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.…”

Concurrent spin squeezing and field tracking with machine learning by Junlei Duan (18393642)

“…Randomly signal generating codeb.Deep learning codec.data pre-processing code The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”

Image 1_An explainable analysis of depression status and influencing factors among nursing students.png by Yingying Li (50341)

“…Data cleaning was performed in Excel, and statistical analyses were conducted using SPSS Statistics version 27.0 and Python 3.9.</p>Results<p>The incidence of depression among nursing students is 28.60%. …”

<b>IEEE 14 bus test systems row data </b> by meysam shahriyari (22599314)

“…Each row in the dataset represents one simulated case, and each column corresponds to an input feature used in the deep learning model.…”

Indirect Reciprocity and the Evolution of Prejudicial Groups by Gualtiero Colombo (19078925)

“…This is conducted through an agent based model over a population of agents that interact through a `donation game' in which resources are donated to third parties at a cost without receiving a direct benefit. …”

Summary of Tourism Dataset. by Jing Zhang (23775)

“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”

Segment-wise Spending Analysis. by Jing Zhang (23775)

“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”

Hyperparameter Parameter Setting. by Jing Zhang (23775)

“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”

Marketing Campaign Analysis. by Jing Zhang (23775)

“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”

Visitor Segmentation Validation Accuracy. by Jing Zhang (23775)

“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”

Integration of VAE and RNN Architecture. by Jing Zhang (23775)

“…The proposed TourVaRNN integrates variational autoencoders to capture latent variables representing visitor preferences and spending habits, while recurrent neural networks model complex temporal dependencies in tourism data. …”

6. Motif Code Theory by William Terry (22279591)

“…<p dir="ltr">The Motif Code Theory (MCT) simulation code, mct_unified_code.py, is a Python 3.9 script that models the universe as a time-dependent directed multigraph G(t) = (V(t), E(t)) with N=10^7 vertices (representing quantum fields/particles) and edges (interactions). …”

Neural-Signal Tokenization and Real-Time Contextual Foundation Modelling for Sovereign-Scale AGI Systems by Lakshit Mathur (20894549)

“…</p><p dir="ltr"><b>Availability</b> — The repository includes LaTeX sources, trained model checkpoints, Python/PyTorch code, and synthetic datasets. Data are released under a Creative Commons Attribution-NonCommercial-4.0 (CC BY-NC 4.0) license; code under MIT License.…”

Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil) by Amanda Bueno de Moraes (22559249)

“…The code implements a statistical–computational workflow for parameter selection (VIF, Bartlett and KMO tests, PCA and FA with <i>varimax</i>) and then trains and evaluates machine-learning models to predict three key physico-chemical indicators: turbidity, true color, and total iron. …”

Missing Value Imputation in Relational Data Using Variational Inference by Simon Fontaine (7046618)

“…Additional results, implementation details, a Python implementation, and the code reproducing the results are available online. …”

Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i> by Hao Chen (20313552)

“…</p><p dir="ltr">The dataset includes:</p><ol><li>Raw locomotor activity measurements (.txt files) with 1-minute resolution</li><li>Breeding experiment data (Pair_breeding.csv) documenting nest IDs, population sources, photoperiod treatments, and breeding success</li><li>Activity measurement metadata (Loc_metadataset.csv) containing detailed experimental parameters and daily activity metrics extracted using tsfresh</li></ol><p dir="ltr">The repository also includes complete analysis pipelines implemented in both Python (3.8.8) and R (4.3.1), featuring:</p><ul><li>Data preprocessing and machine learning model development</li><li>Statistical analyses</li><li>Visualization scripts for generating Shapley plots, activity pattern plots, and other figures</li></ul><p></p>…”

Probabilistic-QSR-GeoQA by Mohammad Kazemi (19442467)

“…<p dir="ltr">The code and data are related to the paper Mohammad Kazemi Beydokhti, Matt Duckham, Amy L. …”

Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 by Jordan Waters (21620558)

“…<br><br><br><b>ORCID ID: https://orcid.org/0009-0009-0793-8089</b><br></p><p dir="ltr"><b>Code Availability:</b></p><p dir="ltr"><b>All Python tools used for GoP simulations and predictions are available at:</b></p><p dir="ltr"><b>https://github.com/Jwaters290/GoP-Probabilistic-Curvature</b><br><br>The Gravity of Probability framework is implemented in this public Python codebase that reproduces all published GoP predictions from preexisting DESI data, using a single fixed set of global parameters. …”

Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis by Alan Glanz (22109698)

“…</p><h2><b>Included Files</b></h2><h3><b>1. </b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.…”

Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2) by Tahir Bhatti (20961974)

“…Full source code and version details are available upon request.…”