Analyses of the mitochondrial complex I activity and ATP and ROS productions in Pns10-GFP expressing Sf9 cells and RRSV viruliferous <i>N. lugens.</i> by Lianshun Zheng (22086585)

Changes in the expression of NF-κB-related inflammatory factors, TERT and telomerase activity in KGN cells in each group. by Haoxuan Xue (19949764)

Effect of MGO on <i>in vitro</i> maturation and developmental competence of mouse COCs and DOs. by Shahrzad Ronasi (20933556)

Changes in the expression of apoptosis-related factors Bax, Bcl-2, and Caspase-3 in KGN cells in each group. by Haoxuan Xue (19949764)

Protective effect of SMND-309 against liver injury in acute liver injury model mice. by Yao Dong (3308124)

LPS treatment increases the expression of NF-κB-related inflammatory factors, hTERT and cell apoptosis in KGN cell and correlation between NF-κB-related inflammatory factors, TERT... by Haoxuan Xue (19949764)

SEM morphology of power: (a)17−4PH; (b)TiC. by Dian Yu Luo (22656111)

“…Compared to the commercial blade, the wear of the laser-cladded blade was decreased by 67%. This study successfully applied wear-resistant laser cladding coatings on the surface of harvester blades with small substrate thickness, significantly extending their service life.…”

<i>BgILP1-8</i> expression in different <i>Blattella germanica</i> adult male tissues and in response to starvation. by Viviana Pagone (22086362)

SlABCG9 Functioning as a Jasmonic Acid Transporter Influences Tomato Resistance to Botrytis cinerea by Ning Tao (109880)

“…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. …”

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

“…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. …”

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

“…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. …”

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

“…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. …”

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

“…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. …”

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

“…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. …”

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

“…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. …”

DyHead Structure. by Zhongjian Xie (4633099)

“…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. …”

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

“…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. …”

Structure of GSConv network. by Zhongjian Xie (4633099)

“…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. …”

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

“…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. …”

Improved model distillation structure. by Zhongjian Xie (4633099)

“…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. …”