ANOVA for I optimal design of Axitinib loaded Spanlastics. by Randa Mohammed Zaki (21637175)

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The kinetic release data of the optimized formula compared to drug suspension. by Randa Mohammed Zaki (21637175)

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Open data. by Larissa Brazolotto Ferreira (17671168)

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Impact of 5′ nucleotidase disruption on <i>M</i>. <i>bovis</i> growth phenotype in axenic conditions. by Aga E. Gelgie (17661720)

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General and sociodemographic characteristics of the EBF and EBF+ groups. by Larissa Brazolotto Ferreira (17671168)

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Mapping of transposon insertions in the selected mutants of <i>M</i>. <i>bovis</i> PG45. by Aga E. Gelgie (17661720)

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Effect of ibuprofen (IBU) on COX-2 expression. by Katarina Grossmannova (7543517)

“…P < 0.05 was considered significant. *denotes P < 0.05, ** P < 0.01, *** P < 0.001, and **** P < 0.0001, respectively. …”

MGPC module. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Comparative experiment. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Pruning experiment. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Parameter setting table. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

DTADH module. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Ablation experiment. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Multi scale detection. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Screening for K⁺ channel mutants with altered susceptibility to <i>V. cholerae.</i> by Longjun Pu (20685717)

MFDPN module. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Detection effect of different sizes. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Radar chart comparing indicators. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

MFD-YOLO structure. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Detection results of each category. by Bo Tong (2138632)

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”