The results of OLS model. by Pengfei Yu (680800)

“…<div><p>This paper examines the spatial distribution pattern and influencing factors of Martial Arts Schools (MASs) based on Baidu map data and Geographic Information System (GIS) in China. Using python to obtain the latitude and longitude data of the MASs through Baidu Map API, and with the help of ArcGIS (10.7) to coordinate information presented on the map of China. …”

Regional regression parameters of GWR model. by Pengfei Yu (680800)

“…<div><p>This paper examines the spatial distribution pattern and influencing factors of Martial Arts Schools (MASs) based on Baidu map data and Geographic Information System (GIS) in China. Using python to obtain the latitude and longitude data of the MASs through Baidu Map API, and with the help of ArcGIS (10.7) to coordinate information presented on the map of China. …”

<b>AutoMated tool for Antimicrobial resistance Surveillance System version 3.1 (AMASS3.1)</b> by Chalida Rangsiwutisak (10501496)

“…;</li><li><i>Enterococcus</i> <i>faecalis</i> and <i>E. faecium</i> have been explicitly included in the pathogens under the survey (while <i>Enterococcus</i> spp. are used in the AMASS version 2.0);</li><li>We have added a few antibiotics in the list of antibiotics for a few pathogens under the survey;</li></ol><p dir="ltr">Technical aspects</p><ol><li>We have added a configuration for “Annex C: Cluster signals” in Configuration.xlsx;</li><li>We have improved the algorithm to support more several date formats;</li><li>We have improved the algorithm to translate data files;</li><li>We have improved Data_verification_logfile report to present local languages of the variable names and values (according to how they were recorded in the data files) in the report;</li><li>We have improved Annex B: Data indicators to support a larger data set;</li><li>We have used only Python rather than R + Python (as used in the AMASSv2.0);</li><li>We have set a default config for infection origin stratification by allowing a specimen collected two calendar days before the hospital admission date and one day after the hospital discharge date into consideration. …”

Predicting coding regions on unassembled reads, how hard can it be? - Genome Informatics 2024 by Amanda Clare (98717)

“…Predictions are made on the set of reads, using several prediction tools. The locations and directions of the predictions on the reads are then combined with the information about locations and directions of the reads on the genome using Python code to produce detailed results regarding the correct, incorrect and alternative starts and stops with respect to the genome-level annotation.…”

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. …”

Code and data for evaluating oil spill amount from text-form incident information by Yiming Liu (18823387)

“…The code is written in Python and operated using Jupyter Lab and Anaconda. …”

Workflow of T cell activation analysis. by Yitong Ma (8144697)

Evaluation and Statistical Analysis Code for "Multi-Task Learning for Joint Fisheye Compression and Perception for Autonomous Driving" by Basem Ahmed (18127861)

“…</li></ul><p dir="ltr">These scripts are implemented in Python using the PyTorch framework and are provided to ensure the reproducibility of the experimental results presented in the manuscript.…”

Code for the HIVE Appendicitis prediction modelRepository with LLM_data_extractor_optuna for automated feature extraction by Anoeska Schipper (18513465)

“…</p><p dir="ltr"><b>LLM Data Extractor optuna repo</b> is a Python framework for generating and evaluating clinical text predictions using large language models (LLMs) like <code>qwen2.5</code>. …”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…The <b>innovations</b> and <b>steps</b> in Case 3, including data download, sample generation, and parallel computation optimization, were independently developed and are not dependent on the GeoCube’s code.</p><h2>Requirements</h2><p dir="ltr">The codes use the following dependencies with Python 3.8</p><ul><li>torch==2.0.0</li><li>torch_geometric==2.5.3</li><li>networkx==2.6.3</li><li>pyshp==2.3.1</li><li>tensorrt==8.6.1</li><li>matplotlib==3.7.2</li><li>scipy==1.10.1</li><li>scikit-learn==1.3.0</li><li>geopandas==0.13.2</li></ul><p><br></p>…”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…The <b>innovations</b> and <b>steps</b> in Case 3, including data download, sample generation, and parallel computation optimization, were independently developed and are not dependent on the GeoCube’s code.</p><h2>Requirements</h2><p dir="ltr">The codes use the following dependencies with Python 3.8</p><ul><li>torch==2.0.0</li><li>torch_geometric==2.5.3</li><li>networkx==2.6.3</li><li>pyshp==2.3.1</li><li>tensorrt==8.6.1</li><li>matplotlib==3.7.2</li><li>scipy==1.10.1</li><li>scikit-learn==1.3.0</li><li>geopandas==0.13.2</li></ul><p><br></p>…”

Flowchart describing the AI-LES program. by Evan Mitchell (20995743)

“…In this article, we present a proof-of-concept Python program that leverages artificial intelligence (AI) tools (specifically, ChatGPT) to parse a batch of journal articles and extract relevant results, greatly reducing the human time investment in this action without compromising on accuracy. …”

Quetzal: Comprehensive Peptide Fragmentation Annotation and Visualization by Eric W. Deutsch (13887)

“…We describe how Quetzal annotates spectra using the new Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) mzPAF standard for fragment ion peak annotation, including the Python-based code, a web-service end point that provides annotation services, and a web-based application for annotating spectra and producing publication-quality figures. …”

Quetzal: Comprehensive Peptide Fragmentation Annotation and Visualization by Eric W. Deutsch (13887)

“…We describe how Quetzal annotates spectra using the new Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) mzPAF standard for fragment ion peak annotation, including the Python-based code, a web-service end point that provides annotation services, and a web-based application for annotating spectra and producing publication-quality figures. …”

Data Sheet 1_COCαDA - a fast and scalable algorithm for interatomic contact detection in proteins using Cα distance matrices.pdf by Rafael Pereira Lemos (9104911)

“…Here, we introduce COCαDA (COntact search pruning by Cα Distance Analysis), a Python-based command-line tool for improving search pruning in large-scale interatomic protein contact analysis using alpha-carbon (Cα) distance matrices. …”

Research Data and Code on Characteristics and Drivers of Plant Diversity in Viaduct Footprint Spaces of a Mountainous, High-Density City—A Case Study of Central Chongqing by Junjie Zhang (355622)

“…</li><li>Derived data including calculated plant diversity metrics and environmental factor data.</li><li>R and python code used for statistical analysis.</li></ul><p dir="ltr">Data collection was conducted through on-site field surveys in the central urban area of Chongqing, China, from April to October 2024.…”

Anisotropic Skyrmion and Multi-<i>q </i>Spin Dynamics in Centrosymmetric Gd₂PdSi₃: Data and Code by Matjaž Gomilšek (14278739)

“…Python script file<br>*.dat, [no extension] ... ASCII data file. …”

M-SGWR model by M. Naser Lessani (17817475)

“…The repo contains all the necessary information, including the python code "M-SGWR", datasets and the instruction of how to reproduce the results presented in the article. …”

Data and analysis code for manuscript "Preparations for ultra-high dose rate 25-90 MeV electron irradiation experiments with a compact, high-peak-current, X-band linear accelerator... by Haytham Effarah (11979509)

“…</p><p dir="ltr">The environment.yml file can create a conda virtual environment named "prep4vhee" with the required Python version and dependencies using the following conda command:</p><pre>conda env create -f environment.yml<br></pre><p dir="ltr">TOPAS input decks are also included in some folders with seeds set to reproduce Monte Carlo simulation results presented in the manuscript. …”