Demonstration of Isosteric Heat of Adsorption Calculation using AIFs and pyGAPs by Jack Evans (11275386)

“…</p><p dir="ltr">The calculation is performed using the Clausius-Clapeyron method as implemented in the <code><strong>pyGAPS</strong></code> Python library for adsorption science. …”

HCC Evaluation Dataset and Results by Jens-Rene Giesen (18461928)

“…</p><h3>Report Script</h3><p dir="ltr">On the top-level directory you find a <code>report.py</code> file, which is an executable Python script. …”

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

“…Raw and Processed Data</p> <p><br></p> <p>EEG brainwave recordings (raw and preprocessed signals)</p> <p><br></p> <p>Neurofeedback score datasets ( Neuron-Spectrum.NET )</p> <p><br></p> <p>Statistical analysis data (e.g., SPSS, MATLAB, or Python files)</p> <p><br></p> <p>Cognitive achievement test scores and student performance data</p> <p><br></p> <p><br></p> <p><br></p> <p>2. …”

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

“…Raw and Processed Data</p> <p><br></p> <p>EEG brainwave recordings (raw and preprocessed signals)</p> <p><br></p> <p>Neurofeedback score datasets ( Neuron-Spectrum.NET )</p> <p><br></p> <p>Statistical analysis data (e.g., SPSS, MATLAB, or Python files)</p> <p><br></p> <p>Cognitive achievement test scores and student performance data</p> <p><br></p> <p><br></p> <p><br></p> <p>2. …”

The artifacts and data for the paper "DD4AV: Detecting Atomicity Violations in Interrupt-Driven Programs with Guided Concolic Execution and Filtering" (OOPSLA 2025) by zixuan yuan (17602152)

“…</li><li><ul><li><code><strong>DBDS</strong></code>: The code implements our proposed dynamic scheduling execution method, which systematically explores task interleaving for atomicity violation detection, enhanced by an effective prefix-directed strategy.…”

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

“…</p><p dir="ltr">The Python programming source code used to run the calculation of ET0 and AI is provided and available online on Figshare at:</p><p dir="ltr">https://figshare.com/articles/software/Global_Aridity_Index_and_Potential_Evapotranspiration_Climate_Database_v3_-_Algorithm_Code_Python_/20005589</p><p dir="ltr">Peer-Review Reference and Proper Citation:</p><p dir="ltr">Zomer, R.J.; Xu, J.; Trabuco, A. 2022. …”

Gene Editing using Transformer Architecture by Rishabh Garg (5261744)

“…</p><p dir="ltr">Once TASAG detects a deviation from a reference sequence (e.g., the H-Bot sequence), it facilitates on-screen gene editing, enabling targeted mutations or the insertion of desired genes. Implementation requires Python and deep learning frameworks like TensorFlow or PyTorch, with optional use of Biopython for genetic sequence handling. …”

Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i> by Hao Chen (20313552)

“…</p><p dir="ltr">The dataset includes:</p><ol><li>Raw locomotor activity measurements (.txt files) with 1-minute resolution</li><li>Breeding experiment data (Pair_breeding.csv) documenting nest IDs, population sources, photoperiod treatments, and breeding success</li><li>Activity measurement metadata (Loc_metadataset.csv) containing detailed experimental parameters and daily activity metrics extracted using tsfresh</li></ol><p dir="ltr">The repository also includes complete analysis pipelines implemented in both Python (3.8.8) and R (4.3.1), featuring:</p><ul><li>Data preprocessing and machine learning model development</li><li>Statistical analyses</li><li>Visualization scripts for generating Shapley plots, activity pattern plots, and other figures</li></ul><p></p>…”

Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2) by Tahir Bhatti (20961974)

“…Full source code and version details are available upon request.…”

Probabilistic-QSR-GeoQA by Mohammad Kazemi (19442467)

“…<p dir="ltr">The code and data are related to the paper Mohammad Kazemi Beydokhti, Matt Duckham, Amy L. …”

MCCN Case Study 3 - Select optimal survey locality by Donald Hobern (21435904)

“…</p><p dir="ltr">The dataset contains input files for the case study (source_data), RO-Crate metadata (ro-crate-metadata.json), results from the case study (results), and Jupyter Notebook (MCCN-CASE 3.ipynb)</p><h4><b>Research Activity Identifier (RAiD)</b></h4><p dir="ltr">RAiD: https://doi.org/10.26292/8679d473</p><h4><b>Case Studies</b></h4><p dir="ltr">This repository contains code and sample data for the following case studies. …”

Supplement Number 1 by Susama Agarwala (21628328)

“…Python files containing the implementation of the graphical calculus on generalized Wilson loop diagrams…”

Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis by Alan Glanz (22109698)

“…</p><p dir="ltr">Genosophus addresses this gap by offering:</p><ul><li>A <b>quantitative diagnostic toolkit</b> for internal model health</li><li>A <b>framework for detecting emergent structure</b></li><li>A <b>method to measure phase transitions, collapse, or stabilization</b></li><li>A <b>model-agnostic system for embedding-space dynamics</b></li></ul><p dir="ltr">This tool is intended for use in interpretability research, safety evaluations, representation studies, and monitoring model behavior during training or fine-tuning.</p><h2><b>Included Files</b></h2><h3><b>1. </b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.…”

NanoDB: Research Activity Data Management System by Lorenci Gjurgjaj (19702207)

“…In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …”

<b>Data Availability</b> by Bonyad Ahmadi (20750327)

“…</p><p dir="ltr">python scripts documenting the implementation of the Mixture Density Network (MDN) algorithm, including hyperparameter tuning and uncertainty quantification.…”

<b>Data Availability</b> by Bonyad Ahmadi (20750327)

“…</p><p dir="ltr">python scripts documenting the implementation of the Mixture Density Network (MDN) algorithm, including hyperparameter tuning and uncertainty quantification.…”

face recognation with Flask by Muammar, SST, M.Kom (21435692)

“…Built using the <b>Flask</b> web framework (Python), this system provides a lightweight and scalable solution for implementing facial recognition capabilities in real-time or on-demand through a browser interface.…”

Supervised Classification of Burned Areas Using Spectral Reflectance and Machine Learning by Baptista Boanha (22424668)

“…Six Python scripts are provided, each implementing a distinct machine learning algorithm—Random Forest, k-Nearest Neighbors (k-NN), Multi-Layer Perceptron (MLP), Decision Tree, Naïve Bayes, and Logistic Regression. …”

IGD-cyberbullying-detection-AI by Bryan James (19921044)

“…</p><h2>Requirements</h2><p dir="ltr">To run this code, you'll need the following dependencies:</p><ul><li>Python 3.x</li><li>TensorFlow</li><li>scikit-learn</li><li>pandas</li><li>numpy</li><li>matplotlib</li><li>imbalanced-learn</li></ul><p dir="ltr">You can install the required dependencies using the provided <code>requirements.txt</code> file.…”

Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event by Thomas Clemens Carmine (19756929)

“…Includes imputation statistics, data dictionary, and the Python imputation code (Imputation_Air_Pollutants_NABEL.py). …”