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Dataset results
53 results for “spectral model”
Dataset of Paper "Kinetic modeling of the synergistic thermal and spectral actions on the inactivation of Cryptosporidium parvum in water by sunlight"
<p>Dataset of Paper "Kinetic modeling of the synergistic thermal and spectral actions on the inactivation of Cryptosporidium parvum in water by sunlight"</p> <p>- Data of the experimental disinfection profiles for the viable <em>C. parvum</em> oocysts.</p>
Dataset of Paper: "Kinetic modeling of the synergistic thermal and spectral actions on the inactivation of viruses in water by sunlight" (DOI:
<p>Dataset of Paper: "Kinetic modeling of the synergistic thermal and spectral actions on the inactivation of viruses in water by sunlight"</p> <p>- Data of the experimental disinfection of the MS2 virus.</p> <p>- Data of the kinetic constant value of the MS2 virus inactivation for experimental data and predicted data using action spectra models with different quantum yield values.</p> <p>- Observed and predicted kinetic constants for the MS2 inactivation by SODIS for all the scenarios and conditions studied. The predicted kinetic constants were obtained from the complete kinetic model described in this work.</p>
Modeling plant roots spectral induced polarization signature - data
<p>Data used for Figures</p>
Machine Learning Mid-Infrared Spectral Models for Predicting Modal Mineralogy of CI/CM Chondritic Asteroids and Bennu
<p>This is supporting data for the paper titled "Machine Learning Mid-Infrared Spectral Models for Predicting Modal Mineralogy of CI/CM Chondritic Asteroids and Bennu". Figure S1 compares model performance of nonnegative LSMA and PLS from Pan et al. (2015). Tables S1 through S5 provide XRD data, metadata, MIR spectra using the laboratory conversion, MIR spectra using the OTES conversion and quantitative XRD results for Murchison meteorite. </p>
Toward nebular spectral modeling of magnetar-powered supernovae
<p>The set of models analyzed in Omand and Jerkstrand (2023). The zip files contain all data for the corresponding epoch and composition. All the outputs for each model are contained in the folder with the model's ID, using the system explained in the paper.</p>
Determination of the responsivity of a predictable quantum efficient detector over a wide spectral range based on a 3D model of charge carrier recombination losses
<p>We present a method to determine the internal quantum deficiency (IQD) of a predictable quantum efficient detector (PQED) based on measured photocurrent dependence on bias voltage and a 3D simulation model of charge carrier recombination losses. The simulation model of silicon photodiodes includes wafer doping concentration, fixed charge of SiO2 layer, bulk lifetime of charge carriers and surface recombination velocity as the fitted parameters. With only one set of physical photodiode defining parameters, the simulation shows excellent agreement with experimental data at power levels from 100 μW to 1000 μW with variation in illumination beam size. We could also predict the dependence of IQD on bias voltage at the wavelength of 476 nm using photodiode parameters determined independently at 647 nm wavelength. The fitted values of doping concentration and fixed charge extracted from the simulation model are in close agreement with the expected parameter values determined earlier. At bias voltages larger than 5 V at the wavelength of 476 nm, the internal quantum efficiency of one of the tested PQEDs is measured to be 0.999 970 ± 0.000 027, where the relative expanded uncertainty of 0.000 027 is one of the lowest values ever achieved in spectral responsivity measurement of optical detectors.</p>
Stellar properties of observed stars stripped in binaries in the Magellanic Clouds - Spectral Models
<p>This Zenodo repository is one of three Zenodo repositories related to the article "Stellar properties of observed stars stripped in binaries in the Magellanic Clouds" by Y. Götberg, M.R. Drout, A.P. Ji, J.H. Groh, B.A. Ludwig, P.A. Crowther, N. Smith, A. de Koter, and S.E. de Mink. In the article, we analyze the optical spectra of ten stars and measure their stellar properties using spectral fitting. This repository contains the full spectral model grid computed using the 1D non-LTE radiative transfer code CMFGEN (see Hillier & Miller 1998 and http://kookaburra.phyast.pitt.edu/hillier/web/CMFGEN.htm). The grid spans three parameters: temperature, surface gravity, and surface hydrogen mass fraction (which also sets the surface helium mass fraction; Y = 1 - X - Z). See Section 4.1 for more details. Below, we describe the content presented here in more detail:</p> <ul> <li><strong>0_ReadMe.txt</strong>: A text file where we describe some more details regarding the content.</li> <li><strong>S41_spectral_model_grid_parameters.txt (95 KB):</strong> A table containing relevant parameter information for each model in the spectral model grid presented in Section 4.1.</li> <li><strong>S41_spectra_spectral_model_grid.tar.gz (479MB)</strong>: A .tar.gz containing the spectral energy distributions and normalized spectra in a text file for each model. The full CMFGEN models are provided as well (see below). This .tar.gz becomes 3.2 GB when inflated.</li> <li>Complete CMFGEN models for the full spectral model grid. Because of the size of these models, we group them into tarballs with one surface hydrogen mass fraction and one effective temperature, labeled for example <strong>XHs0.01_T40000.tar.gz</strong> (that is, this tarball contains a set of models with different surface gravity). Each of these have a size of ~1-3GB and when inflated the total content is ~5GB, and each model has about 500MB.</li> </ul>
Data associated with manuscript "Predicting wave-induced sediment resuspension at the perimeter of lakes using a steady-state spectral wave model"
Open the record for dataset details and reuse information.
Advancing the HEIMDALL model: seasonal spectral irradiance through the Pan-Arctic icescape. - Supplementary Data
<p>Code to replicate figures in publication Advancing the HEIMDALL model: seasonal spectral irradiance through the Pan-Arctic icescape.</p>
SITS-Former: A pre-trained spatio-spectral-temporal representation model for Sentinel-2 time series classifcation
<p>This is the unlabeled dataset we introduced in the presented paper '<strong>SITS-Former: A pre-trained spatio-spectral-temporal representation model for Sentinel-2 time series classifcation</strong>'. This dataset can be used to pre-train a specified deep learning model (such as SITS-Former, CNN-Transformer, ConvLSTM. etc) for patch-based Sentinel-2 time series classification. </p> <p>In this dataset, each sample corresponds to an unlabeled image patch time series, which is stored as a separate numpy file named '<em>unlabeled_XXX.npz</em>'. You can use '<em>np.load</em>' to open a saved '<em>.npz</em>' file and get two arrays (querid by "ts" and "doy") from the returned dictionary. The code will be released at <em>https://github.com/linlei1214/SITS-Former</em> soon.</p>
Modeling and Experimental Study of The Effect of Pore Water Velocity on the Spectral Induced Polarization Signature in Porous Media - Dataset
<p>Readme file is attached to every zip file.</p>
X-ray models from "An XMM-Newton spectral survey of 12 µm selected galaxies - I. X-ray data"
<p>Copied table models that used to be hosted at http://astro.ic.ac.uk/mbrightman/home</p> <p>from publication: https://ui.adsabs.harvard.edu/abs/2011MNRAS.413.1206B</p>
Time series of fluxes, biochemical and spectral variables simulated SCOPE model
<p>The dataset contains:</p> <ul> <li>Time series of fluxes, biochemical and spectral variables simulated with Soil Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model, parameterized using structural vegetation parameters as well as meteorological data from the research station of Majadas de Tiétar (39°56′24.68″N, 5°45′50.27″W) (Cáceres, Spain)</li> <li>Time series of decomposed Photochemical Reflectance Index, far-red solar-induced chlorophyll fluorescence and far-red fluorescence yield into seasonal, diurnal and sub-diurnal components with Singular Spectrum Analysis</li> </ul>
ScienceDex guides
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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.