Hydrogen bond interactions between Akt1/Akt2-IN-1 (red) and the AKT2 protein (blue) as predicted by molecular docking analyses. by Sadia Afrin Runa (22504971)

UHPLC-ESI-qTOF-MS/MS base peak chromatograms of <i>T. oliverianum</i> above ground parts in negative ionization mode. by Rania F. Ahmed (10032039)

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. …”

Representative structure of some metabolites identified in <i>T. oliverianum</i> above-ground parts <i>using</i> UPLC-MS. by Rania F. Ahmed (10032039)

S1 Data - by Perumal Vivekanandhan (4863484)

“…<div><p><i>Aedes albopictus</i>, known as the Asian tiger mosquito, is a significant vector for dengue fever, chikungunya, zika virus, yellow fever. …”

Photomicrographs of hepatic sections stained with picrosirius red (bright field and polarized light) and hepatic immunohistochemical expression of α-SMA in different experimental g... by Rania F. Ahmed (10032039)

Fig 3 - by Xinyi Xia (7516694)

UPLC-ESI/MS-MS based characterization of phytoconstituents of the ethanol (EtOH) and ethyl acetate (EtOAc) extracts of <i><i>T. oliverianum</i></i> above-ground parts in negative i... by Rania F. Ahmed (10032039)

Total match head impacts by header scenario. by Rachel S. Watson (21864061)

“…Repetitive head impact exposure by position was associated with significant decreases in absolute error (<i><i>p < </i></i>0.001), increases in peak velocity <i><i>(p < </i></i>0.001), and increases in reaction time (<i><i>p < </i></i>0.001). …”

Study Flowchart. by Jae-Heung Cho (798319)

“…Despite no significant differences in pain reduction at week 5, CMT was found to be a cost-effective treatment for TMD, particularly for improving function and quality of life. …”