Aggregate Measurement Image in IPP. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.82 to 0.84. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.86 to 0.88. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.7 to 0.75. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.87 to 0.9. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.74 to 0.76. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen 1.55 to 1.60. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 1.70 to 1.75. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

Internal changes of the specimen of 0.89 to 1. by Nan Ru (9594384)

“…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …”

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. …”

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. …”

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

Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds by Gloria Castañeda-Valencia (20758502)

“…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …”

SRL OF TIM by Jefferson Rodrigo Speck (21510347)

“…</li><li><code><strong>plot_scripts/</strong></code>: Includes data files and Python scripts used to generate the visualizations presented in the review (e.g., bar charts, pie charts, distribution graphs).…”

<b>China’s naturally regenerated forests currently have greater aboveground carbon accumulation rates than newly planted forests</b> by Kai Cheng (18367101)

“…As well as, the Google earth engine code for detecting their ages and extents, python code for modelling the carbon accumulation rate of China’s PYF and NYF, python code for evaluating the influence of various factors on the patterns and differences in AGC accumulation rates between NYF and PYF in China.…”

MEG Dataset and Analysis Scripts for “The Effects of Task Similarity During Representation Learning in Brains and Neural Networks” by Nicholas Menghi (22426174)

“…</p><h3><b>Contents</b></h3><ul><li><b>MEG data</b> (results of the correlation between empirical and model matrices at different dimensionalities and domains)</li><li><b>Behavioral data</b> (behavioural accuracy performance: "Spatual Source Data")</li><li><b>Analysis script</b></li><li><b>Python package </b>developed to help with retrieving and computing simple operations</li></ul><h3><b>Data format</b></h3><p dir="ltr">Data are organized according to a structured folder layout (see <code>README.md</code> in the repository) and include:</p><ul><li><code>npy</code> MEG files (numpy)</li><li><code>.csv</code> behavioral files</li><li>Python scripts using MNE-Python for statistical analysis and visualization</li></ul><h3><b>Usage</b></h3><p dir="ltr">The provided scripts reproduce the statistical tests and figures presented in the manuscript. …”

dataset by Jingyi Chang (20404166)

“…<p dir="ltr">The R and Python code used to perform the analysis and generate the results and visualizations presented in the forest canopy height, and the related data and results produced in the research analyses.…”

Moulin distributions during 2016-2021 on the southwest Greenland Ice Sheet by Kang Yang (7323734)

“…</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.…”

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. …”