Fig 9 - BC. حسب Curtis Chepsiror (21368103)

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

"…</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). …"

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

"…</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). …"

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

"…<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. …"

Factors affecting LLINs usage at household level. حسب Job Oyweri (22041452)

"…Bed ownership was 50.8% in the pyrethroid-LLIN group and 55.3% in the PBO-LLIN group. Not owning a bed decreased the likelihood of net usage by 13.3% [aOR=0.867 (95% CI = 0.816–0.920), p < 0.001]. …"

Net usage across intervention arms. حسب Job Oyweri (22041452)

"…Bed ownership was 50.8% in the pyrethroid-LLIN group and 55.3% in the PBO-LLIN group. Not owning a bed decreased the likelihood of net usage by 13.3% [aOR=0.867 (95% CI = 0.816–0.920), p < 0.001]. …"

Factors associated with malaria infection. حسب Job Oyweri (22041452)

"…Bed ownership was 50.8% in the pyrethroid-LLIN group and 55.3% in the PBO-LLIN group. Not owning a bed decreased the likelihood of net usage by 13.3% [aOR=0.867 (95% CI = 0.816–0.920), p < 0.001]. …"

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

"…<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. …"

Correlation between urinary Br- levels and ERP indices in all participants before (n = 50) and after (n = 50) work. حسب Jungmi Choi (4740150)

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

"…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. …"

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

"…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. …"

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

"…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. …"

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

"…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. …"

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

"…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. …"

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

"…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. …"

DyHead Structure. حسب Zhongjian Xie (4633099)

"…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. …"

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

"…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. …"

Structure of GSConv network. حسب Zhongjian Xie (4633099)

"…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. …"

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

"…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. …"

Improved model distillation structure. حسب Zhongjian Xie (4633099)

"…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. …"