Swelling pressure versus free swelling ratio curve. by Yonggang Huang (223155)

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Shematic representation for the mechanism of the swelling pressure: (a)soil without added fiber; (b)soil with added fiber. by Yonggang Huang (223155)

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Influence of UHMWPE length on swelling pressure. by Yonggang Huang (223155)

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UHMWPF parameters. by Yonggang Huang (223155)

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The test results of swelling pressure of reinforced expansive soil. by Yonggang Huang (223155)

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Influence of UHMWPE content on swelling pressure. by Yonggang Huang (223155)

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Sampling point (Source: by Yonggang Huang (223155)

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Enrichment Analysis Based on Ferroptosis-Related Differentially Expressed Genes. by Jiyong Zhang (2498740)

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Correlation between hub genes and 50 hallmark signaling pathways. by Jiyong Zhang (2498740)

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ROC curves for hub genes. by Jiyong Zhang (2498740)

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Intersection genes obtained from the PPI network and PPI network analysis of intersection genes. colored circles represent genes. by Jiyong Zhang (2498740)

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Expression profile heatmaps of key genes in gene sets. by Jiyong Zhang (2498740)

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Influence of UHMWPE length on free swelling ratio. by Yonggang Huang (223155)

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Construction of the WGCNA Co-expression Network. by Jiyong Zhang (2498740)

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Influence of UHMWPE content on free swelling ratio. by Yonggang Huang (223155)

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Soil partice-size distribution. by Yonggang Huang (223155)

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Differential Gene Expression Associated with Non-Alcoholic Fatty Liver Disease. by Jiyong Zhang (2498740)

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Interaction analysis of hub genes. by Jiyong Zhang (2498740)

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Testing set error. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”

Internal structure of an LSTM cell. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”