Dot Net Perlsc# optimizationTop 37 C# Example Pages

["#abbBBBB[BBBBBBBBBBBBBZBBBBBbBBBBBBBBBB+BBBBBBZBBBBBBBBBaBBBBBBBBBBBBB(BBB/BBBBBBBBBBBbBBBBBBB`BBBBBBBBBBbKX","Optimization."," Deep in the ocean an octopus hides from predators. It disguises itself on the ocean floor. When attacked, it releases dark ink.","For an octopus,"," survival depends on escape. It optimizes to avoid being eaten. A C# program too can be optimized for performance, to work better and faster.","Benchmark."," We must take measurements. Use Stopwatch and your mission will become easier. Keep track of the numbers in a text file (the octopus lacks this advantage). ","Benchmark ","benchmark","Benchmark: memory hierarchy ","memory-hierarchy","Benchmark: ProfileOptimization ","profileoptimization","Benchmark: use Stopwatch ","stopwatch","Methods."," Now consider your methods. Once your figure out the important ones, begin to apply optimizations. Attack excess allocations first. The ocean is deep and dangerous. ","Methods: fast return ","return-optimization","Methods: reduce call depth ","method-call-depth","Methods: reduce method size ","method-size","Methods: reduce parameters ","parameter-optimization","Methods: reduce recursion ","recursion-optimization","Methods: reorder parameters ","method-parameter","Methods: return multiple values fast ","multiple-return-values","Methods: store field in variable ","local-variable-field-optimization","Methods: use AggressiveInlining ","aggressiveinlining","Methods: use async ","async","Methods: use const values ","const","Methods: use pasted inline code ","inline-optimization","Methods: view IL ","il-disassembler","List optimizations."," The List is a beautiful thing. But if you use it foolishly, your program ends up in bad shape. A predator (like a shark) may eat it before it finishes. ","Lists: count fast ","count-array","Lists: prefer for-loop ","list-contains","Lists: remove fast ","remove-element","Lists: use capacity ","capacity","Lists: use Clear ","list-clear","Dictionary optimizations."," A giant squid signals danger. In a similar way the Dictionary signals a program that is fast. Use a dictionary if lookups are needed. ","Dictionary: change add order ","dictionary-order","Dictionary: increase memory ","dictionary-optimization","Dictionary: measure memory ","dictionary-memory","Dictionary: reduce data ","dictionary-size","Dictionary: shorten keys ","dictionary-string-key","Dictionary: test before adding ","dictionary-test","Dictionary: use IEqualityComparer ","iequalitycomparer","Dictionary: use memoization ","memoization","Dictionary: use StringComparer ","dictionary-stringcomparer","Dictionary: use TryGetValue ","trygetvalue","Memory optimizations."," Memory is a physical thing. It has shape and size (like an atom). In our performance quest we should conserve memory\u2014use as little as possible. ","Memory: locality of reference ","locality-of-reference","Memory: measure class size ","class-fields","Memory: temporal locality ","temporal-locality","Memory: use arrays ","array-memory","Memory: use bit masks ","mask-optimization","Memory: use BitArray ","bitarray","Array optimizations."," Arrays store elements in a fast way. As the octopus hides, it could store its location in a compact array. This would help it escape faster. ","Array: assign elements fast ","array-optimization","Array: count fast ","count-array","Array: flatten 2D array ","flatten-array","Array: use Buffer.BlockCopy ","buffer","Array: use byte array ","byte-array","Array: use jagged array ","jagged-array","Array: use lookup table ","char-lookup-table","Array: use sentinel element ","sentinel","Array: use separate arrays ","memory","String optimizations."," Strings are immutable. Often we must create new strings as a program runs. These excess allocations are slow. We remove them if possible. ","Strings: avoid Replace ","replace","Strings: avoid ToUpper, ToLower ","string-isupper-islower","Strings: combine format strings ","format","Strings: fast for-loop ","string-for-loop","Strings: fast int parse ","parse","Strings: lowercase characters fast ","char-lowercase-optimization","Strings: memory size ","string-memory","Strings: path optimization ","path","Strings: split on chars ","split","Strings: ToString int optimization ","tostring-integer-optimization","Strings: use ASCII ","ascii-string-representation","Strings: use lastIndexOf ","lastindexof","Strings: use short strings ","string-performance","Regex optimizations."," In the deepest part of the ocean, we find regular expressions. But even Regex can be optimized. Often we optimize a Regex by removing it. ","Regex: optimize ","regex-performance","Regex: prefer string loop ","regex-versus-loop","Regex: use Compiled ","regexoptions-compiled","StringBuilder optimizations."," The StringBuilder is like a List. It grows as needed. After each operation, no allocation happens\u2014and this speeds up programs. ","StringBuilder: append ranges ","stringbuilder-append-substring","StringBuilder: consider strings ","stringbuilder-performance","StringBuilder: data types ","stringbuilder-data-types","StringBuilder: fast int append ","integer-append-optimization","StringBuilder: reduce appends ","stringbuilder-append-performance","StringBuilder: remove concats ","stringbuilder-mistake","StringBuilder: store data efficiently ","stringbuilder-memory","StringBuilder: use cache ","stringbuilder-cache","StringBuilder: use capacity ","stringbuilder-capacity","StringBuilder: use chars ","stringbuilder-optimization","StringBuilder: use Equals ","stringbuilder-equals","Class optimizations."," Prefer classes to structs. When we pass a class to a method, only a reference is copied. With classes we avoid moving things in memory. ","Classes: avoid structs ","struct-versus-class","Classes: cache DateTime ","datetime-performance","Classes: cache typeof ","typeof","Classes: use static fields ","static-field","Classes: use structs ","struct","Classes: use tree ","tree","Classes: use Tuple ","tuple-keyvaluepair","Branch optimizations."," For survival the octopus does not spend its time evaluating slow logic. It moves quickly. For C# we speed up our branches with switches or for-loops. ","Statements: avoid LINQ ","linq","Statements: avoid yield ","yield","Statements: hoist try, catch ","exception-optimization","Statements: jam loop ","loop-jamming","Statements: reorder if ","reorder-if","Statements: unwind loop ","loop-unwinding","Statements: use complex expressions ","arithmetic-expression-optimization","Statements: use decrement ","decrement-optimization","Statements: use for ","for-foreach","Statements: use switch ","if-switch-performance","Some research."," You can find many optimization tips in Code Complete. I recommend this book for some tips. Some strategies may not be useful in C#. Many are still relevant. ","Use a high-quality design. Make the program right. Make it modular and easily modifiable so that it's easy to work on later. When it's complete and correct, check the performance. If the program lumbers, make it fast and small. Don't optimize until you know you need to.","Code Complete","A final note."," As an octopus, hiding on the ocean floor is something to optimize for. In C# programs, optimizations to reduce allocations and reduce logical tests are more effective. "]

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bq+JlcvxanP7osNX0Yr4V7C2xW1an46txUTx5fGlvz1m/L8GPebZna1iJmtHaKqdS3+p6xp5QRdP39Kx93YT89ZudIL/StJmlarAhqNcY6hD833N+t/Vn8X/iZtrlZqTRrVJcnaoRI2UhHiu6dPvk/UxHv0YrYANVrVtU0l4TZTudVvwtX97Tf/u/Qea1ky6dZZYU/QbsRWv1Dj0Ju/h6iPGlizLzf8k+nnGytFdCtToB06rb6rN5G0/ql1R9Cy5IfApv3vyZrqKz1YtN1aqi1VtsltFiSWfqbiPHXa3+q6odPq/IeOnZ+z6eOs1zGYhxdSV8J6am2EcLKufkL9Y5F4cCTPUD2jETEESIaoh9sMWe4FE/LxnjjnWmekG8d+3+iftyK9nVW0givciQZXryK4b3tNRH4N9vD4NsmG3dmuLNZwwwzSDDDDAM1OdhnNs0PJfFnquf4QX/AKlQr/4zqC:AGvH@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?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$/9j/2wCE?gGBgYGBggGBggMCAcIDA4KCAgKDhANDQ4NDRARDA4NDQ4MEQ8SExQTEg8YGBoaGBgjIiIiIycnJycnJycnJycB.gI.oJCw@Cw4LDQsOEQ4ODg4REw0NDg0NExgRDw8PDxEYFhcUFBQXFhoaGBgaGiEhICEhJycnJycnJycnJ:BABEIAJIA8AMAIgABEQECEQH/xACH?ABBQEB))))AQIDBAUGBx?AQMCAwUEBwUFBwUB)AgABAwQRBRIhBhMiMVEyQWFxBxQjQlKBkRUzcqGxNWJ0s8EkNHOy0fDxFlNUkqLhEQACAgAEBAUF?MB))AQIREiFBUQMxYYEicZGhsRMyQmLBBNHw8f/a?wD?ABAQIBAD8A9/QhCABCEIAEIQgAQhCABCEIAEIQgASXZKq2+a6RuhUrLKFWergEshSCJ2zZbtfzUjTATMQu2vzZGJBTJdEaKHesjeMi0BMkuyi3rKIp2SYkFFjO10o@MypNPqpBmRiQtFrRLoq++ZLvmS2hKJ0KPeMnZmSiDkWZJmZJmZACpubTkkI2VaSV01uhUXUIQnCAhCEACEIQAIQh?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?hCEACEIQAIQh?sZ21fzWysZ34n81Dxvx7knD17FOrZxBztrZ3t18FxtXstTYjXRYlXnLLV2fNJmcBjG3DHHHqzNrr9ea7qQdFkVDyRzZMnBbtPe7+WirySerHqUou45Pcxo9mNnYY92OHQ878Q5v813W1RytSRjTxj7EGsAfD5KFydIBFfkkTSqhrlN85N+bs2BkaRuqVxZUIzKN26dFbZ96OhJ4qd9CUTa6lZ2VZoHv2n1t9FK5NHGWtsrO/K/LwSpvYHWg2pFrKg9rq0MoSWDM5vbNqzs/wCajOky31ctXLV7vq97fJJ9zyEaogYmutGnfgWdHRbrLxmXPUnu73e93WhEIkzapVe2fmIOY3KRw+n5KV3aybuBuRXe5flozafRQVcBSxFEEjxZrcYszuzM7Xaz9eSVYleWu+grocTtdTBazKlHAURNx3jEGHLze7e9mv0VmO90qvVUIb6EIVkjBCEIAEIQgAQhCABCEIAEIQgAWM/afzWysIpGzP5qHjfj3JOGPVapjA25a9zpsldTgWTO2bll569FBBW0ldLNTRyDJLDb1iISu4O/LNbyVdzj9tpkmB1bTreivJHlTIyG5NfUe03Raj0sUls7eLav0somw6CP7u/TV76NybVLhGNbEUTBID99ns/myZMcgM4QF7Sz5bWd72u2jq7FTjGzizaXvr1TvVod482Qd7bLntxWbuuklCUlQ6LS0szMKlxKxeuOxR24b2cr+bdysVFUPtAsRvld3EWu/LkysOAg3C1m8FE4hmcsrZuvekUJKKjf9HOcXJ5V0Q6.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?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?hCEACwijfM/mt1VNw11HxI4h0XRnZX6KtT1DyHMBD91Jk6s7dz3/VbW4ZM9XbXK3ionw2PxrVGFXVcA2hNqjNnyexF7sTs+TX9/uvp1T8OkkmiLORSCDtlkkHJJ+.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.Bhe/5f0SN2G8lIhNFIkj9t/wAKmQkFIR7LeSQfvy8mU6EMA6f77krPxD5JEJw0dfXmlvpzTEJQJLuo5CJgd7uhCUD/2Q==%iVBORw0KG;)NSUhEUg?AIw?AB4C)?FqEXt)oElEQVR4Ae3ZsQ3DIBBAUfbfwxNcfR0dEpInIiOEI7Li4v0JXv9bnLS+dp3UIke13MFErxZXi7mqzR1MX9U6DAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDMyPmLyr5Q4mRrW43vUo14uCgYGBgflDMDBx0mOYvKvlc5i5qk0YGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYmHdiclTL5zAnfQArQiNkrpqF2)ABJRU5Er@ggg==$/9j/2wCE?gGBgYGBggGBggMCAcIDA4KCAgKDhANDQ4NDRARDA4NDQ4MEQ8SExQTEg8YGBoaGBgjIiIiIycnJycnJycnJycB.gI.oJCw@Cw4LDQsOEQ4ODg4REw0NDg0NExgRDw8PDxEYFhcUFBQXFhoaGBgaGiEhICEhJycnJycnJycnJ:BABEIAIYA0gMAIgABEQECEQH/xABq?E?QUBAQ)))?BAECAwUGBwgQ?EDAgMDBAoNCAkF)?I?QMEEQUSIQYiMRNBUWEHFCMyQnFygbHRM0NSU2JzdIKRobKzwQgVJTVEkqLCNDZFY4OTw9LTdaPh4vH/2gAMAw?AQAC?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?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?kSpEAI6a6c6a6VCM8o48H/tRU/Zi/liqJm2Ws4xtNVU8QzzAYMBDH7TvnYBbwF1UNYqvThjjz8y/wAqmTVIaVYg+dvvU8RvGS6am3T0kTSSkOly0tpd3fOHfxZvJcrs2Pii0gLIbxUBDyOYXL7aM7Lto79URO3U0g/VPf8Af3VCIPjKUNQknrKzn3Hqb6m5jvNDWRejzM4Cbt052b5F3U9PZI6aUZdZSaS93Z2Z22ysdBI443Wks01bLMxgTlp08zdsac+OU2W3a/4h6fZ0WnEsU/Ig6vUD+OrHd1jqyLft2W5vARVRx0PN5J41jq9h8+brK1lHUQVB084aTD8Hbzb4KKGMDVPoUYB1YWl4WnIK5o+n1ouxa3xt8Piq0aFstqZaewWuCKP06RmIvZj+Hm6ltU/YW3TsnvVFJOATgLkUTOBfLuzrDXKDZ2XpITATlh2+PxZZjiejaGSEYgYYMO4fa97/AETdPL5G+HgwM1CWtHojAO/dXUkPV7K55qd9PZS54YiJ+A4tPFtF5+t/kyL15eWcGQuPEtGT/wDm/wAqReoqDUWfoJY/KMpuUrOmCjkqayVIKKhCEACEIQAIQh?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?hCEACRKhACOmunJHSiDHSJ7sm4SiDUJ2EmEAIq+QRGtk6W9Y4lJnwwLNsrHCpK+pjir5h5THsLbu+dxbsl5BHRKfMZgCdo93+ePBc8UVLNq9qQxZmZu23mko6nmaQ5LBELvl3bDs/wDWXYxnIbRQt7OdeWxj5JyXkXJLBGANp0t2XLcqian0aGbTv/WUozEU7jGTcqH6Yn7t/ouWGtp53mpqkxKHL8oybD7v4JeQi3eTnrgaahat0vrwwfsth+6psurh4auiIBN/SKKbOow2DS/ZibLvnH8FwVNJoqGhiyWvHLLzZ03/AKS8llbgjG3OZs3rS07/AINlFJWyQEFPIXq4ujzyzLnr60oIRt4fqcNJ8Xb/?TRf0sBlD6XYJPn2YkfuD/Utp6enqwbkuwF3+G/muGqjqKVxAifT3HGcZVkfo9LBHzI2HsO/wDe7Llnu1IUBiUeps7C++W80W5ETi+g2G9MGBlF/Btu6le+U/MccOQ7dTKqKniq2cqM+v8A3Jvv9zqvn51OeiUXAkbWwo19INNNIFRFj3tO2O6sFleG6mT04Ys5A2L7sM77LVpjVcCtCpUiVIAIQh?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?Wp/JvRzQX6czcXH0Q22znPMi+Ca5txaI07s9JQhCgAEIQgAQhCABCEIAEIQgAQhCABCEIA/9k=$/9j/2wCE?gGBgYGBggGBggMCAcIDA4KCAgKDhANDQ4NDRARDA4NDQ4MEQ8SExQTEg8YGBoaGBgjIiIiIycnJycnJycnJycB.gI.oJCw@Cw4LDQsOEQ4ODg4REw0NDg0NExgRDw8PDxEYFhcUFBQXFhoaGBgaGiEhICEhJycnJycnJycnJ:BABEIAFYA5gMAIgABEQECEQH/xABj)BwEB))))AQIDBAUGBwgQ?EDAgMEAwgO.QD)?I?QMEBRESIQYTIjFBUWEUIzJCYnFysQcVMzVDUnOBkZKhsrPBFiQ0U2OCwtHhJSY20oOi8P/a?wD?AB?I?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.c5cPDvHXPK+jphusoQu+GZ/FZmZuhh7FNoblLJYSpzD4Kuj5+Bu3aTKs1bLjnId4XVzUFo8xRuwsOQGEnbmb4Nq6i08UkBVRFM5M5kwg/Lwn1Xa7bbh7kh4fEH7qt4aYQw0RWhmO3U5/ww+6ycuVSdDQy1UYsRR5eEu0mFXMcLYaMslPUEREzv0upIBonFS2W8z3KeSKWMAyBm4cetut1eKSIYKK74oI1QXu91dtqwggCMhKNj42J3xci8pupVv6WXH91B9U/wDuncElbFBZSn2nr5TcSjh5Y+CX/dBGgtSmyTiR;5slM6gVfgOuf7RRlxLolQD6rLXS3vLjooNTG5Mrm1zDHIzuuFXot3VkHY3qVHIaudsv1a9yQ+RH91lnN7qmoo3YWWpOrEmZsVaUEBTSCGVyzPhwrpFV7GlTBYhuG8YjjF5CDDifNhl82HSuZ0VQ8RDq66NX7aXCo2PpAzDu5ZZKeQMPgwEcvbiotQJ5n1LweHL+88pLmOpwpe5DAWeTCXNq+XDH+6xO0EX6tbpsG9yKIvSAy0+ZsFX3wP9Ds8+Xomiz+ieb7Mysb77w2yUMfdaj1;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.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:2Q==%iVBORw0KG;)NSUhEUg?APg?ACZCAM)1pwfG)wFBMVEX:::NwsSqYyWaw5abPu5rlofrdOarGEi7rNvMmal73429OspMK1tMn+/L9Ub3XIsHPLyZf66aHa36avybjv1YTE27uMqqPc9Lv:M+Gf22XkYBlYFP78tva0b/9+efu5dLi1sijnY7NxbO/uab16tesppP/+/DUzLnHwK7n38y1sZ7:fcfGBi5297j6eCrythv3d/Q7+WPt9Bkmcd9qMfw9eWMpMja7NBGerrT4NvMztTf0LhQisH/7+Hf9uX/w1QH?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?RkbKDAYlfnCZCw/twACACwMdyzPLqlb7Aibx1zoJf4JkyxiiyBz+/urq6+PP6+vz6jw28mgrYDA4QZUcTwCACH9DwBARC?OcA8YjZjxh81H34XFEgDjiSoJ+dr8VXoMndCL9b3iV2Chnn5HcPvz63n21hRNGCgEidcCkQsae+YHBCjlWaGYCHxKJUA8Q9eXuiTfyBS7i0Dt5xFzcr1vpO3i1AHGMRl72vowwl5cZv1rBNSLKVAaGImjVRtZY1WNTH5lDZ7aILlgbBDO/NCvKnOrjuzrKU0s9BVwybYqy: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;8OhZ7TVzItqeKft3A3CwROBa4sXNiKE7w6AV2Fhxz3VbcT38Ov3MJ3hipein6YjUrBohqutZbfSTFf3IUDwNSZ?Q8cxyXjycw9cGTHodOwhUHYFRms2SM2pyzP0qpEHITwY6wQPcVj5UxRfJXU+TiV7qQ9juhvIJLSj25NAtdtB27H4CR00G4oTRDyvmu6m3z8nZePf8fbzOyEjwbPOjkdndebQu388tjws0t3LpbwynPANc/Cv4icP1a8Pud/rJw634puH4W+KyF+c4J/9e+GS43yiNrmFV3AdjmEhLZPyidmqJAFUlQEkf4/u/qvBJ4kp1NJt7vTKZ29jMVg6JuqfWo2ziNOzs3wP9+xwP8i48HeN/fr/l7wS9ah3TthuISdoFc9PQJT9A4hk+pVM0v70uyYVl8+26pJv2uXqe1/PXga03MlDpOsa9ugkYI9wlQKZg5yk/BSwrvCXbDtjiIYReM4d3NhobQvx78IKxUrSsaW7GluFnoSyI/FXI2iw2tW2a9ztYaqWYni4sbNvDkyXV2U9G6a5flkOnWDegM@jWGgXwl0K21gH/CKUbZXFKW9vMSyWim05mcWGZx2TRYZ5icc64cXNNRcLC7w6i8eSgmObRRTcDo3GjarPp+8Fvs14TRtGWFIG+gR8p1mJIQmtDKWCmqSyufYlevDZwZ8ygTsK2IspNXrTCW2I0vTwKshXgAC5LthW/HBmSqL6De4MoXyrytsuG4PuVyHoManDlPRQaYSts3lGwtd+y4slDyUgsHa+upmh9+HfBO+Z9s46+ONjvixr+V1iAQ9gnlxWy6xaoPgvbUew3cPbsCnUgigiOtVuI+0YYxJAG7RV62ED/VNNLI+AqYRrhl3H8brkkIdjkUFcVI8ozuAdhzJt7oAze13TF4NxdrFlx7boGiui9CLcSmXH8qx7vj9aTZXZ5AlmKCK5rNqMy+FIyEWOHeQbXHup7d?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.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: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@MUqe40beomlwse2sz7NetAzLEqbiaZRwAl44PgJvRMwV2Lk82V938LZyGzh7D8z+FRyeSIUQrbBLOBLr8I+TDoft/wUuwu5R5H019AcBvrGAfP8GtSXSJ+jgtZRCAzwX21c81cKF0/BankKpHmYhv4zPIg7hTB4WIwYhSSTT@dZsfRLZWVxijpMx1mPkwrT0xhkP06FkqpX/cceXyuGAZnDa6YoM7gYGpozuDVGvwXvyE/ABLi5xaps5jLTAGrYwDklORlg2OUulbDLivtVJFqNDXcA7+FEx2LADr/5v5J1rvZiBUSYcLCK1l5lcMT4lTdwRNlTnSIovsDqnIyrbhyTy6fscNX3H4IDzgMih7mq6GUHlyW9hvob8EYQkYjfwftU92IBDlxfYT2vob6DdxXZDL6VFhx38PY7uHVuVCfL0NkONYIde/60gdsPwU/Enr0BeNjB12XJ4GqSMqn8JNSxbQK4ALehFV42lQFv8kgGdyEE9QquEKFhwf40GVzEHicOGJx00Ld7fAhhTKMrRvx7yH8Ad0slhr05hjnkt4vr63zzXtkOoRbwOOtxB0eob+Ark24pg2O6ISw+ylfwbgmyAzhcLntg/zQfr8ni0hIT2XGbn4bUDXD0kZ8AxcPGlCoGIDcNJXC2fbo9cSSX;GvuxJvtyW4iaw8MJfQrvm6ei+7yoLWM+s0vFBtBbPTdoM8AhKHOqHP66JvGbOQA0+VpoJrsaZnT+Xm8efK4XyIobEp1A3AVVjCOMqt5gzgPwl1iOV2xpGvau+R/dap0FbypttnkdoakCWhwg/At2VnbRy9krmZtWRW2V8ANzhnU7ezwhls4WZG7hP1myGoo5FflzFVU23SrKvUhvdPjPJJ/a4@X823HcA/D0BIv2OwTUx+c8spRrB3wa+DPJO1bMe3xUs4z2DFz1Mn6+mfyQpf1PwB/gD/AHehTDtZa234iu0w9hDIj+umh9D1rkdDbvi5MNHlXYwgkN+CtD64TeB57Jx1rkwoKjM3lcRkXvNSoulHX8gkaWAzusziXM7pOT1o2K+Q9Lm8TMA6OnfVxgwdgdbLKbyJ7JhT1WlbO23UjgtFz224zc9Ka3PrVZwXqvRp3LSAdJFS4j6VYcMrhZzEjZpGcx10eMybECm75Vs9QRLI5QMplrbcIHWgpfUejHQzHu9GKgVEkrhqwsDpgKO9/gxe2GADrJviDgXBlR6KwyInCrFK+FZaIDrpYqTqui67pXKAO9rwR7gDTOTQU/McX9Ld3C5C.ujClsj2ZJ7Er0pNlJmATeH8hTquAlz1F+FXhH3wsDqv61MEAIsN8KA15uhQHTcS8MO?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)BJRU5Er@ggg==%iVBORw0KG;)NSUhEUg?AMk?ABAC)ACVEgzJ)kklEQVR4Xu3YOwrAIBAEUO8PucjexhOZysVGQtgiH96UUwy8Stk2ZnqbGUuy7OMylan61uclJ.@.@.@.xc6QklmR5ZLUFVKbqW+1+tpLKVH3rUQ@.@SZ+JtcpkGVltJZWp+pZ/Fw@.@.mJ24rbygMSEhISEpLfvIz+XW+R@.@.@.@CcKq7/sEUc4H8)ASUVORK5CYII=!