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algorithm b » algorithm _ (توسيع البحث), algorithms _ (توسيع البحث)
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm both (توسيع البحث)
python function » protein function (توسيع البحث)
algorithm i » algorithm ai (توسيع البحث), algorithm _ (توسيع البحث), algorithm a (توسيع البحث)
algorithm b » algorithm _ (توسيع البحث), algorithms _ (توسيع البحث)
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<b>Opti2Phase</b>: Python scripts for two-stage focal reducer
منشور في 2025"…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…"
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Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection
منشور في 2025"…</p><p dir="ltr"><br></p><p dir="ltr">For more information about the data, one may refer to the article below:</p><p dir="ltr">Aref S, Ng B (2025) Troika algorithm: Approximate optimization for accurate clique partitioning and clustering of weighted networks. …"
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<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043)
منشور في 2025"…The described extracted features were used to predict leaf betalain content (µg per FW) using multiple machine learning regression algorithms (Linear regression, Ridge regression, Gradient boosting, Decision tree, Random forest and Support vector machine) using the <i>Scikit-learn</i> 1.2.1 library in Python (v.3.10.1) (list of hyperparameters used is given in <a href="#sup1" target="_blank">Supplementary Data S5</a>). …"
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GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios
منشور في 2025"…High-resolution global distribution projections of 10 rodent genera under diverse SSP–RCP scenarios, 2021–2100. <i>Sci Data</i> <b>12</b>, 1467 (2025). <a href="https://doi.org/10.1038/s41597-025-05793-0" rel="noreferrer nofollow noopener" target="_blank">https://doi.org/10.1038/s41597-025-05793-0</a></p><p dir="ltr">Understanding the potential impact of climate change on species distributions is crucial for biodiversity conservation and ecosystem management. …"
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Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model
منشور في 2025"…<p dir="ltr">The <i>zip</i> file contains the code for the functional excitation-inhibition ratio (fE/I) and theta-gamma (θ-γ) phase-amplitude coupling (PAC) analyses described in the paper titled "<b>Hippocampal and cortical activity reflect early </b><b>hyperexcitability</b><b> in an Alzheimer's mouse model</b>" submitted to <i>Brain Communications</i> in April 2025.…"
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<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 .…"
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MCCN Case Study 2 - Spatial projection via modelled data
منشور في 2025"…</p><h4><b>Data sources</b></h4><ul><li><b>BradGinns_SOIL2004_SoilData.csv</b> - Soil measurements from the University of Sydney Llara Campey farm site from 2004, corresponding to sites L1, L3 and L4 describing mid-depth, soil apparent electrical conductivity (ECa), GammaK, Clay, Silt, Sand, pH and soil electrical conductivity (EC)</li><li><b>Llara_Campey_field_boundaries_poly.shp</b> - Field boundary shapes for the University of Sydney Llara Campey farm site</li></ul><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 rioxarray pykrige</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Select soil sample measurements for pH or EC at 45 cm depth</li><li>Split sample measurements into 80% subset to model interpolated layers and 20% to test interpolated layers</li><li>Generate STAC metadata for layers</li><li>Load data cube</li><li>Interpolate pH and EC across site using the 80% subset and three different 2D interpolation methods from rioxarray (nearest, linear and cubic) and one from pykrige (linear)</li><li>Calculate the error between each layer of interpolated values and measured values for the 20% setaside for testing</li><li>Compare the mean and standard deviation of the errors for each interpolation method</li><li>Clean up and package results as RO-Crate</li></ol><h4><b>Notes</b></h4><ul><li>The granularity of variability in soil data significantly compromises all methods</li><li>Depending on the 80/20 split, different methods may appear more reliable, but the pykrige linear method is most often best</li></ul><p><br></p>…"
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Mechanomics Code - JVT
منشور في 2025"…<p dir="ltr">Entry is a part of <b>Mechanomics</b> collection (<a href="https://doi.org/10.6084/m9.figshare.c.5399826" target="_blank">10.6084/m9.figshare.c.5399826</a>) that contains materials supporting findings presented in the following manuscript:</p><p dir="ltr"><i>Urbanska, M., Ge, Y.…"
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Code and data for evaluating oil spill amount from text-form incident information
منشور في 2025"…These are separately stored in the folders “description” and “posts”.</p><h2>Algorithms for Evaluating Release Amount (RA)</h2><p dir="ltr">The algorithms are split into the following three notebooks based on their functions:</p><ol><li><b>"1_RA_extraction.ipynb"</b>:</li><li><ul><li>Identifies oil spill-related incidents from raw incident data.…"
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Spatiotemporal Soil Erosion Dataset for the Yarlung Tsangpo River Basin (1990–2100)
منشور في 2025"…Bias correction was conducted using a 25-year baseline (1990–2014), with adjustments made monthly to correct for seasonal biases. The corrected bias functions were then applied to adjust the years (2020–2100) of daily rainfall data using the "ibicus" package, an open-source Python tool for bias adjustment and climate model evaluation. …"
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Landscape17
منشور في 2025"…Transition states were verified through Hessian analysis, confirming exactly one negative eigenvalue. Only transition states with barriers below 1 eV were retained. …"
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Code
منشور في 2025"…The first convolutional layer uses a 2D convolution with 8 filters, each with a size 1 × 8, and a stride of 1, followed by a ReLU activation function. …"