بدائل البحث:
files implementation » time implementation (توسيع البحث), pilot implementation (توسيع البحث), assess implementation (توسيع البحث)
python model » python tool (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
files implementation » time implementation (توسيع البحث), pilot implementation (توسيع البحث), assess implementation (توسيع البحث)
python model » python tool (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
-
141
-
142
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.…"
-
143
Moulin distributions during 2016-2021 on the southwest Greenland Ice Sheet
منشور في 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.…"
-
144
Audio Datasets of belt conveyor rollers in mines
منشور في 2024"…</li><li><b>Python Code: </b>This code validates the accuracy and usability of the audio feature datasets in real-time monitoring of belt conveyor roller operational states.…"
-
145
Supplement Number 1
منشور في 2025"…Python files containing the implementation of the graphical calculus on generalized Wilson loop diagrams…"
-
146
Social media images of China's terraces
منشور في 2025"…</p><p dir="ltr">These images can be used for training classification models. All code used for model training and testing is available at: https://github.com/chen7092/Deep-learning-for-cultural-ecosystem-services-of-terraces.…"
-
147
<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b>
منشور في 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 .…"
-
148
<b>Anthropogenic nutrient inputs cause excessive algal growth for nearly half the world’s population</b>
منشور في 2025"…</p><p dir="ltr">Models: R code to explore different models for implementation via Python in ArcGIS</p><p dir="ltr">!geotiffs: GeoTIFF raster files at level 6 of HydroBasins for current, zero human effect and the difference between current and zer human effect.…"
-
149
Supplementary material for "Euler inversion: Locating sources of potential-field data through inversion of Euler's homogeneity equation"
منشور في 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. …"
-
150
NanoDB: Research Activity Data Management System
منشور في 2024"…In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …"
-
151
The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network"
منشور في 2024"…</li></ul><h2>Codes</h2><p dir="ltr">This repository contains the following Python codes:</p><ul><li>`data_processing.py`: Contains the implementation of data processing and feature extraction. …"
-
152
<b>Data Availability</b>
منشور في 2025"…</p><p dir="ltr">python scripts documenting the implementation of the Mixture Density Network (MDN) algorithm, including hyperparameter tuning and uncertainty quantification.…"
-
153
<b>Data Availability</b>
منشور في 2025"…</p><p dir="ltr">python scripts documenting the implementation of the Mixture Density Network (MDN) algorithm, including hyperparameter tuning and uncertainty quantification.…"
-
154
Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games"
منشور في 2024"…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…"
-
155
Reproducible Code and Data for figures
منشور في 2025"…</i></p><p dir="ltr">It contains:</p><p dir="ltr">✅ <b>Python Code</b> – Scripts used for data preprocessing, and visualization.…"
-
156
Sonification of Growing Black Hole
منشور في 2024"…We used the open source Python package STRAUSS to produce the sonification (Trayford and Harrison 2023). …"
-
157
Digital Twin for Chemical Sciences
منشور في 2025"…The procedure for generating data in Figure 3 can be found in the demo notebook in Supplementary Code. The procedure for generating data of Figure 4 has been uploaded in fig4_figshare.zip file. …"
-
158
Improving the calibration of an integrated CA-What If? digital planning framework
منشور في 2025"…</p><p dir="ltr">This dataset includes (1) all required data for reproducing the materials within the manuscript, (2) detailed Python codes of the proposed CA-What If? model, and (3) a step-by-step instruction document.…"
-
159
Attention and Cognitive Workload
منشور في 2025"…</p><p dir="ltr">The data for subject 2 do not include the 2nd part of the acquisition (python task) because the equipment stopped acquiring; subject 3 has the 1st (N-Back task and mental subtraction) and the 2nd part (python tutorial) together in the <code>First part</code> folder (file <code>D1_S3_PB_description.json</code> indicates the start and end of each task); subject 4 only has the mental subtraction task in the 1st part acquisition and in subject 8, the subtraction task data is included in the 2nd part acquisition, along with python task.…"
-
160
Bacterial persistence modulates the speed, magnitude and onset of antibiotic resistance evolution
منشور في 2025"…</p><p dir="ltr">Repository structure</p><p dir="ltr">Fig_1/</p><ul><li>Probability of emergence analysis</li><li>Fig_1.py: contour plot generation</li></ul><p dir="ltr">Fig_2/</p><ul><li>MIC evolution simulations</li><li>Fig_2_a/: R-based simulation analysis</li><li>Fig_2_b/: Python visualization</li><li>Fig_2_c/: speed of resistance evolution analysis</li><li>Fig_2_d/: time to resistance analysis</li></ul><p dir="ltr">Fig_3/</p><ul><li>Distribution analysis</li><li>Fig_3_a-b.R: density plots and bar charts (empirical and simulated)</li></ul><p dir="ltr">Fig_4/</p><ul><li>Mutation analysis</li><li>Fig_4_a-b/: mutation counting analysis</li><li><ul><li>Fig_4_a/: simulation data (sim)</li><li>Fig_4_b/: empirical data (emp)</li></ul></li><li>Fig_4_c/: gene ontology and functional analysis</li></ul><p dir="ltr">Fig_5/</p><ul><li>Large-scale evolutionary simulations</li><li>Fig_5_a-b/: heatmap visualizations</li><li>Fig_5_c/: MIC and extinction analysis (empirical)</li></ul><p dir="ltr">Fig_6/</p><ul><li>Population size effects</li><li>Fig_6.py: population size analysis simulations</li></ul><p dir="ltr">S1_figure/</p><ul><li>Supplementary experimental data</li></ul><p dir="ltr">S2_figure/</p><ul><li>Supplementary frequency analysis</li></ul><p dir="ltr">S3_figure/</p><ul><li>Supplementary probability analysis</li></ul><p dir="ltr">scripts_simulations_cluster/</p><ul><li>Large-scale, cluster-optimized simulations</li></ul><p dir="ltr">complete_data/</p><ul><li>Reference to the full data sheet (full data set deposited elsewhere)</li></ul><p dir="ltr">Script types and languages</p><p dir="ltr">Python scripts (.py)</p><ul><li>Mathematical modeling: survival functions, probability calculations</li><li>Stochastic simulations: tau-leaping population dynamics</li><li>Data processing: mutation analysis, frequency calculations</li><li>Visualization: plotting with matplotlib and seaborn</li><li>Typical dependencies: numpy, pandas, matplotlib, seaborn, scipy</li></ul><p dir="ltr">R scripts (.R)</p><ul><li>Statistical analysis: distribution fitting, density plots</li><li>Advanced visualization: publication-quality figures (ggplot2)</li><li>Data manipulation: dplyr / tidyr workflows</li><li>Typical dependencies: dplyr, tidyr, ggplot2, readxl, cowplot</li></ul><p dir="ltr">Data requirements</p><p dir="ltr">The scripts are designed to run using the complete_data.xlsx file and, where relevant, the raw simulation outputs and empirical data sets as described above. …"