Showing 1,661 - 1,680 results of 1,792 for search '(( significantly greatest decrease ) OR ( significantly ((smaller decrease) OR (small decrease)) ))', query time: 0.31s Refine Results
  1. 1661

    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)

    Published 2025
    “…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 (I<sup>2</sup> = 76%). …”
  2. 1662

    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)

    Published 2025
    “…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 (I<sup>2</sup> = 76%). …”
  3. 1663

    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)

    Published 2025
    “…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 (I<sup>2</sup> = 76%). …”
  4. 1664

    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)

    Published 2025
    “…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 (I<sup>2</sup> = 76%). …”
  5. 1665

    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)

    Published 2025
    “…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. …”
  6. 1666

    Minimal test data set by Wenshun Sheng (21485393)

    Published 2025
    “…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. …”
  7. 1667

    OSNet network structure. by Wenshun Sheng (21485393)

    Published 2025
    “…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. …”
  8. 1668

    YOLOv8 overall framework. by Wenshun Sheng (21485393)

    Published 2025
    “…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. …”
  9. 1669

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

    Published 2025
    “…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. …”
  10. 1670

    Network structure of OSA. by Wenshun Sheng (21485393)

    Published 2025
    “…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. …”
  11. 1671

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

    Published 2025
    “…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. …”
  12. 1672

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

    Published 2025
    “…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. …”
  13. 1673

    Algorithm flowchart of OFEO. by Wenshun Sheng (21485393)

    Published 2025
    “…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. …”
  14. 1674

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

    Published 2025
    “…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. …”
  15. 1675

    Improved detection layer. by Wenshun Sheng (21485393)

    Published 2025
    “…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. …”
  16. 1676

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

    Published 2025
    “…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. …”
  17. 1677

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

    Published 2025
    “…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. …”
  18. 1678

    Data Sheet 1_Alpine steppe vegetation communities are more sensitive to plateau pika disturbance than alpine meadows.docx by Rui Hua (127074)

    Published 2025
    “…</p>Results<p>The results showed that the alpine steppe was more sensitive to pika disturbance, with significant decreases in biomass, vegetation height, and coverage even at low disturbance levels. …”
  19. 1679

    Optimisation of read depth, DNA quantity, and unique alternate observation threshold. by Melinda L. Tursky (20790436)

    Published 2025
    “…Lower read depth may contribute to an overestimated VAF of very small variants, although differences did not reach significance. …”
  20. 1680

    Automated matching and visualisation of magnetic flux leakage data in shale gas pipeline based on ICP and DBSCAN algorithm by Leyao Gu (17897654)

    Published 2025
    “…The findings show that small-scale datasets or higher false detection rates lead to decreased accuracy. …”