بدائل البحث:
after implementing » after implementation (توسيع البحث), model implementing (توسيع البحث)
code implementing » model implementing (توسيع البحث), consider implementing (توسيع البحث), _ implementing (توسيع البحث)
after implementing » after implementation (توسيع البحث), model implementing (توسيع البحث)
code implementing » model implementing (توسيع البحث), consider implementing (توسيع البحث), _ implementing (توسيع البحث)
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141
Concurrent spin squeezing and field tracking with machine learning
منشور في 2025"…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. …"
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142
Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1
منشور في 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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143
Neural-Signal Tokenization and Real-Time Contextual Foundation Modelling for Sovereign-Scale AGI Systems
منشور في 2025"…</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.…"
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144
Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil)
منشور في 2025"…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. …"
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145
Missing Value Imputation in Relational Data Using Variational Inference
منشور في 2025"…Additional results, implementation details, a Python implementation, and the code reproducing the results are available online. …"
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146
Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i>
منشور في 2025"…</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>…"
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147
Probabilistic-QSR-GeoQA
منشور في 2024"…<p dir="ltr">The code and data are related to the paper Mohammad Kazemi Beydokhti, Matt Duckham, Amy L. …"
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148
Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789
منشور في 2025"…<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. …"
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149
Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis
منشور في 2025"…</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.…"
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150
Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2)
منشور في 2025"…Full source code and version details are available upon request.…"
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151
Table & Figure.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks
منشور في 2025"…Supplementary Materials</p> <p><br></p> <p>Experimental protocols and study design details</p> <p><br></p> <p>Questionnaires, surveys, or rubrics used in the study</p> <p><br></p> <p>Educational materials related to HOTS-based mathematics tasks</p> <p><br></p> <p><br></p> <p><br></p> <p>3. Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …"
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152
Raw Data EEG.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks
منشور في 2025"…Supplementary Materials</p> <p><br></p> <p>Experimental protocols and study design details</p> <p><br></p> <p>Questionnaires, surveys, or rubrics used in the study</p> <p><br></p> <p>Educational materials related to HOTS-based mathematics tasks</p> <p><br></p> <p><br></p> <p><br></p> <p>3. Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …"
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153
Online Resource: Reservoir Computing as a Promising Approach for False Data Injection Attack Detection in Smart Grids
منشور في 2025"…</li><li><b>3_literature_analysis_and_mapping.ipynb</b><br>Contains the Python code used for executing the systematic mapping study (SMS), including automated processing of literature data and thematic clustering.…"
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154
Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx
منشور في 2025"…Its efficiency and scalability make it well-suited for early-stage antibody discovery, repertoire profiling, and therapeutic design, particularly in the absence of structural data. The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…"
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155
Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds
منشور في 2025"…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …"
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156
Dataset for: Phylotranscriptomics reveals the phylogeny of Asparagales and the evolution of allium flavor biosynthesis, Nature Communications,DOI:10.1038/s41467-024-53943-6
منشور في 2024"…Extract the TPM.</p><p dir="ltr">After running Salmon, each species has three quant.sf files, renamed as quant1.sf, quant2.sf, quant3.sf.…"
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157
MCCN Case Study 3 - Select optimal survey locality
منشور في 2025"…</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>…"
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158
Advancing Solar Magnetic Field Modeling
منشور في 2025"…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …"
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159
Data files accompanying our PLoS One publication
منشور في 2025"…The videos were digitized and the positional data were saved in .xlsx or .csv format, respectively. The python codes contain the numerical implementations of our mathematical models.…"
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160
Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx
منشور في 2025"…Statistical analyses were conducted using Python and R, with significance set at p < 0.05.</p>Results<p>In this study, we developed an integrated predictive model for HER2 status in breast cancer by combining deep learning-based MRI features and clinical data. …"