Box-whisker plots of the relative abundances (%) of coccolithophore species characteristic for the “pseudo-stadial” (PS; 1854.6–1852.8 cm), the interstadial before the YTT eruption... by Jose Dominick Guballa (19739909)

Analysis of stress-related gene expression in cherry shrimp (<i>N</i>. <i>davidi</i> var. red). by Wei-Wei Hou (3405947)

Correlations between feed additives and color-related genes. by Wei-Wei Hou (3405947)

Two-dimensional quadrant analysis of cherry shrimp (<i>N</i>. <i>davidi</i> var. red) bodycolor parameters (<i>L*</i> and <i>a*</i> values) in different feed treatment groups on da... by Wei-Wei Hou (3405947)

Sox2 is upstream of <i>Atoh1</i> and <i>Huwe1</i> in embryonic development and <i>Huwe1</i> knockdown results in hair cell generation from dividing supporting cells. by Yen-Fu Cheng (5819855)

<i>SLC2A2</i> is essential for liver differentiation in developing vertebrates by Yejin Kim (740789)

“…The mRNA expression levels were normalized to β-actin. A significant increase (p-value < 0.001, ***) in igf1r expression was observed in <i>SLC2A2</i> MO-injected embryos compared to the control group. …”

The biological characteristics of the I7L protein (pI7L). by Meilin Li (1832905)

Amino acid metabolic pathways are influenced by the NC1 POM cycle over expression. by Bonnie A. McNeil (22331601)

“…Box and whisker plots of selected metabolites that displayed significant increase or decrease in the NC1 POM cycle producing strain (NC), red boxes, or empty vector producing strain (YC) green boxes. …”

Valve closing capability and hemolymph flow analysis. by Christian Meyer (6035)

“…Pixel intensity in ROI 1 increases if hemolymph packages pass and decreases, if valves close after each heartbeat, respectively. …”

A proposed model on the impact of DHA and ARA supplementation on <i>L. vannamei</i> health. by Virak Visudtiphole (11574169)

Validation and predictive accuracy of the cerebrovascular model, by Hadi Esfandi (21387211)

Bone-related serum chemistry endpoints: Aquamin (180-day treatment group) versus placebo. by Muhammad N. Aslam (6598001)

Comparison of Mean Absolute Error (MAE) in Millimeters as a Function of Kernel Size. by Liu Liu (512237)

“…After this point, the Reduced Depth model’s MAE increases significantly, while the Full Model’s performance stabilizes before slightly increasing again.…”

Dataset visualization diagram. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

Dataset sample images. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

Performance comparison of different models. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

C2f and BC2f module structure diagrams. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

YOLOv8n detection results diagram. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

YOLOv8n-BWG model structure diagram. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

BiFormer structure diagram. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”