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we decrease » _ decrease (Expand Search), nn decrease (Expand Search), teer decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), teer decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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5841
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5842
Analyses of directed phase lag index (dPLI [44]) for excitatory/inhibitory (E/I) ratios with respect to pyramidal (Pyr) and parvalbumin (PV) populations (<i>A</i>) and Pyr and soma...
Published 2025“…<p>Black circles and gray pentagons represent the mean values of dPLI from PV to Pyr and from SOM to Pyr populations, respectively. …”
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5843
SlABCG9 Functioning as a Jasmonic Acid Transporter Influences Tomato Resistance to Botrytis cinerea
Published 2025“…Assays using Xenopus oocytes, yeast cell sensitivity, and JA-inhibited primary root growth confirmed that SlABCG9 functions as a JA influx transporter. The knockout mutant lines of <i>SlABCG9</i> showed decreased JA contents, suppressed defense gene <i>PDF1.2</i>’s expression, reduced antioxidant enzyme activity, and severe disease symptoms compared to wild-type controls. …”
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5844
The overall framework of CARAFE.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5845
KPD-YOLOv7-GD network structure diagram.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5846
Comparison experiment of accuracy improvement.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5847
Comparison of different pruning rates.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5848
Comparison of experimental results at ablation.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5849
Result of comparison of different lightweight.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5850
DyHead Structure.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5851
The parameters of the training phase.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5852
Structure of GSConv network.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5853
Comparison experiment of accuracy improvement.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5854
Improved model distillation structure.
Published 2025“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
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5855
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5856
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5857
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5858
Presentation_1_Multifaceted neuroprotective approach of Trolox in Alzheimer's disease mouse model: targeting Aβ pathology, neuroinflammation, oxidative stress, and synaptic dysfunc...
Published 2024“…This research study is significant as it aims to assess the neuroprotective properties of vitamin E (VE) analog Trolox in an Aβ<sub>1 − 42</sub>-induced AD mouse model. …”
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5859
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5860
Ignition delay process shot by high-speed camera.
Published 2025“…The evolution of the fractal dimension of the lubricating oil droplet flame shows a trend of first increasing and then slowly decreasing. …”