raven
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Group: Forum Members
Posts: 36,
Visits: 78
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Hi Dave,
How would I go about presenting certain trials randomly for a given amount of times?
For example, if I want to run TrialA 3 times, TrialB 4 times, and TrialC 5 times, but each trial must be run in random order without being repeated for a total trial count of 12.
I looked at the Inquisit Language Reference for the block and trial elements, to see if this is possible, but the block element only seems to be able to run a certain number of trials sequentially, not randomly, as per the code example:
<block Block1>
/ trials=[1-12=noreplace(1-3=TrialA; 4-7=TrialB; 8-12=TrialC)]
</Block1> Thank you!
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Dave
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Group: Administrators
Posts: 13K,
Visits: 101K
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+xHi Dave, How would I go about presenting certain trials randomly for a given amount of times? For example, if I want to run TrialA 3 times, TrialB 4 times, and TrialC 5 times, but each trial must be run in random order without being repeated for a total trial count of 12. I looked at the Inquisit Language Reference for the block and trial elements, to see if this is possible, but the block element only seems to be able to run a certain number of trials sequentially, not randomly, as per the code example: <block Block1> / trials=[1-12=noreplace(1-3=TrialA; 4-7=TrialB; 8-12=TrialC)] </Block1> Thank you! You set up your noreplace() pool with the desired proportions. / trials = [1-12 = noreplace(TrialA, TrialA, TrialA, TrialB, TrialB, TrialB, TrialB, TrialC, TrialC, TrialC, TrialC, TrialC)] This is covered in the documentation, see the examples at https://www.millisecond.com/support/docs/current/html/language/attributes/trials.htm
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raven
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Group: Forum Members
Posts: 36,
Visits: 78
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+x+xHi Dave, How would I go about presenting certain trials randomly for a given amount of times? For example, if I want to run TrialA 3 times, TrialB 4 times, and TrialC 5 times, but each trial must be run in random order without being repeated for a total trial count of 12. I looked at the Inquisit Language Reference for the block and trial elements, to see if this is possible, but the block element only seems to be able to run a certain number of trials sequentially, not randomly, as per the code example: <block Block1> / trials=[1-12=noreplace(1-3=TrialA; 4-7=TrialB; 8-12=TrialC)] </Block1> Thank you! You set up your noreplace() pool with the desired proportions. / trials = [1-12 = noreplace(TrialA, TrialA, TrialA, TrialB, TrialB, TrialB, TrialB, TrialC, TrialC, TrialC, TrialC, TrialC)] This is covered in the documentation, see the examples at https://www.millisecond.com/support/docs/current/html/language/attributes/trials.htm![](data:image/png;base64,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) Thanks Dave, That makes sense! :)
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raven
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Group: Forum Members
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+x+xHi Dave, How would I go about presenting certain trials randomly for a given amount of times? For example, if I want to run TrialA 3 times, TrialB 4 times, and TrialC 5 times, but each trial must be run in random order without being repeated for a total trial count of 12. I looked at the Inquisit Language Reference for the block and trial elements, to see if this is possible, but the block element only seems to be able to run a certain number of trials sequentially, not randomly, as per the code example: <block Block1> / trials=[1-12=noreplace(1-3=TrialA; 4-7=TrialB; 8-12=TrialC)] </Block1> Thank you! You set up your noreplace() pool with the desired proportions. / trials = [1-12 = noreplace(TrialA, TrialA, TrialA, TrialB, TrialB, TrialB, TrialB, TrialC, TrialC, TrialC, TrialC, TrialC)] This is covered in the documentation, see the examples at https://www.millisecond.com/support/docs/current/html/language/attributes/trials.htm![](data:image/png;base64,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) Hi Dave, I've been testing the above that you recommended, but not getting the desired result. For example, with the following code, I would like TrialA's to be presented 12 times (e.g., TrialA1 and TrialA2 in the 3/4 ratio, so that TrialA1 is shown 9 times and TrialA2 is shown 3 times), Trial B's 12 times (with the respective 3/4 ratio), TrialC's 12 times (with the respective 1/2 ratio), and Trial D's 12 times (with the respective 1/2 ratio). / trials = [1-48 = noreplace(TrialA1, TrialA1, TrialA1, TrailA2, TrialB1, TrialB1, TrialB1, TrialB2, TrialC1, TrialC2, TrialD1, TrialD2)] How is this possible? Thanks!
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Dave
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Group: Administrators
Posts: 13K,
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+x+x+xHi Dave, How would I go about presenting certain trials randomly for a given amount of times? For example, if I want to run TrialA 3 times, TrialB 4 times, and TrialC 5 times, but each trial must be run in random order without being repeated for a total trial count of 12. I looked at the Inquisit Language Reference for the block and trial elements, to see if this is possible, but the block element only seems to be able to run a certain number of trials sequentially, not randomly, as per the code example: <block Block1> / trials=[1-12=noreplace(1-3=TrialA; 4-7=TrialB; 8-12=TrialC)] </Block1> Thank you! You set up your noreplace() pool with the desired proportions. / trials = [1-12 = noreplace(TrialA, TrialA, TrialA, TrialB, TrialB, TrialB, TrialB, TrialC, TrialC, TrialC, TrialC, TrialC)] This is covered in the documentation, see the examples at https://www.millisecond.com/support/docs/current/html/language/attributes/trials.htm![](data:image/png;base64,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) Hi Dave, I've been testing the above that you recommended, but not getting the desired result. For example, with the following code, I would like TrialA's to be presented 12 times (e.g., TrialA1 and TrialA2 in the 3/4 ratio, so that TrialA1 is shown 9 times and TrialA2 is shown 3 times), Trial B's 12 times (with the respective 3/4 ratio), TrialC's 12 times (with the respective 1/2 ratio), and Trial D's 12 times (with the respective 1/2 ratio). / trials = [1-48 = noreplace(TrialA1, TrialA1, TrialA1, TrailA2, TrialB1, TrialB1, TrialB1, TrialB2, TrialC1, TrialC2, TrialD1, TrialD2)] How is this possible? Thanks! You have 12 entries in the pool. 48/12 = 4, .i.e. each entry stands for 4 trials. You'll get 3 x 4 = 12 TrialA1, 1 x 4 = 4 = TrialA2, 3 x 4 = 12 TrialB1, 1 x 4 = TrialB2, 4 x TrialC1, 4 x TrialC2, 4 x TrialD1, and 4 x TrialD2. If you want something else, adjust accordingly.
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raven
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+x+x+x+xHi Dave, How would I go about presenting certain trials randomly for a given amount of times? For example, if I want to run TrialA 3 times, TrialB 4 times, and TrialC 5 times, but each trial must be run in random order without being repeated for a total trial count of 12. I looked at the Inquisit Language Reference for the block and trial elements, to see if this is possible, but the block element only seems to be able to run a certain number of trials sequentially, not randomly, as per the code example: <block Block1> / trials=[1-12=noreplace(1-3=TrialA; 4-7=TrialB; 8-12=TrialC)] </Block1> Thank you! You set up your noreplace() pool with the desired proportions. / trials = [1-12 = noreplace(TrialA, TrialA, TrialA, TrialB, TrialB, TrialB, TrialB, TrialC, TrialC, TrialC, TrialC, TrialC)] This is covered in the documentation, see the examples at https://www.millisecond.com/support/docs/current/html/language/attributes/trials.htm![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABFUAAAB9CAYAAABj01yDAAAgAElEQVR4Xu3deYBO1f8H8PfMWEokhPoiJEa21vliKtp/WSJESJKyRWQnydhlCWWJEIVKQkqS4kuUFGVpsZUtaRJZY8aY37n3Pst97j13ebbxzHjPX+V5nnvveZ1zzzn3c88Slyn+4OIvPT3Nxbf4FQpQgAIUoAAFKEABClCAAhSgAAUocGkIxDGocmlkNFNJAQpQgAIUoAAFKEABClCAAhSgQGQFGFSJrCePRgEKUIACFKAABShAAQpQgAIUoMAlIuA6qHKJeDCZFKAABShAAQpQgAIUoAAFKEABClDAlQCDKq6Y+CUKUIACFKAABShAAQpQgAIUoAAFKBAowKAKSwQFKEABClCAAhSgAAUoQAEKUIACFAhBgEGVEND4EwpQgAIUoAAFKEABClCAAhSgAAUowKAKywAFKEABClCAAhSgAAUoQAEKUIACFAhBgEGVEND4EwpQgAIUoAAFKEABClCAAhSgAAUowKAKywAFKEABClCAAhSgAAUoQAEKUIACFAhBgEGVEND4EwpQgAIUoAAFKEABClCAAhSgAAUowKAKywAFKEABClCAAhSgAAUoQAEKUIACFAhBgEGVEND4EwpQgAIUoAAFKEABClCAAhSgAAUowKAKywAFKEABClCAAhSgAAUoQAEKUIACFAhBgEGVEND4EwpQgAIUoAAFKEABClCAAhSgAAUowKAKywAFKEABClCAAhSgAAUoQAEKUIACFAhBgEGVEND4EwpQgAIUoAAFKEABClCAAhSgAAUowKAKywAFKEABClCAAhSgAAUoQAEKUIACFAhBgEGVEND4EwpQgAIUoAAFKEABClCAAhSgAAUowKAKywAFKEABClCAAhSgAAUoQAEKUIACFAhBgEGVEND4EwpQgAIUoAAFKEABClCAAhSgAAUowKAKywAFKEABClCAAhSgAAUoQAEKUIACFAhBgEGVEND4EwpQgAIUoAAFKEABClCAAhSgAAUoEMGgytd4p+cKnO+VgieujRzsmXWvYcKy3Th+PgHna7TDuCY3OhzccB3fvIbuq67F8/0fRenIXZbnSCdwaPMOpN+YhNKXR/zg4oAuTCOZvkgeK8IcJ5YMQt8jD2HqMzUjfGT94Q5gzbAx2FjnVfS+LYqnMRw6a9IWgfSc3I0tv+ZGuZtKI7/F4bJNWiLAEXiI4OqCi+dkqFNc5GnEqWL1gKlbsf7ENbjjhmIurtC5bg6+7XJx2qh+JXr1n71FcPdOVAnCOngG/vlpPQ4Xr4WKRVwcKIva24tX17gwiMhXIumeU8piRGDdHSSLyrHlxQRVb7tL0kX5VtCOxvqaZdeXb0H1axzavaCOdVFKToROyvITCUiXQRWt0H1yPF56zrhaPTHq4YORD6pkiI5rv49xstMQtL8eyMhIQEKCU7KzMqiyEe/3XojUdqPRuYLTdYXyuXPHHUFXxDbXEcljhZJcm99kTccweg8VdhyRTNuf7/THWxVGRico9N0U9F2aD48NaYNblQSdWYVpE/7GQy809QUsI5kWpyIU6bTKjuf+HMHVBVnpFOhoqFOMeWqHvnYM+h1vLur6Uk5ZE9bn7s1dnEZSRq1+dfKjIRj4a3UM6PZ/KOp4aIe6OaS2y/GkUf5ClOo/RwvDvRNEnlmCZBzFnrmvYMb2a3D/mC64z/fFDPz70yLM/+Ab7DlxHhnxuXFluYfQ4pn7cL28ewO4Lve/Y93IMViVPBAv1XYRVYlEeyuO0XfhHguGG/CgSHtSNF5IuDZxWWRlx3N9jki6B1ePu0xdDvraL1g+aCXyDH7Of0+FU45T1+G9N5di+5E0pCEXEoomok7btrjraouOvqRMBFdvx3BWBO1orK+DKLuRqGPdULq+h90cTFL2rH4WTL8GDu1eUMdyk47of+fsZyMxeGUBQ9unP6/MMojyE/0kZNszuAyqBKZv5+tdMatEb0Pn2kUAIFim3xdi7PjDuGWsvlPkdJCsDKo4XUu4n7swDboitrmmSB4r3KQbfp81D6FReqhwsIhc2o5g49ghWHNPFo202TYD/T+6Ch1f8I8Ci1xanApQpNMqO16kz+FPU9Y5GR1d1CkW9Afm9MLkwt2iHFSJsLmkjDqVLHefOziG1Ha5O3P0vhWl+i9Yi3Dz7OSP+GzqLGzOXwIZv+VBDX1QJUN0JietxhWNW6F6qQLIm7YHq8a9hqVlnsGEFlWktFEr95Fuby2co1HXRNpEdrxIn8OXuZF2j94NGXtHPvoJpo74FRX0ffKQPVPx9csjsLzicxjQsBzy4hyOLHoZI369GX17NUBxSeqjViZiQTpoxzDq63DrWJdeEc0vWdlzeR32XwvDMSLnj/BBfl+MsXO3An8VsX52jpplhNOSDQ8X8aBK/KO349Rnq7HzVAbichdByUbt0TGpuIhBa39pO97H2+9usPzca3h+wwxM+nwnUo9nIFf+y5BZKBntu9ZDKWTgpPhs1sc7ceic7BwOQZWMw/hpzhtYsOtv/Hs+HnFFKqLeM097IuO/4NNBr+OnRhPQ42btSs5+MgyDVl+Ou4b2RP3LlH/ROv0ra47EgDu2BozOUTovI+MexTMnl+DtH5Xj50KeMjXQ/MlHUdk7X0J0+FbPno9Vf2Qij4jNp+fNi9ziqKcrP4ZRj1YzFCEtLRkNq+Lc6q9Us/gCpXFTy6fR/IYrte8aK2Lb9HnzYCneXbQWvxzV3tTF12iLkY3EtCrDsc5vmYkxi/5G5XY90aCk8c2Bcm3focRLyTg2aR6++gco/vgrwu0Atrw+G0v3H8Wp9Ey1DJRp2Q0dq/ivt9O2mzC4xLeY9eVBHEuPM+SBco3nkLp8Emas3S+mfeUWby+qoHmVvzH1ULJ/+o9jOrXrK96xBH6bv95nV7NtG9z23SzM+UY7dp4y9+KpTnU9byl1lWuu6Ri4IAEPD38a//Xlym6sHDwJP9QfJ0aCGDz+2Ygl0xZik/rGJR4JBf+DpDa90Kik8mOtzM5Y+gsOCxNjHpo6vWrapuPdHUdx7oKkDInPf3xnNj788Q+Rhjgk5C2H2n3rIN+0N7Hyr9PIyH0FLhOFKv7OZzHgvqtVS806E5m58uLKKk3R+fHbUUhSYdnen7ryUWLDdIxfvgNHzsbjinx5xJHK4/5BbVBF3AP9UmugZ75vMWeb9fVbp0/Jgxn4vfWTKLNoOj7+/Szi7u2N4XVK6K52F74cO1uSVvEd7/21/zTSRNnOX6khnnniTlyrvIVW3l6/M9lzb0KUzStx5T1P4YUHzpuOl3BHfdz1w8eSc+y3KPeGeufMD/js9cX46q/joh4QeSHu25ptu/ruI6cHHTUfFmhv08/nyo/iyS3x9MOVcJVHQfn9iITW6JFrEab/7yCOFLkbPfs0EvWj4U8pl1MXYKO41y+I9Ba+vxYqr1mHox090zSN9cfepZj59lrtLb765rAyGnZqggIfvIJFO47hVNwVuCJvHE6Ub4wxLYtZ5lXmtncwZen3OPyP9gYy8D4T1yjyaf28D7DiN6WMiHq40H/R8oXbcXysrAx78/VdrD54Un5PiHR02nYrJty6E68t+AGpmTeiSZNcWLvsZ1MZTZZ8t/7LHXGz4Y3+sS9fw5zP9yH1jFZP5rupBbq1vNWTB9ZBFcu2y6nOsriuWqb71L4+gUPZ0+qjt/D2iu3YJ9oUpU4o9vAL6JV8Qh2RuvmOJ1B2w3tqmZGVPePl2JVV63ZcfxS/ZYt98nol2bZ+Dbyik5+Mw6TLmqB/4nfuXsp8PRHd/1dCMkX4OH6aPV5S7m+D7P7r1ScJe4aN1k0fdW4LA6YmS++9p1C9gKSilv2TTVDFsU52aKP8p7M2gW27pbXpxnaoy+PlcchkXAdPpX0eRH1zwTBtN0j3AEvDfe263Fm1W0p7YZwWb6w7tL5Kqa5lseOt/6l17wVJ3zkwy23qgIwfsGTQXOxo+BL6Jmn9rowNEzFoWX40HPw0kkRbaF+3yevn9i0uw/K31+H3k5lqnzy3qAkrd+yNxnv9U+yLi/5ynx23YmD3uv7RfmfWYE7KasR3Ny4NoLwZ/wRne+j+ff97GD3pKGqM7oTAes/+XvRPDQ+l36cAOfS5DPebc9vglJ8ZOLf5LUxZuFX0CUUfrmApPHjX1Viz/nK00b2kCjitCAB/NW0Wlou+zTmlH1f1Ydx9ZAG+vsP7Es1Qrizqk9t+tO67SfsUTu2JpD9aq++TuE7aZxDz6p3aQXXZg8Bni3L31UL6RknZK27xHHIucNkH+/6IQ1AloI8kr8ek/Wmr9lwWPDP8m6tnSWmzcECMlpyMLQ0boPDMTSg2TjeizPv9PYswed5X5vtYtfTXVco1jIqrj1Z/L9eeRcQdr/SBetz/L5bPXIwf1D6l4flOnMP2GcKyD17WZSMX+1+LcFDlHXxX/E6069oEFS8TD51752PslD9RZXB3PKSsOXLkE0wZuwn5n+2L1teJB7F/1mDu6JVI6zAMbWULnsg6CSLCmrLgJKp37ow61yjHWIf5Y5fggK8BsQuqZODAnP6YdPp+dGn3IErlzkDahikY8VEm7u7fFXeLwIcSWR2f7xm80rSicsEigDIOK06fw2X1x2gP0upQ5v8hz4D+aHKVuRAO/zodJRr1QIcaVyOvKECbJw3B/FJdMLbxDeJ4p7HttQF4u1h7DH2skojMn8AvU4ZgxjUdPZ8bC4xyfM20Y/dmKC+u99+f5mLy7D9wfb9+aFxYfD/gZnROn5IHU0evwb+Ne6Ozco1pJ8RDQwKKXXVF4LH2L8SEKT/j6ucGoFUJ2bho5do+xu7iV6Fq086oXzYv4tTpWafxx69HULB0aeRT4g475mDkrJOoMaoL7onTrrfvon3Il9wOvesniu+cwx/zhmDk8Qcw4tm7tbU6Nr6GgR/F4/5enVC7oDj3oSWY9uoa/HBDM09QxUU61YpZb6edZ8LWc/5zZ+zByjET8VXNQRh0rzJcW1+5KgEUEWBr8jK6VfEEUHa9jWGzz+L+oe1QI4BEy9f51z2PoQ3LiEfIDKSn/oWTRa5BYeWnapk9h3u86THcF4EP2FraJqY3wAtP3Sl+L97eLBiBIUfu8fhon0/483bPfQZxrqM4Xayo6OJIGodf52PEzCNI9pRviPw+fAq4prAnyKUvck73p7ExkDQOSlqGrz+H4k16aeVL3APbp43AbF8Zd0qfkoaJWJdZCEXqdcBTtxZCLum0P1lDmCru11H4uHxn7c2X8dzrXkGvL0vi2b7N1CBa5r+H8de5oqLsK5kkO57s36zKvbGjnIoDu+JQrHxRcZ9n4Pyq8ej3TRk851nbyTao4smHvG264MmKIv2et+krK3nLF9SHutHbMnFZ2Tro0KymKCcZ4t4zBj6V6x+HL6p63gQqDdpb4zHjl1yo9Pwgbe2rgDzUyvzmut7O+Dmc/eMEzl6rlC3APELRJq+O7MYv8dehYmFRR3vqwQXXK9NElbCPkk8jsOCqRujbujaK5jmHf1NFMLBYYXH/W+fr8uva4Lkm1bR7QrzRHLWjoi8vlXT0/CwVxQskoUHHeqiYOxPnE3Ihl0UHRvbdM4agSvrBHTh09Q0orbRlaT/h45HT8bMvoBrsSBUXdZZVGozNgkN9ovjalT2lPho89zDKdeyJ5mUvR4K4D46evwZFCmj2H6Ulou7z7XCvkndObbSLsgrHkSpOo0sd6lerfpbjebUfKi9Oev2ajFFd7pWuFSUbmSu//w4ZHu6d20J/UMX+3nPVlbQJqtjXyc5tlPH8ZhOHet2hHZIZu69vjHVGMO6yPpf3wSKYcmdVF8rqCVlQ5T1svjYZT3fx9J3VftNR3JLi6TsHWweodcR5PPBCR9yRuRELRohp6i1HokslrY2wr9ts6mdZGdPXsWoAZR0u6zcAjyn9U+VPTAHptjERL5hGn5zGnhmDMRWevg6O4uc3RmNGweZ4ucXNvhex+qRb3YuBQZVg+31OfRLz3efcNjjkp+I48WcU6+J9FtqIha+9gw257vD1EQLPelq0v4MwPdcjvn7hiY8nYPSXf6Bgswme6d76cuVQn1j03eR9Crv2xK4/KuszuGgH1b675NnisGzmgsV3vzOspWnbHwkiqBJMfzrIPok+wK72o22fJeUtwnExhXno8QZ4udW/WCACU9KgivJTaVsheZ4VfflizfqiW5Loh/6zErNGfIJf8t2Ah7oq/YMEpK+fhCGf5Pe/fHZ6hrDtg7tq5WL+SxEOqryHgy31b/H3YvXQSfixyVhRmWsPAinpLTwBC80mMIhh8DJl/Glsmdgf71xvmHokKu2umyp7ouM2HTQxj3DWS2uRu6c+Yq4dc0lVz4O1Utl8VQ4vKJF28f2ZKTtQ8cETeO/P/8Orj4vhK6KxGrDoMjQf1ApVDQvJKukb9HPVwDde4i1Y1w3lPddmvnmV3wzYl4whYh6/eeSAkhajqXa9Cyr01d7eBzRozulT1isYeroBJogFX72jh3zqnmP16lISa15ehEONXkSv2yQP3+oPtKDF7obDMLCW1Xe839O9qRHn6LMoHnVGddaCLMqfeDsxatop3KuOCpHnsVJORqQ30YIqbvJRvb738McT/lFHEEGR4dOP4b+ju+IBz7kDH24D80f57AWxOK7Xyrqsatf8XqluGNRYGcaq/8sQjWFPvF91uBjZJAJX6p9+tNMV6n3h6xSoQbv1KDC0l2dklPi6OlTvZ5QaJkZLXZDlsfd8ksZBDQQdQ40+XXC/EqCy+XO8P10GVWzvAaf0XaalYWn5jnhZBB5NZdR3/ZK0ivpi9Bv/ok7KE+Le9Pzp71dRT3RfL4IqvVqIAKURIpigiqzcB/eQbRdUkd6jaj6m4UHPyCnl94O3lEPrga1xk1W2KuV9xnEkewOaSpLVsrQR+b11YECeKiP1ZmBbnQHoXkM0ogYi+UOOm7zS6n5fGZddl12+Sr+vXevux7S2RQ3WLjyL5JTeaOi9zZRjWgRVZN91Gj0UmP7g8ttVnWWVhiDrE9MtHtCOWrSh6o+0e2D5Tfr2NUME/rvjvYrewHPg0d2U1UgEVazrV5sKzU1Q5Yz5gdN4RKsHOfP95zSM3C54ZH/v2Vbc3g9tgir2/RLnNsrRxKleP2DfDrkPqsjqm3DcjSnT55Fduy5vP8ztlvugil3fOfBsbvLL87B7oS6ezPgEb17eEmNE/9WqPQ3wt6ufnYIq4gWC0t+ZVcIbQA/s65jKsQi475w9BjN2X0CBuFzIW6cTut1V0tCH8v/KXVAlyH6fU9lVR6jb/5nbBvtnIVm9mSbWwei7qbx8Uw1pn3cLlvSfiV2PykaqONQnFkEVxz6FwqAvA9Lrsskv1313SR/LMhAg+a6s3ddloV2/35TT+mMF0Z8Otk9iDKrY19mS8ihehL8y8zjuGqSMRtNG8IQbVHlp5826EdBafTivTA+MFi+PtT9zIMb2Gd+2D+50l2WPzyMcVDEOcwxs7JSKZ+Ye8xPAicTH5Lu6mG4ii8Yz4Hs2HRc3c47Vh47duGGMePD+UgRrtidhXMMjGO95WCstHg5ePN1IC7BICpRph5qAm1t78/GWeGs/UoyEyeUZqfJ6oTYW87nlHXelQh58thGmPCUmpuiP7yJ98vVwPIVVHKvH58AtCb/iu6KPYfTTNSwbN8udiUQjue+zeVj8zR84GadELs4j7VQ+VOghezPuOW/AdcvzOKASdJFO6fVJHrptK9cjS/Ha6D0or4y0yrMZi178AP90HC4fVZW6CvOmLsP2uOJIvPth1Ktxo3gDr6RPS49skWdtgedSgQ+c4hrHjf8Sqaqd/q8QqiiGF+zWGZLZiRW935+EqZuPiVEN1XF/vbq4rUQ+y7dAtveny6CK7T3glL5rnTrIXhPJ99SHUtmijdqCjfeJYac/zHgVC/fGo2DV2nj4odraSAr1L5igimyXM8O9mnYQWxbMw6e7TyBNycoLaThzprRv4TC7B3g3a1Y5BQDUJEk7FvajAtJ2zMcbszfhQMGySHrgYdS52TPiTBzOKqgi3S3r0Bosfnc1tp9M13jPncGh6z0jzWw7PPJ8le3gFnA9Vse0CKrIjmccMfbvT8vw/kcbsO+sdi9mnD2Ns8neh4Uggypu6iyHjqC+nNrVJ7Ate3b3l/wzuzbDTVkNP6giUm5Zv9p0tJyCKhl7sW7sa1hR6TkMelgZYSj/c36Qs6iTgmwL7e49m1T6P3JTxrzfDihrzm2U8fwmE8d63b4dCiaoYq5vDOU2SPfAtBnua9flzuq+chtUse87B16jy/xSA4ZzsTH+JjyWok370f6UEc82dZtdPeQYVBGH3zIdA5YWQKuBLXCjvg9l2iEzA6fWTsKE/6Xj+voP4JY9K/HB5r/FqPDn8fwd/iUD9Gl3vhcl3k79Pseyayz9Dn7SXTvNz0KmdSmDdTf1WQLTblufWARVpDts2rUnDnWsrJ6QrZMZ2PZatK0uRlf4csqYPrv+iNNCtQHHct+fttxExEWfRNq/sysfoi1bM3omdjyWIjZ1UUajRSaoYiwPSn6+X1VZ+sL75iowrxyf8W374K5auZj/UpYHVcwL3AbTKcqCoIp6g03EtsYv48G13hEGB8SK5+/iSMeuSBRTSNbc4x2NY47S2QdVRFpPfosFY+diS0Z+XCYCDhnX1kZr35oeRgvroMrwC49pgZ0IB1X6LvwdhWtVRdEvt+J4y5fQ/Wb9a1/99cmuzT8UUJuupHzf/iFOPWIWBlVGzQFaWC6sah5GrATBFlUeiEFFPkD/ZYUDFmU1l9xzOLlzDb74cDW+PlkYtTr1Rj0XQQI3ASPfuWwbMesHpsx/9+Hnz5bik69/xd/VnsSAljfDuC2ybcBNuYAIBVXsF58OL6jiZvv0C3//hO+WL8Fn244js+5zGFhbWfgmkkEV7/DpRz1DdY1l3DByw1CQ3DyoRiuoovW5z+Cv75fh0xUbsDWzKpr3FOsQiQ6x66CKZ4rhmab9tGGj4pAB15sdgiqeKTJlO/fRpqqKv7BGqrh54A0iqGK97btT2cumQRU1B2T1azD9B913RSd048TXsaRYM/Rp5V0nR34s5wc57+/0tiG2hRb3nquepJsy5j2QJKhiXabMZ3f7sGT8pVU7FLmgSojuvguV9WvclLusD6o45tcJMap1xDLsifsP7hjQE3W9Db5T3Rbsw73p+9rUkx1Nx+KZvWJq3aH75COj1YDLLpR7SXdt6rTzX1G2Xx809C4gpitEzveiPKhi2+9zCr4aC7GTX4wEVezactkDv7xP4dCeZIegilN/JKigilYY3PSnsy6okoFjS4ZjdHozDFVf1it/0QuqfJik3wjDHFRx84wv74O7auVi/ktZGlT5a8EADD2iWzvDicd0wxqHFnoO4Hb6jzrMT7wR0C+M5Zlu4pv+Iw6pjAR5Jd8dqLlhGzL6KmunaP826ao7UHXVNiSo66l4C27gwj5OQZW0L15G75+TMELM37YKV/hZrKf/BExXWnWtNmTQRfrcTP9RjlVSLGyWsiwXHujbGbWMT9++m9bF2xXb6QaelEqGpy+88UUMfbCYj0K57hQxbUmd/uMinVYjVYILqojTi7cufVZdg+aFvsTi//QOuCbr4puBfW/2wdSrnxcjUQqro5PmlPCuq2P+VUBjps5JXomMzhbrDNkOt3QRkFA6MqP2o5JkRy3H+zMSQRWn9Dk1cD4+SVrFfNeR0/60nodupBd56w+URTKoIunYiY7YoLfOopZnJxK7oIhx2pl62ZLpP9K3Svo0ytYAMpYf2wd5ZXeGYVh3v9aIug6qSI4ZMH0v2Ok/Sv0w8TBue9mzLpOaRvP0H2lAzcVbIS+ZPk/M+aMNY1+U6J0aE+RIFTd1lqugijba0bo+cSp7ztN/jA9rdsFWN2U1IiNVAu5dff1qs723VYffE1BZXrI1ujXzL/5sVZ87P8h5f6mvQyT1iZu20HcRgfeeU1dJ/TzkoIpTmTKf3WTiWK8bjmFohyIXVAnX3e6+tit3QQRVTG247Jx2bbmb/DohhuqnYOH1ndE1Yx5GHLwTg0SfU+m2OtZtYU3/0fJZWaeoz7GaaHFwOTbW061Lpy8G0vpOSfc4bKqvm7at+43zvRhCUCXIsuvo5yKoovRnR6Q3xbjWt/pHyKlTI8raTP/5Gle8oFurRm0Dp2BbA4uFagNuOUN94nqkikN7Euz0HzftoNTPqn6zuF/16XPqjzj1Oe3aZZv+dFBBFUPeBzdSxXrkmlIEvCPiA4qDi1E/smtQ7j+7oIrjM4RtH9xVKxfzX8rSoIp3kdQT9Z/D87WUeZPKgp47cDChEsoq64Qa/2QZryzA9e5x3Prcc2gQ4kK1E0/eg24d6kgXqlUvQdxEvVcdQ6G8t6Fdj3raKubK2gxLD+KKuCp43DfSIYSRKgfex4SJ6/CHb3qHZGcMn4MWVPEvYCbWSxQL645cnIakgZ7ofsAN71lwyy59YrutCRM3IXfz5/HMrdpCtQf+PotS14oAhmGY287Xh6kLY734TLJv1xF/FskqM8+cOzG9SV2IN+0vbBMLY763Ky8SpQtjeo5mzGexmFHfz/Kibk/vQrXLMXvKZ/imTOBCtfb5GELjKq1ctYe39eevRXVhru0AZfxTFsZLRf6SZVFAeaktFhZdOeY1fH3nQLxUWxRsz5uNkk911hYeFW9cz+3fi8NFE1FajAAwTjvQFqKthic7tEC1gsoimSfw++/HULBsaTG6RFvcbdrJmmjbqYFYEFpZqPYgjuYvjeL5tAe/xeV7eBbMFdciFujakfkflCuqTPkR95tYWGrwpwXReGgb3GpMhieib3l/GhsXka6B757Bfd5FcMXxnBsD75tEq/S5CAyp1y1Jq2cB1A/y1fUsRK0tRrsnNR43lC6mLs73e6GyKHOFkknaAsDD/kjGALGeUVHp8WTnsOp06/9d20Vs832D0KdWIbEQ6A6smjQdq1PL4h4XQRWtntyIhJlq37IAAB68SURBVKe7oW2i9UK1jkEVaLtVfXmzf6Hag+9OwuStmRYL1abi4K4LKHz9Ndoi0+oipctwvM1odK7gWf/q7CN4qcOdnvrAIq/UTnkqqg7ojgZXZuLC7oWYOnMjtpd71DPNU1mhfhyWlWiOHs1rqAvVntufin+uKyW20bTO149KtkX3ptYL1UqDKpIyatXZCSi7opPTY01xtOnXGtVyi4V018/CeLHj3InkHp7FdoMMqoh7T12A2q5udhVU0doiZaFZeX3iXPawaSpSFh1H5We6oZFnodrfTxVAyaJHDQutahWE7Qg2F2U16KCKKc8c6ldZlaz8m6z/EGRARTmMupZWQLm3Gmmmvx+CbQvt7r1UsaPeNCy/sQ361Q4+iORcJzuVKTOw2cShXndoh2TG5n+zahvCcTemTX9fB1PurK5NqYNfxeqqnvXWxNQkZTHWt3673F8Hu3gIN+WAQ58ic+1Y9F5/nbaQd6ZY23DkBHx1zxAxbF+sf+dYt9nUz57AYL7uL+FJ7wYGsnpLWY9w2HL8mvcmz/qDkpvUsyvQOW87J+pIrX97HtUtFuh1vhdD6fc59UkM1+7o5yJIpr4A2oMSnb0L1W7FR6+/iTWZ1gvVqsH0y72jX8/h+MrJmCh2p7u82UTJQrX2bbnShrjqu6mBG7u+jF1/VFZ3umgHrYIqsrJn9V19mXTRH1Gm6FuO/NIfK5j+tFV7LvJ+1JRdKNa1P9qqG7asw7xXPsD3l/vz3lWdbdXuqf/uMFLFhWUoQRWnZ3zbPviudzBW3Pv3PPeEOjI6u/5lbVBFUdr7Kd5653NtO1/xmJf7qmK4pVUfNHG7+4/41bnN72LmR5vV7SDN2zY7TDcRjdquD6bj/e+V7WgTJNv5imsUDcKbL32IHbV7eTrQ4t/UCOs7+Pa/z+oW2g0yqHJkBaaN24gr2vdSd11QhmmdP/UzVk+cqtuBRl+Uvsb8F35EuacKYft8t1sqO6dPvwWmslVo5n+fxOgmVczTO058hfmjF+C3Op7GOKCUWzxU7F+GmW+u8m2ZXbZla9zy6SzseHywZLcRzwFNnV8RRFjyhm7b4xpoX+0IXt5xEyYpI1WUP8d8DKVxlXeM/pjXV+xOVMe/O5Hpbj+C3XOmYu4vyjba4kFe3e7uUTz7WJK2+4+hzEKY5xVbeddt9zTEeqDmQERA2sSW07nzocCNDdH+iepagC9gSzqILZXL4o5e3VBPvIbK2PUeXp+1AfvFVst5HuiJoTd8iynz1uGgukWustVzKdzeujMae6Y0mJJid3+aGolUbJ02Ae/vPoOzuSqh0cj26pbKTqO1AvPOmD63QRVJWh8UCzeLgNa3s+bhI3WrXiBX3qtw+V2t8OL/3YB/N83A9MU/q1uxi0/UrbobdngC1ZXAlcJqtBPHM/+bbItMbyPmH7l1fsubeO09ZbtEbQvt5LZ3I2PyOhQYqW1x5zh9R5cPVlsqOwdVxIlS12HBzCW+7e9KNaqPKp9/iP1tZFsq78b6cbOxIvWUaqdsOV3k7ifR9UHP4stH/od5kz/CVlHvnq76BCa1VrZUlnVGTmDv2+Mxa/sxz/bH96LLXYcxamNFjBcBWvVP3frau0VyPOIL3o6mL7ZUA32yfAjMV8k245YBCXMZVbZUdlxTRTx8fzNZbOl94Iy6NbeylWCXq1dgzLlWIQZVXNRZboMqDvWJU9nzbvE+SwSJlHtBqa+K1u2D3nedCT6oYmjTpVswOw6vN9bVxjx7FMXmTLapX021mPYPFus/yNdd8qxZpeyIZfwzlXttS2Xz/Weou4JqC+3uvd1iwf8p+CixLV5pJtppq7+QR6o4t1FuTGzr9V+X2LdDEmO4rm/CcTemTF8Wndp1/W9t2i1DOTDVwaEEVezqgAQx7WfYWiR00wU+xIPlSBHovkl5GXe5U91mVz+fxuFFEzHlm1ScRTEk9XgBTXVbKvu78SewefyLmF+6q8XOlpqd0hd9a+G32PdPGtLUNrkMajVvj4es+ieO92Io/T5j3Szpc+mzOqS2wVg+9Ftii/OJ/mCTekWwRuxE2tRqS2W1zZyPVeqWyvlRPLkl7v1zOj6/Rb77j21bLl5Aueq7iXQ7tic2/VHzPaxsqez0jGL1wkJS9gzbAPuyyfCC2L4/4tDn1B/LqR7TlxPL9jwDf382AdNW7/c9gxrzPupBFfFy1nQfS7ZUlq2pYjdSRU2+zTOEbR9cbOoyYGk6kvv2Up9lsutfSEGV7JrYi33dJ8V2V33+fMC0KK/jWhYX+8Iv6fNrw1E31tHvanVJgzDxFKAABShAAQpQQC4gneZBLApQgAI5W4BBlazMX7GGw8CF6bi/l2dai3jboAyNf3X6NlxptYZGVl4fz2UQ0KbLpKwqghYDWqGK/Y7E1KMABShAAQpQgAKXsIA2tXZoam0M9qzjcgljMOkUoMAlJMCgSpZmtjat5e2NB3EyPg/i0jOQUKQMbmvwOOqqa23wL2YExNA9ZZi4MnWjZtuuaFBSmyLCPwpQgAIUoAAFKECBQAFl2sLw9SfFdJZqaNKlDZKkmxxQjQIUoEDOFGBQJWfmK1NFAQpQgAIUoAAFKEABClCAAhSgQJQFGFSJMjAPTwEKUIACFKAABShAAQpQgAIUoEDOFGBQJWfmK1NFAQpQgAIUoAAFKEABClCAAhSgQJQFGFSJMjAPTwEKUIACFKAABShAAQpQgAIUoEDOFGBQJWfmK1NFAQpQgAIUoAAFKEABClCAAhSgQJQFGFSJMjAPTwEKUIACFKAABShAAQpQgAIUoEDOFGBQJWfmK1NFAQpQgAIUoAAFKEABClCAAhSgQJQFGFSJMjAPTwEKUIACFKAABShAAQpQgAIUoEDOFGBQJWfmK1NFAQpQgAIUoAAFKEABClCAAhSgQJQFGFSJMjAPTwEKUIACFKAABShAAQpQgAIUoEDOFGBQJWfmK1NFAQpQgAIUoAAFKEABClCAAhSgQJQFGFSJMjAPTwEKUIACFKAABShAAQpQgAIUoEDOFGBQJWfmK1NFAQpQgAIUoAAFKEABClCAAhSgQJQFGFSJMjAPTwEKUIACFKAABShAAQpQgAIUoEDOFGBQJWfmK1NFAQpQgAIUoAAFKEABClCAAhSgQJQFGFSJMjAPTwEKUIACFKAABShAAQpQgAIUoEDOFHAdVElPT8uZAkwVBShAAQpQgAIUoAAFKEABClCAAhQIQYBBlRDQ+BMKUIACFKAABShAAQpQgAIUoAAFKMCgCssABShAAQpQgAIUoAAFKEABClCAAhQIQYBBlRDQ+BMKUIACFKAABShAAQpQgAIUoAAFKMCgCssABShAAQpQgAIUoAAFKEABClCAAhQIQSBqQZVDPUajzMqKWLP9EdTMvGC6tOX1BqDh5wn+f589BGktQkiB5Cdx+BbN8izF4jlDI3bMYK4s95YPUSFpN0p93xufVjanXbWZfMp/yB7tkDayVDCnsP2uapunAdIWV4/YMXkgClCAAhSgAAUoQAEKUIACFKAABQIFLlpQxXsZ0QiAROOYwRQcp6CKP+0HMTzxdaQ07sCgSjDA/C4FKEABClCAAhSgAAUoQAEKUCAGBBhUiUImMKgSBVQekgIUoAAFKEABClCAAhSgAAUoEGMCEQ2qKMGE6x6Pw9wfH0Hp7qPU6T8LH9qJR189oSVbMs3FblRJwBShuIK4d1PgdBrlfIlJm7AzzqPq+c6Kyt+Ypv+ox/qiHPqmtcPQCxm22aBOz/ntRqT89A1S9l2P/mk345dci7E4MQlrt5fA+NxLTFOL4uAfdZLZfLM6/afW7ER82Wajdn0VbjdNhdL/xjj9xzRFyDA9yucW5028OIfnO8bpP7nffANxHQ+on2dW8ueRbFpWjJVPXg4FKEABClCAAhSgAAUoQAEKUCBmBSISVPEFNxL9gQNfUMATSLEavWEVVDGuyWL8ve+cPc3rkeiPmd4i+Ck26rmnJOC+TS1wV+MpvsDKz7lW4cT3fTBrphYw0q8XowYuOiWoQZtR3y/Sgj0ej+TM/dJpPlZBFf2xlACQ0cj3//XqS9dN0QdVZGvbyPIrZksoL4wCFKAABShAAQpQgAIUoAAFKBCjAmEFVXwP9/FlTSNAjA/zVgEEWVBF9l3jv9kthOs75uwOSBks1ixJGRbUgrXaSJXaasBCDVC0Go70Ft+iaZ41alDFciRMtY7q2iiyAJLseq1MZAvN6v/NGHQxli3vd/eWXeNLh6z8+Uaw1K3HRW1j9AblZVGAAhSgAAUoQAEKUIACFKBA7AqEFFTxB1OuMk3J8SY1vKCKefceXwCi0sP+YIfFDjcBU2Mk026cssMpqKLs6KNPX60fFqN80t9ocl6bWhROUMU20LK/ujo6xju1ynFnJcmUKVnafaOKGFxxKhr8nAIUoAAFKEABClCAAhSgAAUo4BMIKaji/XVwI1Xk2xxHdaSK2FL5w7nBby/sJqiiXLd35Eq3Pv3R0DNKRbGRBVVko0+iPVIls8FW35Qk2ToyHKnCmoACFKAABShAAQpQgAIUoAAFKBC6QFhBFe9pLddUEeuSeBeX1dYpudo0TSjsNVXqmaeuSNdU8YxwcUPlJqiiHEcLlNyAR5ZlItEzSsUbVFHXVPGs9+LzmTMkYBpS2GuqiIVzZaNVTGuqGNy5poqbUsDvUIACFKAABShAAQpQgAIUoAAF7AUiElTRB1cCdv/x7qCzNx6wmIoS0d1/lAsRO9wo6580y7PUt0OP3YgaGY/boIrVYrnKvyvTgRp2P4ZxE45rp5DufGS9iG5Iu/94zmEcFePbRYm7/7A+oAAFKEABClCAAhSgAAUoQAEKREwgokGViF1VNjmQ1Y5G2eTyeZkUoAAFKEABClCAAhSgAAUoQAEKhCHAoEqIeMaFc0M8DH9GAQpQgAIUoAAFKEABClCAAhSgQDYVYFAlyIzzBVOUKU0h7CwU5On4dQpQgAIUoAAFKEABClCAAhSgAAViVIBBlRjNGF4WBShAAQpQgAIUoAAFKEABClCAArEtwKBKbOcPr44CFKAABShAAQpQgAIUoAAFKECBGBVgUCVGM4aXRQEKUIACFKAABShAAQpQgAIUoEBsCzCoEtv5w6ujAAUoQAEKUIACFKAABShAAQpQIEYFGFSJ0YzhZVGAAhSgAAUoQAEKUIACFKAABSgQ2wIMqsR2/vDqKEABClCAAhSgAAUoQAEKUIACFIhRAQZVYjRjeFkUoAAFKEABClCAAhSgAAUoQAEKxLZARIMqud98A3FLqyFtcfUsS3XuLR8iMWkTds4ZgrQW7k4bh2/RLM9SLI6L034QVwZ909ph6IUMdwdw+S3Vo+MB/7fr1stSG5eXma2+5stvT9ahwu1Ys/0R1My8cFHScajHaJSZkoB7N/XGp5UvzjVEI+HL6w1Aw/3Vg7JVLSaf8l9Oj3ZIG1kqGpeXrY+ZHWyVOrJpnjU48X2fgHIdSn2brTMrCy8+FFuntsz3eb360rbH9PuLXJ9mITdPRQEKUIACFKAABSImELGgShwOYljiCpzd1T7iwQm71IbSEdUfTw18dEqIXlDlleLSB1PFa3ji60jJ89+gHly91273e1MwJ4d2lNWH+JUVQ/IL9w4KN//CPX+0fx/Kg7+pbDbuwKCKJKOygy2DKtG+w8zHj2Zbppa5L8rZtnPK+a97PA5zf7x4QeqsV+cZKUABClCAAhSgQPgCEQuqhDJKRe3o5WlwUUdvZHVQxfdmMP4qPPQQ8Ome8kEFBdz8PvebX6Hf03epwS3fw3+lhy+qc/hF1XyEixlUsTt3NMu1L//nDJWOzHL6PBr5YDymr8xFIahCW08wNgq2+ny0CqqEWn4udrlUAgYVknaj1PfRGVF2Mesib544tWVO9w6DKqGWbv6OAhSgAAUoQIFLXSAiQRXtIepdrF0UOFTcCtc0TcD7Rd30GG8HcG/ZNf4pBbrpBAHHiCtomn5hGq0RJ5/iY9URNV1jCKM91GNbjFRRkhxuR9zt791+z5sNUnudn92Qcd9nszsgZbAYibM3XkyvMudPYP7588b78FNrdiK+bLMRO5VpPhb2snT5HuiV83r/DNNQTNevfG+2f/qY6XPJ72VTI9yUa+VUpilMunNbldthF/ZpI5v06fKmT/w+vYXnYdvic2VqnNe2zPd3I/8tS7Tpb3b5Kpmu5ua+iEZQhbZaZkfD1luMAox7JOGRcTt8039CrW+dyq1SLt3UGW7KnVpvfZ7gv+9F+U1fHB841dP7qaFOMh1fd09665mdvf9ChXb7tCN47g3T/eo9vq7OuthtmS/JFlO6vJ8zqGLVY+G/U4ACFKAABShAAXuBiARVQhmlolyW3ZszXwfZ80CrdmzztjBNJ7Aepr4Pa28uq6614eu092xv+r0sqBKpt5qxEFQJ5SHMZ+95cNAfI31knPZwr3tTrg9uJGd+oz3EiJE4yjojKyrvNwXctHVIrvYNRdeXA1/AIVFbKyU5U/l94PkCHgIN03+Ua92+rSQqV9W+ZTyX6zUGPGVFVhac8tWuXBuH+OvL37ALGzQ7i1Eo2kO1Zz2gEEaq+M4drwWxlPM1zbMNiefN6wmpbr/VNo1u+nHbAWGrrZNiNV0hlDLntqKmbXRGqhjrQau1gmT1rVOZdCq3+tF3VnWGU7lzmt5iV6cb025Mjy/gog+kGNYOcxy5pgR7LkJbpr+vnO5LBlXc1kL8HgUoQAEKUIACFAgUCDuoEuwoFf3pHYMqLqYGuRmmbteZlAVVnB68TW9EvYkyvP10evgOdgSJsfC6+b3xO6ZREvqDeh4aZPni/bfMlMOmYfT6B5YVlT1BFcuHfvNDoT4PRn2/yHR8q3S6Sb8xf52GyJsfsMzX63Reu3Jt/K3+Ac432sRmnR2nB1i7z4MJFloFVQIf0uQBHqeHt3AqYdpGJ6iiulbr6As6W9Wr8qCK8/pQduXSqUwby4vx+25+b1f27eo7ZdF1p/vdF7y1WN/JadqNr/lwGEmiBaes89+pblN+7xSU5Joq4dRO/C0FKEABClCAApeqQNhBlVBHqTh18MLtiLqZBqJcg11HNGBot244uNvCEmpQRRr4iDNPX3Lq7Ls1NKbHNqjSYKtpYV/9iIX0Fi5HUnh3XvI9UWjpi0RQxW7ql5OZ5TQT49QzmwVyHYOF+ikK3vTrpwB5d7RSpj5ZTV0KcaSK23UlrIIqTlOnnB783N47Vt+jbeSDKrIH9WCCKt68Cqi3gii3boIiduXOTbDQ6jtWQQr9YsKlu49yXBDbcaRKGC8IItGWefOIQZVwayD+ngIUoAAFKEABCpgFwgqqhDNKJZpBFePirOG+3dMCLyd867Zkh5EqVg/FsThSRV8sZQ8/+gcc/dbJsgcZY16FO1JFVmk4BcuCGU1hVynJptc4PYBGc6SKcRqd1bliZaQKbd01eZEKqpiCK7pt7sMZqeJU7pzuCTV4brNQbSyPVIlkW+Z0X3L6j7v7hd+iAAUoQAEKUIACRoGwgirhjFJRLsRuioHbURZu5vgHvaaKbvccpw657YPbRVqo1s0wcLvrtnvISF9cwt2aKjbrghjXOTEGVRKTNmFnz3bqVAS7bUZlQRXjv1muqZKYZLHVtWekjWT9He91Ok05syvXdunJvWUDJibUxLNVMtVTyR4WfQ9GKcMsdv/xjGSQfO7mjb43jbI0GH8f6poqvtFAIYz+oq39SJVQbfX3jW8do32FTAuAy8p+uOXWKSjiptxpa6oUNl2vm3vW1ZoqDlu32wVaL2Zbpq9bneotBlXYQaQABShAAQpQgAKhCYQcVAl3lErAQ6N3KohkxwRlTrvdn1VHMWAKSFwZvDUjDq2f/s23a4P3mNKFapVgSMcDgacN4QFQ1tGWDmP3nsnFOdz8XjqSRrKTi5Wr05tb0zXo8s3pASngoX3yKf8liDzST/8pV1dsN738uPa5YSpBwDEkC9UG7JLToz5SFi1Fiu4BUWqoO4fT58r57Yb72/kov5WOFhJ5n1npQ6gBJWXaj/dPknbT9CbDd6w+Dzeo4ku3N99Evi98aCceffVEQB45vREP9cHfqc6gradcKvnjoi7R3/8BU0zE2lAPbLobV9yy2rf7j/e78qBKeOXWTZ0RMC3PotyZ6j3DrmGmqX3GHX709ZFk9x9l4Wz9SDlLP7Wg+qdrhhNUUcu0vj0Sxw2mLdNfo9N1MKhi1SLy3ylAAQpQgAIUoIC9QMhBlXBHqVwKGeM0TeRSMAg2jcE8+Ad77Eh+3/cQarOobCTPl5OOFYmAbE7yiGRaaBtJzZxzLKfdkdTgjZgixYVqc06eMyUUoAAFKEABCmSdQEhBFXbc3WWQacRAEKNF3J0h530ruwRVvPLa9KIEy2kHOS+Hwk+Rm52Fwj/LpXkE2l6a+W6Vat8ooHr1TdujK79xGlVHTQpQgAIUoAAFKEABZ4GQgirOh+U3KBCaQHYLqoSWSv6KAhSgAAUoQAEKUIACFKAABXKCAIMqOSEXmQYKUIACFKAABShAAQpQgAIUoAAFslyAQZUsJ+cJKUABClCAAhSgAAUoQAEKUIACFMgJAgyq5IRcZBooQAEKUIACFKAABShAAQpQgAIUyHIBBlWynJwnpAAFKEABClCAAhSgAAUoQAEKUCAnCDCokhNykWmgAAUoQAEKUIACFKAABShAAQpQIMsFGFTJcnKekAIUoAAFKEABClCAAhSgAAUoQIGcIMCgSk7IRaaBAhSgAAUoQAEKUIACFKAABShAgSwXyNKgSu4330Dc0mpIW1wdy+sNQMM8DdT/lv2pn3+e4P9o9hCktYiMTxy+RbM8S7F4ztCIHTMyV8ajUIACFKAABShAAQpQgAIUoAAFKJBdBLIsqBKHgxiWuAJnd7XH0AsZjkEVL2A0AiDROGZ2yXBeJwUoQAEKUIACFKAABShAAQpQgAKREciyoIp+lIpy6U4jVRhUiUwG8ygUoAAFKEABClCAAhSgAAUoQAEKREcgokGV3Fs+xHWPx2Huj4+gZuYF3xUro1SGJ76LtYv64NPK2r97gyofpi31T/ORTPGxG1USMEUoriDu3dTbd3zlHId6jEaZyaf8chVux5rtjyA58xvT9B/1WF+UQ9+0dkiu0w8NWw3n1KDolDkelQIUoAAFKEABClCAAhSgAAUokCMEIhJUUYIpiUmbsDNRC1roAyqKknGUii+ooqyZ4gmkqN/plKAGNZTpQd4/q6CKGjBZWdF3PuUaKiTtRqnvtcCK+vmUBFOgRTmu/pjpLZSAz+tIadwBaSNL+c7rC9hEcC2XHFFimAgKUIACFKAABShAAQpQgAIUoAAFVIGwgiq+4ER8WVMwxB8UMY9S8QVVdAvVWgVPZP+ujXwJDITo/y19ZJw0UGIK1MzugJTB4jgpw6SjUnzH3FdIGpxhGaIABShAAQpQgAIUoAAFKEABClDg0hUIKajiD6Zc5RhskI1SCT+oYt69xxcAqfQw0hfH2+7u47v+uDjAMyXIOLpGXySCSe+lW5SYcgpQgAIUoAAFKEABClCAAhSgwKUlEFJQxUvkNFJFtpaK97fGhWqN03dM59BtfxyxkSrimB/Otd7amSNVLq2bgamlAAUoQAEKUIACFKAABShAAQoEIxBWUMV7Iqs1VaxGqSi/0y8M69tieX9105osYa2poixS67D4rW9NFTHCJW1xdZ8d11QJphjxuxSgAAUoQAEKUIACFKAABShAgUtPICJBFX1wxbv7T3LmftOOP3peNWhRrQYajduIxco0nLgy0nVZIrr7j+ccwy5sCJgeZBxxw91/Lr0bgSmmAAUoQAEKUIACFKAABShAAQoEKxDRoIr+5HajVIK9SH6fAhSgAAUoQAEKUIACFKAABShAAQrEmkBUgip2a6nEGgCvhwIUoAAFKEABClCAAhSgAAUoQAEKhCIQlaBKKBfC31CAAhSgAAUoQAEKUIACFKAABShAgewkwKBKdsotXisFKEABClCAAhSgAAUoQAEKUIACMSPAoErMZAUvhAIUoAAFKEABClCAAhSgAAUoQIHsJMCgSnbKLV4rBShAAQpQgAIUoAAFKEABClCAAjEjwKBKzGQFL4QCFKAABShAAQpQgAIUoAAFKECB7CTAoEp2yi1eKwUoQAEKUIACFKAABShAAQpQgAIxI+A6qBIzV8wLoQAFKEABClCAAhSgAAUoQAEKUIACMSDAoEoMZAIvgQIUoAAFKEABClCAAhSgAAUoQIHsJ8CgSvbLM14xBShAAQpQgAIUoAAFKEABClCAAjEgwKBKDGQCL4ECFKAABShAAQpQgAIUoAAFKECB7CfAoEr2yzNeMQUoQAEKUIACFKAABShAAQpQgAIxIMCgSgxkAi+BAhSgAAUoQAEKUIACFKAABShAgewnwKBK9sszXjEFKEABClCAAhSgAAUoQAEKUIACMSDAoEoMZAIvgQIUoAAFKEABClCAAhSgAAUoQIHsJ8CgSvbLM14xBShAAQpQgAIUoAAFKEABClCAAjEg8P/4i3SyJnlN0QAAAABJRU5ErkJggg==) Hi Dave, I've been testing the above that you recommended, but not getting the desired result. For example, with the following code, I would like TrialA's to be presented 12 times (e.g., TrialA1 and TrialA2 in the 3/4 ratio, so that TrialA1 is shown 9 times and TrialA2 is shown 3 times), Trial B's 12 times (with the respective 3/4 ratio), TrialC's 12 times (with the respective 1/2 ratio), and Trial D's 12 times (with the respective 1/2 ratio). / trials = [1-48 = noreplace(TrialA1, TrialA1, TrialA1, TrailA2, TrialB1, TrialB1, TrialB1, TrialB2, TrialC1, TrialC2, TrialD1, TrialD2)] How is this possible? Thanks! You have 12 entries in the pool. 48/12 = 4, .i.e. each entry stands for 4 trials. You'll get 3 x 4 = 12 TrialA1, 1 x 4 = 4 = TrialA2, 3 x 4 = 12 TrialB1, 1 x 4 = TrialB2, 4 x TrialC1, 4 x TrialC2, 4 x TrialD1, and 4 x TrialD2. If you want something else, adjust accordingly. Thanks Dave
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