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CSF2_HUMAN netOGlyc-4. CARBOHYD 119 119 0. . CSF2_HUMAN netOGlyc-4. CARBOHYD 122 122 0. . Article abstract. REFERENCE Precision mapping

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34 7 17 0 1 6 1 214 16.4 712 75 30 52 32 18:48 11 Chandler Stephenson C. Stephenson 58.1 1,162 2022-23 VGK 81 16 49 65 +12 26 6 9 1 2 5 0 120 13.3 675 74 56 64 30 19:01 12 Paul Stastny P. Stastny 57.6 486 2022-23 CAR 73 9 13 22 +4 16 2 2 0 0 3 0 80 11.3 280 21 18 20 8 11:52 13 Jean-Gabriel Pageau J. Pageau 57.2 1,256 2022-23 NYI 70 13 27 40 -2 14 5 3 3 1 2 0 123 10.6 719 175 61 33 35 17:37 14 Mark Kastelic M. Kastelic 56.9 590 2022-23 OTT 65 7 4 11 -6 102 0 0 0 0 2 0 73 9.6 336 154 37 19 15 8:54 15 Bo Horvat B. Horvat 56.9 1,685 2022-23 TOT 79 38 32 70 -1 18 12 10 4 1 5 1 229 16.6 958 57 55 38 37 20:39 16 Ross Colton R. Colton 56.1 189 2022-23 TBL 81 16 16 32 -8 50 4 5 0 0 3 0 153 10.5 106 188 28 38 20 12:21 17 Vincent Trocheck V. Trocheck 56.1 1,286 2022-23 NYR 82 22 42 64 +3 58 9 8 0 0 3 0 225 9.8 721 182 44 55 64 19:19 18 Radek Faksa R. Faksa 56.0 552 2022-23 DAL 81 11 9 20 +9 39 0 0 1 1 3 0 88 12.5 309 89 69 26 18 13:43 19 Anze Kopitar A. Kopitar 55.9 1,608 2022-23 LAK 82 28 46 74 +20 4 7 13 0 1 4 0 169 16.6 899 68 87 46 49 20:18 20 Nico Sturm N. Sturm 55.8 880 2022-23 SJS 74 14 12 26 -13 23 0 0 1 0 1 0 119 11.8 491 $94.99 $135.70 SKU: miku-usp-1-984 Sales: 0 Sources Guardians of the Galaxy Vol.3 Size XS, S, M, L, XL, XXL,3XL, Tailor Made Material Twill, leather, thin leather Applicable Gender Male Error Range 1-5cm Includes Jumpsuit*1, (extra option) shoes*2 Men's Size Chart Size Unit Height Chest Waist Hip XS cm 163-167 84-89 69-74 81-86 inch 64-66 33-35 27-29 32-34 S cm 168-172 91-97 76-81 89-94 inch 66-68 36-38 30-32 35-37 M cm 173-177 98-104 84-89 97-102 inch 68-70 39-41 33-35 38-40 L cm 178-182 107-112 91-97 104-109 inch 70-72 42-44 36-38 41-43 XL cm 183-187 114-119 99-104 112-117 inch 72-74 45-47 39-41 44-46 XXL cm 188-192 122-127 107-112 119-124 inch 74-76 48-50 42-44 47-49 XXXL cm 193-197 130-135 114-119 127-132 inch 76-78 51-53 45-47 50-52 Men's Shoes Size Chart Feet Length 240 245 250 255 260 265 270 275 280 285 EUR 38 39 40 41 42 43 44 45 46 47 US 5.5 6.5 7 8 8.5 9.5 10 11 11.5 12 Reviews (0) Info There are no reviews View more Add your review Reviews (0)

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189cm (6'2") / 75kg (165lbs) February 12, 1993 (32 years old) 2012, Samsung Lions, Round: 2, Overall Pick: 12 20억원 ($1,481,000) / 1억3천만원 ($96,000) 본리 Elem ➞ 경복 MS ➞ Daegu HS ➞ Samsung ➞ Sangmu Year Team BA OBP SLG OPS G PA AB R H 2B 3B HR RBI SB CS BB SO TB GDP HBP SH SF IBB E --> RISP PHBA 2024 Samsung .343 .417 .627 1.044 129 568 493 92 169 39 1 33 115 13 4 55 73 309 6 12 2 6 4 1 --> .341 .000 2023 Samsung .336 .407 .494 .901 119 515 453 65 152 37 1 11 71 12 4 53 81 224 5 4 2 3 2 0 --> .395 .000 2022 Samsung .293 .340 .401 .741 99 442 409 69 120 23 3 5 38 11 1 27 84 164 7 3 1 2 2 4 --> .248 .000 2021 Samsung .306 .361 .519 .880 139 610 543 107 166 30 10 22 88 27 4 48 98 282 9 6 1 12 3 3 --> .283 .000 2020 Samsung .307 .385 .478 .863 118 510 446 70 137 27 2 15 78 19 5 51 91 213 4 8 1 4 3 2 --> .336 .000 2019 Samsung .267 .327 .444 .771 122 526 475 66 127 27 6 15 71 11 3 38 88 211 5 7 0 6 2 2 --> .302 .500 2018 Samsung .333 .392 .533 .925 116 529 478 100 159 26 5 20 84 10 0 43 110 255 4 5 1 2 2 4 --> .378 .000 2017 Samsung .310 .383 .527 .910 144 647 564 108 175 39 10 21 107 10 4 63 138 297 1 10 0 10 1 5 --> .352 .000 2016 Samsung .343 .420 .547 .967 108 495 428 105 147 19 13 14 77 10 5 55 68 234 4 5 2 5 1 7 --> .352 .500 2015 Samsung .349 .417 .534 .951 116 465 410 97 143 33 5 11 57 17 7 45 79 219 3 6 0 4 0 13 --> .330 .600 Career .318 .385 .512 .897 1210 5307 4699 879 1495 300 56 167 786 140 37 478 910 2408 48 66 41 --> Compare vs. Other Hitters ». CSF2_HUMAN netOGlyc-4. CARBOHYD 119 119 0. . CSF2_HUMAN netOGlyc-4. CARBOHYD 122 122 0. . Article abstract. REFERENCE Precision mapping

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Correct answer and right logic.Now observe the time between 11 to 12, either it can either be A.M or P.M, the hands are not coinciding between 11’o o’clock and 12’o o’clock. The coinciding of hands at 12’ o clock is the coincidence between 12 and 1 and 11 and 12. Hence, in 12 hours, there will only be 11 coincidence, extending the logic for 24 hours of the day, there will be 22 coincidences.If 12:0:0 A.M is the first coincidence of the hands in a day then the next collision will be at 1’o o’clock 5 minutes, but the evaluation of seconds is difficult, but not impossible.Logical calculation:We know in 12 hours there will be 11 coincidences. Therefore, one collision will happen at:Frequency of one collision = (12 hours)/11Frequency of one collision = (12*60 mins)/11Frequency of one collision = (720 mins)/11Frequency of one collision = 65(5/11)The value 65(5/11) indicates that the hands of a clock coincide after every 65 minutes 5/11 of a minute. i.e. if 12:0:0 is the first collision, then the exact time of the next collision will be obtained by adding 65(5/11) to 12 o’clock.The below table denotes the time at which both the hands of a clock collide:Frequency of collisionTime in mixed fractionExact time1st12:0:012:0:02nd1:5:5/111:5:273rd2:10:10/112:10:544th3:16:16/113:16:215th4:21:9/114:21:166th5:27:3/115:27:367th6:32:8/116:32:438th7:38:2/117:38:109th8:43:7/118:43:3810th9:49:1/119:49:511th10:54:6/1110:54:3212th11:59:11/1112:0:0Q.2 How many times in a day do the minute and hour hands of clock form a 180° straight line in a day?The hands of the clock make one 180° straight line every hour except between 5’o clock and 6’o clock. A precise Expiring Prize Points 0 Expires: 0 My Account Cash4Life® is a multi-state game that costs $2 per play. EZ Match is available as an add-on and costs an additional $1 per play.Cash4Life has a top prize of $1,000 a day for life, as well as a second-tier prize of $1,000 a week for life!Drawings are held daily at approximately 8 p.m. Cash4Life Number Frequencies White-ball numbers Cash Ball Numbers Number # of times drawn % of times drawn # of times drawn % of times drawn 1 124 8.61% 386 26.79% 2 117 8.12% 351 24.36% 3 103 7.15% 366 25.4% 4 97 6.73% 338 23.46% 5 139 9.65% 6 126 8.74% 7 109 7.56% 8 135 9.37% 9 135 9.37% 10 129 8.95% 11 113 7.84% 12 105 7.29% 13 143 9.92% 14 131 9.09% 15 127 8.81% 16 123 8.54% 17 101 7.01% 18 107 7.43% 19 109 7.56% 20 101 7.01% 21 130 9.02% 22 120 8.33% 23 127 8.81% 24 117 8.12% 25 125 8.67% 26 136 9.44% 27 119 8.26% 28 117 8.12% 29 118 8.19% 30 113 7.84% 31 119 8.26% 32 105 7.29% 33 117 8.12% 34 129 8.95% 35 109 7.56% 36 123 8.54% 37 116 8.05% 38 121 8.4% 39 130 9.02% 40 119 8.26% 41 115 7.98% 42 116 8.05% 43 115 7.98% 44 131 9.09% 45 124 8.61% 46 134 9.3% 47 111 7.7% 48 117 8.12% 49 115 7.98% 50 121 8.4% 51 130 9.02% 52 132 9.16% 53 117 8.12% 54 111 7.7% 55 130 9.02% 56 127 8.81% 57 130 9.02% 58 116 8.05% 59 120 8.33% 60 109 7.56% The number frequency information above has been generated using drawing data from Apr. 11, 2021, through Mar. 20, 2025 (1441 draws).

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Equally spaced bins, using 5 bins in each dimension.x = randn(1000,1);y = randn(1000,1);nbins = 5;h = histogram2(x,y,nbins)h = Histogram2 with properties: Data: [1000x2 double] Values: [5x5 double] NumBins: [5 5] XBinEdges: [-4 -2.4000 -0.8000 0.8000 2.4000 4] YBinEdges: [-4 -2.4000 -0.8000 0.8000 2.4000 4] BinWidth: [1.6000 1.6000] Normalization: 'count' FaceColor: 'auto' EdgeColor: [0.1500 0.1500 0.1500] Use GET to show all propertiesFind the resulting bin counts.counts = 5×5 0 2 3 1 0 2 40 124 47 4 1 119 341 109 10 1 32 117 33 1 0 4 8 1 0Adjust Number of Histogram BinsGenerate 1,000 pairs of random numbers and create a bivariate histogram.x = randn(1000,1);y = randn(1000,1);h = histogram2(x,y)h = Histogram2 with properties: Data: [1000x2 double] Values: [15x15 double] NumBins: [15 15] XBinEdges: [-3.5000 -3 -2.5000 -2 -1.5000 -1 -0.5000 0 0.5000 1 1.5000 2 2.5000 3 3.5000 4] YBinEdges: [-3.5000 -3 -2.5000 -2 -1.5000 -1 -0.5000 0 0.5000 1 1.5000 2 2.5000 3 3.5000 4] BinWidth: [0.5000 0.5000] Normalization: 'count' FaceColor: 'auto' EdgeColor: [0.1500 0.1500 0.1500] Use GET to show all propertiesUse the morebins function to coarsely adjust the number of bins in the x dimension.nbins = morebins(h,'x');nbins = morebins(h,'x')Use the fewerbins function to adjust the number of bins in the y dimension.nbins = fewerbins(h,'y');nbins = fewerbins(h,'y')Adjust the number of bins at a fine grain level by explicitly setting the number of bins.Color Histogram Bars by HeightCreate a bivariate histogram using 1,000 normally distributed random numbers with 12 bins in each dimension. Specify FaceColor as 'flat' to color the histogram bars by height.h = histogram2(randn(1000,1),randn(1000,1),[12 12],'FaceColor','flat');colorbarTiled Histogram ViewGenerate random data and plot a bivariate tiled histogram. Display the empty bins by specifying ShowEmptyBins as 'on'.x = 2*randn(1000,1)+2;y = 5*randn(1000,1)+3;h = histogram2(x,y,'DisplayStyle','tile','ShowEmptyBins','on');Specify Bin Edges of HistogramGenerate 1,000 pairs of random numbers and create a bivariate histogram. Specify the bin edges using two vectors, with infinitely wide bins on the boundary of the histogram to capture all outliers that do not satisfy |x|2.x = randn(1000,1);y = randn(1000,1);Xedges = [-Inf -2:0.4:2 Inf];Yedges = [-Inf -2:0.4:2 Inf];h = histogram2(x,y,Xedges,Yedges)h = Histogram2 with properties: Data: [1000x2 double] Values: [12x12 double] NumBins:

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0.187890 GiB/sec, Avg_Latency: 162.422553 usecs ops: 5863720 total_time 119.049917 secsdgx2> gdsio -D /nvme23/gds_dir -d 0 -w 16 -s 1G -i 4K -x 0 -I 2 -k 0308 -T 120IoType: RANDREAD XferType: GPUD Threads: 16 DataSetSize: 48209436/16777216(KiB) IOSize: 4(KiB) Throughput: 0.385008 GiB/sec, Avg_Latency: 158.918796 usecs ops: 12052359 total_time 119.415992 secsdgx2> gdsio -D /nvme23/gds_dir -d 0 -w 32 -s 1G -i 4K -x 0 -I 2 -k 0308 -T 120IoType: RANDREAD XferType: GPUD Threads: 32 DataSetSize: 114100280/33554432(KiB) IOSize: 4(KiB) Throughput: 0.908862 GiB/sec, Avg_Latency: 139.107219 usecs ops: 28525070 total_time 119.726070 secsdgx2> gdsio -D /nvme23/gds_dir -d 0 -w 64 -s 1G -i 4K -x 0 -I 2 -k 0308 -T 120IoType: RANDREAD XferType: GPUD Threads: 64 DataSetSize: 231576720/67108864(KiB) IOSize: 4(KiB) Throughput: 1.848647 GiB/sec, Avg_Latency: 134.554997 usecs ops: 57894180 total_time 119.465109 secsdgx2> gdsio -D /nvme23/gds_dir -d 0 -w 128 -s 1G -i 4K -x 0 -I 2 -k 0308 -T 120IoType: RANDREAD XferType: GPUD Threads: 128 DataSetSize: 406924776/134217728(KiB) IOSize: 4(KiB) Throughput: 3.243165 GiB/sec, Avg_Latency: 151.508258 usecs ops: 101731194 total_time 119.658960 secsWe can compute the IOPS by dividing the ops value by the total time. Note in all cases the totaltime was just over 119 seconds (120 seconds was specified as the run duration on the command line).It is interesting to observe the average latency on each run (Avg_Latency) actually gets better as the numberof threads and IOPS increases, with 134.5us average latency at 484,612 IOPS running 64 threads. Increasingthe thread count to 128, we observe a slight uptick in latency to 151.51us while sustaining 850,240