cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5593284
title: 'Signal integrity' in the Audiovisual Media Services Directive: Process, positions and policies examined and explained

description: Tables 1 & 2 can be used as complementary material for readers of the forthcoming article (2021) in the Journal of Digital Media & Policy entitled <em>‘Signal integrity’ in the Audiovisual Media Services Directive: Process, positions and policies examined and explained.</em> Table 1 looks at the Mapping of modifications, processes and cases referred to by Article 7b and Recital 26 exemptions, while Table 2 presents the stakeholders' argumentation relating to signal integrity based on economic and cultural positions, and the scope of the measure. For the online version of the article, these tables are referred to in-text in the shape of hyperlinks and full links in the printed version. The article aims to get a broad picture of current practices, positions and policy on signal integrity. Based on the findings, this article proposes a clear framework for the implementation of Article 7b. It identifies the key considerations made in relation to exemptions and consent and reveals the positions of the key stakeholders and the vacuum that is exists at the level of MS regulation. Therefore, the concept of ‘signal integrity’ and the legal protections it sets on broadcasters’ signal will be explored.
DOI: 10.5281/zenodo.5593283
title: 'Signal integrity' in the Audiovisual Media Services Directive: Process, positions and policies examined and explained

description: Tables 1 & 2 can be used as complementary material for readers of the forthcoming article (2021) in the Journal of Digital Media & Policy entitled <em>‘Signal integrity’ in the Audiovisual Media Services Directive: Process, positions and policies examined and explained.</em> Table 1 looks at the Mapping of modifications, processes and cases referred to by Article 7b and Recital 26 exemptions, while Table 2 presents the stakeholders' argumentation relating to signal integrity based on economic and cultural positions, and the scope of the measure. For the online version of the article, these tables are referred to in-text in the shape of hyperlinks and full links in the printed version. The article aims to get a broad picture of current practices, positions and policy on signal integrity. Based on the findings, this article proposes a clear framework for the implementation of Article 7b. It identifies the key considerations made in relation to exemptions and consent and reveals the positions of the key stakeholders and the vacuum that is exists at the level of MS regulation. Therefore, the concept of ‘signal integrity’ and the legal protections it sets on broadcasters’ signal will be explored.
DOI: 10.5281/zenodo.5593238
title: Training Data for the NeonTreeEvaluation Benchmark

description: This dataset is the large training data files for the NeonTreeEvaluation Benchmark for individual tree detection from airborne imagery. For each geographic site, given by the NEON four letter code (e.g HARV -&gt; Harvard Forest), there are up to 4 files: a RGB image, a LiDAR tile, and a 426 band hyperpspectral file, and a 1m canopy height file. For more information on the benchmark, and the corresponding R package, see https://github.com/weecology/NeonTreeEvaluation_package Annotations for the tiles, made by looking at the RGB are under version control here: https://github.com/weecology/NeonTreeEvaluation/tree/master/annotations
DOI: 10.5066/p9ipkwfl
title: Data for Machine Learning Predictions of Nitrate in Groundwater Used for Drinking Supply in the Conterminous United States

description: A three-dimensional extreme gradient boosting (XGB) machine learning model was developed to predict the distribution of nitrate in groundwater across the conterminous United States (CONUS). Nitrate was predicted at a 1-square-kilometer (km) resolution for two drinking water zones, each of variable depth, one for domestic supply and one for public supply. The model used measured nitrate concentrations from 12,082 wells, and included predictor variables representing well characteristics, hydrologic conditions, soil type, geology, land use, climate, and nitrogen inputs. Predictor variables derived from empirical or numerical process-based models were also included to integrate information on controlling processes and conditions. This data release documents the model and provides the model results. The model and results are discussed in the associated journal article, Ransom and others (2021). Included in this data release are, 1) a model archive of the R project: source code, input files (including model training and hold-out data, rasters of all final predictor variables, and rasters representing domestic and public supply depth zones), and output files (output files are two rasters of predicted nitrate concentration at the depth zones typical of domestic and public supply wells), 2) a read_me file describing the model archive and an explanation of its use, and 3) tables describing model variables, model fit statistics, and model results [these tables are also included in the Supporting Information published with the journal article Ransom and others (2021)].
DOI: 10.15468/ztag53
title: Re-descriptions of eight chigger mite species (Acariformes: Trombiculidae) of the Leptotrombidium generic complex from Vietnam

description: This dataset contains the digitized treatments in Plazi based on the original journal article Stekolnikov, Alexandr A., Antonovskaia, Anastasia A. (2021): Re-descriptions of eight chigger mite species (Acariformes: Trombiculidae) of the Leptotrombidium generic complex from Vietnam. Zootaxa 5057 (3): 329-363, DOI: https://doi.org/10.11646/zootaxa.5057.3.2
DOI: 10.15139/s3/cadoyp
title: Small business revenue

description: This dataset represents the percent change in net revenue of open small businesses in North Carolina counties calculated as a seven-day moving average, which is seasonally adjusted and indexed to January 4-31 2020. The data obtained from the Opportunity Insights data repository in Github includes the daily percentage change in net revenue of open small businesses compared to January 2020 levels. The data is then aggregated as a rolling 7-day average. Twenty-two of North Carolina’s 100 counties are represented in this dataset, none of which are non-CBSA (outside of both metropolitan and micropolitan areas). Additionally, only one county is identified as having high pre-existing unemployment, and two as having lower median income. As a result, the dataset disproportionately represents relatively prosperous metropolitan centers and does not represent other regions of the state.
DOI: 10.6084/m9.figshare.16862008
title: Gene Abundances from Project: Oxidative stress enhances integrase activity during wastewater treatment

description: Gene abundances measured by qPCR:Antimicrobial resistance: (<i>intI1</i>, <i>sul1</i>, <i>sul2</i>, <i>dfrA1</i>)<i>,<br></i><i>E.coli</i> (<i>uidA</i>), <br>and total bacterial: 16S rRNA gene<br>from pilot scale constructed wetlands treating municipal wastewater.
DOI: 10.6084/m9.figshare.16862008.v1
title: Gene Abundances from Project: Oxidative stress enhances integrase activity during wastewater treatment

description: Gene abundances measured by qPCR:Antimicrobial resistance: (<i>intI1</i>, <i>sul1</i>, <i>sul2</i>, <i>dfrA1</i>)<i>,<br></i><i>E.coli</i> (<i>uidA</i>), <br>and total bacterial: 16S rRNA gene<br>from pilot scale constructed wetlands treating municipal wastewater.
DOI: 10.5281/zenodo.5575241
title: Simulations of Coronal Mass Ejections on the star ε Eridani

description: These files include simulated Titov- Démoulin CME events on the star epsilon Eridani due to be published in Ó Fionnagáin et al. (2021). These simulations are conducted using the BATS-R-US AWSOM model, defined by van der Holst et al. (2014) and Gombosi et al. (2018). Provided in this dataset are the CME events at the 10 minute post-eruption mark. The datasets are provided in binary format (.plt), readable by the Tecplot software. The columns included in this data are given below and consist of position [x,y,z], velocity [x,y,z], magnetic field [x,y,z], Alfvén wave energy densities, Pressure [electron, ion_parallel, ion_perpendicular, current [x, y, z]. variables = X [R], Y [R], Z [R], rho [g/cm^3], U_x [km/s], U_y [km/s], U_z [km/s], B_x [Gauss], B_y [Gauss], B_z [Gauss], Ehot [erg/cm^3], I01 [erg/cm^3], I02 [erg/cm^3], Pe [dyne/cm^2], P_par [dyne/cm^2], P_perp [dyne/cm^2], P [dyne/cm^2], J_x [`mA/m^2], J_y [`mA/m^2], J_z [`mA/m^2] Providing the entire dataset was unfeasible due to the large size of the data. However, the entire dataset can be made available upon reasonable request from the authors. This research was funded by the Irish Research Council (IRC).
DOI: 10.5281/zenodo.5575240
title: Simulations of Coronal Mass Ejections on the star ε Eridani

description: These files include simulated Titov- Démoulin CME events on the star epsilon Eridani due to be published in Ó Fionnagáin et al. (2021). These simulations are conducted using the BATS-R-US AWSOM model, defined by van der Holst et al. (2014) and Gombosi et al. (2018). Provided in this dataset are the CME events at the 10 minute post-eruption mark. The datasets are provided in binary format (.plt), readable by the Tecplot software. The columns included in this data are given below and consist of position [x,y,z], velocity [x,y,z], magnetic field [x,y,z], Alfvén wave energy densities, Pressure [electron, ion_parallel, ion_perpendicular, current [x, y, z]. variables = X [R], Y [R], Z [R], rho [g/cm^3], U_x [km/s], U_y [km/s], U_z [km/s], B_x [Gauss], B_y [Gauss], B_z [Gauss], Ehot [erg/cm^3], I01 [erg/cm^3], I02 [erg/cm^3], Pe [dyne/cm^2], P_par [dyne/cm^2], P_perp [dyne/cm^2], P [dyne/cm^2], J_x [`mA/m^2], J_y [`mA/m^2], J_z [`mA/m^2] Providing the entire dataset was unfeasible due to the large size of the data. However, the entire dataset can be made available upon reasonable request from the authors. This research was funded by the Irish Research Council (IRC).
DOI: 10.6084/m9.figshare.16862023
title: Supplementary Material – Flora of Pernambuco, Brazil: Bignonieae (Bignoniaceae)

description: Flora of Pernambuco, Brazil: Bignonieae (Bignoniaceae) – http://dx.doi.org/10.1590/2175-7860202172103<br><b>Appendix S1 – </b>List of additional material examined.
DOI: 10.6084/m9.figshare.16862023.v1
title: Supplementary Material – Flora of Pernambuco, Brazil: Bignonieae (Bignoniaceae)

description: Flora of Pernambuco, Brazil: Bignonieae (Bignoniaceae) – http://dx.doi.org/10.1590/2175-7860202172103<br><b>Appendix S1 – </b>List of additional material examined.
DOI: 10.5281/zenodo.5593338
title: MEaSUREs ITS_LIVE Sentinel-1 Image-Pair Glacier and Ice Sheet Surface Velocities: Version 2 (Greenland Sample Products)

description: We provide 21 sample products of MEaSUREs ITS_LIVE Sentinel-1 Image-Pair Glacier and Ice Sheet Surface Velocities: Version 2 in three test regions of Greenland Ice Sheet. The full archive of version 2 ITS_LIVE products (including image pair maps, data cubes and mosaics) from Sentinel-1 as well as other optical sensors (Landsat-4/5/6/7/8 and Sentinel-2) can be found at the ITS_LIVE project website: https://its-live.jpl.nasa.gov. <strong>Sensor</strong>: Sentinel-1A/B <strong>Processor</strong>: ISCEv2.4.1 (topsApp -&gt; Geogridv1.4.0 -&gt; autoRIFTv1.4.0) <strong>Project</strong>: NASA MEaSUREs project ITS_LIVE <strong>Region 1</strong> (69.13N, 50.88W; Jakobshavn Isbræ Glacier): 7 ascending image pairs <strong>Region 2</strong> (77.61N, 42.79W; central north of interior Greenland): 3 ascending image pairs <strong>Region 3</strong> (72.48N, 35.87W; central south of interior Greenland): 10 descending image pairs and 1 ascending image pair This serves as a supplementary dataset for the companion journal article submitted to Earth System Science Data (to appear). <strong>Acknowledgement</strong>: This effort was funded by the NASA MEaSUREs program in contribution to the Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project (https://its-live.jpl.nasa.gov/) and through Alex Gardner’s participation in the NASA NISAR Science Team.
DOI: 10.5281/zenodo.5524465
title: H-alpha spectroscopy of the recurrent nova RS Oph during the 2021 outburst

description: We report spectroscopic observations of the H-alpha emission line of the recurrent nova RS Oph obtained between 12 and 23 August 2021 during the recent outburst. The data are Coude spectra in FITS format.
DOI: 10.5281/zenodo.5524464
title: H-alpha spectroscopy of the recurrent nova RS Oph during the 2021 outburst

description: We report spectroscopic observations of the H-alpha emission line of the recurrent nova RS Oph obtained between 12 and 23 August 2021 during the recent outburst. The data are Coude spectra in FITS format.
DOI: 10.5281/zenodo.5515231
title: The observed mass distribution of Galactic black hole LMXBs is biased against massive black holes

description: Jupyter Notebook plus necessary data files to recreate the figures, the numbers reported, and a table in the publication. Also available at: http://arxiv.org/abs/2104.03596
DOI: 10.5281/zenodo.5503610
title: Catalogues of voids as antihalos in the local Universe

description: These archives contain the data products described in "Catalogues of voids as antihalos in the local Universe" by H. Desmond, M. Hutt, J. Devriendt and A. Slyz (2021). See the readme for further details.
DOI: 10.5281/zenodo.5515230
title: The observed mass distribution of Galactic black hole LMXBs is biased against massive black holes

description: Jupyter Notebook plus necessary data files to recreate the figures, the numbers reported, and a table in the publication. Also available at: http://arxiv.org/abs/2104.03596
DOI: 10.5281/zenodo.5512490
title: ESPRESSO spectra of HE0515-4414 and absorption profile fits

description: VLT/ESPRESSO spectra of HE0515-4414 and absorption profile fits associated with Murphy et al. (2021, A&A, submitted). This is the first release of this repository. It was prepared just prior to submission of the associated paper to Astronomy & Astrophysics in mid-September 2021.
DOI: 10.5281/zenodo.5503609
title: Catalogues of voids as antihalos in the local Universe

description: These archives contain the data products described in "Catalogues of voids as antihalos in the local Universe" by H. Desmond, M. Hutt, J. Devriendt and A. Slyz (2021). See the readme for further details.
DOI: 10.5281/zenodo.5512489
title: ESPRESSO spectra of HE0515-4414 and absorption profile fits

description: VLT/ESPRESSO spectra of HE0515-4414 and absorption profile fits associated with Murphy et al. (2021, A&A, submitted). This is the first release of this repository. It was prepared just prior to submission of the associated paper to Astronomy & Astrophysics in mid-September 2021.
DOI: 10.6084/m9.figshare.16858540
title: Directorio de Centros Docentes no Universitarios usados como base de contacto en Comscienciaeduspain

description: Directorio de Centros Docentes no Universitarios usado para el desarrollo del proyecto Comscienciaeduspain, ejecutado con la colaboración de la Fundación Española para la Ciencia y la Tecnología - Ministerio de Ciencia e Innovación.
DOI: 10.5281/zenodo.5410754
title: astroneb/WR_PN_Kinematic_Models: WR-PN-Kinematic-Models.1.1

description: <strong>Morpho-kinematic properties of Wolf-Rayet planetary nebulae. Supplementary Data</strong> <strong>Figure 5.</strong> The interactive figure of the morpho-kinematic mesh models of the PNe M 3-30, Hb 4, IC 1297, Th 2-A, Pe 1-1, M 1-32, M 3-15, M 1-25, Hen 2-142, K 2-16, MGC 6578, M 2-42, NGC 6567 and NGC 6629. <strong>Citation</strong> <pre><code class="language-bash">@article{Danehkar2021, author = {{Danehkar}, A.}, title = {Morpho-kinematic properties of Wolf-Rayet planetary nebulae}, journal = {submitted (arXiv:2107.03994)}, volume = {}, number = {}, pages = {}, year = {2021}, doi = {} }</code></pre> <strong>Learn More</strong> GitPage: https://astroneb.github.io/WR_PN_Kinematic_Models/
DOI: 10.6084/m9.figshare.16858540.v2
title: Directorio de Centros Docentes no Universitarios usados como base de contacto en Comscienciaeduspain

description: Directorio de Centros Docentes no Universitarios usado para el desarrollo del proyecto Comscienciaeduspain, ejecutado con la colaboración de la Fundación Española para la Ciencia y la Tecnología - Ministerio de Ciencia e Innovación.
DOI: 10.6084/m9.figshare.16858540.v1
title: Directorio de centros - 16_09_2021.xlsx

description: Directorio de Centros Docentes no Universitarios usado para el desarrollo del proyecto Comscienciaeduspain, ejecutado con la colaboración de la Fundación Española para la Ciencia y la Tecnología - Ministerio de Ciencia e Innovación.
DOI: 10.7284/144029
title: Splitbeam Echosounder data collected during research cruise AR59 using a Kongsberg EK80 instrument system onboard the platform RV Neil Armstrong

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/144909
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise LMG1101 using a Sea-Bird SBE-911+ instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/144910
title: Expendable Probe data collected during research cruise LMG1101 using a Sippican MK21 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/144911
title: Expendable Probe data collected during research cruise LMG1101 using a Sippican MK21 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/144913
title: GNSS (Global Navigation Satellite System) data collected during research cruise LMG1101 using a Garmin 19x instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/144914
title: Gyrocompass data collected during research cruise LMG1101 using a SGB Meridian instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/144915
title: INS (Inertial Navigation System) data collected during research cruise LMG1101 using a Kongsberg Seapath 330+ instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/144919
title: Singlebeam Echosounder data collected during research cruise LMG1101 using a Knudsen 3260 instrument system onboard the platform RV Laurence M. Gould

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.5281/zenodo.5593399
title: Argania spinosa decontaminated FSCR

description: .
DOI: 10.5281/zenodo.5593398
title: Argania spinosa decontaminated FSCR

description: .
DOI: 10.5517/ccdc.csd.cc21l9lk
title: CCDC 1894428: Experimental Crystal Structure Determination

description: Related Article: Lanhua Chen, Yugang Zhang, Zhehui Weng, Zhiyong Liu, Jiarong Zhang, Yaxing Wang, Shuao Wang|2020|Chin.J.Chem.|39|597|doi:10.1002/cjoc.202000510
DOI: 10.5281/zenodo.5593334
title: MCIC Multisite sMRI Dataset Preprocessed with VBM

description: This is a multisite structural MRI dataset preprocessed with voxel-based morphometry (VBM). This data can be used to demonstrate how federated voxelwise regression works on the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC).<br> <br> As described in Gazula et al, 2018, this data comes from the Mind Clinical Imaging Consortium (MCIC) collection, a publicly accessible, online data repository containing curated anatomical and functional MRI, in addition to other data, collected from individuals with and without a schizophrenia spectrum disorder (Gollub et al., 2013) and available via the COINS data exchange https://coins.mrn.org (Scott et al., 2011).<br> <br> The final cohort for whom data are available includes 146 patients and 160 controls with site distribution as follows: Site B (IA) 40 patients/67 controls; Site D (MGH) 32/23; Site C (UMN) 32/26; Site A (UNM) 42/44, respectively. These T1-weighted structural MRI (sMRI) images were acquired with the following scan parameters: <em>TR</em> = 2, 530<em>ms</em> for 3 T, <em>TR</em> = 12<em>ms</em> for 1.5 T; <em>TE</em> = 3.79<em>ms</em> for 3 T, <em>TE</em> = 4.76<em>ms</em> for 1.5 T; <em>FA</em> = 7° for 3 T, <em>FA</em> = 20° for 1.5 T; <em>TI</em> = 1100<em>ms</em>for 3 T; <em>Bandwidth</em> = 181 for 3 T, <em>Bandwidth</em> = 110 for 1.5 T; <em>voxelsize</em> = 0.625 × 0.625<em>mm</em>; slice thickness 1.5 mm; <em>FOV</em>= 16−18<em>cm</em>. The T1-weighted sMRI data were preprocessed using the Statistical Parametric Mapping software using unified segmentation (Ashburner and Friston, 2005), in which image registration, bias correction and tissue classification were performed using a single integrated algorithm resulting in individual brains segmented into gray matter, white matter and cerebrospinal fluid and nonlinearly warped to the Montreal Neurological Institute (MNI) standard space. The resulting gray matter concentration (GMC) images were re-sliced to 2 × 2 × 2<em>mm</em>, resulting in 91 × 109 × 91 voxels.
description: {"references": ["Gollub, R. L., Shoemaker, J. M., King, M. D., White, T., Ehrlich, S., Sponheim, S. R., Clark, V. P., Turner, J. A., Mueller, B. A., Magnotta, V., O'Leary, D., Ho, B. C., Brauns, S., Manoach, D. S., Seidman, L., Bustillo, J. R., Lauriello, J., Bockholt, J., Lim, K. O., Rosen, B. R., \u2026 Andreasen, N. C. (2013). The MCIC collection: a shared repository of multi-modal, multi-site brain image data from a clinical investigation of schizophrenia. Neuroinformatics, 11(3), 367\u2013388. https://doi.org/10.1007/s12021-013-9184-3", "Gazula, H., Baker, B. T., Damaraju, E., Plis, S. M., Panta, S. R., Silva, R. F., & Calhoun, V. D. (2018). Decentralized Analysis of Brain Imaging Data: Voxel-Based Morphometry and Dynamic Functional Network Connectivity. Frontiers in neuroinformatics, 12, 55. https://doi.org/10.3389/fninf.2018.00055"]}