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78 results for “argon”
Net community production (NCP) and gross oxygen production (GOP), based on oxygen-argon ratios and triple oxygen isotopes, from seasonal NES-LTER Transect cruises in 2018
This data package provides net community production (NCP) and gross oxygen production (GOP, a measure of gross primary production) for the winter, spring, summer, and fall Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises in 2018. Two tables are provided: a high-frequency table with NCP rates calculated from measurements of O2/Ar made continuously by an at-sea equilibrator inlet mass spectrometer (EIMS), and a low-frequency table with both NCP and GOP rates calculated for discrete samples measured post-cruise. The GOP rates were calculated from triple O2 isotopic (TOI) ratios. These data are derived from the EIMS and TOI data for the NES-LTER Transect cruises in EDI data package knb-lter-nes.6.3.
Net community production (NCP) and gross oxygen production (GOP), based on oxygen-argon ratios and triple oxygen isotopes, from seasonal NES-LTER Transect cruises in 2019
This data package provides net community production (NCP) and gross oxygen production (GOP, a measure of gross primary production) for the winter, spring, summer, and fall Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises in 2019. Two tables are provided: a high-frequency table with NCP rates calculated from measurements of O2/Ar made continuously by an at-sea equilibrator inlet mass spectrometer (EIMS), and a low-frequency table with both NCP and GOP rates calculated for discrete samples measured post-cruise. The GOP rates were calculated from triple O2 isotopic (TOI) ratios. These data are derived from the EIMS and TOI data for the NES-LTER Transect cruises in EDI data package knb-lter-nes.6.3.
Oxygen-argon dissolved gas ratios using Equilibrator Inlet Mass Spectrometry (EIMS) and triple oxygen isotopes (TOI) from NES-LTER Transect cruises, ongoing since 2018
In order to calculate net community production (NCP) rates on Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) transect cruises, gas tracer data were collected with a continuous at-sea mass spectrometer. The ratio of O2/Ar, measured continuously from underway water, yields 8,000-15,000 rates of NCP per cruise. Discrete water samples (50 to 150 per cruise) were collected for triple oxygen isotope (TOI) analysis to estimate gross primary production (GPP) rates and ratios of NCP/GPP. Along-shelf (upstream-downstream) transects were conducted in addition to the main across-shelf transect. This data package provides two types of data tables for NES-LTER transect cruises beginning in 2018: a high-frequency continuous Equilibration Inlet Mass Spectrometer (EIMS) table, provided by year, and a low-frequency discrete triple oxygen isotope (TOI) table with all years combined. Rates calculated from these measurements are provided as separate packages, per year, in the EDI repository.
Net community production (NCP) and gross oxygen production (GOP), based on oxygen-argon ratios and triple oxygen isotopes, from seasonal NES-LTER Transect cruises in 2020
This data package provides net community production (NCP) and gross oxygen production (GOP, a measure of gross primary production) for the winter, spring, and summer Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises in 2020. Two tables are provided: a high-frequency table with NCP rates calculated from measurements of O2/Ar made continuously by an at-sea equilibrator inlet mass spectrometer (EIMS), and a low-frequency table with both NCP and GOP rates calculated for discrete samples measured post-cruise. The GOP rates were calculated from triple O2 isotopic (TOI) ratios. These data are derived from the EIMS and TOI data for the NES-LTER Transect cruises in EDI data package knb-lter-nes.6.3.
Net community production (NCP) and gross oxygen production (GOP), based on oxygen-argon ratios and triple oxygen isotopes, from seasonal NES-LTER Transect cruises in 2021
This data package provides net community production (NCP) and gross oxygen production (GOP, a measure of gross primary production) for the winter and summer Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises in 2021. Two tables are provided: a high-frequency table with NCP rates calculated from measurements of O2/Ar made continuously by an at-sea equilibrator inlet mass spectrometer (EIMS), and a low-frequency table with both NCP and GOP rates calculated for discrete samples measured post-cruise. The GOP rates were calculated from triple O2 isotopic (TOI) ratios. These data are derived from the EIMS and TOI data for the NES-LTER Transect cruises in EDI data package knb-lter-nes.6.3.
Net community production (NCP) and gross oxygen production (GOP), based on oxygen-argon ratios and triple oxygen isotopes, from seasonal NES-LTER Transect cruises in 2022
This data package provides net community production (NCP) and gross oxygen production (GOP, a measure of gross primary production) for the winter and summer Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises in 2022. Two tables are provided: a high-frequency table with NCP rates calculated from measurements of O2/Ar made continuously by an at-sea equilibrator inlet mass spectrometer (EIMS), and a low-frequency table with both NCP and GOP rates calculated for discrete samples measured post-cruise. The GOP rates were calculated from triple O2 isotopic (TOI) ratios. These data are derived from the EIMS and TOI data for the NES-LTER Transect cruises in EDI data package knb-lter-nes.6.3.
COHERENT Collaboration data release from the first detection of coherent elastic neutrino-nucleus scattering on argon
<p>Release of COHERENT collaboration data from the first detection of coherent elastic neutrino-nucleus scattering (CEvNS) on argon. This data release corresponds with the results of "Analysis A" published in arXiv:2003.10630[nucl-ex]. The data release enables further studies of CEvNS.</p> <p>Use of the data release is presented in the accompanying pdf document within this submission. Example code is included within the release as part of this submission. The materials here are also available at http://coherent.ornl.gov/data/, which preserves the directory structure used within the accompanying document. Note the use of the example code in this release expects the directory structure written within the accompanying pdf document.</p>
Data for a publication "Argon plasma-modified bacterial nanocellulose: Cell-specific differences in the interaction with fibroblasts and endothelial cells"
<p>A dataset containing data for the published article "Argon plasma-modified bacterial nanocellulose: Cell-specific differences in the interaction with fibroblasts and endothelial cells".</p> <p> </p> <p>For more details, please read the <strong>README - Description of data and analysis informations.txt</strong> file.</p> <p><strong>Dataset versions:</strong></p> <p><strong>V1:</strong> The first dataset containing a majority of the data.</p> <p><strong>V2:</strong> Dataset contains all the data mentioned in the article in the appropriate file formats for long-term preservation and accessibility.</p>
Supplemental material for "Liquid argon light collection and veto modeling in GERDA Phase II"
<p>Data set for Fig. 7 of "Liquid argon light collection and veto modeling in GERDA Phase II", scientific publicaton by the GERDA Collaboration.</p>
Dataset for "Narrow range of early habitable Venus scenarios permitted by modelling of oxygen loss and radiogenic argon degassing"
<p>Code and datasets required to reproduce figures in main text of Warren & Kite 2023 "Narrow range of early habitable Venus scenarios permitted by modelling of oxygen loss and radiogenic argon degassing." https://www.pnas.org/doi/full/10.1073/pnas.2209751120</p> <p>Code and usage instructions are also available at: github.com/aowarren/Venus_O2</p> <p>After downloading, code will need to be modified to find files in chosen directories for running the full model (also requires installation of VolcGases from github.com/Nicholaswogan/VolcGases) and files for re-creating plots. All .zip files contain data used to create figures in paper. Instructions to reproduce figures below:</p> <p> </p> <p><strong>1. To reproduce full dataset</strong>, download all files excluding .zip files and install VolcGases. Modify "modular_functions_clean_redox.py" to match VolcGases installation.</p> <p><em>For runaway greenhouse runs:</em> Ensure "modular_functions_clean_redox.py" line 512 is commented out. Run "adding_dissolution_clean.py" followed by "ext1line.py" to pre-run runaway greenhouse model and save output to read into full model (this speeds up running the entire suite of "melting" models, but is not strictly necessary). Next, use "gridsearch_all_redox.csv" to set model parameters, then run "input_clean_redox.py" to initiate model. </p> <p><em>For runs without runaway greenhouse melting:</em> uncomment "modular_functions_clean_redox.py" line 512. Use "gridsearch_all_redox.csv" to set model parameters, then run "input_clean_redox.py" to initiate model. </p> <p><strong>2. To reproduce Figures 2, 3, S1, and S2</strong>, either download all zip files beginning with "Fig2_" and "Fig3_", extract all files to single location, or save all new model output into a single directory and use "plot_together.py" to generate figures (instructions contained within script). Use same script to reproduce Figures S9 and S10 with data in "t_atm_sensitivity.zip" and "bH_sensitivity.zip". </p> <p><strong>3. To reproduce Figures 4 and 5</strong>, If using new model runs to generate plots, first run "gen_data_forplots.py". Alternatively, download:</p> <ul> <li>e_statistics_nomelt_CO_FMQ0.npz </li> <li>e_wd_statistics_melt_CO_FMQ0.npz</li> <li>40_Ar_hab_dlith_KU_mix_52522.csv</li> <li>40_Ar_hab_dlith_KU_nomix_52522.csv</li> </ul> <p>Then, run maintext_plotting_new.py.</p> <p><strong>4. To reproduce Figures S5 to S8</strong>, run "Ar_plots.py". Requires: "serpent_dehyd2.csv" and "eclogite_transition.csv".</p>
Experimental raw data sets associated with certified reference material BAM-P116 (titanium dioxide) for comparison of nitrogen and argon sorption, available in the universal adsorption information format (AIF)
<p>These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.<br>The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.<br>It is recommended to use the following requirements for the molecular cross-sectional area:<br>Nitrogen: 0.1620 nm²<br>Argon: 0.1420 nm²</p> <p>Expected specific surface area for nitrogen (BET): 305 to 345 m²/g<br>Expected specific surface area for argon (BET): 300 to 310 m²/g</p> <p>Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.<br>The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.<br>These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.</p>
Calculated values of the third dielectric virial coefficient of helium-4, neon-20, and argon-40
<p>Calculated values of the third dielectric virial coefficient of helium-4 (file Ceps_He4.dat), neon-20 (file Ceps_Ne20.dat), and argon-40 (file Ceps_Ar40.dat)</p> <p>ASCII format. Each file has a header whose lines begin with # describing the content.</p> <p>For details on the calculation see <a href="https://doi.org/10.1063/5.0077684">https://doi.org/10.1063/5.0077684</a> or <a href="https://arxiv.org/abs/2111.02691">https://arxiv.org/abs/2111.02691</a></p>
QM/MM nonadiabatic trajectories for cytosine in argon, benzene and water
<p>The dataset includes all trajectories for the nonadiabatic (QM/MM) molecular dynamics simulations of cytosine in argon, benzene and water. Each tar.gz directory contains two directories: INPUT and RESULTS. In this latter one has the 50 trajectories for cytosine in argon and benzene and the 75 trajectories for cytosine in water. In the files named dyn.out one has the atomic coordinates, velocities and energies for each time step.</p>
Reactions of cold argon plasma with condensed-phase peptides and proteins for mass spectrometry imaging and structural elucidation - ESI
<p>ESI data for the paper 'Reactions of cold argon plasma with condensed-phase peptides and proteins for mass spectrometry imaging and structural elucidation'.</p>
Experimental raw data sets associated with certified reference material BAM-P115 (titanium dioxide) for comparison of nitrogen and argon sorption, available in the universal adsorption information format (AIF)
<p>These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.<br>The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.<br>It is recommended to use the following requirements for the molecular cross-sectional area:<br>Nitrogen: 0.1620 nm²<br>Argon: 0.1420 nm²</p> <p>Expected specific surface area for nitrogen (BET): 140 to 154 m²/g<br>Expected specific surface area for argon (BET): 129 to 135 m²/g</p> <p>Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.<br>The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.<br>These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.</p>
Experimental raw data sets associated with certified reference material BAM-P114 (titanium dioxide) for comparison of nitrogen and argon sorption, available in the universal adsorption information format (AIF)
<p>These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.<br>The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.<br>It is recommended to use the following requirements for the molecular cross-sectional area:<br>Nitrogen: 0.1620 nm²<br>Argon: 0.1420 nm²</p> <p>Expected specific surface area for nitrogen (BET): 24 to 25 m²/g<br>Expected specific surface area for argon (BET): 20 m²/g</p> <p>Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.<br>The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.<br>These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.</p>
Simple Liquid-Argon Track Samples (SLATS)
<p>The data set we release here covers two data domains. Each domain is populated by a variant of a LArTPC detector simulation used in the ProtoDUNE-SP experiment. The two domains differ in one feature—the detector response function. The domain real is generated with a 2D response, and the fake domain is generated with a quasi-1D response. The dataset can be used to train unpaired image translation algorithms. </p>
Argon Plasma Coagulation Versus Endoscopic Mucosal Resection for Gastric Adenoma (CLER-GA)
ClinicalTrials.gov study NCT07161479. IPD Sharing: YES. Countries: 1. Publications: 5.
Solid-liquid coexistence of neon, argon, krypton, and xenon
<p>Data for the publications "Solid-liquid coexistence of neon, argon, krypton, and xenon" by Aditya N. Singh, Jeppe C. Dyre and Ulf R. Pedersen.</p>
Low-level argon and air in helium for CNNs
<p>This repository contains datasets used for analyzing low-level argon and air impurity in helium. These datasets were utilized in the research paper titled "Impurity Gas Detection for SNF Canisters Using Probabilistic Deep Learning and Acoustic Sensing" available at (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4675917).</p> <p>Files</p> <p>1. Input_set.npy: This file contains the input dataset, consisting of excitation and gas concentration pairs.<br>2. Response_set.npy: This file contains the response dataset.<br>3. Concen_set.npy: This file contains the concentration pairs of Argon and Air used in the experiments.<br>4. Image_train.npy: This file contains the STFT spectrum data for the training set.<br>5. Image_test.npy:This file contains the STFT spectrum data for the testing set.</p> <p>Data Structure</p> <p>Image_train.npy<br>- Shape:(65,011, 38, 44, 2)<br>- Description: This array contains the STFT spectra for the training set.<br> - The first dimension (65,011) represents the number of training samples.<br> - The second and third dimensions (38, 44) represent the size of the STFT spectrum.<br> - The fourth dimension (2) represents the two channels:<br> - One channel contains the STFT of the excitation signal.<br> - The other channel contains the STFT of the response signal.</p> <p>Image_test.npy<br>- Shape: (27,862, 38, 44, 2)<br>- Description: This array contains the STFT spectra for the testing set.<br> - The first dimension (27,862) represents the number of testing samples.<br> - The second and third dimensions (38, 44) represent the size of the STFT spectrum.<br> - The fourth dimension (2) represents the two channels:<br> - One channel contains the STFT of the excitation signal.<br> - The other channel contains the STFT of the response signal.</p> <p>Input_set.npy<br>- Shape: (101,919, 253)<br>- Description: This array contains the input parameters for the ultrasonic experiments.<br> - The first 251 columns contain the excitation parameters.<br> - The last 2 columns represent the concentration pairs of Argon and Air.</p> <p>Response_set.npy<br>- Shape: (101,919, 426)<br>- Description: This array contains the ultrasonic response data corresponding to the input parameters in `Input_set.npy`.<br> - The 426 columns represent the time-series data points of the ultrasonic response.</p> <p>Concen_set.npy<br>- Shape: Corresponds to the concentration pairs of Argon and Air.<br>- Description: This array contains the concentration pairs used in the experiments.</p> <p>X_pure_new.npy<br>Shape: (4,718, 427)<br>Description: This array contains data representing pure helium samples.<br>The first 426 columns represent the response features of each sample.<br>The 427th column is the label for binary classification, and all values in this column are zeros, indicating that these are pure samples.</p> <p>X_with_impurity_new.npy<br>Shape: (101,700, 429)<br>Description: This array contains data representing samples with impurities.<br>The first 426 columns represent the response features of each sample.<br>The 427th column is the label for binary classification, and all values in this column are ones, indicating that these are impure samples.<br>The last two columns represent the concentrations of impurities in the samples.</p> <p>Citation<br>If you use this dataset in your research, please cite the above paper.</p> <p>Contact<br>For any questions or issues related to this dataset, please contact the repository owner via bozhouzh@usc.edu.</p>
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