Cnot4 homozygous knockout mice are embryonic lethal. by Tomokazu Yamaguchi (8284989)

Microbial erosion diagram. by Wen Wang (6570)

“…The test results show that the composite specimens with different slit angles and different solution environments have significant differences in the loading process. The samples mainly experience tensile failure, with shear failure as a supplement. …”

Physical parameters. by Wen Wang (6570)

“…The test results show that the composite specimens with different slit angles and different solution environments have significant differences in the loading process. The samples mainly experience tensile failure, with shear failure as a supplement. …”

Horizontal survey line distance diagram. by Wen Wang (6570)

“…The test results show that the composite specimens with different slit angles and different solution environments have significant differences in the loading process. The samples mainly experience tensile failure, with shear failure as a supplement. …”

Primary antibodies used for immunoblot analysis. by Iratxe Zuazo-Gaztelu (21071939)

“…IRE1 silencing led to activation of TP53 and CDKN1A/p21 in conjunction with increased DNA damage and chromosome instability, while decreasing heterochromatin as well as DNA and histone H3K9me3 methylation. …”

Displacement field X₁OY₁ coordinate. by Wen Wang (6570)

“…The test results show that the composite specimens with different slit angles and different solution environments have significant differences in the loading process. The samples mainly experience tensile failure, with shear failure as a supplement. …”

Fuchioka dataset 251021. by Yusuke Fuchioka (22806178)

“…</p><p>Conclusions</p><p>Quantitative 3D-MRI analysis revealed significant cartilage thickness decreases after OWHTO, predominantly in the medial aspect of the PF joint. …”

Identification of differentially expressed proteins. by Du Leng (20421711)

Scheme of the SiTFarm tool–farm to sector level. by Jure Brečko (20314959)

“…However, the variability is significant, with a coefficient of variation 0.74. Only 25% of farms exceeded 17.15 €/h, while 25% did not surpass 4.46 €/h. …”

S1 File - by Jure Brečko (20314959)

“…However, the variability is significant, with a coefficient of variation 0.74. Only 25% of farms exceeded 17.15 €/h, while 25% did not surpass 4.46 €/h. …”

GHG emissions in TAHs. by Jure Brečko (20314959)

“…However, the variability is significant, with a coefficient of variation 0.74. Only 25% of farms exceeded 17.15 €/h, while 25% did not surpass 4.46 €/h. …”

Variation law of UCS. by Wenyu Lv (20139458)

“…Notably, the attenuation constant λ follows a monotonically decreasing pattern with increasing loading rate. …”

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. …”