cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e113747v1-24469
title: Replication data for: An Empirical Analysis of the Gender Gap in Mathematics

description: We document and analyze the emergence of a substantial gender gap in mathematics in the early years of schooling using a large, recent, and nationally representative panel of US children. There are no mean differences between boys and girls upon entry to school, but girls lose more than two-tenths of a standard deviation relative to boys over the first six years of school. The ground lost by girls relative to boys is roughly half as large as the black-white test score gap that appears over these same ages. We document the presence of this gender math gap across every strata of society. We explore a wide range of possible explanations in the data, including less investment by girls in math, low parental expectations, and biased tests, but find little support for these theories. Moving to cross-country comparisons, we find earlier results linking the gender gap in math to measures of gender equality are sensitive to the inclusion of Muslim countries, where, in spite of women's low status, there is little or no gender gap in math. (JEL I23, J26)
DOI: 10.5258/soton/d1353
title: Dataset for: Designing silicon-core fiber tapers for efficient supercontinuum generation in the greenhouse has absorption region

description: Dataset supports: Campling, J, Horak, P. & Peacock, A.C. (2020).Designing silicon-core fiber tapers for efficient supercontinuum generation in the greenhouse gas absorption region. Journal of the Optical Society of America B
DOI: 10.5281/zenodo.3834914
title: iNRACM: Incorporating 15N into the Regional Atmospheric Chemistry Mechanism (RACM) for assessing the role photochemistry plays in controlling the isotopic composition of NOx, NOy, and atmospheric nitrate

description: <sup>15</sup>N compounds and reactions were incorporated into Regional Atmospheric Chemistry Mechanism (RACM), based on recent experimental or calculated values of isotope fractionation factors (α), to simulate δ<sup>15</sup>N values in NO<sub>y</sub> compounds.
description: {"references": ["Stockwell, W. R., Kirchner, F., Kuhn, M., & Seefeld, S. (1997). A new mechanism for regional atmospheric chemistry modeling. Journal of Geophysical Research: Atmospheres, 102(D22), 25847-25879.", "Huan Fang (2019), \"SboxN15,\" https://mygeohub.org/resources/sbox."]}
DOI: 10.5281/zenodo.3834915
title: iNRACM: Incorporating 15N into the Regional Atmospheric Chemistry Mechanism (RACM) for assessing the role photochemistry plays in controlling the isotopic composition of NOx, NOy, and atmospheric nitrate

description: <sup>15</sup>N compounds and reactions were incorporated into Regional Atmospheric Chemistry Mechanism (RACM), based on recent experimental or calculated values of isotope fractionation factors (α), to simulate δ<sup>15</sup>N values in NO<sub>y</sub> compounds.
description: {"references": ["Stockwell, W. R., Kirchner, F., Kuhn, M., & Seefeld, S. (1997). A new mechanism for regional atmospheric chemistry modeling. Journal of Geophysical Research: Atmospheres, 102(D22), 25847-25879."]}
DOI: 10.17632/2tdr72g76v.1
title: Mass spectrometry raw file from metabolomics study of GH deficiency

description: The .RAW files obtained were extracted using Xcalibur (software version 3.0.63, ThermoFisher Scientific). The biogical matrix used was plasma.
DOI: 10.5281/zenodo.3834916
title: iNRACM: Incorporating 15N into the Regional Atmospheric Chemistry Mechanism (RACM) for assessing the role photochemistry plays in controlling the isotopic composition of NOx, NOy, and atmospheric nitrate

description: <sup>15</sup>N compounds and reactions were incorporated into Regional Atmospheric Chemistry Mechanism (RACM), based on recent experimental or calculated values of isotope fractionation factors (α), to simulate δ<sup>15</sup>N values in NO<sub>y</sub> compounds.
description: {"references": ["Stockwell, W. R., Kirchner, F., Kuhn, M., & Seefeld, S. (1997). A new mechanism for regional atmospheric chemistry modeling. Journal of Geophysical Research: Atmospheres, 102(D22), 25847-25879."]}
DOI: 10.5281/zenodo.3834918
title: Database of EMG signals extracted from four hand movements

description: The database is composed of samples of EMG signals captured from 4 hand movements performed by two people: Participant 1 and Participant 2. Participant 1 has cerebral palsy, while the other does not have any diagnosed disability. The signals were captured by two pairs of bipolar electrodes and two Olimex Shield EMG / EKG plates (ch1 and ch2), each channel represents the potential difference between two electrodes where the first pair (ch1) was positioned at the ends of the lower muscle of the anti-arm. And the second (ch2), in posterior muscle of the anti-arm. All movements were performed with the arm at rest and the palm pointing upwards. There are two files for each movement ('Movimento'_ch1 and' Movimento'_ch2) where each line of the file represents a signal of 1600 samples of the movement performed. each file has 1600 samples (400 for each movement). The movements are: &lt;ROTULOS&gt; &lt;MOVEMENT&gt; &lt;DESCRIPTION&gt; 1 --------- Open (123 amostars) --------------- open the palm 2 --------- Bass (127 samples) ----------------- move open hand down 3 --------- Up (119 samples) -------------------- move open hand up 4 --------- Close (131 samples) ---------------- Close hand
DOI: 10.5281/zenodo.3834919
title: Database of EMG signals extracted from four hand movements

description: The database is composed of samples of EMG signals captured from 4 hand movements performed by two people: Participant 1 and Participant 2. Participant 1 has cerebral palsy, while the other does not have any diagnosed disability. The signals were captured by two pairs of bipolar electrodes and two Olimex Shield EMG / EKG plates (ch1 and ch2), each channel represents the potential difference between two electrodes where the first pair (ch1) was positioned at the ends of the lower muscle of the anti-arm. And the second (ch2), in posterior muscle of the anti-arm. All movements were performed with the arm at rest and the palm pointing upwards. There are two files for each movement ('Movimento'_ch1 and' Movimento'_ch2) where each line of the file represents a signal of 1600 samples of the movement performed. each file has 1600 samples (400 for each movement). The movements are: &lt;ROTULOS&gt; &lt;MOVEMENT&gt; &lt;DESCRIPTION&gt; 1 --------- Open (123 amostars) --------------- open the palm 2 --------- Bass (127 samples) ----------------- move open hand down 3 --------- Up (119 samples) -------------------- move open hand up 4 --------- Close (131 samples) ---------------- Close hand
DOI: 10.5281/zenodo.3834920
title: iNRACM: Incorporating 15N into the Regional Atmospheric Chemistry Mechanism (RACM) for assessing the role photochemistry plays in controlling the isotopic composition of NOx, NOy, and atmospheric nitrate

description: <sup>15</sup>N compounds and reactions were incorporated into Regional Atmospheric Chemistry Mechanism (RACM), based on recent experimental or calculated values of isotope fractionation factors (α), to simulate δ<sup>15</sup>N values in NO<sub>y</sub> compounds.
description: {"references": ["Stockwell, W. R., Kirchner, F., Kuhn, M., & Seefeld, S. (1997). A new mechanism for regional atmospheric chemistry modeling. Journal of Geophysical Research: Atmospheres, 102(D22), 25847-25879."]}
DOI: 10.5281/zenodo.3835559
title: Schrijverskabinet RDF

description: The Panpoëticon Batavûm is a collection of small portraits of Dutch poets (and writers in general). The collection was set up at the beginning of the eighteenth century by the painter Arnoud Halen (1673-1732). As a collection the Panpoëticon is no longer intact, but fortunately researchers at Radboud University have made a beautiful digital reconstruction, which can be seen at http://www.schrijverskabinet.nl/. By modelling the data from the Schrijverskabinet as RDF, we can connect the entities that are included in the Schrijverskabinet to other relevant datasets that for instance include more detailed biographical information, such as ECARTICO, ONSTAGE, and Wikidata. Also, a link to the Linked Open Data from the Koninklijke Bibliotheek allows us to retrieve primary and secondary works for an author included in the Panpoëticon. We then can start asking questions such as 'To what extent were the authors of popular pieces in the Amsterdam Theatre included in the Panpoeticon?' and 'What was the geographical distribution of the poets included in the Panpoeticon?'. The data was first converted to be used in an Amsterdam Time Machine / UvA CREATE datasprint. More information is available here: https://uvacreate.gitlab.io/datasprint-ecartico-2020/ This release can be considered stable. Changes compared to the previous development releases (see: https://github.com/LvanWissen/schrijverskabinet-rdf/releases): All persons are now linked (<code>owl:sameAs</code>) to an identifier from the DBNL Added the 'quote' from the portrait page to the RDF as value of <code>schema:text</code> Changes from schrijverskabinet.nl reflected in RDF Documentation improved This release should get a citable Zenodo DOI <strong>Reference to the original data:</strong> Deinsen, L. van and T. van Strien (eds.), Het schrijverskabinet. Panpoëticon Batavûm, 2016, http://www.schrijverskabinet.nl/.
description: {"references": ["Deinsen, L. van and T. van Strien (eds.), Het schrijverskabinet. Panpo\u00ebticon Batav\u00fbm, 2016, http://www.schrijverskabinet.nl/."]}
DOI: 10.21227/3k27-1010
title: CoMMonS: Challenging Microscopic Material Surface Dataset

description: As one of the research directions atnbsp;OLIVES Lab @ Georgia Tech, we focus on recognizing textures and materials in real-world images, which plays an important role in object recognition and scene understanding.nbsp;Aiming at describing objects or scenes with more detailed information, we explore how to computationally characterize apparent or latent properties (e.g. surface smoothness) of materials, i.e., computational material characterization, which moves a step further beyond material recognition. For this purpose, we introduce a large, publicly available dataset named challenging microscopic material surface dataset (CoMMonS).nbsp;We utilize a powerful microscope to capture high-resolution images with fine details of fabric surfaces. Thenbsp;CoMMonSnbsp;dataset consists of 6,912 images covering 24 fabric samples in a controlled environment under varying imaging conditions such as lighting, zoom levels, geometric variations, and touching directions. This dataset can be used to assess the performance of existing deep learning-based algorithms and to develop our own method for material characterization in terms of fabric properties such as fiber length, surface smoothness, and toweling effect.nbsp;Please refer to ournbsp;GitHub pagenbsp;for code, papers, and more information.
DOI: 10.21227/zzsw-3w48
title: CoMMonS: Challenging Microscopic Material Surface Dataset

description: As one of the research directions atnbsp;OLIVES Lab @ Georgia Tech, we focus on recognizing textures and materials in real-world images, which plays an important role in object recognition and scene understanding.nbsp;Aiming at describing objects or scenes with more detailed information, we explore how to computationally characterize apparent or latent properties (e.g. surface smoothness) of materials, i.e., computational material characterization, which moves a step further beyond material recognition. For this purpose, we introduce a large, publicly available dataset named challenging microscopic material surface dataset (CoMMonS).nbsp;We utilize a powerful microscope to capture high-resolution images with fine details of fabric surfaces. Thenbsp;CoMMonSnbsp;dataset consists of 6,912 images covering 24 fabric samples in a controlled environment under varying imaging conditions such as lighting, zoom levels, geometric variations, and touching directions. This dataset can be used to assess the performance of existing deep learning-based algorithms and to develop our own method for material characterization in terms of fabric properties such as fiber length, surface smoothness, and toweling effect.nbsp;Please refer to ournbsp;GitHub pagenbsp;for code, papers, and more information.
DOI: 10.17632/2tdr72g76v.2
title: Mass spectrometry raw file from metabolomics study of GH deficiency

description: The .RAW files obtained were extracted using Xcalibur (software version 3.0.63, ThermoFisher Scientific). The biogical matrix used was plasma.
DOI: 10.25386/genetics.12340562
title: Supplemental Material for Chen and Montell, 2020

description: Figures S1 - S3, Tables S1 and S2.
DOI: 10.25386/genetics.12340562.v1
title: Supplemental Material for Chen and Montell, 2020

description: Figures S1 - S3, Tables S1 and S2.
DOI: 10.5281/zenodo.3834917
title: IDTReeS 2020 Competition Data

description: Data provided by the Integrating Data science with Trees and Remote Sensing (IDTReeS) research group for use in the IDTReeS Competition. Geospatial and tabular data to be used in two data science tasks focused on using remote sensing data to quantify the locations, sizes and species identities of millions of trees and on determining how these methods generalize to other forests. Vector data are the geographic extents of Individual Tree Crown boundaries that have been identified by researchers in the IDTReeS group. The data were generated primarily by Sarah Graves, Sergio Marconi, and Benjamin Weinstein, with support from Stephanie Bohlman, Ethan White, and members of the IDTReeS group. Remote Sensing and Field data were generated by the National Ecological Observatory Network (NEON, Copyright © 2017 Battelle). Data were selected, downloaded, and packaged by Sergio Marconi. The most recent available data of the following products are provided: National Ecological Observatory Network. 2020. Data Product DP1.30010.001, High-resolution orthorectified camera imagery. Provisional data downloaded from http://data.neonscience.org on March 4, 2020. Battelle, Boulder, CO, USA NEON. 2020. National Ecological Observatory Network. 2020. Data Product DP1.30003.001, Discrete return LiDAR point cloud. Provisional data downloaded from http://data.neonscience.org on March 4, 2020. Battelle, Boulder, CO, USA NEON. 2020. National Ecological Observatory Network. 2020. Data Product DP1.10098.001, Woody plant vegetation structure. Provisional data downloaded from http://data.neonscience.org on March 4, 2020. Battelle, Boulder, CO, USA NEON. 2020. National Ecological Observatory Network. 2020. Data Product DP3.30015.001, Ecosystem structure. Provisional data downloaded from http://data.neonscience.org on March 4, 2020. Battelle, Boulder, CO, USA NEON. 2020. NEON has the following data policy: ‘The National Ecological Observatory Network is a program sponsored by the National Science Foundation and operated under cooperative agreement by Battelle Memorial Institute. This material is based in part upon work supported by the National Science Foundation through the NEON Program.’ THE NEON DATA PRODUCTS ARE PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE NEON DATA PRODUCTS BE LIABLE FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE NEON DATA PRODUCTS.
description: This data is supported by the National Science Foundation through grant 1926542 and by the Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative through grant GBMF4563 to E.P. White, and the NSF Dimension of Biodiversity program grant (DEB-1442280) and USDA/NIFA McIntire-Stennis program (FLA-FOR-005470).
DOI: 10.5519/qd.sxdrrtbk
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5266 records)
DOI: 10.17632/gj49rzjxhr.1
title: Ply Scheme-Xu

description: The raw data in the research "The effects of ply scheme on the effective thermal conductivity of carbonized fabric-type ablative materials" The raw data consists of the following two parts, which are available in the file "Sim-Date" A) The deduced results of the ETC of the carbonized ablator with different levels of dislocation B) The ETC of the carbonized ablator with different layer angle
DOI: 10.17632/zk32frw6p5.6
title: COVID-19 Dataset

description: This a data about the corona virus COVID-19. It contains the actual reported data. Also, it includes the predicted COVID-19 data in the future based on a model developed to predict in the future. The model used will be published in one of the journals later and will be found on my profile with title "Optimistic Prediction Model For the COVID-19 Coronavirus Pandemic based on the Reported Data Analysis". The daily folder contains the daily data. The predicted folder contains the predicted data for each country. The total cases folder contains the total cases for each country. he section folder contains a latex code for plotting the figures for each country. Also the source file from European Centre for Disease Prevention and Control is included. More updated files available in the website of European Centre for Disease Prevention and Control.
DOI: 10.5281/zenodo.3833973
title: Spectrograms of the SOL dataset

description: This is the dataset accompanying the paper Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders published at ISMIR2019. Due to the copyright, only the extracted spectrograms are shared. The repo is at https://github.com/yjlolo/gmvae-synth.
DOI: 10.5281/zenodo.3833974
title: Spectrograms of the SOL dataset

description: This is the dataset accompanying the paper Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders published at ISMIR2019. Due to the copyright, only the extracted spectrograms are shared. The repo is at https://github.com/yjlolo/gmvae-synth.
DOI: 10.15161/oar.it/23673
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.17632/7tb4d66z7c.1
title: Untargeted metabolic screening of preterm infants on a human milk diet
DOI: 10.17632/gj49rzjxhr.2
title: Ply Scheme-Xu

description: The raw data in the research "The effects of ply scheme on the effective thermal conductivity of carbonized fabric-type ablative materials" The raw data consists of the following two parts, which are available in the file "Sim-Date" A) The deduced results of the ETC of the carbonized ablator with different levels of dislocation B) The ETC of the carbonized ablator with different layer angle
DOI: 10.17632/gj49rzjxhr.3
title: Ply Scheme-Xu

description: The raw data in the research "The effects of ply scheme on the effective thermal conductivity of carbonized fabric-type ablative materials" The raw data consists of the following two parts, which are available in the file "Sim-Date" A) The deduced results of the ETC of the carbonized ablator with different levels of dislocation B) The ETC of the carbonized ablator with different layer angle
DOI: 10.17632/jrcbbtvbjj.1
title: ECT anaesthesia data set

description: Complete data set to "Anaesthesiologic staff’s opinion on Electroconvulsive Therapy ".
DOI: 10.17632/257pzrpdzd.1
title: Data catalog (Central Himalaya), earthquake magnitude ranges from ML 1 to 5.7 (tested for earthquake frequency-size distributions).
DOI: 10.17632/257pzrpdzd.2
title: Data catalog (Central Himalaya), earthquake magnitude ranges from ML 1 to 5.7 (tested for earthquake frequency-size distributions).
DOI: 10.17632/jrcbbtvbjj.2
title: ECT anaesthesia data set

description: Complete data set to "Anaesthesiologic staff’s opinion on Electroconvulsive Therapy ".
DOI: 10.17632/znrzchc6wj.2
title: Passive acoustic measurement of bedload transport: towards a global calibration curve?
DOI: 10.17632/696sjsnsx3.1
title: Data for: Nigeria’s Working Poor Households - Characterizing Factors and Proposals for Welfare Programs

description: The paper focuses on the increasing incidence of working poor families in Nigeria. Data from the ILO and NBS suggest that, not only is the number of working poor families in Nigeria increasing, it is increasing despite governments efforts at increasing the number of jobs created through the National Economic Recovery Growth Plan (ERGP). This point to the assertion that, removing working poor families out of poverty will not solely depend on their being employed. The paper uses data from Nigeria’s General Household Survey (2018/2019 to characterize inducing factors of working poor families in Nigeria. The estimated results suggest that female – headed households, polygamous and divorced households, individuals who have never been married, size of employment establishment, and household expenditures, are inducing factors of the increase in working poor families in Nigeria. We recommend the supplementing of working poor families incomes through Living wage Laws and the establishment of a Contributory Savings Accounts. Extending health coverage through the establishment of State Health Insurance Schemes and the provision of affordable and quality housing through a state guaranteed Mortgage Schemes.
DOI: 10.17632/8b8ygpt596.2
title: COVID-19 full DB official Russian Data by Regions 2020

description: This DB based on all available reports by the Communicational center of Government of the Russian Federation. Official Russian COVID-19 data published daily by the Government of Russia (on the Russian language) in the form of raw data is a daily updated report in a pdf form. Each piece has daily updates. We are providing a working link on every cell of data in the dataset. This DB is an attempt to manually collect critical variables from the report into a machine-readable format. These datasets are ready to be used for analysis and modeling. Variables: location; date; new cases [diagnosed]; cases [cumulative]; recovered [new]; recovered [cumulative]; deaths [new]; deaths [cumulative]; tests [new tests administered]; tests [cumulative]; test_positive [cumulative]; hospitalization [cumulative]; icu [cumulative or population]; on_invasive_ventilators [cumulative or population]; test_negative [cumulative]; hospital beds; web links. All Data divided by date (time) and regions (Oblast) of the Russian Federation.
DOI: 10.21227/pgke-2836
title: GPS data collected from "Xinda" autonomous vehicle of Chang'an University

description: The file 'GPS_P2.zip' is the dataset collected from the GNSS sensor of "Xinda" autonomous vehicle in the Connected Autonomous Vehicles Test Fields (the CAVs Test Fields) Weishui Campus,Chang'an University.The file 'fault.zip' is the simulated faults in the healthy data in '.mat' format, where X_abrupt, X_noise and X_drift represent abrupt faults, noise and drift in the long run are added into the healthy data, respectively.The file 'xindaBrakeApproximationTraing.zip' is the data collected from the brake system from 'Xinda', where the meaning of each column is 'brake hydraulic pressure', 'velocity', 'acceleration', respectively.