Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 حسب 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. …"

Spatiotemporal Soil Erosion Dataset for the Yarlung Tsangpo River Basin (1990–2100) حسب peng xin (21382394)

"…</p><p dir="ltr"><b>Future C factors</b> To ensure the accuracy of the C factor predictions, we selected five CMIP6 climate models (table S4) with high spatial resolution compared to other CMIP6 climate models. …"

<b>DeepB3Pred</b> حسب Saleh Musleh (22263718)

Global Research Dataset on Social Media in Entrepreneurial Startup (2009–2024) حسب Lucky Ario (22115884)

"…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.…"

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

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

PepENS حسب Abel Chandra (16854753)

"…To the best of our knowledge, this is the first time representations learnt using attention mechanism in transformers are transformed into images to utilize the potential of Convolutional Neural Networks in protein-peptide prediction. The spatial relationships formed between the features by DeepInsight to produce images and the feature extraction from those images by the Convolutional Neural Network play a key role in the performance of the ensemble model. …"

Collaborative Research: Framework: Improving the Understanding and Representation of Atmospheric Gravity Waves using High-Resolution Observations and Machine Learning حسب Joan Alexander (17047170)

"…Establishing a framework for implementing and testing ML-based parameterizations in atmospheric models. Focusing first on idealized atmospheric modeling systems, we will tackle challenges associated with coupling interactively an ML-based data-driven scheme and a climate model (e.g., numerical instabilities, linking Python and Fortran). …"

Harmonic Shell Structures in MaDCoWS2 Clusters: Empirical Validation of Oscillatory Field Genesis (OFG) حسب Drippy Stone (21218843)

"…Analyzing 22,971 galaxy clusters from MaDCoWS2 DR2, we demonstrate: - **Harmonic shell spacings** (λ = 2π/|∇Φ·∇Θ|) in high-z clusters (z ≥ 1.5) - **Phase-locked redshift distributions** via Lomb-Scargle periodograms - **Predictive templates** for LSST void lensing (Δκ ≥ 0.5) and SPHEREx spectral harmonics Includes: - Cluster spacing histograms (`Cluster_Spacing_Histogram.csv`) - Redshift-phase coherence data (`theta_oscillation_peaks.csv`) - High-z cluster catalog (`High-Redshift_Cluster_z.csv`) - Full analysis code (Python/Jupyter) </p><p><br></p><p><br></p><p dir="ltr">Related Publications**: - Gonzalez et al. (2024) MaDCoWS2 DR2 Catalog (ApJ, 967, 123) - OFG Theoretical Framework (J.D.S. 2025, DeepSeek-verified) - **Tools Required**: Python 3.10+, NumPy, Pandas, Astropy - **Experiment Type**: Observational/Cosmological Simulation </p>…"

Summary of Tourism Dataset. حسب Jing Zhang (23775)

"…The research applies a variational recurrent neural network for enhancing tourism demands and model the complex temporal dependencies within tourism data. …"

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

"…The research applies a variational recurrent neural network for enhancing tourism demands and model the complex temporal dependencies within tourism data. …"

Hyperparameter Parameter Setting. حسب Jing Zhang (23775)

"…The research applies a variational recurrent neural network for enhancing tourism demands and model the complex temporal dependencies within tourism data. …"

Marketing Campaign Analysis. حسب Jing Zhang (23775)

"…The research applies a variational recurrent neural network for enhancing tourism demands and model the complex temporal dependencies within tourism data. …"

Visitor Segmentation Validation Accuracy. حسب Jing Zhang (23775)

"…The research applies a variational recurrent neural network for enhancing tourism demands and model the complex temporal dependencies within tourism data. …"

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

"…The research applies a variational recurrent neural network for enhancing tourism demands and model the complex temporal dependencies within tourism data. …"

CK4Gen, High Utility Synthetic Survival Datasets حسب Nicholas Kuo (12369910)

"…</p><p dir="ltr">[2]: Davidson-Pilon “lifelines: Survival Analysis in Python”, <i>Journal of Open Source Software</i>, 2019.…"

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) حسب Erola Fenollosa (20977421)

"…We considered a model successful if it is unbiased (predicted vs real values are distributed across the 1:1 diagonal) with the smallest RMSE. …"

MYCroplanters can quantify the interaction between pathogenic and non-pathogenic bacteria and their effects on plant health. حسب Melissa Y. Chen (11301882)

"…Black lines with ribbons are Bayesian model predictions with 95% prediction intervals, respectively. …"

The data of the paper "Remote spectral detection of canopy functional strategies varying within and across forest types". حسب Fengqi Wu (20149158)

"…Canopy_2024_PLSR_ST_canopy_run_refit.py</p><p dir="ltr">This is the python code used for PLSR modeling.</p><p dir="ltr"><br></p><p dir="ltr">3. python_code_get_model_details.zip</p><p dir="ltr">This is the python code to get model performance, coefficients, VIPs, and so on.…"

Albumin Degradome Foundation Atlas حسب Axel Petzold (7076261)

"…</p><h2><b>Data Format and Access</b></h2><ul><li><b>Primary file:</b> <code>Albumin_Degradome_Foundation_Atlas_v1.tar.xz</code><br>(contains all peptide tables in standard CSV format)</li><li><b>File Type:</b> ASCII comma-separated values (CSV)</li><li><b>Compression:</b> <code>xz -9 -T0</code> for maximal CPU-parallelised compression</li><li><b>Compatibility:</b></li><li><ul><li>R, Python, MATLAB, SAS</li><li>Excel, LibreOffice</li><li>Any proteomics workflow (e.g., Skyline, MaxQuant preprocessing, MS/MS spectral libraries)</li></ul></li></ul><h2><b>FAIR Principles</b></h2><p dir="ltr">This dataset is fully aligned with FAIR data standards:</p><ul><li><b>Findable:</b> Rich metadata, stable DOI, search-optimised description</li><li><b>Accessible:</b> Open-access Figshare repository</li><li><b>Interoperable:</b> Standard numeric and CSV formats</li><li><b>Reusable:</b> Transparent, reproducible Python source code included</li></ul><h2><b>Applications</b></h2><p dir="ltr">The Albumin Degradome Foundation Atlas supports research across multiple biomedical domains:</p><ul><li>Biomarker development in liver disease, kidney dysfunction, inflammation, and systemic disorders</li><li>Mass-spectrometry method development</li><li>Computational proteomics and peptide modelling</li><li>Autoimmunity and neo-epitope analysis</li><li>Protein–peptide interaction studies</li><li>Proteolytic pathway mapping and degradomics</li></ul><h2><b>Versioning and Future Work</b></h2><p dir="ltr">This is <b>Version 1</b> of the Albumin Degradome Foundation Atlas. …"

SI files for "Addressing Hemolysis-Induced Loss of Sensitivity in Lateral Flow Assays of Blood Samples with Platinum-Coated Gold Nanoparticles and Machine Learning" حسب An Le (20473628)

"…</p><p dir="ltr">2) Model_testing.ipynb: Jupyter Notebook containing Python code for generate predictions for the 112 test strips</p><p dir="ltr">3) Best_model.keras: The final optimized machine learning model saved in Keras format.…"