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11 results for “energy spectrum”
Supplementary Data for Inhomogeneous Energy Injection in the 21-cm Power Spectrum: Sensitivity to Dark Matter Decay
<p>This dataset contains the interpolation tables for use with the DM21cm code release as part of "Inhomogeneous Energy Injection in the 21-cm Power Spectrum: Sensitivity to Dark Matter Decay." For details on usage, see the public github repository at: https://github.com/yitiansun/DM21cm. </p>
The Cosmic-Ray Energy Spectrum
<p>This plot shows a compilation of the cosmic-ray energy spectrum measured by several experiments (after 2000).</p> <p>References are listed in a dedicated GitHub <a href="https://github.com/carmeloevoli/The_CR_Spectrum">repository</a>.</p>
Full electronic tables for 'Spectrum and energy levels of the high-lying singly excited configurations of Nd III'
<p>Full electronic versions of table extracts of the accepted version of the preprint at <a href="https://doi.org/10.48550/arXiv.2408.07830">https://doi.org/10.48550/arXiv.2408.07830</a></p>
Data from: Can IR images of the water surface be used to quantify the energy spectrum and the turbulent kinetic energy dissipation rate?
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Data files for "Curvature in the very-high energy gamma-ray spectrum of M87"
<h1>Summary</h1> <p>In this repository, we provide some auxiliary material in connection to our paper “Curvature in the very-high energy gamma-ray spectrum of M87" accepted for publication in the Astronomy and Astrophysics (A&A) Journal and available on Arxiv through the ID <a href="https://arxiv.org/abs/2402.13330" target="_blank" rel="noopener">arXiv:2402.13330</a>. For the full list of authors, please refer to the paper.</p> <p>In the publication, we study the very-high energy gamma-ray spectrum of a stacked high emission state of M87 using H.E.S.S. observations. We detect a curvature in the spectrum that is not related to the EBL absorption. In addition to that, we show that the gamma-gamma absorption by star light from the galaxy is weak to explain the measured curvature and that it is unlikely that different high states with similar spectral distribution could be able to explain the same curvature.</p> <h1>Data and example code</h1> <h2>ECSV tables</h2> <p>The ecsv tables provide the means to reproduce the figures found in the paper. They can be opened with `astropy.QTable` as demonstrated below.</p> <pre><code>from astropy.table import QTable table = QTable.read('Fig1_lightcurve_table.ecsv') print(table)</code></pre> <p>The following example shows how to reproduce Fig. A2 from the paper (the modules imported are needed in the loaded enviroment):</p> <pre><code>from astropy.table import QTable from scipy.stats import gmean %matplotlib inline import matplotlib.pyplot as plt import numpy as np import seaborn as sns from ebltable.ebl_from_model import EBL cmap = sns.color_palette("colorblind", as_cmap=True) colors = sns.color_palette("colorblind", 6) ebl = {} for m in ["finke2022", "kneiske", "dominguez-upper"]: ebl[m] = EBL.readmodel(m) lmu = np.logspace(-1,3.,100) z = 0.0042 nuInu = {} for m, e in ebl.items(): nuInu[m] = e.ebl_array(z,lmu) nuInu table = QTable.read('FigA2_EBL_ULs.ecsv') wavelengths = table["Wavelength"].value wavelengths = wavelengths counter = 0 for m in ["finke2022", "kneiske", "dominguez-upper"]: plt.loglog(lmu,nuInu[m], lw = 2.,label=f"{m} UL", color=colors[counter] ) ULs = table[f"{m} UL"][(wavelengths>12.4)*(wavelengths<40)].value plt.loglog(wavelengths[(wavelengths>12.4)*(wavelengths<40)],ULs, lw = 2., label = f"UL (this work)", ls='dashed', color=colors[counter]) plt.arrow(gmean(wavelengths[(wavelengths>12.4)*(wavelengths<40)]), np.median(ULs), 0, -0.2*np.median(ULs), head_width=5 ,head_length=0.1*np.median(ULs), alpha=0.5, color=colors[counter]) counter+=1 plt.gca().set_xlabel('Wavelength ($\mu$m)',size = 'x-large') plt.gca().set_ylabel(r'$\nu I_\nu (\mathrm{nW}\,\mathrm{sr}^{-1}\mathrm{m}^{-2})$',size = 'x-large') plt.legend(loc = 'lower center', ncol = 2) plt.tight_layout() plt.show()</code></pre> <h2>Text files</h2> <p>The text files provide the gammapy fit results for the various analyses in the main text of the paper. For a complete definition of the models, we refer the reader to the paper. The name of the file is given by <em>fit_stacked_M87_<strong>MODEL</strong>_flux_90perc_<strong>ENERGYRANGE</strong>_90perc.txt</em>, where <strong>MODEL</strong> is the spectral model fitted (e.g., <em>PLxEBLfinke2022</em> or <em>PLxEBLfinke2022-free</em> in case the EBL intensity alpha_norm is a free parameter) and <strong>ENERGYRANGE</strong> is the energy range of the reduced dataset (e.g., <em>0.3_31.6TeV</em>).</p> <p> </p>
Auto Continuous Positive Airway Pressure (CPAP) Based Energy Spectrum Analysis of Flow for Treatment of Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS)
ClinicalTrials.gov study NCT00750165. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Linking size spectrum, energy flux and trophic multifunctionality in soil food webs of tropical land-use systems
1. Many ecosystem functions depend on the structure of food webs, which heavily relies on the body size spectrum of the community. Despite that, little is known on how the size spectrum of soil animals responds to agricultural practices in tropical land-use systems and how these responses affect ecosystem functioning. 2. We studied land-use induced changes in belowground communities in tropical lowland ecosystems in Sumatra (Jambi province, Indonesia), a hotspot of tropical rainforest conversion to rubber and oil palm plantations. The study included ca. 30,000 measured individuals from 33 high-order taxa of meso- and macrofauna spanning eight orders of magnitude in body mass. Using individual body masses we calculated the metabolism of trophic guilds and used food-web models to calculate energy fluxes and infer ecosystem functions, such as decomposition, herbivory, primary and intraguild predation. 3. Land-use change was associated with reduced abundance and taxonomic diversity of soil invertebrates, but strong increase in total biomass and moderate changes in total energy flux. These changes were due to increased biomass of large-sized decomposers in soil, in particular earthworms, with their share in community metabolism increasing from 11% in rainforest to 59-76% in jungle rubber, and rubber and oil palm plantations. Decomposition, i.e. the energy flux to decomposers, stayed unchanged, but herbivory, primary and intraguild predation decreased by an order of magnitude in plantation systems. Intraguild predation was very important, being responsible for 38% of the energy flux in rainforest according to our model. 4. Conversion of rainforest into monoculture plantations is associated by an uneven loss of size classes and trophic levels of soil invertebrates resulting in sequestration of energy in large-sized primary consumers and restricted flux of energy to higher trophic levels. Pronounced differences between rainforest and jungle rubber reflect sensitivity of rainforest soil animal communities to moderate land-use changes. Soil communities in plantation systems sustained high total energy flux despite reduced biodiversity. The high energy flux into large decomposers but low energy fluxes to other trophic guilds suggests that trophic multifunctionality of belowground communities is compromised in plantation systems.
Elemental Contrast in Secondary Electron Energy Spectrum
<p>The following data is collected from a secondary electron energy spectrometer. These data are a part of the project which intended to investigate the secondary electron energy spectrum of metal and semiconductor materials </p>
Data from: Linking size spectrum, energy flux and trophic multifunctionality in soil food webs of tropical land-use systems
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SUISEI ENERGY SPECTRUM PARTICLE MEASUREMENTS V1.0
A floppy was received at IHW-Lead Center through Dr. Oyama. It contained the following description: ***SUISEI ESP / Solar Wind Parameters *** T. Mukai Institute of Space and Astronautical Science Sagamihara, Kanagawa 229 Japan
SUISEI ENERGY SPECTRUM PARTICLE MEASUREMENTS V1.0
A floppy was received at IHW-Lead Center through Dr. Oyama. It contained the following description: ***SUISEI ESP / Solar Wind Parameters *** T. Mukai Institute of Space and Astronautical Science Sagamihara, Kanagawa 229 Japan
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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
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.