Concurrent spin squeezing and field tracking with machine learning by Junlei Duan (18393642)

“…Randomly signal generating codeb.Deep learning codec.data pre-processing code The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”

Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 by Jordan Waters (21620558)

“…<br><br><br><b>ORCID ID: https://orcid.org/0009-0009-0793-8089</b><br></p><p dir="ltr"><b>Code Availability:</b></p><p dir="ltr"><b>All Python tools used for GoP simulations and predictions are available at:</b></p><p dir="ltr"><b>https://github.com/Jwaters290/GoP-Probabilistic-Curvature</b><br><br>The Gravity of Probability framework is implemented in this public Python codebase that reproduces all published GoP predictions from preexisting DESI data, using a single fixed set of global parameters. …”

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). …”

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.…”

Gene Editing using Transformer Architecture by Rishabh Garg (5261744)

“…., 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. …”

Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds by Gloria Castañeda-Valencia (20758502)

“…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …”

Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection by Huichao Yin (14589020)

“…<p dir="ltr">Python image preprocessing and model implementation for research of "Deep Learning-Based Visual Enhancement and Real-Time Underground-Mine Water Inflow Detection".…”

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

“…</p><p dir="ltr">Reproducibility Resources:</p><p dir="ltr">Python scripts for reproducing figures, preprocessing data, and training machine learning models (SVM, MLP, XGB, BRR, KRR).…”

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

“…</p><p dir="ltr">Reproducibility Resources:</p><p dir="ltr">Python scripts for reproducing figures, preprocessing data, and training machine learning models (SVM, MLP, XGB, BRR, KRR).…”

Supplementary Material by Aris Shahbazian (22464325)

“…The supplementary material includes the full Python-based implementation of the AI-driven optimization framework described in the manuscript. …”

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

“…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. 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. …”

Bayesian Changepoint Detection via Logistic Regression and the Topological Analysis of Image Series by Andrew M. Thomas (712104)

“…The method also successfully recovers the location and nature of changes in more traditional changepoint tasks. An implementation of our method is available in the Python package bclr.…”

A Fully Configurable Open-Source Software-Defined Digital Quantized Spiking Neural Core Architecture by Nagarajan Kandasamy (8400168)

“…QUANTISENC’s software-defined hardware design methodology allows the user to train an SNN model using Python and evaluate performance of its hardware implementation, such as area, power, latency, and throughput. …”

Fast, FAIR, and Scalable: Managing Big Data in HPC with Zarr by Alfonso Ladino (21447002)

“…</p><p dir="ltr">In this work, we apply the scientific datacube model to the transformation of large-scale radar datasets from Colombia and the U.S. …”

PTPC v1.0 Numerical Baseline: Stable Multi-Bounce Cosmology Simulation by David Lewis Stewart Parry (22188211)

“…PTPC v1.0 Numerical Baseline: Stable Multi-Bounce Cosmology Simulation This release provides the complete, reproducible numerical implementation of the Parry Tensional Phase Collapse (PTPC) model — the dynamic core of the Universal Heartbeat Theory (UHT/PTPC). …”

MSc Personalised Medicine at Ulster University by Steven Watterson (100045)

“…</b> Introducing computational approaches to studying genes, proteins or metabolites, this module teaches Python coding, data analysis and how to work with the databases that support data analysis.…”

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by Andrew Rogers (17623239)

“…</p><h2>Software and Spatial Resolution</h2><p dir="ltr">The VRE siting model is implemented using Python and relies heavily on ArcGIS for comprehensive spatial data handling and analysis.…”

Soulware-Lite by Abhiram Gnyanijaya (21572942)

“…It supports OpenAI GPT-4, Anthropic Claude, Google Gemini, Meta LLaMA, and other open-source models.</p><p><br></p><p dir="ltr">Soulware-Lite is the first live implementation of a cognitive conscience layer, born from architectural failures in AI output hallucination and anchored by integrity principles like MAP/ARP and RDIP. …”

Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”

Table 2_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”