Supplementary file 3_Exploring the role of ferroptosis in pemphigus: identification of diagnostic markers and regulatory mechanisms.docx by Jing Mao (148640)

“…This study aims to investigate the expression patterns and potential biological functions of ferroptosis-related genes in pemphigus, as well as their regulatory mechanisms.…”

Table 2_Integration of single-cell sequencing and machine learning identifies key macrophage-associated genetic signatures in lumbar disc degeneration.xlsx by Hongxing Zhang (209372)

“…A panel of 101 machine learning algorithms was employed to screen diagnostic genes, with ROC curves used for validation. …”

Table 4_Integration of single-cell sequencing and machine learning identifies key macrophage-associated genetic signatures in lumbar disc degeneration.xlsx by Hongxing Zhang (209372)

“…A panel of 101 machine learning algorithms was employed to screen diagnostic genes, with ROC curves used for validation. …”

Table 3_Integration of single-cell sequencing and machine learning identifies key macrophage-associated genetic signatures in lumbar disc degeneration.xlsx by Hongxing Zhang (209372)

“…A panel of 101 machine learning algorithms was employed to screen diagnostic genes, with ROC curves used for validation. …”

Data Sheet 2_Integration of single-cell sequencing and machine learning identifies key macrophage-associated genetic signatures in lumbar disc degeneration.pdf by Hongxing Zhang (209372)

“…A panel of 101 machine learning algorithms was employed to screen diagnostic genes, with ROC curves used for validation. …”

Desmoke-LAP: Desmoking in Laparoscopic Surgery Dataset by Yirou Pan (22560914)

“…<p dir="ltr"><b>This is the publicly available dataset from robot-assisted laparoscopic hysterectomy surgery providing a benchmark for designing and validating smoke removal algorithms. </b> </p><h3><b>Overview</b></h3><p dir="ltr">The dataset contains frames and video clips from 10 robot-assisted laparoscopic hysterectomy procedure videos. …”

Collaborative research: CyberTraining: Implementation: Medium: Training users, developers, and instructors at the chemistry/physics/materials science interface by Francesco Paesani (5128004)

“…<p dir="ltr">Our research program focuses on two components.<br><br>Component 1: The training of students and researchers in computational tools and techniques is a significant challenge in the current educational system, which tends to prioritize analytical theory and experimental practice. …”

Table 2_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx by Zhiqiang Lin (747094)

“…MASH can be classified into two subtypes, cluster 1 and cluster 2, based on these feature genes. …”

Table 2_Identification and verification of biomarkers associated with neutrophils in acute myocardial infarction: integrated analysis of bulk RNA-seq, expression quantitative trait... by Guoqing Liu (93712)

“…Hub genes were screened using the least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms. A cellular model of AMI was established using oxygen- and glucose-deprived AC16 cells. …”

Image 2_Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer.jpeg by Ruoya Wang (842048)

“…Four high-risk independent prognostic factors (OAZ1, SRM, SMOX, and SMS) were validated as being upregulated in breast cancer tissues. …”

Image 3_Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer.jpeg by Ruoya Wang (842048)

“…Four high-risk independent prognostic factors (OAZ1, SRM, SMOX, and SMS) were validated as being upregulated in breast cancer tissues. …”

Table 2_Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer.xlsx by Ruoya Wang (842048)

“…Four high-risk independent prognostic factors (OAZ1, SRM, SMOX, and SMS) were validated as being upregulated in breast cancer tissues. …”

FCP dataset for forecasting temperature, PV, price, and load by Hanwen Zhang (18259666)

“…<p dir="ltr">Singapore aims to transform into a green and sustainable city by 2030. One of the key actions is to phase out Internal Combustion Engine (ICE) vehicles and significantly expand electric vehicle (EV) adoption. …”

IUTF Dataset(Enhanced): Enabling Cross-Border Resource for Analysing the Impact of Rainfall on Urban Transportation Systems by Xuhui Lin (19505503)

“…</p><h2>Data Structure</h2><p dir="ltr">The dataset is organized into four primary components:</p><ol><li><b>Road Network Data</b>: Topological representations including spatial geometry, functional classification, and connectivity information</li><li><b>Traffic Sensor Data</b>: Sensor metadata, locations, and measurements at both 5-minute and hourly resolutions</li><li><b>Precipitation Data</b>: Hourly meteorological information with spatial grid cell metadata</li><li><b>Derived Analytical Matrices</b>: Pre-computed structures for advanced spatial-temporal modelling and network analyses</li></ol><h2>File Formats</h2><ul><li><b>Tabular Data</b>: Apache Parquet format for optimal compression and fast query performance</li><li><b>Numerical Matrices</b>: NumPy NPZ format for efficient scientific computing</li><li><b>Total Size</b>: Approximately 2 GB uncompressed</li></ul><h2>Applications</h2><p dir="ltr">The IUTF dataset enables diverse analytical applications including:</p><ul><li><b>Traffic Flow Prediction</b>: Developing weather-aware traffic forecasting models</li><li><b>Infrastructure Planning</b>: Identifying vulnerable network components and prioritizing investments</li><li><b>Resilience Assessment</b>: Quantifying system recovery curves, robustness metrics, and adaptive capacity</li><li><b>Climate Adaptation</b>: Supporting evidence-based transportation planning under changing precipitation patterns</li><li><b>Emergency Management</b>: Improving response strategies for weather-related traffic disruptions</li></ul><h2>Methodology</h2><p dir="ltr">The dataset creation involved three main stages:</p><ol><li><b>Data Collection</b>: Sourcing traffic data from UTD19, road networks from OpenStreetMap, and precipitation data from ERA5 reanalysis</li><li><b>Spatio-Temporal Harmonization</b>: Comprehensive integration using novel algorithms for spatial alignment and temporal synchronization</li><li><b>Quality Assurance</b>: Rigorous validation and technical verification across all cities and data components</li></ol><h2>Code Availability</h2><p dir="ltr">Processing code is available at: https://github.com/viviRG2024/IUTDF_processing</p>…”