Search alternatives:
effective implementation » effective prevention (Expand Search)
code implementation » model implementation (Expand Search), time implementation (Expand Search), world implementation (Expand Search)
python effective » proven effective (Expand Search), 1_the effective (Expand Search), 2_the effective (Expand Search)
effective implementation » effective prevention (Expand Search)
code implementation » model implementation (Expand Search), time implementation (Expand Search), world implementation (Expand Search)
python effective » proven effective (Expand Search), 1_the effective (Expand Search), 2_the effective (Expand Search)
-
161
Leue Modulation Coefficients (LMC): A Smooth Continuum Embedding of Bounded Arithmetic Data
Published 2025“…This Zenodo package includes: the full research paper (PDF), a complete Python implementation generating the LMC field and conductivity model, a numerical plot comparing discrete LMC values with the smoothed continuum field, a cover letter and supporting documentation. …”
-
162
Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2)
Published 2025“…Full source code and version details are available upon request.…”
-
163
Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model
Published 2025“…</p><p dir="ltr">All data are available upon request. The standalone Python implementation of the fE/I algorithm is available under a CC-BY-NC-SA license at <a href="https://github.com/arthur-ervin/crosci" target="_blank">https://github.com/arthur-ervin/crosci</a>. …”
-
164
Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event
Published 2025“…Includes imputation statistics, data dictionary, and the Python imputation code (Imputation_Air_Pollutants_NABEL.py). …”
-
165
Advancing Solar Magnetic Field Modeling
Published 2025“…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …”
-
166
Data files accompanying our PLoS One publication
Published 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.…”
-
167
CNG-ARCO-RADAR.pdf
Published 2025“…This approach uses a suite of Python libraries, including Xarray (Xarray-Datatree), Xradar, and Zarr, to implement a hierarchical tree-like data model. …”
-
168
ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation
Published 2025“…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”
-
169
ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation
Published 2025“…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”
-
170
Mapping Policy Coherence in National UK Food Systems (2008– 2024): Analysing the Integration of Climate Change Mitigation and Adaptation Strategies, LEAP 2025 conference, Oxford
Published 2025“…</p><p dir="ltr">Data Screening inclusion criteria followed the Food Systems Countdown Initiative (FSCI).2</p><p><br></p><p dir="ltr">diets, nutrition and health</p><p dir="ltr">diet quality, food security, food environments, policies affecting</p><p dir="ltr">food environments</p><p dir="ltr">environment and climate</p><p dir="ltr">land use, greenhouse gas emissions, water use, pollution, biosphere integrity</p><p dir="ltr">livelihoods, poverty, and equity</p><p dir="ltr">poverty and income, employment, social protection, rights</p><p dir="ltr">governance</p><p dir="ltr">shared vision, strategic planning and policies, effective implementation, accountability</p><p dir="ltr">resilience and sustainability</p><p dir="ltr">exposure to shocks, resilience capacities, agrobiodiversity, food security stability</p><p><br></p><p dir="ltr">Findings</p><p dir="ltr">o N=157 policy documents integrate climate change considerations.…”
-
171
Data Sheet 1_COCαDA - a fast and scalable algorithm for interatomic contact detection in proteins using Cα distance matrices.pdf
Published 2025“…Here, we introduce COCαDA (COntact search pruning by Cα Distance Analysis), a Python-based command-line tool for improving search pruning in large-scale interatomic protein contact analysis using alpha-carbon (Cα) distance matrices. …”
-
172
MSc Personalised Medicine at Ulster University
Published 2025“…</b> Introducing computational approaches to studying genes, proteins or metabolites, this module teaches Python coding, data analysis and how to work with the databases that support data analysis.…”
-
173
Research Database
Published 2025“…Data were processed using <b>Python-based automation scripts</b> for scraping, cleaning, geocoding, and calculating geodesic distances between each property and the nearest community garden. …”
-
174
Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples
Published 2025“…Image processing algorithms, implemented in Python using adaptive thresholding techniques, were applied to segment particles from the background. …”
-
175
Image 1_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif
Published 2025“…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …”
-
176
Image 2_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif
Published 2025“…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …”
-
177
Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025
Published 2025“…</p><h2>Software and Spatial Resolution</h2><p dir="ltr">The VRE siting model is implemented using Python and relies heavily on ArcGIS for comprehensive spatial data handling and analysis.…”
-
178
Core data
Published 2025“…</p><p><br></p><p dir="ltr">For the 5′ UTR library, we developed a Python script to extract sequences and Unique Molecular Identifiers (UMIs) from the FASTQ files. …”