["$ keyvaluepair..G$ ","|KeyValuePair$returns two values|foreach loop on Dictionary$lambda, sorts KeyValuePairs$tests KeyValuePair performance|","OHFYXKeyValuePairXFFusing System;Fusing System.Collections.Generic;FFclass ProgramF{FOstatic void Main()FO{XFOO// Shows a List of Hs.FOOXvar list = new List<XHX<string, int>>();FOOlist.Add(new H<string, int>(XYCatYX, 1));FOOlist.Add(new H<string, int>(XYDogYX, 2));FOOlist.Add(new H<string, int>(XYRabbitYX, 4));FFOOXforeachX (var element in list)FOO{FOOOConsole.WriteLine(element);FOO}FO}F}FFXFF[Cat, 1]F[Dog, 2]F[Rabbit, 4]XFFusing System;Fusing System.Collections.Generic;FFclass ProgramF{FOstatic void Main()FO{FOOConsole.WriteLine(GetNames());FO}FFOstatic XHX<string, string> GetNames()FO{XFOO// Gets collection of first and last name.FOOXstring firstName = XYSundarYX;FOOstring lastName = XYPichaiYX;FOOreturn new H<string, string>(firstName, lastName);FO}F}FFXFF[Sundar, Pichai]XError:XFFProperty or indexer 'System.Collections.Generic.H...Key'Fcannot be assigned to--it is read-only.XFFusing System;Fusing System.Collections.Generic;FFclass ProgramF{FOstatic void Main()FO{FOOXDictionaryX<string, int> birds = new Dictionary<string, int>()FOO{FOOO{ XYcrowYX, 10 }, { XYrobinYX, 5 }FOO};XFFOO// Use H to use foreach on Dictionary.FOOXforeachX (XHX<string, int> bird in birds)FOO{FOOOConsole.WriteLine($YPair here: {bird.Key}, {bird.Value}Y);FOO}FO}F}FFXFFPair here: crow, 10FPair here: robin, 5XFFusing System.Collections.Generic;FFclass ProgramF{FOstatic void Main()FO{FOOvar data = new List<H<int, int>>()FOO{FOOOnew XHX<int, int>(1, 6),FOOOnew H<int, int>(1, 2),FOOOnew H<int, int>(3, 4)FOO};XFOO// Sort pairs in list in descending order based on the value.FOO// ... Use reverse order of A and B to mean descending sort.FOOXdata.XSortX((a, b) => (b.Value.CompareTo(a.Value)));FOOXforeachX (var pair in data)FOO{FOOOSystem.Console.WriteLine(pair);FOO}FO}F}FFXFF[1, 6]F[3, 4]F[1, 2]XImplementation of H: C#XFF[Serializable, StructLayout(LayoutKind.Sequential)]Fpublic struct H<TKey, TValue>F{FOprivate TKey key;FOprivate TValue value;FOpublic H(TKey key, TValue value);FOpublic TKey Key { get; }FOpublic TValue Value { get; }FOpublic override string ToString();F}XH performance:XFFMethod that uses normal struct: X0.32 nsXFMethod that uses H: X4.35 nsXVersion 1:XFFstruct CustomPairF{FOpublic int Key;FOpublic string Value;F}FFXVersion 2:XFFH<int, string>XFFusing System;Fusing System.Collections.Generic;Fusing System.Diagnostics;FFstruct CustomPairF{FOpublic int Key;FOpublic string Value;F}FFclass ProgramF{FOconst int _max = 300000000;FOstatic void Main()FO{FOOCustomPair p1;FOOp1.Key = 4;FOOp1.Value = XYperlsYX;FOOMethod(p1);FFOOH<int, string> p2 = new H<int, string>(4, YperlsY);FOOMethod(p2);FFOOfor (int a = 0; a < 5; a++)FOO{FOOOvar s1 = Stopwatch.StartNew();FOOOfor (int i = 0; i < _max; i++)FOOO{FOOOOMethod(p1);FOOOOMethod(p1);FOOO}FOOOs1.Stop();FOOOvar s2 = Stopwatch.StartNew();FOOOfor (int i = 0; i < _max; i++)FOOO{FOOOOMethod(p2);FOOOOMethod(p2);FOOO}FOOOs2.Stop();FFOOOConsole.WriteLine(((double)(s1.Elapsed.TotalMilliseconds * 1000000) /FOOOO_max).ToString(Y0.00 nsY));FOOOConsole.WriteLine(((double)(s2.Elapsed.TotalMilliseconds * 1000000) /FOOOO_max).ToString(Y0.00 nsY));FOO}FOOConsole.Read();FO}FFOstatic int XMethodX(CustomPair pair)FO{FOOreturn pair.Key + pair.Value.Length;FO}FFOstatic int XMethodX(H<int, string> pair)FO{FOOreturn pair.Key + pair.Value.Length;FO}F}FFXFFX0.32 nsXOCustomPairFX4.35 nsXOHF0.32 nsF4.34 nsF0.32 nsF4.36 nsF0.32 nsF4.35 nsF0.32 nsF4.36 nsX","A/EAEBBBffBee3[+CC~| 9845}XCE 768}(PcB~E 58G57}*C 795}.Ba~E.BP%BCEXP4A+BPF3CE 455}8#CECCEbBC3BX","KeyValuePair."," The crow pushes against the latch. The gate unlocks. Inside, it finds seed and nourishment. The action (a push with its beak) has a result (a value).","For this intelligent bird,"," the action and the value are not just separate. They are linked together. In C# a KeyValuePair struct (often used inside dictionaries) joins 2 things together.","First example."," KeyValuePair is not just for the birds. Here we use it in a List. We store pairs of values in a single List. Two Lists could be used, but that might complicate matters. ","We initialize a new List of type KeyValuePair. This shows the required syntax form.","Inside the brackets in the KeyValuePair, there are two types separated by a comma (string, int).","Constructor: ","We can create a new KeyValuePair with its constructor. The constructor is shown in the Add() calls.","Return, KeyValuePair."," Often we need to return 2 values from a method. We can do this with KeyValuePair. Here is an example of the syntax\u2014it can be tricky at first to use. ","This is clearer than a 2-element array. Consider out or ref parameters instead.","Parameters ","parameter","Error."," When using KeyValuePair, you may get this error at some point. The C# compiler doesn't allow you to assign the Key and Value properties. This must be assigned in the constructor. ","Foreach, Dictionary."," A common use of KeyValuePair is in a loop over a Dictionary. The Dictionary has an enumerator that returns each key and value in a KeyValuePair, one at a time. ","Dictionary ","dictionary","Var: ","An improved syntax could be to use the var keyword with the foreach loop over your Dictionary. This shortens the syntax.","Var ","var","Sort, lambda."," To sort KeyValuePairs, we can use Comparison methods. A lambda is the cleanest way to do this. Here we sort in descending order by the Value of each pair. ","For descending, we take the second argument, and compare it to the first (instead of the other way around).","Sort, no lambdas."," How can we sort a collection of KeyValuePair instances? We can implement custom sorting Comparison method\u2014no lambdas are required. We use the delegate method syntax. ","Sort KeyValuePair List ","sort-keyvaluepair","Sort, parallel lists."," We can use KeyValuePair in a List to create 2 parallel Lists. These are easily sorted, keeping both values together. ","Shuffle: ","Randomly shuffled arrays are more complicated than you might at first expect. KeyValuePair, and List, can help here.","Shuffle Array ","shuffle","Implementation."," Here is the basic layout of the KeyValuePair struct. The KeyValuePair has two private fields, and two public properties that retrieve the values of those fields. ","Property ","property","ToString."," When you want to display the values, call ToString or pass the KeyValuePair to Console.Write or Console.WriteLine. This will implicitly call ToString. ","Console.Write ","console-write","Internally ToString uses a StringBuilder. This may cause memory pressure. Avoiding ToString can speed up programs.","StringBuilder ","stringbuilder","Performance, KeyValuePair."," Is there any advantage to using custom structs instead of KeyValuePair generic types? The two approaches are equivalent in functionality. ","Performance, code used."," Here is the code. It is always possible to use custom structs with two fields instead of a KeyValuePair with those types. ","Struct ","struct","Performance, benchmark."," Next we look at a benchmark that compares the two structs. You would think that the .NET Framework would compile the 2 methods in the exactly same way. ","But: ","I found the methods are inlined in different ways. Something small differences matter for performance.","Overload ","overload","Performance, analysis."," To analyze the results, I looked inside the 2 Method implementations in the IL Disassembler tool. They have the same code size. ","But: ","In the KeyValuePair version, the call instruction is used instead of ldfld because KeyValuePair uses properties.","IL Disassembler ","il-disassembler","After C# compilation, the program is JIT-compiled during runtime. The behavior of the inliner is sometimes hard to determine.","Thus: ","It is possible to improve performance by replacing a KeyValuePair with a regular struct.","Benchmark ","benchmark","Discussion."," In some contexts\u2014such as internal method code\u2014using KeyValuePair is convenient and simple. But using a class can enhance the clarity of your program. ","Class ","class","Therefore: ","Prefer classes when the usage is not trivial. This improves object-oriented design.","Tuple."," Another option in the .NET Framework is the Tuple type. You can have a two-element Tuple. A Tuple is a class, not a struct. It can also have many more items in it. ","Tuple ","tuple","An intelligent summary."," Keys and values are everywhere\u2014if you think carefully. A term has a definition. An action has a result. KeyValuePair has many uses throughout C# programs."]

$/9j/2wBD?@.@.@.sLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwv/wQARCACCANIDACI?RE?hEA/8QApw?AQUBAQE)))?AMEBQYHAgEIAQEBAQE))))?QIDE?BAwIDAwYGDAkHCgc)CAQME?UREhMGISIUIzEyM0IVQUNSYWIHFiRRU2Nxc3SSorM0NXKBgpOytMIlRHWjscPwFyYnRYOEkaHB0jY3VFVk0eIRAQEB?ICAgIDAQ))ABEQIxIVESQWGhcYGC0f/a?wD?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?sdkk8rtFtlaeTWjNOZc+bDMArhjlTNT5wM6oq7kToSobZlVTZ2zIvS@lPsDUwq+Os21qSOVBE3quGFQ1/TC1vqPTmaw/WDUsRIqYLUBtA6qWxzDo1GU/rBpC9LHBXIYIq9cERU9KJjUtVT.TatknSiAX/BMatDTguttuguIOCBivvoSYpXTh1jnznnSlFFFaYFFFFAUUUUBRRRQFUj2Qlc9rEsGhU1cdjAv67P8AwVd6zr2TpGjs+yGZR1pzQcK/ESC/7aDG0tz7sBkgRUJt1C0CwHP62Oak0hzZDpIjANCrmYlU0RA+1TdHX5KgpNqqA3pqSOKiLh3l9am8UHs7i5sQRFElU+jHxpWWlwYYRi42/lEtjI20okROdTrbqc3i5q8wcCAvuFXA1pKoq8WPVE6q0YGJcmHEdTFEXKpp1jRVrRL+EKNs43EjAgc7HxHJ6e961S9xqdU4FqyW63PtMNySzRl1HRZMusHWI8vVrjZa6MtQIbDDD7htq4Inhwuce9MVqxPNNjb31VwgRYR5/ePmeiq5sowRWSISoic66TZEuGHOYblqfS/bi2XQgut/fisOC4chvWZNUyh1h+tmzU2enPubTtkEYE@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?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;lGFPiz8o4VVw3V1gte7k6ajrndI1qguzX1xQUytt4pmeewLTZb9YvsBqOOc23VxN/AuNwYtzWLhjquYiw2S9oX7WmHeKqQ1bIz5uSRkO6zzjTk+W0atvu5Vw00UOIc+OmLTfUDTbb8nVWWbIuT53O4rqOvnlYYaPKOmK9iwZdRhrvP+fznaOVYUvzmKwbI3HfltijhdIwLa18PNdDjMv;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?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?DqCI4qpLlRN5eMl9Yq7omvK9ooqoKo/sgWa432wcgtjKPyOWR3VBXG2kRsUdzkpumA8Of8urxRQM4kCDADJCixoyYIOEdltlME+bAKo03ZW+ObRXW5xJdv5Pc47UfXlMvPz7c0LeRzkHkOP1q0Wigp1v2SaY2S9qk2SbrSi8DkiOCMuZXZRyuHU18pceXv1Mv2G2S41rjS2SfC1uRnYed1wSB6MGRp0tImxMvOEhyfF1MUUBRRRQFFFFAUUUUBRRRQFFFFB4vQvyUnj6VpWig4BVWu6KKAoWiigQxXh3r1vfpeiigKKKKAooooCiiigKKKKAooooCiiig:Z$/9j/2wCE?YEBQYFBAYGBQYHBwYIChAKCg@ChQODwwQFxQYGBcUFhYaHSUfGhsjHBYWICwgIyYnKSopGR8tMC0oMCUoKSgBBwcHCggKEwoKEygaFhooKC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KP/BABEIAKgAyAMAIgABEQECEQH/xABx?E?wEBAQEB)))AQIDBAUGBwgQ?EDAwIC.IH?IDAQ)ABAgMEBREGEhMhBxQVIjEyUWFxQVIWIzNCgZGhJCUXQ2LhEQE?gEDBQE?w))?AQIRAxIxBBMhMkFRFCJh/9oADAM?AEBAgEAPwD+qSsv6T/hSxWX9J/wpKt/WXnZ91LI9/3O/soDol4sTMNUlf8Acv8AZfiv+4xLEYa11Lfro4rvUvxDnLlMQ6a6lv1vvLbjA0i838FMN6XmZw0ABVu))))?AVl/Sf8KWKy/pP+FJVv6y80AHS8RJJVCckLQuWMsnlauknj0nen0bpetNop+FwlXfv4bsbcc85xjBWW1Z+Pc3GsC9/+D4mHT3atBQVdVd77TzupYt7IK18bd2xMqrfXPievU2FldR0tJ2ndoOrN/Vp6t0cknJE77k5uKujT9ofSg8OlsDKezVFu7Tu8nGdu6xJVudOzw5Nf4on/AO+pTSMVJS01dTUV1r7nwKt0cz62ZZXxSI1uY0cqJyRML9TJ2voAQS))))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;I9RTU893bEnWpKbPDdJ9VblE5fwgPSAS?AQpJCgUcYvN1MnAcz2p6GD2p6IdT0MnNCPDm2J6BrUybbRtB4Sw3jM2GzQlqw0Qo0ugQsQQQSpMpKkKVLYZWsk;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?IfJ0Nh07Prm6XeGHi36nfHxpH7vyswo1qN+nNmM+JpX6D0zX1s1ZV2iCWpmcr5JNzu8q/yelbLWtJfLzXcVruvPidsRObNkaN5/1k9YIw8W9aYs97qI57rQx1MsbdjXOVfDOcclEmmrRJZ4rW+hj7PidvZDz7q5Vc+Ofr/p7IJRtfFTWilsOobHFZYFpaeqkm6y2Nztsm2J23dz+i+B9QYXStmgudspY2s4VU6TiLhcptYrkx/KHXtL1c2tTNme0YNNo2lssdjPBLU7yfJfaT9UGUxTysCwKN9qmAaAZNjIqbFCVLUZFDVxQuwvC8fkQ0i85nH5ELFZa0niXT6mUPmX4Kbl9S8PmX4K4xDffvvGGoAKOg?Hm2+lfDd7rPtXZO6Pb74YiKekc8Dn9aqkc5Va1W7U9O6d)cdYkHXKPixbpsu4T/ALF28/7TkdGxSJYmvnge53eYq7U9cpg1JyrNIZ7CNvsagK9uGWBg1AydtQFwE7VQTgAwqUU0KEwpaGbjNxo4zcaQ5LrM8qFirPKhYiVvkBpD5l+DM0iRd3gvgQ00/aGoAM3W?DNzJN67ZEx6bSzkdy2u/wsAK4dtxu/nAajueXf4WAFNi72u3eX2Lg))AE8C.SplBXapcBO2JZcJfVBwPk1A3Sr2q/YUbE3BZGt9EJAzK0ViPgACFg)))))B:9k=%iVBORw0KG;)NSUhEUg?AJU?ABqCAM?ACCuOOx)YFBMVEX::/+cj:fD:ObMy8vl5OT/+9fx8fH/+s7W1dTNzMbd3Nz:vb/+978+/vo48f69cjx7Mfr6+v:/z4+Pjx7+bX1cve28fT0cbi38fb2Mfm5NjHxsbe3NHw7dT49NyvOr81?AGaklEQVR4Xu2a6Y6jOhCFq2z2nezpnuX93/J2Jk6O4wNprGEUXSnnXzO4+PBnOQWD5HMRl+Dvx8OdhOlyl51wUA1jMRCR8sd0SnGp3YFU/Gz+HEuEsvEKcPzLbWgghn5LtUuuVEknSHc9mAulvlfYfUNV08AIKkl5siQN6gIXFdJvqBIaGEPVJXTzOc3epId5Kla4iaPCgBq1aTLIAxQyVeLq0cAkoCrDfIqLMeZGnj9glsaYLQskhUxVJqzwD1B9ozpcqUYNkolLqzrCiVPqhhTTAk+zCq+XO5zdXYYD3YUO31M1herHfSXA0llVzaTAagwUEtVIk1nj+CIqsaqDo0qw1KtBtZVJgR9aQeEklTsh.T2EVTbQrXHUnErsVctttMCez0HConq6CnEnQ7LqDBZ1X0rTa8DVdXObKGDBgqZKlB4LXrSkOpXFsQKkmGyarfVD+BmgRooJKoCCn2B+iug2suTGFU9Oay7P21kTmAWK.qq0dMJgTqfjEVdgekGuCPBRZNoJCoGiiEwEqzOKpGsTvctqrtrMBWCiicpJJiuE0m9taz2pDqM0fQ+vDucF85VmYFWrGBQqJq9cNTuHO32oRUCHco2B3gL5NZgbqVQCFTmVu11BcokVTYHdyu3sgTgRIoZCoo9AVGUGF3OGGurDwTKIFCpoLCTqS7CYynMjD4oy+2TwVKoJCpUG7jbqfSQuKpJKtA/VvmBJ4uAkkhU23VKazd7RzVMtXn3k/3TT9XPxdICplKWj05hRBIVKP6MULJSfG8QFbIVPau8Ho7F4HxVAn6OfQgfMLhUF5zOKDNYCpfYX3dAm08laRupzriWiSQAoVEBYWJ+2U2kVR4KOy9loYEUq.qJxCZCgknqq8NVVoaUggBQqZCisPey9T7Y2f7bSe4UJc0YJngayQqSRzpSBQonqG7uZPlR54IBBrHesdCpnK6hkCVaKpUvwoq+rtYhsSWKlmCDpSpoJC7L2RVLnXVLXeA08XCjzrQ7CREhUUYu+NpCrRVNEDDwTyI0mwkRKV65Ox9xIVZ8pf0NLsSGAQK.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:BYJuFVMcBv1BRVPy9De2ZOp4DsGSO6uT913o/Dnht/Vc9g5l6G+6mjCZrshrHyqpUYtTPMGIDq5dTtbIylZhCHzKeqEcmKoJanUq27QMXdrClVFbWpAKXfQA7RFG1jcRRLfjeZpen1ydlY+9gPVHNdmsW1VbrGTZl4u9MjW19qkNEtTWpUtqZtqa9f+z580VU3dQe0NwE9n9F9TMPsrxOesPa8bFK/4aKQ1QcestQb/7cjNfIjS+jkvxJy/QqKpsVfTULlb2KyvuB4ZapfRHVVi/BdFHL9AIqfEMw/kyAdDq7loncZOg5KHQWhepwqLv6vU8v2e/vQ8zLqKTRubTyOiqxxRzUK6mkmSS38joqTBe1TC+jQozf9GUWTK9OY+wl5ome/wDRYQ+FO9vD/)ABJRU5Er@ggg==%iVBORw0KG;)NSUhEUg?ANI)wCAM?ABTy9T5)GFBMVEX::g/dZodGSYrJDPz8+o2pXD/6wnJycNREam?ADOklEQVR4Xu2Y0bLiQAhEbZjE: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)ABJRU5Er@ggg==%iVBORw0KG;)NSUhEUg?AII?ACCCAM?AC93eDP)MFBMVEX7r11HR0f8yZHLklZZUEmyg1P8uXLjoVmLbE5pWUrAi1X+6tPVmFfyqVx4YUz:v3zEySO?ABHElEQVR4Xu3cS4rDQAxF0av6+5fsf7ed0ANDV8b1GvLOCu5AWMhg83w5UkOgpeP58k5IyKTfhIZQeyckpNKTA7GDhFiiIdb4KmZmZmZmZnadH1ysdMYHpxOc4ISbE5zgBCc4oesTKDG7WGrEZGOtGpPBWjkmlbUu+TTCNiUA4nl8gHoeB4B2S+wsF390lnuopxGqehRg1z6YmJdlRqBIp3FelgWFqp5GyOpphEu6JudleSFRxw0xs1xHxDZqR+Tc7k3dQb2syy4ruO0A2tO6dBYb8pOy62/7PWZZfttHBXCCfhy7/PXCJj+sI8vfLwwQNwwU8j0PW0ZkHyUiytiRMDMzMzMzM2v6gIRY4kDs0H/wrv/s/3/8/ED/C4gfHWoMKlwF198)ASUVORK5CYII=$/9j/2wCE?gGBgYGBggGBggMCAcIDA4KCAgKDhANDQ4NDRARDA4NDQ4MEQ8SExQTEg8YGBoaGBgjIiIiIycnJycnJycnJycB.gI.oJCw@Cw4LDQsOEQ4ODg4REw0NDg0NExgRDw8PDxEYFhcUFBQXFhoaGBgaGiEhICEhJycnJycnJycnJ:BABEIAKQA6AMAIgABEQECEQH/xAB3?E?gMBAQE)))?QIDBAUGBwgQ?EDAgIFBwkEBgs))BAgMEEQUSBhMhIjEHMkFRUmGRFBUjU3FygaGxQpLB0QgkM2JjohYlJidDRIKys+HwEQEBAQADAQ)))?ARESITEC/9oADAM?AEBAgEAPwD7+AQ?ICUlcxw9KNLcG0SofLsXmyZr6mFm9JI7qY38eB8grv0hKvXf1dgseo/jyOz/wAiNA+9ZlB8u0T5bMBx6pZQYrCuFVUio2N73I+Fzvftu/FPifUbbOIDMpbMVspAQyAqjibkiSCLi4E3JK3FwLArcXAsCtxcYLArcXGCwIuTc.QSQ)ACACAkIBXoJS/NGkK13KRykOwxkv6vrnU0HZjghVc7/bxcfccH0A0SwikbRwYXBNs35qiNssj/AHnPT6bD4xyXt/vKX21n0cfoxvAJfFOVfktwqnwubSXR2BKSWl36yljvkcxV/aM7Kt6U4WPS8i2lNRj+jT6CueslXhTmw6x32onJ6P47FPX6Wp/ZfGW2/wAnP/xuPk/6PqK2XHOrLB9XhD7mUcWKu4BGK3L3MaqEXYSYvci5W4uMTi1xcpcZicMXuLmPMLjEMlxcx5ibk4he5NzHclFIwZLkopRFISVuZW8FIsGVCSEJIEgAg?BBVSSFCUFegkjoJWfnnkziezlHXM1eNXxRepx+hm8DA2mp2P1jImNf28qX+hmbwCXhOVDSqfR3CJKXze6op8ThlpvKmvy6t7m5d9uXvum0+W8k+lTdHMSnofIpKyTFHRRRNhVL5rr2ujePu+lGA0+kuCVWE1CJ6VvoXr9iVvMd4/I+dck2g0+GVdVjeLwqyoge+mpI3J2VyySfgnxCH1xFWybLdfcQq7CLlbkpxFwilLhFJTxXIuVuRckxbMLlLkK5CcLF7i5iWQjWOJxSs9xcwaxxKSOGKthFJRTXSV3UWSZ3UhFGyhrSc93tLJOvUY1XapWjLHM5nehtMe16XapoEtVb8dpUdEGvHUJwebCKlr9B?ACpBJxcaZpE50XmOSFjdut16Kt+rLsUlZ1yF4Hk3VGntM1ZH09JVNb9iNVRyp4odXBMehxqmdKxixTROyVEDucxwS6hdvAqnAsn?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)BVzdhi1a3M4Aw6pesJF3mYgCLJYhSxVQmKKY3GRTG4tGT5Yzyumeh9NpRSRzRPdS43h+aXB8RjcrXQzbHdGxWOVqI5FTgeqKksnsx5zQ7A8TwXDpvPVatZidfM6srMquWCKWS2aOma9boz6rtsnBPRLwUFJHoyNznEpzpifI2Nu8poS1L5L/Zb3FZZHSOzeBiUhFLkXBlZR1MnNjW3fs+pKlYrkZjZ821nY+aFVw6t9X80DHWvmIVxm8hrfUu8Ci0VZ6h/;1VhVSiqHKt+pSlyLQVTZo8TqaJ24uaPsO4fA1URXLupfqRDq0WA1E9n1K6qP8AmX4dBUdqhxOmruYuWRP8NePw6zeNaloqajblgYnvLtcvxNkg))?BBCkkKEqKUUylFQleVhUpYyqhWxZklYzn10u8kSfZ2/E6VjgyyZ5HO71C2oUNY6RyMam1Stzfoo0yazpdw9gRWekpo4l4Zn25y/gb6Gq1crk7jbbwv0BSpQlAiFkQhSlibE2JI1V4mqX9Zl9931NyjwaqqrPemqi7TuK+xDvwYZSwSOmy55XKrszttvYbgQ1KTDaWjT0bN/wBY7abYJI)))?IJAFbFVLkWJWlY1KKZVIsFpWvKnon+6q/I8zmPWOZmare5Tx77te5vTdUJ1bkyZjtQNTUx+6n0OBmO7RPSSmjd02yr8Acmaxnhk+y74KYgQra3kQshqRzOZ3obDZo3dIVtZLEkI5vaTxJunWQqk)))))AIJAFbCxICVbHlMYgWnrX9mTfb+PzPW2OdjFCtZTbieli3md6dQNeUzHQwqrbHIsEi7knNvwR3/ZzFvcXJTr1ypt7wcahxjVtSGrRXM4NkTnJ3L1odaOaGZPQyNf7F2+HEhGsgAC?ALr1k3XrIAE5ndak6x/aXxKgC+tk7SmWne9z1Ryraxrmam56+wDb)))))AefxnB1crqulbt4yRp/uQ88fQTlYhgcFWqyxLqpu7mr7UA8kSir1m1VYbWUirrY1y9tvN8TUAuk03rHeKl0q6r1z/vKYQBseXVnr3+JPnCt9c7xNYAbaYnXetXwQumLV1+en3UNEJxQD2TY5MrXZV4J8ydXJ2VNyH9jH7rfoXA0Mj+yvgZaZFzrstsNo))))))ADXloKOb9pAzwspsADQXBcN9Qniv5lVwPDfVfzKdEAcpdH8O7L/ALxjdo/QfxPvJ+R2QBwX4DRW4yfeT8jUlwqmZzXP8U/I9SAKxp6NnuonyL))?f:Z%iVBORw0KG;)NSUhEUg?AJY?ABdCAM?ABw8G+n)GFBMVEX:/+DvOv76rDR5flpsu/a3MKayPD88s5VVf4y?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@XmApXmApXrusptQVaa6w3VFyLLQb5f38Lo)AElFTkSuQmCC%iVBORw0KG;)NSUhEUg?ALM?ABSCAM)o0hXm)MFBMVEVl4fzS:fO:by:3d9/7B8f74:6T6P145Pyp7fz::U9v3j:rq:zc:nW:hthqPe?AD9klEQVR4XtTZ2W7DIBQEUKS7sHjJ: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)AElFTkSuQmCC$/9j/2wBD?@.@.sLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwv/wQARCAB6AOYDACI?RE?hEA/8QAog?AgMBAQE)))?AUDBAYCAQcBAQEBAQE))))BAgMEE?CAQMBBAQJBgsGBQUB?ABAgMABBESBRMhIjEyQUIGFCMzUVJhYnJDU2NxgpIHFTRzgYORk6Ky0iQ2dKGxwmSztcHwJVSEw9HiEQEB?ECBQIGAw))?ARECAyExQVFhEvAyQlJxgcKiscH/2gAMAw?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.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.Y6a71ituF0vDDGxJIyT0nJ/qoEMakEDBHQcn+quwwr2iZveuXRXADDIHEdI/0oSNEzpGM9PEn/AFruiiZvJGY@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?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.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.ApJIBIY9sjeiobSJI4EVXduULJO2N7Lw6er1vhq1pAyASOGAPU+r3mqsWqQOC4Y8Ack9GDXOsyalxgDGFPYPb7zVYeEZABYAdA4dP3aiWBVPS3E4JJH9NFVRxYAnAB4+jhU0LEOy9nSMej2VMYEJOCeJznh0+zlrkQoHyCfR0:wA1FyZwHh+yp6gg?OPZU9bjhq+KiiiijIooooCiiigPTWZwZRPrYqPGZEUqBxAOONaX01n0AIYYH5VJ/zGqV12+pdc2kD3aTvIxFtHIg1SEAbzQzkkfBSUwb6C2iyG8eut66bw+UhUtJzfw1pbtV0XHAdD9nuLWfhAEuzsAcI5MY4dysujsRRCK7mAIeWTxaMsScKp0eTJark1uTfbPt4xiGBHmkG.dIVUyB71KiSbSIEnHjWcE8M7zppvCzeO3hyci2AHHo4VVUAifiy+nKod/cXDdHd16P+1TtbRG72eCpBjt5GUqMcdCqN57tWIFUbHtuAwZIsjHTmRat3I/t6f4fh99ac@ZQPxZcgMNUs8udQ5XJfhn1amhmll2xGjKypb279g7Qo1LirF8B+LoOA4yxZ4fTLUyfl859Fqf9Wp2Unl0/iudU@kvL7Sv7z+LkSrayNi8uOfqi1ttA9UafV9ei1AMezMgdeU9Hbh6ZRAfi+PgPP56O3eNTvPwhHMiIbSEySBLeDymQQqTSdJGF85p1VpXB4cA5zq5+HW6nd9Wq1wqlXJAJMnHI9lMpRx6OxKf7RUd4wCHkZio4RRDA4D0Cl7SEqpc?LkQg4AHY0x/wBtNJgFgcrw4dI4GlbAaI+A82W/T6aixooGyiEdOBjhhRw7tTE6eg5Y/wCXtPvVFCALdSOBITP7K6xwqsOs5GSOI6R7KjBBOTxHRwH+ldjt+o1F6KDzPEj00DicV6Ov+ivE6f01FXoDyn9FT1Xg7311YrUcdXxUUUUVWRRRRQFFFFB:9k=%iVBORw0KG;)NSUhEUg?AL4?ABaBAM?AD0j/E6)GFBMVEX::yQmNChfJfX1+Q@C4uLjV1dXq6uomAbS5?ABZ0lEQVR4Xu3aMWvDMBAF4GuJpbX9C/0FgXfZDYoze5DTVUNMVi3N72+tUI9FB30Qt3qz+TDo/DiB5dUSWfL8Zsj2/RepzdO3L9X5Zb/5zW/+cVyA2LN89DIlCXuij/7v+s2/p/mP2D/N77BEE9fHgewjUc+3Q0/1Df3TfM75sudz09+XpsfoN5+4vtPE9e9Na/fnscr3gCZmP3wAmom+dAEA9jRfdlzfBarfAZpJ+9s6PzzfFZ7oayL3zz/dP29r/9Tdxm3+HNbzrbyNG3w/B8D;zf506LjOLL8okOE5us575j+KEL1h6vFv8fiAxqJ/hFLpsTy5RbZ93cXub6In/qN9qcbrgbfnQrQ7et9QN/rfZzKEmfyAT1X+zjki2k+SztDK/fbACiA0XK+c6yffx/Lyxjnx8X6+b9AE3F/Lo8afT8H8HwXg2E/tPabj1gyJJLvVp3l65CJ/ePPeSv7Z/Ob/1Pa/wmfEePG6VyNvUw)ASUVORK5CYII=%iVBORw0KG;)NSUhEUg?AHY?ABbCAM?ACRS4HL)DFBMVEX::R0dHr6+u9vb03N4B1?ABZ0lEQVR4Xu3ZwQ7.AhF0Xlv/v+f3ai4aJDe0BoTWDOcltimworwM9a9sZ/xK3bYYYcddthhhx12WFvSfoUk+xArhmvk4VnZ17FhHsrXsC5U6GdVKKFu1tUijOVquJzNVckR0rEbGW/gMPIHPkx/+YW3vS4UqEAKZB1o6Zl2DxtqsSctrEItJrqDBa+xBtZ5i/Pb5azKpwIQYJNS5BKDRT02SAYs6HEI6mJFsjmb9Djrche77mSjDmhOA6siqx5WkNV5dlgXWfewG7K7nR122GGHHVaQ1R+w83UB2B9+Of7ld/KCLHn2+Rl3sQqWPm/i7Na9rNHfakM2Ag0RUMPAoQxwsKDLpqm+eEL0behoNnOkiRt1+fSE1WDIlNUTyzK83QgXcrKJtIFb2xU4H+n7c4chKbkSndiM6Oye0WzlVVCXGLvE1HAv3bYZ9EvFLSoroJTlsAyOB4vkMHP5k5Zku3E3n9sOrD0eRUsd7kaAx8c)ASUVORK5CYII=%iVBORw0KG;)NSUhEUg?AMg?ABJCAM?ABPapnR)MFBMVEX::9amn+z879o6Lx:rj:T/MTH95OP/9PT8ubj/?Dj0cTR/+3b6drx9O/W9ORYTpHN?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.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)ABJRU5Er@ggg==%iVBORw0KG;)NSUhEUg?AIw?AB4C)?FqEXt)oElEQVR4Ae3ZsQ3DIBBAUfbfwxNcfR0dEpInIiOEI7Li4v0JXv9bnLS+dp3UIke13MFErxZXi7mqzR1MX9U6DAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDMyPmLyr5Q4mRrW43vUo14uCgYGBgflDMDBx0mOYvKvlc5i5qk0YGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYmHdiclTL5zAnfQArQiNkrpqF2)ABJRU5Er@ggg==!A%iVBORw0KG;)NSUhEUg?AJY?ACKCAM?AB/y0Mw)YFBMVEX::3Hh73KSn3Nzf7qan/+fn91tb/9fX5aWn4WFj8vb36jIz6kpL+6en:v74TEz5fHz6hIT90dH93d35YmL+8PD+4uL:Pz9y8v4Q0P8xsb8tbX5cHD6mpr7pKT5dnb11Thq?AB6ElEQVR4Ae3Y2YrjQAyFYZ0q7/uS2Nk6/f5vOTBIJA3pNHNhfIbWd2/4ERaIkldg5Gc3KNmKZ3nWFjwrMVxZML8wy7MyIz9bMrVB1gY8y7M8y7M8y7M8y7M8y7NYb/kc/+J3ZXmWZ3lWfICJ3/GnEc/yLM/yLM/yLM/yLM/yLM/yLM/yLM/yLM/yLM/yLM/6n7NSzqx8oyzP8qwjVVaAaqmyItRMldVDZVRZJdSJKquAqqiyBqiEKquBaqiyEqiCKquCih1T1gwzM2WlMAlTlpRQ/cqU1cBUTFkXmLgQZeUB5pzxZMmIh3Fa5WE9zlOVXPfJyvAsHMbm46Meh6KM+KvcIcs+euO8U9YS8E7YKUsSvJXulNXVeOe4U5Z0d7yxyAvpplkmK/GtSV7IYWRL3WkIeOFc1Iu8cISKsrF0SuqijAFA7A9Dc69OSyrfaGHdwmSGKoXJCaoQJleoUZg0UHdhUkBVQiQNUDPlHx9SITJSLmIboBLKPcQiPDKYg/DIe5hKaKyfMP3KUzWAcFj5J2BunZBoS8DEVkhcIh4uwiGv8eQuHE5nPPkQCu2AL1WdEEjvAc+uwuDS41mchEB6wxdFKxS+ZIV@ToZzGERGjeoeF0JL6z6KDxsXLdFyGTAYRI+9aUTLn8AHeMh+Y1hhGE)ASUVORK5CYII=%iVBORw0KG;)NSUhEUg?AP)CZCAM)mcEcy)wFBMVEXW9f+41Ppyj/CltvJVWMNVZ/FGS+hPheNxdsHS4/ze7fwYbs7Tze3f8OlNQpEZI+ymq6PQz7R3en2QlpNES1DY9v/m:+3uaqHiIjy/v/e/v:/8uyxMWVo6FoZ2TT3M/Z+f/t+duKf3ASFRr::Q6/OduMS40dng9/7T9P/P8/9thJXq+v5YaXt+lqn7/tnD3ubU8Pjv8PHl4+qJpcjN7Pz+/+7i+PDX8v6Kq/PF9v+oxvfX9frR5uTC4vn29fi7GR7g?AUIElEQVR4XuTVV27jMBSGUS7hXvaqXtxL6vTZ/66GMpxwhIytlyCxPR9E6PngF0TS/Bfd3RmzWq1mM0Fumnl/n3ulIDDNioIcuj3w77v7PPf+wHyNvoAFuSEmDsrETFp6E+C0pgJgTJ+OAb12sDFmJWdwUpmWHUJ3nQublx+tIEO2fSt8lQ5WFrQGxRRgjqhFAl8VM2X3A2yEDYwe1AEYRKNyUKocM4/KMZLAV8VM2ZYxBnRIH+akwSlAhAy2Cp1SqEosqc8ZIqj0SV8ccxaZJHUOjA5Ah0hDhSVS5lhc1GUBHeaK5ahAaQrARtfShTKLYhK8p8FlOWJeQunKoKh2kY6BBgDN4PB5H88IfJFrzq2ci2JiYQquYlt@SIgBK1DhOqDcXhSnwh+im23K/IPphBkYY00pLBCNrA2ciEmwAErusWlU0feSPlJ4MSMuWPPiwSYSyOMnRfxbWe91g9m/yh3nvN84xfFWfAwJlNagz4VPaZpSOAPY6aerTTFnJDFsGffSfbLkCYsW1PxUPeab/gyW+qaPtpJ8HDoKaZmIUDn+92u/SFIAn8EcwxufWelNCY8iCarPf/us01Wt0Zz3fF10LWteM/rR3kWfI7pI/NnS6yVMWttQd4V/DSUlFM1ccG1iZNyHsE847pmm2zdmKreNRXvPP3mQ+9bOZ9YeMyE7g2zSBd5Ar/7mNPg+qur18tqnW0aw5es7njoge+MepBC9n4hv0gjTfSeBY+Ye/EXc6ScBk8z/5BfBykIw0AUht8ddMYmi.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:X/E2E1xJKVSmyuffBYbo9d3Sx82lJcxisz8C1xocerAf039ljVq+xAVeuZYp1PouLhNNfczKp358QN8uGf9tYB7MIAauRQkC7/qt1rd6fTY28IMgN2eZWvRXvhHPVKD+fBx8naqem9enfkgH+T2/HtPHy8Nwusrf2DBUzBzycetODKoN9uPY+sb1/6g5w97GcSMMy80HoxsYlSlypBlI1Jwtk6JpEvJVbuLopP: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.u0AzcBV0WdrRbrQ0DQEQIubCgvvg3w8zgSMExls68rBkxkKE1dbDYus+xnLJm011V8c0aA9ggzDEh46so7mhFZHVs5k7asB9nJt4RO6rnEwOGG7HZgdjMT0IMcE8qMn7B9nlPhqELDb5frWROpamNKMBsY/oCACdY1B0o3QMyO4jlmnV4cBADhAdAKsD22PpzZLrdUKGSsZp8eCZso7QSAkMW9n/Ip+2Mh7hwMw4Cn+B5LujWX3U27RZj/YItoi41dJ@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?SaMCcNl4LZdXdV1tb5O5/X9RakPfywxACNSaU:+wTtNNCX4Trcrfs1Nf3fruthBm7u1qA+fOKhXkLzR9KmZn1Pd/d3X/r13T008xfk94vC2N9/IOCfWY+gv67vr9iv19f76+MwX1Tr7qf1dUWrK38wYKXa9nQ64f8JPEvZ36+m6/q6bprrdTXgdEymiwN0HwgTEZuX9jtgx0BHQnj8gflOfxma6xzCqr0kDubmgJn4vTHbZzWxed1eAztohwkeVxP9gDhOESMg3;9HxLzbeB2Dr7rl/X9evoBk37/Mpb6Z3d3wOFADEQB+DIw7ADIsAuC1CUVdGloGvb:6xzYDnITePuUR4AfIyXhCHp59DG34F9ZI7rjYWrAYxsoDFzDN6bCG3hHZjjkdZPbt21btgdQQ7tPDjrw32oasrWv+n+hjlooFnwdzb7nkxWdce5gDGtNDBnwK8nLNR62NtR8j9UEB7sV+LFOW781FeYViUeHJkXIb7JUycaCAX2wefzqT/IWe1UGzm1MvHgq671m@9JFNpXXpSVc1WJh5ceutHaUzqbfvEIU80EBAcSY7SRSgEQNECwOtd+k4ifQUwEeDIEgtzqwlwniDAyfUUdFPNgEsQqKVzDpsfParf?w4T3ABNBAYDGBC8wUI9idRBnReLQ)BJRU5Er@ggg==%iVBORw0KG;)NSUhEUg?ANE?ACBCAM?ABpaq8q)wFBMVEX:/+ZUbjWiZDeYWLok1fuz1DqtU6sf7/y41AzMNJmb9r08FHatYrExqnlZCPY1ZP1/lHvzW7r/oL5:mIi3ny/2nf6GvML1z6:7N1sfp++OyqJOtrMrK5KTv9tDK/7Lj/1XV1HXl:fS/pTcLRjx/e7Q8MlRUkjv/yzt5CDqmxz1/1vevsfb/OLo/0DuyRb5/fDozS6OH5vx:r3+uLQ:Te/2Xx/hz+/vnZ:S:/HI:P2/64BAQDY/3j67uiA0taU?AUmklEQVR4XsTZ53bjNhAFYKOzk+q9ufe2PfX93yqDS5AgZNmK/yT3KEfyLJ3w2wGGpHLy/+Tnycm0/eyDgi8PUJl2a6j8/wnPfEAvvNna4E2mlLZ?qpANTgg75TeYqfT/8Dz3IkDoBBUkbACZPPbnhT8O53J6vsHMvr36UtjGKf3dw8ACJ4gDeirD8rOE1T8oR2S4zS/CxR6M+rmbnR3NJVNU1BM6F6P8fcPHxFoAM/XbmB6vkBh3VYvUG3KqLfK1t2KUPMBCaIwH1sAQvA5Y5lkMZNMvSuiHk0H3f/4eg0DGkWablANyzDVoPYQ7EGA9g4MRMf75CkpJbIxLJIx47EQLKreaVF/SiJ7RsNuZjXp6+wKWdfvQ+oSOjSkG;LMgB50RxqST9pt0C0uPKZkTUQHTVVZIpULzeMImxYkuo4FjJJpGFZdBBEoukUa+aqm3z99eKCTj3/E1nX71dUteX1Fap1Ccpnf2gtmv4cUG3xp0+OJkF03FSRJtLZkigxY2aZr8peKmOAmFY8NpJztoyOiYZDdMKLqEe1pH4fNqIhqp3asz+URJh+EKFGDToigilIJA1hqB8ia5cei6MoIRB9TFhRRGPGenscrDoCNaJ1bkHrYSOa0/pHiyiA2SrKOMX1zBoaZd1H7KTBwIlQu8Jvt6LB6J10NQmjU+fjUWcvFSwWhGJCUUHEXKRVVTKjokhprVXasmrRxZ5o9o5oHogAQzEQYfqFosVi4fbRyQc9qiriCBZTmJBVNxGB4kjETiRjA9mIJUnCjMGb9qsOTZrNZk5En9ypzz8WoQOu1opACkTEyW0ds+5k0EcOiAggEqth5IkCkLQWNjKNSDEjNAY69VLWZsmY4JwnCXna6QsRTuo90dyJ2n20eCPCqPAiZOFF077PXou49SSCIiMAPYgRRYwS+tMitRUnklUvTphUVtfnVqRMMrCkL3YMtCJ4Tk/3RUOIUAXGqnKUUHSipkvPx0ShyV48E8YSIYtChpejqBCYESIlMRONCL2KKk41Vd3lbrxzbqbkAakVoROnlI4or9sxn6MK0SLP8zWQQY9AoulXi6DO85kXnRy+p9PYCoxpWajgAhtJISBimRXFvHIiyCThkmSxZFxKwcdjwwX/;Sii1CUe9GFE6FqPUCedkQLMriJvg4nA5Gs6I89kCX1sLcTJqSGpyWlQhAToyLOJK1JAhG2F3MxSilKVYp+cTmWXJSj0dKYZdmK5l3RF4iINMTaymsCtSgUwYNaKPITPZzelrTeE2mdGcboZUFC3wUiVQBEIoaXIpAVGSnSSKWppgJPeMpND38vwvT7XjTPh1aUX6IVrkl55/agFeHKOcxRaESrITYM/RHmH0T50M26rujZa3p8uTQmoRi7B4TQwV2AktIuOYgQQUZnFVmlNImIpJnknBqdJYkweSBq7sDQil+Uh4cHNMntbvoRRbSoXoUPjWje0r1o/y4o3EjcJMZmvOPcCCMY00J07obsiKMiQMx+ED2SONKdjCrya5nqqjLMECg1diyMPhaBtKg7BJCrOREKlNPTh30RSKEIV9hmI62A4ZzLXX8s6RNjCddCEQiTHCJVWAjWnOQsAqfyS9L0IiHvdFrxJCMRT0xmxv1GdPqFRPN1s9mtBiLK5WVOuby0n9saZY2CC3Vr3QYgNCl8FHE9+npmPZySuW5xLDspZHA/VCkl3R5iPOIcoiaVqnSqRVqRSCaaNlGS0CLuU+A5pReRbB5woi0JIQ7Srb09znsgAsl7HIjy83655B3QjqNfJOoF93haynosiKJQpIGojYyiVMuqoq3XZyQySVmasRch4HjQwfP/1i29OWyO4HpGCxmm8LEcIVBWZll2dgZRxo01CSGDh4tIusnNcJvQFdnFp3GPSiKajnxJoHxnSgv6AxzkV9fz7Ru9kMaDH4IafPsmUp2i50RCgq9UkPssK1cEopCpzDi3JoDakEhJNxWEchxHgkwppRtRnxnDS4AggsYFmM/mVzenbbBB/fcwACF/U39WZy4kMuhRIMJDBYmw6IK7VgIhEYkje4GVqZ0KklsQROB8pPn9syjngch/z9f9qpJ65DzUKOoRkbgRvbBHqWx6pB3Gd0ragpJVRLNORvQEkZisX+evM+/Zg/xOLxd8RG0vh1EAuQym4ADU5jJfbTYbizmDCMmyfiCKCtcijW2UMalalZBOpO+EtL3lM4tBzt562pPtmg5iIPWsUORJ033SfIOUWHsrEmUl5xIiT4okBgPTGh1J636NRzWJQaTUnZRUG/H8u01X1MFAdTxe5lV+zflAFJqeAcrLlRWV5ZITyvBxKEq1FgkhsIvKsoqMYSBmfZBsg3SvN9ZCb7crtgWoEfnmeMpn0/GA5NddKEIgWpX3OfbSfWZHQ0YXk3AfFYJBlCoWJ3isTZXiMUtYj0i9KCKR3OpCahJ974q85y3ot9/on7DiC+EaPDDpEOykUPSAHt0vNxtsJLSovuB2H9LryVDaZ1sT9dw3D0r0qHO8SgUJldaPQhQQNSAShZPAOeh1PN5zYHh3mjQ4tJHy/D5fEWlVlhwJH2pbkajuSuEmuNS2OfbRMHuU6vr6+uWmx0SxhciBzlqQ53wmaA9EoWl/NpwEGWw2s9ns/j4nWd0jjvEbNEnVD6+JqCpdQEQcUUUsTq7N64+FJtHj4yIW2+02Ny1oU3u86NMcl5CEOJDXdJfd7HK2vJ9tLCkjk+FvRJGWVoQrrJQpRCl1K3qNWQwRgV4muy3F5A5EonDBfZrjc7hJhzhYdnRLP7tfYYjTusuwjRC/j5Sqlx3uU5Um0+P1j/NX8SInMbthYxLdTNR2+10LMQbIidqB8HlNmH0RunM4F/Q4MqNc2h7VovKAiJrEuJQK/2+iKG5+UDgZb+SkmNgWTbIdqQ3nfwWiAPR5zuErLDTvZv?0eUlxviKll25JyKSEtQjpivKzc3t7e355NySnsTTTVGcnxNoiwsU2+0WADnRUdBxTUii5XZyNBBRsJGoRyXvu/hhJ60oEdH1jx83lNvz8wIkTITb88fHx+8xs138LnbwALRpNtG/4rh8IHLNOZq5X3WYDdSlkARRMXl9nby+1KInRW16IpAVXT++kGhHDUrYjhu/5jaboEPHNB+bvOZ4vjgRSPYqW2bjfdHL7W0xodEwOS9unp6eyHR7XlgRTDaTZHw2Ho9FBlAgOqYJIQdI1Jx/iLfD3TiRLAr?qqhQXT17GQFcQC7STNWV0nTBBTB/Ij6/R9rzr0YXzDTO/HuuPYkin9/OreKKn?eEcAkpJ47qQj4lwvVEuLlnLbIoaX@2mbnwheSUd59SiIuRvQKQQzhIkqJ8dte1CAotJfAKfRcxBjBnbpmn6Pg7acfK8AQ1eOCBRTaCfE92/SAiHNe/PF0zcs5R0nreG4XRFiKQ1pqyPkb7ryGJgRMiU9yTKvP0wZBFmLsuwXx4AEtE7dzUZtf82n8gjIpBwZRtOyCxqW6t1zqIeKNVCZFl2uag4xd6tkmFII7/2fb+u6Goyi5xqZOwepsyi2w0Dt?Zy2PXx3OCvTF5bFl09eL0VnnFUCS+StO0ro9HnHulo/doZFf7X0VSEoHWIqS1rbUQSfrWxLGddjr63lecssRTNeVIl0cRvUeDcqD5B/L1GYHo?+DWITMHbWt1hCBlCOTKW2TuD?XSMPR9QhSgKVEggBaC2C5kNHbXsQAqeisEhIk6iFCCTqqG90wz9T1XudiuOoiDwvA+iYBD5EtNFV1ZOIXgpyo5G;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;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.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@WIRsm3LfuFmc6kK5R3JwAMQMasxRl;YSNUi/rMrXFKZlCyC8TOMbOIsMNdaqYmL1O8NU7pnFvbUoYjEGEBfcTAZ9U4hRvRt+9N03QJf2NcWDVO8VxuT+/v+XrivFevxG58YLQ6cV6J67hSWjXOa/GRdUawOnFekmH1Jn1Fqb0wuy82D0rthRvplW3WjTQ8aJxXbiQ0zn/EdRheq9r+AGeqWIzMOXaZ)AElFTkSuQmCC$/9j/2wCE?YEBQYFBAYGBQYHBwYIChAKCg@ChQODwwQFxQYGBcUFhYaHSUfGhsjHBYWICwgIyYnKSopGR8tMC0oMCUoKSgBBwcHCggKEwoKEygaFhooKC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KC;KP/BABEIAEoA0gMAIgABEQECEQH/xABd?ACAwEBAQE)))?QIDBAUHBggQ?AEBAMEBgYHBgcB)?ABAgMEBRESEyFRBiIxQQcUMmFxgRUjUlORsSQzNUKh0eEWF2KSwcIlJzaChLKz8f/a?wD?AB?I?D8A/U4AqgqAIMAiZhX?Bw8hVcB5W6fiMinju5BkkwjMa7gXDHjn3Axz7hKwFRsuIFxDH1g9CB1g9CBhqANlwLshj6wrQgsdVOBAw1AqNVwLhjx1aEDHPuE8MFRsuBcMeOfcDHPuBYYBtuBcMPWD7gFEK0IGGYiY23C6uQ5xOq0IbU3WlkXAI004hHUWVF2gz59wuLgQgYaaiYAgCImGFzAEfE?wBADAIVBUFAUCAEowqgUQQYBTEHun4jnuq3zHQebNZHmXEc99pWKrMhY2ImI3AuEcM9SBhnqQuoEC8O4V2HqQsQg68SEjDFiUnoHh5dovCovJG4WfIQU0WuQgCgzrSrQxXcNREVFJ5U5jIaD1IWcQB3AuELT1IFp6kGAO7MNKsxBBevTw4kOglKa9lPwCUEJwZFvDZblxEIcizyIaaZDKs8xKgz2nxqNJcCFbhFXkLE8CETMBEGAMAiGEEfESETSdQwBVAC09Q?E?ABiK+QiJL5DkbQTtqTNM3tLeefM0ttp1KnPzISIhWfEdOmZjDEuNpibL03q4JrmY4+FtLNu241K4f+Decp4:Av2OgLVdYdiX3/fKXveX61FiSIjzMQUnUx2bBC0cT0VO5b9mxyYtn3MR/Q/1IWS2fG/MCl8whFQsZT2rkiYrNB8jHSEkiS0hJSCojUxqQorSDWW6KUpMSqqnEQFhKOgidqK60pQhRloLbQYeYkRiJmZiqhaEChaELsPxBh+ILggmUIuTulxGy1PskKmUdnxGm0QUGmoSaaENOQz2i7QQMWpMwzpoQkICYiJhg?IT))AgCIBKhAoQYBXzIecdM7htwkt8Xf7R6VaPNemts1wUtt1d/tFzHbIRMuY83ke2k0lDhdWjHMP3ajuT8DHosk6QoiaWw6Jcl2OX2LF0JR+B/mPC30KxT8R910T/AOq5fn98/wDqY3OtpoaqCPEeq+i59M/tKOKDZ9zDF8z/AFMc5cqh5TtdK2YUl76DUpS1do6nmPQrSHyE5NCtvZSlJlutHdnmWZ8RivBaY7i21eyfwAhs/ZP4DpWkC0QvEcMeUyZ2abVzKN/xtctwXPVwzfa+Zf1H0swg46VbIzPrMc7FRCUqWl7NNpULLj4/EZNo5RslMFvxPpGH;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.rUPDoJDTSSQnyFozLVcdRI?AEQ)YADFNpXCTaFOHjmcRH4p7yMbQAI9ADxzazoxfavflJnEte7++X5j5/Ylv0JtLCxEalbbbKjv3T0PkP0GONMYKFdnUIt2GYWsyPeU2Rnl3jSmIPsqEaDknGTvaH7PbOWS/wB+4XrFeBfl8R15Js/BSn1jSVOxSu0+4e93+A7AQp+QY?AIAHBid@DEvYr0uavr7SklXwI6DtQsOz.6GIZpDTKC3UJIWADuM+YBwYjY+QRERjuyxrEr901JI/IjoOw1Cw7MIUKyyhuHttw0ZFTyFwAXGfEwDnQMkl0DAOwUNCp6q6o1LbUZrJRmRFzM9A4iTS+IlpS9yFR1Ot2EiqM615U5jo?Ac6NkkvjZcxAxUPfCMW4aL1FbaVCzI6nkLYiWwUTgdYhmncD6u9N1nDXwIbAgZgGGJlEDEzNiYPM/TGU2tuXK3ePKtOYlByiBhI+IjYdj6VEfWOXqO7OvM6F5DYJAzAMEdKIGOjIaKimL4iGP1S71JtzryPPPUCJRAomy5ngfTlptU7erQi4VpwIuQ3gAGOeuTQHpZMzwPpyS+tvUWVKcK0PLuDm8ogZu023MWMbDVcnfUn5GQ3g)AC)?P/9k=!