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864 results for “numerative”
Numerical simulation of supercell thunderstorms (at 50 meter resolution) associated with above anvil cirrus plumes
Open the record for dataset details and reuse information.
Numerical simulation of cool hydrothermal processes in the upper volcanic crust beneath a marine sediment pond: North Pond, North Atlantic Ocean
Open the record for dataset details and reuse information.
Observational data and numerical experimental files for subglacial discharge plume in Bowdoin Fjord, northwestern Greenland
<p>The dataset includes observational data and all the files used in the numerical experiments. Additionally, this includes the codes to generate the figures and analysis. Please see Ohashi et al. (2019) for details (<a href="https://www.ocean-sci-discuss.net/os-2019-33/">https://www.ocean-sci-discuss.net/os-2019-33/</a>).</p>
Supporting dataset for "Numerical insights into the effects of model geometric distortion in laboratory experiments of urban flooding"
<p>The supporting datasets includes:</p> <p>(1) All the Figures in the manuscript in .fig format </p> <p> - Figures in main text</p> <p> - Figures in SI</p> <p>(2) Original matrice data for the results of each run</p> <p> - A file that explains detailed data content in tree structure;</p> <p> - 4 sub-repositories which contain data for models in different scales</p>
Full results of numerical experiments described in research paper "A conservative index heuristic for routing problems with multiple heterogeneous service facilities"
<p>These files include the complete results of the numerical experiments described in our research paper, "A conservative index heuristic for routing problems with multiple heterogeneous service facilities".</p>
Breaking the Mold: A corpus study of numeral+noun phrases in Scottish Gaelic - Corpus Data
<p>Hello! This is the corpus data compiled in the searches done for my master's thesis: Breaking the Mold: A corpus study of numeral + noun phrases in Scottish Gaelic. The data comes from the Digital Archive of Scottish Gaelic's Corpas na Gàidhlig (<a href="https://dasg.ac.uk/corpus/">https://dasg.ac.uk/corpus/</a>). </p> <p>The relevant data are discussed in the thesis, but the full corpus is found here for anyone who wishes to view it. </p> <p>For any questions, please contact me: emma.mckenzie(at)helsinki.fi </p>
Lituya Bay 1958 Tsunami – pre-event bathymetry reconstruction and 3D-numerical modelling utilizing the CFD software Flow-3D
<p>Simulation video, Model code, STL.File of the solid bodies</p>
The dataset of the manuscript "Numerical study of the initial condition and emission on simulating PM2.5 concentrations in Comprehensive Air Quality Model with extensions version 6.1 (CAMx v6.1): Taking Xi'an as example"
<ul> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/bcfile.rar?versionId=4909d094-5877-408e-bd4f-0c969c54e585">bcfile.rar</a>: the clean initial and boundary condition files.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/Emis_forNov.rar?versionId=0a1e8b66-5157-4819-8c03-20fb7797d8ef">Emis_forNov.rar</a> and <a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/Emis_forDec.rar?versionId=d4db00f1-ec1b-4096-973e-6a87133e4eac">Emis_forDec.rar</a>: the emission files in November and December 2016.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/tuvfile.rar?versionId=5dcf0977-e416-466e-9089-bbf0726c788d">tuvfile.rar</a> and <a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/o3mapfile.rar?versionId=9c25cae9-f00e-4ad3-b4dc-7a721f7f44d7">o3mapfile.rar</a>: the photolysis files.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/camx.cp1.rar?versionId=09ded31b-4c42-4e40-a21c-0f18877e9e41">camx.cp[1-5].rar</a>: the results of sensitivity experiments for using clean initial condition files.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/camx.r1120p1.rar?versionId=45d6e209-8e66-43ed-bc0b-dc8af5521352">camx.r1120p[1-3].rar</a>: the results of sensitivity experiments for R1120.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/camx.r1124.rar?versionId=c138e436-0416-4701-948d-ce761cf6c5cf">camx.r1124.rar</a>: the results of sensitivity experiments for R1124.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/contnuous_B12.rar?versionId=34485c43-77ac-4001-8a6d-a57b7ff821e3">contnuous_B12.rar</a>: the results of sensitivity experiments for CT12.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/contnuous_B24.rar?versionId=0f325a61-f19c-4bac-b8b4-7e229c332bf9">contnuous_B24.rar</a>: the results of sensitivity experiments for CT24.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/scripts.zip?versionId=b030444c-51a5-4673-b9d1-7e80ec42a3b9">scripts.zip</a>: all scripts covering every data processing action for all the results reported in the paper.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/data.zip?versionId=52917a53-fca7-4a72-ba2f-a2ce7593adc4">data.zip</a>: final data tables used to plot figures and tables.</li> </ul>
The role of storms in sand wave formation: A numerical modeling study
<p>The data is mainly the results from the simulation for manuscript "The role of storms in sand wave formation: A numerical modeling study".</p>
Experimental and Simulation Results of "3D Printed Biomodels for Flow Visualization in Stenotic Vessels: An Experimental and Numerical Study" - version 2
<p>This repository contains the experimental and simulation results of the article "3D Printed Biomodels for Flow Visualization in Stenotic Vessels: An Experimental and Numerical Study" by Carvalho, V., Rodrigues, N., Ribeiro, R., Costa, P., Lima, R., Teixeira, S., published in <em>Micromachines</em> <strong>11, 6</strong> (2020). https://doi.org/10.3390/mi11060549</p>
Numerical Fire Spread Simulation Based on Material Pyrolysis - An Application to the CHRISTIFIRE Phase 1 Horizontal Cable Tray Tests - Data Set
<p>This data set is a supplementary resource for the article "<a href="http://www.mdpi.com/2571-6255/3/3/33">Numerical Fire Spread Simulation Based on Material Pyrolysis - An Application to the CHRISTIFIRE Phase 1 Horizontal Cable Tray Tests</a>", published by the peer-reviewed open access journal <a href="https://www.mdpi.com/journal/fire">Fire</a>. It is part of the "<a href="https://www.researchgate.net/project/Fire-Propagation-in-Cable-Tray-Installations">Fire Propagation in Cable Tray Installations</a>" project. The provided data is only a summary of the full data produced for the article, due to its size.</p> <p>This article was previously submitted to the Fire Safety Journal and got eventually rejected.</p> <p>The information is structured into multiple *.rar archieves, which mimic the sub-directory structure created for the work. To be able to run the analysis scripts without much tweaking, extract all archieves into the same directory, with each archieve being a sub-directory in it.</p> <p>The data set is comprised of:</p> <ul> <li>The PROPTI and FDS input files used for the inverse modelling process (IMP) -- the 13* archieves.</li> <li>Full FDS simulation data of the mirco-combustion calorimeter (MCC) simulations of the best parameter sets per generation of the IMP runs, for jacket and insulator materials.</li> <li>Full FDS simulation data of the Cone Calorimeter simulations of the best parameter sets per generation of the IMP runs, for all three (25 kW/m², 50 kW/m², 75 kW/m²) incident heat flux conditions.</li> <li>FDS input files for the MT3 simulations, but full data only for the best parameter sets per IMP run (see below).</li> <li>Jupyter notebooks used for the analysis of the simulation responses including the scripts and plots generated for, and used in, the paper (RunReports).</li> <li>A general information directory, containing the FDS input file templates, experimental data used as target and Python scripts containing helper functions.</li> <li>Videos of a qualitative comparison of the SmokeView animation of the best parameter set in a cable tray simulation against a video from the experiment and an animation of the GAUGE_HEAT_FLUX development for the same simulation over the course of the simulation.</li> </ul> <p>Due to the size of the MT3 simulation data, only the FDS input files for the best parameter sets per generation are uploaded. Complete FDS simulation data is only provieded for the best perameter set of each IMP run, these are :</p> <p>IMP run, best rep.<br> --------------------------------<br> imp_13b, 110751<br> imp_13c, 121106<br> imp_13d, 137738<br> imp_13e, 97493<br> imp_13f, 91988<br> imp_13g, 86988<br> imp_13h, 17480<br> imp_13b_1, 19033<br> imp_13b_2, 25043<br> imp_13b_3b, 24149<br> imp_13b_4, 29666<br> imp_13h_1, 10685<br> imp_13h_2, 10024<br> imp_13h_3, 10109<br> imp_13i, 13253</p> <p> </p> <p>Note: The individual runs of the IMP are named differently as compared to the labeling used in the paper, as described below:</p> <p>IMP run, label in paper<br> --------------------------------</p> <p>imp_13b, T<sub>b</sub><br> imp_13c, T<sub>a</sub><br> imp_13d, T<sub>c</sub><br> imp_13e, T<sub>a,b,c</sub><br> imp_13f, T<sub>b,c</sub><br> imp_13g, T<sub>a,c</sub><br> imp_13h, T<sub>a,b,c</sub>L<sub>A,L1,HC</sub><br> imp_13b_1, T<sub>b</sub>L<sub>1</sub><br> imp_13b_2, T<sub>b</sub>P<sub>L1</sub><br> imp_13b_3b, T<sub>b</sub>P<sub>L1</sub>L<sub>1</sub><br> imp_13b_4, T<sub>b</sub>P<sub>L2,HT</sub><br> imp_13h_1, T<sub>a,b,c</sub>P<sub>A,L1,HC</sub>L<sub>1</sub><br> imp_13h_2, T<sub>a,b,c</sub>P<sub>A,L1,HC</sub>L<sub>2</sub><br> imp_13h_3, T<sub>a,b,c</sub>P<sub>A,L1,HC</sub>L<sub>3</sub><br> imp_13i, T<sub>b</sub>P<sub>A,L1,HC</sub></p> <p> </p> <p>Version 2 changes:</p> <p>Added pre-print.</p> <p> </p> <p>Version 3 changes:</p> <p>Added new files that where produced during the revision process, after the original manuscript got rejected by the Fire Safety Journal. This revision corresponds to the intitial manuscript that was submitted to the journal <a href="https://www.mdpi.com/journal/fire">Fire</a>. The respective Zip archieves are labeled with a "_Revision01".</p>
Data for paper "Effects of inflow conditions on plunge points and vertical profiles of turbidity currents on sloping flume based on 3D numerical simulation"
<p>This set of xlsx files, metadata of model results and Matlab code accompanies the manuscript "Effects of inflow conditions on plunge points and vertical profiles of turbidity currents on sloping flume based on 3D numerical simulation" by Ruoyin Zhang, Baosheng Wu, and Bangwen Zhang. This is the first release of the data.</p>
Data from: Numerical ordinality in a wild nectarivore
<p>Ordinality is a numerical property that nectarivores may use to remember the specific order in which to visit a sequence of flowers, a foraging strategy also known as traplining. In this experiment, we tested whether wild, free-living rufous hummingbirds (Selasphorus rufus) could use ordinality to visit a rewarded flower. Birds were presented with a series of linear arrays of 10 artificial flowers; only one flower in each array was rewarded with sucrose solution. During training, birds learned to locate the correct flower independent of absolute spatial location. The birds showed no significant decrease in accuracy depending on which ordinal position (1st, 2nd, 3rd or 4th) was rewarded, which suggests that they used an object-indexing mechanism of numerical processing, rather than a magnitude-based system. When distance cues between flowers were made irrelevant during test trials, birds were still able to locate the correct flower. The distribution of errors during both training and testing indicates that the birds may have used a so-called 'working up' strategy to locate the correct ordinal position. These results provide the first demonstration of numerical ordinal abilities in a wild vertebrate and suggest that such abilities could be used during foraging in the wild.</p>
Spatial-numerical associations in humans
<p>Number sense requires an ability to estimate values and respective differences - although how brains most efficiently processes information remains unknown. We tested if participants demonstrate processing preferences for horizontal or vertical representations during paired number comparisons. For numbers above the subitizing range of 1-4 with the largest number positioned upwards, participants demonstrated significantly faster and more accurate responses. </p>
Stability properties of a projector-splitting scheme for dynamical low rank approximation of random parabolic equations - Numerical tests
<p>Code used to obtain numerical results for the work titled "Stability properties of a projector-splitting scheme for dynamical low rank approximation of random parabolic equations".</p> <p>Associated publication (pre-print) is available at https://arxiv.org/abs/2006.05211</p>
Data Supplement for "A unified numerical model for wetting of soft substrates"
<p>This dataset contains the data for Fig. 3(a) of our publication</p> <p><em>Aland, S. & Mokbel, D.<br> A unified numerical model for wetting of soft substrates<br> (submitted to International Journal for Numerical Methods in Engineering 2020).</em></p> <p>The data are stored in the files "PresentSimulation.csv", <span class="math-tex">\(\)</span>"ReferenceSolution.csv" and "Experiments.csv".</p> <p>We provide a MLX-File (Live Code File Format), which can be called in a MATLAB editor by entering "Fig3a_live".<br> Alternatively, we also provide a M-File that can be used in the same manner, entering "Fig3a" in a MATLAB editor.</p> <p>We used MatlabR2019b.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Numerical model code, input files and output data for publication ``Mixing and Transformation in a Deep Western Boundary Current: a case study''
<p>Contains numerical model data (code, input files, selected output) to supplement publication ``Mixing and Transformation in a Deep Western Boundary current'', by Spingys and co-authors. All umerical model data, including any errors, is the responsibility of Sonya Legg. This data set will allow reproduction of simulations used in the above-referenced paper.</p>
Data from: Numerical models for assessing the risk of leaflet thrombosis post-transcatheter aortic valve-in-valve implantation
<p>Leaflet thrombosis has been suggested as the reason for the reduced leaflet motion in cases of hypoattenuated leaflet thickening of bioprosthetic aortic valves. This work aimed to estimate the risk of leaflet thrombosis in two post-ViV configurations, using five different numerical approaches. Realistic ViV configurations were calculated by modeling the deployments of the latest version of transcatheter aortic valve devices (Medtronic Evolut PRO, Edwards SAPIEN 3) in the surgical Sorin Mitroflow. Computational fluid dynamics simulations of blood flow followed the dry models. Lagrangian and Eulerian measures of near-wall stagnation were implemented by particle and concentration tracking, respectively, to estimate the thrombogenicity and to predict the risk locations. Most of the numerical approaches indicate on a higher leaflet thrombosis risk in the Edwards SAPIEN 3 device because of its intra-annular implantation. The Eulerian approaches estimated high-risk locations in agreement with the WSS separation points. On the other hand, the Lagrangian approaches predicted high-risk locations at the proximal regions of the leaflets matching the low WSS magnitude regions of both TAVI models and reported clinical and experimental data. The proposed methods can help optimizing future designs of transcatheter aortic valves with minimal thrombotic risks.</p>
FIGURE 2. Caecid growth stages. Roman numerals identify and arrows delimit each stage. A in A Rosetta Stone for eastern Pacific Caecidae (Gastropoda: Caenogastropoda)
FIGURE 2. Caecid growth stages. Roman numerals identify and arrows delimit each stage. A. Arrow pointing to an incised line. B. Arrow pointing to a suture. C. Arrow pointing to area with pronounced increase in diameter. D. Arrow pointing to change in sculpture. E. Arrow pointing to a varix.
Experimental Data for "Seismic wave attenuation and dispersion due to partial fluid saturation: Direct measurements and numerical simulations based on X-Ray CT"
<p>Experimental Data from a Berea sandstone sample. Includes X-ray CT scans and mechanical response of sample.</p> <p>Abstract</p> <p>Quantitatively assessing seismic attenuation caused by fluid pressure diffusion (FPD) in partially saturated rocks is challenging because of its sensitivity to the spatial fluid distribution. To address this challenge we performed depressurisation experiments to induce the exsolution of carbon dioxide from water in a Berea sandstone sample. In a first set of experiments we used medical X-ray computed tomography (CT) to characterise the fluid distribution. At an equilibrium pressure of ~1 MPa and applying a fluid pressure decline rate of ~0.6 MPa per minute, we allowed a change in saturation of less than 1 %. The gas was heterogeneously distributed along the length of the sample, with most of the gas exsolving near the sample outlet. In a second set of experiments, at the same pressure and temperature, following a very similar exsolution protocol, we measured the frequency dependent attenuation and modulus dispersion between 0.1 and 1000 Hz using the forced oscillation method. We observed significant attenuation and dispersion in the extensional and bulk deformation modes, however not in the shear mode. Lastly, we use the fluid distribution derived from the X-ray CT as an input for numerical simulations of FPD to compute the attenuation and modulus dispersion. The numerical solutions are in close agreement with the attenuation and modulus dispersion measured in the laboratory. Our methodology allows for accurately relating attenuation and dispersion to the fluid distribution, which can be applied to improving the seismic monitoring of the subsurface.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.