Showing 2,661 - 2,680 results of 5,616 for search '(( significantly higher decrease ) OR ( significantly small decrease ))', query time: 0.34s Refine Results
  1. 2661

    Flow chart of the study participants. by Milton W. Musaba (8431944)

    Published 2025
    “…</p><p>Results</p><p>Bedside resuscitation increased significantly in the post-implementation period (9.3% versus 45.3%, <i>p</i> < 0.001 while early cord clamping decreased (26.7% versus 12.0%, <i>p</i> = 0.042). …”
  2. 2662

    Suggested modifications for the BabySaver. by Milton W. Musaba (8431944)

    Published 2025
    “…</p><p>Results</p><p>Bedside resuscitation increased significantly in the post-implementation period (9.3% versus 45.3%, <i>p</i> < 0.001 while early cord clamping decreased (26.7% versus 12.0%, <i>p</i> = 0.042). …”
  3. 2663

    TSA alleviates the induction of inflammatory cytokines in <i>Col4a3</i> KO mice. by Yoon Seok Nam (20678482)

    Published 2025
    “…<p>(A) The mRNA level of proinflammatory cytokines IL-1β and TGF-β1 was higher in the cochlea of <i>Col4a3</i> KO mice, while IL-6 and TNF-α were significantly increased compared to wild-type (WT) mice. …”
  4. 2664

    The number of male–male agonistic interactions in relation to females with maximal swelling. by Heungjin Ryu (10747673)

    Published 2025
    “…<b>(D)</b> Visualization of the interdependency between the number of males and females with maximal swelling on the male aggression rate (significant interaction in LM-2E) shows that when there were a greater number of males in the party, e.g., Mean + 1SD (9.6 males in D), the male aggression rate decreased as the number of females with maximal swelling increased. …”
  5. 2665
  6. 2666
  7. 2667

    The overall framework of CARAFE. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  8. 2668

    KPD-YOLOv7-GD network structure diagram. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  9. 2669

    Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  10. 2670

    Comparison of different pruning rates. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  11. 2671

    Comparison of experimental results at ablation. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  12. 2672

    Result of comparison of different lightweight. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  13. 2673

    DyHead Structure. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  14. 2674

    The parameters of the training phase. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  15. 2675

    Structure of GSConv network. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  16. 2676

    Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  17. 2677

    Improved model distillation structure. by Zhongjian Xie (4633099)

    Published 2025
    “…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
  18. 2678

    Trends of HIV/AIDS in Ethiopia (1990-2021). by Tegene Atamenta Kitaw (17930374)

    Published 2025
    “…Mortality rates rose from 14.2 per 100,000 in 1990 to 79.7 in 2000 but decreased to 13.6 by 2021, with an AAPC of -1.19%. …”
  19. 2679

    S1 Graphical abstract - by Huimin Xian (20390006)

    Published 2024
    “…</p><p>Conclusions</p><p>In patients with MVD-STEMI, the incidence of MACEs was lower in FCR than in FIR, and the decrease was particularly significant in the DM cohort. …”
  20. 2680

    Procedural characteristics. by Huimin Xian (20390006)

    Published 2024
    “…</p><p>Conclusions</p><p>In patients with MVD-STEMI, the incidence of MACEs was lower in FCR than in FIR, and the decrease was particularly significant in the DM cohort. …”