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83 results for “Computational methods”
Phlorest phylogeny derived from Robinson and Holton 2012 'Internal Classification of the Alor-Pantar Language Family Using Computational Methods Applied to the Lexicon'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Robinson, L. C., & Holton, G. (2012). Internal Classification of the Alor-Pantar Language Family Using Computational Methods Applied to the Lexicon. Language Dynamics and Change, 2(2), 123-149. doi:10.1163/22105832-20120201</p> </blockquote>
Voltage controlled iontronic switches: a computational method to predict electrowetting in hydrophobically gated nanopores
<p>Folder with numbered names ("0", "0.1", "n0.5") have the data from restrained molecular dynamics (".dat") and some trajectories (".xyz") at the applied voltage corresponding to the name of the folder. "n" in the folder name correspond to the negative voltages.</p> <p>Folders "wetting" and "drying" contain the data used to compute the wetting and drying rates at different applied voltages using Molecular Dynamics.</p>
Personal Online Dosimetry Using Computational Methods: The PODIUM Project and the Future of Active Dosimetry
<p>Individual monitoring of workers exposed to external ionizing radiation is essential to allow application of the ALARA principle and follow up of the official dose limits. However, large uncertainties still exist in personal dosimetry. Also, many practical problems exist for personal dosimetry, with many dosemeters getting lost and the reluctance of many workers to wear one or more dosemeters.</p> <p>Most legal dosimetry is done with passive dosemeters, which are analyzed after the wearing period in an accredited lab. Active dosemeters are also widely used, although mostly only for ALARA purposes or for specific exposure situations. Although the active dosemeters are dosimetrically and technically at least equivalent to passive dosemeters, their higher cost limits their use as only legal dosemeters.</p> <p>In an attempt of reinventing dosimetry by using the modern evolutions in simulations, artificial intelligence and computer vision, the PODIUM project was set up. PODIUM was a short feasibility project, funded by the EC CONCERT programme.</p> <p>The objective of the PODIUM project was to improve personal dosimetry by an innovative approach: the development of an online dosimetry application based on computer simulations without the use of physical dosemeters. Operational quantities, protection quantities and radiosensitive organ doses (e.g. eye lens, brain, heart, extremities) can be calculated based on the use of modern technology such as personal tracking devices, flexible individualized phantoms and scanning of geometry set-up. When combined with fast simulation codes, the aim was to perform personal dosimetry in real-time.</p> <p>We applied and validated the methodology for two situations where improvements in dosimetry are urgently needed: neutron workplaces and interventional radiology. Several validation and test measurements were done in different hospitals, and in 2 workplace fields with significant neutron exposure. Personal doses could be calculated within acceptable simulation times, just based on captured movements of the workers and information of the radiation fields. These doses agreed with the results from physical dosemeters within the standard uncertainties that are accepted in personal dosimetry.</p> <p>This PODIUM dosimetry method can also be used to visualize the radiation in near real time. This will increase awareness of radiation protection among workers and will improve the application of the ALARA principle, and it can also be used in training modules. The use of neural networks and big data will help in further reducing simulation time, making real time simulations and dosimetry without physical dosemeters possible in the near future.</p>
A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations
<p>Supporting information dataset for <em>A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations, </em>including Flex ddG binding free energy predictions, epistasis calculations, pathway probabilities, Rosetta files and structural files. </p>
Cloud computing is one of the most popular and sophisticated technologies adopted by organizations worldwide. Some world-leading organizations enhance their efficiency and effectiveness by using cloud computing technology. Working from home (WFH) has been a popular trend among organizations during the coronavirus (COVID-19) pandemic. The COVID-19 saw a breakthrough in work cultures and environments where working from home was a remarkable success in remote working environments, despite being a rare phenomenon in Sri Lanka. Yet, it is argued that the deployment of work from home has not been effective among Sri Lankan business organizations due to a lack of IT infrastructure, facilities, and knowledge. The purpose of the study is to investigate the impact of cloud computing, embracing the service models (Infrastructure as a Service, Platform as a Service, and Software as a Service) as theoretical lenses and testing the COVID-19 as the moderator. The study has been conducted based on a deductive approach and adopted a stratified random sampling method. The sample consisted of 384 IT employees among those who had experienced working from home. The study utilized multiple regression and found that cloud computing service models significantly impact work from home with the moderating effect of COVID-19.
<p>Cloud computing is one of the most popular and sophisticated technologies adopted by organizations worldwide. Some world-leading organizations enhance their efficiency and effectiveness by using cloud computing technology. Working from home (WFH) has been a popular trend among organizations during the coronavirus (COVID-19) pandemic. The COVID-19 saw a breakthrough in work cultures and environments where working from home was a remarkable success in remote working environments, despite being a rare phenomenon in Sri Lanka. Yet, it is argued that the deployment of work from home has not been effective among Sri Lankan business organizations due to a lack of IT infrastructure, facilities, and knowledge. The purpose of the study is to investigate the impact of cloud computing, embracing the service models (Infrastructure as a Service, Platform as a Service, and Software as a Service) as theoretical lenses and testing the COVID-19 as the moderator. The study has been conducted based on a deductive approach and adopted a stratified random sampling method. The sample consisted of 384 IT employees among those who had experienced working from home. The study utilized multiple regression and found that cloud computing service models significantly impact work from home with the moderating effect of COVID-19.</p>
Discontinuous Galerkin time-domain method for the computation of electromagnetic resonant modes
<p>Data generated for the paper "The application of a high-order discontinuous Galerkin time-domain method for the computation of electromagnetic resonant modes" published in Applied Mathematical Modelling. It includes:</p> <ul> <li>Meshes</li> <li>Time domain signals</li> <li>Spectra</li> <li>Figures</li> </ul>
Input data of the multi-patch geometries used in: A. Farahat, H. M. Verhelst, J. Kiendl, M. Kapl, Isogeometric analysis for multi-patch structured Kirchhoff–Love shells, Computer Methods in Applied Mechanics and Engineering 411 (2023) 116060 DOI: 10.1016/j.cma.2023.116060
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The dataset of the manuscript "GPU-HADVPPM4HIP V1.0: higher model accuracy on China's domestically GPU-like accelerator using heterogeneous compute interface for portability (HIP) technology to accelerate the piecewise parabolic method (PPM) in an air quality model (CAMx V6.10)"
<p><strong>bcfile.zip:</strong> the clean boundary condition files.</p> <p><strong>CAMxv6x_cpp.zip: </strong>the source code of CAMx-HIP version which coupled with HIP-HADVPPM scheme.</p> <p><strong>data.zip:</strong> final data tables used to plot figures.</p> <p><strong>emisfile.zip: </strong>the emission files.</p> <p><strong>icfile.zip:</strong> the clean initial condition files.</p> <p><strong>tuvfile.zip </strong>and <strong>o3mapfile.zip:</strong> the photolysis files.</p> <p><strong>outputfile.zip:</strong> the computation results outputted by CAMx model for Fortran version on the Intel Xeon E5-2682 v4 CPU, CUDA version on the NVIDIA K40m and V100 clusters, and HIP version on the China' s domestically heterogeneous cluster A.</p> <p><strong>wrfcamx.zip:</strong> the meteorological files.</p> <p><strong>offline_test_cuda.zip: </strong>the advection module code written in CUDA C language</p> <p><strong>offline_test_fortran.zip:</strong> the advection module code written in Fortran language</p> <p><strong>offline_test_hip.zip: </strong>the advection module code written in HIP C language</p>
Dataset: Methods for computing the maximum performance of computational models of fMRI responses.
<p>Accompanying data for manuscript: Methods for computing the maximum performance of computational models of fMRI responses. written by Agustin Lage-Castellanos, Giancarlo Valente, Elia Formisano, Federico De Martino, submitted for publication in Plos Computational Biology, July 2018.</p> <p>This dataset provide the Betas for subcortical and a subset of the cortical voxels for three subjects in matlab format.</p> <p>The field bTest refers to the Beta coefficients for every voxel in the test data. The fields beta1 and beta2 refer to the split-half partitions of the bTest coefficients. The field varBparam refers to the parametric variances of the Beta coefficients and the field varBBootstrap refers to the variances of the Betas computed with bootstrap. </p>
Combining graph neural networks and computer vision methods for cell nuclei classification in lung tissue
<p>Database of the article "Combining graph neural networks and computer vision methods for cell nuclei classification in lung tissue ".</p>
Data from: Bubbling water-treating DBD plasma device optimization using experimental and computational methods
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Figure 5. Muscle mass reconstruction method for M in A Computational Analysis of Limb and Body Dimensions in Tyrannosaurus rex with Implications for Locomotion, Ontogeny, and Growth
Figure 5. Muscle mass reconstruction method for M. caudofemoralis longus (see Methods); Carnegie specimen depicted. Dorsal and right lateral views are shown on topı and in the bottom row are caudal views of the right femur and then caudal vertebrae (8th and 17th). Red shaded volumes are the M. caudofemoralis longus reconstruction. Note a small space for M. caudofemoralis brevis (not reconstructed) is left around the ilium/sacrum and lateral to the CFL insertion. doi:10.1371/journal.pone.0026037.g005
Data from: Oscillatory signatures underlie growth regimes in Arabidopsis pollen tubes: computational methods to estimate tip location, periodicity and synchronization in growing cells
Oscillations in pollen tubes have been reported for many cellular processes, including growth, extracellular ion fluxes, and cytosolic ion concentrations. However, there is a shortage of quantitative methods to measure and characterize the different dynamic regimes observed. Herein, a suite of open-source computational methods and original algorithms were integrated into an automated analysis pipeline that we employed to characterize specific oscillatory signatures in pollen tubes of Arabidopsis thaliana (Col-0). Importantly, it enabled us to detect and quantify a Ca2+ spiking behaviour upon growth arrest and synchronized oscillations involving growth, extracellular H+ fluxes, and cytosolic Ca2+, providing the basis for novel hypotheses. Our computational approach includes a new tip detection method with subpixel resolution using linear regression, showing improved ability to detect oscillations when compared to currently available methods. We named this data analysis pipeline 'Computational Heuristics for Understanding Kymographs and aNalysis of Oscillations Relying on Regression and Improved Statistics', or CHUKNORRIS. It can integrate diverse data types (imaging, electrophysiology), extract quantitative and time-explicit estimates of oscillatory characteristics from isolated time series (period and amplitude) or pairs (phase relationships and delays), and evaluate their synchronization state. Here, its performance is tested with ratiometric and single channel kymographs, ion flux data, and growth rate analysis.
Data from: Is computer-assisted instruction more effective than other educational methods in achieving ECG competence amongst medical students and residents? A systematic review and meta-analysis.
Objectives It remains unclear whether computer-assisted instruction (CAI) is more effective than other teaching methods in acquiring and retaining ECG competence amongst medical students and residents. Design This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Data sources Electronic literature searches of PubMed, databases via EBSCOhost, Scopus, Web of Science, Google Scholar and grey literature were conducted on 28 November 2017. We subsequently reviewed the citation indexes of articles identified by the search. Eligibility criteria Studies were included if a comparative research design was used to evaluate the efficacy of CAI versus other methods of ECG instruction, as determined by the acquisition and/or retention of ECG competence of medical students and/or residents. Data extraction and synthesis Two reviewers independently extracted data from all eligible studies and assessed the risk of bias. After duplicates were removed, 559 papers were screened. Thirteen studies met the eligibility criteria. Eight studies reported sufficient data to be included in the meta-analysis. Results In all studies, CAI was compared to face-to-face ECG instruction. There was a wide range of computer-assisted and face-to-face teaching methods. Overall, the meta-analysis found no significant difference in acquired ECG competence between those who received computer-assisted or face-to-face instruction. However, sub-analyses showed that CAI in a blended learning context was better than face-to-face teaching alone, especially if trainees had unlimited access to teaching materials and/or deliberate practice with feedback. There was no conclusive evidence that CAI was better than face-to-face teaching for longer-term retention of ECG competence. Conclusion CAI was not better than face-to-face ECG teaching. However, this meta-analysis was constrained by significant heterogeneity amongst studies. Nevertheless, the finding that blended learning is more effective than face-to-face ECG teaching is important in the era of increased implementation of e-learning. PROSPERO registration number CRD42017067054
Huntingtin linker sequence determination by computational methods - correspondence with Alex Holehouse
<p>Huntingtin open lab notebook project</p>
The 3'-RACE data (InPACT: A computational method for accurate characterization of intronic polyadenylation from RNA sequencing data)
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A computationally efficient method for parameter sensitivity analysis of microbially-explicit biogeochemical models accounting for long-term behavior
<p>The dataset is for the manuscript entitled "A computationally efficient method for parameter sensitivity analysis of microbially-explicit biogeochemical models accounting for long-term behavior".</p>
UAS dataset for Crop Water Stress Index computation and Triangle Method applications
<p>This dataset is related with a field campaigns carried out on a tangerine field located near Palermo (Sicily), within the Harmonious COST action CA16219 - Harmonization of UAS techniques for agricultural and natural ecosystems monitoring-, activities framework. The general aim was to acquire UAS (Unmanned Aerial Systems) remotely sensed imagery to detect the vegetation stress status. A multispectral camera (RIKOLA) and a thermal one (FLIR) were used. The images are already georeferenced with 3.7 cm pixel size. The dataset could be used to compute the Crop Water Stress Index and to compute the moisture status of the field by means of a combined use of the optical and thermal images. The dataset includes meteo data registered by a meteo station nearby the site.</p>
scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis
<p>Analysis code for the paper "scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis"</p>
The input data of the multi-patch geometries used in: M. Kapl, A. Kosmač, V. Vitrih, Isogeometric collocation for solving the biharmonic equation over planar multi-patch domains, Computer Methods in Applied Mechanics and Engineering 424 (2024) 116882; DOI: 10.1016/j.cma.2024.116882
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.