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1,206 results for “gamma”
Auditory Gamma Entrainment
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Gamma dose rate monitoring using a Silicon Photomultiplier-based plastic scintillation detector
<p>Data set in support of the publication "Gamma dose rate monitoring using a Silicon Photomultiplier-based plastic scintillation detector". It contains measurement campaign data, radionuclide sources data, measurement count rate per radionuclide.</p>
Chlorophyll a concentration, particulate organique carbon, and particle mean size index [gamma; 0.2 - 20 µm] measured using an hyperspectral spectrophotometer [ACS, Wetlabs] during the Tara Pacific Expedition 2016-2018
<p>The Tara Pacific expedition (2016-2018) sampled coral ecosystems around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples (Gorsky et al. 2019, Planes et al. 2019, Flores et al. 2020). The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide the continuous dataset originating from the hyperspectral and multispectral spectrophotometers [ACS] instruments acquiring continuously during the full course of the campaign. Surface seawater was pumped continuously through a hull inlet located 1.5 m under the waterline using a membrane pump (10 LPM; Shurflo), circulated through a vortex debubbler, a flow meter, and distributed to a number of flow-through instruments. An [ACS] spectrophotometer (WETLabs) measured hyper-spectral (4 nm resolution) attenuation and absorption in the visible and near infrared except between Panama and Tahiti where an AC-9 multispectral spectrophotometer (WETLabs) was used instead. The flow was automatically directed through a 0.2 µm filter for 10 minutes every hour before being circulated through the spectrophotometer to eliminate the impact of biofouling and instrument drift and estimate particulate absorption [ap] and attenuation [cp] (Slade et al. 2010). Chlorophyll a content was estimated from particulate absorption line height at 676 nm (Boss et al. 2001). The particulate organic carbon concentration [poc] was estimated using an empirical relation (Gardner et al. 2006) between measured [poc] and measured [cp]. An indicator for size distribution of particles between 0.2 and ~20 µm [gamma] was calculated from [cp] (Boss et al 2001). The data was processed with custom software for underway optical data (InLineAnalysis software available on GitHub). The detailed information regarding the data processing is given in the processing report attached with the data and in Lombard et al. (In prep.). These results are preliminary: no matchup with in-situ chlorophyll from HPLC or [poc] measurements were performed.</p>
Data in New $^{63}$Ga(p,$\gamma$)$^{64}$Ge and $^{64}$Ge(p,$\gamma$)$^{65}$As reaction rates corresponding to the temperature regime of thermonuclear X-ray bursts
<p>Abstract quoted from <a href="https://doi.org/10.1103/PhysRevC.110.065804" target="_blank" rel="noopener">Physical Review C 110 (2024) 065804</a> [<a href="https://arxiv.org/abs/2406.14624">arXiv:2406.14624</a>] </p> <p>We compute the $^{63}$Ga(p,$\gamma$)$^{64}$Ge and $^{64}$Ge(p,$\gamma$)$^{65}$As thermonuclear reaction rates using the latest experimental input supplemented with theoretical nuclear spectroscopic information. The experimental input consists of the latest proton thresholds of $^{64}$Ge and $^{65}$As, and the nuclear spectroscopic information of $^{65}$As, whereas the theoretical nuclear spectroscopic information for $^{64}$Ge and $^{65}$As are deduced from the full <em>pf</em>-shell space configuration-interaction shell-model calculations with the GXPF1A Hamiltonian. Both thermonuclear reaction rates are determined with known uncertainties at the energies that correspond to the Gamow windows of the temperature regime relevant to type I x-ray bursts, covering the typical temperature range of the thermonuclear runaway of the GS 1826$-$24 periodic bursts and SAX J1808.4$-$3658 photospheric radius expansion bursts. </p>
Dataset: Environmental Gamma Dose Rate Measurements using CZT Detectors
<h1>Scope</h1> <p>This dataset compiles the raw and partely processed data for the manuscript <em>Environmental Gamma Dose Rate Measurements using CZT</em><br><em>Detectors </em>by Sebastian Kreutzer, Loïc Martin, Didier Miallier, and Norbert Mercier. </p> <h1>Dataset structure</h1> <ul> <li>00_Measurement_Data: All original spectra recorded with a Kromek GR1+ and Kromek RayMon10 GR1 detector. All files have the file ending .spe</li> <li>10_GEANT4 modelling results as .xlsx and .ods + simulation code in ZIP file</li> <li>20_System_Calibrations: The final detector calibration results as .rda (external representation of R objects)</li> <li>30_R_Scripts: A compact version of R scripts used to derive the results in the manuscript as HTML and Quatro file</li> <li>40_RadionuclideComposition_WH2024: Raw data from the radionuclide measurements of sample WH2024 (.ud, .pdf)</li> <li>60_RadionuclideComposition_Flossi: Radionuclide concentrations of the granute block Flossi extracted from an unpublished Diplom thesis by Uwe Rieser (1991)</li> <li>70_Heidelberg_Dataset4gamma: Dataset for the R package 'gamma' with nuclide concentration results for Weiße-Hohl, Flossi and calculated dose rates </li> <li>80_Strain_Relief_3D_printing: Construction files for printing the strain relief adapter for the GR1. Please note that all files in this subfolder are subject to CC BY-NC licence conditions, excluding commercial use. </li> </ul> <p> </p>
Simulation of the Galactic field millisecond pulsar population and its gamma- and X-ray emission
<p>Monte Carlo simulation of the millisecond pulsar population in the Galactic field. The simulation includes four spatial components:</p> <ul> <li>the disk;</li> <li>the boxy bulge;</li> <li>the nuclear stellar cluster;</li> <li>the nuclear stellar disk.</li> </ul> <p>The last 3 components together form the Galactic bulge. There is one file per component, each containing at least 100 Monte Carlo simulations. Each line contains:</p> <ul> <li>the longitude L in deg;</li> <li>the latitude B in deg;</li> <li>the line of sight S in kpc;</li> <li>the 0.1-100 GeV gamma-ray flux in erg/cm^2/s;</li> <li>the X-ray spectral index;</li> <li>the gamma-to-X flux ratio, where the gamma-ray flux is the same as in the fourth column and the X-ray flux is the 2-10 keV unabsorbed one</li> </ul> <pre>of a simulated MSP. More information about the simulation can be found in the related paper. </pre>
Datasets for "The Search for Topographic Correlations within the Reiner Gamma Swirl"
<p>Topographic data at 0.8 m/pixel resolution with 16-bit integer values for the subregion are available as a GeoTiff file. Definition files for the K-Means and MLC algorithms in classifying swirl units for the subregion are available as ASCII text files. Masking definition files for the study region and subregion are available as shapefiles. See README file for further details.</p> <p>Data used in the research article:</p> <p>Weirich, J.R., D.L. Domingue, F.C. Chuang, A.A. Sickafoose, M.D. Richardson, Eric E. Palmer, and R.W. Gaskell, 2023. The Search for Topographic Correlations within the Reiner Gamma Swirl. The Planetary Science Journal, 4:212. DOI: 10.3847/PSJ/ace2b8</p>
Datasets for "Mapping Lunar Swirls with Machine Learning: The Application of Unsupervised and Supervised Classification Algorithms in Reiner Gamma and Mare Ingenii"
<p>Final surface reflectance data at 2.6 m/pixel resolution with floating point values are available as GeoTiff and ASCII text files. Definition files for the K-Means and MLC algorithms in classifying swirl units are also available as ASCII text files. See README file for further details.</p> <p>Data used in the research article:</p> <p>Chuang, F.C., M.D. Richardson, J.R. Weirich, A.A. Sickafoose, and D.L. Domingue, 2022. Mapping Lunar Swirls with Machine Learning: The Application of Unsupervised and Supervised Image Classification Algorithms in Reiner Gamma and Mare Ingenii. The Planetary Science Journal, 3:231. doi://10.3847/PSJ/ac8f43</p> <p> </p>
The short gamma-ray burst population in a quasi-universal jet scenario: MCMC chains
<p>The paper "The short gamma-ray burst population in a quasi-universal jet scenario" (https://arxiv.org/abs/2306.15488) described an effort in modelling the short gamma-ray burst population under the assumption that all jets share the same angular profile.</p> <p>This repository contains <strong>emcee </strong>hdf5 files with the MCMC chains corresponding to the "full sample" and "flux-limited sample" analyses described in the paper.</p>
Multisensory Gamma Entrainment
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Data suppporting Thomas, Atri & Melott "Gamma Ray Bursts: Not so Much Deadlier than We Thought"
<p>This data supports publication Thomas, Atri, and Melott 2020 "Gamma Ray Bursts: Not so Much Deadlier than We Thought"</p> <p><em>Monthly Notices of the Royal Astronomical Society</em>, Volume 500, Issue 2, January 2021, Pages 1970–1973, <a href="https://doi.org/10.1093/mnras/staa3364">https://doi.org/10.1093/mnras/staa3364</a></p> <p>The paper can be found as a pre-print: https://arxiv.org/abs/2009.14078</p> <p>Data included here are:</p> <ul> <li>Photon spectra for high-energy photon afterglow of GRB</li> <li>Ionization rate profiles calculated from photon spectra</li> <li>Surface-level muon flux</li> <li>Selected (post-processed) output from the GSFC atmosphere model, in netCDF format. </li> </ul> <p>Full raw data may be obtained upon request of the first author (Brian Thomas brian.thomas@washburn.edu).</p>
Genomes and full-length 16S reference sequences for 27 Alpha- and Gamma-Proteobacterial isolates from Red Sea Acropora corals
<p>Coral-associated bacteria contribute to the biology of their host, but the underlying molecular interactions are largely unknown. To further our functional understanding, we obtained 27 alpha- and gamma-proteobacterial isolates, many of which are Rhodobacteraceae, from three coral species of the genus <em>Acropora </em>and assembled/annotated their genomes as a resource for further functional studies. Our results reveal the immense taxonomic and genetic diversity of common alpha- and gamma-proteobacterial coral-associated bacteria. We hope these data provide a framework to study the function of specific bacteria in the coral holobiont. Isolates are available upon request.</p>
IODP Expedition 391 Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
IODP Expedition 397T Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
IODP Expedition 383 Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
Corrected IODP Gamma Ray Attenuation (GRA) densities and calculated porosities derived from the LILY Database
<div>The dataset <strong>GRA_Densities_Corrected_and_Porosities_2023-12-26.csv</strong> is derived from an analysis of data from the LILY Database (<a href="https://doi.org/10.5281/zenodo.8408296">https://doi.org/10.5281/zenodo.8408296</a>) as described in Childress et al. (2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>). The file contains over 3.7 million corrected gamma ray attenuation (GRA) bulk density data derived from the LILY database file GRA_DataLITH.csv. It also contains over 3.7 million porosity estimates that are computed from the corrected GRA bulk density using grain densities computed for each lithology from Moisture and Density (MAD) grain densities (derived from LILY file MAD_DataLITH.csv).</div> <div> </div> <div><strong>Citation: </strong>Please cite Childress et al. (2024) when using these data:</div> <div>Childress, L.B., Acton, G.D., Percuoco, V.P., Hastedt, M., 2024. The LILY Database: Linking Lithology to IODP Physical, Chemical, and Magnetic Properties Data, <em>Geochemistry, Geophysics, Geosystems, 25</em>, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>.</div> <div> </div> <div><strong>GRA_Densities_Corrected_and_Porosities_2023-12-26.csv</strong> file size uncompressed is 950 Mb.</div> <div> </div> <div><strong>Data File format:</strong></div> <ul> <li>Exp: expedition number</li> <li>Site: site number</li> <li>Hole: hole number</li> <li>Core: core number</li> <li>Type: Type indicates the coring tool used to recover the core (typical types are F, H, R, X; see Table S3 in Childress et al., 2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>).</li> <li>Sect: section number</li> <li>Offset (cm): position of the observation, measured relative to the top of a section.</li> <li>Depth CSF-A (m): location of the observation expressed relative to the top of a hole.</li> <li>Bulk density (GRA): bulk GRA density measured on whole core sections in g/cm^3.</li> <li>Timestamp (UTC): date and time the observation was made.</li> <li>Instrument: abbreviation or mnemonic for the GRA sensing device used to make this observation (GRA1 or GRA2).</li> <li>Instrument group: abbreviation or mnemonic for the data collection device (logger) used to acquire this observation (WRMSL).</li> <li>Text ID: automatically generated unique database identifier for a sample, visible on printed labels.</li> <li>Prefix: Prefix of the lithology</li> <li>Principal: Principal lithology</li> <li>Suffix: Suffix of the lithology</li> <li>Full Lithology: full lithologic name = Prefix + Principal + Suffix</li> <li>Simplified Lithology: categorization of lithologies (see Supporting Information in Childress et al., 2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>)</li> <li>Lithology Type: Sedimentary, Igneous, or Metamorphic</li> <li>Degree of Consolidation: consolidation state of the lithology.</li> <li>Lithology Subtype: categorization of lithologies (see Supporting Information in Childress et al., 2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>).</li> <li>Expanded Core Type: the actual coring type used, because some coring types were incorrectly grouped in the "Type" column (see Childress et al., 2024 for an explanation)</li> <li>Latitude (DD): Latitude in decimal degrees</li> <li>Longitude (DD): Longitude in decimal degrees</li> <li>Water Depth (mbsl): water depth in meters below sea level</li> <li>Grain Density: grain density associated with the Principal lithology, computed from MAD data</li> <li>Mean MAD Bulk Density: mean MAD bulk density associated with the Principal lithology.</li> <li>Std MAD Bulk Density: standard deviation in the MAD bulk densities for each Principal lithology.</li> <li>Correction Basis: the GRA bulk densities are corrected based on coring tool used. If the RCB was used, then the lithology cored by the RCB is used in determining the size of the correction.</li> <li>Median Difference: The correction that will be applied based on the median difference between the raw GRA bulk density and the colocated MAD bulk density for a specific Correction Basis.</li> <li>GRA Bulk Density Corrected: The corrected GRA bulk density in g/cm^3.</li> <li>Porosity: porosity computed from the corrected GRA bulk densities and grain density.</li> <li>Deviation: difference between "GRA Bulk Density Corrected" and "Mean MAD Bulk Density", which is the deviation the corrected density has from that expected for its Principal lithology.</li> <li>N Deviations: The number of standard deviations by which the observation differs from the expected value (= Deviation/(Std MAD Bulk Density)), which is useful for identifying outliers.</li> </ul> <h3>GitHub Repository:</h3> <ul> <li>Contains a few notebooks to demonstrate how to work with the LILY database</li> <li><a title="IODP LILY GitHub Repository" href="https://github.com/IODP?tab=repositories">IODP LILY GitHub Repository</a> </li> </ul>
IODP Expedition 378 Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
Dataset for the TGM2 (Protein-glutamine gamma-glutamyltransferase 2) antibody screening study
<p><strong>This antibody characterization dataset is related to the F1000 research article openly available at F1000Research.</strong></p> <p><em>This project contains the following underlying data included in a study aimed at characterizing seventeen commercial antibodies against Protein-glutamine gamma-glutamyltransferase 2 (TGM2) protein, encoded by TGM2 gene. The original study is also available on the Zenodo YCharOS community (<a href="https://doi.org/10.5281/zenodo.10819348">https://doi.org/10.5281/zenodo.10819348</a>).</em></p>
IODP Expedition 367 Natural gamma radiation
Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.
Resources for Mitigating Chemotherapy Side Effects through Targeted Gamma-Ray Delivery and CNNs
<p>This repository includes datasets and code used in the study "Mitigating Chemotherapy Side Effects through Targeted Gamma-Ray Delivery and Convolutional Neural Networks." The resources comprise:<br>- Binding Affinity Data: Used for simulations.<br>- Brain Tumor MRI and Chest CT Scan Datasets: Used for model training.<br>- Lightweight Deep CNN: Code for building and testing models.</p>
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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)
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DANDI Archive for NWB datasets
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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.