Spearman correlation of age with proportions of cell types in men, for each brain region. by Arttu Autio-Kimura (20454681)

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Principal Component Analysis (PCA) to illustrate the distribution of the significant lipid metabolites among the groups (NL, SS and MASH). by Laia Bertran (3685147)

Synthetic feasibility scores of 20 molecular fragments. by Bin Pan (742525)

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The scatter plot of the target variable solubility dataset. by Bin Pan (742525)

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Samples with the highest solubility after high-throughput screening. by Bin Pan (742525)

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Assessment values of machine learning models. by Bin Pan (742525)

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List of datasets in AqSolDB. by Bin Pan (742525)

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Schematic workflow diagram of the StackBoost model framework. by Bin Pan (742525)

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Comparison of training and predicted values of compound water solubility for different machine learning models: (A) AdaBoost, (B) GBDT, (C) LGBM, (D) RF, (E) XGBoost, (F) RF, and (... by Bin Pan (742525)

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Pearson correlation analysis between pairs of feature parameters. by Bin Pan (742525)

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Comparison of actual vs predicted values after transfer. by Bin Pan (742525)

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List of available information in each column of AqSolDB. by Bin Pan (742525)

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3D Scatter plot of features related to water-soluble materials. by Bin Pan (742525)

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Workflow diagram of the prediction algorithm framework. by Bin Pan (742525)

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Feature importance derived from SHAP analysis. by Bin Pan (742525)

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Root mean square fluctuations of the wild-type (green line) and mutant (H5Q) (purple line) proteins of AKR1C3 (complexed with the ligand NADPH). by Md. Akeruzzaman Shaon (21511929)

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Comparative analysis of macronutrient compositions between baseline and end of intervention (*p < 0.05, ^ns Non-significant results). by Duc Tran Quang (20564967)

Comparative analysis of caloric intake between baseline and end of intervention (*p < 0.05, ^ns Non-significant results). by Duc Tran Quang (20564967)

Results of RF regression model validation and significance of influencing factors (desert area change and spatiotemporal characteristics of ERI). by Mingyue Sun (4638535)

Comparison with Existing Studies. by Na Zhao (112953)

“…The results indicate that: (1) the presence of pores prolongs both the time to failure and the onset of the AE burst stage, with longer durations observed at higher pore dip angles; (2) AE signal amplitude and frequency vary significantly across different loading stages, and the b-value exhibits an “increase–fluctuation–decrease” trend, with the decreasing stage serving as a precursor to rock instability; (3) pore dip angle strongly influences crack propagation types: dip angles of 0°–30° favor axial cracks and through-going wing cracks, 45°–75° angles tend to induce co-planar and wing crack connectivity, while 90° angles cause crack deviation, hindering through-going failure; (4) intact rock fails in a tensile–shear mixed mode, whereas the number of shear cracks in rocks with pores initially increases and then decreases with dip angle, reaching a maximum at 45°, resulting in shear-dominated failure. …”