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<b>Altered cognitive processes shape tactile perception in autism.</b> (data)
Published 2025“…The perceptual decision-making setup was controlled by Bpod (Sanworks) through scripts in Python (PyBpod, https://pybpod.readthedocs.io/en/latest/). …”
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Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1
Published 2025“…</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. …”
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Global Research Dataset on Social Media in Entrepreneurial Startup (2009–2024)
Published 2025“…Analytical outputs are organized into multiple formats: CSV files for raw bibliometric data; PNG images for thematic maps, trend topic visualizations, and research flowcharts; and CSV and PNG outputs for annual publication trajectories and polynomial regression-based modeling projections. Visualization and analysis were conducted using Microsoft Excel for summary statistics, R Biblioshiny for thematic and trend mapping, and Python for projection modeling.…”
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Data Sheet 1_Establishing a real-time biomarker-to-LLM interface: a modular pipeline for HRV signal acquisition, processing, and physiological state interpretation via generative A...
Published 2025“…</p>Discussion<p>This system represents an early prototype of bioadaptive AI, in which physiological signals are incorporated as part of the model's input context.…”
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Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout.
Published 2025“…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …”
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MYCroplanters can quantify the interaction between pathogenic and non-pathogenic bacteria and their effects on plant health.
Published 2025“…(e) Figure showing data from (d) converted into binary health/disease scores. Each dot represents a single plant. Black lines with ribbons are Bayesian model predictions with 95% prediction intervals, respectively. …”
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GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios
Published 2025“…Here, <i>Genus</i> represents the rodent genus, <i>GCM</i> denotes the global climate model used, <i>Year</i> specifies the projected time period, <i>SSP-RCP</i> indicates the shared socioeconomic pathway and representative concentration pathway, and <i>Statistics</i> describes the file’s data characteristics. …”
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Overview of generalized weighted averages.
Published 2025“…GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…”
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<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043)
Published 2025“…In total, 75 % of the labelled observations were assigned to train and 25 % to test the model. To evaluate the model performance, the root mean squared root error (RMSE, the standard deviation of the residuals that represents the mean difference between the prediction and the real value for the test set) and <i>R</i><sup>2</sup> were used, which was calculated using r2_score() from <i>Scikit-learn</i> metrics. …”
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Overview of deep learning terminology.
Published 2024“…This paper introduces the geodl R package, which supports pixel-level classification applied to a wide range of geospatial or Earth science data that can be represented as multidimensional arrays where each channel or band holds a predictor variable. geodl is built on the torch package, which supports the implementation of DL using the R and C++ languages without the need for installing a Python/PyTorch environment. …”
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Missing and Unaccounted-for People in Mexico (1960s–2025)
Published 2025“…</li><li><b>Requirements File:</b> A <code>requirements.txt</code> file listing the necessary Python libraries to run the script seamlessly.…”
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<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b>
Published 2025“…</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 .…”
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Moulin distributions during 2016-2021 on the southwest Greenland Ice Sheet
Published 2025“…</p><p><br></p><ul><li>00_Satellite-derived moulins: Moulins directly mapped from Sentinel-2 imagery, representing actual moulin positions;</li><li>01_Snapped moulins: Moulins snapped to DEM-modeled supraglacial drainage networks, primarily used for analyses;</li><li>02_Moulin recurrences: Recurring moulins determined from the snapped moulins;</li><li>03_Internally drained catchments: Internally drained catchment (IDC) associated with each moulin;</li><li>04_Surface meltwater runoff: surface meltwater runoff calculated from MAR for the study area, elevation bins, and IDCs; </li><li>05_DEM-derived: Topographic features modeled from ArcticDEM, including elevation bins, depressions and drainage networks;</li><li>06_GWR: Variables for conducting geographically weighted regression (GWR) analysis;</li></ul><p><br></p><ul><li>Code_01_Mapping moulins on the southwestern GrIS.ipynb: A Jupyter Notebook to analyze moulin distributions, reproducing most of the analyses and figures presented in the manuscript using the provided datasets;</li><li>Code_02_pre1_calculate Strain Rate from XY ice velocity.py: A preprocessing Python script to calculate strain rate for the GWR analysis;</li><li>Code_02_pre2_calculate Driving Stress from ice thickness and surface slope.py: A preprocessing Python script to calculate driving stress for the GWR analysis;</li><li>Code_02_GWR analysis.ipynb: A Jupyter Notebook to conduct the GWR analysis using the provided datasets.…”
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Social media images of China's terraces
Published 2025“…Geo-tagged images were collected using Weibo cookies and Python-based scraping tools (available at: https://github.com/dataabc/weibo-search). …”
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CpG Signature Profiling and Heatmap Visualization of SARS-CoV Genomes: Tracing the Genomic Divergence From SARS-CoV (2003) to SARS-CoV-2 (2019)
Published 2025“…Heatmap Generation</p><p dir="ltr">Tools :</p><p dir="ltr">Heatmaps were generated using Python's seaborn library (sns.heatmap) and matplotlib for visualization.…”
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Supplementary material for "Euler inversion: Locating sources of potential-field data through inversion of Euler's homogeneity equation"
Published 2025“…</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. …”
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<b>Dataset for manuscript: </b><b>Phylogenetic and genomic insights into the evolution of terpenoid biosynthesis genes in diverse plant lineages</b>
Published 2025“…</p><p dir="ltr"> 'boxplot.py': This script is executed in Visual Studio Code, using Python 3.10.4 as the runtime environment.…”