Expression pattern of statistically significantly differentially expressed immune-related genes in CL patients compared to healthy volunteers. by Nasrin Masoudzadeh (20300511)

Atg14 plays a cell-intrinsic role in orchestrating eTreg survival but not terminal differentiation. by Erienne G. Norton (9612079)

Microhardness of various samples. by Huashen Guan (20454677)

“…After shot peening, the wear resistance of the sample significantly improved, and the amount of wear significantly decreased. …”

Shot peening process parameters. by Huashen Guan (20454677)

“…After shot peening, the wear resistance of the sample significantly improved, and the amount of wear significantly decreased. …”

Schematic diagram of pin-disk wear. by Huashen Guan (20454677)

“…After shot peening, the wear resistance of the sample significantly improved, and the amount of wear significantly decreased. …”

Parameters of the sliding wear test. by Huashen Guan (20454677)

“…After shot peening, the wear resistance of the sample significantly improved, and the amount of wear significantly decreased. …”

Finite element model of shot peening. by Huashen Guan (20454677)

“…After shot peening, the wear resistance of the sample significantly improved, and the amount of wear significantly decreased. …”

Wear morphology of the UT sample. by Huashen Guan (20454677)

“…After shot peening, the wear resistance of the sample significantly improved, and the amount of wear significantly decreased. …”

Surface roughness of various samples. by Huashen Guan (20454677)

“…After shot peening, the wear resistance of the sample significantly improved, and the amount of wear significantly decreased. …”

Atg14 deficiency in Tregs induces a type-I-dominant lymphoproliferative disease and cell-intrinsic reductions in eTregs. by Erienne G. Norton (9612079)

Detail of the personalized-enhanced GCN. by Yuanming Ding (12842858)

“…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”

Enhanced multi-component module. by Yuanming Ding (12842858)

“…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”

The architecture of the TCBiL. by Yuanming Ding (12842858)

“…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”

Detail of the encoder. by Yuanming Ding (12842858)

“…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”

Detail of the Fourier transform. by Yuanming Ding (12842858)

“…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”

Detail of the decoder. by Yuanming Ding (12842858)

“…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”

Encoder-decoder architecture. by Yuanming Ding (12842858)

“…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”

Dataset description. by Yuanming Ding (12842858)

“…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”

PeMSD8. by Yuanming Ding (12842858)

Age-standardized hepatocellular carcinoma (HCC) incidence rates, by viral hepatitis status, the surveillance, epidemiology, and end results–medicare database, 2007–2017. by Joy Jiang (5483006)