Spearman correlations between the age of the sample donor (20–70 years) and estimated proportions of neuronal, glial, and endothelial cells. by Arttu Autio-Kimura (20454681)

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Box plots for subsets of female originating samples, displaying the distributions of the proportions of neuronal, glial, and endothelial cells. by Arttu Autio-Kimura (20454681)

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Box plots for subsets of male originating samples, displaying the distributions of the proportions of neuronal, glial, and endothelial cells. by Arttu Autio-Kimura (20454681)

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Box plot displaying the distributions of the deconvolution derived proportions of cell types. by Arttu Autio-Kimura (20454681)

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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)

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)

a) FB image processing featuring (1) FB map, (2) TWOMBLI mask, (3) FB-mask multiplied image, and (4) Ridge detection selection of contours. b) TWOMBLI Output Descriptions. (1) Area... by Zoë Dinkel (21402766)

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Comparison of the results of our model and other methods. by Weijia Zhu (65481)

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

Significant repeated measurements sEMG outcomes. by María Benito-de-Pedro (22057468)

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Significant single measurement sEMG outcomes. by María Benito-de-Pedro (22057468)

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Some examples of selected Chinese characters. by Weijia Zhu (65481)

“…Our model shows clear enhancements in structural accuracy (SSIM improved to 0.91), pixel-level fidelity (RMSE reduced to 2.68), perceptual quality aligned with human vision (LPIPS reduced to 0.07), and stylistic realism (FID decreased to 13.87). It reduces the model size to 100M parameters, cuts training time to just 1.3 hours, and lowers inference time to only 21 minutes. …”

Preparation of uniaxial compression and Brazilian tension test specimens: (a) core drilling; (b) specimen preparation; (c) completed test specimens. by Hong Zhang (25820)

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Testing equipment and typical specimen failure modes: by Hong Zhang (25820)

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Values of critical shape factor (<i>β</i>′) for different allowable relative deviations (<i>w</i>₂, in %). by Hong Zhang (25820)

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Soft phyllite specimens at different degrees of weathering: (a) strongly weathered; (b) weakly weathered; (c) slightly weathered. by Hong Zhang (25820)

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Schematic of the actual failure cross-sectional area. by Hong Zhang (25820)

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Schematic for measuring <i>D</i> and <i>D</i>′ values. by Hong Zhang (25820)

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