Table 3_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Data Sheet 1_Characterization of the salivary microbiome in healthy individuals under fatigue status.docx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Table 5_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Table 4_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Table 2_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Table 1_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Framework of the Methodology. by Yibin Zhang (1426579)

“…Tracking is the most crucial data processing step to generate accurate and reliable trajectories of road users from raw point clouds collected from LiDAR sensors. …”

Supporting documents for the <i>APSB</i> manuscript "<i>Metabolic reactions based molecular networking for xenobiotic profiling of complex samples</i>" by Haodong Zhu (20627600)

“…</li><li><b>Node and Edge files of MRMN</b><b> </b>for LC-MS data of biological samples following the administration output by the YaoLab@JNU platform: These files are intended for offline processing of MRMN with Cytoscape</li></ol><p></p>…”

Table 1_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.docx by Yuwen ShangGuan (22633190)

“…Missing data were handled using random forest algorithm, feature selection was performed using Boruta algorithm, and SMOTE technique addressed class imbalance. …”

Table 1_Non-obtrusive monitoring of obstructive sleep apnea syndrome based on ballistocardiography: a preliminary study.docx by Biyong Zhang (20906192)

“…This can reduce both the data to be stored or transmitted and the computational load. …”

Opponent Style Representation Learning Method Based on Spatio-Temporal Features by Jinpeng Zhang (22759856)

“…</p><p dir="ltr"><b>Data Sources</b>: Experimental data combines:</p><ol><li>Logs from the <a href="https://github.com/vwxyzjn/gym-microrts-paper" target="_blank">gym-microrts-paper</a> benchmark suite</li><li>Built-in agent logs from the MicroRTS platform</li></ol><p dir="ltr">Generate Log Data (using selected agents):</p><ol><li>The following three files are logs generated by running selected intelligent agents:<br><br>1model_vs_model.py<br>2model_vs_model.py<br>3odel_vs_model.py</li><li>datatool1 is a data processing tool. …”

Supplementary file 3_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm is data-agnostic and enables users to optimise indicator selection with diverse datasets spanning research, industry, and policy contexts. …”

Supplementary file 2_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm is data-agnostic and enables users to optimise indicator selection with diverse datasets spanning research, industry, and policy contexts. …”

Supplementary file 6_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm is data-agnostic and enables users to optimise indicator selection with diverse datasets spanning research, industry, and policy contexts. …”

Supplementary file 1_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm is data-agnostic and enables users to optimise indicator selection with diverse datasets spanning research, industry, and policy contexts. …”

Supplementary file 4_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm is data-agnostic and enables users to optimise indicator selection with diverse datasets spanning research, industry, and policy contexts. …”

Supplementary file 5_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm is data-agnostic and enables users to optimise indicator selection with diverse datasets spanning research, industry, and policy contexts. …”

The Comparison of MOTA for Different Thresholds. by Yibin Zhang (1426579)

“…Tracking is the most crucial data processing step to generate accurate and reliable trajectories of road users from raw point clouds collected from LiDAR sensors. …”

Demonstration of the Result of Clustering. by Yibin Zhang (1426579)

“…Tracking is the most crucial data processing step to generate accurate and reliable trajectories of road users from raw point clouds collected from LiDAR sensors. …”

Summary of Dataset Scenario and Performance. by Yibin Zhang (1426579)

“…Tracking is the most crucial data processing step to generate accurate and reliable trajectories of road users from raw point clouds collected from LiDAR sensors. …”