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. …”

Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil) by Amanda Bueno de Moraes (22559249)

“…The code implements a statistical–computational workflow for parameter selection (VIF, Bartlett and KMO tests, PCA and FA with <i>varimax</i>) and then trains and evaluates machine-learning models to predict three key physico-chemical indicators: turbidity, true color, and total iron. …”

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. …”

Collaborative Research: Framework: Improving the Understanding and Representation of Atmospheric Gravity Waves using High-Resolution Observations and Machine Learning by Joan Alexander (17047170)

“…Establishing a framework for implementing and testing ML-based parameterizations in atmospheric models. …”

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

“…The included Python scripts simulate a low-RAM cosmological oscillator that evolves through successive nonsingular “bounces,” demonstrating a self-consistent cyclic universe in which curvature, tension, and entropy reset in finite, periodic intervals. …”

Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model by Marina Diachenko (19739092)

“…</p><p dir="ltr">All data are available upon request. The standalone Python implementation of the fE/I algorithm is available under a CC-BY-NC-SA license at <a href="https://github.com/arthur-ervin/crosci" target="_blank">https://github.com/arthur-ervin/crosci</a>. …”

Dataset for: Phylotranscriptomics reveals the phylogeny of Asparagales and the evolution of allium flavor biosynthesis, Nature Communications，DOI：10.1038/s41467-024-53943-6 by Xiao-Xiao Wang (2447920)

“…Extract homologs for all the 501 samples</p><p dir="ltr"><i>python2 blast_to_mcl.py all.rawblast 0.25 >mcl_all_rawblast_out_nohup_out_0.25</i></p><p dir="ltr"><i>mcl mcl_all_rawblast_out_nohup_out_0.25 --abc -te 80 -tf 'gq(5)' -I 1.5 -o hit-frac0.25_I1.5_e5</i></p><p dir="ltr"><i>python2 write_fasta_files_from_mcl.py all.fa hit-frac0.25_I1.5_e5 minimal_taxa outDIR</i></p><p><br></p><p dir="ltr"><b>Step 5: Build Maximum likelihood tree for each homolog group</b></p><p dir="ltr"><i>python2 fasta_to_tree_pxclsq.py fasta_dir number_cores dna bootstrap(y)</i></p><p><br></p><p dir="ltr"><b>Step 6: Extract ortholog groups</b></p><p dir="ltr">Instead of 1to1, MI, RT, or MO methods in Ya et al. (2014), we used a revised version of DISCO (https://github.com/JSdoubleL/DISCO) to infer homologs. …”

Core data by Baoqiang Chen (21099509)

“…</p><p><br></p><p dir="ltr">For the 5′ UTR library, we developed a Python script to extract sequences and Unique Molecular Identifiers (UMIs) from the FASTQ files. …”

Landscape Change Monitoring System (LCMS) Conterminous United States Cause of Change (Image Service) by U.S. Forest Service (17476914)

“…Reference data are collected using TimeSync, a web-based tool that helps analysts visualize and interpret the Landsat data record from 1984-present (Cohen et al., 2010).Outputs fall into three categories: change, land cover, and land use. …”

A Structured Attempt at a Polynomial-Time Solution to the Subset Sum Problem and Its Implications for P vs NP by MInakshi Aggarwal (21677633)

“…The manuscript includes theoretical formulation, Python implementation, verified output snapshots, and detailed analysis — aimed at opening fresh discourse on the P vs NP question. …”

Soulware-Lite by Abhiram Gnyanijaya (21572942)

“…</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. …”

Leue Modulation Coefficients (LMC): A Smooth Continuum Embedding of Bounded Arithmetic Data by Jeanette Leue (22470409)

“…This Zenodo package includes: the full research paper (PDF), a complete Python implementation generating the LMC field and conductivity model, a numerical plot comparing discrete LMC values with the smoothed continuum field, a cover letter and supporting documentation. …”

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. …”

Comprehensive Fluid and Gravitational Dynamics Script for General Symbolic Navier-Stokes Calculations and Validation by Stylianos Touloumidis (19938747)

“…It provides a flexible foundation on which theoretical assumptions can be validated, and practical calculations performed. Implemented in Python with symbolic calculations, the script facilitates in-depth analysis of complex flow patterns and makes advanced mathematical computations more accessible. …”

Contrast enhancement of digital images using dragonfly algorithm by Soumyajit Saha (19726163)

“…The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”

Compiled Global Dataset on Digital Business Model Research by Dimas Fauzan Aryadefa (22123186)

“…</p><p dir="ltr">For the modeling component, annual publication growth is projected from 2025–2034 using a logistic growth model (S-curve) implemented in Python. …”

Knowledge Graph validation using SHACL Shapes by Ángel Iglesias Préstamo (19745767)

“…Leveraging Rust’s performance and safety features, rudof provides efficient validation tools and Python bindings for integration with data science workflows. …”

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.…”

ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation by Hong Zhu (109912)

“…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”

ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation by Hong Zhu (109912)

“…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”