpl+uu/DydDyDV2n6IrCintdWs36ChBoilWH+bIXOuWNaWxLpFmZ2K95wu+e46f1zRLqG+hSISFczs5fhNX9dpwqBdDv1KRCRrmRmb8frA3MeXlPaJ1taIJEKUKVARLrV+XgRgp/hzTdQ6aFiIs2gPgUiIiICqE+BiIiI+FQpEBEREUCVAhEREfGpUiAiIiKAKgUiIiLiU6VAREREAFUKRERExKdKgYiIiACqFIiIiIhPlQIREREBVCkQERERnyoFIiIiAqhSICIiIj5VCkRERARQpUBERER8qhSIiIgIoEqBiIiI+FQpEBEREUCVAhEREfGpUiAiIiKAKgUiIiLiU6VAREREAFUKRERExNfX6gK02pw5c9wxxxzT6mKIiIg0xd133/24c25u3LqurxQcc8wx3HXXXa0uhoiISFOY2c+T1qn5QERERABVCkRERMSnSoGIiIgAqhSIiIiIT5UCERERAVQpEBEREV/TKwVm9lwz+6yZ3W5mT5uZM7NjMva5yN/uuzHrevz1281sv5nda2ZnNqr8IiIinaoVkYIlwFnAE8DmrI3N7PnAR4BdCZt8DLgU+BywGvge8CUze2MZhRUREekWrUhedKtzbj6Amf0B8LqM7f8e2AC8gEh5zWwe8AFgnXPu0/7im8xsCbAO+K8yCy4iItLJmh4pcM5N5N3WzN4OvBS4KGGT1wOHAVdHll8NvNjMFtdUSBERkS5U2Y6GZnYk8LfAh5xzexI2eyEwBmyNLL/P/3d5g4onIiLScSpbKQA+BTwIXJmyzWzgSeeciyzfE1ovIiIiOVRyQiQzOwU4F3hpzAf+lE2BuPWWcfzzgfMBFi1aVGsxRUREOkpVIwWXA58HfmFmR5jZEXgVmF7/935/uz3AkWYWrQQcGVo/jXPuCufcCufcirlzY2ePFBER6TpVrRQsA96DN2wx+DkJONH//3v97e4D+oFjI/sHfQnub3hJRUREOkQlmw+AV8cs+wzQC/whhzoWfh14BjgHuCy07TuAHzvntjWykCJSHZu2DLP+jj3sHBln/mAfa1fNZvXSoVYXS6SttKRSYGZv9f/7Mv/f1Wa2G9jtnLvFOXdzzD5PAn3hdc65XWb2t8BFZrYPuAc4G3gN8JYGXoKIVMimLcN84tbd7B/3uhjtGBnnE7fuBlDFQKSAVkUKvhT5fb3/7y3AaQWP9RFgBHg/sAD4KXCWc25jPQUUkfax/o49kxWCwP5xx/o79qhSIFJASyoFzrnU0QEJ+5yWsPwg8HH/R0S60M6R8ULLRSReVTsaiojkNn8w/vtN0nIRiadKgYi0vbWrZjOzb2oAcmafsXaV8peJFKFqtIi0vaDfgEYfiNRHlQIR6Qirlw6pEiBSJzUfiIiICKBIgUjLKNmOiFSNKgUiLaBkOyJSRWo+EGmBtGQ7IiKtokqBSAso2Y6IVJEqBSItoGQ7IlJFqhSItICS7YhIFelriUgLKNmOiFSRKgUiLaJkOyJSNWo+EBEREUCVAhEREfGpUiAiIiKAKgUiIiLiU6VAREREAFUKRERExKchiSIiNdJMl9JpVCkQEamBZrqUTqTmAxGRGmimS+lEqhSIiNRAM11KJ1KlQESkBprpUjqRKgUiIjXQTJfSiVSlFRGpgWa6lE6kSoGISI0006V0GjUfiIiICKBKgYiIiPhUKRARERFAlQIRERHxqaOhiEhOmutAOp0qBSIiOWiuA+kGaj4QEclBcx1IN1ClQEQkB811IN1AlQIRkRw014F0A1UKRERy0FwH0g1UxRURyUFzHUg3UKVARCQnzXUgnU7NByIiIgKoUiAiIiI+VQpEREQEUKVAREREfKoUiIiICKBKgYiIiPhUKRARERGgBZUCM3uumX3WzG43s6fNzJnZMZFtVpjZFWb2E3+bh81sg5ktjjlej5ldZGbbzWy/md1rZmc263pEREQ6RSsiBUuAs4AngM0J27wNeCHwd8Bq4ELgpcBdZnZ0ZNuPAZcCn/O3/R7wJTN7Y+klFxER6WCtyGh4q3NuPoCZ/QHwupht/to5tzu8wMxuA7YB7wYu9pfNAz4ArHPOfdrf9CYzWwKsA/6rMZcgIiLSeZpeKXDOTeTYZnfMsp+b2W7gOaHFrwcOA66ObH418M9mttg5t62e8opINazbvJPrH9jHhIMegzOWzeLCU+a3ulgNt2nLsOZbkKZpm46GZrYMmAc8EFr8QmAM2BrZ/D7/3+VNKJqINNi6zTu57n6vQgAw4eC6+/exbvPO1haswTZtGeYTt+5mx8g4DtgxMs4nbt3Npi3DrS6adKi2qBSYWR/wD8Bu4POhVbOBJ51zLrLLntB6EWlz1z+wr9DyTrH+jj3sH5/69rZ/3LH+jj0Je4jUpy0qBXidCF8JvMM590RouQHRCkGwPJGZnW9md5nZXbt3T2upEJGKmYj7K09Z3il2jowXWi5Sr8pXCszsk8D5wLucc9+MrN4DHGlm0UrAkaH10zjnrnDOrXDOrZg7d265BRaR0vUkVPOTlneK+YPx3b6SlovUq9KVAjP7CN5wxPc75/4tZpP7gH7g2MjyoC/B/Q0snog0yRnLZhVa3inWrprNzL6pNZ+ZfcbaVWoZlcaobHXTzP4I+DjwEefcZxM2+zrwDHAOcFlo+TuAH2vkgUhnCEYZVG30QaNHBgTH0ugDaZaWVArM7K3+f1/m/7vaH2642zl3i5m9DfgM3of+jWZ2Ymj3Yefc/QDOuV1m9rfARWa2D7gHOBt4DfCWZlyLiDTHhafMb3klICwYGRB0BAxGBgClVwxUCZBmaVWk4EuR39f7/94CnAa8Aa+z4Bv8n7Bgm8BHgBHg/cAC4KfAWc65jaWWWEQkJG1kgD7EpV21pFLgnEvtHuScOw84L+exDuI1M3y87oKJiOSkkQHSiSrd0VBEpKo0MkA6kSoFIiI10MgA6USq0oqI1EAjA6QTqVIgIlIjjQyQTqPmAxEREQEUKRDpOFWbardq5WlWmZp13VW8v9K+VCkQ6SDNSqjTruVpVpmadd1VvL/S3tR8INJBqjbVbtXKA80pU7Ouu4r3V9qbKgUiHaRqCXWqVp60c5dZpmZddxXvr7Q3VQpEOkjVEupUrTxp5y6zTM267ireX2lvqhSIdJAyE+ps2jLMmg3bWXX5VtZs2M6mLcMtLU9ZmlGmZl13Fe+vtDdVJ0U6SFkJdcrqwFbFBD/NKFOzrruK91famznnsrfqYCtWrHB33XVXq4shUilrNmxnR0y79ILBPjaec0zzCyQipTGzu51zK+LWqflARKZRBzaR7qRKgYhMow5sIt1JlQIRmUYd2ES6k6r9IjKNOrC1D6U5ljKpUiAisTQDYPUpzbGUTc0HIiJtSmmOpWyKFIh0sW4NPa/bvJPrH9jHhIMegzOWzeLCU+a3uliFaZSIlE2RApEuFYSed4yM4zgUeq4lc2E7Wbd5J9fd71UIACYcXHf/PtZt3tnagtVAo0SkbKoUiHSpbg09X//AvkLLq0yjRKRsqk6KdKluDT1PJCRxTVpeZRolImVTpUCkS80f7ItNZdzpoecei68A9Nj0Ze1Ao0SkTGo+EOlS3Rp6PmPZrELLRbpJZ38lEJFE3Rp6DkYZ5B190K0jNKQ7aZZEzZIoIgmiyYHAi6Z8+NS5qhhI29IsiSIiNejWERrSvVQpEBFJ0K0jNKR7qVIgIpJAyYGk26hSICKSoFtHaEj3UnVXRCRBt47QkO6lSoGISAolB5JuouYDERERARQpEJEEStoj0n1UKRCRaaJJe4JplQFVDEQ6mJoPRGQaJe0R6U6KFIhURJXC9Ura01xVevbS3VQpEKmAqoXru3Va5Vao2rOX7qbmA5EKqFq4Xkl7mqdqz166m6r9IhVQtXB9OybtqUIIPq0MSeuq9uylu6lSIFIBVQzXt1PSniqE4NPKACSuq+Kzl+6l5gORClC4vj5VCMGnlSFtnZ69VImqoiIV0I7h+iqpQgi+ljLsHBnXs5dKUaVApCLaKVxfNVUIwWeVIW2dnr1UhZoPRKTtVSEEn1aGKpRPJI+mRwrM7LnAnwMrgOOBAWCxc257ZLuZwMeAdwBHAD8E/tw5d2tkux7/eBcAC4CfAh91zl3X2CsRkaqoQgg+TxkaUb4qjLqQzmHOueytyjyh2WnANcDdQC/wOuIrBRuA04EPAj8D3gesBl7hnPthaLu/Aj4AfMQ/5tuAdwNvcs79V1Z5VqxY4e666666r0tEpNmiIx7Ai0B8+NS5qhhIIjO72zm3Im5dK5oPbnXOzXfOvRH4UtwGZnY88HbgT5xz/+ic+w5wFvAw8NHQdvPwKgTrnHOfds7d5Jy7ALgJWNfoCxERaaUqjLqQztL05gPn3ESOzd4MHMCLKAT7jZvZF4ELzazfOTcGvB44DLg6sv/VwD+b2WLn3LaSii4dpN1Drms3PsKdj45N/r5yYT/r1xw9bbus61y3eSfXP7CPCQc9Bmcsm8WFp8zPXNeK+5dWHph+T/oMDjpiy9eM8jfjHFUYdSGdpaqjD14IbHPOPR1Zfh9eJWCJ//8XAmPA1pjtAJYDqhTIFFVIdFOP6IcfwJ2PjrF24yNTKgZZ17lu806uu3/f5PYTjim/J607fsFA0+9fWlkvPGV+7D0JvkBHy9eM59+s15gZxLUAm01fJpJHVUcfzAaeiFm+J7Q++PdJN71jRHQ7kUntHnKNfvglLc+6zusf2Eec6x/Yl7quFfcvrTyQfE8C4fI1o/zNukcTCV3CkpaLZKlqpMCAuJd1tP6bd7upK83OB84HWLRoUS3lkzbWjiHXcCg6r6zrrOUDZcK15v6V8eEXlK/M8kebCE5aNMBtD4/G5iRIO0e7N2dJ56hqpGAP8d/yjwytD/490mxasCy63RTOuSucc2uvBDwAACAASURBVCuccyvmzp1bd2GlvSQltKlqrvkgFL1jZDy2Bpwk6zp7EqrOPZa+rhX3L608eQXlK6v80eeyY2Sc6+7fl1ghSDpH3HE+cetuNm0ZLlQekTJUtVJwH7DYzJ4VWb4ceIZDfQjuA/qBY2O2A7i/YSWUttVuiWTiQtFxVi7sn/J71nWesWxW7HHOWDYrdV0r7l9aeWD6tUeFy1dW+fM+l6xz1NPUMGcgvlaUtFwkS1UrBV8DZgC/HSwwsz7gbOCb/sgDgK/jVRLOiez/DuDHGnkgcVYvHeLDp85lwWAfBiwY7Kv0uO48Ye240QdZ13nhKfM5c/msyW/bPQZnLvd69Keta8X9SysPwPo1R0+rGPQZseUrq/xFmhvSzlFPc8amc4+lN7Ks118uUoumJy8CMLO3+v99LfAeYC2wG9jtnLvF3+aLeEMOP4g3guC9wJuAVzrn7gkdax3wx8CHgXvwKg4XAG9xzm3MKouSF0nVrdmwPTYkvWCwj43nHNP8AgmQ/Fyisp7Ta698iOGx6e/DQ/3Gd85L/3CPG3UByUNURSA9eVGrGlGjSYvW+//eApzm//+dwF8BH8dLc3wv8IZwhcD3EWAEeD+H0hyfladCINIO1q6aHZu1rqrNHd0i7rlE5XlOltBf2tL7SwP5R6KI5NWSSoFzLvPV7pwbBf7U/0nb7iBexeHj5ZROpFqqkNe/qG7oTR/3XILRB0Wue3gsPp9b0nKRRqpmd2sRmaKdptZt9+RQRZTxXKow7bNIoKodDUWkTbV7cqhmq2c0RNKoi6zRGCJJVCkQkVK1Y3KoVqpnNETcqAt1MpR6KD4lIqVSOLy4epohVAGQMilSICKlarfkUCJyiKruIm2uWT39856nUaMlumFEg0irqVIg0saa1dO/6HnKHi3RTSMaRFpJzQcibaxZPf1bPaKg1ecX6RaKFIhUUDR9bVKP8kb29A+H65Ny9jVrREE3j2hQs4k0kyIFIhUTl8/+zkfHWLvxkWnbNmoa47zTNTdrREG7TXddFk2rLM2mSoFIxRTJZ9+onv55pwXeMTLOy6/YyrrNOxO32bRlmDUbtrPq8q2s2bC9pg+0bh3RkKfZpIz7KxLo7Gq2SIdrVE//ImH5CQfX3b8PYHIq40BZHQTbcf6HMmQ1m6gDppRNlQKRNteIeRGSEhAtGOxj11PjTMQEEa5/YN+0SkHaN92iZW6n+R/KkpUIqsz7KwJqPhCpnCrks48L1/cZjB6YiK0QALHLu7mDYJq8If+sZhPdXymbKgUiFVOFfPbRfPxD/YYZ7E2ZzrcnZkL0bu0gmKZI58GseRGG+uPfwpOWi2Tp3r9MkQqrQj77cLh+zYbtDI+lf/s8Y9msacvWrpo9pc0buqODYJqiIf+0ZhOXMDYkablIFlUKRCRTWji6x7wKQbQ/AXRfB8E8OQXKDPnvG4v/8E9aLpJFlQIRyZTW8XDjOcek7tstHQTzjgQocxZJzUgpZVPDk4hk6tY8AUXkTcVc5r3Uc5GyqTop0uaiIeujh3q5+7ExJlx6aD9u30bMfFiFNL3rNu/k+gf2Td6T5x3ey8/3Hsx1j/LKk1MguA9D/T0c1uuF+eu5J6uXDnHvjtEp13b6cYNdEZmpVRVej1WmSoFIG4sLWYfDyWUmFqqlGaAKyXXWbd45eQ/Auyfbnjw45feke1REWig/eh/2jk0ws8+47DXz6roPm7YMc8ODI5PDQScc3PDgCMcvGNAHXYwqvB6rTs0HIm0sbzri6x/YN21ZM2YerMLshnHXXs92SdJC+Y26D1W4v+1E9yubKgUibSxvj/VWJRaqQnKdpGRLtW6XJC2nQKPuQxXubzvR/cqm5gORNpYUso5KSizU6J7rs/qN4ZjhcbP6YwrUID2W7wM/7h4VldTE0qh7rdEHxeh+ZVOkQKSNxYWs4yQlFmp0z3UjvmxJyxsh7trr2a4WjbrXGn1QjO5XNlWPRNpY3KiAvKMPskYUlNFLezghLXLS8jS1lie49jJGH9RahkYlceq25FD10v3KZs51d+arFStWuLvuuqvVxRCplGgvbfC+UYXz7uexZsP2mpMeNaI89ahCGUTKYGZ3O+dWxK1T84GITFNWL+2ywrVV6DVehTKINJqaD0RkmiKJeOYP9nHSogFue3h0Wki2rHBtFXqNV6EMIo2mSoGITFMkEc+OkfEpyYGiCWHKmPugCr3Gq1AGkUZT84GITFM0EU9U2WH1KvQar0IZRBpNVVwRmSYt7H/JjbtyHaPMsHrZOf6jcyHkGX2gnuvSDVQpEJFYSWH/pIREUWWG1cvM8R83F0LeuQ+6ZRpo6V5qPhCRQvIkHio7rF5mz/+kOQ7qnftApBMoUiDSRfKOGoDpIfaXHdXPI8MH2Zsj8dCL5x02eZyzrtk2ZVbCxUf0cu3ZiwuVu8ye/0kpj4Plq696iMdHD23U3wMHHA1NdFTkuURFyztnwNh07rGZ5ROJo+RFSl4kXSIu+U5UkIzn3h2jU0LstThz+SzuefTpKRWCQNGKwWuvfCi2yWKo3/jOecU+AFdevjVx3ZwBm/IBm+TM5ekVgyKJjoo8l+i+0QpB+DpUMZAkSl4kIoVGDZQRSr/+gX2xFQIgcXmSZs2hkKdCANlNDUWaO+oZzZFU3rzXIRKl5gORLpE31L5zZJwyPlLqnYo4rMw5FMqQdW1FmjuKPBeRRlOkQKRL5B0NMH+wr5RphMs4RiCp7LWMcEgqV5HyZm1bpLxFnotIo6lSINIl8kyzHIwaKGMa4TOWzWLxEb2x65KWJykzcVDStZ2xbBZzBvLVDLLuT5HyFnkuUUnlzXsdIlGqFIh0idVLh/jwqXNZMNiH4c1UeObyWVN+DzqzXXjKfM5cPmvyG3GPeR/kwe8GDPQyuV/0Q37xEb3c9vAo2588SG/k86mW0QdxZa91dsK4aws6Dm4699hpH6j9PcRuW1Z5izyXqLjyqpOh1EOjDzT6QCRTWm96oObe8yLSfGmjD9RIJSKZsnrT5+09r0qBSLWpUiDSBupJhFNrfv7wcZI+8ov0iG9l7/my7olIp1OlQKTi4qYqDk9NXOu2Rc6ZZP5gH08fONj0uRCKKOueiHQDdTQUqbh6E+HUMkdAnoQ6QY/4VsyFUESZ8yaIdLrKVgrM7CQz+6aZ7TKzYTO7x8zeFdlmppl9ysweM7NRM7vdzE5tVZlFGqGMRDh5QvebtgyzZsN2Vl2+lR0p20d7xKclEKp3pEAZypw3QaTTVbL5wMxeAnwb+B7wbuBp4K3A582s3zn39/6mnwdOBz4I/Ax4H/ANM3uFc+6HzS+5SPnmD/bFfkgnJcLJu21Y3uaCBYN9bDznmFznjNu2FWq9JyLdqKqRgrcBvcAa59xXnXPfcs5dAHwfOBfAzI4H3g78iXPuH51z3wHOAh4GPtqicouUrt5EOHlC90WaC8o6Z7NUvXwiVVLVqvJhwAFgNLL8SeBI//9v9re5JljpnBs3sy8CF/oRhbFmFFakkVYvHWLjT/Zy56OHXs7hqYmj2/7d7bvZH/piPDgju0NdnlC6m3CZ0yqXOeIhepy1Gx+Zcg9WLuxn/ZqjM/cN9m/26A3pbJ36Oqlk8iIzexFeVOBK4K/wmg9+G1gP/K5z7ov+h/+vOedeENn3LLyKwoucc/dlnUvJi6Tq1m3eGTuNcVxmvbOu2VbTVMVrNmxP7UcQGJwBr186K3d5ikhLkBStFAWCikGRqYprLUMnvOFLOdr9ddJ2Uyc7534MnAa8Bfgl8ATw/wHvcc590d9str88ak9ovUjbS5qmN255rVMV58m/DzByoFh5ikgbJRBXIQAmlzdy1IVGKkhUJ79OKtl8YGZLgeuA+4D34DUjvAX4BzPb75zbgNexOS7MkfnOZmbnA+cDLFq0qKxiizRE0jS9ZU5NHA2xpx26UeWpZ5RAWSMMNFJB8ujk10klIwXAJ/D6C7zJOfefzrnvOOf+CLgW+L9m1oMXEYiLBgR9DhKrbM65K5xzK5xzK+bOnVt22UVKVcZUv3msXjrExnOO4Y4LlrSkPPVMj1zW1MplTtEsnauTXydVrRS8GLjXOXcgsvwO4NnAPLwowmIze1Zkm+XAM8DWhpdSpAnSpvqNKmuq4sEZycuLlKeItFECKxf2x+4TLC9rhIFGKkgenfw6qWqlYAdwgpkdFln+cmA/XhTga8AMvA6IAJhZH3A28E2NPJBOkTbVb9S1Zy+Onca46FTFN71rybSKweAMb3mR8sQJJ0las2E7m7YMA+nTDa9fc/S0ikF49EFZUyuXOUWzdK5Ofp1UdfTBW4EvAd/EG3EwijcE8X3A3zrn/tTf7ovA6/GSF20D3gu8CXilc+6ePOfS6AOR5mn3XtsinaAdRx98GXgj0A/8E16nw5PxKgUfDG36TuBfgI8DNwBHA2/IWyEQkebq5F7bIp2gsr0inHObgE0Z24wCf+r/iAjVS6oSTToUp8q9tqt2P0UaqbKVAhEprmrTBOepEEB1e21X7X6KNFolmw9EpDZVC8/nqRBUudd21e6nSKNVs3ouIqmSQtrtlFTFoPLh+CreTzVnSCOpUiDSZtJC2u00TXBWkqQqqNr9VHOGNJqaD0TaTFpIu2pJVbKSDlVd1e6nmjOk0SqZp6CZlKdAWiUaBj56qJe7HxubnI74jGXxCYFWXb41dW6CwRnexEVRcVMcp50zOuPinAGjr7c3dm6EILFRnOhxakmm1Epp4froFNLh+1ckzJ9327Rn3w7NMVINaXkKqhdTFOkCcWHgcJh6wjE5PXG0YjCr3xgeS64WxFUIgmOGO/6lnfOeR5+eNrPi46MOiG9LHzkAr/7nrdMqBpu2DPPYyMSUZY+NTLBpy3DbfHCtXjoUW9bolNbh+3f8goHcYf4iTQJJzRngzQ6n5gSpl5oPRFogLgwcJ246YsueCLQu1z+wL3Oq5ThxlZFODnenTSFd5LqLbJtniutOub/SGooUiLRA3t7rcdMRD49NTF9YojKmZA7C4UnfapOuPy0cXzVpU0gXGbVQZNu8U1xXcbSJtIfMSIGZ9ST9NKOAIp0ob+/1uOmIG93zvd4pkINweFKFAOKvIQjHBx+2QTh+3ead9RWoQdKmkC4ytW7RaXjDU1wv6OApfKU18nywjwMH4n7MbNzMHjOzDWa2rIHlFOkoecLAED8dcd59a3XGslmFp1qGQ9MtZzWN9BmMHpiYNktiWji+itKmkC4yaqGeEQ5VGx0h7S9PdfKjkBil6gUWAquBNWb2CufcfWUVTqRTRcPARUYfRPftMzgQ+gudM2Ds2e8KNwOEz7lpyzAX37hr2jZD/ca+MZc6+iAtdD3Ub4wecOz1m0DCHePSwvFVFDybtOaOPCMK4l4LeUcQ1LOvSJxShiSa2QBwG7DVOXdW3QdsIg1JlG7x8iu2xn7A9hh8//ypowbWbNgeG/5fMNjHxnOOST1P2r5A4rpdT43nLp+I1K7hQxKdc6Nm9jfA35RxPJFOVE962lrHvM/sM0YzRjnEhcHrSe+7dtXsKUPsAml9DHaOjPNby2dNGeIXLV+7pfdtt/KKQLmjD34BHF7i8UQ6Rj3paYvsG902rkJgeO2BaU0U9aT3DYe00yoC0eOmhePbLb1vu5VXJFBmpWApsLvE44l0jLSx6FkfEkX2zZP/wAzuyAjHx33bL9KBLUj4k9SUEBY+7oWnzI+tpNRz/1qh3corEiilUmBmC4APA98o43ginaaecHwZY97DJpyXLrdRnd/ylidIy3vSogHW37GHS27clXieKs5WmKbdyisSyKwUmNlVKauD0QcnAo8Dl5RULpGOUk84vsi+Q/09kz370+RJiZuU3reIpLIHHRbzhtmrNlthlnYrr0ggT56CU4FTEn5WAYcB/wd4qXPuFw0qp0hba9ZY9OmDBdM1OiVuVtnzpvhtt/H47VZekYBmSdSQRClRtMf5SYsGuO3hUXaOjDOr3zCM4bGJaeuy8hSsvuohf0Iiz+AMGOzvmxbaz5pBMctAn7F/3CV+073zgiWx11mk7HMGjE3nHgskz/pnwB0XTO33kHacKtLoA6mqtCGJqhSoUiAliYbC48zsMz586lyAzG0Bzlw+K3bGwqTjxiUcKttHXzOv7rIH0yfnzYcQnX45ehwRya+UPAV+gqJe59yI/3s/cB7wErxRB1c657bXXVqRNpWn5384NJ53lsQ8Gf2aOTNekRkek8oefMDnHeWQVCmqZTZHEUmWp6Ph4cBVwBuBHjPbBJwLfB0I1zTeb2Yvd8492JCSilRc3p7lRXqgF0nx26ye7XlzD+Qpe6vS9Cq0LxIvT6TgL4HXAOuAfcD7gI3AEXgdDe8DjgeuBi4G3tGQkopUXFI7fNx2kO/DNUg0lEd0DoR2UcYohyKUWEgkWZ7RB78JXOyc+0vn3P8Gfhd4BfBR59xdzrlR59z3gE8AJzWwrCKVlmf2wiA0nnemw/5ecs9YeMDVP+1xmQb6LLHsRWdhTLqsWi4374gHkW6Up1JwNBDuiRf8P9pM8FPgOWUUSqQdrV46xIdPncuCwT4Mr7PcyoX9kx/UPQanHzc4+c04vG2SsYNw7dmLJ6clzpLWb3jBYN+04xSfIDm//eOOa89ePK0CMGfAGB23aVMn12vTlmHWbNieeVwlFhJJlqf5YAYwFvo9+H/0L2icxr7HiFReOBQehKmDtvUJBzc8OMLxCwYmtwu2TeqFP3+wj3WbdzJyIN/5s5IFhQXlO5ij02CStJkPg2aS8OiAydD96PjkfnlC90lJmYb6e6YeN0eTgBILiSTLEymA+GbNNmy9FGmeImHqtGQ31z8wfebAOCsX9hdKmpN3FEGStKaQIufME7pPSsoULC/rXot0u7xV441m9kxk2X+ZWfj7y2EllUmk5cronV4kTJ3WCz9P7oGVC/tZv+boyd/zlL3WcHkwZ0H0uPWcM6ss+8biKwXB8rLutUi3y1MpuApFBaSLlNU7vWiYOqkXfo/FD+/rMfh+zGyHeXvz5x0tERXNNFjGObNC91n7lXWvRbpdZvOBc+4859w78/40o9AijVRW7/SywtRnLJtVaHleeUdAhBXcPNc589yTrP3UJCBSjjzJi55f5IDOuZ/VXhyR1iurd3o9Yepo88XKhf2JcwvU2tSxeukQG3+ylzsfHcvcNnCwzphhrfdk9dIh7t0xOpklMTySo57jishUeZoPtlKs+UAjEKStldk7vZYwdVzzxZP7D3Lpq+dNO1Y9TR3rNu8sVCGAcnro13pPbnhwJHEkR63HFZGp8vyFq0lAukrefPyNktZ8Ef3QK7JtVN5RDYFWhuPruU4RyS+zUuCc+9dmFESkKoqEosvMoR8cK6nz346RcVZevhXwwnFzUzoKhreF+CmPs8J//T0QTg3w4nmHTV7b2o2PTIkyREc/xF1X3HTScb/H3cM8TTqaz0Ckfpo6WVMnS43ipkoOpjCut8mgEfJOeZzmzOWzePjJZ2KbHeIqBrVcV9w9/PUrfxabvOjw/h6+fd7zS30WIp0uberkvMmLRCSizBz69SYSatY5rn9gX2I/hLjltZwz7h6WmbxIRJKpUiBSozJz6Dcj734Z5ygylXM954zuV2byIhFJpkqBSI1mJoyzSVqepr+EMTtD/elJBMoYOVB0FsZazxndL+k44eRFZZ5fpFupUiBSo/0Hiy1PM1bDPlGWMZFwLcmKos5YNouVC/tj18Utr+WccaMclLxIpDlUKRCpUVIkvZZW+zJ6EwyPTUyOMoi684IlsVM796e8A8wZsCnTPp+53EuYtH7N0dMqAEmjD1YvHeL04wanHGflwv4pZThz+awpv8d1Dowre3i7rPUiko9iayI1SpuToKxjRbf5/vlLUqdZBhIrBlBegp+k4YdRcUmHfrTrmZo+sLPKruRFIvVTpECkRmXOSZBnn2CbdgqVa1SASHtRpEC6UhmJboK5B8L5+MNzEtRzLONQk0KPwcuO6ue2h0dZdflW5g/2cfpxg5MJf2b2GaPjjotv3MWlN+3iZUf188jwwVzXVuQ+1HLPNCpApL0oeZGSF3Wddkt0k1bee3eMct396emKk66tyH2o9Z4lNXUsGOxj4znHpJZbRBpDyYtEQtotpJ1W3jzzFyRdW5H7UOs9a6emDhFpg0qBmb3RzG41sxEzGzazu8zsNaH1R5rZP5nZ42b2lJl928xe3MoyS7W1W0g7qVw7RsZzJxOKO0bWfdi0ZZg1G7az6vKtiXMsZN0zjQoQaS+V7lNgZhcAn/N/PoZXiTkBeJa/3oCvAYuBPwSeAC4CbjKzE5xzv2hFuaXaZvUbwzEZ8mZlJP9plaTyFhGXxCdtiui8cxbkSQ6kUQEi7aOylQIzOwb4DPBB59xnQqu+Efr/m4GTgdc4527y97sd2AZ8CPijphRW2opN6cYXXV49SeXNKylcnzZFdJ45C9QMINJ5KlspAN4FTAD/kLLNm4FHgwoBgHNur5ltBN6CKgVtqdFT4A7HzLaXtjzNus07c48+WH3VQzw+mvxB2wvUm9iwx2D2TJtynvCUx9HyPu/wXn6+9+Dk76cfN8jqpUNccuOuzHPtD414iF53+BkO9ffgcOwbcw0Z4VC2ImUo8vwbpQplkM5R5T4FJwM/Ad5mZg+Z2biZbTWz94W2eSHw45h97wMWmdlgMwoq5QnC1jtGxnF47eafuHU3m7YMl3aOsvLkr9u8k+vu3zclMc919+9j3ead07bNqhBA/RUC8D4Qoue589Ex1m3eGVvebU8enPL7DQ+OsGnLcKG4RPS6o89w79gEw2Mu83k249lnKVKGIs+/UapQBuksVa4ULASWAp8C1gGvA74FfM7M3u9vMxuvH0FU0CX6yEYXUsrVjJEBZfWIT+r5H7c8q0JQhoE+Sy1TPSMV8giOn9X0UPYIhzIVKUOR598oVSiDdJYqNx/0ALOA85xz/+Evu9Hva3CRmf0dJDa2pjYOm9n5wPkAixYtKqu8UoJmjAwIQsH1hqmTev4XnV64LPvHXeI3/CJlqvVeB+fIs38toyGaoUgZqvD8q1AG6SxVrhT8D16k4FuR5d8E3gAchRcRiPt6F0QI4qIIOOeuAK4AL3lRGYWVcqT1iC9TGT3iy5z7oAzzB/vY9VT8MMWgTHk+LJKeQZbgHHn2LzoaolmKlKEKz78KZZDOUuXmg/sSlgcv9wl/mxfGbLMceNg5N9KIgknjtFOymyJzH8wZaOy7dHCP0sqUZ36F4DiDM4qXIW1uhrhzRFXh2RcpQ5lzX9SqCmWQzlLlSMH1wO8Drwe+HFr+euAXzrkdZvY14J1m9irn3C0AZjYErAG+0OwCS/3KCu03Q565D8I9w7MkjT6IGyWQNL9BcJ/SyhRel3ack/9xK+EBGQaY/800OjdD+BzRZ5h39EEVnn2RMpQ590WtqlAG6SyVnfvAT0z0HeB44CPAz4C3Au8G3umcu9LMeoDvAkcDH+RQ8qKXAMc75x7JOo/mPpBGCXqGJ2nX+RaqWF4Rya8t5z5wXm3lN4EvApcB/wmcCJzjnLvS32YCeBNev4P1eNGFg8Cr81QIRBopqwd4u863ICKdq8rNBzjnhoH3+T9J2+zBS3T0rmaVSySPPE0Gtfasb3TCmiqMBBCR5qtspECk3eXpAV5Lz/pmJKwpK8GTiLQXVQpEGiSrB3itPeubkbCmCiMBRKT5VO0XaZBoz3ADZvbC/oPU1bO+GQlrqjASQESaT5UCkQa68JT5pQ8Pa1bCGk15LNJ91Hwg0maUsEZEGkWRAmmKZkyJW+Qc9ZQnvO+sfsMwhscmYlPkGnDHBUtiz3n0UC93PzY2OYJghjElWdCcAWPTuccC00cbzBmYOj3yyoX9kxGJsu5DkXXRa1ECHZH2VNnkRc2i5EWN14xEOEXOUU954vbNYsBlr5lXeD/wPvxftXgwNQkSHCo/UMp9SDtO3Lo4Zy5XxUCkitKSF6lSoEpBw63ZsD12kpkFg31sPOeYpp+jnvIk7ZtlQY2TDEFyH4K4cwCl3Ie04ySti+ox+P75SzK3E5HmSqsUqPlAGq4ZiXCKnKOe8tRa5nquNe+ogrRzlHUfilxH2dP3NqMJSqTbqaOhNFwzEuEUOUc95am1zPVca95RBfMH+0q7D7WsiypzNETQ1LFjZByHF6n4xK272bRluLyTiIgqBVK7TVuGWbNhO6su38qaDdsT36CbkQinyDnqKU/WtMBxrMb9AkWmPC7rPhRdl1budZt38vIrtrLy8q28/IqtNWVe1FwMIs2h5gOpSbSTWvDNDZgW0m1GIpwi56inPNF9i4w+iJ4z3GM/Tdz0uElTHsedp577kHdd0uiD6EyRQUrm8HXlobkYRJpDHQ3V0bAmzeg82E1WXr41cd2dF7RvZ72XX7E1MdFSkU6Ier2JlEcdDaV03fTNrdax/HnWN8LajY9w56Njk7+vXNjP+jVHN/ScScpKybx21ezYIZK1NkF1aqfFTr0uaR5VCqQmcaHyYHknSWsmAVKbUIo0sRze38PecOai0PIiohUCgDsfHWPtxkdaUjEoKyVzmU1QRZ5LO+nU65LmUkdDqUm3zKKX1sEtq/Nbkc5xjvivzknLk0QrBFnLG63MlMyrlw6x8ZxjuOOCJWw855iaP+g6tdNip16XNFdnfa2TpumWWfTqGctfZN99Y/Ef/knLGyEaej5p0QC3PTxa1/O98JT5PPzkM9OaM1qZ6bDTmr6C55aUUKpdr0taQ5UCqVk3zKKX1UyStq5IE0urm2PiQs/hUQO1hqI3bRnmR7uembLsR7ueYdOW4Za9dlp9r8uUJ+12O16XtI6aD0RS1DqWP2vfIucpYuXC/kLLA3Gh56haQtFVDGl3UtNX1nNr1+uS1lEVUtpKdLbA8Gx8Zc6SGO2wN8Ng3DFt23t3jE4pz+AMuPjGXVx84y4AFh/Ry+i45coZ8He372Z/6Avs4IzkR8TRnAAAIABJREFUb+VJ5V+/5ujYst/16BhrNmxPPH/eEHOwXd6mhlaF6tOe7+qlQ9Oe2+nHDdbcabHWkSllSLuPCzq0SU8aS5UCaRtpiXCOXzCQu+d1Vi/tuB78B9z0oX2btgxzw4Mjk73rJxxTpjMG2PbkQVYu7M8cS3/WNdum7fv4qOOsa7Zx7dmLC5U/KGOR3uhJIfWo+YN9hZoaWhGqz7ruuOd2w4MjHL9goHDTSK0jU8qSdH+Vv0FqpeYDaRvXPxA/ffD1D+wrFKbO2jZvD/48Ife044Vte/Jg7uV5r7XIPcmTujgIRRdpamhFqL7MUSG1nqdZzSad1BQi1aBIgbSNtEQ4zZolMRyCLxoCLyucnLf8Ra4zbjRJUpPAJX7TSJ5ytmKUStZ1l9WkUeYsk7W+NrplFJA0jyoF0jbSEuHM+5Xm9PTPExqPU2ZimbzlL3qdeUeTFGlqKHLcsmRdd1lNGvWMTAmr97XRDaOApHnUfCBtIy0RTpk9/bMmAEwLjcdZubA/M5yc9IcYtzzvtTYqtFykqaEVyhwVUut5ipyjiiM0pHspUiBtI262wPDoA5g+c9+lN3kjAcLbZoVcD+bIF7RjZHxyhMFAn7F/3DF/sI+BPjelH0DQOXFVwoRHQTg56ZRxy/OGjBsVWi7S1NAKWddd1n2pd5bJQKclU5L2plkSNUtiR4qOVAicuXxWZja9pBn50mQdN2uWv9de+RDDMdkLh/qN75x3bKGySHvRDJDSbGmzJKr5QDpS2kiFLHmbBYocNyucbMSfL2m5dA6NIJAqUfOBtJW8vbTrmbI3HBbOGzEIjpuW1Geov4fDer35DIJ16+/YwyU37kpsPhiOmTkxS5GEOkcP9XL3Y2OJzTHSeBpBIFWiSoG0jSK9tI349vi837uDHt0rE/oCRPVY9vwBe8cmmNlnXPaaeQCZOeuheI/4ogl1wpWecDIoVQyaSyMIpCrUfCBto0gv7f7e+GMkLU+SNWdA4Ixlswol9cmzbS0h5KIJdeLkaWIRkc6kSIG0jaxe2uHQeNJH31h84sBEcXMJzBkw9ux300LuSSMMovI0SdSaj7+MnuxJTSEKaYt0PlUKpG2kJYvJM4VssG1R4fkO0gz197C3hj4AcWrNx19LQp2opKaQRuTuF5FqUfOBtI20XtqNCscX4RLjE7WpJYFN0YQ6cZKaQpRQR6TzKU+B8hSkakUIOXzOof4eHG6yx360t/zLjurnkeGDqd+ADabtG9XfA+Ev+YuP6J2cnTA6XfPzDu/l53sP5hrJkEdSp8hg3R0XLCn0HFZf9dCUGRfnDBibzj0281qiTSFpZZrVbxjG8NhEQ18XaVNli0ht0vIUqFKgSkGiuJD8zD7jw6fObVjFIG8zQF5BApikZEZpFh/Ry0sXPqvwfkUM9MKtf7CEX7/yZ7FND4f39/BnJ83J/RzOumZb7MyKi4/o5Z0vfXbu4ySVJ0kjXhf1JKASkWRKXiQ1aUUIOW8P+TzCzQW19Kjf9uTBhvfE3+9/fic1PThcoeeQNgVzkeMUbQppxOuingRUIlIbVQokUStyspd17AWDfZx+3CDr79jDqsu31hzqr3U/88uwcmE/PSnN+MHh98WkOA6Wl/UckppY4o6TVJ40Zb8u6klAJSK1UaVAEiX11K+lB3+95yxigd/GfcODI+xIGZ6YR9oHepo7LljC2lWz+dGuZ1I/xILDp93rRj+HpOmlyzhOPZLufa3PRESyqVIgiVqRk72WeQfCioxGyLL4iN7E6ZrT9Pt/VblGRPjJlMqahreoItNL13KceqRNlS0ijaE8BZKoFTnZa5l3AA6NMAjKd4k/rXGtwqMPHn7ymcTkRVH9PfDddy8B8oXTgz4Fq5cOce+O0Sk97cPJi6LrXjzvsMl5E2p5LtH7FZU1PXIzRh/kmSpblGRKyqVKgaRqRU724Jx5pzCOm2I2KYlPmh6D75+/ZMqyTVuG+dGuZ6YsGzkAl756XuZ9yVOGIO3ypi3D3PDgyGRFI5y8CJi2LlxJCScW6rHsNve464xThXz8F54yX5WAFEoyJWVT84FUVp4Qdlnhb4gPS9czAiNPGYK0y/XOWRBsmye0rvB751CSKSmbIgXSFEWm8w3WrV46xMaf7J3yrXjxEb2MjlvsceLmKHjmINMSHe0cGae/1/tAdsSHpcNJc+LsGBmfNoNi9Dhx5Y9ykDoTY5Ee/TtHxqeF3MOJkYqG3xWWrr5WjBCSzqZKgTRc0el8g3X37hid9oG67cmDsclrohUCYEpWvwkHP9r1TK4EO7UkOgrOEZ56eN3mnakVgjzmD/bx9IGDDOcYIhh0Wiwj5K6wdHvImutCpCg1H0jDFQ2NB+uKJK/J8+GbN6xab3KcYP96jxM0jRj5mkH2F5wBMo3C0u2hFSOEpLO1TaXAzL5uZs7MPh5ZfqSZ/ZOZPW5mT5nZt83sxa0qp0yXFMrcMTKemlCnEclr8oRV602OM+GoK2GS4aU3PqwXLrlxV+50w2Xm9FFYuj2sXjrEh0+dy4LBvsmEWY1MQy6dry1iTGb2O8DxMcsN+BqwGPhD4AngIuAmMzvBOfeLphZUYtUyEmD+YB+7noqvGNSTvCZPWDWpB3+env2BtM2yjnPZa+bVNP9DmUl9FJZuH1UYJSKdo/KRAjM7Avhb4E9jVr8ZOBn4Xefcvzvnvu4v6wE+1LxSSppaE+EUSV6zcmF/7uNmSTtvnvPkOf7iI3pj1y0+orfmxEtljipQWFqkO1V+lkQzuwI41jn3WjNzwF855/7CX/d54A3OuedE9vlX4DTn3POyjq9ZEsuTZ4RBnimOw/tFp84NjyDIGn2QNlLhxMu3Em2CD77B9xjMsKlTKYe3mT3TpnRirFV0uubBGfD0eL5oRDiBUqOS+qRNW1zmyARNjyzSXG07dbKZnQx8GzjeOffTmErB94C9zrnXR/b7EPDXwCzn3EjaOVQpKEfeaZaTEhLFJSCq9RxZ4ioERZ25fBb/cf++utvxVy7sZ/2ao2sa8dDIKYTT7jVQ2pTamh5ZpPnacupkM5sBXA582jn304TNZuP1I4gKukgf2YiyyXR5e6vXE5Yuq0d8GZ30r3+g/goBHBo1UctIhUZOIVzriJGiND2ySLVUudfQnwMDwF+lbBPOzRJdnryT2fnA+QCLFi2qtXwSktVbPRxuntVv9Pf2FM6bX6Ue8WVP31vL8Ro5hXAt97qW56DpkUWqpZKVAjNbBHwE+AOg38zCvbv6/c6H+/AiAnFfMYMIQVwUAefcFcAV4DUflFXubpbWWz0aih4ec8zs83rZFwk3V6lHfJGRCPUcLxhRUPYojCxZ97qs55B13SLSXFVtPng+MBO4Gu+DPfgB+ID//xcD9wEvjNl/OfBwVn8CKU9as0BZ4eayesTH9/sv5oxls3KmFEo3ww4dL+k8rZhCuFlTOWt6ZJFqqWSkAPgh8OqY5TfhVRQ+D2zFy1HwTjN7lXPuFgAzGwLWAF9oUlmF9GmWk6YxzhNujvZyP/24wcnpe7OaHpJ6tX/vgiWp8w2ANxJg5MD05eHjXHjKfFZdvnVa+9WCwb7J8g30ObY9mdyLIagrXXjK/GlTNK9c2D+ls10ze+jnmTa7jNEHmh5ZpFoqPfogKmb0QQ/wXeBo4IMcSl70ErwRC49kHVOjDxqv1hEH9Yw2SOvVDmT29K+1N32SX7/yZ7GZCQ/v7+Hb5z2/tJEVIiJZ2nL0QR7OuQngTcC3gPXA9Xidy1+dp0IgzVFruLmeZoe0Xu15eraXneffJYxVCJZrrgERqYKqNh/Ecs5Na8Z1zu0B3uX/SAWtXjrEv9zzP1PC6EcN9mR+A65ntEEZvdqTzhNu0pjZ601EFEzBHE16NGfA2HTusexLmOUwWF70WjWtsYg0QltHCqQ9rN34yLR29W1PHmTtxvRgTlJv9rzzFyQtz9uzPe48QZh/x8g4Dhg9eGhM7ISbngXx8VHH6qseyryWItcaLUMwrfGmLcP5LkxEJIEqBdJwSdMaZ013XE8v91p68+c5Ty3zEjw+6jKvpci1qqlBRBqlrZoPpLvE9YA/adEA6+/YwyU37koNm+fp1R5eF53P4MXzDps2b8NO/5t5LS6OGYERPsfqpUPcu2N0SplOP24w9tpalcRJTRbVpOciZWqr0QeNoNEHjZc2/O/OC5bkPk6jeuinjVQ4fsFATdMY5xXk+C9ybfXMH1ErjY6oJj0XqUXHjj6Q9pA03XDRaYgbFTZPG6lQ6zTGRc9d5NpaMa2xmiyqSc9FyqbmA2m49WuOnjatcTA7IEyf8ji8LiwpPL5jZJxVl29lVr9h2OScCtHEQdGpirNMuPh0vmUKRkNkNQlEEzHNnmnsD+0SboooayriPM0mtSSgqjW8vfqqh6Y08QQjO+o9ZzuH36s0H4h0BlUKpCniPuRheoUAvA6Iazc+Mm2ffn/4XxyHN6dCMBYg7sO8SIWg2Yb6e2KTGw3190xr3phwTPlwBO+erdu8E2DatsHvRSoGcWHpOFkjQaLHCUZKAIU+eKMVAjg0siNaMShyzrLK1ypVmg9EOoOaD6SlioxMGCtjzuOKSktulHca4bTETEWnIs7TbNLoBFRh0QpB2vIi52z38HsrmpKks6k6KTUrEnYtI6TdyV1i05Ib5b3utMRMeZI25R1lYZA7zN6KpEx5zhmcJ6l5qF3C73nmqBApQpUCqUmRsGtc+Dtr7oE4ZU9XXCVJTSP9vfDMRL7rrmea5bzNBUVHOBQJb6e9porIOmeea22n8PvqpUOqBEhp1HwgNSkSdk0LaRcZmdCJ0+nOGfA+rZOaRsYO5r/uPNMsb9oyzJoN21l1+VbWbNg+mQWxaHNB0nGi1q6aTSS6TZ9ROClTcJ+i4pZnhdSzrlXhd+lmqhRITYqEhdPmIVi/5uhpFYCk0QcXnjKfM5fPmvzW22PetgsG+zBgqN84vL8Hw/tGu/iI3in792e82oPjlK3PiD1uuPd80keUA45fMJD6h9pjh/IdpElLj5wWLg/uZzD2vWiaZbP03wNpr6lN5x47rQKQNPpg9dIhPnzq3MnnGS572nmI2Vak27RPjEwqpUhYOCnsH3y4J41MiHPhKfNrGl5XRFqypVqaMMZddpKmtHu0/o49xA2ciAvlp0Vlbnt4NPGbeNLzjDtH2jf66Ifp+jv2cCBS+AMTxG6bGfZPGH4YJy2kXuRaRbqNKgVSk7WrZsdmUosLu56xbFZsH4JamgPK6twYXfe8w3v5+d6DmR/4jerTkHaP/iOh/0XRqEzaN/HLXjNv2vOc0QNPHzjIqsu3TrnXRaJERbYt8pqqR7POI9KOVCmQmhTp9Xz8ggGuv3/flG+7Pf7yIsrs3BhdF53FsdnS5mq47eHR3FEZI74pIhgxkHSc6PMc6u/hqWcm/NwPU+91kShRkW2b1ZNePfZFkmnuA8190HBl5eovcpyXX7E1tcmimaMY+gxuPz//HA9RRfLbn/pPWxmNqd8M9MJFr5oeDahlfoWkb9pxx1FufpHqSZv7QJECabiyUrGW1bmx2cYd00LwccJNI9GUzacfN8htD49mfrNNyvi4/2Cxb8hp97rIcYrM/pilndMRi7QLVQqk4cpKxVpm58ZmVw7CvfQhO91uNGXzDQ+O5Pp2nXWP8o5pL+s4m7YMc8ODI5P3e8LBDQ+OcPyCgUIf6O2ejlikXWhIojRcWalYixwnbbx+K/MdFEm3m2e/qFbc6zRlpRFu93TEIu1CkQJpuKxwc96wcFwo+qjBHi69aRcX37hrSue8C0+Zz8NPPjNlDgWjtkyKZSvSSz9pm6SRFdF7BN6H58U37uLSm3blTi9dVme8IimH085T1dkAz7pm25ROqouP6OXasxe3sEQi9VGlQJoiKdxcdEa7aCg6/IYcHmFw/IIBfrTrmSn7V6VL7VBMFqU8ZQv2SxtZcfyCgSn3KKzojIllpM+d2WeMxkRAgihE3udfxdkAoxUC8F6PZ12zTRUDaVtqPpCWqndGuzjXP7Av97atkH+Ko/j90hIU5bnuojMm1iOuQhBenvf5V3E2wKRhrK0e3ipSD0UKpCmSQsRlJMKJSkvUUwVJMyLm3a+WBEXR7aoi7/NvZm4BjXKQbqZKgTRcWoi4jEQ4UT0G834l37ZRd16wJDXNcRlm9dc2w0JwT9JGVuS57qwZE8uUlkwJiic3avSHs0Y5SLdT84E0XFqIuEhYOG7bOGcsm5V72ziN/sy0mDNknTN8T9JGVuS57maOvujvTV9etWaBIs1Z0Qm3spaLtANFCqTh6kmEEw3lHjXYM6XNds6AsWe/Y8Id+lZ63f37uP6BfbnnM4jK2jzp229ee8cmWLNhe+6w9ILIPUlLiRwI7ll/rzf9siN+u0aHytOmhIbqpRwu0px17dmLNfpAOo4qBdJwtSbCiQvlRj0+6jhzuffNt6z5DLI+9Pv9NL0bf7J3ypDHIqJh6aIz96XNFlkksVCjQ+V5mgea0SyQV9FRDqoASKdR84E0XK0h4iKjDcrsUZ8U8g4E4eRaKwTR40BrwujNSAhUteaBLO1WXpGyKVLQhZrdu7rWEHGR0QZlSgp5h9XSiTHpOMG8CHnnNyhL0YRAtbxuqtY8kKXdyitSNlUKukyrelfXEiLOO9qg3QXzIuSd36AsRULl9bxuqtQ8kEe7lVekTGo+6DLtlEO+nhEE9WjVMP5mP4ciofJ2et2ISO0UKegyVcwhnxSWjoZyi3xY9xg1jT5odI6CLGU8hyJzSUD9UymLSOdQpaDLVC2HfFZYOlw5WLNhe67mhGAI3ydu3V2p7H151Psciob5y5pKWUQ6g5oPukzVelcXCUvnaU4IrqXKcx8kKeM5NCrMX7XXjYg0hqr5XaZqvauLhKVXLx2alhsgnLwIYMyfJrgd9PfA2MSh392EV/ag/LUkwmlUmL+e101Wc0ZZo2GSppNulSLl0XwLUhWqFHShKvWuntVvDMdMEBQ3P8C6zTun5QZ4fHTqvu0UGwhXCOJ+r2Ua3qH+HvZGD0T8dM1F1fK6yWrO+P/bu/8oO8r6juPv7+4mS3AJBAOE0GiggBrLUdskoFSR0tamMSDFX4hUbItYrLWttrXYCrX+oPW0p61tWrEiimmxItbkIP6EFsoRSWyriAhJTZoghERJsllNlmzy9I+Z2cydzMyduXd+7v28ztlzz86de+e5z/64z/0+z/P9FrUbJq2cdB0DgzztUb0FaRJNH0it4uoAJB2vsuRvU+TNyphUlrnXcs396jadUdR0R1o56TrkaY92dkiTKFIgtRqP+VSbdLxtiwbrkFSWOel4Wti6iJB2t+mMoqY70spJlympj/K0Rzs7pEk0KJBajQ7D/pgPw3GphvstRDQIikpIBBQS0u42PVTUroa0ctJlSeu/PO3Rzg5pEk0fSK26VdEL61aTQIpLSFRUSLvb9FBRuxrSykmXJa2P8rRHOzukSTQUlVolffKPO56lJkFgyODoEZg40Eur+rNgbGQ6nDx18OARiyGD9vVa2hmSV7YXkZAoLRdE3pB2t+mhFWfM5Zvb93W8lpVnjuWewoiWkzbgqGG47Tt7uXfrvlJW86eF/bOUtw40bUeQDDYNCqRWecKsSaHoqHDyojomHBbNHWbdZYunw8thR/lll6P/8PNkUuy2sr3fhETdHpP3/LTQ+B0bx7n9kYnp34FDDm5/ZILnLZgD5JvCCMpJB/2+r+TV/N1eW1p566gm7QiSwabpA6lVnjBrUig6rAnJi4Jtk2WtKi9qpX3e2hK9hLS7hcbLmMKoajW/wv4yEylSIJVICgO/88UnsXX3Ux35B5YtHJ3+hBUOk6cx6HjeaxuQwKjbqvJwn+TRbWV7L7UPskQMTh4byh3W7zY90MvK++0TU6xas6X2Og0K+8tMpEGBlK7bKvcHdjzVcf4DO57ijo3jfHP7vo4weZJjR4f4yhWndRwbNqg7y3HayvtonySJm0ZJm3LptfbB2Tds6jrw2rz7IFev28aqZx+b+Rpp0wMrzpjbNQSfNFhJu2aVq/kV9peZRtMHUrpeQ8RZw+FxiXnqHBAsWzgKpK+8zzq9ETeNkjbl0mvoPOsq/fWPTea6Rrdz00Lw3aY38tTIUFhfJJvGRgrM7JXApcBS4ERgK3Ab8H7n3N7QefOADwKvAOYAXwN+1zn3QOWNLlETc6NnbVOvIeKskhLz1GH+HOMbj0+mLhzcM3koNhVx1KnHDccuVEubclmecN2kkHv4ZzhnxKYX56XJ8/Psdm6WEHza9EZSjYxuzyki8Ro7KADegTcQuAZ4FHgBcB1wvpm9yDl3yMwMWAucCrwV2AX8EXCXmT3fOfdoLS0vWBNzo+dpU68h4qyKyOvfi/VXnd7xfXRXQL827z7I9fc8EZsrP2nKJW1HQbe6A/um3PTuiLSiUnnC81nOTQvBB/cllc1OmhJQWF+kN02ePljlnHu1c26Nc+4/nHN/Dfw2cDbwUv+cC4GfBS53zv2Lc+4L/rEh4A/qaHQZmpgbvd+Sx1lDxFnETR8EIfwqlZFnP2+u/Dwh97TnSeq/ZQtHc4Xniwrla0pApBqNjRQ453bGHF7v357i314IPOacuyv0uD1mtg64CG8Q0XpNzI3erU3d9t2fdeLs6U9yH/uvH+Yu/BM2PumOuN6QlZ8WOU9ugV7lzZUfXe2fdF7a82yfmGL7xBRjszqTPy1bOMrqVYumv8+7w6GfUL6mBESq0dhBQYLz/NuH/NvnAt+OOe9B4FfNbMw5N1FJy0rUxNzoaW3K8ma5/rFJrr/nCbbufirTgGDB2Ah79h/MNOcNM7t4UlrfR1f7x+lWdyAwceDIgUAgT3i+qFC+pgREytfk6YMOZnYK8B7gK865Df7h4/HWEUQFMex5VbStbE0MnRbRps8+tLdjsVyS4HmzDghmurS+z7KrIa3uQFSWn4+IzBytGBSY2RjwOWAKeGP4LuIjxKn/6czsTWa2wcw27NwZN0vRLCvOmMs1LzmBBWMjGN6n5rhUuW1rU5aERE14rU2T1vdZppTCdQeC55F63bFxnFVrtrD8w5tYtWYLd2wcr7tJMqAa/9/AzI7C22FwGnBeZEfBk3jRgqggQhAXRcA5dwNwA8DSpUtb8fGziaHTftuUlIQncH9kdf8glk5OKv2b1PdZ6hnErfyvYn2ExGvi7iIZXI2OFJjZLOAzwHLgl2NyDzyIt64gagmwdSasJ5jJLn7OMamr3KOOGsDSyXlL/3abEkia4snzc5BiNXF3kQyuxkYKzGwIWANcAKx0zt0Xc9pa4I1mdp5z7j/8x80FVgH/XFljBTicCCfLJ/pwfYPzb9zUscp9dAi2jR9k+Yc3MXd0CIdj72TcxsPmyRPNGJsFP55iuibA8UdZR5nlcB9lFV2lH+6/tBX7q1ct4up12zrWEJx63PD0z6Gu1f5NTNpVtCbuLpLB1dhBAfD3wKuA9wE/MrNzQvc96k8jrMXLYPhJM/t9DicvMuAvKm7vQIvL5R8kwgGOuC9ItrPuu3s6BgQAk4cOJzTKkvmvSfIMXMKv+5CjY0AAh/uol+17vbxxhncZNCGk3YQ2VKGJu4tkcDV5+mCFf/suvDf+8NdvADjnDgEvB74MrAY+CxwEznfObau6wYOs1/oGWt2erM4QchNC2k1oQxWauLtIBldjh6LOucUZz3sS+DX/S2rSSwhU4dHugj4Kl5AeMm+tQd6phW7CofqkiEeVP7M8pafbPLWgxEzSJI0dFEi7pIVAf3zgYGIJ4bjjbZA3mVKvThobOaKmwiHH9PdFDQyylnKuMqTdLUnTTJpaaOLuIhlMTZ4+kBZJC4GmlRBu4+r2qpIpBddJqqlQZK2FLEmPqg5p503SNBOnFkSqpkGBFCKaUOfY0SFmD8O1d+5IXCy4Z/IQ28YPMn9O5z/++XNs+nnm9FksqWhDBivPHMv0qW7IvBX84VwDc0ZsOuHQJUuO6UhAFP0+SEiUlMuhiFTOQdKctNwGQXtWnjnG6vufLDXBTjiJz+r7n2TlmWO5kjRpSkqkP5o+kMIEIdCsoWiIL5s8cQCueaH3iTQICTfFIQe3PzLB8xbMyXTu4xOHuO78E0tJ8pSU2CirLD+nBWMjrLtscSXh+rhr3P7IRGxGS63YFymHIgVSuCyh6DRpuxaaIGhflvfkIkLaSQmM8iY2iurWv+HpgirC9UWV4xaR3mlY3VJNXnldRAi36WHgbqmEo+fGpREemwVjoyPTP8NznzGHe7fuO+JnGiwmLHr3QVofL4j8TlURrs9zDa3YFymHBgUt1PSV10mh3aDwTpY31JNynNtWEwdg4oD3+rZPTHXsMIj+TN/54pMK34KY9nNad9niTOcWGa7Pew2t2BcpnqYPWqjpK6/TQrtZyvXmOXcmK/tnmicEX0W4XlMCIvVTpKCFmr7yOktoN3xfNGx+7jPmdOTunz1Ma2ofBIqq6FjmzzRPCL6KcL2mBETqZ8616V9t8ZYuXeo2bNhQdzNySdpCFhf2bZu0GgrvvnNHjS3Lbsjg6286nbNv2NT3tsFjR4f4yhWnFdMwERHAzL7hnFsad58iBS109fLjY984s4ZZ61ikmHbNcArfOPunHO++cwdDQBvKIwW7Ai5+zjEd6wR60a74iIi0nQYFLdRPmLWORYpp1/zm9n2Z3zjjBgSjQ15VxaYwmM5hsHX3U30/396WpoEWkXbSoKClei6Pm7JIsaxBQdo1d/wo/5x53DRJEaH6uOtA/A6IpPscTPdlWgXIpIREUUrGIyJV0u6DAVPHIsWk594+MdXTG3n4+YK0uEUPCMBrX9yAIJiqSXtdy2PyEoRlSTzU5pX34XTFZaVEFpHiaVAwYJI+eZb5ifSY0WK3FQbPF0xLVJnLIJx/f+5o8p9PtzHKO198EpcsOWY6VfGQwbKFo7F5/tsm/HNxHJ4u0sBApPkUmxww/S5S7IUVtkGRnU+gAAAQOElEQVQv/HzJaXoXjHlZAosOHkSnLXpdBBhUhiwjIVET1DFFJSLF0KBgwORdpFjEToXxglcCBs+XFr4vw/aJKc6+YdN0iuFeFgHOHoYNj02yas2W0vo9vJujn5TIvbah6Xk0RCSZBgUDKOsixaJ2KiSlrw0LPoV3K+MbPB/A3NGhxLLMSfqNWRxyTO+WyPK6wMs18PZz52fuy376/fp7nujYzRFub56BQT9tUAVDkfbSmgJJVFQ65W7pisPTF3nO7SV8Pzrcf8lh8IoTZU3D7HC5+rKffv/sQ/HbO5OOJ+mnDUpXLNJeGrpLom5h4Kzh5eiUxTGjhmGMTx7ipLERFs0d5rq7dngJigx+5uRRto0fjD03SIF87Z07evrEv/9gDw+Kcch5r2vdd/ekbj0EGJ90jE9mD6n3E35P2oWRd3dGP21QumKR9tKgQBKlhYHzhpeTpiziwt3rH5vkkiVHzoPHpUCu0/X3PNF1QNBNXEi9n/B7Uv6DvNGRfqcAVMFQpJ00fSCJ0sLARU0t5Al3J+02qMOcEcsdko8qoyJhUv6DLHkRimqDiLSXIgWSKC0MfG1CcaKkqYVoJcTgefKEu9NC10Vtesz6PPun+qtKsKCkioRBdKXf3QeaAhAZTKqS2MIqiU2QVqkxLhdCVFD5MGltgAH3X3V65mvu+vFUITUQ1l91Ohfc9L+Md9luuGBshB0/6i0jY1BFUUSkDmlVEjV9ID3JO7UQFUw1JJ0VdzztmkUMCE49bhg4nBwpSXDNvCH5QK+PExEpmwYF0pMVZ8zlmpecEJuWN2uSmm57/KN581ecMZezTpzdcc7JY0O51zHEveXPn2P862tOBdKTLYVfZ5ZUxcsWjnbcH7eAsmiqOyAivdKaAulZ0grzrEl9ugnnzQevzHJ0tf/m3fn2GCZNb0wc8N5MV5wxN7H9cdUZm5aquI7S2CIycyhSIIXLmtQnq2CqoajV/t12TrR55X1Ru0JEZDBpUDCAyg4vR6cWivBED2WWhyHX9EZQ8nj1/U9y1omzp8P+BuAc1965o/HheNUdEJF+aPpgwFQVXg5PLWSpZxCsyE8696Qcq/3jwvxhwwZJ6yCDKYtwGxyHMyE2PRyvugMi0g9FCgZMHeHlLNMJwYr8tNB9llX7WcL8/eY/anI4vs1THyJSP318GDBF1TPII5oIZ3QYJg96n8CjyXXSkuasOGMuW3c/1bHY8NTjhtk3ZZUn2GlqOL6fpENl/OxFpF00KBgwRdYzyCNPLvykc+/YOM4DO57qOPb4xKHptQJVanI4vpe6A9q1ICKg6YOBU0U9g7IU1b5lC0f7asdMDMc3/WcvItVo7scdKUU/9Qz60Wto+vp7npjO458kb/tWr1rEqz+1uSPHwfw5xsjwcGythrmjQzgceyfdjA2ra9dC8TQdI22kQcEAypt0qN9Qea+h6WhZ5SR523fHxnEen+jMWjhxAK554eD+09auhWJpOkbaStMHMq2sleu9hqazJCvqpX0KlR9JuxaKpd8xaSt9DJBpZZXL7TU0nTZlYNBz+8oMlV+9blvH7ohlC0dZvWpR389bNpVKLpamY6StNCiQDr2sXO+m19D0kMUPDPotPVxWqDw6IABY/9gkV6/b1pqBgQYBxdB0jLSVpg+kdL2GppOSFfVberisUHl0QNDtuMxcmo6RttKwVUrXa2g6SGgU7D6IJjqquj0iWel3TNrKnOsz52vLLV261G3YsKHuZsgMsOzDmxLvW39V79MdIiJFMrNvOOeWxt2n6QORgiQlReo3WZKISFU0KBApyOpVi44YALRl94GICGhNgUihNAAQkTZTpEBERESAGTIoMLNFZnarme0xs3Ezu83MnlF3u0RERNqk9YMCMzsauBN4NvAG4HLgDOAuM3tanW0TERFpk5mwpuBK4DTgWc65TQBm9i1gI3AV8Fc1tk1ERKQ1Wh8pAC4E7gsGBADOuc3AvcBFtbVKRESkZWbCoOC5wLdjjj8ILKm4LSIiIq01EwYFxwO7Yo4/CcyruC0iIiKtNRMGBQBxuZot5ph3h9mbzGyDmW3YuXNnic0SERFpj5kwKNiFFy2Imkd8BAHn3A3OuaXOuaUnnHBCqY0TERFpi5kwKHgQb11B1BLgOxW3RUREpLVmwqBgLXCOmZ0WHDCzxcC5/n0iIiKSwUwYFHwE2AJ8zswuMrMLgc8B24AP19kwERGRNmn9oMA59yPg54BHgJuBNcBm4OeccxN1tk1ERKRNZkJGQ5xzW4FL6m6HiIhIm7U+UiAiIiLFMOfitvgPDjPbCfxfQU83H/hBQc81U6mPulMfpVP/dKc+6m6Q++iZzrnY/fgDPygokpltcM4trbsdTaY+6k59lE790536qDv1UTxNH4iIiAigQYGIiIj4NCgo1g11N6AF1EfdqY/SqX+6Ux91pz6KoTUFIiIiAihSICIiIj4NCkLMbJGZ3Wpme8xs3MxuM7NnZHzsUWb2QTN73Mz2mdnXzOwlkXPONLO/MbNvmdmEf+5aM3teOa+oeGX3UcxjLjUzZ2aPFvMKyldVH5nZKWZ2o5ltN7NJM9tsZh8o9tWUo4o+MrOn+39v3/PP22xmf2dmjS+N2mf/vN/MvmRmP/T/dq5IOfdKM/uu//vzsJm9ubAXUbKy+8jMTjazD5jZBv8aO83sq93+Z7Wec05f3hTK0cBG4NvAK4CLgAeA/wWeluHxa4DdwJXABcBtwD7g+aFzfgv4FvB24HzgYuBrwH7gZ+rugyb0UeT844DtwOPAo3W//ib1EbAY+D7wn8CrgfOANwB/VncfNKGPAAPuBXYCvwm8FLga+KH/N2d190OJ/bMXuAf4OOCAKxLOuxI4BLzP/3/0Xv/736y7D5rQR8DLge8BfwL8ArASuN3vo5fX3Qel9W3dDWjKF/A24CBweujYqcAU8HtdHvs8/xfrjaFjI8DDwNrQsfnRf0bAscAu4BN190ET+ijymBuALwI30Z5BQSV9BHwBuB+YVfdrbmIfAWf6570p8vg3+8efVXc/lNE//rlD/u3pKW94I8AO4OOR4zfiJfRp9O9VRX10HDAS028PA3fX3QdlfWn64LALgfucc5uCA865zXifNi7K8NgDwKdCj50CbgFeZmaj/rEfOP83K3TeHrxiTqcU8SJKVnofBczsXOD1wFuKaXplSu8jM/tJ4GXAh5xzB4ptfiWq+D2a7d+ORx6/279t8v++fvoH59yhDNd4IXAC8MnI8ZuBpwM/m7m19Si9j5xzu/3frfCxKeB/aMf/6540+Q+jas/FC0VFPQgsyfDYzc65H8c8djbeaDSWmR0P/BTwUPam1qaSPjKzWXhRgg+G/+hbooo+Ote/3WdmX/bng3eZ2SfM7Om9NrxCVfTRg8DdwJ+Y2VIzGzOz5cC7gTucc03+e+unf/Jcg5jrPOjfFnWdslTRR0cws9l4A6om//70RYOCw47HC+NHPQnM6+Oxwf1JPoQ3//nX3RrYAFX10R8Co0ArFs1FVNFHC/3bG/GiTCvw+mwl8EUza/rfdel95Efkfhkv1Lsebw7563hzxE2vqNpP/+S5BjHXyfI/qwmq6KM41wE/Afx5ideo1YwonVyguKQNluFx1stjzeyPgNcBv96iT8Sl9pGZnQ68C7jYObc/f/Maoezfo+BN/9+dc8H0yp1mtgc/jA7ckaWhNarib+0jwDl46wgeAp4D/Clwq5mtyhhmr0uv/ZNV8FxtTlRTdh91PrHZ64B34i3mvaes69RNg4LDdhE/Op5H/Ig07EkgbivMvND9HfytP+8H/tg5d2OOdtapij76W+BO4D4zO84/Nhsw//tJ59y+XK2uVhV99EP/9suR877k376AZg8KSu8jM1sJXAr8vHPuq/59d5vZ9/D6aRXwuZztrko//ZNVOCLweOj48ZH7m6qKPppmZqvwFjx/1Dl3bdHP3yRNDzNW6UEOz7OFLQG+k+Gxp5rZ0TGPfQroiAKY2eXAauAvnXPv6625taiij5bghX13hb4uxQuZ76L5UwpV9FEw75v0Ka/Jn4Chmj46y79dHznvfv/2OdmaWot++ifPNYi5TjAfX9R1ylJFHwFgZhcAnwY+C1xV5HM3kQYFh60FzjGz04IDZrYYb1HX2gyPnQW8KvTYEeA1wJecc5Oh4xcDHwP+yTn3jqIaX5Eq+ui1eHumw19fxNsmdT7wdwW8jjJV0Uf34eVv+KXI44Pvo2+ETVNFH233b5dHHn+2f/v9XhpekX76J6uv4f1NXRY5/nq8KMG9BV2nLFX0EWb2QryI0leB1zd8yqkYde+JbMoX8DS8TxkP4G1puRD4Jt7CpLHQec/E2wv77sjjb8H7JPsbeAlVbsVLSvTToXNe4h/7L+BFePOdwdcL6u6DJvRRwnVvoj15CirpI7xERQ74R+AX8RLz7ALuosGJearqI2Au3hv/Y3jJi873b7cDW8PXadpXAf1zHvBKvGRpDm8g/UrglZHz3owXVXovXnKn9/jfv6XuPmhCHwHPxhsgbfH7J/z/+py6+6C0vq27AU36wpur/Aze3ua9wL8BiyPnLPZ/ia6LHJ8D/JX/T2c/3krnl0bOuc5/bNzXlrpffxP6KOGaN9GSQUGVfQRcjrctaxJvXvhDNPjNruo+AhYBHwU2++dtxlt8eErdr7/k/vn3pP8zMde5Cm8HyyRehsCr637tTekj4Iqkc+L6cqZ8qUqiiIiIAFpTICIiIj4NCkRERATQoEBERER8GhSIiIgIoEGBiIiI+DQoEBEREUCDAhGpiJndZGaP1t0OEUmmQYGIiIgAGhSIiIiIT4MCEemLmZ1uZjeb2WYz22dm3zOzfzCzeQnnv8jM1pvZfjPbYmZvDd233MycX6o2+rh/MLOdZjarzNcjMsg0KBCRfi0EHgV+B3gZXmGdC4DPx5w7F/gU8HHgFXg56P/WzK4AcM7dDzyMV9dhmpnNBl4N3OKcO1DGixARVPtARIrllzI+B7gHr3Lhf/vHb8Kr7nipc+6W0PlfBs7EK2bjzOxdwB8DC5xze/xzXoFXz/5sf+AgIiVQpEBE+mJms83sGjP7rpntAw7gDQgAnhU5/SBeZbuwW/Aq3p3if/9JYBR4Veicy4GHNSAQKZcGBSLSrw/glQX/JLASWA78in/fUZFzd8WE/5/wb08BcM79H3A3/hSCmR3nP+/NRTdcRDqN1N0AEWm91wKfcM69NzhgZmMJ584zs1mRgcFJ/u33Q8duBj5iZs/EW6cwG1hTYJtFJIYiBSLSr6PxpgzC3phw7jBwSeTYa4GtdA4KPg3sBy7Dixjc7Zzb0ndLRSSVIgUi0q8vAG8wsweATXhTBy9KOHcv8BdmNh/YCFwK/DxwhQutenbOjZvZWuAtwMnAlSW2X0R8GhSISL/eChjwPv/7z+O92cctChzHiwz8DXAW3nqCtznnPh5z7s3Aa/AiBrcW3GYRiaEtiSIiIgJoTYGIiIj4NCgQERERQIMCERER8WlQICIiIoAGBSIiIuLToEBEREQADQpERETEp0GBiIiIABoUiIiIiO//AS9HVlkVQqanAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<Figure size 576x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.figure(figsize=(8,8))\n",
-    "plt.scatter(abv, ibu, color='#3498db') \n",
-    "plt.title('Scatter plot of alcohol-by-volume vs. IBU \\n')\n",
-    "plt.xlabel('abv')\n",
-    "plt.ylabel('IBU');"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Hmm. That's a bit of a mess. Too many dots! But we do make out that the beers with low alcohol-by-volume tend to have low bitterness. For higher alcohol fraction, the beers can be anywhere on the bitterness scale: there's a lot of vertical spread on those dots to the right of the plot. \n",
-    "\n",
-    "An idea! What if the bitterness has something to do with _style_? "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Bubble chart\n",
-    "\n",
-    "What we imagined is that we could group together the beers by style, and then make a new scatter plot where each marker corresponds to a style. The beers within a style, though, have many values of alcohol fraction and bitterness: we have to come up with a \"summary value\" for each style. Well, why not the _mean_… we can calculate the average `abv` and the average `ibu` for all the beers in each style, use that pair as $(x,y)$ coordinate, and put a dot there representing the style. \n",
-    "\n",
-    "Better yet! We'll make the size of the \"dot\" proportional to the popularity of the style in our data set! This is called a **bubble chart**.\n",
-    "\n",
-    "How to achieve this idea? We searched online for \"mean of a column with pandas\" and we landed in [`dataframe.mean()`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.mean.html). This could be helpful… But we don't want the mean of a _whole_ column—we want the mean of the column values grouped by _style_. Searching online again, we landed in [`dataframe.groupby()`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html). This is amazing: `pandas` can group a series for you! \n",
-    "\n",
-    "Here's what we want to do: group beers by style, then compute the mean of `abv` and `ibu` in the groups. We experimented with `beers_clean.groupby('style').mean()` and were amazed… However, one thing was bothersome: `pandas` computed the mean (by style) of every column, including the `id` and `brewery_id`, which have no business being averaged. So we decided to first drop the columns we don't need, leaving only `abv`, `ibu` and `style`. We can use the [`dataframe.drop()`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.drop.html) method for that. Check it out!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "beers_styles = beers_clean.drop(['Unnamed: 0','name','brewery_id','ounces','id'], axis=1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We now have a dataframe with only the numeric features `abv` and `ibu`, and the categorical feature `style`. Let's find out how many beers we have of each style—we'd like to use this information to set the size of the style bubbles."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "style_counts = beers_styles['style'].value_counts()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "pandas.core.series.Series"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "type(style_counts)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "90"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "len(style_counts)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The number of beers in each style appears on each row of `style_counts`, sorted in decreasing order of count. We have 90 different styles, and the most popular style is the \"American IPA,\" with 301 beers…\n",
-    "\n",
-    "##### Discuss with your neighbor:\n",
-    "\n",
-    "* What happened? We used to have 99 styles and 424 counts in the \"American IPA\" style. Why is it different now?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "OK. We want to characterize each style of beer with the _mean values_ of the numeric features, `abv` and `ibu`, within that style. Let's get those means."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "style_means = beers_styles.groupby('style').mean()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "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>abv</th>\n",
-       "      <th>ibu</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>style</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>Abbey Single Ale</th>\n",
-       "      <td>0.049000</td>\n",
-       "      <td>22.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Altbier</th>\n",
-       "      <td>0.054625</td>\n",
-       "      <td>34.125000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>American Adjunct Lager</th>\n",
-       "      <td>0.046545</td>\n",
-       "      <td>11.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>American Amber / Red Ale</th>\n",
-       "      <td>0.057195</td>\n",
-       "      <td>36.298701</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>American Amber / Red Lager</th>\n",
-       "      <td>0.048063</td>\n",
-       "      <td>23.250000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Tripel</th>\n",
-       "      <td>0.089750</td>\n",
-       "      <td>23.500000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Vienna Lager</th>\n",
-       "      <td>0.050429</td>\n",
-       "      <td>24.357143</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Wheat Ale</th>\n",
-       "      <td>0.060000</td>\n",
-       "      <td>24.000000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Winter Warmer</th>\n",
-       "      <td>0.069500</td>\n",
-       "      <td>24.625000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Witbier</th>\n",
-       "      <td>0.050417</td>\n",
-       "      <td>16.208333</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>90 rows × 2 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                 abv        ibu\n",
-       "style                                          \n",
-       "Abbey Single Ale            0.049000  22.000000\n",
-       "Altbier                     0.054625  34.125000\n",
-       "American Adjunct Lager      0.046545  11.000000\n",
-       "American Amber / Red Ale    0.057195  36.298701\n",
-       "American Amber / Red Lager  0.048063  23.250000\n",
-       "...                              ...        ...\n",
-       "Tripel                      0.089750  23.500000\n",
-       "Vienna Lager                0.050429  24.357143\n",
-       "Wheat Ale                   0.060000  24.000000\n",
-       "Winter Warmer               0.069500  24.625000\n",
-       "Witbier                     0.050417  16.208333\n",
-       "\n",
-       "[90 rows x 2 columns]"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "style_means"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Looking good! We have the information we need: the average `abv` and `ibu` by style, and the counts by style. The only problem is that `style_counts` is sorted by decreasing count value, while `style_means` is sorted alphabetically by style. Ugh."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Notice that `style_means` is a dataframe that is now using the style string as a _label_ for each row. Meanwhile, `style_counts` is a `pandas` series, and it also uses the style as label or index to each element.\n",
-    "\n",
-    "More online searching and we find the [`series.sort_index()`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.sort_index.html) method. It will sort our style counts in alphabetical order of style, which is what we want."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "style_counts = style_counts.sort_index()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Abbey Single Ale               2\n",
-       "Altbier                        8\n",
-       "American Adjunct Lager        11\n",
-       "American Amber / Red Ale      77\n",
-       "American Amber / Red Lager    16\n",
-       "American Barleywine            2\n",
-       "American Black Ale            20\n",
-       "American Blonde Ale           61\n",
-       "American Brown Ale            38\n",
-       "American Dark Wheat Ale        5\n",
-       "Name: style, dtype: int64"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "style_counts[0:10]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Above, we used Matplotlib to create a scatter plot using two NumPy arrays as the `x` and `y` parameters. Like we saw previously with histograms, `pandas` also has available some plotting methods (calling Matplotlib internally). Scatter plots made easy!\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 576x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "style_means.plot.scatter(figsize=(8,8), \n",
-    "                         x='abv', y='ibu', s=style_counts, \n",
-    "                         title='Beer ABV vs. IBU mean values by style');"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "That's rad! Perhaps the bubbles are too small. We could multiply the `style_counts` by a factor of 5, or maybe 10? You should experiment. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "But we are feeling gung-ho about this now, and decided to find a way to make the _color_ of the bubbles also vary with the style counts. Below, we import the [`colormap`](https://matplotlib.org/api/cm_api.html) module of Matplotlib, and we set our colors using the [_viridis_ colormap](https://matplotlib.org/examples/color/colormaps_reference.html) on the values of `style_counts`, then we repeat the plot with these colors on the bubbles and some transparency. _What do you think?_"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from matplotlib import cm\n",
-    "colors = cm.viridis(style_counts.values)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x720 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "style_means.plot.scatter(figsize=(10,10), \n",
-    "                         x='abv', y='ibu', s=style_counts*20, color=colors,\n",
-    "                         title='Beer ABV vs. IBU mean values by style\\n',\n",
-    "                         alpha=0.3); #alpha sets the transparency"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "It looks like the most popular beers do follow a linear relationship between alcohol fraction and IBU. We learned a lot about beer without having a sip!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "_Wait... one more thing!_ What if we add a text label next to the bigger bubbles, to identify the style? \n",
-    "\n",
-    "OK, here we go a bit overboard, but we couldn't help it. We played around a lot to get this version of the plot. It uses `enumerate` to get pairs of indices and values from a list of style names; an `if` statement to select only the large-count styles; and the [`iloc[]`](http://pandas.pydata.org/pandas-docs/version/0.17.0/generated/pandas.DataFrame.iloc.html) slicing method of `pandas` to get a slice based on index position, and extract `abv` and `ibu` values to an $(x,y)$ coordinate for placing the annotation text. _Are we overkeen or what!_ "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x720 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = style_means.plot.scatter(figsize=(10,10), \n",
-    "                               x='abv', y='ibu', s=style_counts*20, color=colors,\n",
-    "                               title='Beer ABV vs. IBU mean values by style\\n',\n",
-    "                               alpha=0.3);\n",
-    "\n",
-    "for i, txt in enumerate(list(style_counts.index.values)):\n",
-    "    if style_counts.values[i] > 65:\n",
-    "        ax.annotate(txt, (style_means.abv.iloc[i],style_means.ibu.iloc[i]), fontsize=12)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## What we've learned\n",
-    "\n",
-    "* You should always plot your data.\n",
-    "* The concepts of quantitative and categorical data.\n",
-    "* Plotting histograms directly on columns of dataframes, using `pandas`.\n",
-    "* Computing variance and standard deviation using NumPy built-in functions.\n",
-    "* The concept of median, and how to compute it with NumPy.\n",
-    "* Making box plots using `pyplot`.\n",
-    "* Five statistics of a box plot: the quartiles Q1, Q2 (median) and Q3 (and  interquartile range Q3$-$Q1), upper and lower extremes.\n",
-    "* Visualizing categorical data with bar plots.\n",
-    "* Visualizing multiple data with scatter plots and bubble charts.\n",
-    "* `pandas` is awesome!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## References\n",
-    "\n",
-    "1. [Craft beer datatset](https://github.com/nickhould/craft-beers-dataset) by Jean-Nicholas Hould.\n",
-    "2. [What's The Meaning Of IBU?](https://beerconnoisseur.com/articles/whats-meaning-ibu) by Jim Dykstra for The Beer Connoisseur (2015).\n",
-    "3. 40 years of boxplots (2011). Hadley Wickham and Lisa Stryjewski, _Am. Statistician_. [PDF available](http://vita.had.co.nz/papers/boxplots.pdf)\n",
-    "4. [John Wilder Tukey](https://www.britannica.com/biography/John-Wilder-Tukey), Encyclopædia Britannica.\n",
-    "5. John W. Tukey: His life and professional contributions (2002). David R. Brillinger, _Ann. Statistics_. [PDF available](https://www.stat.berkeley.edu/~brill/Papers/life.pdf)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Problems\n",
-    "\n",
-    "1. Many beers do not report the IBU of the beer because it is very small. We may be accidentally removing whole categories of beer from our dataset by removing rows that do not include the IBU measure. \n",
-    "\n",
-    "    a. Use the command `beers_filled = beers.fillna(0)` to clean the `beers` dataframe\n",
-    "    \n",
-    "    b. Repeat the steps above to recreate the plot \"Beer ABV vs. IBU mean values by style\" \n",
-    "    scatter plot with `beers_filled`. What differences do you notice between the plots? "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "2. Gordon Moore created an empirical prediction that the rate of semiconductors on a computer chip would double every two years. This prediction was known as Moore's law. Gordon Moore had originally only expected this empirical relation to hold from 1965 - 1975 [[1](https://en.wikipedia.org/wiki/Moore%27s_law),[2](https://spectrum.ieee.org/computing/hardware/gordon-moore-the-man-whose-name-means-progress)], but semiconductor manufacuturers were able to keep up with Moore's law until 2015. \n",
-    "\n",
-    "    In the folder \"../data\" is a comma separated value (CSV) file, \"transistor_data.csv\" [taken from wikipedia 01/2020](https://en.wikipedia.org/wiki/Transistor_count#Microprocessors). \n",
-    "    Load the csv into a pandas dataframe, it has the following headings:\n",
-    "\n",
-    "    |Processor| MOS transistor count| Date of Introduction|Designer|MOSprocess|Area|\n",
-    "    |---|---|---|---|---|---|\n",
-    "\n",
-    "    a. In the years 2017, what was the average MOS transistor count? \n",
-    "    Make a boxplot of the transistor count in 2017 and find the first, second and third quartiles.\n",
-    "\n",
-    "    b. Create a semilog y-axis scatter plot (i.e. `plt.semilogy`) for the \n",
-    "    \"Date of Introduction\" vs \"MOS transistor count\". \n",
-    "    Color the data according to the \"Designer\"."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "widgets": {
-   "state": {},
-   "version": "1.1.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/.ipynb_checkpoints/03_Linear_Regression_with_Real_Data-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/03_Linear_Regression_with_Real_Data-checkpoint.ipynb
deleted file mode 100644
index 21438c1..0000000
--- a/notebooks/.ipynb_checkpoints/03_Linear_Regression_with_Real_Data-checkpoint.ipynb
+++ /dev/null
@@ -1,974 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "###### Modified under Creative Commons Attribution license CC-BY 4.0, code under BSD 3-Clause License © 2020 R.C. Cooper"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Linear regression with real data"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Earth temperature over time\n",
-    "\n",
-    "In this lesson, we will analyze real data of Earth temperature over time.\n",
-    "\n",
-    "Is global temperature rising? How much? This is a question of burning importance in today's world!\n",
-    "\n",
-    "Data about global temperatures are available from several sources: NASA, the National Climatic Data Center (NCDC) and the University of East Anglia in the UK. Check out the [University Corporation for Atmospheric Research](https://www2.ucar.edu/climate/faq/how-much-has-global-temperature-risen-last-100-years) (UCAR) for an in-depth discussion.\n",
-    "\n",
-    "The [NASA Goddard Space Flight Center](http://svs.gsfc.nasa.gov/goto?3901) is one of our sources of global climate data. They produced the video below showing a color map of the changing global surface **temperature anomalies** from 1880 to 2015.\n",
-    "\n",
-    "The term [global temperature anomaly](https://www.ncdc.noaa.gov/monitoring-references/faq/anomalies.php) means the difference in temperature with respect to a reference value or a long-term average. It is a very useful way of looking at the problem and in many ways better than absolute temperature. For example, a winter month may be colder than average in Washington DC, and also in Miami, but the absolute temperatures will be different in both places."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/jpeg": 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\n",
-      "text/html": [
-       "\n",
-       "        <iframe\n",
-       "            width=\"400\"\n",
-       "            height=\"300\"\n",
-       "            src=\"https://www.youtube.com/embed/gGOzHVUQCw0\"\n",
-       "            frameborder=\"0\"\n",
-       "            allowfullscreen\n",
-       "        ></iframe>\n",
-       "        "
-      ],
-      "text/plain": [
-       "<IPython.lib.display.YouTubeVideo at 0x7f2e4a375290>"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from IPython.display import YouTubeVideo\n",
-    "YouTubeVideo('gGOzHVUQCw0')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "How would we go about understanding the _trends_ from the data on global temperature?\n",
-    "\n",
-    "The first step in analyzing unknown data is to generate some simple plots using **Matplotlib**. We are going to look at the temperature-anomaly history, contained in a file, and make our first plot to explore this data. \n",
-    "\n",
-    "We are going to smooth the data and then we'll fit a line to it to find a trend, plotting along the way to see how it all looks.\n",
-    "\n",
-    "Let's get started!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Step 1: Read a data file\n",
-    "\n",
-    "We took the data from the [NOAA](https://www.ncdc.noaa.gov/cag/) (National Oceanic and Atmospheric Administration) webpage. Feel free to play around with the webpage and analyze data on your own, but for now, let's make sure we're working with the same dataset.\n",
-    "\n",
-    "\n",
-    "We have a file named `land_global_temperature_anomaly-1880-2016.csv` in our `data` folder. This file contains the year on the first column, and averages of land temperature anomaly listed sequentially on the second column, from the year 1880 to 2016. We will load the file, then make an initial plot to see what it looks like.\n",
-    "\n",
-    "\n",
-    "Let's start by importing NumPy and pandas"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To load our data from the file, we'll use the function [`numpy.loadtxt()`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html), which lets us immediately save the data into NumPy arrays. (We encourage you to read the documentation for details on how the function works.) Here, we'll save the data into the arrays `year` and `temp_anomaly`. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fname = '../data/land_global_temperature_anomaly-1880-2016.csv'\n",
-    "\n",
-    "temp_data = pd.read_csv(fname,skiprows=4)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "##### Exercise\n",
-    "\n",
-    "Inspect the data by printing `temp_data`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Step 2: Plot the data\n",
-    "\n",
-    "Let's first load the **Matplotlib** module called `pyplot`, for making 2D plots. Remember that to get the plots inside the notebook, we use a special \"magic\" command, `%matplotlib inline`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "#Import rcParams to set font styles\n",
-    "from matplotlib import rcParams\n",
-    "\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The `plot()` function of the `pyplot` module makes simple line plots. We avoid that stuff that appeared on top of the figure, that `Out[x]: [< ...>]` ugliness, by adding a semicolon at the end of the plotting command."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Set font style and size \n",
-    "rcParams['font.family'] = 'sans'\n",
-    "rcParams['font.size'] = 16\n",
-    "rcParams['lines.linewidth'] = 3"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x360 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "#You can set the size of the figure by doing:\n",
-    "plt.figure(figsize=(10,5))\n",
-    "\n",
-    "#Plotting\n",
-    "plt.plot(temp_data['Year'], temp_data['Value'], color='#2929a3', linestyle='-', linewidth=1) \n",
-    "plt.title('Land global temperature anomalies. \\n')\n",
-    "plt.xlabel('Year')\n",
-    "plt.ylabel('Land temperature anomaly [°C]')\n",
-    "plt.grid();"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Step 3: Least-squares linear regression \n",
-    "\n",
-    "In order to have an idea of the general behavior of our data, we can find a smooth curve that (approximately) fits the points. We generally look for a curve that's simple (e.g., a polynomial), and does not reproduce the noise that's always present in experimental data. \n",
-    "\n",
-    "Let $f(x)$ be the function that we'll fit to the $n+1$ data points: $(x_i, y_i)$, $i = 0, 1, ... ,n$:\n",
-    "\n",
-    "$$ \n",
-    "    f(x) = f(x; a_0, a_1, ... , a_m) \n",
-    "$$\n",
-    "\n",
-    "The notation above means that $f$ is a function of $x$, with $m+1$ variable parameters $a_0, a_1, ... , a_m$, where $m < n$. We need to choose the form of $f(x)$ _a priori_, by inspecting the experimental data and knowing something about the phenomenon we've measured. Thus, curve fitting consists of two steps: \n",
-    "\n",
-    "1. Choosing the form of $f(x)$.\n",
-    "2. Computing the parameters that will give us the \"best fit\" to the data. \n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### What is the \"best\" fit?\n",
-    "\n",
-    "When the noise in the data is limited to the $y$-coordinate, it's common to use a **least-squares fit** [2], which minimizes the function\n",
-    "\n",
-    "$$\n",
-    "\\begin{equation}    \n",
-    "    S(a_0, a_1, ... , a_m) = \\sum_{i=0}^{n} [y_i - f(x_i)]^2\n",
-    "\\end{equation}~~~~~~(1)   \n",
-    "$$\n",
-    "\n",
-    "with respect to each $a_j$. We find the values of the parameters for the best fit by solving the following equations:\n",
-    "\n",
-    "$$\n",
-    "\\begin{equation}\n",
-    "    \\frac{\\partial{S}}{\\partial{a_k}} = 0, \\quad k = 0, 1, ... , m.\n",
-    "\\end{equation}~~~~~~(2)\n",
-    "$$\n",
-    "\n",
-    "Here, the terms $r_i = y_i - f(x_i)$ are called residuals: they tell us the discrepancy between the data and the fitting function at $x_i$. \n",
-    "\n",
-    "Take a look at the function $S$: what we want to minimize is the sum of the squares of the residuals. The equations (2) are generally nonlinear in $a_j$ and might be difficult to solve. Therefore, the fitting function is commonly chosen as a linear combination of specified functions $f_j(x)$, \n",
-    "\n",
-    "$$\n",
-    "\\begin{equation*}\n",
-    "    f(x) = a_0f_0(x) + a_1f_1(x) + ... + a_mf_m(x)\n",
-    "\\end{equation*}~~~~~~(3)\n",
-    "$$\n",
-    "\n",
-    "which results in equations (2) being linear. In the case that the fitting function is polynomial, we have have $f_0(x) = 1, \\; f_1(x) = x, \\; f_2(x) = x^2$, and so on.  "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Linear regression \n",
-    "\n",
-    "When we talk about linear regression we mean \"fitting a function to the data.\" In this case,\n",
-    "\n",
-    "$$\n",
-    "\\begin{equation}\n",
-    "    f(x) = a_0 + a_1x\n",
-    "\\end{equation}~~~~~~(4)\n",
-    "$$\n",
-    "\n",
-    "The function that we'll minimize is:\n",
-    "\n",
-    "$$\n",
-    "\\begin{equation}\n",
-    "    S(a_0, a_1) = \\sum_{i=0}^{n} [y_i - f(x_i)]^2 = \\sum_{i=0}^{n} (y_i - a_0 - a_1x_i)^2 \n",
-    "\\end{equation}~~~~~~(5)    \n",
-    "$$\n",
-    "\n",
-    "Equations (2) become:\n",
-    "\n",
-    "$$\n",
-    "\\begin{equation}\n",
-    "    \\frac{\\partial{S}}{\\partial{a_0}} =  \\sum_{i=0}^{n} -2(y_i - a_0 - a_1x_i) = 2 \\left[ a_0(n+1) + a_1\\sum_{i=0}^{n} x_i - \\sum_{i=0}^{n} y_i \\right] = 0\n",
-    "\\end{equation}~~~~~~(6)    \n",
-    "$$\n",
-    "\n",
-    "$$\n",
-    "\\begin{equation}\n",
-    "    \\frac{\\partial{S}}{\\partial{a_1}} =  \\sum_{i=0}^{n} -2(y_i - a_0 - a_1x_i)x_i = 2 \\left[ a_0\\sum_{i=0}^{n} x_i + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i \\right] = 0\n",
-    "\\end{equation}~~~~~~(7)    \n",
-    "$$\n",
-    "\n",
-    "Let's divide both equations by $2(n+1)$ and rearrange terms.\n",
-    "\n",
-    "Rearranging (6) and (7):\n",
-    "\n",
-    "$$\n",
-    "\\begin{align}\n",
-    "    2 \\left[ a_0(n+1) + a_1\\sum_{i=0}^{n} x_i - \\sum_{i=0}^{n} y_i \\right] &= 0 \\nonumber \\\\ \n",
-    "    \\frac{a_0(n+1)}{n+1} + a_1 \\frac{\\sum_{i=0}^{n} x_i}{n+1} - \\frac{\\sum_{i=0}^{n} y_i}{n+1} &= 0 \\\\\n",
-    "\\end{align}~~~~~~(8)\n",
-    "$$\n",
-    "\n",
-    "$$\n",
-    "\\begin{align}\n",
-    "    a_0  = \\bar{y} - a_1\\bar{x}\n",
-    "\\end{align}~~~~~~(9)\n",
-    "$$\n",
-    "\n",
-    "where $\\bar{x} = \\frac{\\sum_{i=0}^{n} x_i}{n+1}$ and $\\bar{y} = \\frac{\\sum_{i=0}^{n} y_i}{n+1}$.\n",
-    "\n",
-    "Rearranging (7):\n",
-    "\n",
-    "$$\n",
-    "\\begin{align}\n",
-    "    2 \\left[ a_0\\sum_{i=0}^{n} x_i + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i \\right] &= 0 \\\\\n",
-    "    a_0\\sum_{i=0}^{n} x_i + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i &=0 \\\\\n",
-    "\\end{align}~~~~~~(10)\n",
-    "$$\n",
-    "\n",
-    "Now, if we replace $a_0$ from equation (8) into (9) and rearrange terms:\n",
-    "\n",
-    "$$\n",
-    "\\begin{align*}\n",
-    "    (\\bar{y} - a_1\\bar{x})\\sum_{i=0}^{n} x_i  + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i  &= 0 \\\\ \n",
-    "\\end{align*}~~~~~~(11)\n",
-    "$$\n",
-    "\n",
-    "Replacing the definitions of the mean values into the equation,  \n",
-    "\n",
-    "$$\n",
-    "\\begin{align*}\n",
-    "    \\left[\\frac{1}{n+1}\\sum_{i=0}^{n} y_i  - \\frac{a_1}{n+1}\\sum_{i=0}^{n} x_i \\right]\\sum_{i=0}^{n} x_i  + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i  &= 0  \\\\ \n",
-    "     \\frac{1}{n+1}\\sum_{i=0}^{n} y_i \\sum_{i=0}^{n} x_i - \\frac{a_1}{n+1}\\sum_{i=0}^{n} x_i \\sum_{i=0}^{n} x_i  + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i  &= 0  \\\\ \n",
-    "\\end{align*}~~~~~~(12)\n",
-    "$$\n",
-    "\n",
-    "Leaving everything in terms of $\\bar{x}$, \n",
-    "\n",
-    "$$\n",
-    "\\begin{align*}\n",
-    "    \\sum_{i=0}^{n} y_i \\bar{x} - a_1\\sum_{i=0}^{n} x_i \\bar{x} + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i  = 0  \n",
-    "\\end{align*}~~~~~~(13)\n",
-    "$$\n",
-    "\n",
-    "Grouping the terms that have $a_1$ on the left-hand side and the rest on the right-hand side:\n",
-    "\n",
-    "$$\n",
-    "\\begin{align*}\n",
-    "    a_1\\left[ \\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_i \\bar{x}\\right] &= \\sum_{i=0}^{n} x_iy_i - \\sum_{i=0}^{n} y_i \\bar{x} \\\\\n",
-    "    a_1 \\sum_{i=0}^{n} (x_{i}^2 - x_i \\bar{x}) &= \\sum_{i=0}^{n} (x_iy_i -  y_i \\bar{x}) \\\\\n",
-    "    a_1 \\sum_{i=0}^{n} x_{i}(x_{i} -\\bar{x}) &= \\sum_{i=0}^{n} y_i(x_i - \\bar{x})    \n",
-    "\\end{align*}~~~~~~(14)\n",
-    "$$\n",
-    "\n",
-    "Finally, we get that:\n",
-    "\n",
-    "$$\n",
-    "\\begin{align}\n",
-    "    a_1 = \\frac{ \\sum_{i=0}^{n} y_{i} (x_i - \\bar{x})}{\\sum_{i=0}^{n} x_i (x_i - \\bar{x})}\n",
-    "\\end{align}~~~~~~(15)\n",
-    "$$\n",
-    "\n",
-    "Then our coefficients are:\n",
-    "\n",
-    "$$\n",
-    "\\begin{align}\n",
-    "    a_1 = \\frac{ \\sum_{i=0}^{n} y_{i} (x_i - \\bar{x})}{\\sum_{i=0}^{n} x_i (x_i - \\bar{x})} \\quad , \\quad a_0  = \\bar{y} - a_1\\bar{x}\n",
-    "\\end{align}~~~~~~(16)\n",
-    "$$"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Let's fit!\n",
-    "\n",
-    "Let's now fit a straight line through the temperature-anomaly data, to see the trend over time. We'll use least-squares linear regression to find the slope and intercept of a line \n",
-    "\n",
-    "$y = a_1x+a_0$\n",
-    "\n",
-    "that fits our data.\n",
-    "\n",
-    "In our case, the `x`-data corresponds to `Year`, and the `y`-data is `Value`. To calculate our coefficients with the formula above, we need the mean values of our data. Since we'll need to compute the mean for both `x` and `y`. \n",
-    "\n",
-    "It is good coding practice to *avoid repeating* ourselves: we want to write code that is reusable, not only because it leads to less typing but also because it reduces errors. If you find yourself doing the same calculation multiple times, it's better to encapsulate it into a *function*. \n",
-    "\n",
-    "Remember the _key concept_ from [02_Working_with_Python](../../CompMech01-Getting-started/notebooks/02_Working_with_Python.ipynb): A function is a compact collection of code that executes some action on its arguments. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Exercise \n",
-    "\n",
-    "Calculate the mean of the `year` and `temp_anomaly` arrays using the NumPy built-in function, `np.mean`.\n",
-    "\n",
-    "Assign the means to `mean_x` and `mean_y`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true,
-    "jupyter": {
-     "outputs_hidden": true
-    }
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now that we have mean values, we can compute our coefficients by following equations (12). We first calculate $a_1$ and then use that value to calculate $a_0$.\n",
-    "\n",
-    "Our coefficients are:\n",
-    "\n",
-    "$$\n",
-    "    a_1 = \\frac{ \\sum_{i=0}^{n} y_{i} (x_i - \\bar{x})}{\\sum_{i=0}^{n} x_i (x_i - \\bar{x})} \\quad , \\quad a_0  = \\bar{y} - a_1\\bar{x}\n",
-    "$$ \n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We already calculated the mean values of the data arrays, but the formula requires two sums over new derived arrays. Guess what, NumPy has a built-in function for that: [`numpy.sum()`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html). Study the code below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "xi = temp_data['Year'].values\n",
-    "yi = temp_data['Value'].values\n",
-    "\n",
-    "x_mean = np.mean(xi)\n",
-    "y_mean = np.mean(yi)\n",
-    "\n",
-    "a_1 = np.sum(yi*(xi - x_mean)) / np.sum(xi*(xi - x_mean)) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.01037028394347266\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(a_1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "a_0 = y_mean - a_1*x_mean"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "-20.148685384658464\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(a_0)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "##### Exercise\n",
-    "\n",
-    "Write a function that computes the coefficients, call the function to compute them and compare the result with the values we obtained before. As a hint, we give you the structure that you should follow:\n",
-    "\n",
-    "```python\n",
-    "def coefficients(x, y, x_mean, y_mean):\n",
-    "    \"\"\"\n",
-    "    Write docstrings here\n",
-    "    \"\"\"\n",
-    "\n",
-    "    a_1 = \n",
-    "    a_0 = \n",
-    "    \n",
-    "    return a_1, a_0\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def coefficients(x, y, x_mean, y_mean):\n",
-    "    \"\"\"\n",
-    "    Write docstrings here\n",
-    "    Arguments\n",
-    "    ---------\n",
-    "    ??\n",
-    "    Returns\n",
-    "    -------\n",
-    "    ??\n",
-    "    \"\"\"\n",
-    "    # your code here\n",
-    "    \n",
-    "    return a_1, a_0"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We now have the coefficients of a linear function that best fits our data. With them, we can compute the predicted values of temperature anomaly, according to our fit. Check again the equations above: the values we are going to compute are $f(x_i)$. \n",
-    "\n",
-    "Let's call `reg` the array obtined from evaluating $f(x_i)$ for all years."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "reg = a_0 + a_1 * xi"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "With the values of our linear regression, we can plot it on top of the original data to see how they look together. Study the code below. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x360 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.figure(figsize=(10, 5))\n",
-    "\n",
-    "plt.plot(xi, yi,'s', color='#2929a3', linewidth=1, alpha=0.5,label='Measured anomoly') \n",
-    "plt.plot(xi, reg, 'k--', linewidth=2, label='Linear regression')\n",
-    "plt.xlabel('Year')\n",
-    "plt.ylabel('Land temperature anomaly [°C]')\n",
-    "plt.legend(loc='best', fontsize=15)\n",
-    "plt.grid();"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Step 4: Apply regression using NumPy"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Above, we coded linear regression from scratch. But, guess what: we didn't have to because NumPy has built-in functions that do what we need!\n",
-    "\n",
-    "Yes! Python and NumPy are here to help! With [`polyfit()`](https://docs.scipy.org/doc/numpy-1.10.0/reference/generated/numpy.polyfit.html), we get the slope and $y$-intercept of the line that best fits the data. With [`poly1d()`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.poly1d.html), we can build the linear function from its slope and $y$-intercept.\n",
-    "\n",
-    "Check it out:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# First fit with NumPy, then name the coefficients obtained a_1n, a_0n:\n",
-    "a_1n, a_0n = np.polyfit(xi, yi, 1)\n",
-    "\n",
-    "f_linear = np.poly1d((a_1n, a_0n)) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.010370283943472659\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(a_1n)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "-20.148685384658457\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(a_0n)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      " \n",
-      "0.01037 x - 20.15\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(f_linear)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The assignment `f_linear = np.poly1d((a_1n,a_0n))` creates a 1D polynomial. This means that the function only has one independent variable i.e. f(x) = (some value). You can create your own polynomial functions in a similar way using _anonymous functions_ i.e. `lambda`.\n",
-    "\n",
-    "```python\n",
-    "f_linear = lambda x: a_1n*x + a_0n\n",
-    "```\n",
-    "\n",
-    "In the line of code given above, we create the same assignment for `f_linear(x)`. One benefit of writing this out yourself is that you can see how each input is used directly. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Exercise\n",
-    "\n",
-    "Use the `lambda` function to assign `f_linear` to our 1D polynomial instead of the `np.poly1d` assignment. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 720x360 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.figure(figsize=(10, 5))\n",
-    "\n",
-    "plt.plot(xi, yi,'s', color='#2929a3', linewidth=1, alpha=0.5,label='Measured anomoly')\n",
-    "plt.plot(xi, f_linear(xi), 'k--', linewidth=2, label='Linear regression')\n",
-    "plt.xlabel('Year')\n",
-    "plt.ylabel('Land temperature anomaly [°C]')\n",
-    "plt.legend(loc='best', fontsize=15)\n",
-    "plt.grid();"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## \"Split regression\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "If you look at the plot above, you might notice that around 1970 the temperature starts increasing faster that the previous trend. So maybe one single straight line does not give us a good-enough fit.\n",
-    "\n",
-    "What if we break the data in two (before and after 1970) and do a linear regression in each segment? \n",
-    "\n",
-    "To do that, we first need to find the position in our `year` array where the year 1970 is located. Thankfully, NumPy has a function called  [`numpy.where()`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.where.html) that can help us. We pass a condition and `numpy.where()` tells us where in the array the condition is `True`. \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'numpy' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-22-019124a4bf3b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwhere\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0myear\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;36m1970\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m: name 'numpy' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "numpy.where(year==1970)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To split the data, we use the powerful instrument of _slicing_ with the colon notation. Remember that a colon between two indices indicates a range of values from a `start` to an `end`. The rule is that `[start:end]` includes the element at index `start` but excludes the one at index `end`. For example, to grab the first 3 years in our `year` array, we do:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "year[0:3]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now we know how to split our data in two sets, to get two regression lines. We need two slices of the arrays `year` and `temp_anomaly`, which we'll save in new variable names below. After that, we complete two linear fits using the helpful NumPy functions we learned above."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "year_1 , temp_anomaly_1 = year[0:90], temp_anomaly[0:90]\n",
-    "year_2 , temp_anomaly_2 = year[90:], temp_anomaly[90:]\n",
-    "\n",
-    "m1, b1 = numpy.polyfit(year_1, temp_anomaly_1, 1)\n",
-    "m2, b2 = numpy.polyfit(year_2, temp_anomaly_2, 1)\n",
-    "\n",
-    "f_linear_1 = numpy.poly1d((m1, b1))\n",
-    "f_linear_2 = numpy.poly1d((m2, b2))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plt.figure(figsize=(10, 5))\n",
-    "\n",
-    "plt.plot(year, temp_anomaly, color='#2929a3', linestyle='-', linewidth=1, alpha=0.5) \n",
-    "plt.plot(year_1, f_linear_1(year_1), 'g--', linewidth=2, label='1880-1969')\n",
-    "plt.plot(year_2, f_linear_2(year_2), 'r--', linewidth=2, label='1970-2016')\n",
-    "\n",
-    "plt.xlabel('Year')\n",
-    "plt.ylabel('Land temperature anomaly [°C]')\n",
-    "plt.legend(loc='best', fontsize=15)\n",
-    "plt.grid();"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Discussion exercise\n",
-    "We have two different curves for two different parts of our data set. A little problem with this and is that the end point of our first regression doesn't match the starting point of the second regression. We did this for the purpose of learning, but it is not rigorously correct. \n",
-    "\n",
-    "How would you fix this issue? \n",
-    "\n",
-    "What would your new function, $f(x)$, look like?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## We learned:\n",
-    "\n",
-    "* Making our plots more beautiful\n",
-    "* Defining and calling custom Python functions\n",
-    "* Applying linear regression to data\n",
-    "* NumPy built-ins for linear regression\n",
-    "* The Earth is warming up!!!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## References\n",
-    "\n",
-    "1. [_Essential skills for reproducible research computing_](https://barbagroup.github.io/essential_skills_RRC/) (2017). Lorena A. Barba,  Natalia C. Clementi, Gilbert Forsyth. \n",
-    "2. _Numerical Methods in Engineering with Python 3_ (2013). Jaan Kiusalaas. Cambridge University Press.\n",
-    "3. _Effective Computation in Physics: Field Guide to Research with Python_ (2015). Anthony Scopatz & Kathryn D. Huff. O'Reilly Media, Inc.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Problems\n",
-    "\n",
-    "1. There is a csv file in '../data/primary-energy-consumption-by-region.csv' that has the energy consumption of different regions of the world from 1965 until 2018 [Our world in Data](https://ourworldindata.org/energy). \n",
-    "We are going to compare the energy consumption of the United States to all of Europe. Load the data into a pandas dataframe. *Note: we can get certain rows of the data frame by specifying what we're looking for e.g. \n",
-    "`EUR = dataframe[dataframe['Entity']=='Europe']` will give us all the rows from Europe's energy consumption.*\n",
-    "\n",
-    "    a. Plot the total energy consumption of the United States and Europe\n",
-    "    \n",
-    "    b. Use a linear least-squares regression to find a function for the energy consumption as a function of year\n",
-    "    \n",
-    "    energy consumed = $f(t) = At+B$\n",
-    "    \n",
-    "    c. At what year would you change split the data and use two lines like we did in the \n",
-    "    land temperature anomoly? Split the data and perform two linear fits. \n",
-    "    \n",
-    "    d. What is your prediction for US energy use in 2025? How about European energy use in 2025?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "energy = pd.read_csv('../data/primary-energy-consumption-by-region.csv')\n",
-    "CAN = energy[energy['Entity']=='Canada']\n",
-    "USA = energy[energy['Entity']=='United States']\n",
-    "EUR = energy[energy['Entity']=='Europe']\n",
-    "plt.plot(USA['Year'],USA['Primary Energy Consumption (terawatt-hours)'],'-o')\n",
-    "plt.plot(EUR['Year'],EUR['Primary Energy Consumption (terawatt-hours)'],'-s')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "2. We plotted Gordon Moore's empirical prediction that the rate of semiconductors on a computer chip would double every two years in [02_Seeing_Stats](./02_Seeing_Stats.ipynb). This prediction was known as Moore's law. Gordon Moore had originally only expected this empirical relation to hold from 1965 - 1975 [[1](https://en.wikipedia.org/wiki/Moore%27s_law),[2](https://spectrum.ieee.org/computing/hardware/gordon-moore-the-man-whose-name-means-progress)], but semiconductor manufacuturers were able to keep up with Moore's law until 2015. \n",
-    "\n",
-    "We can use a linear regression to find our own historical Moore's Law.    \n",
-    "\n",
-    "Use your code from [02_Seeing_Stats](./02_Seeing_Stats.ipynb) to plot the semilog y-axis scatter plot \n",
-    "(i.e. `plt.semilogy`) for the \"Date of Introduction\" vs \"MOS transistor count\". \n",
-    "Color the data according to the \"Designer\".\n",
-    "\n",
-    "Create a linear regression for the data in the form of \n",
-    "\n",
-    "$log(transistor~count)= f(date) = A\\cdot date+B$\n",
-    "\n",
-    "rearranging\n",
-    "\n",
-    "$transistor~count= e^{f(date)} = e^B e^{A\\cdot date}$\n",
-    "\n",
-    "You can perform a least-squares linear regression using the following assignments\n",
-    "\n",
-    "$x_i=$ `dataframe['Date of Introduction'].values`\n",
-    "\n",
-    "and\n",
-    "\n",
-    "$y_i=$ as `np.log(dataframe['MOS transistor count'].values)`\n",
-    "\n",
-    "a. Plot your function on the semilog y-axis scatter plot\n",
-    "\n",
-    "b. What are the values of constants $A$ and $B$ for our Moore's law fit? How does this compare to Gordon Moore's prediction that MOS transistor count doubles every two years?\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "anaconda-cloud": {},
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "widgets": {
-   "state": {},
-   "version": "1.1.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/.ipynb_checkpoints/04_Stats_and_Montecarlo-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/04_Stats_and_Montecarlo-checkpoint.ipynb
deleted file mode 100644
index e24a004..0000000
--- a/notebooks/.ipynb_checkpoints/04_Stats_and_Montecarlo-checkpoint.ipynb
+++ /dev/null
@@ -1,965 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "###### Content created under Creative Commons Attribution license CC-BY 4.0, code under BSD 3-Clause License © 2020 R.C. Cooper"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "# Statistics and Monte-Carlo Models\n",
-    "\n",
-    "Monte Carlo models use random numbers to either understand statistics or generate a solution [1]. \n",
-    "The main element in a Monte Carlo model is the use of random numbers. Monte Carlo methods are very useful if you can easily execute a function lots of time or even in parallel. \n",
-    "\n",
-    "We can generate random numbers in many ways, but most programming languages have 'pseudo'-random number generators. \n",
-    "\n",
-    "In Python, we use the numpy library as such\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "x=np.random.rand(10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "#Import rcParams to set font styles\n",
-    "from matplotlib import rcParams\n",
-    "\n",
-    "#Set font style and size \n",
-    "rcParams['font.family'] = 'sans'\n",
-    "rcParams['font.size'] = 16\n",
-    "rcParams['lines.linewidth'] = 3"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(array([3., 1., 0., 0., 1., 0., 0., 2., 1., 2.]),\n",
-       " array([0.34837708, 0.41148652, 0.47459596, 0.53770539, 0.60081483,\n",
-       "        0.66392427, 0.72703371, 0.79014314, 0.85325258, 0.91636202,\n",
-       "        0.97947146]),\n",
-       " <a list of 10 Patch objects>)"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.hist(x,bins=10, color='b', histtype='bar', edgecolor='w')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The `numpy.random.rand(10)` function generates 10 random numbers between 0 and 1. The pyplot function `hist` then displays a histogram of these randomly generated numbers. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Exercise and Discussion\n",
-    "\n",
-    "Try generating more random numbers and plotting histograms of the results i.e. increase `10` to larger values. \n",
-    "\n",
-    "What should the histogram of `x` look like if Python is generating truly random numbers?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "## Examples of Monte Carlo models:\n",
-    "\n",
-    "Monte Carlo models have a wide array of applications. We are going to use Monte Carlo models in later modules to explore how uncertainty in measurements can be incorporated into computational models. The three main applications for Monte Carlo models are used in three main classes: optimization, numerical integration, and generating population distributions [1]. \n",
-    "\n",
-    "Here is a brief list of Monte Carlo model use cases in real-world applications:\n",
-    "\n",
-    "- [Eigenvlaues in supercritical systems](https://link.springer.com/chapter/10.1007%2FBFb0049064)\n",
-    "- [average time between failures for reliability](http://www.egr.msu.edu/~mitraj/research/pubs/proc/singh-mitra_em_stdby_ias95.pdf)\n",
-    "- disordered materials (physics)\n",
-    "- [Calculation of the energy output of a wind farm](http://www.mdpi.com/1996-1073/9/4/286/pdf)\n",
-    "- [US Coast Guard rescue missions](https://en.wikipedia.org/wiki/Search_and_Rescue_Optimal_Planning_System)\n",
-    "- [Radiation shielding](http://www.sciencedirect.com/science/article/pii/S0920379612000580)\n",
-    "- [Predict number of asteroids that hit body of water](https://cneos.jpl.nasa.gov/sentry/intro.html)\n",
-    "- [Financial modeling](https://en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance)\n",
-    "\n",
-    "We will explore Monte Carlo modeling through the use of three examples:\n",
-    "\n",
-    "1. Calculate the value of $\\pi$\n",
-    "\n",
-    "2. Calculate the integral of a function\n",
-    "\n",
-    "3. Propagate uncertainty in manufacturing into uncertainty in failure load"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "\n",
-    "\n",
-    "# Example 1: Calculate $\\pi$ with random numbers. \n",
-    "\n",
-    "Assuming we can actually generate random numbers (a topic of philosophical and heated debates) we can populate a unit square with random points and determine the ratio of points inside and outside of a circle.\n",
-    "\n",
-    "![Unit circle and unit square](../images/MonteCarloPi.gif)\n",
-    "\n",
-    "![1/4 Unit circle and 1/4 unit square](../images/MonteCarloPi_rand.gif)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "The ratio of the area of the circle to the square is:\n",
-    "\n",
-    "$\\frac{\\pi r^{2}}{4r^{2}}=\\frac{\\pi}{4}$\n",
-    "\n",
-    "So if we know the fraction of random points that are within the unit circle, then we can calculate $\\pi$\n",
-    "\n",
-    "(number of points in circle)/(total number of points)=$\\pi/4$"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.61262684, 0.8262925 , 0.59955407, 0.43229944, 0.66224665,\n",
-       "       0.61154899, 0.34189469, 0.94126304, 0.41459117, 0.6400169 ])"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.random.rand(10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "slideshow": {
-     "slide_type": "fragment"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "def montecarlopi(N):\n",
-    "    '''Create random x-y-coordinates to and use ratio of circle-to-square to \n",
-    "    calculate the value of pi\n",
-    "    i.e. Acircle/Asquare = pi/4\n",
-    "    Arguments\n",
-    "    ---------\n",
-    "    N: number of random points to produce between x=0-1 and y=0-1\n",
-    "    \n",
-    "    Returns\n",
-    "    -------\n",
-    "    our_pi: the best prediction of pi using N points\n",
-    "    '''\n",
-    "    \n",
-    "\n",
-    "    x=np.random.rand(N,1);\n",
-    "    y=np.random.rand(N,1);\n",
-    "    R=np.sqrt(x**2+y**2); # compute radius\n",
-    "    num_in_circle=sum(R<1);\n",
-    "    total_num_pts =len(R);\n",
-    "    our_pi = 4*num_in_circle/total_num_pts;\n",
-    "    return our_pi"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "mean value for pi = 3.188800\n",
-      "standard deviation is 0.041097\n",
-      "actual pi is 3.141593\n"
-     ]
-    }
-   ],
-   "source": [
-    "test_pi=np.zeros(10)\n",
-    "for i in range(0,10):\n",
-    "    test_pi[i]=montecarlopi(1000);\n",
-    "\n",
-    "print('mean value for pi = %f'%np.mean(test_pi))\n",
-    "print('standard deviation is %f'%np.std(test_pi))\n",
-    "print('actual pi is %f'%np.pi)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Exercises\n",
-    "\n",
-    "1. Why is there a standard deviation for the value of $\\pi$ calculated with a Monte Carlo method? Does it depend upon how many times you run the function i.e. the size of `test_pi`? or the number of random points `N`? Alter the script above to discover correlations\n",
-    "\n",
-    "2. How well does our function `montecarlopi` converge to the true value of $\\pi$ (you can use `np.pi` as a true value)? Plot the convergence as we did in [03-Numerical_error](https://github.uconn.edu/rcc02007/CompMech01-Getting-started/blob/master/notebooks/03-Numerical_error.ipynb)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Example 2: Calculate the integral of a function\n",
-    "\n",
-    "One way to calculate the integral of a function, $f(x)$, is to approximate it as a Riemann sum as such\n",
-    "\n",
-    "$I=\\int_{a}^{b}f(x) dx \\approx \\Delta x \\left(f(a)+f(a+\\Delta x)+f(a+2\\Delta x)+...+f(b)\\right))$.\n",
-    "\n",
-    "Another way to integrate this function is with a [Monte Carlo approach](https://en.wikipedia.org/wiki/Monte_Carlo_integration) [2, 3]. We can approximate the integral as such\n",
-    "\n",
-    "$I=\\int_{a}^{b}f(x) dx \\approx \\frac{1}{n}\\sum_{i=1}^n f(x_i)$. \n",
-    "\n",
-    "where $x_i$ are uniformly random values of $x$ over the interval $[a,b]$. We were actually doing this in two dimensions in Example #1 when we compared the area of the circle to the area of a square. \n",
-    "\n",
-    "Visually, this approximation can be represented by the following figure.\n",
-    "\n",
-    "![Integration approximation](../images/integrals.png)\n",
-    "\n",
-    "The figure above shows the exact integral on the left as compared to two approximations, the Riemann sum (top-right) and Monte Carlo method (bottom-right). \n",
-    "\n",
-    "The main benefit in using a Monte Carlo integration over a Riemann sum (or another non-random method e.g. trapezoidal) is that the integration converges as \n",
-    "\n",
-    "$error \\approx \\frac{1}{\\sqrt{n}}$\n",
-    "\n",
-    "independent of the number of dimensions in the formula. Non-random methods have convergence rates that depend upon the step size along each axis, so with two dimensions reducing the step size to 1/3 increases n by 4, in three dimensions its 8, in 4D its  16, and so on. We'll do an example with a 1D function to introduce the concept. \n",
-    "\n",
-    "You can even integrate functions that are not easy to evaluate, such as the [area of light shown by the bat signal](http://leios.github.io/Batman_Montecarlo)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Exercise (Discussion)\n",
-    "\n",
-    "Why does the Monte Carlo method work? Is there a benefit to random numbers as opposed to using an ordered set divided into equally-spaced intervals?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In this example, we will calculate the integral  $I=\\int_{1}^{3}f(x)dx$ where\n",
-    "\n",
-    "$I=\\int_{1}^{3}\\frac{x}{1+x^2}dx \\approx \\frac{1}{n}\\sum_{i=1}^n \\frac{x_i}{1+x_i^2}$\n",
-    "\n",
-    "Our first objective is to take random numbers between 0 and 1 and turn them into random number between 1 and 3. This process is called _scaling_ or _transforming_ our variable $x_{i}$"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "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": [
-    "ri=np.random.rand(100)\n",
-    "\n",
-    "xi=1+(3-1)*ri # scaling equation for our uniform distribution 0..1 to 1..3\n",
-    "\n",
-    "plt.hist(xi,label='x_i: our scaled var')\n",
-    "plt.hist(ri,label='r_i: our original var')\n",
-    "plt.legend();\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Exercise\n",
-    "\n",
-    "Compare the scaled histogram to the original histogram. What is similar? What is different?\n",
-    "\n",
-    "Make a scaling equation to get uniformly random numbers between 10 and 20. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Performing the integration\n",
-    "\n",
-    "If you have been doing a lot of calculus lately, you may know that \n",
-    "\n",
-    "$\\int\\frac{x}{1+x^2}dx = \\frac{\\log({x^2+1})}{2}$. \n",
-    "\n",
-    "If not, Python's [Sympy: Symbolic algebra](https://docs.sympy.org/1.5.1/modules/integrals/integrals.html) can help you jog your memory [4]. It will also give us an exact solution to judge our convergence. \n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/latex": [
-       "$\\displaystyle \\frac{\\log{\\left(x^{2} + 1 \\right)}}{2}$"
-      ],
-      "text/plain": [
-       "log(x**2 + 1)/2"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import sympy\n",
-    "\n",
-    "x=sympy.Symbol('x')\n",
-    "\n",
-    "sympy.integrate(x/(1+x**2),x)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/latex": [
-       "$\\displaystyle 0.80471895621705$"
-      ],
-      "text/plain": [
-       "0.804718956217050"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sympy.integrate(x/(1+x**2),(x,1,3)).evalf()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "So the exact integral that we are approximating is\n",
-    "\n",
-    "$I=\\frac{\\log{10}}{2}-\\frac{\\log{2}}{2}=0.80471895621705$\n",
-    "\n",
-    "_Note: We won't be using sympy for general numerical methods. It is helpful to do some algebra for us, but in general we want to use arrays so that our solutions can be scaled up and solved quicker by the computer._"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.7824846191561594\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'f(x)')"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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3Qo/izu+9EeVlprkCd4vBXZmN5J1nfRe3DtLd8iIiV+EOblK8dXiyMvu+XvBex3q1h3S8bbB6VgtQ1a9w55sbAO+FqwCISGUR+S/HE8IJ253ndnLeWpLmbdz+6G7vlqe0WEpw/BaSWG0D4ewAymdwAPICbv/9soiEnntGRBqm7ee88+1zcfu5biGjjiD71/FswWu99A6q05ZZGbcfCCe7+xxfvotIV8QwXNV5KLBSXKfwS3BHvhWB1riN+w8gO73kvIhLpAtE5ANvGRfhmghOuDo5yAJgkXeOKe0+1yrAw6r6SzaWnyVVXSgiw3BJaIWITMR9ztNwV7E9DTynqr+LyIe4Hdt3IjLdG6cH7n7H3tGM6yS8hLvY5TUR6YqryXbBNfOEXjDUBPjQu+BnKe4HUAN3HnQ/8ErQuNNxO/JXROR9b/hPYa4kDOcV3IU3E0XkXdw5jvbeslJwpyKCzcVtc7d5B2HbgN2qOoqM3YhLdm97F02sxCWOC3C3cdwTQZzZoqrHRGQQ7vzRNG873Yg7Sm6DO9AZmckscrLshUR+FD7Mi+kJETkX97uqi9uGt+PWXU5Mx3XL+K6IfIa7Snqmqs5U1U9F5HHcgecqEfkcdxtMEu5WrNbAlZx4UVE4A3D7sl7AWm9ev3plDXFNxgm4e9XBdZV4D/Ci97k34K6ubY27eC80aWSbqq4SkfuBJ4GfROR/HL+3sgbwcpgryWNpOu4zThKRWbjTBp+o6k+4uxnOAa4GOonINI7f+3sW7mKfNhw/Z3oz7j7XD71tO+0+1+q4DiIaRxqU91t5BXeA96OIfII7H3+Jt4xwd3NkuF1lsAx/vous7tXR9PcQtQJewzU97fM+1EbcBnkDXs89euL9QgMymJ/gEvYy3NHLelyyLUn4exbHefOrBTyI2zkewjVr3BRm/iMIuTc0s2GZxYtrFv6M4z0vrcX9SBsGjVMSV8v/jeO9M92K+wIVr0eSoPFP+IyZrPtw8XYiwvtcgz7D994624w7uDlhXeMu9HgCd4/bFu+zrMadIjgzzHzvw+3MjgR/ToJ6aMrkc3XBnTfbg9uhfwDUIYP7Z3EHKz9424uGxB12feIusHiD9L2AvQhUCDNu2HWX1bAMxm+Ku7Btu7fcVbij8VPDjJtCDu5zPdlxcS0EL3rr5LC3jt4g/H2gGW6v4YbhWkqewf2uUzPYVi/C7T+2ecvfiGttuJMwPWhl8RkvxtVi13vb+D7czv5Zgu5z98Zthus4YyfuoO5z3J0BI4jwdxbJcNwFgTNxF+rt97bd67PxmcLOO7vbKa7pdaz3/R4lzH4Od8vKdG+dHPK2ic9xB1klQsZNxl2EuM8bfyLu9/4T7oA3eNwT1mnI8MK4+85X4fY1v3rTFM7gs2S4XUXjuyDzPJDhsNC/tBvO8wQRGYe7H6mGhunf2BhjjD+8c7ZbcLfstfQ7Hr/l6+e5GmOMiS4ROUVE/hJSloBrdi2G6y6wwMu3j6EyxhgTE6WBDSLyBe4ahhK4uzUa4U7RZXVBaoFgydUYY0x27MXdAtUFd7FYEdz5z+eAR9R1K1jg5alzrsYYY0xeYOdcjTHGmCiz5GqMMcZEmSVXY4wxJsosuRoTRERURGLS56uI9BeRH0Rkv4hsF5EPMuhmMqPpB3jxZfY3Nsx054nIZyKywVv2LyLyqrjH/QWPd4qI9BaRN0RkhTfubhGZKSLXZBDTiExisQtbTIFlVwsbkwvk+CMZ1+AeAl0W97DyriLSVl03dFlZyPG+UEMNwD02LN1zh0XkNtxVnNtxj/TbgbtlYhDQx1v2Ym/0Wrgejv7EPRP2I9zzdC8Dxnvjhj6/Oc14TuyqMNp9NhuTZ9jVwsYEERHFPdw9pw+yDp5nfVxf3CuBVuo9Dcfr1P9b3BNB2udg/mVx/UPvA05T7+Hn3oMZtuG6iGukqn8ETTME16fsOFUd6JVVAboD4zX9IxOTcE+xqe7FPz9o2AjcQcO5qppysp/BmPzGmoWNib0BuMd9/UuDHjOnqrNxjz1rl53m4TCuwt1r+HZaYvX8Bden7I/BidWT9mCFwFNCVHWjqr6iIY9MVPds3zHe23CP7TLGhLBmYWNiL+2ZkV+GGfY57mkuHXC925yMQd7rayHlm3HNwc1EpKKqBj8o+mLvdVqEyzjivaZmMLy9iLTEdQq/HPg6JNEbU6BYcjUmC95zRQdkY5K1qjou6H0dYI+qbgkzbtojEmuHGRZJbE1wT3j5UVV/DB6mquqdcx2He9TWh7gnmDTEPXLvVY4/VzWzZSTiasfgnoQSzsMh738XkatVNdLkbUy+YsnVmKxVx51XjNQ3uISWphTHn4UZ6k/v9YQHhkfoWu81tNYKgKq+JSLbgLdwj4VMMw94Q1WPhJsuxEO4x+eNV9UlIcMW4p5U9Q2upnw67kKt+4EpItJCVZdG+mGMyS/snKsxWVDVFFWVbPx1CjebaMclIoVxDxQ/hEue4ca5Dnde93XcQcKpuAdjC+5B7pk+GFxErsY9O3kxcEvocFX9SFXfUNXfVPWgqq5S1UeB23BPSLn3JD+eMXmaJVdjYu9PMq6ZlvJed5/EfHvhLlr6SFV3hg70LpIaBUxW1bu9BLhPVefgHjp/BHgio5mLyF9xSXkF0DX4YqwIjMedn22bjWmMyTesWdiYLEThnOsvQGsRqRDmvGsd73XVSYSWdiHTCR1HeLrifuMpoQNUdbOILAeaikhhVU13T6qIXAq8A6wGumRwvjhDqnpYRPYAxbMznTH5hSVXY7JWnZydc/0GaI1LdqHNtxd4r99mJyAROd2b3zpchw/hFPFey2cwPAk4RsgVwCLSA3jXm/e5YW7jiSS+2riOMuZld1pj8gNrFjYmC1E45zoOd4vKcBEpmVbodSLRHZilqiuCyk8RkfoiUiuTsAbgfr/jVPVYBuPM9l5vEJHKwQO8c7FVgRnB03vnYP8H/I5LrBszCkBECotIcpjyMsB/vLcTMvkMxuRb1kOTMUFi0UOTN98RHO/+cCJQBuiHS7rpuj/0mqHXAL+pavUw8xJcU3NNoKaqrs1kuROAPrhzuh8CW3FX/nYF9gMdVfV7b9z6uKt/iwBveDGEWqiqH3njl8Hd2rPQ+9sMnAZchKstfwb0iPCKZGPyFWsWNiYXqOoIEVkL3AoMBQ7gOpAYrqrLszm7Drh+gKdlllg9VwEzgGuAvwJFcbcFvQU8pqrLgsatxPGm5LAd9eMuVPrI+/8A8Dyuybsbrhl4H/AT8F/gP5nUqo3J16zmaowxxkSZnXM1xhhjosySqzHGGBNlllyNMcaYKLPkaowxxkSZXS0conz58lq9enW/wzDGmDzlhx9+2KaqSVmPWTBYcg1RvXp1vv/+e7/DMMaYPEVEfvM7hnhizcLGGGNMlFlyNcYYY6LMkqsxxhgTZZZcjTHGmCiL2+QqIlVF5H0R2S0if4rIRBE5I8JpNYO/qHbGbowxxoQTl1cLi0hxYBpwCOgPKPAoMF1EzlLVfRHMZhwwOqRsZTTjNMYYY8KJy+QKXI97nFY9VV0FICKLcY/ZGgw8G8E8Nqrq3NiFaIwxxoQXr8m1BzA3LbECqOoaEZkF9CSy5GrixNGjR/nll19YuHAhixYtYvHixezatYuSJUtSqlSpdK/ly5enZcuWNG/enMKFC/sdujHGnJR4Ta4NgUlhypcCl0c4jxtF5G7cw6jnAv9Q1RlRis9kYdmyZYwaNYr58+fz008/ceDAgWxNX6xYMVq1akX79u1p164dbdq0oWTJkjGK1hhjoitek2s5YGeY8h24BzJn5b/AFOB3oBpwNzBNRLqqakroyCJyA3ADwBlnRHTNlMnAggUL+Ne//sXEiRNzNJ8DBw6QkpJCSkoKAImJiXTt2pUBAwbQs2dPihYtGoVojTEmNuLyYekichh4RlXvCyn/F3CPqmbroEBESgJLgPWq2i6zcZOTk9W6P8y+2bNn869//YtPP/007PDKlSvTtGlTmjRpQpMmTahcuTJ79+5lz549gb8///yT1atXM3PmTNasWZPhssqUKUO/fv0YOHAgycnJiEisPpYxJkIi8oOqJvsdR7yI15rrTlztNVRZwtdoM6Wqe0TkE+DanAZm0lu8eDG3334706dPP2FY9+7duemmmzj77LNJSspef94bN25k5syZzJgxg5kzZ7Jo0aLAsF27djFq1ChGjRpFgwYNGDJkCNdeey3FixfP8ecxxphoiNea6zSgcGgtU0RScDF3PIl5jgIGqmqm7YlWc43cxx9/TL9+/di/f3+gTES4/PLLuf/++2nSpEnUlrV27VreeOMNxo0bF7ZWm5SUxJ133smNN95IqVKlorZcY0xkrOaaXrx2IvEx0FpEaqYViEh1oK03LFtEpBTQDZgXpfgKNFXlmWeeoVevXoHEmpiYyDXXXMOyZct49913o5pYwT2t6KGHHmLVqlWkpKTQv3//dDXVrVu3cu+991K9enVGjBjBjh07orp8Y4zJjnituZYAFgEHgAdwnUg8ApQEzlLVvd541YBfgYdV9WGv7C6gHjCd4xc0pZV1yeqKYau5Zu7IkSPcfPPNjBkzJlBWo0YNJk+eTMOGDXM1lj179jB+/HhGjhzJ+vXr0w079dRTGTp0KPfeey9lypTJ1biMKYis5ppeXNZcvR6YOuN6VHoTeAtYA3ROS6weARJJ/zl+BhoAzwNf4u6JXQO0s1txcmbXrl1cdNFF6RJr27ZtmTdvXq4nVoCSJUty8803s2rVKl599VVq164dGLZ3716efPJJateuzQsvvMCRI0dyPT5jTMEVlzVXP1nNNbzVq1fTrVs3VqxYESi76qqrGDt2LEWKFPExsuNSU1N57733eOyxx1i6dGm6YXXr1mXkyJH06NHDri42Jgas5ppeXNZcTXzZvHkzHTp0SJdYH374Yd588824SawAhQoV4sorr2Tx4sVMmDCB6tWrB4atXLmSXr160blzZ3744Qf/gjTGFAiWXE2mUlNT6du3Lxs3bgSgSJEivPPOOzz44INxWwNMSEigT58+LF++nJEjR1K6dOnAsJSUFFq0aMHgwYPtoidjTMxYcjWZGj58eKCXJBHho48+om/fvv4GFaGiRYty9913s2rVKm6++WYSExMBd7XzmDFjqFevHuPGjcNOjRhjos2Sq8nQhx9+yMiRIwPv//nPf3LhhRf6GNHJKV++PC+88AJLly6lW7dugfJt27YxcOBAOnbseMI5WmOMyQlLriaslStX0r9//8D7iy++mOHDh/sYUc7Vq1ePyZMn8+GHH1K1atVA+YwZM2jatCnDhg1j375IHhVsjDGZs+RqTrBv3z569+7Nnj17ANeBw5tvvklCQt7fXESEXr16sXz5coYNG0ahQq4H0NTUVJ566ikaNWrEV1995XOUxpi8Lu/vLU1UqSqDBw9myZIlgLuA6YMPPqBcuXBdPeddJUqU4Mknn+THH3+kffv2gfK1a9fStWtXBg0axM6d2e7G2hhjALvP9QQF/T7Xl19+maFDhwbejx07lkGDBvkYUXQ9M+LEMlXl+0Xj+fjzv3Pg4PGEWvLUSlx28Us0PvOyQNmdYaY3xth9rqGs5moCli1bxu233x54f+211+arxJoREaFF0wEMG7qcsxpcHijfs3cT49/rzfj3evPnnj98jNAYk9dYcjUBw4YNC3QT2KxZM1588UWfI8pdJU+tyDWXv8eAPh9S6tTKgfKflk/kqZcbsmDxW3bbjjEmIvH6PFeTy77++ms++eQTwNXkXn/9dYoWzfTpfPnG7JTQkl50aNKJJb/ezdpNrwJw4OBO3v7wbyw68z16XzKaUqdWAqyZ2BgTntVcDceOHeOuu+4KvB8wYEDUHxmX1xQuVIbm9f5Du7O+onjR6oHypT9/zFMvNbBarDEmU5ZcDf/9739ZuHAhAMWKFeORRx7xOaL4UaFsF7qcvZgap90YKEurxY5/7zI2bdrkY3TGmHhlybWAO3DgQLrOIe666y6qVKniY0Tx55RCJWlW52XanfUVZUtXC5QvWfERDRs25N133/UxOmNMPLLkWsA999xzbNiwAYAKFSpw9913+xxR/KpQtgt33vgTbc4eEijbsWMHffv2pU+fPmzbtl3DjAcAACAASURBVM3H6Iwx8cSSawG2ZcsWHn/88cD7hx9+mJIlS/oYUfwrWqQkvS8ZxQ1Xf0mZ0mcEyt977z0aNWrExx9/7GN0xph4Ycm1APvnP/8Z6OLwzDPP5Nprr/U5oryjbs3zuOvGn9Kts82bN9OzZ08GDBjArl27fIzOGOM3S64F1IoVKxg9enTg/VNPPRXoZ9dEpmiRUrz66qtMmTKFypWP3xc7fvx4GjduzBdffOFjdMYYP1lyLaDuuecejh49CkDnzp25+OKLfY4o7+rWrRtLlizhyiuvDJRt2LCBCy64gJtuuom9e/f6GJ0xxg+WXAugb7/9NnBuUER4+umnERGfo8rbypUrx1tvvcX7779P+fLlA+WjRo2iSZMmzJgxw8fojDG5zdoBC6Bnnnkm8P/VV19Ns2bNfIwm70v/MIDeDB3Qng+mDGbJio8AWL16NR07dKRDm79zYedHOaXQ8Z6vrIcnY/Inq7kWMGvXrmXy5MmB93n9AejxqGSJCvS/YiL9er1B0SKlAVCUb+Y8w/+Nbs763wvuU5eMKSgsuRYwr7zySqDbvvPPP5+6dev6HFH+JCKc3eRq7rppCXVrnR8o37JtOS+82prPpj1I6tHDPkZojIklS64FyMGDB3n11VcD74Of22pio0yp07n+qs/o3e0VCp9SAoBjepSvZjzKv//TItDtpDEmf7HkWoC8++67bN++HYBq1arRrVs3nyMqGESENsmDufPGxdSs1jFQ/sfmxbRo0YJHHnkk8Kg/Y0z+YMm1AHnppZcC/994440kJib6GE3B85eyNRnSfxo9L3iOUwoVAyA1NZWHHnqINm3asGTJEp8jNMZEiyXXAmL+/Pl89913ABQpUsR6Y/JJgiTQvvVt/H3IQqqd3iZQ/sMPP3D22Wfz2GOPkZqa6mOExphosORaQATXWvv27ZvuXkyT+5L+UpehA2cwcuRIChcuDMDhw4cZPnw4rVu3tlqsMXlc3CZXEakqIu+LyG4R+VNEJorIGVlPecJ87hMRFZGZsYgzL9i6dSsTJkwIvLcLmeJDQkIid999Nz/++CMtWrQIlFst1pi8Ly6Tq4gUB6YB9YH+wNVAHWC6iJTIxnxqAsOBLbGIM68YO3Yshw+72z5atmyZbkdu/NegQQNmz57NE088YbVYY/KJeO2h6XqgJlBPVVcBiMhi4BdgMPBshPMZBbwF1CN+P2tMHT16lFGjRgXeW601fsxOAUakvStEIe7h1uu68+6kgazfOB9wtdimTZrTpcMDdG53L4USXfK1np2MiW9xWXMFegBz0xIrgKquAWYBPSOZgYhcCTQH7otJhHnElClTWLduHQDly5fniiuu8Dkik5lKSQ24edAsLu7yBIleIj167AhfpPyDf49Jtt6djMkj4rU21xCYFKZ8KXB5VhOLSFng/4BhqrqjIHdKH3wh03XXXUfRokUzGdv4ZXZK8LtCFOUezm3WgwU/D2LHnrkA/LHlJ/79n1bUrXo3R478g1NOKRaYwmqyxsSXeK25lgN2hinfAZSNYPqngJXAuEgWJiI3iMj3IvL91q1bIw4y3v388898+eWXACQkJDBkyBCfIzLZUarEmXRsNpPGtZ4lMSEtkR5j5foneXZ0U9asK7DX6BkT9+I1uQJomLIsq6Ai0h64BrhR0zrRzWpBqmNUNVlVk5OSkrIZZvx65ZVXAv93796datWq+RiNORkiidQ5/Q66JP9EUplzA+Vbt6/kpdfb88EnN3Hg4G4fIzTGhBOvyXUnrvYaqizha7TBRgNjgQ0iUkZEyuCavxO990WiG2p8Onr0aLrbb2666SYfozE5dWqxWrQ76yua1RlNocSSgfI534/iqZcbMGlSuLMoxhi/xGtyXYo77xqqAbAsi2nPBIbgknDaX1ugtff/jdELM37NmjWLTZs2AVChQgW6dOnic0Qmp0QSqHHaDZyXvJQz614SKP9zz+/06tWLv/71r/zxxx8+RmiMSROvyfVjoLV3nyoAIlIdlyQ/zmLac8P8LQKWeP+/H/1w48///ve/wP+XXXaZ9SOcjxQvWpVBfT/mb70ncGqJCoHyDz74gDPPPJMxY8Zw7NgxHyM0xsRrcv0PsBaYJCI9RaQH7urh9bhmXwBEpJqIpIrIQ2llqpoS+gfsAnZ77zfk6ifxwbFjx/jggw8C7y+/PMsLrE0eIyI0bdSHYUOX07LpoED57t27GTx4MB07dmTp0qU+RmhMwRaXyVVV9wGdcVf8vonrCGIN0FlV9waNKkAicfo5/DJr1qxA82BSUhIdOnTwOSITK8WLleOKnmP5+uuvqVWrVqB85syZNG3alPvuu4/9+/f7GKExBVPcJiVVXaeqvVW1lKqWVNVeqro2ZJy1qiqqOiKLeXVS1XaxjDeehDYJFyoUr7czm2jp3LkzP/30E/fdd1/g+05NTeWJJ56gYcOGfPrppz5HaEzBYnvdfMaahAuW2SnePyMAivGXwo9x+/VX8cEnQwL3wa5du5Zu3bpxVoO/0vOC5yhdqgpgHU8YE0txW3M1J2f27Nn8/vvvgOvusGPHjj5HZHJbpQoNuXHAN1ze/VWKFzt+R9viZe8z8qX6pMx+mqNHj/gYoTH5nyXXfMaahA24h7K3an4tw4au4Owm1wTKDx3ey5Qv7+bZ0U1JSUnxL0Bj8jnb8+Yjx44d4/33j99pZE3CBdPslOB3SVQrM57iTQay8Jeh7NnvbhPfvHUZ5557Ls0aX0n3rk9TqmRlwJqKjYkWq7nmI3PmzEnXJNypUyd/AzJxI6lMJ7qcvZBGNZ8iMeH4I5F//OltnnyxHt/Medaaio2JIkuu+Uhwk/Cll15qTcImnYSEU6hb9S66tlzB6Ul9AuWHDu9h8hd38swrZ/HFF1/4GKEx+Ycl13zCmoRNpIoXOZ2WDSYw+OqvqFC+fqB8y7YVXHDBBfTq1YvVq1f7GKExeZ8l13xi7ty5bNy4EYC//OUvnHvuuVlMYQq6OjW78Pchi7ik69MUKXz8YQCTJk2iQYMGDB8+nL1792YyB2NMRiy55hPWJGxORqHEwnQ6507uuWUlyU0HBMoPHTrEY489Rr169Rg/frz1VWxMNllyzQesSdjkVKlTK9G35+vMnTuXli1bBsp///13BgwYQIsWLfj22299jNCYvMWSaz4wb948NmxwzyMoV66cNQmbk9aqVSvmzJnDuHHjqFSpUqB8wYIFdOzYkd69e/Prr7/6GKExeYO1HeYDoU3Cp5xyio/RmLxodor3zwhwx9z9uWVgb6bPfJKUOU+TmnoQgIkTJzLpo8m0bXkL53UYHugByu6PNSY9q7nmcarKxIkTA++tSdhES5HCp3Jh50e45+afad74qkD50WNH+Hbuszz+fC1SZj/NES/xGmOOs+Sax/3888/89ttvAJQqVYrOnTv7HJHJb8qWPoMrL/svt1w7l+pVzwmUHzi4iylf3s2TL9bjzTfftIuejAliyTWPC77pv0uXLtYkbGKm2umtGDpwJlf/9T3Kl6sdKN+1ex3XXHMNZ599tnVCYYzHkmseF7wzO//8832MxBQEIkKThpdz101L6XXRC5QonhQYtnDhQi644AK6dOnCvHnzfIzSGP9Zcs3DDh06xPTp0wPvLbma3FIosTDtWt7Mfbeu4rz2D1CsWLHAsGnTptG6dWsuvfRSli5d6mOUxvjHkmseNmfOHPbv3w9ArVq1qFmzps8RmYKmaJFSXNj5EVatWsX1119PYmJiYNhHH31E48aN6d+/P2vXrvUvSGN8YMk1D7MmYRMvTjvtNMaMGcOyZcvo0+f4QwFUlTfeeIO6desydOjQQBedxuR3llzzMEuuJt7UrVuXCRMmsGDBAi666KJA+ZEjR3j55ZepVasWt912G5s2bfIxSmNiz5JrHrV161YWLFgAQGJiovXKZOJKs2bN+PTTT/n2229p27ZtoPzQoUM8//zz1KxZk7vuuoutW7f6GKUxsWPJNY/6+uuvUVUAWrduTenSpX2OyJgTtW/fnhkzZvD555+n67P4wIEDPPPMM9SoUYN77rmHLVu2+BilMdFn3R/mUdYkbPKCZ0YACHA+l1/YlUa1PuXzlIfY+Idrddm3bx8jR47k/559gTbJN9LpnLsoVbIyYF0qmrzNaq55kKpacjV5jojQoG43br/+ewb0+ZDKFc8KDDuSeoBv5z7LY/+uwUdTb2XXnxt8jNSYnLPkmgctX748cNVlmTJlSE5O9jkiYyInIjSq34s7Bv9I/ysmclqlpoFhqUcPMXP+Czz+fC2GDBnC6tWrfYzUmJNnyTUPCu3y0B6MbvKiBEmg8ZmXcscNCxjY92OqntYiMOzo0cOMHj2aOnXqcOWVV7J48WIfIzUm+yy55kHByfWCCy7wMRJjck5EaFivO7deN4/rrppKtdPbBIYdO3aMd955hyZNmtC9e3dmz57tY6TGRM6Sax5z6NAhUlJSAu+7du3qXzDGRJGIUL/2hdw8aBZDrpl2wrY9ZcoU2rZtS4cOHZgyZYo9hcfEtbhNriJSVUTeF5HdIvKniEwUkTMimK6aiEwSkd9E5ICIbBORFBG5KKtp84KZM2dy4MABwN2wX716dX8DMibKRITaNc7liy++4LvvvuOyyy5DRALDZ8yYQffu3WnUqBFjx47l0KFDPkZrTHhxebJORIoD04BDQH9AgUeB6SJylqruy2TyU4FtwAPABqAUcD3wqYj0VtWJmUwb9+wqYVMQzE4BRgAkc07jD6hdeQXTZj3JgsX/5dixVMBd2Hfddddxx+0P0K7lrbRJHkLxYmUBu43H+C9ea67XAzWBXqr6kapOAnoA1YDBmU2oqktV9VpVfVNVp3vT9sIl2oGxDjzWLLmagqhC+fr07fk699+6mo5t7qJI4ZKBYXv2bmLqtPt59P+q8uGnt7B1+y8+RmqME6/JtQcwV1VXpRWo6hpgFtAzuzNT1VRgN3AkahH6YPPmzSxcuBCAQoUK0alTJ38DMiaXlSldle7nP8UDd6yn23kjKV2ySmDY4SP7mPXdi4x8sR49evRg2rRpgV7MjMlt8ZpcGwJLwpQvBRpEMgMRSRCRQiJSSUQeBOoCL0Uxxlz31VdfBf4/55xzKFmyZCZjG5N/FStamnPb3s19t62mb6/xVK7QODBMUSZPnkyXLl1o2rQpr7/+OgcPHvQxWlMQxWtyLQfsDFO+Aygb4TxG4mqqfwDDgL6q+nV0wvOHNQkbk16hxMIkN7mGvw9ZxA1Xf8mZdbqlG7548WIGDRpE1apVuf/++1m3bp1PkZqCJl6TK7iLmEJJmLKMPAe0ALoDU4G3ReSScCOKyA0i8r2IfB+vT+mwLg+NyZiIULfmeVx75RSGDV3BTTfdRPHixQPDt23bxuOPP06NGjXo3bs306dPtyZjE1Pxmlx34mqvocoSvkZ7AlXdoKrfq+oUVb0CmAs8ncG4Y1Q1WVWTk5KSTjroWFq+fHngGZjlypWjefPmPkdkTHyqUL4eL730EuvXr+eJJ56gatWqgWHHjh1j4sSJdO7cmcaNGzNq1Cj+/PNPH6M1+VW8JteluPOuoRoAy05ynt8DtU86Ip/NnDkz8H+HDh1ITEz0MRpj4l+5cuW45557WL16NR9++CGdO3dON3zp0qXcdNNNVKlShSFDhrBo0SKfIjX5Ubwm14+B1iJSM61ARKoDbb1h2SIiCUA74NcoxZfrgpNru3btfIzEmLylUKFC9OrVi6+//jqQUEuUKBEYvnfvXkaPHk3Tpk0555xzeOONNwIdtRhzsuI1uf4HWAtMEpGeItIDmASsB0anjeT1xpQqIg8FlY0QkedFpI+IdBSRPsBnQEvgH7n6KaLIkqsxOdegQQNeeuklNm7cyAsvvECDBulvPpgzZw79+/enSpUq3HbbbSxZEu6mBWOyFrPk6t0C01xE2opIPREpHOm0Xg9MnYGVwJvAW8AaoLOq7g1eDJBI+s+xAGgEvAB8gbtq+CDQXlUn5OQz+WXjxo2sWbMGgGLFitGsWTOfIzImbytdujQ333wzS5Ys4ZtvvqFv376ccsopgeE7d+7k+eefp3HjxrRp04axY8eyd+/eTOZoTHpR7f5QRJKB64ALgaohgw+LyHfAO8BbqprpVQSqug7oncU4awm5glhVP+Ykmo7j2axZswL/t2rVisKFIz5OMcZkQkTo0KEDHTp0YMuWLbz22muMGTMmcDALMHfuXObOncsdd9xBv379GDhwIK1atUrX37ExoaJScxWRZBFJAeYDbYDJuC4MewEXAP1wPYVuA54A1ovIcBEpGo3l53fWJGxM7FWoUIF7772XVatW8eWXX3LFFVekq83u2bOHMWPG0KZNGxo2bMhTTz0VuILfmFDRahb+BlgINFTVJqp6i6q+pqqTVfUrVX1PVZ9U1cuAisANwGXA3VFafr4WXHO15GpMbCUkJHDeeefx7rvvsnHjRp5++mnq1auXbpzly5czbNgwTj/9dLp3787EiRM5fPiwTxGbeBSt5FpLVW9X1eVZjaiqB1X1XVU9GxgTpeXnW3v27An0J5yQkECbNm2ymMIYEy1JSUnceeedLF++nBkzZjBo0KB0VxofPXqUKVOm0Lt3bypXrszQoUOZN2+edVBhopNcVfWk2kZUdXM0lp+fzZ07N/BQ6LPOOotSpUr5HJExBY+I0K5dO8aOHcumTZt4/fXX6dChQ7pxduzYwcsvv0zr1q2pX78+jz76KGvXrvUnYOO7qF8tnNVDyUXEmoKzwc63GhNfTj31VAYMGMA333zDL7/8wvDhwznjjDPSjbNy5UoefPBBatSoQYcOHXjllVfYvn27TxEbP8TiVpxPROT/Qm+98W7N+Qp4LAbLzLcsuRoTv2rXrs2jjz7KmjVrmD59OgMHDjzhaVUzZszgxhtvpFKlSnTv3p0JEyawf/9+nyI2uSUWyXUI7krhuSJSD0BEugOLcY996xKDZeZLR44cYe7cuYH3bdu29TEaY0xGEhIS6NSpE6+99hqbNm3i7bff5sILLyQh4fguNjU1lSlTptCvXz8qVKjA3/72NyZPnsyhQ4d8jNzEStSTq6qOwT2NJhH4QUQmAh8B3wJNVPXbaC8zv1q4cGHgCLd69eqcfvrpPkdkjMlK8eLF6devH1OnTuX333/n+eefp1WrVunG2bdvH2+99RY9evSgYsWKDBo0iM8//5wjR474FLWJtpj00ORdNTwQl2B74TrN76uqET3RxjjWJGxM3laxYkVuueUW5s6dy6pVq3jkkUeoX79+unF2797N66+/zoUXXkjlypUZPHgwX331FampqT5FbaIhJslVRG7A1VRXAPfjuiOcIyJ59qk0fghOrtYkbEzeVqtWLR544AGWLVvGjz/+yL333kv16tXTjbN9+3bGjBlD165dqVSpEtdff73VaPOoWFwt/AHwCvAq0EpVn8B1ml8E+FFEBkZ7mfmRqlrN1Zh8SERo2rQpjz/+OKtXr2bevHn8/e9/p0qVKunG2759O6+++ioXXnghFStWZODAgUyePJmDBw/6FLnJjljUXNsBl3idShwGUNWluPOw43BJ12Rh1apVbNmyBYAyZcqc8PQOY0zeJyK0bNmSZ555hnXr1jFjxgxuu+22ExLtzp07GTduHD169CApKYkrrriCd955xx70HsdikVybqOqnoYWqekhVbwF6xGCZ+U5ok3DwVYfGmPwnISGBdu3a8dxzz7Fu3Tpmz57NHXfcQdWq6Z+BsnfvXv73v/9x5ZVXkpSUxMUXX8yYMWP4448/fIrchBOLq4Uz7a1JVT+J9jLzI2sSNqbgSuvq9Nlnn+W3335j7ty53HPPPdSpUyfdeIcPH2bq1KkMHjyY0047jVatWvHYY4+xZMkS64LRZ9F6Ks6lJzFNZRFpHY3l50eWXI0x4JqOW7VqxRNPPMHPP//MkiVLePjhh8M+13n+/PkMHz6cxo0bU6dOHe644w6+/vpre6iAD6JVc31JRBaJyBARKZfZiCLSXkTGAKuAs6K0/Hxly5YtrFy5EoDChQuTnJzsc0TGmHggIjRs2JAHH3yQBQsWsHr1ap577jnOPfdcEhMT043766+/8txzz3HeeedRvnx5Lr/8csaPHx+4lsPEVrQell4HuBN4GHhBRJYDi4CtwCGgLFATSAZK427T6aqqs6O0/Hwl+BFzLVq0oGhRe+ytMeZENWrU4LbbbuO2225jx44dTJ06lUmTJjF16lT27t0bGG/Pnj28//77vP/++4GLqC666CIuvvhizj77bLumIwai9VScfar6MFAFuArXacTZwCDgDqA7rkOJf+Oe+XquJdaMWZOwMSa7ypUrx1VXXcV7773Htm3b+Oyzz7jllluoUaNGuvFUlXnz5jFixAhatmxJpUqVuOaaa5gwYQI7duzwKfr8J1rnXHeISHNVPQJcCDyiqg1UtYyqFlXVKqraRVX/qaororHM/MySqzEmJ4oUKcIFF1zA888/z6+//srSpUt58sknad++/Qm11K1bt/Lmm2/Sr18/kpKSuO+++3yKOn+JVltACVwnEQADgKQozbfA2bdvHwsWLAi8P+ecc3yMxhiT14kIDRo0YNiwYXz77bds3bqVCRMm0L9/fypUqJBu3GPHjlGzZk2fIs1fonXO9TfgehFJS7DNRCTDE4XWeX/G5s+fH+hTtGHDhpQrl+n1YcYYky3lypWjT58+9OnTh2PHjrFgwQKmTp3Kp59+yvz587nookwfyW0iFK3k+gQwGugPKPByBuOJNzwxg+EF3rx58wL/W63VGBNLCQkJJCcnk5yczIMPPsjOnTspW7as32HlC1FJrqr6mohMxT2vdTpwK7A8GvMuaL777rvA/y1btvQxEmNMQWOJNXqiVXNFVf8A/hCR8cAnqromWvMuSObPnx/4v0WLFj5GYowx5mRFLbmmUVV76s1J2rRpExs2bACgWLFiNGzY0OeIjDHGnAy7cziOBDcJN2/enEKFon7sY4wxJhdYco0j1iRsjDH5gyXXOGIXMxljTP5gyTVOqGq65Go1V2OMybviNrmKSFUReV9EdovInyIyUUTOiGC6ZBEZIyIrRGS/iKwTkbdEpEZW0/ppzZo1gX49y5YtS61atXyOyBhjzMmKy+QqIsWBaUB9XMcUV+OevDNdREpkMXlfoCHwPHARcC/QHPheRKrGLOgcCj3fKiI+RmOMMSYn4vVy1Otxj6irp6qrAERkMfALMBh4NpNpn1TVrcEFIjILWOPN96GYRJxD1iRsjDH5R1zWXIEewNy0xArgdUoxC+iZ2YShidUr+w33bNkqUY4zaiy5GmNM/hGvybUhsCRM+VKgQXZnJiJnAhWI0y4ZU1NT+eGHHwLv7UphY4zJ2+I1uZYDdoYp3wFkq/NLESkEvIKruY7NYJwbROR7Efl+69YTKr4xt3z5cvbv3w9AlSpVqFy5cq7HYIwxJnriNbmCe3pOqJO5yudF4Bzgb6oaLmGjqmNUNVlVk5OScv9RtNYkbIwx+Uu8XtC0E1d7DVWW8DXasETkceAGoL+qfhGl2KIu+EphaxI2xpi8L16T61LceddQDYBlkcxARIbjbsO5VVXfjGJsUWc1V2OMyV/itVn4Y6C1iNRMKxCR6kBbb1imRORW4FFguKq+EKMYo+LgwYMsXrw48D45OdnHaIwxxkRDvCbX/wBrgUki0lNEegCTgPXA6LSRRKSaiKSKyENBZX2B54DPgGki0jroL9tXGsfawoULSU1NBaBu3bqUKVPG54iMMcbkVFw2C6vqPhHpDPwf8CbuQqavgdtVdW/QqAIkkv4g4UKv/ELvL9g3QKcYhX1SrEnYGGPyn7hMrgCqug7oncU4awm5glhVBwADYhVXtFlyNcaY/Cdem4ULDEuuxhiT/1hy9dHu3btZsWIFAImJiTRr1szniIwxxkSDJVcfBXd52LhxY4oVK+ZjNMYYY6LFkquPrEnYGGPyJ0uuPrKemYwxJn+y5Oojq7kaY0z+ZMnVJ5s2bWL9+vUAFCtWjIYNw/X2aIwxJi+y5OqT4Fpr8+bNKVQobm85NsYYk02WXH1iTcLGGJN/WXL1yYIFCwL/W2f9xhiTv1hy9cmPP/4Y+N86jzDGmPzFkqsPNm/ezO+//w64i5nq1avnc0TGGGOiyZKrD4JrrU2aNCExMdHHaIwxxkSbJVcfWJOwMcbkb5ZcfWDJ1Rhj8jdLrj4ITq7Nmzf3MRJjjDGxYMk1l+3evZtVq1YBUKhQIRo1auRzRMYYY6LNkmsuW7RoUeD/Bg0aUKRIER+jMcYYEwuWXHOZnW81xpj8z5JrLrPzrcYYk/9Zcs1lwd0eWs3VGGPyJ0uuuejgwYMsW7Ys8L5JkyY+RmOMMSZWLLnmoiVLlnD06FEAateuTalSpXyOyBhjTCxYcs1Fdr7VGGMKBkuuucjOtxpjTMFgyTUX2W04xhhTMFhyzSVHjx5l8eLFgfeWXI0xJv+y5JpLfv75Zw4cOABAlSpVqFChgs8RGWOMiZW4Ta4iUlVE3heR3SLyp4hMFJEzIpz2MRH5QkS2i4iKyIAYh5slO99qjDEFR1wmVxEpDkwD6gP9gauBOsB0ESkRwSxuAYoBU2IWZDbZ+VZjjCk4CvkdQAauB2oC9VR1FYCILAZ+AQYDz2YxfWlVPSYitYFrYhpphCy5GmNMwRGXNVegBzA3LbECqOoaYBbQM6uJVfVYDGPLNlW15GqMMQVIvCbXhsCSMOVLgQa5HEuOrV27ll27dgFQtmxZqlWr5nNExhhjYilek2s5YGeY8h1A2WgvTERuEJHvReT7rVu3Rnv2J9RaRSTqyzDGGBM/4jW5AmiYsphkJVUdo6rJqpqclJQU9flbk7AxxhQs8Zpcd+Jqr6HKEr5GG9csuRpjTMESr8l1Ke68a6gGwLIw5XEt+B5X67DfGGPyv3hNrh8DrUWkZlqBiFQH2nrD+q4ArwAACUdJREFU8ozNmzfzxx9/AFC8eHHq1q3rc0TGGGNiLV6T63+AtcAkEekpIj2AScB6YHTaSCJSTURSReSh4IlFpKOI/BW40CtKFpG/emW5KrhJ+KyzziIxMTG3QzDGGJPL4rITCVXdJyKdgf8D3sRdyPQ1cLuq7g0aVYBETjxI+CfQMej9UO8vbZpcY+dbjTGm4InL5AqgquuA3lmMs5YwyVJVO8Umquyz863GGFPwxGuzcL6xcOHCwP9Nmzb1MRJjjDG5xZJrDO3du5dff/0VgMTERBo1auRzRMYYY3KDJdcY+umnn1B1fWHUr1+fokWL+hyRMcaY3GDJNYaCm4SbNGniYyTGGGNykyXXGFq0aFHgf0uuxhhTcFhyjaHg5GoXMxljTMFhyTVGjh49yuLFiwPvreZqjDEFhyXXGPn111/Zv38/ABUrVqRixYo+R2SMMSa3WHKNETvfaowxBZcl1xixziOMMabgsuQaI1ZzNcaYgsuSa4xYcjXGmILLkmsMbN++nQ0bNgBQpEgR6tWr53NExhhjcpMl1xgIrrU2atSIQoXi9uFDxhhjYsCSawxYk7AxxhRsllxjwK4UNsaYgs2SawxYzdUYYwo2S65RdvjwYZYtWxZ4f9ZZZ/kYjTHGGD9Yco2yFStWcOTIEQCqV69OmTJlfI7IGGNMbrPkGmX2DFdjjDGWXKPMzrcaY4yx5Bpl9gxXY4wxllyjSFWtWdgYY4wl12j6/fff2b59OwAlS5akevXq/gZkjDHGF5Zcoyj0fGtCgq1eY4wpiGzvH0XWJGyMMQYsuUaVXSlsjDEGLLlGlV0pbIwxBiy5Rs2+fftYuXIlAAkJCTRq1MjniIwxxvglbpOriFQVkfdFZLeI/CkiE0XkjAinLSoiT4nIHyJyQETmiEiHWMa7ZMkSVBWAunXrUqxYsVguzhhjTByLy+QqIsWBaUB9oD9wNVAHmC4iJSKYxVjgeuAh4BLgD+BzEYlZW601CRtjjElTyO8AMnA9UBOop6qrAERkMfALMBh4NqMJRaQJcCUwSFVf98q+AZYCDwM9YhGwXSlsjDEmTVzWXHEJcG5aYgVQ1TXALKBnBNMeAd4NmjYVmABcICJFoh+uXSlsjDHmuHhNrg2BJWHKlwINIph2jaruDzNtYaB2zsNL79ixYyxevDjw3pKrMcYUbJJ2EU48EZHDwLOqem9I+aPAvaqaYXO2iHwBlFLV1iHl5wFfAh1UdUbIsBuAG7y39YCfcxB+eWBbDqYvaGx9ZY+tr+yx9ZU9OVlf1VQ1KZrB5GXxes4VIFzWlwimk+xOq6pjgDERxpX5wkW+V9XkaMyrILD1lT22vrLH1lf22PqKnnhtFt4JlAtTXtYblpkdmUybNtwYY4yJmXhNrktx505DNQCWRTBtDe92ntBpDwOrTpzEGGOMiZ54Ta4fA61FpGZagYhUB9p6w7Ka9hTg8qBpCwF9gC9U9VC0gw0RleblAsTWV/bY+soeW1/ZY+srSuL1gqYSwCLgAPAA7hzqI0BJ4CxV3euNVw34FXhYVR/+//buLVSzMY7j+PeXzCaUXKBQGoc7JJKkmNEMKdxMiqKUC6dCyPGCMibCKBdyJTmmJEWUQzY3YxxySJjIyFzIOEXIMP4u1trZ2HtmzFrttV77+6m3993v3rt+7661/+t51nqe/6zffxw4FbgG+Ay4mGYziROq6u0F/CiSpEVolCPXqvoJWA5sAB4CHqEpkstnCmsrwC78+3NcADwA3Ao8CxwEnGZhlSQthFGOXCVJmmSjHLlOki4NBhajJAcmubdtpvBzkmqvp2sOSVYleTLJ520Tio+TrEmy19DZxijJqUleTvJlkl+TbEryRJLtbT6jVpLn2+Py1qGzTDKLawc9NBhYjA4FzqZZUvXadn5WcDWwFbgBOA24j+YegheSePz+2z7AW8BlwErgepqVB+vaezS0DUnOAdxirgdj3kRiEux0g4FF7NWq2g8gyYU0/wA1vzOqavOsr6eTfAs8CJxMc3KnVlU9Bjw2+70k64GPgFXAXUPkmgRJ9gbWAlcCjw4cZ+J55ttNlwYDi1JV/TF0hknyj8I64432+YCFzDLBvmmffxs0xfjdAXzQnqCoI4trN10aDEg766T2+cNBU4xYkl2SLElyGHA/8CVNZyzNIcmJwPnAJUNn+b9wWribfZh7O8Zv+Wu7Rak3SQ6g6Uv8YlW9OXSeEXsdOKZ9/QnNMr6vBswzWkl2pTkBubOqujQt0SyOXLvb2QYD0n+SZE/gaeB3mrXcmt95wPHAucAPNDeAHTxkoBG7FtgdWD10kP8TR67ddGkwIO2wJLvRbO25FDipqjYNHGnUqmpmyvz1JM8BG4HrgIsGCzVC7bLBG4ELgakkU7O+PdXe5PRjVW0dJOAEc+TaTZcGA9IOaaftngSOA06vqvcHjjRRqup7mqnhQ4fOMkJLgd2Ah2kGBDMPaJaBfQccMUy0yWZx7aZLgwFpu9q1rI8ApwBnVdW6gSNNnCT70axF/3ToLCP0DrBsjgc0BXcZdhLbKW5/2MGONhjQ3yVZ1b48hWaa7hJgM7C5qqYHCzZCSe6j+RutBp75x7c3OT38d0meAt4G3qO51no4zbrN/YHjqmrDgPEmRpICVlfVTUNnmVQW147aaxZrgRU0NzK9BFxRVRuHzDVm7YE7l+mqOnkhs4xdko3AfDsL3VJVNy9cmvFLci3NDmCHAEuAL4BXgDUekzvO4tqdxVWSpJ55zVWSpJ5ZXCVJ6pnFVZKknllcJUnqmcVVkqSeWVwlSeqZxVWSpJ5ZXCVJ6pnFVZKknllcpZFKskeSj5KsbzvjzLy/MskfSS4dMp+k+bn9oTRiSY4G1gFrq+q6JPvSbEq/vqrOHDadpPlYXKWRS3IlcBewkqbH5hHAUVX19aDBJM3L4iqNXJIAzwLLaTq9rKiql4ZNJWlbvOYqjVw1Z8APAVPAuxZWafwsrtLIJdkfuIemCfhRSS4fOJKk7bC4SiPWTgk/CGwBVtAU2duTHDloMEnb5DVXacSSXAXcASyvqukkS2juHp4Cjq2qXwYNKGlOjlylkWqX4dwGrKmqaYCq2gKcAxwM3D1cOknb4shVkqSeOXKVJKlnFldJknpmcZUkqWcWV0mSemZxlSSpZxZXSZJ6ZnGVJKlnFldJknr2JyX0Vfrsz2CuAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "f= lambda x:x/(1+x**2)\n",
-    "\n",
-    "n=10\n",
-    "ri=np.random.rand(n)\n",
-    "\n",
-    "xi=1+(3-1)*ri # scaling equation for our uniform distribution 0..1 to 1..3\n",
-    "# we scaled our variable by a factor of 2 so we scale the bins accorcdingly\n",
-    "bin_scale = 3-1 \n",
-    "\n",
-    "my_I=sum(f(xi))/n*bin_scale\n",
-    "print(my_I)\n",
-    "\n",
-    "plt.bar(xi,f(xi),width=bin_scale/n,color=[0.1,0,1,0.5])\n",
-    "plt.plot(np.linspace(0,4),f(np.linspace(0,4)),color='k')\n",
-    "plt.title('Graphical illustration of Monte Carlo'+\\\n",
-    "          ' integration\\n I={:.4f}'.format(my_I))\n",
-    "plt.xlabel('x')\n",
-    "plt.ylabel('f(x)')\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def montecarlo_integrate(f,a,b,N):\n",
-    "    '''Estimate the integral of a function f(x) from a->b with N \n",
-    "    randomly chosen points\n",
-    "    Arguments\n",
-    "    ---------\n",
-    "    f: a function of the form f=lambda x: ...\n",
-    "    a: the lower bound of the integration\n",
-    "    b: the upper bound of the integration\n",
-    "    N: number of random points to produce between xi=a-b\n",
-    "    \n",
-    "    Returns\n",
-    "    -------\n",
-    "    our_I: the best prediction of the integral using N points \n",
-    "    '''\n",
-    "    ri=np.random.rand(n)\n",
-    "\n",
-    "    xi=a+(b-a)*ri # scaling equation for our uniform distribution 0..1 to 1..3\n",
-    "    # we scaled our variable by a factor of 2 so we scale the bins accorcdingly\n",
-    "    bin_scale = b-a\n",
-    "\n",
-    "    our_I=sum(f(xi))/n*bin_scale\n",
-    "    \n",
-    "    return our_I\n",
-    "    "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In the above function, we have defined a general Monte Carlo integration function. Now, we can create a for loop to try the function multiple times and get an average and standard deviation. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "mean value is     I = 0.81410075695566\n",
-      "standard deviation is 0.028138512733038436\n",
-      "actual            I = 0.80471895621705\n",
-      "error in mean       = -0.009381800738609947\n"
-     ]
-    }
-   ],
-   "source": [
-    "test_I=np.zeros(10)\n",
-    "for i in range(0,10):\n",
-    "    test_I[i]=montecarlo_integrate(f,1,3,500);\n",
-    "\n",
-    "print('mean value is     I = {}'.format(np.mean(test_I)))\n",
-    "print('standard deviation is {}'.format(np.std(test_I)))\n",
-    "print('actual            I = 0.80471895621705')\n",
-    "print('error in mean       = {}'.format(0.80471895621705-np.mean(test_I)))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "### Example 3: Determine uncertainty in failure load based on geometry uncertainty\n",
-    "\n",
-    "In this example, we know that a steel bar will break under 940 MPa tensile stress. The bar is 1 mm by 2 mm with a tolerance of 10 %. What is the range of tensile loads that can be safely applied to the beam?\n",
-    "\n",
-    "$\\sigma_{UTS}=\\frac{F_{fail}}{wh}$\n",
-    "\n",
-    "$F_{fail}=\\sigma_{UTS}wh$"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "N=10000;\n",
-    "r=np.random.rand(N,1);\n",
-    "wmean=1; # in mm\n",
-    "wmin=wmean-wmean*0.1;\n",
-    "wmax=wmean+wmean*0.1;\n",
-    "hmean=2; # in mm\n",
-    "hmin=hmean-hmean*0.1;\n",
-    "hmax=hmean+hmean*0.1;\n",
-    "\n",
-    "wrand=wmin+(wmax-wmin)*r;\n",
-    "hrand=hmin+(hmax-hmin)*r;\n",
-    "\n",
-    "uts=940; # in N/mm^2=MPa\n",
-    "\n",
-    "Ffail=uts*wrand*hrand*1e-3; # force in kN\n",
-    "plt.hist(Ffail,bins=20,)\n",
-    "plt.xlabel('failure load (kN)')\n",
-    "plt.ylabel('relative counts')\n",
-    "plt.title('Failure load is {:.2f}+/- {:.2f} kN'.format(np.mean(Ffail),np.std(Ffail)));"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "Normally, the tolerance is not a maximum/minimum specification, but instead a normal distribution that describes the standard deviation, or the 68% confidence interval.\n",
-    "\n",
-    "So instead, we should generate normally distributed dimensions."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "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": [
-    "N=10000;\n",
-    "wmean=1; # in mm\n",
-    "wstd=wmean*0.1; # standard deviation in mm\n",
-    "hmean=2; # in mm\n",
-    "hstd=hmean*0.1; # standard deviation in mm\n",
-    "\n",
-    "\n",
-    "wrand=np.random.normal(wmean,wstd,size=N);\n",
-    "hrand=np.random.normal(hmean,hstd,size=N);\n",
-    "uts=940; # in N/mm^2=MPa\n",
-    "\n",
-    "Ffail=uts*wrand*hrand*1e-3; # force in kN\n",
-    "plt.hist(Ffail,bins=20)\n",
-    "#plt.xlabel('failure load (kN)')\n",
-    "#plt.ylabel('relative counts')\n",
-    "plt.title('Failure load is {:.2f}+/- {:.2f} kN'.format(np.mean(Ffail),np.std(Ffail)));"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In this propagation of uncertainty, the final value of failure load seems to be independent of wheher the distribution is uniformly random or normally distributed. In both cases, the failure load is $\\approx 1.9 \\pm 0.25$ kN.\n",
-    "\n",
-    "The difference is much more apparent if you look at the number of occurrences that failure will occur whether the dimensions are uniformly random or normally distributed. \n",
-    "\n",
-    "For the uniformly random case, there are approximately 500 parts out of 10,000 that will fail at 1.9 kN. \n",
-    "\n",
-    "For the normally distributed case, there are approximately 1500 parts out of 10,000 that will fail at 1.9 kN. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Where does a normal distribution come from?\n",
-    "\n",
-    "\"Everybody believes in the exponential law of errors: the experimenters, because they think it can be proved by mathematics; and the mathematicians, because they believe it has been established by observation\" [5].\n",
-    "\n",
-    "In the previous example, we drew dimensions from uniformly random distributions and normally distributed random distributions. Why do we use the \"normal\" distribution to describe data with a mean and standard deviation? There are exact statistical methods to derive the normal distribution, but let's take a look at a Monte Carlo approach. \n",
-    "\n",
-    "Let's say there are 10 different independent factors that could change the dimensions of the steel bar in question e.g. which tool was used, how old the blade is, the humidity, the temperature, and the list goes on. \n",
-    "\n",
-    "Let's consider one dimension. \n",
-    "Each of these factors could change the dimensions of the part, let's use a uniform scale of -1/2-1/2.\n",
-    "If the effect is 0, the dimension is exactly as specified. If the effect is -1/2, the dimension is much smaller. Conversely, if the effect is 1/2 the dimension is much larger. Now, we use a Monte Carlo model to generate 10 effects on 10,000 parts as shown in the next block."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "factors = np.random.rand(10000,10)-1/2 # each row represents a part and each column is an effect (-1/2-1/2)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now, we have created 10,000 parts with 10 uniformly random effects between -1/2-1/2. \n",
-    "\n",
-    "We sum the effects and look at the final part distribution. The x-axis is labeled \"A.U.\" for arbitrary units, we are just assuming an effect of -1/2-1/2 for each of the 10 factors.  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'number of parts')"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "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": [
-    "dims = np.sum(factors,axis=1)\n",
-    "\n",
-    "plt.hist(dims,30)\n",
-    "plt.xlabel('effect A.U.')\n",
-    "plt.ylabel('number of parts')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now, depending upon which random numbers were generated, you should see what looks like a normal distribution. \n",
-    "\n",
-    "Normal distributions come from the assumption that we have a large (or infinite) number of uncontrollable factors that can change our desired result. In our case, ideally each factor would have an effect of 0, because then it is exactly as specified, but the reality is that we can't control most factors. As engineers, we always have to consider the uncertainty in our models and measurements. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## We learned:\n",
-    "\n",
-    "* How to generate \"random\" numbers in Python$^+$\n",
-    "* The definition of a Monte Carlo model\n",
-    "* How to calculate $\\pi$ with Monte Carlo\n",
-    "* How to take the integral of a function with Monte Carlo\n",
-    "* How to propagate uncertainty in a model with Monte Carlo\n",
-    "* **Bonus**: use Sympy to do calculus and algebra for us! *no need for Wolfram, sorry Stephen*\n",
-    "* How to generate a normal distribution using uniformly random numbers\n",
-    "\n",
-    "$^+$ Remember, the computer only generates pseudo-random numbers. For further information **and** truly random numbers  check [www.random.org](https://www.random.org/randomness/) "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "# References\n",
-    "\n",
-    "1. [Why the Monte Carlo method is so important today\n",
-    "Dirk P. Kroese, Tim Brereton *et al.* Wiley Interdisciplinary Reviews: Computational Statistics, 6, 6, 11 2014](https://onlinelibrary.wiley.com/doi/full/10.1002/wics.1314)\n",
-    "\n",
-    "2. [Wikipedia: Monte Carlo integration](https://en.wikipedia.org/wiki/Monte_Carlo_integration)\n",
-    "\n",
-    "3. [Weinzierl, S. (2000). \"Introduction to Monte Carlo methods\"](https://arxiv.org/abs/hep-ph/0006269)\n",
-    "\n",
-    "4. Meurer A, _et al._ (2017) SymPy: symbolic computing in Python. PeerJ Computer Science 3:e103 https://doi.org/10.7717/peerj-cs.103\n",
-    "\n",
-    "5. Whittaker, E. T. and Robinson, G. \"Normal Frequency Distribution.\" Ch. 8 in The Calculus of Observations: A Treatise on Numerical Mathematics, 4th ed. New York: Dover, p. 179, 1967."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Problems\n",
-    "\n",
-    "1. Calculate the area of a unit circle using the Monte Carlo integration method that we devloped in Example 2. Calculate the area of a quarter of the circle, then multiply the final result by 4. \n",
-    "\n",
-    "    _Hint: You have to create a function that describes the perimeter of the circle._\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "2. 100 steel rods are going to be used to support a 1000 kg structure. The\n",
-    "rods will buckle when the load in any rod exceeds the [critical buckling\n",
-    "load](https://en.wikipedia.org/wiki/Euler%27s_critical_load)\n",
-    "\n",
-    "    $P_{cr}=\\frac{\\pi^3 Er^4}{16L^2}$\n",
-    "\n",
-    "    where E=200e9 Pa, r=0.01 m +/-0.001 m, and L is the \n",
-    "    length of the rods supporting the structure. Create a Monte\n",
-    "    Carlo model `montecarlo_buckle` that predicts \n",
-    "    the mean and standard deviation of the buckling load for 100\n",
-    "    samples with normally distributed dimensions r and L. \n",
-    "\n",
-    "    ```python\n",
-    "    mean_buckle_load,std_buckle_load=\\\n",
-    "    montecarlo_buckle(E,r_mean,r_std,L,N=100)\n",
-    "    ```\n",
-    "\n",
-    "    a. What is the mean_buckle_load and std_buckle_load for L=5 m?\n",
-    "\n",
-    "    b. What length, L, should the beams be so that only 2.5% will \n",
-    "    reach the critical buckling load?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def montecarlo_buckle(E,r_mean,r_std,L,N=100):\n",
-    "    '''Generate N rods of length L with radii of r=r_mean+/-r_std\n",
-    "    then calculate the mean and std of the buckling loads in for the\n",
-    "    rod population holding a 1000-kg structure\n",
-    "    Arguments\n",
-    "    ---------\n",
-    "    E: Young's modulus [note: keep units consistent]\n",
-    "    r_mean: mean radius of the N rods holding the structure\n",
-    "    r_std: standard deviation of the N rods holding the structure\n",
-    "    L: length of the rods (or the height of the structure)\n",
-    "    N: number of rods holding the structure, default is N=100 rods\n",
-    "    Returns\n",
-    "    -------\n",
-    "    mean_buckle_load: mean buckling load of N rods under 1000*9.81/N-Newton load\n",
-    "    std_buckle_load: std dev buckling load of N rods under 1000*9.81/N-Newton load\n",
-    "    '''\n",
-    "    \n",
-    "    # your code here"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "3. Generate your own normal distribution using uniformly random numbers between -1/2 and 1/2. \n",
-    "\n",
-    "    a. What is the effect of changing the number of factors?\n",
-    "    \n",
-    "    b. What is the effect of changing the number of samples?\n",
-    "    \n",
-    "    *Hint: for a-b try plotting histograms of the results.*\n",
-    "    \n",
-    "    c. How would you change the mean in your generated distribution?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "celltoolbar": "Slideshow",
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/project/.ipynb_checkpoints/02_Analyze-data_project-checkpoint.ipynb b/project/.ipynb_checkpoints/02_Analyze-data_project-checkpoint.ipynb
deleted file mode 100644
index 9b149ff..0000000
--- a/project/.ipynb_checkpoints/02_Analyze-data_project-checkpoint.ipynb
+++ /dev/null
@@ -1,140 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Computational Mechanics Project #02 - Create specifications for a projectile robot\n",
-    "\n",
-    "On the first day of class, we threw $2\"\\times~2\"$ dampened paper (spitballs) at a target on the whiteboard. Now, we are going to analyze the accuracy of the class with some cool Python tools and design a robot that has the same accuracy and precision as the class, but we will have the robot move farther away from the target and use a simpler projectile i.e. a tennis ball so we don't need to worry about knuckle-ball physics. \n",
-    "\n",
-    "The goal of this project is to determine the precision of necessary components for a robot that can reproduce the class throwing distibution. We have generated pseudo random numbers using `numpy.random`, but the class target practice is an example of truly random distributions. If we repeated the exercise, there is a vanishingly small probability that we would hit the same points on the target, and there are no deterministic models that could take into account all of the factors that affected each hit on the board. \n",
-    "\n",
-    "<img src=\"../images/robot_design.png\" style=\"height: 250px;\"/>\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now, we ask ourselves some questions:\n",
-    "\n",
-    "1. How do we quantify the class accuracy and precision?\n",
-    "\n",
-    "2. If we design a robot, what design components can we control?\n",
-    "\n",
-    "3. How can we relate the controlled components to the class accuracy, and specify the component precision?\n",
-    "\n",
-    "The first question, we have some experience from our work in [02_Seeing_Stats](../notebooks/02_Seeing_Stats.ipynb). We can define the mean, standard deviation, measure the first, second, and third quartiles,  etc. \n",
-    "\n",
-    "The second question is a physical question. We cannot control the placement of the robot or the target those are chosen for us. We cannot control temperature, mechanical vibrations, etc. We *can* control the desired initial velocity. The initial velocity will have some speed and direction, and both will be subject to random noise. Once the speed and direction are set, the location on the target is determined by kinematic equations for an object in freefall, as such\n",
-    "\n",
-    "$x_{impact} = \\frac{v_x}{v_y}d + x(0)~~~~~~~~~~~~~~~~~~~~(1.a)$\n",
-    "\n",
-    "$z_{impact} = d\\left(\\frac{v_z(0)}{v_y}-\\frac{g}{2v_y^2}d\\right)+ z(0)~~~~~(1.b)$.\n",
-    "\n",
-    "Where the location of impact is at a $y$-distance of $d$ at a point on the target with coordinates $(x_{impact},~z_{impact})$, and the initial velocity is $\\bar{v}=v_x\\hat{i}+v_y\\hat{j}+v_z(0)\\hat{k}$, the object is released at an initial location $\\bar{r}(0)=x(0)\\hat{i}+0\\hat{j}+z(0)\\hat{k}$, and the only acceleration is due to gravity, $\\bar{a}=-g\\hat{k}$. Equation (1) becomes much easier to  evaluate if we assume that $v_x=0$, resulting in an evalution of the accuracy of the height of the impact, $z_{impact}$, as such\n",
-    "\n",
-    "$x_{impact} = x(0)~~~~~~~~~~~~~~~~~~~~(2.a)$\n",
-    "\n",
-    "$z_{impact} = \\frac{d}{\\cos{\\theta}}\\left(\\sin{\\theta}-\\frac{g}{2v_0^2\\cos{\\theta}}d\\right)+ z(0)~~~~~(2.b)$.\n",
-    "\n",
-    "Where $\\theta$ is the angle of the initial velocity and $v_0$ is the initial speed. Equation (2) restricts the analysis to height accuracy. You can incorporate the 2D impact analysis if you finish the 1D analysis. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The third question, is how we can relate equation (2) to the measured points of impact? For this, we can use Monte Carlo methods *(There are other methods, but Monte Carlo is one of the most straight-forward)*. Our Monte Carlo approach is as such, if we have a desired initial speed, $v_0$, and desired angle, $\\theta$, we can propagate the uncertainty of our actual speeds and angles into the $z_{impact}$ locations. Then, we can choose distributions in speed and angles that match the distributions in $z_{impact}$ locations. Here are the steps:\n",
-    "\n",
-    "1. Generate random $\\theta_i$ and $v_{0~i}$ variables\n",
-    "\n",
-    "2. Plug into eqn 2 for random $z_{impact~i}$ locations\n",
-    "\n",
-    "3. Compare to our measured $z_{impact}$ location statistics\n",
-    "\n",
-    "4. Repeat 1-3 until the predicted uncertainty matches the desired uncertainty, we can use a number of comparison metrics:\n",
-    "    \n",
-    "    - standard deviation\n",
-    "    \n",
-    "    - first, second, and third quartiles\n",
-    "    \n",
-    "    - visually, with box plots and histograms"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Project Deliverables\n",
-    "\n",
-    "1. Statistical analysis of class accuracy and precision (x- and z-locations) data is in the csv file  [../data/target_data.csv](../data/target_data.csv) _Note: if you want to see how I turned the images into data check out the jupyter notebook [process_target_practice](./process_target_practice.ipynb)\n",
-    "\n",
-    "2. A Monte Carlo model to generate impact heights based upon uncertainty in $\\theta_0$ and $v_0$. \n",
-    "\n",
-    "3. The precision required to recreate the class accuracy and precision with a robot. \n",
-    "**You must show some validation of your work**\n",
-    "\n",
-    "4. [BONUS] Repeat 2-3 taking into account the variation in $x_{impact}$ due to misalignment. \n",
-    "\n",
-    "Given constants and constraints:\n",
-    "\n",
-    "- $d=$3 m, distance to target\n",
-    "\n",
-    "- $g=$9.81 m/s$^2$, acceleration due to gravity\n",
-    "\n",
-    "- $z(0)=$0.3 m,  the initial height is 0.3 m above the bull's eye\n",
-    "\n",
-    "- 4 m/s$<v_0<$12 m/s, the initial velocity is always higher than 9 mph and less than 27 mph"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "#Import rcParams to set font styles\n",
-    "from matplotlib import rcParams\n",
-    "\n",
-    "#Set font style and size \n",
-    "rcParams['font.family'] = 'sans'\n",
-    "rcParams['font.size'] = 16\n",
-    "rcParams['lines.linewidth'] = 3"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/project/.ipynb_checkpoints/process_target_practice-checkpoint.ipynb b/project/.ipynb_checkpoints/process_target_practice-checkpoint.ipynb
deleted file mode 100644
index ce8d8be..0000000
--- a/project/.ipynb_checkpoints/process_target_practice-checkpoint.ipynb
+++ /dev/null
@@ -1,7674 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Creating quantitative data from an image\n",
-    "\n",
-    "In this _preview_ notebook, we will generate the location of board hits by clicking on an image displayed by matplotlib. We will repeat this process in the next Module_03-IVPs. \n",
-    "\n",
-    "The first step is to import the libraries we need, the new functions here are \n",
-    "\n",
-    "- `imread`: a function that creates a numpy array that can be plotted with plt.imshow\n",
-    "\n",
-    "- `%matplotlib notebook`: is a \"magic\" command that allows for an interactive matplotlib figure. There's one extra plotting step of creating a figure before plotting with `plt.figure()`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "from matplotlib.image import imread\n",
-    "import numpy as np\n",
-    "%matplotlib notebook"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Read in images target_01 and target_02\n",
-    "\n",
-    "Now we read in target_01.jpg and target_02.jpg into variables `im1` and `im2`. These are the images of the whiteboard. The black lines are perpendicular to each other and 36\" (0.9144 m) long. We'll display `im1` to start."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7fb6e71858d0>"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "im1 = imread('../data/target_01.jpg')\n",
-    "im2 = imread('../data/target_02.jpg')\n",
-    "plt.figure()\n",
-    "plt.imshow(im1)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Capture mouse clicks on the frame\n",
-    "\n",
-    "Okay! Here is where things get really interesting. Matplotlib has the ability to create [event connections](https://matplotlib.org/devdocs/users/event_handling.html?highlight=mpl_connect), that is, connect the figure canvas to user-interface events on it, like mouse clicks. \n",
-    "\n",
-    "To use this ability, you write a function with the events you want to capture, and then connect this function to the Matplotlib \"event manager\" using [`mpl_connect()`](https://matplotlib.org/devdocs/api/backend_bases_api.html#matplotlib.backend_bases.FigureCanvasBase.mpl_connect). In this case, we connect the `'button_press_event'` to the function named `onclick()`, which captures the $(x,y)$ coordinates of the mouse click on the figure. Magic!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def onclick(event):\n",
-    "    '''Capture the x,y coordinates of a mouse click on the image'''\n",
-    "    ix, iy = event.xdata, event.ydata\n",
-    "    coords.append([ix, iy]) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(3)\n",
-    "plt.imshow(im1, interpolation='nearest')\n",
-    "\n",
-    "coords = []\n",
-    "connectId = fig.canvas.mpl_connect('button_press_event', onclick)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Notice that in the previous code cell, we created an empty list named `coords`, and inside the `onclick()` function, we are appending to it the $(x,y)$ coordinates of each mouse click on the figure. After executing the cell above, you have a connection to the figure, via the user interface: try clicking with your mouse on the endpoints of the white lines of the metered panel (click on the edge of the panel to get approximately equal $x$ coordinates), then print the contents of the `coords` list below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[]"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "coords"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The $x$ coordinates are pretty close, but there is some variation due to our shaky hand (or bad eyesight), and perhaps because the metered panel is not perfectly vertical. We can cast the `coords` list to a NumPy array, then grab all the first elements of the coordinate pairs, then get the standard deviation as an indication of our error in the mouse-click captures."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Save your work to a file\n",
-    "\n",
-    "In the next two code cells, we assign the clicks that were in the list `coords` to a numpy array `hits1`. Then, we save this array to the file `hits_im1.npy`. This is a numpy-readable file that we can load back into our workspace later as `np.load('../data/hits_im1.npy')`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "hits1 = np.array(coords)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "np.save('../data/hits_im1.npy',hits1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fb6dd4a2d50>]"
-      ]
-     },
-     "execution_count": 47,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "plt.figure()\n",
-    "plt.imshow(im1)\n",
-    "\n",
-    "plt.plot(hits1[:,0],hits1[:,1],'x')\n",
-    "#plt.plot(rings[:,0],rings[:,1],'s')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Rinse and repeat\n",
-    "\n",
-    "Now we will repeat the process for `hits2` collecting the hit locations in target_02.jpg."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Capture mouse clicks on the frame\n",
-    "\n",
-    "Once again we create [event connections](https://matplotlib.org/devdocs/users/event_handling.html?highlight=mpl_connect), that is, connect the figure canvas to user-interface events on it, like mouse clicks. \n",
-    "We connect the `'button_press_event'` to the function named `onclick()`, which captures the $(x,y)$ coordinates of the mouse click on the figure. Magic!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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sQ8c5hLlXGY/PjpJwHZztV1fTUDtoMWVGAoeJQUwgI7eJ33voED3ESEFZLh3D5AGwLkB8nfxPUBBW+4awNAivRhbB25uBDAyuu/kZKYkACKRBwAj8+7PcY/akNxIFvg3owwFLrXUW9GRMGgXclIOt6OTTFsgAqjnHYy56oMGDnQBKMwHjkyAmopOOM86GHewont6ZBndAN2689RlydsGRKEDmCP64rzKSgSAptM8eC9Wim8iAs5SsPNe5y34GR23+77rXPYVKCkQN/i2IueKNkbk+CJXIXRfLBnLqT06jO/wsX5DZ0AT5J/lX+cbeB4eRT7oI3xCVBF5dLABrQYAq4iZ63MHhsihOwhOI+Rbz9NXB758PwzAdB28fnp6nKBP+j6i2EmfAIMliz5u5gtgj74QqBNYwy7AD04Ppxn9DttUzuewNaFj09G+vFR0Ug73lG+AJO/W77pffWD5NcFdOgQhcyfHw+7JHpCehE6Gt+Eh/S76MBf0023SBLm5XI1TzMbN+/fvbR/96C8tALgA4LApX9IXAODb3/7WMAxifDGkGPXu3bsjgoRxIbLBkoA+8bxQdih5CQgek/JkJAAANN0joDiUpUV5AIX+2zCgJ8eRJ8U7WKZ1pYYiEVBLg3owACDGeRegTS8WYZzeZYK2GLdAbi4UhceHgKI0HJi4MuJ6vvN+LDvod/dg4+/KR3Mv0o0ZyixA4MHMiwFQOqiJPhcA7GAYpe39D0Boy2Ou5D1CgdJiuc5zZ5gDB0Wew4kB4xNFirLuCpHI61TKM6q6EyVuy3qxyGPLlc5HDgAdxMIXDpiurz13TRGDAgcWzaY9xqK+IiM+TgdbYRgKfzO2TBmsqFLl9/GbRyd35qwMK33mkxxZQI47EYwZvtK9vBeQCL84TeBXnEAHda6AfK4cxDMHfKIrupFUxOUoItdzmZf2g79reZXIt0AfIC9oX3mxuq73R0SugBp9i/svMv+W/tBO6DnJ+VHqBGjSQY/THF2EfBIFHG3LCS5HbR/v+zvQq077BxxQ4234jWii8zS6jL7TdpcngAtyyLuRISJVkXJiedyMT9diifk4l4FTR16FPhPoczlnrPoEgDF/WnmKVZBagYJvOz8iX/ze9Y6Pm3c74NS1fPf50MFpxzKHkwih+JDnJ48nX2CjoKnTyvvl4NwdGHdM3Ha53mJuSXkSINX3Z5756AKACwC62n30754DKEUgEIiAZM5URqYwAAPclfIEXAGIQtkczM0bAmCh/CJ3ZuaTheEszxnDz3skNCcVAcHjGkJXEUEUkYRKeREAEZQZgjTAm3n0rugQxK7Y9PcwvBX2jz4I/GkjTF0DrLmiof1h0EsJpuJVrmImRqMc8j2XsUTCONxQ0B4KV3+f1iYWxomywLBfKX+lQB2/hdIiPQnAp1WcMrYoGinui9rws/NsedVEAwAPrqDx1l2RddrSpt+DYXBO7mAFw4UyB2AMo1egeoCqMuCDJpW7SGRFURh51s5/DhYxfMkLExAwN/6eDiaJ1EYEvHJTfWzDKSnAQpsHipZrk08tUQnER9SACDEbNKox74vTxWkOL/cIoYNhBxwO+HXdeYz7fM6HjBHpqciFaCknUvJJf1zGoRkG0A134YgRLSeyBQ0F2BzA0S7ROJ+PeLbkX44TNNM98LADa0UVAU0OXB1A0leXU655lB768ZuDbKcFc0S0lXcxRkCPAwposs/x4nnG5aCk98EjvgCb6ytSQhLQMSba8fkc4GrL3L1wEpQ+oUWh49qApXSV4l1Av8tvpHYoI+ZwAkPksssZtIQXGCOyplWVfFeCf8AmaUQOuNw5J3cQB2TqpwReofcrQKJ2db/spe4jv5iABPNE3wl+QMceCaSfbiPVLjooaZa51h/60DMLAC4A+Oigz58cOYBvffP2siee2ElcVZ6FGM+jLRhTPn3JEaWrZdrIYzm/3E5Oj7ajw5Pt+ia9KxRIKNbyzt0Q6HcJFREClBNJzCgoQCpGzRV1RNaEarSMW4n1sQSs95FcX7knvkTgAMMBSQCeMtQhiAKzF7Xjz5Y1UGx80ncUPYoHRZjXa6dbAUL5y1rKdAULuNQ86CfNy0kttxPJ5J3d0OC1x9iU+1I5ZQIWETWo3D/oGvOqMVpeodPFk9pdkesetUFUE8PnSt7Blc+5z2k39ChvNzzc45E2Ns842IPe9BO+3/f3w7xw+p/PzN2mPoe028EAfWEufZzQK5aRZPwuM8oc+28i1ni9aVkeejP+/t4+Rp9HvYMIhT6ZG2TLwYE7Kz4OeK/LifN65+/+W59fB3wdbEKzABFVYWCAu9Afc2PTGKvA3VXOjYMM3x08lnbLGUO+D46ng+tARxHCcFx9GVfvsA0e8b6bLTah8F50ZZ9rxrlPfuAfj/QCquETaOBRvJ3IJzvda3z0xx0E+MHnx+XNeUDfR0WG60xL4XcHqTgCagf5p83oQyyXJtnguyGH5szMPuWGDugEkMImxN+VF85vLtf5XC6942g7vzlodIDn+jP1SqbnwIO74HU3MjhofLCNDY96js08rr+xYzjK+nvfO6AxY2TD2vPPP7/90i+tJeDQqSsH8EsHgb4EfFI7uXz5EwWkTxgaho9SFRV1SSs2l0h17/m9i6kv8Zy2qwBTbrjcaKGY09vKTQSuVN3o8zueIoaWDQkoHLzQKEdTHinC342g/tYuNldyykNkbAFiy7vF08wyBbslaBB6N3AAYLy6fCaXsxV106dyZoQCAG4o/qlcMzH5QDsPaywyfijiAcJbqZyYR5WtOMyNOQBnB3HsulWZBgcv3YioTz4GN1ZuxACOPte8z+fcjQhLZXA2RsjpiFJkrHGvAXH3muGJEZmo5XzGR/oC9/lYdS1lIfPyEppVvleBDadjl0bGj9Hmd4xJ9ill6LAAvd4Tu8G1C/LqYjs5ztzbzk/wPvzrRo4xYGzo878FUPtvDwOEum/fP13v5ZkAZAB/jyIhC8zhAMRHWY6j6wQHhg6YkHH65bRmU0jMbe3SjchhOZ7uCCAT6L4Bdgrc0QbPoB/ifaUHvY9OT8ZPv/nNQQe0cvmATxxMIgfQiBxTrjs9uOZysi8KxqoDfOZ0SSfxYDvS9ueb1HHBtzeZA+m8jB6AlocHx9vBYW7+U9GqGHet3Q86jl29s1xS1+uAKX0CALXi5DoIWXOQyxxJT2eb6nsB0trV3OUmczMvozwMQFL3iLf125StmZ83QHTb2AgohpfQm/okWun91vW+ac3/VnuKpn/0o2sJOORxAcC9uviLuggA/JEf+c/bE088WUm8GYFDmbo36cqkKzaMv0qveCRodykgI3EOGhw80XmUgCsxSiToGsKP4geIhtDXJg2PPul7/C3gZEuZCCIAbwCNKi0TIOD0JCI0+ke/HTAg2BgxV4xufAE6HQgoLzAiNHuUkgPeHlU4UpzoYIsEeObCvWKn4agfZzk8CmihnFBwRJoAFvTfjYIbMhSuAyfe63MCXQNgVw09Bwjef96Fcu4Aqv8e/bFl9lFDzmrBAQDdYLmRVpseGYMn3eAKAHokzukAP8yowsxXnOBmOjXwJlE/dRWDdamSRo1G3lcHSE4Ljw45vV2mkJfB5xYRc1nSd+aJ/jM22mPOcMC4D57qER9oxPP8jt7Q88gXspJ5YemQOb/obwxyBy4AsuCfq1k2JPqnFYFK33A6Akjh3aPTk3hW90dOIIn/ladLnUA9d/8qd+47zbs8ICdOuz4vjJ3xQBd0gK77Pa6f0U3qA5FB9W1uoJi1PklbcR4AnPs4XHfBGwJ1QYubjJCybIqs9jHB56qdyCaM2EB3mNHpy6p3mDw0o7Hu2DBm77fezcYIB3GMnXvzb5UlmxsJfW5cV+sZ6hbm8wkWMy9RdsPrCObmO+9nBERaJLpHSN1RD3BtOcPod+QMAMnyse7VJpAPf3jtAg4+XQAQcXv0Ty8D8/jjTwRDk9ug7wgSuXVuiDCSgCoiZ9wTyrQS50OAbjKion8DeFVExaN8CCXKyA1QBwNZSiXBHe+Nd2pppsp4hOGoJdwAh1aAFCHUPRF1rACHnmWJGkXonhyeGwbYlTEgh7wQwKcbKgyKG7VRFudgFrx2WqAgUNxSqCx99fc/oIiPKh+mcsu6cteyM6UZMOjd0PuY3WDALw78mDvmmTZjd7gl3wN6HGCi0N3xQHF6zqU/c6qIc+XzRQRzT+kLjzoxFt7hEuTg16MaitL1iB870eVAMC5oCw26YnfQlgZSTkvy7+V9FUKfO7vZOQlvu0Ghff/EoBDpcT5gftQfjzAjAx4JwuAzFp+zDtb7eB1Iek6uy9GQ1YoADYBRaSLwAEbXDSXPAiCdDwB48InoS9+D17QxjZ2+5jT0SJaDCiKJLv8BDilEX3qG38fSqe1+h+a6J3fKzjQXlxXfHd3p5QDFdWOff9ctDq7REfscKJ8z0kpcNpDf68qr26rIsusv+r7j3BRw1qqFnhEQjFqs1xT8T5nSO91hzx24yq3LVBtoC19jewBLDuSYF8ZJXT/o6UBSPOG74r09LweTbXIYQtYSfMDJkn64fxEBiKC75HrUMzyIen8OmB3ouZzy3dM/iEaKdz72sV9eOYALAD466PMnHQDqJJDz80ygda8eIBdKWBXvtYxip2Podwy5C2IokMq5C4EtT1rv7xFGBzf6zY2RgztXit1oK5J2enpnXPbdum6M43vl8vhGlHjwMJedud8jfgKEKBdAqQNaV5gYWxSVG1Q3LqmktEQyT0nZ144bYBmfLD+hItAiZiYos1zgc0CkFKIwT6oRWCltIzcTJavn3bv3/gCOHAxicDzC6eCtGygUHwraeY1+OkADsOt+3rFjsCoqQ5QIxUxb8BZ/+/v9ffsMaS5JZ+SFeXNehb8jSlP87YDE+cdBjs8R/Y7cpgCvW2zWifdUIWjmnyVy51HvF0aY3zuwmZG1mdPVeRPe7fRw3meMPk8+bvgefuvaCicJg8icDKDRZNDb8yiKgIXzGvzJ8jfzBmgEsAACVMRZEXTmI/IGqwA0tNY9g443WxR+1jPQXW2qT4oEOlB1nnF+dXniOrzNMz6/DiKcPozJAZ235xEk5qnzIO9jrBoHm+r8GdcNMcbDLFYdsln5gTtAfBRwn6sTM3qplAqifRlZUypM0jM3kWTpldxU0oEWTr/zJwDb6dblHv513e68Aw8yn722KYAs9V2WhEkacDBB7oKWfQy7UGXO3Gb5+7q+1H04mC5XPKM2lQO46gCmNlkRwK5VH+HvkQP4trdsZ3ce26nw795jgL6j9N6I5lH3z8EVBmgovCpvEcJoRYvdCKOoUPL69GUfFB3C7YY8lYOEkMLKVoVfiroKuXZlAGgFwPE3YXyEs4MOB3bjGdv8EFFEq6DvCtmNwK6x1DkcxdR+dJdd2zEIwwgdSPUGEIRGKI4eYeA6gFCbQACADkb2GRMUGIrRjboDgc5+aldeL3XwMI4AHt4LL/gYPJqGoSXq6IAlnIXaZevjcEXLe+EBf08Hg9BJ7zxWGSErLO40RFkLAEZurEC5HeWGcYSnxVf+ftXGDENSeYWp0KDgg5tweNbBgwMDN4YeJXeauNxoTnCyxlutcLcD1zR4c0OYfnN58nEFELYNRIB36Ixc0y93HHnOAS18gNxlfbYZiWXHrm8C2WfgaVOOUwCBorUigtrwof7heMb4SiA5Fs55RhFEjnuj7IzeqaVnX9mAbjhm+tv50nUJc+C83YEifYSnAEZEcJ2XGa9HQl2PApgGiCunDz2DzKDjmK+hA66zcHgeK5kOM+1D/5CXmKBZED7vUd5rOjs+RugDP3mkLqOfAlx54gdHbvq7nJ70Re2z03vwgKU90G/nx7mEnmNyJwMQSFSx6/c+nuCLSqfSb6yAMFaXQ7cPXSb1XqU8vPjii+skEOziWgLuJveL/9s3gWgJWMtoISgVjWC3qwuaK5owQvKQBWG0G68KQneFFsoqjjDN5dkpcBlxJKTuAoSi3/X4U3NzNGkvFsvzXRB96TB+qyhMuH0AACAASURBVAKy0Vgt32kcqk2oz1CAVd3dlQR0QBmjdEjGlrB7kVe9twMsFLgrZAUkUcaeiO6KFbAVz0du0xYRwACAdXYpdPd3YIiCjnWIrMqKhPGtSCB99OgWbXXPGaPQlT58wXWUXOdKV8TME0CgK3FXhK6k/fporx0tqDkRPwOIiA6haKGR82pwl+X2xJ+kKciQVdFzDKQDA3gDpY+DNKKDyEcdFewAbgCdOqbK58PHuhORbvXgHFxAewcUXSZdpvcBRfhG7cLv/ozPMzyyw6N2LjfAUP1nridfcSrDjLQ54PXcsDwOLIv6+kkhityFjqko7NBRx3m0W+zUtSLNLifOe6JDGOnTk7ifTSPkFWocfvpORHwqzUUlZvg77lFh6JqjPg87gNKO2XNZSfDx4DnqLs/uGPLsjLTtnitOW65Xnc7uYPd3D5mpHMDeB3hP1IAH1J5vYsj5ypQdB4u8Cx5JHuN4vxx/9tM3YSXP+LI2fUpgmUf2oU9oW+/qzg3t6DeKRLMsnLzhm5ImcHXaAwyhAzRQ4IQi0X01Br3l+nAf3Rm33qHNKWsTSHL6igB2y/oIf/ddwGoiPKBKeI9TPCpURPTPjUsIZtXmo7ite/BDAdZxOWEUq5AzHqxHExy4YaBdQQM+XHgQatrDMOXfnLRQB7jvKWQqwCdPlmiMRyrdCO4qmHlGpEfE1GcXaCIgO5ti2jFS2d88yYKlK6KijAlPlqUa3Xf39CQigNqg5wDXxw+o1PNSQF62J2ipcy9rKYPxER3AUPQx0b4ru27o+M3Hg9JHOUInX9Z1Wnq0qCtyWJ1xh7GpYru0QbvOX26IAXHUPBTw0zml3D/AcAHAOBnk6nLkkzoAcoNGX4kkBH9SF43SF7Xrl/p+8ooCEFWEqy8f0m/4wQGELyXxboAatHbDAvDiGvPgAN55yJ0CB6b7wI3Lvsbv/UFOvaQM9zOfc55ziZGlwTySK52ejB5l1N8BZ/B6OXbs+mUTB7mBvAd6YuidTtpdH2OuM4HZZBXyIT1mtRtDLqOAnYEE6VA2iyjiVaCU6CNgxAEX84rM9flD/tGJruucV/jdnR0i59zHO/qJMMisloDzUIBZDQAeUEQvSmuRc83RaIc3saHDyzEFj5annryWwIxC+IzReY35zs0X89SN7IucB+Xa6vtuhQjnI/QXOhQ555g5HArmjJxHgKeWdon8T56bJZUIVjB/0BwnyfvtaUhuF9z2IVPwpK9+TCcxgbAigOskkAUAHwHq7X9k5gC+LSJXeNZdIQ/FXCdxeERgh3HtlAy1EZspLP+PdiZ4YIfdPGvVBUWAhcOyhxdaQAlBc48OwOXgxJUDbbhBdQH05TN/DmUIXWgfQ7wPZHSDShso5zkj17FpAUVCf7oxB0zF76M49VVEIMKoFLB2xaZ3kTzuCou+OUBzurtSg6YOPjAmDkT0TB+zgwQ978YooikWxXLwBzjpoNGdDwyI9yGUf5XUCXpTtqWWfQDQAGOPIDA+leIRGGdFNnhFxuwoo9iMAWDnZY3gK69V5nzkxibmP6KCFJhJw8qSnke+MWbMi4NPBw9ON+dRvjt4dyA4xl5L3i7/Tmdv02XJgce+/tCG8wN8vg/c5PszYpTHcc28XAcMApOkGASwqXQIB20hR3Y8r/6O+n1VGBy57DLuYBEQQc0/HA9F/fTO0EFV3oqIIP3kOn9H/m4BqO7oOfBDxqAPG2o8PWXwm+1C7vPSAaI7OMyBz3fcL0fWNuh51DbGUZvJxtm4BRajPZWnUiH6HEx8eJ9SryXAQw6TZxSdS6Dj+gXQn58czzZ3NTOGnvfp+hYd4Q6Fzzf8Re4zqTy7K0cT5LM7fQDjWkLvm9xcdtQmZadIF3EgiJ6gX7u6Ncm5AOC0misCOGnxyN8AgG95y1viLGAp3NixZWePSiC1lBaAq2odoRAEGqlqfn5xf2wOYTkYsIO3ibCSl6H3YIT5zSM3/ObRFD2jdwIMHVjkElEe9g2A0mc3pigZjHlXBv4MRjUMR4FPFIR71YwV79EjM7ONXIJIsJSeZnimVji0A0C1S07fUGSVqJ7nsR/EIfY3x4fbcXnGDjoAFHqnKxloT+KxGwH6q2sOFNxw4anyuxsvp6crtA5EnHEdRHRFjAHpQGDMsZyNAtEBhuvs0YARMi4CmrWRg7E52Od7AJQ6wJ6+qSTLs5/97HZ29yycpJgznRZW0UIVc6ZMEM+wVAzfcupIAoksnxHna0eeVISy0kjWkl+coVo5edDV5wdec8fD+d3By1heLmNMew4MmGfawDjDIw5UHMR1wL9rtFjandETeKVHZ5FHEuuzPmZUpozNAF5z08eJ7A/eqbItyCqyiEwRCYSfXB5wdDq9AtDZGcGd5sylgF44XOX0OriCfr7M6TIGvyMfHhVnvty59Ws+1z5frgP6eOmbX2du4j1VkJ7f0SGhhy5nPb+ICHptyIPrjKJX/UDq/h1VyRgHPOkMpW5LezCX9eeYpgOQkb+pPwPwX85lbhxQ7BE8NWmlzXKKLLPxZDdvcd+mD5cD6DPK2VR5Geicsp2pNT5OXdN/TsSR3Yo0IysZ022H2yffEHnvnnIA1y7gmNOVA/jIuG886LuAz87uDuFw5eUeFsAHJRgKK/R0HpMWyuA6a4ixZZ/j06IQswEo90Q97O3GWN/Jo+tKK4w7yYCRbJulBfJf5pnwO33x2mY9mjIFHKWWW/8xjl2JoqwxNvMoobnzzQ2iK+1UIgfDy+7gqxvzVHbzTNE8gQAgmQBdYzs9Ot4pM4EBBIh4xATl1r377plP73nym4M/lJ0btH2G1UE8z/MMytsVPEbRlXAHLYNuUggVTeQklagxVoXEXUkPw9jKxRAtjKPwLi5GPbXzi/Pt+Wc/vz35qlduJ2en203UppubEZLdMjrYQZpLaI45l3pnuQ8B7OQFzeHZnTsPbOiBvwAA8JEDazf2XSu43DjI7iAScO2OSwcXvBNngmf43Ff2ZYAvi3KrHWgMr3cDmoV756k4wYfHmYOn9znfajMHEfAOSmkDPmbFQONEZgXyFDV0IMzYiejpvfcusoQL7widUdH447Ms7cIuYiLzkluPGqO36IfrDeZaYAHgwLMBLnXmbulWZAY92p0kzyWGxg5ud8CfHKZWfcH5C9l1fojfI7qXjnGAXBVd3o6icDTjU+kXdsTqqwNGL/PDPGEjks8lGwmqOKINp4BP2vNAAjKSbV5HORnX/S5T3OvPEPkjh9j1meuS5MGkii9LM3Z4Hx055lyVG+I893TKec+4/+gwnEqXa51drOc/8pGPrTIwCwB2Nf9of88cwLePzQvdS0NB6Q1hjCvPBmYOJq3NHyjlEIgqwhqGq3YDj14WGHSFi3LzKJO8JQkHxqobIAlFComESQqDsydnsi+ggiVj3Q+wdBCHImX8WaCZXKSZb+QKAAEGaDnIQzHpHrzLCWYSXIpGIz+wdtN5QjFG35VxjxJoR5qWosKoVskKQMbledbdcwOgfvUohit2DCVKkrHRB9pC6XPdgYP3t4MiDBe8wvwwL24gvE0pcBlG+uXLM9QxDPrXC+mD8xjP6pOcJQeh8Bm783Tf1c3V9o//92e2V7/61dvR8Ukcnqw5i3vO8qSOAC+WSxmnkykSUOWGADssF+t6gCY7r9mBnYMi+q93xI5jqy/HXD3ovCR4wpgSUXAjC2hjfpz/dc35sANBeBqHC55ywOZ84zLj/OKA3seg92mZDbDk44w5qSh60KZy0q5Ug03Lh9tNOEL+DOASWkZuYBWKjvYKAEIT6MVvnCE8ZPVoLlNSbFptxL+Kzgusdhp0hzCBw+5mhQGcagepO6rwmtfco8/OM+gwaK17POfPHWvm0OUbHgMko+cGr5gOAaB5P5lvbZsSAFSOdSzVH+ZYJ29lbT2XaWQ+warAc0bWcgMJ4P9mOzs7qZIxs4QMOsnBYI4vV4UCpJYDBs/y92w7d7mjN7v+QE77KUUag8q0aCVt2pAEnvA5MqZl8ovz3IkPLxOkiDFUKhW8Th9kkxYATC5cEcCBph79CwDwzW9+8/bEE1kIGkUyhNjKmqCwtOxFvoMrLBS2vBdXujJ42lGMYOg3Ijz0HuF1RcL7EADa7wYFIcLg4enqeghZFXbm/WpH91BNHmOZhidPQUEJoAz9WYyVG2P/3ZWGG+Fd0JTL7ce1tIH3h/FxzxaD7KBG12ToLq4vYonqpuqZRQ2taynIs1iOYvkKgIURedDg7nqcrnz03fPn6BvGCwOxzxt38OGGG+OCUUVpYwxoayjNijJ04OncH+DPdlVy7849xc/Oi/E7R1uVUeb9sfvu/v2gZ7Qd+UoVyRDS43isq3neso7dE9g7rKiSCj1fXcyCzxqTzvrFCDH3PuYZzZ6RMBwJd5LIK+RaH6s7EX4P73RnYBj4MoD0BzoiE87/I9pRtAAAdbnm731jRedMQEnuWBp9IkWpG1JHkaqCQWapljHyyfuQSedZngVE9fIuOw6tlQ9x0BU6oM4M7vSFp5Ed9FZE9Q5ylUK7haGz61KAkkffnO4AJQeZvG8fL6BLHegxft5P/+CZye+zPmroyMqThR9IWSAaqDliF663md8zn5O51n0+bte3zJmif/Hv+iCcqnRAcP7zJzZ3MD7mWStDScO5eSXkz8pHIQOdfmoLoIdd6hv1ul6El92J4FmXH97PPLv9gwZ+mIHsp2j3zDPrKLiY77UE7Kr+0b77EnAeOZOJ+R2MIFQoBnkwCCfgiYhMCNGFjt+ZZ9SyC1LPuDJEEPECHXx2QKX3jFzESnpm274bFRSjCyJLdCyj6r1SOuRmsTR69+7dsXTN5gm8VcaHQkNZoMzUpp8ty4w40HBlOJYyyrN1pYgCQCkAprk++n98Usdb6cT1XK7WcUFnxycZ5RTwbUuTKEbo4wYR+og2zI0DWIwIn92YOoBB6bkx6krxAc+4olYAIzdWzk8obHcEglaVwA4/MA7a8Wgo/YO23hd4KN5Z4C2Nnpa9cule/5TvFP/sLOIAzpxxWiVCog7gpXbMz+Uyon9OXwe7atajI+4YQFN4izZcCzBmB8z7ALHPKfR0eYfPO0BH/inBQg6cv9eNcRppzxnLqPUEorVxoIx5Xp+12HRv0uBiGPwYd/G4PgFV5OFFHb89pVSYa9dFkWoCiC0ngNIu0KXLwgDPBeLgW9dByETwi21gU96uywY7mKETc+nLvu6YMm9OU5c/dIUif8yV37s7F5NzeJ+eHxFPi0aGHr682u5oV/wFZbzyeXL9Us4yfYd/OOOZgzd35SRQzKXeDt6g58lJtnVwMyslyLeKeTzMU0TUF9dtpCNAd+iqZ1y/erqSr+Rg1zxK7baRE12I7qtN3ctxcvscL6/7F21VBQcOVgjHoKpweCFp2S85lC+++PzKASyGWgDQtf0jfgcA/tiPvW07Pj7dWRolsiBG5hgbBDQ84+MUykhmtwPrVUtPv/NbBwUuMK5Y3fPz6BSChPJzYIjnqGtE9DAU7nU5IOgnZqCU3fjxfgd5ACL6iQIeERArpuptASD9/vT+VIJlJsqjcFGqAB6AWlf4bvyzZEWeYoCi47kOQH0O1Q9+J6I7DXIubYZir5213gcAiRuxbrxQyLSzz8vlGQe73SNnTuGdTlOUtXL+1GN2MPKc3iFQ5uNhLPTR++7Ai2ci0aCKlFMvExo7yIJ+Yby2OovWjuDDoDhtnFf5Hn0ug9B5zufWgay/24031/05QAHzxzjHeFu5Ih8jtANoIS+RilE7cXu/oK/TOw13AiE2aOzQogo1hzMT57POGnKAg+DDWn7N3NiZjO8lW5ynGAuy63pk0CFO20nQqjZjjOVM5Uk8E9DO8ec1ys9Abz9OTu2jV9CRDjLQHS6HHplyYNHBH0CIdBcAB2k86PSs+JBRPfiEZ935YZ59Tjyq6U7x/drYNPNns16rAB67uelvn88srJyg0flS3wGRGQWU03ATPMOmkOyblnezDVIHiBQzTvjOdyC72ZRjAQilD673Bs/b0XXcx28ONrlGcIH3Q0sHu4OXK20AW6d7Y8OZVtzuZQ7gM888s3IAVwTwERFfe6znAAZDK4fm+GR4dwAkVwwuyIA/V2wosQ7kukJxgwWIc+HjPF0MOYYQw+jLH9zj/XFwAmChn9yH0GIU9i2ppdLVMmh6oCGYVWNwLnskcWd0StYigZ4bdf3dT6+ATg4mMQr0S/SP6vuWN8L4wpBEBDBBjisbBxrTC58H3EMX5tfBGoqJd5L7luOfBsSNkhsuZzfa8DHuA3pccwDDXHkEz8Eo/Ab9fdksDHjljDltoEs8axG8GHPk9FWEqoAY9zEf0CCifRbRCPpVm9FO7QxU3zyKFnwnGlrBX+aCeeVdD5MbgCq74rs8OKiljRG1svIcDiT8e+cN52PelZsk0nDr9+CjSgGJi0cZnZHskCiv2pWcBpHgIPOzKPlCH/JM2FmXbcozBaEzgtgjd+ismXObnOigzcG7ywh6JKLHdpKR7mEjgRyuXoKGnD82qbC0Gw6WnR7S5QZ94nPufNodYHgI8Abd9bcDUZwkHEmXAeYVnlCb8Io7AtACEBYyYPKCftDGDy3NqvwL8pMb6HJOKf6fRyfmMW9BF8rExDXJQs6nO/viD5ZvO58yDmiR/dTK08zdnqB41m7VWMktJGoHP09dU+en16qY2nZaOqid/OqRzd3jI8nBRG+4LXP6Rz8ODzbV4NU9kh2qbagPCwCmLK8I4P8EDOiFoHWOLgpejAdY8ALJD1OULrQYeBQTjI6yodsd/EmIWIJ82NBcwfEdhYUy6QafMXVA5WDIFY4rXPqOgUJpQQc3pg4MeE7KjlIHeL2hFB9SUkZtYLx8Lvr7RR+Mv76fHOYGEC1Z+b8OjLqip58YN73npZdeGlFdH78bRuYbWnfjAT19zl3hM3duRJ1ffG47mHUexAD43HfjyZjhEze0KH3NB0AuIohlmOgz8xwRxjgxYB5ST80052sZSS/tI5Dn8+pz2+fIDfpYErIdtLwH2vvzDmqgPXI2jO1DTkOYjksaZgyhG12P3AAonN8wxDLYAk+6R+kIOZ9pdJOXidbkctyk927B9hzDLE0FnzE25ILcPeeVMNZVm4/nyOc6v0xHamzYqPnugBsae0TG00igE3zizwMIAYDsJu5gwWXQZYD74Ffmw3XBBMTT8exy5O24vurvcucBkBIguPLCoa02T53WZiTPSXXdGM8EcNdyfToF3v/Ji5njyXyKtpG7XEvHeV9u8MPRxgmm3AsgdOq2edSc2u3O9RxPAjQKivvcwaOZEpVtUFps2hel2yQfo1tcDyLjfs1tlTu6GhOyM3hKByzgvBYfv/DCC+souOKXBQAfhpK+iOuzDuCPbnfvPr6T8wHjIhick8vyAq+RkiBZNc6GrNM+PHkWEKk8BpQG0RwUlNqRgBCB61X6XcHo3dxHP30ZB6F3hdfBK5tQPFqUyljLC3N3Fu0OY2MRG4wg73Eg2Y3VMNy1LAiAY/z078HlkZmwjKL0Poeyvp5HbIWSUdFi6ayKvmCEUS4oS/rkHjRjcMPMe3UfO1FRxN5/ANnDAA4gyAEkkYpuGPVO6Nt/2zevzq8YEAykG3KfF8bl4NANBgbE83oGLWqzEMVu4x0NGA6eqxSJAIbsGq5lTeYSo+u823nIZWAaogn6GQegz9tyg+Qqwu/tMsZYoT/RJzeWg68tn8+XNBmDg8oEtqdjE8xMI0mAzQYCjC/zqI1OAm1j/o8OA+QJUF6X8xM6xI5xdGCDfgE0eF1AfnNHcSw711GLRBoV0SMiHzSpEliK/gWP1+lJAJ2g/dU8No73+9zzXua1bxxxxwaaRmT1qHaiV1kofqPvAFa1Cw/Ag8ih8+Q+uYNHvI9cCz12eDxBXuU0Hx4cb1c3isiRt6dl/NQfu3KXtR4TZOV3/vEO7u986/LhDknKXUamfV5TnrNPnErS+Zc5Qy9pqTl5qJUksrOzPSWF5/vc0leAMLqFOUHvD75S+gPHWxYAVB3AtQkkZ2wBQJeGR/wOAHzrW98aUZ8ODGBaCZGKVyos7UoND1GgT0IgAIjRw5jE9ZPdJWWPLjiAcCFx5URbKAIJzT6g0qN89NW9YL4DYOgvxpLzRt3T9jF7fhjvw/B6tMk9vDRq6e0OhWLJ6a4MUMauQFAKDmL1DH1kaWscYyXlV/XlOmt0cIZhoQ/Q2o0F43fFrGsdvLkSgyZ+X+9LV87+u4NVN0DOX65MHWi4seRZ+sM4cWRoD8PnICiiSFVGx2kf/aaOXOWfhqNQOWqRZ1oFYeED+gqIcsMD73VghQzAZw58HRT7/Ph8cp3n+jPensu6P5c8OwvcOt857aCfg26PUHWDBybmvThazBfz73IIcBp00o7Q2OhxFZugRn+qBNVOpLaWHHXNl4xjPGwWqXqCODLMkQCeQGV3SDhjOOSzIvBsSpEsxlJ4bSyRPMZGlToBw/mRJT7G7oDMgTP6j36FvF1knumg3zbLmPAOBxl6NmjQdjX7XPV5RVfy/iiWXnVMB38o6mc7hLcbbXLI1Jnku4zkuk5OnsgCzcHjcSzOYZQOTMCVm/USsM2IGDSh3QS382QR3euy5HQFGCZvJCUBioBvd3Sd/oBod/zdsYI/SRVAPzqt3ZYgV573rd8j/aWcCORDZWO0OvMrv/IrKwdwAcBuSh/tbweAdx9/LHI1PAICc4vhYWpC3mJQ7V7CiKBAMFaAAYQKwIYHiEFA2aDEMLoYGp7DgCJM5KP58oLf60rAFRoCiLDST3bL7fNy8/k8kSAFVOOmqGluvKAsBQoDcDMVfeXnWQkCp5l7xhgADDa0cOPoS8BEHhTRGPPRFAgcAn37vAEcfB48928o/wJFRBYcGHXaqf/wiwMgjJDe5fPobXVD4aDODSH85cDWgXj3zifQfzCJ3w0LtHd6Oa/GGKpgtB8b52CMjSMCgw4mO/By/nQaAD59rh2gQgeXCbXtAILf3Aj5cx615t0dUEJj+NDp30Er/UO+XTNN+mZdtzT8uZM087xSjtQP+uUAUG05CIOOAbIUGTzYxk7gGK+W0eos3s4zDo4E5CLX6vhkbDQRzX2DGwDL+Vigz2mWkc3j8c64t2pB0nfG1h1YT39hDnFSmE/nceiqa+f3LqL4MoCC1RHkQP3iNCHXy/qu2po9V3KA74PcJHajU8drORId1IG5jofjaDjFOhOQZf6eSl0FLSxKTP1AHwc7ebXrlzOf833HmqFNJ4/4KU/oDrXBiSJJo1mGBj2cFSOyH5l6osBEbhqBbugq5A358ygyesHlKeagivH779gYdzY7kO0yHLJ3mP10W6VdwVr2/uhHVxmYAMWrDMyjgT5/CgD4kz/1jthmjrC4stNuX5Quyg6BUCFjJf8KCLqBluCwA82BBcKHQtsX0QAUuaFG2OQpywvq4JAxSXBVysV3i04AtnvWqpQAgsvzeF8oeYxYXD+ceSw64kgJyx2k5P2UPkj3chpYFRBJgOYbTdww8R1PE0Pgf7uxR8GgwNwY5zLY3BDSgfg+sMV4ByAxA+qRHVd+HaR6VBSDGALbNkp0I89Y9B4ixoCJYehr+Z1nHZTSvoMm7zN9cEDkNOjjUzsodQcLboydR30e/R0YFW+D9zIup+GO0rfzWL1NDBnvR954VweJDsKhHZ/MF3MPUEUmMPjIhMsncugyxjWcRn0+CNpmcV7Gm7SY+Vu0Sd/13l52ZNBNGxA4OUGAq87FFl7QEjGrEDg38ALvJlLIdQE75jMAxVVGgqE39GejB9cHjeqowAB9VQpINHD92SPQ0JV56LrAnSv/Leh0k8WDob3AAqDNeYvfXZ6gQY9qMe/QDD3uoNK/K2wHALy8Fqgv8HhzFbZAupu22DQlHQrNH3S856khuUScG0W4nzQPpRJgj2ZqDE75PF4OHYqeSedWuXepm9CPXdfy26R5nXhVx43COx6IoI/oCp9rlxV/r89p2F9Fo+uf7Kyu6V0LACZRFgAc7PHoXzwC+NhjOoZq96ByomgIWBC+klPjqJqjzO+4e3YnhNyNFwpNv3tirytfV5zumXbDj1D68qvaAeh1Zan7KX3gxtDbVf9U3oYzGh3U6DePujiFAVn0HaXu4Eu/nZ7m7sXRbjXiNHIgg+J3oAStGN9QCLV840ByLAEpWlknrRwc6nimXH5xgLNrdGsnZYGrAD6XV9u//uu/hof8H5569VhOwZhgHLxfDujoJ+PHUMALGEoMKQDW54o5cO+c7843bhQcrOh7X27bBwB4pjs5zFsHRBobxqpHp+CFfXKw7xkHOQ7EOgiETk4fH6vToBvSzrtdW3SaEWV6GD9iQB3Y8v7kRwo15zJhP3s1T3RQCodyq3YLwk9AkQAC+vq80f8O7juIg0d4Ft7t+sDpAcjhmsti/HYY+11zI1Cd+av3iObSceN0iNr1y7ypPSI/gC8cwTghw37vst5lXlGwcHLkhNY6epzJWxtQ2XGLI3R9cxmRswHCDwEwszCy3oH+dZ0Dr3skLO5T1EzR2lr5iHN8bzJCpZzEOB/bSoPR/gSVuSFIoC75Kd/PEZmAsvxtHiCQtMj8PcZDbh5zhx5C/l2P7/I6u3RnPUrG3nkJOaXNPja3T86zDibpL/zoVQ5YYtdvHjiBt45PTyLIok0gCwAmFywA2DX5I/ztAFAKzBOPR+7eVW3Rr6W/WPatulh8Pzs5DcbFAIaCrHpJKLfupbkn5N4vCrAbIv7Wc0QXOuhC4SKoXXki4LzbjchO1LNyuTD+Dva4xljlbcdJI5VQQiRDfYkjyqz+nPe3g1HAku5hHv4toIRy0P0oaAd2PtbYJVzLlW7YHWg4uJNxCw+5jtdiDh2wuLH06FCnKe1iYFDC6o+fq+pgkLah0cNAzZiDmmjadh7yKFsHYa6sATZc86iqv8cNjEe2vM+8n6gAzwyDbRuJNEZfpuZdDlwcckapRQAAIABJREFUFHQQzpiRt84DPv7O911leNsPAI/KWfV+ITOZ6D+PTiQS4wBwylKWAXH5x1BCiyydNM/hdtl3cOby5O35uDQHOBOdXxhv52/o7bI+dIA2uZUDxvjpBzzU+8h7/X1+jet6B+9BHvrftO36UbCUiN/F/VyGZkyhJ67znHSnEfVQaV9jAZR4xFjvAdgq0hi0URmf2smta9qbE/wfKxzZQ9cPARDttI7uFDjQTlrmKopSBDjxw1NsstzVbrACnqPQNCWFtLI1+mypBa5vob/boe5kwqPuqLluxxnXuAksuI5n81zXE26zoAPOArVZmcsXX3xxAcASgAUAu/Z+hL/9KLiXvexl4wzC4aXWmYQAPoQghNnyBYOpY31zepe6F6XiCtwFQN99g4grxQ6c9BvAz4WmK3uUHO9xUKB7qeCOUcZD5L4OiqAFgMDfh4A7eOC9A1zEkWCVlFzeeNCvqsruKsoZjevKiOhIKtJ2HiqbFSLyN/MA/y160g73YMzUtpY+pcQceDl4QsHr0yMtbmB69A/6ulH1d8MjPm5XoK6Q6Tv9kPPCEonPCXzCnPJ3Gocs4YDBAtiQGO5j7DzBnAHwfD70mzaIKFHe6ePgij7y+7723Sj52J1PHXA4cPW+6ztyw3fu9X5kX8jDm6kDgNbJ9+lw7EZMc+cucwfg8uVbHKO8x8vMzHepDeaSMfCu5JVZc5D+IJ/OXxhM6OZ/R96YnNrKDQx+PM2SMJ60H/SvDRyDrznfvI4CZI4c6JOPGxtHjvO0DPrmn64H+1x32WSMjANn2uk9nLCDGX2Dhsji2M1+Q+HlB/UIMkIf4M3OB+N6oMEsxQ2wP4yI4GHurrk+qEMDFCDQUmvOISBHfct5mqVe3FFyhzLpl+CS2oAKQsgBR59PuzEj0dDPl4uhOY6Tg/iQ4ToqLu/LqDVt48wCtAmWIM8e7HB6+vx1GUSH+NwrFxBbqzFGDuAzH1mbQFYE0GHIo3/fXQJ+LATJPUUUHwrOozjk/Z2cnWbdplp2hPlJynVFwlFpbpgRRH32KIYDhG7EH2ZEdwSowJIbX4DGjEjMZNseLXHlgzJFiQOYJoDjjMssQuq/hz6MQ+vz2DA3/B3wuLH3CIeewcskekbEwJPVQ3mF3jiMnYlaasOwYfT8nbpz18hOz9o5y+fJAcYwPBU15Rk3ijzLb/siOrT5ICip0zQqT4f37euPG8phjGq5COU7QSBAZBbq7kaEvnS+YBxuHPV90LWiId4eCt7Bk9PFwbNf7+CQd3O/gweuuUHyuXLZcHCEXGOYH2bs0/DmisDc0TlLdyCvDm6QFwA2xlRtJI/Q3jTqtMNvRHMoLEzfuY/xsnTHdQeJ0CHGWsfHoeuoI+i01Tuoq6nfMf5EyZhbaM47xzJwLw5uu/bhFb3PnayhY7TMm0I8ImlBx4PjTfWd/J3QAj7pMhvRwTiVpqJw0kXKTLRdwN6P4azaEi5RVHS7y6o2f0SKSRU1n7zLUi2gTfIxI4QP9LPylbPtOfauK3DcWPoV+Mxcwgo91o5h52F4LyORc4ew06w7ptAkNvUcaEWrVkVqd79HAnUvG+agq9rr11yWO7DVb75K4w43R6nKMf/IRxYADD22NoG4CD3a9w4A1QrKNAFLhvyd2ZWQihELBarzDO/ngdv654DAvRwXyO4VYSQw0m5wvc19IND72AEb7blnj3FCKXi/PaKDkutA0RWng5CgxfVlnMbmRk7tEAkIr7dO6/CxOijYB0IxPtDJjbfPPJ6rH+vGM1nGIs9RHe1c3kQeZ+5qnsVOZ8mGOgKrSjDwLge3EzzMKvjMA0A45yh35wGqnI59zGpzLDsVTzLPzBG7Gp02GHR/h/MaTgaKGX5iDPoEqNEnaAUPxdiqMHMUeC7D1yXQ5yoUVu1A3MejDjycX+ifR3o8VQHZgH/gVeTOHQjf6dmXwt2gU05jGis2L+QmiA683WGBp12eHbDTXx8XO+uJPkJ/eAZAQtJ/PpugE8C3r09u3OkPPBfHxVVkPlYAVLLFAZE2t9WRbgC7AG1VLoaNHf4bz/sY4UPXIcy167IOmOPdVSNZKwUBNg9PohQXjjbvYcctS50CiEFzlVPRs1HscO4qFQZSfb7jw3RUg3YV0VQbsWHjThbvjj7WyR9EfFUwfcyfwGUEACsFJsqBKQ9QujD1QdD3aAIkn5c85UXL0yej+LN0ETuExzsLdBE1dICP/Mf8VMrNLm0pZp31BR24ezuezsF9/rvbDeSZOdd7Nc6+QuV60AMPLuN8z7ZqM2XNYRwDp2h7lQ/SBsgPf/BDKwK4AGA3N4/291gCfutbtsfu3E2PvHatuTLvCgxAMwzoQSav7hPQHsVyUIZQoCjdMLnAoYwQNPcKMRA82z1bDK8raPrpkQQJMEskbrxRAt4HB7lELaOt2AaXJS68XEHS4HIcGRb0PMxdyDsG8iCXoShvQOkdFIkDMMrGAGQxgg429D0K5coGxAllKnlwsukkBM5JdYPE7scEUlfbYeX85PFKuezHZyjp7Wokxes6Rkk007iIluRySgJjX1pxpwClO3fypTOBUu1GHJoQlXCl74DA3wF4dAW+zzjDoxgw30zibbjUOd/BiwBK6IHx0XMOcH0OuBe+9r8dqDmg5Lp/6nfo7w6D2lP/+M1lIfjlaBr/zvsDMNRybN6ffKHzWZGfro14DiMLnwDYnabd0HadkPM+C/M6v0MT9IkbaO87Z/Uifx4BdIDCOBygedsOfn3+dV3yqXs9xcTHzT1EfeDToXt0Ipj0w01FSAvIscnD+wbQC9oQ3Yvj1m6260tVp54VC+CRyN+utuW0xorN/XvpoOU6a0Y968hCzUPcI0CHQyM8umWEDz0Uc1l6Yjje0dmsSkDRZ+SOfMDU7fd3duUyt8zrLl+lw6o+KTLG0vDU87u1A93xgta+EcOdUHcseM7rxjofex890EDOn67Be+7MsJqDDKFrkAmXZWh7//Jie+ZDH14AcAHArmIf7W8A4Nve9rbIvQmDVTt7JXQCKSiJAaQqAjgYVAejR2x/5v8hhOG51JmGroy7UXYj7gbfDaMbapS0e3/ds3OF5OAPZT6Wf8rzd6OPgHufMUSebIzXFkZQnu/x8XZ+PwEciiFifje5zMg4XRlhUHz5al9UjfYAYfzNeJxWDhhVHgMFHcY/Tk54sCAtB90neNIOufKYKw9lKqTryJeKfBqZh6vdJVQHpCzTkFc3ogp2Dq33lTlWH3aizhSerTpiDtwHnY2+GBsHjR1AdomBp5z/MN4AStqgz/ok2ur3OADdp8j53SPOw/BXPie8zbscYPA8AAZ+6YCP34mOJE0z2jUdhop21ZJfAsDdZV7AKjKTfctdlPOsXqK7s1zKvnmC7i4P7ry4cea7n8kbRpTCi9UYso98ubw7YAu+qqXQ4Js60cMjeg5AnebQzPkGmYWv3XkBZLuuCx5TgWQ7tQNA7nM5+H+bZyzrPpZxoy/h0FlZlEj3SDCOLgueqk0QAQIlrhVN2wFXnGRS4DqisbFWkW05KA7wVwAx6BMFn+eqgvMxu3qp7Yhe7Q6t65bc+JH1VnEqOzja5efdclzwputHUhuS1rkKorb1349zc13qu3Fd3ue8cjawagpmmRv4BbDoTrDe6Y4YNM3Aw52dM+ZTFHNJm3frWQHAFQFMCVxLwN2CPcLfAwD+2Nsj6R9BHIZD8Z3DeVZnMHAdS+NAiufCq6llCl27uLqM7esoYZRhAMaHnNPoOTYoXQwPCteXs/Z5bkQ16KMbGMjkCtq9Ln53I4vSdCM/geA0ph4pGu+u6vaMhR1zKCi1DahDKXTg4oowDEGBBI96dqAQdQA5jaAM/mUkf+dRTCgXtRW0OOB4pMwxkmGPHMIyIBqbpk0KU4qdXZoZjWGJkzqHuZTh/xx0MP+upLnX54xrjHe+J8GGR18xCslXU4HyzMz9oU7jTFdwkOB98lw675fzwWx/1yDruhvbTgt3AhxoeHRhHz9wDYDIPCKDgCGPKLn8uSzsGPYC3Yrk3bmj48UqZ7WOwEJe9ZkrAIq6UOttbuRgLG7suOY8qqib94uTNtwx8/Nz6Xe0G7gjl2Q7DyE70MP5PK6ZQ8PzuhZGW8Kpf0fprMFT7rgwLueBDg593h4AjoqqxzmNdWycVUvo7yF/b8ypwGs52kSQaB9aSv86YHHZoW6rrnHd+9ffD89O/Zj91rsU5UOOOT8b3UQaAXPAffGcHQHjc5q6MyO7REWZS86R5n5knzHT7uiPRYizBJbKE6Vj3vVSnyvuwenRsqtqy+6bY5dbxgp/oNMdlKNDegDAZSvHlCswAtYEUNSuxvD+979/RQAXAHRz8ujfAYA/9uM/GXkfriydcd3o7BR9VhHoytcSg8aS5WXt6jrOwqAIBsBupy07JJz3oYTI0/LRoZCpnQUwciHmuytoFATv8NB/b9+NFX1xsAs47tENV8TcEzk1l+fbiRRPGVLRJ+hctkb3juhfJX9j3N0AETHpwNOVYiidqlMGCGZ8DpRRrBxlpTYAHtAqrm0JDLk/+zmP3CJSlHTV8vLMNcpE7nluq5f+wKBQqHpXkeb7VIMQQ+XGfBr4dCz0ry8TOghiLub8JIBmzBmtzWVF2u608rndB1CHUSzj5vzI+5mHDsD8XRgC52GfP97j7Y8NPrZJxg2MGyKML/wFj0w+T3pmZDKBMrSkb7RBnpbLIEaWe4lwOv3cmaJ9jYdqAMELrQD5iLRFStruzlXn105LjkN0IOk6bo6lTqyhmHSNW5FHeIJ5Zw780w2782Muh5YOjNj7zEMTCHRdAt3j8/AkSrcE3WoTR8yp4pfXCZxjZUbSzvnS1VcBREX7mFsHWc6n6BN0okcgnQ9j/OX0KyKI3vPI1FFtTlF/MucvZdN1pAOvnMOs9ei61WlKtQZ3NCZvsuFjam+ihhEhruVkObsO3FiZgU+I8IvXtcnDednBZdc/g+ZVGsnHqrbF43ovp0tJFaL3u0x0x33oB9uBTsqVjoP78IfXEnDwydoEMpn/Ub8NAPgTPz6YFePiylnM61E1vsfupDI89CG8TDso242Bf9c9vuzpQAYh9uUM312HYsErQnDxAInccJ8LsANDjFsHi250USBTseSSp4MFlKeDXPeyoSmCTPtSrKKhzlCWwmd5yMEJijNBUeZnOTDl3fsULsrd56gvAXHKwQRWCaj0T/3N3M65FOFALulQFs4OWHcAgUEk8jiXgeZuv6QH0YU0allXbi5XdjBOjqWDC+gMwPHaW/DAnLfMzcmCwzMaiBHS2JRb5Mv5+2hEu/AEf/vyrvoDjzKfXNsHLBhrBxn629/jhnq+I+cE+XIawge9/ezD3HnJffQVuXLA5DLYQW4Hjb3f6pN24sb4OKrNTvOIM3OVowYAE6aRUa9nutGETtCS6Bj9dhAEjzA/Gocv3XZd4XpwGGdbFnW+RG7V9pDHg3KYMmw5AKzr2WijwpEeAY13F+Bjrn3s8GO8t3QxZVF0DZDnIMjnVtfhG59blxXa0WfXwQ7mHUDmSsH9qINaB/vGXHvEPp3F6WB0J27Yk1pJYAwTkOfZwp234Fk5lxzzpmvoHRwi1/EcCdftgOtWRQIfe+yxnR3YvNuXttHPbi+jnMueEml+D/Puc8YqFbyiPnzoQ2sTSMj7AoCw8KN/OgBUmBtjrU+ieQ7MXIjw8qhMT14Lno4rZTcQbnzcwKGseQeKGS/t4YI+d5+idN1QO0BwJYoiRSFg0FDiXVG6wnZFQb9oe5/RHgZGSqCWf3YAjHY1bpm/Q4V/vQMj5V56jPFqizIRAB2nL8YXhe7K342b07MrPt7N8VqjLS3bXWc9Ngci1IBj6Uxte+QQ2jlYhGsnvT0vbSaVwxdTsecSiQPZnO9Z/zDbnlEInpXRSR6J2RqC4+eO0tekaW5ccRnYx4cOPFHgDvYB7pMOM61i19hm4j7X4Od8f0ZUHQCQp6nr5B3Fw3UcmkfxR4T3+Gi7PFe+6ulOlKbzC3zk8sM9yLD3D2Lu9i9lEz5VRISk+C4nvjTrdHI+cfntgMWdPZ6hn/TJ5wkd0Vc6AJHwnfeT8Y4dunVObtxbS7vx28HcNMVcnhyfDYc3eOio+HWbR0zGvXXuLjwXTqH4u4otU4w5xibQXEXFyQmMv7XpSysBOgqvjuX05U+XR/EQf/foLHTkHbOtLKEUrPZATcisZTrr9eVmDejocuy8ga7LdxJE4ISQqevQy/RtX/Sfd7leZO70m+fK6nkv1wIQCyflMuslug51vnPZcLvhfQsanWSqxNj4Vbmn8CefvBMdQ24hS+IvvfTC9qEPPbOWgBcAhMW+tE8A4E/8xE9squfnxhYFhBcSnmItB4YQHOYuQym88CRrR1nsLhsJ5SlEPTKGIZDXGsfE3c+kXyW5ntaB7EShUE4IGF6Tjxzj9qCXmIYW4e/A0JWSK5ZuOLpB4d7eJ9/968p0GA5FUo+PRsRhKG8pvCiJoCWWy1gyhv4AigFCatkHZTH6XaUDXEGhADGA+vTzVPcZWjf8EXUpJYghiyXmOg2Bshi0T8QmFBh5Wiohcz2XXWnH56JzcQdcPENkF9AO/fS37+CGJoO+VTqkg0LqknWAkHxEBCENGpES+oYhY358ntygumfv4/TxJ69kUrrPH8tatEdb0JlIl+g7j1jT7uybOBvXZWUkppe/RP7bPscn+qD0jsr/pB14p8umfvdoiUfFyPVjLhi3O3rQBUcJedlHU5dxf24u5yV4cOOPQQVwOH+4DHRHqjuuHPcmEMZceJvok6BpATwHHIAAeBU6cioHO1o9RcX11wCFsTM3N5rBm+RqwxNDZ1V5kanTCmKVjk6dP4EktGKe9Im8UelBpVp4xp3Q3Yg9x7xROmg6tO4kwBc4Sf5eZAwaIx/wo97tET1o1Y9T87lyGUTWAMd63kEfMu/OEfyH3Pgqyz7nwfnV5dt5mz65DDm4vHf/PPTb/Xvn2wc+8IEFABcA/NKAH08DAH/8J94RCksbQRACFBdCpgiVFOD9i3upeK4zbwegg3KgUCnM7t4V+SzHJ3ncmc7hBQzqPXdO70Z7XFf+XByr8+JL8W79IzfEFa8fa+RGH+HkU/dxrys1RT8lfDpqR/f6Uqv6qaVA9U/3OdhEWXiUMo1ALi0qZK/xAdbU9ycef1lc58QDRfJEc43ZQYH68Pzzz293zh7bWcpBQQdYlKGvXdnqAzTCsNw7fzHGgkEBAFJCRv3CiDBOnADdE3QrcN53SmJkI6JT55NiwPV+gKQrUT3j3rfaJ6pAP1CM5M/oOvR1Dxljm8o9QZofOaUlZF1jrBgT+MON7I0cm0pd4Nxkz7XkvShl5gDPvCtzolwsHwOQxF+aI9FEETj10cedBn6e3YycXl7nyQQ4U8io+hP9vLzIHLrL85gLn2/KbmhzQIKd3JkfbWiTT2z+yd3Meg4egb4AU8mi/infC9AUMhgbE9KxCb6rgvAaY44zT6bwUxjSQKdzeHIyI2OK0Hq5DbWvv2kH+VCf7t+/txOdCXCqlYtB33So+CcZJiWAUx30m+5RPyTbF1d5WgWObqRnnKhcU5XtOciTPc7OcqeqzmhVW9AuQUGVL7q43B5//PFI7dC8S4/pLNfTE525ng6zaCOdqLboA/yJPtV9WnpEL77iFa8YekHtPvHky7fnnntuAJenXvmqeJ/m8bkXvrC9/OUvj/w20jl0RvkLL6T+0Tv0XrWvvuma5ha51G/6T5TMnWTuA9RCS9FAuuyJJ54Yp+0kiFSOcPIIoFXv59g09ZMd9fqMk6mur2Ms6hegT8++8pWvDBCErkZHkEeafUte4kxp9L7bjcxhzlNJOIlE49W86dksL3MY78cG6J3UIMUhEkBDl4p3gr/PToccXl1kJFH/dC8yEbKkd49c5jweU31AttCP6pPm+YPvXwAwdNNaAh667ZG/AAB/8Ad/cLtz9/GxnV0MfPfOnWEYJHRntUuYkyzOleNhtd/0HUNIh0JxVEmUVMbpDR6fJJiTcoThJUxSwmL+8JCvD7bLi4tSPgnKcgeqDNzuGbuKGmrHMZ4ly2+cRuKeKYokgMFhFj6NVTdFqaoGIoYjFHSVTkAhBXA8OQ4jgfGOEgBEVioaAtjRPaHMt4Pt8Sdelkbg9DSeDQB5uMW4PUqqCIN7t/p+cpoGEwAcXut2uN05OwkFLrAopQc4ScCT7Wj8EVXR0vHJceQcYhAienaWYBygItrHe+7kEWt+0H3Q5iaXTaJdnYVcOyZ5f4ztKouDo+wxvrxjRDauZn5O9j0jGxiL0ScVww2DmxsBAKoJmtKovPTS+fbEE4+HUj87vRtKm2T7s+Oqy2Z5ZPCpAzuPeOYEZ62xy6v7I5p8eZHLx//tv/3D9p/+09fE+GXIBMACpBWoyrEXuLjI81jDkF+obMTd+I1IQgCNG0VcrwPEAHyCd68yQu7/icyIDpfXVWj35nr7v/7PP97+1//tf4+IcvB6lQsRmIE3MOySG4D6AO0nOWfibwxRyhU8keCH3ZqhA65zcwBRJiK1wQfXbK6Zp1oQ8dR9UTuzgJjyxdQGkU8BLNF6ni+bvMfca34xzp7wH1Gp64MAdAFmquqAALd4n80Mkhb4E16YQOl0J99L7zw/f2k4gurjnZNcRg/Zvb7cnn/uhaCTeAHAOTYzXF8lsLiXPAIf69mX7p+PItNVP3k7qLIuAHjxTICY83RsBIzElzgG6t/nPve5AE76JPKKXtandPiLL7wwQJVAmpxR6ePPfOYz26te9argT7Wr/wIcGieAR38/9dRToRv07wuffzbGL1CKDH3h888HQNPfgF7Jzv3zy0hbicBA/XZR5VPunZ/X81WIXc7b9cH2heefi7kWLQUQX3z+he2xx+9EqS14RHoL3aLvqmcrvsHhQ5fjrOn9ai/6cZ0rUHpe4wh9kVKynV/ci99E3wgMHKa+Y6WLOdScSo5EEwCs+iyaqT8s+6ot0UNtxdnZAsJVDujg5jrul/6KIMVZ2gc5pdBV71N/f+EXfmFFABcARF19aZ8AwJ//uXdur3nNa4LZ/vmf/3kYYAELMbUY+cknnyyQcRTfxZC69z/8L1+xPfvss6HcJEDydp569Su3ey/dD4MohfQv//2/b0899Zos2vnSvRACtYFwSTj022c/+9kQEi0F6516VuBI7QOIiMLJeL76Va/Z/uVf/iUEM4T0OJVxKGBFNCS0xwclXC+FUpEiQQHoM5TbdYKVI216qMR/vHq8PCJsLAdg7Nj5pneG974JUJ1tUm4BBo5OdxQDZQUUSQ2AWbXtAICxdHcyz/Mk2hKGXjvsrBaevqt0hT6l6EQb9ZuICTWv6PPF9U2AxeuLWQoFww/Iw7N34Kg5DXBP4dgCfKr4L6OtyFuCgjSoMqyaE80h3m5Gj+WRZ4mNAI/yiM/Pt8cfe2wsTdN3QMGM+uTyDFE9IrFSpGHczs7CmGFY1R/xD3Ot6wH2bZlH6Ej4I/pYO9aJhJ6e5ekEpydnwffwtxwajSHH91KVrKjSOgXS1LdwaB5LJ+r8XhrvcKzuJjD1cQIixHtEbKOvlbN4cT/H/fInn4i+EJHRmBinHAvARtJ2d5f0dYH2Q12vVAA9f3R8uKl9oscOLEMGTtL5urzYBV44fyenikCmQ+CRxAGKL9JpUZBDY3/xpXsR8bi5UVmLjNABjJmbqDNnZVJw2nDk1EdAJvyhexyEwnfBk3VyCyBAxYyRJ33+678+G7tS/+N//Mp4r4DR5z//7EgrgNcADR49dnmEt3GavI84tvCgA049J1lJWiQYiR36JSvBK7UhhuuP37kb/A7tzs/TwYgd1AKlVX4LAMGO/ywKn8CCmoicq0uf0CeSa5w4cRQ7ZVVeSgD1fgEU5srngEg3EcF5xrOiqhlR8zO8A/gUaFJ7GptkLsZSDixRUaJi6BEif6zc6HnAHXRFXwNwdU9EfS8uRtkZ3UOUnSiq9Hssv17cyzPSzx7LfL6o7nC2PfHyxwOQ6YQUgX/1mXZ0X9i//+efQ+/Krulv7eZVwEJ8pnkYduhK0eJcCWJe08F5adjKd797AcDQ8SsC+KWBPz0NAPyF9/z8dvfu49EgCgql6+F/PCSWiojeueJXxETCIua/e5rFMXX4eoCjWp6S6glPW8so8p5rWUBZR+HdH8ydxAjCAFwVLpfw6T0YY7VBJIpEad5D0naalTgeYye3jRMvbqptDAnGJYyITr2wxGAUcvxWyjT6ev8qvG/9jncuWuSyVxpJvFLACtd0P8rLgSHeJvdHRFBGuVWZ5z4MJYoZAEhfXdFndCcBnBtNIm8YPwyJPqWQobW8eaEoveO0igxfF0ilbX+fDP9Wx3DpuhQnUWXAbtxfh74LsEB3AAJRH4wT44Jn9fekhYDBzAWFrhkhmJsxiASNaGko9Jn7F/wbIDGVM8tTAv6AIacRQMrnFAPp73ApZnMN/Cci5FwmUGIZLb+LH9NRmAAqASFLeREJq00CFOsV4NVyLXSgTz7PhwL1tZQJjT2SGHxySWQvl7YYk8950K9qUDoP+nnYN8U7AqwChjt8VSCQa84fyOYAOHW6CY4bESB+9/FG5LFAJrwvww2toAVACL5iDPt00g7vFgAhYgsfOW1ow69N4DU3tjlvowMZkztp+s5coicYD7LMuJEn3q330pZHwFUHVL/FfZSvkvNwXeWhrFRJjj91CbRw/ps8n7VIk8Yl6FYYnmcBd6472JXPO7L/1D2cud7o0z733bmccnQUjjrzCx3lbN19LKOAgDTmEuf96jJrYOrviPZVSg/pTjEXh6lH0PvdadDzCWLPww6/8EJGPgUokT/9LVD8Mz/7zhUBXADQzcajfwcAvufd7wzGc6XowuFCyHcULEoJI4gikgeKwonD1C8uAxi5V8yzKDmAC0qgGykUFUrJFSJKmn5JYKOAZ9X2kreraBlKibZ8PCiUrvI8AAAgAElEQVQOQGXkgNSSGEqV5Hk3CvnOuauU/tMXFIqDD5SGvOpUvrk8gvGBJl2J+VwwfgeQKH3AH0bFFbMraOacefP7UHYYMn/fADuR8K6zP6cB8vFzlBT9Yu4E/snPC16LfLAscxN0KxCp5TvoyBw4jRgfOU2d9tMws8sY8DRL+QAmhgNhZ1qPcZaS199EN1l6cr5k3pAfB6k+d52mPOfz0Hma53383O9aoAN+l6shtwVkoxRRRXT1m5aKdX+eIGE77Gsejsroq/8XFzlnyWvzVAqX6wPlRCnyW/MZkhJHIc5zxjlTWZE/55M+Dnh1h7/2FBxH3rhf/aNP/qzPAWAIevY5BeS68wYtaRMQ4GCQdqExDjX98X753MMP3kdAlMu4fndgF3NYDjX1FIe8Vx1F6bCxKajkzWmbfRKwz8/YEFUnqIQ8KF3mYNuUVsFSbNJLjkDm40Y/qn6g2xJ4l/QcZC/ou91UqZ+M5rpDyhw6iHN5Qk4pKO4nvohuLMUCdLnGc8gI80GkkKV8xuA2Eh4BwDlvaJMOtRy9bZ4nOODzjH5z3Y+d0Keikj/7cz+/AOACgI8O+vxJAOB7f+HdEaImz0DCiSEWw6JgYHj3gIkGYogdULmylWAqEogifRhIgvnxWh2woVgAaD3iRZvauNDHwM5JPDEAq96HkQ6wWAfD587KXBcEtPB+faom2enRTMwHADqYYAxu3KGPKzhX8gCMbrTcODhI6/e5Qu0GpStMp7WDO+8vNPUoHBGwmEtb0oW2olrmcWp3cypz0YLl2NiKYEvF3Qg6bwBu+xzob6cDfKpARLaXmxu47uAyjcA8jcYBMd9dufNu7yd0djlx8OL9c0Dk8uG8Bc2JfNAPIjIOSKBnByvOW5qjF198PnINkbneP5a7GAu/q92k1zzhAxrQZ0VyReM5L+kASWQcTIXhrMLbGNF4n9WpE9iHJxgDbUAX57/O/8gpfQNk6boDLYwvPMX9Tjd37ACSyGSfxz7HgAvnHfRMj2gBbpF9xuT6A3p5/uxYLSmwzPNzXnLMoRe0CiEgcqXl4ZOqq3gVAM7HJp0XNDv0o+TyZA7Kveiewf/K64ySUNSOzEhh8qxWOGplp46YY4l5H79CM++/zznADfrAF9gq3+TlusoBN31jzF1m9XuPyHaeQoZYhoZnCGg4b6i96PdhOkds0IJfGCv9QsY7X+s+ZFTflebxc+981wKACwDCfl/a51wCfjryGbQ7FyaEWRFa3hRCVudZutCiXD2agCKUAOAdIViuED1C5oYOBYgniHJE0AnL8wxATtFGlt52gMJRlkHh+VAmOrlEeTFx3lAuPesffWLcEwxKweaSVxgY1dqy80VdsXobPRLAO0iyhpYoJ1eCoczLiNI/nveEcugFQHPjQl8wfu6V9qVUH3NX0PQrlGZbzmaMg1YF/uhztFX5Z8xpXw51JYlS3jUOCcoFTmZkK4EHhtqX8KAJ/Dn7n/fzj77DS36dnYjQ3J+jb7Tr88I7XaZSnuoYGNt01I2US7YDNDdeTpcO4phnUiy07OunEUThYO04PqglLDuVwXlM34eD1M5kzjFnpMafEVnpJ2AkkgArH0+fysNTKsGUqwhPxd+xFGxHhrkOcr3Ed9qIyGXx3L456jLtMteNM/JGm75s7MbeQbXa82gTPOH6zefVAZHeT46vy5EDQuS6y4XzAe0w7wIscgJiFaZ2ver8bvhU97PD3wszx3tvtnB0qemp+wLQXkm/nm46WlLPcKYyfC6d6MAbgAUgd/0C37js7vDEOGZyFlP3qCP0wdnzjRidV9y2wJ8A9G53ujzTP+aIuaOv6EnGHfJ3OeulRvtxFOesL+i8gNNCmhXpVfCf7lVe+zve8dMLAC4A6Kzz6N8BgO9773vCWxEATIWRuXvOzHhiafhPgpm5BwMBmEG4opq/DN5JRsq6UgYEAAa7omdkEgLKFPBOgIML6jCitfPRD5F37wqlHUnA985DAaoPJCXrd7xhBy/Zfp6agHLRs8r3c6WGQu6REDcW7nHuU1T7+ouhFZ3ca9S9+5YaextOX35z4AN49whfV4wxh3YEkkckOvhhSc8jLpQ8cAXqRsD7CHggKkOfnQcAIQDA4QRU1FE5e7r/qsrlMB4tWUL3DvrgBegMj+FU6G/PlZoGnqhi5otmn6iDNsHmzEmc0TIHrT5vHQhiaMJw13ms+yJaLr9p7fM0Ai3bRnQ2NsBMZ4e2MKj+iVyF76eT2uykCwyoyzbyPwCBlhnZ1NEcMHdguEeR48jQLID+bwEoB56ur3i3z61HEaErPABY9zbgP+S23+P8A0AYgLdesI/PRWt0H/0jQs39DlCc7xmvg1neyTzR3wSkyhXWJpyj7Vq51dfUSJwbyvSc2tMmMeadsWnzh8tkvlcAMk9mkfM7wXOVFLrKkkLKWaVP6ovrLZd5aABodeBMhA2dih3xFRx0mNPE5x96sESvtvhOcKI7gOgc5wHkvuta2nD9Hn252q1YEG1VfnuP+u0D/S4/Gq82tPzUT//MAoALAD466PMnAYDvftfTsTtJ2/VRknhUaTuORxkMBM+NsxjVcyXcIHn0DiXg0RgHGCgLByIYun0eGkKDcsCI9Xd24ACQirIBZ7l71/uMkaW/YUwL5JFH6NEdFGT2J+uKPSyypXtRdK6weT+KcZ9hQjEC0PQebUIYuZa2ZO00cUDh7eqdGGA3iB5hcNoIOIgMyumi78PzjVNMcoOLAzYA4wReuQuVEhw+N64EXam7InQe8T67MYZOLFO6YYAuAENF466u0hjmb+yencufOD88y71EtZ0XdkE/IDOXwPnHMun1qM2XvwDa0nD7wfWTP7Mdlr8zn1FjyKXvNLjwmIORyQOkNaRzFkv0lQPo9E/+5SzcjFhO8DmXep1fuYe50Duj3AV8mQTM99oZzgPM2qkLDkAdCDq/uC5zAOrGn3vgS+bQ2/GIuY/BQcrkmwlMAX3oK+gDXxChZiwOIJhvaO4rIoBQp+Pk6dww4CstPibXiUmTw5G/F7xzlUW+Y2z6brnLvIPcPWiqdw09U8612vKUHu+fywm8KBkC+DoQ3wd0WfaEDuQrIkNsdHK6u35BH7qz5PxE/7qen0A2gZv+E/FzvcO8A0ZJN/J5Z+7HPMuG1qEIyPm45yBLH+lvB7bqH3OtZ1Wa5md/Zi0Bx/ytXcCu/h7tOwDw6Z9/V+QAsjLVla/qzclk7xqxOrKqDgj3JT3yJNwou2f7MIWFsPiSkwtr9/AIk1NSoHuV7JRFuWpcCKnujfzFWq7CCOgdFKJ2w+PKQW0wHhf0vMcMXoEKB1QotU7jDmA0bvdKHcSh+DpIhH4TaEzvHNrs4xQ3mG6sHHzrevwWSxkJSOhj0CJKI8zdlbwvDEBtbiEXLBKgaxNI9+gdXEFbB8fero/fger03uNcruHU0N9dAKexAKByh7L+CRSKf1544cV0jqoET87lLKMDPZNWgHuW2HKJM3c+A6bkJGBggrsLvPVNRAWUiofyec7e3t0swdh9vnifgxsHQUMmwsGb+ZQY7AlutNyXm3OIgCJHPc0CeXEwJp6A3lr+x+C7k4dM7gNZYYSr1M8+kIdOcL7oAMrvccDqINC/u/Ph8upyheO0LwfNI2au61z2AENOM0CM85SPy/WByzrghL46HRV0ipWQyvsL3q4SM0p/YdMGshG5dVXjVNdok3ezySL6OhyEmefLux2gOpBlPGpP/3c3kcxTXBifv5/vvtN7RK4rsjnaV0Ucq1YAnR30OVBEn7nzzjx0uorvqZYRtN+OYvcvY1YbccJV6cPUjwkAQx63XF3DzsXO/DrqD1rRFv3S/bJLaxdwzsoCgPss+Rd5DQD4rnf+fNQzcqUcAlOHl2P8UTR6zSgbcpNGvxsfVx4OPhzE+RIwRh7FoOe7J+jghD4h0AOgGDDhmpOle4Ja4uigAuUsT1nt638oyFrFexgIQYFPAzKNfo/SuZL2/mE8HHCiDN14Qd99BlC/Bcgq4+sGgvud3t5v3gWd3ADqGsqPKCqGsyvJaLNOYmAjiK4BNiq8FENnnhys6BoeMKAh+SzB0/37VffsIUB59ntuCPG+Jq8LZM98PCJzzAcnuTBXWjZOXoj45e4u2TgXNndBAPgodzMjfXPZefYlI3jO27wvaKBdx7ZjNjevJGCjD7SF/PalNDe6zhPMJzw+DFIBwjluwH6CXLV3HJulHNTOzQfQTz0E4A+5rx3e4UiUXKnf4awV0Iv5rpxX+DT4eY/j5bqpOwEOIlhihdddJzm9XZ7oH+AInvRVENrjGsAafejy1gEsegK+5338zf3cx9/Ic9dlereu9f4FiL7MKDTAjTnytk8OtXkhN3i4w4Mu8k93ypA1T4voOkt/w5/Q020BehxQqPQclWHx5VZ/P3qS59xWOPALnbNndznzo754GoPbMXiE+QBsuj7VNZ3uQqF4vYv3894o7F92UqXQAuxdS19cBTCMsZQagq7QCLqpTemjn/4vP7uWgBcA/CKR3kNuBwC+853v3B5/LOuZoYxDEKrGEQwfwrhlkVsUDQqYaBtCresebUMQXei7wnbQQbvxzusCaQdVImTPIeQIDmNw5YjiGJtRrqYyDKVaQI+dv4AnDqjn+e796n79hoJA6aHE8szM/Ed/aMujFPsAGsYZGqLwKEzdFVs31h0gAhLcuNAXlOC+OfN76IMbIqezA6x4Ty0HB1QqUKFyLxHZ27OD2A2kK21fSnOg5MYXkIjSJtooIEGkKg1sGkiBrosLnWiwmwuYoCqXYJ1/ma+Z55rRRfoQ/d0pZ5O/A668ZMzk8wR/HTzvzJVAYC3R0n8tUwMAxb6e8hB0rzzNhxk5N95uYIJ2Yym8ynlUnUHAN+9j3G7oATBjfFVfUn0CUARtrbQPRvULzz03jv+K6EjxCHzdVZjzndr3iIzLnMsJ/YC3GEMHNn0c/M68dJ7f6/wUuOX9OJXwqdPNael9cRl22WBeNR6e5fcu365vo7hm7Q6mbd4XbVUOIJE9fut5eA66HKjoOvbDdQH05jnXH51/HIBjA9CPTifaYhz6m6ib7iNAAS90IE4UEcDu7bku3cdXal91A6lLGHQqMBfFbyo/F5lXLmCM+SAjgaoLGACQmokHqoV6GFHE0Bc6sUk6qs6Thl4CgP/lZ35uAcAFAP/nAkAdLyMBObajxDCkKEP/e3g21Y1Q2LUTEAXnSxwOcPhORIx23ZDSht7DP+7D09unwFAYHF3UAQVCjmHPJZCMvoQQV4SHv91ADKVQUY9QAlbEekQxarlPECd31WXCt9qEll0pQRMfE+PlGoCQMYk2LENhkJgXlBrK1cfT6ezv6aATRcY8uOEBDHagyViiT+R7tSVGV7DuydNf525oFvxZ9E6ANs8VdX70sTqt3Hjzzu6M7ONTf673TxHBXMLKvmEwXWbop9PL++VGDaDMJpvgGQNztM990Wbl/nnUR/30PFMASgcqDq5o2+Wtyx98xr1urPvzaoeIT4yBvy3XMehdUSlkV8tcnKrjfXHQwL16P2CW372PPl7G6rKBDLn8OSAZKwEWpfZ7eacDG+Q8nYzKs6QGYqtZ2HVfl0X97REhxgZoZiz7eF7XPLLIEYtOJ8q/uMwOUGKbcFwencf30c11G/1lvtCR+kRGcM6ge58zXe/yDV/6+OEv51nviy/tInMd/PFu6EupKvUfcOn6iGoYvHM4VpsKqc8SYgJ78U8BjFyPf2BnPfw5+Hw7ijqCPlZF33/yHT+1AOACgC6Sj/7dN4HEgePFcBHBuj93qhFhcAU1DJe8F44Ao9RDef4kx/K72vUTLFAQCJ4reb2Tw7g96RmhRUgREJSMg6EhyBXF8CRcFJ1q+Z1fznNaHdA4yECZSq419u5p+0kf2UbulMtdw7OmYAq6wEu+EyPBPQBSfXq0r4M6FAaKDYXv4IJn9iUy+xgY8975teVkDC7zCT0B890xYHM0EQQAJPOCcneaK3LHkqcDzj6/jN95JwBRRV21w9VpNsCTne7h73VDq+tEi8a828kRzu8AO+cVp6ODGIAQPEo7ilLqedroz7BhhusDlOZicABQnBro4mD2YfPL2KK/5BraDu8ENnmSCnOrT9qGZp2HXd4jp6xqPnY9EY5eK7m0jwedt+ED7nPAQN+gj/NZ1zVOS//NgfTDIobIgTt0DpwAhO4IdLDn86TIDqcEQSOcarXruk7Xd53rXDtUXl/w4g0F2RM4aaeu3q3VC/5R9QCZ8Ag7c0p+dLy/2nadhIwAeJHxHu3t+gjApzG4vneZIHqHbnfnaZ+tgVboOXjVHRXe5fSFX7x952VOKYInvI+uu5x/gj+vD+LsdkXyzu+/FNHCjMzr7PesDUh/6HvIQske/O47hnVNNmbtAk4uXjmAQ5wf/UvfBBIMKH1yMxP8MSwYJwRkKHlSqCwvEHDIUioKxpWuCxpnOeLxumJFIbkQIjwAU/fK9JtXmXdFq/sE+Nzzc4ND/Sr6OSJOkfckQ3s0Eqij3Wsq16vg6qxen0pb3pvyO2YSPH3p4BUF5MtEHj1A2e7bnCJl6crYgaQbYpQqSqaDo27MHMxBo258Yzy1vBvRHovmBOhoyfu8G9Dq493X1x4R2Qf2HaChODEufj+0xwFhjvdFifSbR5rhN4w8tOFYOz6dTjvGx06/CBoCehQJqaP1HEC4kaMdlx36o7OrybN0A9eNZPCSgTD9TjTG5x3ggqyH3NYmEQczuo6Me/RoHPtmJ4uwMWjHyVNfaic4zwS/2LIpwMIBGU6L6yT4X7LqOymdB9SGnwnt4BHd5PKAcec9bpihbY+4ul6E17jmsoysY/DdMUGfuZ5w/nY94aAt25i5bsxN7zftelF8nCyc9Z151ikxlRJBm/QhwKXtaoV/GQ80xjn0/qZ+zNUXB7qdpzqARm8i5y676CbX9y472BG/Rh+789ZlER7399MOMkOf4tktUx4IYpzdyV3bvhIUuX/ajFObzqIvleKk5+Odh0kn+qlz01cdwAUAHx3xtSfHUXBPvzuOTQulFBG9XFoJ4awE9ZFkW/X/VDgar0QMLm8nBFZ5Dm1pRsweRrXKzLiCcmPiBtZBXTdSHoVACSBgHhHjPrzTEFZTaih6hBhlSJkBdqjlRpEEgHjUIfB2VJbKKeiaCqRm5C5az9IZpyfbzWVWx5cX5+N0peeKDZDB2PlN13dyT9idS4J3O9qJd0Enj2w5oHNj4eAcGjkI8kgVOztjgi1/DAWv3ynOipHuoMbZ0ucdUIACdMONUuYejxLTPhELeEx9Ei9g7OAPIq0T2NkZwbZLdgCvyjnTc3funJWC3j2/FYCg/gkEBR1bfh3RzgEcq1CyR8UYZxheO05t0Iyzfi35fxj62kjBPDNvGKJu6DxyMmSjlvJ3AK0VhIb+HAfI1hj1NzaAlIOw06fQBbnZgDpz0MuBdwcy3eA7+HT+ZZ4AFzyHnLvRdhADP5Af5mAPGgJM9W7foAAw8t+dr5ljd6xo3zdc7APyU09NkKzaqqnPqNdaoKHOVub0DZd3UkYoA6PVjADKhxM84vQG2FGFhNp0Ba0BdK4PGFMHpQAmnyfRVkv8AOCuX6CJPuk7vMM114k+79CYNrre8Lnx6GJ/J3Ppm1rQXcyp2wyXr+A1Ld9qY9PZae78rZzdyOlTfp/OCy6QiEPqwRL4Ff5ng4hq4a5NIDkDX9YRwHe9613b008/7fph+4qv+Irtn/7pn+KaGEq/f/zjH9+effbZ7Q1veMP2q7/6q9vrX//68Yyuv/nNb97++I//OK59z/d8z/bLv/zL2yte8Yqddv+tP3wJ+Pj0ZKc4aYKZ4+3q4sHSHiFYh5nEGl53HbsVE6ODryP/PYGgNpIo9B2q/nDWKXNjLiGIv2vXMV6PFh+GEj48CSCh0DqGyw0EhgilrLC7lrR53r1wnveoppSd6lphBBBq/R3RvShcVsvdNfYwipfTs4szM6v46TwaLjcKoAxVlFV97F7nw/IE+/yheD264CBP93vSNgoShevAqUf5AG3diLki9d9csft87kTeCiykczBPg9D98f6KIvJuj+7oXQJJp9ohauVEYt4txzA1Qu4wRnl3IyB6k9CNQRmKVv2oZVj95nRgt3LQuJaBR9SzluMYO0vXtKH76VPMd+0o130+dvrsjk7ws5XbCeNH3mcdneZy4PzqBo1j1pAVcgpDtqtYNkvMbkCRA7XlsuN8yzzDo3qeJd9wAquEC+Bx9MGWMQXGNS/IL5EaB9DO333MzoM+5/Cprxww733+/fo+fTkAequzyb3MGzwtJ/Hm4Go7uhEN/Hi1eTShnmHsLIsyNk/ZcF7UdeWinV+mXoy801C2MUtD1yml5fHHH98+/elPb1/3dV+XS4u562osPXq7zK8DZsaG/kAuR2CgIq7Qv69eoMPRfYxxVI+wMijwFKBq6sraMNZOoIHPegkelx/Ao64puKE2fRXEAbvrK42XFSn0o0f+uNZlIuSv8vtSdlPvx/9KG0Iv6MCF2Bks8K489JPjKNLufDZs0/HRdnlxHnMte73OAk7O/LIHgH/4h3+4/emf/unQN5rw17zmNfH3+9///u29733v9ru/+7vbN3zDN2zapPFnf/ZnIdBPPPFE3PPd3/3d2z/8wz8ESNS/H/qhH9q+9mu/dvuTP/mTfTps7zWPAJ7eOdvZLq8H1CeFqF3BoWR1lFQIzk0qIKJ8gD3yF6IauoBf+Kp5L4aX45604y+MRNVywvNi63xGP3IH8uXFdYBA+hHvLsPs0SO15Um0EtC+DMFzDoQAWG4Mg+EkoMeZlxdnANcRSdc3F9v1VeYEasOHln3xkr1v03Muep2cJiisHB3pjohGVCHibuh6dMaVEu/p0QMMryvzrmR6VMXf66COtli22ed50ydvMzY06Pgom3fvZ87t3BHnYCHmOCd6JoKXUsWAEVUTL4mP4AHy7ThWDCBGOZDYJVzRKQBlzHPV29Mu4GGQOFuV4/h8V7OWsmqTD+0xvvgMvq76ZhwfaMecEUHdAdk1YXrODQ0AStcUQYv+Fhhkjn3OAa1edFtzoZ3YAVY4iq2WpQPAMhfVdgA5K6OBDPEezjcJOteSNrJJzUjAqfMeBngHbJuWcj7w55kTeMz/7rypfhPFh4703/WHyweAcYeHi3f7Eq23Ae8P/VhLfvTJ56fr0y4bzDPROGRyynnW4JNO2qnFJ4episMzbuijSKt0FnPZnQ7nP94P3eEzp5NN1XBuibTvcyBdrziY7Ho8nL6qHkDfff5xELr+6fzkwNT1I3zAmNxxog23Bx4h1jPw6+B/y5mVbaKeX+zqrSjteH9VnyDNSgBQwZOLKkSv74Db8YziItcZmNCRlCsCmJz3ZQ8A/+iP/mj75Cc/6XIU38WQr33ta7e3vvWt2zve8Y64piU/RQgFDH/4h394+9u//dvtda973faXf/mXER3UP31/4xvfuH3qU5/avvEbv/GBdvddGGcBv/s9253H7taRWQVQTPHLg6lTo4ZXgxJzQQyFe65jh2p5RBkk5TUr2yGjYofB9CFMtelE3hJK8ETg6voq7gkBkZG6ysRntZuRlFxOdaFH4PFi8fZcmblyp98OGvUdoOiea4TzaynclVFXAmk0VFYm8wxj2ZgdYEeZqM+y8Si1cD0329B3V7QoPF1zY+LAgIgBUUS8cQciHQyizPDMHVy4MXO6upHYAdu1DOkGHkUWQKNtoGAuBex4hohTB6Q7gKSiSkQNB5B0AMmOTQNp3ch0WmRwNzdi6Dt94DgyByPeP6oBDp4pA+EOSTxbffLyJ8FHFdXrAGAspZvQBs0qb87Bl89bFOaryGFIlNddpC3Oc7PjsPq8efSNKGZEC2sumfuIslguF/KDcR1lgGqsDtq83y6LzuMPgFkrit3nFJ5Fbnvkjzkac2upEw6w6Ls7WMglz+odbPrqMjZlJCN/KacJuPmt6+IcZ+lALa5Ecfr5DDpgt+86hDxXJ+gD6SlzqmdE3IGO05659D514NeXyT26586czwntdZ0FgGIsDrZcn9Kunie3s/Op00MBhgCMVUql2yX65jzluhX9ytg80gdgJarI2B7mVIQuU8BD+q2irvQVkKw2OOHEAbOehB/1OfLQD64XADQm/bIHgB/84Ae3J598MkL6AnHve9/7Ilz/d3/3d9vXf/3Xb3/1V3+1fcu3fMsY8pve9KZY3v3EJz6x/c7v/M729re/ffvc5z63o0v0+0c+8pHtB37gB74oAPie9zy9nZ7e2dluj5LAgLuCde+RZQk8N+UMupcUwqO8wgNVv9QhQ/MA+BHVqjp8rnwR9hCYOq1jCF7VR0JoUVAIKs8GcDvJUwxcAfAeNzwOdPQ7u30F1CIKMoreziO7FO2DLlFdXxXda+cduU2UluE3hDvuU26YVYAPQ1M7OlEUAywVoOlecQdOzA3jdTDiXjgAUJ9ew7Ebj6DFzjFmfvZn0gKlyn1jbNWYK3kUe/BXO4KM5/9f9t4E2PbsKu/bd773DT2qW2qp1WKQsCQQwikjiHElKVdkCCCGEGOGgKEwCY5xCiGpWwMyQlKrhe0owQHMLCPKVApCZXBVEBASoCCOTGwQQlg0SCBLaqkldau7X7/37nxT31rrt/d39juvbD+UpJQ6r+rVvfec/7CHNXxr7TVwNMlcXMmEIucoVl6nyYPYPVLVls7BW4Aji4vrCtmAqEAT9MsachzjADjmXcCxryvHpfSwnWL2XIFBg4Bg97JRw/B6Cq+D1KlMEp7G7lWrmEJ/DuCZ9x0fHASQ2NraToBipUe6cZCDrSLX6Y2FpwQQXZHp3ewXnt24ttYC+nU61eN7jHF5PVlTPOfzWrA3ADunQwd0jNUBgcsCxhHG61EalnxPvKg/bwaaDuwCfGbaTJe/nd6r7Z/zIO8O4KbM0a2tdnSaJVJQ/PTaJbQEWgz+jT7kCQD1bk4l3EpOcc0AACAASURBVKsa4KJkGMBuBqL9uNE6tUCffZ8LwM4GmgM5B1cuy5FlADn2hLi3eU1cngCOPFGQtfF3+74wT38ueozKEjPAi9OuqWB0EsJwVvBc93QC0iLetfYh9EWBQJ2UQQOz9xwjpestteirECJf5zS0DgMArjqBJGt9SgPAX/zFX4zN1PHuww8/HEe88ty9+93vjmPeL/qiL2of+tCHwhPIPx3xvv/972+/9Eu/FGBRx8MPPvhg/16/6HkCf6961asWPucPEb/+808ewGc+85nt9a9/XTt//mLEI8gQhdBptTYDBxgULx0CUz/jiHRrI4s3q+BlW49EEhFwZvzVca/VqfL7scpgIo1JLnNAhSv0WVDMSgBwhBJxIMJ7YMJ+7GyxKfG803F0PFvOHbAIyGyOQqqhCMwzksLwLJqtLyjPEqrxnIg/VL3A9Bq4AkTJOBCaAauvIUqRz/x5KB23trHSGbcLR38nQr0rtfLIOFDzNXbw6vPWc/AW9UD6Okrx2lsxRiuZkEK1YtIo54J30bJIA3gsSz6wWEwHAfEejlsNDLIu7iVB4LsyZS6dNmEwq4Po3mfWMX7WtaHAy2M075srg3kdoUmexZpRcHsMZdEbhEKcj7jgGe9z4sCXvQPQsd9uZPFO9ySzXsz9esDCASKgzdfLgSOKEz68Zk+t7h5z8L3ydWZdna/8d+cheNPnIA9eJoqtdT6P+zmmrVJTrI3zEHMSoOMegUj4WN/7iYaegbziGoE//eOEQc/yvXXQxwnB8FCm99vXD+Dle+984PLTPYJOqy6THPzwuQPrZTLFPdGz4Ray6njIU3n+nCd5ntMGY/b9A/C7DAMQQ4sa70zLy2QhvAMtxZHwZq4rn7EOPgaBW7LUeXfQvqRDlVnTfK9cebK96tV/Z1UH8FMdACIE+KnsHnn97r333vaFX/iFAQAfeuihdtddd/VLv/3bv7194AMfaG9/+9sDAMoTKLDo/57znOe0b/u2b2uvfOUr51fE38uST/S5Ek4E9oIZFOu2kZmb8k6KECF+QBjCMIDdaQIWmCQEkkIDS0FHmxx5upTiXjXwIvDVauDJSsK9nhmaaU0po1bX6l4YA6+eZ2jBYAgAV0ZiHJ49H0foerJHUQxcgwdQ2XazognmLI9gF2aV0RjCWfOhw0RvHza6gfQjBcVXFuDeDOdLxhG6Je2g1jfVBfr8OfN3YOeAb1aU/h1CzIU9inAGdH5cgoAGkPDMZeBlBqHMZUEh1HG8PEy+BsT8UV5kqzw2ZFhHosbZWT+anJ/N+Gblw+esGYJaa+Vz4755PR2Y4NUDvKJwfW36++x43I+cl43bFSc8mIpO3uTD3l9ZHsS93d3gYQA2BpXGEvOpde2ZyeZNjGvLOOlrzzF2xQ3yefeAL3QrGWvG2s0K3PfU135+7gwMHPBeDwzPYM2NEnjFASHyy0EDssQB7gwS2Y8s96T4uny6DL2QEVP8ZMgpO0kAYKRnbCtkgeRAyM4qKxVA/UzPrHZ5Fb/pJwW6XjJHz+PEw+k0EnMqxMG9Z/A6QBFa10/o3/dvmfxxOpx5nfVUnUNl/iJreZ/rDQdJ/rl7JwP00V2oki4cpMeab9Bne3Tp8T13HYbOmsGvy1Y5MmLttDHFA1r7SPSZsuGdZ2NdwvVqHT8wUk9T70gjerw4MoWsYSWL8L3GoDJgqzqAuZuf0h7AZejsxS9+cXv2s5/dXvGKV/w/dgR8PQ+gPJB7O7tJ4NFZIIPWZ6vHrTj/DssqhctRBdKn50zPwT1ORmIcB8fx1HG42Lt1tJUdMxaUswJnUyr2ZZuP6Px6t8oRcG5tIbAcHCH4OL7yuDgExs5mHiXHutRxrwsWjsEAkrxbXgFi/hHUeWxTGc7VCizK04TXMAXNrJRYF8aKYp/BG3uBEA9mWdKJgDVhnACD2UJ1BRjKyI5WOcKZwSiCn3n4MV4ot/Ky+l7p9xC05tFj7Kw772ZtfG6uzBzEzsDOhTRK2unHleD8HHhiNiTce7AMWM6f+R7pfcSzMh5fF+bIuBwQycvnpYqkbwT+4ih4Y60dHWYcGW3V9LmyQ/u8U6P1o99Qpih/aJC4QjKG7ZgMvmV+xKLCn/1oyzyhbhj43GY69vmy3zMQn++HH10+8BznJ+aPQvd99mNgwIXTM+P0dxMKMow3Ax/RuzllqhdjVjw0tDnPbzx7PYBf8FFlkjpwpkQLAHGWGdC6Gx7MGR70+fizWUtokTVww133cqzr987ygHdiiGucALtZNiFv+HzZeiNXoC/fx5mnHTByHc8EDPNOl7tc40Zv7EsZmA5MFcOuOPW+/moHt56dgaBFl98ATr73MePgiBjQ4kHWeH//Snvlq1at4GIfzpwrodZP0Z8CZvIA6pj3ta99bRz9vvSlLw2PoP7Jkr/zzjuvSQJ5xzve0V70ohfFNfpd3sMbSQKRB1Cp8iwphOwC3q07B3ZYvYeHx2HVRCkUWanrVerkeNS9o/6aXPdSFpHNezY8PHHUu7bZ9g8PegZyKMuz41BiAAlXLChTGLIHzRbwIY5HawTAc4+gPie+BPJB8C9YdIU/da/KxSgpBIGCwAbscj+lYOSh0T0hPM/KQ2jBzXF/xQjxLLcuERCMx4+rZ7CFsHdl6QLZgZ+uQUC5suAa9+70o9opjo6i2y6wHbABjlh7V6p6j3saEMAOqDxLVlvAd16KBTp1AY6CQ/C6AA5QVJ5DgC90wzoA5H3e0IfWXx4Najo6P+j+ZUrMacnphrH7nFECvI+xzx7dJx59tD3tjqe0xx6/FPbR8VpmXJ8cnbav+/pvah/7+MPtHe/4rSYv6SOPPNIrCASNWGHoAKBW4oQxxRpZF5uYl8WiMg+UpHuLoB08Tx2o1lGj7nVwwTsH7wxDdOYJnsn9fD97pB0o4CGm4wZjdWDjwNXpwA3fma+SF9XdQR6hPAbG4At5YJm3QRsVz5x0krIg/5FtrRjK/C5bSY6WYqw38gBvosbH+tK/3I0J539+91qirNMyMObZxJ5454augzlqakK78+kL/AS9+z7ANz7nBaBl8aEuY9yDCahyeeZGK7wEn7oHTt8xx3mtu1FmJaP6swT2Sj+cqidwhPIs7lvoVIUD1DE/8pC1d90boQTWXUvX6jTuiSceWx0BF2F9SgPAl7/85e0lL3lJu+eee9pHP/rRiAH89V//9faud72rPetZzwqg98ADD7S3vvWtTce6OvL9tV/7tWvKwOiY+Ed/9EdjSQQede+NlIF5/eu+r6kVHPF/eh6M6sdIs7JOgXGStc4ktHSkWe1ugjnkuDs5jc88uFrMEJXQz457AWm5uwF2UTYkMgczYziaEVnWnitLF9SAPKxUwBDADEXN5yghPZv+wa6A9L0XjnYlFQJC8YkSCCqkWuVcjpUIQomcItYUUFn2RZadBLuKQwfzl+DIGoL5vA4idHx8lMc3+tzBrQM/AIN7ZbkHz+Qy0MFnftzJOrt17EIVxYLS5T0ek+QgU9dFXOh2FkVF4C3bQ93XP7euEAF8SqAGAD887B4EjJV5PCgg3+OgO09gmHoUs+6+jqwt6+3WOvPkJ+9EuDM2FCvvdo+Pex+05lor1siVkD+D/dg/Xmt/696Xt82W2eVv+6n/rr3whc9r//uvvD1oZWtbWfn5PI4B5QHUGkcHEnnsIzwjwyT4Bw/op2cuw2saM8WtmbuDMTwWDgiZi/OkK3F4FPpnjr5WDgb43DNEfQxOF+6BZh3DAN0qHrSevV3RW1tLn3eOWScbo0sDz2T9KAWVfCUP3npb29RJSIaGIC9StmbyTTfq1tStaDsMRgckLrNif6puHO/u/F4eQ9bP9xUDwuXFDECcj9kf9s7X1AGOg7jZSHEPnNM6vM6RtY8XTzLvg+eCHgvssk8ANtZh5jXfG/aRdcVgcONQcop4PL3fQ40YI3qmG4fhCT3pBebn98wA1WmMvV92NL+5uR5hHfDY4eF+u++V37OKAfxU9wB+3dd9XdT1+/jHPx61/+S5e8Mb3hClXWA2eeUE7rwQ9Od8zud0If3oo49eUwj6B3/wB2+oEPT3fe/rwqOhukUiNrwiKO0OSCKuBavUAIliXnR0fFxZt2d5tBu1ApvqjU1xVKr3t1HN4isrGJAXTE/GYZXJmC17FJS71/WZH9+IoTR+Jdu4YnPBFYos4m/GUTUCE4GK0MLrgDDSfbtb23FEI6EOiJLAT+GWb42yMKnS6+hN1fVHG6U+twCNmQQCmFFBV71jmSJFUTIfBCEgawZ1xN/wbFfEs4J06xx6ZF18zXkWAnSZte5KBIGq+zxWCS8BwlrPc68La45i4DqUzVC8aURAH8xD3yN0ebbT0Py+2Suh+5kb6+GAhmxX1iNqElZtwBDeVpqG+xzM6zOO0xH2/M0zUTool1RGZ+G5P9i/EoBO4G7/6pV2pBhb9UROiy5bIxIHRscYaitWhi70EaVeBFzK6OjMU8dRXVlaAhCKEZry9WM+AC7Fg2k87Al76ECPvYG2fR+hBYDAbJQyXgfx0As8Mnu9XSY4YHCe9/FmRm4eneNdCg7vx+MZ95U0ky0hz5QQp6NCJdqt5xFxyJ1KDJM8UWiJQkAiHtBqTy4YDtGWMmWdvEJuoMcYK6tI73cgxTMwoKBPfU68t+8bv8/AysEN+40scp6YZRbrNBs/3AMoc4PCjTX/HANf74AefOwOArXXHmLh8m/WBb7m0JHLGJdvfa7r6000vbO1m2W6ysMHcJyrUPBOaFDv9BMojBLNQYBvpwqlay1WMYBDGn1KewBdqP5/+bt3AhEApGYRzIj3aAjTLJ4bgqaCzyHoriSP1P7pJBpgUyx6rbdJyyLJ0Q5HwlEdQqocSBR6rmSPEPjlnZmtRhShmBpBiEKB8Weh6GuMIHHh4gACoabr3GuFEkIAIgB0FDyEz+hvmUHCWf46hRTHAhz5CCNv9BZxDrpcsaBIUEaAtWXWeFfOVsTXLdgZvLhQ5j2srwtAlAnCjHcjXHnu9TwG19LRtUdbrLvv1ew9ACi6ohlKN4E2is2BIMp29hb5mkMPgA9ADXOF1lA+HCk6/fvY2a8Q9AJdJF2Yt2nZnFFoKCp/vn7nOAiPnkAAx3R40LtStZI3mkeslQX4A2r0OZ4++jkTi0lJHo8VdDqSt0R0Ae1p3ihmp13Wxg0PnyPK1cEf4A6jxgEH68Ka+JH+fGzvoNmBhO/1MqAD/TmY9Lkznvl9rIX4Ozx+1ELV/ulcY309QkjC0FY5PwHu6u7B8+nB6/Q3j0PPlqdQ/3qd0vWU0Hih4RnGyJzZe5d9nW7s+NIBltML68V6+l7PMtbBpD+DdfJ98PqKfA/AdBALncHDvN/5hTECsuAPB9Q+/nmcThMAZ2QJ92k+xycYrDI+RzF6N9IZJ/IbgxqjGCcEToyUX6k74EUBzVUSSFLsCgC6trnB3wGA3/e6v9MuXLy5P4U4DhcWyVjZbQHLMmokrWegq/6FklHF+VO1hxOgy0eK+DOeKL0zdC+KMjEc7VanD4QQih2G49jPFeusQFx5wkguZGaAgmKAGVH6CBP+nr2CDgY6cDoR4BOyrZZMlemMQDhpmX25tZ7WfQghBe3XsW8qiuH9Q8DgOcFi9K1m/ChcfqKQOXpwpepzmoUlgFCfz96PGTDPQFjjmr0x/l6sa79P9/jRh75zwI+wZJzcC/CcFc2sIHyu+l3PE2ACPGm8btUvAxooU8Dv7GmA7meg5nRMRwye5eCdNWfuXMN4MXQAtE7zvHs+Oj6sUk8LxpNaFu5sBxB1pendUAIsQI8V3DsrMRl+l558rN18020d6MHjMyjDe8K+OS+yPjNtzqKMPWQc0Pi/zvsLbcBfgDUfC6DYgTP0AHCCv934YF3dKBz8MQo/y9NPiAd7pWzt5JP0AmJIsA7QF9UB4EOXXSlHNgJMIvOILcQD6PvmwJH1Y+7QH3Q1gyQ+5yf7cc14zWPs6+O866Bpvt/fP8sI53uAEvsJ7emd8IHT/Swjnfd0LzHMrKN+zke28CRGxizLFO8eHbGW6cPiN69jCN1A68uMenmOexhOedtlbN33ylevjoBXAPAGEd90GwDw/je8sdEKjngtiBzgEQpIAFBHW80KwVamEwwdXUMoTFpIT+ViAkStnQb4i37B5SkIwSlPWS8Lk9lPgBC31nSNmCCOX+WxnEpVzIIO5kcgzEc/CBFnSBdYfO9KYfYsMb4u3CobjL8R5LrPEyZC+Fs2sAtiF7oIJrdOe7zQfNS4pFgr4Nu9aYxtVq4oZVfObiGjxFwpLRPwLky1XyT/MEeEOO9xxcDcoQ/2mHefqC1SZZGzJgB0B2HMG2PFwcd8HI5SYG99ztAACrMbP1ZnkGfPa+VgA7DrABJ21HUOnhw4MTYUk+8Ba6NjYPGygOZtt9/ePvaxj3UgvbuzE0dHAJmd3d0e9qBnYSgBGHh+7IMl3YSirWNjaElzga71E+8NcYyzInfxM+/VDMz82mXPWQYmAQOsnxtu0CTPmkGpr7PzQZdrlck8ywf/O9+fsmtDPcuP0+Pn3TrGXo/kjwAYOv61slDze3QflQJ0hNw9pnWEzJjxMDotO9B1OeJ8N/Mxz3OjCqAye/Tde+uyRc8QTUhWY3yJFl3WsUfst++rg3zuQS9h5M48pvvdWPbxzNfC205fzNfpBEAIDbG2y66VbvR36nfXLy5PXJdorvBNHlln+zf9e/yxx9qtt94aSSCvfs33rgDgCgB+cgGgkkC8F7AIz+MS3BtEGzfFOoiA6SIRSr3AH0SPR0hHwQpoVVyRrCQdNUeBZwLyo0ZgtoqLe0qxyFujd8wMjbICwCBUHSxphQaoTGGL8OB3Bxd855azg5HZqnTL0gWJxkAch7/PhYcUQljqlRkcVnkdJWe5mVFVnjHMQoe1XSbUZpDKfAEBDpR1v4S0QBrryLhnS9WV4fVAz/UocxaKXVlvrrfTqn7PPuOl0PvcIIlniEzKYPDrWHe3zl3ZMa4ZsM+C3v/2fdXvDrxDIVfvYd9n6IT5Mif2vwPZKhTunj1XyD4PxjGDDT1LvcGlICKpY2OjPePuu9tHPvjBdloB7IC4qA24t9d5gL1UNxYyY8P7U0aEMofh45MTJTFt5XfV/cSNAOhp9thCIx7v6HTjfMzc2LMZALonz8GAx3exThgY7Fd+nvG4zi8DjC1Sbe51GrsoYvbPvUM8P8eeR+w5ztjlfroRYEqJYgoFOB3lrOBtxu3AM04SlEBHXcDy+kWWr04bqu5o7NlGvttjeaEl54GZr8d4Rzs59sFlKSANees0znv4CWjBGPA1drmD/GI9GRsyCj7R37rGTzO4BgPEQxBiJ8wQ5j0uf2facpngcn42DF0fOOid39EBbrX482di2Ooe1tVlRIapRAGYHj+usYsWr17db/fee98KAK4A4CcXACoBRWBL/7wtmB+JITjd2+LKKxg2EGB6Bx0gObMg9AUKyY+oyJg4Pg6B0fIo1JUgzOhC3oUczNkFRRu9OOk57Mrdx+5AEsWO8nPB5kIEBdqVHD05q/ejv4tjHq1DCGnV9NpUSZjRJmhR+es4fXhSXUHw3tlidiufeB8A3AzWHIS4MHehy/zZL46i52f6Ps975AqNtcPjFPeFdSyFqfo/qguZs2K+7ilgbKdx1DL6qrpnE4Nh5g4AiK5FmKKYZhDgHoZlXhTCIxyMAUR5jwO2eX2df3g3CsgVEUrF1wPlwboAdM7t7bXHn3gi1u3ihQuRQ3VwcNgTBIh93Ioi64M3Yw608iOEw3o3595Wyaat7QCAAoxSss4/DvyYu9OJrzHfy+DAG8R+QUvwfi8bVYk9fh1r7jQLvek5PH8YSspyTgJbRrMOZPL9izyq7H66bMiYRWkHAIsTi5JdFSpDIgf8ynGtAKCDHKd1fa7nxVGm+CLEacbR9OdYhyHKwEiWKIbQDWWAowM6DJYOvAuMZvLJaOGptV0WPuIgnXFynScxzXLEj2aZBzJ3lkU8Fz5k/9zIIu7UvYfsnwwdGS/wuubqIRLQP2vhNAdfzWPUPaKnWd9o7BggAHC/N/tkqzRaFpOGrv2dzN9pNxMJszWgjoK57/DwqN133ytXAHAFAGcVd2N/cwSsXsDRCq6yqmbrBiAYIKOlV0YtblDqXRm203Z0nMyC527bCijDfIoNHAo4ir1kQHQlhbhnIATFcQoo4QSEpD5HuRJTKOAIsykJBUZTGzoxqgesO7Nr9VwguGXP5y6cWW3mz7NCsCvrueL7HNQ5eAQoZXHXRY9AtoPaiI4A7Ie/R3PyMhuM3cfEGiCMXHjiuQFs+POcitgrB+Gz8tS9fkzjgo456n6OjLrgiwzJ9XZyKq9VZiFGxfzw0ox9japZpyNOECHJswGpPYPVuobMQtbvdUUGHfoz3XPcadaOP+d95xmAHhfmDjZmxQj4GrxQR8GmMDqNlwLpBpQBgQsXLsSxr7KAg4/khdrYiG4gAln6FwB+e7t73Tu4Lu8CyR9BMwEGBWgWQz1i/83T5B5RzR3+cloEGPCZ0yb74HTHes0AwUEQCpH9X0aHzt9uJLCe8MbMo7wn93gkbgHwcm8Xy1KN8WeB95HNn6caUfZJAMsKyGscrFfMuTx+vj5BT1ub6fGrxAyeAcAjrMT52T1tPj+dPFBYGmPUDRLoE5rX/gJW/fnIHC9ZNPMJ++h7PINslyfzPmDseJkYpysHu/Cr6yl40dus+ckINOQGmtOG02vwVHVSmenH5xBrJPtUe1Wdr7T3yBb43HUKdOoJdkdH2a51GFGKFc1s4/vue9UKAK4A4I0BvvmungX8+te1vb3z/RgBoSAC9OMb9yzNzBzEf3wSx7swf3h71rPJtj4TENO/8IgdZcZsBM/WP+4TM1Bk1xUezAfT8J037A6QShseMaF1MnDLW9foPWIqZ0zG4p4qnuHWqCsqfc96uOBzAAawARyE4DjNFk4R6F8oNpTamiBxHld1cL25FUp8uzyMLiAQ3Ch6H6evGdch0PgOIab9RrD6PHQdXh4EPcfcZKAujLXG7eDRFUFmtZ2pLuqYozLeJCw3BPhP4yeAkPV1MIRQdaXA/HS9B2z7vvueAGD8GQAPaB2Q4R4OPzJ1j5oDQacPnq+1JbQiaTRDHtw7EB6FqYet7tPxrXiC/fG1VYyV2klCg0+98872oYceiuzB7QqjONjfj7Xe3dvLGNtSMLom1lK9Ri8/2fbOnY+jZF0RntmKE+zlLKw+HkqaOWCwABYcEKNAnVfc2+Pr7PfBLwAWX1c31GbAz54zJmgcgOUeLwC9//T7UmZtL5SM0rWUeMln6+9wEwbgi+oAwnVKioti0ZW0UaEvjFefC6QrQefkMOtl4lUMvpN8qJAR9pxYQae9oPk6hYixlfxYABuRAk45qgT37slEnkLHzrO+p3i9WFOuY80dgLKObmDDY/Cwg3W/bgZsTgusxQx2fZ/ZT4xQnRD0NayWhjxzBnj+t+uE2SPpXkhoKsbQVBImjQH2CR3Aurv8dR0I/S/K1LOI8/2e71n1Ao71/f9TJ5AZmP2/9fdCGZhz6vs7CsKKCCmDgmJxhoQ4Q6GetSj5gpAmczEEQ2j5zHpVb8QQ9BJOOt7QKaBa3pRSCQFWWcUuHGBaNdfWs0I5q5agQGdED45G9y64uxKvQtIxVnkbT496HS68Uy7sZnDl++GW6rxPAXIPMuiZIx8UKEcIHbQWAJSS0Ji3at6sax5bKL6nilFHqQGV28iq8KoRNY+LdUeBINwAPe4JcdCHcEc5Mgb2wAUYz+Q7FDrClucyBp8PNeBiDdUFQcfh8nbakY0rcta6g+CK7fHjR+bm++LzccEKMAS0zsrCs999fWYvFoLbBbQrQwcSrA/fO4hlLeUJdMDpiiHmUgYG++drr715+l13tY99/OM9Ox8+TOCSxaW3t7ba/sFBU1JIzF9HY5X1q+/gA9ULVO2xWbmzBh10lJcSfgPAuVxg39gPnun85esBgOBZ/O107DQ/0xi0gxHoCTu+/siTmX8Jf+n7shCOMLo7sBaMXUAwgUB6/PJnhXDU8SxxXRoTwFDX6BlRR25nZ+FoGlplrJKLzgd+CjCKS+eRcdBfHSxQczBAhQHAGdw5n2Ag6jMAD3Q8y5KZB5z2fD3Z89lQ5HkuV6AxjE4HsT7OmZ78bx+78/L8/mW0yb4QGz3LG187xg9P5knWWTs+PIlTMryTzF9/exKNjwe54Xo2dIPipM/O2tUragX3mpUHcAUAZ9F1Y38DANWJZHdXQn9472C+DgJU5HlndHNACAZzquTJVlo6rgiCkeRvUPav1SQLoo8hSwmNnsMzQIERmV0XhlMj8HJU9K4iEVJGT1nzzgXjqvWcHRU76NFc+BvF6QJqVoquqB2A6B6yX3kewA/LMuZWTd51jY58uVb51hLq8Xcs3zgm5j204HNl5oISwY117QKWPUJRInAQ8jzT5+7AzAEhY9ZnHg/j3on5eQ6KXAC74mXPr7ePjM3pijm7kmC9XXn67z5O30MHcTMoxULXNXir3TuOUJ8BbNCPHaN274HViXMQAz+Qfev074rj5ptuak9cutSPjPRcjYsi6HhD9beOhYNOqkB11CcsT2QE00eP7owT5HjR+bLPrY6VXTmyLr7friwdRMyK19eKtZ/BnitbwB8072CDMbL3flzYgdmSTh/OIyjs5PFs8cZc9Ddzze+z20fen793WpLHTScjVCyIrkFp9Ln31z27Tm+dv8pQdBpnnjKc5SkMz2A9VwboLHMlRyRP4Hv2YwZ3fp8DG8Y1g755vWeANM/Nect5dX6un0ZoTDMvM05oyenGPXPQ42wYLpsHn/kpCfzDqRDvdU+oz0lG1NZWxtQjf33tiKfWZ4uJRKkDdATsexS0trbW9g90BLwCgCFHVx7AGwN9fhcA8HWve131Cc3ixU7M0fN0/yCFiR0/OrBxJRpMVgJPHr6eGFLt4EJhtLuJ2AAAIABJREFUxAFnWkryQnSLs4RyL0pbf8+W3knFVQS4DIVadeuqxl4UorYsRuaMUIYZmSd9MbFeAYLzHH3tUADzLszCqAvp8sQgNBgDgeXZQzS9B2G10yEgkiSUPZhK5Hr/OH6YFWsctx8eLtzLvFB4rIOvywyYZqXsa4kCYQz+fP/dBSbCcRbiM3hwIe0AzdcB5erK3QW5xxGxb10hl4EQyqViCFH+oWzrqHRWWqH4q/aZAs/1PFcw+g6Q1ZVoXUdmrhRFFDGvRIxuYNBvuZIt8CJ4v15d20FQWQNSJvIkacwE50d8ZSkiAcAL5893IAOPJA+lR9BpwWmANWGN8UryuV+rcc0gm/sAMOzPvA8zCOP5rK9+8nyn1/l3N86WGWrLAKfzNIobAKhs4LngdcxxYzPCMg6OT+Ln8DoOL2BsgCWHxburlVsHSwYUoYNe008nLAbonCeYW1/Peq6fQPj1DkQc+LHO3eAv2vZ9cjnv4Iw5LAP+fqTraw7/6vkk7Lh8c17y7OaZXrjHx8aYeYbLXMbq4Bu55fLFf1/mgWSP9A4HcTqZkqMEmeunB1zLHJCNxDC7YSndRjIkexwxgKs6gKnzVwDwuljg3/iLXgfw/vvj2JLsIz3ACVelX2hxA/GKWMUkrlC5T/1/A+gpHlCREMc68ssK+CEgWyZ0hGfDWkq5t0dCwYGL3osg0POwykJhlEcvvHsVgMv1HC92wafYjEo2cUZ0jyfCDQHpwgoFicBB6KFk9Uzc/C6c500JUGetpPR3xAuZJZ9CZhTL5tl+xIsgQpi44pqFE2OY5+fr7orUQR+CE8HI3BwIYqXrMwekgJW5/h7vmmPxUPIzqJppb9m4fR0AE3x2PQ8hexf9pwuMdS9IHQPiFYtnTTF6M/iJ5+HlDnpcBO7LPCwzYIq5Lqk1GPtrmbwEvmvs0cLtLNvDQf9RjkPG0NpZOz46iePdAIfVvUPjPD4+aptb2xX7NzJOnZbYQ40d73gcdYmfrR7nvOaBfcrIcx5whc36I1OgHwclKHU3GGYA43s/G2jQ1AyYmCNGXwdkNtgZGEBH8H4YzVGeRbXbskMR/+AhB2SxJtUhhHnFuun4tgrIB++elderrfUOIsx/5gUfYweQ1k/beRk+RQZBK8hv5IuDQdZz5mt0wEwDzsMO+pcZeA4mNQYHVIxhnpPziwN8pz/Wlv0II694xNdv3i9oljlfTx8wJo2lF3qWc8NOc/BEOvD00AWXt6xNl2un2eWFeVzd32+vXAHAXJMVAJwhxb/93/0I+E33t91txQBmr18JMeKhsKKWKVsEiYMx/S6PmmL7NtT9o7wPIdzt2MOFy+HBcdveyWsFDnVkzD+BvQCLKlEWMenKtFJ/zfXspSlAV8cDMIoAoTO6CwVZaPGUyijuCl/hdpsjzob392cWMGA93Jp14YeQ8Xc6E7uSQtGFUo0Cd9nLM7ODw08UrZ40F4rAxniaWvLpegXwZ9B5/uNYCQ9Qgkw8rOwTgg2F69Yw1/eg/4plQpDNitsBMIANpaCfGBIuZFkP3jW/P2ZSHgiexX4yB7xADkBZT7xfAAQ9a6HWHb15a0/l+cNbF4ftMmwwTiqhJd5jLBbK8zSD7VGuvTwKsWNlIAmAsdbxeCvr0enEPsO7Jo+cg0WujbFQQ7OOlYNfq7aY1krHwkoMufXWW9pHPvJwvr+1OBZW7UCtPaBHCTcKXWP/kp4lB8b73eDR+1XiwkMH2LOZXxyIoQS1dsSwwU8uvRysOCCD1jxeUvdpHEkX0HvG+LpydTDgxovXW3M+Za35LPl6K4YpQ3kRbIpv0wu8VvKFen36Uwkhyr51HujAs4AgdQJ9j7sMrO4sIbcstAWa4jMHk6zrDIT1DDfuWWvf35nXZ4DUZSYe7QnwOk9es47VCMD3hnn5WGeQ6rrGwZ/23sMwXG4TutClY+kf3+dZryEzZuOdd7rMZm4OQBWRztpDg+y10yDzn+P9oOV4xslRlYLJREnx7ioGMHdzBQBdYt7g7x4DuLOz1T0OG5bx5ooYRnWhAcNgBXV3ffX/XYj/KOGFZ8O9bpEEKyEqC4pG9aHoMv4tEkjk6avjY5hLiSFuvYcgW88MWmc4FIUzpzM5HUpm4eAW7uwRcTCIcvKxAHDciu0K30qoIAy6Aq5YnRjLaZYgwFp36xxgt1HgnUziEcuZSgmB7IKQ5zkwYe5c5/fN1jPr4sLPFZDPyS1bF6Qu8H0t56QQBw7+XgcbPvZZETKfWah32s4qweG1w7un7/avXmnnzp1P+iug5awW8XIFInknc3Ulpe+IH3IFtaBI64tFYDFq9vmcAp0VuITOb7rppnbpySczjODstD3taXe1D33oQ+2zPus57Y/+6I/jc62rPH947bQeQZuWNT1oVTwkQNVH3A0tfSIAqGd6DCB7KB7wBAwHcbrXZQrXunfW185pVr+7saD3LcZQEcOcFhHggOfxXsBOjjcBnYPC+Xcf74Js6tnuOa7cowKHWjvxsYGk4LVK0tC1kd1boITyLPwNPTsQgl58PZeBM93rMZHOT8gffnId1/C58z605/yD3F/2ft8jl6fJSOthfPMe1w/uWfV3IRcx+mYAy/hmDz/v8KQdl7/+Ox68GbzqmkWDIcfu8pD3cq9ClJTkqCQQ9x7qVEvOEefxGQgDWuNzq5ChZ69awQ3puwKArolu8PcBAF/fVEw2GMky2ER0ePQo+8GrnAld+bm1Ex6p8lT4s7Ew1Rcza46lIIzg2M2dqAknBgqfhWLh5K07XQsPoLyIjEvgL+49y9gnHXe5sHbrDqGEQBajUXIBhkTQwOAu3FAoun9eCxeqPAsPmgtSV/ieMHHNNSoWG3XYFDCex0BDQGWsGYWiEUTZZEXBQrUm1ZIq13a0Fcr9y2zFAcbwlnDviGlzLw/KmrHPAHEGWAgzB30ATwfH7JlfD7BB0cxWNWvOkdQywR3KWoK0jAE9IzLwKj406EM0Xy5UV7CML5ar7gcL9etyEF2Z+f14+fAmMsdlx6HwlIdDuJcr1g+AWvQPne1duKVdfuKRtrN7vh0dZ6kXdVbZ2t6ULyL498nLl7M7QoE9/URpJQA8jRITGuMdd9xZXiYSj5I2eJ+uiRJNNWj2DL6aAQTAk+8ByMyZdXF64DuXK/NRmgNi1c1kfN5P28eNIk8+Hh1B8pqRZMXxto8BfnE5MdOKjoH5x3cpfzKu2hW9vPrbG5lVTOs2/a610Oc6+g2yKw8zQN2Ni1nmOv0TcqM1AyQzf57BeHzfktRzHvOxp1/vpytBmxV6I8MbGeFAeRmA8ndBA24Edp4wjydzwHHg6+3g0efqOmBxT8dcfV/n93riB8+63tox5y6T49RqgPzIAC9ZHsZAHR3PXsDBCzWakjGKAVx5AHNNVgCwi5sb/2UBAJ47lwu7ltY7FuFsiUG4ELsL/MWCvOm2PlYtwDoKpthsdBMwzwnPQGDLgoryMRyLKcnjrILsq0n2Yt/EUWUdIeLeCIQcQAQGRhm71YUw0rtdWTM2hCNARtfjaXBh6pa8C0Nc/LPCZLxaw/T6FaFX+yoEufYnj+cBzhpntrpSoDnB5QJ9PmbfJx3xSzFxDOcgCmUzAy8XnsxnBni6xgE4+8ecPZjbqdaft2zNXdnPCstpB5DvyjkSG+pl7DtAK66rZA6e40CzGxpFrzPNx/xI2LCj4liHEtrEAjoQYp0YLwI/6yOOGDx4zQ2RWIvK1NW1n/aZn91e8Hmf1/7JL/zj7u1V6AX0custt7SPP/JIjrNiM/09WRmkwimsCwjjcFnAOENhCUwfHrY/fPDB9rmf+7kLng1XhItArcIv7Pgag1HvY8yebOF0q2e5gemgKr/L1m1JlwmwxBt4zYeHqMItekzYaEvJPsHn+Yw8lWAufOYgiYK/Tp85vjw6xlMZgGJnu50eJX8iXwUK9btCPR59/LEmjy71/5Bb8IzLqPmzGKfFOSOHfKxO6/C50xh7z3sBjcg8l6Ox1mu51lRfwFPH3Fx2sL5eRNppgO8Zl/O08wbP9GPemT6Yp4ehzOsxzxuel5HDfKFNXbustJCDao2XChARvmRewEUZPLzXziO+9gqjAnTqc8UArgpBl15cxQC6Cr2x3z0JRN4wCUtZqwhiMY6Ik76OMA/CEMEK0aKwUmAOkBeMVMdGKF9GLOFBmRjARwCcNRXETQYIQFglZRAq8bPq+7mAd+WKEElFXUfL1k0ExnawgwBAyCI4/ajLQQ5Cx61SwLMLThTDfMyBxYxHMgQpPZWrZESub3oIRlmYUbJHSkbAkHccK+Na61qtr9gf1pxM77xP3omxXw5yXHDrc8bIPvM+NxKWKRTuxUBA4C0DqC4Al4EHrPUZqPmx0/x86LWvQ4UYIJB55lifEULgmbfhKazkjE6/BWb0jojdGwGZPdbP263NynBBgeNpI96UBKkCk66s3PP2rX/jb7ezzZ32th/9r4JvVOdS41RilwDgRz/60Ugc0ZpJOakUDMptVnK+/r7G+hw+4/hX46GQejfyqj6g722sjcV0LgNSvi7w5TIDw0HfLHe4b9B7er/p0zvoYLElHPVPJbOg7aF4hwcn55EySeMIOaVOHfKonwjoZRkWtY1zD18ARiJI1QGnYvoYj9efBEAobpD3ZPO9cVLi9KxrvGh9gC/VSC05hxx1gx7Dz+Wjg8x57/hbYTIRj117yU/4J05pwuOeYTnMCz7jHawt9+k5HnPsRqADb9bA40cdAPrzZwDpNIU3GVpymTJ7FxmrrznviX21fuAh2ysGNIzebfV1TxmL7HNdxdhdtzAmjObQoyVTVDB85QFMSbHyACIx/ww/AYAPvOmNbWf3XLdyZ4/QLLBgaP2E0V0BJPONrgdBzOWJiS4EpRCCEddS0AVYqviZYKz1rXZ8miCS7wUjsaSDsSrWD4GfGY87C0IK5gohZpaxCzwHPV2YLbH8EXhYrLOFO3snYP5l1rXG7AKUbQxvonURoOUTQJTsQVeoKOehzKXs0xuy6C1Iz8cAOtQnSwCofw5el1nUAFiNhzE54II2/DPWFyEKMHal5oq904PF3zjNzYLb3+Wg1L0J0EjSVmaL+7j6ohSAgUZRfvGOoLn1jBWU59fas2EcBYAgS7c8Bh4OAM3MysrpQddgdLmy8XVhvPFZKJvNdnRwFApoa3uj3X333e1973tf8Ocdd9zRHn744QCE8iKo8DOeP3iYnzMQYN2gsfhZSVfsCaCJ/fW9dN5ijsvoapFOU0a40mV9nX7ZX49pZP9z3Nn/dxg8i8JSRlWuacoxhaQQ3jDoWIZVgkg3bKFdzeX4WO/Ivq/Ru3Vjs8f3zWDNlb3o4uA4E1Zmnoh9ODmNnuGsxbyWTjMOlIiTjjkUGESGdzBnhsqQB7kevI89xyNLQp7zzoIhVsX5o8SXZdzOIM7HMMsJl5U+DoAWuglgxn47L8/ypusPqlCU55V3M3/+7sC7gDpyDprAaHc6hm74TOFJZAMD0vluPuXg+WHgG7jOZ6pqRoJ/JYGsysDkbq0A4KIsu6G/FgtBqwzMWcTFEagqgsVaAtw4E7iwjfi9LbLkUngriylBXh79dOUYFvRGdgORoM/zqd4xRDElca0yEaseUngK618v+2Kz1viICRQwnBWZH1VEskl5W7wEiVt/eh6Cw70Cug/rzL0wfj2CC7A0C6QZfFL+hWcgiAB7kSFYmcFDURLDtx5xRKGQaj1pVp8Fack+TAXmx7BDGY0iqy4MXWGz1yhdF1pOfA6gA2xZbbkATdXDVuOIGnj1z0EENJdKfDG2irXjPe75G0q76kMSu2fHs9nmLOP6Yk71fuLj2FOENJ4z9h0gGPOCHu14MD4CXG5sBJDDOEKhuuFABrKv1YIyL3qDXv07aIF9dYNC81KPYCmNZz/72e1dv//72XKweFogNuIM6zhZY9Lfjz/+WLv55ls6v/qaAoq1Jvpda8U73fhZpvAd0LGW7D3xjq7Mg57rSBxwNBsa8KcDo0UAmCcaPAvay7Hksa/iAdlr+GbxPVbUOXIYoijfNUkjeNsHb6ex5aDd57dgWCirujopsZ7Myb2DDogAE3SVgLZY24ilrgL87Adj8XVwQMXzPWlC9Ktr4EOnXQFC7xbV+bXkK3+zJtD4LDugK/gEDx+gytfE9xfZ4jLLART76PTBOxyI80z2xJ/nDgSXPQuypvRV3F/hSmqBqu5Y0muKA0SWshesJ+/EM+h07/uterqrLOChaVYA0LXuDf7uAFCN5CFOz6wLj1TVDIOhnWFgimg3tb0dgsJBBs90C1fPCSFzmNYvlhLCq3sgK44tLLKqHYig0/N8XLjeg9mnEi8wmwsPngPYwPpC2DFuGB0Fx9iWMTDCcZlAQZk5U/NsYn18ffW7t3iiKCwdQqQwQnhQ+LWsVYBRPiuPMocQS0GePUyzw0EKnATnLrBdMGERs2bM08EZnkPm58rbr+c9rrwReotjH8DPBTnvdKHO74A31hWwCnsM8Gw9iPmyEi0cWPK8Ba/zVNPPlZuvn9MP4+d7B0BkHjs9MZ8BJq71iLFmgGq6dnQPju3nc5/73Pae97wnYz43NxfaUwUgLM9I1gJN48mNF8aBx1Pros9Q5L7urugA575nM41p/MuuYx6uqJ3eXJHOfO1rM9qz5UYzN4yjHHuuibwtDpbccxjrFMeamcWZezoMW+j9ejQwA2TIDr4RP7sR6TSsMbmHaaYPB5n9PXXa4d8h21jTMJqPs9Yc43B54TQw5p8y2+dDDCBjxkD3d7Muvj7sG2FArD0G9qyP/EiZMfveu+yZDROXv3o+CYAOIv0aeNZlhvNj57NINMsyTzF/VapYVwKWKuBmm1KdZPEe6J09dHDr/ARQ7aCznbYrKgR936tWreBWHkDEx5/tJwDwTW96UzCECzEXliJCCNytMl0DYWfB4hSIMOIssBntMmHolqXfh5cwBPRZBnh7hmSUj6lxxC9WQ9CFuSsSPndF5948FIiDDH02KyON0+NRHIgMJTFAGEBqBjSe7eeN3+nnyb7EGLdGT1Ldx9FTKt6MT8rSFnmcwz8HKmQQO2B1wIaQXga8WBvWYgZiDiRROF4s2NeQ90APPBsa4ucMIF34umJx+nKg6YLbr4mxU8rDQw3CM3RtopJ7LhwURybwektvX/RrHlml0AF9kJ228Nz5mJx/WBcA0rynM6+xtpr7hd29tn902LZUUP3goN1+++3RLzgSPioLGt6lAwj9qn39/R3aR0rf+D7PxoODs2WyYJZaXDMnnjntshYuJ1zh807Gy7rP4ND50oEUYCUBUAJg/cuTjY125cp+GJyK80M+qVe3rvMxxT1n6u2dR7duDDo9q+xLAD4VOoiqPoNfHQjhYXNeTF5Xe7CMk3YvHkZPN7jlnarC90F7StigcH7Jat/vWTbP6+XjdMNG9x0dDtkc4PJE/LC9+P4IodiMde2GaQm6mEfVfdWY8G6yhqwLPXrdYPSTAL2bbG7dA111x4LVdJ0NSgd+/h08vUwWZU3OKgklUVDyQwkgjF3NFOQRXOZAwPnAu2fPZsqps1USiAmOlQdwlqI38Lcngah7gAtuLEGUFISPYEyX9bDeUzlK+dWRY3hURvwKTOHMCOHLShKzINAzg3WjiWnCpQ7IU8Ncy7oM5mobyewnab1H6znL4HUgwNEGghlBgbJnrgg5hCmCwEGBLzdCEoHkVrQrfMCKK8ywrNtaFIoNxj8+6bXC8PYxnhAQ1S1APwUWI+aoSvfo+emxTcGTMUmjAO3Y39FdZBborvAZuytVLNgZyHWlZO3UXJkwd4RcKIzIZh4g1ZU27wREOhjw9QOULdsPVxw+F5+PAwd/BzTixoYDttlgiTreKtsRoHyUGWHeDjaw+t2Y8etcIbsSmlm8K/n6grVVSSSNj17A8XnFLD7z7rvbRx5+uHuUdK0y9QVu4A83wDRGxhsGT5WymJXjDAJ9n1GeXDMr69lzO9MNezzLpwCkU5gBPMD+uLHgyttDPxirfgIEc7/S2JI8GvF968V3I9M47llLA2BncytCMhjzKOqeAIF99r0UYEQu+vjn/fZ9QfZR9J41832A5gWqWLuQ33U03L8vY6eD4ClWmv2CV51+ATTxrLXMPu+GkoBnFfbXPewVfBkJS5FRPgrGz3zsgJb14yf06p7NmS9nQOvrjDNjNh58vsg7rT3eUt+HTjuVZOhyLjx/Egzra9ketY6CfR1cLvj8dGnG2so7m7U6V1nAgzpWAHCWDjfwtx8Bnzt3bsFa9RgtF9CAHDLmvAZXAqoUABAuxyhB9OsqC3MaYE/Hv4DJyBpbT89JCDC1VSL+qxRqCJ+1FCLdKlVxaCWdVeybOnkgAGeB44LXgYaeq3EQ6wKQWQYoHOSwJjMDB6C7TiFcV3yARGULhtCviDJXEgBAvcv3I4RRHQHL03B4ctjUKyT/ZT9h/iHAENqA7BSUhawLVM8CcbaGWTfWcrbMWZ+FPSql1xWi14WcuqvMY3ag7vvBmrMH0CQKbQ5BcKE872sXuiR0VMwi68QzuY+5IcQFYgEOuoYxD8/44jFhvi/3R+CdRAXek4bViDFzoIUCRqnxPj3Ty7WIl/U3NE0WoTqFPOc5z2l/8id/0pUxRdmhWxSde0tYP+amMdKOzpXnMhAITUD7biQxfs1nyBUr/1RHrayJe+W4J99PmZZc2/TKjxIrM4gG6Dg4hNZ9HwT6rjV4RnHuAWgT9MW11i/G1waDZxldUPPTaWy+l3ctgGG9rfqgM0cMs5hjZe0qptqNDaon6BqnJZ4R93kyyFoVom9VImxLfbAz3i3eV+DHQX/IwJPsQ43cgF9jP1UQumR6rNv6VjYCKI/8zG/+uX6nTah7rZOnMmQJmgEkIv+ct1gTNxbQBbNRgDyY17l76xQaUkkwcfQb5aWO4zg4wJ+Mi83UM1sbm1njtv5ds3c6PlYFDDrP1MnOpUuX2qte/T2rI+DVEbCrsRv/3Y+A5QFMqxjwlYDCwRLC3Jw2vcgpAk7WsphS+hRPXrcKo+bsAG2AoCjwfKZYpJwLMRVymSuYFiUNAOwK6TTjLMLK0lgr+QMBz8q4l0jfzRmWzux4pfxYZQYczGe2NhEubiE7k/d5WAcJV66MA3AxavoNpcP1HBuxP3kcPI6R3Ds0A7msf1xJEGXZesyJ77kLJxTwrMRd8M/ACUE8z3NWdoAb7ndF6crQ94Kx+bNcwC9bexf2bnE7sPP5d29FgRS/pyvMytwD0PiznFZmpQZ4EWifPTc+Dwfa3UtTihJa5tnQbWSYHhzkMaOVk2Fuuj5qTtaNgAE3EHgvfK/vBPzc88Y1jJ/98bXx/ZuP4Vgz9oWSJk4PTm9Oa8MwzaSxvAcjcXRh8HJIvjfMleQ1nwvrJLnEszPEYtRYzDXLVoz6XeuNEJN3fjxjsZ93gAGOCfWzjRqDM434+vgaz/zksqO/V7LWvI7sjQAgz0U26h4MVwBg55/ILksZG88rg91lzDzu2LMq4+X0y/pzDEz7zfhbR8YVnuDzgRbmtWBfun6pntPO413HFA+wNtwDndJOjr2ZjduZ75gvY4oYXPXF1pF76aQ4eq9WpXG/gb4u4ytGm/2Mn1FFfnSzYU2uXt1v9973yhUAXAFAJ78b/x0A+IY3fF/b3T3XPXLLlCEEi9DUT2LOMvavgmBV3Vzp62qQrjIGvbbZccR3hJfpLAOP9U+fqWxFCJOz9XSTVxFoudC3N1WyIi2ofGcel5Dx29vHqfTA2Vpcf3x6FF10NrcyyNkB4TXCt7JSHbg4sHBAgldR4wagIGDdu+egAQExKzEXTMsAF/F/jKUL71qD6Blc/Wj1btWI4ugP0OWKlzXAo+FAKp5TdQb9fa5k5mM4n7d7HTgmmYHPTD8I6euBSVcofi904N93RTX1f2Wu/o4ZnPEdIIeSLfqcubDX8/Oc81CGY15ZWsfX0+mX97kiEvjRHs6eNKen+bhUzxE/BPhoLUq9PPnkk01JXVlPMxX7Pffc09773vdGv2AUaux7TcKP2mdgS9FeZU4D/q4H8Gbah86hJb5fBuoc3LkCHoq/vOU9iWmULclpDJACvQMK6f7hYMIN1OTz0RIuy77gvV08vkUOJGjKIuzpzV1MDsFgup7RQFu4GPnU8cLlBmVdwmO1sd1BmMtEASjfEzyDAnMYdx0kF7iYy2Lpb/i8F4nfrNJb8tDVPwBkHO+W4T0bMPAZa9W9ctUKrtN9AaRYu6l6A89AvrC+zvv+GR49N1xYR+bu17NeY98GEPe15Xd0hxtJjEXzUX3MoEF1ryKDvcCgQpQwstBvGEPwgtRo36M6nXH5seoEMiTu6gjYtc8N/j48gG9sOzt73QJ074szDsyclmK69/W7gqE5+g2AV4IKIBJELKFT6fILnjwdY0ixnJ6EazwCZcujN2eT6Xk9KLoEhyzIYCCdKlQ5Ge8Z7B4J5qLP9ByBJhSfMzXCDLCJIPK4IYQ2CQ6+BTPgRNkjaFCKztz8zprqKGl4Hkb8DIqU3qEhlKpEjB9DuUJxD6ie6UAGUELGMEIqhWgC8/x9eBjdGp5BEMLSASvX89kMaPoxisV3utDlHb5GzMGL2roidUA2AMS1RXhdUQHe2IMx92rLZ8fX7IPTeBfeVYOOYuiuzAEDvvcYD9AgCiGB+UischDvwNHXivnoe4FC8aNApX7qCEnvck+uEkB0HcYDY/Uje3k2oGF97rzi+82asPa+b8zJ18L5YvawJLjKYsK+77zD6YsxSPk6jy/el7UxMVyH8k8Qk+s2PHVZPJrPRxkU8R3evZwfIRfDi+ulZ7pyt/7mHRBaX+BlNNL5pkoAwJsBiAwsxVzKQzerAvhE3rXYdxnZdXTr2bch65SwMbVFhKecNpHLeAr78XLL2qD9OVUQGppJg2MjCpV3uVzHyvpOBrtoEY+s0wzgS+NZxnN4yZDHbjQKOMkgolQZNOLFdIgBAAAgAElEQVTynKNj9obWm86LvgbsFyAuZFgtvhKtjqI2ZGYBx7XRkXKxP72+A9yGU6Pq3gaNm0OFPRT/vvo1r115AFcewJnNb+xvTwLZ3VUWsARkBjcnI8ljt90r1ydwycB9L41Bn1HvqXocmXRr4YFwQdPjPypkTUIEYewKL5RveQq7x6KChlFyPeZPMS46Lo5OJqM3pYCmg7HZk+QKnne7tQ4ARMEAgGeljGBB0FFiYBbqPk8Hd3F8W3GPruD6PFsKjggWr6MltY5CoMxgkc8R5niNHODgGUnKSQ/gmPvoDYxXRc/a3oYuxvGxC8hZ+fpaAihYU1f+CFHmzndQNc8BKKEMHGjMIMg5wu9nTdkb36NY42qDCEiNe7U2USw441R5HgBh/G0B8AWgc1zjyM0B0wz08tk6HszsU/dWMR9iQVEc/GQtOMZ76lOf2h555JG4DbpDcVI+CTrh50nNPcYVfJQ9iKF71srXgN8B8Q7k3Bvs++H8s+x35w0ACDSR+ycQu1g8GUDBdcgyjmfZB4ya5HedKCyujxtObpg4LSaIzBOPDKfY6Jm/FJ6OtbbWjLEu5W7NE9WUVQ5y+Bt6ClBXhrPvYfBxG+3rAD+xbiYju0zTka+AHwCkOiixtn29T+S8Os74PMnnuqfzCvX96nMBuUhhq5qSgHU3wINXvUwKMdyV3Bf7xrvq2AOagpbYh5k33bBkbi479By8n7Ms8X3W/PH88w7W2+Wxywyn24USOr3jzUgo4hkxXiX5rbVwcujnzD/oVR0Da319nPsHB6syMLWRKw/gjWG+hbs8CUQxgAMEXBu/4pZOEvRZk8LQkRL9ULd3dtrhYXafgOh7PIMahlfChoSMrMSwStcz0Fr/UF7BIPHcjDcSE4TyHzkLcT2CuKfbVwp+BwMEKZcSI8nBmbsL21KUsyeCBUNQ8+xZMHAfYMuPhB24+BEezwZQY+EvrF/V+tM4aRyvMWChBqhVsWzLPMVi5F2Mnc/9uH4WnLk29KSlBVUCP+oF+tEF+8aYZ5CMEnLPQqcNC/ie13U+cp6PPh0cocCgCT2L61kXB7+AO6cDVxAudPPzjC2jT7ayrBHU0I8rhAE+RggE4C7H6EeNeUSnMenoVp54+jzzbMbLus2KyAEJxod2UQoDcKB79DtB8czRgTM1CVkr6MZ5xEG3H80xBqdD3T+De+6hbuEMzvX8UYZlsWWbnkeMIN7BmRbHnibAy3p/+GaGFzCBQsb0sQbDU5573eWLtfubT0fca4hnlSYbAnzOm9HGUTRfmf4AsBnwAGLE48F31WuX62KO5V3r/MZxrBXd7zQtsFgZunF9hdQwb8BzrFOd0kRsXiFWgJS8c5yYBG2oBE0dDbuRQIwgJz26BuOY/QkPZsUo6ne9dy5P4zwbQLKSVjwMAfnltOjyYJYb7v2eeZdn+akOR9fuLfT78H52/VVJXMQCzjJmBnwhv6vkEGMNHjsdoVHM57I6gazqACa2WPUC/rMjQPcAZiHodOEjFDNGJmNcXCkmYyr7a/wrqNCBCMAt7js9y8DYqeCwAN0QmqcR/6f3K44PxpKQGdZ2xficloJXX8rKWAulf3qUMTLWisiBgCt5B3YzmOA7P5rTZ660XOG7IEc5AwjdOkSROwBBmDhQQiiggFByjNMBYlivqjpv9RFTsOuoLoEhXoox/wFAXPno+gHEPCOPo8hUjHg5Fr2G6c3QWGmk7oBlXvtrQdaohTYDDtbD1xxhPYPlZWvswDB/1zwXs/AcuGZm+yidwbrAD+y3fjpQ1TjxBg/gSDKUg/TsUevgi2eJ9+jRDGh0T6MbKBpzALzKojw6PVBhpqZqSTraFQDE28c+z2vJms774eAT+kMR8SznoWVgFYMDUAigZP0S7GWcpBtJAHj3wDmwXAR1OQr35g2lu9gje1yTwBBPqzy7SRdZxw7PpXsPo1BzGZj++4idHZnIopdI7Dit8iZ1r++3vvc5OWhxXuk8X965+Ls8gzHP8sbhuRv8u1hbUJ/j3fIkkP6ubDKeXsLK6o0SMwbwAGSMFR5ETvE3AJaC/Bz7Oo05MPIx++/wBOAPeTIbRLOhC31Bbz7OZYAMHcRaME+AMfN1PcTeQcPwmRwiMmA4SZvvJdlkfieyww2MGIc1Q3jy8uUVAKxNWgFAA183+isA8M1vfnO5wFMp6dhXMX7U9csjwuFVSWmZIIJ/wZQVY4NAwHqKMi1l/XaBc6IjRb3nOI5vA8goKzHS6VM5h6IpMAdAys+qzVIczaViDYZUb2AVRKm4QDJ6sei6F3EtFaf+0cGEMcP0M0O65egCaAYgCCk8FShGV6LO5K4EuBYh5WvuwswBkt7n3UFCwYdHMEvxaN0yPlNrmgLele14VnpKhtXtnUHIWsyyJW6ZiwRQ4n0fLG7NlT/v4j1Ot64cZ6DhCsDBB2uyDEyyDwA0XcOe0AWCfXRgnePI4H6OTL3MCGCQecf6V0N4wNVQ5mnQOFDOtcukqUE7iyV8SB7J52RYRq4j8WrpCkepP3Zw1v69f/9L2vrZcfuD3/mtuH5X3viKn4OWUYyM2enNlZ0rLZ8be0lmbH43ErrYQ6cD9kj8xvozb+bgytRp0MfkoBAP9fAuZr9fxJEbWKL7ITsqSL8NT6CDA9adMQ86zPqb69WtQ3GAp0eqdrAbITG33nprxGUBzuOdW5txTcxbRZ/PRuJYAKSynn3uM0BywBFjUTtMlcKqEiyx3qqEQF/0Am4AbwdGY+/qyFVj0HJQOJ/j5hC8Ke8BgG5UQTsxhypCHd9XbB8ytvN6HVUjX/0UhvWa6VDPcC8c/D/z/kwfC3MsfvduUW48IRfcQw2t6zocGMjLHuZTRgv9wPGI+lxUGDrnmxIOeTk8zIthB27owBN9XJVIpnHIA/vdL3vFKgZw5QG8Uci3eJ8ngWSV+7RipXQ8w9cZtCcDWCmDE8VHKTZtgxpcldVbr4tSLrKJI3VVFuap+py3kxCimdXGOxDWujUYpmr7BSjSMUF0XcgMY/3Ue7ugrlgXLFwHKryje9NKmIYgi3itxWNU/nYFOIOU2bLU+3gnxxSubH2ODoZ4ru6dhbYDDFdMCNKICdsYx1gzIEmlWL2V+zHxKOA9rHq8vKPkDGMsMbZAPH5c5mvrQtjnC0h0pY9wnC16nsezuIef7DeZz7NHgoE6OB9HROnB9L0bYxplMwYIo21ceodCP9aRIkI/FXfSps9f12bM3mgVxdgAUQ72AXpOtw7aPO7W3/PN33lv+9Ef+ZG2e3o5wN/53b0Yz6d/+rPaH/7hH3Zg4uvEOFgH/gb0OijO+RYoKMOCdSB2iixYB3DLPEX63kG53k/s2DJeY28cXPpaA0KpR5r8k7MZNUo5yaBUDMkdlUBm7ejck84+JPhMr47GH++UKDtbj9g/YvquOe6tNo0BKBREalUR9BwKQGudHLT6nvT1mkJlIgZQ8X6VUEG5EY5uZzp0kAjoA2ghSxysOLMz54XPquYdR7nI0aALi090HuY0BIDqfM6z+4lJAUov0QPN+TOdPhz4OpjTNSSLuczRNS5zAX6sPzJDCVKcaniMYIK8QnlmCEbMYzguRutBnum9wRkj/DA7FgJ8Vjyw1kX6elUHsHh7dQS8oI9v6A8A4AMP3B/lI/B8ZFmD7EzhigLhGsRsilAJH5G1ZN4h7g3hLsxWgb6R5bveIktKwDAYUMIxJEh5/pQ8ou4gEWd41j2DWGW63nstokSj8KiO78LCH7E/LnCGd2axFh7K3BW8C2KEdAeolU3nIAklNQBFAgLKezBOrSNCZZkw07sQyv58jzcZ3on0+Dlw9D0jSzGF7fAkMbeclzwVAuLyVo3yJWRN+vPcMnePiwtWnyf3Ao7n9k7UseMeXQ9IZz1dOS7M29p1uWfBAf0Y+8j2lHdvBuD5ruFNJqsdsCHDBwNp3vN8xyiqC+3penXjUHwtCjJBfMaeOSheptxmRen7kHNMBXTlbKtdFIOtp2dQRlUWyh0KCn70WCY3aAAaWcMzj2bH3mX2bM47vW3zWIgrxUjx/cTjOu/xHEcJLzhw13uoaTh4pYoI13dXr14O+nU6WeTBUUYKhe+gx3mB72cwKr7IbOlMBDquzHu9M9u+LYZVjDjaKl8VgDGTP2JfJaWICbRkENYPWgue39iO5Y498BOR6rIRAFUt1KqwMh48D3+J51bMHoWgeSYnNe7Fcq/UbOgG3cgLSW296uRx9UqGHEgOLxpHAwgBgNhjN6ZCtlTPd0rfMEZk4nzcOxswGCDQArzocpY1RmY54EO+EwYgOuF69yB2BjBPPPcGMI8ExtRBaUCM/sOsGwB8HuOg40zE4rr9/YNVHcBa+NURsFPgDf7uhaDVPSBB32hyDrOlMM0jKH2WsTLpuYtsJVndm0PB4j3Q51ub6U4X0ffWP3jbKuaP42QESz8CsJqAMUVKyVT8TIBEaz0UjHZ22rYrSB+PIbEoXoQ65qEYlyqLscwahTFnj4wDAGKGEDwwt3s6EGJsE9fO4M/Bko/HvTEujMj+FaIORVHlcwg+n7NUMwMy2+wt/kulzh4nyMorcj6pcEMoVrVuKT2FCbinwRWpz5H5Mw9fPwcSfO7PQUj7emjPpIwJIdAeML7ZK8ccMB4GMBghDB77CD35Pg7gkp5DlBFr5pmkOZ/FI0b3Evh66Uo3tJZ5AHyfdK97OVBOJ8ooPNoPj4O8jfpcvWv39nbaxYsX22OPPdY9nu7l4N0OBBkTNE/9vLyGEjCLfMe4uAaFhzeH7GmPbVykP5JsBrD0Zw6+SdBBLN+gz+HRy/VNQ1LrwRFdtkwcMcchm7a2sn9zFR92ulz0/qWcOFJM31ryAvtwcHC1be7oKPjkmtALnyNGzTW0vzEM1WUgBYOnyyBOQaxrBvTJkS5ZtyFzp1aL+vvoOJODBBqdzokBZF25n72APjfWd8LDtbuTJcD2do/az//8D7T/5K9+Z7ty+Vw7a7nWrHfqjNHhxY3wGewjKzx5iWvge2QuHnnuAbQ7YHVQy3iQJQ7oALyDt70qwohvRq47fbjMCV3IUX15ofVM9tYBq4NZxjTLPjkzyMhfZQEPjloBwEUJekN/zQAwgdo47knhQLmDDI5GwGaw+qhXpBPZWVnpfhI/QvEcDc9WKNqzZIywoiPj7TDiarC+ghmsuTZ9gXXU7Eysa9wzRPZZMGIMshT3Set1BuN6K0UTgEVtMitYGmDoVjSgxoUWylOvmS05vnPmd+GH4BoKblFIuiBGiGBl6jspo4hzVLyRvIYFACkXM47xaZ+XngrGQGzbCFhOzxQg0ZvU6x4yTFl7vS+9ONd2HNA17kWZ18eVA0rI1xJvJ2P1n3r27MEZa5zhBxgztPPSs4lB8/f4urpQz6Pb9CrNwpnuDwkGs08sSgmAQuwZHp+ZNqCrqHtWnvBQLlVNzBXzrCQdKMQ6qo3i0WE7bOvttjue3i4//lA7t3OuyTOmf5rHlQN5ZZJm2BuAb9L88NrongE0AQkYCZlM4GvFeBzAQtuujDkmxrOM4nRgCFAasmQUd4b/xvWLvcGdz8jaBnhQvsrH4/yFHAIgk4GbntMcg/iKVm+AXaXCKTbwdC17BHtSiMvDBflkX2j/dfoS9QUrAcUBxbzXMmrDQK42awOoD+BB1jCvYU7ZrSK7wwRNVyBi54eSkw6kWHMHcFH5Ye3h9jM/+/3tzqfc2g72n2wChY98/LR943/6vdbqMEH20WH1Oa/sY2hjlq2zh707Aqp8jQM2l/8+NuSMe7B5LrTlRt4M/p3vMPZivagVWT9nj/oC7VkMZSQpVp971wezPGBsrh9iLGcnUWA6svr399t9r3z1KgZwFQN4Q3jvmpsWW8FlBwJAwRDOoQ4sMzjjx4jbWWZtdSvmOGP4YA6EbA8ylhCyVOIZCJCoCcPqCENCS+/38XXGqvpWCMC47/So9xnWu3SsHExWVhpMzhixmK+ndLGKff4IIBSK/3QvKgrS39FLPZRXgXv9mf4ZnotllnNi3QQRUlRDoHL0u1hcengHSFbAY5D7zT8pJwQe4+qWsva4EibYPwcCfr0fKzlNIISvByAcgDmQRFiyJigWgI0D61mRumKbwQzPSRqjHt96V9KAV2K69Kyt3Z0I+tcaaDx0agHIQvuhmCp8gPlyFAwtuhdgBg5c48r9K77qr7Wn3XN3O95o7Ye//y3t3FbSwJr2bVOxuZtte2O7HR2pVZnCN7bDPRaJLADOilfz/XIQF+87O2yXL11q5y7ethC3O68t4JH5wZ/j8zweA2gyJ2gMoxMQ7fvhezorUZ4HXUM3GCgD8A7vznwMNwDA6EfOPDrQrfptGqf4TMfBinJGiYeHXZZvWcUxf9X5PEljQv8wYNh72sE56HAwMgtv6LfLgSoDM4y7UatT17qBwslHhF9s7iTNWnFmnq3Po/ZnJNIctscff3f7X37p59q5vQzNUeHmaJYSNQ3X2hOPX2lf/7U/0I+qmYvGxHG/G7DwBHLB5QcyHy+yrl0mg/x50ImvFd+z7s7rXMf+LjNYnQcWwGGdiITssuLZer56+CpGXbpPTo+Ie7ckSqcnB6XXGgl24lDhJC9/xX0rALgCgJ9cAPjGN76+XTh/vrLJqAFHFmSVfKn4PgQWStAZC88do8NKjkLRdXQWIKWEVSRrVOxVt0KnqYUyjFCIzPL1oqKuBEOYVE9NxRJ2AKWsOWJsqt9wKCJ5TQCMBb5c2MwrjFJ27weC0q+F0QGK1wjqWocBvsbdLjA9ps0VBgLfhd2s8EIIhZ6pavTW2H2A7PQGptIcGYrsGTXv5F2c99r3Uu9JwTWKmvq6OHibaYU19ev9WETvBeg7IEaIzwDFj3KZp4OEUCotDQAHWSgJF8xOw4wDOqKmWhgXGxuhXAW8j451DHvatnbOxc8AyRtZSN2zwvXu8KZXsDygXcpCsaEcmfmc4Q/nEwrufvU3fFv72bf9ZLt4bqfd9NRnt4++97fb+tZ2jOv223bbT/7034n3HR+tty/+D7+mPf+5L4oY3P3D03ZwIA9mZl06ABeYpVgxypgyKHSh6XxlvZAFcmbaDhqowscJiDMTegE41n14bpl77uPk8e+xjeP41HkgZEzxGUp9UdHmnN0DxR4T5E/iFPyWzx/HHBhZes/B8UkkYulf1OrUqcXWZtT747kq3N5DNCxxoIOKKgTPuBfkZYXMLJsjdEqbTYoHd7BdhfYx2oPXFC5qXsBYiyo67Ou2td3ar/5vP9auXv5IOzq+2ja2NtUgr52dHSXNqwD2yeUKw1lrB/vH7au+8s1Rl8A9cIA3Ny52tvfa4dH+whE0hlzns5LLswzQ3KJd7pIMfOdVEj+W8Tfz92d7AX/fB+jJ6TWOZQXki47cexvVME6ykYHAYMrYpB1+6llkKLsB6D2Jh3yWvlpvV65eXZWBKYJfHQHPCOUG/vYkEAWq461I5iXrLwk9mXMchzhBI1zmlPseSFtHhL2+VBw15FEditiBJUpOnT2C2SW0qtdlCG2r/+dMFUxbIDCSROqYF8ETDKwWctWkm/ZIuo4af3oGFikCKTw6dUyNYHMr2YGDgxOEC2NEgM8gWt/PAfEIMgc5Lii64K9YJnkiUMwxn4gLJHFhtO8KZX+WR4Fe147A/rSyLdB/I+Od2BOscPalA8rwIC1mxbnAnBVa91xYyZgBTq20z5LsbF+TpJ/Rso4YxQBfOu6U9V0GQZTyKMUHLfqz5j0NxUGcqoHRiIE6O2y7mxvtH7313vaJxy63W27daxvba+3qFYUxqOTJSbuyf9Re8Nl/sb3o81/cPvMz/lx75NH9dnj0ZDs7rSLDUmMC4cR1FXABADLW2TPAfgDMulJRnNtGaxcv3hzgXnGAP/OPv7ddvClj3Y4ODtre3m5T1x/F5goEah5r63vt5HizPfrI4+1pT3t2+8ov/9a2tp5xbeybg3d4YPaYBM1uJC27AYQR4LzhgJYyRk5TWV5mJNYkbVCaaFQZ4DkO9Bc9zSMBxDOZmZd7hADmGVuW4BKgpxhptRTLY+Aqyk5Sx9FpW9vcCG+geFBgUIBPf89AA76Nua6v9SP5WN8KbWFf5+PJZQYB4KTPp4pG93i+KuzsxhZt5OBP31t4UGv4P/yTv9t2ty/HqUmECGykbNQ+nJyutcuXr7Sn3H4x9lv0vn/c2uXH99o3fv339v2nj3TwYx1xO8h0oI+8dNpALjpYZy6M1eUnny0C98Wsb5dLaXBkNxMHqrNRGoFR4SnNEzD+dfozJ4c+k/O3l0EzY4TnOq37mPk+12V0shL1X7lydZUEsgKAN4D0rnPLDAAhPoAgzOsMByg6Ph7gDbAyEzWKQLAsGKVq9qV7arTNckXnzI8XRQo1gtGrdq8EycHh1VCczrzBeFYQmVZyrowQrhzDcQ/gDOUKKHSvJkrIY6cAdwBHrl9k5MUixy4EUKKssSsIxs26otgABPFTa2LHTSFEqwOB1kmKH5Cj6zp4sCxG99ggHMkMjhpmBZp4vytbxpuAMjOKXTi6xesA2JXbrIz9fsZ+PRBBqQ/GzVEa97FWJ4dHbWsns3F1bfcW18tcGSKQUQgOgGOf13cC6Pyjn/jbbXtzrR2ebLbTs6uRIfroJw7bU24/F8L68pWztrOt0IqTtrG13R5/4qC99jU/0i5f2e89T1F68zoxX1dyM224IlM5pMPjo4ih1fOf8fSntMcfe6z92E+8vN1y207b3jhuF86LHo7bpSeV+LDX7rrr9vbBD32k82Zr6uN91v7m3/yH7eOPfGLBSwrQQGGjkFkb54OFMVdmP3zd17m8n/HcAuhOH5QvGrUbc/YoRjx0+mxZCAG8mrQ16q7l+0fyA2s61pLMzbzm8ERZvsMgOVO8pmKXVYIqsu9H3CbjF08CHLtss1AXvUv8wjUdBG1maI3+ATKQocg1BwvIDr2DMiVxslHZwvrcE0Lgs6iXaobV4PkBbhS7dusde+1tb/sv286Wys0ch3daQFDrt70jWmnZk/h0rV25ctiOjs/aud299iVf/Lp2eko5sXwmQMuNWGjcacuBlxs+LgvjGar3KiC2No6XeQ734QF0GTsbVey/r6UDYnn6wvjXUW85QuDZlIfEoaZX+TTKEK1H4gbfxX5Xtx9XxcvAqq+Pvpe3XIaHwOSVy1dWAHAFAD/5APANb/i+duHChYUjmQRsITkXMm2HosrPESpusesaZzpc2VE6pjKjnPk7E1YSA4I+kj6qBlkXkqOBQxZ+LtCn8i+ecNLLFFQ/YPdm9MbpFfTcQaEdHQXTb2WbOvdc9LHJk1gFWBH8s0DTtTzbAYZ7HXSNW6EuFFxpYk06INL3kY1byTT6jiMsykwEkN2g5Ai9ZseRGmvvQm0o2ixYy3fst48RACAlnv+Gt9BrXgFwmWsHZlVuZAbgAAwHE/57gDjrUBPflQdFigmBC9BzUOdKn/c6UGDd47qif07tAjwo9mvzifYzb31N26i1VZxZzP5sox0enba93Z125epha2eb7Q/evd/u/vT19scPnra7795qb37gJ9ulJ/ejiLDKxOzuZgb+rBwA/r7+ACAHNef3zrVv/OZvaVvnttqv/uY/b8973vPaP337/9wuXX6y3X//t7fbnrLRbrq40dbXDtttt94U4HV7a7c98uiltn8wjilPT9ba4cFZ++vf8t+ERweec3C6sDZWCkqfo3ABX8xp3sN4bnXJ0DXRwacycasdbAd7biz5HsJPPp5u3BDbeFKdUtSZoxTzIg0txrbqmQLIOulw2YaMIy4WHsPYySLUoyj+TF8YssgDH0PQDD2CreUc1zhQc77k904bSzx/vn/U04syTNvj9CXeXzLOeTDGKi/g//iqtruz3ra2vXtNgpxHHjlod911MWhGvK7nbG48p33Jl/yNa8oF8Q7CDZAH0JYblYA9z9xPVqSzUSafjSzz0QmJfWZevM+9djyLMTlduay/5nvTD6Nb1mINxxEmME7QHGAzb5e76CbXI+Pd41RFSSCvWMUAplhe1QFc0Bc39MecBIJyzoetZyDrFl6ja2NmEGh5X8bqLGPA7sGS1UvNv1IeznDE+vln3kFEzEPhZ/c8RNavjovqCNKFSweO1nc2mp1bQ3UXlAIPAbZO0xInhgtBC+hEcAEUnYkZG9ewTg4CZ6+SW50ukIZSG0HzMTDtDT0kLXN0KCvFARJ3MooZj64WizFYer8fnTFmPIAUmkUx6icZhQH4qzEg9dAQYBzhoLBc4DsYnBXdDNjc2zWUwahFRp9kSv0wft6Lp3D8Pdre8ewQwIprOhYISPCPMZPXaA8y+uhg/3L78R95abvlluy0Ik/gUcWxXbp00m697UK7dOly+1d/etKe9/w72nse/Fh78om1MFq+8Av+Qvvqr/nPYxuj1aFhvwS21bFlq0rvWD2xBEQZt0nc5Zf9pS9oOxuH7ZGTC237jme03/7VX26PP/HR9uSlo/bWn7633XLbetvdVsb4cXvG08+146PWzp3fbR/+yBNte2c94rrEuwcHCu7fbN/wjX+vHVXGv97ncqEbNAUaoDdX0PNnueYZRuGxd+x5zLdqhdInN+ZZNoVnZPNs/fSMaWhQ4/Pj13xHLrBKV2ku0Cat31hzhKjLjJBdVS6A8Y/kjlybpNUqD9MTRJLnZBjBM8s8XmTaA3S5xj1G8CXjnMFSzKd6/UpuxXhKxsFveh6dkUSDACif64Islqzd3Gw/9wv3tq31k3bu/E5vFarTH923uXmuPfbYk21zYy8yVL/pm+5vZ6dZM5K4Yh/rLIuRnR7+orHjzcw4w0THY50HEJxlBvvH/vLTwZbL4NAnJUOhc/bKk1a6frAC8D3Lv7onIVeQo17vkFMq5xGXg3onYHeBJ+pYOWn2uB0eHrV7710lgawA4A3BvWtvmgEggsyJM5RUxePwBJhSJQwUO5hCKwUhR8MiasXhBfE2qxuIx84sOvcy7VgAACAASURBVD/aTGFWYKQ6h3QPotoVSRgohk8Fn0tBdI9aCTYsKbyQMN7SYytZ73UkBKO7knKFHMcpUeAz2yVFLKLFx7kAdWXiSst/n9cT0OLAEQs21lOOkyoe6+9lfnwWQqSyc2mRlR6jUeIn93W0e3PqQEjGWOt9C6Ul5DmtIxgCuYMmotNBJuA4qJ49C7PgBlTMFOpeGBfuo/5XGid4/nT8JVMAj0wPByjl7MJ/PYr3Ro2hhZJCm1VX8kweZdFvgWv3aEcM1MlJe/yRR9vP//wD7bZbpVCPKqj7cpT1eOiDh23/8LDdfvtWgL52utMODtfaU++8q33FV/wXbWv35nZ4NGKTNA/F6O3snm9HUuILa5geFwG4UFjEMZaCeMlLvrL99M/+XLt596wdH+xnHN7JWSjl3/iNt7Rbb91rly9faqcn++3i+Uwy+cSlg3blcmu7e/J2ZajA8eFme/yJ0/ZdL/uJdnKUNR41rve///3tWc/6tNgC7V0aQwmkXKkJGJ+cJHhOXksaC7q08hmpmPO7Dr6jfaHiEoZHxZ8/PMy2Zga2UMDwyTiiFfgb2ZTuZdHveJEW3hX1TjPBJ2k5QQggTfLQeSQNzhGHOsIbaD03xhx8Zzzs6zcbPfy9TE7wfpcDXbaIci3rdOYj6qIibwA7C8ZjGHjH7Qf+wb3t+c/ba2vroy/8qeRwFII+a5cvn7X/4C9/S7vzKc9vpydHC6cl0A8AiDX2tZ7BPTyrpBZaeiKrkCnI2Q7IrZsTa+YyZgbVPk+uw8BnTa6nYjmRclkNTQFe8bZiOAEKoXfunYEfezn6hFObNePZxaMvW7WCS5mz8gBej0T/zT/3XsAKDE+hspicIc+ejoMQVE74KfiSOBGQAJa4Dq9Q9JtcTCrR9wAtRowVFG3l9Oz1szC21TGEWBiURMT/Kc2+jgKwbnkusUNYjl52gffG2M/W2s5W9iSmfqALERdaZA7rHSqfoCQSn78Lc5SF7wbXIrgQ4qydrzH38RwpwBAgVVKAtY/POUKqjNxT9Tquem+j6DN7tHhc5aDXgWcXWsJ18vBWU3gXlH0+ynaLmiIDADKn2eLuCr+sXl/rmXIXAdvITkeghzdT2ZNlGGQ5iow9QpHQn5qjWsCjAB5z9LWWrpegFQ16cfMBOrOHahgCJyoOfKU9+Lv/R/tff+1t7TmfeXf74/d+sN19z4UAYleuCgRttDvvvL3tnT/XHnzPB9p3v+JH2uXLJ00nvtEGUYZMZQVfufRoO3fxKQE+NrWcBTw0lwRVeVSqv7NrT/Lq4f7ldnxwRTCn3fX0u9vDH3mora8pOP/h9g/+27/fjo8utfX1tba1ddZ2t1q7+57zmcawdtL2rx7FWPb2ttvB/mn76MfO2ite9cOtneW4TqPO40akXwQdlCf9pJczSd7JtcxaniODPQiyjIGM4T2u417FSiUfHnVjIU4AKjM/+FigcL14vGLm4IeIs6tjXUC67tFnu1vb4QUkdo/95dgcI8V5V79nbLFq2u2WRw8jaVF29ezoiAVMOoIfyYKOFnHKjK9ORsgnstC70VqA2mkdGethAdAqoAo5BzhaADwIhJo4QAN6kdyMd+jYWJUYqHFX8pxnKXzh537hJ9qdd3ygXd1/orU10eBp5C2dnK63Fzz/y9pnPucvtbNyEPQ1MEDmvMV6e7ydhwlgXIQeWNuMOEM5GRiPy23kUB+rHWW7V48xuX7wtULmIofcGAXYuQdcSSDedjDflZ+lkZYgmPfOJ0OsB3uCXCFee5aH4fwo+lLSzb33vXJVBmYFAGdVeWN/AwDvv/8NbWdnLyw6CXEHJAgYFzh85palM0mCigR9YZGrpVv1RbzeSN31rqPnYITK2uzvw7tUGVmeyCHGU1yTg5juEauzpPREZOCwjowluJzxAUMcAQ6gMWpqOchzgce9CBf3xs3ryTtZC/5GuCN4UBIIO57pQiQURwXRM570mGZR2vynfZAcIZiduK88rkHwUtsQBTQXMdY4witiCgbgzBy9/AwC2wEvc/K1dct+Vmhcz5hyfzPRpQtL7WkB4yhkfXYW9JwJOZWJKY+e6HtrJ2tPAhqjdMc4Du6CuQA0RbbTes9ivRpCjEPe4w2BnON2eHCl/dBbvlN5oO38zWvt/DkBqPX2oQ8ctrufeb5dvXrYLl8+bd/+HT/QHn/s0XbnXfe0M4FMeZXrmFHxnLL+/UgMwJeg79rg/Qh8VULU0dX22JOX27e89FXtx97yd9uddzytXXr0o9kZRzpKsbBrm+344In2iSuPth//sR9uN53fbefPtbZ3bqM9eemwPfHEYXvBn//C9pVf/R0BfhlHePFU0HZJVwmNKXk/kw/2DwSgtvoRemSjFliTTICG5WEMY/FIXSlIIDodIR5lVDhIY/56BgZO0FEB/w4UejhCHr/yTo7MkRHxXShYOoyIqM7aRhRDTy8vCjqByihKPYANR8BJjyOsYZRa0bWEKISRtDnKpDhYcVmLPJwBBDSP4cv6dBlSiXZR1D5KtgxwioHtsgpv4CyTApAcPNR+8qf+YfvTP3myvfhL9trZ6XY7PllrH/nwSfumb35tbwcX/C3QozZuFhri++Uyy+UeIJ5rka8OSgGJsVZTJxTW3McPHTjIRja6s4J34emd73MZhfyJPSrDLK+/Hl2MBge+BxgwPr/BQ5ld7HI+EijrVOLy5cvtlatC0LFGKw/g9ZDUv8Xn3QP4wP1ta3s3BLEEefYRxZuSAMKJGIWOUoKBUPgOAIPxomxADmyB0WXxr01dPGz8WwTYb6Zg7UIuH9SvRAiS+BGg0z1MOlaSnFfrt6r/p1gvmbIIQz3M42RCaJeXQtcMr8a1Hk9/xjVznMqYMGhXQowVgTRbgezFDJr6HlVGrxRhjFnwtpTYOJ7Io6zcOzp3VCxkHTf6kUQIoik4HS+gA1bGFPMJT696nup3JUtkbAst22bPJ/ciFN1qduCX61JHttDQZpS67jQgMBXr0fJYb3NzK45K8YBKaL//fX/YPuM5z2/be+faSWWxC/SKBrc3E8BkjGoCZq0lICi8Fsd5FMtn4WXeVu/Tg3ZyeBbxgL/+9p9vD3/8X7aPPPQv2+7u+XblsoLjj6M+yh23/rn2VV/3sra7dzFK8fD8zK7MoPZYOvOq4/3znsmAE/3UvUcH+1HsWUWf28lx+9hH3t8O22YTNr3rjqe0y1cea4eH6+3uZ93TPvyv3te++K99a/vnv/kr7eoVFayWUVSA5/S43XT+YjvQMfJmHuOyJx1oxCuUBLMezenPn7tQ8bTp6VNrtHN7F1VtMfn9+CSSlGSMHB/uj4zd4yPgVBao7n2GtYMCYgkW4Sf97gZneAdLBrjDS59RVoZ7IRKyf3lW0qyyWCter3g1SwfR5aU8oTGU8mZubPa+vgCY6PNb8WB+pMoYcw0qc7jCCuB3V/j0cXbjz/fB5YfHBrrc6YbC6fD2s38zXwkADtCaMZqM+dz58+3vff93tz/+0/32FS95SvvABz/Rvv5rX9fWNndbOzloa+tbRR8J/DDcKQXkAAwQp89crrIGITcMrLOuseoVOxrzKpDZ+w0XDQiAzoBNc2Y93UHhKhLj12W4r8E81iRIlYcadU+RMQ54oVU9y5sGeD1Q94T6/umd0CgedT1b966OgHP3VgDQqfgGf/cyMIpb0j8d94owZ6vIX+FCRIQpYtURlZhJwjyZXIUuNwJM7mzLckxLSX/vbiuguLKbynODdRrgLSBjZlvyrwt7FIFZt3GMUe133ArnHoBSHNlG8FHVfNrazDjCKhaNV6hbk6WEAFEuJBBWQ7nkM2el2edZjev1N8p+VgAOsrnPS1wwDoQjQp0EjDGm0YtW78CTIWHiHgdi5Vgfn4s8FtTt0udKhmH+PIO5hgfLj5JOB3AI75HVe8S7OsY0vLAIeoQ+4wrFGceLOmoOVRHgNAB/9SYOQb4hz5M6G6wH0F/bFqBaa2ubW+nVqe4o1KtUnFwc+x0kzfJeEkAwCPRsDzXQOkixiE4FHgFp7/yt/6l9zuf/lXb50hPtp37o5e20XWpPferF9sgnHm1b6xfbC/78f9w+79/9y22jCZyutT9452+357/wC9r2bgJA0d/Y2ywwHWCP4tUVd5f7UuDv6CBi/S5c3G1/9Wu/vKnozw++6b9uX/lVX9Oe8ex72k+85S1t7+JN7aYL59qlxx/Pvdg8bRduu2dJ+EZ6/6XdUKaEWbT1bAXJOkFrHt8V9FEdEOjVLMsLGhAoPD0+SmCnOLqwCvW7gPZheJGyzIhMh7WeZAQIFZgM3lS2dxVZjr2pLPhu7Fjdx7i3alTCC25g+e/INedz5AnXedgKsYGDbzKEZpY7wcsVr7hMrrpBBa0xF2jSZS7AIflihMd0kG61NYN3RS9H2Zki9r9iBClEThKSy704w1F47dp6e81rX9YeeODN7epVhSLsBA86oGSNevegsyx8PmJBR4a06NtbLAII9ZnoGN4EALGWeML7GCvJpYMl9aJXwk0BMzfUwiiocAn2iu/pxBRrJI+v1QQMT3Nlp7seij3qxlEaCPoHbTiN6HOKOyPfXdbAR/PPfGYC8ghJiU4gV1dJILURKwB4g6DPbxtJIG8sr0lWeqd3YSqBjDdC6eWx2jh+w0r3+Ax9DxgSA0V2bpVKCCZQLFAVi5UCl2clBGMpUxG/CtVKaAUIqB6SnfnFGnUkFYxjhZ3jmKtq1+k9Pq7I7I3OInksFPOsUhHukesARDWurIm5C1gECCDFrTnAmwsdHzuCwK9zMMiYHXjOoJvn6dhQnkzFpgQ0KiAzA2b2hPEiUJMehoAGrFH+pdNL1Vz0cfKsuGc9S0HEfpcXjcQg1tbXj9+9vA3PcxrVPHKt6SNd/YrlpdscBYHlN5JyUqxf20xj5ORY4G+j7e6dC6AYHtCKvQurfHNk+p7bO1/gJ/c8a7ydtA15+KJLhjo5CASNGLfoALG93TY3ttqRAuBP9sPztb/f2s72ejs7vNJ+/If+VltrT7atrTva1/9nf79tyDMZ4QdrbWN7J9ZsbzvHIaNpey97YQuwan6qAaYYWM0nvH0ad3knSYy4dOlS++vf8NXtjx/6cPuVX/6NdvP5jfbE45fbxtlJ27v1Ke0/+tKXtF/8uZ9p+weX2l/50i9vv/Mv3tWOymMKzYhXVMfw6kG2B2Pe6eUfJV4w9tgXaFn1AzOGbj+LjAunWYzf8eGVdnooT6jKS53Euy4/callsffj8GKKjimtkkCFns4jqQG694SoLmvUmzpi79IbHKWQepKW4i7zSBfa09oHkDfwn2AmaY7jPQwhB4PQKsksmWGsxJFBU/5cYned9wEN8MfMo8ghQEqfu/E4z+NeBxnu6ZRBJAM4jAqyzqtEFnvJ8SqnMpr/ruLwDisGVW3NFF9cST45PsWyZuHzLgurK5DLCgdQ7E8YjnVEzfiRSy47GZ+DTtkOAcTwnJeckK6ZwZoDeoxMgKdK3TgtI2cFv1hvAJj+hga0Bvo318PlHj1TY4NnZ2/fLOsAqawZHlNdF2B6MzuBvPzl965iAFcewE8C+mstjnBuvvnm9sAD90fmYjBj1X8SYUO0WEIwjTOMBHZ6hEZbJgSXfrrl1t3wVRpBQM34tcf8pYAoQFFp+gjy8DrVMUAcX+gsTUeP1V81ssciaD0FQXicNkawc4IVAZ4M2BWDhqDUUzeTweW98GMAZ2qE6lAAI8aI72Zhh1eHdUTgu2DynsCzktDzXCDM3qp4TpQgWTxiz3tyLVN4plJGyeozEibc4xDvrwbm7lk9UjsrC3rvSqe8fwEmKhHFq9izHuwh9IEiQOgBiBcVHX2KRwZzXLcmnJd7txHKV/u+GcWelfih3ryHxydtZ3s3Yu0u7u2197zrHe2ez/r8drahY+L0Fl49vBqxcTtbGZeFUuljU1snHb8cXG2bO9uRYCBQlmuXMZEU2z44UhcIOSLW2/m93fbxRx4OQPDw+3+/PXHpSvvsF/7Ffo+AipIUDk6STrv3KrrZ5HPxCrAeABg8jvop+hZoOzq62i7ubreDK1fbydpGe+4Ln9f+z9/8vXZ6cjXg/dPvvK393u/9Xju/u9W+49Xf1d7+3/9y9zACwre2d9rJcSaabG6pd3AGtFOWAxrKsaZ8iOTvGEeCq16TskriKDs6HPlrJ+G1C549UtHg/daUXKZCvodH2WkiojHFs1lTLuat+pIVWsA6oZDxfONdcwMD3kJWURLJ4yvZY4y52bjJv5NfAAYk3wA6PaFkGGkjYWnQvDzhFWaiwuAVpxgAu2KdkSmAFL3DwydmueLyw8EjXr6gzwqf6UC9SsYE/Spb/Og0vWaR1TtKQ0WUdIFgOQUOjg57m8LRG36ULOpyxqoL6P5lOgO65qfGds1+WW90B4fMIzya5TRgXWg44MDX+crlDu9WvDDjpI6lwhEWT0rkWcxwEwAZnlfxdweT1h+YfYfG0AEdbNeg/agbOvR9GAD5tO0LAK7qAOY+rLKA/+wgcCSB3N/OnVsEgLQRc6uLIziPeXDPGQp0Zli3cAOA1PGNLM3ZcxhMqOB4BTFLAJWVyFFTVMqvzEmVHZDgUlPyheLOdVzFeOJ4+qyNI6XI1kqrNoRPKSssvGC6ShxBOKGEu4fMWgIhcBaEbFnpGjeCBSvPLV8UCWDZLWLfYcAjGZccD8oDSPspV2AuVIcwIpZu1C4DlIdl248asy1VgCEpCB2vFEiZLXMBQmJGo1xaNbz3eCunIUAe8+G7LsSnDgUcK1GKKISjvEilnEWLscbHp21v71xb39wOb7O8ezu7exEbp+NLeWja1k60bztWiZPKak4DJcMVADysl4wiGQMhtCsmLpSIwM6WwiVUx2W9K+mor3Z02j764Q+2Z97zrFjPw6uH7f1/9LvtmZ/5ue348CCTI5RMomSr06N2ur0Xni5aHSYNivjTsxv7UvFj8JXev7WzHcZP1BFsh+2Pf/+ftb/wohe3jzz8gbZ74altc+t8e8HnPbP9i//rwfbowx9u58/vtVtuuak9/MEH2+b2Xrtw4Za2Lj6q7jB+9DZ4stZ2KlLNXkELMuQUQ6mi1njUYm2KZtZO1Pc44wB1jY5/A/DFKddJgGv9XDs7jaSQBS+g8J96gFuRZNbBQY+DI+2XvJCAs/Rwq2NEepFJjnK61J7rP16bUfpltFFMI230Ok7eTa9fV/BxaqAWbzmiyBWq2o142kPRc2xdnXzgiwE0ExQRjuDzQxbps25UW1FueAuwgRzsQEUZttvb0U0pPNE6Gq6ewQCxAEAVU5xJfAJcKS9ZN81dz8xEmXIAnJ1kdnF1I4k9ouRXvSMSkqyUkfO+h5VwDT/d+OYEqMvlaqsI4GPuzAfghsGPI0A/tRbQUtCZJVwxNs0/nl1gVTUSczz5U2sA/fNOjo9dhwAI+czDbILX7d04IaDjo8PD9l0vfdnKA7gCgH928KcneBawel2KuBEScVRa8SzD2zWC8fEMQMAB0GTqWz0svCTOhHHcu5VME4pPwrCOeiVwYPJw5Vc3Eu53izKs5PWtUv4HCwkBIUQ21gNISnmG0KJDRSmDZLaz9GjR7aKAaSiuapgOQzpgYTzu0UKA+HGNC0uUIfe4EHfh43N14OzKjv1wwBfWfmWzqgSGC9iuJAroztTD8wJYHQ+PRNBCHbUwFxQxyh+hFdcqjqtn1C4m2Lh3wz01zMHBMZ+N76w3MGB0TcAuAUoU797ZbsehzLbb+tZ2HPuub+y0/aPDduHCTXFspdhAAcE1eUVO0zus1mkobwfDM5iXooQ3fO+Io9JYlQARJSKUYBKZnkft0Ucfbbfeemv3Lm5v5lH0gbLWVQamYmGlXIlnDOUlD6AnuVjSk8YtcIoxII9keHMOD9rh0Vm75fZntp29o/ZZz312e+c7f7/dfffd7b0P/mm7+6lPae/87X/anvGsZ/VEllhjKXaVVKl4J+guFXsCXdG1vEBarx6+UUk3rJX/lHEW9TrVd1pHw/tXoiPN0WECvJOjg4gXPjs+bIf7V4IP9fnp0X6vVxn10CrBiaLjC0Cous94FnAo6TJCstfu6LPNvFzR+vEu4CGB1Vm7cOFc298/7DUB3aOOAndPUZ6aZLyqe9mdd5O/Rwclsszhe58f43E54HzkMXbwDx5O9zi5zOH3AMLy7B0cRGeQyOwnm5qksvKEhWETsXu7YewNT7SKTufxfI5L4G8k5ySqylCNo4PDhbp+DvriMnkg1fkJz68lf3DtQkJWZWn3k5pINhyJGSSseWkvN/BjvSt2D5kmMBcNDYonQ8dwAlX8N1q/CTim8ajr3IAidhgjne89C5vP2FvGoLnyXucnGTCKkVwlgSQ1rDyAnwQMCAB84xtf3wQAxbz8OziUktExEDXIstuHhNxiiZHR7kzx+ArERzhizSFwg1kLhHANSj4ESFZhyMxgWZdRciQBHO7x8NjUMS8MwhFwZxgrECvFQnX8YLKKZwRo6ohpANz1iDfku/58awGEEOn313d+tOQAxhM+HOwsgGJLkvB72Qu36B2IzevrY+uWccUGhjA6ykzTlMtkDNuxj7ZfypN6erLkKQRdHhiAJV6iBOJ5FB9gqBfntjhPP1qqubpwTYWbR4jQhQtElIw+k7cz6EiJPPLyFEha29oKcLe5q36/621751yAQR3b6n4dacoTuL6pXr57vYZklAOSx7Bix3xfobv+2ZSwpFhSWecaO4orrpUDTwbG0XF74tKjbW/3YgqtOHpej5AEHRXr+U/uZ+C6jmc/74X/TiphoVPrPqFnceSURlWuLUBCOuvJxx4W0mpf+mVfFOEP/+x3rrQXvvB8u/p4a+/+o4fa2dFhu/PW8+1dv/vOdu6mW9vu1jjuVmmcP33/+9qnPeszevycA5H/m733gJLsrK6FT+WqjtMTpRmFEUIaSUiAkJUsEJJAIsmA8TPmYQzYGIRJFgghgsFggwLRvzGPh/2b4ISxnzHBmCSwCEpgIcAIUEAzCpM107m7cr219/n2vadLg70W6F8/Xqt7rVnTXXXr1ne/cM4++yTcL4thKiGhBtvE95Hq+MWQCZV1wfxgbnp9MJ98YGstLXmLyX6bCg3u4G5ziQYaXb+dZp7dC9drKuPD+UVd0JCZHOOR/Vz45kOsJq73XrupfmZm3A4MoIvrg0rcDN5fWejZDQGvu4i9o2Q2D+ZXyIsXVhcAwD24PzvYx3nVBL+/hxfkMs9ZM/yt59FeU+mlKN51FqLMjGA1yhL9jvsrxpGxuSmJi0k9HWc7cS0TMlByp1DOujQNM28CMtHDg/HFM5qFliTQ6GDZS9Fw7Zisldz6Ia4a13jMayqYnuQpgKlkVSQSNGcY9/B4ohyXkSLGjTIvdDsCoFWYhcCyP08CGOlcS44yNApkBXrSpzPo35cSCtMaRxnMvTi0zhHwHYohlLfoUHMLhnG1FdwqAHwIoJ/fIiaBiAHEwaungHglgOiwSyBGBgrvSZkrw1OHWgdXB2w43o/xPV5cIbMiJTggL/BuF6U21CdUwc+JjZFCUF06fZ+UhZhFCB+yk6ghlcCh3H1wXcGFxWcsONCUsMBYZNnpGSJwEXsT2TZ8Nqb6S3nrWgrFBIiUHSZmMwJOLXJUeNnCh4xn1XfjdbHeYcgEPBQbqNciO6A4IDF0UkoZMxCseyl8KsvQ1QGuN/wIGGSKLblO8LeYCykWKbYIuDRHvqY5MFThZ6xplnXIIqwlq9ZHrAiXKpjhcpUJFRDQ7gp2hq1WHU3dQnImRmurtcGz7d2zw9avP4ru2sg8R2UeDyLGzlqUTPJwLTI/N2Mjo1Xr9/JCwtzLJFvK3gO35IWUOSeplIjHNnmAO+IaM1BsA+smAM37JFCBBIp1Ix3rtXt28uNOs29+7Yf2qDNOth/+cC87djA7EjF71rHt2++0hx271ZbnPY6RMUzWtXbfQd6wwhQrSmDB85OX26B7Mk0C9lEV7cZScWYaap1lKtROu5mBIOu2rNNedvd5oWRLM/s4jnZzwYjDyOygh7LXEsX3jo307aN/+8bE5Fdt+uC8TU5OWa06Qtlw9NFH26aNR9rU5BabmtpgtXrdCoNR27dvX2Y8EvAQwJeYFexyywtYO7PrwFAAKp4/yQSVnpFyxucRR6r6hrqXDF6dMQEPzIXPp9hkB4AEM4Yi3VVbWF5KsZU5KM3OYRpUBIKSRwJacq9KhkmmRKNWtSf1HCi4zFjqJIslq9xd7t0ocI4ki5SUJLmJ65HMwyLJGiOAb3DbK0xDJX4U0qP9FcGcxirZpPkTAy+dI/Y2W5+Q6atUEIxB7lvcLzJvKwz/9HxwEWMsSvbi8ySGU9+r+rZRluc60g0rVr+o5dUuMMbMiArxjVHHaM1037hm0MVg+lcBoG+wVQYwap+f8ffYCg5sHxjATPEGpYvbe6yUAyUdTH2tNqqAg6wmvB9j/MBs8NqyAtxdCEPAKJZCqfy4h9gzWau6v4BDTt27UmK8WujxS1zHQCMvZ6ADxqIlyQJkHd2WK2B2IQC4TAyOvjeyG3oefbcsvjgv+pyUaQR2+l1gK3OlJvAmMLJC6Kfip5pXCuiBW83I7EPWZgYSIGhQcw1xYyqVIwZVcSxmFCZo46cfzncCwgLcUdBGZixuNwpVBfcDMNOV5+U9oiAXiBJrE+8RreZcQPsVUSFnmckJyNNtymD2qgv22iiBX6lWY9cCsH8oCE32r+wMId7H8ATs8R07791uW446xgVLqsGXrZMK6TJFIY9/0ti43xDWkFgfKRmekcQqZixPymYHA6gOJfzSNGdUpOWyfe+7/26PeORpDypdoTEhGYeuqb5nGlb7A7vwvKPtC9+atvnZ+2xs8mF8b1BatF6nbqUiWLiOPXDvj+yILUfZwZlZGx8d869OBk9UhkqgElDAPllCeacU27Uwd9Cm1m3KXNBJJDsjhDlijUONERnUHv8H1urMtgAAIABJREFUpYji6wO6fzuMtWotzvDjneY8XdgsxMzsXZTF8Qzk8dGe/cVHL7MRlI9KjDRkCRJMMA/TMy2+vn7NhFVqZZubmbeLnvQSKxfW2uioZ3f73Hksqxu2vpZi9cAsD7tUoxGi3wf8Tg/8z+WDJ45h7XTm1XUkAhy5E7X3NQbuufRckrHREI1GmvangJ/OvUAn7s3nSIBOCTQ6VzpPsbWjSjgpjjrVOc50QQZsk4HCqgtg01O2tbvqizRAOR6YG5AJCoQMPXQ5/lTBQXOj3sRRfwzLesk+zYtkCxg5ssRi3ZMBkoHFVPEBYUf6wWfx3V5/s53W0s9CNIBwnWepZyciSxKLLt+4bwToXAb6vtNaSQ6IzR9+FoLkFDuLz0rv+N7r2cLCol2x2gnE5fQvahLI17/+dXvXu95lt9xyi+3evdv++Z//2Z75zGdmmw8b4m1ve5v9+Z//uU1PT9uZZ55pH/jAB+wRj3hEdg1ef9WrXmWf+cxn+NrTn/50e//7329r1qzJrvmP//gPe8UrXmHf+ta3bO3atXbJJZfYm9/85ix1PbvwP/lFAPCaa67iYWCAq6uFzDKOQEwbWgLhpwHBCNgiGFQ8j/drdcbBqfpcONO9BLdROsjx87mAUoZgHm+SCTYIpRRLonpmvEfflSvvm7ocUHmnCtU6pBQsAQDq+yWQJFhk3cdDrKmOIDECiYzdLHmNN7kp8LrcHbiHhAe+kwARrZfCfFAwMd3U3eZRofB3KP8U1xjXTGAzbglZ4gIuWlsJ5whiefACCxjBEvtDpcK/ruicvTkUGI4Kjc+S5oI7LysGm9fX4n0Up6k6ZkxScUOiXPEalsVKw8q1uvUI4itWHx1j2RXsbTCDKhINY4PAEesPRiuBFY01zqfAaafd9bZzaQ7QWg1tsfR3Fa419ktz8A02i+ubYlBxnda5szxja9ZttOWmF4jGj9amCyaugnJMrngiy6GzGIEJ5gaFm1mUt1yy0dFxm5mbtvHRCZuZnrcTTz7W7tmx204783D72r9+yw7u32ePfsypNn1gZsUZ1/nhvCDOEu7blNEtVoTJvFkv4HyPxfXkWrFeXwLvyOAlWGuTHSIz3GlxLpaXlqzbnE/u2EVIHWu2llMmuQNA/MzN/Mi+ct1HWDqGpWLg2i14Fr+3gnZDYPs9bZuZ7djJJ43Z8577NluY61o/MJY6izmDp0xmrxWIddN66v9o+JCtKzlbKLkAowD3RUZ3fj4c0MWzB2Yc34v4XO2p+B08tsFAwzWKJYtnTnIzyoi4X7Ns3pCZH59J+wzXCdZonGD2KM9SeMgK2Z3WHWENBJUpPlzyEGVKkFHr4/JarvLQSMZo7ACneibK3bL6S7vRGMHtsPzV57SGZOcS0IoeBcnnTKZkbmd/xpxxdNJA3gTJZGVfaw8yHj2VMhv2GOi58D/e01mKwFBnBN8VkwI1TsnbKAt0Hwf5PWu3WnbZahkYP2e/qADw85//vF1//fX2mMc8xn7t137tQQDwmmuusXe84x320Y9+1I4//nh7+9vfbgCNt99+u42Pe6zQU57yFLv//vsJEvHzkpe8xLZu3Wqf/exnXSDOzfGz559/vr3pTW+yO+64w174whfaH/7hH9pll10mefBf/h9dwLDyXaF65pqUjXeN8AOqINYIgiSkvHMClFErY5YEeAS8KPjoeUOPUbcQfXPncWgS0kgokOLRoY9sosCHhBcFQs+8M0PbuzvoYOI7YbUCALB4L8AnrW4X+LIIkdlFlgAMgd84zxQObbikyKPbQkI2Kme8pjgc/K75wzXxwA+7XtmrU6xfYgYlKNSGSIJNY4hKBe+5kPL2bxFEiDHANRkgDhl5w9aqBLCAruZba6HnoNIvels6jckzJFfW2YqMRdxHESgqczIyr1ynzL+kPr2uVNHFBkCqUESCR8VQzqQ+MmrdQcnq9YZn+QH0FasEV2Bw5KZHJuyt3/66nXrWeTYxWrSZWRSF9r2cPXuhRPZPAr6W6gdWaxV2kVgGcxXYNM59up4AbXmJ+wjzjZp9Y2NjPvfcZIiHK3Bc6LAR68WJtYmARfsebt8q2tqBwWahWHQCGbFSpWqHrWvYju3fs1N/+Sz2FL712w+wBdyBA9ut11yySrVhGzcexl7DOeBOrReRXBNqoCGLWkYBwV0q0j7MlEjY4HXE9tUqSBZBUWew72Aq4db1AsGIR2y3kbhl1lqeZwZwc3GG8YDg6cEeejwfjLmOfeXaD9rBA7dbpVpluIFaVmKftFooytu0kZGGtdol23lf08rFZXvJS68yG3hNvghu4/6LBpHAVwRhAllcW3rAC/6/MmFDO0K8rjnB+muv6qzHcxTPYDxPmsM4lijEo2xRzLHeXyF3wHqlVnr4LoEasVY6d5nsVNZu6tmeFVsf6r6iwues75ni+yhrEtNN925K5GO8XwJmkl0YYwfhDlkGbe6ViQZ1BD4ChKzkkOSmzlpcq/halMUrSIrMeM07ICkuUTpuOMTDk5MQw+gyFWNzD4kXapY7WKBQckXromeR/Mz2zlAViSg/dN4kR7Vey8uLqy7gNLG/sABw+MBGBhALu3nzZrv00kvtiiuu4KUATJs2bTIAQ7B4P/rRj+ykk06ym266iewgfvD72WefbT/+8Y9t27Zt9sEPftDe8IY32N69e525M7Orr76aLCGAY7Tc4niGfx8GgLHlmwBCZIYi7R2FlQ5ctGZigKvACcEFisQCXvWhTHImUELRDwwroWWxUbA4h6l1CWceKLUHghsHZT8AtlLsUwYiUq1AxRtSmIXG8zx0CB4HTEy9i2nVKip4aPJ0oCVgJIyoJNPhjla6Dr7+15xo/BJuVCKubfIC2HDlJkCrzysI2v/Oe0hGhSABFa1oWaDRQpbwiYqe4xlOThlqGs+sTSnYVK8NQ8/YEbA9yf0sZaO/h5Uc/s73TKA1AxiB9qegTevEjF4gDCR5VGtWQosqtOkqlfl3bWSC9f7wrOVq3ao1j/9DVjACqlfE5FjBZvbvtDXrDssKWmdzqVaIqV62no/Kotsnq6PzArfkoNu3O+78kW3bdqLPT3pfa+eMQ9Hu23GXHXXsCWQJYfwtLDYzoCl3ofaXgF+2loN+ApA+ShgGt//4Njvu+FNs/dqinXjiZrv2y9+ztRs3EQDX6127+8e77MCuu2xkYo2t27jBSsU8dIDfB+WdSnVw/ROo4V5JrvGC6qElQ07PRBkQWjuKWefyoFA5SzbhHOcAEIxGv9ukUdZcPEgA2FxaTLFTYBFL1u0t2Uf/8jW2Zk3FSpUiXXICgF5oHG4zV8xs9zgY2HKrZb/x6+8Mva9z1z3mQm42nbksbCGVxNFcR1ACBo9mYcow1t6I13CtUpa6+nOrRmE8B8M6QvHIcX9wTRMAiwA2Gr56P75G+cHUF2dPZYQL6GchJ4oRTv3a/Xz6fKrk0jBooQcnzRGfJ7HUkE0xRIidQn6K4pGHKXbtiHs7GiQR4A2DeMn1yKzhsypGL4AcdWGUxzgv0BXdft6xBPdEkg+SfvJsX5dxkDVRdvn3e4iCvkPgUEaxQOGwjhDIlNzVdcPGvMgD36cdYoXVLGDfWP8tAeDdd99txx57rH3nO9+xU089NTsiz3jGM+je/djHPmYf/vCH7TWveY3NzHhsjH7w/vve9z777d/+bXv+85/PWkCf/vSns/dvvfVWso74jmOO8Xim/+ondwFfbbWax0YRmFC4+1HN2Tn/W5XuhwWUWLFc+a+sn8UPJ3YoZpb6Qc0LEvM70TA9tNcRAJSFLWHg40vhvinWg24AAUuwmXCfpjpqEmhUVCmODveQ+1VKBNcBQCr+Q0Jp+MByIwaXaAR3EgLxtcjkaNyZmyBlLmbAEBm1iZmj+blCIeQ9PnEfxLUpkQDCBuwp5yHF2mRld9TrdCgLT8/h+wWMiYtvxWDmwtfrIzLWMmX0COxS0QDUD9Axw4Eay0IEdjGC4J+2N2MPY1yvfxSCShZKgJi1/RhCh9ZqFStUPOMXSR9gwqr1MRSRs0Zj1ABcKrV61pFGmcW6f1xLAVE82/zcQVsztSF1A3F3Ed5XMWKfMZ8vtDnDzx13/NiOP/4Enw8w0+08s5XrlZItInjA53qsXecJI8MB7ivY5n6PrmuYCFJqnrw1aV1D/9Nla820rVrv28NP2Ww//B6SMRbMeku2e/tdVhsZtan1h5OVjEwSO6v0zG797i12+i+dyRqKmRIreNklCAk8r+aNjDu6MRSLtuu+n9hhWx6WYv5wOFI/X8b+dm3P7p122KYNVGS9dpuf63Wb1msvW295kUoO9+90PGmENR7LPfvrj11q9RoAqu87ZNm6oeR9iTGWXs/ZpWKhZr1+2379mdcQmEdZgXkdZr+07vEca10i6CAISGsTWaVWt8XyNoPEFNEdnWIMGdOV2iJGoKzPD5+HCFZg2KvAuMYRPSA6P9GQGjb8M2CFTFzEDCc2PgIZl+mpCHrKgo2A5kEsfAClYvzUDYV1DlFVIekOyTI8h9e/9PPsrzuAYm1BxoF7yIPkiQr7S+6hJqy6c1BOB3Yyzk9mkKb7YS2ZCMIkOTfoHQSzVTh//HnVozjV4Qyx7lH+a+0ie6y9Mzz/0hfDAFDPhP91BvG76o7idz2TdB7OBpj11U4gac1+UV3AUbFhQ0QG8IYbbrBzzjnHdu7cSSZQP3Dx3nPPPfbFL37RrrzySrqH4daNP3D5AvyB+bvooovoEpaLGNft2rXLtmzZYvgOsIWH+oHgxT/9AAAeeeSRdvXVV3pLKwbI525RjF/CQQdHmz0KtLhZ4yGWoJESGbbidBCGrWgW2g2Zv5nyQ+P6BAx1qFijLNVyE10/QLuilBHGihpZsLIrcD0jM9cSrU9wCH+aAndtwPY7EjbDwpcgMfVGjXMRFcnw74cSWtlipN6WwyBSRZhz4eIAxFu/+XjFKOGzDhzc+i+lPrmaZzG4uJeC1vEZzCGEjwtP6OBUaiWrfeUgOx9DnwH8+gEjw+QOxB5aj+U1vICt1yOUUNb6CwQNK0Wf+xzcDgvCrOODlQjqUZeMz1ypWQ/zB9aPnUBKGQBEAgjGglInmC+C4QSMqXRSmZGVz5fKuCBQvNKzXmGErcqk0LSfNe8E3akUjBQD5vSmr37aLnzqs2x+CR16c0aH54oJEzAyHMTih8V5O6k3cooNlGLk57t55xq59TRunpFywebmF23dxKj10Zau17LTH3uqfe3rd3B9995/l3WbHRZ9H5tYm4VIaN8o21sJAuMTNZufa2Vxiqh7hh90PPG9kPM85XLJ2ox59L2AOccP2y+mnr8ssNv3OnLz0wfI9EEGNSpFW547SEDghgT2Fs46XG1d+4dPXGalMvYgWpOhXEhejLnbQSgJQETBbrttwQ47vGKVUtH+53OuTqVyfG61Zsq8z4BGqGJAIyPF2lK+qGNRMiC1/3ENQB/2o4ChDGDV/8v6VQ+1kozgZViGRuClfr0AbvEcRJAR2a94tihPMx+0FxnHOnBdUyIS5V4Cf5mrNslMB9QuSyTDotzUntT+j8l6lDsJWMlIWKEzUhcmufhV7Dxey+dCyEbKMafsTRnG8TzEsel86YxKp6DcC5Ib9bdAqPa8rvf5U9ckj2FeOe9520mxndJvmnudRe3/Q+lIrV/cS5rb6DXDvaKxgvlCzOxqJxA/z/8tGUABQIC1ww8/PBP8L37xi+2+++6zL3zhCwSAYAIRExh/jjvuOHvRi15kr3/96wkAwfJ96EMfyi4BqETB1xtvvNHOOuusFZ/VH29961uZgDL8A/cxsuUEtCJVro0qwDMsEHLQ4co+WkMSdvFQCgxoc0ehpzIsyOyCq5jJHGDwUC4jCKNogdNlFYCO2D0dPgkWCBG2nksMJ7+/jzpfeeYzD3JKLJBAUYkTzZncK3Fe9Ey6VwR+EgpRwOl9sAVUeGBK0nPguTmOFFSuz/tnEFjtbezwN0ErgVn+9yC5cNxlAabIQZWem/cJmZQ+5rwdmQv/wNzh72S5U4jCnQkml4wC2B9kdnrWrxhACsYU36Z5intK6xcVSa7A0liTBZ/tVfbyTUAUjAZr07l7lxmJyPJFEki1wXUem5hkUgaMA3QI4XehX3Ct7nOR6geq9qTmGQkkYJY0XgK6bodsGPrdIuivVzCWPAEnASAqQ0BNVr2XLADbwAbFLmNS8Z0CCSha3UcMXMpixlqTWSwhmcX7rYJlBcuX7Tu5YLMkDJQ1cgDWTuVWCGYBRtuz9rgzz7bRmtm137nbSpWGDfoL9pM7fmgjCPQvl2zzEVvJMMW4MCUUYSy10sB6hQo7rLiiT/Uj037I9nCKEYTRkK0Pxpqy1PE/6+0xoQPu8D478nSaTVtanDcUxkZZmNKga63FhWRwCQA68/3Xf/syq1WK7E+M65inUCzacrNpnbbZ1LoJazU9i3dxcYmu7Wc8/a0ZS6m1xPjUm1XKXXJCgFBKPTJr8QzLNR/PCFzIYGiYkV2tU1a1ukhQyYGq7qHYXsqXxGhz3lI9UsXuaX9mjFVi8NgLOpSR0t/xLMWuSBrDcKs3FkhOIONB4EsdXFLGrgwDzVUGphKbtgKoBOCkPR/nbEViBI29XBtl5kR6PtZi7HS9VV1g/fAJsGFqX6rkD62pZKOMJM0X5gJxpKpEEHWKP5vHK+dz6bJTLKjOb7xGox8GyHg9usUFkuO+i2EeeH2YVYyEAQwLtIJbTQLxGf9vCQD//3YB/zQGEKATAJDuoAQmoNhijJSEhDawhEBM8BBo0jUxK0suUR2YaD1lgC5Z3PhudugIMXqHskC9knved5P3jD02D5EJKyDEw5WyfTVe/p9qDGYKIVnM2RhDgLU+F+NqJDwwluF4m8g6UIioiLFi/pLwoUBNrAOFFlvWEbXxefEa2CIHb7i2kBRbK2tZxtZiZe+Ugj6omH+4o2RlYuwRsEegnAk4gDuMKcT1kbdKrjUJUraEKjiTiP8FAAUIIhOYKcLgPvfrHMRKaWh/CUBm7t8E3nw6UhcCsAVMgqhbqVJnVxDMGTqBYA6qtbqDmFACBkoN5XME3nA2mPnHGnSpI0DoLMCxocyFFW2sPrBWt2Rt9LJNP9h3AFT1hrdok/uOWaspTlJ7whVUznbKuJqcHCeDtthCkgRapWEcqdtJSGaQMqxVYcR4wP+BA/NWLrUMCSpT6zbYzN132VOefY4t2Ij921fvtE73gG04crPtu+1Om19eZu08rBcyX3td3z+sl1koMEQF8ceoXwgjQm5ehYMgHlBKFf9jjCgrJHAlBYxkpk4TfbULrAWI5+S8DHrWhRsYSSL9gbU7S9ZvLVq3CVc1WGjvqEEDbVC0v/mbV9kY6imyV3Df5hc6NrWmRjA/6JdsdmaBAJXgvzNvreWyPe95V64oqYFlkgwSYysGKwKYyPTnRomYdWdn8bqS37yUCBzv7maVXJO8gpEXAZbOHRm4ULCeTGLqsx0Bh84BABu+O7rsdU41zgxchDqp8T1u1VRD1LVo7hEZBigZaEqGaZYMQUPKDXSMn3F03eRqR6x28rgoxlr3iUApGgrxGXRt1jouGa6QKXruaDxKluge0j+SGVG+CbCr+4cA13CoTq6fUikiykkveeOGRN7+Tec5ssYCdbpP9r0BbEtH6Jxo/Oq4Ez+Tkx19W1pcsstfd8VqK7j/rgAQCw3X76tf/Wp73etexz0Cgbhx48YHJYHcfPPNdsYZZ/Aa/A5WLyaBvPGNb2QSiPoYIonkT//0T3+mJBAwgCwEndwhEnBiBD04FpmGeUNsbUwyWCGORMIU76sQZiz4rPIA6sgxLMQ8rmRgvdSkfFiA4PosbiIJMwbylqqG+mg6VMr2pbKEwILCRdmUEIeSHeB+nq0aBSQF1SHczhIwYO04JynWiYxcAog/TThFoeRCOO+zyz9T+RRCWRUgRZIDmKhkjSLQnJUYAAjBzKB7BJlLF1RsvdTpWK3qbl3OSQrYFsDidzGjMrdwuynAXZaxCnd3unn7J7bxajXZx1bzgHmCgvd+q96+i0HoiP1CgDgSf1DXLbiRh1lAv5eD+WHmRK9hEbkmAy+qyk4grAOIIs9lJnmUqjUmgZBRqzTYFg6lYHhdGcCwxvmhGw8JAW13d8d5icaGBHmmwErGfc2etmn/YUwKJRhp1AhTACj7zaZZsUoWkHuN8yDDyhlUX+PUfL5XtH7Je1OTiU6Zh3HPRIB887Uft3Oe9AJrtxZtcX6W8/fEC8+2a794k/Vtxqr1DSwAPTI5ZjMHFuyBPbut3FtEWq5t3rqNcuWUU06xRh1A2ZPJWHQbwKDg4SA0wkKigMCsF652zkZKVIrNnxVdJsq2vNwyG3ScVU4gGfcUAERHELQJQxYwAVAPzFkC1qk49cc//jJbt24t3cXFysD27GzZEUdib5stLTVtfHTEDjtis13/jbtt8+EVOzA9sN954ZUc2zD4EogSUIuKWnJMMiQWdPe5cddqYdBJyR6Bvgo1JAnoPcU7hE3kO4lrzlqJ3rKS7F/a2zpzESSRrUPZFgZp+3nO91HuquR9xWwn4znKKhnkKs9CeZV+IlCM4TfxnLLbD9sU+ockm6OMdpnp54myPbX71Droc3DFxrZxkf0SuFZ3EngZqthvQ+Wy4hxhPw4n9yi2W/tAe1XxtZyv5LWKc6o5gYEZwVj8vshq6np6mVJY0PDaO3jM94NkTDQ+BPbj3tT6sY5mq2W/f+lrVgHgLzIAXFhYsLvuuouLjUSP9773vSzXglp9Rx11FIHeVVddZR/5yEcMbl2wb9ddd92DysDATSwXL2IEYbGrDAwSQJANfMEFFxiA4J133skyMG95y1t+pjIw73jHH7N+WDzI2pja6MNATRaZNmvMuhpm+/LN7wLED+TK7Ckpfe/ZgcbwQCcu7KIQ14HgYU4t4aCmcro8sUmDvAcormV2b2IH1b81aymXWD6Ct5RAwsMKT2xSwlIAhxJ8WbsjgpFc6eiQxzGvYBsSOyABopZbUQBkcZkAgSqfQGbPO1sUSjWW3fF2T+m1BCqlXGISTMZsJrZRwCVTFGAcUya1l0PxuKysXiLZmyaVutYSmZv8PN5DP+ACFGA7i4/y9c7ZMgnkXLjl5YA0vyvARDI8UnEezwIGkEKBZwJZZwDL9VFngkoVskPMDobLF11CqlUCQAeCzspwfdKw8PpwCYc4J2K64b6E60nKMAPYIbb0y5//lD3hyRd7MlUCSPo+F/IOOuMP29UV0JGjwuSjeN7EzjAxKfWuFiuLOD+A//17d9s5jzvNvvedn9j+B3bbMcc90k4/4yi7+es/sNPPQleQO237nXfYrh07rNGo2/GPOj1jbphFnhQh+sLu27fb1kwdlrEefHYo/8CoH9h/v61df6QRb6QErGyfA7CwFqC7vbFXME88o4ZkDSR+dKyL4tL9nrU7iywNA1c52WSeQcQLdgm2//bvXmmou6h6ofsfWLZNG+DK96xVyJJmC0Zg2dqtgU2tPdGecN7/NNVCHt5TURFHEKMzLlmCsccgfYKrArJCExhMbDz2O84990IK0aDMCUo/GjVa2wgulEEdz0YGBlOBet/sPo8CqTRwQ//cTD6FGECB3mjAx/2VsYxDoG5YfsmAFlhduX8B9mD4rQSVYO9y2ZzLcgBAGLUah+6lsRKcJqNQPYZ1TQRaEZQNP5PmHy1FsxZrSZ/gNZ1NuaUZlxvinmPCoxtqeds3ljNKXh6NS2OJrmKBTbG6uo/GtkIIhHhUjS13b/dXYwDDZP3CuoAB5gD4hn9e8IIXMLkDmwRxeAB3sRD0ySefnH0EDeSHC0H/2Z/92YMKQb/85S9nIWg0m3/pS19KABjBxoMGMfSCsoABSOECljCJsQsSAvGgauNHYCZmILru/rOYieGDHwWA2CIcyHioNT4yNsnSJeOE+nOpMb1A3qFYpCxuh8SFU/nsTpLia7z4bQ46M7YyWm+B9YnPMKxIWC0/tBCickGNNSjHxEKKQcrWLNXQEuPjwhyZkO7S7LN0DrLFRiho2YaqXHYmq9OxxugYY2NGxsYyt6N3vYCLzl2cmVBM1n+rtczkH58bz/Lm7KBumxRCL5XvSMqm22l7j1XEd3Xa/k9AkaVh1MUhz1LlXDDOKc8E9PlbCYRWKMAQB6gizErgAOvpc+O1G9EKroKs3xLYwYrVG8gALvHvaq3BOnlkTq1kN379y/a4C56WFdGm4A6uMQpdJLMwvtELx9JoQPZrCvyngkLpmxSrCSXF+oWJRUW+RL1Wtd37DhAwyt2I5xsODRDziXXy+ME83tGVilgfr4GnOYrhF82FeY7lpG1b7fAj1zG+65Zv32kP7NlrS80WjcUbvn6dzcw+YAcfOGAnn3YmE360h7E+ZF5S/UPFjmIs37r+K3bOeU8mq4V1np3eYxs2HeXPS/azRVe74sy4x1JmJ8cOkIc4SlZR6XAfgOVbXJgj4zfowuXdtAJDC3rsCMLt2S/YYYdN2Ac/9OJUziQxUAD0FQfS6sUrEDo727NnPuOVtmbqqGyeho1Inb/Iwkj+yEDDNWSQUkww/garOzpSp+tf7Jli0YYNK4EB3Wf24G4bX3uYs+PBCxGBQJQheh3/A/RnST+pdikNChhCye0sA4NnN7HMlJeprA+z85MBKfCoayMo0XMNz5nmCgCJmbuhLuowANV7vFfKiI7yXW5YjjPtdY1foFuyPgmhLAM4MyqCLuOapXtRzqZ7St4DlGdzLpmWPq/1jnGEudzOwSxZXTYtyIFglKWS4ZHF07XRzYxxCHBKj8oIj4Bba6jnBS2ytLS86gJO6/YLCwD/K9D1i/S+ACBcwCpUGwWXNqSo9AiqRHUPCwoppwgSJSCiJRrBk9zLeF/KkawHa375P9xD1jj/BrGQYmgi6JXrl9ck1m+F0lYtO72buoTo4Mbq+BDWigkScFPNQQACzgdi7VJmcgYwk5skzuWGSLNTAAAgAElEQVQwMOffqaWZhC7mLmZQMmsVYLdYtlqtzj6wcHsidg2uTjBdiM9CzTvcA683Ox7YH5lG3V8lDRVEj9ebzTZZixhbBMscClmWNspuwO2L+yLWi4qjh+D+lrVby2RtnN1B7FuTzA33AdzFqeUewSQVv7+XGxbuRoygJ56RbH+p0wIahWWJLIChDloBAEvVEfZz5d+lKoEf/y6jDl6DSSB0b4HJwn2S+41jST1wtFfRyWNheo+Nrz+CgegrFFNiiR3oeFmSSsms2U716PpKDEEZlTxoH989HFcbWZlobOk67SHOJ53LOWBGkWeFYCwtLdrFF51hX7j2u9bsDuwpT360feozX7cj1m+2SqNoc9MztmvnfdbptGxiYsJqY1PcUwL5mnMPJfD4rkwhGdzq/kxIqlHsJ0v2oDxM6lYDt2+763/jvMwd2MNsY5xEGYge5+esMsIGAADbrSUm2uA9thAEWISh0O/b2HjPPvyXl9vIyJihEG654p0UsAdmpjtWrRashs4pJZVz6tuznvV663bHVgT0ax/pebUvdU4UBkAGi/XwUCfUQwykjBnfxq5F/h7Gh7OjedI+9rlURQFnex1ARBnmMbNA4ZINAvuRMVMYTlYaK3pF4BZOWcJxX0VgontFwHao8zWsl6K8WgFMQ7JEtmfCMwzfR71/4z6OvXXZfWro83GtOH7MX5KxUa5J13D+cZ+UdBPBE2VVYvX0usYYn1H6xQ2alQWfpZek8wROxerF+0p+CNDG+cfn6T1IMlH3ic8bx7ZiXgY9JjitxgD6DK0CwOGT9jP8LQD4zne+k4pRG9rBm8dkaXNq80fhpM0u6yjGUuE1HdbMihmynoZBUQRCULoIIo+WocpTKHsuKi8JGAlsF8EJPKb+pMpmk6CW8pQggQsJ8U/wViJOjGxOKqiq5BBNc+a+AROlUoSxzlWohZVdm8rMcD5S9Xw9Q7Tg/TUAP7BMBfY3pSvYSg5qEPdXLlOYsBhyyRMccF+2OUu1ryQUoUwJ/gIjqbnX2mDuNXdwzWWxSekzqG3GXq69LllGZMO2l5eY0ekHsk8mEC5glvtIyQ8qDQPuDT+MKEstt3zeYwutnN0Cc+eMoe+BWAJGAIXuvwQAq1WwoXCBV8iQgpxDNxAAmsbImJclSS3DyKok5lB7neNILbDw2pqxhn31X//Rfuncp7HG3VLKOswUctYWymv/RVaH651AD8bPFmOps0u9ig4gvi8BEXTm/Lx4TDBK2fjeRE08z4DX92rv5qDe3apbj95kGw9fY9/42g9IfLb7A3vc40+xb17/XVs4ME+3b2lgtmvPXqtUizY2voZxvxnwYawsWGVngDOlj+znoPQBdjGemZk5fh619pAFi/8R66luGeiOsn7NuM0vLJFJlZIEyEOSBwwHyhQwG4tz3DtgnVFup0wm3OMm69WB3XzTv9jd2++y3Xt22Nqphs2C7ezXrNtrWaNWsHoNRtjAe4wXBvbC336Pzc4gJjWvpyZlGo1YnWWtAa9XGzO2HMm72ETF7IDPX4HhAfe05GNkgDSPGYBEzF+oTydGyceWh8dkgCC1AOP7qS2fg8/8PkgyQeyzPB+xZmoEJivAjs5cYiPxmRhDF+cjgtMM1KSkLe/3nce14doIFjVnYjGz7iQq94SC+ymuT2BIcjyOASw/DYgEuFUPUEYF3awsMZQXk4/jwHsuG3NGT5+NpbG8EUJ+rdY4X58CZS7lYAKVEQRKhkZGL+rUqK/03FFHUj6GCgwrVXqfcne1ELTPyioAXLk7fqa/MgB4zTVWZys4j4PSRpZSi/EL0aKBSzHLdgzCNlo0EnhiBGWdxr+jxSoFh9cowJipkOr/pVgjMX8ZazfUskilVMgApkMvAaNnO9RhY1xVyvSUwPC+pnlMlpSK4vUwX9XUGmwF65ZiAXU9BenAlScZjBD8LcEpJY+/WeSYzeqRVIBeo2XWskNP2xJ+r6HHrbc5qyCDk10TEHgPIOiCTrFjWrMI3n1dcmEnoUXBCLat5xmCGeABcwf3bhdAsGmtdpPMGGNhumBxlpkYwk4PsKJR5LfXofuKYCa5vgkSQkkHrb3mOFPUKXkkU+IhAYTPgaLF6AMLNx2BS5UAsFz1ki8jjVEr1WpWRuxfsUzmCvOCORTo0b0FsLxHcN7yjc8PLy8LH3vRWjyLKw9ndsRGxbXPjJGBx5BBcGuNZRh5eQlPFlE5i2zPhYxfGSmaF4Kies2azK51NrSU2NGl5aYVSz1b6JTsvPO22c033GGPeuRJ9p2bvmvlqrehQ5pRp7tkteoYW9Lpvtk5SclEBD/J+OFeSSBQz+GK388XAC6eY3JsnG3x6GhPxYUJalvLLCcDg641P8/6lHgN391cWrBup0nWD6VxwAiCzfRwBfSd9aSibB9az0pwfcJIK6V+y0m50yXaW7ZKFaEQbX42nj983/z8rE1OTmXxW1H2ePZp6kBUdbe9ZN+BAwds3boN6SzmhdmxP7gOKR6MoRiNhrXA7g25Yw8lF/uon0lDzzP08ZwCB3h+zzB2+UejGHFzyfsgQIZzjz3KPdjveHmXIa9EZMW0PzU3UUZG0BorBuhZJHMdLKekoZ/iDhbeonGVCkTzu1MRaHgadN9D7X3pCD4fRBo/671/49i5hqEnsH7XXgUAxI/cvHp+PV+uizgaBxgp/jCfG9zD5arOJM9eiGOMxkVcazcYksUQNPUKUB4KbOvsyBvkuqNn8/ML9rorXr+aBLIKAH8mvPegD2WdQK662hqjI5mbRiUqtLmjezBuWgFEHRhdL9ZCByKyhwKEUegcysqUYAALB7cPD21ymeL3mMmVgQQKSleKPHApi5AWclYzbyWYo+uk26MVXauAZctZKAoGlutA+Q9YHSkWjFl+iAPy2mgrgF/qkqBMuSwuKt03gkmVUpAgl2ASSEV2Kwsjo78tAFAFCR/jXti4Wuf/uB86XoD1Q49Nj68pkAmLP1TUcKsTMKWOL2oHFer85QwXynM0U1cPxPSBgmgT8MCNiLltLi9Zv+Mxf632MmO3wBD2+mjxlZc/IVPMCeyv6KUqQReFpQCJM4VhblOJEsUAqg4gnhdgGTF+iAEkE1Wusk9ufWzMqoy/Q1Zw2VAUGkyp9oIMGK0j/m6iVy4zCgHwsI/yvtged+h9rKv1Gnv8jozWbXmptYJB4XlJpSukMA8ceMDWr9+QYjnzEku5e9D3qMbmQeZiR8FuVe2wjQ37q7/6gH3ykx+zpYVl+4M3v9Om1h1mGzdutU4LrrKyNVvzVq+N28LMQetg/1eK9rQnnmX/eu23uYTTBw5asVy0hz/8OFtcXDTEGyNBjfGRAFIoFkwDws+SzhbduilG1veVv8+1LZcI+gTsI4Ch8kugmawe+gB3lq3TcgOh225y36AWIGIA+XfXWU8vK7RyH0WXor5H7JXkUTQ6JVvkIo2skc4dwVFihOHmFTDg/wgtMGf4gDg5D+lHoIXnFr2oh2J+BSwUH6q1ZW27EFOG8ySw6THNOMFec1M9lAUAtWcd9Pg+QoKOvBtMlKHb0/cOitlHT4fkatxrmcEy5KGJMlpnNcooluZGzdYEgnBvl2nODMb7Zq5zgMUEiABSefYpsVbGo64YcwgD4nlKgA+fj6CLsiN5P5iFnYw0RtGmRBlPPsw9C5KFbvylpKWUuSy5rn2iufPn9fnVnsP9PU7bDedhcDesN/F3BNgiPHIDy+/jc+jsJ87rFa9/4yoAXAWADy0AvPqqd5ABjJ0lpIj1TdEFJWvyUJakrJ1MkSeKP5aR0XtS/Ppbh3RYkArM8d4sAJxncEnpuEBzCz5jD1Nlex0+KQYJ7ggUlUmsQxkPclQUBHxMBshbpumgRiCX/c4uCB6vKCWUrR78lNjMcOGmwy6hy+BzABYWCHYwVxudsHIpMViI8wPQYZ/XEQcOBWcY2Y80uJsVz5U9bxZzp/i7vJSH1pn/sz5t6vcLQNfremwgYr3abVtaWDQr9Oi+azeXqKx6aIfG69peyR/dQVwjkZ2Au1CCNBoDUXnz9yJ7IWTsqzKA1SFBSSBsA0fr3rt99IvIlq7a6MgY3eRwUw5KZavX4O5ErTgvjaO1kPKCImu1F63BTGKP11IYBBJlHEQ6GBypV+xf/+mjdu5TfjM9izMzrKvHtmi5K0fGDxgyZLRqf+3bt882bNjg2clJYSg2CNctLO60N7/pdba4uGxzB2+3anHJ6jUApoItLPcM0wxPaKVasL/91PftwP59tmZigqVSHve4c+zf//07LHEzKNTt4qeeZl/55l2Myeu1F+1pv/pk+/Ft99ns/JzPAxyxg65969vX27mPvTBkwueAVMoO8ahx/rDX8HfOouLhnSGFksR7bPGW3JlMrOl2yRguLy2wbRrYP8YBojg2Oh4sLuRFdEO2OealtdwkA6aszpy98RjFYaWK9YqGrM6XzhtZIYwtxdb6s3jfV2SW+94Kz8xwEmd0ao267dhxtx155NHOxGIPpCQagiHObQFVdzIQpjEivIHnoGAEvWAABQIlK3EtzpbiIZkA1B+w0DljAtWuM2UjD58nytfUjScanlF7SDZGJnRYvkvGetjEypZtiq/Lzgx7vedsuWR77A4i0JXJo8TeaYwA43j2YYM4A5Qprk8JJJzHrMUcnhmJfV5rk6Vm1N2JIA39r/OKBLqnEuF8bO6alp5xYJhYyBQWRT0QSAXf5874x7mMiSOad32n9qWu11xF4OyfIZr2VnCXr9YB5Br9d2gF99DAtP/v7pJnAb+DbgtZ/IjzgQIUmNOBjUAtd/Hk9HbcwBEU6WBHxSEGD/fBIZESkUCXBSg2EvdoN1scJ9g6ATR9J70oyeokwEsZmwIWUtCy6iTM9GxSKAInuo7uHbqAU9IH3aIrYyTx/qEUUgYyCkWOOQJAgtzUXF2ANHMBJyULFy/ng+VOilZqNOi6q9UqVqo56MN8wAEE5VhEjFvZXc0UUGpMn4R2HkuWYpsSaKml7OAsEw4CL8VtCQRC+BQTU9hqLrBpOuO35uaQL2vd5WWW9YAbGHMBtgfMj5f1SKwrsrVTXJ8ARdwzEaBrHThnsbN8ytb1ZwM4rjKeUgAQwLlSb5BBAQMIgTw6PpmVh5menbHJqXVZB4xDGSNiSbHOriycEUMsIBJxxBRg38IqHxv3tUBpE+0bMTzRSNJeuuEbX7UnXvg0W255ok12vnpmtZGSPftpW21yoswxLiz2mcGN+yF2b/3ass3ONa3RqNn0Ax3bvadv1974Eztw8KBNjI8SvKjFmrPWFVtcWrJGvWwHpw9Yc3HBsH6btmy1tevWM6nHE2Oc3SIgoEvZwZ8UmPYumBWdHYB0Z03dxS2jJ2NvkvEjBQbF2qKhAKZv2ZYXl+jyBQPWWVzwAlB9jxdE5jBY2IL5Wc+UJ7PMHXBqbHpP1w0bkNpLESDhd9RyHB8f92QPhFWoMwvAWzK+WDOy07VqvZGax4LdQavB9P2IAQzdI1hzUmx1GvfOO2+1o084zVrNdpYEgNqHWF/0EsZYwIISNJKdGpBlZqxtqlME44rzk9yZAjEqp+WyQ6VYXBYSYAQAOBynGM9YPAdRBnItkPOfaqJGMK1zArB1qPqFKwAqDMhUbUG6IQOfqSTTsBEYQVbUgmIA4ULODNZ0Lrn2gZlT4iC/M3g+8li7fN/6c7ucZoWIxL45MYHzASYYvwMMulEQ95QY6QgeAeZxRnQ2NLd6nriPhwkE7WOOY9DjWV0FgD5zqwDwIcCFmQv4mmuyTiC+ob3WlYpMx82rWDEKq3QAZXXHtkTDil2HQ2BJFnMU2lKW+eF0ZQNhSMAQMhNlfeHzOqjR/SsAKGWt6zWuyGiqyn1seRSvH7bUHHxSPAWaPl8QCQXND7urlPKeuBJsXvMwLxgrgcj6dUzK8XILUEaFYhUBbzYxiR6uPauOjGeJO8hyVewf3XFFJDzkNavEMKlGVwTZ2Xem9ZSAguKQ5c//IcC7LQpcAD0wOGADe8kd3IEC67fJ3oC1gCvVC716+RSuM0pYgLkIrmcBwcz6T6xtND4AAPUZJQKxCwHK4AAQUuEWye6xPE69QXcoaluCLZlYs5bz02iMWg+MpG8kPp+UWAYwVrjDHegDCHqruz7b4sXsWwn7aOmLDRA4Glau6Js7YO9nd35hOvh8/aI1al37rWefYPMLKPNRYvbrwsKctdsoQ2IGMu3Rp43b/Ny8jU+UbMdPevbCl7zZnvjU52bM9+S6dbY0v2Dz83NWGBTs3PMfYzMHO/b973/XFuenbbnVs4nJKRsfn3CQAMA3KNot3/k2i8+P1cv2D//49/b0Zz7Xugmwg0lF6zWM89s3Xmenn30BgTlYWiXoYA7QIxfXIBZwpIaA+WYeZ1gYsPQL5qzTWmJmOZRavV61uQf202BYbs75mUePNxg9RQc9mSGX2NVoLERFHJVoZGii8Sp5RVA7cOOt3hj1ckKpaHitXkWeE/9GGAHmQW3eeugxWHSDdHRsxG647lr7pXPO4/swCHh2qyUaBACZ9dERKw6KGdsL+apYazwbz1ZIskKh6YP7d9nU+sOs20bsrTOe6KOscyIDWN4OyW08J0JBJENlXKxgbYNLNTM+EgiL4T65cZ2XUZHcZ93R1K9dMlYynS5p7Oxi8tYglAAVAEJfY53vYbCOci48k6pvGOLnMrlBhm/A4tCSUVEdMnkuuYMzozrFLEbZ47/nnaQk1xV75/fOE7UgC9z1m3t/ol6LzB+e7z/zemk9GFqQWGbpP62xZCP1SLdty8vN1RjAtNCrAPAhBIAoA0MmKQvmddZDClIgi26PWi1TNBLKikvBxo0HOwMTocWZCmhGBg7XyTWiA6v7DLOQeux42JSNllmW8JQIWMF4CgBCgjMDHGyl5kpGQC8Wf0XsSvxOlYZwKyQvRaPPxsMbQUXGgoW+xTrgUlQSruq8IEaW/WvZ6myEBY7R6mxyYsq7bFQr9COV4RJGyZMi4tzy7EWMx5k/D9jn+HSIEmsTlUBkrPpAGyl+hsxDF2xN27pg+Dptshfdtmf+Li0ukP0rwp3XbnksHXqi0n2KeKbkspJLHFYtXN8xwD+Ug4ggmlm0yXqnmwVdK+AiBkBO+xQMDYS1F4N2ZTs6NkmmptYYTcYMuoNUOW9ZG75CyXbv3GFHHXMM4xm9l3IqZYIYKrQx63ntLri50Y+224LQXglMBnDLJaZzYX7OxsbH7aZvftlOP+t8skwo3q6MQ62DsrKphhITPlIze/6zT2Av4FanaJ0Wxgzwh+eu2uxs20ZGCjaxZtyqlUXb/pOeHX/yNrvynR+1Ss1Z/M1HHG67du6xVqttT7zgVNt/oGfb7/qh1aqjtnfP/fboM86wW2/5vq2ZWsv2gGIh8f83v/5vdu7jL3TGggWzHXzlAL1ikxMjNj27mHaR+lAb74Xv33HX7XbkUQ9L+86TgjCn3/jal+yss86xFjvJdK1aHNgDDzzgAK/VpGEBwNhF8lCqtwhDBN+tZAjfCISdvC/Xhe3lPD43ehJ01nUOo4uOZy7FC+N9dJGBG7hYQhxkiS71Ix72cD4DWszhf7wOw8dDNuAexr4E+w63X3Lzpr7JqlGIz+Ez5WqJ8XFgNcF6FpKhg++GEYX32si+HyDeCy55AMOmtVN7PCbJkFXvJNBcz1yk0XvhhoR3MMLPT/PiRG9EBMeZjAiGkGRANIolu6IakmEZvTN6PzP4oVpSQhjG0GzlyUzxWi5zAm2Ub1UPseC+ZMF9sJv+jAK7Aq/Ry4MzRt3C5Bkl+awEr/G5xHr7POTx5NHg8FqcbtBL52g+DmVQx0z+OLZIQsgTpvmXDNLZwX7HXL32ta9bjQFcZQDjsfvZf48MIDIRpWQl7GXZxde16aOFGQWIBItcFXIrrXDjJIUgl2M8XMMAMr4nAR7LJ+h6Mk0pKSN+N4AXAF5U6jqsHFsCi5EZlKtUbMKwYMLrtPwQz5ZKh2gcmUsvlVhQ2zF8DxQVwJsEZbSw9R3+XsWDmRMDCHAjAFhrjDABgZmjyRVVLdes3el4WQ/ElBVQagQgJm81lrk0Qj0tCiusRVLw0U1Od1ECiAB4UMRIZJiamKQCQg03gLxBD66qJcYHImjd2svWbC5TkXuQduqfyvZmzgBGS1fsDV3Faf2kuLROAik+Xmf88MOi1SlRASwp3J/Mki6VCAxq9VGfq5ExZxXoxvFyR9zjqeYdXNkgdQAAUIJEew5r+tUvfsqecNGvEEAiHg/7DFm4sMYj+wK6KKs3lko5QPEDNGCT6TlVZiUKeipHJD10W1axov3Ba8+2QbFjzeWerV1bZ0/jThcu02ZWVPqOHx+00VGzhQWzw49ca+9499cIQuCaP+LIjbZn90G6Vo866gg7/thN9tV/u8ked+6Z9tlPfdHOOf98+/dv3WJTa9dnwgM1ATHPWJtqxWuV0bgwy1ps8ezjPCWgS1CUmFRkGK9Zs4bu8Ga7ba0lByxS0Hi2coo1xP4ACCr1OjYzN8u5aS7OMwkEe4k5KCnMQ4WEo7zhWcPnQ/hIPKtSmlLsmmuwcTQ8kRCUxo65xzqNT6zNOsTAyEVRdeTfYt3BwvLsEoDP2pr1G1bUhdy76x7bctSx3v4v9emG2x5nXXsZBgfXN5XZkeyj1wR7h2EwXWs1l5nlj1jaxcV5xgcihnBpeZHF1ynbUgybZGruBfGkBCZihAzuYQCnRf9pLNwwmJGcElunvRyNRX4HW7/5D89QkpOI1RM5MHz2I/gaZhwpj5IcYus4JY+oskPoiIL5VHkW6aA4bu6PBLrdSIAcdoNBxruvlVy/cgfnLKPi+yK4jzpSZ0FGiFje6EGSbo1AUABR8677aE9znQeQs63VOoDaX6sxgD878NMnYyFoMICKf1Dmow4rNqQOn4SONq02a7QoJXAivS+2MFrlXvMMQbmq8J93/hhmAnUvfB8TDBLbqAPoRlmuvCV4o2tO94jfp+cZBmUScjqUEQTyECM7GXFISWlGYRqtbh10uoED4yYXbbw2i8EiI+Tt3qiw4FbDv2KdbBKSG7BeJYCcxPo4YHSA46nLqVl7cpM485dnp0XBF8cewbzWEcoWAJCxmozv61u3s8yyInDztBZQD7BtvSZYHJT8aKeuDl74md8FpjWVgwF/Q9dXyJjTXluhIMDUgVVKbjmOzRBYr0Qgj93C642GJ3uoSDZjIktw+zas0qhbpVihazg5pzymLvUPFTsRrXcyNWBPGVvat1q1Yq02St4s2+c+9zl78lOeQSCKrigyGKisikWbm50mGPe9mbNn2rPo+OH7y1vUMb5L9Q77fbvqLedbf9AxtJUEoGL2bb9jrWYHlW5sbLRuM9OzVquO2/z8EntnX/W+WxgryMSBQdfGR9dYCQk6Awc4T3rC6falL37Nzn/S4+3vPv4vTHbZsmULM4MxZk9GKdj+gwcJ5P7lk39vFz/rOfzur3z5C3bRUy/OSt4wzjL0XpUSJ9vVBTBDuZzOysxgxpR2ydqgD3CztcRnbi8t2tLCPGFle2ne3cNoJ8jMWzB7K4trZ2ckdWGB+zSWgxGTLxCCRBjsBTFiMiCwZ3JGFhnkcAE7W47C6iitVCzXrFavM24RoRe6vm84j0kmdlU2a2VrsayaAPeA2Wi9YK2ux1R6sWtPWHEXsBe2BpuOfQHWD3PA7Ohmi2zn0tICC62r3zY8EzpDD5K3CSBShjKJLB/bMMOUG2B5T+xhUKZrJOujt0RnhnLOg7Az2Yy/WZMAADB5EiSXh4GgvB6It2S1gJBJy+/XPaKXIIFOlbyR4Ra9MTHuEedT74nBjfoo/7yDPrl6FV/ue8qBqMJC8k5G7haOMl7zpb2odZLrPHNPp+zjCJKl13y/e5FrMOeXvXY1CYTzuQoAH0oAeCWtXBVfFfWtAxE3MH6XW0OKMypvsUja5AJQ0WqUtRYPefwugSYBE1eSeVZYPBwZs5gaqmtWooARqBGDKAA4bBnLks4tvVx5SyjK7SOXropS6ztwT7EVFI7Ifk3ZYZpHCqXMTevFkAVANV+oW+e14kre6SNluSLjt4p4pVLJaux/i1qAdVrbYjWKqTwMlB3HXXTXPL4DggtKDSCawD65uMWmxPlTM3TGLLWd8UIGJ0vBtJd4P7hFkZnZ63etvbhoPfR5TZmLaF7u1rLHcBIEwk2caqfh84qB0VpHa9z3DDKCU3JCCu5GzKMLWp8fD+BHcewK2av6qLfCGxlFEgiUOYBhg91TcD2+C6DAC8TmRofCEHwfgBmomiFuia67DngvxoXxugTitB/cWneWF0yTDBu/V55tLQCTMcWFQhZ+gc/h57KXX2BrpwZU+o2RGu83MTFu99+33yYmazbSqNiBA7M2NTVp+/fNGkJk/9f/+0Mmd3D/GMBc2wqDrj3wwEG6wk8+9Uz71g3ftIsuPt8+/5kv2fqNGw1ssvq7oqAx5zTtlVKxRhCnNoO8cbFA0I/YyiKKtPfzft7a20hcqI00yPTWqmV276CLFxnByOhte1cVGBU/ufOHdsSWLewBvDB3kEWguQ/YbxrtBd3w0FlmrB4AGVyqqb4kFXiqzBLPdWYgwmAggHAjk/GxCDlJdff8zKDcSyXroIMwArB34+OT9KYyvrZcYsIRQgqwp2A8j44ggST1yk51ACP44Bf1CyzF84VP/o1dcPH/YO9u7XXKDLa+c7aU56HdTB1C+syyB4uL19DqD7Gj2HssG5PObTRw9fysG0jDqMdWawI50fCVvJVciwa3ZIHku+TZsFEs8BeNl2hM8swnljYa3/FzuicTSdSVKfVf12ciE5ixYt7HkMBQrmA9E3VPEmTSDwCJOO8iKpTVL10mXeTP6kalEhCdGPF9E5MBlQgi2RrXVech6gXJdr2medPnpdciEKQhxdanZotLC3bFFW9adQGvAsCfH/zhDjkDeCWZJVmU3mA9r+8UN+xwkDBdRak8AJCZxR8AACAASURBVK6LQkIASxs9/q/f4wFxgbiSyRsGl/pbh0nfwXpXofaUgGoMto4HNc6ghFQEABGcRjAp6xdghs8KFihZlivBk4M6dBeRcJUAzsuyeJCxhHAUjGIACVgAbKp16xWKNjI6QfAIIEhXJzuDIAGiwrkjOErrkQkY9CAmq+jxU1BiDMpODJwr6JVM1Yp5TkHrdLGkoOXlhRkKQ7wGBYYyHrhPt7lozaXFrKI+2UPti1QLkHOoeolQUMlvpOvi3MMVKAAI5Y3yOxC8vg7JxU2XnpfFAUip1DzmDy5gzNU4gCBAcgHKHAWhPQ7SQQ+UFGrOobq/ryCVBMBKF/UUvayEz6VnptKdTKDvzyZhf+ePfmA/2b7DLr74YtYGBOjAONX5wxVcl2smRXbrrbfaaaedxuxPxBpC2X/gvb9v8/M/IvDDddWa18RD/bzDNm5gooHH5w3stu9P29q1JfvAh/7Njn34I+2bN1xvc3MzdsK242xsfJJZizP7D9i6wzfb7bffbs981pPts5/9mu2+f7s99rEX2HLHmV0Hxp58RAOl4nOsfXHzzTfbOWedTbe59rz3o/ayFwhSZ/HmgbO7999/vx15xGYvBWRm7W7biv0OsipseWHZ2q1Fa5Q9yWJ6/0679977CHKhqAHwsD+YQJLaCQpoY3wAQP2uGzxwqw6DAJ67xFDqbGVnn3UO3UXJYuI9swZyicpjKcusxKxxhF3UqnWGEOBaJBihswzug/qP9ZGGtVper1DARR4InWOe9wSSNZ+cqyQzEXOKa7s9dEFBEXUkxyB8wjtNNBcXrdtFnUTvt40QCz576rQjwOF70cvI+Hd26UFwBstj5iQvBYhkoGuseF1uacmx7H5pjys2Wt6DyJ4B+Kukkfb2MHCM18cwG/bxTQALrK+HviSjMTGLDCchgE/PmGIEYwFozSvnIDGOuWxV+am8Jix1B+RI6qfOSgfpeyiDUmx6FjISClHrXLCEUDJE8Rlcy9CP5KaOaySAlxvj6RlDJQCMAfOcEQ5pHvA3svmvuOINqwBwFQA+tADwnddcbXWwAVnj+VBMOQkXHYKMcUsHLII/ARyCjaKzJsN1kXCNGKEVleJTfT18Fta5lCruIxo/gj6MR8Aqp+pXVlzXIVLGWhTM8RBSwCelrmdQJhi7WTDbzQGdQAoYCFqcqdtIpPNXuBVYvN4/q2cSa+j1pvJuJdHygwBnBwuwecysLFmlMUKXLz4/PjHFDiRFsFqFAZlAKBt3A5fIWPT7fm9mzqb2UZoDZQpz3EjE6PtzRqaWy1Bw1wPRNfYCyry0UBAaSrjtcU+9ri3Oz3mgfs/beeF9fhfX25NJ1BYuriNfTkBUu1qWvKx1rbWPGUBVBkoOAAFeAKxwr9ooSuU0mPCB+YPixv9wDxPgDJDM1PD4orQJxydGbXF+gcpHTLDvdVeiYOMAujW2m66/wU4//XRXrKlmIa5DQWzMJ77va9d92c785XMz5YvvnpycpOEFNgk/KHKu78O94R5enNlhf/xHz7ZazZlvxp9VqgSEo2NVq1dr1mZHFncd/+TOBfv0Z+6w5dYD9uz/8Xg7sM/d9NVq2Y47cbO99/2ftU67zevPPf8s+8xnrqOCXTcFoDPCeKivfvVaO+/8C3k/sKKsJdnrJRe1gwsBdRbjToWjpQgzUAPGk9m7qXvHwKzTa9uPb/uuHX/CyYz9w7UAUWAou+15+4PXPcPWrpm0Vn+NveR33mTNTosFyBEPCGApxblu3TomjTA5KbHbANlkclPcmYw5MIVQpnEP8XwVyja/uMB+yCx3wxZ9TStVJ2xsdNya7Y6NT045614q2fp168gAA/jiNczrvj277cijt7prHqk/LOmEkIFSliHuShxscd+KlXoqieSAmg3nMC8Ib0gKnh4OFFHveOYw1mfH9rts3dQaAkCw7J0uSjEh/ALnyc+j9g4Lc+sApfAPvMZ1S+BQ5xtjEFNJMFf0Djfo1KKzKRCXGa0phi5dkCkgyfMoPw9l6DvQTZ2HQn/l7PtSqaVoBFMWpWekDOBYUzu3JFtwT7i4cW0EsTrX+s7o1fJnygEmQJw+ix7hrn/8uzUPAJqZbEwGocbEYv2pa5K+V+dCujDOa5wf3d9jrn1dpGNZyzB1JsJnVrOAc9yz6gJ+CDCgGMB3vesa7y5B5ed0N5mLdGCjBSQgIzAT/87AUSoP4IfALaRoacr9pUPrSrXLtH5kPwpUSdkKILjl6a4/HTS6nBDjE2JMNLYILnQg4zgkCOVelhDLgFrKMosATsyCMxEe/xO/W5Z1FIyZtZg6YuT1+RzM6Pn0PQ6aE5vHumweK1Yq1xnHBraPZU2Q8NBosD4dgR4YsNTPVLWnLKtjmDedZz2/BAwluNhVgJFYK5uz+xr1WNIC17DGHzqntJbp3iNb0e/Z0sIs45rYvaCNWDSPZ3L2zAUbgKOAJucebclSO7q4ZsMAEfOCz9crZfuTP32LXf7aK63T61u35zF2AFPMTk9JJFUyNSlOslSysfEJzg8AXLPdsgZcmGQW3FC58ZvX2WPPPY/7fe/9O+ze711v3XLNHnvRszJWWfsGY0OcGxQ3vpd7oGTsIoO6fnTZsOxPmcyox+Q564M1gXKfHJ+wG2++yc455xxft8QccK67Hdu4aZ0979lbrVorMbYR3U0G/ZJt/8lee9SjN1uv4y4+gKODBxfs9h8t2eiU2drxmu3bi6z2rk0/0EOkmZ18oll9/Bh79RX/2xojVdu0aROB+M6du239YYexVMtSEyAL59/7T4NNZYiAFaxcQzypux4JWMswSsrWbPeyZBwpMZxFxFxq/b7/vVtt2wknUGnv37PHptZOsnTK7t07baRWtM7ibrv2S582s4N2223f5ndccskHDQR1u+N1z5jZm8pAcc1YD8/Hw96/2EO9NkGADAWdN41LcgTgL++Y4Qke2APIVu8XUm/tSoPgd3JqLeM4b7rpBjvv/CeSdRmbWENmEN/TTjF8Aha4kc9fYn17PcbyYR7Xbjycc4JxIJAfsZbKfkdpFIyT+8jQGs8LquO1+3bczS4ty4vzPFfzC3MspI49BhCs53Kg56w+2ER+F05X6hssA1AqQ/I3ysKMcQodOYblUgSF8bOSWwKLEQQNn+soW8WOefKU19qkpyMVDo+AT/cWcF0BBkPSiZg76aUsMSWxoJLVGZOoAtKJ8YsGjeZpWNVGFpU9iHuoG+lJKCI83JBK5a/SDTi20L0k6gUBRc2x6gfi5loHAMDLX7caA8g9tBoD+PMjwFgIGn1BkUEYmT79LiAoV1EUtNqcslyi0HAXgGdW4Qd/44CwBRQLaoa4DxbqRIabd/uQK2rFU6bWPmzzQ09x+p9WritzglBzi07CIlpcOWsYGt4nhk6HTwxlFJQSKMMAOIJMCbeogCJwiIffXZh4fmezsrlQl46UsEFAWSxZoz7C2CNYhY2JCbJ/EDpoedaojTAZtt0fsJ5jZBWpJMP8aC7wGhSsFPYw6FKcptgXKF53CUIhu9sQ9em8/t8gy1ikK6vj8Vu8Zx+gUUVu81Idw1ZwFIBxPvQ7AN573nOpjY9VvBRHYcJe9vI/sla7S2AHdm8Al3CpyDjASr1GZQImCOw2noeGAtp5oWB2Ee3/1BYK2eBw7QJOVKzd61ujgkDvDusv4h7zS4vWXnb3jDMTeRkYzPFIDSq3wmt37t3vBbBTLBGKgOMHwNDPg+/T7du3c92PO24b9wIAx+z0jE2tH7fffcEJtm7dWltcbtvaqcPsu9/9vh191DrbvXvJjjlmikB65iAyrqu2e1fT9u9dslNPG7WdO5vsALLURMs6s5MesdlazV12+NbH2YVP/A175at+z+7dfq996lOfssc/6alWr5Zsz74DNtKY8CLr3b5tmBqxe7bfbaNr1hMoHnX0MdZBMWSEGRQKNj09bRNTUxl4leGXnb/MZY5ziDNfsk6zQ3ctwBxKA916wyfsE3/3FzY7O2/33dezrVsRi9ex33vl+2zNmBdnBlhmJ5rUjxtlYuD+Hh2byLL3yQaS2VsZgC+5kQGbkD2+4qyRaUePaN8rVka7xQbjI5EMg2uR/QvgCKa0nxLNGG6BkkKhALF+F0CAG3wLuoT02ra43GRfak/aKrDkEH4E2MT+MeYvdUpZmluwcqVAADg3M22VqhudDItIGdbuHfE44qyXeWqbSXlUhAsYGfC+XzU2PKsM32FgorMoWSlZKhmhM6m/JeOY9JEKMWeGpcDZUK/b4dhFyDV13vHWyDnw0b7SmtJQQsxzaMsnvaO2ci5fEcqRXOBKtAieK90Pz4O4aLDkMZElgtzh/ZTpAfZo9t7kuD4DtWFfRB2mvafnF2EQ904OoFH6KQ8hWnUB5zO5CgB/fvyXxQBec83VNoLA7VRTTfE2Ajf6KoE8HUhZZfGg6CBKqETAJAbPM6hCP1pYrsmiJmuUfBkCH3lCiWdO6vDkHQaStZWYQQk5jVOHTkJBCiuCMwm5lYkA7kIVU8ixhSy0CPh0T7IKiT0VgARoADui51D8S5zHqJSoaPpINPAMaawLylLg93pj3MpQULUa/9Ur9dSjFD2B89gyCaKigtzZ2ioHynL5RCsVikJ/83sL3gUASgfJHQLxcEmx9Eu/z/p/yP7F/aDMwHoAjbM2W2phxJIwCkYHy4hEkMScxtilyBw86PdCx665+nW2ZsJseQlt8gp26av/JBO6mDMreXwfYt84t8USXX1wBWOuWNi8WLCN6ybtda86y57xrMvt+Ec+yQFAsWL9YpfZwsxETIoez4w+zItLzsrwHwyV1LpLCR6f+Mv32Csu/wM7MI24ra6hWDCAnzPG7m7CmoIpZAwaprdoBOET45NZvB3GgrFe/pqzzQpdxp596XP32+MvmLKlZtfarb7dd0/L5qa79pVvfMUuu+zVdvcd37fDt4wYqo5MH1iyxtio3X4bYrJ6BuIWxtFRRzbs9X/0YZuamrITjt9mL3jeqbbUHNjr3/wRe8SJJ1mnX7JP/Z+/the86BXWaS5apVpjrb/9+/fb4YcfTlCEtRofGbcDSEgoFO2ee++2hx/3CGvUyja3uJi50VSX7nP/56/sooufTYYURgFYWxp/naZd8XtPINg0W7KZ2YotLbVtZLRg6zastVe/6l2cF8yjYkhlfOqcETyhfl7q7azrsF/xfTqzGUgxL9kkVx9BDoyjgid1gLEFKAKoQ0tBMIDYokiOQ+KPl11CCC1AsHeFQAmkAtYzlSiRfIGBosQ1yAC4rQ/fdBjXH6D/iK3HMIFrudmmqxyMH5M7UvwfMsvxZWD8OG8t9E725Cp/fuwvZ9hlZHMMgeXiORazlop5U8ak9nFRdsmgjyolemkk8/RaXIPsPglYybBD6IfOsMBNPPMCS1mcYOrRWyqUrY1yOSEkR2soYCpwKd3ipIK71yVTFZLgPdvzLGTJIZEDukf8nICjd7D00jYR3OkzZFlLXt2A7nVkpKfkvuExa28M69Sog4YBtcr96LkQivPay1+/GgO4ygA+BOhvKAnEC0HnFkxmOaev0kHVZs8OQbK8IfQUvBoZAQFCuUvVWiuyYVmR5ESP5x0/YN16NlvOCuWFeiEEFQRMsBgSKgQCI9CMyRqybocBnsY7fIDj80bLcXgldKCjMIogWEJM44rCMf8dQIx94tz1W6oQAOJ9AEBoDTC2EDblorvu0IIKPwrEzixKcFrIkGUWpANl6N1YlDiOVc8T5w+/06ULtsEGVM5AMMgIZbxSr2ut5UXPZhx0vHQFC7BCwSEW1BlAfg+C+zvuthegHt5LiGWEEpcy4ff3D9qH//xd1hiF4u/bwemevfWtH0ohA/5c1cYEg/bRiWBktM5SJ3hmdGLAvLj7smKv/L3zbLKxi0kfk5vOsuf+1qV24vFnWLc/iqZ2HquYgD4+98+f/IQ97eJf9exTxBCyZ20eL4U6bhOjZVvulTgfEvIAgY2RujWXW1l/3VKxQLcrOmXoHqgVCDCINnn37brPjjpqq73gOWdYsdSxE085277ypevsiKPQ3aRqO++dtkKvbL/1vBdZZXyD/fpvPM+e/cwTWIy43e7Y2nXjtmfvvB15xIhVqlX70W1dO/DAAu8/tXHEjjiibmvXTli3u2S79yzax/7mVpsYrVm9Uea6LTYL1u52uD6tDgoyO3vEnsqDgR04cMA2bFhnzeYu++O3vsCK/YN20dPfZuec+6tcCwB/uvs7nr2YdX8Aa9X1ftDXvO0S273zFlteQnzgshWsbnv3dXntEVtqVqpuspddcoW7nUOtNgLCBHoEWnyP5O36EMMVwY3AoNy/8byR3WNSkMf34ZnZdrFYtvXr16cWXjCsakxqOemkk7j3q2DcC55osmf/Pptas4HJSc7wupsP3hTJOFyHmn6jYx6ne+3n/gmOazv/Kc/muVHITb/nGeQycFEGCLGSSAzCGYN7uId5xJykBCR5EiiXU/yYzpMnOpU5Lhhn2m8RzBAUplZviAGUnM+AXDDUNXc5aAvhIilBQgBL5WAk76L+iIZ5PlbEwnYNABDeDCVeRcB0KAIiyl+B/mHZPvxMYgmHAWomo5LRzwwxlqT0tXQd43GV/gz+WqbLABWTkaGxah4j+NXeFQiVHFSSTXQ9M048xSovLS+vJoGkBV9lAB8CDJgXgr6aJQbgMtOBGxYAOlxSjNq0UdjqMzoQEhh+SByAxNcEyNRsg4cqNU5XQ25nw/JeoLn72bsO4HBDSUs5i8mL3xPHrPHqOXE/gdcoAKKFqufB+3JNCzRFMBitybyhuGdrDlua+JwEwLBV6t+HBAF3uYGhgILCXEBhQamhEwji58BMNBCcDuVDQOhMB9ciAWIJLD0f2A4AORQ+Rq27XJDlAj2uL3vipuD9QUoCgSLEfeGSg+CGkkKiRD/VMvOyKc746F4E1xCSBQ/Yjgyo5ocsKTInmeyh9OCivfd9b7SJcbmWATDqdulrrsliJem+g2u3UGJbL4AJloSBC7juzODI+ATBaLVWsLe94VQba4xZqz1vvS4A5yb7o/dcb72uGF+5FAs20qja0qKDXvRzhSsOMZEx7AGM0L49d9vaTVsZ3hCfWesvJYBAfm8T53UwkZTCeofpefHef3z/O3bMcSfYmqkxe/pTT7ax8bqNNiZs13277FGPOMuueMt7zQruyl6/fp392q88whZRfLkwsP17zZ7yK5tt164lu+WmGW5R2AcAgaedvslKFYCBki0s1O2d7/4sx7Ju7ThrN7b6iMUqMtFkfhnZxmWrFMwmx8r26tf8mvU691unOUt3ebnqcXoj4w+3t7zjm9btIjkDWc9pnVOmNGNDsafRHm60Y6/4nafYwtIDtrDQ41ojEWZhsWH79s3bCdsOt5e97A+SAeFMF34iA6i9Es+4QCfPrdIhcA5SsgTPQwqr0NnG/2AQcXY8xKLC5BqcrQ2HbUjFggH0anxv7969tnnLEYY2cTB+wJJiLDCoaqnAs4fNOGvvYRCeGYrrcI/Z2WmyqQB6s7MztnHjpiyBYRlhBqnFGljz+flFMn84WwCCjK8Fu5xiAKNRzTlJyR2SwwiVyZj3FHogYCaZOAxUogzXZ6OBGPVCJvtcsBxSI0l2614xEWXFBxgKk5L/Eug8lNzMiYCViXUEakMVKQQENWZmEaeYaO6d9Bn8HskLyclMXnqvRj4j2ccsxMH1mgpdM3QodQ9R4qL0pp41c02nECWCyhRrH78veqtgkEKswyB4/RtWy8BQh6/GAP78CDB2AgGDIGEl5Syhi00f40VyoeIZjNGqjspOm1uFNIcPrz6nQyLr3i0hr1MXE0jU2JzgLfmJMyCW6gBmFuWQq1YKmUI/ZRBHMCiQNwx8h6n7CFpwH7kj4ufia8OAUxajxi2lj/GtzKSDK8vZDMQN4Z5ICECix/i4M1v4QTkKKGu6d61I1xxbrIW5ywAgStcg1g2B5ECHqXwBI9qSENQ84TM5yzJgAgdadOF/vIf4P4ydXUE6HVucn3X2oI9uDt4z1msHOmuTzVvqCBJdv5ojrQHLvYSsZXz+Pe+5zKbWoD9rx5aXijY+epg99wUvt5HRyYwpZawpsoERFznqcYFQtuXSwBojE5wvhhAMutbuLdl7/vDxtrDQsg2batZpT9kvn/cyO//C5/A6dGPAGgGg/e1f/YX9xm++kO3JWkhI6HXtphtvtDPOPJPPpbOxce2U7Z92wJW5oLp9JnFMP7DfkMV633332THHHJO5q3SWosGh++G1/fvvsWuufplNT89aeVCzrUc+0i5949tt165d9vBjj+dc77jnLjv5lG32vOecYd1e2eZmC/aYXzrCvvql7TY6WrCjj63bvdv7tm5jyxqNmq3bMEIAu9iZtPe///P26U99wi560tNtzcQkn3tucc6m1qy3uek77d3vfrm1m3tTgHvNKCYKiAdEXC9ip5C4NbBLXnWdjU2O8XUqQryb3HL1aoUxcCgdNDI2bp//p4/Yl770T/ajO+6yesWsUS/brr1dO/XUbfayV73e5qeXuWeUGSkFif/xWizxEkGC9lGZ/ZtRILrihaRTz27Mp1hghWQw2x6s36DAtUZZmlq1YRNTEzY25slD1VLVqg3PyMYew5lj/Gx9hK3j5heWrQH/O7KKE3hBiRjMRTQ+IzhFpimfo+Vu3Taz6ns2Oz/DntUwShEr2VzCvzkWHEcMKq6FERPrI6rjirKAcQ3PccrGlswRkMYcRAZVhon2reJcoyyNwInyd8iAi3JRRriePf6v64bvQXdq0ccdPy9ZiuvjOKMREPVRBKu+CVOSnnlNxAi4NE96tijDo07id4PVZliL/457OcDGsucVImjQwB2cssOlpbVP8b9CgFYakHn7TulF7SUZzsvNpdUkkDShqwBQO+vn+D92AlHnAp6ZVKpFSikK2cha6XWBmLjJM6sr9FXVoY3lT/QZxcdFC0mAgIcutXSLLmgJVB02gRcdsDiuaM1KIOJ/WWrDzKHmQYc0ghQJmWHLTdfE74qHPAq/jA1KAELKSdfQdZPKstDFW6owMB3gRu44uIG1RnKpsg4eEiJCYokAIIEFkiASI+F10FKpGNXXSlZuBMQAjazNhn6lKbZvcW6eteKQHYn7gqVAjBLe7yPYv48WYq2sbVUU2Ipt0XxprNFi13N5mY6Bvfe9r7VaDQkfJbv3nh7B12Mfd6FNrllnlepIKqZcYK/ee3bca9u2nUhGFEkx46Mj3EHlivpdO0NzYPoOe/dbn2Nbj11je/cv2477+3bu+c+2l/zuFd6lo1xxNiuVNBGbwRivCjqDtMkuMjA/sbx6BtUsw/8AA7gHwyxSRxV/Pk+O2rHjbjv66GNYJqOFTNqREQdRpaK96Pnn26YNEyzo/OhTLrDf/O3ft8ZonedB+xvgH+TJu971SltcuMe+8fU9dvY5a+yGbyzYtpNGzQrLNjpStE0bt9j99++0Tq9kkxNFm54v2P/639fZSB3ueBgaNQOuu+SSJ1ilPG3t1rKNjFStWlaZCzARKKHj4QYC8Sga/fZ3f8/mFxY5b7iPFwP385UBOLQ6Q9Fwdr/wjOkvfu4f7ayzH2tzi11bWkSWq1cikHLGgyHbXHXiAE48Ccjhjs6tQKeAgljAaFgBdMlow/1Vt5DMeqViY5MT1u64uxvZ0t+6/mt2zuMv8uQP9q8FSEQdTWeUv/Cvn7MnPflpDvz6ee1Bri1iwXqhV2wCh9zrAy91hXMJgEevQsc7pTDzueCMJ8oSoSA22gDSAGu3+D4BHwpIJ9egz68zgCtAQzrTmiutGb4vysBo5Eb5qtcly3UmBVCi7IyGzDAI09nX2kS5qdcku6PcPRS4z8BtkFPq96u4QdxD7KhkXyQpVBpGbKjAbNQXUquZHEp6UePz1nQpVCeMhVnBAweBcfwR1Or7DqUbJHcx7ux8J5YQ+/7yyy9fjQFcZQB/DtQXPjrcC1jWiRRdFK5xM+qw61bYyLKodUBkQUXhIoEtd3B8CtxfblwKnJ6Xg8HvKrqMGBVZtplQQ6cNdm1wd7BcDBKE+k59V2TnDgVcZf1GK0xCKlrEOtw6qBGsSrgK2OjAa27i+xEU6nv4zCjFk1hBB4CoczdCpYHEBnb0qKAgdM0GvQHjlMggFr0/K8tdIJYuCRIGfw8SqyfwIFdxAi+YZ44R+oxtneAa9exCgrmel4EBO4e9Q+DX6bMOXnNpgQoKALC5NJ+KNXeyTG1Z9rJmKfwGOTjQ3ESFIEUFi/vKt7/SJifQDm9gU+vX2sa1j7BTHvXLtmZqncdqWZnzwqzqQtlGRupU3LhHve5xlF+99vP23Oe9wGZnASjcan/lK59kY+UH7JiHrbW//vt9tnayZyecvMX+5P3/YpXSOltuevKL1hf3Y8hAAucyliTMtUcIctilwllidrGo1bxHsnqZJpBOdzldR14OZOfOnXb0MVu57192yRPJHNbLm+zscy+2M88+Z4XrmWALbC4Le3ftGb/6OOssmiHPCkv4m88/xW68cYc9/OHH2w3f/K4tLQxs0xbsobLVKmvsPX/6GWc6Kyg507D6yIhZd9ouv+y8DPhWqh53S7dvMErwOS9QXbHZ+TG76pp/ssboRMYsYw6ksIsAUN0BawliLyGzFckpbHLfWbCDB2b5DEgiEmvMM8ZC0KgdGDL+UzJWVNw6a5p/AWTJMO1rrRPPE5IHmODh5+qO2//Dtp10KhNA1q6ZIoOHLHCeoZRNf++9O+yEbaewPy9c9wCnqDMZQRJ+R8gAjA/J1AzQpjXmWR2gNh7Kv6A8zBJjQJfg8lVf4FbL2s0mW+Vhz3kh6NQ1JCuQ7Qa7amzGcUiOi+HK5ibJhGiUiVmVTJSRqDmOoC0CygiUcK2AeDToDwWihg3yeP5d/nkcqeS1zswwCGW/YcToMZFrZZkVGSiZ3E1dQzw20q8XqyzD4FBEAK6J8XmcNxogYfS70AAAIABJREFUME7dqIiy3d3/qXZmcPVKF+k74loN6wZcgzVhXGrqpoKwgVUA6DtulQF8CDCgAOA734k6gBB0VL8OuhKgkpDQocfBkWs4MjYRaGHz4sDotXidW4eunKLQlkBwAY2imAVXEMnSV7aVHxSP/xN40kGKDKAAnASvBFo8aNEy1ZiHGcF4TRSYEkTxGXRQcxbP2athoOtz4O5zjSsC7Oz31LSeABsup5ExdmxBoV5ltaKmGIQ/WAtESiqWhYIzuYlXgOJS3phd7hEAOH8Od0NEIE0FMPDsZ7EOSBKAcAabgx/U1mNMoIHtarEmoNc39N6vXhDXwZ5ApuaErt6UuRkNDwroFNQOxuuqt7/GqvWeLS90bdtxJ9umw4+zkx95Kt3jY+hi0/f+nJ4c43USWduyULCpdetYTPfILVtsZm6OmZwAqhT+vYG98Pmn26knbrLPfXm/HXX0wLYePW5Ly3NWqay1/+f937TBIPUag1s7FTenokvryJ616QcgVOAY66hixFgfN5KQJe7uQa965KV75ua8CDXcfnDm47Ojo3W77LJn2cGZBXvfe/7BUKkRzwNXP+YT66qe3Mg0BdB98Yt/xXq9tj36UUfZ/v1d+8H3d9n5Fz7Stt/9Y5tcV7cD++aYnF0o1uylr3irXXDBr9rMwX1WrY8R4GPeRkbG7bWXPtKqdY8JBeM3s7Bs5130PPvBtz5LoCoFdeIZT7cbr/2s1aoFu+Z9tzKDuttLHSigkFGihH87IEb5k09+8u/JnKFw8vzMLFlFMJzYJ83lJe43KWb1Ao7Aelgm6cwKqPP8oIebSiqlM8izhjj91AeaMiLrJe1gDSEEAIAo2A23LmpvYp6ZlFSqWKWEpJARZngDuH3jG1+z8857YhYKoLP2gx/eZiduO8G77gT2SIAKc4Jxau/AJY+1BABkIazBwBaXcZbmPOO+6z2Dcb4IiNOek8zj+U2fiwaLGLA4ZxFU4fPKWH4QsINRkmIoJcsl2zBWZtWHnxgylDHhQcYR0AeWMuoMGcUZq5xAz7CxhM9HY0sJHRq75P4wwKSOSPuBa5CSN5SsFHVIlMnSCwK3kkuS9X5fT2DxMaRC1WleBA5FhDCxKcR/S9ZGMKh5kvEuHYa1f+1rX7vKAK4CwIcA/YUs4KuuuipZq55Np0MWN2tksSKI0sGTEFYxTAHI4Y3tI0echwviePCcZXCBmSWISOmisG5y4XjMSw4QxM4MC7DozojWcASHAnBRgEh4DFubUZBLyEpgac74PCh3MfB4ochSaNU03ijcdD+9RsGdulJgLsEegU1SwW7ME0AgwXrRUv0/xLmgFp6K4qKuozOCmeAMAkrPLOGkuZD1DgYWCp2fRfZuqmfHFl1oVdUEW+GKbN++fWSI3B0MF7AngOBHyorCP3UnkSKIADC6tCQ4YdmjFdrVV74yc83t3nXALjj/GXb4lq0s00EruezKGs9aq9U5BwBWiD8bbYyQEcVc6NkkhMFggll+yYtPtY0bDrMf377HNm8u2cZNNVu39rF26avfY52eC3W435UwhDkQwJAS0f6gwG43rQSGCYlPAEWDvm05fBNr6OnZd+7ebUds3pwxgrDw1XuXCrbcs5e+7Fds28PPtN+95HIbm5iy7T+5w47ZejzjGAuK9SqUeN+RUcT3rbG3ve23bP/eB2xqfZkgstsp2I7t0wQs83PT1utXbM/ujh15zGYrFmatVKvbxz/+DVuYblmhXGFS0fN/8wQ78shRgrNCAQyjWYtt07xnbr8PMOJ1Q/fumbM1k2vsne+72XoD33tS0mD7AG60zsgAv+Xb/24nnHSiLaDOH2redXrWWkyMMhIc6A5NiTSp3p3Or2TDsMGkc5jJG2C5LJvTDS0aPGAiExBA0htkCutGVlKf6HKFcYowJMDyIewCYJBuf3RNAaBNxie+E0AeZyCGnSB2cHZ+jrG2mEtmfMNNn9YL66C4PT0PwDdkJ4qMH9i/l4be7Pw8i7wjcYRF1DteLgaLgRI4eNaMaUaSXR9gRN1GVtY55TkMPcklZ4blumQU5447xhPwHKx65xwBFP0vmR3XIMpYrYlk0DCbOHy/KMcFDDN5MQQgo0yV/NL99NlD66CVcYyS9bqHiA6NRWY8IF4kEyg7U29y11leL1Ls97BOinoojldzrOfBe1Fu435Isrv88tVC0Jyr1SSQnx8ExkLQaPDuhwwHPrkCQy2nuFnFPAjICOwNgzdCvZDBK2GjTDdt+rjZ8wbcuVsXbqAVrcsSQykloXFIIWusUSDF75Igk4DIrHIJ6OSiyw5/EDqZEE/XRKZUSkD/S2gJUMryjvEh0dUi0CNwAnaCQDAFr2dZwehdWWsw/ozsRMGFRRbbA6YoWdBgINDZQWPBvXVdL8WxRGEtwSdw7gwDmDtnnuDqxefwuscj9QkEEecGwEdQ2PaSQFBSAoGYyywuJyWdRPCNNdF6SDkxW3gAxqVnH/iTN9r+A1174MDAzjv3RHvCBc+kq3fQa9uGw47m96JAMLYb5gUgEC5N/MNuxnzATV6t1uzLX/yiPeHCCzOFxvmu/F/23gPI0rO6Ft0nnz6dw8xo8oxGQjlniZFAsoIJNhbPtmyybeBhWcCMJIIviKhMMAIb8HUCChAXYxDYBBElIYKEEsqjGU1OnbtP98nh1dr7W/+/+zB6da/Mq7Jf9VRJ3X3OH7+w99pp7Yy89lWnS7vdkP7eHlX437tzn+w7sN9oMhbkcKHLRrxHELrDu4BqQ58dXiUUzDjiXYA1jIl6iIJnO4WuEe2WtJqWzzYzO6lVqCNDQ/r329/2e1Io9MmHPvgZ9QL29g5Y3loItSH/EpWBK1askKOOO15+ed/Dks6k5D1//QpZs2aNfPuOh+WEUwuyb09NhodaUqq0pFlPy2yxIelURmam6jI4InLaWRukODMr+VwPmgzKp/72q5Jqz8pb336hpJPWfcfWQULHs9qoam4avc0o/q3WWzI+1SOf+tvvR3yL6uUK1c2cX+z92ZkJDdkDeGMNwSubardkbr5ooTOMSQcApDHKfUzPl9/D0ZrXkFzcGs0DAIYWrbNOCO/qPjMeQHoAkfbQ3Y2QeF7uvesncv7vvETpe7AmmWbhQaiXIT09Ba3gVW5KV9FqBoJVe+M/pcyBNxV1RWyxqJW+NT0f18Q61M46NRSFVPV8/IRn1OQovE9acRMphMjYC978XOAmxfUoYyiXuc85Rt476IEbP/cy1msgfz3ua8oVb1z7Z6Dc51zyHvicnlTKdjV0XZs0f2/ejwaYB7HGhRgXZbFgQ3WT4/hbCHyRmhD/4zNQbvq1B5DM+3p9Qc8rZT/XM8fPrwu+G/cI549PwHFE5fk737kIAHXsFgGg3wLP7/eFVcDmTfJeKZ9Dwco7HnMo76AHZH4z4HNP1tkJJik8bOMjXyqmxCAoZS9e7zX0m9a72OmmZz7KoaxRbkBV/q6vMI/1wuu5BH2n0PPCUWn84A0kk4kLBXvg45/Dz6KCafCTKcCzi8AD2AUlJebxw/wh/DnQi9w360vMcVbiWoZcQKwF4JcMLbSi1nFppedQcBeoDQBsoJR0XDI5JaFFbK5Za2rOHqg+oFq18KHVUi8OwBeUED2DzTp6ATelUS9HngO/HjRfPYR+KTwjQRl6K+vbtBIKkPKFttx0wzulXEnK5ERTNp59hPz+K//c0gBC43h4cKAQlZOt3da2bMid6yl067sgBIt5Rhu9TDLmjES/ZH22dku9L1Dyf/RH58qK1T1y2yfukbaEPsaeMiKdk59853a57PLXKgCLhHqrLRV4/lJpmZ6clL6BgQjIaGg62dbOF7d8/FVSqc1ozuLc1IySNQMgosobcw4wMF9syehoVQ4cLMnwcEI+86lva6gdpMzoyoF35Jovz5fkrIsv0hDq/GRFdu98Sj7w4Stk3+6iPPLAPjnxlBGp1mZlagotxFJSnhdZu26ltvBrJydkfKwsF5x3vrznvZ+QUtnA+53f+a785N5bpVKaka5CTj2p+0bLctJpp8n4wS3ahWTp0qUyPzeuBiO8eG3Jya233C+NZiXilqPhoetLRGrgtWtWZWauqvQvADPF+XlpVNBDGfmANWmHUKfuH3i0Qu4pDUyvPLluuXfgbUaLPqxV6/gS0wlRdmHcsGYxJ1DgbLOIEDq77sDrBxnX29+r88k8Qe4LgH4UQXnjlfsNIFlbJDraEYIIHmOGZOzF1TzQdkt2792n/X+L8yXrs90wz4922AlUTCp7FQCi2t7oU5Bq4Y08HY/gISQA7AQd/JuAFH/78UTaMPs/Y3/6wgrKMIKWBbLPcWT6/c3fOVcEerwGDfPIAHRt6X7j3cJ3PhzM6xKM674OFboe+EXANoBzffZwHMfCA081ipsIPcewEOkadAZQh/jx8+d7A8SDY68HeQ2/Zvg+HHush02bNi2GgBcBoIcKz//32AN444KWYNzMFAYEXd51T8HnQaIXHtwA/AybO+pP63Ji/CIngKQHjd958EAB6q1BbloCMh7PDRmFgjqGihuTitQLKF7Dhzy8d8xbsp3v6oUIBRcBjhfCfAcPuhcKAISBU1GfU7WKValkpCtv3S2Qj1XId6vgVtqJBACt5V/iORDizICiQjeNDQDfiVYqO1Ygt9C/t7dI9VoN9rY1ig+lqqib1w9jqEpPu6DUtGE9k9k5rxwDVkd6IanrJITJOC98h2yuLe/966ul1kjJ/HxbXvK7Z8gFF/x+tGYRJoYi9OFxeEhBgI0xQ8FGX1+PhoHxDAhXr1yxWsfClAU8puA0LMnPfnavXHTR72hIEN5AAET2j+XcwBIvBICNd8SYVyslBRR33/VTGRoekCOPOEp+/KMfyMWXvURbs+VzaQWlmK8P3/R7culll8uPvv8NmZycVs/TzPS8pNI5GRjsk2IReXpdsmv3lD7jyHBeXvPq6+XUU06RaqUe0jVEtjzzpGzb9oy8+MJLZWRkUJYuGZZntmyXqZlpefe7rrDQYzIt1XJdUpmUtBptmZ1BJW9bbr/9y5LPLVWglEmjCAJ8k3FXC8zBlX91tgwM5jS3E3mAx5x2sfzgu1+XpYMZaSe7ZWZqQgb6s6EzBvgns3LbJx/T7iHK5Yj2WCEXj7QlzXpV10ul1lDCafUih3WF35EzWJyect5sC41yjygRcxb3tPCn96brZyAfh+cNXlmx77mOvDzA7wSBSc3zQ+5jXiuv87nuKIc035WT/j5rCaf8mUhJyGaV/xLzBm8495t51wBqy+ZxDt5arBsQPhfUQ20pE/ozVPIqmEeagIbDwadZ0ucvVazNIgAgeABJqI5zQbFk+wSGlnFSekDiZSJ+97KGMum5ZJz/3hu53lD3YVAvVjtBjQdFON+HyjkvXjZ6HUJZT3ngDXWvo1RuE8x1GNqQn14veCCp8o9zoe0yjVNWj3d58DQccB+vK2JgZ23gOvUjAS71SmSQO+CJ75jPi+99EWIn3RHW1aZNVy8CwEUA+PxBnz/TA0B4SPiP4IYgj4ub33cq6M6Nyu89cPSWmt/ktNb4kwKEIMVvKoR1wHaPRvFUCJ3WVScI9ZvPn+MTx3kvvrf3/nmLzYNBPq8Pjfhx8SDWPyOFngepPo/Qg0f8jnZwUQhYlZklbeOf9v2tNwRVmgcOHJB1q9dJMmOhYF8BrBns4R+Vjw9nqIBDx4dQFeyFNN5zenpawY1/P4A/dJ4oEfzhp0AxIQewrB4JeCy0athxMqoABR9hUIQUqvpcwfvHMSJwROTthg+/Sw6OqjqRnu6s3HDDDZLAMwdOSMzDxPgBWb5ijfKoIXSMtmvwsgF8mGBH+DtpBUoAgwkDiPE/KOam5LNo+xU6E6AasdnQXCy8cwRiE+ZRZc6r9nRFv9kkKlmr6mlE1wx4Ie+99x659JKXyoGD+xRkvPs9l+pPeBSq9YYsXX64PsvP7nlQki2R9S/o17AgsjFmi1Xl17vpg9+U3Xv2KeiF13H1ylXqEcRBlXpDEo2WpDJJaaUL0pVqSrW0X974l6+WJqrpgWFD26oDe+vS1y/y+te9RS677HL1GsKvkcuDegYhQiaxt+Tmm98s07O7pV4rS09fSnL5lOSSaNVlBR1KNyQ2v7o3WimpNFfLh97/RanVi/K9b39D/uCVb5BazdoGWs4iDIW6HBwbU6oV8BvCIziHkGcbxkRNpGXeM3R0UWJp9nUN6SSeI9QrUO51lTvaai+mRfHhYRqjVOypbE69hRo5yGak0NVrqQPJpPT0dluou52Q/sFB+fc7/k1eeMHv6N5jgYeuicA1qGCvih7b3crJidxPNRwkoWkElBc4g+sb7wfCZ/ytRVTa8aOp+YnwACK/M5WwqlDm/Fl6hS0S7DW+O/cVZTJlMPeU34tc9xgbyniCLHzXGXL1su5Q4dhIVgYQBrlF+R2tkSALeCzn1gMzGLl4V0/r4s/nu3L+niunUJ8xREE8iNQxCi9PnWByxEid9fuo20fM28ew9IJ1Frq+aKSmI6edx3nZ65+dgNg7CTgedDbwHXEsKs43b14sAtG1vBgCdnrref5KAAhlaiEqS+InOOkERFzgPvxLBc5HoJAg0CBo4jUj69eFHTsB5aEAIgWGP5YbZ4HwCFZm52desFEY+mf21hnBnd+sFECdArZTCNEy9qCZXgpf2MKx9fmIXkjjOhRO8Ebhd4AXfoZrAuA8u32rtqji82VT6dD6zbX1C0nKBJq8t4EZ64lKYaTegpC75IEpro9Wb/geismUT0LDd6CqqNWqCvbQ77VeLQWWfYStDCz4eWeFpgd68KJ5sE0FY16eirz73e+TZjMjS5dBWWXk2qvfF+czhRaG8MwhWX7t2rWSK3QrPUQh36X3R1I9PUe0zLWBe2gdFuVFuuflM+P8QhdaowGctBVc4ngUNCiYSKPXc0k9RACFePZcVz7meAOnGzqmSFPJlt/x3kv0HGBPzO0Rx54pK1cdIXt3b5fvffMO6R3Iyitfebl89zv/IftH69Lb1yW33XKHjE3MyD133y2nnX6mDAwMKGCr12ty1113yVlnnGlhz3yPdvPoTzXkNW/4fenuTkqxiOfPS3GmJjffeqsMD66UoZHhqCIbQEnHBKFTreQuS293nwwPZuS1f/Ei/Xv1yh7N2dP9DmDGEFz4TNdSoynVRkre957vK0E0PGTFeXSMsRB3DUo9lVSaG4S7ValVqzo29YaBvlJx1vJX1XCwdebXBeWIBxDcg9xfXqHa75b7xspP7hWcBwAPbzH+g0cd//r6BnR+lXcTpOqZtPSAhD1pHIf1tlXb437gUARDDYp9qLwpa7xxgZxQFI8oYOvo/KCVwC2j1IGXGAaEkqvD6xcI2Js1Mz4ADjFf2naRwM9RwlCmMfeNlerc85RPnfLMy0TKWBY+sC2bN4A7ZTbXA+Vop4eQ91OgFXXSIGF1zPagYDmAMG9kc04XyBGn93isfu9ytmlQ+xxjnObXgpfzPJ5t4DyA1mcLHkXmUuIzm3fr2mTXMi5ArlHKbB7rx9rLHQ8s9RkJRkN4GuT711zzjkUP4CIAfJ6Ir+O0mAbmFhVsfpOqwg9hW1X6oQLMb3Rv8RDw0BpTazqAGIZwEHLBfVToBlc7Fzl/dm4sPEcG4atW7CqHZ8kEkIEcCqZDWb98Xr/JOQwUKh78HEpA8fpeqHmAyY3u78Wx8SDKg1AqEN6PY0UhQYsSf5s3Ih0qDg2ga2/bZEoKIRTM+cF14f1QcBPCGKq0wako8HKIIAwHZYSKRigufdaUVSwrr1zgsIKiV+EVqGbwex0FAIHKoApvX6OhbbEoYOcrZYGyQjiFbeA4LgYa7R/nGaBBeewc038nYGxJUd79zg/LS152hOzcUZItT++Rj3/skzI5OS49vf1RCNJAMqoyG1KcnZZ1q1fJrx9/TM4882x9j2eeelqOOe4EGz90Q9CxshwxjoMnGsbzYpzvvecuOe+886z4IigBgmdTeBhd80qjIALevW3btim5M9Y68slmZ6fVS/voIw/I3ff9veSyrIA3T8/keFnANrN0JCvtpvUsVsDZtJ/Xf+hb0qy2NUSpTeqbgVqnVZd77r1bjjryaBlZuVbOffFF8u9f+6pIZVrWrB6WP3vzH+m6mRhvyt7tO+VLX7lTinMTcvpp50q5Mh8pKXgjh4eXyPxcWao15ONZH9kr3/pi6etrSrYrJ4VcVuoAwE1TelGIE9AWfYgHjpf3v/8L8uzOZ5R0GnOLamz8A8iD12yuOK2e0ieffFJWr10beZC10EGNT+s1rR4w9pBGKpfyGho9DO7LtUSZ5UNzOE9J1Ll+sd7SVnjB+QU4VdCgodOE5PIwgC1XFNRCrLCHB1m7g6RzkkZPPMy1Vton1dBKKJ9kTOmEd8M6wPsWelFJbDBKvcXI48N+03hlnLMH7kPlA0ykZB75fs22rhvI51qo9m0EDyHTLdgjGe/A8DoBoTe6cSsdo1B44kEJjTPKGu57nu9lOcENDXzuY62AD6TH2POMHvgoAsOzfA7KznqkU+KIgAEsy3HVde5oZLzs8M+2wGEQ6KzYihPvbXLL5Cb/JgjDuVgLzNmkPgGIxHdMW+JzeD3i9aV2GArUTMYNiEr5uEsWxx0/vWPFX4My0OsWb/DAULjqqrctAsBFAPjbBYA333yzCj5uqsgC7OCr61TgXMyq+LQEPt4E3jOGBa8u/dDblmClEzh5i4eb2l+HQiW2uowsFNf1G+xQYIKWKa0xAi//DF5wehDi34/nExTTYuwUECookayvOXmWn9OZh0Nrlu/l7+9BJ8GhdgcJFZnqZcpkpaeArgQG1BAyiRRiK3AChopbXo/NyjWcAa8EOmSE8AWPAThkXhOO59xSwQB9ID8JJLrIM8MvRglTU68bOmSwFzDBohdqGBeOIzxOPj2AhgTfGdfdtedJuf32z8vatb0yX07Jm//8PVH1I4Ekxxj3M0Jo44LTdl4aNg/5W+mM/OqRh+Tcs86N7ovxgwCHwu3t79d9sH/vblm9eq3zPhn1kJ8zrkOuLQKMe3/6EznrzHPUG4r3hOcLhTaYO4CLt73jMg1jg2KFPHDgA0Q1cH9ft5IIg6IEgAFhVYRMP3Tdv0ml3FAPHfcdUiE01JlKyuTkpLzqjX8m1fmWfPMb/yqz47tk2ZIR+b+veoPyDZ596plyw01/J1/516/IusPXy/r1G6L9SqU+PrZXVq08XIWLArBGQ/7205ulXN4trSRIeZFaYDQg8ArOFZvyx//XJrn44tdoODqVbCofY6fnBt7OHTuf1bxLhMpn0eNWc0TR5aNkYxR4GXFdI8ZGoU5dC0D4z7jWjPDdAxKuzxgUAPRA2Ru4JwiCZ8nvf6RX4FlhYNUb1gEE6x7yhO0W4TnG/qD3WH+mrJUagKqmYQCU5nNKB+P3cGe+G85hykD0jsrpZ55ycDkqpVEyrZ4+hPq1/WKtodya3ivOHEAFbYFcmnuHMpN/+3f2z0cZRkOfx1EmcowjvRCIlAmedC/Q2+YLNjQ2YHl5JEuOcu3IvxfAH3WN8YYaKCZFDtJ9FtzLhbo9EFNZrh7slHbT0fcI8pZyh/17o17IdoEF1cZ4FjUgg9eZ/IjUS5Q1NDI5H1yfHC/yqfLdPFilDsU1+b0/n3qCMoXvqakelZps3rx5EQAuAsDfPgDUNlUO8GGhsqLUCwIuem+ZEQT5TRkpeGcFEXRxI1GZMsxDpe+Bpn9Tbw3xXhRo3qrCcQSjVG4eXBIgekXCZ/H38Od0CkXe348ZPXydAJoCmR4M3j8Wfuad8NY534sWqYWTkL9mnj2jN0lINmWs9PgeCg7XyGTSkhDrmgFvg3ZDDcqPwJbvxj6p+JshK/D9IScKifHMt9L3DeFRVA5rrlYyoZ4OVMgpQW2jZs3rW+Y9Nkoh81SpIGZBgDpSgnUciKkj4BqUO8ZSK42DZ/CWm/6HHHv8EnnF729Sax7P1jknOIfUJKpIEyiiEalXqhoChkcKvIEaSk+nZM+ePQqEYLEjz7FWa2heGpWGeoZTRi49OTEdpUjQ4OBPgHxTpnjflh4PryieAeOE4zxv4JWbXiJLlvVKC3mDAg8EOpWgFyoqqWuSkKSUy3XtOQu3YGluTj583ddlYmZOrz1XLKmKbbabGkpGIc7Y2AG56m1XyZbHd8lP7v2hJGuz0ts3IGOje2VgcKmBukRSlowMyI5dB+SoFxyhFcm4nq6dVEpb5oGQmmOOcVgyUpC3br5AvSTo+bv/wJx89tM/lGotK9VmRVo1tFQTySI0Wrc+08pl2LBqYniRMTZT0xMKsPB+KIoBuIO3DDmklUpZAaWCgEZJGgFkwkOpfavpkQ4eZG8w4NkJpvC8lqdlQBGeMS+nSE5PYwGhfD4TSNYBCDLZvII6GAxaHRz4JAkObJ9kZe/e3bJy5Wr1DhrHJLtBmMcJ74k9yvWPNdeVy8uB0THLpxWr9q5W5i2sDIMKXG/VigI+/AOopyyslucsxSJ0x6hoe7xgcAejEOf4saDc6TS0PUDslIX+WA9MVG6EQgnKDsoLBXrBsxWBwtAtg/NAuco2bJS3JpfQPxqGvEWH4jk1bxn+VnCnHVIMZFPnANgp2EeOpXYwilOYFDyGl/D303PDu/AdGZHRtRGKNLjuvAHvDVnKLL8ebWzsqh7gUQ9RR3hnhtefnA/dr66zFWQUDI7FHMAwtos5gB4aPb/fPQ0MhBU3Ca8WC9SFZKAUIFykXOgUSN7T5Z8Mxyn3FXvRhlY8HqzxGbi5uDkIXOj98ICG4R/vZeMGpFCkgPbPQ0FGIa1KmJ1HQo6iB2U4znsmPYt859hF7PrIYw8Awd+bgozvyft4TyKOJygmqMVPhJ4Q0sohjyxlysc8FBbuyeeNhgLH5tHoHvQbKGQIVb4KrgI/m1nLcXcQncvQLUHDxmE8IrAMwtpmQxVYSRW3eWvmSxVpNVEYwkR1Cw1rpWRQ4Br88Gw+AAAgAElEQVTiC/Q4pjPaWixBoOeVNQWlB/BPb/mVHLHhlEi40mhh+BnnQLAqMGu2tL0ZlCv+m5stGjF0V1aT6oeHlmh1dELggUnKI79+SM455xypzJc0cZ/cfkkATVSTJqyzCsY1jy4erpqaYJWpDlOzM7JkyRIr5EBhDUB48Crgfd567cul0JuS4048XebnpmXH9qdkeKjPaD+QUJZMhTzOlJSKZQ2jvv2qT0u9ho4U9IqkZHx8VPr7BxXY7t67Sy574Zny4KNPSiuZkZ3PPilnn3Ou1CUnR29YJ1u3PK0Exzv37NQiqvXr1hjolJTc+7N75Jyzz5PJqXEDhIm0ZEI+HBT4WzdfKn/zkdtlajYpQ4NLtGhDq6N1DmOQD8JtzOnM7JRSxNx1149l48YL9DONAKRQQFJXT1ehu1d+9av75LjjTlBwjC4uAIEYa4wjctxQZIFxU29krapULAxb+vFHdSw8d5QrUJYwlhQohGIQA+gxEwHog2j06LpLZwV0KeDaxHrB2sKeembr03LSCSdaL25U3Ye8rMcff1xOPvlUW4vBI8j74zzdfyGtAiAW/wAqsV9i48a4NNk7GRQ4OA9rADmRMEowvOVKCYmXus/U096shfaMANGWI0n5QflImUywRNlFuagGZgApBElRJa1NrH3vPHukVGEYndQpPA8gTaM9wYijEetBpRaGLKCsgeyx57dnB3CKw6TWScgKkyjzuQYMbCL3sq69udmfF39T3kfv5pwbBJVKtp6D5xYGr/Nch9QlL4888KMcJwCmfDP9Y6FfhoO5JryO4Rz5ueDvPgrndRHWNOb+7W9f9ADqWC0CQA8nnt/vURHIh6+X7l6r8vTAhIveW4wMA3JzULCa5W3J/jyPoV7vSfO5hFz0fnMRJHJzUYDREsb3/ncKBj43fvLZKPAZWugEiB44dnqTvEClIOO7eu8mOzd44eRBC7xQ2jbK5SoS/DyXcObGJyD14M+KB8AR2JIMktKz5r0BjQfPw/uC8DiN/qWhRzxwXBySSmpFoh9LFI/gMxyDd0eFJ8ONncoD41pvgqYCTeobmsOHsC88gPCCQSHjP1rCHH+uUgAWXrOr21qkeQHJ9/CrGpZ9JgMvtRWVeIVAQ4XGggGblnZh0P614E/s6tJ1E7dkS0v/YL/c+7Nvy6knvUiT/CvBC6MeUwdUvdeUc+vnyIM7zq0f2+nibCjasBypv9z0MjnmpKMll0PLuXlBt7AdW5+StYevlQN79qrnD5xwUFCtdkrqtZZc8Yfvkv6BdZoDiHw7gFTkjDVR4ZxMyLadO+RNr3yp3H7HnVrg8eTjj8l5L3qhzM215OwzTpSt25+RRqUmRx9/nHzzW9+TU088TvLdBb2W0q9grYR+uxkdi4qC97n5WWm1LMHdvHYp1K9qO0LuB1Vy0NFN837Ca2ytGg1AmEHYkLt+8iM574XnK9Cr1cxbWqliPpFLCroXeL+sGhZhbQBi7gEAQq4ZznOseA3wccwtJcLAI/YLC4yUHFq95WYU0TjBPRCexznKK9lqyKD2mEYnlS4FbaBiWb3mcDUMovZutgottSVtHqp8JifzITTMrkrc5yZTDAxTpqi8QrFLrarV3No1BmkUKI7B/kKv5RpyQa0PsJJBo94+VGJbwQG6gMSVwJTBNmex8a5rFiCFsjpsMMozL7tZAMKogsrckE9HUEjjlZW2zDOM+AeR7w2jxoWJ9ZYhf5stPRnCx1cAb17v4HnNoxzSRlhhHEAhQvfY48qDqGDVUi0iPdZZgBZAL9+ZXjb+1DkKkRTudUbCYgMj8KQGY4xyyp7b0qF8LrU37iPjgPyEQS9QF/GnXyOmPxu6Jxc9gDbaiwDw+WG+BWcRAN50002qGCFgsHA9mOLi5cLsFL5UjgReBDq2mS2MzLCEBygejHHDdwI0eoEomOhZpMDwlqW3eD2gJFggSPDhZnqOCFA9UKUi995JWm70yvmNTYuPSpGgmcdQCfB5OoGzB4gca55DJQgwqWPQhqLJGhBsN81bEbyXDEtyXnx+IZUOfxLsURiC8FaVBvo0BHoUPgPCdvRkqpcClBXgb6ujkrOioWA8H2hNNBcweG4I1mnhRyAwJHd7cM7x7/TWcl1A+eG5uI44xlwnlrDd1Dy7Wz/6LvnYzZ+W4mxJvQPwVGGOLMk/J616U/7m76+VTKJfXv1HfyWHHXZY1FcX1wMY5H3gydTWYKmU3P2zH8j5516kHhjmtTbopQiejXitmfIFQOb753JZuerdL5NUMifHn36B1Jo1ySTa8sRjv9BK466MeT/gEQMVTaKVlNVr1svI8AlyzNEvDvmaKQUZ9BbgOf7gJZdouPqO//ihbDhivfz9P3xaTjrhZDliw3o55eTT5JmnwRm4TVavXim79h2UDWvXSO9Av4YePWC4/8EH5IxTT1NjAB5Mpb5JZzTMX67avHuPjDeyNIrQbmlrQsoJADBUL+IcfI/cNpyDMQFIRAEE1gwUPMAf/2mHlJZxACLXlesp+j54lTlHfn15g42gUPdOOqHeT+OLjPNyQViOnEt4AfGM+A55pMbJ1pDBgYEoh1dClf2zzz4r69at0+ph5q9pUQxyfpGrm8C82zh4TxjlYjaXsf7Z8FK2LN8SBTbVUll/VxAIQuwSwDIANfgAbezgAUQerc1bUwuueN3fkGEBoDIsDsOMxNAKV4KHn7JVxzMY2dE4Bu8b8+hwjJdj3ugBECOdCj/Xn/aHeSpDmNTrkvjYOI9S9z1bz7FIrG3V0jrWAXAZIBAtptKaNVc9y2fFtSAHohxB/zwk2g/3UpkZgCPXlwd5lP/4jiF5fI/PYSx4tgGuP8O95hwhoMTvHngScFL2xte3cxc9gDF8WQSAv1UAeIPmRvlFTiHPz/ym52b1Viw+w9/kfaMSJ4DwXhJuikNZnriOFy7eGvSC1JR0JSpgiEKUFFau4tQLIr+hucHoveQmpdAmePFDTasXn1H5eWvNgxO/6Rl28M/pQSsBG8/hPVmgge+RQ6RCMZ1Q7x8sXQg1eP8QoiR459hHz5qAtygmxIV3jO+oVYvpONma92f1G6+BhH1odstRs/Av3gUdIPAZKkdxD+S8NVpGAh0nupuCUmUO8NUwMOkVh58jD5a57lgtjHfrBK4KngVEvQj7iQwv6ZHrP3yVtFoJmZ4qyic+8jn1RuLcudlp6e/vlVZqTv7p87fJ7FRN3v/Xf2PPXiprdwpwKOqcpuDBiilyWLlpFbJm6dv82NhCaSAhf9/BMVm9arkq6S07dsqalSslEzoH4LjN171Cli4dltlSTUYPFOXkkzbI5MSo9jymlwoKv1JDcQDix0kZGTpOLvvdN7pQWVxhCO8Y5gnVr/Bubdm2RbZufVyuu+562bFjh/TkkjLQ3y8bN26UL/2vr8r0TFFOPPYYBe3wIFMh0aOGZ8Qxvb39Or9NSSj4iPLL4NUOuWgGVg1UZVIpKSBvEV4ydNdpIA/OQmz5bFbmynOaWwp6E/WMhxxPpQ6qV80Tqfm7Gc0TTKUR/rW+ufDsxNX/BiQIWigjKDdoMPF9OF+YPwBZePb4zLgfPIF4BoBVlSvleVm/boNV8hYK0tvXHc23AkRwBqZTmuKACm+kG6CDiAIHkGZnkH9oe8q88cilDblpqVAwhxxOZTOwTh74XgFvtSrl0GMb1ELlMgB622iEQnQD9ENKdM1e0CHvje/PvQRPnzeWKVNobKosCh2GvHzneHJ8GR5lCJhgx6h6QCxuFDs05pRDz9F8mRcSxmvsmTN9wLxnphMgKhHy/kJBB5+vUWtKMm3HW4THCv/MwLa1oAZZ8G7SW4k1FsmLAMD0/VykyiIGMRUNrq+GNDAr+UpD8YrXBTSGaIByXC3NyRgX8I4c21heLGwf5/ed17emSwKPZCol09Mz8o53LLaCUx21GAL2S/H5/d6ZA8gFTWCiSi1Y2gRfXohwA/qQnPe4eYCH8yjwPQijICfQsM0dJ/xSCNGTRaHKzRYJHZe7R+BGC9M/J86j9c9r+fd8Louv8708EKQlx2fqtGw5nh7MUkh7zx+vqaGrQPZMYavXDMCjEwCi6AMhSwV+CUuaJuBUnrt2qIwL/WyhfE1wIiSU1JCWKV7jHuT5PA5ACLk2mpuleVQ5KZbmNe8PFcPI+7OwL0JU4AK04yisPbjF+wCsMSzOsecYcW5oDVO44lmQL8jreiWlXkFzZ+g73Pap66SQb8jYeEP27JqTd139Zjnt9HO1EhdrfmhoSK7/yKslkx2Q6lxKrtl0k/T3Dcbkwe2k7Ny9S9asXhlTQcC1kwCZse2AQ80pwoM4zBLKQ4gT/G0BfOucS1M+9PHXaWgx0UrII49NyimnLVPwgwIa/APowDVmirMKEBrVlvT1HCmXv/Jtuh9ZMcuxwligYhRzcNhhK+Tg+EG568ffl4svfbmsXrZEJqen5Ih1q2WuWJTJ2aIWZhyxfpWtsWZLHn3icTnxxJOCBwOt7AB60du4LXMlK+qphFxPVH2jjzDmAf9s7NHiblpGRkb0M5yfzQBsF2VoaECeefpxOeqo4yJlhtAm+RfxPvAgE1wqoGyDeBuVuBlJprJy8MBEqP61cGhn1T/lFr/j/HB/Y+3ofKEcWgGXebgz4EEKBiM6puAzPDs8sVh/8LLD82sV5CG3FGTOeP+WEZojrzEOMSN9M6NGQDpjBSAENF6umCyFkWH50DSa8R70CmL9jI4eUCCBkLkaW+i8gxBwoEmJZCVonVwf80j+BU8YZSzlEvejrp9Q3OE1CPdcNI4ufy6SG8GrF3nbwgUIdugMIBiHN5lGH2WflwuxMyGwSQBcYi0Fea20Ry2AudCpw+1BGrP6bKHwjPtT+/0G8MbQdZgY/cGxgXcyWgshVz2Xz0dUNOQFpC6hl87WmP4/kgs2bsb5yJxAjhPXJOWbl3PeecDxYC91nIe5XwwBB/m7CAD9ln1+v8cA8Mao16UHNgRi3Cj0enSCQYI0bn4vJLjJKay4gShk+Dc3iPcY+uvyGXAPWtMeyPGeFISdXjzvFeNG7/TG8W9uSgpAvm8k7A5BYk2g7J+DytBb136TxxZsbCX6fBOCuGhM6g0l2IUXDfy7OD+TTkWFHgy9EcBpCCsUckDJqJcG4KRmVjGfxXIKA29gCKHg2VlRi/to+FXboxlHWalUlnnlJhPNB4Q3Ft9hbkAJskChB28s34PgoRNUew8Gn43jifvjvf3a41rldSnoAXhvuukdUiq3pdCTlJdf/Pty5hnnKM9du12Xnr6M/I/3/ZnSq6xbe5S8Y9NtCqC0R3FQdjqfkpCtz26TFStWaGhQKUmSCSn0dKv3p5DK6riQQxPC/v5HHpKTjjlG7vrZ3argL9x4kYA3WYs3gufhug9fKV29JRk7MCu5bF5mi8i3A3BKSLmOsRQpdINcGikZAB9tedMbrwc0VI8gC6nwvlx3+vzJpnqn8O/uu38q519wroZ83/CqP5Nvfftrcv4ZZ8u/3/lDmS5Oy1Eb1kutXJFMPq8e5HYD3GVmLADsoyABeX7FSl3GJ2YikuQt27bKurUbNCdO11PWqnC1ICnKHzUjIptOSTZ0XsH6oBED8IS8SA3jNa0lm9ITtdFNJSvtREM+cdu7ZGq8JOvWoSdvTT1hG8//UznqBSdGuYdUplyrfs1xLViqmAE9eDFRCBQBGwDYlOW96npT+qOU9o+GJ7inyzzuvT09OuZ9/eCcTGioFsAO3T5G9+8TdBLp6x+MDCitdK7XtQsMjKN8V5d6yC1RMvYe00vK99CczxD+19SKyrzMzCIHE7u4KeUSejlXlRwa3m6MC3P//F6yYgi2dcQ9rVLW/sUhfKV6Ug7LmIQdQJeAmsfDq+aNd8ozgiyOpw/zehmqv2vqwG/miccGvFExAfBwjxM8MnSsHtDA8+evb3rAjNzIYxfeCfdVeRgcGRwbD8h4PzWCQxRLr+n5SkPqA75XPRHCxfgdxUkwvrxsN70HmQqZGIjIXWi6U2NTP9IhYB72hWsFMufaaxc9gLreFgHg8wN9/izvAYQwZik8FyFBF4WLD5vgOwImCgSCPQJFCjtuNg8CeW1a4wxVqIANPGAUMH6z8jwKfYaW+TktT8vfifNJKGQ7hZa/H0GiB2z+ul4w0gPFd/QCmIqZtBN8b44ZnjESmq5NGq/px59AVoVUs6WKCeFf8tqlgfrQwgth4VCN6M/3wk1DvaF6MxKuwYuD50EytQkxU+AEknguzj1yqBTkVarKAViu1LSiGAoL/wBEkL+F4wnUO+eI48Gx53gQ8HaCaK4n78nwc4F7KmFvIH0wUua2fOpvPyjzZfAUJuTTn/pHeerpZ2TD+iPkPe9/jXT3WDipO9snH7zOQsS6BlHtG6oYcY+YJBYFHKAFSciWLVtk/dq1qvC9F07nL4Q/2S0F3j+AxK7ePvnuD78nL7nkUh0nrI2JyemohzDGT8ejgV65LSmB8qMtUgtFNlBwoMnA3piZmVLwQQMCz3300UfLY489Fj3vQw89JDfeeL3c8fVvyktf+jtSmpqULTu3S193v6SzeZFaAENt49Sj8sI7g+BbyZgTCSnVmlIqW0GPr9bGO9CI8zlLmCt41jwAxHlaHKIhbSviAaQBIEsF6g9UBycTWZmcOiDLlmbllls/IImkhX4BsPGOf3XlzZpiQA8XrkO54WUPf7d9jMpzqwgm5yRBvqY5tKy4QNdeJqegVNMJkm0ZGRzSfZbLZox4HQUl8B5mcrrO8f5Kx5Sx1ouR8RwKrLoLefWi+n1gWx8Gl3nU4S0kmGHBByMA6KkMmwPhX4TT1Vtano+KubRiVmwMvDFpYCsGmxaGjLu3RCFp58WLQZ15SLkmtEKX1VwklXZFEtQnlH8K0MKHXtZGnUmi/tt4PotE8FysGavojvsaMzRr3kowFBiY5VhbxXeca0lPHu/HPsk0TpgD6B0d+q6u9R3fXUFYyK0G8KMOUXAdxsDSfyArY7nhHSAsTvL6h3qG65hg3Z9nhVExdy6eqTg3K9de865FHsBFAPifB3+4gi8CQS4LPTPcAN5DtiCXImwG772jkido8GCRAorX9WCJSoRABedFYT9XZcVzKNg8OI2FlQkGD854nH8nXD8SCOSocwqNz+KFKu/La1PJeIDoBR5nyH9GRcPPfFj7UO+gFmkIy+JcDTllU+r9IzBMJcEFaCTHCFEij4nK3AQKwl3ZBfkoJI62Ss3QGxfhCoRZgxcHYWFarvAaWEhTNDdLO1SISLE4J/gYOV0oGoCHA+ukOD8X5b34NURr33vz/PedwM8ros45pdD3wh/vAmXZ19Mr86Wi9qO99SM3ykCfeXKOPPpoeeHZ58uXbv+kjAwhj6st1UpDPvLBb2hIGvFbtGsDiNO8IpdWkM0bhx07O3iwDi9WIoMsdPAvNqQhbZmbmVPuQfC6wTsGPwuAlXpvQ34T9wgIubWvbyshNWlrlS16AGuxjSQUQJrCgXFkYIxGBoE888jAxYfPHvj1g3LRxgtkenJC1q8/UtavGlRP267dB+WY446Vytys3PXTe+SiC86XAwfH5LBlS2zO9B519QBibOYqVZkrm6cX84e8NLYmXGgEwYAAFVEiVKaDiRL5cKBWcSkHyJ2ttzSEivORY6iFDa2m3hdeqZtvvVJWrhxRwNjT2yWPP3FAjj12uczNVKV/aLm85LLXR/lwEfBw/HCHWjegYsE9CFwNUFgOJ2UWSZ2xjvq6C8YDmEyo11DfK53R/VUPreWA95OQNwQHSfOiA6iAYghA0mpTRarzJSn09UYAGPe///775fTTT9c9iHWr4DJp+bXwHKIq2qiWqjoW+B7A3OSj0S+psew441QOB0BEL5Q35PAs4XH1uQx8ho4/jtrIQpr0Hhqoo8whwAQw9OFi5tXpughyWK8fvGHmpYvTU9QQCIVTlFl4Jn03UtQE44RgSN9JUoHzz4ymWNaad9zyouPuIgTYKtcDiCXNDYCd7iWunw6vH3sCk9gaRPc6nk7PwEPKamtS4eBvA3q29u29zNjCTx+BIRilYYz3p9cSY8pIHOZ+sRWczfaiB/C3gAG9B9DoG1yHhrAh6BX0wIoLlouZStgrcFqUtG5o7fCxPZDy4MpbZt5q8kCKybQEXx5scXNRMfA5/DG8Ls+nRYZNR/48L1jwTKacDDh6MEoL1nvaPCjk7/69vOL0wI/hPO8RU4qJIAShHHQ82xAgBtbgnYBHUGlhAv8dvFQxMGJ3kLg6LgaVVryA60Ap4Pq4lydZNiUCD6B5AQEQGOZFiBAKHEqKeV0YJ+R04R/DfhR+Hljzd44P54njzvn28w5FCI9cp+GBa0VtyYIS1Xds1+Rt126WFYd1S62OzhXwHogU8gkp9LdloAde75acffrvyUsv+xNLrA9tx6gocZ2f//I+OfP00yKFmE1ZUj+GHT+jEDB6NktLyY0BHqFCUV165w++L+efc56CKnQmIV8gFDzfF55UXAsAcGJ6RvK5glaRau9XeIsCCXAa9DyBw9FaTiFftiW7du3QUDXAGbxEj2/dJicefYQUUgnJ5HvkBRtWKVHzvtFxWb58ufRkjEvy8ccfkbPOOk+q5YoCHXAk4n7FEnrRVqRcr6mXF/cgFQWqrLlWzWtr3hGAN1uTRuzbk89JPoc2ahaWxnVBX6PezhR6FBcjyqb5ag0oWm77xCb1/GEtr1g1rB620QNjUqs2ZWBgSH73d18ntZoRNHPv+TVExd+53wjGuO60jVvYV+o9D92EaEwBeGI/4NnhDcRz5LKocrbOKzQAU8q/aR0xuK91zSasXRwJir084Vhgf6Cwi95yeK6xf7AO4PmDl5HFN6y8j2VXS7vu4B89jARUbM1mMo/dT8wrD6MP8+U96Kxi9uFyzLXlr1lOnpenfAaVU+G9/TGcF74z2+0ZhZM9Fe9/KMNO13XwsPlx4zmgfgEhvjceCVYVRLlqXvwdGVodNGVhUUb50nxHHTWujfDuOqe20EK6gDkb1GButbSKXdeQYwKweYgJ/r1s87qHawljjevRYULKGOoDAMCrr7520QO4CABtE/1n/3kPIACg9775xerBnBe69D4Q3BEAYsH6nBFed4HgCA9PAeDB4wKLLQgYfN8ZbjuUUOW9O71ttF75DBT+ncKK1yTI4D0JjnkehTg3rwfI9OzxWH8MBaV/Hw92bLPT+o4r03AevClQElmtdrVilmwyKYXuQLYc2r4BAPK5YXEz/GOgJmbRh+DnHOYACBjuUA9DHFoxxWJ5QgjVQYHDY4UQcA20L+1AF5KwXCFVaK1A4OvCU5xjP3Zcw155eu8qBSWee+nIMhkdP7gg4Z3CUd8r5DfRK6HEve2G/OVVb5PeXvijGnLWKcfJ6199pTTqJdm79yn53Bf/SQb7C3LV226SNcvX63vpXEeBLHtC9B0eGRpakIOIz5H/qOOaTsj7b3yzvOzSP5Cu1GFy8oknSamE3L6CKgeQZ+e68vKL+34up596hjz11FNy7NHHyN59BzRXDO9cbtSVpqQKsu1KVb1/+BznmxJDZxG0ToNisSpKGx8rDCF4x7EXX3yRhoQP7N+vAHX96hVSnpmRGXDNtVqydGhQCl1peebpp+W0U05VMAaPpb5ToyVTM3MagkbLP1SlwgDA9VETjN9RN8mxt3UVCkKCRwbhz1wqKV35rCRQVZlNKaWNeuFabdm6a6eCmyOPPMqKG+oJ+enPvyCPPPKgTE5V5fB1Q5LOiVTRT7iZlvJ8S4qVOfnz174neJEsZ5LGGZ6Fe/5Qa0qf0T8zKuPDHqJBhGvlwIeIPdWVV2MDOYzokGL8biABzylRt8qZJqpOc3a7YDygUh50SvDcYC8gX5CE5ZSDWgCTaKk3nUAVBQ6irfHKerka2i2iACdwAhLcKThsgo8x9iodyjhXsBT2seWimUzwICcCaIrj7HqdMpXVuzSAo3dgFa0rPvH6iO+lACx4ALmXKe+8vjCDwhHtA9jqZ2lLWwm9kwkmvTFpz2TrUd8v5EDSa8jn8qCTspkhYX3vkMPMAjy+A0ZGvXzBu+qfW9/FeTGVAseNM0E054CyjTqVesnmJYDVBS09Yy/nIgCMV9iiB9Dvtuf5u/cAQth5gBBbJSYoubn4k9ZXp1eHgorKoRPY4Xtv9XlQwNegEKKnjwUM+N57HrzA99fxG9Q/Dz6nAPt/u6//jkCIXkKGwj1Q9M/tNzgFiBdABH4UggS7/nMCQH8MrEvtKJBoqZLCffBZFzjNQqN7VjsyeTh+D3b6sPGjJ9MUolUxZlRxGfDz5Nb2niZY8R8AEkJc8PLh76r2/gUItO+h1KAYcR5pPah01DoPFd5ca51rQXVp8D5zLDFG+RwARFvK9ZhTD8dyXlTBBf45zBG8WQDiGm5OteXBB+6RL3/p3+Skk4+VK99yjXIp4vraKQRMzIFIGHmW9AYFzW6hLybKB8+TrUkrisF13rT5jwXkb6iIXb60Wz7wjtukKzssE5OTSu8C3JPOmecQ1cwKpurm6alUS1JtJKx4BtqmFYB2w9pv4R04B7ESNa8s7g+PDkmTcRyqnB944AE5/PB1RsGSzyNoJutWL5cde0cVUK5ZdZgkmuib3KtgDl4u/NMxqzdl67Yd0t0/oF5DA4BmEBjYiL0aULze0MHYoQJY12Y6Id35vHoBtSIykdaimtWrVyvIxDODDxrjB4D8nvdeJX39ouHfNAAjPGtNkeJsRWrVlGzafL2Mj01r95R8F6hZLPVBQUZY15QvXGdcH954xD6CIUWPMsPAuF8hZyTR6llPJaSn0GVh+8g7nrZq80Rac11ZZIVcTwPIbF+W0WdHRTPGi7RKXNsA7MydhCeQzwdwp952acv01GwUGuc7mnco5v7j+zLnjXveAwuGeCmrOV/8m1QjTAnhM9r3ft4XdgbyMp6yg7yCC0BpKMLxe537f6E+iBsJ+F7Cfm5JreJlq1Kd+k0AACAASURBVMkoWwO6hgMA49rwjgrqEiUNCGuHgI15fgTC+k6OdJ7vpIYDi0A0JG3/8Bzw1FN+2NqzTic0oAj8vO6i0R/pLc9LqPRSCImnVE5s3vSORQ/gogfweSK+jtMIAG+55RYLraEFWPA6+Fw+7zXiJfwGp9Jm/hitcuY58FgVkK6RO4GB34idYMlfk5uH9/PC3SdaU7hQIMSC7jfHzQM2Ai4CFT4r/+b9vRePQNBvbII5JqgTtPJzjkdn2ERBTABhFFreIlfFyjCw5valpSvLNlPZkLtmCd9e2HsvGd9FwRNyCgEsNQTMApC4IjAeLeP/w3MzdwsUMM3QFg7KXD0T0lYAiGM4t/QIUvhzLAgm+DxecfHcGOwkpFGblOmpURleelTkeeJ8UaEhPIdx27V7hxx55JEKGJHEj0ppvKOxfYmCHQJUeL0inrgwJn690MtEoD4/X9aCE/yD1wZjuHP0Gbn1o9epF3Dfnob09IssGemWbCYtN7/vM9KqZjREjv0FIEGlB+qRbdu3K2BrSVIqDWv3hLHY/uxTctiqDYGcOuaRI7Dx+VRqMMBDooUICTnrrLPkbz72cTntjNM1VAbwkQ+FFFBQUNLDg0NS6M5qBXkua6FOzBXIhxHax/wiLAugD9oYAl2/f21dmYJTXjYJleYpKwTpzhaktwAgZWsLuaHgNswm09rtZKo4p51FMC7IlWy35uQTt71PMtm29PT1SG/vgIyPTcrY2JxMTInc8KFbdX7p7VSPTAjJeeW8MDRoihleOJynsgF9Y9Hez617Grng08Sc9/Z0a8s/ZFMU8l26ZjBWuh8D7yOIuvkPn2u6TNMAIMYQ+8E/H/eyru828tHAjYIWgxYXRUqAGVoi99//Szny6GO0CAgGlRpX4E10RTusGlZ5CK9XyGWj0XYo+cJnsO9IJs3oStzFKQZB5oX2RhnlNfcf94aCWFd4R1lm4XHbe1z7lOs2VvY9nodyKG4J95tk2tzvXJOUb6xwVg9+IOBGGNbGLY4gqVwJYV56AAn+/N4nyOSYLZjLUHFM7zGuwyp/5UB01Dkqa0OLOMq0hQa/efExFvA0MtrESJLSIqXTUppf7AQS7bfFKuD/PAj0IWAoQkuEjyvAcAcqbA9O4g0Xu+yxybRhfMhL4eZcKHBi7w2FiN9kVPz8jBvOe/280sc1uFl4PQoYXsPf57kAmBdgHmRSYHmBQ8HohSLOp2VJQenBi//df++VhweS3rrFMbQo4enR3JQW2OQN1AAA4lwF2+rEiSkHOH585k6LHcfTM0GBzPtxHHANJKRzLbA9HPLCAACR1walhzmCwoPCQpiYx3slHQGfkF/Dv/EMOM5/T8DInx5g+/ngO+EzVm/SswKFDYyiVZwolEkZ6OU643U8WFbvkAuH4RgUufT1dLvwWVwt3dvfI3/1zpdKrWoJ5slkSiYmGpJO1WXZYYMyOTmlvHJvfP17ZPVha9WbBM8T37cGjj20oGsh3FqzPShJ9br5+aIHEM+G0LvlquF+pjCGRpbJxNg+HXd47R5+6AE5/YwzIjJjjIkv5BocsE4XyEFDmBN0KMw5KqMzB6p/A9k3OAC9Icb9SGUNJYh8vcce+7V8/etfl1Url8vrXvN6SbYykk40ZKivTyqlklYCK4dhQmTnrn0ytGRE15B6+SolaTYSMjq6Rb7yvz4rqXRLlixbKrt3z8qb/+JajTGnU/kIjHBPcQ95Y89/53N28bkCvQAACaYxJ5pr22pLLmcGUT6X1XEBlQ1SLwgATZljIRlhuDfQUByVzaNdIVoJphTYUbZgXfg1Db5IwBAQrBPU6h4K/2kqgHp+RbkY8Q8E0JR/XD98fwXArvsS1zgJ0LnGvUwgd515Hw2g8Xm5N3iMN1r5HpQrlKuU/d4LqM8RtT2zfGQvQ+136wEcV/TGJNqdz02D3e/ZWDbYaMRGvdGwUBZ5XUADm7I2MkRJ/Ow8hPp+LiwbvX/oaqIjF0LInB/yBtoTGUG9L95SeeWKKWF0RMZxMGo4F5yXcrUkm96+mAOow70IALn1n//PTiJoLzhpEVOwegXMTRZbayboaKWycIFCCNdQtv1A78LQLq/deb1O5e8tToYDaOVToOFePveO16QCwHE4h+DAW3UEZZ2Cjc/vrUIvkKhAuJn5fhRwXkh565Gf+2IWjiU/M8FkQgPf0ZuKMCfui0pgVLsV0Fmj3TBC2uAd4DjwXXltrhT9m8TRoScq7uu7f1CQgdiZlDoAdgrotFq2LfOVilUohjw40MFAwQMw2JyZ5wIFBBR2XGPeG+JBvZ+DzpUdCdcO4czxZ7svhEtQeQqPH4CyhslB2RJCxF4BRcAZ/UQR/k1Zro+uf7C6uIprf388ZzqTl5tu2yTN1pzs2z+meW6VMqo3jRdscBBAIik9fd0yP1eTzVddL8tGlkipGINkJVputqQ4X1XPqXmyLRQP1UXQ5sEx82s5v8gVA6zJ5ODVEQ29P/boI3Lueefp+ZgTpSsJBhPeP5PPSTdATjYrA339MjZ+UBrVmrY3G5+a1HvjvFrd9o036OhZ0nUsVRkZ6ZEPfODdcmA/0gPg0WtJby8UXEu+/qWvSaME7zHCc/D0mEIsNRpSrhrdDMbVvJ8lLTL62lc/Iw/9ertc/+GPRICP8sfvOcoPH7kgcAGoY8UslbuhA/OOazaFy4vDGsc5e/bskXWrV0mjXpPhwX7pymXVaECaBUC3rqPATqBrILRMVPmCbiXt4OUN3j8dK4tMRv9mZqeMjxD8i6HrjMpOVEY3mlJHakW1GpFvK2iGvzCAQ84F3sPLHP3cASzbg+bRp3w0OWT9dT1I5Nr27+ZllnWoMXJj7lECFL8erFgs8Iyy4tbxplKexevZvH92LWtFSoOTwIeym3qA8syD79hwNw+ql+94X5MRBkA5Bnrf0EWEk2PdfOIiOl4nBvILK9r5PX5SJ0URopBW4uVNpx6Nn1ttiqigiEUo/njkzG7afM1iCHgRAD5/0OfP9ACQBKnMTaEgpYDB3xB2ZNvnBvbhULMk42o4/zs3gRcqtL7wk+FSPp8HgR6ALRRKdjSP9d41/7tXHnwOhoz9c3Xem991ghY+g9+cPszrzzvU7xQUBNlMsPYCjkKKuWm0WCEkzFvRVACYA+Fuzrx/pHfgdT3I0tCjxHQPrChWMBAIojkPFLymICzMhWdmaBdjp2Ff7a9rPHF6brsl1QpIMkxZ4f6dxUAcY35HYOvnw4PsGPyHnDANMTEXzax7Ki0dIwDbkBPZlc2pssujMjWfiTj+vNLWsQrFAfh9bGJcli5dqhWYAE1oQcfjGdJSxZ0Q2fSOP5e1RwzJfHFWCxoQ3kS4s1pLyNREXQaHEnLYimH1wkl7qUxO7JPlK3tl7+5JqZSycuuNf6tFNKVqTcfTvDrmwWDuEcGXYhfHx8ZxsTlrazFKIW/h0WJxXp584tdy+hlnWaGQ9ki2PUaDCCFa9L61/Dx0H8nL6MH90lXo0+P37N4uhd4+6S4YPVSnd57gKZtLyrXXXK25ewMD3VLoakuxVJLxgyJLluUUEA4VBuSjN/+NgpsDBw7I4OCwlGp1SxdIiJRLVWmloLitwryJYpGG9R3mmFMBE9j5te0rt70xwbXGa+jPuuVg6pwHEIixUcoXjFUKnsaU5PMZySZTks/GBNddOaMX4XgeSgozj65O4uEQ0l1oPMSIkJ43TalAKDjkf9aazSifVj3GYU9xLzICgWdnGFL3WsTpGLqfhFAkZbFvTxYXh9mxndEJAidbe5S1gTDcyV2+m8nhhXmDdl0zYs0IWAigvDfey1k+r5f3sSyIU2U80DNZa8/gwSG9mPzcnskMrchodroLebeeF5DrkDqP3nA/p1yfNJbVCxlVI2cjvcl39NckoPUhcFR402imPIRBswgAbR0uegAPJX3+Dz8jALzxxhulu7cnso6pbLySIbjzgAsbwHus8B1Bohe63DjczAQY3rtI7xyP9WBsgZUUKlW9d9FbYX4IYqEX0zYQkDFM4IUOvyOgpLD1GxGfEaz69/HneGDrFRKvg3tDUHjljnP4eadQiwFdW5WTKl9JCCot0/hdSaCtiIPPxnMY0qeQid5fwHNn4A4sHlrQ4LqseKFO8GAEzwa6EAJG4j5ynZBXhs9JCG0AEF0NDLRwrPm7F+Sd64lKBMJQnxVWe6hoJMu/PVtcpcz1hM8hurEG4QGEx0aBbqodwuaZqP0Xx5jzoPQeSt0Sql1Df1sAQO/10TXfaio43L17t9x027WydNmg9o+FgEborlZDkn5KuntQGCDS05fW4x+8f1xWrOiS0dGaTIw15etf/aLs2j+m44S9CHoVgj8ASiMfNtohGhheUePz6akx6e0bEUk0NFF8ZmZGiyy2PP2krFi5ekFYHeOE8DC8oninBRRDoU9r5DEPwJ9hyE7DTrklUy259aPvknYzLzMzFTn26AGZr8zL6jWr5Of3bJee3qTk81n50v/8giSboqkBeH6QcyN/DmsVPIP1BsLgJUmkrcUc8+i4vxju9PuH64bHRODceYepZGnM4idprWgAacFTAz2UrYgjA17NTFry+S7JJsGrmZNCPnQ7CZ1ouruME3KuNK+V01xLpqhDSQArUkNuJnYa55D7gfsK52vlNzx92mUibUTczZaOD45HqgVlDOVuJ2DyZMs2Llat7OWsN35iWWnozleXe3lPKphOGUfAyPw2zgWBjC9coizlXNizm2cZsofeTT/H/J1RH2+E0OjjWHqDgOd5PcacWXZFWQhu+f6BPDt4huP3Wch32JlWwPnAfTs9qDCyOuedY+D1hMp+RCGcHugEwXNzRbn6msVOIIsA8P8Q6D3X4QSAH/nIRzRES4HCjc2fWIgMK3JT4TsKE4IiggsfivUKi16ezoXPvwk6eF8PhHiMV4bcoJ1K0T83n4kggUKE70ow4hWst+x4HD2d/noe2PiNz2NxTbLuUyh5QNip1BXYOfJr/34EKhAS6oVADhhCOfBa5CxZnZ1HPHhT7wCqPF3zc44r5onPxTmjtclx8aANChwAQucbfWIDKW1VC0SsAhIUMeqxCNWPfAfmanItUpnQU0jwhTCshprc8yIcosnaLmRHAY7rcLxVgacMMGFMFACCBw8eTlfkop5CDWnF1BGa+xfCvX5tsECE649FMDZedUklc3Lt+94ohd6WlIoVpW6ZK6ItlMjSZf0yOVFUYue16/vl4P6W7NxZlHdvvlrWr3uBVGsIo5e1ihogUIsbkkkNg+Ed6D3lvuHa9cYL1oDxolll8RlnnCHoIPGFz/+LnH3ORvV0eEXW21NQjy2Pp9LynjYWlNBAIYjgvuJewueFgsjmze+UgYGUzBXRUaElF118rHz7Px6Do1TuuP0fJdlOylPPPCPHHnO8cli2kvBUoptMRQFzuQ5vMXIbrRUawsAELbgX+SQ5Bz7qwHXUuW55LMYS5/M9aWhqV50ArmFAdWUzcB0rAET3iK6uvIwM9KpRDGNC10pbNB/wJ/fdLxvPOM0AYyAdNoATRz9+8sAv5dxTTpXuXMFaCAaKIs4dDTXMMcDw3fc/KKedeLyC88nJaX3eiubTtnRdIu+Ta4L71+8p9rzVOcKzajFZXLXL8SHDgI/WWBGGAUbbV8xXtD3iZRbH28toK+CIe+F6WY0xZrEK5ZsHRP5YygYCd/z0usL/fii5TiDGaEl8vNHJYL+avDB+Q/yLDMAgb3QfBE+5l/1eXvnrcy9wj/Ecyhasb+Zwe+CP47zOiIGxpctgblEQwuvh+sgBXKwCtlWy6AH8LYDAQ7WC86CEi89vBAodr1S4GSm0sbCVkR3WdT1OICdQ81agCc6FSTL8nufiGAocX/RB8OCVAK1FWk8cJgpNnsNnxnEAv560mAqPXjMfnvQb3Xuy+DnP5f0oaPncfDcvMHmsn9LO8ynAQbILIZ5JGt0GaDZAE4BcJf9sKmyDh49eLfzNcWEYg4rRg2g/NgpCkqaQIeg5rxgveC1wPfTUBQhBvhzyyEBlYsDDlAfHzxsAHpDqMynvgxHLqiczhNDI6QUF1wnsjYohXjv0emrOFoBxOqmkxAZyjbuOCpsA0AQxnjNOX+BYE1xGY5TJya8e/JWcefLJkaW+/+A+OTg+JmefeZK89o1/qPetN1uSz6akqWCwLiPDGZmcbMrgQF62P1OSv/vUJyWdTMp9939Hjjvl5RoiBmguVeYlm8mHitWmnHHWWfLTu3+8QFEwxEblhnEsVeqy6Zr/oUrun//xM7JyWZ+84Khj5OGHH5VGvSKTU1Ny7gsvECSjjc9WZOXK5fK9b31NizLgaeKaBVgC+EM/YVZvY3xQGWxKLM5zArjGvVH601tIyQc/dJ2Uiuhcop0JJZdNyl++8XXykhf/jgz090uu0CsnnPVCObBzuzz0q19qrtxssSS7Dh406pmaVbv2ZPNSRieIQLiMn95I0DWeSmoVM8L0oM7xRh35G/36wjvCU8f1g7/ZVxrv19PdJUcfeYQ8+sSTmqN54MA+nYO+3oIsGxyU5ctG5IgNG+S+X96vc4GuSbj+sWefhZeQn/7sXg0tX3DZJSLpgrTQ8SLRlvvv/L4WvIAUHO9QA2k42sahUUazaflu1WpUfIO9k0inNIQ+W6nLwclZqbWbUinXBJ15lP9PK9WtoElzC5OxcY41jD0G7kXIXoTWtcdyKGygLKJswU+MvZfpCmgWtFRMOpLrOKxsMpcAMaXrxfaJ7aXO1AUcT5lDHUO94mWy9655WcXrEVh53eTlJ1sm4p21c492UorThCjbGP7tlOf6bAEMEuBTR1Eu8H6UD6zA9qCYY84OPl73+XQnGuBel+g7wpQK1b84Hv8gcxdDwIsA8LcA/ewSBIDXX3+9Ult4C8VbfjiWlhw3IDctFmehUIisbA+e6D3ygIKbx3sx/GZWAcSG28H69N4ogj1ekxuInkFambQe/Wb1ShO/R94A14/SAzT+zmt6AOMBXSxUfI/K+Pp+83sw65+NVh+tS44JQQ3vgVZU2vIN3grkcSFnCYUhCfMMkgOQY0grk54QFj1469ODQL4jP4PQsdy/uDE5nlsb3jdaUsfYNYweBp8pjUjSenp6UEUh5oE4547KeoEVHbgH/Rxo/ldlXsO66lQJSsi/K37XMYKiTCe0WKYLIBnh6paBfeT4Tc9Man7fi87fKEOrNqgym9j9rNz3qwekNDcv6Jusa6jZkiXDg1JCMn3DijS0NVvwHuraSCLfJyupXFve+4FrZOuz+2RkKKu5fRjnoaEB2bt3ShKtjFz/3htlaLhfxqbLMl+qKejjmvdGFY0nrpd4bAz0Uhl5ZYrxRkePfCEnTzz6azn2hBN1DtBGLJcHjxhyxOCPtH7SfrzxnJ3KVws00pZyYAUA8d7knsRnXbm23HTjdcrXe/xxp8kvf/GAvPXKN8mF52+UrLRkoL9Hli9dpvutq6dXHn7k11JvJ2Vydk72j41LJoscqYbmwKm3LGnABPegF5ReoU75weMpFNl5w4BSXPHNfaSg1VFR2Tiah0jpbHDPSlkGBgakv6dLBrvyml6BtnFtgF6xkKrKr2pFeodHFNjVUbGrnuek1Kot6cmlpdq08cI/GDToJYwuLiDdHlZScUyHpVSA3gUeRq0Eh7KvNWXX1LSgIhs0PJq/iyB/BmOC+yOfk4Uc5M9jJa/IYG+fzMzP6b4l8PIeNDyX9/z5tRArGPPq8TuugVgGh8RAty6YM8xr8Fi/x/165/fMg6ac430xzj76RE81wSzlvA9Zc41wj7BwhX/HHkZL+zAgF0cDfAGGT6npfEaCWvBqIjXHyzNdI5HRGned8c4KyjZ/jwg4hlxmr8dgKG5e7ASiS2vRAxjv0uf9m+cBZBEIra5405tQIc0JLTGGYbzlgs+gNOjy5uaiIPeCyAsWfy/mFPJ7r3QoHPiMBFZeGVHQ0yLtFGweQHoh5YGtB6exEImJQ3lsp2fQhGrMpeUBZ2eIRBVUICwl6PMeTS/EOAb6vrWq5niBN61WLsnwyJBMTk5KJiFy6UUXSa1SkWd37FDqkpGhYdm9d4++Ju/hQT66GuBv9fwg9BU6TqggC8nouOeFL3qx/OBHP5YXv/jF8qMf/SgCH+PTszJbKhsYE5FXXf5SmS/OyU9++bDMl+dUqXO8PeA24RiDZRS2qKBTPlcLW2kPVXClucb0FNyc/841hOvCGEH+3B/83svlP77zXentycvRR2yQ/fv3RTyA3pN4xStfLrXSvEizIenuXvnGv39XQOoLQMu5RxgZYBfeKPR4xTPCW0XAxDZjCBWms1m54vV/KO1GQgZHUpJO4TiRbVtEPvfPfy+ZVE6KxVmZnkeHjYV5XQRznes7XvdM1Lfx9p4vAEYM31yxpF6hge6CzNZqui5A+FxrJyMuPIJ/rjfvNcd1egtdUm3WFcg02g0FHFCQtnYMGFPhUumxN20OXJWptPQVcjLQlZXhwUA3E1gAEBtH4dDeiRkpzs1b27uubuuAgZhxABOUOZ2KfYHRBDoXrb6Nc7h8z98IDIY1RY+N7VG8U05SKfQrzkt3b1qmpsYkk+7TApxUuyXLlw7KYHe3VgQbP6C9e73e0IorXC+mAW4J4OE8vI0gv86ktbIZK7kGbkAFyjlBcQjIwm2PtaQ3b8YKNhHy/NBmEMdOlcuyf3peyugQU0LOJKr+U5pvq3OP2W6R2468mzFhP4p6MG9sR0dZRwDMcfaymWDL7w8C5M69xmMWyuS4L6+XrTzGy0A6B2IAZmPbCYq83jkUyPPv5fdNLPdjkNopm+1vpN3EHIUqw0EEHngz6STwukynK0QovHzje/oUBZVlWmRkLBj454tICPD4GfeWGgSuHZ6tu6q89W1XL1YB/1cGgHfffbfceuutysS/f/9+5cV6xStewXUqr3/96+Vzn/tc9Dd+AXHrL37xi+gzeBiuueYa+fKXv6yC8aKLLpK/+7u/k1WrVkXH7Nq1S6688kpVyAhX/Omf/qkgl49tbBbc4Dn+8CFgBQFh4fvKTW58zUkIeUa+CIKXJghjOJebmTlwfnNzM1GIUAFRQHhAx43Mn/T2eEXgQZ238jo3EIEbwQg3qhdQtDCp2Pj+/NsLMS8UcE0fnvbvSMXDsfKClu/B+/r78XlxPMYIni14tQAcMBfI5yqkkgoGhwcGZW5mUnoG+iKKF3hAAFQ4nqSEoJeQie/aYSRp4VqsPfU+VWuatK+dNHJd6uEFYTHWI95T24UV55WjDGBJx7JZlZOPP1ZqjaY88fTWCCyoYA5FBX5uKewUiEClBZoGjsmhBK1fypx3WN+NGiolSSfRlAa8M/19SuLbrFbU60YlTkVhaxOel6Z2nrDrhVZ5SesignE+5+wzdcwffvhhHRs8K8YDITiE5jAPOBakKMoD16rK5VdcIRuOSUsmBWXRLa+94q2Szg7K9BxafVlYDe9PwIrxYzcPGjZcQ51Gi//bryWMDWh74B06eGCPHHXUcarcMI+gG2HnC447vbKcE+z7kSVD0pVKafEBCxBYAWpKKrQvaycjihxdp4HzThVooyxLBgpy2MgS6crnogILPN/3f/BD2bhxoxyYnlegNV2c0/CvGgWhi8ahvDvco/ypwAAt14yYxLw48Pjhd5ff5/eeggvtQbxdfvyjr0oygfC3CKbkycdBwizS3Z2Qvv62XHDBpfKHL/8TyYBcG3mJdYt0cI8jzI/wLNaAUZcYmMezF9ApRClyrPClnkjJjl07ZfXKVZFBhOMyqDZGZx9YQFBqaCeHvuPNtlTbIltHJ7Ra2jqKIDQvcsT6w2V87KBMAuh3VOL6vyPDFd5U7G9HKUTDlPPuZVtnmNj2SgxG/DxQJ8SGSNxj2K/RzvXr17UHZV5HUDfgJ+/DvW9ykcV48KouzD/0uoEyFKvE08OwCtiMIUtl4Xm4Hlu/EZDS2PPHdMr/zr91DgJYJB8jr0cATMO8E2CyrSVlFe4/NzcrmzYvdgLRNfhflQfwO9/5jtx7771y6qmnyitf+cpDAsCDBw/KP//zP0e6DEoFypX/3vKWt8i3vvUt+Zd/+RftE3r11VerlwegkkDh5JNPliVLlshHP/pRmZiYkNe97nVy+eWXyyc/+cn/HeynxxAAArCyE4h5YLw1ZhuDwCDeKGYBqwB2TbaN1HNhVRUFkwc5fjNzkXtwwOtS4FC4cuPQ2xYLH7uiFzYeSPjjcC49jV7oeKsO55Lyxg+oF1h+M/NenQCHwtWfR8Drx4W/85rx+Ji3AHMC0t5kuyYzJQOAsBLB5dZutwSUJ2edcZI8+dQWfbcYeBs1AnKucF98h0R2VF1izjUJut6QE48/Xp7a+oyG7X509z1y9AuOkkcffVSpTZQOJcwxBTI8eLOlkrSSGQ1p8flxfXgrWD3L9yAAJGDpzOuiwsLzMGmf51IZcO35uVRgjHynuaKg1+45Z50tP//lfTIyNCjVWlnKc8irS0b9dkEOjZAoOlHg3MmxUbngvHPlia1bFSxOT09aVwt0gOjpljNPPlG2794na1atlu9///u6rwEzntq6TS7/g1fI/FxJuvNJ+do3/l2WDvTI5GxRLr3kQnns4Yfkh7/4gXzx6/8gc+NN+eu//qQ+J1qxrVy5UvYfOBClIOiY0Svk1jDXMgGh/5uf+b3HPYFxQ27Z8qX9kk7ltOMGALvfU17h8bo4H4oPxQ8o6JmamdcwNudG17ISVds+07SQVlM7ZOBvPMtgj+XOHbFyacgPrWlBghoI8KKmbO/tGp1SUI0iGAD/sYOjMrJ0ibUa7KAu4V5k0Rn3FICe7uVggBgDiBVSYY6VridcKxqbVlueefpueXLLvdKVb8noOHK+srJta1GVdXevyNKlaOmV0E4g6LX95696s5xw9AulBR7MekPKWrghsmf/Plm5ao0CTnj1UEUPwuhsOyE9XTntpoI5nyobgTMAXwNGQjojjVGCiAAAIABJREFUR204XLZufVbS7aZ0oQI5aeMHoD49Py8l8DdKUkZn57XgKgICIOxGSDqZkrn5cuSJ9bIO88OUHYyFN4StGMX48FhIxfQOM4iNiPxQoMrLJpNhcX6hAWMLdXq94I0G5gTj+RhG95EJnTflwbRoxAJKlZCv6L3Vdh3LPWR42usLviM+syIQA7K2Dxq6z+NUnhCKD63kIrkVdBzO47n0CnIf+L3rQbWXcQjjI63Exiam1+I1FXiHUIp2iAl7jN56nAO5+PZNi0TQOsf/VQFgJ1g4lAdwenpavvGNb/hDo99B4wBg94UvfEH++I//WD/ft2+fhv2+/e1vy6WXXioAmS972cuUhmLFihV6zO23367exdHR0ahV1SFv4D4kAPzYxz5mybJpE5wGHswqonucCzIGOOYp4QZkMjEFlW06E/beq0aF5YGSV3D4HBuH1Vm8Ds/z+TtUOlRGarmhHVMQIlR4viqZ5+Ce9ADSI6ICuCPkSKHnNzOf3R/Le3WCSy8QeHznTz92XtDw3fkTwYnTTjlJfnLP3ZLPFSTflZVsMqGcZUhWn5qZlfmZSRlcslSOXL9OBvu6NJx59y9+JamubvViwIOoHGiJpsghaCIADqFQ8UwQODAILrzwQilXa2rYmHcYjeZzsnPPHmmn4Tk2ehiCQ21t1mppkr6S9CZM4fgx9IoC79c5F50hFh6PufVeL680cI9qxZSudRdBD82WDPR0a8/bjeecLU889aRMjI0rWIRnZc3ypXJwbEJm50uy8dxz5KEH7pfe/kEZ6CvI7r37ZWh4QHbt3q/Pj+IJAJWMds/IaKcMeHX27NklPaDkSSP0mZf+vh4FzevWr5btTz8ptURafvbIVi160PZngg4s+ahvKMel05jhnvPj5teZN14URKpSS8m6VStlx45nZRgguFpVwNLd06eeLIA6Vhl7Rcb9oGH0rpyuAXA6wqvKe1J0cE/Y3gZ1igE8eKhGerpk985n5JILL5RqBeAvIZVqTU444QR56qmnAnNAUnaPTWprq0YyKcXZaa0GViCXSCo4xzrjPmaHEoI4RhlI3cMiJa0AD95AFjKosgh5fwjf4/rjo8/KI4//QLY9u0d276zJ4BAAbVKWLElKobulVcuT0005fH1B533/gYbUyiKf/eg/iNRSgo4feFlct16qSCqflWQipXL68HXrpFwu6R7T4rJqSVLZbqlWy7Jq9UrZtXdUDQhp1NQzl8tmZWz/HpXvnOdSua7AuruvT/7hi1+RI084UalSvBFGOUH56g1jLzc6vVI+/NiZbkMOPY4ZzyXAwffMg/PGCI63tRS3LOwEkLwm9UMnYOX1/HFeRvjzuP4oa73x7SNQBJC8jtcpMS3Mwm5XGpkPfaW53g5leFHnUE756I/pTSuMUdmWtLxtGM3WqQkUYHX9ybHT6JoWzyESQqPf8lUJzI0HcNEDqGvkvzMABPhTBv6BAbngggsERRhITMc/hHQR8oXHb3BwMIJrJ510koaSP/CBD8h1110nd9xxhzzyyCPR91NTU+pFxPnI1frf+UcAeMMNN2hFoIYBUYmpKSlmXZsr2irQ4k0bV5OSTJTHUPh44EeA50OuVCr8jp1CuHm8UuQG5sb3ipLgzSspgi4K/shjELHAx0zvBGP+efgO/hloiXnwRgHkBQUBLO/JDU6B7e/nk387Bar3unCMoDDmKik59bgj5cmtTyjFCTyAvd0GZs465SgFwL965EmZnCrK8ccfL6vWvkDue+IpOfeFG6XQlRQl+2lXZWrXdvnpL+/XOaZnBWN5xumnytzMnPaohULGvw3rD5fde/cJDBcFXK2mKu9iuarkz/BEsJ2bAuzA7E9ATcDmBTbnzc+t9/RR4HtDQR+GPTadkI0VlIWxMW+o7ASARW4rimVGBvq0iAPfI5QHQ4vrWX+GLioAbgZ+S+rtyXUVNIx+3y9+Lqedcab0FLoFLfkgrFevXCkHx8akNDsja9ccJsWZaSl0dWnFMeYBSdvwzE6VG/Lglj1SLJWNPLtai6ovse4h2DkHnGsm0xuFhgE78OTBA0dQxiR+gvW+AJxWLR+Rc045WR7dsk2aSt1TlampGenu7pFqIymj05NSLZUlncsr7QnHwZSNhdSYFI88zqRWoNrYEShq+Dh4AzEnqBFJt1pywrFHSk82LQMD/eoZRogdvHkYw5HhIZmYnFJjYdfohOTyPfpuG885S776zW/JkqFhvf6+A6PmSUIFbSqlgBXjyZQEpCdgbrP5nIyPjumzIe9Te/222grQML8AxAQEaswEDs/dex6U1etWyiMP7pG+AbTAy0mhgDlJyuHruiSdG5CZqTGZnqkqkJ+arWl4diA5JO+75sOSaNZk9eFrZa7SkL5sSp7etk16+oYir5Y06rJ+zWoZny5qegbmcN2q5TI+U4r6+lYrJUkGLxf2MP5pdXI+LxPFqoxPT8ry1WvksW07pIHsVUfH0mko4DvKCwIoEGkDNNL4puzlsX7/8Xd28MCYWW6cVfPy3rY2gwc4EB3HxliscbiP/XN27n3KTO/Btu1tnjjuaS8T/PMcSr95g4i/M6Tt5a6BNzgnYiqo2JgPPZVD1yj/HHQuxF7E3ww9+/EmOMykLUVAw/iBlgvdcqxFXByNiuQRhkC/t3/2eUvX+CIADGPy3xUAfuUrX1GwtXbtWtm+fbu8973vVUsX4V0Iui996Uvyhje8IeoDyUVwySWXyPr16+Wzn/2svOlNb5IdO3bInXfeuWAf4HyEjf/kT/7kUPtDr0liVxwAAAjL85ZbbtF7k4oDixTgwnKEAAhZZRbzXLHCkyFftgmia59CI17AccUVH67TquPnBA743ocBPBjAfdjOyFuPPBfXImjz1Vv0GBHkeYHjhSw9Vprz5SoHeTy9JxQQCnwCaCboo7LkM1Fw+Pc4FHjhcV5Ya1WkJKTStVKueM0r5Msfv0l6+gakO5+W5csPk8pcUZXw/FxVqwnPOvdcmRgbk+m5kkwU52X58uVSmtovS4YHpFwGIJiKPGl8Vw/QCWQp0LAOImsUbeDKKGKAdwntvKpReAReZI4NnhdrCIAL1yPVDt4F1wVAwnf4Ry+t5RzmIgohhEXUsxjCfMqbpsn3ZiXjexS8KIVM8EToGmzWNaSbQXVfoi39vQX1/uB87D8SLQPU4n693QXN55udNmAIYIZnxDPjHHhbu/Ldmtfb198jBYQHszgmIWWQL69YIj1deak1W3p97K2dew5KundIlfn45Kxs37U/osuAd7RcreixACv4D0U5OA/ABt9zvPGsFiZGr1jzLtiYZQ1khhD9hsNXyfj4uNx2001y3IoB+eAn/6eCIVXw6byMTU7I9MysXhvXLJYrCvjwrhh/GJxgA8DfJPw+5tjjZf/oQSmV5tTABKjDsf09vRE4g9d1aGRQ+vJ5Genvlu5CVqlS8Mw4fumSw/RZ2826nHzKSep5/uLt/yqgrp6cnVHaHORwMvTIjjM0KiKvlRi9FOZLcwCz4EKJO5yovAqAFuuCAFKBfOBW1PSE1qx87V8/Lc9un5Punrw06iU59fR+2bd3RoYHs7J7T01Wr+7XsZ0ebcumt7xdTjjqNH3G5UuWyoHxCTWKpV6X3u4u5ejDPgDNEDzshXxOqnXzVA+NLJXhgW559tlnpbdnQFMEsD9f+OKN8vMf3aW5bCtXrJC9e/dqpfDs7Jz0DvTLvokpNbCmwQUYeg6zZy6NJoKWTsOaso+yykcV+BlBH4EjZYAZIgvz5fwxNDoU9Ltetmzn5kEfjXns6d80cOLqYi/3KZe9zPURJOwJei496KUcXQiaYp1joG8hqbp/L8pcAEN4ADk+MTg2T5w3WKnb/DgTvHrATfmfzuSsX3sCnX4Wvr+NVcI4CFNZUOnrqxAoY05APH715kUiaB33/64AsBOZQaEADCKEixy+5wKAF198sWzYsEE+85nPKADcuXOnfO9731twOQjMz3/+83LFFVccEgC+//3vVw9i5z8AQCWCTlgoh+5sbHIDNtY2xwCJkQAbBxvzJqySlFZ2p3fHh2Q7wZ/3lNFqwzHes0dAQeHC+1IweOBFcEVwyU1Ea4w/uVEpRHkND75o/XKje4+ifwbb4Jb7EgsIGxsvpPj8VGheWMUW6EJSVYJIW/QipfRKefmrL5cH7/ymzI3vkq5MVvsBQxkiFxRrYNXKNXpfgBtwBHqKGIIKDZEFZRn6peuxpeKcAk0AM4AHgCgo5JGREZmbLapCn5ialn2jB2Xs4Ljs3LNP5qsGMpTIOJGQiekpgdVL0mTOCcA8ng9rDaCFwByfAzDgngBE+Ju9a/n+g/0DlpMZvCVahBHIknt6TVnjPrgmWuTB64VOKclmW3ryWT2v0J3XkC1SJ6hE1q1bI9u2bdNzLYQI0AqQ0SXz80Xp6urWKtpsoVva9Zok02mZmSnKspF+yefT0q4b79qy4UH14GAeZ+aqmstWrDTkmT0HZb7aiApn6rWKdBV6dOqVMidUInKN+Z9Y3+rVCuuIISUqVu5HjAXAx8jwoKxcNiLHHbFBVg71yg/vu19pcNK5grxg3Rr59t2/kEYzIatWrdAcRngBUyBADkUTyPtjwUe8T+glMb449UY0G9JSihXLNcW94W3r7cpra7ljX7BO8tkuA7i9gxoGHeyztACO+7M7tsv+0VFppQzEzhVnZNnS5TIxMxWlA+iLt+O2XnE4LO4tDUUZ7TmxHCvlyAuVyl6+0BuUSYv80z99QJ56sipwqm68oF8ef7QkSw+zlnCzxapUimn5+C23SaVY1ffqzqKgxwoqcL/xiSlZumRYmrW6UuWQb09jJk2RYmVOlgwPSzqZkNnpKU0fgMcJe+PMF10iB/fule2PPSIpdK0JnjaMzeDSlXJgz05JprOyb3pO9kzNSCLkWHrj08spyhWOA77zoJCGrZ6TDBxzwVjlmFL+ePkce/dsDVjY0vpNMyxpwMuAlVVWx2FNXAvXJ0E95SnBGs7hPeip9eC2cy/wmNgojTUZ5SzXKP6mUellK/ur89om92N6o6iyP/QD9jLc77tO/UGDmYCN78goj46FUmlZFANhYfOoIp0GWwqAOlSHY80nY11i+tCI0zdfvQgA/38FAPEyRx55pPzFX/yFvPOd7/z/NAT8XB7Am266yRRuCP/QFQ3PCfnWvBXZaNU1yT+2TmwjEsBxM3B7+s8JtLww8IKLiicGl3aVTgHlLURek0LfPJdxQ3Dev1Mo+k3M4/19mZuH7zwwfi4h5a1DPosnwvbP1Hk/n6fI96EQIYBCfp69S0qy+V454sj1sm/H09KVRVuuQC+g7dnMQwRr3cC88fJhjlUgh24ZBMkalkgmNZ8Ungj2VqUwxXv5HtBQ7I1WW0anZzV3S68f8ldwX1TbqmKW2BtI4e3XiSqukEuFEBvHj1WVtJy5Hqkw6BXm/GkVcLDam42ahmkBXvFeK1ccJulmU047Zr2ku3rloUcelXrbxoDrlETgpqhact65Z8tP7/l/2HvzYM3Pq0zsfPv97tbdau2y5X0hCG9jwAEqoZKpmZqpDKmhKBMDNgzGw8SrbMuWLGPjDWuzBDYuY4wBM8OQZBjCpCAMjMnExBiIzWAcvFuyJUuyZHVL6u67ffuXes45z/s+309XMG7zB0ndW9XV937fb3mX857znP1P7NnfdpV9+ou3R3Zvt2unTz9gj33MFfZd3/kd9qm//IsSgD8ZH9iFJ07Y+vqG3XHnV2x/urCHdme2aHft//nsF6zb65XagYP1jexIUMMQSPNhXQl3ntJwKGEhhPlT16pnW+sbHjICEPakK6+w7c2hW/lQLBlAFJbLs7s7ds/XT9nZnV0H5yjazfVUOgOYQ/wZXcEKEEgvyPjFvvlYse9w1Wbs3fbWlj3jqU+wh888aE98/BM8rhiFjLc2AvTiPEBReWjnnG0fO2Gf/eKXSqwUy7kooEH8KGnHBSXc1G0UpY41gcXNywUhbUUyOdXi411eUIpjbeDr6ve1p/Yzb3ur/Yt/8RP2W7/zQS/cff/9c7vgIrO/98x/YN/x3O+17c0N2+j17PgaSv8sPNsb70fWblmznD+VZgc0/Z5ddulFbo3dWBt4Oaad3bAswxL/+c9+wfqDdQ8h+MxnPuOfO+2h5AuyyRGCMJ7aRU94in34T/7MgaNbZZeIp9z3jHq+/xGKLtyMUrIGSTcEMTx7+N5d6lkomWtJPqfrX+6RDkWkxQB8HQc0/ozsJqKKMHlXnNVaroa0zPHHPTURI8BRUHsoOjFnyg2eXVWm+cwiv6QNHteLZ4zjgdXZQzrY1jR7AhM085yR/1OJ4JiYzQ+DCNeKY+Yz+LnPAYcF7QFhkez0y1kH/RK4k6+tGg+i/uiRCzhp4v8vFkAwQ2QFfuADH7AXvehF7gpCEsiv//qv2/Of/3yfLayEKAHTTAK55557nKHgB65lZAKfTxLITTfd5NYXP/iw9GXhUgQoQ7DyELjZv6EZhRAJy4Bqdvo7mY1q4wRa1IIUVJFp6IFWYEYGo8CSDJgMRZ+nY+Ph4iEls6PAUGCqB1mFMJmBMiY9tEVgJVOg0MYYWV9KNUWCRT6PWnPTdQ3rBFxxz3zGt9vtt3/Ga5UhS3w6GtnaAK3MYMWqjJLr7VaxdGXDNfpffudzbXNz3f7w//iYg0IKRQIuzgX3IJPWAUNq63S97o/Gdt8DDztYQBYn+7c2LbDKBJugv9CVgHX9jOtSBU4VEBgj15lAna7REPBItOi71fKJl19i//W3P8P+6OOftHa/a1c99cn2xdvv9Lk/97nP8axhz5SetWy4PrDv/Z7vtg//nx/x2DUIB3Ry2N7etP29XS93gvhCyCpPBqCVdzFz9+2pM3tRv22ytJ29fW9pp0IQ84MV6PhxZP1HHNBh9Ey6VBCsghVzjz1d2nd/x9+zT/ynT9lVT3uiLadT++q999pjL7vErrzyMfa1+79uO3sHdue9X/duGF9/4HRYRrLkCuOaSKP8P94V3gCUn8B4K9ioFjgHgGltw7VYv2c8/ek26Hfcs/HHf/zH9sTHPs7dx65EdszuuvNuGwyHdmZ3z26/866o+biIen7l7LTCquRnsF3b/fm4LBQcCFI95wSr5BvMcMelBShkrUE8G/GP+H8yP2c//97bbH2zZa946Zus21r3dT1xbNsu3NyyxeTA1vt9B9jIDAaAwjs8jGBjYF+/52t22WVXFJAeIQ6gpYixxD7DKo133fXVexyYe5Idsoc7bY81veKyyzyJxIENLP0HY7vjwYftzGhql190id359fsdMHRYZaHTzjqSsLANVgAhXZXMguZ51lhfTwQTLw5pi/w4eAfrPoZCzefE+kYh6VVeV71CEU9IhTVkQ1M+KH+vMePI6o295/j4O/9W2aHgSnm68le9ZlW2MBs3492RaSxxj14PEsoYlOZsy3aY/NN1pPJGXq7ypih2SL7zlnsIGejafBqJH3gf3sO1ItjE/AeDnj189qy97prrjuoA/l12AUPzvv322/2wPPvZzzZk2CIpAwwQ/+CGRXkYADfE8V1//fWGmn6f+9znnEHjB2Vgfvd3f9fj+XAPagICKDbLwFxyySVecxDaPzKAkSRyPmVg4AJGsDwOs2dtgjmgFIb35ayxbaiQrtqfHsSm1U8ZBq8jIFGQpgKfIIsHis+s2ttqRiIFhB5APewqHFaZV4yOFsHme8lIcL+6n3UeqiU3QWxTe6yCM95L5qTWFb6T66bPwO9hIZw6g0K/ULSCg0DCs1Dq5BnP+DY7dnzLvnz7l5yBIg7p2c+8ykYHe379H33s/7bNDRS5jbIJSy9L0LXJdORaqWrSHB+YMp7xyU992tfqW572FPvUZz4bBWbbXY8vRPwTyl1AkOE5BOJce66NWvX4ma4F15PrwLXWNVegtEJfELLeQ7ha1VxEtdEFpG8XHdsIV5OZbW1s2Npa32NfUeam3+vaYG1ohpiu1sIm45lHvbaWC68jiEdjbY4f37YzZ855CQ7MEa5cZpViXA8+dMbmrY49tDOyO+693xNhCN5UUXFQtUxXapanoKVVlRzSJy2BnC+FYaXtuWf9wq39tCsvsy9++U57wfOfb2telLpnv/8fP2IXnbzQ1jc27cMf+Zj1h2sO7ABQAELwE0I8AtQJ9ANMV6sGxoakNYQVxE9cz9p1btiAQLOgJSTVIKYQSWTHNtbtkgsvdPAcmZhTO7O7aw8+fM52RkhSmYarOwGZj2kmLc7SHUZ6ydwkF5oKLJq042ce7m24ubPGHl2g/iy4bn0qc7QBtvFo5kAN81gfrNlyMfUkqwu2N2yt27Nnfdu32pdv/6I/65Of/KQ969uusu/5p8/HjfbR3//fV/rKgvbWN4ZOg1gTuMadzyxbtnP2XFq30gXovbo9rslamcl8dndkn77nazZZLG3/7I4dv/gSXyMklbzwB37A/rc/+EO37k4mIw9XUOWA6wRATcBDUFiUpqwNiPvwHcEGvq9AmhZpN06WkB/GIoYCU8NctPOPxo0n15P745wqeCTtw5jAcjLkCaAnFvbnGWcoge6/8gzOh+tC2uBZdNpICybiXaHoUQ6wqwcAWfCRGoZAZYfPpVJL17GuB+WW8io3HgDho/Yoe/2mVRDWbucZ4Dm5P7M5yjCFkoU5H5WBidX8OxsD+JGPfOTQLFxY537hF37BQRqYBxgpQCDA4dvf/nYXSPyBr/91r3udxwNqIWi9BqDxpS996SMKQbOgc3nYX/OLdgKhBdDjK2AIbDYBT42MB0hdm0HocQ+tVofFezQBGQ+WWp5A5Cw4zWc07ysMLus6NWMMydRWBW8VyE0gpxaapnap15LpcElxgLV4r8uSQ1x1/EzBrgorMgoyIBekGXBMhoMxIjGH1sdBCq9uB1a/cCGhfdSVV15p3/m859m/++3/1a56+tNsOBzY7rk9u+++e72NFBrdfxdq5X3iz92KdWxrw7MuYa1BfUq2xFKmpfMC0PNWaL01u+PLd3kMGdzA7NzBvVAwQW1YrVmPBtr1vU1FgUJD73WlJTODSbOwVIOhg4lub67bVr/lbrvj2xv+eOwbrBNo4QY3Js7Mzu6+Z7tOJ5FxO51N3O22sTb0Dg3wNMJqNsg2c3u757wm4Oe/+AVfj8suvcJ+89//R3f/Yj0oqKj0bG9teLb0NF3diTxKsoUqO1Q6SCNc/+ZRDnqa2/RgZBdeeIE94fIL7c57T9t0tGsXX3yRtTtdu//UaTt5/Jjdd+ohBx/YL5zRUG5Yk4znPQARhVuJBU4LLWk91jCEosf/SekkzMNjPXtRBuPY1rYDNQCqfmtuoxmSc9bcKonxIeAeiRGoU8g4YtyPZ7IbC0GwghwV7ATFul4Afkz24R6oVYZKlfMgyGMLiyosmjgzHY/TQveOsGJt9bphVc4eyL42HbO13tAtl5gvEqugNCC8wN2ZUEp6bQfJPLfLTttGO/ulJzXm74Cr23dLoFuVUYR8OrFzs4WNJjMbz+Z2kL3VQVuImeytDVw5RwKOK2+ZUVqBV2bxLmt3Da6Zt5QTS1e1WkUhdOVHyqdUcSP9VpqsygJpP+6NuNICrsTCRU8Hv+P1dQwBPPk83ecmD1fgpXSAe+nqJihUKyDnxH7BTitSO7LJz/lsnSPPDMZUQF2Jj48VIg0S1PLa4rkCCEzeVMbksaw1nAlY4CgGMNbz7ywAbDLpv8t/ayFoAEDXyFA8NbPOHEih9qsDray6TyCIQyIWwTgoadbO7Em65HhA6KpTMzlj33BImfV3mMZFbZHr2TS186Cq64CMLMa/2qaNYIQHUzVgCgq+U61ZPJxNgKyMgvdTcOEdBC3UrpvgloCJwp/j4dp5ks5yNTOshXp9HTwbVsG222uwdxBMEM1L1FjbOWcnL32M143sALwsYeGa2L/7179ua+tbZVwYnwOf8b4LshMnLy5CC/OhMIb7CzUB0aFgD83mO217+My5KPA7DQsP1p3AjAzPu4tkBq+6avV8KBCvjLlm9+pnPqasMekMQSxZDhznC9sYDuyiY9s26LftiksutssvvcQtX7Bkgd7u/PJdhnIMyLyEBRzjgmK2trFuj3/slW5Zx7rf98B9DnQwNwdPqJc5RueHli07HTu3P3ZwdfrMGZst2razt+uhFJwvxjdB67hW22bLDATP7HoIOAV8TYsGhWNTYFPpYgzeWrdj33nVU328H//UZ23r+Jaduv/rtuz0vV0fLMburm8tfRx+ftB7d8kyMOEOA7CLcVcXIYWtKlQEGni/AnAqLrB44XrMDfF/Xn8S4GotasUhbg/Aideg+wXKvNAC6ePzHtTp5kU2uJdqri0ZCZp5hlXxA8jRs8prFAx6qRuGriwRMhDZ6ThT672BnyOA0i994fP2jKc/zXcMQI80jnWE1difiZ6+Xngard7a9icf/4T9N9/7Pd5RB3UScekc3XPgTt+Ic/enn/gL+/ZnP6OALiQFwfKJkjnYq4OZhXLVabnyMMs4O9AM6GkFGKG2HGIzfY+jdzN5DotvF17Xiox+VyrTuhYeANwbcbuqZBE4ci9Ii8GbgidpKANBUpx91r0LRU0VbOWrFXRGCZo423Q1x17yfj6DtMA5FIDbjkLW5NGkE/X44HdmlAe/Cs+I/2uEbVCmKH9S2aYAUGsP4nPcq9ZBXqtz95hWm/veOwjsVTDNKCK8e2dn16553ZEL+AgA/i2hypVWcO4ayjpqsyi/AhewHzavkxbEicbtwcDT/ZKuVKSvM8A2rAuRMUagw8NAJsQp6PeqeR52L7/ns8gIyPibVgEePLU86QEkOGkCEn0OmWyTWfFvzkO1U3522Pia2uejAaDCvNOt6YI1y/E4OJwhxqbrzKrb7YQVYJ6FR0uZkK53L8Bexrq3bbwwWx90rQ97VqtbSmqQOc4mB27RGm5sF60dLgmClNFoEnXXJlO34ODnYBJuPIAeMNW0on9BAAAgAElEQVTC8PD3eOxiWxk4GXJTsKhAV2uDCg3uFWhTtXeuKwo0Q3DDVdvrdrwOHyyna/2ex0+tpduFa8Ix0FIAoErQBTAFkIQC2hy/A5QWOm1MI/sZpXnGU9sfj11Y4zOv3ZfACs/yZ6Qlg3NROsB6MYNehTItYiqMKZxDyIZlzcFl2+wxJ7Y8kedLX7nLdvYnDmZ7yOJ2KxC7EMR9sGQBZIRQDbDHc6UgS4W5Ar2g2xBusHTRUq2KEcAe1gLzwPPx3TrcsWllxD0YA1y6DjqdzVSQQIDoykxaGRdQYFLAczz+bs9KrkKf4+Z4yE+wftxjfAcFF8/BPLAmCJfotFuuPBzs7btiMOyhI0jLe/m61aobGfYXnrigdPBgLCWeg/ABjcctACITRlwJTMsp3n364TOGwuTex3geyhNSqE4jI7/bd7ran6JDCiyVOIue8lJCDMijaX0PK1TG40k3FFgYC8iREi5NfkUFVpXkAsSlMwatV1SUqbSSFhQYcf+U33Nv9Nl6PkiPVJq5p3wu6YDnQ+VHkWVSz68JPleVzADyDgr7UZdR5QrpR2UF30/eqfN1OsgQoqbM43xLMlv2POfzQOOqSMc7F7a3t38EAJNYjyyAfwsgUF3Aw41110BUs3FhDuIDMKRrKDOrnKFzMwgcHYCwjdBqf0UeDj3EekD0cJJJKAgiWFPgpYyDQI3PJ9PgO8hMlFnwgB+2lE1mwb8pHAkSmkyMbZUIgHE9x+KCINsBlS4GsoZcI51L0dqRqduK/cFnyLp0V6ZbANsRnJ6Au5/uYQoeH6Pj+JqQwHWgYKbw4Oe+3u2IgcR94fLve0iCu4GncxtPoiYfXFRcD4YPeG9Uj2WBiziAqf4oKKeWrMJfhTkZu48hwa3m13AP8HwI0elsbMe3Nj1+Dy5bWG1QjqPfbdsaukFk7JoDgMz6mywQq4aODdGKrAneQygvbcG2XC1zyx/qv+3th2sXQNDnnTUTuZYQ5gp2m2tBQdT8n7SstKj3Bv2GtQelWSA0Bms9j+HF+qFuGPYJz0WPYNYLJE3FWYIFJ8Cf0ji7u2iBbwWiMY6Mu8z4SwL4iPN7JNAirSntMeTDFYikN46fXT1gLSQ9MIOS6+BrAItWZr/qOlMwE/RwftxzngecK7ruoDggDrDXbtug33W6AfBbzmc27MfZYykY/I7xI3Z7PkUdQ/NWb6P9A7vrrrvtqqc/xcfN9VAQCuvhotPxLOjHX355XANFYW72pbvu8taDu6ORjeew9i1sZ3/PWm5xjOxYKCGaeQx3cNBLxG7Csu3zzPZiWEusE9aA49H9VF6qPFL5KRU7BVqkm8NolIBGaUvPNX8veysFoMmbXeFqhB9xj/ncJj0VJbGsSc2ex71sk8m58RwUZUGSY5ogUxVZ8mKVBbwea6XK8GE8vfCZZXhfmMlelHEJh4pC0Af22muOysD4vv1/IQv4MGDxd+kztQCi/RLch3o4mtY5EnHR8rMOm8YdEqgxM1jnWzSctCxSEK0KnkfWjuJBxf8EUzx0eoiVGemzybA4n8PAhTIhBZl8pmp5fDZBk64LGRe1YmWCFJAKbJvMlGu7KqQJzBcOgLDeUTZlCUjiMUeDdE0RTHlgu5RuAPOPTi/V4kFg1wQVuk/M+g1GHEIHn6Ekxf7BqABAFjZ1IZjXoK0gkkV0PZsu8EcCjxgNmfyqlh4ulSK4Sv/cACJuEQX4Wc5sfdB3BWVzOAy3XadtiJTaBJ2XWB1mswaIVosHXdhk4mGpikxVgJX9ydytNSP8jo4ocOUuI/6PjN3XFy657K8NAIkfvotzU4HGzw7jE6Qz0iqsUwDkbpXK2odws8JFjdZ0Z3f2/DGjvX3rD5HZWjP1+R5VEkiLGvvHM+fAJ2NeSaN1PBGn5IWQM3ZVwVd5b+Zc4NqwWIeS4TxD4uQ8oYgehgwnCBdlAvOsk8bx4l66h7lumuVKoMfzTwBI3uElgVBGycunRCbocjZzd/rmMEp1wAo46HXd+kce9+Wv3GXf+vSn+b5/9E//zL77ed9pf/rxT9jznvMcfw5KB8Xcwk1aQUBk2MJKOIGrc7awuX+0jGz6VtvGk4ntjCdeLHs8mUXP5ASAmAcUDv74uiT4K+uWyUt0TTMJpslzlXfRukz6wjoxXlQBHteT8d6kXwXfvF5Bpj5DzzGBNBUE7pMq8ajNyRqD+mwds9Ng0p/uNferec70b7fGwYDBxL9UtJUXqazRuXI9lJc158TzxnPBdfe/04vufGFZ+4JTlsQ6t+zgYHQEAJPojwDgYRLiG/yMAPBd73qX9QfDwtiaGiDj9PB4FRjwSShwAjBBz0v9AaHzkPLgErxRMydYUgGnh5xCSBk3fn+07EkeRDI7MhL8Taalwp6xZHg/Ez00y0yfp8KdVg7N1CxCiYQqsSv6HBXGTeaqoFAZqJckSUGMz5EIApkAtyfcm1xPWEzQ61eZOwAge63qM1UwKVP2eWatOPweexRuPASoTyC0sgsDLIBweXJfNWifwLC598o0m/tFhq0CThkor0fJBIwLyoaDP1hGEd/WMY+7ctcvrGL9FN6wCPaQABLXek/jdE3GmGucKMcL96lf6zF+Zx18I1ZtNJna7sHEM2kRv8aSMFhjb/wuVoSYT9utNtwjpRnOlzTBuer/XAsF0wRiPF/4G4ICVszjW9u2e4AOInDTArQEMKeA5FkmjegZVcHItcb3tJJxLBw3i+vi3Wu9cPvy3K/ck1Ypv28ZgJJKURRLqbFnVZFcuNLiPMhjFqHBRKFcKKy4DvGFBJNcM8YAqtBeBWEVLAAcoXyNZymn627Q7XpnljhHHVvvd6yPs5fxWRjPV+++11BIHIkceIbTH6y9yCidz2zpZ6a+h7xyvlzaGkosIZkqvSf4DmtcFInxzE6ja0h/4EoFfvbyer9Oyu/4+XTFKECyr10WeYe1kta/JkDhueZZ1DOq1+J3VWR5XT2fsW8Mc2jKjya9NPmp0qDyePKjoBHQVBb6TmWN4yItNwHeYeCT+8F7CRQJtmi4KLGheY6b8oi0xPvwP61+amFtAtHm+QUtg37dEt4deJUGXe8qXxc2Go3tda9/w1EZmCMLII/UN/c/AeANN93oxWJ5+EjMFFK0KiloUiagYKaAOR9aLTOhVg8Ffgo6CNRwp1ofm8KPh4Lv1fuamiUFgo5XtTe6ZQgWyUz4twJerg/nSGYSFpNgvo8sf1D3qK4BmPLcrVUcizIGZVwEKGQKsGbh2shGRfZh1BxDrbpmHBKZlAumtAaigDcZPteR2qr7TH0BsrBrFvclcy+dKFqogTe36SzaMsFFBcsF1zhAWey9JzkwkF9cMrSwcX7KvBUQ83c8j6VkKDB8fi5gEwgADWcQNQAgEhEAALFmbr0BoJ1FK7gQvKtN1+O5YX1CXB1AH+YMUAfBDEHqgG+2sPFs5pY/WPjg+k1PWyQxZCwbxoK4MiZbqCDkfqtCwd/1VCv9kn6UVvU5EF6L6cL6w76d2D7mbkMmmVDokmZ5lrnupDkqVaxRWMfCkI6aKUzwFvTVKrGSSr8EOLpn3ueUbi/JIFZA4oVxW90SY1eAoscjV5c1gKDTAZJukQSRljb8reukPKR5prxwcrcVMYDMbkYiSL8XCoN3icHf/Zr0kcAOXVYO9nY9PhdrijJCiH0MnhTnO6yX0UUJpV5wHeO/uA9+ZiwUVJTgwv+wACLEYJQhFgi54DrCAshzS6sSlDDOH+/F93j3L//q9faKl95qO7u7jVjQODeapEC+y/c0QSHfyTUkfyQvafJmPb+kC97DPdGzH/dHXCrHwPuoVHBfSS+MlzuMlyqvwzzVaMDn8xq2ufPxJTDneuqYVd7xXFGmke+RX1cAV08Sz7S/fxlhBOjkhFhXWABp3FB5DFpCDOARAIx1PLIAqpQ4z98VAG6sbznTYp9N1UxJ3NTslcm4Bi7JHuWgZNX3JvDT6ynwlNDJuBSk0fqgh5AgrHkwKeA0PmYFMLD9jmh2+i4FfE1QRiuJLre6KfgctaZwHQMMVS3dNfaOucWKP1yr5hqQweN/MDEIqchKRVxggAzfI1i+ENw/nxkS6NRlQsBDYelzSwsf95PdPjhvBzNpvcI1vubtKKsAK9fBFMkfc88E9mzFdO0r+PN5J/DjnvD5ur5cA9KSMtBmMg/H69ckkPPfM/OzP+jawf7Yjm0NPUYSGbLoooJyOVvDQal5yCzDujchgPGDuXlrO9TDBCCczUuiy/4ECRbn3A3OxAUIX4DGpuKAJI39MVrkBUDWWmlNwEf6Wclulj7Ueu5UeNY1c7Tt5WyQxIB+zbTKoBMMlBRaACmYlKa538zm51nguBSsUoh51xeAGm9wsHRawH2gSRXIemZ4JvT8U5By38u72oi7TKYv1jKnnez+QTBS4ljZ5jC9pPRgcK7kcbwPFnSAUu/GMZ/ZOroitVtONygDgwQbKE7Htjb97GFsBXTNlnbH3XfZk1BX8o7b7Vnf8q02m2Ld4+ws2h2LlAInVunCM7cvffkue+qTn+KxvShD5C0MoVDNkBDT9jADnKuD2dQ/r/SCBJ7pSva4v0sAIF63sTG0973vNY6Ooc+87KU32zRrOnP/SDsK5JoA3vc354Pry9y9RMlq8o2eaQWPeubJ50iD2B/NmCedK9AjbyKdKLhXkKWKQqFRd8XH+rHDDa105C1BG9J1JBVYNRAoYCSv43roGqnSw/s1JEJBKGv/uSzwrirRYWexrEXmQ/61bXd3z15/7fVHFsAjAKjs9Px/L2Vgbn2Xm595qKgFlgMIrSyTP2hJ0oOuIKzExaVLhxX+4Yogw1ULmjIG1T75zKZ1T4FpUyCSQSroJBNQEEmG09RiVag2GSKeQ/exghN9lzIijIVaPpmDvi8YQoCj7Na0UrZCmWDVUCOJA/ciK9GLzLYz9m2JDO1O6VKA+yvTieDwqMm1mpyj60+Lb5NBk8kDWPo6TEIiI0gdDBXFoFnWQ4G5l46RVl4KLDkn1Zi5/mS0FCBNAM/PfY3Syoxr2PMYwhxzX+t1Iw5wDUIcmcDo59q1zmDNBt2wWFHYEcTMEsiiAG+sVSvKkxhAYMT/wfIJqydisyCYIHgpeJaZdenjQdHuztK2ttdtdDC1g/2pWwwTDawkm3DuqjyoQsA14Ge6VrGGoVzg/y987hP26U9/yr7/B15cXHfcd1cUkFQBsOw9UMM1HJbPiBtFlmmUBAmLEulXFbV6/lkPMNCW8gLeS57R3F+dn5bP0HOsIKLQQ1r9eEbwv5/vTt8tKLSsl72FoQXAWCzher4wZoQJ4Ht07gAARGb9Fz73GY/nA+30kGQFi/08gOJ/+vzt9u1XPc1pCJ0ikMX9ha9+xa56ytM8SQTj8PVLFx/HqOfN4/O4voCzM9BY9FfeH41sNIvQgoN0AWP+sLSjXAx5ENcUY8d3sWdtW9/o2m0/d7Vtrg/MlkiMWtjDD43smtfeYK02OsjUcBc+S/myrjv5GnlpBWZRsmUFECdwotGAdEd+RMu/giSNOeU7FGypPMK7sNaMO28qy5VXROY7f3QOlCmkMyoIOAuUE6wFSD7lltk0Gig9H8arVDaydBTlAZU7sAGdo88Dw/WzifCGoJ8qX5YeA3hkAYwdPbIAFtI+/18IAG/0VnCbj2DeZE5e8mWl4nscev5UzTQsMv63N7+eusAFEHBNa7YaDE0LAZ/TDD4nkyYTweF0LT0FDcdH4asCqik8myAislprbUO+i/NSDbM5z8OEsDIaMhQCMM6zaqeR1u82q0bGGQEN7yETUCYNAQHQCDdwpx1ZbbD84L14JywKqj3HOkUtRzKxmG8UaSXT5bp6RiW00XQF+34i63AaLjZYurD9sE4gsQH7hmtoBcTznNHDwpiMjjTCeSlY1vWlYFABxLnoOMlkMVfuHS2AXnMOmdGIkWxFHOCw33MAiBIdvkZwzwEEIWfXM9rDFYPYPsRowVoDdy9cu4jV8qzLOeJwRl6iA+DPy3GwXVnSPcbi2cKzfbvxnTd5kk6QGQDWwgZrLXvFK15pG1tXeGYu14Egi/M/TAHhNUr3fn8ngNz73vNO67U3bHd/HztuL3/lK9DF2N9NWjyx3fMz+sCpU9burLuFs4LHsBpzP9WNScCA72NvFg6IWI4Ea0hrIPejyZkU/PB30Cz3tQjfRwGSuM7PbS/q2HGtSB9Oa+3YTx97WifdTJ4FuHkPxqZ1R3GewFuw13D9DodrnviBjjroqoIflBTC97gO6wmrMMAh9gBu/tHB2PqDnq8D3Y3omY1D5p0+Uimg0uPZy+76Xdp0iuQqdsdAFq/ZwRgKQ4QjzKB0TAOgs49zk39SEdnY7Nr73v9ab22ImOGv3j2xY8fj7D/4wMTe9rafXUlUIj3xeVxb5WlN/hl7Fn3HCajIpwnKeD/3Q+mB+893Kt/V5/hZTR4Z8iGeAuCpP6SBFWt4ZreTd/IdPFvkU7TisRZgKBPBOxTMKV03gSf+JoCmXKEc4Hspn5q8j60NcY5ZRYI1X2MMoYzuHezbddf+1JEF8AgANlnr+f1dysC86xZbG2Qv4HyUEj8PKZkaCHnFjJ0HtAizzNRkKRQeNAIn/k/tiPdVgFRjZyiMisDPdzUPpjJDBae6MmRUKjwOY0p60A8DKiqACZqobcKt6Ew914DCTQUPmanHwkuVeH9vAjPMgUIbnxP4uqD1wrLLbLuFxJAEPL3Q7HkvwKQC2abA4Dw4X1j4mnNXIQALBQU+BBIsHwBDrHvngtDrQcYYYJFwy4Qz7trzlmu2Oh7Woav3c/5N4NCkE9ZH5No4w/dEELTgQnD/siSCYG8ABGHJAQDAmLG27nZza9/M3W+wcnrsH6xjnbZb/Q4Oxj5/gEKPDURMVnYGqfOGW3jXfu5nEVeLhIi57exEq7HhBh7VD8vwcs8LBr/6mhttbzfK6eCHtKkWO6V1riN6g9/11a96N5Pf+re/YZ//zO1p8ZjbyQuP2e7O2KbzkV199TVuhfXQgX7H/qd//UG7/fZ77eSFA3vLW2+2e+97sFg94MJl/CJ/h7ENcyYdA/T5ec6M5shwri0a+buDarEgKhjQ86nXkR61EoFfi5jB6Ni2YrFVZaac47wW37GcjI7DP28oXQQI7t6dzb1VIPZo2OvZRq9nm1trfsZKoCfc3PPoVIL9QrLNVn/NlmqxkRZrd586ZZdegN7Pq6V2esxYzb330ArkuPj5aXmrN8SXRsmXWHF8Dgsg182VAgdDYQFudR60/+Xf/LwrLwBok3HQFRT806fO2Hi6tKc//Wn23/93LzNk1ipfIs2pFZdgldfxOwV9PM9c16aCTOUPz1BQhGfRmkblRmWEgkP8rrGKCkj5/KZ84ZiVBxdloVQTSONEKcgeLm0fJ3hZljtTGuIcVCZxXZq0fRiNqlLs31sAe/Ac31excHvkccbJogPMG65/8xEAPAKA5wf4mndpHcC14UbRCvWQqhDm/XqgVYuii9S7MmQj7QBQjH+qZSjIWPgs/E2BDC0bJn58RquAam9qgqfbkgdUrYBkuAqmqKkRfOJ6Pcgap6YMu6m9UdNUMKJgSQEPmVsEg9em6Ax0dgbFBIkQdY+IJaPg8vFmViQYh1sBs0UcZJRrzAjFyrpSZHgrjJV9czPpA9mUZOIrIDnjrxzMZYC9A79kjNgnAEAAQy8Ow0wILwVT+0grgOHvCv7+us8ISJs0R+DmLpW0CpS5ZjkSB4Fpedne2LBuqxbo9a4pbbTSioLluBcWHYwFgfeMZzsYRV1Az6JFBwYX0hHfNUWGcCYkZBF/Q6zdL/3S2+3ii7bsK185Z6N9dGdBdX+z7e2era11bWN76JbEdmtq/UHLM3Z/5IVvttMPoUdsMHwKRxWMnB/P3EUnN+y6666x8QEzmmPfYZmM89S1H//Jl9j2xqZbgN/97tvswpPo+b20h8/u22Rk9tNvebPBo+j70Y1ewP47rL8JegA9vG7dIdZOWqPYKaUmkdTi3xw391yFtwJDCtFHWEjEukoQoHGSeC7PG85EeX66WPk3AQHHUdczM3jTigk+tr296YXwj61veDIRsuyxnmyH52Ps9Nx6d//999vFF1+84uGo54i91GOm2CnMYZxdcRiLBgJzXpI9pD3WFvF/E3SZIXAMJWqlCHSWf8Hc/uzPf8f+6i//yLo9FDNf2P7ewg5GLXvqUy+0nbM7ruQM13rWsa79k+/7MRuuX/kIC5fyWQInZnnrvpEG8T95C69XJZJ70wRI/JxWMwVm5K18ngI/8mR8p9dxDMpXgu/XWqbxXWQSVxnHpLjwBjGJz+dFvuzu2drUgN8BHBYZk/uncdSkbQWiruBBdZeSTAwXUB5HfsyWi7ge3WCuvfYoC9jp66gO4DcPAksdwJtvssEg6oSRMPX/yghW23LxsFEw8BA60Engh+8ozHhdU3vEc9wKM0Hj65oU0dSYVbvSw6UCk+/TsTCuioJFQVi4QKs7+5HCiZareo0yOAWZTSZE5uiMP0vQ6PwC+FVXBtw1zJxuAiRlIrQGwoUEqw4AH56Ldffy3K2FdWF96aQVBoAPFsN2uM8pPLkO+i6t+0UmHS3E4BKNGnf+jHnEwSG2iEw8hD/in7IUBVlqAocmmFMK1jH851C2WhkAAEljsI4G40c85NKD9vGDpIRBloQp+4cgdncXRn0/B3WzqCkYcVYtO3N2x7tBgDaZjUnLLccc848yLyh6/du/dau1Wwd25eMusdFkx2y+YR/76H12xZUD++pXJraxhX0zO/vQ3E5e0rbtY317wQ++Gc70IlB45kiPvhetjnV7Hbv4wm17w/Uv98D+fZT6cxqCYhEQY7BmNh7BCrqwl73yNXbpJVv2np99q3V6AxuPwjp99uzCLrts2049uGuvu+Y6my9ZYgOldaZuXVaBrudNzxOTPngtsq9JIxoCoUKcYE1DMHgP59u0BDVp5TBaKmCE8XcuRYMWaFklTet5CmUCoRMBZkDHm8N1D7zHmUQIgZ+fVtvuu+8+7+FOoHz23K6duOCYD+/0qYfskgtPlhZ2qqjCfTdEP+TsNMP4v+AfUWoG8X5+JlHeptP2rF10pQBNQaFyQJ5WRK4nCj63W337vT/4FTv1wB3W7YRFdmNr0049cMb6fbSQHNl4umZnz0zs5AXozAIlYGov/tHrbdbaorfRn815cZ2UvzXBFfkpZYV6LJR+FVSqYrwK+FfBGT0/0Zq3ZgQ36aQJEvl3lU1RIorZ/Q6gJZSIdFUBaFxP40NREli7Mnmbfy4lzqIaQShQnCP/p1EBf+uZolIfiR8Im6qtD6tMrTVRx+PJURJIbtgRAPzPkZJ/wzUFAN5ys60PN0sNPD30ymhJwOrmI2MlMQNAOECRGoEMKKfgALHjGTxoPCgcLg8vD7sCFTJVCgoFfCqkmjF+HB8PdrUURiwLNHkvCNuo+8Rn8mCr5Y+HlIxT39+ck8Y3kWH69Z6cwTpQwSDA7JmRpgCAc6clEX8D8CAmivNDnBKsUA4mUS8NQi2auThQ9LGm9onnANjwh0AOVg48z90SGfzs6+zMMyyY2D8kSnj7qsU8wTtKLec7skg4/lLLZ1PL1X1sgu+motAEz6RNSDCCPj7D1waWUUNh31aJy+o4Wqxg3ufqli8oIViPKLVx4MI4rAdI/nC6WUZMIPeP61WYOjKwZzN7921vsc2Nvh07ZnbyoqHdfvs5u/yygQ3Xu/aZz+zY1nbfTp7AvsAa0LN77mnZj/+zV9pgHYIZYJLlTKqlAHPFnN73/lts98xZ294e2rmzB7a+0beHH5zYBRd17aFT6AYSyUXzxdxe8fIX2+//hz+w++6930ajhV10Sdc7XPT6S7vzrrFtbmzZ/u6B3Xjrz9hDp/cymxc0A79v1tzjfkrIlZ/PjA+Fb3vVYpft2LJMSdkjKYTcBGE8W01eoxZHvoNr3hTcPIMFBKYg9l692RlFzyTppNJLgD9PoUg3cem20+3acA3nqoYy+HlGLOUDp+ziiy/ytRtNow3igw+csiuf8HgvwF3afZm5UvHAAw/YEx/3eM8Uxj1uAZwtHWBC+YifWOz98Yilw4vlT3khDjXqFv77//Abdt99n7dOZ+zvR7JRq7Vh1o6arLPp0r7+AACW2cUXml12yQX2qU8/ZN3umr34R37ALnnMc4p1V/mpgi38rvyCZ4DnTs+C7o2Gf+DzCrSCvqqSECCYcoEyICx4AdoUUB/Ga+OeuJayivKJ78bZIO+PObC/enhngu/iDM2qKzgBo89RyxblIHxOpSh9gGidK+mOc8B7dVxUXtFByH88XlsNIfG8g9HIrr32jUcu4CMLYJHZ39QvmgSysRFlYMj8eKBJzHr43ELScNPiMzAjumQxsMlk5DWtAEBq47jVA8Ln4/Dhd7diZRC3n4XU2Ai86K5ToUPQyUPFg7bKYAK4NF3EPHwUIAQr/FxdFNSOFSQ2LRX4W8ej4yyCJTVFZgFj7bz7QPZdRkxbNEmotepib7rWSTcy7vFYKU9maXsxaACZSGcIIcz3FaEovYId0KS84XqDGWL/ELdGFwn3wEFQ1gX0otKzWSnM6wAI9qtp7c/L9WyumQPItnd3La4jZZb4HdfEmKv2yzESLOB7CiHNBMb3WAt8h2QQAEBfB6n5BytVWMwwluj/ycbwAHCs6Yjge497RKwjwB/GJY3mXbim1dPHDefcom1nz9xv733Pe224jmQC7O3E1jYGdtmlmw769vYOgq5nGEPbnvnMf2AXX/oUW1+P/sv8oTsJQtDjLBcLu/zSC+ytb3mLWSv2HfJrMhu7JbDTjnIX2Nabb36r3XTDjW4NRP/mhx4K19PJi/pmy4n1Bx372j0ALNjLhf3ky15qJ7ZP+L5ruSfsVVV0IlOYSkrsQZwpF9xZ0qgJ1JtgS4U3AQ0FNsF0E6wREDSt+Wpx4ZnlmSONMFEoQuVq0hB5GgEpQQ6LOmrdfdYAACAASURBVM/mEy9szWQR7oN34smElMFgaKceuNdOnry4AGEqTqCVvf1z1uvEM+IH9FgtWkjFRiFpjgF8FdnMAISoM4l34TvN/PX5ed1RxKU+bO97/6322MdEh5uD0dS+8MWpPftZHRuN8NyOnT2DBBKzK64Y+nPv+GLEnD7u8Wbf9bzvs6c8/btLhyCOg+E8VFwJDDED8gYFZbrHytNxvYetJOjhHvHviBMPz0StGxvn3634SLaZoNpAhDaoFS14OaxmMabY91qPNHhQtcyRz6iiiX3x9o2lXiML3q+2gyQvBb/lfLhW5JGkayrPXiEgZRrXzRXqrG/JccDiC9p0es0C33ALY05cJ9Ae5PUbf+otRwDwCAB+U7iv3NwEgBTaZLaq5RHoFKEr9fTIJOD2paCO4NlojQVB7JaizBYthC+xTny3C5MslcEsPgrFwqDFjUmAQYZMtxKBGIURBYqOn64AdktgfA/Hp5YJrgnHQkGkpV4CvFQQTcagwJOLzwxZAlsAQJ+LlwuLRIPIRIv4MwJfABS0qFJhByER7qsUMch87Q+8FEWInNUK+hSycDn4uqORgbTnQ/a2AxTvYhX1xmCpJBjHPrL4qgsGd9EEoy6uqQQyKwA/48gClNWA+NU1y7pyycyVVpQGCxNH0H/D2uRlQMID7j8AfH7vfFriTEmncIuDPpnYwXVFoWtXZjwbOFzbcMVx7VTJYAeRiIeb2YljQ3vr215vB3sozZMlYlA4e2r2hCe13Uo3WGvbeITer2371qv+W3vSE59pniki2fYQjui/TCCDZ68Nlvavfu1DtrOzb9vHhnb7F++zjc227e9hLwNQvv4Nr7Rf+9UP2Wy2a7u7M7v08oGXeTrz0MROn0aYxcJjwcYTWnTn1umbveo119ka4tpgvU23P9YOc122Ow7auZ88R6Rxroees8MELueC/3He6BLlOdD5q6BWRUpBcoDR6k3A377XcANbuHXhJtXzy2xxfT4BB5XIUhMuC6w7CBuPPRwA68AxIPbz7js/Z09+8lVhQc3EBvBCmNwmkygMDeu548+0DjmIyjOHc876k05zPoewzmMu0Y0GsaQdm+eZBs3hDGLcH/mj37Y//djH7Pjxju2NlnbhiYVtbK87gASNnT69tPWh2eMed4Hd+ZWz9vUH5ra11bbnPufb7O//wxe4e9T3L7OSVbrwPHP9Oe/DlGB8h/FjjTAftXJpXDn3OGgnABfBFHky16Oe/1CAFUDGeofCxkzZJp8nbTBJLzqK1JaF5D20RGp4TFOR8XEnkKUhQWkcY1O+WM9t7TjkCs8CJZhAD9XCz3qiDFnA99z/oN2gv2uvO8oCdpl2FAP4zYNA7QU83MheodBG0szdZKyq8RDsUPsn8Ts4SCtVAUTdqtkQDClwU4ZeABIOdzYw52cKetRCoFYBXktBrUy+uWIFCGVwcLjPaiYrDzCtgDzc1I45BrVYKmOkkKRVRTVhPru0HwMzTDdrxALmTwo0ZxxpweS9BJ/UOCFgMAd8z64gcVhq9iRBLV0zqtkDeKuA57Us0urlYRLEOXPPsjJ0I4eQYAxYrCM1dk9MyA4ZTesOWnBVAR0WpwD7tcjsYXvHvaWFx+eamaf4n/GAKADNNaMS4Va9bG/GAs54L6xy7CuL7x0MTTHXGIuCUAKjAvAzRvKii7fsphte7XhuOl23+++DKy5i9C65dN3bJQ7Xlnb5Y7bt3Nl9e+63/2M7edGTSikm0gnPD63SYd2Y286ZU/YLv/ABGwx66e5zD5T/PO+7n2N/+ed/ad1eCp32wk5c2LHdHWQ/b9k9d++UtfBkow5qH7dsY7NvL/nnP2njacsVDIJmPXsEe65spZJWzkC+n4qKClK1uuP6zc2u/fpv/JK96IUvtr09FHqGchj9ThUcNM8SQQhplB1FuO88pydPnrQzZ854TBV/EN6hFivuJXkAn0F6Ja9zi3rWZ2N9SZwHAFeGVNA1yvIwyK7l8/Gc3d1d7z6D6zRJBu9UYEWQEvwQILwmz5Xr0qqFe2nBxPveccOb7TGXXWp333PKnvWsk3b23GlbzBe2P+ra/t7MLr10YOfOjG08bduZhxd24oK2vepV73BrFM6PKr3sGc7x8WzyncozuG7kT5WvBc/R+Tb5JMAb5Ue8IxS1ui6uDvtaQBEKvpDxtlknjzRJGlNaI//lvnO9eK75LuUNnI8rEl5svP6QX9ANzG9Ip+R3PL+HKTD4TOUVFFCE8CADGCAQdOrnPgt9U6HxXsDoBHLdkQs4ZNphqKEpJY7+/mtXoBSCvuUWgytjkVl/GiNBpkrGyANHIlahy7i7SAAJQe6HsJV/Z5Yl73GXYhZodetS9l3FZ86AUXMsDzq3W7UqHvCqJVZ3FJmIBp8XwJBu2lXmEZ01UArFD7TEQFHo83oFXnyPCsdiBUggTcuZxsKFpIO7NltruSUugIavT+4css+awJsMRq2b7i7J2KUaQxZPIZP1VzpTjpg2/I5sVGZf43stdo3nkNkDHLJeFV2TBGpk/rGvAUBDg2ccWTL1BICkiwKQ3XUY18LSRHeiZo8raKSLjckwjAGsbqAasOYCPEstOFDj3xlQH9ZNmO6CMbPfrM/NZU08C0kvHDetBVEeJZQGt2BNxv7/cKtn733PGz0T+NTpfbvvXrhvw4LTG8zt+Pa6nTm37/UBr3zsun3Lf/Ff2RWP/RYHgNwvCi2ukQsFj0Xq2Ht+7h0O/pDQsXOuxnC+6tWvtNFsav/qg79kk+nCNrc7HiJw+RUnrd3ddWvQA/e3bG+33gMBi3GAJgZrHXv51a+23Z2RbW1tlX1Q0Es6J2NRwF3OtQTCU4CV67od+9Av32w7u1Pb30NbPpQoGdprr3m7nT2zVzwIh1ma9LyrQqRgXhUcJEgVvpFKEPeKyi2tVMrzeF5pYfOah3BTLlkyJKx7OG8Ea1Bw8NNtRTFu0iv7PzOmEp8HnUYdSYISPAdnsbc2cMsPwSLpQQFgrANDINiBp2Uf+tCv2B1f/or1ehgbLNsTQ0nIdqtn6xtTr3uJ1pGoRfmyl/10uhgDZDWt+uoq5zkn/+BYKj8Jj8DBwUFxlzeBoAJdKmHNODtaAqvsiPPF9edesV+v0iBBqirbBJ9qxcR1w+HwEf2qVfEtgNdL7AQ4Jh07CMy2muS/uF55g55Zgl7SQ5xrlMMhoM3nW3i+qGBH3HZt1QeQj7JT1xx1Agn5eAQASf7n/79aANfgI1hGMgF/qjskGAQZPA8ICVQ19fJdloKBNZBmd7eYZLCsHgy+z4WkFx1eRK07PwD4djUgnVoUSyjgbx52Hj48nxqoavscn1ooaMHxN0nf2mLdkDXhfSoIORfOje4OCk4FhPjMO2rAPSXdVbiWdIGogNM5hcDB3ALM9XqDYsmCxQxaKwGgzodri+f3e2t2MIqgf3VlqNWCrZPI3ADGqQxwbHg/3RQsCItSItSwAbaaa8qacj4PB/81qcKvRV9WcbFREKplhoInzF6hXBz2UwD3fGGdXgR57+zsuJBiXBfXnbRNoAUBC3e7KhDVAlVjE1kGRYHQoLe0X3z/m6zTXbfZPBIBvnIHkqNa7m5H6Rc8d2dn4oUgf/AFP2CXXPY4V8K4Xpgv94a0jHV97GOO21vf8kbb3t421AV74P59T/h4zetfa4PuwK58/OPtL/784/bLH/xg0AisCr2ObW2vmbUO7IrLtuzrp/fsnruyJ5iZu6O9sPc4gkL/x1e83OkKmdMUfKR3ggGOj9YwnAtYDgECCGpI/+QpeBa+e89732K9LkrhTGy4BgHftp1zIzt2omtPftLT7Z9+/z+zvd2DtEaHcqDKhvKhIqzT+qvCGG40p+kE/QoYDqOXJo1V8ErXd/aaznZwUHRJY9w3urKb1n7SLJOqYGF1vrUM+iWvJQ+hgl0ALK+hgpiWdljEIlYsgNKv/ssbbO/cjg2HAXTOnB3a3V99KPgo2kYOzN7xjptcGYFFswCfBMjk0QpilBcpf1S+qoYCzJVKEvhI8KtwMwctMNmlhoEUPpPzW6WdWHeWdKFCqzyTZcO4/gRtaoHknhzGW7nu/M73C8CvWZWCLv6M19akENIl95P0pPxf6Y5jBS9C68pWJ2q8euKS1KqM+U6OkkBk8Y4A4KEi7xv7kADwtttus14/4srIqGjO5sE4TIOjJUjdiSow8CxYICjkVctSZlwEK1tqLaalr6u3GsqWXwQsfA7vIyhjbT8yD1pRCFQYb0Qwy0OGg0dGq8kqarEjg1OgQLDAOZPJUViW54vZ3+edrg7Oo+xadlBRMEHmQYYcgCTAH91tBJwBGLJbgLR8C+Ya8TZRQZ9ZpqFhUriSaVZNO66bzyZujY1iI/HTdGWxXRwBkdPRcrXkDN4DdysC6yH4mAji9OO1yyILD+211DLCNSdDdWGbWYGM/VHKrxaEAIZcOwoZWgk0fpMtrbiWYPy0xDAeqVoolg52kMwBQAthDpeol07pdhxcejypF31GMD7axY1dw28vxvbhD3/Y/vzjn3SL22Btaf/oH/8Tu/iSp3jAv4I+FUouANtde9e73hQxm3NvW+tze8VrXmmt7rptDdc8UBz7/PlP/5V99KMfjRZ2o6n1YRXqdbwEzdmHJzYVIyDwM8aCMj8//MIftuHgAltfX1txm3N9KdgVdKtCyHOE63l+XOnoRyzjoN+2D/zSLXZuB27xjm1vh0US1jqEFJw7M/Ws7WPH1+zYBRfbj/zQSxyY4rkETzx3PGdNBcmVrEawvq9lJqwoaNQzrKCHYEHPu/JHVZTxORUFhiOoMkW+xPXgc0iHHA+fo2NiZmil6UcmT/F+jBkt7X7zt95tO7sP27kzc7vzzpFtHfOoWFvfXNprrn6n9wOOCO2ahQvgock/TUnCd3B/m38T9FB+kJfgfEaMdbi/gzfH+Sb/5twI7Mi/SWN8pwIpustZwovlvFRZchpslGZxa38mF1KekLerMuzjg9Wfmdqene83lrAWPItZ45y/nl9VllT28VyTfzt/yYoNvgZIPnL+sldiCrF+u+fO2rXXv+koCeTIAtg8nuf3tyaBbG5u+0MUlOgB1UOjDBeHmtfx8BUtNrtCxAFnM+4MKs+gJRfCiNaBaT3dfwBk7oKAlpvthph96FqzxJbhXeqOJmPmPJqanTJ5ArbqIvAVKAec2iDv0XubgIPrQ8bfZGIRyxIASrVTMkwKLQoJ1YBVwFKbboIi3MfPOE5dAx2fCkAF+lWwpksz223p3lehGwzc72FGbbpLVhisl+AIaxOcyGWMnrgRa0Gg3twzp4nM7lPN3p8hHVMUMBfaQ25Ijk+VGAoeXQP9nmMn2KOwQhyg9vltCkDOi3TBd1MgUEnBnDymMtdiPkNdtih6zmfw2WoFwHdYC6fv1sTe/tNv88D+f/R9329PeuK3Rsxky+yhhx+wY8dO2Jfvut0uu/Rx9vM/d5s/F63AIPuuuOKEg4MzD/W8jIz+vPBHf8guOHFpCGck0aTljAoBr1XBrLSpilYTIPHv3/u9f2kPnH7QHjp94F0qHvv4LfvavTt24njHev22jSdze+h0xCauDVA8e+jg8Sd+4vUOyCuwqFZ/nlNdP45VLU9IDCGIoDKhZ5sCm8rHI5KLMg5UwR3Ho3tFkEOAockfqmSRX4I2CHK4TgB+AJNUuGrR+AoAFcBEIoTDETsYnbF3vP0Gg9d6axOxsDDv9exVV/+0X9NtR6IPzMP+P8o5SQUHrifXgfMtIT6Sqc41V7ATaxrKJtef5VlwPT035HHkgVyDuD/4htJRPZvVPepAPQZR5BDPGset9IrfCe6dFrinmaSD9XavlSTF6XooWGWok/IS9eDwXeo14lh0Ls1zrnSscmQyOjhyAefBPrIArrDu8/tDXcDufhJX2mFaGAlVD0TTVVHAmJjIWWuJRK/Pbh5OPBuAkG6bEIy1rZQDiSz06uXK0hKE63jgVcj781xDh4UpSlio0Kpu6XARVtBbw38fTSNVoc9nUovXGKOQ7BHrp6B6FdjFHjbXg9fzubgmNOWFAwe8h5ZNMlC+h+CDbjqN7+O8aQXj+un74XbAuvF5se/stNAu7cC4r+h44fe71h9lQXxNG7F/Ps/M3EV4AJNrlJYUyDOhhevFJCMVmhgXy8f4O7VelxSmbsaE0pqKuWK9uLYUaBgrrJVOW+h7ulitX/lorjqeFWXuEFUR+4X+r55TWwCwnmCCXRV+TZCLv1HvMRSGcCnD6uiCdnpg3X7U9ZxOZvbz774lrLdLs2c997HWb8/tE5+4L0FHuOR+7MdfaOubF4RlOYEf3tG0qKjlRi0nVMxo1dD5FCDUatnP3vZ2p4due2DT2diQMHP27I7Np11PTEBpmksv27A52tLNUZ5jbuPx0l772reWLHSuKcGcnlsH8x3EW2apFcQfZxY8hTdcbJwbP6MSAJ5CHlHAmHSOcP4jPKfus8MYX68ASljXGtuq++fnie7QhncgzhhASoAg7cJReVfNQgbw4w/HgljCT/3VX9qHP/w7dslFfbv66ht9jXk/z5sCF/IeKiIKnhirrR6RcuYbLSuVV+o+EQAqAFKgo/TCvSm8Mvmmg0kCM9A/eB8MCKz56FV+stNSyjLEUPNHAXNRKIXnUilgVybsM3isekRUtpA+PBY0rYoR8lTjhfX8kPcoSMTYaAmmcqDjrQrP0kb7B0dJILk4RwBQT8x5/l4sgDfeaMPhxkqm4/7+vseQKCAgwyADVAGsLkF+7/97LF7G9qXmSGZbmCnis5B04WU0ItMUgMlBRCZBKMDioQjr1SrDJtPQMTSFp7PqjEnhoQwNm22bIuaRVjVlVI/Q1JPh6DsIHihc6FaMeXedSTHTFwytHvKqMStDVncoARvnh3vj996KtszxqCWKlgZ1dZC5qQDnHPk/+76yfAtKX/BZK2uboT2LLK5KIeGWPGQP5/76+qeg1fhOMn4qGCoIMI9Sj20lniiI3y0OqSjwfr6fAJZ/65gpsOq+hiIAVzVSdPhTaJ69OeVdALwU/NzLppLENUevWQerEh/ZVDBUSeCYKWweTUGoa7a0+WTqZxe0gj6144M9e+973u3ZhpOxr4bHIbJP7A/9yAvs5EWXFTpkFxDSFt+tgIhnV0FBU7HTMeN8wf17481vs35vYHt7YztxQd9dv6AlJKjsnpvb+mbL4wLXN2AZfNiOH+/aK179RltOq8WZe6XKEYW786EsseEKkoNI9FLL5CpXUKqyyLNaLOjeizf4EDIyCS7IL8i7FDwp2Mf1rClJxZd8gIA19nQ1sSAAH5OKoh82ACRAPrp5REmgOh7StCoJsS41W73dBZ8ZOtB2wJOhFRyPKidNxVTBtdeoy/p0ld8EsCKo1Pv5/NWzwILLNdyGPIc0zTXmM8n7wS8JzkjnrhAD3NHyRyDHFmv5f/G4xGBXwpx8HxqdO5yuwZPzevIg8gGOsViJ0xtBesDntJRyHkW5OKQ3tspC3Rf8rs0MvEbrURJI4cdHAPA8QZ/e1uwFzBgQmsgVCICZstyHMmBqRNWNCktJlvKAAF0iBpDWNS0LEpakSP0PrZoWqrDCIMApAqX549enBo7fo4htMEsFDTxUYZ2JjDseZFpslOnEvEPAsPSICjN9nlqQ8HlllAEgq9ZPLX61lIPzlXRxx/1ZHV/qKhKgFqbajtpRTesVhR7+p7uUa0Xgx9pZCvB0TQkAHeShZVw3MieViXOeZMKQkKoVu3TInwWKtWbZFe4Nx6L0FI4btLeKkAC4LylQFLg1hQDMWAGmIqGo7nvW1EprQQGvoIFe1+fG9WTdM6wnhRTd2ByrjyXro1FQcr1p+SrgLMuX6Hia9Og0hCXOmEF/TxYqVBegnk8Kd4IQBSN8PoEAz0Ds28wTOLBOozHSQLv2nttu9UDy+bxll1+x4W5Xty4tzX78JS9xBZBCTQGgzoNnQl2DpBMCZFyjCgvXF+M8drxlt956q509c+AxiMdPDP3ac+d2vWB2fzCwwXDhgm53p2Nr6zO3rLzmVTe4dZN02azXybnj3aQ537PsCwwLIIEhyp4AACqQUxCl1iTlO6zPpkCf55Tj8cLs6c5lkpbSPvmd7jH5Ug0RiELD5AvgueTHTHji9woeKtjMep3LiLvD0eT9Ora4NwCl16Cb1zhGnh2uq46X+0y6qwp08IAmoCFvIsCNPczKB8WbUMtUxbkLSx7j91iCycFaGgQciGYoEGm0CRKToYRiTLc1+SyBI8vOZJwqeRCy/vFcdY2TtrlXxZWcoTLkiZCVLlOQ6JfZvBzjinUfcX/g7Q0jQmnZOY9scK7rdDw6cgEnMR4BwL9FAHjDDTfY2nCjCOBiHk8tBH/TikUhStM2mcqKlYtaGKS617JKgNZCTbVp0awJ/lh3jYWfSfCzeRxAPSA+No87DFBHhq2AhXFtIbgJzOqCqeZZgWF1b1LLo8DjXBXA8Gn8jEw5MhYjYy208ZrQUMBW6fJROwKAyVV3dLi8i5BCPbNlFmvNoGaCF3ZkIaNlSZe6HquNxxmzqdYcgD64ZJ2pZuN53WeNE2y6AFVY+L6hi0kyxKbwi6zfKGxbAGAmpTQBehEkjCuk9lzWs9YL81xgKT1EwObCzbuORDY5wQgzLzl2CnIFf5CKtA4pENCzoZ/7tWkdVICoQtFpNddXQSUso0rLapUioFHQ3qQ9zoOxlrwWgeR+Pmdz+8qdX7B/8z//tp042XfX6sGB2XTSsh/75z9m62tbxcLCvtJ8xqrVqnbRIBhbAfXibuP93Fechfe//21mrTXb3Rmbt1r2bjDR6uvJTz1u587uuUBcXx/Y7t7IS5YcTMb2ype+vYRnYDx65vEUrjfGEkpcukXT1cteq3h26buagECt4dwr0gkAZLHuWY09LtbcBAikPa6JsmbdS9J083oFMFRsWE5plcaqIqtJSxHiEf1ulYdwPFwTvoefk+ZYb5U8gcok15pjII/n+jApR2lTgbV6dGoMYLjJndfMo+A8vCHkd05PWYOPXhi6ZL3CQcaAezIGwCBLMGWShgIsP88ZxsBkDVoTuQbkVaQZ8gCuGdeT3geshcuwLMKd6CyTW8Kbw5AVjAX/aDihYsT7oYyw44fyIiaEeDFzkXGIATyqAxjUeAQA/xYB4I033WzD4XopC0KmxUNAgqXWp1pe86CoMI0g2aoZqiuBQCKeFdYKMh4wBnSXiIwrFxMBhtLd6Wb9dsQJxsGhe0cq9M+yBmEy+mA61cXLA0ewF+OOGl4UBFXQZiZyWiAjKzl+oClG6ZUkzNIXkkK9CnfXngXQKvMDo3o0Yerrvpx5bS8CPU36UCFBRhpCMsAzLE0EH/geGasKQBDbdpjlY9lKxpw948jo2Y2AFhcWXKYAJhCioKPVFW5gT4BIUObj7oQ7Odqz1axhpSNq4bSwUOBrLFMFQbVYs4ODpBGWpIEFroC4pBtYLLnn86yRSOCiwtoZT1pvle4VFFNowg1OIYN3U9D4M2ghzyB8usO5L/heLT8KpjhOPoPrNBtPbG19w6bo3DKbROzSZFriL2Fx+8UP3GCj3bbXEOz05/aiH/1JpxEqOKVGohQd55nnuJXt6Bpwvei2Uo8A1gf9h2+77UZbLqLfMoAfQCD37fFPusD2d3dsNDbb2ti24eaBTUdTO7s7t5e/9E3+WtK272sqGavgKVyF/IxAjfSHz9WKzmdS0aPwLwAwrc0oyhtWpHg2rTZesy27o/geZTIF+aPuua6bzoNj0D1WoEbafwSwkZ7FhZ4kHo/rEECLpWKqC1TBHw34BeymJZV/+zEVy5uGkijvafIQvgO0SAsu19rnzYS7VH69DmrW3COd4720uJFWmtdwDM5PUwlxoCcuV1puwbthWQQf9nVJhZr8171XDfpXIE0aUksz5JTHAGYnJ8QlovPOZDoqYTlN62Tw/l6hJZ8v41Zzvb1Ie8aKQjFADODr33DUCcRp56gOoLKU8/u9uIBvubX0HSShUvDp4VIN8TChx+8plAKwQcvLenAWmb7KaIPZibUra7uxFy7jByGoALaceWZ2mAImMim6jp15ZfYpQaLGIq4y4QCQOGzRDQTCRmvAVwuTE5/H8WVdxCXaTiGnE26lqBvF2cbapdBIxob4EvxQEEVw/mqP2dCCazFtdzX4cOJdXF8yJu4RmRKZYMyxJr00hTgsT+7/kZhIMmhYAsGgnHHOItmAQkrXnf2DGTzv65gZ3ytavZAo1pmWpVZ2lFCmzjGsAB/Gj+ZzFAA13+Mlb9o577Rs8vlscca1QOIKaRnv1UxT7pPTVP6g3zKBro7PE5JQ0y3jI/FLEVhIaNBA9fwdlkgfB62vXli6glGewcPAKPeeYGM5PrDdycwGa0Ov/eeerbS4EvSjI0WvA3gOYI/+q9l7u8RjBp0TEOr7VfhizNw/ugQpqDl+WovIT9D944Z3vs0B9MHewo5fMLQHT+1nbbdQ4h575abt7I5tMkELM7N+z+xNb36bHRxUpYxCnjTEvW/+jzHq+dC9UkCofEy5KO9VMFjWOi2DBFdcD66bKzSMH8y6mASI5JEKhPhcvp+0zTE3z23MlQlt9fw+giYa2bpq7aKiQoWG8zzszOpzFUzqeHlG1KKqe6Ig2wu8S+wzeS+uwf0Ai7SwKfjjXul6lz3JMBjwX75LLYtcQ/BfWhIJ5mjJ5H1NGai0T3pv8iYASgBYT6Q8xHWsz+ZYYAFktxqlVeUVsS8RPrJ/cAQAC80dAUBlV+f3e80CvsUGa2v+EGdead6mJqrErtqpMgBluOU+s+j3ORgUkOFaEoLgIXjTRcwMWS/5AitcalS0+MHU74ciixyTsTA7LQ5JxIUp81QGxPEp2AQ4DaYd4NItSouZwfXsJRhSo1QXqApof34GSPP5tLrx3WRutPxRaKBfJormMt5FBRE1bwekWUib8ZBkDhTAZBxkME1QSPDtTDMNlQQ9ytij5y84bwAAIABJREFUDVHfLRr+uWv8UTKBgEf32z+bRTE5Z+iIH0zLFgEgrqFFqGjgGdCNheu2a+LNYRTM51FoKiDR79RtQ6sUxu6Wwoyzc0GRMXgEyM7YEwDrfuF9ZPRusZQWTbE2tUWdWihwrdf0QoZzBvX7PkWHZ7e8IjavFtlmTcaabOKdIxzjR3wkxnWYcOV6ce7HtzZtZ//Au0n4ns2mduzYMUMyF2kO1s+mVQqW1ya4o4DVNVEg1AQkfCauUTDN6/D5HV/+lP1ff/SHDvDQI5l1BxEqgWQUHO2NzZ7NZkubTRfW7UU1gFdffZ0XLldexPnouPk73rliZWpYlHTselb0LLiFb5EdZJwXwcrfjeSStNSTPghAuAbF8sZQCndzVyWwvD9BP/mGgpsmLepZb85Zzz/Hoso7P+N58R7ZmZ2vtMVQm7/uHPKapptZzyfBE2mW761u80gGKfwuFiTokpavRgs5elwUmJE3kx/ibwJ70oDKKsgQ8tqmoQL3MZRG7+VacI1VtrAIeFMGKoDmeLnnHCPWkTSh60261fqk5B94LuTFtW9881EdwCML4GHH9Bv/rADAW262QX/4iHi6JpGS8bqmlkyNFikQKplNAYNiWcK9LlhxHSx4sKRk5i/qUiFA3d+XWWx8fhy6yMglECHzhYBgdpq7gTP7bzH3AKMC4HiAgzHWeEa8rzCqrAeF+1CIloeVYIGCnsy4WEDS6lOz+iLDj++PLNdwIR+2nmwaT+ailhN/hs89gstdCOe6qwv9MAEeQHU1lpAuRiAaAlnOIxqeAg/V1nM1DokWmJgXgbNr5+lWBwicjFCGJN1M+TmpkqCKMXDuikXhZHHL1zXLxJi8WZm8zpU0x7n62NKKRuGmzL7QpYACJHpQUNDNpkKTTdrxGaw6jGvC2lKo1bIfYUVGtuUsadCFnbgJdd25Jgo+YLmERTAsx2nlyUQZChSugY8JtTOXC4ML2F3rnY5BuRjv70UMY7ay47pjPASNKpiUrvn8VUtyTWbi+vA6nkcK4FCqaukmn3NrZg8//KD94i9+0Fpplb7wYnQOGdneDpRB0DrGZtbrgy7M1oab9vKXXb0CoDj25hgUAK7sXyPA3rsswPKSn/t6ILyCrkOx1B52rgg8mrSqVsUmH1RQUYC0hFVUpUWsxnmOVFlRy1DQRk3YUtCryiRpq0n7vt+9cIMWEJOWYAWQqmgpH+X7KBMUQHKOeK5a8IL2VzOwWTYF9+McFX6Ug1I+R3rleH0P2RM591Pv5/6FXKnJJQrSmol1ZS0a5Xma82TsIeUfaxuyMwhd0EH7GYfNtqeZnKRnhPSoSTWI3XWeZPE/lLtrrztyATsdHFkAv3HA17yDAPBn3nmjNytvCloKKwoNHmwKXmWazWtd8EphYLeiMY5EBuLMMi18TMmPAqBRjJMMQK0/BJBRB1AEk7fvCRcpGUrlbp2SnRwBycE8UBpjNonYPLc8Ztxh3BdCTHtPuqUrrUpcLwUgcS1KAYQbI0Brgr8cDBmQ30+rSXm3lEmQdWLwsrcnyhpYjFlUxsy5s/UbAZAzw7T2+GduXQr3uzNNxBe2I9OYYyZoJ7OnkOP4J5NRgNIl+5HOiyUQVkA8t4ANF3ihJATd1NZQXOOVsR4CmFeAUrq3lO6C4WfB7fyeFjUvEsP2SgKASdt8tz7Pv0vrHbMYI8FnNWaynotZJF3MFw4AC4BIN7evRScE3eBRXMnMImcYgruyZ7VjAyyasT9ZSRBKTbdjB/CZLpaF5iDcvZwSxpJJNxq0r6BXwZDSEoHJYeCBoEa/w72I02T8IgU26YjCDeMYrvfsnTe+zY5td21/d2mTydzmM2RNzm1tDTHBc7vmmnf4s0hDTWCjYyVNcjy4lp9RGeD7qfhphqVnBkvtQP7ue5jhGM4bEjz6s5GcJb22mwJd50+eyevBpjj+CD0JXsHx895HA3C8TsEmaVkBJemZe6C1QPXZ5K8863wu79ex8RzxWgWf/E4VHfCZ2IvM/HfLe00oas71MKBJeiP/UCsk95P77ePJLGLcR5DrIC6ThNRqzfdxjQrQToCpNFXOtJSbcfrKkmf4ncYCDxVKVzeMChEqFLIgeF7wR3WbM9RGv+P4wW+ve8NRJxCnlyMAKOjgPH8lAEQWMBh3J4v+KlNRLYqMWAEMDzoPPoWJH6oEYiRgZrhR2NK1qi7gYNIxIS3c3LSeBS8JAEPmEPWbIgtVXXN+2DKphAyYPSoLE2SCxxJFjCfpBo/EFPagxBjwXBWkZOzonRrB0VEBvzKgWsgan5EhqMuH20cgQYbDcjq+XpIkQqYWDcVrphj+5lo7E3QLW42vLPvXyY4S/qKoz4d1QDHwArLSVUTmzHHj+2o1iI2aTUb52cLBjz8294HrE0WhUayZ/UBZMqJaITzWJS2xFVTV+K/4rFo9/N3L1aQPrh3v9yD68aQkwmD83U4Uj33Eeue7MYbJDHXX0L4sQGULwr5VXTdNYY/nYW5g0t5WK93jfpaWkf3ujD5jYNnvmGctzg1dwk7RWQQ4rNY8h3Tjkw59DdJ6rkIc84Z1Fu5UtWwqKOL1eq7xPVs8FlpI5UStE3ivZoXyWaQXvodKon6uewsQNZ+P7dZbftaAVy88uY7mdZ4McvWrfqrOm0whLfvNMTeBymHKhN7DM0d+5eU6LIF9J1rt6Vr59Wk9VGsfS8rweeRTBBHra0MH5xwPBT7bDNZEtloEXt+r5V3IE+OMxBv1WoKKJl0X/ph8kXPm/ukZ5zh1PnpmOX4FUKoY6ph4Fit/E4ArAFDXk2CIc2kaGfi58nzKGp5J/A1ANuiDP1b+4bxcyqrgWUrTCmgV8Cq9NpUQZvz6eMRq65bJ5BfeuCBL27DzSBNsKv3qd/wcY8c5P7IAJt0fAUAeq/P/f6UQ9Mb6CtMj2EEvXz/UWS9JtbMmAyJjIQETjEGAVRAIoAGX78yFYilbwvZvnlm7jPhAMHtYMNBntdOR/sDBSIJxhMXKrVlezyoD4FdcXVFQlcWSyZw9ILjddpcvLWaFGa5oqbW8BMYGpu8ZgKWIaLhmPQjYQtijeGtopmhfhVqHGeflSSxhV/J1Sq20aNyspSUFsFV44jnUftl5IITEarcUd3g0il0XRgZgiD5R+YN1wQ9jU7DePQGTvA9WPS8cl2sPsOMMGjX2lrB+TQIqeQ/NWg3fx+9gfW6LFjpNeIW2UhLlMFBSE3ZqEgvWiCVTvGVfJsZQ0OA5dAGr1s/vixIhcX+qwCCJg5mdXFsFpHCPK6CGEHf6RXPVrC2HOcIVzixgd9GWWEmML7O9UWj6kPi0oAMW/KW7tu3Z0r7Hvo5MFonwgvH4IJ7V7XjBba9B1u3YBce37dzZXTkr1d3Ndz+aoMNNh1nc+G7SoVoJuc60vuFvAgYKbN0r8gu+B2vZ7S3sPe9+t7u7Xv3q64qlhMpiFYj70VO7FT2k+U66HLlP+j6OleBF+Vc9y5nlm0jb5xuEVvq14m8ARAXvhV+i8HRaEnmfKsdqIWUnI86J57EJBnSc/J3rj2up7Nbrwj2sz+P60TOiQKsJdEkT3DM9S7S2NRWgR1No8QzuSaxDdTnTCqjvU0VTQTx/17UkgHPFWwoy+7xToW/yFs6b/NdpAm7WVAhpPFDa5fh0n7j3fk4ylAjPwv7yXncLz4J+OK9SuWARFkB4oMq5afdKjG5G5BSFGNeC3x4BwKDqIwtgOd7n/4u2ghuub0rKeS2VocxHDyoYCZg025DxkK/EfOTQqOHBkkaNjAzMn99peywfrSDu7gT/QvakLVcyh8mo/ZDBzuSALzJ+ET8IHFmFU9TjCyUQlpDsgZngSxkkn4v2QhhvfxAuNLiKid3ioGoGXhQ1dabW6mRcZC1ozeezjA3/9uLG0pBcQUiAyCiEqgBBgQgZRjDoWsyYTIm1/PxBnmgRwMXXPgEzasQBUDDpp1gusN6dXgE6ypB9XPPIiHUwltm+82kU6UVsoO8ZXBtZBoWWLwCTUmwaYwG+z8QRFaQsw1NcuZnNy/nj3aA5T86QOC5l0s0xEyCQMaPsDeka6wO6iPmEQuDCjKWH0iroCkhmCSNgHCET/CGgQFKMWwFHBys1AQECsf5hqQuLJ91iFDjcHwUiao1B9xWnk3kNi1i2I5TB5uF6RsFrvIsu2OMntu3smZ0gA0lsUcsf157vXTlfaT1RocvfFWBxLfkOvYa/P5oALwJZyquARr1zTMYVP4IHtWa+Dmd27reTFzxhxY2mQprgk3urrjbP4kd3EHHvNgH5ihtYihyXe1NpIl2VcaZrmHMmfSigccUpz4qC8XIOkxa5zgo4lNZJN3FdKMoMr+BziwInpXN0nZQXE+DjewX55PNq+dN3k6YUvCrdYG1i/aM8kq9Fnjk9n7hOLYJFMf4bsuM9XChjT32/aWFshpKk0sVxOr2nEq7r5Xspvdt1XfSs4DrEMZI3MKyAxgUcIYbVwCDiVma3CEaNQNKfK83pntb9wnPJ+0aj/SMXcDLdIwBYxM/5/1IsgDfdZAN0Xs86Vzy4RUhKSQUKXT20YZ6OQGq1GoSUjdIY/Ckgxa1E6OyB6u7Ivl2UBAcybpZWgalnMWMP2gCMzgQbLmAWwqXA00y0KkSCsVG4xMHOGJXs5elACe6eLOgCAOemRQdmYWbEM5qae4Bbfh6/q+vWmSqzCJPxeFJHFixll4uJ9xLNGn4hvleSJfCcAA5hufM4N39OgATVYtvdns094zYSPPATz67r0O2F1qrasgpDtZjMphGThfcB0MD6BYbmc18wFhAMONy9/j749twlHFZAgCCWY/E1AX0k2Oc4NHavuc64hvTH5Bj9zAFoI5ifz6A7tINsc0+QCA2c++nP6/ScjmvMGuuo1WLZvt7z6GyDd/ka5ZwXs6mXwsGz8I/PKfNw4FsBpwIynp9VUBz1DLGO8T6EGiwNoJBxlZODkQ03N4p1OEpH1FgjjpNnW912Cih4vhV86lrqOVaQoPSiwAtn2Pc06w0qnfnoc594D58f6xBhILyn0AbWezG2bies7Apilf/EetdkGt4/myN2lfXlIjbN3aGItUzPg1q9VKFQoO7Cfhl7gpZzBJi+1mnoYjHpJk/lvDUW8LAzqEo3FCyc+eY55TUKUvQ+8gQ8ny7VOL/Bs/Varr+eOf6urmC+i+dO94ifNXlRPDvigP3MJajjWvD5BEKqlJV7xBPlYwBAkuf4G6QGYJkPwzuS/3azhzDGWCyUCQSbSo7SeXOe3vVjMimKtIecJN/TOoQBNDOExE9zKIVu6OA5ZWkx9jEWpc0Vy6MYQG7nkQWwrMQ38UtJArnhnd471EsdiKaljAYEqIIswE6NW6HQpYDF39GoG0wm/ifT8UOSrd5Y+gWsmrFMfA8Ag4OzTtvBGK1JRSBBgCdodUCA1lYyrspQOM6azUpBGoIrmGC4EZJBwXImgdpuSVu2PYZkPDnw8RA0rDLQmjhSWi1JPS4KSsYIat9JBcFc+xButR1QgLuI7WP7uhayU1OrDq091gzAT91xMd5gPIXxw8KWWiqFvmrHBEfF4pYgj1X8CQCdsc8DCOEHAAjArgKgsBx6yZ3MaHZm7a1Zs/VcxiIW5aJhIfT97IV7VH8ooBXYEwgQvKrLC7ECzICMOD+sQewniAhrxHVjmALcwwRHpPvWMoAm/rnVLUHdbDL2+Rfg4P1/a40/BXEUlmoJUyBQwA2KcnOdmGDjgDBWgq5hjnE8G9vmcLNkuR8GDghm+J2Okfuuc1ZwoKBLr20qDh6LyCQvsWrz3XRf0tLB98V6RB1R7Ek08UhlodFyTGlf6QJxuVgf1LHc2gKgnNnXvnavC11YceHB2Nk5a1/72j324EMP2Ohgz1qtof3ID78iXLywWee50uQJp9t0GRalOT2uPEMKqnVM5fxnz3PSsvISrg3PIXmBnk8F6k1ezH0kn+W5UJCt+9ccM8dbgXx1KR8G/JpygLJC5QefybafceYiDlfpHfeyDAqBF96plkddW4/QbcY5Zy0+B3L5YoJRfSa+Uj7hCXYNxZ7z5X4rfZMOWG/QPUdoB5hxzsGLa7FpgD7nbd3gN74HEntaQg1kzOSFeA5CPd5w/VEZGKeXoxjAFRl4Xn8QAL7zxhv80CETtIKvAHw8bDwIJGoCPdUucU0zxsTv856HYTUjIHCQgJgrVHqfoBdvJmoI8SOjly7WyrDAmLObwjzuQ95B9Iwlw64xVAEC4XaLmn9kSrTWBfPLFnWSiUcmrJYQAkXGp/kcWL0erlW3ZkTnEmZA8wAH4K3MjoLf40/wDPEzq1BgCzMV0gUsOACuTeXjmk6pU9ftr0kMVlgquI5+LRBzWgIP03qbez9BpmmWgcGY/VmZ7IE+lbq2AEC13VuMy0FjukOxaV7yhMw7a/RRGDDsCt83Ez3ItKkI6No0D4IybgcquT4Ew87E02oLwIBn9QZ9B8UAdbiugOVW1DV0F3JajR0AzjLjdxFxrcvF1Om8Cubos8xxkrYUUOFanQf3Q+lHk3winhIkFcCGRZ+xLxjD2rBvG+tbtrODnr+1Dh33lO9urp3SPa8lgFCB2QQ1BRAxtpUZ1w0lkfzF96JTux9gvWBN4Tr4+Wh3Vlrn0XpE63AZa69rg26vJGeRxn/t195iw+GazecLG43QHaVn53axPzBWJ+3ZIou/QxjD5Niyn3jxm4IuEwDqGkGIU/C7dwNUnnUDeQ95olrbeN4VLNHDwALiTXCiwKgJpjhHtTBznxTQKd/W5B61/KnCp+9pglNV8klTFdgF2NExc87x/NXOTNHlqca/8b3kqXSl6ro1LYNc36JosYd5tpfzuec71MXKtVsdX8TysVC/8jLNHtdx+hpKKzr8jRAiuISjm0gtt+V8pBWF5iFr+W7KJF+3rDNZ4kuzSxKvgQv4CAAGxR0BwKakO4+/SxbwTTfa+vp6BKxKJpNaWpS5KMMgM1RLEy1vdMGGhjYvrlt2jWAhZwp0ZY5VUAVAU8bCuLxyDQSylzkJfW+RZTMICHmvCjcCQ7oknfEgNgOe5TzUBZykMMsE15WMPq4F6xb6O0trOri44wdjZVyKMl8CamWkAWxqrTIFbgScpWSLu8mypEKnxgN603tYAedIuolC3ATonm4pVhQKiSbzpiDzsWfsH0u/BPCB62NSS79IU3TvhDED+K7xZ3gOhDrBEF3Xvt5YKR9vAEsUTObaMPNVXVBcdwU0Cm5XgA0sft1wkbvigtqNWQ8S4C+sVNH1hKBYLQbU+knPBayl9Q3gF8+YjPYd5GKtCABZA5BW8MPA6mEgzNdqxXIsmcCZ+R3dThAXqD1il1HUdq3n1oiD/XHZa8Z7cj56vpvryb+VrSidKDhsAlsF3RReTV7iMYtp/SBvoVLJGE+3/KUA9zORcZCslUhAoICQoACu31/+lbdZpxtZ+fEDyBUK13TKLPCIE+Z+Yx9/7EffEDygG16HFT6QCR6+P1kgWrs5HAaWud7K3xDywILiPrKcZ6MB0Uq4ShMw6d4QPJJ3cb0Lb5CEI56r5ndNSyKfz3PFdSBtKl+iMsYz2qQP1v/jHnMMobhXuaPrV3gr27VJmEqTV+nags+q1Zm/k/45T35elHw2IJB2gtybw3ikZv1SDgJAAuDFPEKJZHIdDBqehZzWPwWTvpYWITRoI+c8Juv/cb339nbsp9701qNC0EcAUI/++f9OAPiOd/6MgwTGKCg40EPPQ0uGRqaJz+nW42HCwUYsW8T6JzFnBXpWo28KIs8+RaeErE3nQbjZHByu2WBu0cKKByyEjQQZoln3DO5naekGS5m046oCqtZzYyZtJItAkwOyygMJyyCMbdIdwAEjS5pkwV7PHO2itHAr7k8XwzxjbaAd4tnK5OKaSE6hBo3PaH1VZluYOyw/mcCBbGOMjRoztEcIRFhE3ILCwOh0r9YEiKgDqIxUmRw1ZmeSWIdZxHnC2uTMCdZXr8MYApLgiPcBYwIAhubP4tKxn4hda64B/y5MP7OJWci4KewUIOH3FRdvI8ln4Yk8AS4BLuAy95ivZTRuZxFsvBsJMCG8os8rx8VOJ8UKNR9Zb7BuBwd7DoBxHTR0gGIAQAJZhJQ5gIbViThkXgubcx669oxJUgHhAsYtfmlVQOZ1uoXdGiixdA6gex3rD4a2t7cXa56xiLy/KBJiiaEQ43o6baR1i+uv1i6/Pl12zKJUUBHEVTPmqzCNMkluFUGpQoQsiAVcARN5kdIpvydtcO4EQaA7/P57f/AhO33qbpwmzzxvdRHrt2aTMc5a0C1b/6FHcacblahf/JLrY/8l1IA8w0MwkK25AG+LgH7nm+kCppKJ/wkwmmBawXaTdqmA4j3gyatKAAmongZ+r0oElXG1yCGExc/ANEJxeL126jnMzUrw15QyZQ+StlQm8Nm+VllgO+6vpZdW6DUVbt3rRzvvLF2j66zrWc6Mn+Xg75oh7OAQil56g9QqyneWEKUE5uQdXDfSooJtt/oxljtDBNhJKcqIZe1Oj5NveUi597Pv9MqesLEB41A5R75vjCzga994BACPAOD5gz69sxkDyIBmvaYpaIumKskGyoSKNo+MSXeHQZNGn8Rwwfq1YEbFNhYWN3ze7fccaFRGECaWWlU9BGlY7cKdu5J1nO5EWOCgbQUDzw4h6G1bYpEiI5ZMugQmw6LClmZux6suW1iNWASWgrK4YrOFna6DzyeZggpyZVZcDzIKMsxHW3O81zVojI2gKl1fcPfCiualB9BlIy1abmnpZtZrujpZQJrrzPFx7wjiAgAENUBwwPrnc0wQyEh3rCUBbAE0bPS+CAtMfF4TQFQ4HibENH6J6809b46bwoS0WawfGSqoQqjbH0Sx4ln0wXUrUj8spEgMwVgw/94g2o/xhwBqOp44yIdCgWLPnZZFB4PpzGPNAJCRKMM1JTDG3gDAudBotAdr7rcK1+ZJJ93yWcj65fnBtbD+YV5QmDa3jrkLGJ1BcNa5fhRcAUzDYlHATqtZd7Fm7nMspZOGZLsypgnXKI8AAPTWeEy8QsJSxhofxjdwP5UZ9kp2JSbjcSmMCXJ071kCiJnWpx74rP3+7/9bPzODHhSAKNMxmfZsOEAVg12bLXq2nKMncc9pArD/hT/6+hJ3S+W2Ko0ZvyXxgR7Ez5gFsaxzrARRvq84PhmZpvuhQFABB3lQSVTIdSQQ4lkgL+Ha83PSFtef96nC1QSoCiZJx8q3mudPlS8Fds17ItnOyzsUHl94T4OXcz58Hm7gGdS10n1RxYFhNUX+SD1A3s814Jrxc54n7gO7fHAf9X+eCV2nCoZptU85JIcZ8gklxdhdqKxh1OsvoUW8JazW4yMXcC7IkQu4KRnO42/NAu6h87oLwRAGesjIqJtARom+CH4GeqcWRE3fs32TefHQFqFQOm4gpiZ6y4JRjSfRlxhatgsYmMRpRcz3UGsloMDfFOywKKIor4IxlnFxwe99dvGu2tu1apYdm8zGNvAM2SxivAxhOZ0EAPX7YQlAsgNqF0rtPrVK6CEmc8D9AA6MO4trpGi0JLOQkdJ9glXC/Z1e1EBre3HTtpcAceaclj9PdIBQk9g/JqaQCfOZCnYc8GWmKT5HjCaLOCv4I/DjfhI8ufVPil7XjiNIBAngjn/q0qXQIdjTa1YEaKMgtmrl2Bv2wnUg4vFxNdAc64H5t7v9AlIACAD2ZtOopQiwTIA0QrwOYzRZRse1z7B8stg1soHnk6lngjIDmICK/5ezkvUQdU9IwzpWFSwY4z7czInGue4EtjyvvleIQerDzd2yDRQhHu05vWqIho8lAYx3C/EWgPFGCkPuTVFKsm2jKm5xQ217qEIb7/AwhEcBlMpn+E6CLQJS5w/McPdwgrDiosah4K0aS1ZiSoO+jm3N7Zc/eLNhHwH4ANLcuj8B8F3aaIJSMH3rD9reZ5UJKy/4wWtivVBmZ1bBK8u/uBXUC91nRcukSVWk/AwlLyJtc32alh3udRO8KaAJxavyGF6rMdU8c9zHw0BeUSCkyxL5iys+qQyQH/A9CrQUXOre0eq9em9k/zu/grZ0SOY3PCQcM/mm8iOuH8eg4PdvkkmkGefNUs2Ca4P3Kq+p4K3GJ3N/mjwKz2jOvzzXEzxqfVVPdswkEH+OJ5uFYszzG14rWDhCoaBMc7nc6dj+/u5RGZjcjCMAeB6Ar3mLxgCiLpwL5YwDbGqYKpiVUenh8IKYGQhMxuSWOFsWN5lbpOTgEJzpgaeAIwhN0RSCKhM9yESbTJNAFAHzdI2phhtt2SpAiRpw2XMxazGVOBUc4Ozs4c9I4MJDqwyd68NDS2bFZylYLsA3kzbqWodmHEwwMn/1x58Bt5//H65jlHahWzmYaFix4D7yJJtSKDuYDWveBTMLQVatP/G7u44WSxtPR26RDeET7msAHMZFUWAT+LU7ETPle5IlUlS4kLnOZgvrwNordd4oVJr7eZhg4HiVPri+pCPYmFee6S6wiJHsr607UFpbWy8JH75uCKcDsJOCz4zhabG1HKyd84mDS8/0nU09A3cyHRliAfH+CdoAtjs2nk2tl3UMYyxhBYQBkQBLBbLSSFPouNVXXOc8XwrUSI9QSgBytzaGYflrdd3VySK1eLYrLq20GKN/sXSJ8D1Ddn32LPWzBst8AiwHyAIcVeCrckeBSRpQRcHB63K1HSCv132FFZD3N2MAHWRK5xgNF8CZGvYH9q53vcEuvGRgvU4t9zQeT2w+gwK2sO3tDadrKA6wEMIG+KIXvsFBMzt/4H+uDzqrcDy+LlBO2Zovwzu4dwoIFcRgzPguFMDaAo48jTykgAuWo5LYNn6noIS8T9ebSXkl+Sa9L7rWTg+NKg/kQ2od5vjUOt/0wMQ1sSZx3lMp9fNTY7mVB5JutUsG76dypMlDaqHDWnEMBHMRX5qhNhmX7OdPmCmeTzmkskcBZZP3HKawsjoC5acojOlZAAAgAElEQVTKGoa+uEUbciSLP/t8M2ynhMxkogzeiQ4icANjbrDoU0YinOP6Nx61gvN9PsoCfgQ++IY/0BhAuIlcg1uEUOAB8b6lqHWUwdCHgRIFdQQDzpxbLRtD8HjWE8togCmEGxjuVlpbmodYhSG1wojLCW0Rn5E5KZAgOPKD6F0rIolEGbAyNb4/hBMziSNrrRQIzrZ2zOJtgrsieCX9vynYCUYUqARIJVviGFnBP6yBUfoCgC8AXMmOS0BDsAIAQwskBYwLiSzzQoZLgEhrI/6PDOWwHlFjHu3vhZXTY7QAEKLIM+OKeB1anqklCvOOIr61Rh73j2viMYA5bRd2aX1qav8q0FQ4amyT0gmLTTPmj/via98yt7bCVY77h8MNt/bBQgpLKsEpSrtYC270uVPOnAk2y8gA9tZPnrW+tOVi7lo5frwd3nQS8XZwDcMJ61bcWj6Gc4AFS4tgc905BhXqTQWAwprCjuCDtAEgijOMdfX4uuWiWLFojfN70xoBo7GvOzqUeN3KOJOwnOsP1o9nikK5qQA5rUlAP4U2zxh5Ct3FvFYFMWmAawHgW0A94urYSUUsN4VuEqASKALgf+CDb7DN9aF1uhGCQGWLStNkktnay64L216vby/4oesiugHWS4DURXRD8rXOwvPkV17U17tOZJzr6rIVXkULrIJFAl2le9JIUYTS6kelx2ugZj9ydhKhkulxw3mWGBbNM0e+GAOq8WiFblDGCFayjFkNIfvI9nTkvXruuD+gi+jsxAz4CPnp96P4uYJ1B5zZr9mLJkv5saZLWUEV38/9cNkEviVxyE5PmaFbzpJYaUnXfG6hy0apJp0r90N5j/IX0jjH5eDRom0owCH3gbyouc8uLxly5LUBffGzuUCA1b39fbvuuuuPYgCPAOA3jPUOvUEBIDobOHiL6rJFOwJhKsB7NGCjh5sJIdRyAQAZ481iwJ5tWeqa1e4GqoHhOSwNgc+960EjI5hAhKCVwokMZ7W/aiwDnkUtmzFawQRqFm0p5sm6UFlSQLXFpuYYYwxGx+/IXJiBVgSHW79iHPFD7ZiJKcFCHBxlqRaujQtWOCAXZr3BIIva1uyzFc02S8WQManQ9gDwTiQ7IMYPe4s4Ex9zJt0A1HC9YEUiKCPQIROlENMet2RyYXXNeE7MG903ktkRvAMUFSGnPTXTunJY7BKvx9xcwEKweYxZtTrgvU5Hw3XvguLljmDZbcdeDdaGvs4IA/DOKJD5sHZ5Ynmt3Yd3OF0T4MymNpuO3LLm3032fQ3xwxqIBIA8fApmCBBxv2Zpk4YoBEmvFEY8Z9xPrj8Fk/fWnS29rifCLtDTGCAGFi6UhlFLnwpCT2QBIE4LPi18vF4tTuQBHAsBCC2EK0JQ+iuX/U2w5EJPMi5V8JPWmeHLsapbjPcqTevZhoL1m795o00mY3fzAgAGnwgrXswD9IFNBwCcuHvgBf/DNbZcRIJHtxPhAr4usAQKf/RzIvFaCigUtDTBQeGVkPHgg/lTlbRaeohuVe6Hn7NubUlI4NDcE9KLWhNxzqO7UVj1+Z0qHgCAnK8CQN3/pmLGc0JeR+VPY391PE7TOWe/N4s5N2WL0ipprDlmL7cihd8xTqcdeYff24gBLACbJcW0C5CUZCIdMg5Qz53yf/Jc3Wsvf5beGspUyifeW2kXXpZwOy8swDEAINzjnBMA4BuPLIAhw48sgIVvnPcv6gL2bEgUOs5ECTLIpiCiBkuhq4QM4icQcEEoMTB+cBA0LqCvKdzorsDnrs0KkyJQ0Ht0bDxYq8IHMXqeNRLJE7BiNeqSVQDmR3Tlnc60shyHChsyBTLCpuVKGSrfp1aM+ntYHKPwMIB2jZNUwAQpw2e6kMgkDx9xWhGDSdSsX1wPcAEggFhIFU5ktBD6Mb6lx0Cxp69/uIisXwKowuSz7p8yfRUIbSmYHHOIWEcySPzPzEOuG4stOxjPLi/6fK63zoGFgUn8KBuD+700itSJjmxfWPmQ/BHt71Dnz+sBwnKTpXNI96Q5PAuP8XFAMQIdsJVWZvkCALownU+dthxEs9ep1/2r2bl4znSx/H/ZexNgzbOyzPPcLW9m1l4FVRSySCtoqD3idIMiajSySYTTGhrjNjOhRowL2k63e7NTVRTLoNGjztg63dPSaqvE9IgriKOIe8R040awiCgIiAJVlLVk5t3vxPO+7++c53/yq54gMWLKiC8jqu693/dfzvIuz3nX7hKGv2aQOYDJyPj0eaNInQah+bTUUoxWfZkVH7qTPb4pkVSxX+yZK/YOWmQ5Lwu9K0rWuis+cyf2WEArcZGlkZL2yHAEJLo7LcZXYBDed0szc06TZvIICpX1my2H8MO/+z9e0q6+Zqdn6bK/Icc2TtrRfoY2nD9/a7vnnnsiZvKf/bMXt4O9Usa1XmQLI9dcjiTgWNbAg94pID3TMGsJX/NcBxJdBlZbvC7oNxO8Csw5vcS+VLYvexQ/rQKCj9tpj3s78C4rMHTiwJt3Alix9LocAAzmOMaexbg5IFcxaF8Lp+/L6K0+ABABtpD9HXxVH+DQGSTO1cHc94EDSQeNdbhzWQ1PuCWVPfPPlAWspMfBL9m9yV3grAlua9cpzFVz2dmpsma2PgLJF9cAsLPAGgD2pbjyXzwLWHUAFd+CAHIGhlABf7gzcAvPCiqKfKoMjBW97CfUsJJVba1yK0nZnlHLslKwnPb8vS4YIiPXykYAZNSPNxFNnvBlgp/dC6k4hnUnFUfG21EiQOMIt0IlemjeWO5cQLJGroxRZK7guoVkaqk3Tn8DCCJcF4K64q0AvJEtTY9JKdwS+pHgYAkfnKBd6Ol7ubr0T5XlOwA+OgylotO7uzm6Ii5XnP5WXJauJSmBuEwH/wPAycqT1jMlp+hzxcdRmDv3I7NxXeljEXSagAZiX1RUterfIbBdMYRDRTSghIGI79tqu7vn4m8ddvQ9CktJINAn74jvyHTXz7CK5qFGcX8XLzyQbuDjKvp8nNZRWSEje3UamytbFI/zmAMZfmcvNSZoaBWQx7WL5Z09Vsy9AKArUj+cuKIb+5XZ7+FKrOxd3Y9rsFdcqk453apXFn1K51AwmaSu+Lyeq3fJxRx7q9qPRxna4PuYijCLO/Md1kBoFh6DZ9yCyOHjl3/5B6I8D2vtSnt7ezd4YXNzo919z1Hb2ztqt956rv03//S/b+fPPqJ3GQJYaCzzv55MYy3VOpCeyhHNoM8PjqvuAWCxbr53wdMGhvu86gAFzwMsJV/7wa/CGgDD6U1YdnYK+VNhGkswl7Pwz3gX3pQIk4jEjky0Q28krxdfllWVLh4LeVeH7j4+S+QiYKbLzlpUt7xFH/V6V8BPK5FE+I/Lc8YF/SED+Ny/d0CouXGg1Tyk80SDqfdUwkeH6FFtAD7WzzlsKvd2eBw0fuiZblE6pK9jAHPD1wDwMlH0sX8wl4GhSGo/EVUQuAQ0zIhQ8lMgp0Nvl6TvO5OJ4HEtVbu2zkiqz0VwuwRR1fDCciPh58oZqyKfwdx8vlDgk1s3BBHB/DoRRpG2kQGsmmY6aQXjKdawSq0g8BBmCAr9dKDnQHA+pepaV2YIPAcGuEwA2HpGBP/LjXmI+0rAJBNAQggW6B2n2OxrCrjxcSCANA4VcI72Ya36OFfcHta6UAgnioRLUBNrV/FB+jv/LWMrXSmk4bXcTFkMcriWpnif+XQdY6/s0jjFlxt4AOaMNZsFNzQVxi65tpWZvTOKPJ85e3XGAlYWMNY/3wvep3epLIjau7FHAX4FZI/UIURx3YfhWj3YuxQZwT7WzDkc5RwcYDmIY5+WdDAyT2fLCxmoJGtheXLlHhn0lzIhRYDX3cwONHxM/N6TOwwk+D2slR8qdK+szG5N5/ugYSWY1CFmlUUl4gtbWq9ZD2gVYAJ/c7/zndMF3wf432rtP/z0K9rZHVpcJq8nOEn3M/Ls8FhHAsU777TP+sfPbp/8D57Yg/ZnmQLdyUU8FP5IaoLnNAaXS86Tvt8cZgF4ITc3C7hXFnWsh9zVJxli4mulUiL63PkIbQCQZg5xn7VYZD/jXvEM8aAWejEDQAdKzMnXPec2xW4WQF4ctCrxqMvwsg5yDQdYLGaMI/aM8AwKphPWQzcSMsZpe1m95jVfwkkWB84p7IQ5Op3nmSj5GlrX94zP5X/K4Kq9WC73OHgWTcx8pPf5IQj5Kmspe33/Aw+0F75w3QpuDQA/dqy38o7ZAighrFpmIcAqTkfCaHtHBVtHrTAYMaxA1deX5ASYCsEQJzNpyyL8ne3hAgwms567EX+iIsqVQRr3ys1RcTIUMRXDzdbHVL7ptolCmz25Ivv3huK2XqQoa541Z7ZF4opVz+d5zN0FpwtBP9VzrQtHTsmuLFFyGRNIzbwqQ1DWPamnruh63FCC1QDeO7s9G3gogmUB5shCFbAtK18A0nInIbzCwlWgS+VNcLshuPK6VPZYnFxpD0WTSjesJtXLFSCNolsSJeVqmH+ehrPbxVKZ6G+UgwvSWPtuBVbB1+1w8YZF7PCwXXPdjW33zNl2Znen7V3SmpXl16wfAJY//dN3tCc84VMXMY/Qz8nhpZjX0f5BlH7ROinxYwEUlB1cQNeVL+P2tfPr2AeUDBZQ1o72Y5RGwvrXs5Vprdc22t13391ufNhN3drgwNPf40oO+tVn1OScDz6s+byfWh8sfXF/WW5mANkBlH2v4u8OGl3GsO633HJL+/CHP9zdnvCQK2vGFrzSjttb3vL69t73vC0OTBHqsN/afffvt6vOZ+yf4i+1FyoNc3isv7fa53z2c9o//PQn99JHgETtBbQYh8Tq1AD/9j2yBBXGpmuIU9ZnWHf8dz9ck8gjeUzrsEhqs/aJ8E/0LLca0cgJxgNN83kAzjrEBV9bTKSPAZ7vrmYrjE7CggNZB0BZWH/E/jpoTP0yOhh12RrntlEeZd7X2QoecqoWIXSM/7NSU0FLZaGDn5BBjB9QuAr4hR6yjiXQQBwSK8zGPwP0K9FMFmb3qMzv1X3RP/gouwdhVXSZt72VvHTx0qV1DGDt8doC+HcAAj0JRC5gWcMQoJ6sACMjlDl9IyzSjbLZBVWcvjHxW5cQZdNJmGDVcOXG9Q7EXAmgOLnOFX8XsnXiiur8VsQ5+qVaXboFiKtTHUzL3JzpXWi48kNZugJA2fEZf+POWqV4sfgBYrNtUp5U6f4gMKN/PTGmjT6THdhuZS9nhAfzBDBF947KjpYFkOexpnFfVetH2QUQqa4cGgutzVAmxO8h5AYoGEkdgNS0jNCVYxRlGAA5s7YDSMS7smwK6+/KZgYfsS9W+oVEGSn+KJItwHoyTtnnzl6d1o4qkt3pSTUdVT+yDg3sMdbtSPQ4Vc/f/bCiHu5fasflPsf9m5mqqQCdNvQ3dOAKMebrYKhcVq4sBDQpoOxWlP2DS6FAxIP+U/f+7UfvbtfdcOMCQDs4YM7QfNBL0ZV+J3GJdcIaz/u7i8o6PoRKLouxAPYMEPp3FGUPa3bVaySTdkUf4Qfb+8ueP7kZDw8uto3Nk3bTTTeFtfboUOEpu23/8KRt76jiwW47Pkj5hYxxetMazbTNekW5HZLESh7P4wQI9+sqBnqun+h7wWGa2qfIU6+Byv1xCN8UbWesJTy/BGPJa3pu0FQVo+aghxx38ANI5LP420JYWBef3+VAaYwJHcLa6oDth3jAD+sH3wlgKYuWg7PL/VUHmq53rAMJ43JejHWzQv0+Dz/cQpuui/gMXnIrfYazCMipfmz+Yw39J++Ghxi3J5voObiS9ZxwAT//hess4LULuNPWx/WLA8CoYySVWycnMYgzySpBi/UhiLfcxBB8F+qWfg8jZm29ZRsylIqepf+w2CGcAogUUyNEIrhf2Z+FJcg2HYkfWAJlDRiB5gtwJtdsxfs5YHKryCzU+zwsvgSB6KfUDszKHT6Xn0HowPQIegpPE0Ac2aMFCLvlIE78CbqZTxfS5brm+QJ+/FNWL8J1Bvkq6dIFqBXNkiByAbkKkDFXwKd10YpXs48pNLPosq6FTnqbs1KQpyq2G8V/EwT7nuk+TuyMK95RiR2hJKKPbCo8JcpIIO/sbrcPf/iudssjbl3UWYTeNJb3vfc97bGP+wdxskdpA9AU+xdJLQeXYg57F+/rLfKyOvRR2xTooXZiCf8Z4GlMKDT2DPABHzh/wIcLIKKkg1OFBiR4EbhRKaewLFYP3Q9+4P3tEz7h0Zmogvvewi04DDigHGB8FHgOXpCbtrpxzEJnFc3npo9OOrQ4Y77YbpA5KHboqF9X1miUrfPUrJT9b2hObmAB576u1T8ZkJ78k4lQMw2vAunIt5AB26NLygyseX8HTVVSpc+Dsjq1mBw43DKoDOToN0wXFbwais3cTut+8IK6wejKalPn9RvjGpUF2k6ai/mKPq3wN7Le6T2ly7ILDGPTdw6mWHeXgbnelkXP2MsyTJs2B3TO44DseR2RXX44gh4d0EZmsdWI5BrmiAUemesWeWhP3806Z5WO0MFrGDOqaUA0GMjyN1kaZzRXYJ183Zin0zCyEjoUj69dwLmTawvgxwX98mZ3AQsAIqzO7JwNhQIjuFBysCGzeyRZKGkp6mPp8D+qm8vsru857UTz7DDHp+CaQSBTcvAFw3MtipJrsE70RBC5SiuGj0KckYVW/XZd0fA+Pdtdiv47a+JgZX4GY/PTIgrHBdblzD1AsJ7ZwVAopBQ+PFuJBYpd81O2FGz2Rk6BrHUmztABRdTlql6+CE7ep+sCjMgyJ8uACSp9B/hjrdxq6wrS12Ts67AC8r3vZ+5hgkG/H1DnFg0KAlPqhZhCOkWEALWYzVi/6pQi97hO0h+5+8PtkY98VPurv3p/+8THPr635HJAzx553csAcAXqNF4BQN2zf+n+yPwN66C6yVgLuA6+q+AsawIYjPdUluDpxknvMw1/cV23BhW/LHjj9Ki6tKRVVd9pf+iIctddd7XHfOJjw3IgZd6tUJPsAPRB664kASyucP0wwD3zgYlkELfEx9zMhdmVadUt7DLBEhmU7OOyYhX/8hnTEk0o0cjBIoregcUY81bvBgR9ditfuX2Dx05l/R0Fsnk+QEP8GmC4ygH52ixkW4Evrg2+V6ytZUILtMXf1GmcrKLuEengVr3K63rW1mWZ9kJlgbAEzocNl3F+MOnAsOJ4XQe4d8TBUSaG4dYfpbGcTiKmrk6KvC/4uCoFAL6cXF026HsKnLtc4vrQA5OhwWkFGatnLK14GQupdZIejP7hk3WVtYMvHGxyUEu+SiCq59OmUd8DDpm3zx+XcMqlEc4kPl6XgcndXQPASYhfyZ9eBkZEh0AL5aNSaBb34BYchAqJEnG6VIV8FRWutj9cD0OHEK8izuM0P1qCJSMR2J8xexk6mNISxabnYLnqoFDgaCvbocXYo+F39HVPpVgxHAlo0mqImX+2NLgyRFi4e0IgVtd4nUAEvf/Uc8PyUnGHDg7dOoowQMnlOlTvXuZO71B1nyh3G2sYLqzKih7gIcvt8G7dg4BEwUWZl8hWHTUYwwpXrcpYW99HP/XP80NA8s4EmDvdkoaVyJVy0my2ikL5ueJy0IiwDuG6tRnxd/pse/dMjDmSVUzYJgDZbg88cF+7/sabIwNY66R/73zn29sTP/NJPfYJ4ITC0TxxbTPnoMeWXT6U9KHkEBXLTno7bip/w3670tH9DsaZZ4DGyEZX4GtaafwfANBdRG4h4R0Ce39770fb+bPnFq5y8fO73vXO9phPfFwCv7LeobBcgc2gx5U0+8w4Ov2U8nbQwNyChzZHVxhXnrzXw018jnqe9pK99+4n0AaHFB8nzw16jW4rAxDrWSjc2fX2YOAXfvQDCwCQLiou2/g9rq9i1a7cu8ysNmA6sDKfuK7qUvb13sxi/CT9ePzgPO/uymx54ArwspPzR3YGP1Y8NRmo0D3XzbJP94Ss3Rgtz2J/qqQK9DqDo5xrgp+UnfmTNWJvo9jxivZstA/te2peKQdKbgwAGPo78Po4vWgdKemDTJrBmI+JObqeQH4jg12eh0QrUKvPkeV8PvOCA8++LovSNUMqCIyuAWCuxxoALtTFlf0xZwEjLDixRDX8Al/BABTtzBTIzuAhtCzZowf4Wv9UPx2i6sbpb3kSBLi59YnSAs70LohCMMlNqtO0nfpiLLU8Ljj1u9focgZ1JdeFQT1Dz3KQ4kJgdiN0ZWfFRlHAfjIPQCnXnQBN9SfOk9/onSm0EIryZABzhHEKmtGFgT3jXUpQQIB1AV6LksAwAVgUxK12e349ynCmMlckDlji/Yoli/pjOS+EWyq4zBIEsMdn1epMgFBCM/c2QbyDZ9absQBAlCzipV94NgBQLuAooBtFn3XASEWpJAC6XACqOCQQhsDYBfiEpORGV+ePo4P9tJjKflNJH75WDoodZOma3bM77WAv3bf9ngIBYfWTe7dCE3zdUVrU9dPB65M/9dPan739T+IyALvi7/78z97VHvWYx4YFI+itigAHILQEldjzKvuyCgywLvCIW6b9gNDBYIQs1J5vWmmLotGwblVdwqDRAi7InZne4POZxv2QgtWFGFgAAQkUDp4d1PoeMX72m3vcukTWta+Jg5LYAytyPn8HTzI+QPNIZ4hm3su9rIQTXLkun1weOqjmoKXxOoidD3SEkLDmTheMlX0PWrVsftZJP6FLPuP9DnxTbo4SXCpy7LTEu9kH1n3mfz7PZP9RdF8Wv9BRVoGC9Y9SKkXzfuBwV7AfinwsbrFz6ym8y14CxFN+ZJUGfefhJKvWd15n9AtldELGyONwcNCe97wXrGMA1wDwygDffBcA8I47X9bUCQSTehf0dQoVIYfgiGr4JdijBEi6dAEcKoYZf5W7ypkumHpbRXqHSZvejwgFCD8tfNmj14EDJzm5mfPeKtVCz1IFkesE7Cn11VInTsXVHxLrnQsnhAJK362frhBcCcUzK86jA0XLHHaBgoB1AeynyqVSzvZ1uEZ5vyx2YaWyjEmUPgqpC8eKrxP4Qzli9Yx7KhYsgVtmSM//ULwoQge0zJf7WJd8RnUwiQSSpbs/FQV9Wel6kgBQgDFpYViGfe0BuoDDVDJZPkRrs10dPvhMYwrLSVyTBaHlRs+9TRd7B+RWPdqBF8BW1r/9g70ojaOCrBunxwEEZf2L8VRtxL5XVsEfulZGZzR6j167I0C+18s0K5BAkVueXdnGPpTVMLJEz1zdTg5VlzBdXqHwt7fa2976J+3TPuMfxnMU4jG7Jhe0U9n4q/Z1VlrMB7rgb+gl4tOKz3FJLoCBYo01/l7KYwAe32+AGnvkQAZadQCHQp4tM66o4T+AF/wC/2FBW1h15KIvzwMueeZOYfsOGKqSga4X8KZ2oK9h0GuBn74HqloaHSsOMzZ2M+uiYpWOWMANFbY/7Nn+IaePy7qp+8ptzB7GnDaX7RtdTs2Ah7W47HBgBZKxbvr6oy86mLUAYJcrud/Zj1xji5JTvbBkGgHcIrY4HFVrUXgiQNdUCsrBdoQbyfpeCVWMw613Gjf7MFvxoD3G4LLeLYcO5HPdkr99f9lD6Bc9hl4FIDIGdI/0n9O0rlu3gkvKe8haAF/xile0n/3Zn23vfOc7owvD537u57ZXvepV7VM+5VO6flUswHd913e1n/7pn474nKc//enth3/4h9ujHvWofs373ve+9q3f+q3tTW96Uzzna77ma9r3fd/3LRq6/+Zv/mb7ju/4jva2t72tPfKRj2zf8z3f0775m7/5MkX+YB8AAF/+yldkO6pTxc+lUPETHcIHYY41IerWmXUrCvWr9tqWegBnwPGCQWQNKMWWQAZwkIJuAIxM2ugughLAIUAK5Km0C03aUarzqTqCoU/TFal7lezhzDgLOu4HrJGc4UrDLTke3Ms9fpL2k52DsBkYuoJjTKnYhuWM58Y6EdBfYHMGf64U5/FEmzPLTMtrR1KOCykEmStQaIn56BoHlvpe1rZ9xRpVbcHL57d0KSEQc+4JfNkLAAH1EDV+LJb0NY7xVaxYrI+oJPqapqtf/4VlSC6wejZ0QKJItEpTz04reB0KQhmi2zvh/j06PIgC1sr81T9ZBLPt2wAIrgSh6QAV1TMWKw20GfM0l6eDohlosa/sX6xbO26K2d3fu9itvACHd7z9T9qnfvp/1UsrKVmA55MU0q1VVY8TQOJWN7eesR/sD7zhPOLJH4ADfe/rEeuvcINyB1B2yoHi4pnlWhvKMWWHW7BYH+htyUvLupGs7TwfzwyFLjtv10GTNezvqwQP+NAPc/oMC1IHiVaOKsDeToa8uGyiDIzG56CIuTEmWjYDqDjUwKd9v+tQLN3jBx/mOL/H98FBnNNLrKGsndU1JmhHVvYqSxOypDd9G1pIPJR90CtExhQU4wXMAcSgefgrrqskjxirFX5GbnliDTJsln3Qu+7pBgG6v6j3N1UVppZxjM/5hL2hvJBnObuuQcZyPfShsQyv1rBY8q6LFy6sC0EXrTxkAeAXfdEXta/6qq9qT3rSk4KpX/CCF7S3vvWt7e1vf3tk6enfc5/73PaLv/iL7TWveU2UJ/jO7/zO9tGPfrS95S1v6cDriU98Ynv4wx/evv/7vz/qeX3t135t+7Iv+7L2Qz/0Q/GM97znPe0zPuMz2jd8wze0b/qmb2q/+7u/277lW74lQOWXf/mXG0s9+K+rysCo3ASZeSGQ1By+WjX17LIAYbIajXZJVXu3Z9RtVYsyKVaAoFSdlLta5ujZYq5kklEGA+agO8fsCgzBJwBThT31tyx7cXq14p8uMHA5dyYsK6bHebl1a5WwQCACWruALKaNpuSHeXrnPS64ES6ccgFQfmr1e1NxZmJNKlurDF9xcKEAq00cgiPiW6pXqFvw3HoSbdQs/iYLOo8SErQwyzkm4IwsySrSPZ9kXcl0kJgaOYAAACAASURBVLKlbNgsO+OKOH/PIGsXfA5CKaC6sDhuZc0tYrsWiiCyVBM0xvM30yq4EbXfRsFfJYXQVzkFf5bWcaWqDFrilWKNRPzqWiHwd6TSL1lHUV1UBGD0OevlhwC4LkCMwF+VOOnKtBI/HNR14a9ONmpGbO0Usfrx3ACVSgSOvqFnIv6W+2WhPHfV+fbbv/nm9pSnfl64fj2LF2XntBegzeJGXTE6SNDnhGPMVrPgxQDag74631isV+dDZXxTfNhqjwLOWJuV9GVZ/ViuHLT4oYXnODDDouM0tgroRtzfin9xv+hCluPqmOIHuxmoMjbKANF32UEudBhjLxc6ViIHYTwrxrsxuiJxzQwYoUunSWiAzxw0sw4OxoLeChh5dnC8s1oCxn1kfispvmKTuzUtsoqzw5KDHTxBXf7hqqWEWNUNZK36mOvz8EpZQWjeB9DluUO3LOWPvmdusQ7QaoU9xRxLjnjYy7x2+R56u6dFE/mT8nx4jKAP+OxyEkt+5oCjOd1//4X24hevC0EH/f996QX8kY98pN18881N1rov+IIvCP+9gN1P/MRPtK/8yq+Mff/gBz/YHv3oR7fXv/717dnPfnZ7wxve0L74i7+4vf/97w/Lnv79zM/8TPu6r/u6KIR67bXXtu/93u9tv/ALv9De8Y53dNqR9e+P//iP2+///u+vFFrzh7MFUETm8QpyOSA8YBCeESdXWVuqfZvcqqrtFAxS1r1gchMcxGe4wPZCnjCi+E6WxMzmHUzUFaxlTQbT1aB6dfj6mzHqvc6MvHMJgobSQhj6PQhFnrVdc0Xp9e8tDovxYkkE8OinrkeRzsIABZguYILFtRfZWsjH56dcxusAzYUmzwV8prUt5z0rCRfQlKVxBedKuQtu63zhJ15oRrSRGXUjmQVgrLp6Y6wZ14MS99+pD+jAQtbBcP9SeLbMIlobgSPyK2TJi+LQZjlNBZtAkHnEoaRamx2fpnv89OS4nR5kCR3V3ou92MtewBxgAEoOeOO5isOyQxTKgPHOc417iKGbrLzsE1aOGHPF2Ukx68Alj4FA2Jt+7f9uX/iMZ4ZFZv/wIBKlLlOi1gGB8bMOvk7s4Xw/tBu0Udm7Pi94kGcCUp1m4EO3AmINczrLg1BWHQAgzzzsdNHHUe5T+GLVNe4K7s+sLjkOdAEvGkvEVKqIssCOtbHs87GONw5IeT8gTOMiCY/saV1DNxDkImACWRzvqbaXDpZ9/WfeW7Xu/hm02dfaWku6jMNzy7x8X3s/4uo4wrpD5xG6Q9xgVCAYCVAB3ib3eLfMRZx3yizokL2BzlwG4sViz1yH9f0oHeWHftZM91PJQp/J0CAvEu9nzSXPSGAcvExTgjJOTHOcZTR7MGReVmcgflefy1u4LgOTu/P3BgC++93vbo9//OPDCiiLnVy6cvnK4nfDDTdAa+0zP/Mz25d+6Ze22267LVD+z//8zweY458ald94441x/9Oe9rQAk5/1WZ/VfuAHfqBf87rXva59xVd8RcQo9erx/Vv1ft3vfWD1sQCggOedd94ZSoOuHHHaK4sQAr5bKjhxqhxCVVhPJZQxHWHfqS4RVF8PpSUhXMHeJACEEqtMWV3rQChPtxvBgPoZfxcoWIIi62NZwsoVcCi1ApF9LlYfyhUI97kAd2Ebn9NKro9lxK6sCtq35e8g1IOFEWRYBlx4Z0xXxophDcyxLYuydldKnT5duCA8PXMaYUN9vY1qL+VKegg376oyZsMaBVix+EHmw2eu+BjLrFz4e6nMc464u5lTKF4r8h1jVjHnotdQknLZmstRdQD5HAsgsVzDWpBhAvwXNSbVeusoe/yeqNvH/l4oXK1lWAQPVUw7T+rMAQWEW3wBCktZpwBLC8kMRvhbdTX9u75n1rVE44j3bZ72TM1UxNvR5vCNb3h9+ydf+PSwVDmQ8hqKvn/MwRWsgw5XuvPBwsu7+D3wD1nIKGrmzhxnwOtKH77syrFqIPqcnG+YEyCS7ikoZ6jYaZx7AAuAKwc9zssC0/ru4bfc3P7mg3/dZVckdUu+HGVYCwe0AbJobShLasamQiMxP0sGpz1e8O62ZGEeXqC3WOcq++Jz6muKrCrLE0DSedRl7szHrEnPIDeAz2fwJc+Mvymubt1GHOwqRIg9lQEhD2GXJz1Bjz2xx5oKzIcsp10OLk7HrD/W0Vjrig8UqNutRKlYu7Isdq9NyQVZKnsYQ8n/bB+axZ85TLosYG5Okw5SfaxLGi7ZYF4AdQJZA8Ck9L8XAFBE9yVf8iVN4O23f/u3Y+A/9VM/1b7+679+AcT0+bOe9az2uMc9rv3oj/5o+8Zv/Mb23ve+t/3qr/6qy5yI05Pb+Ku/+qvbE57whLAIPv/5z+/X/N7v/V576lOfGhbFW2+9dXGv/njpS18aAHP+d/vtt3f3dBCv8horDlDCB3AiIRTxdpVZm0DxqKnRuFv1qIauCBEYLRlAijJPS/SKFbP15xdwhBFciS5Ag7XmCcFDjbTqxyqG7IA1X9zjReJzgo0tgYWWPl3olckfoYnAceHqJ1sYGeZ2MKV7QohV6yKumRURysfdxUNx5DNGP2ESJTLJw+OH/DTrCgPwmC5LvT2tiQ54Z6Xqc+wuyhq4zwPgtFj3WPrR3m4el4M6rKK5/um2zXFl2IC/K9c63S36vSeA9AbqG2GNYk0SAGYsYACVKhfEOxQjKqCnuKQcU06QhCDF+UW7twB++zGuSxceiDZ6WkssqvN69L830tqrA1hXRBEfOeJ8AmhU27teuFgB/EeXZ9HCCzEeuYnOZDydFO/RwWH7pE/6pPa+D7y//crr39D+yRc+rZ09s9sD0/UeSooAbobVYZTj4TsUHvTtQNQtfkFNFsS/UOpVgzDWtHoGE8zPGgyLjCUGWbkRAIa7VuEff6/LCXjVfzJ++BlQeBl/V/Ys8wLUdjl3kvGHtOBzvnFg6b/nHEeLtJCB1Qkl5lKt3mJNWoJH3k8cdoTkmPxzvu8u6VqYmbeRq5qD/iOGuYOxokfWxGVZyKbI6j9ZZM13IFbdRZBhXY5afCTPpUZglkHKkB7pFGhMgCwz4asdZF0zyx9oxg+Z815z4JjBLfJq1b2zzPUDHmP0tUX+AmLZk1GHNg8F3OuHcecrxooMcoOCrlsXgh7I5e8FAFQSxy//8i+33/md3+kJHg8GAJ/5zGeG4P6RH/mRAIB/+Zd/2d74xjcusJoY9sd//McjxlAAUEDyec97Xr9GcYCf93mf1/76r/+6PeIRj7gM6D2YBfCOO+5It1HF8ETDcUoZtMxIg2hDMej0UxmUKazS1Zsp+VXY14DFSNWXclV1dMWGZawEZVWCEVDg5krkdAxwmwUMz9DnlHWB2ftpfuoZ2Rm8xuiCBaEHE8OEDpK6ULfm4ChWwADAyy0KFMJGgCMkF260qX+sCxyUMsBJzx7u3FGeBqXB8xGK3I+SdOWHQgaIIRh1DxYjV/4O5mZh2oV/xfvhavZxoNAdfPAckkDyOaNQ9FKhmyW0QB0xPwEMt4bABQDGXmxuRCYw65bvz+QTaNI7nwTIKgCoewQUTw4Eug+bcpf1GbThtAKNxJqVqx2Ah7LnPvah71vnjcz8nIEljB39iNXjenOjndmuYtpy9+7vt91zZ9sb3/Ar7Quf8fS2u3MmCgAH8FOtpEACVWi4atZ5Uohb39gn1n6x78vShfFYnzdKT+/sn1cHDNxz3NPfacWMoe9uua+4SAdbrqw7GHHZQ3zw1Ncbvpp5owNM5aVbPO9lAKLKoTCvGSxhuWevoC1Zv1KWZgcfrFuSuWFVnBOCWsazRvmZ8rrEPMsT47RDizcHs11ulfdF9QGRHz4nxungDz7uMqxqhuL2Dn6llV91F9EYZhmNfOVgxfuJ25MRALDn+9GBPda2sti5HNP1WkOKLAPUZ56R7I39tJ7BAbjKgAAApQbhqoPEfFgJEC2eqtqzeGZm2em6A5DnypnPPBEIr06Gp2Rr0IODdR3Azk8P9RjAb/u2b2s/93M/137rt34rLHv8+//TBTwjwkUSyNkEgAFcFLwrxVOFgf203J9hySFhmVLyQblxk1F09FOMIGAPd5dO+DKXb4flDoYNJioGd6Xgp1M+DxtluUIZcyiLFW2jXED6/B14oHjdNcZ9MK9fD+jlnfNJ1IWPW/NQpgh9t5oyDz9ZAojmU6cLbn0HeOPz2YLoStznwdpGOQZrwo7i9fHNa+fA3JWfr5vTDXvrbm1/Js/Qz7w2Yx6TPqyVl9EMCsITQHKtEgCG9aoKUntx7c0oGl44aGoiD3AHIAr8STGrnmDUNTxVV5XDAIXq/MEeuQJlrqxRL3VRFj7u4ZDV27RZzJg/Lw8/qfQTu203JWsd7h9Eh5toA3f1uT4nPV+g7xd+6RfbM57xjLQ8RDa8MqPT0oQSx8IXz7V+r678+4GnH06yzhntx1btudavu+5CFCwtnvByDFolYzQ3SuRYPCbAx4FnxDwWoGGcPM/LMi3eMYFT5yl/dvCOylV5LdEKQQl6q4Qayr84Dec6pQt+tq47vVElhQNJf5aVAdL1OniTQNTBbdVP9LnB7w6+9b3HB5PY5FnOl9HYVAoq5ZwKOaWbdnG9Wfa6fKlDBclE8/rn/RXTXQX6g7+thmnwndUNZR+GHCf8JWWDy8uZTv2Q6d85QJ7phzE7+OdensfhhbWEh/BY5d/jQK5nQZccMOCPWUb2fa4gSz+cpgVw3Qs49uihCgC12QJ/isd785vfHPF//o8kkJ/8yZ+MeD39k8VOJWDmJJAPfOAD3ZX72te+NjKBPQlEmcTKLuafsov/6I/+6GNOAnnZy+/sbqJQ/gKAsgwo1qyAngJgMxYlE0MkmChVADGHgKz4ujilqbDx1kbbO9iPUhVdmG2mi7kDoqlxt2Idzp8/391Wug7XZwhrOwkiMFbFskiwDJfpyOTiRMopzwWVMz7rikJnnrFGsrzUiXIGAYsNX5H96Nc7wGU9HLTi9tX8NBfPwER4uQLmdIyQ8jkyT4CdA8wQzVa/a9W4AEcuxLCUOlhEYA7QlwoV0E7ANOP3vfMxDEuFQOAySSctyVJMAjX5fLcA4j5r0TM1C2ynws1i0EJEAZ4PM9Oug7JSdKr5Jxq8dOFiWP3k6lP2ryx/crMKAEo1sm6uqPiM/aTmHRYcAvcHQEye4nPWhWxLgafLXMFKUDg47Hu2e0YHqurZq3kdHIYbWF4FvQeXX1gpwyY53GtxVnuQhAWPSQMAkTWOFdEtSn6Q0TzmVnD+vOTltPzL6EmizOJ5UVJ8Weg8qhGYNTDeozBQS5xxxQ7A0z7EnlSBewCErGJRr48CzEoyMSviYm/LTRvu2h5yYK7KAoAccgE8yIQcyzCdRswgMa1ltfaDcAenNTbRCPwOrwC0Vx0YWQcOVh2UW2szXYMlG352WQF/cjCMMcmSXBm/rAUWbmJOnQ9yzPmeAEiynJPJTccSaxvqcjgs2irYvog1HolbKZcHQO38UzF77pVxsM96AeSYs/Z+bhIQNGax48hVSowhpz32ngOqGwSgmfkADcDONdaBfLtCozJsRO9RbP8aACYnPWQBoEqxyM2rJA6v/XfddddlokWVgfmlX/qliOdTYodqAqrUy1wG5pZbbmmvfvWrI2FE8X5KEpnLwKgEjErBKPNXWcBXUgbmzle8PBgMQRQB8JGBKxB4HD+7tcV7m1Z6fGxISTgxda/wbgyOQCTpQ0AxAEXFJDlw6cHtU3cLrgmGsGbfFHbW8zQPMplnxpuVPM9zobAU1AkqNB4YHkvZ0oWY4GZ2ayE0hgtk6aZGyLlgQ3h5EVkHen7aRIjMoNXnzXeMFyEXIN4SCvwZ+tzdvljgcI2yFrPFYR7HPD9oCLCBy7RbEEoRedwZ402lmEDJ9yDurbp/em4K8yyfE+PezFiqfuqvsjkS8OfO7bbDgxETxz6gpA4P9sOSHa7fg7124cL9Ee+6t3+p7W7vNGUusxbcy550haEyIgUaZLkLZXuS5XF8X6HBmWbnNQ6QomSS0xaWP54Til2VXKyN3W/8+pvas77o2fme47SsorQ7UKuSQJSJcetIACSBz0pyQdGjrHif848fYvQOWSL1sx8q3ctgPDzPU89RlxP97ABu6l4CwAC0rKK/7j4uKx7WQ6fhmGdZ1mY+Rh4gO2QN5nf2aoCBBKq+h35wGSAiAWbMscJtOggBVBXgiEP3Zma4x95UIhGADsARMoZC0Zs7PTN8BhqsFfzNWOPvo0qCqnqH8/xYCwG8GE/RBmVwFGYgC6l3bUor5EHn2S5/qoxXn1cdQB1kuSyGV5xntA+sm9MIsg3a4Z5Y74ppd/7jew6QTkf6jFJmLqc4PLhOSbmRpaeQU8zB6YJxwEf6zg/VsiKPQ/GoBCG9tk4CyRV9yAJAF6Bsvn7+2I/9WIA4/RNBffd3f3cARS8ErYxc/qkQtMDkXAg6CjbXP5WW+fZv//ZeCFqlYa6kEPRtd9zerrnmmhD0YvoQKlUTTIScLsbsoCCw1a+p2AddIxdwWF1EzFY6gJNlJH4ouL8quAMAvU0bjEhRTwo3A14cYOk5xExoTCHYKE1TPynEyed0JkFZw6hdgBcoBfAFE05ZrrMgAqwAGgB7Dry6wrSgZldebvFAICJ8ERYIBB97Xy+zdM6AxIUf6+EFrllbB2vzO9wigeLhPYxXf3ucaMTlVNFp5Q65IPTnz+5rBOcMhHIeqTQdLMTvGyPhI8q3tM0AalHT76QtSimEolACxtFxOz7Yb2evuUZpf2kVqxACgLH67gn0SvCq+HMkzxwdR/cP9R0kTof7UBDsWVfYFSBPpwbqabLmWL50fdBPkPLyUOHrHWvUssVU/NtM4AtN6aee86Zf+/WQOR/60Ic6KKHtXafTimUTEHHLDXJsAZS2qiNQHRwCLFUyi1sDna96o4fNjZ4ZG/tf7k6UroMNjR9a8nnHVLEalvvvMoAcWZxlbS6XchxiCyywRihwnod7nXdAr8gCXR/JatWDOkFGysVVoN1lP4fIfHYeTDq/bbTo0KIi5BGKsT0K4rMHlOMCNFJU3MFqX5eae4DuqiPngMZ5z/cp6M26t6zUYwod8D7AVTuS57AOna5lJTfvDuMNOa4MdqtF6h4L1qvH561w9UIXyFYOregrPQNQ6LzUZX3FhqY8yWoLyDJ+AiC71bLCU+JCDCEG1HX9mTNngx6QISR/6bvZ0sheaKxp5UzwSAy0Yv78ACSs8KIXvWTdCu6hDACd8R/qv3sMoCxOxJyI6HQaVKFmb6UDg2PJkSt2JH+UG6SsgRHfx6m1n14TJKDEAZIuOAAb/plbFWBOFaLuykllLwpgAigcHOV8st6UCwVcuvyM55WAIxgY4dHfa0KLZ7HPM1DS97htsaK4YGUdAcm4Z2ZBiqBgTghIBCpKizgfBDLXo1A3d7bbyWGuv89rdsH6KZxxO7hBIPIMxufWBsAMgI41AjAPJZEHDrIpHUz5GLtLt8BN7kdaXMKtW6fotDRtte0z6dZNy1hdV2Behyit1dFJtusKJVJlZHhnhA7sbLWDvUthBTzY22v7ly6GQru0lz/bcdJggoGMbfKfrD+ALhVHWvC8bRegpNNPxfrFutb1tODSISqsWFXbj3sExASqBFBJ+PiNX/+19tTP/4IAi3JnB9ivOK0Y69FoNUUhaD+sOH9Q283n63zsgJHfHWx4gLuDNuhh5iUHLS5HnbZJkHHwAE84KNN6+SGLOXZatL7F3fpcsW+8O94r0B9d/MpDwoHTAXEBiw7wVpSLQpbMfLSIKVMAjh12nPd5tsbkmaIuo1gnDiP66YfIVbILXvV7WTdoAWDpMsSvJ1OYsbsL3J81wJYAGOEh2du371XpDUAnci/5bGQNU1fQ6U6/u3XQgR8yhoOw0w970sG3xT66btL48SxoTQTgJI88wx6ZhRzS/azjrDOQs9T9SzrO/UW+r7OAhyR4yFoAH+qgz8cHAJQLWCdQuVyoPB5KqqwDDkB6DToDehnEywkqrWYwbQip6PaR4CuUnbnxnDER3roXRrwMxCAUqw8wQvDMjt47GoO7BUHPEJjlVBaMKJciLiVzNXdjFY3rrZUTY0FwdGA1Vbbvil/uK8s+Ix7RwaCDJhdECCCssi7MeI5nPc/g0QUM8SnKFpXlqiu5Gptnr7JHrqR8X/KEXVbiKrvjytrH7fNx4enKg5P7Kgsq1gOslH4azndWJrnAD6V29PlWunxRQls7yrjMJAjN9eEPvykyeN/9p29t11x/c9u96oasx2EKJ2kk6/3JySz3b9Q+k8P55LipTJ9+OgjmdxQia5HF0gEheahaKNuKacNS1bM5wz0bPT4iESXopjqV6G/F1kLTsnhqCtCGePsP3/Kf29Oe/oyIB1QXIikpAKAAd9xDhqVa4BW/O+jRHALMV7s71qgDsdN0EQvk+sFhloO+JsiTuL7i8cICp1aUlfHqIEcWstjPiOdMn0GMu+ri8Tdj5W+nraCFigHsVqyyEEKb0Az7MIMcgZsoY1NtB/1Q5Ie/B9MBZKZHEk55LbDIBo/VczuQqYxpX3Pe6eCccQLyABoAhxkY+ViRv50OrEA984gDtA4Plkij32c5grWXZyU/ZLKGyyP4Op+b1+izOCy7JdvkMnMcdJS0kOBKoDHfgMt9BrFYE3V9lL+p9cejNVvn+JtDOgcKdIZ7rnJ+o44h4BPX8arDjM/H+c3f12VxtcwLALi2ACYdPlSTQB6M+R+KnwMA77jzZVkGRiUYqhsI7dsgXhcCCAL9RDCEApYp+yDjPSLovlxaAXIKhMmti9BBiCAgdI+InKr4DjwXJ/qw1B1WAU6AnI6ECQj0fsARChKBELWnqpAy83CrJC6f6AG5sDYtrYerxqbPOAH6urhiQjkhvPib06QDQr8GZTaf+LlmYa2xjM55/q4s+d1/zsoCsOrzZf/8J0CcuXJ9gAesqlbF312/DjBP5I5Vd4VSGrMA5vMO/mR9m2IAo+vFzm53i0LL7O2LX/g/tV0ZDnfOtK3to/YvX/qjbbNoh/n20i/76vZxGIo/s25TmSkD2Pc4PrMkGv5GiMtiDW1SZF0JUpzww6kbMbEZR+XxddA+vBhrWyBCcw2FJnf7ZsYS6TkCeH/wn/9T+0dPenIkeGEJ4rndNVfJDCQjOG+yl5QmcVDWLZNlTRaQiziyim/k2uqk14Gbgyrv4Y1bnLmuAlQAi7AyVXkq9svBiVvOgm92lhmsvPe+e+9u115/w2UxW1jKPF5M7+4g6LTmagdVxst+O98wnl78ulrHhUythLsOAqoDTdCKAV5/LuOLd1SZGI9hhJ86aFlh8efeuO90WN2Qk5F9bf9m+c8+9kvU1s8P0mYZT7lIIs+IfeXeYSwYlkDXO+x7XpfJXPDyHGMpYCcLf3SgihqZWfLJLXvu8dCzkTGM3//2fQTYwefsScYcJ0iW1S7HmwaH7HyU/OhAfQaFrt9msEvyjDoQveiFt61dwGsA+HcDJ90FfM1VV7fDw+N06UqJ1CmbOI2d7bSuoeOw4onowyJWpmoHO87YR8ejoK2fNjlpoXiw0rgQd1Dn2VYxHk7S5obz1kIohhDQZc2AwQVG5RaN8h41sR5/UrEr3IcrnJXvAt9aaYVlJ1pVZUyHF1p1AMWYuiWC2CbrREGWKzX0EvDUMbfABgJLzwNQYSFgnPN7h4LN/r4zUHHgBbjsIKZn8saOVMmLVB7650BPz0Eo5ik9G96jnBxMrCpDw/ry7AX4qD6+HawoNm1jqx0eZ9HyHO9mj2k7e/5Me+D+e9v9976/vfWPf6e97Z1va9dfe669/W377VGP2W7//Lt/JKx9NLaPuRxmmZeDQ8XhZG09WdLC2FhFobuytNhOrJ4r9/vkMIAba6z3aF2if7NbSSq72Lk8aLYsnayNLHayAuoZojWBVPZAa/Cbv/Hm9qTPfnLsj2J8cc8F4K9yMDNgh9cYPxaqrtyr/Ap0RsmUPiYrnxJ0btfHfCqL1eksxlAu11kx+iEDemIssdaHR21rpzLCK8kGBcqhCHkTc5Jy3q6WctXqUnOI9VXZlWo11xN3Gl0r1AEmk1JiTNqjRaeLrEvpBzi6yZBg00Fe7bWD4U7fouWWWag7u5lA05MucPkWMORw5esBOOoA36x2rCUJIHM4Rgftxc8dCFWrOwBpB+IU/zbLJXTDmHKOWcsTsMU4Mh5ygHPfa10reaGYOmp08uzUOWX9J9ZRHp4KOwratBahfbze57c6TEGH0LPTCrIq+KXoWms2DAzePSitmN4L2F3WPNfls34X75PhzPoM1/LgZ313ae9Ce/GLbl8DwDUA/LsFgLe/7I7MAt7Y7mb948jc2g4w4y44mAEgEQkfpvyj/Vv1LZRSyn/ZWg4zfz8RW60wP/UgeAAV3RJhFiSNqQt0WsBhjah4LD+RdtBZ5WsAkt21qhNrjdYVewiBikuJawFBuM5QeFXUOoqbmtDl5MmOeeYrQNAF4ywEETZyBUroAcpmBToDJhdoutaD2WfXLILfhd+sbF3JJJDLbhwz0OEZ7A8KyV0s7C9zmRUj+65xsk8oCglYPy3H/ijeLxqGVHHjskDru93z59rrfubl7Z6PfqTt70vYZrLExuZRe8c7W7vhup32klf+m3bx4l4oWtYqx6CSL3ttf/9S7/d6dHyYIFYu0wJ+Gs9sgXUO1XXBQxsnXZnPYJlnJbcs+yCzTr1uIAWKN7M7AJm2cjEqUJwszD/703e1T/uMT8/5Vi3ArgyVhFGuVYDAYszlfuT6XopDZVs8KL/iFXe2d7OUyvRv5kGSLZx+AZ39YKb4yyo35cAYWppBgx+kLisZU+V1eAegNORYWbn8efo95FPguayfmONKkJgHmex7TLs3Dikc0KgBh1U1rHwFHLWHMd4CcQ6m+B1Xqt8n2uQARaIIIG9xeOhjzFhf/dN9EeJjGLFjywAAIABJREFUh3TWGhd8XFtdRnw/+H0c5seaAECZ27z3gz+y7usMQAfASv5BtxCGhMUv5cygO7e0ddouvUNvehkBSCYM/quGBeiZtFZnKIbvAbKHMfAdB1gvw8WYmMcsZzVO6VXxDpZ51pN70AfjYJ5WQ8YR8iCSjbajDMw6CSSpbO0CvkzUfuwfuAtYQeKKAZQbNwRaNZjvmWGW2h6AZaqS7/F0fjIVeJotPAiCyBi2oGkXxJoNJyhXjjA818rilkwymoQDSHk2Jv8ev1GuWrmrQ/lZPEjE7Hmsi7WRizHJ/WDxMAA0hKBbujRuFyQAPWIIWQcXQA4AcT+QNZjzEQAh2WBpTXIgyTqR+evWBgdgw0rirplcS8DdsBSMFmysOTE+XOs/Z3AoYUcCBgDVT8QOFrwOl4+9J36Y1VQVxcKFawAQAauf/+dPvbBd2j9sW22n7V6lbEf1/txtf/iW/Xb+ms122yv/bVTZjxIOcQo46a0aD/YuJig8yHpcshSG0C439SzAUQKMmXUkccPXZJU7vydbVHmWqNcnuGkdRaAL9hglJgUR1gNZkU5ae+8H3tc+4RM+Ie696lwmgQAWoDkUj4M6xsjeUDMwrqmxCDz1GDDV6bMCxfBrKPCyssV7pxp20WHoOK2f/k5iAak1Gms3lVfxuS8A6WklOxS4C2sR8ZNV1ob3ocw5PCFzev3Fkk/jAJpu/BxLytuxnyNsIflw1BIE0PshjWfyPI+nw0pMuUB319NrmDnwfuedfsArqyqW0qDN49Nwicd+WPymywTqIaJRZO8MOqk6hVEhoizIyS2Zla6xcNBzS3R2fso4OT0n3cECtNr7zMAdYDDjWLGm+bokXS0Pnc5nThOS09A7Ywo+aS36/lKODFoFzKUcP40DoXQi/BGd8KxVnsad786qGBpnrvuoDzloJYlF38viR5gQ6wufDZoYOo2DuEKS7r//3vaSl75sbQFcA8CPHeytuqMngdx5Z8QASjgAllAQYkYRuE6QbtUBcHF9WJjCslItqSyJAmbsAtMsCC683RIxGHNYQwCWek4/dQJGrY6UgCVK0ZlL49A/ysF061S5eyUUouB1AcJUeJm0IsteZ2hz1aJQGTsuPcDrDAR4Bj97goYVOZ0BLzEmKeSzj2+uhQSlSgekhcmVKONyoTUDh2G5yGSDeWwoLC+RoOv8OQhGP8HPwNb30q27PJ+EHfZqpUVqkU059r/T6XGenGU1SQGb8zk4Omqv+ZEXtY0tZfte3U5O72033NDaXR/ebx/6cAL6f/Wv/227/4G9tqEkhOgCoZidvXD5KgFE77j4wP1pKai4PSWAOHCJtd9ISwauRFfKxPbBA7jhtAbE2CnzPg5gAlflVnNAPSuKnrxT1jopF1kApbi0hu9+15+1Rz3m0TFOWQkd/HkRX3jJ99DlQK8dWDHCkVVbhdwpFM/1zC8OFjtZ6Bm60n2aY+yv6iNalQA/CPAMQApZvPC9W6MGjY7DkB8uoMW4t7tzR9/iADAW/sE7ACTQK4p4eCyzPhvP90NK0nt6ToJPwzw9iiAvAKv1UI5DLTGZkcxUCTZllfSSO/P7nHc6KFwBzGPNq4g29KkEHs3TM9NZY+g6aKRcwbHXlQ0dz6hi1s7nftDxg32uddb0zBZnWFWHxRK60Hs4wMIvvAO5hqyg9JjLvWhaYNn50Kh0FJ6ZPABnnGB+n/3qBz2OsBvWfObD3Of0HvjeQhs9sbKUMEYC1sVBvI8Lj08A96OjWIt1HcBcxLUFcBWi+xg/AwDedttt7eqrrw4R6W14EIxByGYl4zVO7DAkpy2ZvSlSGoTeg6gzWSMEbLVv0/cwF++E0WHoLqzKzTssV7LojF6jiuuD4eIenc4qA7j3Gi4A190gZs0MhVwdTSQo6DqCUprBpZ7pFkEUSA9SpgepgVLWCuWjuS7GbL0vEQ48T3uEoAJksja+Zv4OB8MIGKyy7GVen3E1/HMgCtATOHIh7EowwHJlZ68C4IxzlSUEheMKWM9AWM6CNb9LV0mCqKzTFvskhVRu+/3j1n7hP/6v7dL9f9OOj4/aTTfd0La3Dtv+3lH7k7fttbNnz7SXf/+/bvv76dqV5Tsyhjc228WLD7SNU/X/TbCiFnCqAajrYg6nCfhc8cV1p0dte+vMwuUW11QMp1tP4vfKRj1QDKO0sdyqFpc6g3no1sFNvLedRqKKYuIEBj96193txofdNJKyCmDwPGiatV0FprxjCKBoBmC4XTuPWPebbkWs7NLDo/2+N1hC8jCT6+jK1UEOoIB3MBbojL9ZE+bYwaDAXyVYzPyCu5n563vezdrwfvhg/j4PRofdQ9Czzk+GhYg4XWQc74V+AICL8UVdy6RnYgMjtthCELxAd99DFQU/br2tHVY1Xbu1nbGFDvyGlX8A9FhLlQqSu9qqB2CZDFlS5Yfcaso+uoxmXPlZxuiOfrcjjlhz9cMR1k/2VxUl9JmSO2g/Cj+ynnpGWOM8275okrFR31UH6LG3God4PeMVdbCWjEn+p0XlsjC5LH7EeqfVMuM3nW44PKAbmRMHX31O6AZgT9csOqecnLRLFy+2F79knQQS+7XOAl7o6iv6AwB4++23h4VPwAzBOZ/mAGliZBjbwQOCGLdKCK0KtAVQKZ4weqkeL83pgB8XwKsAhAMPtxggMAMYCQxYEV1i8gBZWCoTUOVJnYQWBxuRMKJTryVcuIILa6GVlqGZuZ4F+HLQ4qBq1e/Mwdff38fvEkgSMBKe/v5ZWbqidIHsoHEo56VFDYE4QGSCQ/YdS1EKsKW1dW//Yts9c667/SlL4s8E2LHHWAEAFtAB4C5dK1XsuxYv55SZdmGdqP6+C7C0tR2FoD/0V3/SfvvX/mM7cyZj1HbObLQbbrylvenNH247Z47at3/Pv2w33vS4vm/0yVWnjwCFVQw6lH8VgtbnAaLLusNcIrNXBF6ZlVgdwkrgbtJjcxlWBw/tJ8CP5znIc4sBewot6TrV/4sC0epVfHwcAPDmR9wSypD4QfZhBkE9O3gj3YO8N9bCSupgJVKMcKy13O7Wlq2Dy3L39kxfOm1YsWFcYrwPGmavfe4OWh3k+TrwOQCC56XCyJg+ARnnS57brUOWjAMo8nWPULnJg5F7kBbBOOiGlatKUm2OdpRYBP15HusY/GZt+R5snrqfsQkIBv9Ud44uW2JrMiubkBMODvAVrnZi/4ImyspLsemIWRSNV+ay7o2i4RyqT1skX8nC3A/UBbzgWz2X33WNLFuKo0xLIL19icDOwu2AKLcCupEgwJYdNLpFULF9VXWgW//Ku+IycrhhsbLWLlYCWdLVSGwDgM5yzMNzXF75765LkXXzYWeODed7Do0ar9rIvujFL127gNcA8Irw3mU3dQD4sjuiThjumlB60z8dREPxU3st6nBVEdyy5ukuubC6Ij89jSB1CQuEcigTawQOUEFAwKQOxhCcCGsHfzAaAiAA6HG1HirFBEjg2Vh0ZIHcVnV/C17vJ2GyeassDYKK0/siTtAEkStkxo0AYKxuPeB5LljcCuJ74fNeuGjqpTNwSkWVcYPMi/dwah4CeLQvOlLNt6PMtHNQTnzLUMzDPaLnakyuBJivxwXNADfAm1lHXen5fJYWFyr3572xLqHw0nXD2hwen7Sjk822vXGxvfanXtnObB21c2c32s6Z1t7xrtN2sH/azp7baJ/7lKe1p3zhl4cSFXjSTz0HoB1zO9wvpZRFmCM04ihP+m7JkIWCjHGfl9O3ShgtDlhVJk3WFMBnV+SWYTwA+Sg74fPN8jc7Ud/vb++7N5T2uavOx6MctMQHlsHqrI47Wmug93mdugBzgNhTrCRT/N7EC8xT7uCD/VEKp9Nf9d1FDvDTgYGD+lXA12mK93E/31Fbcav6JfucRS+UCoJ+fX90rfYPyw0xbfO1MfbqgZ71G6u12tQBCLAJb3cAXHF07BdrAY07TfAMPuvPrMMEfLQAtpWBrja+AnjdYl6JPYrrdJ7r7uiNnH8ehkYdRujbwbmP0echsAcPCBxrDd1ix77O6+58jzwNGa/Dl4UbyTPj/MHaRf1Xqx152Xp5a9P6Mt+JFXjEJ86H0JkfOZD6ugD49NP1kNPfKvqG3qLdZPGvZM6/fN4L1gBwDQAndHaFfwIAX3LbS9tV56+Jp/ipDaUecUm4Sav6vSxgAMBo2RaFVkfh41DKp6fhikpz9jCdY92Yh+3Cyq1BCEgYEME5WwyxbjGPUGCMdypBEvealS+Y1gaUJ9UUNHwXbezK4uRCBWHrAG0W0PoO4Dkrd+5jXv4T4KZ3uJtsBsFuXcBCBwAM56DFLfL+UUtPQi6tPgGGtzbDFenCGKG2VNRLt13gilpzF4LMgTE6eNV1HA7GuEbvaYQsQDmF/gAfXclEgcehBOI6ZU4enrQLl+5qv/K6/6XtnDlp11y1HbFpv/P7J2337Gk7v3vcPvvJT26f/5yvrbik7PQwaOwo1r274CMJ5CBcX/sHe1FYW24jxqn7WH+UV4yxulFgSYn9lHWNQP2NpA93X8caSlvXv5nOHPjodwFArSXrrRZwt956a89CdPCERRC6AoizvwBBB44kdLh1sit/K+8S49RZsXrssndhKayCz2TgOn8uDokV6uEgaOYbsmVZF57lpWu4P+LnptIt8JC7gHW9g8++LtHPOeMMF7S9ooyJ5IhwIGsIT/As7mcdw5plWcd87sligEDnHeQdwHRx0KxMcsVc6r0hjyr+Tod4WQb7/LfSJdwLkVOmpmImvQ4kdB5rZIcIPoee9JMSJ0kj4hO5dynaPMJ2nI6ZwwKIUvh76ozS96LqzPJ37CGhNxXzjTxGv8ELWWqmXOLWucnlGM9lvTvNWwxrfpYHUtztGDEwgCgsykGrrxnviALtcvGXpy3K3RSA1VjXADClwNoFfIWgz2/rFsA77uxJHuGGsn89CaJiM7oiLECBYDqoE9miUnqBRmJfQsZVbBbCuisHOg5Uhi3XwWwuNN3F45mUzlBuOQvmqly1+LzctFEwtN6XLroBUnm/Ay0/pQI8XBn6CRHLDONnnvOp30ETwNUB4HyqRTDijtU9rAHvp1yE1gnlmFs6OqWwxTzfrayjPmD1Xq318vHlfAY4AfjMoMTB+iw4URZdcZurxgEVax33B4BIGo3L4+ChwPbhFmNPBK8CnB0dt5977R3tpodd3Y6O9trJ6U77wz/eq5jX4/Z5T/nk9sx/+q1ta2v02QY46ATOXg4ge9hOVVz28CDjD4/2YzwIbWi104g6fYjsZJ05GtmzxMIqi1llx4mtIvNec+29dA0E+gGKd4VyqjqA7NNdH/5I1P+79vrrwhKfgxxxdkHbZaUiQYLnxYGlaoQAMCgZ4iAoCjiXpZ01m/dZ66JnxOFiY7RR4zkzTcOTrCnXOfAKXpTFzMvVlAXNS6w4KPC19DkEZ4SHI91+PSN0Y6wVaxp0X7KKigExFosbjMOywg/U79YORBwIyJiFPlb9dPnCugaAJCYw7EKVhVw9eefnBJ1M6+PPjfGUxRB5EOtSGejhMp9aX4aMUbF2s7RjtSZWkHk6ICXxQ5a/XO/ROQPgxBiQK9yf8rszQD8IY1gIHqxkEkJxAoCqluJO9teFBpFz9PKVB6gnU5lXi0QR10PIVz/ck/zh8gqQqfAY5qYxYADgIOAHXwf9rsckf0LuHB9nEsi6E0gQwhoADm654t96GZiXvbwnIcAwXZhbkgMnSUChgzcEvPdyRIAPRZhDdRDkoGpWnP43z4K53LqicXBaXgqdUYqBXsEOiACvESdo9ftYUIJ0XQBh+ZsVCMLBBYErQj/Z8t6R2LF6XVwBMl8HbLhWUaB6h5+cHSgsPx+WMl9jFzz+e+4Z1j4ptnQ1cg1KDnpgjx2Eu+LxsVymkEzhsFcI93ze6GkawlnZiFWJ3wV5apkMRzjYf6D95L97dbv5ZnWo2Wp33bXdPvg3Am3KQNxsj/ukR7b/4X/8rrbRzgSYDFcsWdVSrpUAwh7qp+oDnlZBaP3U+rCfMT9lZgsfV0tFEhAihKJ6AbM/kfeBC4syK5VVTN04Bz/87uPRGKWIKTOh/dm/lKUs5Nb2dY53HWWGqtbQDzl+HeABOpxLusAnERdIjF+vi1mJXpFVPeJiZ5pwaxs85DzqtITi5Bm4zHFX57qkNdvdrMPyRsH3EeeY8806c8Skddo3a6AL2Rm4xgGmMk65TnVPAdd+L3zssX6+Jl1mWM/mWWZyDVnB/ZkGdKCtoJECjd1iulW9wEWg6h9dXg1AnQOveLas3OYf8XhSeN49R4wP0JX0lbVDvZzKmFeVpbEDZbBvWeTojzsbBaDVBeCsxZak4ODiFnnAFHPsdGKbhE5yvvCDRKf7kke8P40n1DQUX+VhAr2JnGTc8B9WPxLzlpbwDK2R9VbXrQFgrv4aALpUucLfexmYl78yS2hU8CyWDhhhLtOBQnBGD0AgQrV4o0X9P6+hVFZAhu1gDoZ0AMK4EOT9FGdgMhi63h1lXMol7WBT7+tzkbAs4OdAL+6rGEWEEM9w12ooTos76QWia1IulBCEMD4n1hng8j4HeXo3e+MucJ8X17ui8N+HgslAdQrVpoBC+VFa5ripZ3AotaoJSaKDC2DAlvadgG32ZVZovl/M2YGy7z/jdoHr8xuJH7FaWbahXFiMT+/Lzhin0cP3uut22o/+0J3txuu32tlz2+39f7XV7r73QrvjZd/X3v+Bd7cLe/vt8Y//zMj4g8ZUAsbd70nLST9Ba6eHkXEbCnDjtB3uJaDs8zrJloesRVeglfELTcd82+gpjJsUK0xYDqrkTCiMsGou3cKxhxstFAQ0FtbfU1nbdsI13A87RZ8daCgrdGsrLIQoKt+P3pKu+u7GfRvqiqGyT9V6UV4qkjuql28HtMRoFsjgun54rP68fohxBcsarlL+0GhSQgJ1ko5WHb54FvThtDbzTgDTfuhZdqsAPDggdSArC6GsiTN/R2HnqovY17gOAw6gA7hUjOWU27GgycjopW7r1PFjnn/Q4WbSTy8wXUWuo61eZbDGOlRPaPoeA+5YI6cP6N3nz7tZJ/ZWINC/I6EN4ORy1pNjwmMzxeoFXxxlgWRfA8lkhSSp1p/LS1eRuhd3Lh6vTNwZB7FlwefRLm6V1U48prklPWTsLOATPuiydPKAuddoFc3GoaRc8tLXt92+rgO4BoBXCPjm2xwAirBh4pmBcTei9F0hO9GG+b1cA4DHfpoqsBTKalJCCAhXGvyOlQsrggsVDyKeFYSfYrnXBbIzuJ9ecQ+7CyDASHX66NYrm8cMMrEeef2n2erlCm8GTJzeHSC7i3YurM11DtQR1jyL9ch3kXhhwMPA7Nh/EkMu73PrNOJxSa4QUPLMz/fO6QOw52vka8L88p3Djb2wBlf2qr9DAFAA8a6/eXt74+tfF0kt93z0pH3dN3xTu+r6R7fd3Z0AV9qnrWoj5hbGOAhUYssY41EkhERB7oj/O2nqDiJzXxa2lUlSvWqV6m4dParcCy7ToMnTJUhEASXATHAefGAlP7AcQdOsAZm/+hul9tG7PtJuvvkRofD1GUCd5/r75s8uO8BsZtsragDSQ5affb8qxk+f+zMdbHXwV4rNaQlQx2GL5zroYC+4Fhr3tYlrZOmyrF8/iKCQ07o89Qou/hjrcyy7cwD1OPhxSCTbtMoVEe8s53SPoSxhR0HvlaCz3OIewiGgGHPYzFJIjH1h9VfgQ8Ug+oEZ2bkApYGSy71bbmHG4pYpvUcZvfGdkj8Um1q+/w5mqiUhPEwSHSBScgiPDOvFO3K4aRH0fXQZ4HLPeZ99dlnvAAs5pLhtZC+8AC1yQOAZ0BV7Sqy7Vy9gHTWWGbClThkdiFzm+QFhuIXTK6HxKARJNEOoDp93UBrhSWpRmPI6OoGss4ATqK/LwHz8KNA7gah0ByeXGZDMYGVmHj/xuBUxajbJLK6SGeqeQPkCKdWKt4hkkimQmtPdSNVfFm4NEaKTVBVa7YDUkzTqFOZWKZQzCgdrjmpK6XlxoqQzSbkQHJTMzO1gR2vmrgaApErfEBSMsHFhzfO519eSHXbwhsCbwaGf0ufnz9YVnueAeAjo6nVqHVZc+aI0eJ8LZebgwIK98gQYt6zxvAejZkCYTtZkLfqzELKHAnJVs6u7vDpgTNqT9U+uz+OTnba5nYWRmRuHCQpIwwPdchdgrrVLly60zZOkWc03+vgqfuxAbtZMHlGAvd4ToOv4qNdKCz2quL4CPrEvLS188BQWcFqQxfg2SvHQC1jdQaxciBT7Axf3AnaoCPWZ3e1wpl2679529XXXx7MVgM5eOHh08OVj8HglBy1Y/TqNCejJD7+RJT2c3+ZD2Qz0g+as7EiCsQF2iPHrh4VKiIkxl2veQWbwThXQvmw9J/coNDqDzwFKMskt9qhKjiAj3OKEskY2xFoVgOy8Xck+vCs1WK5XB6/WZUVfd/flybKmnL7D5d1lltzP2oLLizcsLYbGZBwKQuYp41s0VXRJKIPWEhAd39fzHcwwfugBy1oCvCwrBl0wJ2qH0hmE0joOrhyUsle6nznTK33sc1UDKJ0QDQkqHAEDhu4nYZH96nw/FepeCdRL70BzOddRVgjadf3pBgzAsMtMp1/WifnGTyuVswaAg4DXAPDjx3/Ny8CcO3tVj0NyQY5QOJag2NnpbmInUsCPJ2cEE0Qck3XTwD1c1jQJWAHA+cSKIkCoOICCcVGUeo9Am37SwcMZ0OcCaOxLN1kgYPoZMKVLZkjXYGArdzErIf6G+Tk5ooB5/+zSBZDxswPbFWVmUIoo3BmoIhh9LRgX12Ix1HhmkM997I0rylWkh1BbBVpnV8wMhHXvwgpbD3GAKmVx3z3vbtfd8Ji2sZlZe1l7rUUcYCjGraRPWsIRC5bfpjtUKG5zY7e1jQRdDq4R0IeHCd5YF/3MmoDHbe/ixSiZpPXS+u1fuhjdQTZO1Lw+XbBRTkMFdCvJIj6TJapisVir2MNKXGD93XLk82e/gybKspWzIq6tkoFkydw4abfcfGv7iz//s3b9jTd0/uIdACt4CRDtf3MQ8c+Sp8taRp2/KH1SyTm2b07LTkMd8NDejqzaat3mtICM4Z4oOlz/ACwdMJe7Pd51lH1lZ97XZ1w/9nb06YXmO5ixTGTWyA9gTjtBf1UbT7sK/zEH6ikGLVjhefjKD3DQpY+V5yRRZlyfzzXa/xUt+cEm5GP0L1bNzirlUnTD4SpqCFaNRC/8HW71Atq0pwOAuTwYoNnd3lkLcdBwrnOubQJD5AJlqubDCMANMAhtcK+DfPbTQTblxlx+U9vVdQ6doaAZLJjQvo/LXbtJlwk8uUY/WWuXyf49NAAt+zyc54MHVcygDlYqFr0uBJ2rtgaAXRRe+S8AwJe9/M4mAOiAQ0QH8OJzGE+1lcQ0Dhpc6EDg3aRdVdn1TASZvwtl4y4aFB4MsVCAbkFBieeDu1Lvp+8CmAhVTvU1kCZgK6YOASzhFOUeMj6QeXDypMg0n192gjeh5mDLhb6fcl0QuGJBiLBWLqxmoDd/58IKAYoCdeHt68raMh7fb4SgC1gHh1h8Z9DM/F0YLoSzWYuYp4/TgWunldOsQ+kKJ2ICo+vByNgMIR1B9BmjxhqFRbkXNa4khYqh4pmDm5JWUczp8s22iLIeyg2se+7+0F+33fPn2rbKjESge7p2Sd7geb6/WJAW7bRw91JmyOL82BdabunviM8qha593d87jM4OqrV39lxaN5UBLKWh/5iL78HMWw7iHRwPxT2ShygI7WAmFFVZrJwe4lkVI4jLGLrRuOJ3a0KDLHEFHM8zgMO+xv5UsWrKkgRoqRIlznsuKQH7s8xLmTUSZBL0pixA0Tv9O50CAGWo1BywhoU80bmkkn2cZ11OAC5m4AC9wL/Iow7Oa13UAYZ2bewtMtdlSd/nivX1rGQy0UMmV7avaK13AlG8YCVJOY243BlyE5BHwliGBWQcbyaFKCwDF/KQ+cnjxNX52rub3D9HPjFfgK/vT9BaxQ1GzVoLi5j3V+/xMCGfK+uuGEae7/pJ33uXGx8L9IZ+5TruYX49ltXaDa4B4ODgNQB0aXaFv/dWcLe/LDuBWBsehBRWvU641d2DV7oCAMA5E8ZzcPlaHSee58xBUK8L7VnYItgYH4obheLvdmAzTpvlcq54xWB8AGVlKxI/snDphjk+QaYrDYSpK9ZZKDA2rmGdXGgGcCgXGPfP79HfCtaPot3Wzs6f489w8AaodCXGO+fPXEGxBqy7C1r23oEb38/WTd+LGfy75biDnSkbGBDiCi2ulVaVxiXTsayCaW1zC0R2GNA8jitmB9ph/Zg3698D0WXdOz5oB0cZ3N2B0/FhO9i7JBtcOzlUyY8CgDpIBIMsy+TMawAAdJfifNhivn3NzPXpPHR4cBzA7757H2jXXJtF3TXmm266KQrH+r9ZKXonDxRhrwlH31hl+ZKYUAc553cfC+5NgEx81zI4XgCQ2ofQD/N3emW/4xp3d1toRqfJypgFyKxyh7K3CbKGdcrHPSxkebhlv/o4zWLs+xRgqdyT3CcrIGsZVt3Tzd6WzcHvDHZdfmH5YVwxdsW19poouasO4GZ6cdoO2q+QGz53a5fKuAQAruxgEmvc/ev7AihywNpBcBy80yIowMf6j3UbQNBbr7lFl7G6YcDlrMuiPm96+tbBr8uhSkKkhI/rD+7lWg4HUey99hYa8PWljdwAhNsZAmK95BmjfiI7ZppjTWedqkQ08TRjkAv4BS988boQ9NoCeIWIb7oNAPjS229r11x9XTfLQ9DOVBEHM8XYuVJ2F4N/HoHnar9VZUMwt4dwteLL+nt2eSBYnPkcyMFcYZGsOn7+HATUDCqQn5QK0HuYM6dwF9IIdc0fJiZOhvEwVj95ayzEUjmAQrB7EosHJzsAdCXaLUfm1pmOyil5AAAgAElEQVQtcP5+feduXhd6Mf7tnQRP1cN3Xv953Zx8WBPez9hQMoArnjEDED9RO2Cer0NB6nPP1kb1hfdRdFQuVwFB5TrSrgo3MIojwO5WJTQU8HdFj8WP599/792R8HH9jTd3UKDv7r///nZuV885bsfqCFIuYKzmMaeq4wf9QmO93p+1g/N1Yp9mhdCBW4FAWQTO7Z4NC5gsTKInDggax8UL97err72mXXPV1dEZJNaJmDvLVISGYwyV6KACwvAS4/BxdRBc2ZnzWPmbOXsHEd7DM2ae8Xtjv0iksHIlrlhZ3w64ynrKXkLX7DO05/eN9R8xmjGO6Jkr8JrxWB0QyM1bA4PW+/MElDdUDiS9CYxr5oUZuMX6ViyeP1PjpeQLz1BsaRQwroxdXe8H6HkNkS/wKWvjcarLeNeMPQUMHh+mp8QBJLzuFkqnCyU5KPaUdXHw5gfEtLRlwwBicF32c5ByveJ7B136PlMRAits9HW3ygZ8jrxnvWN+ZeTQelKU2XkAOoIWFAfIc/TdiCdOwkX3uZwBBKJj3foba1ghI5EMVuERijdeA8DcibUF0DXlFf7uAPDs7vkObvxkD0MQAQcTopgBAi6QEbDhbi0XShe6WNIwwVdZjdnqAiP5KdAB0Cqh7wDGK6ojePQzBCGn9bIyIQxmQe2WEj/5OrM7cHSrgSvEINg6fbuS0twQDrrXA+CZn4+B8bvQ8szs2To2W1T0LAf3+0fH7cxWnloDyHB6LuvirPgRYHyOdZD5oZwQ3tCR7sOdwjrMdJRjWMZZIkh9zMv1yKBw7o1nWl3ALO122ja3R81CBHoI2Wodx/idlu+95+52/Y0Pa5cu3N/EGxvbw50cVhKt5dFBgMOT46OeBRxjiQPFUZNLLiw2VjTdFaRbAhwk+mEBPnMrCIpaFoGrzp0PRS0LoOYmhXvu/G67/74LAVDOnM3i1pFtuHXmskMWSnHV+rMuDtadrn0PffzQ+MLSrezgKW5WfxOfJvqIhBqL5euK0BI4nMf8gOeAycc40+xybdMK5Z+RoNAtVbkIGesV9QIrWcLa4i1osBIDyHalzl7neyUHnalY6hUxe52XKmPX6cX5DFnY56pwvercASByYD0f1rt1O/hgtAb0PRLI7M+s2oGMQcBEz1wceGowHHD9ULiUrVQfmMFxyiAyiGVhS/pMyyX/fL0Zj+uGkIMlS7SP8TwLqcDj43RN9m/QkWJ+LWbS5f3qQ/JIdGFdXRbPAHUG675frJ1+qqUj/b11mBR/PP8FL1pbANcA8AoR33SbA0DFAM6gC2XtSgih7WDBBb0LBBcEBOTOwM0Vj4OspcAgduTyelwoMKxDGotOnmT4+vddgJbVQid7Xd9P9eGiqiKxtVbU93PGREjyE0HiQHJWQn767crFGs9rHJQDANTxDAcm+sxPj6wnBYAdbPgY9DvPZU1cmc5gxBU68+MaxtotWuau9ZO7K/N5XDPIcWDn6+trzO+DhkZRaD0vQM5uunllBUT5CzBJ0c8lIRRVNgtqxqms3ijBcSZDI+b10d8qBq1/x0f7CayPs/NDFB23umJhjayi1LNy9r95jyt6jYe6bawRP8Pqt5MZvrLs4eLeP7jUrrv2hnZ6ctQu7R3EOuyc2QqQKEXiYR1uCYr12siEAdaFdwGwGKODrxlkQQNck9b5AZ6YMzzlvAHN8r44AJZDnetzLwTEiAcdz852YwnqmIfmiFxKGhKYEO1kmaN8TrruGLvuV/mNAPrlrXBwxJz5CT0DJLJhyOivjTxjTEOe5HXsucbivKDr/DnQPj97yRVVQy93cMyh3LkRY2aWZu5D1jIuDtoun5EZcZAp8O57TVcb59HUCwqTWfaf7rxYrtikAUrBjN7bSTMZg6l/AC73tKCPco+x2I6Y9ABh9R5kctctsshVglfwehFcrLE1FCCL2BOr2QdPqkl6yRJq+t1lswM/15EzXbD3Xghav+/U4VzPPjjcC7pYWwBzw9YWQCTlx/GzxwDecXtYOTxrFUXogh4Q56+EGUNQEmdhBZq7e6BO8XmaHvXRUJRuDUP4h/Irq5RbGxBaDmAAq0OQLtsY6XvqoEWDcDFrmethVO7luX7aQzDyHgSL17tizfRzdpfMJ1isSPNpeR7/DJwcJCB43ZXsVje+5ydj8v1zwQwQZv7sA+5uXYvwY1zdxWKWG18rnuXWTQeJjMXpbRWQZl389J+CNGtwQUeyAOqarc1UWp2WrH2Vni+wpJg+6MqtFV4CxQtds45dGR0luDo8uJQWClkCTxNEoMBivVTmReVejo5iTDOYRCFwD2vRgX/FuHXlKxdjO44+x9EarzJxI76OeNZjZecetXPnr46xRXJGxeFprqyZnuO0mgB22Q6SPWKczr8+Zp4JeAx62i6ru2VVcx110Ngn/QTwEcc3A56x/2kRSn6ELmVBzIQuX9OxH7nf+W+UO0qQlRmd+TPV/kJRW5IOcoGx8fxYC8IKonzMTu5NWYBnixi0MB9MeLdbwP2g4iCtj3UrAQg8Cj+IzkPuWV1Jfy+07LKPebOOyCreRT1B3eNr0b83AdPpsdz389/c44d/tsj1AAd8lw187/vEvHtL0pLFsePVn17QEsC7AHW4f6tKBbVfna7Rd8iwHFfusx98nC9YI3SH5uzJHzxTnwPo453VrSfJ9TTqAL70pbevLYBrAGgc9nH86q3gcI2JWAElIkYJaWdsF44OwJxwEVAwmQOLmYF9+ACnrvhWzE3fIdRgatrPCdA5aHOFBYNyqo/vLMsTYcJYOY3B1K4QXGg6cGG4uqeXhKDNXCkQhMDs7nWh7tP2GD4X0rMAm5WzgwwfV18H6yCg/fZsXVe6+m7OBvfT7KwsnVZ8TDO4cZDAdS5AHfj6GiPgGaO78OId9EqNzNMU+rluWets/J3JIKoBHEpzKzsH6H7ewXqzfvMabakDyOFhWAD17sO9zLZVJBfzHQovsx7n8TM333P2Vi44gTbi5+b1JEidQwgdY2QN1He3PvKWdtddd3XXcPBGxQDqvUEjm6PLAWBFCQuMm7Z1/e8CRlyLcmStwtJHxm8VMp7n6O467nf+owaiK07eN4OMQVcCsukyXIIJ9xp4iMHI0sXFl+9LAL/Y+3qm15abeYR5hAzqlsM8nPAfe8y9/rmDxJwjNLRsWze/d1G2peIl41lRjzwzdmPtKp4PiyLyAVk1PieRaVCkx7TNa+MHdPbGr2E/+M4BH/Q81jrnLD5hDTpd9XjdZcs+dBXyljqu0EXwO0YHOygCupCHPr6YLxnDsqCy/2VV1vzEcylL0mI5rklrs57B2PRddCYqtzI6TH/juYFm/UBK6R2N8fj0KJ77onUv4OTNdSHoFejoY/zIs4AF9BDMWAQAK4BCmIXXzAzM9ShZ3LAIF57vTB2m7mIyFxw8S9dyEkUJhEXDXKYIxbReKPg+3SgObLr1q2oTzu9aNSd9BhPPCt0VkYNE3YMAYFyAyfkUD7PrHgC0Ax9/rj/TrWC8gzV1S2NX6JPS5rn6ye8umN1V7IrXgVoAnsPDDEQ36wi/rwLJsyJ0txPr7ODAhaLPxRVo7vO2mqktwJ00HkK+gxerNRLPbpsJAE824n7W3kGi7z+/d4B4clTFoC9lOaF6xsHhxXb+3G47f/5c2909Gwkjly5mU3fekXMvS/SKki+AVWrsobAjg7YsVA9cuC/WHzr37ge65ty5c+2ee+7p5S6o9claxmGnevX6+mIBDEV3ZqspIcQPAg7W+l6Ui9eLXUOnDnwYux/UYhxWwFnXcMhgXKtkjfOK86Mr/5QTUtIJHABq7PHcxWHw+dISCC0yjs7LFrca91YnmJCVVSPOeVP3uSUwQFpkJmdNR9zdyC/ABuuhcADFhunv4N3tYe2MuW4mfSgLPniwAGDUDazWb9ALctnlEHvra+tr7yrGZY/PCb5GftLtYpbJA6iPQuislYMuB2kuJ3xcrGP0CjJ3bFjgyXy2WGxd43zuz+oysSbrem3WRbSBw6KMgQM6wqDg68kcXR94ghvr2mVPqrRI8HrxuhPIGgB+jDjvQS8HAL7yVa+K07OYRcwK8803iqidUB1AwOwIYgAaJxyuRdiFoNHJprIRcTPyHH9eV36W6TaDTbc2Ahrd2oIy4v2ALgelvNPfx3NXARQXVvPv+ps1YG4IhVlxzQJL7/8vWRk9RsvB3Kzcoj6eKqQUOGI99FNj4NTscUm+p1yHcHShxnpAK+w741m1P7PrzIGBK3o/ePBcB33sz3j3sPypHl8ojKoNSPeQ+LAAoAOE2Is6MLhy9/HzPsaIMo61iuLPJ5EJfHBwMQDGffd+qL3p19/Y/vI9d3UWuuqq1p785M9uj3/Cp7ezu1cvklfYlwSlA3jE2KrKtYYucOVjVFyQxiKgpzhAaFn7Gn9vbEYiivYXi4SeEWuqDOUq8aK6heogQps65ukHEAcGjMFpbwCqckNXxxOnOQDHDC5ifLU3DuRYPBla6K2r+ZJQ1IFTudzhGb1zkeRwOsA2pUng12WsXhBJjweUTExaGQcl5wF4/EwdYHlm0E4VPO5rWLUJOYjm2DNTmLUdBcxHj19952vLmvR7qt4hPZsB0kEL1jGGOFLkYC9UbvLXW1c6zwOukAeMYaYP1xczOGMODuz7HJJjF3SaNDJc8nhMoI95TWR1ncc1A1Q/HDv4uuygIqNDuYtd/qOzZOWFxpZzVrY48bOjDJCPy+eMDNZPl5sO/sOesanuQifB0y95yW1rF/DaAuhkd+W/eyu4MztnF7EqgAkIFubhhIPw9dMjigOXlCtvtyp2BZASswNOFw7O4LzDT+G8C6HrgtEZzsGsCw9XXigLennq/tla6YDMAdu8Ts68/m4HESgOV6p8zzohvIaQpWtFKoy0nO5GFqosSSFCy5JESQXWhr3zsflaOlAOFWj9RX0tGTcCc37GbNlwIO37g8BzxcL3/tn8PPZ8BroUfHZaOFWR23IBd2W0mfFhGhfr/MADD7Rrrrsu1pA1d7c773JhzXqGJTo6hByFBVB//+09f9V+/DX/IXxu0NvV15xtFx5QwshG+6qv/LJ208NukS2qW3sWB4Nq6dVde7Q5qQVijIzn/gfujRqeUg6yBvoanT97ru0fHmTJmnPnFkAi3lldPTrwU3ePk7ScDnC9jGf1z9lHrCIAhKCL04x3dCUMvUPTxEQK/GFNxrLFtb7XDpR5twMVpzGXWwJ9o3XYSLpIeqEuIJajfIoDBMqQ+Fz8QBgJBwZA6IkeLn8VTi7Lb4CGzTnhgVp5WXalz6csvfAa6y6crN8B9QA+559YMwN/8JRb5gAwLgcvn3cdFizWL8At7dbo4mIt1xgHFjZ4zeNqmZNkl1/P+7kn8qpCvllIworYTA4FyEB4HPnU1y4KlVfrNrMGRjzwwUG8J/a9EkIoHaM5d1kUlt3R8UTXa246BBwdy/1fcZHR77gSczaJ+829Z37Qtsa/qE5QYUO6NqtWpGVZMYC33XbHGgCuAWDnm4/rF28Fd/VV1/asOQQ5iglBjoJFELqQRaA4UJxBD393UEOyRDElDOOK3AWgPncguVCcBG7nzal8y92LAHQBzrtcgehdWE8USxJt6up5CL4ZjC4VRW7HDALn07R/j9ByxeoCB7A8uxak0ByoRKcKq8nmoM5BKooDcDIrUgddvu/z85wWfA6+d/zuSoN5uLBGMTGmWZk5vWkcIXDL9ZxKIwHwglaqVVasfWWGygoiCw8KhecGvcsKWKU05r1grKzjmO9xOz3M+mX7B3vt+GC//eAPfn9Y6vi3ta2s1Kx99JTP/px2w40Pj647Nz7s4YtuFaxVX+cqVhnvVGhiZayzJ3LdXrhwIT4nTheFQeIKLb4oicT6zj2JeUeslWqOnW6GsXTu9tHvLwDd6brcv7FuZBFPnT2412nRe9dq7BzAeC774ICDtXe+43rCKAbdjWxsF5TIH4CZ8yzXuWxxC5EfTJ1OnNbh2Sgds50HjlXjpbZfB8aVk6q/tY7Mux/IZKktd7HzCiAQPnPAGS5iuX6rvmDQ/ulIgnB+pcWggxRZtCjUzDogx7EYIoeYt/Mh6wiPMzYHZynvRrKQ64mUR4TiHF5WxojnxzsLiAc/r6gZyTo7Lfi+QQe6zi2OjNXbyHXPlfrdV5a5DllYB3Ww8Djv5ZqmDGP9nA4ZI/NK71ECTrmA1xbA3L11DOBMxVfwtyeBiFj95OTKkdOuMxsWMa6DiMMqUifE2YoWwewnKqtQ/RNp01XuSGLlECjumnTF4UILwYISkOme/sK+JC6sh4AerpbL5h4ew60AgDxvFnAOVACZCC+UMQIbd7ALN353YOqAL8FAuqQcTOdcabOUpRAoaeHKcla6CDhXon7N7Kqe99hBs37ne9Z+FQlyIJgVKkrRgajv0TxfTtqhHK1H6xDgo0VcjKPqlsV7rfMHMV9SdszHs9+P63RPfB5K1ZUa90Xnj8OD7ARyctLu/sift3//Y6+Nc4cMCam4Apq2s+e22nOe85x26yMf2/eSNXGA4L9rPzhYxZyqE0fMefM0rH5y4ypOL76myLMCxvcP2rXXXhsWQHd9hdXP+vgSU4j1Q9nCAh+0bOOAAAhxINrpv0AjCSNB8xujuHqsQLX+63tXrkvfy5le532GPgbfjD7iDtxYV+gcmlmAHSsCzufwoY+1g7NF+ZKyIln5FpdDHDLywLG0OM4yibVJpaZg/3Rfw6vaH2hfoH++P+aq3sBljWPsvFcZ6BEzWGMhJtCBbOet6jENzeU6Zu/eAFVWvQHej9qTh1m/UW5lX0PGwvNm+emWY1ynyHmAX66DnpsgEd6DNpDberascBpX0CyZthgXCHkx66XrOOg6APKiLE8aE2L+5RqeDw4h+zd3kuZ7sl8mFOU404JIFYoOKEuWsf7adyzh0G7+zHI5axfwoP41AFylbT/GzwCAL7ntpWGVmMvAYBrvp5KK2etgq6wSnJj0elw4CDYxB8JRTATTz4kGbnmaFYH+nsutICBhFIBWF4BWyiEr+S8L0WLZg7ldafj7HJwxJ8CdK4cusIupEZgIi/mUjFJiXA6meJZbxrCcpfCgtIQU4FYmQES7rNG/GAXgyt8VqAMN1tvXlHkDKBHeACJOtwhMvtdzSeqBHhDqlJBhrd3CsSoImvFyP2Py8S6FdQKhELqbCRQDLFxW8iPjo5gvewRd6x4liPSsWnP5sG5Bv4rhKgDY2lF79SteETkA5HSkHtlqn/OUz2pPetLnh3WNOfOcoINWbjX5j6rEC+sZyqWyd+kIoGt0/+HRfvCshzDsnjkXCmvv0oV2ZvdctJJSx5A+x5a1L2Nk0f86Ad8qYOJxdOzlrLygc187Eksc5HNfAA/i1mxdKUbMc5wfnbdcaadrN0MjBLqU7AFo5vNxYEgw012nVirGaW8+9MxgEvmitfO1YAxdJlTc7Sw/oGnW2/mQzzKPTVRRSUPVncXbwEW/Gx12q8QQ7/X1AeQhd5HFigvlur7ecpiUBbzzpYqfF7h0XtTvHofse9+zcas7k9PAzM8zwGc/oU+6gqRXdrTgBFBCe/A8ex1ys0Cc0x2yC13hdDXLY+Rn3y/KXJWHh2fIOMCckYWHh6OmK4cVng/9+QGXdzEPaHAYDY5iPrIAvmidBBJssgaAHyPYW3W51wE8f+7qqqnFqeXyDgYiQlVI54QK40O4ELUTMMSN4HRXgFuHAGJyZ+kUxH0LpkahT3GDzkAIQplhGA8A0AGVvt9Sur8F4LpSBmSggPUd4/X6XA4eECiuvPWZuxP0nZ/wAYDDqjGyWV14deFdLpHczwwiP9k4aVuq8bZR2cRkAvZ4nRGzwlqh9BwYO0B0kKV5E1+2CuC7snXg6+s9WxC6srMuD5oLp+ZZQc4gtR9KpmK7ctprPFef3273/e29bUv1Lbd222k7ant7B233zNkEzafplnNFGMq+rGxkFYfyFECTC62UoeLbwtKgMi3BEwftL979B+3nfvZXkm63Ntottzy8feTDH47nfc1/99+26294RHwXa1wdG6KFm1xVKhxTGZ1RQkVvq1ZQMb4CbSj02PmoY5lxdp61Cy+qBqBiAC/sX4oM5Ouuuy7u8X2P+aqOYMUCzhZdB9fOJx2UFu+4FSa+K0uVKz/ff1ySAQSrVRprEz+rcDEgncxWaII9GzSx7O07A4acxwjK72U7rBB7f6bF/1GUeYDAPES6FXTEn44x1Kb0mGov5dNljPj1dBTc7mvitSsVj1m1HTtwrvWirl/wWLl5Hay6bHZQ7X2E52tmnoyM5M20XgVtVKY29Ndlbd3o7/FQE3/PrA86T3gMZT0PnZFJQMvi0IyV+y+j1aofS13G+XtsqcyBAzbyOvScZK0dUhwkxneZQVTGhQwfIiabOfshofPmlDnOPHm+8wJ1KdcA0Hd8DQCXq3GFfy1awZ09m64f4uemeDuY3k3kfOav95OoC2y/P5RqZVlxOnWid2sgisOVjjO9CyFAWmQ8VsZwKOjDw4iT8n+hCKsgNELdBdt8up+FpSs3nydKerZw6n4HeT4WQBiWRQeIrLd+EiMloOTjw+2xVExyXYxgNN6BkMHdjhJlfAhoV9isN3vFPQA8n0tYJaqTxDjJ01dWBVPTlTTWc2Rd6jP23k/IKM0O6M2dyNhi7gGs0hr0s6/9n9vZs2faJz72ie2/ftKzEsAJBGymy9xBvNO0agOGNVX/O91sR6dLd1/Mvcq/yPoXrp2jg/a///Arws17/wNH7bnP/RdhBfx//tPvtj98yx+0537LPw/3rBS+A1ksYawFtdvYgwBdx6OsxaxIw2W/WdbxKtUCqNV3R8cHYY0VALlw8f62s73b65dBD7F+uHANfMyKdT4c+cHIx9v5vGIA/eASWcflfg461Mi2trLyQNWtC+uX8Qq8OQPXPGRldm/S1Ei6iTZ8ZaFzgD8ss8k/VCGQrAh+os2blRJxUJX0J8tfqHJz88sim7Fyi8OQxfS5jGAf9byQVdUSLsrAbOShlBjMyNau9RAQnkvFuLz138OapwPO8chgDt4yy3fsW7md4T0/BAJYYt7eEqMKk3NwcfmJm5N17+CxABPrmXyetTEHXSeITnoaZbycP/1w7a5YB5+6P/jbTfHInDgwjc4r0SKuAJnLXU03O+SNouDsoa+V76vknesZLJgOHBkntWxx+7rsd3d0rmOOQYlm61ZwueJrC+ACzlzZH54FjOvIgRZmbhE2J7qurP4/ii5rRB7PgCLgfpgXgSkhQz9Q3uvWKYQAiiiCfEuozBaoEDImzBFGAJgO3izbVfNTNqW3snNw1BWb9Z71uTggnK1rMDfjdHeuAy/AI+CL8bpwG0ooM8R4L89EePBcB1SArxncQj1ukZ2VuisGB5p8HgLK3CEuGLMA8mkYmlSSJuXyEPZkWaJIALSufBnzvA+p9LYi5k/rrnt3to7ba/7Nv2ofuuu43XDjZnvq53xu+0dPeVY06kg6GhZA5gmtqead5gcAzFI6afnRv9PKXCQ78ejgsJ2cHreDS/e0d77zbe3TPu0fB+1t7+y0E7lay8oW5VwKkDvY8b1Q309KswTNyvpTbkAHDb4uAnmxBhUrJnevlJCeK0tcrGVZktQKDiXnygwA6Icx/37mG1fCTrOL3w0Adho/3Qy3NS3rjg+Pwnqlf31/q3dyBz1xSCOjeChu6EC0k/dW4eMqr+KHhdi3qheZ8iP3NAo2l6JnDFwb76dlpOpMhgVqgAHR0P7+pR7uwBi6O3A73bdYrti/2JeSW4tDJNbQKsLNnmABjHELKALsCphQN5AkD2jDZY4sd3IVA0T0s7siFbdXNK6xcz+yr8sXlVcq6yOWQOQqa+a85HJols+EgmTcMu34KPmSfwvcoyNImGANsVRDAwBf/eRQmjxR8ZfWpSjGUvF8eg9WvrmMjPiW+2MNKkMYGannQLP8rvF4IhJx2oQvuXyDBuZneHIIPMgeiN7WSSC5KmsA2FXSlf/Ss4DvuDPKRMxCE4KGgSFgV4ictPWZMwe/++g4OQFwXIBwnQNNmMGFKEyOUnJggiDQdwEoFUxNSn91/ghhVQztAG9plSoFUeUbfN4oJoCyxuYFkWFono1SdCHp32mOVIlnvQOATMIMwaZrR0wXwjItarJWyXDlSoy+mgBn9titc76WLnQcBPBMxu4nV8amuQJ+h9LdbIcWRyR36oGazJelZ3Q8GJTCGJfzGK5xp1O/9qjaXR0eXWi/+H/9WPuL99zbtndau+XhZ9qzn/O17ZGP+URz+VbB3AqeZw6AWKcN6LXzg2xmSnY6VbZhBb6fZHwfysDXV9Yc/nbe6aBALmYSBqjNZ+3knIfmIuPhRqwYvogxLEugxn9mJzObowdwaxFEDp+jrCkB4/OFj5bWs7Tc8g8Fpr+d5vtzynUZf1fMYtxzmm5zWaYCJMjCGkbb/Ay6WvJc9uv1fXDFqXcA7JgX9M5+zsCGcet7+I9DpoOf8dlIQhhgMsNhhnxKMBsywqx/jI85sYaxvmYV5V4H+Mg35I4fGOKwUzUI50MicplnusWfObFGDqwe7DvkXfBb8S6ymvlwr8uAVXLP5Z/rAPo7w9PIVU8QYS0DvNXa815Z9rDY8b1kfWTsVnKHHyT1O2uIzkBexxjLMgwQDGuhecacXlJHKns4w0oyMS/luIM6B8bsTefFyTU81iZ5b50EMiThGgC6VrjC370TiBSD/sFUMLELHO+hSBs1gN+s+DgJI2Rgek5vKML5dOiCnWtnoIjA0uktBNvkXnDhzklQz93b308XmPfsnGIAUWx+SnehiMJIJk8FwFxcCOs6ByoOHP06BDzKDeXrp1zmz54MsEIWcyrVAynVcifxDqx+PGNW6i4QtW6AQQcqzGMW+FzPmOe/AWStYrq68N7caLvbO031Ch1soCx8DFg2XRHq9yixUT1c45rqcpDK97j90uv+fXVHw8QAACAASURBVHvH2z9ACFB75rM/vz3pc54dND5A+QCss9Jlv3yvoqh5WRpDYaht2GG6G9OdlUDc6SH2qqxhcufGWhY4ohhvgP0CgBR7Dr7Bimat1VijrpAFqKrHr54rMEjIwz0fvatdfe01maFYFlq9C0u7gyLGHAcnuY0tFIT99zXy9UHJedJI7lFaMWkNF7wuZzzWeVn7qu6h8ziKedBGZoEC5thD0U+60gh1GC342GPfDwcxST/D3YxiX8WnaYlKV2Wuf7qeoecEkCoInta9TudlrYtn4sovANzBXtjEU1ZEMW5zOWKFjnfWurl3RM/lb+6DPpBfzpv63cE6shdQ0mW1xWDyDj3f5bHzYySndGtpAiD+hu7c6+EyyPc96WyEt7DG2qc5UYe5+PPZH+bOs0Nmq05fhaYgX0JeKcGwYsFj3KVL3cMUALC3lBwWSx97vlPxoRzKR+ykH97RG7qeNWE8zo8hE+JAmdZrjV/1PG+7/WXrOoBrC+AVIr7ptrkMTMSj0MeyF7EcDO3CDSGM4HHA6GADBu0CrywugAV/HwyBUGO4zsiY0xFsEQdVglD3UdDTgSfKjLhDYkAi5qcymwGwft9SYYys0VkRzmANIezC1pnbrUzzWiE4XUiigF3gpEUp4+dyLXO1sISkVQJlNMqJuIJBULM3ADwEFopsFThinC6Yfe3y9+12qCxFrJKKHSpr4OFhZrC6gp6Bhis1xsgcKQvhay0QGHuxfdz+tx98dbtwvxRKhvjIGPz8l7wqFPU4ZIxsyHltdc1CmVd/VlmpAPfH5ZrUnDy2Ud/7Ps7zijUr8IH7re9xFX6ONd9Qa8Os9+hAVGCAeF0sO24ZFA/snt1pB3v77aprrm57l3LODqCCWOr5HD70kR9ofE2cF9gLxux/+z4BWmIOxwe9vAxzieznsgA6f/gzkAEo78Xzw6WeZTug5ZQL1Y2krP2cAkKumJJHhlBUfRxKRy1PxV0FmOwJI8vevNAfgMR5W1ZAl4sOVpy2ZxDn7f68D7TGAS0gN53+fb/gK7c4MV8+S4ExEnE6X9QhMuRAtZpz+oP+PfsVt66eB+9k+ZJRBzFjkkecJGswxj0Ss5x/+N2NA9CD771b5ByASt73d0SNxQTzIUPL1cs6Drc/2eV5SOC/pfzUYW8kRUKrmjO1N2c9BP0CUpG1rh/hRw647LUsgOtWcLnKawsg1PZx/HQLoOLfsP5hBUCo+oncAR+FLGFMCtBqSAJbMpnPlkG3OLlihGHFEDBFP9H1xIK03vQeqnMfTrNgIWwXgb1RqDZP8SHsifOwuD7cOQTp6lqsCQ7oUIj66S4PwKALJhfSjAthDshAYLMOzJ3TIe/BypLPzNIA584pc3pkyZHlGLFuARRzHxxsrQKekJIrMQfas2L2MTNeaCWF1ka4ixR/FONVaZYAg4lWmZtbhZm/vktAmt0tWMNc1wS3BPuzR2EB3dpqr37lbW1nZ6Pt77V23fXZ4eZffOeL27GUnbXOwk2DgHWlioJgjgBrAcCDw/1RfuRYcxklhgB/Th/QMwAjxqvajlWcl8LRMbdIZSHDMNu1zZYX2rjpeVI04l3+8Q7dc+GBB9rDbr6p7e9lkXD2cpVSYn1J0lDCiK7zvYH+Z9r0A0IHolW6JOjvdLNt72yGe5r6gHGPDgP/L3tvGmt5dpb7rXP2GWvodvu2uy1hX5vEQC4XJESYbEUIHAUxXEE+RIIPCIFIgIAhxM61jJF7qOpum6tERrYVMA7GDgL5Q8IookhICWCHUQQpzOMXbMCxaXe7qk7VmfaJnvd9f2s9e9Wum7jckUyySyqdc/b+D2t4h2e9o/WoZQ7+PMadAENWtjzsDHrLNnHQQNIUNTJz7byEFHVC4T89P92oo74kmZchn6weaHaGWI1D9HV12o291OGjrLfaV4DeTG8uE4tR0nJKnF+Bd0AD97MGDs58DdftM+sBnYg/KVbdn1ehFMHvZfFGjsPfXRaUFVdjJVubhN5cm+q8U5asGJ/1ak/5lP8AU4zDQTL8hNxgzoyDv1kb3wvkt8u1+CySbRYZElQgEQDIc/shp1zO6MTQHTGPDPsghjDLwuz1w9YM2BmDH8bYp74Q1u2EBCeN7/RkUwam0/eFU4ev3Ob3/8cr4ADwspqVdkZMhqCPLwzEyQSlOFeCd6b00+jMyF0RVfySCyoAkVtRYEYHLQ7KyDxjXDwjTrpnZ70zCI3CM+RoKwo8d0FmbasQIoxrHZgDvLjgYf0AhAgLF2j6zJ/r4IBx+zVujdNzHITyvhTKqTBQwCgx1t7Btp86EejrFP0qmBtdFdg/lChjAvRpXK4YV10vqUAR/OzZLPRXAUvOFGsnBwDiB3t8WPRbfa791//mHYHz5FV93Q/+F+3w0gNtd7HbXS4Bhq0QtAM/3kv3AYqwav2i8LIU5iKBbPJD0pDPZ973+ftYf6xUFVhPljBlaLwTh9OI06LGrXhQ8aHTvMalFncvfujBACE6JJBdynprTCh1wADjdosUNKD7ACC6l8MiB6YOYizL1+kcWaLncI+/r5fCscMY8atDoA2rjMsEB0pJewNsRTmock92ZT61E5vlE2vja6VwE8kNQE0AnopBWwdCBO6d52bAAkBxWolrqhWf6jPC736odBDO+BwQzgDNZcoMrHWYibHLHK1De/XRDquseWpmfoaekcHEcJKQkmt0ETlPeja0HnOVhTtCIKp4ubm8xWtaMzwDo0/yan1Tvd9pi3XS8/NAfNhprPM2NGB9fJWkNYcP0WcampN7mDAjpznfc9aH1pwcvD0MypOvALP8xIrv+zjiBkflAMmfJ564tnEBbyyAQyR+Or91F/D1p9u+ysBUnb0QBhVXFyfXrXQfBdFvD7edn6ziFKRYLLm3iM2zTCk/8TBmt2zwu4MKlA51AbEweqIIgkrMNAcfxxwUizel8sc9luKPQEGQwNAOQhD4gOABFJYRh4TrGYEOM3sbLhQN7wGszRYwFJADbgdtvuepvLMI7snJEBZYQVA8KF5XEA58XDEj4N3dPsaUQMzHk1m+y7DwBTjYykLFDj6TttKVyfrOAJN95T6UpBSB5keMzbAajDp+KvNyuH/R3vXOZ9qtG6193b/6V+2Vn/cv217ba4sdnfaHGyfWpPquMhb/mTSV1qMOApYZp6W4v14PsOL+2HNX6tzL3kJjnT6iBW3GwHXFuTXqnSWNjqLNDiBQHAC3qw9cbs8/d6NbqqUEdb36BL/kJS9JBbaV4R26J12eGRfoNIlSu5eFkO/nNWONkBkxVlkyK9mD9YZu4Z1Yo+iakvvoYCWvXVcyaHTD4JCDG5g4zMVit8DXiEXrvFx8zzvdKqRxonhnsBRuxA4cR93GXtOxMuD1nqD9iv9zWvd1RXZ2WVjZ510mEhdord9mULbCS9m08q7kE97D/NlD6InPfe8c1M97NgNZQC6Zwfo7aWuU5gEAuiyK91Z2tb+D6gAOnnDpQ+/IIhLo+Bzw6DzXwX3Rl9ex1ZyRe4zBdUPIfGI66SRSXi0HoEN/ZHHw8feQOchD3unywA9c6FB0X65vAuATuYAff3IDADcAEHL99H6uywLupzqCUHWSS20ZIiYZd7gTEaQzWILxUDoIeCx7wWhVa81PuCjIWUAh7LoQjPZAVU+uakfBlKxKuHsqUWPFQlOCHKuEfnLqnAWlgxEAKGPhVKf7AXUzkOoCCLdzDc6FIQoUwevCeBYUs8IOUFIdVrgfi9tsPfS5OOX4GFeBBso2QabvKYrO6QVlIDDmzwxBWocIyUcH+ew398a1ZllBYeX7htWKuSYIyAzo977n3wS4+Y//k29r/+zhlyokP/vkVnykA4xY43LBsv7MPYEpXSYyJKEXJ1bih4RyBL4PgOh068A9Pje3brfgVGBk0Jtlbkf2qFymtgYoOFf4HZi2Fta+xe5Bu3SQrbAAMR/7+EfbI488Es/zfZ0Bnq+976fG5mEdzpPal1HOozpWmHUbADiDzLvoQklU1ULMD6B5X7rXcq6DYpEBrPmQPaNMi9Mqd8Y8k6D6Tz1Xa6ZDXO57FqGHRgGT0C3vlBV6BrZOqw4gfd3cysPnDib6wbsOrXpf7EmFLkS2dCVZ6H3QdAd29P0FWNdBBxqKRBP6PUeYzulK3KePBR532dgBaxVajmvOsrxQtLGrIvQOPIl3Zd84qOeBatUa6PsWsaz7+1aCRzJoxNdCG8OinIk9rBk8MuhjJPIgr/WdGyLicxKgrPsHfYAJKuYwkKBzLw63eUBdLWu0DoC7DIcGALyMhwOawh5IUokYwA0ADBLcxAB+etgv7u6FoJ+83q5cubISYOyCqgMJSwzR/fl5S1fxXsZauRJ1pehuUU5qESReQe+zNciFmwM7FKoEYrh40e7VzQDhjbCP8WDRLIsOjbwdEHHycguZlxmYBR9AL8ZQwtBPeQAzXw+AGte51RNhiyBHKa8oL+uaoedqTf2fg0piT+bnONhBOTNWn2/WVRu9LONEv61+IxmDJwUo0MXeOEhhfijRiFs8S7CUmZsHPQN4nl9XioU9L8IyMtzGWfg3Y8BcaB4d32w/+Z63t9e97o3tbJmZ2d3tstIL2DqtVKurWIcqRDzWH0WS71Jv3djzsmIG7ZO5W9ZO7aGf4Dv9VybsytqrwG/FWjkoClBqtf/Iop33kXWTUlB83cP/7JH2iU98Ij6+c3yULt/lWcRfXr50tWemdqBAzFMdHqCFGWRC5zOg4f0OROH/DoQqc3UGRtAbCpzEAeeBlD8UelYW6EjeIQ52ANekhXHIywMI/OZz6nKlasF5UgJzwnpOD9cBSoYLmILjohsHEMhNijsDNDSWOSEk1s7Kxbic01gcmMvC5nsArbE/gGe3LMb91RNb1we/KCSz5K7oZu4N7YdP3jcfQIJuq3Zg7GGVhQngVbUKV9d8GZa04NkCpCkLltG9iG4a1ATMQ7ssaX5wGQki0OoMrhIMjwL4AM5xWBxxng50+8GjSr9orMHf1Jmt0Bv0oEBrB+ZxWJB1PWNR9SxqySLLPHaTz9BTTjsODMfcRls7hXs8vnEBbwDgC4D9VgDgtetPN8UAwugOVPxEigXQrXpiEikp1RpTU/qz01S8fsqDsLEmuKDjxOTutjmeSffjjoQJ5VZQCIt+Suz4KY/x8R7eH4yNFSBKK4xYEgdeuh/r4IjFGCUmEEAwsQNJ9gbl7+NGIHGflLfexX93G86KmO94PooGRYEyRfH5mHxtAGdOQ75eQ1mnIMUCMoTT3fE7AZor5gnaYRw8G7fwAEF39y12hTfKbgw3IArBXdABzmSNW8pIct5u3brRHnjgRTE9hCi9gIciX7WIxRr2AhDDJckexvdnCiVI60MI/wBvI4AdmpjX10GR70lYv7HqWBHts6nLiwMzB4rsE+ERKrCsYu6hWFUcui3ac5/4x/aSR9MC6KCLvYEeHUQ4LcwKzNe0g1uLFfM9dwuggxl4kr2Bn7UW0Z5PbfEEggsc+xi13nn/OATwbKdxlLMnIzjPOt+S/DGDVH/e6r0j5EKHJGhW4/QYSae1mUf9eX4dFml4s4OUijdFTjjvOhBxcOHgD1nRM3WtdiP77SAFcOlyGnDthoFYs2mfGA9yINc1qy0I/IWciprSI1zozmmGhgTvFKCCvobcW41LVIgGrtFZH0LP7uKVHJN1lzWQZTHeV0YNjAK9S0gl3uj9WEChWZdT+dnQP+ytd5/iMOoHfj8kO0/w7Hxv9TIXbW1vt5u3brUnn7y+cQFvLIAzyd/f31gAn376rdG5AGEbTF4xKFlkNl0jmUSR70JAplsuM1LFkB1EWt0sP0nK1RJB6fUgP8Uxiy70ty8icxCG5hQZMX0ZYRw/KXfC2Cq2Oe5DsAVDyTxfhaFDWVlmF0Ja13vyi65DCMzlOBCeCN5+klzJ4lo9yes9CCEHS7PQ198z6EMIaw1Z5zkDebYidAW75nkoPQcHAzRzkh6dC3LP0+U6MnpbgL8BEEc1fgdDu9sZH6O9J0bIxwZ4YL+Gyw/gnSVvUlFURnHFFcpKuK2sibIUspZ6Zlo9RlkQX3PoEvoiIzXmgqvtfMQyquVbgAcDfyi84YZKYIsbHj5x8BdlXMpywj4H7VyM2mHsjYMHehAHvS3TmqH36Nkq+6Kev5qv/mudH7h6OQ5H4SIu1xRrw4GB5/v+wTeevMNaOVBycIsC70qy+hTDGw5OfE26BV19ZmVNO1W7lmwT52MN8Heh8jmK70sg4fwBaOlWmur44bJqzGG0G/P6frG3lnHLnHzOIytz1KKc+R4eh0fvJZ2hnRX6o7c181fpJANZDrxnQML4uyyJ3a84tMVYLx8vgI61xLqqv/UuEv38MMCaBqApyyR76vJcbtGQVRU/frCbZZcW27LY7raT6vkO7yv/Xdwz5EIejj2TVu/Gys5a5CH7tIcLOFiFvtBPftjxfYEfeq3bsv65tRkgKP1AzUfXAYzN6VL3YBF0/eY05Yd9aIf19woOR0dHGwBYi7hxAd9LqnwKn3cA+MzbglH9H9Y6twhQRy8EVwABgaN00fWsrsqwJfNODJAMU5aVApY929G6R/hJlbg6Z5quRLBMVR0/BG3gwWi5lYpfWb6ueHATEQcEuPOTImMAPCCcENb8RHH68xGM/T1WcsYFqJib0yD3uAAFOAHG+CmXiQQCQi37ZqZr9uIsBSBC0QEE7+B0yd+zMtf9ZKR10L6lSLrV4sb6Tu5fnqPvBQJ5HgI81kq1+WTRqVZUnIZxX2dG70hecTA9zyX+Vj/UKtug97rVBSuk5qHvojNKtH5KNy7rA017TOAMVKraRwfaAiZy/4aisLlAB51OK8nAQQ6/M/eIOa2CsR2QtnHan2nLaQxQAmCD9uEzfU63mMODvbZ3sB8JIioV4/s/00DnT4sv4zOu7UBlyhBl7oypy5EtC9yrDx1oMh6nWwd+fL9KE7IC5qGT7G++Z52hXVq+Oe86CPQamgAX5uxjgx8BmewPdARI8AOF8y6hCvAXdKDndA9IWT9JThLomw9zLp8dNDD/OSYTmgcQ9bmTeV7xhU6rY+2GVYvv/cDm8qXLtkr+2t8b7nhf+321xwtgnrwYQKliBiUPlltqFZg8RqHuXPsEsax3grWwFdZnWW8QEJg0lgdXfcYaQ3spM3I1iRnU80kMnHlM13kpofkQmQaCjCGdZRbPcvkS7yrd4ACStXLagUb1neTGJgs4920DAF0a3OfvAMC3PPZEe+ihh+KkFa2lgis4JY+imQBAXpfXZTC8rHGexYkwQmn02JLtDBqOe6seFAoGAQujykUanTvKtBeMXO8LAS1XUAmxtIQlEEVgK3AXZupMrdNnCSrG6IpL1wGwXAG5wO3Kvk7rUri4c115My8Ehv4G+N0LILhgRZj4iRi3I67ZKLSseYYbJS2wdHLQ7+6K9/HQQio7LGTJCd9XwLEAFwJLcXxdYO0MS6kL+ZjXMschLB5rLUx+lsH1w8KHS0d0c3JX2ySUloOPoZQz/lAgz/sIRxZy1Hbdit7A+hmZ1ovdKN0iIOjrP++jC2bNg/eFgN9V79fj6NvAd77XrJcCtv3gAU0D1KA19j/2u3r+6hqsBw5qoAnoGn5gfnJnkYVOSSRZAK9cPmyLnbS4X7p0KZ6NZYH3YPnw8UB3KDTWBTr2eF7n3dkaAt0G71kHDNY91qZKjwC45QqGZ3U/wfDJv4p5HdY7HYgYm/OnjztpMz0WznO4kZ0GHOAAONjj3Ld8nw69yT9az+odjeWuQICPy9/tip+9iGsVq6c6luIXS06aW/8xnqyZp0P7sJA7iNU7KWkCDTptuVyEJpGRi7LUOXhxl2bUb7ROMS6z9LtaEOr7Ffmt9o+xEaqakAARGab6nCGrMrOi9qoyrUuGz7phrG+2Xcu/6YyUbvpcjzmTfChLZD1yWe/QQcljq0dZrTEuPRea6j3ntxZhdMDYoWeLL9ELHDZnGpv1CuA39zWBLHJIz3788cc3LuANALxPxDfd5gBQCuJAGVeVVeqE2QFACdEo8lwuAlrkRFPtyupyoRqCplpa6XPFCKpJPcI4vt/KoH2PQ4Ho/VTk8YIu5DlNKttM7l+KUMczqyC1JwwwHz8Z+6k8hXwqHz1bLjR+R1i6sIWpEaoOiFD8Dq7cJYBycKCD4HXBOp++0+26Wo8OgeaKhXXUs8h21u+4JnJcVOcfmdXs/wAdo1E8z0xj6wBKfY7lstL3jFsJEyt7Xtmd+p7nuUXOgUWMsBQrn8eet4t2fKT+tvvdahBrZ+PiPsUcobT0Ge5N1jjA1PlZKGD2lvg6lWwOEFhghRZ2gD5AFBaE4IMqF+G0wNgd0Ik3YixblVVa68mc/Z55TdyKjBKDdhQwrjqAHMz0jocffrh9/OMf76DJn72Orl1cwB8cMFCSDtRD+UdrttNhvVKyi5X+6X2Bd1LB+3c6GOofFnlKgjhAYe/0GTwNPeMqZJ9Z+/F3HTxX6sglsI9scSu87CBYz3fwDR3r4KSEJubBXHJ/h4vYeYQxzfu6jjY50AZtnmTYjMvAvd2DdrbUwWokiIw2daNdHTSBZ8J5CZAUXXvOz8Ld7Ic0fc/nAker1sSU2XHNaVrazqrEkNy98L7mHDF351nnT/PisCAZpufrcKZYXh2eEuxlbUueOwB48rEDM/YHS2zuzwgXSV5KahZg17g0HsoIUVTeQTv7k9a95E2fDzJi8HcCPmQGPO7JSdABITzoBvaDkmFei9CvkQv4+vVNDGCs7aYQtIvn+/u91wF8+qmmyv+0yEnQtuhdM4LpS4iHoDKwBqGLWSO+a2+vXMPpft1XzJ8yFZWlt8x6ZN0aUtXxyQQGlDj4CEYrJaL4HxjMha2An5jrtE6CISgL+OlnCHMVWF0MCxDAA0aG0VlJF9TMke843Wq8Q1kNJaHvPQbMwaoDD4Arc5nH5GNxJcjnnOjTnTGy5FAm68CDKxqsRSS6zAqfcaEQ6JyBAuzjVsRoxfkEGKoTvaxw/drlSKAAXDs4Zu6sqYQhgNCtFTOlDxdyWm4DlJU7OhSzwK0UTlmbNWYAG0qdNVESQlhgLNtdiR+hhOTmrhIhgA8PU8iDTDajn4GEA3r2PGhKe7bYbUrg6MCo5sCYGCOK30ET11DXD9Civ/X/oRc9EAcifS7edHp1RQ7te0HaGWxiFZ+Bij7H8uHu+Bnsi4fj30W57S7S7Q8QCD6q0iUAuVTYWdTZaY79QWEz1r6PUZ0g38NneS17kxnG+Q83Yo6vHxisnps/v3syrJ0Yzw4urPVWAD9hMdzPs4esWUaheq2fhFPOa4BiCtcDPhzA+bwinKYOPcRjp/t7tDGDNtLrkRntAln6XZ/l51UY2qoNJNDPMbFXEUtdYF9jRg7pe7l59S91QR0aq2JDytGLtlv3620CgOIjpYlEK8dePzT3zuUCSUApc1dpYuiD0b0my8gcrlh/OcCk7KtKEucZNsG7co+znm2C0TJuVGUB1hL60306CGCF53P4QoBOv0cheWsrx/wY+8qeVhw5ni2tnca8aQWXXLsBgLMmvI+/5zIwGZ+RCkNuAAWVR5cBndbP01LR41lKSIhh5fbqyryKwEYUVlkKEYBVcD5CkwUG9eyT42Q0b3yegnTVveOKMISR9f/UGAAVoXxh2jrRIzgHYBpgiQKvKHVOafzNsvrpzwGJCwgUvysrd5e5UmRN+togFEsAusvAlW6uS1QRXnGVobxcIPOZg06EV+6XLAqj6PEYd7oeEPz5eZ70Xfk6gIr4OwXwq/J/1bVDoRG0Tw0v5javLX87YEI4Mm4HGdCJW2MjYakAYN/TUsqsh34CLFAIbsliHQJMRg3AdF9JKWDtoPj3LLShW4AetOJrxfwEAJX4MZSXJ1cljXJfKs8RjhGgoZSCfy6eEl+refyDD16NQ5H2X0WhdYB60YteFIqIcTI+P2DMANYVoNOrz93vgQYZf8xvaxkyRBZPPvcDEMBbZWv2duReHe3dRrzocIexZszDr3fAlvt0J4qkZ8u8jClzWoCOIvlEB8bz9Z0w1oFRwN+873EYqKxWABN0Fe+72Io4UPiJZ2e7uWxZ6XThMsDnhyUM+tABxPnL7yMRgmvJgB6xkEOmuFXsLiA96RodjnZ3vedvAm0le+jzsAyenXUZvVXA/7T6mevgdefktLf0Szdweokc/PO3W/+0fjyf9RrjJV40qzpknDtxqbXO26OWIgeSyAy2/sHxXEIIaCFHfUqrI9jb3lE+ZjvreXJQxELpB8wuC8qq6SEPAETJaI1NoHqTBbwBgPcB9dbf0pNA3vpMujipJk/9qOVWgD+dMAFP/BRxAqyyl2Jpfbnati96ORgUmJvMJQyUtRjfyV+3pZPwqM+m0aJ0UMJh1asTWQiwUoihoC17b+5egXULRecrEZ9FQepR5NjBnYO+PtfJwjMrBbfwdFBcL+UZKGxPuHBgpmfMsXsOdrI+WSoI3uEKHaGPouC7Yb2gBEPGM6EMAWj5rpE4wZogaEkQ0sq7Ej8/OW1bZQHQM0Q6zGOA0Mwon4HcDKQA4rN7mgOI7+dQ/nkQUSygA5rTkzxkYBViLXknY8FC49mvcv8K0CbwO+7Kxq/FOsZPvmOMA2yOdnbxbsU9VaKSK/UZ3CjeMQ496qtch7ChHNJNxr+4rg5elw73A2gI8OnAdeOTt9rLX/7yAIgDBIwMaT6brde8C9DpdD0DRwfPPI/5RKyjHdycF3tNRNHMctn2BHDlEqzOQm4pxEKIwgYEEEcoAOcgMw8yix4T57zlhwd/3gzKU/4UqIsXJZDM+/MAyrNCTtkBNuirDtACwA5U4Ht40A8i0CzXuIfEn6F7kctk7TKeHqKzs1exbSPUBhnqB1boxw/7yOBFHfSpxqDxAca0BwqRyOScaIIcv++U3HaA3F31cejdbnJtbi922nEVBE8r+qBjd8GuA1HICn3n8hc3PPJWERgT3AAAIABJREFUP6Ft31/4H2sb/Z+1rugTubaDPioOXQCRd6UOkbWzgG/VI+T7Du4L1EOv6Dn91Lv9kNt5xoDo7dubMjBdzm1cwJ8+DuydQK5da5cuX10JQBco68q9YrrkbhNIkKuAGkVinhRAGXSs1H6EyKwM+vOUCJK1PBIIVHkHwBonfpgAxdoFvVXJd6CIAA+Gj1GVkK4TKIo5AncL9LmFBkExAFGCoxBuKmZc4M/HgXJ0BezAjDm4kArQWqfg2bLoazcDlXXK060KDqLcVe5KBqCRp2ksLV5rL90y/ENwz7EsPi+sYv5Zvifdd6wf82bNWRO3FPVT+BS073sL6HAQg+JECXcX0Q6utaF42R//iYu470dZWGOdIgs6i27rbwLimQ+fM08UMkCJmJ577R9jdlqArviOpBf2m4OV1pfYTgC6/j68tB8lVcLSVOEXt27dav/Rf/g17YMf+tAKPXNft+5b8pSPCcuKA2R4SuOFT2dgxlhjXarzBHsYz6dUibXow3LiBZVpm9fpZifdxtQPlAWPBAUOi4A99ig2sUqr+KEUetezWYdZwkIv6w4vnnEcMtEybB0kQwPwNmu6Mj6z9q7ya8parSdJXIypg5GyOgEIc82zELN+du+IPotEllEw+1TVGiiwXrFv8xrwLJdn4gfi2vYWCYS0MeoKAigCxEG/gs0a42mUaNqOg5AAYNBTuYaRWzPvM2f2imfCC9AiciXXbHivck7DxUzR6THXIQ8Bycj8qG4ha91ZlrhhPwaoS53mYRm6Bh5jTOgT5L3La+aHNZAkvUwC2bSCC7m/AYAza37qf49ewNfb7v7esOgJYC0zLsJP+9Gc2zNrm9xLKYw8kzOFzlC4KHwRv5/eXdnT8SBP2mmhuituyILGEYwwlAsJvY9SGLou41uSYUMYW30rXRvFoa1moI+L0xtMjWIJsFvlbRx4wewoZZSfg2GAEmvrSoHveK8rWxSsWwJcuQDWOOmOIs4JOEPsVZuzfCeFdTNCmgB+xkAGWjBcxIBSEy+vd2CJAGSP83s6iazGxWH5ZDyzRQnlBbhwkDsrU+IYXZE60GLvPR4r1qeSUoZVNOONONDEfAKYpBXKnwkNcYhgvPM4WZ8Z4LF2rLPvudNGPzCV5QCl60C7g6EqXu7ro4zlvcPM/tWzPnnjuabEAbLEuZafSJB+UKp9X7WqjAQu5ufAyEF1BzWK/ysvgtY3eL3oEdpyC1HcV1Y8D6FQpixtx3R/dAFa0rJvlCEa9Dp6HaOo4V+/hvqPPhZ+9z3lM/Z70BYlSYbM6zRs2cF+8NE6DT7LlXc+8HE6vcx0ziEEQNFprSchDSulnq9EBaxNfvDyvRfAcU9P+Xa614U1Abw4UNO49Z+OH7Gv2y3c+hFXp2dL/pY35/hUmdQpg9tCGfRJG9AHawJN8hO+dRnBfmCpdvr0Th3wDEDfAeWQgaKrnSxLbpa/vhZlwY9GCGVdliVTYQZ6HrVu5/Ixzt+MU5/N2cartJEWZlnyr19/epMF/JkMAN/61re2n/u5n2t/9md/1g4PD9trXvOa9iM/8iPt8z7v8zpC+6qv+qr267/+6yuI7Zu/+ZvbBz7wgf6Z2jr9wA/8QPulX/ql+Owbv/Eb2zvf+c6I4eHfH/7hH7bXve517Xd/93fbi1/84vbd3/3d7S1vectdgmXlRfYHAPDJJ5+MVnAShCg7nd7CqmLuNLlpETRR0Pn2rSgzoeuWVYgTAaU4v27qN9M3QmdW7jC0gxgEDYp5RSjR3FtlPioeCqbRs/1EhZVxq3qiIsh16uR3FDwAhhM2YJRTLtYfjROLj+Y5ToAjjkvPxjLloHIdoFmnfDlF6tnuukBgAJYBm+4+moU7awggdUDjwgYl5crQQYaDhlmBMUcHrfOepNJISzLrwNqR8cdaMBa+R9kxdpRogHjL1psB5VAeGZTudCl3sQM4B2sx1mp3pzE5IIuYoALB0GwHPDUBt8q4RWYG7U4PKCPmPu8TrrkZMKCMozVcJSedHN9u+weXmjKCRcfHJ7cjDlC/O31A8+tAh9Mlvzt4m+naFXWfM/F/ZH4v00vAoarLDLOayfLHXkB/WAC7EtUOWEkSfQ4duMxjfRk3QMG9BxHWcJ5WXsUjOi2PkkmjRA30kDwu92AeFphXvDOZaCUcYQVslwxjz/2ZyA4OJE5bHARTrpHtOtzeHmrCXFnLXLtRSieHmEkPjMOBVK5dWplHrdhRHN2toQHuK15Oz92rUkwhJxUbXHG0AqHMZ3m6bCeVZCgLIEX84XkHg7E3lpjB4YADDrzthgunBzqBpHwY/bbRaXo+MhfvUS9mXeFCAVTLqCAZoL8pKaTnAvjcKsqYZ+DsB13fb5dBg78SAG5iAJOzP2MtgF/7tV/bvuVbvqV96Zd+aSiaH/7hH24Can/yJ38S7db0TwDwcz/3c9u1a9e6nBJYfPDBB/vfX/d1X9c+/OEPt5/4iZ+Iz77ru76rvfKVr2y//Mu/HH8LvOkZX/3VXx3v+Iu/+Iv27d/+7VEn6A1veIPLv3v+7i5gvR9mkSA82Nvv6f96gIKzI8aCki07eWqhjpefaMUj6c7N3owSUs7Qeh7gyUEAA8UaCDPC4CmsMg4HIQeD8B2nOj7HSuep9a5Y/H4UuT5DiDio4loU5jpLCXNjLg42+A6FB6BxUAx4QfE7CGLuKACNB4CKMnVhBuhzAOdz5L2+ByhRhJyDKVdCrAXjZJ0cnBH8jBKDvngm4+Mens8Y2CdfN5+LEzaf42rycTNn36+8l2zQVIgO5DI0lZi1kcEcd1mGqK8ddAEvzOuue7t1uwbPXFGkbpFkXaAhny8giPdzCJGMiQPZctkEAGXZp5uOegSLp65eebCDEmiogyzLzHVrEXTogM/3y0Etz2LfnZaDP6sm4AofW+KFK8DYs4pIIE4wXL3Vhqzz2/ZWB268z0Eu8scPDTwHWuHQG3uk+prlmuYQDCj1QxTv8lIyjB9LdwIADptkr5IoMcAm43A5g1xzGREWvCq4zx5k31p5O4Z1HqDH3qR1bsT9YqH3fQQgaiySgXoXfNrlc1WEQC7LEqu9If5Qz43Wb9WfWe9VdrAKqUuvADaRWVtbWTtTZWCijFeFjfT+3NUykT1kz/V+B5POE87rzq+6B9eq1kV/HxzkPMOQUNZHjcdlq+sbgC77laE0WRMSPqEkzLpDCXTvsngdb896QSEczzzzzMYC+JkMAH0j9fvHPvax9sgjj4TF7yu/8ivjawHAL/qiL2o/+qM/Ol8ef//pn/5p+/zP//z227/92+3Lv/zL4zP9/upXvzosi7Im/tiP/Vj7oR/6ofbRj360M8Hb3va2sBIKOMIMa19QH7oFUACwC04F8quUh061UV5kWGxk2YMZPAONUi1xClOtP7kaK7aPMSCIpACCecoih6JAmUUf0cgiLldAFaXGJayAagS5gyl9hnvUhRqAqVtwsOaU65eMTsbnjAfo8s+4DkGtuSAM3ALiAp3nrNsXvuO0y4nRBYTfh4XNQQvXArIAI11BGuCYFRj7g0D1gGRdS9KHK1RfA8bmigJgwbs4rXMtc5gtm9AA4+bvdSDR1wvBOwPRe9F/rnn1Ka2SEkpqoeuJLIMhqMMalMqb9zE3fUa8KnTowNPXaAZLPh8H+dCoW2z0vVsLnK6YH5Zpj3n7u4/8bXv5K/55JCBoLEe3syUcNQfFKwIuhEYwP6d5PmN+ABIHvnw2A6+ZXpy/50OYDpIRy1chJjGGszx09hInI7I3pi1ABgjhGt3nMYWs1QwOWDe976S66JDHhqXRLTcOcH3vmLvLOL7PnySHrPaf1hkC2okxWxcJfqeEFc9jPLF25YLUzzHHjLljrtkvd7Xe4jog74cOB1laB/jXQeks66CR2JMIhhSwOg13qJJhAlidZwgOlsCUU/ISLdup+mzHuzJ0iLUW8I7x1r67DES+ceCf19/pVb8rgSstuWmR1bvT45CuacbO/J1uSAoBzDkv5/5nVQYqJSDTnMahE7c6j30aRa+RLe4xQM9KX8ub+Pzzz7cHHnjg36ba/z//3WesBXBe+b/6q79qn/M5nxNWwC/4gi+IrwUA//iP/zgI8dFHH22y9slyd/Xq1fj+ve99b3v961/fnnvuuZXHyf379re/vX3Hd3xH+7Zv+7YghF/8xV/s1/zBH/xB++Iv/uL2N3/zN+2zP/uz7yICCXv9558ISlmBskQSuwCju+BwZa4q9RGYLQtJSzdxFHpeVvu1yNrLmEBlRjkocGsYQi4SQNRvuNw3MTYloGxl0oUzib6arYJdqZiV0QUqQhbLmK4HLLmycaHO2ACZCAPuc+XhgsKVhCt1f04XbmbNdAGPVdDBJevvoA4h5O/M3xOwuNWI9dA9AAQfH8IJoeNuRl9fV3ZY9wbwyZg/V34ODBGebumi1p8Lbz+tOwHP9Ohj8THyHtYcQOzgBpcXa8izAsjTmSJAX9Y0jDkpcUBIqv457fAcB2kA0XWA1td7tvyx7zN45B3Qm1u6Nb5I/Dg8DNpWXUHxpnhdBd551vGdo+gyETU/rWMFc9Jz4BesH4RXwMcOEPyA4gBmBltxnQ5zqioga5gK9VQMIOVfaIHmssZ5BbqImL+djBGegQdxg5qPrueg6vsTIIDs9Cr6HbGE5fplTiv0trVaH7B7JKq+nR+o4CunLWggn5mlhPJQmgWLnf7g1R4TVpvTgUNPEEmrovMVtJPzT/kZAFetBytDljXzA0v3KKiBTtG/6IR/0EKXq0u6YuTz+xisuHe3nlbZFfUDvnrpMLKDsUTq+QH6MmC83Tk9ayenyWPaY6eFTCipON3dnXZ2kpUE4LnZI+SyGqsfPJt0RTb0sFQGDZSLmTqAJM0oudEPZbm2WYoJnsQyqO+0f+JHwKDLBvjMLYkd9CtUowqTJw3gnWjt9vGd9tS1TSHo4Jd/CkkgIoRv+qZvaorn++AHP9gZ6j3veU8AtJe+9KXtj/7oj8KS96pXvar96q/+alwjM+/73ve+cOv6P7l8Bf50/dd8zdeESxgXsa77u7/7u/ZZn/VZ7Td/8zfDWjj/e+KJJ5ri/eZ/1566XpXRM4sOpnawhJAiEDvcItWQ3l06eVrLsjFyS4jIHSy4AAohqd7AZdHDTXt2fhLB6q4Eg+Eiuc5iXsodzTg9K8vnSE5ruklGf1I/7fmccU3AoDAv4CaAQp1snfn92TNwArx1RVYDBAS5AmWtmYMrulkp8k7WAGst9/r3M7hyQcT9KHyAgAOSGYR1EF+W1Bkg+x74viHIXWHpWqy3AAgX2Mybz1z4Bx0VoEABM1Z/xwDri3YuK7NqG14sw968Qi+V8BKFr3EDVqFt0QIAwMGu7z3v9v0DJKBg3BLAfvszmJMfTBy0s1ZaD3etA7Z0gAIkRTjDxVm7c3Q7egNHUXQr9gsfQAOsmYMZFJ1bNeaDi8ebMZdO1+rRV5Z8jYUDmQOuGZywBmQCY5nr62X1Hn0skmH6F65JxRoWqPG1jO/Lzef7GO/Mli79MNPjoOu5ugZ54Tzhz/ffZ9qPMVWf2qT17G3rQDHpOUvMzPIA165b7uZx+Bi7VVgWNTJtS44GP9F6Tsm79C+33t7ao6D5rSx8r39yRxJu0AF/S2un/o5exrKob+XcVJdS0D8tgAlQBbLEYwKAmq0KQcu8gEXW5YsAYF8Hxe2eDiBNvDcuaD+ccVCCxpHl/N3nW3oBHUTnEGSknumgOe/fjTH5+/gdb4qu0/rjTocu5rF2WrfwkuSRDOdQ2z+tuYw1GwvgPxEA+H3f933tV37lV9qHPvSh9rKXvWxFyfgfv//7v9++5Eu+pOmnLHgCgO9///vbn//5n6/cI0vid37nd7Y3velNAQAFIt/97nf3az7ykY/Ee37rt36rfcVXfMVd77uXBfCpp57qAb4IfwnPiJVYVlaWsKGERxF9uGPLhausse6WVLEy2fNVG6viOS4UYFzWQJg4hG8VmEaJAapgyi5YymoHE4Z1pToLhJCoE6kzEcqLZzuTIiz5zAWs5o9yRdi5C9ldbChFmBoB7opf3zEGP9HyTtbNQZ4Lc99EV6rMLy2GZBSO4GzWgjExbt6zbqyMc1ZkLjzXjdNd+PNzfcy+dg5mOs1ZTTzGAODAonYv4DSvme/tyhrK6qPSIdXT12nM10y/iw4EAOMAE/UN00e17tkDgI+aktDHrMAdWPnv894AalFC0FKAyeh7PAoW+/sdVB2fnbbdbbl9LyIZREkh87hYOwfLTgvOL+vohvV1l+kK/VX9v/hM4LMqhTvwEsgTDGDOPpbumqXvd/W/Zixh+SuLEfLKLauK53NAFPcZ2KEDTMyzEksCvFjdUfYw6KVkIuVkugWtxqdrFUe9u0gLEYAPQB4AyVqLrcq7PFwCDJkj4IN9YT76e06ecpDO73gE4FWfz12HpEr8073Bs9tZs7XTPV1dYkPVaSetYC4noVWtVbToPD9vl/b35DsaNTlVaqm1dnx82pZhqTwL/RIyTX3EKxGROazQVCWYROhAZbl3eqg4PvSFj5215pm51mnNy0PaqOfIGiO39XPIIUropMcLnnKQOPM9YJT953mMhdhEyRuPU0Qu6HMZcDYA8J8AAPz+7//+9gu/8AvtN37jN9a6Y10paYMVNPrTP/3TTdnA/2+5gP2d+t2TQOR+RkhAcCJUCTKsQnEKq7gMgUFZE6LZdVn9UqALnCngN9u+BUArK9/dJ9xx4gzmbmqps9dOT0bMFYyFNS7+vsjeqTMgcuZ2RTIrLVycnDBhcASJnutgdFburhAR5KwtwhTlhjBHcLhQ8PE76OJ9LpgRfvN1oxG6xwINtxLrMJTKqrD25yHEHUDovZya+ckcHAy6YmIfdD3rOAtpWmZROJa1cCG+qhiTVhLwjvmxlz5P9nUdkO2Asix787rMynlYfytoXyqskm98Txn3DGwZA1Y6dwV1V2Ktse83NBD3h/t5tE0LHpBbsupzOu3xO8BAwPXs+ER1VeIQ5mCd9RXPeZsq3/+Zd6B91imVZh6a4FXG3hWeAGCrThFlxfc9ZO/n/e6HNyy0lfzBOsXP2g8SRVjTUMQF8hxsxRgJY6lxk/Dh32EV6/NXTHQVPvdYQayNgAWnY89avosWawx8PuhOrsZcy+QzaD1dooAwaBCgO9OAAHHcrzVQS0ZZ2XSQlhVuezESa6zQcLjj1dGHzko7+x1cIX9intXbXbHeAB6XT13GbSUoVCcd1SFUaZjdHbUOHG5jjens7KKdkOihpEHRVLmjAXG4sVkvp8sOVK1lIPwGTSbIk0U1AaMDYdaS9U0Zk8kiHueesmyURku6UkcrJbakpdYPdIwVOgYgY/12LwZjYO2QxYB7jUm/bwBg8cVnqgtYGynw9/M///Pt137t1yL+7//un9zAX/iFX9gTRUgC+Z3f+Z32ZV/2ZXG7fpdVz5NA3vzmN0cSCK5PBYi+4x3v+JSTQNRgOgJ0q9I7DKX3zowShFmNvncWe738i4RonBSrX2oWZR2WKbnbVDwTIU82YAimKsopABgC7TxBR1TNlw1mTQV3rbMXQ/VkAgcJfhp2RSCBJNGKEgc0ADRxgbpCRWnBpLwHIYhQ0nsCGFeclebqQBFh70oexeWKdRaqCBePpdQzVD5BWXYEOCcwGyVuEHj+PlckTp+aP5YKn7uvUwq7bI3mis2VhD5n/q7gHRC5hcUF6BzP4+vua7IO4LlCpaC17neLnwMtH5srWFeoXTifD/rl+3WAT2NAcfihwgEOe8GzZwDsYPuiNC57ipE96K2AofdODiVNbFYltigBBKB2eHA59hglk/RytwsSemaM6+bSrUK1IOw5ytD5yS2ErAUF5/U3c2APsQARH+g0y7oHPqpDKeOdLUYuA9g33h/jLatu55NKfoj7ytoH8A2lXXFsDv788MT6O0jBHd0bJk1WQGSKr/kMtpENjD2vZd9STnaApBjtOiAgwx2QBE9V4WzfswCLFLyv0BxiNiMuW678zhwZn8b6+nhDdwjxCRTJWLC7iLIwe7ujzqu6hAhEKgUj+gBHV6d8JusBGOyJIOqGo3CMHpoxKkPMYNQPglqnUcJrJHTR3YVGBsgXCnuTSAOIS7mWxfKRSw7kfI3ZJz9kzjKLMTv/+zzivVXv8vj0pD35+BMbC+Bncgzg937v97af/dmfjeQMr/2nEi8KCv3rv/7r9jM/8zPt67/+69vDDz8c5WFUtkXf/d7v/V4HXEoMUUwfLl6VgXnFK17Ry8DIDKznv/a1r20Cgn/5l38ZZWAee+yxT7kMjACggsVFaGJWESknS0CWJxVIcASAU1gP9aOqdc9ZtcuS5VDlJ2TZlPtJBT71TC/cS0IHjMRPXY+g5ZSJEkJJO1By8OQgDCCjBBesUQgXAUABUgSYAxCKgWoMzvgoHRfsDp5Q6i4QHVT4OFE2zvjrnuXJKzMQ4nrFsF2cqbbaiJMhdmRWIlhsugKOxBDrjRzAYZQzYE5DMOYJ+vQ0s/hyH9I6MSeBOPBkrLMSdwuGC0oHep0uAlAjeFe7l2gcgJqIRYvAfuqdpSJCUHf9NRUjdjqEvjoQq37AutfnBX343jF29h7apSwICna+Z77PXXsODFCOboFkXA5+HHCqBiD057UAna/ncWF98XVx2udz1orxs9bwuoNyB34+J1fWrHnE7lmdxj6fas0X87c6pf6MDhBl4cJtT6ybFTqOsfbEn+r8U9fFvlVNQAddnpUMPfscWQcOUytARMWs5Xbs7QWzJ7rT++CV0ZXH5Z/vK2EVLg/7+8pN2unqPA/v+gevAYD7/AQcySy+GGDQwaXu99i6fq/FALoclitcbmAduXd35vqOrZ2cnlkXkFwfZG9YIytJJ4CRQK3FaDrIgr+pxacxcPhmvi5jWFPNB94c8jaTwIjB9KSalI+5S+y/y3yNyQ9wUTP3zp2VOcEj8Bz3uwWxH64KqN+8eXNTBqaY4zM2CcQVqwv4n/qpnwqA9rd/+7ftW7/1WyP5QxuqLNxv+IZviCxgFXPm37PPPntXIeh3vetddxWCVpyhCkE/9NBD7Xu+53sCAN5rDLPCcRfwlQeyFRxZebq2u9dKKER5F53qZK6vJBAEn+4NsFju3pUYPcUqmVsDJoRBAWeMe3Zr+Hzmk5IrYILQEVAwtQvXjPJJ4KJnCaDK8uBWAt4/Azo/8Tnj6l4K8OJ6wILI+iBsVoB077CRO9PjKGuj/P0uGAC2w7pSbfs0syhcLMFUJ2qyLc09gvsVesj1Tbf33t5BCEPvC8z6oVjYg8w4vgh3pMqlkOHI2rDGruhd6CYgSVe+QL/qRfqYOiAJpSkFstq9BEHLuBxw8U5ZFkJ5VdwYCR8+Jlfe7IHHdSmGjlIRzKkLZ9srFKuvkyt/vndlzmczb7Lm/rlbGyPMVgq9MiGdPrSu1LHU56oH6JYdWQABgw4G/Bn6fdR1SysTc0F5OQD1PV+lq3UzG8lcZAdT8gnQFXsiN2BZpNkjX3esf/CJrnGQ70qZUSAvsLIEvxJrtrMIyxJuUGQh7xR40ru6JfQsrWG4v2c6d6U+g+AOssyChnwZ65eJIA74HHRDI5HZXfGG+mymuXiXJXVAfxxkSKhwEBjPrthqYjYJu3HZx/75+uqzfthQceiL1nYWW+Gl2N4acati6pPjs7YtV+vFMg6V0hN+SGWMvc2fkGT1iOaAonfPeij28Ew6SYf4u9t4Iu90eMUy7YDdjRN8DzANS2Ul0bhr2fcUL4YDRKfhUXA6ecHpNmTQziJ0sX4GmLxo7ejoZnvqqU0dwNjvz1QX8Hpx95n5qQNACfvRezDrb4lgIwZQClAB2pX1q3gigSgHcmL6riAuxikuKsjv74Sp3wXZbE2D0V2ZO1O7u9BP3TClKwE+008PvE2hdhbdS/SdX4fQQaB3YWhlY/jMq+IjkFGQDkhd0c8nT4QFc9R7Uaj6TM9xAMtz+Q4QSAKIPpfVS0BHcSrHx7dXXPq+PutAzFAsCXZ8jV3gD/CXNO2Kn3e41TJoqLq1BPiNllCqr0fmbiq4syoOTFxb33tZY3TgkDWj4oTinYpjUsB2YcYARKUIOH2nC3gE1DNeX3sHbf59KNJ6dq5Flh3x650+A2RWPJXTBDTjBxcUjbtEGbuvqSt7FE5X2uLHstavoy09R+stnj66daPaNZ5FgeMrl7OG2Lx3K+BqTQszeMQPSwAO5gfPcSB00DrPJ+Zc5WEi3MO6ZsyAk/kz7jikaf5lUUPC6joOgtAh9zA/59X4vcpapWJJCxPygX1lzk4juHPj3WWJlLURIOp7zjvZZweLDgxw8/sBxJMMkGdOL97bGBmi5+O9CZotq6YDDVzDPifGBU25HOz714anQRUbSJpTeaGgT7PyZfbuMuoBHu7tBo6T25V1VeKHIkR1X7iBqw6gAydoaq4H6YCZcc58JC9FNCOwNqJ+qIB+oRus7tA6xgA3Suhd8CGHcC+14+DXacBp12kd2sVFrbFE4wWVvqnuXFrjm5+80Z5+etMKLvnUd58V3Pz8lFYAAKj2dX6K9QBc2iM5g0VcTMWYYNmT5W9bgd6KtpLLJaqjV9DyebZ+oj/wrIBRFh5w6wISIOVmdRfq/M7kZ2HgQm1Wvgh2V8YIUZSXC0F/B/NwIYJSRaA4SHalNltsEAirwJC+q5ml5nGJWPhkIfAMX81DRU/1b1hE01LHPLhXc5cFVO6JUBJWIseVta811toulCerHcKRdyEM4/PI8lRUZ1o2AG0r4KgsFQhgijMn6FstmOv1/DTGcYLPEhOc/H3/XBHMyiL+LrCpOpYCgAh4B0usB5+RkOGfO5jSdaovGLXFKnbJQbjuG6DVyo8UsbF3DmC6FaoUG+5WFJXmGeEXiyzZgWVa16nEkvO70zl74fvoQMFpxOfA+N2yxtoxP7ekOH3pHt4Ra3WRoRnOX+yh8wk8xrvXKW14jmvrmumwAAAgAElEQVSYlyetOB24Yp4Bsa+TeGZ/d29kH5MAUAkrvlf9EFAgzOPXWJtV16O6aiSYoiWZj5HfY247lVxjdAUdQiMdvCqZqGImZ0CNjNW9gJku16zunwMhkkFCJpy3trNbpVIs+SYP2XHaixjAA2UCV9yixiXZFYls24uoA4je6HHIGnMdruIQfDqSErt+qaQRDsmyhkILlHVh3PP+Mwb2XdfxGWAZ+hztK3PNdc98iOPg7u0D/TnzPrrHQcmTqpco0EpmOpnxwQtnp+0tb3l8EwO4AYCfEs6758VzJxCEokAfAjqIv+JgRKBy7SqGSC7PXbX6EfMF+FPLtyzxQOaZYgBnoOYASsS+ZXWPsP7NVkCYE+WDQHNl5CdbBAbvmq1Zs2Jx0OXgcVa8PA9h4mcQfucerC8OOHiPKz9PXnGwmHPImEkJBJ/rqmUhTV+5JqMMDODEN5+kCK7zMfqauhKc1wDLCO+cAZXvb44hgV9Y9iqeS4pA350uM95U/1CuWN0Yg6+rnpPXZ7FrrY+y8NjvofAU55SucAd/vhY+bt9HubITqJ4HWGNsDmJcoIfyk1WjslGhd1cQ+v2kEkgAgMzXxzFbffvcZV0qa9+8N9zPvrCPAD61f0NRshb7e1kw2vmDd0GP/D1bPqArtwLOnznPO4hakQUq9l41DFGkGpPHtGFZ8jmx1+sOKPoO2eHyYAUwVacR1s0te84D0L3zJG69GEMlWHCPA1P21sM9AMOUmfG1cCCTY80Ys5x/9nYmvjfGpVp6krdm1epyi0zpinsE2PG9h5mwlnpOxD1XL2TGxrrJexPhAKq+UOvnB5YAO9k7sfMi78tYRxnwt8MFrDIwaZXLsII41G4v2vGpQP926BD3BnkJH/aEtfc19wPEvJ6aHx4tl2d9ftG8oIB00STVCZCZSVdUpxgyl3chJ9xCOx+sCKlgftybY08wLH2qv7Vei52dCN8I6/J51mJULd9NGZiNBfAFQYAAQJmVlQRydHQUjBJEXPWwINIewN5G3actBQnL8qKwjCgHoeQQufQywcJbGYlZ47OKRYvnhlVwFDpFIXQhvjPqC+qEOYp0Tu7nOiEiuGDy+XTmjIeigWHnd3cBVrGCDk4dFGje3mcYoXI3mBttq1C+Dn4Yc2bXVmeC6iHqz2KcCBeACePT324RnBWTA1x/rgM31knfeywMtKCfWEldiQNwfa10nXp8ss6pkEbJmri2wM1YgxwN63AXiJD7V43jqyyHKywy9IjxyVZuaT3MtRpjcRAGYBqfpbKLjNsSyg4UfXx+QPE9dQXAGPW9gxzm6IAG5ejzmgGNvmPtdT38yd7pPaLL23fS+ueKj4K+fiChlpvqujno8zGgSIkNnoWQzyHlwSgPA5322KjK8OeemHMlEcBDzNHXyA9zvr5z/Gw8oxIt4h3lovUDwTowGd9b5i9xiIxBbudIpKiyMF5qxtcD3uJ9Aldh+SuXtaxUHFjcUpe/55N0rw7a2g8Hgb4+PofOt/BFdSqJta0QiWifVy33XBYAFJlD0GjV/xPw07NpGeh74HSt5yEX5L7EAxFxeKLH6Kiy1fb2MiYveSiTQCKRLWggk8z6HKckIApMB/C2fQL8s+4u+532nXaZs1uvqcGHrAPgw7PsFbTJM/jen8/v8I3LEZfLMV/FIgpce6eqaG2a1kDR3cnJnXbt2lMbALixAM6i9/7+BgCSBYxi5zTlQACGoKZUVnlXY3cdhc8zWPXsoh3sp3Uw3HMFFDwWB8JHgYaSrVMX70UxwTA6WerZKBQHLq4Y/TQGo8KgCEpO5TAnwsyVF8wNUyPk/F3uznJmZidciSPM+GwGSq6UBFDy2aPenebrp30HXb7zer6DGl/rIXCrN2cBxVmBOJDk2f4chDxz4H4Ha6yXrynAx/ch1rNi/HxNuN+BH/MKMFNxRQG+KZFSpUDmOfe4QWK0whWeMUz+/BmAjXVdrsQCQlcOSrg31y7LRDjomoEjCsnpwYHQOpDD/us7tyy5wuYgwlqq8sCzn/h4px0UnWK11oFaxjNbU6BP3yM/gDAfeNrpWeOd6aeDva2d3u+be2Y6dyXa5YEF/cOT8D77orHguYj1rCLTKHTnU8bH2nrXCW+JFmNRUW25XSv+MOZS1jbolmcHkLaQBoEX5IbLPAcgua6jzAju0pShGdMaYRSW1MW+6WfUrquMdd4Xz48OHCNcxPeEZ3EIiuurFzt76nuLjOC9VE2AbsMiqHifCsuQgUAHMemJS5cOuyVN3yvx4+w8WzDqeaoWwXOCFmrcIUO9pmHFEMecBaYFagtEMj6XbegZPygwXz3bjQPojFmf8Dny3GWffp9rFeqz2f0L38Az8b2WiiLiZXDQdb17yHbWbrxxYxMD2HXSJgbw/kCf3+UAUKVSIOxgdinmCogmbkQnLirci5EUY3RaJUTOFTOlDK5yB4eykEs4FG22+HHF51YQPu+nZvyAZo1QHlvJlD5OV8KeeOAWjLAqVF9hGFrf057OlTcCK9wSa+pbuWKGuWlD5GvnYMtPpq7wuT6FfzZxz/lQuiT/ZswINRdgAEMHbQAtFN2sXBzUOZiZQceskGcQ44LMacrBAAqRObjS8e/mZ0EHPnZXRDHHnt1LhurILCVhJNbPuhowB8rerANaTg+MI34uBTy3Agz6ocGBcOzN7l4qk7LCMIfZ8sD8RYvE70Fz0DXPhlY0Nj/8+PcOPvwQoCB93RcWwpZWQQpCc78runkv/W8HZ3zugGodKOygsYoHA3xivEoqm5I/nO5ckc9rMFspXdn7+gFA/YCi33Ev45qN5I1FWp8c8M7ggHHE4UNu0eqQQaFlaJx9DXAly5d1OsFq6ECD/YN/sfoR4uCgS3JW12EpmwFPPIs6gGX5o6hxjKeCbyUb3auCxRTQ6vKaebkcoIUnWcI+nzhERI1K1XJtbXd7K4pAkzUL6BQvCgCGzBWQqyQQdJAfRmJfrB0foJ4GBXONxXVWYXfjQ0McLKBNaMZlDnPz0kzc7zQ2P8PlA/xNggfrKx2qNdrZrS4o1faUfcXdr7hTde3auIA3LuBPH/1NnUAiYNwKF4t5egHWypLTiVp9GgP8UB+rWrylG1g8rIzfvCYKLUcm4iKUDsAKheMK3hkFxohnRIyhPDjpHlgBd5XYMANIP11H4dLqQQpDI8wkDJhzlj4ZmcwoFASzAyp+Z8w+JpSHjwGLjVsl2cAce2bKpTKhTtcosuzj8rXjGQ4UEVS4jlxpz+DBQVhX1OV/imQB9ZCtrgBzZq8+96Sd2TXi4NzBiSty3+d5bVgXEkXuBqDpoqUuLW6zANnVOSPmS4uwWqzc16xb6GNkT32NfH0E6Ci9gjvb1z2ujXIx5fo0C4WP3X+flbgrnHuBasYHnQEC1OZN4xItQtP6TDGA+jyAX4FmBdqjtOaxzXR/L0GzwqOWYMTzZnqi4LPzIG3EYs+mZ/hhQb876OYZgAM9J+h+J60wADMOesQ2r5ub7gtX5clpL5UDPzsQdFDtn3fAV/IQq5LTFu8Nq3CBQdbf66LmdRTlTpco8XK8J+XK6NcOPbhMCtBabl72z9eT9WaePSFIlrh20S1PDkpdDq7b41l2Bg2GZTQBoMf/Oe2JFwUAtQ4KFaF9KMW2Vw5hogNLdqG4NmXJ6GM/H+wcRGoPghcq49wtyPxONQzJbQ4LzM/3weUaa7KOL+DzDj4XGVcvWS+AL0PJDOLVUKGHS5Rwk0zfdAJJit5kAb8AENAtgDtK0ReryspRwe9B7FV0kzZIIeAWe/F2EamIV6b9PNGZyVv1u85Pqq5gnucU5+AKB6GFQHLrgO6AcVGqcVqv56woZwvg9dIpnPK7gJsAI4wJ880MjeJxcOMAxq9HyM+ggrHz/b3AwKzwVfpBAeAIJYS1u8RYN4RTCP7qizkrLAcrzDszbAUYshAqBVR5JwAdhecKAUEaB4WpRtzqXBTvl2DWT8cISoDY/I50pWbgNYkkQROigLJqrILCKutjLd50vyyFsj5kYehyRRFfGHFYdVipfsqxT6ozFmVpEtCJduVqdosBax+UHQ3vsxi3fhdY1Pd6t373ufm+uKVqnYKdacX3medwqJoVPZYKVz4zaJyfh3IDvLFnzp/+He/EguLgdAbH/Zoq9wONMT7Fmzk/OQ3NdeX8unhndQvSdVoPLwSMjIFvWTfkC+Pk+7j3NMvlMH+XNTMA0N9uFWJ9vIZggFPrKzzzpoOzbP2WgBb6ZxxKmtsOi3HKW+bWQUwdOvr1axJ93Grl8iOeVwd9581V4ImcT/pmHjP4Q9bFzwi/lJxREehF299Pq+meQHcl/UQruNPknQBDVftO82PdoB8srSFL1JGlinijqwCIdM9w3nMZKoOHy2rfH2gP/aFn+CFf97nl1MF3X1OqZFAeymIwc+0ijiFa5AWfzyWQqnWdy2DVDVbFjo0FcAMAXwD4N3oBKwZQnUiiDtHhQTs9PlmpZRVEXcWgg1jVADz8ulUPsJ9WhrIjm0kWvDxFFXNbFp4m4QLarWwwrn7KEqWTfQjiMvlEyZk6vTsjA4D8RAVTOiPjgnbhjDJCOeDmXqdkuRZB4GNgXgjP+XSIgIW5/fuxJgl+JHhwMyNY1yna2YLmoFm/I0DdeqAsXOrxdQFb1pgAS8pCq3V38Id10McdYKta/blCy6SLUSjbBWnswd5uFv+qunQjw9czcLfDkhfzVvB9FZ4WqOO9cTiwCvyMjbXSPHWN7ok9VzB8gMXhek9FlqVg9A7Pmqboss/T35HjFzhdVvawwKd+H5nwgGasdtzv67UKakfHhvmA4EraQU0A0nJLQl+sgbuhuc75DBqeeRJl7yAToMM4/DvAFJaYoOnqASzZ4YCxZ44GP4/DBEqWuCqfL7zNTxS187mvLTzlz5gBswOFlFeZpME/rFb+LOd538O4trKEkS8Ollzm5DjT8p/jz+LoScvqC2wxlAUUOJjoO9Y49rg6f/hnXANI9MNuzHmZMpv5R69ggTNlpFbPXL5zoLfuoImXQNf3EJ+Ie9yKRMHD3d2eACYAeFHgeWtrpx2fnIQFPURBJX74HnJ4ZJ0F/IhHp5e1dBR9joOGxceWUMeY3II/gzf2nf1CXs0g1/cQemdNYv5Vx09Wu/CuyRMR/ZhzrUM+l/5Tggwl8CX15EVTSJXTs8a5sQAOKbixAL4AEBALoFLLFQOIEoVpEITBiJVFSVN3FMgsWHRKDcudhAs9JVX/TKnti91gdD9twQwIOk+8mIV0oYSo0Ktx6GSp+AkY2oU4wmN+LsJutm4BXgIkKJargKq7j2BIwAoKXX8787vSQukgFBE4CJQBzLy6PPE92ZbNQcFQ0js9gYL361q3UgFOZYnSMwSCFHMTLtIqv6LOIQhXxgpgQAjyTt3jgGsel4Nu6CNi9dQnuhI+Yt4l7eb9Yj0Brx3Q7Sg2plrdnZ91ixvP8WcPIDlKwLgipdA0sYEJBIcLErd2358oT1HdFSr7mPZQ0Iq78DVm1TMjYzJcx5MlxsG6g655vV0BwBcOJPwg4IeJWXFCH/zEss7z+dst3TpoicdQbiRizeBrFkMzkHIAxbMYn1y20U5SlnkVkidWV+8uJRljKxcvYNEPb/BTrGNd5zFp7B383IGOFYmfQawDVx//zMvwg8vCUPJ1WCZeze/r6zm1Y2MvoS0HoSljyahOENFBtLWtAxzpJ3sKwCMLOORAhSowfpfBxNUxbwfNrB1WVuQkzyFWjaLT8Yyl2oGqAPRWUyfhvT3qFra22N0NWSuL5vkyrfTEeYervEBczKuKc5OgE+MS4LVyPC6PoFMO0Kl/MvY79EX2g+pAlW4q6w5BM40DjNlL15PwkH4iA0J3VhgS+xwVMooG/JCQlTN0CBilcgDxmySQDQB8AWDfeMQoA3M93A5RaqDiE0SUMHgn+CrE6/X9sM71ExMZvXGKqbIvCDtlfZ2lcoQRULTzCQ9FPgvZYIxwHSQjR/HMqoflgsyVDZ8zc5Slt7ry9wMoXQg6Qzrw0/gdIPnJcAj1UbLDQa1+90DlAcAycQYg1AFIvSv64UqoVNcBVx6p1NMtdXCw14OrdW2W6korF4KqSjWWyylHt9Jxg+y0yrx0IAJAc6uCz09jcTDk4EpjVlyQxhFhBWVx8XXuAlbxMgUaHaxRtFnPmgU3QD8/z+81HtFe0LOEvyx0shxahxG3duj90LfumQs+O43F86M7ybCoxL5EZ5a0qDjggm6gf3ftO0hZR4N8Bu0Ayn3tUIaAGYCSgyfGAJAl9inmYslTQX+LFt18ZhciNOAWMweBvN+VHDwti18HmVkoEgLsLlBADSDLD1AO3OY18HHqXoAAY0MmILfgMeiIQ6oDIP+MvWR+fEcYTcw3in+PRK5VmhwtwBzUc+DjM9YKmZXjzDhh9hhwx5x5j4M9umjEWlDXtXia6+OhlU0Pbc887vLNadPpTWuid9BFSs9Q5RyNWmOUXDpXzF+VJ6qOehEyIRewxqr5sobxczctsiq+TWyedBUAl/Xww2wAsKlvMN8HvVZYiJ4h2peFDd3k9BL8WyEB0I0n8jjYdHoiNIDQKNZLnisAoOsdvf/wYK8nhQH8oEElgchbt3EBb1zAA8V9Gr95IWiSQCKwVr0by/2nz4+PFR+2SIYWSJS7xkBXBxNWUHN/rxjV6v1hYXTr2wxyutKv5yNYXPjGNTrD4ZauFnUo01DWVbuN5VmxFFiXAT7vzGkZgnqet1PypAcUiVtzHDwwFhQYisLXzUEAglbzRJl6CyMUDpmoKCpXBBlrR5xlFg4dIFc+0Gwvxzix3jpwpgAy73NFoM/cfenCtivACliO6xY7Ua8PaxvPEi3duXPSY+VcKeuadJ2mlVKWDwe7AoDM2WO9XInNYx8FXC/anVtH7caNj7Z/91X/oj1/QzGWspquuqF9Hx1Yahwh4Ks2IPundVChZ7XgQwFA14o/5HeuX1G41g8aWo93Vus7wC3KgGe5omE94Ct+utULegRIdUVeSVJ9LjL6mbUCGoE/Ongj+7UAr1sPAVP+TFn3Ts+Oe/xwB1wXZ2EFlDVQz54tsLzX+YzPADwOLt06w5q5ddT3FrqfPRIO7ly88mz/3t2lHayd5sHXgbADTI0LubAqR5QZnRb5Dq4m+mDOyUsVl9odiIrKWYa7EV5z+QDdOaijdIqS+xQGBLgC1PAzxlkWVh0OWHPmAZ2SYMF+EZO3u7MddQB3hQQVx101OQO463C6bO3O6Ulv08m4keNejsfXhxhAZJHLe31G1Qr2rAO4siqG29ra9+EJmvUHCSdzpjE0K+Cof4BIxiHr5q6+K29YX9eKW+/vKT7yfurzHmpNN4Wgc2U3LmCXTPf5e08CefqpnvkVzBVWotGEXG2JZHHjFKmAba955GAEopUgC2VTADDqBdYJ0K/H+uMKzU/ELuQ7428tFX4YXUQQyjA2Cm52c8F4rjz8VM3nDtiwyqxTqL7kKG7d61aZLsStfIfmBsBzZUUSRgpGSlGM6vPUrjtdnpYVL2OGlOkpkB4CczuDiwVQBLJcmAE8XSFwskQBHp8pE3orkib4jvG4hQfhDxhkXxwchpLpfXwzpoln9ljBiD8aBWG5R+90i1/Pniu34Kw8fW4IVBf4eod6jh4f32r/5z/8Tfuf/6f/tanqkUoWvebVX9m+5Ev/g3brdnVcqEbzKHCeA806IITWMilluGxWLTqr3USSTisphj7GxSsD+CuBRP2SR8Fz3su4sCjqzT3eCre+dWtwnmPdoAH/22mV/XR6duAUYLLKulAKxIFCjJWuEHIjb1XXEbJ1CxzFgUL0bEH2zu++z8yfcawo8im5q4Nbi2fFojMnhDmoWwcIO6CwAsrzGJ2nQm7WAcH3zGVE8kFaikfsX8YCch1ylDEJWLnMTdmUoKO7nMsqiBXS91m/M3eNq7eANOt3b19mySSz7PN9dvnl9APd4AJVnT4Z6w52BFi3o6Bxypzqea5DorwWKrVkCTDwEXF06IrguwK9rLWDbddddNEA/MIPcTipZgdhScQocJbuVwp2e79nnoG8QccwLmLFM7s3w176PaYHkSnIXQf1tIJjPUlq1DV37hy169c3vYBjrzZ1AB2C3N/v3QJ4/Vqc/qj7R9sZ6vxRoTxq8UkxLdK6J6JEmTtjyfW7ty/QWD09u8Wt+rOW0lLvSBQIQjtUacU/OGM5s/VraQdmLZHmlYAB3SoEszNmgIszOCd7t7yg8F3YwOgOZLnO3zMLD+JoeLfHProSIHxsKOtUEhlMnO5nrY2EJEHYKPDVOWcvWj+5I1x8PhFKFetalfkLuDswlqAW4FH8oJ636kodBwcUIN9rrmoDl4kosvRllmwkcxQ44AQMDVDvb95XvndgwLoxf33XW8UtL9rR8VH779793wbNXbmiLhmyeqhUUUQStP/sP/3P2+7BQ215qvGNTEfeHQC13NVYPMa+ZG/jYQnLhJVQatEhx7sfJF9g5XR60e8O/rpiKlciNJtzk+lsO97jYJ7EHVcsfM8azX87rQIc4DkUHvcGze2oRFOCW9aAtWEN3GoPkOm0WXF+8575fGewF9bI07Oe7MC1cxgF78ACinUIHmQsPnb2gDVzwOC84NZCP2wQi8YBD95zaxXvS5lRaaEd8Fgdy4nY6bCUXYKSdqgXivvXx+vzYg3cktsBUnUKgZbkZpVFjfZr0LvLE5eZPNsPBz5f/R7JGi1llHhfkSusZ4zpYtlOT84ifOIsPDc5u5Ar5XYV7xBf2HnbCnvTHYRC0YMn0+UsmmHOTgt0h4mYSAU91MFb7wo6qFq4Ts8e98g4Y52su4r4ImPhs22lDBVBFxUb7wfnAKLmqcnZj+5YMZdyY4uvr127tnEBbwDgrA7v728A4ONPPtYuX77aywCQPZVCI0+rGTJbsVbVScGVEcIirANliUC4D3dIFjqmJZyCtcP9Y+Zw3UMMHkILZQ94gYF0cIuivgoml+ukykEoAcWVFs/nOVJewewV5I4gXwcmXJj4726xdAGIIgE4jlPhdo8ziTUyV6lbFBAqfN+tZdYz1/cFoTWAx6AFhB2fAFpcSDPnIdgrE7Yq26PwVkGien6mCSisOFV6JrOWFditouASehV7VYJcAuxAsTxtKxJSVPdLMXICMSpHk8K11FtZd2OXrIQGGchYwBzksD9DGY7Yvwg2P7vd3v2uH48XPPLobtteXLTbN/fa1vZZuKS1xMcnrV2//lh77kZmQXrCilvdYu70XVVXiJ0sbwGwCiB7kWAuC31jAdWcsXquuvsoVRN7Yb1eARPwmAMrahMCPBzcONjDIscY5ZL1f9DksD6Pb+E76Cfgh3Izlum2Zc7QvPY5AGIdHuL74s0uE4oH3SoFcHFgBY3FO41nHOQ7X8LjfmBBaXvIgObp9QLn8I4ZKLsM8VJTuFDncSJ/GHeOK7OK4cv8OSonRNsvyzwe65pu04j9rcoAASwqe1dAhQPkLOuQR1zLM+8Vs+kyu1v4VJ8v6HjsN7LZgf1aOdi22p7qwCoOcFvZwGn1Azxq7MtzHZQuwluUc0z+8D2cwWgH5YpsqZjGoAnr+NPXr8JJ/Lk9qdGKS8f1FVcY46sErgh7uhjdQpCZ8EXI6Mrc1rgC+Mq1vTyNuFnoLKx76pJi3jDq3MbheF9x8+jP0as7jC7bi2jVqratmxjAjQXw/hDfdBcAUKcKZQEHYYtJqyYUhO7CLASKTPeVnRot4VTDq0oUhPKSYCtlGMRe5TVKtfdR6MR3r5P2LNRDGAH01IJOVj+1yFEiSKT7V/p8CVB9L8YUU0XHgVIeLtgRQg7IcPu6YnPFpM9RKLOw9XVyMAlYdKsAv/PsWXGjqFH2WFtRNAE4IkM1kw+Wp5kUg9BDIbiwciCIEuL5cd0i3Zik4rE+3MezYw2UsedlIiqOJgAhxVoL6BC3h4LQu3BpSSkMAJmCv/8d2crZFi9IsyvRUUpE72N92TvWCEtmgHChsfOj9s4ffXdlnbZ2eKDq+4ftYnmnnZyoDZVqW+Zsd/cX7Xtf9/oAYj5v/Q6ojwujVdVOxK6hEHINRyHvcIVXbCY1Ap0OZ4Xnz4E2AV8OjqA3V7yMlTitiNdVeZXlVvJPzU8AjkOQ72PQTV2H1WQdiCBJBPrq4Gx5mu+KBvfpdoyxX2C5yvV1i9RsVcP6zr3Mzw80HfxYLKIDK+cv1tN5jHdCMz6Pmfd5lvO7ZA516HyP/KAE2BtjSUuY7/06OcN9AE2XXckDWA/zABbPq8x+AIjTLPwxy6c+n+pRPO9zB1nny0jCYNz9EFFhQn4Yptcwax4xgC3DXkT7AoDIqQgpWmYN0ugFXL2BXSaRrRvzZto6OBZQ4z2MwVuVUs8WMCfPFgkdThOx3sXnvDtipRfbPWPaD81OR7v7e+MQXN1e5AqIjieL3d7IAHqNUmv7++HOD/4q4cp+DXA8ksZYd92zAYC5YBsX8ATm7ufPYQF8IogSS10Qu9VQmgVgnHYqXiWZWIBwK0AfgAbwEIxbmZiyIiZwrFMe5hUCna1jh+7zAqvMTwyMYOxCO8qfqJBsgpKI7aBWoeIFy1JBeYi5FhmABGDHfONURtZoWSnnU+66dXewFiBU2WgFVFDgDqr0Oy5hrkMg8Cy9158b0TIVaxSAa5mxKw4KWB8AEQJen3fFXL/zXuYn16WKH/vnsnjJYiHQxj5rjRBQLiQRyLo+Ck5XuIAr/1BWZOJ5ViOJBW0Uj8YC4BZJ9slj55hrCty0Tt46er615XH73z74v7Q//ZMPx9gffelBlJ/Q65977qxdunLRHnrR5Xbzxnm4hl//hn/dbt3OOomAFf0kDqtbXBdZ/zDXdpSegRbpDYzLjrIwTkceRjGDBs0x9jpStweAWNmXC5Xa2G/KEhzrPor2Rpxd9XYVL6D8uoWn1r6DEbm/i2f8kMR6B09PWcJ+r6we0FenCfGhdfvQoYi/8i8AACAASURBVDHmtsxadw6KuGemZ+dLLIfst18LbfJznXWvA4ayrPMcFDTv8us6+LY+tytrYjGHgxeq7qTAQFkA4UNAsgNIlyfQyCxzqBOoawVCsWY6TbhVLMZIaRriBK0Hu6xLkSxRre2Ie8OtSWmbcOfKu1LuV9bXD+u9bWgd5PZ2VAImrZxyAe/sZuZ/ZEjLcnmaJ5J0AVMNb7jDNS49Iw4rFasXoLJKwPihkvFQQobkjjgYKFylDqlzkowf0L1sDvOFbkOeloXRaUy/B72fqZxNGkCo8Re6zyyn3c3M+kcsZ8YM+j6HMbPkOTJT8d6bLODkkA0AXIc8PsXPAIBveVwu4MvdFYsSEkGHkDFLD6fsIbQy0cMZUQwQRN+WUafvoOIB5TWECVMhpotOgDLeKYVNaY6Kt5KiCMa7UDmNTJHvLlNiC1UjbnsnQCiFVPU8meDl6nLLAADJ3WiAC07PXCPFLMUKyOEUh7JyAe1WQQeS/mwHJygOF/6M060bKXyyh2YozHK3AijYcn0X7saI68leubFvgIcS/Lw3xlVJGrwPIYRrU89CuK9zDbJOoXhKwYQyIkOggK2Eu1s6EKgx93ItKQElTsT1zliLGF+Czag7HvXPMl6I+n2sqQPrAaKzxMzZ+VH78Xe+ux0eLNrtOxK0rb3oIVnuWrtz+6IdHy/aS15y2A4OF+0jH36uybD6xje+OcCuCjuz3wHSBYrLaokSSLeduhaI/oidzFIzWP+wmghQAsxZE83VQaBbatgvVzgO7LFGOPADoMnaF2u6fRGuJVc03iIx9qFcutT/S75MICiLoA5N0DLPj/uqdp9bgRzo9efi1qtDn9M4e4eccZ5wVy2gyhUlLlM/BDiwclcnQHNeqxXZVQc9ZCD81enXekHH2ppHoANEC/HItRgxmtCShy74fkPPJGT4gY7vch6jlieA3ulqpgtZ8ERjWi+VUsGlq3sEsAS0eleN6onMes3PhxZ9voAUl5X6TAkgUegaAChLYBWGj3WPklaL6ASyzrIpoIdV0TtUuapz8M+YNT+9O+RlZUV3gDi5mKWTogNW7aeXeHEZ31ujVniKnsf+CERjTZahw9eB8WVproMEMBYKoBjB7kGrseVFo8uWnqc4700v4A0A/BRh3r0v74Wgrz0ZVioJJQSTwB9BsGG+twLJgMJQ0t01N8CCmD2yfiNVV2ow/ylW7+ROtjfLGJYCNfUMAUA/YcFcAeIi4SEtLF2Am8UxLBLJVv3kNM6TqQhxiyJIUTQOiu6lMLACoYS41zPzAoRVEekOUsvyh9sDoenCkwQO3SMrDvXYBrjLrgA+BqyTur7v2dZ229/JbEG6ZNCJAuXgikfjdesIABSQqXsoJo3y1/2yDrKrruxRknym5+DOS8C5qrT0fGUGKiZ0xDTlmOJZCkeokkOsRbb/DXtWlF5B2fc1KJrQeon2bh3daIvlUfuJd7+/LFApV69cbe3mzdZe8cqr7e///ka7c5RS+ZFHHmqvefWXt1f9e/9+gE1ACbSYP9OKEW4eWWErazLXLQ8cUnoCrwK2EUNkQMFBIIBgBlAoEE8e4VoHnjMNd5CwSHc2QK6X8KjDmkCdLHWuFEnskFUu9vnkvF26dKmXBgEIRIxfuXhRuDNY8L2P+EP2UZ1SCmQ5sAAQolRRxswP3mUNHIyipOeD17qxca1LRf9M6wXNzha6oOsSKlzjoFQ0x3iJkc19LaVVVnxAK3zi76d6Aq3BJEujv3pZmQNUVRxZPpuuIaNriVus3W06rJKZRYvbMw6+vVNFZsfC+1jrkLthBa9+8C4LuR5Zyt6GSN9ubbdcwDFXALHiwZcZ3hEtRe1fPyDUWIIequizLkNOE9cZFr6qvRj3KpyFsJQ6dEFT7DE8t3JgqXZ4/V3l7XDPk+sLNy5grJhpbGV/C+CFjqwEPj1DABi+0FqFLBGfqN1qJTkqBvBtb3vbJgZwYwF8YTDgnAU8rEsJtPqJPOo0jYD1EBh1CpU8jBIme4uwFog5lN0bHVEFiKjJV/Fbnemi7XARevQ9VGHO6rpQsRQhPHbqZEWRXbVMqnp3EpJhEdzZ6qc9ibWIN5IL2JgsBJiVi2Ac/PSTHtYuBzQBYMtV5YIU4aGfrJ8rQwQHOzaDJBTeAHupYYiR68qtMmUpEJ2nSoGhi4gF1PWZcVrW2GjEnidRFJBbCHSdC0L22xU3ChBh3KvoW9Z1PL+KtAqUBXBQkddTuc93QlDjsj8pF6bey/vHO/IwEEVTo99vAigUfnQvKTd30FW0zxyHAdaV9QwwsLPVnv/Es+39P/mT7fLlnXb7Ttac07/P/RcPtlu3brVLBzvt8Mql9n/878+2hx+51I7vnLfve91/2Y5PKxYyElSSF6hniOKNtdaaR0BdxvzFftRBBUXBugMMiXxAAXgcGmsDjwFqOrCrPXXwAJ9Ct7Heqr5SPIgFwu8J657Wm8bKW5XgdZH9Vx2IOa8QRqFn8z6n9xnU9OunxCzuwRLvh46Zv5xOsZRyH2MFIHbgUMp1pvmZTvT3nBABz7nM66CqEg54D+NmLVDilDfiOmjVAewMJFwWofRdbjhgAfjpM67VurHXrK/PJeK7y/WKq5bs2hh3lVbxd7NeThPzQYRDROxbxUYClrur/qLkgSVs6JrjKrsiT5HzMwd2XaM4Oxkk4BPphFiLChGJ3wvAxtirJR4g1GU01s547mIUeAa4h5wvEAhf6YAeMfKSHZQ0oo1buWlD1p4lT/k+OL1BC3clSVbN3cgSrucm3Y4Wmbr39vGd9vT1pzYAcAMAX1gA+MS1J6MMDIwfikndFwrw6HTWAZIsGyXMQymV9SOYv0p5pD6Ue6hiT6QsumUskyhCGFUcEAklESMoHlD8oeLGqg6aygFIACG0JAyifpbFFVECIMrKhGu5tZ0CpWFer38hDGpeGocYWz/n0yBzRIC5sHah68ARQYMyQBgAqhwI8DvX8EwEOO9H+VEqRXUAqTkXY4v+kgn6XHALDDI2wEMCGd0/Mq9nhejC3YUi1zE3NW4fIK6yAytkIK0johMa2ns7tHTtAjB4riusBEiq0qcYwYwHCqtjCUi/FxA1A+l0mdxq21un7b3veU9YGE5PLtrVq0qK2GnLi+MoAbPVttvRrWXb3Tlon7xxJzzrP/iGNwXtEnOnd7iiF+DVmHItSmiXBYKagDPwyD1I9JndWDJecwb+WNpRFigEgKCDsQ4WC1ECbqWkYl2Kv3jHCqioOn1Yo8iIhzbYWz2rg3DrckIcLcofgMTf/IxMf7PUO5B1wDODISyg0DVWL9aBz/VeDjrzswHRjI15AC743gEC6z2DHEpkSTaxR27VdzmQNJ3853TtcsETXKBh1gC+0/2EvPhzqJ8HIEpuGeCDsbh8o0A0JVMAOZQ88ZJQAEGAeN+/CGzLQ5kfKuT+dFnDPLvcUXH7RcoIZTr7IUH1OWM9FW5R1tfZwiz3NB1ABPToMsJexF6VC5d5spbuNYnfq4xQdyubZ0jvvXr5Slg4GfsKgI/as7nOAP0ur6uixHwYCqC5u5s0ar3S4V0HfNCyg7/QvRWGJdm9iQFMabaJAeyq4/5/8U4gl65c7u2q3MXQg2KL6GGsODVXAD9ZtpHSXkoOpsxCnSODE4YSsd85GbXr4nMpe9kOdZCsGkwunCMGw5qsi6l0n+JbIgBX1kbVXFsIDOlZ+U8xibpOSSquOBDyKCJAhD6f29WhPF3QIRgDnFagL9mgbi10gehKivdpLSV8eIYDyVFgmNp8so5lUquudzcoig33LHMV4Lq0f9Bu3j6KmECUM0o2Frwshg4mXZkDCDpgXAwAo4LFAeoqOB6LSrdMVYbdKHQ7Oh3kKXckAczUPBTNKI7tezGDao1TZWhEm7dvPNfe/773tcNDJUgcR72/h1+y227dumgv/+dX2sc+ers9/8njdvXKoh2fyPW31/71G3+o3T4+T1e8TiNRuPYkijLTCUSKFSUclldZoUsBCxgHrVVQt4OuUHB1YEKJOCiAHuY1QOE6KOG5DpwAqYBTLBHsnStt3gGdusKb30fZJKcbFFdX8gU2iS2UFR7ADh24cpwV7AwG5/E43/mYoXHWBh7yd3aQWyVrnAcdzMxWs5n+kVE6kAqQ+KFtfmaCmVET0/fOlb7vw3xoAGiGDLOwGeJ/Vw4RAmYVy5YKMuVD59d6EfPlvWGxPz/r1jRoKFyoAnpVAJtDLM9jP+IwXtY32ojSfUPvSIvtRVNnqJ5koqSQqJGZB9dMHkyZgIzva1/zIrHDw3gAUQBxp3eS71y2QyvwZ+dd5LcB3BhL9s6MMdLhxL0gkShVfeldT7FvfmCNtawDgZ4NfQYfW53AOGzG4S3d3OrCpX/ypty8eXOTBVyEuwGAs5a4j78BgI898XgEAvfm1VOZBhjmLoIuws1srmXbi9iUtNSEINlJq50DLRjFhW0AmZOTjDdT668qEhsMXRGEwSgVEMyJHyUqgYw7QPcHUxbwXA18z0WSuzrAj0505hqWCV6JI8msVWrGsgQRIADP2QXmwskVGBZG1rcLTwOkrmzc7YdgpKBxKLPFTreMpasp+zirlZIrGkqYRBZuJSQ4AEFAU0zYT/yzhcrJK4WW6ndlrFvsqZRAZUFi4dI8Y+7V2D0sHbWfJFLkWgyrgL9Hz3MLCGvKWt0N/hIkSmjqvfvbJ+0d7/zxUMQS5Pv7e+3oltYog7Bf+e+8qN345J32iefutIdefLmd3F627/n+14eVdLmsAsuipQIO7Hf+PTKhszjvyMBmDv2AUHFMmbwyCs4CzNy95nODTnxPZyDO2OAr7vdDRz8YVAkS9i/2ayrmDEDQcwWCI/5XRGMhEMyPsejn7o5aRh4Hb9FKzsHCOksg8wN0YFXhXdAPdOlyBB6E5hzY+HtZF+e5brWxDiS+xgAnQLZbEHE99/W2RCnkU8qJDAlwAMbfmp8DeOYXBfejD/NIEsjaeFXqpWr/UWCY58TcdxYrMX3sUdDB3DN3q4W8J66QjNoOQCmxIr6twxtWypVxK7miSrKcHp/EQVx/izW833CW59sK/ZI8nIliCuMI+RBdOXKtehHmKuMly14kWESsYIa16DoPAWBM8X2FoXSvkfEudKWflGLpn9ERxbqgyIJOpxreuxJnmtzcE6TY67vCEqydH3QYC2E1NIP+qgauwqb0e3TRUihHWYIF8DeFoJOyNwDwPgDffEsHgI891i5fvZIxe8p0jMytJDyE387ebhOTA778FB7gQ9a8xV6emMIVPLpJpPawNmlTbTWEFC7fEERVj5ACnL2nbVkB06s0Ysk4Bboi9ASEHG+1HiLg1rLBVhRpNaYX85FJOa/dutO/Kx6uBzS6u2YGCKylnhnrX+UYVNqG/r6Ay0xMKNvm1AWCcitpiatOEaU08p3DXZzWP62HkhiyqwfCMC1cw20+K0QUD3PyNU8BX/16I25PmbTbUadwsVc9d7v1kM4GSS9ZRDotR4ACnjcDHd7hCtbpQd+/4+3/TdR7Fa0cXlJyzGnb32vt9u2ttqOqQRc7bW8vT+A3b+ZJ+w1vfFN37yLImZ9+Yk0CmA9lnwCY/XZ6oWOKA+wOls0q5dYKn58DT5S0f48i12cOomIsFQ8LP6OwOGRdLKVhKvbWygjpevaAOE4HMDMojbUS31ufWNZrdpW6EnTaYvwOch1EOZ0B+LjW+Y3nz0AQ+mbtfT9YH/bALfhuxQU8YhGLMVc4BGsy6CZjcpnXTMsBeMoFCcBwelbhYCUCkDCXBz0yTBMw+Xjd0ska0GLSPSpYynQNsjfWtqyGnVbM1dsLJ5dYiLkGc60WtWdNY2wVxgMA9HX0otwJhLKbBmsZ4zWANNM1dMEa+LqxR4yF+ThdzId39FrsydZOHHB9v1z+xOfLjB1FD7isgBZjT6sdqsC9kt1kZGDPAugpoaXCGDJxcnhovDWg3q8kkGeeeWYTA7gBgDMcub+/vQ4gMYAhrMuVJwIOF4FS9OtkpNMYrkO+53SI9S4YKJJDMuM3mKdOk2HiVkKDukFU4eJQFCoHYgKIlPsQ9HWqi/fW6VVWnsyeT0HhircL1QoWprxBZL4l4qnrdUqPoMNwPXfLQJW/iHjEKn/hCltz8N6cZNKuByV52ndBj/ICSOkn6+zCg9/TvUplfIoiJ3DL5AOEylgPxjIAy+paoeBj3eS2rJhB1pH72WOBDMAZin0Weg5kNabbJ7fbgVxlW5ESFG7iCwVzqwVcWKOq7+aWEn1kmRsxUzNFrwK9XFOUQn5HPN4yk5J299vNGx9t73n3T0YswP7BTrt9VC3Y1JZqX6VR9trZ+Z129arW5rD94Bve3G7dutHdUQh3uX/Jqh6WtdHZIfeu4vvW9CuOeZol3MGK04CvK8oKuvP1iOtKQYZyw5VWCmWFF+oQw2e4c51vZOk4Oz9ZWVMU4qx4HYS58k1tuQoAoXtA2pzRDL34O1C6gDUHI27pQfmyLl0G1QGCz32euN0Yd7QAk8XNLNSx7mUN8ooE/hz6z8a4K1SF9dK4BjBb7dM8yyrqxQmk3zm63fb2Dtpu1R2Nteo15JI/FPfMesgKGGMPwJBWMcbA3Ff2rqx6PicO3FEmpYCcex967UCtB7F/1aEm3qG4uzrMrwC/Gld4dMI7owLQ6aVwGQkADR44b+1MLeMIoajWauw5Mp4DcpfV5qGZZYaPCb5lTXDTck3I59NlWNz0HWu5su/F2zEm1Sco3UZ3IuQFY429KgAYJcrqcBxl0nIjk23mg1t9JkAY7VKlM0/zUP7kk09uAOAGAN4f4JvvWokBvHSpp/93xpHSqj6ElOZA0O7uHUSZF4QQRZ7TKrQXQWrURvL39rY4FgDvylzX4tJdpzD8FBmMU/F/IUQQxnJHqji15BpZcgUuEUD5zqwx2E+KXrCzXUTcFwIXy4uYG4b3Z/EcF7owNqdwt9RwCpdg0r2eichzET78PdYxwYfc5vv7h1FqRADDi4eyLwAJBM14tvw0Ag/DlXkma1GVTqDQtAMRFDaghHXz8TFmfz8KMar9Wya2A0YUvn8/n+792dQFxBLD/kQNxLNhAdUea61k8VMzdYGld73zx9Lymd70dvXqYfvkjdvtv3rjD/dMQz13BMZnHUa5rzOmqRKZSvFi7U4MNFzajDeARwG2dXNyZcM68B49w9f5XoDQFWvf47LGUauvJ3RwqCn3lcZH6SFBS1e683NjPGUhYc3jkFTJHgD1GThCfx18lfUE/nLQCs05Xzgd+rMcIM7Keh77/Dzor4eJUOOvRw+PQ5NbjOIgVElyWK3unt+Ia2Xs7LPvZ1iJrOKCqEdAwa3rPkfJ1gTU9PXOIsndQzLxF/wR8tGScXgnY5Hs5HCPOxkeZp24hz12gOVyZgDgiiNUBEYJLz80QiMZm11g3NtkqgVaAWo/ZMfhUTHLO8NTwPv9Z5dLBWDhrb5X1Z5QANzHHyEMVa5IyYzu9tfnMe9qWoDc97VivVzv8Yywqpee8b2Bz2ONA2Am7YWcqvhieeA2SSCFnS/u1oovDCr6/9FT3AJ45dLlbqVSTAigJZRXNQgn2ysUhMWVxFZsLapWX7oS3YXXFUWVN9F3EaO1vx/X4nKkWGmAowILZOE6g42T7ziFdoDDaf5cxrGsVxanxQKHbC9CDOEaljKdaCv2T4kkoWwLAFOFXtYSrY3GQLLMyjPqBS7k9WzNlQQRF0RuTUW5u7JDwLgykwuYEzBrnfdkwDLWRBfYjBdg0RXCYidAkZ6vDGOBXtbGlYQDb72bA0EX4lUs3AGzsGVaFNIqQvybUBfPc1Cna7pC6spqNWbOwYHAndcxdBCo50KDjCHrk0f9oaDpSwfb7YnHr7dLl7faa1/72vYvv/DVWTjaqvOnMM/s6Xw3lr+xTkMUZb9WP1R0UGIlevgsrA7lbnelitWW5/rzmBPXM+dZHMb3BQC957U+i9imcC+Ofr4otmHhHOAHnun0WfbcDmbbIrP3y5ITa6a6nJVtP+/xirKth+sarHrraMIPBvA6tIfydLngfAA4gmccKDrYBaAFHZalKyxFykCv8ikoclkBkVd4LgbAGtnvrB3v9jVZAX8UIS4AgJUo3IL2j9hTly8OqqAL3PYua2bZp3XoQL14gnFSGNrBjMsD0Yli+nocYblrsYqxrtyfP8+7C5Tr9Ey5QqOne60B+8vYYyxlbWMO0b1E5Y7w8tT3fpBmvIp3lPyOGNXdrJOaFtbkEYUuERIRz1cpJNXJVLWK6igFSISX9GzkFW3dfNzQiYPnBO6pH9FrQYu973HxzFbqTyzqoQ+3t5s6gTx17frGArixAK7IhPv+Y+4F3EFRmfv5O4i0rIEhvK2MhQsIV1T87iAEcODCHGXg7hmPg3OgwzN5J/cAZmBK/nZFi/JiDLNADmaWMFEB7OmkHMp1OxU7LuF1gnUGSShrfjKGGSCgeGZFNoNUwJ6y51TwOUFOJq2g8GZA6evPdaugMcmHsbmCQmChYPQdwo5982f203C5ppmPro2s2oP9/p5oPVxuLAClrBu0b3Pgy/euXDhAcFAZHTiy84KvnT/LlX/+vmj72vetrGfJnBOwZs9j1rAL9XLn4haOeVr4QtQ7VOJHWYn0fuVRkNDCevshCTAFKIROZ54C6EEz7I0De54Re1QlYXSwCWV/ka5855W712SAWKdplwczmIAfsGj74cittAAX1gAlOsB7WnUcmPnazFYTX0vmxDgdfABseRbAhyQzaFVrQ/tHp21kA8pY4/O1YRyDRnXwSfedgzX2NfaGWNkOAC4CIHlLTa739c3OQMN96O/m9xm4ra5n1ttkrtCU0xzrwXtn+Tm/h+t9zVYBeh6+SAbpHqWKkaRSBGMCzMd+WbhD50HzJuCenvfd//YWdQ58WUe9D1Drc3DecNkYz64e8/Bb1PeLz1dr5jqIB+Q68IOWtKYKATg9O24He/vt1u2jDhRFpzdvfrI988ymEHTQ6cYCeN+4r9/oLmAJbLK0OPEGmKCHZBX4DAFYhTL1IIJ2XUgHQculYB0QFMOgv1FcLtjiOVbjbVY0PBtBBdM6eETIOhDy+1zRuBJC8TAeWtERH8PnGp9OkDRFZywhkKpcAIA0hGVvYTbq5UUR0XIdOOAFYLAxrjD5zgWsrwOCknV1Jch3bjXytUWoO8BhDCgMlLHvj65x5affV1wc1f9ZAewAKheeKBXijWI+ZXXuloGKa0M4dstLWRq8/A176Pvq8+BzLHu834Fv0orkd1oOw0Jwdh71B6EzjQEggWLowHnVUNN5bJ4/X/jn0KnzEN87nziI4b2uqOmrSweQGK/6AFuMLD2BZ0uiW43ZK+hnBbQUWHHe8kPaOsDQwZb1/HXp5QrX7/+3XcP8oRe3mhLbB3DoyWC1R5Q4iXfJ/lIH3r6Wy9HRp9OKDoBnSRdOA6zNAHmZXJVzThC4DmDzLj8chhysNpoei+cgJV31+UynQYCFbsfinXICr0D107V2mXQXonuSxuJyCf5wfnGeAUj5dU6vgOWUOclHmp8sWdFhpmJWEySnl8D5Q7/3BCJc1HILV+ymyyHWE1qMyhRV59UNFi7/2LOQnRVzqH3DQkjMs8bAwdflWLeeapzb6WmarYH5jlEOiLXS5xxeJXPYbz80aF1UkzBk7/K8nZ2etievbQpBB41tAKCLx/v73QGgXJQIty6QKxNX4M2DgPW2WUARSE3WLkBsPiUzUlfKLuBE7A4S1wlcTtXurtIzcPXoHcMyRAmFcv9ZLAwnNxSkCwRAFnPFZO/AIsZmFiJKIuBGRkDpWelSzkDg2VLIegfAtC4M/I5Vj+tQaLMwwYWGcqb8C4VVURLzugE2HFgDlriX/dRPWtehdGcF4ACCNQYkhpKrxCKeqc/WWS5nAe/WFFnfAGQz8HNwxFq5YHWQgQKG5mbFHK3edKCpgxDucubsawbNMNcYY1kqmJ/vr4N6xuRrCgAD/Pr8fQ/1fbiSFdNX5VpYU9ZmBq6Mn2fPgAKeYE7ODzMPYNl0oDNbN7nfFSjzD7pVEXFljQssVD07FDDznp/hh5RuGbI+rSR/IZt8TPHu6iTh459piXcApnL8CWiSltMSD7DIQsdZBmaWdW6Fg7aDJ6cSOxxWY09MXvneJoAYgBSwxb6yZrTbBIgwbvgB+s2/V2sH+jW+/1jYGSe6QKEpgD3Go3GEIaBiG2Pe1c88ypxYdyXnJeKsPcQDOaVxEj7kPAQgdVkzNGPGGSLX2Av22xOB4gAokNku4j26R9d3/aIDQnUlwqUMGExwqg0d/bdDT0SSWxaFHnuU8zg+qe/20rJ7dqJOSmohmcBR+3x4sBcJao89vnEBa/02APD+MN/KXQ4A1REDIaafnAQ5HXWmqngxV0o8FACie72HLISP68mVijM9wGVWSs6sAAq3SLmC6AxtsTMOKB1sIsBcmSOw3NriwprvsTrRwjLcBzu7AQgVOCxXWwgMWnTSD/Wiuo5Ue7H9g+y16iDKFZXPDRCBcvYxzha5WEt5mc5GRwIH7ShXB3+uwPndLRQIa9aQewUS6SXNurjijLWpeCH22Pd9Vsy82y1u7uIUnSnxxRUsNCWAFmtZLntAJmOFrgE8Dgahe487TQGc7woLdgFCV/rwRgDFUnj6PjJ1VQanPmNt2GssC76erE+fT2Ue8r4Yr2L3pu420GiCkrRUOk1BM3zG/BlbCNVKbpmt8et4xg8ruhdFPQNHLDgk1ECzDrSYs6BQXwsrmM0z11Ug0PNQ6rzDQSaHHo2R65j7DPagDQcQDshR8gpdyHnosLpa55T1h67c7e9gi+xQ9X2F/6Ex4kL1Pg5LfrgLWrjLvYz1bPR3Zt0ALwKmWJsYp74LwFNJOc6n3nEk12q4NlMuZSwvcwX0rpOrkfhg3W88Jpr1BswpHjDBVoYq6HPoCPpFvwBS9TmlZaBln3/enzHG8DSufmSVxqTeuw5e8WJouDjqOQAAIABJREFUT1SGRd8dK5yl5Nmd2yom/8l2uH8pwlzkvj05PmsPPHilndw+6lnaDzxwpZ0eZ3gBbm7GKSufz09yQyEjKvyskAAqVBzdvNX++w98YBMDuAGAXfd9Wr8AAJ944on24IMP9m4UzkC8AEaHIWFWrnXgBFPqGgpuzorNgRrP4hqEkYMaF9b6nM4Zo7p8Kg9XpgBRn8MMXsSQmPxRoijAdUoesAIw65loZelxEOUArVtstkt5RMbhTo/3GUJ0tbXbbDHhOsAK83ElDGBBEAcYsRIhDgwARrPS53pXmgBpF7p+6nZacJDK+vMuhKDPbXYTAnBmcNgV6/I8u3OU9UWuWv3dAWhZ7FBuAize3YX1QyHM6+AWtmhWX8oorvfivx6Lpe4JFUMKLdNtwOl3PgD5WPrBwpIiopZfWYJk1TpWTcWyFAP2HDDG79WybAbyHCJ8PA7s4e+5OwSHsr6v5TIDSABi4AsHmtCmnkEHDXp8a5xY+T2pQM+BtpxnoWXumcE1gEk/of8Z9OvzOESUxV0lVgAPuRbIkblVX1YFGFU8VtsvOpBhHeEJ9od1VFswlP46GqRkCN0j5C5Vof07x9k9yWWdv8vlj57roJiDGDzlB2NdJ1nNPQ76uc5pwOVVVH2IA1K6QAGc0LLzNrSg9aYKg4C9rL8cJAVSNZ6jozvRqlPv15wFiG7ceD5+P7mTiXg3bt2MEikCXwrPuXS43xM9XvrSl8a49N3B4eV4VszhPPWHZxYzboGxSweHCeROks+QBVyf1Rf24/OIZdxWv/PsF3z79nGMS7RMsW3oQs8SzfW1rexeaI991H16x+HlS+3Zj/9j/NRn6l3+P/zc/7gBgBsA+Gnhvn6zJ4E88MADPbNzBmsiZsVtiBFnITCfplFmEL0YRQyoz2eXnVsD9A4xB4ISAe+Ah8BhBCYMw7ukhPwUjyUH5URgut6jcXE/DA3gnAEonzNXxoZg0jupY+jgyoW/g0mUOcom3JRRmDmtRX7qx/KlawFjWAiYn1sp5nf6u1CqnKg5/TtYG9aCHAsKfR6/3+PfrbPeurJgfg4K5xO+WyW4F1rhsBAJG1NfUhIx4oRfsXtVzzWtoeWCif0qq4eej2VUY/cYngHMdiJRRAIYywPK28EbLfWYGwqQv9k/wBdgDDpk/6ErB1UqsxLvPknFBziK/aUPrNVog4ehVbcKzqAE2uJzaABlDe/6nul5bqkCVEAXoZDVA7ZqvwE+hpUo79c1WJfk6gLYsq7wIsAkaYUMbMoKDRcsPAqdBO9uVykPZX1W5qvzjHd1AQzDx27hA3wCLmfeYo3hAV9PeBVeEbBDrmgdcA12gFitBGU1i/cUvYo+kWMxVoufjr+ru5Dumw99ADGNhRAZ3p30kpZcQJM+AyTHexc77R/+4R8C3Og6eFLjUUzfJ577x/biF784fn/00UfbRz789+1lL3tZ211stWeffTb6zYsu9FPPlU6BFyWPbxzdyv2vnvKMRfNSowE9V1Y4p8vg6cVOU6MCjTeAk5p8V1gJYAs3LrwnkHd0J3Va8v+oxxc6ZCtjPcmOh27cKCHXbbqIR2ZvfH+R3gL4V2O4fPlyzJ1xOQjXZ3sH++3GjRtxHzQfhon/q70zgbLsqur+rbmqu3pKmhACghDEAWRwRhBFJkUQBWT6QGWpiOIECE5LBAVxABVEkiCfMoloRASRSXGhAk5LgQ8RRwJKEjLRY83Tt357n999px+dpKEr1S+dc9dKqvrVffees885e//3f++zz/hEt7q2HPLmXb//hj9sALABwB7DndYvAsAXvOAF3fz8fCweFac/NcD1ZNa48LcaDNXKV69mmBEYbnBt9FSYKtYaiLlwZZ9SkWIMrIuVi7D2tGvwUhtln6Hh1WjVAKym6TXULmoNooZ4GIjV7/WeOj/R/kHtW36AULEyV2nV7Je/azRrxVYb5tq4C0CG+6uM6rHQMNVtj8/iyLfPnGb1/SpH7iX8rRH1WbXSdL4IbOmHxl22bHg87Kut8PnOtxj3AgbjyLuSYxTKthT/9rO679xb9ur0bKL9YpOJspyeSGU+LEcNqv13/uiECGLq/tiOGoA4t2H6NPCuO+dKzNVSoH14NMxHGt6koGOj0bG99RwxOd86bNnWHMM8ccZd0IN6hK6buh2OcT32+Z7caW3emHlmnnLQz50S6ouN9n2BcEFSgkXzsZwPhGIdT+VmO7I/hhCT0VtdXY5+1eFD2ljLhX/zLtgcAKlr3Zws/+7xiwJcAbHzmnYAcARKztWYQ+sbweIGsFlcijXGfIDhOrD/3DDw5x48EO2cnEpWbnaWHfJ5nBpy2LfvQIAowD/AiHuQgfNlaSF3kPJegAcbPnQ4YbnoH6FK3jszPdkdOnQoPgt5llzMGL+tZNDoH//xu2vE9hjmVk/SRtuT82gA7IedF22IzqZOkrrDcVVH8NMcZH53fGpd4FjUYL4G5zouMs68I+RR5KdOCkeonLxSM8R8jsPO810nvF97FaBtdTWqSoTNWFX2eY92Crn0OrocpTmsv5krsTlzbDPA7x9e2hjAnJcns2KfaafaJzcggQED+NwBPV4Sc1F+iFiquzZEhk01iC5yjVYNHvldBeCCEUwOgzW/zwLU4KogNK5+h4WTORzpserBDn5Pw1UrgXphp7JKZMOpEbUBkY0cViAqPr3nYUDgwlZW9d8NM2s80/BNcWBbeqFrg3IjNeCJvxXwIQN64jMGBVT9XHnXIE3m7QRDVOX/1HJV+cZzJrPcgYpK9oO/CTCWVxZj/ghqapaY5/asGvW1PBmmhG5r41CPu0C3blcdeqkBkgCrBleCBb8PI1iPR8h4IxPUMby79sz39RCdvzKRfE9mSkOljIbBv22x/d7vMvTZjmkv4xK2rQG445nn1CTYsQ8+z3GtmWIBpT8xmMgOJw8DXtff5Puu8QRJyaAQFrU0B+8VFPGTNk/NTPfsMP+G4QgHcmMzmIw9e/YEY0pkAcMlKEDnBHu7lbl7Gl7e7fzmObTz6NHj0RbYo3S+sm0LC0t9agl92rdvT6zhAwcO9JEKnkdaC/fz3WCFipOwcHwpxnN9bSXalu3ZitAf7bz66quj/Usri8HuOEdh+bk3QMpElutgw5fOIv8mVMd4LS8lwJMFTWC71a2sLPVtcl2oI2WubE84EGXcZzlXveRmJ9hIZrB2Sp0LAhlDulE3tBxBlvou62fG5pMqX1T97DgE6AmWdlByptaJzsXaFMsOqofV9XXah3pSkFgzquoQ36MOU2/pCLjOBJ8CREGY9oJ/m+tXtyU2HZW0itAbnKUcdUKzoCXzs2dTi3PiGlO3cB/zNFJLtjKtIPRByUMWODtujhdtrvMPYzyKw6lt4d5YizOpV3ESlpaWuz/4w0sbA9gA4PbgWgHg85//8+FFpvecC0AlodGpjXsNdPi9ZkI0zN6vUR4O7fi9GugliEujrMfN7yykUKZ1GYmqjpbAAW9ZDzMB1olHpJlz4t9qYyxzoDLSu9SrVdnpXep5qhRcsCgHnov8YAD0nFV2Nbgz/FJ7goLUGkCEASbHreT+hMLdSs/a52oIVOK1cpMJqMHUicYkyxx4n8CDZ+iRO+bR/rE0ijUgUfHWYCw86HKucQ/gywktAtsoulrq09U1Fn2342E7/El5EwulWlqnBsY1+A/jUACg/dDI8jfb7jtRzhqcUL4WuZ3KYxJhDjVQ9TwZnwIMDMLmGpyc+5tRu9GQp+Et5kifXF7ygwBQ4ZBMZsgtmJ5YmzpTU3mM1NZWt3///gBDtBkQBjAASACsuHjPlZdf0Z1/wW2jn5d9/OPdwYMHY24CfIMNW1vrjh47Ft/n3e5s5Psa9Doc5xzW+Lpu+R5gDVBmWPDI0UO5BsZzt2w9n3y+DAzH0XlqCXLnv8mZ6W485vpaHFfHNb97bwI9C1kXlpr3+CznP/eEwZ0q7FaJHJAvRpiPUKmgwlQV587J9FwAm6J+qddXAw7nQq0D1WWGbWs9o+PsulOHyDY5V+p2xL2kZhT9FnMzwtweL7Y5qE9XiizXzpkOhs9UhwhObJ/rNTarbK6HDGd3zQV7qV6t9bXyrvuuLlLXyLwO9HLqsFrfhHxLXm2k6Wx13dJKphB51U6x79PRQj7K1TWqTTHCBSPHGhE0hg0qDJzjlbrgxOMptRtZezUBn7m2UXamMH3heEWuN5sBKRC62e2d3xN2bGWJoyf3xJwjt497zU927tLXviRbFIrf6HbNzXXY65dfdEkDgA0A9mvhtH4RAL7whS8IhQ34w4DA/ukNhRIuoYR6EerFqChcuIIClYMenItchVN7eCofwSCHjASwsjp+BURqBSXQUon074zDuotShDXpE3nTi56eyiryUW2iGACVbU/JV7vs6rCcIKoGGDVbpbKhTxgpQze5kYDcLU9IKCUvym7OAejNsI0siTW62DCSYDN3ua6VnXKx17TkNtWTwXHjO46BsoszeWtmtoT5AFL2PxRgMcg9KN1YjTMwVfacU7lOzmJ1hF6GDEseD/wFRogzNs1lKrX28pknJrMnIzI4RUZgD6BAlrSNM6BxVvg3Mrvuumvi2UeOLyTAKAzU6vJKKNbBeze7KYBIAaS753d15557bhgC3rNnfm/kLwHGzj1woNso+Zi8Q0YKEM64ELajLdddd10YQ0ATbeRdV111Vbd7956+fciKeyjiums2T4MROIFgAuhsrgc41IhNT08Gc8azXF+sz+PHk0kzn9FxYZ+ghpD206c6LKcM+Cx2OjIPYZ7LqTeGxwTs4WyVNUP7kLft5t8y5AILwbKsRs2KrqwmWydI954wpoVdDoCwyfnNWSKDdzB2FMONNT4z3Rs9PldfJBOWO1FjvnM6xEZurnDe52aDsivaYw9L6M51ITulfnOdJAjI0LOOlnlsPFM5JFCd7NaWs2bbsDydAz5fIMT7ZVx9Z4R9CyuNfHnf4cOHA9DXzpV9F8TgHKs/GSvHzPKU7CaN+RU1SgfREfU2bV4LZjNlJWCtAWKO82B3ee3cCXqiH91EMIfo7xgL9AbOvXUUKY80luAvnKTNHOPYoby21k2Q1tONd6uRE74Rmzzmds/GvaurmTfaEwxbRoI2QlY1oJT9o4+xKYMduGQKlVQK9Qj2AMctxydB/dTURLe0uBglWngmR27S/8WFYyXaFA/qpqdnAphdeOGduk9+8spwVMLhW13u1zNAMja6dKlf+XeMFZtdVjPPcDVOl+pi3RO+p22UHEC3ULeSth06dLx77z9+sAHABgBPC/f1X64B4Pz83vBQVN41cEslMKgRVYOkZAyj8FFhpAZJ9TUrFd8pYEc2zZ81QxWKpDCBJEqrmFSQKlG/G88s98n+hcItCdIaFJWabQ9FPZb5GOuwSf25rqkyrZ/lMzWOA7Yz6w7yXFlBvicorT3SAGxrucEFFlLAqDEV6CAHwkwa1AA0a7kppDZ6fE54zbAa47Z/X3qVettHjhyLPBW8zcsvv7I3irTr6MLxuA8GKID4+kbkACWg6Lr1cqrF7FQyYVywQ7SDsBrG6LzzziODrts9vze+w7Ngo5gPS0sLsYMvyhmUnBcBMWwC4TqACsZPoyag2yq1yBwn5ShQ537nlXLUuZClCiW7mfk1FvT2PebLxfFua+uRfJ3PTgaUZ8aYb+Q4IGOTt20Dz4jNTYvJ8ApAZIBq8LTVbXbTMNNbG93y0koH8OTn1EQaAx0Gj6kSHMTJKVNZSNv3Ot8cEz/XiMua8Xkwd4Qoq+PYon1buT7j6MZyVnbPQBUHoGZoXD8CDh0lc8H8ruvANVCHApWHDAyyi75sZuhVwCnYJrxKWgFjVqegaPSdU+6oFDQZ3qZ/sri8e2khNx4wxvwbcBFrrTi3bnSwzW428N8CaNehYFAwbd9DV5XwnhvN1BuuTVlKAbv9V9/60+oJ/juVtscQpjMZfSmpFM49gS9/ixpzKyu5E7jSkabwzM7NxXMMRfNdAa/RCf+Wocl0HpBdyGx6KnQH65xnogMuuPX5sZlj9+xcByPO93bP5oY7w9nmLC4uLQXL7Tnm0fYCkGBojx4+EvOE/9B35ijmuGU5ltmpyW5pdaVbL3mK5Fbi/FmqZ3J8POrn5RiOd1vjeWrP9PRsd+2113bT0+MFjA5yXJWhY6ZsQ09vboTumpnb3Ttd11xzTbdvz57oI4ANXek6QFZLVCDAUelMJdkMfRvjUkCymyXpK7Kkvzob5+zfHw7lyvJa9//+478bAGwAcHsB4C++gPNQy1nAm+n9jZWdWCy0CPeNdZEoz2IjzyVCtONTAZ7M4zFsrMeLEgrPbyu9NiYx3uHMxHgqjYksH4BSQVl0G5loj9JhEUjnu6hgJlko5OiEsV7N/D8WJAvm+GIuGi7YE55r/hHvtl28IxPckwHkXbe61a2CzeIdAbamp+JvGheAD+8A5NAefiIbjT/Pd/FqoFEgggcVdvR1fLI7dvx4Nzs3nTUDUapFmce5mBVTQ+gsvjs1XkLhCVJ4lwaQdvIfYxNhk8I2el8CyvRwZUw06O7KSzA2OGGA+9fLkX/1uwA0k+UoqrWKKdgqCc0JHhIUaxA3N9NArBZwFRXFyskK/RwpLI5GVqOq0dfQCbYNwXjaQoCpignjfr8bp9Vw4EO1SzZTDJJtDSBVAGMU866MpQ4A95jvIyjSCZElETw6r1bXsrC37K7P0shGH0vtO9ph/k/tYJEzJrMtiPW96VAkABUEB7NXNsL4Ped9zb7Hmq6+76kZbPix/wEsx0881aZ2oAScjhlzz/wxQelgvE48KkVgFJugYJXHNntnJ95ZTrrwZ4DEMj9l+WpH0jXH+K1v5Hzjs1ifxRGZgJkC/hUHpz7RKEqF7J4tToBOmJsXsvQP4Wg2kpgCgJwcs0hTmZrunbXxKBbNeYfJOLkZCaYpQWCmtTCP0SVHDx3uDX4wTrtyp+zc3Ez36WuujbA972cWO/8M/ce8KjmGc7tmk+Xb2so0gKJXACUBKnBomPtRMikZ+rU1gF+CxBjD5SyZFDptYjJ2oSrLiJxsJFu7cOx4N0Xx4lLrkj5xwdylnskw/upyMlqh/8s5y/sO7O8OHTlCMn/oe/5m2BOP0vlBmwXrPIPj0XDOwskr+rVntbfyyMld87tD7/Muw6o44HH6CCkagNZ+U0yuf3RyyHv3bHfk0OFuz5598V5BtmDN8YaZVKfnhqFSK7SU3pnfuzcAMbTeOCBwaSlyVGUo6/Wnftg1m7ur6ZfspQ5cOEdra92f/9XfNwDYAOD2AsAfe9pTQwkz2a/99HWxaAA5sDyphOaCppexisnITrLpmd7opoedSd1M9josyiQOgzszHc+d43uV0YKJnN+3NxQln69t5OYT3p30e9Zc0mDHgtlIpqZmBXqjUoy63qsLWUCE9AwlGXayvQIXGRkBQm5AyDCAbKJeXm1oB6xBhrJqBkNjZp6Y4MBFrncdHmjxFu13hpOzJpZtq0GMYCsAQTlMvGdzS6gbkCaI0Pg7k7JPCYgMJdXsg8yrhkDgMVCIpQBzYSR4bv03nxUAooQ03M0nMKpDY2MyssEuD8LCw/cG8CtzCcOXQCh7lbJiByRlHZItQSb2JcKkpc+Ai5qZ9V4Bj4AmmI+pQQHcGNONDHHXSl1AIkg4gckpYfxwfjhlp7TVd8k+18Yiwm0Wd67OjtUIhYEqBaLDaG3khgWfLVgiN8l+Bvif3d2vcd8naAuHYWrAVCbQyPwk7tVQ2UcBoO8UxDvXgnksbfcd/JvwOcaS+ww9CiQBAOZMuZ6cn66/kCNzYHKimxrPcaZvhNP4Dn9DP7kDmX/zzJjrW/k30zX4jHXueIZDBUBgXkU4n0T/iZInibHOkF/Idz1BieDLeRl6s7DLApKNUkaF3DMc6mMLR3sQH30fZ8PISuSMBZhljpV8vD27U16usZiTk5lSEuMSACxzkGlXMklLWcYIUFgdwRbzaiuLHCMT0hrmdu8ehDnL+oowfjnGTfkDmo4ePRzgKRzQ4gTTR9Ip0Os1e2rOKc6GYffIm+Ms7sK6x9ocH+tD3oaZl5cXe2cK4C4odJ2hG+kDeYprK6vB7LOm6bM6gnt4Hn3hXn6PcdtKxpi1QLgacJzRkNS1Os7OM3/KhPLcZOwzIuTn/Dscg8npDiYySJCSlkKbdNwFl+r/kNlY5k+b/+68es97/6kBwAYAtxcAPvpR3x7FLJmg4c2s5A42/zNUx8Jk8QXTt7EeITS+Q24VOVMqeg0P38Pr0uB6bBrzO41dLgoUA0qK76MMNZbcLyPTM1djA2DB4kRpsegiZ6gAJJ6pMauBTg2YwlMtNbVc4LXBlX1U2Q2embvFzF/TmApSEjicmEvXG99+t3Iu/ggplNwTFULPyhQUo1IXJKrwKH+jYtOoKucamKqsYPPCUJXSGZswoAKRYCsSNQWbs5nskM8T7NXgUGUlQBYEC3JrwFgbao2lbFkPfkudvvokD76nfJWPz7K9vTxKEeg4/q4wzxura2HgbYtGIhmYEn4ujEoN4uP3rjCz49a7GxQaj/IiJYQbY7i22kExjk+Od+ur61Hig0ugZLFjwsA1G+ipIs47AEwY88JkEk6XDU9HhxzIZHk17jDHgzyldJToJ44WF0cQCnRZr7gW5Gyyu5ByI+QmIUPWH88F3OrIuSmE5wQQihyp8ZJHONiRK8gwtIvRTSA1E8xq6IhibGmDoCwjB5krVbMwSD8MacmHk+3hJ/0C2MW89sShoq9wSPke9d14P6fFxPzkdJ5imGNs2eEZR8HlGFvHLZ2HZAgDvI0PcgwjBDk9E++FPULvrJI6ceRIz/rpGPKTcYtQ4OZm9+nDMEqZokGhYEOZ2e9BnqGbgYhOML4BVJaTOYpcsL5UTjKUOr+GdAVFEaIEsPUbGQan0SRbpnOUTB+yRwcDxENOlB2J823z85m5uW51ebmfF8wdAQnfB+jxXPKdBULhmOBATGf5Gu43LzF23VO6ZqLMqy7zKblCL25l6grjTJiW/myVqANAOt5X8lzVDzryAveY8+iysc3YgCRZYN6q5EDo6/HUe3yX8k+mEvCdXbvYhVuc/nLebzjY61vdWhSXz1SCufndHfrGvjrfc/3mTt6wb9PJEi+UGohzjEcq6Xh/6KhSNzfyYikps5GpPaurG91fvOf9DQA2ALi9APCxj/mOyFOSHRGwhMIpobPIh5gooLAbi3Dr7rldYSjx4gRMsYhKgUzZmgAx1ckBslD8nYXqjqzIEdrYjLBCAMStQc0uvkOiMPf0iqIoFhWfhlHaXiBgLocMospB8KKXCh6qw4i2U3DXe/ol/yafOwh1avD9XpQSKMDYZ8jKASAFbgPmJ0EG/8ao53hkGL0GKPXo2/YaZLlJgMEbBmJZOjYvwWUN8HyeYyfQ8zs1wBN8BZYs7IMsXjw/gHIyYzwHZRYGppQQUXlrTHgG7DDjYx8iNFdqdPFsFfdEyUPaKEyXxn9qerABIOZJAYOUUKCfAijnRAJ2nB93baf82XCB4WXTCH3gHsqSwGwwS2QwBC4YtC12qpaSPdyX3znaGzdC4LJiGNdjMDITaRxDwa8sB2hYWUwGPc4EJY+v7DqOkkdjuWbIz4R9YcMJG0wEZwloMnE92jaWbHeUbVnfiB2VtJ25Tt8z/EdKwWSyQHv35QYpQoLhpKR8XNeMAXI0xIaMAUeAB57D58hCdte56xzgHllygUvoiznAYDqUjDe7n9mYE/eWEOH65nrIJ9ZHOcUjIhQzWcONtI1elquZaC/Yr5n+kHHZWX0CIK82fgmCe3Be1iX9lb3kp2kBveNWyur4N9eD4E2ADggC5AxAXc4BAWkylmWsZ2d7kCWwYFz4OyeruH4Fx/H53GymloxPlPzHTBsJYLyyEmFnfuee2snQyeOZ6NMIG+8irWSrW1haCaByfDHXhuktAt8EnMmAyg4HkC6pJ9oFw8syr/xbPeP6CLasbPSqQ7E6A2EPyoYu7VWt701bEXTW+lPnW93kvwO0lnxr57v6UAcCtpDNUxaIdv6EvivlX+q1ErnGJU88cuzLZhRlFUWxl9JhYaxwmJZWKBOT9mFmaioAofL4y79pIeCQdasDePog0E0g3/HoR0YBUhUBBoAJqcJQSfG5nqUGv140KsHME8nwp14PjCEGLRQxVqkq2iwQC0UykSE6FYe1uwCQLDb+HmGOotz1gl38PktDwP2x57EPf8JU5vP9ToATymEUQyw4QkHreaeTlvcJgqj9xGaTYLFKeYgAcyWHzOcJpuJ91eHuyQAkCyo7af6SirRmugSPsFonnHBRcv56IMtO2vU0HoJhvivrxmfIQ6VG34Jp2Lc/DHiwQKtr3cxs5gEBJHtWrcgx2dd9HaEZwAW7cznvEjbFem2AKkE174cZpWDz7Mx8lJaAxSRkA+sLexCM7AwpBNSP2x/3wKZ5dBM5k5TzWFo83nEUMEbQcHgewZQG3w0KAhVC38hmZWmxN6p9/mQJL0e+VhmbLP+wleVZopAx3vd6Rzm0MP4blGjJFAUBznhH4d+FmA8DtqyLkBpzhvsmOCqu5PoZJtJp4R4BLvlK/D1CWqU4b6zN2WTJY2fkBkxegrsx8rRKEfd8D7thN7qlcnIJRkZ2yTng+mR+x47DAuQABtzD3ElgNtet8+wSFuPZkZM7O5c1+RaPB0gz/LW+lruaNaoCJv5NX2X765wq5zVtN3dPwCgz5HoQ2AoAYIjI32WnLO9ws1LqhzzJghIchicB9uSIhZNR5gshVdoQ+WOlHBbt3rN7d3f4+LGYf5bVEUzjmM3MpHOA84EulV0iX5i1XW+UkYFSLr0OKWksOcdWo23k1uF4J5DKeTk7neeMC54CFJVjAQVyOqC+S4feSIn6qAY+fIaes628S5aK9XnkyKE+F05HRNsQY1LWhPpcPZtracCC88518scL0xfO2Fo6Ko65qRTqQ9KM6CNktclnAAAgAElEQVQ6gs3Ha+wm3kqnZHqGcjjpPDGW4dQUGerQ5Ro63q9Hxp6cSh1B16VA23Qd8hJx/HQywpGM0zoKqJ6c7tj4cYc73CHGmTlDsXh+3713Ty8/2kQoHvly/959+yK/mxSC0LOFdVyBOQw9BHimBFvORZjQWpctLS93L3vFqxoD2ADg6YM/niAA/D9PeFw3M53lMMLrmJmLEC/hmfBKSu7OMEMoOBFkAKxkvQIUlTAiC6OutK63h/IIhV6KneLtBFiqAGAAo5IzOD45FuHpXbvmYxHoJQUj0i/OBIgB6DbyFAKPn+LZoSjGt6IKvopQ4BrGfSsL466vlDDeXCb45sHvyWZZXBaFzXf0wH3O5MRU5pZt5PsCzE4k0NPrVT4JjCaDQeE9bEKhL2xIYTwMBYUnWXYI87kGlXfgpdNmwkkYZwAv4EsAvryY4Eijw9hubRCSmS9MTrKC5CXJ7HAv4boE1OmNBiAL5mS92xXhNkJaS8EQHD2SQCAAeWGPAHsARPu6VjY00E/O9GSeyRSg4QURYdC2CF1SaDf7Sn7f1CTg43jPVGcIX3YKpnBXMFw6DzoD9c483qfTIEvA88nNCS+8lH3ZVdIJjiBPFHvJu6KPkcdaUhYEDpZxkbWo2WOdpciTZXNN5bwEW1NKwKxvZPmOUP7l+CjaJOupY4JxApQdOXw0mByeGX0toUueAxAy7BQsQ3UGqc4G79BJYMdxsnfzfdmRBKUTseZ2zyXgW15bjrW3b35P5rd2CZBjzmKM1zf7UKIsEu23XiGyi/zbzUwZwcELx2piMkrTyAqGk7KeoVCu1APJPhpmZLenoFl5yz4F6zKVusD1kvoq12E9DzT8ljix9JLAqnaEaXvqndRvRh8s/6Gui3VB6LScjcvcpB0Wxw6Gt7DFrgHawf3BaK5nODEcygCAuVv9yLGj0f4It0/kxoVwsmc5kmy9D1PLdHNWbqTGlA1QMqU+Vwddnalj4JzTeVX3yXid4AhX+dzmbnO/zDC/B6lQcrwnp0k7ICowyO2lvbDZ3IcDZmg60o2irM18bKaIfPH5+e6CC27bzcxw3u5krBnug3XHIeDvtpv2ku4ic6gDBNKir5S+cU6FDiS9I9bToPB6rDty4Ev5LNoXumYpdybTdllInE1lY4rRStntC5j3fuUIcBQ8r21mKZiwp6VkjroiWMWV5e533/BHDQA2ALi9APCJT3pcNz6WuRxpOLaKIskE+wA2UxzAnROdRW7oAyUVk3SK2klTfaHQSLIutcbYucXfWODpbSXDEXWRAImTE2Eg2BqvQo13spux7DKGkdpYX82E7PH0tiI8VfK5+DceUiigcuYiUqJt9CnBFcpyrFtdop5aFsplkeKxw0xoLIIZq5LJg4UpoTfyjrL/qeB5PgYRJUQ4UhC0vJB9lnnD64sQQDnoOxm49W683CPwQL4Y4mA7CZl2uTtUo2VoKhVlhtP4ybv8HuHRqAdXdqcZTrbGlyVb9L6zBlXZyFBAHs/3/EoYEtlPQoaHjx6O8cLICYJrwBOKdW0tZIpsUZDKuWZ+bLOGVPA/NcVuuNXwumXCkDl9NcQouJEJQrYRrg13vYSaS6kPmLKjx4/3OVkgZQBejHmcJUqh4hI67nJTANmuATzWB8drMTaGo/hbgoGB/DWaMhqGk2yzzAPPd7OUDgV/43uGvGXh43MS+leWIzfT+8Igb+YcWHXnenHWol2zM93icRyDuWBxko1INtwjzpQhP93JCHNIz5F3Oj4JwA3fMea0gVBWsJJlU80A6OS6qplOny3okPV2zgwz1QAH5p7GD3AezFxV01JwrzMZxttNMlUNxxoI6JDyfp0SgWDmxuUa8D7nnuNuO9MZyojEgJFMMOh5xj7DPsq+wczHvCjMsmz8OJuUrMcZ+XclKkA1go5UmMluaXml29gkPzudHkL6q+RhT46HfBgDnWF049oKm254X7KHACHuFXwCKmnz8cVjPZhnF/jxo+lYAKQ8/xqn9vZ3vEM8H6A1Pg4InYv3ousjf3Qiw7IeK3ds4Viwmeg82DcLmWNfIppUTjdRNrRfHSwrLPiXLYOi0NGmEHfKH3uQxyjq1MhC2391THqyW93aejoGztW61iUyAjDr1JDaMTmdm0xoa/Y100nO3X8gZERaC2lREibW4qznCPY1wPzsbDhZMtRGn1hLcZSmDGDZoT0/tytK7iCzS//kTxsAbABwewHgk5/0hPBowjss+T51jk16YStRxw9jw2LCuOzancVJU/kmO4TnooLlHEW+5xZ/QJdMRBgu4nhFmcZiW01gyEJCqWiAUBjkT/FvjDUG3Hp6vMtFPDGWGwCOL2bdL7w23sPvgDR2yvF+jD73RTi6vN9QHEyfmwVqD9y8JQyoipHnunvR0I5sD/8+duRoFBvWOKYxHRRSXixla1QSoVzmUkYYQMsmmE+FsjNMjwFCRgJMlR8Agu8S0ZRhMDRCUrXeqsBDtkmDBXukXJQN9/I9+i0r4jPpZ5ZXSDbQ/C9yhCxgK5iRDTWMSHsECnr8hIIxooIT+pngE6Y1w++0z3fVTEWEmTjCrLAzwWYEq+yZsPndmEflGYZwcEaG5Ux/na+GmQQxMh3KQ4OFXKjzJ2DXWAXTV4GqkP+u3D0YcikARtCoYxWgLUJt7HxMhpwrk/bTsQkiLUBNMWhRtmks1gry4XQOQCRsG3PW0Fdg5VLqSMbIMVfuahr7yU9zdmW5HF9ZjWT2PCc10zUE8OQ7BcNeSgLpTPKemrWk/zwn/vOEoALOaLMAWoNfAzfZGAEk7VP+hlCVI7LAQVDvhQO2vBTjQvgx+rSxGawcFGs6PFPhIOAcTM2mk7e6lLtA0R8Y+oMH93fLyxynl6kYu3dTpJiTW87p8xKR320vuF3m5a1vBOji/ciBZxFiXF5Z6ybGcw3silAoIcTpbmlxuTBs7HRei+/z3SuuvDJ30G6RYzpwakMHT6aTiI6RbQy9VXJ4Ccm6PnItZZQkQr+ptpI1K+tHwOkRg4JiwTm6HycW+eB4O+am8RA5iPcVNlS9o97V+WBu4swmOEy9xn+UkkHH7N93oIT0k2HLsmBLAVSvuvaayJVlgwbAamVhMeTtRinenaBsV9iIW9/61jE+phJIeBDNCKdrdS3L9gD2SgmmcIgmMtJDVCtsYiknlX1Pe7O8mmxtDTpN3TCSQK1FTJoyjOeUski8/yUvfVkDgA0Abi8A/Ip7fkkwICxsFhWLi1BNsFCEZkrisBNZJUorBIAaFRYkrA+fs6AwFsl25Q5IAYrgRs9LFkID6HdYVCxGlHKAsJU80zR2p5XdkG5OkY1BWVs2pfbYyAcR+OG14Tmq8EJpBoCcir7zfnaAmTBOP/guyoU2ydbwWc2SCOYsJiswkEXgJwqtzruSIUGe/o1NAgFSyk5njaxyC8Zzaak/dgtFYokPWY8EeQkSkEMPlKscQEGJYYv6/FaZmgi/FUWmvDCOAPj4fCPDKBoIcmj0agFffThsPeXmpZHnGUsruauUi77IdPIzlWaeMOJ8oE3R53JsYTB5Q6coWEyVeRi7NouDQ1sF0s5L/p05XMnQLCxkSJtXh4xWkl0OBnNskBbB+zlmTgCh0wJ7ze49gSL5f9RZNMRJn+rfo59jXZ8DW7OitEfmNIAOxn6CvbJ5ZONyYYyx0lHaZSaZUtvk/NSBELDTdlmJcBpKuHksiqQPysUwLobWDGvRJtkr3gOYR86OqfqgNurez2dXXnlld8c73jHYIgz1+iYAN+c865mUFBLtkR+bwcj/PH5sMXY13/rgrWKTEP247LJPRA7g4rGjEUmgD6ZTsJbITY20BeobTiSTyQaT888/P5xTTqzgXaEPJifikAjzek8AoVs4X+lIcKKLdUStHxmyHkvm3TGnLx5FF8cWEu3ost3L5YQUnF7HluLXtAW2l/nK2MC+R94hciHGv5V9QN6Ch4hylE0jgGXmiHl8AjbmNu9Ft+EIIw91IUwy7XcNC/Aoi+Jucp55wfnnd5dffnkfeSA/9H8v/2Tm7pa6gBlWXYl7FheW+7xKdMCeffPdRNmDxjo+cPDc6BsFqSPHspzUsm9/Ropoj6wshcsHZAM7lTOvNgD5WDlOsmwOijnjhozJBKBcsTaKHncu9nl+xXniWaYYqMNkKPkOcsf26HjqQNFOdYnAuW97ZSddi+o19aqObejoOKJqLPrF/FF3r6ysdhdf8ooGABsA3F4AeK+7f3HPiOABeZ5neHQlnKZx56dhE8EdCoPkWj1vFk6wL6WWn4rFhWRuGp/LPMk8GDLRQw/venk5WLvw+qnrlBOgmyqlKVC66cVlHhL5URFCKps2AlRUdZrCkyuAVOagBqcqVvOxDPMY/pLez/payeBEyJVcq/Wsm3jsaLKYfkdwByMV3uDycjAbAkjen6CRHLbccZ0sUOYC1uxssFGlplXkY+3bF8aC+4JNWss8FBgKgP0i4cOuix22AlRBoswm70axCQQYF0NqykvPnHCE33f8IldxcqpjFy6XbJDjyH2Mex+iwZsvidOCHR2KNIi5e24wPzIfyn/rjDgXBRyyRsqMPCF2AMOemE9GO6wDZs1A7jdXzmdreB1D5yvvoi0wzAGaykHueu2h+DnDdHUlGOBkk4jgpvVbgTmayqT1mDfTM90K+bbT1JybjAR3+s7YxukqheFDphQEJj8SRiWSz0tZCZ4FgNq/b18wVRRpD9mzS32861YWFyKMBGiPdT0xHcXSF5czPO/axMGiH56YMjc9333q6qt7AN2zGaWOGvmkYUzZBkUpnHQz+p2P2PQAFJPTuWnkWJ7K4DpnPWf6RO4Ud62F8S2FhHO9LHa72Wld8oq5D5lSisWCzqEryLkruoL80dzokSywoMANFnye6zJrbMKQ0Qbem+1LALJnT+4aNhcWxi0dwIyY5HzPPmnQ+SkQkD3nPtMqdLgG6zGdacApgFinC6TG9yO3twAcwKr61XqAnCvL79yH3oHRRo/f/va3j8L5t7nNbUqaSOYEEo2hLTJc6mzaQ5cyspJg0yL4bMZw3UTYk7SCoktpewCWwtLS1pptDxAzPhYy5vcIAZNDupagOuS1uVGl62R0KNlxNjwNqgnUjg2/C+J6xrKwz7ah1hvaKNeydo330A7nof1Q9wkY6++pr/zps0PXkcZC+Zay217w6ryv7Z3vov1GSWRgAf064sj+kle8sgHABgC3FwB+7Vfes9u1CwZgI3YtWiJAwyxtLQDAUG2QoyWbNb87JjxKwfClXi2eWhjQUqfNXBuUQ+zwjBys3PnrpM9dX1meIBN6OVd3oWd4XJSye7JhKHSpfZ4nU0gbDHm4gMNrhvWg7MxMbl7QWw7afQIverLftEE7U6Gwk/Fot2/fgVBkYfTj7Fu+k2Er3hHh8FKQOg4ML8ciGXq1DwFOS9mc2nNU1ioX3s1/Kk5O3AwjWBLaBdkDVi2rysusCtwFdsqBPBQKny6upBefiimN5tJxCsdOlVMDNiNBmlwggI0giLbDOEV7qxwjvXeBtsBMZc2Yk4fjLldqtuW7+S9zz1SSgmTmV8olx0IZwtzwPIDW4aNHYi4KMjAeAA/Gmu+ee/C87la3vk2MDWMI27J/3znd/B5yzNa6/fNZIDgOh98c68YInbJrvNsKxbu4cDRAOmsFdmlhMc8cZh5FntXmZnfk8LHcdTo71S0eW+z2nXMgANvGWhbmJc8Htmd2JgGNY2Kf4rOOE2E2Y8exc1dZhmNQCugytwZpAYTGYM1ydyr3wzBxpUFPkCGwDahWQroABwF6gKCSHJ9GLU8mQI4yhiTl817AEGMWZXBK+Q9+Esrn/dZUk2HluQJtQpkwuzIuNTOrLoj1AjtU2q5zZv6tjLhrl/7pCFqfDkAEGCIXkjXhs+gzQIj0AsOKtN2wP3qQth08eF6wWQBzHST1G+vATWF8l6hBApwEM853dIn6kh3uFvsmpaZngcrZ2bQ7ah1u5ZglwEygE0Cr5IuSj0ytxDw+LUvwRJpGhGpz3ntSTjBtpT4k8hTw0Q7nBm2Oz9E1BeQKyGUFuVfGTx2lnRBA0d46MtLbgpIvyr9r51/7Qh91EFMmuVEEcMt8D1tRyAXXjUCb5wmmT3ASyk5b9ZFznnvDiatKbOUmoAz7q3sy8pC6dqZscrO/OsiurxrIcbCCIH+YzYz2jW+FHqgBoX3hb+GklaiLvzcAOMA9rQzMNmBAdwE/+BvvG6EQvI/YIHDOgaDjCbvCOEQ19fXM5Ym8qLU0SsFezMyG4VPBuID5ux45TcXT00i48Cw6q7Gn6j2LhhzA+V159qwgENAVHmMp6RFGsNrRiTERcGkMNGgqBL6zWimSgcLIY8QscyATEUqbsFBhJ9Kowm7kuZgqnbXVEl6lgHLilp49CwA2PRPMC+2QAahZUT1HlSxGHRDMWHhfbcCzPEnuSg6QR9YbsYLYZZfHrGVIaix2QnMP43YsqvbTy4lgUFfiNJX0xk0ij9zD5YXunAMH4xnn3upgNzE+E04BxU5hQVbXMx9wD7lEHOFX3ofcYgf52lrW8JpOZsedzORJ0Z/rDl9XysWsd2vlXOO9c2ksYwPH+qCI71ZhoFdLPhWlaYJNKCwNBjoVMYkzY1F7sJ53yHyZkwFmMvevY5My8ybyAnNXKIo/GGDAUsndoZ+MMyzPuecc7BYWj0ael8aB9+6Z3xWMneFWCw9zjzUPOW+a4xKpZcd8ynmbyeqePy0jkgY7wz+HDl3X7duT6Ri56zDXGfJjBGPzxUTWRWQMGQ+LEa2uZt6tzhZggjyodCBypy1/t8QEn3tiArLg94VjWevt04c+He3miMJoWzl7213xubucI8QyPzMK/FrQtpwu4dw1pAYgM4WCdyA/izvTJuerhlPnrAYN6oEY3+Xl6L+Fq3XC6siAjhFrU8Bs/3m3oCT6WABUvRuV9/UOcAmX8p0abOgUydjUz2R5xjovR+3xPXMhVeXKKfpZHADZMR0aHdEAgrER6MSNK7WeEOgKWBi72snI37NdJxyVWO3MlokUkKuPeud2qJyXoMd3+z2dS8GefbY/yXwNygfJSKNn1ac1iHMu1P11jHL82eGe6zrHdLBpJ9ZQlU9qm2K+lbJcAkABGs+ux1dHQpCmDdMpj/5z9GCZN879uG8sQaXzW1tmm+p3yggKQl/6m7/VGMDGAG4D+qvKwDzioQ/sd/9GqKMczZNhlkFyPDsL4zSBkvNEwIeq+ipjJyuLl9Cx1Lu7OjXMPCdAx2yGUFUWeo0oI+qJkSQPSOVZLA5zyXiuXqjvANi5SPGK9fT4SZmM8NSnZyJpGDBwpzteGO0jt+n8294uFhVgFyNM7gsFP+nH1PRshEAIXZA74xFtoQzWMyGaGk979u2N+zzm7Zprr+2pe/qNUaV/1LALpmQzDTGA47pPZ97kJz/5ybhn7549HTt5eRbhW9JZ4ti9co5whNx374pd2VwCR4EqwDpkupX1/Tp3DfbGjXdT0yqZCvM/ySujX4xJsp1THXADgGmoO89R3Yr+oJQEoRFKxrpx/waGMUuMCEL07hnPLNuAcvTM1zx/mecBNgLUrOXRXn4u2xt97PL9AbRgQDbW8zSa9a04ezU2P8jOejbn/N4YT3Ms2aWdOX4nnjubYOloSfafyCO5ltdiPuCgJOBKh8c6fYbnmEMyPswjWGtkIFPDLvgjhw93B885tzt0+LroG+NuQWDas3dvnhihsTP85m5L51GkAcxlYjz5hmH0pqf6kkA827bEvaXchCejaDh9Fz91zHAkHLc4R3dsPMbWtUaoX0PXO2LlVA3mh0yXxaE1bLEWy8YCDSyGWkcP1lkjm8Agw4M108T3NOq14fa+3okqwESg0vetsFOOu5pUA22/6v7JsmvkBZjR9w3SLDIfLfRFVSdUfRZzdivzQQU8sMuusRqMCNBsl/fU+ozNB+yGgPmj0Ll/U062k/cHABkn93AiHELWrrJy7EOO42PBYttm151yq4FjDaZpu3OpTlMZjO+gkL3ts2SOoCacKlJOin6iPZkrPAgp58aI1Df2V3CpM4HsB+yducPJ6OHY+D6+N13SOGDZ45kFlMnCCex9n3OfdztXavApYOXvOgB+x3GoQTzP10kM+ZdDFmJ+cDxkKRsWTnVJTUC+L7v4kgYARxkAXnTRRR3/ffzjH4+Jete73rV7znOe033zN39z/Bul/OM//uPd7//+7wegecADHtC9/OUv7253u9u55rv/+Z//6Z72tKd1f/mXfxmA5AlPeEL3ohe96IQE+r/6q7/qnvGMZ3Qf+chHugsuuKB79rOf3T31qU/tn3Eqv8gAPuSB39B5TizgjFAeeU0WRQ1DSV2imenuk5+8orv9bW/X7dozHyEs8hxQ9O7oJWkZtiJ2AJfdfxgtFshsYfBQRsjBcI7FYa19tbqy1K2tDurCmRvBAkKhCf6CXauKcwIcDTd4KDyLPljF48f7XDqSl/NZ6XGaHDzFBpCFZN3M8yOfyTy5VDgJVsK7H5/iHJQ4H1TwyQI2pBuKajONsyDZkJ5huGSekkEMr7acvELY2kRjwJJhMsKPGsmoB1dCfubroDDcDINxTaYhWTnemTljhAHLge4LFF3ee0L4pPd0S/iDkKp5YhoxctuuvvaaaDeJ6wDrKJx9/EifDM/7on9LC1kAeDrLB2XocCMAFGwgQFAWzbFeWDgWLOgCjPSBc+PoJHcYHzznnG7/3ixeC1tNcj7AkX5qhHiv+XE6D25+CDainJsLuElDOJXjXBjmYBmrM4ipkciGHPNeE4TkmDn3ZZSxJ7F5qhQs1/CFY1Ty1NJwDpjiGhzhdGlI/E44ZiS9VecAB6NEqAiA5tFXBfjUbIIsRG342dWokbPmmMZecBTGkO3kG8lY8B2MU230bXfNyBgaS4OXdSStxQlz6N+zPclKCSp0KmTi/LcsYB0CVMcpB8GeP+23fxcwyABpoNUrGmhl51y0fcPP45xkDb/fYb3XgE6wUgNAwZFjGX1az9QRZVOHUL0vQGmwdSSApHPi+wTWwQyyeWIrAVAwdoSStzJdRGDr2AsWhwGeclcH1eBF50QAXj/X5yc4ypxdAZNydB46fjH2BczW+qsGWLwDZ9VLHcW/dQgcn2QpE9jJApIHK+C1z8M2sgaIrn2dRPVzPRdqcCjo492G6l336mPHnXvjiLeICpTdw2z6KLUaa8CIU6dzRmmsiy7+7QYARxkA/umf/mkstDvf+c4xv1796ld3v/qrv9p94AMfCDD4Az/wAx33vOpVr4oE8Wc+85mRn/JP//RP/QK95z3vGTvbXvziF0dO3nd913d1j3zkI7vf/M3fjGdedtll3d3udrfu+77v+7rv//7v7973vvd1P/iDPxig8lGPetTwvL7efwsAH/7wR/TeKJMtcp9K3gPgbnFhITxOWDaS6j0rUlASLAc1ysYylAD5zckK5G3AVPEsPTMWR+YN4W1OR8IzOy75t94uOV6xeKqdWxgOjHwYpZK0rrfNhoEAmLPlfNz+MO800BhIlMPWVu4W08DxPg4+ZyHG1v7C/LBRg4uQEmNjoWWZH0OmgBr/Rr/+93//N8oI0K6rr/10vxECZoh3IktzqAjnnXfwVt3VV38qErRJyA/vrzApAFt2Kl5zzXX9ZhpkFWzkNCdvZE6PyuW8886LnDHaeOvzb9VdedVVRea5s9KyOnGmaSleyvviaC1Kp2x0UdaH9qnkrBdIkjzAxyLRPI/n+EwBLmfihsIswIh6WsqMcaOOGZc5WihCWEz6bAia72t0ZOty7HJOaqyXSxFuQtlhZAtTpKJOFpqdypnakEn8mahfA44aHPAs7g8FPZxrBNgqKylAV9SA87zgrj8LO4xC2ayi8fenhi8NFXXaBnmXMkPeK4jhOz24GyvFk6tdhQGUCkDjuYO8oQS1MlOCiGSAJhLMlY0sAyYmd6rmuQeZH4gh9bt12wbfKYXOSwmmnoUuu+NrlknZ+7xh4CfTpmHlPsFUDQiHf3d3rAZWh61mCocBj8+t0wV8r/qB9rq+6u9H3zfzqDyBQoKOvNCfAeBg3qpyNo6/c9ixqsfaELHfI+qQAE7mLkFdr8O6BFj9u8t6ENDFz24scpoDjBUmWIe0Bt41GOR5tM+2+jdBn+Nvn5K1y4oRgLmo0EBB8+LYsjFHds11bB8GczPXuPdpM3xn2oyc0zkHBoylzwIg8y6BKHKLcSoh87r99dglwNQuZU3Onkwo600HwmhG6qXUP8qnf2+lK0KXcNpH2aUO+EtwTj8GJV9qEJ5jvNGZAkMXlpdXuosvaZtAQt43p6PgMNyAwEc/+tEB7F772td2j33sY2OKXHHFFd3nfd7ndW9729u6hzzkId3b3/727mEPe1iACZg9rje84Q3dd3/3d8duLtian/iJn+je8pa3dB/96Ef7hQ/796EPfaj727/92/6zG/tFAPjQb3lELDpCre4iY4L2u9eKsaBUBwV0I/eF2lgcyF0OqmbyLi1kiRSYtYWFxW5ldT0MjeAB1omFYt7WtdcdCgCysHgk8pcCbC5SMHSsO/+884IhJUeII5lg7fg8NoUU5UTIFkVDQjpgZXMia+MtHc9aTxqY9fXctbdWdhmmcV/vpjmxgx2Gi1ncdnFpodtdqsib+xJ5Nnje5P0U5cK7pgw/lp1qx0pocwA0kgmEyQvDtMFGlqUAWaFsVqhXtxUsKlfkpbGRIFjJQcmDYcUOeBpshkjmBBaQZ+qZR1/YGT2ex69lWDZzOJHLzNQgPK9hizBhSXJWmSWDmDspVU562So6jXGAopKvp4LXINfGZrg/8bwq/GF7fK6smmOZRiCT9u0vn/G9uLcAaI0I74uzO0vul566/TkBoBTGpGbMNIA1WLFfNWBRZhpU76nBhH3X2YmdwSXspUEVmAwzNbB/jt/JjK+GGBYh78sUA9Zc2r80rjUIC9lUuyEUV50AABv2SURBVDj9t4ZP9kb51nIJoFOMq5/XY1uzarWBrGVQA65absrVMbLN/JQdMVHeOWB7fJfzyDYK2s3bk2Fz7QngQkZdqU5Q6q9Z401WrWaf6nb7TgFaLa96bdLvcH76874HZ3brkNh3wNtwn2pgiw6p2+MY9vOO6GIVJva7tW2wPTJN6Jh0wpgfk325qUFOY4a6M8WDMl+DQvI8V50JNCJcHXIpOXch71JH0JBvsJpl7cXPsvmhBt2ASj53vfTyLPPX+RafF7Ac/XabfwXS6nmrbGrnqXYKHQfArQCRvqvnXa+Cuqg1yFm+UI6mIYxPBLtnfT9LCKVzlaREPidTaAYn0uQoAQLjFKbV1e6SS/5vYwBvLgCQSXXppZcGgwcDyBZ/Qr6wSgAbr3vc4x7dt33bt3XPe97zIlz85je/OcCcl7WyCAnf//737+53v/t197rXvbqXvOQl/T1vetObusc85jH9Nv16gfs7kzYS7csFAAR8fsdjv7Nb5szMvXu7A+eeU45Zy/M9ufiJUrBMSIbrMidvZtdceDculKyDNR0lG2B8hg2BhrQ2eOTSqZA18BodP48Qx2QuFJQT3ze0wD14trzbBe17QrmFpzVgMmpFrbGrDaGeHuNnCKA2QsOytS8qX38aHqr7rKLTEA2zUlCo3LNBzsrWWOxQ5jn1/QIqgQSMDpdGLnbPoVjY8VlOc/DvYeCq4rqwnSY0e08mUCdYrw2oIMf+qOCQfYRMSy0t8kTr8ewNWGGT2FCg4hwYrGw/zHFdLLtmg2xPHephLtTsi/MmzksuhgUGmHIkdbgOVgX5WBQ80goKiM5NGgkyh0OOPlMjMSyjYVbDscrPk8l0Dk9NJEOq3GuZxEkR5NhWSf7k23oRto36LsV5ECgLPsbL2cY4YB5SX7MVjqufDQNO14jvs539WPaM1GA3urIXjNv2eu35PNcT7xXA1Gss5AqcL7XhascgGL8y32Vq6jXpc3qnoLyjXjfOXcdvEL6XBU3Q7PwbdhjQWTp3ts17k31OJ4t83HoMfaa5iuqOAGaVHrR9gvDakXD+x3wphYedO4J8gaNATZkIoGUfnT+DaErOOedRjvcgT1a9W7NfFkT2DHTAGvdFChCON+uogLq6HbUu5z2CU4BevDdfHhuo1CeuuxrUqpccS8dD9nYY0LmmnctJ2g8iUAJzfrqTm3t1smunMfR5gLuylmFa15MZBLihe2TR61C1EYQcZ8sOpU3ju4LtAJpTk5HDC6P68sYA5twYZQbwwx/+cHfve9+73532+te/vnvoQx/a8fPJT37yCSCMzjz4wQ+OoqiXXHJJ95SnPCXyB9/1rnfVOi2YLsLGj3/847u73OUuwQj+9E//dH/P+9///u4+97lPMIqEFE92Pfe5zw2QOXw9+Sk/EHlssGcc3aNHEixY2RXleYZMdMMmsH8uECd3Ko+BYfsM9qeq4+WCHQ5h9N5gMXLm/KkU+8V2EupdBTOsxPyOhk8ZqAiHPTruN8xaswm1Yaw/V/EavlSB1u8LIwtDU8qFqIDof9SK48zdYvjXKcVCqG7M/MHBjrIeBFS5hQJYjc3aRoY+atDDOwzr5JFpVPk3NyYNuYZVhRxgtHxuH8OgR4X6VJzDirc2vI6DuWzmKvG5vyMrjqOrQyuCggHwMHRbdlMW1g+wWAMP26JRiAr+W2z+HZRbCSNcTj/gd8EiQMn5ozFPw5tAOHOaMkTFO53bjqOyq4GWZzBnLbo8vlB5er/v5LjASIZfp35fCW1n0cvPYO7qeVSDv95xKv0N/FSS+4cBYE6BQV4tz9HQem+tK/jMtaicHd963ij7Wi51X/182DHic+dJjHvJdevXfSmKWzNg9TsGcsyNRDpXse+d/Ley7nBYyNs01xIWjWfK+td6RmBsu0IulHUqRYqVofJic5dlraI95axk73NduRZ7B4Iw7RDgRAZ1ofY6vDgs/2GdWD/LMfMe15mgUsapZ1dLO3iGDpbPq/Vf9K/scs0UnDwZCgcv5gDjxzoDFG3gkJUQccXQ1U6CObE1GI3zz0uprgDNE1lIvtZtNQDMuZHnfddz0/sNKzt+snmuoZohFXyrg/iOOkvZJcDLixDvyuJSADZtaGzoqMow8bvvds7QNp/tGCSATD0luF9ZX285gMp6lAEgi4aNHCTGv/GNb+xe+cpXdmza+OAHP3hSAPigBz2ou/DCC7uLL744AOAnPvGJ7p3vfGete4OJes1rXtM97nGPCwAIkPypn/qp/h7yAO973/tGhX1yx052XR8D+L1P/aFumurpZXLC4NQLXTADcxTFlUOZZnI39D8LcGIqk1prZoRcPhgdAZ2e4gnKqyS+smi4T9YlPau6bAFGeKNjo2ftBbo4crFn8VYZLT29GhRI9ceCLQd8D7MQ/I3vyjTybBWHrKA7LPUGXeRufFB5xo7J2Ekpw1WS7ycnslRKCSXzfdutvFGkAkgjGSqgeH4Jv0f/ytmW/E6IoQagoZQrBlRDG20u+XOpxgwpD8ox1CCHtsBSuBkhtd5YlBCqL8akZixlantQVnbe1oqxN0Yu8ALuCedgZNjtGMamsHrKRSAZczDyeDLnL+WQgNY5EmF29nFznnXZyepmiDhkoTqmie9pcP2+/arngwyyLGxtmEJeAVTzvNK8UsY5BplHFmutvC/+VmoJyVyHkYTlHSvro4DezbEEobWxj+MPI+yXGzYwSoBFLttTg9sa8MY8Wc+dt/W6in9PdN3C8aUs1zKWu/DjHhk6ypacpJCtxjw2iFeXhs6PfJ/rwLVrW6P9nC1endXLXIzdq+gKWN6ogJcnKQj+Uj6pqwBn1iONtIOye9q553ecO/47p/kgiuDaqgGZ8tXwByMek6/kA4IbKWhc5wqStlDywWJmFD3j+/k3csh/M1cAtstRF5FwoDu1Y3xKflnognLqCUBVPR6F5cscZ24kGEt5Zig3KzNwCVB4lroTBq92xGWoErgMCmKr6400uRZPnE+DEz50rHiPOlb9Ljh0Pg4cp8zlZbTZbKjs+Ck5UT9PGdSsq89W9w/AcDpbPMd8ZP6mHgxAViJKyiccmZI3y33smI+TTTYGm2DoU9QGLbnFkh6+t14HrgGBOsw/98GkXnTJ77QQ8KgzgCequq574AMfGACPvL8zGQIebpcnDTzxe54SoG4cJUq4hG3nBbjxWSy2TZSFoUYMchbyNTwwPZNJs6EQACZhdOLo7ngWz4nK/OV3nrlGbl4xjGtb+V5C0TAhLG/+T54IOSKxyPOIxW6y7LoFIBFiYGft2tpmNzszFXmH01O0s8rBwOjTty3ahUGk0O7gnNE63AFO4rkoPJWfyl35UWZmfS2Lsg4M6GSAE+SHqqedE+Mpi9iEUt6HAlmNAs4YfsDJYDdmAuZBUjHgJ+9L0EKOYBAQhXVDHrKKtK0O49UhjbX1coJGaR9gCtDGsVoBCkoNRPNl4vmwZsyBYlQD9JcQLWMb/d5C8Q1ylJwzGkzlZXtTUZ+461MGKpknQHCCz7CdhcHswV7JExJ0axA0qjUYypzKQWpBbkxCtsg0wVidR6iR8DPHvnZodE4GrOSJoHFQpmIz5CvgSsM22BXJ51Pk5y1nYeiYX0M7YTeoc1jONJYNVH7M7pwHgzIpzkPnRAAHZB1EDAwXRtcCsxjtLN90ghGr8gRrB7BnUqgReN2nu93n7u/Wy1Fb3qdB1Rj73ABRBfw4D2qAYTkU5V07LgK+fl5zRFa5TrifdVDmjSBKACZAseai7a2BZP2Zht51WOtMZZxHRpLbVm9MSvCUOVy5Xv1Zg1uP+KrZT/uSMstNOGVaZCixf17+HUfa/LlcI5vd5HSCqlSUFDKf6k9IAehFe3sWLgssJxhJnV332/awy7mfB6VsTQ2Sc43mhr860sORh97HzlVzmtkoyN8GwBJQTZpNFrnmvqlCBMS6CwIAWSYTmc5E+JwRVR2fJI2jpEFgn2R6S4pJDaoEcQJd2jAMdNU5w3NjMLexI0X3RTkqdG6SAz1xgU2EyWdjVjhIMNmDedLrbqo1cFpIqQ9Le2o7E9GAcsFW0yZk9KpXvz6IJTYD3pKvkQ4BDw8MoI9cO3L22ATyute9LvL1uGDsKAEzvAmEmnCGcv/gD/4g8gjrTSDsJP7Xf/3X/lXsLoZh/Gw2gXzsYx8LYNquJoEmgSaBJoEmgSaB0ZcAG0TrsnGj3+Ltb+HIAkDy8qj5B+BjRy07eH/pl36pe8c73tER6gWovfWtb418PnYHUxOQUi/DZWAoJ8LOYTaMkO/HJpHhMjCUgKEUDKCPXcCfbRkYPAk2oxCuvqV4FG58YRF5+sD2T8/RemLr897RGpCbqDVtnNs430RT64w/9pY4txF63e+os3rsWFQHqVMjzvjgnIEGjCwA/J7v+Z7u3e9+dzB7gKq73/3uUbYF8MdF8u+znvWs2BBSF4IGMHoByKjrN1wIGvrai5zCpz/96X0haN7xuRaCJhR8SwJDjEvr8xlYtTv4SksctXHeQaGfgVe1cb7lgN5bmt4WAN4S+31jqmRkAeCNNXyU/t6UZ1OeozQft7MtbW63ub2d82mUntXm9i1jbjcAeP2rrgHAbdBITZHcMhRJG+c2ztugLkbyEW1ut7k9khNzmxp1S5zfpyK6BgBPRUo3cg+7il74whdGOZk6vLwNjx7ZR7Q+D9IIRnaQtqFhbZzbOG/DNBrJR7S5fcuY20y+W+JYn8qiawDwVKTU7mkSaBJoEmgSaBJoEmgSOIsk0ADgWTSYrStNAk0CTQJNAk0CTQJNAqcigQYAT0VK7Z4mgSaBJoEmgSaBJoEmgbNIAg0AnkWD2brSJNAk0CTQJNAk0CTQJHAqEmgA8FSk1O5pEmgSaBJoEmgSaBJoEjiLJNAA4GkO5stf/vI4aYSC1Xe961273/iN3+i+7uu+7jSfema+/tznPrd73vOed8LLOUnlU5/6VHzGOZD8/RWveEV36NCh7qu/+qu73/qt34p+e/H5j/zIj3Rvectb4qNv/dZvjZNX9u/ff2Y6NfTWv/7rv47x4sQYxuxNb3pTnA7jtV19/PCHP9z90A/9UPcP//APcVINp8387M/+bJzfudPXjfWZE3Je/epXn9Asxvbv/u7v+s/YRcdpO5ySUxder49SovD60572tM8ovM5h8Dt9sSv/j//4j7t/+7d/6+bm5rqv/dqv7X75l3+5+8Iv/MJt7xPF5J/xjGf0xeSf/exnf9bF5LdDPqfS52/4hm/oaG99cbY6Jy19Nmt4VOb3RRdd1PHfxz/+8Wg+uug5z3lOnCLFtV3zdlTGmD7dWJ/PtjE+2dpgrnNa2I/+6I+GzT1bx3o79MINPaMBwNOQMGcLP+lJT+oAgfe5z326Sy65pHvlK18ZZwvf/va3P40nn5mvAgD/6I/+qPuLv/iLvgEc9M25y1wY0Be84AVx/N5d7nKX7vnPf34HuPj3f//3juN1uFC8nL8MSOR6ylOe0n3+539+x5nLo3C9/e1v7973vvd1X/ZlX9Y96lGP+gwAuB19pOYU8rn//e/f/czP/Ez3H//xH3EM4c/93M91z3zmM3dcDDfWZ9p21VVXdb/7u7/btw3QBnD14uhFxpCxP/fcc6MfHK84fPQic+XFL35xHMvIuduPfOQj+6MXd7Lj3/RN39Q97nGP677yK78yDphnHAAtrM3du3dHU7ajT5dddll3t7vdLY6SBOQztzh96LM9TnI7ZHMqfQYcMDd//ud/vn8lALk+wvLG1vAozW/mJDrqzne+c/QHRwYH7wMf+ECAwbNtjOnjjfX5bBvj4bXxj//4j91jHvOYOHULHSsAPBvHejv0QgOAN5EUYUkAEnhkXl/8xV8cjBIeys3tAgD+yZ/8SffBD37wM5oOM8bZiT/2Yz8WR/Jx4V3DEAKaMH4f/ehHuy/5ki8J5gjZcPH7ve9972BiavZlFGQDG1czgNvVR+YDNSEBVdaF5BxrmFDA8ZlgAZX3cJ/5HADIedaM/ckujoED2L32ta/tYIu4rrjiijin+21ve1v3kIc8pANkPuxhD+s4G5p5wgWrxLOvvvrqM35E4jXXXNOdd955wX7d7373iyMMt6NPrAXYbua+F0dJfuhDH4qzxc/kNdxn2gI4uOc979kbzeH2ncoaHuX5TX9wXACBj370o8/6MXb87DNHqJ7NY3z8+PGwuZAuEBDO5VvCer4pdEljAD9Hqa6urna7du3qLr300u7bv/3b+6dASQOghsMsn+NrdvRrAEAUJ2wAwAUQ94u/+Ivdne50p+5jH/tYd+GFF3b//M//3N3rXvfq2/WIRzwiwrt43r/zO78ToTDARH3x91//9V/vnvzkJ+9of27sZcNgaLv6+J3f+Z0BMN785jf3TYCRQHHxjjve8Y431rSb7O/XBwABf7B+jNXXf/3XB9MLYOLiLO0HPOABwfgdOHCgb9s97nGPcHZICyDsRn8BPl6kA2CY+D6e+pm8/uu//qv7gi/4gmABYey2q0+ASdbDS17ykr57OBUwFIuLi93U1NQZ6/ZwnwWAH/nIRyKdA+cNtg9mWgb/VNbwqM7vjY2N0Mcwz6w3Ule2Y96O8hgP9xkHHAB4to4xY4tOwZ7UQPeWsJ5vCkXSAODnKFUYkNve9rYR8iG/yAvABBgiLHpzu2BxMFqEiGCv8LBg7lAm9Icw9+WXX94zPPSPEO8nPvGJ7p3vfGeARUKEhDzri+cB/mDFRukaBkPvf//7t6WPD37wgyPsbRicPjtfeAeM6Jm6TgYASWWYn5/v7nCHO3SENMlVJGxKeBdH4PWvf32MH4xvfdFPwCypD8wD8rDe9a53nXAP32dOPP7xjz9TXQ6wg6MCIP2bv/mbaMd29Ym5DctJPpKX84gxv81tbnNG+n2yPtOQ3/7t344xO//887t/+Zd/iTVJ+PTP//zPo52nsoZHbX4D6llTy8vLMY8Z24c+9KFn9RhfX5/P1jGmX0QUcEwJAc/Ozp4AAM/29XxTKZEGAD9HyV6fQWeCEioDON3cr4WFhWD9SGr/mq/5mgBHw0aN3CfCfu94xzvCeJwM/MK8EJr4yZ/8yZESyfUBwNPtYw2M7DDAmQ0ThAWR5Zm6TgYAh9vC5hjAIAqXHL7rU64PetCDYn5cfPHFJzgC9fNgFV/zmtdEPt6ZutiY8md/9mfde9/73hiDGwKAn22fTubc4BTe9773jU1GAK0zcZ2szydrByD/K77iKwLsw1CfyhoetflNNIYNSEQe3vjGN0YeNhEYIjEnc1zOhjG+vj7DAA5fZ8MYY2OYpziYRB64agZwu3TUqK7nm0qHNAD4OUr2bAwBn0wUKEsYgmc961ktBHyKYe5RDZExvqcCALkP0P693/u9ke+5XeGVz3GpndbXfviHfzhyG9msVIfet6tPoxgevL4+n0yQMIWwtOZ33pxDwPbvgQ98YOgq8lXP9hDwcJ9h44evs2GMWcOkWrHhx4vwN/psfHw8IlCM++mmqYziej4tBXgjX24A8DSkS47cl3/5l0dCqhceGOGmm+MmkGFREPJDkRLeIyxIcv/Tn/70YAS5AMHkiQ1vAvn7v//77qu+6qviHn6H8bo5bQI53T6SJE9IkDC6JVCQ0Utf+tKR3AQyPO7s4CW9gRC2YJYNE6973esit40Ldgs2bXgTCJtcDHsSWiZn50xsAsHoAYTIx3vPe94TgLa+TBo/3T4BkNmVye5iL3Yjwj7t9CaQG+vzyVQdYeAv/dIv7TfHuAnkhtbwKM9v+gjoY4MSeZnbMW9HaYyvz1zZZ9Ithq+zYYyPHTsWqUb1Bbv7RV/0ReGkMt63lLE+DcjyGV9tAPA0pGkZGEJg5KBgMMmxIWeOENrN7aLO28Mf/vAoYYPRJgeQUAr5JvQHEAOwpVwIBpVwEcZ1uAwMIVQ9UcAj3x2VMjDsIiM5novk/V/7tV+LDQokFtPv7egj4IIdz9/4jd8YQPA///M/I0+MjRJnogzMDfWZfrP5h5I4ADfy+GgzITXAgJsDADVvfetbI5+P7zBXAIrDZWDYWMBGIjxx+swmEXY/7/RFKRbCQmxMqXefs8GJsidc29Eny8CwC550CEAfu4DPRBmYG+vzf//3f3e/93u/F/lxBw8eDNDKfEQe5FXJrrAx5IbW8CjNb+Yq7QUAABJIW2DHPSkpRC/OtjFm3t5Qn9mwd7aN8fXpjuHdzmfjWN/UerMBwNOUMOzfr/zKrwQjwu5CdidBI98cL/K0CJVde+214U3B3P3CL/xClHbhskgy4K4uBE2/vTD8w4WgX/ayl41MIWgA68l2pMJUAW62q4+AZvKwKATNzllAAQDwTJSAuaE+w+YA0tg1SQ4VIBD5MO4YVS8S7EkDAFTVhaDrewCNgBDCq4CKJzzhCd2LXvSivhTOTq6J65MzzgvAlGu7+oSTBGuM4wdLDiPBeO/0dWN9Jo/qiU98Ymz+wClg7L7lW74ldgHXNR9PZQ2Pyvwmt/jd73536F/A/d3vfveQP+DvbBxj+nRDfT4bx/hUAeDZtp53Qn80ALgTUm7vaBJoEmgSaBJoEmgSaBIYIQk0ADhCg9Ga0iTQJNAk0CTQJNAk0CSwExJoAHAnpNze0STQJNAk0CTQJNAk0CQwQhJoAHCEBqM1pUmgSaBJoEmgSaBJoElgJyTQAOBOSLm9o0mgSaBJoEmgSaBJoElghCTQAOAIDUZrSpNAk0CTQJNAk0CTQJPATkigAcCdkHJ7R5NAk0CTQJNAk0CTQJPACEmgAcARGozWlCaBJoEmgSaBJoEmgSaBnZBAA4A7IeX2jiaBJoEmgSaBJoEmgSaBEZJAA4AjNBitKU0CTQJNAk0CTQJNAk0COyGBBgB3QsrtHU0CTQJNAk0CTQJNAk0CIySBBgBHaDBaU5oEmgSaBJoEmgSaBJoEdkICDQDuhJTbO5oEmgSaBJoEmgSaBJoERkgCDQCO0GC0pjQJNAk0CTQJNAk0CTQJ7IQEGgDcCSm3dzQJNAk0CTQJNAk0CTQJjJAEGgAcocFoTWkSaBJoEmgSaBJoEmgS2AkJNAC4E1Ju72gSaBJoEmgSaBJoEmgSGCEJNAA4QoPRmtIk0CTQJNAk0CTQJNAksBMSaABwJ6Tc3tEk0CTQJNAk0CTQJNAkMEISaABwhAajNaVJoEmgSaBJoEmgSaBJYCck0ADgTki5vaNJoEmgSaBJoEmgSaBJYIQk0ADgCA1Ga0qTQJNAk0CTQJNAk0CTwE5IoAHAnZBye0eTQJNAk0CTQJNAk0CTwAhJoAHAERqM1pQmgSaBJoEmgSaBJoEmgZ2QQAOAOyHl9o4mgSaBJoEmgSaBJoEmgRGSQAOAIzQYrSlNAk0CTQJNAk0CTQJNAjshgQYAd0LK7R1NAk0CTQJNAk0CTQJNAiMkgQYAR2gwWlOaBJoEmgSaBJoEmgSaBHZCAg0A7oSU2zuaBJoEmgSaBJoEmgSaBEZIAg0AjtBgtKY0CTQJNAk0CTQJNAk0CeyEBBoA3Akpt3c0CTQJNAk0CTQJNAk0CYyQBBoAHKHBaE1pEmgSaBJoEmgSaBJoEtgJCfx/G6xSHWhvXrgAAAAASUVORK5CYII=\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure()\n",
-    "plt.imshow(im2, interpolation='nearest')\n",
-    "\n",
-    "coords = []\n",
-    "connectId = fig.canvas.mpl_connect('button_press_event', onclick)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The $x$ coordinates are pretty close, but there is some variation due to our shaky hand (or bad eyesight), and perhaps because the metered panel is not perfectly vertical. We can cast the `coords` list to a NumPy array, then grab all the first elements of the coordinate pairs, then get the standard deviation as an indication of our error in the mouse-click captures."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "hits2 = np.array(coords)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Save your work to a file\n",
-    "\n",
-    "In the next two code cells, we assign the clicks that were in the list `coords` to a numpy array `hits2`. Then, we save this array to the file `hits_im2.npy`. This is a numpy-readable file that we can load back into our workspace later as `np.load('../data/hits_im2.npy')`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "np.save('../data/hits_im2.npy',hits2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fb6dd532c90>]"
-      ]
-     },
-     "execution_count": 45,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "plt.figure()\n",
-    "plt.imshow(im2)\n",
-    "\n",
-    "plt.plot(hits2[:,0],hits2[:,1],'x')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Set the scale to convert pixels -> meters\n",
-    "\n",
-    "In the next two `imshow` commands, we will choose the corners of the target shown below as location 1, 2, 3, and 4 and the center we will determine from the average locations of locations 1-4 in $\\times$ . \n",
-    "\n",
-    "![Target dimensions and click locations](../images/target.png)\n",
-    "\n",
-    "We use the same `onclick` function to create the `corners1` array for target_01.jpg and `corners2` for targete_02.jpg. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure()\n",
-    "plt.imshow(im1, interpolation='nearest')\n",
-    "\n",
-    "coords = []\n",
-    "connectId = fig.canvas.mpl_connect('button_press_event', onclick)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "corners1 =np.array(coords)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\" width=\"1027\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure()\n",
-    "plt.imshow(im2, interpolation='nearest')\n",
-    "\n",
-    "coords = []\n",
-    "connectId = fig.canvas.mpl_connect('button_press_event', onclick)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "corners2 =np.array(coords)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Set the absolute position and scale results\n",
-    "\n",
-    "With the corner locations save in the `corners1` and `corners2`, we locate the target center as the average x-position and average y-position of all four chosen points. Below, we plot the corners and centers for both images, you can change the `imshow` command to check target_01.jpg and target_02.jpg. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\" width=\"640\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'x-axis')"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "plt.figure()\n",
-    "\n",
-    "center1_x = np.mean(corners1[:,0])\n",
-    "center1_y = np.mean(corners1[:,1])\n",
-    "\n",
-    "center2_x = np.mean(corners2[:,0])\n",
-    "center2_y = np.mean(corners2[:,1])\n",
-    "\n",
-    "plt.imshow(im1)\n",
-    "\n",
-    "plt.plot(corners1[:,0],corners1[:,1],'o')\n",
-    "plt.plot(corners2[:,0],corners2[:,1],'s')\n",
-    "\n",
-    "plt.plot(center1_x,center1_y,'+')\n",
-    "plt.plot(center2_x,center2_y,'x')\n",
-    "plt.plot(1500,2500,'s')\n",
-    "plt.xlabel('y-axis')\n",
-    "plt.ylabel('x-axis')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "You can see above that each image will have a different scale to convert from position in pixels to position in meters. This is the case for all quantitative image data, every time a camera is repositioned you will have a new scale to convert pixels to meters. \n",
-    "\n",
-    "Below, we use the 0.9144-m distance between corner locations to set oour `im1_scale` and `im2_scale` for target_01.jpg and target_02.jpg, respectively. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "target_01.jpg has conversion 0.00059 meter/pixel\n",
-      "target_02.jpg has conversion 0.00048 meter/pixel\n"
-     ]
-    }
-   ],
-   "source": [
-    "d1=np.sqrt((corners1[0,0]-corners1[1,0])**2+(corners1[0,1]-corners1[1,1])**2)\n",
-    "d2=np.sqrt((corners1[2,0]-corners1[3,0])**2+(corners1[2,1]-corners1[3,1])**2)\n",
-    "\n",
-    "\n",
-    "im1_scale = 0.9144/np.mean([d1,d2]) # in 0.9144 meters/ pixel distance\n",
-    "print('target_01.jpg has conversion {:.2} meter/pixel'.format(im1_scale))\n",
-    "d1=np.sqrt((corners2[0,0]-corners2[1,0])**2+(corners2[0,1]-corners2[1,1])**2)\n",
-    "d2=np.sqrt((corners2[2,0]-corners2[3,0])**2+(corners2[2,1]-corners2[3,1])**2)\n",
-    "\n",
-    "\n",
-    "im2_scale = 0.9144/np.mean([d1,d2]) # in 0.9144 meters/ pixel distance\n",
-    "print('target_02.jpg has conversion {:.2} meter/pixel'.format(im2_scale))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Final Data preparation\n",
-    "\n",
-    "So far, we have\n",
-    "\n",
-    "1. Chosen hit points on two images\n",
-    "\n",
-    "2. Chosen calibration points on two images\n",
-    "\n",
-    "2. Determined a local reference in each image i.e. point (0,0)\n",
-    "\n",
-    "3. Determined the scale for each image i.e. convert pixels -> meters\n",
-    "\n",
-    "The final data preparation is to convert the chosen hit points on the two images into (x,y) locations in meters. We will save some other information in case we need to check our work later _(part of creating reproducible research)_.\n",
-    "\n",
-    "The first step is to plot our scaled and centered data from targets 01 and 02. We can also plot the mean location of our hits from the class. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x7fb6dd5bda50>"
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "hits1=np.load('./hits_im1.npy')\n",
-    "hits2=np.load('./hits_im2.npy')\n",
-    "\n",
-    "center_hits1=hits1\n",
-    "center_hits1[:,0]= hits1[:,0]-center1_x\n",
-    "center_hits1[:,1]= hits1[:,1]-center1_y\n",
-    "\n",
-    "center_hits2=hits2\n",
-    "center_hits2[:,0]= hits2[:,0]-center2_x\n",
-    "center_hits2[:,1]= hits2[:,1]-center2_y\n",
-    "\n",
-    "scaled_hits1 = center_hits1*im1_scale\n",
-    "scaled_hits2 = center_hits2*im2_scale\n",
-    "\n",
-    "plt.figure()\n",
-    "plt.plot(scaled_hits1[:,0],scaled_hits1[:,1],'x')\n",
-    "plt.plot(scaled_hits2[:,0],scaled_hits2[:,1],'x')\n",
-    "\n",
-    "plt.plot(np.mean(scaled_hits1[:,0]),np.mean(scaled_hits1[:,1]),'o',label='mean hit target_01')\n",
-    "plt.plot(np.mean(scaled_hits2[:,0]),np.mean(scaled_hits2[:,1]),'o',label='mean hit target_02')\n",
-    "plt.legend()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The locations look good so far, now we export the data to a csv file so we can access it later. \n",
-    "\n",
-    "The csv file will save the following information:\n",
-    "\n",
-    "|throw #| x position (m)| y position (m)|picture x position (pixel)| picture y position (pixel)|target x position (pixel)| target y position (pixel)| image #|\n",
-    "|-------|--------------|---------------|-------|----------|---------|----------|--------|\n",
-    "|arbitrary hit #|centered x position|centered y position|absolute x pixel location|absoluter y pixel location|target center x pixel location|target center y pixel location |either 1 or 2 for target_01.jpg or target_02.jpg|\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "hits1=np.load('../data/hits_im1.npy')\n",
-    "hits2=np.load('../data/hits_im2.npy')\n",
-    "file = open('../data/target_data.csv','w')\n",
-    "file.write('throw #, x position (m), y position (m),')\n",
-    "file.write('picture x position (pixel), picture y position (pixel),')\n",
-    "file.write('target x position (pixel), target y position (pixel), image #\\n')\n",
-    "for i in range(0,len(scaled_hits1)):\n",
-    "    file.write('{},{},{},'.format(i,scaled_hits1[i,0],scaled_hits1[i,1]))\n",
-    "    file.write('{},{},'.format(hits1[i,0],hits1[i,1]))\n",
-    "    file.write('{},{},{}\\n'.format(center1_x,center1_y,1))\n",
-    "for i in range(0,len(scaled_hits2)):\n",
-    "    file.write('{},{},{},'.format(len(scaled_hits1)+i,scaled_hits2[i,0],scaled_hits2[i,1]))\n",
-    "    file.write('{},{},'.format(hits2[i,0],hits2[i,1]))\n",
-    "    file.write('{},{},{}\\n'.format(center2_x,center2_y,2))\n",
-    "file.close()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Congratulations\n",
-    "\n",
-    "Now you can do some statistics on accuracy and precision of the class by loading the csv into a `pandas` dataframe. "
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/project/.ipynb_checkpoints/target_data-checkpoint.csv b/project/.ipynb_checkpoints/target_data-checkpoint.csv
deleted file mode 100644
index 0ac62c8..0000000
--- a/project/.ipynb_checkpoints/target_data-checkpoint.csv
+++ /dev/null
@@ -1,55 +0,0 @@
-throw #, x position (m), y position (m),picture x position (pixel), picture y position (pixel),target x position (pixel), target y position (pixel), image #
-0,-0.45718396926227894,-0.2956137183449811,1260.8551136363637,990.5994318181815,2042.2187500000005,1495.826704545454,1
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-8,-0.1843097677130655,-0.03710131687730526,1727.21875,1432.4176136363633,2042.2187500000005,1495.826704545454,1
-9,-0.07420263375461078,-0.017952250101921842,1915.4005681818185,1465.144886363636,2042.2187500000005,1495.826704545454,1
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-12,0.447609435874587,-0.3626354520588233,2807.2187500000005,876.0539772727266,2042.2187500000005,1495.826704545454,1
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-19,0.3087787017530572,-0.08976125050960974,2569.946022727273,1342.417613636363,2042.2187500000005,1495.826704545454,1
-20,0.21782063456998604,0.1017294172442244,2414.4914772727275,1669.6903409090905,2042.2187500000005,1495.826704545454,1
-21,0.3375023019161323,0.1639638842642205,2619.036931818182,1776.053977272727,2042.2187500000005,1495.826704545454,1
-22,0.12207530069306911,0.2309856179780624,2250.855113636364,1890.5994318181815,2042.2187500000005,1495.826704545454,1
-23,0.1412243674684524,0.3458800186303629,2283.5823863636365,2086.963068181818,2042.2187500000005,1495.826704545454,1
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-30,-0.28905801786881596,-0.12698486845025021412.21875,1254.97443181818152017.9005681818185,1521.0539772727275,2
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