GeoGraphNetworks: Shapefile-Derived Datasets for Accurate and Scalable Graphical Representations by Harish Sharma (18881935)

“…The rail line infrastructure of the USA is represented as a single network that covers the entire country and includes connectivity to Canada. …”

Missing and Unaccounted-for People in Mexico (1960s–2025) by Montserrat Mora (20430644)

“…</li><li><b>Requirements File:</b> A <code>requirements.txt</code> file listing the necessary Python libraries to run the script seamlessly.…”

Physiotherapist-Assisted Wrist Movement Protocol for EEG-Based Corticokinematic Coherence Assessment by Fanni Kovács (21733838)

“…</li></ol><h4><b>Movement File Structure</b></h4><p dir="ltr">Each entry contains:</p><ul><li><code><strong>time</strong></code>: a 32-bit unsigned integer indicating the timestamp in milliseconds,</li><li><code><strong>x</strong></code>, <code><strong>y</strong></code>, <code><strong>z</strong></code>: 16-bit signed integers representing acceleration along the respective axes,</li><li><code><strong>trigger</strong></code>: an 8-bit unsigned integer used to mark event-related triggers for synchronization with the EEG data (e.g., movement onset).…”

Cognitive Fatigue by Rui Varandas (11900993)

“…<br></p><p dir="ltr"><b>HCI features</b> encompass keyboard, mouse, and screenshot data. Below is a Python code snippet for extracting screenshot files from the screenshots CSV file.…”

Multisession fNIRS-EEG data of Post-Stroke Motor Recovery: Recordings During Intact and Paretic Hand Movements by Aleksandra Medvedeva (21221383)

“…The fNIRS .snirf files are accompanied by event files as .txt tables, containing arrays of event timestamps and corresponding event codes. The code for signal reading, preprocessing, and epoching is provided with the dataset in the “Preprocessing” file. …”

Digital Twin for Chemical Sciences by Jin Qian (19339035)

“…The procedure for generating data in Figure 3 can be found in the demo notebook in Supplementary Code. The procedure for generating data of Figure 4 has been uploaded in fig4_figshare.zip file. …”

Sonification of Warming Stripes by Christopher Harrison (9448751)

“…The sonification was produced using the STRAUSS sonification Python package.</p><p dir="ltr">Here we release:<br>1. …”

Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx by Piyachat Udomwong (22563212)

“…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…”

Supplementary material for "Euler inversion: Locating sources of potential-field data through inversion of Euler's homogeneity equation" by Leonardo Uieda (97471)

“…</p><h2>License</h2><p dir="ltr">All Python source code (including <code>.py</code> and <code>.ipynb</code> files) is made available under the MIT license. …”

Sonification of Growing Black Hole by Rose Shepherd (20328444)

“…We used the open source Python package STRAUSS to produce the sonification (Trayford and Harrison 2023). …”

<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> by Shubham Pawar (22471285)

“…</p><p dir="ltr"><b>Input:</b></p><ul><li><code>svi_module/svi_data/svi_info.csv</code> - Image metadata from Step 1</li><li><code>perception_module/trained_models/</code> - Pre-trained models</li></ul><p dir="ltr"><b>Command:</b></p><pre><pre>python -m perception_module.pred \<br> --model-weights .…”

Minami_etal_2025 by Keiichi Mochida (4670800)

“…<h2>Code files related to Minami et al (2025)</h2><p dir="ltr">accession_plot.py:Python script used to generate Fig4a.…”

Genomic Epidemiology of SARS-CoV-2 in Peru from 2020 to 2024 by Pablo Tsukayama (22614461)

“…</p><p dir="ltr"><b>Contents:</b></p><p><b>1. Analysis Code</b></p><p>Core Python scripts used to curate metadata, process genomic data, perform lineage assignments, compute summary statistics, and prepare inputs for downstream phylogenetic and phylogeographic analyses. …”

Tracking when the number of individuals in the video frame changes. by Hirotsugu Azechi (20700528)

“…The removal of unnecessary keypoint data is achieved through a Python code that allows specified ranges of tracking data obtained from DeepLabCut to be rewritten as NaN (no data) (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s019" target="_blank">S1 Protocol</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s010" target="_blank">S10C Fig</a>). …”

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

“…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…”

Satellite monitoring of Greenland wintertime buried lake drainage by Jianing Wei (22400896)

“…Buried_lake_drainage_code</p><p dir="ltr">This folder contains two Python Jupyter Notebooks for detecting wintertime buried lake drainages (BLDs). …”

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. …”

CpG Signature Profiling and Heatmap Visualization of SARS-CoV Genomes: Tracing the Genomic Divergence From SARS-CoV (2003) to SARS-CoV-2 (2019) by Tahir Bhatti (20961974)

“…</p><p dir="ltr">Heatmap Images :</p><p dir="ltr">Heatmaps for CpG counts and O/E ratios comparing Wuhan-Hu-1 with its closest and most distant relatives.</p><p dir="ltr">Python Script :</p><p dir="ltr">Full Python code used for data processing, distance calculation, and heatmap generation.…”

Table 1_Analysis of distribution equilibrium and influencing factors for older adult meal service facilities in mainland China.xlsx by Feng Wang (44414)

“…Objective<p>Analyze the distribution equilibrium of older adult meal service facilities in mainland China and explore the factors influencing their distribution.</p>Methods<p>Use Python to obtain data on older adult meal service facilities, and analyze the equity of older adult meal services using descriptive statistics, the Lorenz curve, the Gini coefficient, and the Spatial Mismatch Index (SMI). …”

JASPEX model by Olugbenga OLUWAGBEMI (21403187)

“…</p><p dir="ltr">We wrote new sets of python codes and developed python programming codes to rework on the map to generate the coloured map of Southwest Nigeria from the map of Nigeria (which represented the region of our study). …”