Forest plot of subgroup analysis for PHR. by Liu Jiahui (22505165)

“…A non-linear relationship was observed, and the risk was reduced when PHR ranged between 4.51 and 10.18, and increased when PHR was outside this range. Subgroup analysis results revealed significant variations in effects across age, gender, lifestyle, and chronic disease groups. …”

Forest plot of subgroup analysis for PA. by Liu Jiahui (22505165)

“…A non-linear relationship was observed, and the risk was reduced when PHR ranged between 4.51 and 10.18, and increased when PHR was outside this range. Subgroup analysis results revealed significant variations in effects across age, gender, lifestyle, and chronic disease groups. …”

Weighted restricted cubic spline plot. by Liu Jiahui (22505165)

“…A non-linear relationship was observed, and the risk was reduced when PHR ranged between 4.51 and 10.18, and increased when PHR was outside this range. Subgroup analysis results revealed significant variations in effects across age, gender, lifestyle, and chronic disease groups. …”

Overview of enriched pathways in FcRγ−/− subclusters. by Megan M. Dunagan (1338867)

Contralateral foot swelling and viral RNA in tissues of FcRγ−/− mice following MAYV infection. by Megan M. Dunagan (1338867)

Results of the metaGE FE and the mash procedures applied to the Arabidopsis dataset. by Annaïg De Walsche (20542982)

Results of the metaGE FE procedure applied to the Arabidopsis dataset to detect markers with competition contrasted effects. by Annaïg De Walsche (20542982)

Results of the mash procedure applied to the Maize dataset. by Annaïg De Walsche (20542982)

Results of the metaGE RE procedure applied to a simulation run corresponding to the “completely random-effect” QTL type. by Annaïg De Walsche (20542982)

A representative video cropped from S1 Video shows pillar displacement as an <i>E. histolytica</i> trophozoite migrates on a fibronectin-coated micropillar array, without <i>E. col... by Yuanning Guo (21417322)

Fibronectin expression in human large intestinal mucosa. by Yuanning Guo (21417322)

Evaluation of stage drift of live imaging. by Yuanning Guo (21417322)

Grouping, experimental procedure, and time points. by Xin Zhang (35492)

(a) Cr;(b) In;(c) Pa;(d) PS;(e) RS;(f) Sc. by Shiwei Yu (6060308)

“…The results indicated that when comparing FasterNet-YOLO with the original model, the parameters were reduced by 49.4%, GFLOPs were reduced by 57.0%, mAP increased by 6.2%, and FPS increased by 54.1%. The improved model not only increases the detection accuracy, but also significantly improves the speed of hot-rolled strip surface defect detection to meet the requirements of real-time detection.…”

Performance of different algorithms. by Shiwei Yu (6060308)

“…The results indicated that when comparing FasterNet-YOLO with the original model, the parameters were reduced by 49.4%, GFLOPs were reduced by 57.0%, mAP increased by 6.2%, and FPS increased by 54.1%. The improved model not only increases the detection accuracy, but also significantly improves the speed of hot-rolled strip surface defect detection to meet the requirements of real-time detection.…”

The improved C3STR structure. by Shiwei Yu (6060308)

“…The results indicated that when comparing FasterNet-YOLO with the original model, the parameters were reduced by 49.4%, GFLOPs were reduced by 57.0%, mAP increased by 6.2%, and FPS increased by 54.1%. The improved model not only increases the detection accuracy, but also significantly improves the speed of hot-rolled strip surface defect detection to meet the requirements of real-time detection.…”

The CBS structure improvement based on DSConv. by Shiwei Yu (6060308)

“…The results indicated that when comparing FasterNet-YOLO with the original model, the parameters were reduced by 49.4%, GFLOPs were reduced by 57.0%, mAP increased by 6.2%, and FPS increased by 54.1%. The improved model not only increases the detection accuracy, but also significantly improves the speed of hot-rolled strip surface defect detection to meet the requirements of real-time detection.…”

Experimental parameter settings. by Shiwei Yu (6060308)

“…The results indicated that when comparing FasterNet-YOLO with the original model, the parameters were reduced by 49.4%, GFLOPs were reduced by 57.0%, mAP increased by 6.2%, and FPS increased by 54.1%. The improved model not only increases the detection accuracy, but also significantly improves the speed of hot-rolled strip surface defect detection to meet the requirements of real-time detection.…”

Experimental environment configuration. by Shiwei Yu (6060308)

“…The results indicated that when comparing FasterNet-YOLO with the original model, the parameters were reduced by 49.4%, GFLOPs were reduced by 57.0%, mAP increased by 6.2%, and FPS increased by 54.1%. The improved model not only increases the detection accuracy, but also significantly improves the speed of hot-rolled strip surface defect detection to meet the requirements of real-time detection.…”

(a) YOLOv5s; (b) FasterNet-YOLO. by Shiwei Yu (6060308)

“…The results indicated that when comparing FasterNet-YOLO with the original model, the parameters were reduced by 49.4%, GFLOPs were reduced by 57.0%, mAP increased by 6.2%, and FPS increased by 54.1%. The improved model not only increases the detection accuracy, but also significantly improves the speed of hot-rolled strip surface defect detection to meet the requirements of real-time detection.…”