Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples by Derek Lam (11944213)

“…Image processing algorithms, implemented in Python using adaptive thresholding techniques, were applied to segment particles from the background. …”

Code and data for reproducing the results in the original paper of DML-Geo by Pengfei CHEN (8059976)

“…</p><p dir="ltr"><b>ridge_gwr.py</b>: Implementations of a modified Geographically Weighted Regression (GWR) with ridge regression</p><p dir="ltr"><b>ridge_sel_bw.py</b>: Implementations of a modified selector of band width in GWR with ridge regression</p><p dir="ltr"><b>scenario_manager.py</b>: Functions to create simulation scenarios</p><p dir="ltr"><b>utility.py</b>: Functions for testing spatial causal effects using different models and placebo tests for inference.…”

Image 1_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif by Xiaobing Li (291454)

“…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …”

Image 2_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif by Xiaobing Li (291454)

“…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …”

Core-Based Smart Sampling Framework: A Theoretical and Experimental Study on Randomized Partitioning for SAT Problems by DURGHAM QARALLEH (21904172)

“…We provide theoretical guarantees on complexity reduction and probabilistic completeness, apply the method to SAT instances, and evaluate its performance using experimental Python implementations. The results show that smart sampling drastically reduces the effective complexity of SAT problems and offers new insights into the structure of NP-complete problems.…”

RabbitSketch by tong zhang (20852432)

“…RabbitSketch achieves significant speedups compared to existing implementations, ranging from 2.30x to 49.55x.In addition, we provide flexible and easy-to-use interfaces for both Python and C++. …”

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. …”

Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games" by Krishnendu Chatterjee (15367413)

“…</p><p dir="ltr">To run each of the experiments, simply execute: <code>python3 [experiment file]</code> where <code>[experiment file]</code> is one of (ii), (iii) or (iv) from the above list.…”

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. …”

DA-Faster-RCNN code by Seunghyeon Wang (16500132)

“…<p dir="ltr">This repository provides the code used in the paper “Domain-Adaptive Faster R-CNN for Non-PPE Identification on Construction Sites from Body-Worn and General Images.” The implementation is written in Python using PyTorch and Detectron2.…”

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. …”

Spotted owl habitat quality maps and disturbance attribution analysis by Josh Barry (7573823)

“…Users may derive annual gains or losses in habitat quality from these layers and apply the provided ArcPython workflow (nest_fire_zonal_stats.py) to attribute change to specific disturbance drivers. …”

adnus by Mehmet Keçeci (14301782)

“…<p dir="ltr">adnus (AdNuS): Advanced Number Systems</p><p dir="ltr">adnus is a Python library that provides an implementation of various advanced number systems. …”

Mapping Policy Coherence in National UK Food Systems (2008– 2024): Analysing the Integration of Climate Change Mitigation and Adaptation Strategies, LEAP 2025 conference, Oxford by Ronja Teschner (20974180)

“…</p><p dir="ltr">This study aims to:</p><p dir="ltr">1) Identify and map UK national food policies regarding climate change mitigation and adaption strategies from 2008 - 2024.</p><p dir="ltr">2) Highlight departments responsible for publication, thematic areas addressed in the policies, policy objectives and implementation strategies.…”

Data files accompanying our PLoS One publication by Peter Hinow (21810605)

“…The videos were digitized and the positional data were saved in .xlsx or .csv format, respectively. The python codes contain the numerical implementations of our mathematical models.…”

World Heritage documents reveal persistent gaps between climate awareness and local action by Yang Chen (20756166)

“…The documents are sourced from publicly available official reports. The analysis section includes a GLM model implemented in R, along with evaluation tools such as correlation heatmaps, ICC agreement analysis, and MCC-based binary classification assessment. …”

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. …”

Automatic data reduction for the typical astronomer by Bradford Holden (21789524)

“…<p dir="ltr">The PypeIt data reduction pipeline (DRP) is a Python-based software package designed to transform “raw” spectroscopic data from an astronomical spectrometer into calibrated, science-ready products. …”

DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

“…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”

DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

“…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”