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6 results for “Nuclear physics”
Detailed abundances based on different nuclear physics for theoretical r-process scenarios
<p>This data set contains detailed abundances (at a time t=10^6 years after the event) for individual trajectories for seven different simulations of potential r-process sites, and based on nine different combinations of nuclear mass models and fission fragment distribution models. The data have been used and are discussed in Cote, Eichler, Yagüe, et al. (https://ui.adsabs.harvard.edu/abs/2020arXiv200604833C/abstract) to determine the isotopic ratios of I129/Cm247 and compare them to meteoritic data.</p> <p>Furthermore, a code is included which samples a subset of trajectories reproducing the measured meteoritic I129/Cm247 abundance ratio of 438 +- 92. See the README file and the publication (https://ui.adsabs.harvard.edu/abs/2020arXiv200604833C/abstract) for more details.</p>
The dataset for publication "Characterization of scintillating materials in use for brachytherapy fiber based dosimeters" by S. Commeti, et al., Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2022.
<p>This dataset is related to paper journal paper with DOI: <a href="http://dx.doi.org/10.1016/j.nima.2022.167083">10.1016/j.nima.2022.167083</a>.</p> <p>The dataset contains raw txt file and matlab files on the transmittance and the attenuation of Gadox and YVO specimens. </p> <p>Data files were prepared by agnieszka.gierej@vub.be</p>
r-process abundances in neutron-rich merger ejecta given different theoretical nuclear physics inputs
<p>This data release contains nucleosynthesis predictions for the r-process abundances presented in Côté, Eichler, Yagüe, Vassh et al. (2021) for compact object merger ejecta based on the publicly available simulation trajectories of Rosswog et al. (2013). All ejecta for the merger scenarios considered here are very neutron-rich (Ye ~ 0.016-0.11). Calculations were performed with the PRISM code (Mumpower et al. 2018) which accounts for nuclear reheating (here with a reheating efficiency of 50%). Results are reported for several different theoretical nuclear physics inputs but all calculations make use of the GEF fission yield prescription (see Vassh et al. 2019). All abundances are given at 1 Myr (10^6 years) post-merger. Please see the README file for more details and references.</p> <p>When using these nucleosynthesis yields, please cite this Zenodo data release (Vassh et al. 2021), and refer to Vassh et al. (2019) and Côté, Eichler, Yagüe, Vassh et al. (2021) for further details on the nuclear data applied as well as Rosswog et al. (2013), Piran et al. (2013), and Korobkin et al. (2012) for further details on the merger ejecta trajectories.</p>
NMMA: A nuclear-physics and multi-messenger astrophysics framework to analyze binary neutron star mergers
<p>Data release associated with the preprint "<em>NMMA: A nuclear-physics and multi-messenger astrophysics framework to analyze binary neutron star mergers</em>"</p> <p>Data includes:</p> <p>EOS files:</p> <ul> <li>5000 eos files with radius (km), mass (Msun), and tidal deformability as columns stored under eos/eos_data</li> <li>prior probabilities for the EOSs are stored in eos/eos_prior_probability.dat</li> </ul> <p>Posterior samples:</p> <ul> <li>Posterior samples based on the analysis of GW170817 and AT2017gfo stored in posterior_samples/GW170817-AT2017gfo_posterior_samples.dat</li> <li>Posterior samples based on the analysis of GW170817, AT2017gfo, and the afterglow of GRB170817A are stored in posterior_samples/GW170817-AT2017gfo-GRB170817A_afterglow_posterior_samples.dat</li> </ul> <p> </p>
Metadata for Sensitivity of He Flames in X-ray Bursts to Nuclear Physics
<p>Metadata, input files, scripts, and jupyter notebook used for the 2D X-ray burst described in paper: "Sensitivity of He Flame in X-ray Burst to Nuclear Physics". The job_info files contain the git hashes of all software used as well as the compiler versions and flags. All *front.dat contains data to generate the flame frot position vs time plot. This data can be generated using the Castro/Exec/science/flame_wave/analysis/front_tracker.py in https://github.com/AMReX-Astro/Castro. All *density.dat files contain the data for density-weighted temperature and nuclear energy generation rate plot. These data can be obtained by using the function: get_weighted_profile(), in the xrb_paper.ipynb. All *cpu.txt files contain the data to generate the number of CPU hours per simulation time plot. These data can be obtained using get_cpu_time.py. All *sum.dat files contain the data for the total mass of C12, O16, Ne20, Mg24, Si28, and S32 over time. These data can be obtained by using amrex/Tools/Plotfile/fvolumesum.cpp in https://github.com/AMReX-Codes/amrex/blob/development/Tools/Plotfile/fvolumesum.cpp. </p>
Impact of the Rapid Normalization of Chronic Hyperglycemia and the Practice of Moderate Physical Activity on the "Receptor Activator of Nuclear Factor-kappa B Ligand / Osteoprotégérine (RANKL / OPG) S
ClinicalTrials.gov study NCT04893135. IPD Sharing: NO. Countries: 1. Publications: 0.
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OpenNeuro
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