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1,574 results for “atmospheres”
ELemental abundances of Planets and brown dwarfs Imaged around Stars (ELPIS): I. Potential Metal Enrichment of the Exoplanet AF Lep b and a Novel Retrieval Approach for Cloudy Self-luminous Atmospheres
<p>This dataset contains materials presented in the paper ``ELemental abundances of Planets and brown dwarfs Imaged around Stars (ELPIS): I. Potential Metal Enrichment of the Exoplanet AF Lep b and a Novel Retrieval Approach for Cloudy Self-luminous Atmospheres'' (Zhang et al. 2023) for publication by Astronomical Journal. Please cite this paper and the Zenodo repository if these data are used in your work.</p> <p>A readme file <strong>README_ELPIS_AFLep.dat</strong> describes the content of the entire dataset. Description of other files:</p> <ul> <li><strong>tull_spectrum_AF_Lep_A.zip</strong>: Tull spectrum of the host star AF Lep A (Section 2)</li> <li><strong>stellar_parameters_AF_Lep_A.zip</strong>: Stellar parameters of AF Lep A inferred by isochrones (Section 3)</li> <li><strong>orbit_analysis_AF_Lep_b.zip</strong>: Orbit analysis of the exoplanet AF Lep b (Section 4)</li> <li><strong>RCE_dlnT_dlnP_forward_models.zip</strong>: The radiave-convective equilibrium (dlnT/dlnP) profiles of several sets of forward models (shown in Figure 5 and Section 6.2)</li> <li><strong>mini_grid_emission_spectra.zip</strong>: A mini-grid of modeled emission spectroscopy (Figure 6 and Section 6.4)</li> <li><strong>fitted_TP_profiles.zip</strong>: Fitted T-P profiles from multiple retrieval runs (Section 7)</li> <li><strong>fitted_model_spectra.zip</strong>: Fitted model spectra from multiple retrieval runs (Section 7)</li> <li><strong>retrieval_parameter_posteriors.zip</strong>: Parameter posteriors from multiple retrieval runs (Section 7).</li> </ul>
Soil and atmospheric drought explain the biophysical conductance responses in diagnostic and prognostic evaporation models over two contrasting European forest sites
<p>This contains the datasets and codes that were used to generate the results and discussions in the manuscript.</p>
Model outputs associated with "Comprehensive multiphase chlorine chemistry in the box model CAABA/MECCA: Implications to atmospheric oxidative capacity"
<p>Model outputs associated with "Comprehensive multiphase chlorine chemistry in the box model CAABA/MECCA: Implications to atmospheric oxidative capacity”.</p>
Data release: Atmospheric neutrino oscillation analysis with neutron tagging and an expanded fiducial volume in Super-Kamiokande I-V
<p><strong>Super-Kamiokande Atmospheric Neutrino Oscillation Analysis Data Release 2023</strong></p> <p>This data release accompanies the publication "Atmospheric neutrino oscillation analysis with neutron tagging and an expanded fiducial volume in Super-Kamiokande I-V." The information provided is divided into two sub-directories:</p> <ul> <li>bins: Contains data & MC counts in each analysis bin for different oscillation configurations</li> <li>chi2: Contains listings of chisquare values at each point in the oscillation parameter space scanned for the analyses described in the accompanying publication</li> </ul> <p><strong>Bin Information</strong></p> <p>This section describes the provided bin information. The `bin` subdirectory includes a ROOT file which contains binning information, data, and MC counts and MC summary statistics in each bin in the form of several ROOT trees. The contents of the ROOT file are also provided as text files within the same subdirectory.</p> <p>There are 930 bins used for atmospheric neutrino data in the analysis. Each ROOT tree and text file contains sequential listing of information for each of the 930 bins, i.e. the first entry or line of each tree and text file corresponds to the first bin, and so on.</p> <p><em>DISCLAIMER</em>: The data and MC counts and summary statistics provided are not expected to be sufficient to identically reproduce the publication fit results. The publication fit results rely on response functions of the bins to variations in the systematic uncertainty parameters which are not included in this release. Additionally, the MC oscillation probabilities used in the publication were computed individually for each MC event and are not possible to reproduce exactly using the binned event information provided with this release.</p> <p><strong>Bin Definitions</strong></p> <p>The ROOT file contains a `BinInfoTree` which lists the sample name associated with each bin, and the upper and lower bin edges of the 2D binning scheme used to bin atmospheric neutrino events. The sample names describe the selections used to place events in each bin, e.g. "subgev" and "multigev" for sub-GeV and multi-GeV events, respectively. Since data from the different SK phases are divided into different analysis samples, each sample name also lists the range of SK phases included in the same, e.g. sk1-5 for SK I, SK II, SK III, SK IV, and SK V, or sk4-5 for SK IV and SK V only. The contents of this tree are also listed in the `bin/sk_2023_BinInfo.txt` file.</p> <p><strong>Data Counts</strong></p> <p>Observed atmospheric neutrino data counts in each bin are listed in the `DataTree` within the ROOT file. The contents of this tree are also listed in the `bin/sk_2023_Data.txt` file.</p> <p><strong>MC Counts and Summary Statistics</strong></p> <p>MC counts and summary statistics of the true MC energies and directions are provided for each true neutrino type in the ROOT trees named `MC*Tree`. The information is provided for three oscillation configurations: The best-fit oscillation parameters in the normal ordering (NO), the best-fit oscillation parameters in the inverted ordering (IO), and without oscillations (NoOsc).</p> <p>The following summary statistics are provided for both the true neutrino energies and directions (cosine zenith angle) of MC events in each bin: Average, RMS, 2.3%, 15.9%, 50%, 84.1%, and 97.7% quantiles. The quantiles approximately correspond to -2, -1, 0, +1, and +2 sigma deviations from the median.</p> <p>The ROOT tree MC information is duplicated in the text files found under the `bin/[normal,inverted,unoscillated]` subdirectories, corresponding to the three oscillation scenarios.</p> <p><strong>Chisquare Information</strong></p> <p>This section describes the provided chisquare information. We provide listings of the relative chisquare values with respect to the global best-fit point in the normal ordering. The listings are provided as text files: The first columns correspond to the oscillation parameters at each grid point, while the final column lists the chisquare value. Chisquare values are provided for both the theta13-free and theta13-constrained analyses.</p> <p>ROOT files containing the 1D delta chisquare profiles for delta CP, and 2D delta chisquare profiles for allowed values of delta m^2 versus sin2 theta23 at 68% and 90% are also provided. There are two ROOT files corresponding to the contours from the theta13-free and theta13-constrained fits.</p> <p>A ROOT macro which draws the contours is also provided. It can be run using the following command from the chi2 directory:</p> <pre><code>> root draw_sk_contours.cc</code></pre> <p> </p>
Photochemical aging of aerosols contributes significantly to the production of atmospheric formic acid
<p>The dataset includes field-observed data, model input data, and filter and solution experiment data.</p>
Atmospheric ammonia reanalysis dataset
<p>The 3D reanalysis dataset for atmospheric ammonia is archived here. This dataset provides monthly data from January 2013 to June 2022, encompassing a geographic range spanning from 72° to 136° longitude and 17.5° to 54° latitude, and offering a horizontal resolution of 0.5° latitude by 0.625° longitude.</p>
Full-coverage, 1-km atmospheric carbon dioxide (CO2) dataset across China
<p>We employed an enhanced regression-based machine learning model to reconstruct full-coverage daily atmospheric CO2 concentrations in China from 2015 to 2020 at a 0.01° spatial resolution. Utilizing spatiotemporal high-resolution column-averaged dry-air mole fraction of CO2 (XCO2) data from the Orbiting Carbon Observatory 2 (OCO-2) as the dependent variable and multi-source environmental factors as independent variables, we achieved overall, spatial, and temporal cross-validation R2 [RMSE] results of 0.98 [0.74 ppm], 0.95 [1.15 ppm], and 0.93 [1.44 ppm], respectively. </p> <p> </p> <p>The annual mean and monthly mean data are archieved in Geotiff format. If you want to use this dataset, please cite the following publication. If you want to more data (e.g., daily XCO2 estimates), please contact us via qqhe@whut.edu.cn.</p> <p>--He, Q., Ye, T., Chen, X., Dong, H., Wang, W., Liang, Y., & Li, Y. (2023). Full-coverage mapping high-resolution atmospheric CO2 concentrations in China from 2015 to 2020: Spatiotemporal variations and coupled trends with particulate pollution. <em>Journal of Cleaner Production</em>, 139290. [<a href="https://doi.org/10.1016/j.jclepro.2023.139290">url</a>]</p> <p> </p> <p>If you want daily data, please go to <a href="13623590">10.5281/zenodo.13623590</a>. If you have any questions or suggestions, please contact us via qqhe@whut.edu.cn.</p> <p> </p> <p>If you want more atmospheric-related datasets, e.g., full-coverage, 1-km AOD and PM2.5 datasets over China, please go to <a href="https://doi.org/10.5281/zenodo.7229348">10.5281/zenodo.7229348.</a></p>
Data from "Atmospheric impacts of chlorinated very short-lived substances over the recent past – Part 2: Impacts on ozone" by Bednarz et al. (2023)
<p>Data from "Atmospheric impacts of chlorinated very short-lived substances over the recent past – Part 2: Impacts on ozone" by Bednarz et al. (2023), which has been accepted for publication in Atmospheric Chemistry and Physics.</p>
Physical Cold Atmospheric Plasma for the Treatment of Cervical Intraepithelial Neoplasia
ClinicalTrials.gov study NCT03218436. IPD Sharing: NO. Countries: 1. Publications: 1.
Atmospheric Pressure and Epistaxis Relationship
ClinicalTrials.gov study NCT06531577. IPD Sharing: NO. Countries: 1. Publications: 2.
Rosacea Treatment Using Non-thermal (cold) Atmospheric Plasma Device
ClinicalTrials.gov study NCT05592548. IPD Sharing: NO. Countries: 1. Publications: 1.
HYPERTENSIVE CRISIS AND ATMOSPHERIC PRESSURE RELATIONSHIP
ClinicalTrials.gov study NCT06635603. IPD Sharing: NO. Countries: 1. Publications: 3.
Effect of Cold Atmospheric Plasma on Patient Comfort During Dental Anesthesia
ClinicalTrials.gov study NCT07288125. IPD Sharing: NO. Countries: 1. Publications: 2.
Gastrointestinal Bleeding and Atmospheric Pressure Relationship
ClinicalTrials.gov study NCT06515353. IPD Sharing: NO. Countries: 1. Publications: 3.
Following of Atmospheric Pollution Exposure During Pregnancy and Effects on Health
ClinicalTrials.gov study NCT02852499. IPD Sharing: Not stated. Countries: 1. Publications: 38.
Air Cold Atmospheric Pressure Plasma Treatment for Acceleration of Venous Ulcer Healing
ClinicalTrials.gov study NCT05894096. IPD Sharing: YES. Countries: 1. Publications: 12.
Cold Atmospheric Plasma for the Endoscopic Treatment of Duodenal Polyps in Patients With Familial Adenomatous Polyposis
ClinicalTrials.gov study NCT06435533. IPD Sharing: Not stated. Countries: 1. Publications: 24.
Thyroid Abnormalities Associated With Exposure to Atmospheric Emissions of Radioactive Iodine
ClinicalTrials.gov study NCT00342693. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Effect of Cold Atmospheric Plasma on Malassezia Folliculitis
ClinicalTrials.gov study NCT04886323. IPD Sharing: NO. Countries: 1. Publications: 7.
Using a Cold Atmospheric Plasma Device to Treat Skin Disorders
ClinicalTrials.gov study NCT02759900. IPD Sharing: Not stated. Countries: 1. Publications: 2.
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
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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.