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5,462 results for “binary”
Thermodynamic modelling of the nature of speciation and phase behavior of binary and ternary mixtures of formaldehyde, water and methanol
<p>Data underlying the journal article titled "Thermodynamic modelling of the nature of speciation and phase behavior of binary and ternary mixtures of formaldehyde, water and methanol" published in the Journal of Molecular Physics </p>
TINDAK PIDANA PENCUCIAN UANG HASIL DARI BINARY OPTION MELALUI PLATFORM BINOMO
<p>kejahatan dan pelanggaran beserta sanksinya seperti halnya kasus penipuan investasi sebagai pelaku tindak pidana pencucian uang maka bentuk dari pertanggungjawaban yang dapat dijeratkan terkait dengan tindak pidana pencucian uang dalam trading <em>binary option</em> pada platform Binomo terdapat didalam Undang-undang Nomor 8 Tahun 2010 tentang Pencegahan dan Pemberantasan Tindak Pidana Pencucian Uang (TPPU).</p>
Translating Non-Binary Coming-Out Reports: Gender-Fair Language Strategies and Use in News Articles
<p>Materials used for the "Translating Non-Binary Coming-Out Reports: Gender-Fair Language Strategies and Use in News Articles" paper appeared in the Journal of Specialised Translation, issue 40. </p> <p>The .xlsx files contain links to the analysed texts as well as a first annotation that was refined in SPSS (see .sav files). </p>
Dataset for "A 5.3-minute-period pulsing white dwarf in a binary detected from radio to X-rays"
<p>Photometric and spectroscopic data obtained for the manuscript "A 5.3-minute-period pulsing white dwarf in a binary detected from radio to X-rays", to be published in Nature Astronomy.</p> <p>This repository includes ultracam log files with photometry for all runs and ESO spectra.</p>
Data release: Comparing gravitational waveform models for binary black hole mergers - a hypermodels approach
<p>We include two main directories, one with the power spectral densities (PSDs) estimated for the events, and one with the posteriors of our analysis for each event.</p> <p> </p> <p><strong>PSDs</strong></p> <p>For most of the events, the sampling rate required for our analysis was higher than the one employed in LVK catalog paper studies. We upload here the PSDs computed for our analysis, divided into two main directories: 2048 for the PSDs computed with sampling rate = 2048 Hz, and 4096 for the ones computed with sampling rate = 4096 Hz. Each directory contains specific directories corresponding to each event, with the PSD for each detector as a *.dat file.</p> <p> </p> <p><strong>Posteriors</strong></p> <p>The 'posteriors.tar.gz' directory contains the *.json files, one for each event, with the results of our analysis.</p> <p> </p>
Support for Transgender and Non-Binary Individuals Seeking Vaginoplasty Study
ClinicalTrials.gov study NCT06436560. IPD Sharing: NO. Countries: 1. Publications: 0.
Transgender Men, Non-binary Persons and Testosterone Treatment BODY IDENTITY CLINIC
ClinicalTrials.gov study NCT04254354. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Prevalence and Risk Factors of HIV Infections in Transgender and Non-binary People in Flanders and Brussels (Belgium)
ClinicalTrials.gov study NCT04930614. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Binary phase separation 3D
<p>Time evolution of a binary phase separating polymer system using Cahn Hilliard equation in three dimensions.</p>
Assimilation of Satellite Radiance Data with the POD-4DEnVar Method for the Forecasting of Binary Typhoons
<p>The data and codes for ploting the figures in our manuscript are provided here.</p>
Binary Data for JGR
<p>Binary data generated by Kinetic PIC code</p>
Data from: Dispersion, sedimentation, and aggregation of multi-walled carbon nanotubes as affected by single and binary mixed surfactants
Two commonly used dispersants octyl phenol ethoxylate (Triton X-100) and sodium dodecyl sulfate (SDS) were employed to explore the effects of single or mixed surfactants on the dispersion, sedimentation, and aggregation of multi-walled carbon nanotubes (MWCNTs). Nonionic surfactant TX100 showed much superior capability to anionic surfactant SDS in dispersing MWCNTs due to the benzene ring structure in its tail group. The addition of SDS reduced the adsorption of TX100 on the surface of MWCNTs and the consequent suspension of MWCNTs. The dispersing ability of TX100-SDS binary mixture was between those of individual SDS and TX100. The introduction of SDS greatly retarded the sedimentation and aggregation of suspended MWCNTs. The critical coagulation concentration (CCC) values of suspended MWCNTs dispersed by TX100 (2000 mg/L), SDS (2000 mg/L), and TX100-SDS (2000 mg/L of each component) were 48.6, 398, and 324 mM, respectively, for the Na+ treatments. The CCC values were much lower for Ca2+ treatments, which were 30.4 and 32.1 mM, respectively, for MWCNT dispersed by TX100 and TX100-SDS mixture. Overall, these results demonstrated that although the introduction of SDS did not improve the ability of TX100 in suspending MWCNTs, the suspensions exhibited more stable properties than those dispersed by TX100 alone. Our findings have important implications on the design of surfactant mixtures and the prediction on the behavior and fate of MWCNTs in water environment.
Data from: FiSSE: A simple non-parametric test for the effects of a binary character on lineage diversification rates
It is widely assumed that phenotypic traits can influence rates of speciation and extinction, and several statistical approaches have been used to test for correlations between character states and lineage diversification. Recent work suggests that model-based tests of state-dependent speciation and extinction are sensitive to model inadequacy and phylogenetic pseudoreplication. We describe a simple non-parametric statistical test ("FiSSE") to assess the effects of a binary character on lineage diversification rates. The method involves computing a test statistic that compares the distributions of branch lengths for lineages with and without a character state of interest. The value of the test statistic is compared to a null distribution generated by simulating character histories on the observed phylogeny. Our tests show that FiSSE can reliably infer trait-dependent speciation on phylogenies of several hundred tips. The method has low power to detect trait-dependent extinction but can infer state-dependent differences in speciation even when net diversification rates are constant. We assemble a range of macroevolutionary scenarios that are problematic for likelihood-based methods, and we find that FiSSE does not show similarly elevated false positive rates. We suggest that non-parametric statistical approaches, such as FiSSE, provide an important complement to formal process-based models for trait-dependent diversification.
Community Radiative Transfer Model binary files
The Community Radiative Transfer Model (CRTM) is a JCSDA developed and distributed community model. It is used within the JCSDA JEDI framework, but is also a commonly used stand-alone radiative transfer model used across various federal agencies, research organizations, and universities. CRTM is licensed under the Creative Commons Zero license, and is fully within the public domain, including the dataset to be hosted here. The present dataset is the "binary files" that are used within the CRTM to enable it to compute clear-sky transmittances for various satellite sensors. There will be either 1 "tarball" file (tar.gz) with a total size of approximately 6 GB or less, or a structured directory consisting of 4139 files binary files consisting of big endian, little endian, netCDF3/4, pdf, and assorted binary assets totaling no more than 10GB (uncompressed). There will be occasion to add individual files, but no more than a weekly occurrence in general.
Supplementary images and table for the manuscript "A-type natriuretic peptide alters the impact of azithromycin on plank-tonic culture and on (monospecies and binary) biofilms of skin bacteria Kytococcus schroeteri and Staphylococcus aureus"
Open the record for dataset details and reuse information.
Data for temperature relaxation in strongly-coupled binary ionic mixtures
<p>This data set contains data and scripts used to generate figures in "Temperature relaxation in strongly-coupled binary ionic mixtures," R. Tucker Sprenkle, L. G. Silvestri, M. S. Murillo, S. D. Bergeson. The data for each figure is contained in a separate zip file.</p> <p>Funding for this research is gratefully acknowledged. M.S.M. and L.G.S. were supported by the U.S. Air Force Office of Scientific Research Grant No. FA9550-17-1-0394. R.T.S and S.D.B. acknowledge support from the U.S. Air Force Office of Scientific Research Grant No. FA9550-17-1-0302 and the National Science Foundation Grant No. PHY-2009999.</p>
Repurposing Domperidone in Secondary Progressive MS - A Simon 2-Stage Phase 2 Futility Trial - Table e1: Results of the binary logistic regression model
<p><b>Objective:</b> To assess whether treatment with the generic drug domperidone can reduce the progression of disability in secondary progressive multiple sclerosis (SPMS), we conducted a phase 2 futility trial following the Simon two-stage design.</p> <p><b>Methods:</b> We enrolled patients in an open-label, Simon two-stage, single-center, phase 2, single-arm futility trial at the Calgary MS Clinic if they met the following criteria: age 18 to 60 years, SPMS, screening EDSS score of 4.0 to 6.5 and screening T25FW of 9 seconds or more. Patients received domperidone 10mg QID for one year. The primary outcome was worsening of disability, defined as worsening of the T25FW performance by 20% or more at 12 months compared to at baseline. This trial is registered with ClinicalTrials.gov, number NCT02308137.</p> <p><b>Results:</b> Between February 13<sup>th</sup>, 2015 and January 3<sup>rd</sup>, 2020, 110 patients were screened, 81 received treatment, 64 completed follow-up, of whom 62 were analysed. The study did not meet its primary endpoint: 22 of 62 (35%) patients experienced significant worsening of disability, which is close to the expected proportion of 40%, and above the pre-defined futility threshold. Patients with higher prolactin levels during the study had a significantly lower risk of disability progression, which may warrant further investigation. Domperidone treatment was reasonably well tolerated, but adverse events occurred in 84% and serious adverse events in 15% of patients.</p> <p><b>Conclusions:</b> Domperidone treatment could not reject futility in reducing disability progression in SPMS. The Simon two-stage trial model may be a useful model for phase 2 studies in progressive MS.</p> <p><b>Classification of Evidence:</b> This study provides Class III evidence that in individuals with secondary progressive multiple sclerosis participating in a futility trial, domperidone treatment could not reject futility in reducing disability progression at 12 months.</p>
Binary model
<p>Simulation inputs to produce OB+BH binary. Description to be expanded later.</p> <p>Mesa version 15140</p>
APOGEE likely binaries with estimated companion masses
<p>This Zenodo has an assortment of data files related to <strong><a href="https://iopscience.iop.org/article/10.3847/2515-5172/ad5964" target="_blank" rel="noopener">Schochet, Tayar & Andrews (2024) "A Lack of Mass-Gap Compact Object Binaries in APOGEE"</a></strong> which sought to identify binary systems with a single stellar component that may be host to a "mass-gap" black hole/neutron star companion. These files utilize data from the Sloan Digital Sky Survey IV's (<a href="https://ui.adsabs.harvard.edu/abs/2017AJ....154...28B/abstract" target="_blank" rel="noopener">Blanton et al. 2017</a>) Apache Point Galactic Evolution Experiment (<a href="https://ui.adsabs.harvard.edu/abs/2017AJ....154...94M/abstract">Majewski et al. 2017</a>) Data Release 17 (<a href="https://ui.adsabs.harvard.edu/abs/2022ApJS..259...35A/abstract" target="_blank" rel="noopener">Abdurro'uf et al. 2022</a>), including stellar abundances from the ASPCAP pipeline (<a href="http://adsabs.harvard.edu/abs/2016AJ....151..144G" target="_blank" rel="noopener">Garcia Perez et al. 2016</a>) and with spectra reduced using the Doppler (<a href="http://adsabs.harvard.edu/abs/2015AJ....150..173N">Nidever et al. 2015</a>). Radius values used in the catalog come from Gaia + SED fitting (<a href="https://iopscience.iop.org/article/10.3847/1538-4365/acabc8" target="_blank" rel="noopener">Yu et al. 2023</a>). </p> <p>In this repository you will find:</p> <p><strong>Files</strong></p> <ul> <li>APOGEE_likely_binaries.csv: datafile contains basic information and IDs for the 4751 likely binary objects from our data reductions (2MASS ID, SNR, nvisits, vsini, vscatter, teff, log(g), M/H and errors for the final 3 stellar parameters).</li> <li>For systems with a radius value from <a href="https://iopscience.iop.org/article/10.3847/1538-4365/acabc8" target="_blank" rel="noopener">Yu et al. 2023</a> (4288/4751), we also provide: <ul> <li>apogee_objects_with_kiauhoku_masses.csv: this file contains masses and ages from the four grids of kiauhoku (<a href="https://ui.adsabs.harvard.edu/abs/2020ApJ...888...43C/abstract" target="_blank" rel="noopener">Claytor et al. 2020</a>) which include models from MIST (MESA Isochrones and Stellar Tracks, <a href="https://ui.adsabs.harvard.edu/abs/2016ApJ...823..102C/abstract" target="_blank" rel="noopener">Choi et al. 2016</a> & <a href="https://ui.adsabs.harvard.edu/abs/2010ascl.soft10083P/abstract" target="_blank" rel="noopener">Paxton et al. 2010</a>), YREC (Yale Rotating stellar Evolution Code, <a href="https://ui.adsabs.harvard.edu/abs/2020arXiv201207957T/abstract" target="_blank" rel="noopener">Tayar et al. 2022</a> & <a href="https://ui.adsabs.harvard.edu/abs/1989ApJ...338..424P/abstract" target="_blank" rel="noopener">Pinsonneault et al. 1989</a>) Dart/DSEP (Dartmouth Stellar Evolution Program, <a href="https://ui.adsabs.harvard.edu/abs/2008ApJS..178...89D/abstract" target="_blank" rel="noopener">Dotter et al. 2008</a>), and GARSTEC/Gars (Garching Stellar Evolution Code, <a href="https://ui.adsabs.harvard.edu/abs/2013MNRAS.429.3645S/abstract" target="_blank" rel="noopener">Serenelli et al. 2013</a> & <a href="https://ui.adsabs.harvard.edu/abs/2008Ap%26SS.316...99W/abstract" target="_blank" rel="noopener">Weiss & Schlattl 2008</a>). These are in the final columns of the csv file, and other columns include Gaia IDs, APOGEE starflag and ASPCAP flags, and RA/Dec along with APOGEE Telescope and Field information for each target.</li> <li>estimated_companions.csv: this file contains estimated minimum companion masses from the tidal synchronization method (CO_mass_rsync) and Joker method (CO_mass_joker) used in<strong> </strong>Schochet et al., and velocity semi-amplitude, eccentricity, and period values from the Joker (K_joker, e_joker, P_joker; <a href="https://ui.adsabs.harvard.edu/abs/2017ApJ...837...20P/abstract">Price-Whelan et al. 2017</a>).</li> </ul> </li> </ul> <p> </p> <p><strong>Programs</strong></p> <ul> <li>spectra_replotter.ipynb: This program replots spectra from the APOGEE servers when given a 2MASS ID, Field, and the telescope (APO/LCO) used for a specific observed object. It will then print out an image of that object's spectra with the apVisit/asVisit <a href="https://data.sdss.org/datamodel/files/APOGEE_REDUX/APRED_VERS/visit/TELESCOPE/FIELD/PLATE_ID/MJD5/apVisit.html#hdu4" target="_blank" rel="noopener">files</a> (pre-RV-shift reduction) plotted above the apStar/asStar <a href="https://data.sdss.org/datamodel/files/APOGEE_REDUX/APRED_VERS/stars/TELESCOPE/FIELD/apStar.html#hdu9" target="_blank" rel="noopener">files</a> (post-RV-shift reduction) so that radial velocity shifts can be quickly identified by eye</li> </ul> <p> </p> <p> </p> <p><em>Notes</em></p> <p>estimated_companions.csv and apogee_objects_with_kiauhoku_masses.csv contain Fiber Dispersion in their data frames, as a reference to the observed trend that vscatter tends to be much lower for objects with 0 fiber dispersion, while objects with fiber dispersion > 0 show larger vscatters, in case there is future focus on investigating this phenomena </p> <p> </p> <p>Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss4.org.</p> <p>SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, Center for Astrophysics | Harvard & Smithsonian (CfA), the Chilean Participation Group, the French Participation Group, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, the Korean Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatório Nacional / MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.</p>
binary_c V2.2.4 with binary_c-python V1.0.0 on Ubuntu 22.04 (Linux Gnome) desktop
<p>The <strong><em>binary_c</em></strong> software framework models the evolution of single, binary and multiple stars, including stellar evolution and nucleosynthesis. It is desgined for stellar population calculations, so is lightweight and versatile, and its support software contains tools for development and data analysis. <strong><em>binary_c</em></strong> is happy in standalone, virtual and HPC environments. Builds on <a href="https://en.wikipedia.org/wiki/Linux">Linux</a>, <a href="https://en.wikipedia.org/wiki/MacOS">OSX</a> and <a href="https://en.wikipedia.org/wiki/Windows_Subsystem_for_Linux">WSL</a>.</p> <p>This is version 2.2.4 of binary_c, with binary_c-python 1.0.0, installed on Kubuntu 24.04 desktop running a Linux kernel. Many useful tools are pre-installed, such as GCC, Clang, meson, ninja, valgrind, emacs, GSL, kcachegrind, gdb, gnuplot, and Jupyter so you can run binary_c-python's notebooks. Also included are commands to run either the latest stable versions or master versions straight from the gitlab repository.</p> <p>Homepage: <a href="https://binary_c.gitlab.io/">https://binary_c.gitlab.io/</a></p> <p>Login details:</p> <ul> <li>User: binary_c</li> <li>Password: binary_c</li> </ul> <p>The virtual machine is compressed with xzip, so you will need to decompress it before use.</p>
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
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.