cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e117543v2
title: The Foveal Avascular Zone Image Database (FAZID)

description: The Foveal Avascular Zone (FAZ) is of clinical importance since the vascular arrangement around the fovea changes with disease and refractive state of the eye. In order to test and validate newly developed automated segmentation algorithms, we have created a public dataset of these retinal fundus images consisting of a total of 304 different images classified into: Diabetic (107), Myopic (109) and Normal (88) eyes. The images are of dimensions 420 x 420 pixels corresponding to 6mm x 6mm dimension of the retina. For each type of image, clear and manually segmented by a clinical expert (ground truth) are available.<br><br>Please use the following citation if you use the database “Jothi Balaji, J.; Agarwal, A.; Raman, R., et al., Comparison of Foveal Avascular Zone in Diabetic Retinopathy, High Myopia and Normal Fundus images. Ophthalmic Technologies XXX, Vol 11218-59. Proc. SPIE (2020).” (To be appeared)
DOI: 10.3886/e120168
title: Family Support of Third-Grade Reading Skills, Motivation, and Habits (transcripts)

description: This folder contains transcripts of parent interviews used in the study, "Family Support of Third-Grade Reading Skills, Motivation, and Habits" (AERA Open, 2017, Vol. 3, No. 3, pp. 1-16). Parents participated in open-ended interviews during a home visit to discuss their home literacy environment. The transcripts include the open-ended portion between the home visitor and the parent or guardian of the third grade student, as well as other excerpts in which parents responses addressed the open-ended questions. All inquiries regarding the data and overall home visit study should be directed to Lauren Capotosto, lcapotos@holycross.edu.
DOI: 10.3886/e120168v1
title: Family Support of Third-Grade Reading Skills, Motivation, and Habits (transcripts)

description: This folder contains transcripts of parent interviews used in the study, "Family Support of Third-Grade Reading Skills, Motivation, and Habits" (AERA Open, 2017, Vol. 3, No. 3, pp. 1-16). Parents participated in open-ended interviews during a home visit to discuss their home literacy environment. The transcripts include the open-ended portion between the home visitor and the parent or guardian of the third grade student, as well as other excerpts in which parents responses addressed the open-ended questions. All inquiries regarding the data and overall home visit study should be directed to Lauren Capotosto, lcapotos@holycross.edu.
DOI: 10.3886/e117762
title: Data and code for: Automatic stabilizers in a low-rate environment

description: In a world where monetary policy cannot assume responsibility for stabilization policy, there is a strong need for fiscal policy to address stabilization issues. In this context, we argue for “semi-automatic stabilizers” , aimed at reducing unemployment slumps rather than output recessions. We show that the hole left by the limits on monetary policy implies a large role for fiscal policy in general, and for semi-automatic stabilizers in particular. Finally, we argue that the design of stabilizers, whether they focus on mechanisms that rely primarily on income or on intertemporal substitution effects, depends crucially on the general design of discretionary policy. <br>
DOI: 10.3886/e117762v2
title: Data and code for: Automatic stabilizers in a low-rate environment

description: In a world where monetary policy cannot assume responsibility for stabilization policy, there is a strong need for fiscal policy to address stabilization issues. In this context, we argue for “semi-automatic stabilizers” , aimed at reducing unemployment slumps rather than output recessions. We show that the hole left by the limits on monetary policy implies a large role for fiscal policy in general, and for semi-automatic stabilizers in particular. Finally, we argue that the design of stabilizers, whether they focus on mechanisms that rely primarily on income or on intertemporal substitution effects, depends crucially on the general design of discretionary policy. <br>
DOI: 10.25919/5f1cc35e4bef4
title: Parkes observations for project P1041 semester 2020APRS_12

description: We recently discovered five millisecond pulsars (MSPs) in the globular cluster Omega Centauri. This is the first pulsar discovery in this globular cluster. Four of these pulsars are isolated with spin periods of 4.1, 4.2, 4.6 and 6.8ms. The fifth has a spin period of 4.8ms and is in an eclipsing binary system with an orbital period of 2.1 hours. We propose to carry out a timing campaign of these new pulsars in order to study the dynamics in the core of Omega Centauri, to reveal the origin of Gamma-ray emission from the core, and to probe the ionised interstellar medium in Omega Centauri. Our proposed observations will also enable us to carry out deeper searches of pulsars in the cluster.
DOI: 10.21227/37hz-wx95
title: FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living

description: DescriptionFallAllD is a large open dataset of human falls and activities of daily living simulated by 15 participants. FallAllD consists of 26420 files collected using three data-loggers worn on the waist, wrist and neck of the subjects. Motion signals are captured using an accelerometer, gyroscope, magnetometer and barometer with efficient configurations that suit the potential applications e.g. fall detection, fall prevention and human activity recognition.Data AcquisitionThree identical data-loggers have been used. They are waist, wrist and neck-worn devices equipped with:· LSM9DS1: 3-axial accelerometer, 3-axial gyroscope and 3-axial magnetometer.· MS5607-02BA03: barometer.Sensors configurations· Accelerometer: Sampling frequency = 238 Hz. Measurement range = ±8 g.· Gyroscope: Sampling frequency = 238 Hz. Angular rate = ± 2000 dps.· Magnetometer: Sampling frequency = 80 Hz. Full scale magnetic field = ±4 Gauss.· Barometer: Sampling frequency = 10 Hz.
DOI: 10.34740/kaggle/dsv/1370620
title: Brain Tumor
DOI: 10.25345/c51j1q
title: MassIVE MSV000085829 - Glycosphingolipids - Caco-2 Differentiation
title: Glycosphingolipids of Caco-2 during differentiation
DOI: 10.5281/zenodo.3959901
title: Changjiang Estuary cruise data in July 2017

description: Changjiang Estuary cruise data in July 2017
DOI: 10.5281/zenodo.3959900
title: Changjiang Estuary cruise data in July 2017

description: Changjiang Estuary cruise data in July 2017
DOI: 10.5281/zenodo.3723448
title: Why is it so Cold in Here? - Posteriors

description: Supplementary material for '<em>Why is it so Cold in Here?: Explaining the Cold Temperatures Retrieved from Transmission Spectra of Exoplanet Atmospheres</em>' - ApJL (2020). This repository contains the posterior probability distributions from the retrievals in Sections 3 and 4 of MacDonald, Goyal, & Lewis (2020). The case studies are a typical 'warm', 'hot', and 'ultra-hot' Jupiter, along with self-consistent models of WASP-17b and WASP-12b. For each retrieval, the corner plot depicts correlations between pairs of retrieved parameters and marginalised histograms for each parameter. Red dashed lines and green squares indicate the true terminator-averaged parameter values used to generate the synthetic observations. The table inset compares the true values with retrieved inferences. Where parameters have clear upper and lower bounds, the median retrieved values and ±1σ confidence levels are given. Otherwise, parameter constraints are expressed as 2σ upper or lower bounds. For any questions, please contact: r.macdonald@astro.cornell.edu
DOI: 10.5281/zenodo.3723447
title: Why is it so Cold in Here? - Posteriors

description: Supplementary material for '<em>Why is it so Cold in Here?: Explaining the Cold Temperatures Retrieved from Transmission Spectra of Exoplanet Atmospheres</em>' - ApJL (2020). This repository contains the posterior probability distributions from the retrievals in Sections 3 and 4 of MacDonald, Goyal, & Lewis (2020). The case studies are a typical 'warm', 'hot', and 'ultra-hot' Jupiter, along with self-consistent models of WASP-17b and WASP-12b. For each retrieval, the corner plot depicts correlations between pairs of retrieved parameters and marginalised histograms for each parameter. Red dashed lines and green squares indicate the true terminator-averaged parameter values used to generate the synthetic observations. The table inset compares the true values with retrieved inferences. Where parameters have clear upper and lower bounds, the median retrieved values and ±1σ confidence levels are given. Otherwise, parameter constraints are expressed as 2σ upper or lower bounds. For any questions, please contact: r.macdonald@astro.cornell.edu
DOI: 10.21227/ghy6-4x65
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Below is the quick overview of this dataset.— Number of tweets : 155,151 tweets
DOI: 10.21227/hwha-gv93
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.— Number of tweets : 344,322,867 tweets
DOI: 10.21227/cesa-5429
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.— Number of tweets : 344,322,867 tweets
DOI: 10.21227/qqzh-hj63
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Below is the quick overview of this dataset.— Number of tweets : 155,151 tweets
DOI: 10.21227/2b02-yx16
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.— Number of tweets : 344,322,867 tweets
DOI: 10.21227/m0v6-8q61
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Below is the quick overview of this dataset.— Number of tweets : 155,151 tweets
DOI: 10.21227/mt22-2a88
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.— Number of tweets : 344,322,867 tweets
DOI: 10.21227/jkkb-7861
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Below is the quick overview of this dataset.— Number of tweets : 155,151 tweets
DOI: 10.21227/naqt-6j33
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.— Number of tweets : 344,322,867 tweets
DOI: 10.25919/5f1d1d5f1860b
title: Parkes observations for project P737 semester 2020APRS_06

description: The aim of this proposal is to carry out tests of the new backend instruments which cannot be carried out during standard maintenance periods. The scheduled time is used to measure beam shapes, determine polarisation calibration solutions and commission the National Facility observing modes for the new wide-band receiver.
DOI: 10.5281/zenodo.3960487
title: Input and Output Data of SGRIST

description: Three SCM cases as in the manuscript.
DOI: 10.5281/zenodo.3960486
title: Input and Output Data of SGRIST

description: Three SCM cases as in the manuscript.
DOI: 10.5281/zenodo.3960483
title: Experimental data for bulk valley transport and Berry curvature spreading at the edge of flat bands

description: This dataset was used in our study of bulk valley transport and Berry curvature spreading at the edge of flat bands in twisted double bilayer graphene.
DOI: 10.5281/zenodo.3960482
title: Experimental data for bulk valley transport and Berry curvature spreading at the edge of flat bands

description: This dataset was used in our study of bulk valley transport and Berry curvature spreading at the edge of flat bands in twisted double bilayer graphene.
DOI: 10.25959/5f1d3f4b279d6
title: The nature and formation of oceanic crust at fast spreading ridges: geochemical results from scientific ocean drilling at Hess Deep
DOI: 10.5281/zenodo.3960010
title: Training Data

description: This is the training data for land use/cover classification and it was collected by doing visual interpretation from Google Earth Pro.
DOI: 10.5281/zenodo.3960009
title: Training Data

description: This is the training data for land use/cover classification and it was collected by doing visual interpretation from Google Earth Pro.
DOI: 10.21227/7rmk-6y51
title: CONFLICT SCENARIOS IN SMART HOME

description: This is a dataset of 104 conflict scenarios in smart homes. The original purpose of generating this dataset is to define and detect conflicts in smart homes.
DOI: 10.21227/eftf-ky76
title: CONFLICT SCENARIOS IN SMART HOME

description: This is a dataset of 104 conflict scenarios in smart homes. The original purpose of generating this dataset is to define and detect conflicts in smart homes.
DOI: 10.5281/zenodo.3960524
title: Supporting datasets used in the paper entitled "High sensitivity of Arctic black carbon radiative effects to subgrid vertical velocity in aerosol activation"

description: This archive contains datasets used in the paper entitled "High sensitivity of Arctic black carbon radiative effects to subgrid vertical velocity in aerosol activation".
DOI: 10.5281/zenodo.3960523
title: Supporting datasets used in the paper entitled "High sensitivity of Arctic black carbon radiative effects to subgrid vertical velocity in aerosol activation"

description: This archive contains datasets used in the paper entitled "High sensitivity of Arctic black carbon radiative effects to subgrid vertical velocity in aerosol activation".
DOI: 10.21227/8pqz-p163
title: Exact Bit Error-Rate Analysis of Two-User NOMA Using QAM with Arbitrary Modulation Orders

description: Exact BER Analysis for Two-user NOMA uUing QAM with Arbitrary Modulation Order
DOI: 10.21227/95sd-1h32
title: Exact Bit Error-Rate Analysis of Two-User NOMA Using QAM with Arbitrary Modulation Orders

description: Exact BER Analysis for Two-user NOMA uUing QAM with Arbitrary Modulation Order
DOI: 10.34740/kaggle/dsv/1371501
title: COVID-19 Indonesia Dataset
DOI: 10.15161/oar.it/30582
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: 10.5281/zenodo.3960539
title: Sourdine. French seventeenth-century verse tragedies for TXM

description: This dataset contains 49 French seventeenth-century tragedies in verse first performed between 1660 and 1695: All 11 tragedies by Racine as well as 38 contemporary tragedies by Thomas Corneille, Pierre Corneille, Boyer, Quinault, Pradon and Campistron. All plays have been received morphological annotation using Freeling and semantic annotation using WordNet. The dataset is available in a binary format for direct import into the TXM text analysis tool (sourdinewn.txm), as well as in the original, annotated XML format (sourdinewn.zip). A metadata table is also available (sourdinewn_metadata.csv). The texts were originally obtained from the "Théâtre classique" platform edited by Paul Fièvre.
DOI: 10.5281/zenodo.6563767
title: Requirements Quality Factor Ontology

description: We investigated a previously published set of research articles concerned with requirements quality, extracted quality factors and other relevant elements from eligible publications, and iteratively constructed an ontology of quality factors for natural language requirements. The documentation of the process, the resulting data set, and a web application to visualize the results are contained in this artifact bundle.
description: This is the first version of the requirements quality factor ontology. Certain parts, in specific the data and structure of the ontology itself, are meant to be live-extensible and will be maintained at https://github.com/JulianFrattini/gere-structure-content
DOI: 10.6084/m9.figshare.19160657.v1
title: ASSESSMENT OF ACCEPTABILITY OF COVID-19 VACCINE BASED ON HEALTH BELIEF MODEL – A QUALITATIVE APPROACH

description: The data include quote responses for the qualitative survey entitled 'ASSESSMENT OF ACCEPTABILITY OF COVID-19 VACCINE BASED ON HEALTH BELIEF MODEL – A QUALITATIVE APPROACH
DOI: 10.6084/m9.figshare.19160657
title: ASSESSMENT OF ACCEPTABILITY OF COVID-19 VACCINE BASED ON HEALTH BELIEF MODEL – A QUALITATIVE APPROACH

description: The data include quote responses for the qualitative survey entitled 'ASSESSMENT OF ACCEPTABILITY OF COVID-19 VACCINE BASED ON HEALTH BELIEF MODEL – A QUALITATIVE APPROACH
DOI: 10.6084/m9.figshare.19947288
title: Additional file 2 of Host-dependent impairment of parasite development and reproduction in the acanthocephalan model

description: Additional file 2. Table S2.
DOI: 10.6084/m9.figshare.19947288.v1
title: Additional file 2 of Host-dependent impairment of parasite development and reproduction in the acanthocephalan model

description: Additional file 2. Table S2.