<b>R</b><b>esidual</b> <b>GCB-Net</b>: Residual Graph Convolutional Broad Network on Emotion Recognition by Qilin Li (535447)

“…<p dir="ltr">Electroencephalogram (EEG) data are commonly applied in the emotion recognition research area. …”

Cringe - Emotional manipulation as a tool of political control in Albanian digital campaigns (2025) by Edlira Gugu (21793610)

“…</p><p dir="ltr"><b>Key findings include:</b></p><ul><li>Perfect correlation (r = 1.000) between cringe intensity and electoral success</li><li>Identification of six strategic cringe tactics used by politicians</li><li>Discovery of 58 anonymous pages using artificial amplification (ratios up to 396:1)</li><li>Evidence of cringe functioning as affective governance and social control</li></ul><p dir="ltr"><b>Dataset contents:</b></p><ul><li>Full research paper (English & Albanian versions)</li><li>Interactive data visualizations and statistical analysis</li><li>Comprehensive emotions lexicon for cringe phenomenon</li><li>Detailed supplementary materials with coded examples</li><li>Methodology documentation and ethics compliance records</li></ul><p dir="ltr"><b>Methodology:</b> Mixed-methods approach combining computational analysis with qualitative discourse analysis. …”

Table 2_Identification and validation of pyroptosis-related genes in Alzheimer’s disease based on multi-transcriptome and machine learning.docx by Yuntai Wang (21356525)

“…Additionally, we validated the expression patterns of these key genes using the expression data from AD mice and constructed potential regulatory networks through time series and correlation analysis.…”

Table 1_Identification and validation of pyroptosis-related genes in Alzheimer’s disease based on multi-transcriptome and machine learning.xlsx by Yuntai Wang (21356525)

“…Additionally, we validated the expression patterns of these key genes using the expression data from AD mice and constructed potential regulatory networks through time series and correlation analysis.…”

An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows by Pierre-Alexis DELAROCHE (22092572)

“…Cloud Workflows}, author={AlbumForge Research Team}, year={2025}, publisher={Figshare}, doi={10.6084/m9.figshare.XXXXXXX}, url={https://figshare.com/articles/dataset/XXXXXXX} } Contributing and Data Governance Issue Reporting Technical issues, data quality concerns, or methodological questions should be reported via GitHub Issues with the following template: **Issue Type**: [Bug Report / Data Quality / Methodology Question] **Hardware Configuration**: [Specify if applicable] **Dataset Version**: [e.g., v1.0.0] **Description**: [Detailed description of the issue] **Reproducibility**: [Steps to reproduce if applicable] **Expected Behavior**: [What should happen] **Actual Behavior**: [What actually happens] Data Update Protocol Dataset versioning follows semantic versioning (SemVer) principles: Major version (X.0.0): Incompatible schema changes Minor version (0.X.0): Backward-compatible feature additions Patch version (0.0.X): Backward-compatible bug fixes Technical Support and Community For advanced technical discussions, algorithmic improvements, or collaborative research opportunities, please contact: Primary Maintainer: research@albumforge.com Technical Issues: github.com/albumforge/ecological-benchmark/issues Methodology Discussions: [Academic collaboration portal] Industry Partnerships: partnerships@albumforge.com Acknowledgments: This research was conducted using computational resources provided by AlbumForge (https://albumforge.com) under the Green Computing Initiative. …”

Table 1_Development of an alkaliptosis-related lncRNA risk model and immunotherapy target analysis in lung adenocarcinoma.docx by Xiang Xiong (1810234)

“…</p>Methods<p>The TCGA database was utilized to obtain RNA-seq-based transcriptome profiling data, clinical information, and mutation data. We conducted multivariate Cox regression analysis to identify alkaliptosis-related lncRNAs. …”

Methodology block diagram. by Gahao Chen (21688843)

“…Six machine learning algorithms - Random Forest (RF), AdaBoost, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Tabular Prior-data Fitted Network version 2.0 (TabPFN-V2) - were implemented with five-fold cross-validation to optimize model hyperparameters. …”

Dependent Random Partitions by Shrinking Toward an Anchor by David B. Dahl (11761055)

“…We show that our model provides better out-of-sample fit in a real data application. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.…”

Video 1_TDE-3: an improved prior for optical flow computation in spiking neural networks.mp4 by Matthew Yedutenko (5142461)

“…We conducted an in-depth quantitative investigation of optical flow coding with TDE and compared TDE-2 vs. TDE-3 in terms of energy efficiency and coding precision. …”

Info-graphics summarising how to navigate the field of AI in the form of a tube (metro) map. by Aidan Crilly (21743791)

“…The rules in this paper are ordered according to the flow of scientific explorations: Framing the scientific problem and finding AI algorithms (Zone 2), coding (Zone 3), and testing and interpreting results (Zone 4). …”

<b>Supplementary Materials for:</b> <b>Pan-Cancer Analysis Reveals LncRNA CDKN2B-AS1 as an Immune-Related Biomarker Validated in LIHC and ACC</b> by Dandan Lin (18192946)

“…This study comprehensively investigates the role of the long non-coding RNA CDKN2B-AS1 in cancer prognosis and tumor microenvironment across multiple cancer types using bioinformatic analyses.…”

Presentation1_Extrachromosomal circular DNAs in prostate adenocarcinoma: global characterizations and a novel prediction model.pdf by Qingliu He (12528332)

“…</p>Methods<p>Circular_seq was used in conjunction with the TCGA-PRAD transcriptome dataset to sequence, annotate, and filter for eccDNA-amplified differentially expressed coding genes (eDEGs) in PRAD and para-cancerous normal prostate tissues. …”

Table 1_A machine learning approach to healthcare needs and barriers using the 100% Community Survey of access to SDOH services.docx by Karikarn Chansiri (9303521)

“…</p>Methods<p>We analyzed survey data from 9,099 adults across 13 New Mexico counties (2019–2024). …”

Image 1_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.tif by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 9_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 6_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 3_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 7_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 10_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 2_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”