Image 3_Acute effects of exercise snacks on postprandial glucose and insulin metabolism in adults with obesity: a systematic review and meta-analysis.pdf by Yuanbo Chang (22654910)

“…Glucose tAUC and mean glucose showed non-significant downward trends. Mean insulin decreased (SMD = −0.54, 95% CI –0.97 to −0.10), albeit with high heterogeneity (I² = 76%). …”

Image 2_Acute effects of exercise snacks on postprandial glucose and insulin metabolism in adults with obesity: a systematic review and meta-analysis.pdf by Yuanbo Chang (22654910)

“…Glucose tAUC and mean glucose showed non-significant downward trends. Mean insulin decreased (SMD = −0.54, 95% CI –0.97 to −0.10), albeit with high heterogeneity (I² = 76%). …”

Table 6_Acute effects of exercise snacks on postprandial glucose and insulin metabolism in adults with obesity: a systematic review and meta-analysis.docx by Yuanbo Chang (22654910)

“…Glucose tAUC and mean glucose showed non-significant downward trends. Mean insulin decreased (SMD = −0.54, 95% CI –0.97 to −0.10), albeit with high heterogeneity (I² = 76%). …”

Table 2_Acute effects of exercise snacks on postprandial glucose and insulin metabolism in adults with obesity: a systematic review and meta-analysis.docx by Yuanbo Chang (22654910)

“…Glucose tAUC and mean glucose showed non-significant downward trends. Mean insulin decreased (SMD = −0.54, 95% CI –0.97 to −0.10), albeit with high heterogeneity (I² = 76%). …”

Image 4_Acute effects of exercise snacks on postprandial glucose and insulin metabolism in adults with obesity: a systematic review and meta-analysis.pdf by Yuanbo Chang (22654910)

“…Glucose tAUC and mean glucose showed non-significant downward trends. Mean insulin decreased (SMD = −0.54, 95% CI –0.97 to −0.10), albeit with high heterogeneity (I² = 76%). …”

Table 5_Acute effects of exercise snacks on postprandial glucose and insulin metabolism in adults with obesity: a systematic review and meta-analysis.docx by Yuanbo Chang (22654910)

“…Glucose tAUC and mean glucose showed non-significant downward trends. Mean insulin decreased (SMD = −0.54, 95% CI –0.97 to −0.10), albeit with high heterogeneity (I² = 76%). …”

Image 1_Acute effects of exercise snacks on postprandial glucose and insulin metabolism in adults with obesity: a systematic review and meta-analysis.pdf by Yuanbo Chang (22654910)

“…Glucose tAUC and mean glucose showed non-significant downward trends. Mean insulin decreased (SMD = −0.54, 95% CI –0.97 to −0.10), albeit with high heterogeneity (I² = 76%). …”

SEAwise synthetic summary report of the findings of WP4 on changes to the ecosystem impacts of fishing in response to spatial management for online tool by Anna Rindorf (6217391)

“…While the attainment of GES could also be found in scenarios with closed areas, this was generally restricted to the indicators at which the closure was aimed while other indicators worsened.</p><p dir="ltr">Decreasing fishing effort to levels compatible with FMSY-min resulted in slightly but not significantly higher average landings in the Adriatic and western Ionian Sea and the North Sea under current climate where currently overfished gadoid stocks were rebuilt in the simulations. …”

Minimal test data set by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

OSNet network structure. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

YOLOv8 overall framework. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

The performance of YOFGD model on MOT16. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

Network structure of OSA. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

The performance of S-YOFEO model on MOT17. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

Five multi-target tracking evaluation indexes. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

Algorithm flowchart of OFEO. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

Partial tracking results of MOT17 dataset. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

Improved detection layer. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

The performance of S-YOFEO model on MOT16. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”

The matching process of EIOU. by Wenshun Sheng (21485393)

“…For the purpose of further enhancing the processing capability of small-scale features, a small target detection head is first introduced to the detection layer of YOLOv8 in this paper with the aim of collecting more detailed information by increasing the detection resolution of YOLOv8 to ensure precise and fast detection. …”