UC division situation. by Hui Yang (91136)

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Comparison of deep partitioning models. by Hui Yang (91136)

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Projection weight distribution. by Hui Yang (91136)

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Horizontal comparison of models. by Hui Yang (91136)

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Adaptive model BD rate analysis. by Hui Yang (91136)

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Index analysis of deep partitioning strategy. by Hui Yang (91136)

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Overall suitability maps for the selected crops. by Ahmed S. Abuzaid (5088119)

“…Soil salinity, sodicity, and depth were the most important determinants of landscape suitability. …”

Monthly averages of ED2 model simulations initialised with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon by Marcos Longo (1928929)

“…</strong> To carry out the ED2 simulations, we used ED2 initialization files generated following the algorithm described in Longo et al. (2020) and available on <a href="https://doi.org/10.5281/zenodo.14768399">Zenodo</a>.…”

Comparison of scSCOPE with other methods in terms of running time. by Sandesh Acharya (11261473)

Error component scores corresponding to the best parameters found by the Covariance Matrix Adaptation Evolution Strategy (CMAES) and Random Search algorithms in Use Case 4 (simplif... by Máté Mohácsi (20469514)

Summary of the results (optimal parameters and resulting correlation coefficients) of the intersubject models for the different selections of training and test sets for Worry/Fear... by Isabel Barradas (20614853)

Table 2_In-depth immunochemical characterization of the serum antibody response using a dual-titration microspot assay.xlsx by Ágnes Kovács (3252267)

Table 1_In-depth immunochemical characterization of the serum antibody response using a dual-titration microspot assay.xlsx by Ágnes Kovács (3252267)

Data Sheet 2_In-depth immunochemical characterization of the serum antibody response using a dual-titration microspot assay.pdf by Ágnes Kovács (3252267)

Data Sheet 1_In-depth immunochemical characterization of the serum antibody response using a dual-titration microspot assay.pdf by Ágnes Kovács (3252267)

Overview of the proposed improvements to the YOLO11 model. by Beigeng Zhao (21637197)

Dive profiles, observations, and decoded hidden state probabilities for selected dive without foraging. by Evan Sidrow (18516509)

Dive profiles, observations, and decoded hidden state probabilities for selected successful foraging dive. by Evan Sidrow (18516509)

Table 1_Identification of mitophagy-related biomarkers in severe acute pancreatitis: integration of WGCNA, machine learning algorithms and scRNA-seq.xlsx by Xiaozhou Xie (11632274)

“…In this study, we aimed to identify crucial mitophagy-related genes in SAP to provide a theoretical basis for in-depth mechanistic investigations. </p>Methods<p>We downloaded the GSE194331 dataset from the Gene Expression Omnibus (GEO), identified differentially expressed genes (DEGs), and used weighted gene co-expression network analysis (WGCNA) and three machine learning algorithms to identify crucial genes. …”

a-c: (a) The nomogram model developed for the prognostic prediction of hub genes from the study. by Devi Soorya Narayana Sasikumar (22331743)