Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
levels decrease » levels decreased (Expand Search), rivers decreased (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
levels decrease » levels decreased (Expand Search), rivers decreased (Expand Search)
-
19881
-
19882
-
19883
Stata file for the experimental hut data.
Published 2024“…A small, non-significant effect of pyriproxyfen on <i>Anopheles</i> fertility was observed for Royal Guard up to 12 months (75% vs 98%, OR: 1.1, 95% CI: 0.0–24.9, p-value = 0.951). …”
-
19884
EHT treatments evaluated.
Published 2024“…A small, non-significant effect of pyriproxyfen on <i>Anopheles</i> fertility was observed for Royal Guard up to 12 months (75% vs 98%, OR: 1.1, 95% CI: 0.0–24.9, p-value = 0.951). …”
-
19885
-
19886
-
19887
-
19888
-
19889
<i>OCA2</i> exon 10 skipping and pigmentation across a continuous spectrum from pathology to physiology.
Published 2025“…This frequent variant increases basal levels of exon 10 skipping on its own and is benignly associated to lightening of the skin and hair in healthy individuals of all ethnicities including with European ancestries (this study). …”
-
19890
Characteristics of schools and participants.
Published 2025“…Interpersonal influences involved varying levels of support from parents, peers, and teachers. …”
-
19891
Themes and sub-themes.
Published 2025“…Interpersonal influences involved varying levels of support from parents, peers, and teachers. …”
-
19892
eSPT Workshop Participants.
Published 2025“…<div><p>Background</p><p>Vector control remains the principal method to prevent malaria transmission and has led to significant reductions in malaria incidence across endemic regions. …”
-
19893
Primer sequences.
Published 2024“…We examined the mRNA expression of <i>Ddit3</i> (CHOP) and <i>Casp3</i> (caspase-3) on day one after the surgery; mRNA expression of both genes appeared to decrease in the KUS121 group, as compared with the control group, although differences between groups were not significant. …”
-
19894
The overall framework of CARAFE.
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. …”
-
19895
KPD-YOLOv7-GD network structure diagram.
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. …”
-
19896
Comparison experiment of accuracy improvement.
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. …”
-
19897
Comparison of different pruning rates.
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. …”
-
19898
Comparison of experimental results at ablation.
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. …”
-
19899
Result of comparison of different lightweight.
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. …”
-
19900
DyHead Structure.
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. …”