The notational conventions used in this paper. by Edward Antonian (21453161)

“…The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. Next, we examine the statistical effect of correlated prediction error and propose a method for Generalized Least Squares (GLS) on graphs. …”

A Tutorial on the Use of Artificial Intelligence Tools for Facial Emotion Recognition in R by Austin Wyman (17559054)

“…We present their advantages, disadvantages, and provide sample code so that researchers can immediately begin designing, collecting, and analyzing emotion data. …”

A dataset mapping the temperate savanna in Northeastern China (2022) by Xiaoya Li (19531363)

“…The derived method provides a new insight to explore the extent of regional and global savannain the future.</p><p dir="ltr">The code and generated maps are publicly accessible. …”

<b>AutoMated tool for Antimicrobial resistance Surveillance System version 3.1 (AMASS3.1)</b> by Chalida Rangsiwutisak (10501496)

“…</li><li>We have revised the text and corrected bugs encountered during data import and translation.</li><li>We have updated SaTScan codes for AnnexC: Cluster signals and report layouts.…”

Raw dataset. by Jun Zhang (48506)

“…<p>Original files of investigated data and algorithm codes.</p> <p>(ZIP)</p>…”

Data Sheet 2_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 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. …”

Table & Figure.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks by NORLIZA BINTI MOHAMED (20739875)

“…Supplementary Materials</p> <p><br></p> <p>Experimental protocols and study design details</p> <p><br></p> <p>Questionnaires, surveys, or rubrics used in the study</p> <p><br></p> <p>Educational materials related to HOTS-based mathematics tasks</p> <p><br></p> <p><br></p> <p><br></p> <p>3. Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”

<b>Analyzing the mechanical heterogeneity of the Chang’e-5 lunar breccia clast: Implications for the elastic modulus of lunar rock</b> by Jiayan Nie (14779711)

“…<p dir="ltr">The raw nanoindentation loading and unloading curves of 02-001 and 02-002 areas and the derived physical quantities in this study can be accessed in this repository. The cited data from Peña‐Asensio et al. (2024a), Moyano-Cambero et al. (2017), Tanbakouei et al. (2019), and the computational codes of the BUS method with the subset simulation algorithm to extract Gaussian components can also be accessible in this repository.…”

Supplementary materials: Real-world phosphorodiamidate morpholino oligomer treatment patterns in Duchenne muscular dystrophy: a claims-based analysis by Shannon Grabich (21742174)

“…PMO treatment patterns were generally similar in patients stratified by algorithm-defined nonambulatory status.<b> Conclusion:</b> In an analysis of administrative claims data, adherence to PMO treatment for DMD was high. …”

Improving the calibration of an integrated CA-What If? digital planning framework by CA What If? (21381170)

“…</p><p dir="ltr">This dataset includes (1) all required data for reproducing the materials within the manuscript, (2) detailed Python codes of the proposed CA-What If? …”

Figure 1 from Prostate Cancer Progression Modeling Provides Insight into Dynamic Molecular Changes Associated with Progressive Disease States by Runpu Chen (14942572)

“…The black line is the constructed principal tree, and the three axes represent the leading components generated by the DDRTree algorithm (denoted as DDRTree 1–3). <b>B,</b> Seven progression states were identified by partitioning the samples on the data manifold. …”

Overcoming limitations to customize DeepVariant for domesticated animals with TrioTrain by Robert Schnabel (236298)

“…However, the growing appeal of a “universal” algorithm has magnified the unknown impacts when used with non-human species. …”

Training and test routes for simulated agents navigating using insect inspired strategies by Amany Said Amin (11234025)

“…<p dir="ltr">These folders contain train routes, test routes and terrain information (labelled as per filenames) for a set of insect-inspired route navigation experiments conducted in Unity.</p><p dir="ltr">For code analysing this data see: <a href="https://github.com/amanyazevedoamin/RecapitulatedTrackConvergence" rel="noreferrer" target="_blank">https://github.com/amanyazevedoamin/RecapitulatedTrackConvergence</a></p><p dir="ltr">All trajectories are 2D and stored as csv files with headings of 'x','y' and 'heading' (degrees)</p><p dir="ltr">The folder names encode the following:</p><p dir="ltr">The first 3 characters corresponds to the training route length: "EXT" is 20m, "LON" is a longer 100m training route</p><p dir="ltr">The second 3 characters refer to the route recapitulation strategy in use.…”

CIAHS-Data.xls by Yingchang Li (22195585)

“…For this purpose, we employed the Natural Breaks classification method to reclassify factor values. This method identifies inherent natural grouping points within the data through the Jenks optimization algorithm, maximizing between-class differences while minimizing within-class differences37. …”