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1,584 results for “Star”
Transcriptomic response of human cells to SARS-CoV-2, RSV and H1N1 (STAR + StringTie)
<p>These data represent results from:</p> <ol> <li>Processing reads from 20 experiments (part of GSE147507) by following a standard approach, which includes using STAR to align the reads to GRCh38 and StringTie to calculate the (raw) counts per experiment. These results depict the transcriptomic response of human cells to SARS-CoV-2, RSV and H1N1, and enrichment analyses based on genes differentially expressed in SARS-CoV-2 but not in RSV or H1N1. (Authors: V.A.-P., M.G.F. and A.G.)</li> <li>Aligning to SARS-CoV-2 and quantifying reads by using HISAT2 and StringTie. (Author: C.R.-A.)</li> </ol> <p>Disclaimer: These results were obtained during the virtual BioHackathon 2020. As such, they are subject to ongoing research and have thus NOT yet undergone any scientific peer-review. That is, none of the contents can be considered to be free of errors and must be taken with caution!</p>
Astrophysical S-factors for H-burning stars
<p> This dataset contains the latest recommendations of astrophysical S-factors for nuclear fusion reactions occurring in hydrogen-burning stars, included in the <strong><em>Solar Fusion III </em></strong>decadal review article (submitted for publication, e-print available at <a href="https://arxiv.org/abs/2405.06470" target="_blank" rel="noopener">arXiv:2405.06470</a>).</p> <p> The data includes S-factors and their derivatives at zero energy (where available). That is, <em>S(0)</em>,<em> S´(0)</em>, <em>S´´(0)</em>, in units of MeV·b, b, and b/MeV, respectively. Fractional uncertainties are also provided (marked as <em>fr_err</em>). Unavailable data are marked as <em>NA</em>.</p> <p> This data was used to compute the <a href="https://zenodo.org/records/10822316">Standard Solar Models B23 / SF-III</a>. </p> <p> For further information and references consult the <strong><em>Solar Fusion III </em></strong> article linked above.</p>
Star Tv kesintisiz izle
<p><strong>Türkiye’nin En Çok İzlenen Kanalı Star Tv</strong></p> <p>Doğuş yayın grubu bünyesinde yayın yapan Star TV Türkiye de ulusal bir kanaldır. Genel yayın yönetmeni de Ömer Özgüner’dir. 1 Mart 1989 tarihinde Ahmet Özal ve Cem Uzan tarafından kurulmuştur. Star TV Türkiye’nin ilk özel televizyonudur. Her evin televizyonun da Star TV’ye muhakkak rastlamaktayız.</p> <p>Star TV tüm Türkiye’ye yayın yapar. Dizileri, yarışmaları ve UEFA şampiyonlar ligi maçlarını yayınlar. İnsanların ilgiyle izlediği bir televizyon kanalıdır. <strong>Star TV izle</strong> konusunda hem televizyon hizmet verir hem de internetten üzerinden bu kanal rahatlıkla izlenebilmektedir. Star TV’nin Televizyon frekansı 12015 MHZ ve Symbol Rate 25500 ayarlarıyla yayın yapmaktadır. FEC değeri ise 5/6, polarizasyonu da H- Yatay. Bunun yanı sıra sadece ismi yazılarak internetten de izlenebilir.</p> <p>Star TV’yi <strong>online canlı izle</strong> konusunda internete bakmak yeterlidir. İnsanların en şikayetçi olduğu konu canlı yayınların donmasıdır. Bunun içinde iyi bir internet sitesi tercih edilmesi gerekir. Web tarayıcısından <strong>kesintisiz donmadan izle</strong> araması yapanlar uygun bir internet sitesine ulaşabileceklerdir. <a href="https://www.canlitvizleme.net">Canlı tv izle</a> me sayfasında sizleride görmek isteriz.</p> <p> </p> <p><a href="https://www.canlitvizleme.net/startv"><strong>https://www.canlitvizleme.net/startv</strong></a></p>
Data from: "Deep Generative Modeling of Periodic Variable Stars Using Physical Parameters"
<p>This dataset was used for the training of a conditioned Variational Autoencoder that generates physically informed light curves of periodic variable stars. The light curves correspond to data obtained from The Optical Gravitational Lensing Experiment (<a href="https://ui.adsabs.harvard.edu/abs/1992AcA....42..253U/abstract">OGLE</a>), while ancillary information was obtained from the Gaia Data Release 2 (<a href="https://ui.adsabs.harvard.edu/link_gateway/2016A&A...595A...1G/doi:10.1051/0004-6361/201629272">GAIA DR2</a>). This repository contains the preprocessed OGLE light curves and the GAIA measurements corresponding to each cross-matched source. We also provided a subsample of cross-matched sources that were carefully validated following several steps described in the companion article (paper reference).</p> <p>This dataset is realized in tandem with the corresponding <a href="https://github.com/jorgemarpa/PELS-VAE">GitHub</a> and <a href="https://arxiv.org/abs/2005.07773">article</a>.</p> <p> </p> <p> </p>
Data Associated with Chemical Cartography with APOGEE: Two-process Parameters and Residual Abundances for 288,789 Stars from Data Release 17
<p>Stellar abundance measurements are subject to systematic errors that induce extra scatter and artificial correlations in elemental abundance patterns. We derive empirical calibration offsets to remove systematic trends with surface gravity log(g) in 17 elemental abundances of 288,789 evolved stars from the SDSS APOGEE survey. We fit these corrected abundances as the sum of a prompt process tracing core-collapse supernovae and a delayed process tracing Type Ia supernovae, thus recasting each star's measurements into the amplitudes A_cc and A_Ia and the element-by-element residuals from this two-parameter fit. Here we present the log(g)-calibrated abundances, fit parameters, process amplitudes, and element-by-element abundance residuals of 288,789 stars (310,427 spectra) in APOGEE DR17 that accompany <a href="https://arxiv.org/abs/2403.08067" target="_blank" rel="noopener">the paper</a>.</p> <p>calibration_values_final.dat contains all derived calibration offsets, including the grids of log(g) calibration offsets and zero-point offsets for two-process model analysis. The first five rows of this catalog are reproduced in Table 2 of the paper.</p> <p>logg_calib_example.ipynb is a Jupyter notebook containing Python code to load calibration_values_final.dat, extract the log(g) calibration offsets for specific element, and apply calibration offsets to 10 sample stars.</p> <p>2process_residual_abund_catalog_final.fits is the catalog of 310,427 APOGEE DR17 spectra (288,789 unique stars) containing calibrated abundances, two-process fit parameters, and abundance residuals. A full listing of columns in this catalog is given in Table 5 of the paper.</p> <p>catalog_examples.ipynb is a Jupyter notebook containing Python code to load 2process_residual_abund_catalog_final.fits, cross match with other catalogs (using AstroNN and the APOGEE DR17 Globular Cluster Value-Added Catalog as examples), and make some example plots utilizing the cross-matched data.</p>
SuperWASP Variable Star Photometry Archive (VeSPA)
<p>This data set contains the metadata for periodic variable stars that have been classified by Citizen Scientists using the <a href="https://www.zooniverse.org/projects/ajnorton/superwasp-variable-stars">SuperWASP Variable Stars Zooniverse project</a>.</p> <p>The data set is in the same format as custom data exports generated via the <a href="https://www.superwasp.org/vespa/">superwasp.org</a> website. It consists of three files:</p> <ul> <li><strong>export.csv</strong>: The main data export in CSV format, containing one row per folded light curve (i.e. multiple rows per source object).</li> <li><strong>fields.yaml</strong>: A YAML-format list of the columns included in the CSV export with an English description of each one.</li> <li><strong>params.yaml</strong>: A YAML-format copy of the search and filtering parameters which were used to generate the export (in this case this is the full data set with no filtering applied). Also includes a data version number which will be incremented with future data releases or changes to the export format.</li> </ul> <p>Photometry data is also available for download in FITS and JSON format, but this is not included here. URLs for the photometry files are included in <strong>export.csv</strong> for ease of downloading.</p> <p><strong>Acknowledgements</strong></p> <p>The SuperWASP project is currently funded and operated by Warwick University and Keele University, and was originally set up by Queen’s University Belfast, the Universities of Keele, St. Andrews and Leicester, the Open University, the Isaac Newton Group, the Instituto de Astrofisica de Canarias, the South African Astronomical Observatory and by STFC.</p> <p>The Zooniverse project on SuperWASP Variable Stars is led by Andrew Norton (The Open University) and builds on work he has done with his former postgraduate students Les Thomas, Stan Payne, Marcus Lohr, Paul Greer, and Heidi Thiemann, and current postgraduate student Adam McMaster.</p> <p>The Zooniverse project on SuperWASP Variable Stars was developed with the help of the ASTERICS Horizon2020 project. ASTERICS is supported by the European Commission Framework Programme Horizon 2020 Research and Innovation action under grant agreement n.653477</p> <p>VeSPA was designed and developed by Adam McMaster as part of his postgraduate work. This work is funded by STFC, DISCnet, and the Open University Space SRA. Server infrastructure was funded by the Open University Space SRA.</p>
Reproduction package for the paper "Bottling the Champagne: Dynamics and Radiation Trapping of Wind-Driven Bubbles around Massive Stars"
<p>Research Data Management package for "Bottling the Champagne: Dynamics and Radiation Trapping of Wind-Driven Bubbles around Massive Stars"</p> <p>Authors: Sam Geen & Alex de Koter</p> <p>Status: Accepted by MNRAS<br> This package aims to provide a full data reproduction pipeline. Please see Readme.md for more information.</p>
Relativistic description of dense matter equation of state and compatibility with neutron star observables: a Bayesian approach
<p>The general behavior of the nuclear equation of state (EOS), relevant for the description of neutron stars (NS), is studied within a Bayesian approach applied to a set of models based on a density-dependent relativistic mean-field description of nuclear matter <a href="https://arxiv.org/abs/2201.12552">Malik et al 2022</a>. The EOS is subjected to a minimal number of constraints based on nuclear saturation properties and the low-density pure neutron matter EOS obtained from a precise next-to-next-to-next-to-leading order (N$^{3}$LO) calculation in chiral effective field theory ($\chi$EFT). The number of final sample parameters corresponding to the posterior sets is around fourteen thousand. We present five EOSs among them, namely DDBl, DDBm, DDBu1, DDBu2, and DDBx. The DDBl, DDBm, DDBu2 were chosen so that the radius of the 1.4$M_\odot$ star has the lower limit, a medium value, and the upper limit of the 90% CI for the conditional probabilities $P(R|M)$. We have also included DDBu1 that has a slightly lower $R_{1.4}$ than the upper limit but lies completely inside the 90% CI for the conditional probabilities $P(R|M)$. The DDBx is the one that predicts a maximum mass of 2.5$M_\odot$ and has the following nuclear matter properties, $K_0=300$ MeV, $J_{sym,0}=30$ MeV and $L_{sym,0}=39$ MeV.</p> <p>We also release our entire sets of ~14K NS matter EOS. All the EOSs are for NS core and starting baryon density is 0.04 fm$^{-3}$. One needs to add their own choice of crust EOS for the star properties calculation. The uncertainty in star properties for the choice of the different crust has been discussed in Section 2.1 of the manuscript (arxiv: 2201.12552). </p> <pre> To extract the entire sets of ~14K NS matter EOS files, one needs to follow the steps, 1) unzip DDB_EOS_14K.zip ----------------------------Note------------------------------------- All the eos files have three columns baryon density (fm-3), energy density (MeV.fm-3), and pressure (MeV.fm-3). The starting density is 0.04 fm-3, as it is NS core eos. One needs to add their own choice of crust eos in order to calculate NS properties. ---------------------------------------------------------------</pre> <p> </p> <p> </p>
The stellar parameters and the quantities of the residual emissions of the detected active stars in the LAMOST-K2 survey
<p>The full Table 1 in <em>Investigation of stellar magnetic activity using variational autoencoder based on low-resolution spectroscopic survey</em> (Xiang, Gu & Cao, 2022, MNRAS, 514, 4781; <a href="https://arxiv.org/abs/2206.07257">arXiv:2206.07257</a>). The columns are LAMOST obsid, K2 ID, Teff, logg, [Fe/H], EW_res_Halpha, EW_res_Ca II 8498, EW_res_Ca II 8542, EW_res_Ca II 8662, log F_Halpha, log F_Ca, log R'_Halpha, log R'_Ca. The chromospheric emissions were detected and measured with the spectral subtraction technique, which removes the inactive template spectra (photospheric contribution) from the observed stellar spectra. In this work, we used the variational autoencoder neural networks to efficiently generate the proper template spectra in a data-driven manner. More details can be found in the associated paper (<a href="https://arxiv.org/abs/2206.07257">https://arxiv.org/abs/2206.07257</a>). The demo code can be found on GitHub (<a href="https://github.com/xylib/vae-for-spectroscopic-survey">https://github.com/xylib/vae-for-spectroscopic-survey</a>).</p>
RESCUER: Cosmological K-corrections for star clusters
<p>**RESCUER: Cosmological K-corrections for star clusters**<br>Authors: Marta Reina-Campos and William E. Harris<br>Date: May 2024</p> <p>Manuscript arXiV ID: arXiv:2310.02307 -- Accepted by MNRAS on May 2024</p> <p>* These tables contain the K-corrections and their uncertainties calculated for star clusters using the E-MILES stellar library.<br>* The authors assumed that star clusters are well represented by single-age and metallicity simple stellar populations (SSPs) described by the BaSTi stellar isochrones and the Chabrier 2003 initial mass function.<br>* Each table corresponds to the K-corrections and their uncertainties for a given combination of filters. The authors considered eleven broad-band filters from the HST/ACS and the JWST/NIRCam cameras. <br>* The uncertainties are estimated using all models within 0.3 dex and 20% in metallicity and age space, respectively, of the target model, and they correspond to the distances to the 10-90th percentiles of the K-corrections of these models.<br>* The tables labeled "csv_homo_filter_X_" correspond to homochromatic K-corrections within the wavelength range of the filter X, whereas those labeled "csv_hetero_filter_X_filter_Y_" contain the K-correction from the observed filter X to the rest-frame filter Y.</p> <p>Within every table:<br>* The K-corrections are given in AB mags<br>* The first column represents the redshift at which the K-correction has been calculated<br>* All of the subsequent columns correspond to the redshift evolution of the K-correction (_target) and their asymmetric uncertainties (_lower and _upper) for a given stellar population, as indicated at the top<br>* The stellar populations are labeled as in the E-MILES stellar library: e.g. "Ech1.30Zm2.27T01.0000", corresponds to a SSP of [M/H] = -2.27 and 1 Gyr old<br>* Dummy values of -100 are placed in the redshifts larger than than the one allowed by the Planck 2018 cosmology.<br>* When an uncertainty equals zero indicates that the target K-correction was smaller/larger than the 10th/90th percentile of the distribution of K-corrections. This typically occurs in models at the edge of the grid of models (i.e. at a corner).</p>
X-Shooting ULLYSES: Massive Stars at low metallicity - II. DR1: Advanced optical data products for the Magellanic Clouds
<p>Xshooter optical spectroscopic data of Magellanic Clouds targets observed by the ESO Large Program X-Shooting ULLYSES: Massive Stars at low metallicity (PI: Vink; Porgram ID: 106.2011Z). <br><br>This version is identical to the previous version but includes the LMC and SMC atlases and the static calibration files with the new flux models (all arms) and spline anchor points (only UVB).</p>
275 Candidates and 149 Validated Planets Orbiting Bright Stars in K2 Campaigns 0-10
<p>This dataset contains transit model posterior distributions and validation analyses for the 275 exoplanet candidates (in 233 systems) analyzed in Mayo et al. (2018), titled "275 Candidates and 149 Validated Planets Orbiting Bright Stars in K2 Campaigns 0-10".</p> <p>The dataset takes the form of 233 compressed directories each corresponding to an exoplanet system and titled after its EPIC ID. Within a given directory there are two numpy pickles named EPICXXXXXXXXX_chains.npy and EPICXXXXXXXXX_lnlikes.npy (where XXXXXXXXX is the 9 digit EPIC number) as well as n subdirectories, where n is the number of planet candidates in the system.</p> <p>The EPICXXXXXXXXX_chains.npy pickle is a representative sample of the posterior distribution of the transit model for a given exoplanet system. The pickle is a numpy array of size (j,k,l), where j is the number of walkers in the Markov chain Monte Carlo ensemble simulation that sampled the posterior distribution (note: we chose to fix j = 2*l), k is the number of walker steps reported in this dataset (the full posteriors were thinned down to between 750 and 10,000 steps), and l is the number of parameters in the transit model for the exoplanet system. The EPICXXXXXXXXX_lnlikes.npy pickle contains the associated ln(likelihood) values for each walker step in the previously described pickle. This pickle is a numpy array of size (j,k) where j and k are defined as above.</p> <p>The number of parameters will always be of the form 4 + 5*n, where n is again the number of planets in the systems. The first four parameters in the pickle are a baseline offset parameter for the normalized flux, a noise parameter to take the place of flux error bars, and two quadratic limb darkening parameters q<sub>1</sub> and q<sub>2</sub> based on Kipping et al. (2013). The next five parameters (and each subsequent set of five parameters in multi-candidate systems) refer to the reference epoch (a mid-transit time in BJD - 2454833), the period (in days), log<sub>10</sub>(R<sub>p</sub>/R<sub>*</sub>), the transit duration (T<sub>IV</sub>-T<sub>I</sub> in days), and the impact parameter. It should be noted that there is no consistent ordering of the planets in the posterior samples (for example, in a three planet system parameters 5-9 may refer to planet b, planet c, or planet d). Therefore, planetary periods should be used as reference to identify candidates. All parameters and the nature of the transit model are described in detail in Mayo et al. (2018).</p> <p>Each subdirectory contains the input and output of the validation analysis conducted via the VESPA validation package (Morton 2012, 2015). For additional details please refer to the relevant citations or the <a href="https://github.com/timothydmorton/VESPA">VESPA github repository</a>. Each subdirectory is named after the appropriate candidate listed in Mayo et al. (2018; specifically Tables 5 and 7).</p>
Evolution of cosmic star formation in the SCUBA-2 Cosmology Legacy Survey
<p>This dataset consists of tabulated data from the figures included in the referenced publication. The following datasets are included:</p> <p>Stacked SFR obscuration (IRX=IR/UV) of UVJ-selected star-forming galaxies:</p> <ul> <li>Weighted mean IRX as a function of Muv & stellar mass (Figure 12): MUV_irx1.dat</li> <li>Weighted mean IRX as a function of beta, over all masses and redshifts: beta_irx.dat</li> <li>Weighted mean IRX as a function of beta, binned by stellar mass (Figure 13): beta_irx_mstar.dat</li> <li>Weighted mean IRX as a function of beta, binned by redshift (Figure 14): beta_irx_z.dat</li> </ul> <p>Cosmic SFR density as a function of redshift for massive galaxies log(Ms/Msol)>10 (Figure 15):</p> <ul> <li>All mass-selected galaxies: sfrd_massive.dat</li> <li>UV-luminous galaxies Muv<M*; log(Ms/Msol)>10: sfrd_hiLUV.dat</li> <li>IR-luminous galaxies detected at 450µm: sfrd_IRdet.dat</li> </ul> <p> </p> <p>Cosmic SFR density as a function of redshift corrected to all stellar masses (Figure 16):</p> <ul> <li>All mass-selected galaxies: sfrd_uvlfcorr.dat</li> <li>UV-luminous galaxies Muv<M*; log(Ms/Msol)>10: sfrd_hiLUV_uvlfcorr.dat</li> </ul> <p>Full details of the binning and stacking methodology are explained in the paper.</p>
Composite X-EUV + optical model spectrum of the planet-hosting star HIP 67522 (HD 120411)
<p>Composite spectrum of HIP 67522 obtained by joining a Phoenix photospheric spectrum with the X-EUV spectrum synthesized from the reconstructed plasma Emission Measure Distribution (EMD) vs. temperature in chromosphere, transition region, and corona. The FITS file contains 3 extensions with the spectrum, the EMD, and the plasma chemical abundances, derived from the analysis of X-ray and FUV high-resolution spectra, obtained with simultaneous observations with XMM-Newton and HST.</p> <p>In the attached figure, the upper panel shows the specific flux at Earth, while the bottom panel is the photon flux at a distance of 1 AU. In green the Phoenix spectrum resampled to a wavelength resolution of 1 Angstrom, down to 1700 A; the XUV spectrum in the range 1-1700 A instead has a resolution of 0.01 A. The green and blue segments in the upper panel, at about 200 nm, mark the Phoenix model flux and the observed flux integrated over the OM UVM2 band.</p>
Data: Dynamics of star clusters with tangentially anisotropic velocity distribution (Pavlik+ 2024)
<p>This dataset represents the results of our <em>N</em>-body simulations of star clusters (SCs). The initial conditions of the models are fully described in the referenced journal article. In short, the SCs start from isotropic, radially anisotropic or tangentially anisotropic initial velocity distributions, and each model is evolved in an external Galactic tidal field, for two different choices of the filling factor.</p>
HI line observations of 290 evolved stars made with the Nancay Radio Telescope - I. Data: online Tables
<p>--- Table B.1: Clear NRT HI detections - basic data </p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> An ^n after a name indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2,3) RA,DEC: literature right ascension and declination of the target from Gaia EDR 3, <br> for epoch J2000.0;<br>(4) Type: target type. <br> Primarily the variability type as listed in Version 5.1 of the General Catalogue of Variable Stars, <br> GCVS (A description of GCVS types is given in https://cdsarc.u-strasbg.fr/ftp/cats/B/gcvs/vartype.txt),<br> but if an object is not included in the GCVS, other identifiers are listed in brackets: <br> HPM = high proper motion star, (OH/IR) = OH/IR maser, LPVc = long-period variable candidate, <br> PN = planetary nebula, pPN = proto-planetary nebula, and post-AGB star;<br>(5,6) Spec & ref: spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD';<br>(7,8) Teff & ref: effective temperature of the star, in K, followed by its literature reference; <br>(9) d: distance of the target, based on its parallax (mainly from the Gaia EDR3), in pc.<br> If no Gaia parallax was available a reference to the distance we adopted is given in Appendix A<br> (for RAFGL 3099, mu Cep, and V Peg);<br>(10) Vlit: published radial velocity of the target in the LSR reference frame, in km/s;<br>(11) Vexp: literature expansion velocity measured from CO or OH 1612 MHz line observations, in km/s. <br> If a pair of values was published for a two-velocity component CO line fit, the largest value is listed here;<br>(12) ref: literature references to the published Vlit and Vexp values; <br>(13) line: spectral line on which the published radial velocity measurement (Vlit) was based;<br>(14,15) Mdot & ref: literature mass loss rates, in solar masses per year, <br> followed by its literature reference.</p> <p>Notes to Table B.1:</p> <p>References: see Table B.1 in the Astronomy & Astrophysics paper.</p> <p><br>--- Table B.2: Clear NRT HI detections - HI data </p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> A ^T after a name indicates that HI line parameters are based on a 'total' spectrum, whereas <br> a ^P indicates that a 'peak' spectrum was used. <br> An ^n indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2) VHI: our central radial velocity in the LSR reference frame of the Gaussian fitted <br> to the HI profile, in km/s.<br>(3) FWHM: our full width half maximum of the Gaussian fitted to the HI line profile, in km/s;<br>(4) Speak: our peak flux density of the HI line profile, in Jy;<br>(5) diam: our estimated angular size of the HI CSE in the east-west direction, in arcmin;<br>(6) FHI: our integrated line flux of the HI profile, in Jy km/s;<br>(7) MHI: our total HI mass, in Msun;<br>(8) HI ref: references to previously published HI studies,<br> see Table B.2 in the Astronomy & Astrophysics paper.</p> <p><br>--- Table B.3: Possible NRT HI detections - basic data</p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> An ^n after a name indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2,3) RA,DEC: literature right ascension and declination of the target from Gaia EDR 3, <br> for epoch J2000.0;<br>(4) Type: target type. <br> Primarily the variability type as listed in Version 5.1 of the General Catalogue of Variable Stars, <br> GCVS (A description of GCVS types is given in https://cdsarc.u-strasbg.fr/ftp/cats/B/gcvs/vartype.txt),<br> but if an object is not included in the GCVS, other identifiers are listed in brackets: <br> HPM = high proper motion star, (OH/IR) = OH/IR maser, LPVc = long-period variable candidate, <br> PN = planetary nebula, pPN = proto-planetary nebula, and post-AGB star;<br>(5,6) Spec & ref: spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD';<br>(7,8) Teff & ref: effective temperature of the star, in K, followed by its literature reference; <br>(9) d: distance of the target, based on its parallax (mainly from the Gaia ED33), in pc.<br> If no Gaia parallax was available a reference to the distance we adopted is given in Appendix A<br> (for RAFGL 3099, mu Cep, and V Peg);<br>(10) Vlit: published radial velocity of the target in the LSR reference frame, in km/s;<br>(11) Vexp: literature expansion velocity measured from CO or OH 1612 MHz line observations, in km/s. <br> If a pair of values was published for a two-velocity component CO line fit, the largest value is listed here;<br>(12) Mdot : literature mass loss rates, in solar masses per year, <br>(13) line: spectral line on which the published radial velocity measurement (Vlit) was based;<br>(14) ref: literature references to the published Vlit, Vexp and Mdot values; </p> <p>Notes to Table B.3:</p> <p>References: see Table B.1 in the Astronomy & Astrophysics paper.</p> <p><br>--- Table B.4: Possible NRT HI detections - HI data</p> <p>Description of the columns:</p> <p>See the description of the columns of Table B.2.</p> <p><br>--- Online only Table 5: Upper limits to NRT HI lines </p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> An ^n after a name indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2,3) RA,DEC: literature right ascension and declination of the target from Gaia EDR 3, <br> for epoch J2000.0;<br>(4) Type: target type. <br> Primarily the variability type as listed in Version 5.1 of the General Catalogue of Variable Stars, <br> GCVS (A description of GCVS types is given in https://cdsarc.u-strasbg.fr/ftp/cats/B/gcvs/vartype.txt),<br> but if an object is not included in the GCVS, other identifiers are listed in brackets: <br> HPM = high proper motion star, (OH/IR) = OH/IR maser, LPVc = long-period variable candidate, <br> PN = planetary nebula, pPN = proto-planetary nebula, and post-AGB star;<br>(5,6) spec & ref: spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD';<br>(7,8) Teff & ref: effective temperature of the star, in K, followed by its literature reference; <br>(9) d: distance of the target, based on its parallax (mainly from the Gaia EDR3, in pc.<br> If no Gaia parallax was available a reference to the distance we adopted is given in Appendix A<br> (for RAFGL 3099, mu Cep, and V Peg);<br>(10) Vlit: published radial velocity of the target in the LSR reference frame, in km/s;<br>(11) Vexp: literature expansion velocity measured from CO or OH 1612 MHz line observations, in km/s. <br> If a pair of values was published for a two-velocity component CO line fit, the largest value is listed here;<br>(12) Mdot : literature mass loss rates, in solar masses per year, <br>(13) ref: literature references for Vlit, Vexp and Mdot, as applicable;<br>(14) line: spectral line on which the published radial velocity measurement (Vlit) was based;<br>(15) Speak: peak flux density of our HI line profile, in Jy;<br>(16) notes: 'old data' indicates objects observed only in 1992/1993, before the renovation of the NRT; <br> 'blue/red side' indicates that either the blue or red side of the HI profile could be used to measure <br> an upper limit to the line flux;<br>(17) HI ref: references to previously published HI studies;</p> <p>Notes to online only Table 5: </p> <p>HI references: see Table B.2 in the Astronomy & Astrophysics paper.<br>Other references: see Table B.1 in the Astronomy & Astrophysics paper.</p> <p><br>--- Online only Table 6: Confused NRT HI spectra</p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br>(2,3) RA, DEC: literature right ascension and declination of the target from Gaia EDR3, <br> for epoch J2000.0; <br>(4) type: target type. Primarily the variability type as listed in Version 5.1 of the <br> General Catalogue of Variable Stars, GCVS; but if an object is not included in the GCVS, <br> other identifiers are listed in brackets: HPM = high proper motion star, (OH/IR) = OH/IR maser, <br> LPVc = long-period variable candidate, PN = planetary nebula, pPN = proto-planetary nebula, <br> and post-AGB star; <br>(5,6) spec & ref spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD'; <br>(7,8) Vlit & ref: published radial velocity of the target in the LSR reference frame, in km/s; <br>(9) line: spectral line on which the published radial velocity measurement (Vlit) was based; <br>(10) notes: 'old data' denotes objects observed only in 1992/1993, before the renovation of the NRT<br> (see Section 3), for which no observations in digital form are available; <br>(11) HI ref: references to previously published HI studies.</p> <p>Notes to online only Table 6:</p> <p>HI references: see Table B.2 in the Astronomy & Astrophysics paper.<br>Other references: see Table B.1 in the Astronomy & Astrophysics paper.</p>
Avoided crossing in gravitational wave spectra from protoneutron star
<p>The data of the gravitational wavefroms of core-collapse supernovae, which are used in Sotani and Takiwaki (2020), Monthly Notices of the Royal Astronomical Society, Volume 498, Issue 3, pp.3503-3512.</p> <p>Data Format:</p> <p>The data are in ASCII format and the two columns are1:time time since bounce in sec</p> <p>2:hplus plus polarization of the GW amplitude. We assume the source distance of 10 kpc.</p> <p>The data are sampled at ~10 kHz, but, the sampling is not uniform in time. Therefore resampling might be necessary.</p>
Stable isotope ratios of C, N and S in Southern Ocean sea stars (1985-2017)
<p>Sea stars (Echinodermata: Asteroidea) are a key component of Southern Ocean benthos, with 16% of the known sea star species living there. In temperate marine environments, sea stars commonly play an important role in food webs, acting as keystone species. However, trophic ecology and functional role of Southern Ocean sea stars are still poorly known, notably due to the scarcity of large-scale studies. Here, we report 24332 trophic marker (stable isotopes and elemental contents of C, N and S of tegument and/or tube feet) and biometric (arm length, disk radius, arm to disk ratio) measurements in 2456 specimens of sea stars. Samples were collected between 12/01/1985 and 08/10/2017 in numerous locations along the Antarctic littoral and Subantarctic islands. The spatial scope of the dataset covers a significant portion of the Southern Ocean (Latitude: 47.717° South to 86.273° South ; longitude: 127.767° West to 162.201° East ; depth: 6 to 5338 m). The dataset contains 133 distinct taxa, including 72 currently accepted species spanning 51 genera, 20 families and multiple feeding guilds / functional groups (suspension feeders, sediment feeders, omnivores, predators of mobile or sessile prey). For 505 specimens, mitochondrial CO1 genes were sequenced to confirm and/or refine taxonomic identifications, and those sequences are already publicly available through the Barcode of Life Data System. This number will grow in the future, as molecular analyses are still in progress. Overall, thanks to its large taxonomic, spatial, and temporal extent, as well as its integrative nature (combining genetic, morphological and ecological data), this dataset can be of wide interest to Southern Ocean ecologists, invertebrate zoologists, benthic ecologists, and environmental managers dealing with associated areas.</p>
Catalogs of Eclipsing Binaries with Pulsating Components, δ Scuti stars and γ Doradus stars
<p>I present a comprehensive, up-to-date catalog of <strong>3324</strong> <strong>eclipsing binary star systems containing pulsating components </strong>(not updated in this version). The initial compilation builds upon existing lists of `oscillating Algol-type eclipsing binaries' (oEA) harboring δ Scuti stars. However, the catalog expands upon this foundation to encompass a broader range of pulsating binary systems identified in recent years. This new catalog is valuable for researchers studying binary stars' evolution and pulsating stars. It incorporates various pulsating variable types across the Hertzsprung-Russell diagram, including δ Scuti stars, γ Doradus stars, β Cephei stars, Cepheids, and red giants exhibiting solar-like oscillations. However, this catalog is NOT an exhaustive list of eclipsing binaries with pulsating components of the above types and it is subject to updates. </p> <p>Many stars in this catalog are potentially interesting for further studies. Due to potential blending and contamination in TESS photometry, the binarity of a few pulsating stars could be attributed to neighboring eclipsing binaries. Follow-up studies of individual systems are necessary to resolve contamination issues and accurately identify the true source of variability. If you use part of the catalog in your research, please cite: Zhou, A.-Y., 2010, arXiv e-prints (DOI: 10.48550/arXiv.1002.2729) (ADS: https://ui.adsabs.harvard.edu/abs/2010arXiv1002.2729Z/abstract)</p> <p>In addition, I have also included the up-to-date catalogs of <strong>118,410 δ Scuti stars</strong> and <strong>41,622 γ Doradus stars</strong>, featuring thousands of unpublished discoveries. For these two catalogs, please cite: </p> <p>Zhou, Ai-Ying, 2024, New Astronomy, Volume 105, 102081 (Published: January 2024)</p> <p>Paper in ADS: https://ui.adsabs.harvard.edu/abs/2024NewA..10502081Z/abstract</p> <p>Paper in Publisher web: https://www.sciencedirect.com/science/article/pii/S1384107623000829</p> <p>Thanks for your reading. Your comments are more than welcome!</p>
A three-dimensional map of the Milky Way using 66,000 Mira variable stars
<p>We provide here full Table 1 from Iwanek, P., et al., 2023, "A three-dimensional map of the Milky Way using 66,000 Mira variable stars", ApJS (accepted for publication, DOI: 10.3847/1538-4365/acad7a), which contains mean magnitudes, distances, extinction values, and photometric chemical types for 65,981 Galactic Miras (Iwanek2023_Table1_GalMirasDist.txt file). The corner plot, i.e., the two-dimensional projections of the multi-dimensional posterior parameter spaces fitted to the Galactic Miras distribution is presented in Figure Iwanek2023_corner_plot.png.</p> <p> </p> <p>Patryk Iwanek is partially supported by Kartezjusz program No. POWR.03.02.00-00-I001/16-00, founded by the National Centre for Research and Development, Poland. Szymon Kozłowski acknowledges the support from the National Science Centre, Poland, via grant OPUS 2018/31/B/ST9/00334. </p> <p>This publication makes use of data products from WISE, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration (NASA). This work is based in part on archival data obtained with the Spitzer Space Telescope, which was operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA.</p>
ScienceDex guides
Understand access before you commit
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.