cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e196861v1
title: Characteristics and burden of acute COVID-19 and long-COVID

description: This dataset consists of 416 individuals (73.9% female) between the ages of 16 and 80 years (M = 44.18, SD = 12.90) with self-reported symptoms of long-COVID who participated in an online survey conducted between March and May 2022. <b><br></b><br>6.0%, 74.3%, and 19.7% of all respondents reported having had an asymptomatic, mild, or severe acute illness, respectively. Out of all participants, 7.8% required hospitalization. The most prevalent symptoms during the acute infection (Mdn = 23.50 symptoms, IQR = 13 - 39) included fatigue, exhaustion, cough, brain fog, and memory problems. The median long-COVID disease duration was 12.10 months (IQR = 2.8 - 17.4). Among 64 inquired long-COVID symptoms (Mdn = 17.00 symptoms, IQR = 9 - 27), participants reported fatigue, exhaustion, memory problems, brain fog, and dyspnea as the most common ongoing symptoms, which were generally experienced as fluctuating and deteriorating after physical or cognitive activity. Common consequences of long-COVID included financial losses (40.5%), changes in the participants’ profession (41.0%), stress resistance (87.5%), sexual life (38.1%), and mood (72.1%), as well as breathing difficulties (41.3%), or an increased drug intake (e.g., medicine, alcohol; 44.6%). In addition, vaccinated individuals exhibited a shorter acute illness duration and an earlier onset of long-COVID symptoms. In general, women reported more long-COVID symptoms than men.<br>
description: The dataset represents data from an online study, including individuals with self-reported symptoms of long-COVID who were recruited through social media advertisements, press releases, and information folders distributed in rehabilitation clinics.
description: Individuals with self-reported symptoms of long-COVID.
DOI: 10.6084/m9.figshare.22634335
title: 学校氛围-自控-手机成瘾 亲子调节 - 副本.sav

description: 学校氛围-自控-手机成瘾 亲子调节 - 副本
DOI: 10.6084/m9.figshare.22634335.v1
title: 学校氛围-自控-手机成瘾 亲子调节 - 副本.sav

description: 学校氛围-自控-手机成瘾 亲子调节 - 副本
DOI: 10.6084/m9.figshare.24953646
title: <b>Parental Autonomy Granting, Peer Attachment, and Problematic Internet Use among Chinese Adolescents: Moderating Effect of the School Climate</b>

description: <b>The first file is the T1 data(N = 926), the second file is the T2 data(N = 853), both of which were analyzed using the SPSS, and the third file is the results of the mediated moderation model analyzed by the Mplus.</b>
DOI: 10.5281/zenodo.8232672
title: All-sky imager observation data from the Chinese Yellow River Station, Ny-Ålesund, Svalbard, on January 16, 2004

description: The data in this paper are from the Chinese Arctic Yellow River Station (YRS) at Ny-Ålesund, Svalbard with the geographic coordinates (78.92°N, 11.93°E) and the corrected geomagnetic latitude 76.24°. Since the end of 2003, three identical all-sky imagers have been installed to observe auroral phenomena. The system records 24 hours of auroral activity from October of each year to March of the following winter. The temporal resolution of two consecutive frames of observations is 10 s. The camera uses a 512 × 512 square pixel array with a geographic zenith located near the center of the field of view. The full-day field of view covers a diameter of about 1000 km. The spatial resolution ranges from 1.1 km at the zenith to 36 km at an altitude of 150 km. This dataset gives the observations from 2004-1-16 used in the article, as well as the data used in comparisons with other methods.
DOI: 10.5281/zenodo.10464819
title: JMA observarion

description: Data is downloaded from https://www.jodc.go.jp/jodcweb/ and https://www.data.jma.go.jp/gmd/kaiyou/db/vessel_obs/data-report/html/ship/ship_e.php?year=2006&season=fall#kisetsu
DOI: 10.5281/zenodo.8232671
title: All-sky imager observation data from the Chinese Yellow River Station, Ny-Ålesund, Svalbard

description: Introduction

The aurora images in this dataset are from the all-sky imagers at the Yellow River Station (YRS). And it is used in the paper Automatically sketching Auroral Skeleton Structure in All-sky Image for Measuring Aurora Arcs.

This dataset consists of the following sections:



N20040116G.zip: 4,319 observation images as of January 16, 2004;

Raw data and reading code.zip: 8634 raw data items of December 23, 2003, and reading code;

80 imgs&annotations.zip: 80 ASI images and the corresponding manual annotations with pixel-level masks.


In the following sections, the data source, acquisition instruments, data characteristics, preprocessing methods and naming conventions of this dataset will be introduced.

Data source:

The auroral images used in this study are ground-based observation data acquired by three-wavelength (427.8, 557.7, and 630.0 nm) all-sky imagers at YRS in Ny-Ålesund, Svalbard. The geographic coordinates of YRS are 78.92°N, 11.93°E, and the corrected geomagnetic latitude is 76.24°, MLT≈UT+3 h.

Data acquisition instruments:

Data were obtained from all-sky CCD auroral imagers. The system can record 24-hour auroral activities from October to March of the following winter each year.

Data characteristics:

The time resolution of the observation results of two consecutive frames is 10 s. The camera uses a 512×512 square pixel array, and the geographic zenith is located near the center of the field of view (FOV). The coverage diameter of the all-sky FOV is approximately 1000 km. The spatial resolution is from 1.1 km at the zenith to 36 km at the horizon at an altitude of 150 km. All aurora images are provided in .bmp image format.

Data preprocess:



Subtracting dark current and rescaling. Dark current is deemed as system noise caused by equipment. It is removed from images before further operation. Every image is then stretched with a cutoff value of 4000 and rescaled from 16 to 8 bits.

Masking and cropping. A circle mask with a radius of 220 pixels is applied to cut off the outer regions where significant wide-angle distortion happens and may contain YRS lights. Then, the original image size of 512×512 is cropped to 440×440 pixels.

 Rotation. We rotated the images counter-clockwise by 61.11 with the north being upward.


Data naming convention:

Each auroral data has a unique file name that contains the N/S, date, band, and time information.

Filename example: N20031221G081212.



N: North pole

20031221: December 21, 2003

G: G-band

081212: 8:12:12 UT
DOI: 10.5281/zenodo.10464846
title: All-sky imager observation data from the Chinese Yellow River Station, Ny-Ålesund, Svalbard

description: Introduction

The aurora images in this dataset are from the all-sky imagers at the Yellow River Station (YRS). And it is used in the paper Automatically sketching Auroral Skeleton Structure in All-sky Image for Measuring Aurora Arcs.

This dataset consists of the following sections:



N20040116G.zip: 4,319 observation images as of January 16, 2004;

Raw data and reading code.zip: 8634 raw data items of December 23, 2003, and reading code;

80 imgs&annotations.zip: 80 ASI images and the corresponding manual annotations with pixel-level masks.


In the following sections, the data source, acquisition instruments, data characteristics, preprocessing methods and naming conventions of this dataset will be introduced.

Data source:

The auroral images used in this study are ground-based observation data acquired by three-wavelength (427.8, 557.7, and 630.0 nm) all-sky imagers at YRS in Ny-Ålesund, Svalbard. The geographic coordinates of YRS are 78.92°N, 11.93°E, and the corrected geomagnetic latitude is 76.24°, MLT≈UT+3 h.

Data acquisition instruments:

Data were obtained from all-sky CCD auroral imagers. The system can record 24-hour auroral activities from October to March of the following winter each year.

Data characteristics:

The time resolution of the observation results of two consecutive frames is 10 s. The camera uses a 512×512 square pixel array, and the geographic zenith is located near the center of the field of view (FOV). The coverage diameter of the all-sky FOV is approximately 1000 km. The spatial resolution is from 1.1 km at the zenith to 36 km at the horizon at an altitude of 150 km. All aurora images are provided in .bmp image format.

Data preprocess:



Subtracting dark current and rescaling. Dark current is deemed as system noise caused by equipment. It is removed from images before further operation. Every image is then stretched with a cutoff value of 4000 and rescaled from 16 to 8 bits.

Masking and cropping. A circle mask with a radius of 220 pixels is applied to cut off the outer regions where significant wide-angle distortion happens and may contain YRS lights. Then, the original image size of 512×512 is cropped to 440×440 pixels.

 Rotation. We rotated the images counter-clockwise by 61.11 with the north being upward.


Data naming convention:

Each auroral data has a unique file name that contains the N/S, date, band, and time information.

Filename example: N20031221G081212.



N: North pole

20031221: December 21, 2003

G: G-band

081212: 8:12:12 UT
DOI: 10.6084/m9.figshare.24953820
title: 11sub_result_ALFF-ReHo(1).xlsx

description: midazolam, thalamocortical communication, functional magnetic resonance imaging, neurotoxicity, chidren
DOI: 10.6084/m9.figshare.24953820.v1
title: 11sub_result_ALFF-ReHo(1).xlsx

description: midazolam, thalamocortical communication, functional magnetic resonance imaging, neurotoxicity, chidren
DOI: 10.6084/m9.figshare.24953874
title: Dataset_Development and Initial Validation of the Constructed Awareness Scale

description: The Constructed Awareness Scale (CAS) is a self-reporting scale that measures personality types according to the Constructed Awareness typology. This study describes the CAS’s development and initial testing. Recommended instrument development procedures, exploratory factor analysis, and internal reliability coefficients revealed evidence for content validity, construct validity, and internal reliability.
DOI: 10.5281/zenodo.10464957
title: POPC bilayer at 310K with the CHARMM36-NBFIX force field, 111 mM NaCl

description: prosECCo 75 paper related data
DOI: 10.5281/zenodo.10464958
title: POPC bilayer at 310K with the CHARMM36-NBFIX force field, 111 mM NaCl

description: prosECCo 75 paper related data
DOI: 10.5281/zenodo.10464945
title: POPC bilayer at 310K with the CHARMM36-NBFIX force field, 111 mM CaCl2

description: prosECCo 75 paper related data
DOI: 10.5281/zenodo.10464946
title: POPC bilayer at 310K with the CHARMM36-NBFIX force field, 111 mM CaCl2

description: prosECCo 75 paper related data
DOI: 10.5281/zenodo.10464960
title: POPC bilayer at 310K with the prosECCo75 force field, 111 mM NaCl

description: prosECCo 75 paper related data
DOI: 10.5281/zenodo.10464959
title: POPC bilayer at 310K with the prosECCo75 force field, 111 mM NaCl

description: prosECCo 75 paper related data
DOI: 10.5281/zenodo.10001724
title: BMRQ dataset and Supplementary Information
DOI: 10.5281/zenodo.10001725
title: BMRQ_dataset
DOI: 10.5281/zenodo.10465073
title: BMRQ dataset and Supplementary Information
DOI: 10.6084/m9.figshare.24953565.v1
title: global carbon emission_20240106

description: different countries and income groups
DOI: 10.6084/m9.figshare.24953565
title: Test_global carbon emission_20240106

description: different countries and income groups
DOI: 10.6084/m9.figshare.24953565.v2
title: global carbon emission_20240106

description: different countries and income groups
DOI: 10.6084/m9.figshare.24953928
title: 20240107_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.6084/m9.figshare.24953928.v1
title: 20240107_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.34740/kaggle/dsv/7350672
title: MoviesDatasets
DOI: 10.34740/kaggle/dsv/7350675
title: Mahanagar Yatayat Transport Dataset
DOI: 10.5281/zenodo.10045807
title: Interannual Variability of Zonal Mean Temperature, Water Vapor, and Clouds in the Tropical Tropopause Layer

description: This is a NetCDF file that holds monthly anomalies for predictors and target variables used in "Interannual Variability of Zonal Mean Temperature, Water Vapor, and Clouds in the Tropical Tropopause Layer".
DOI: 10.5281/zenodo.10045808
title: Interannual Variability of Zonal Mean Temperature, Water Vapor, and Clouds in the Tropical Tropopause Layer

description: This is a NetCDF file that holds monthly anomalies for predictors and target variables used in "Interannual Variability of Zonal Mean Temperature, Water Vapor, and Clouds in the Tropical Tropopause Layer".
DOI: 10.5281/zenodo.10463640
title: Interannual Variability of Zonal Mean Temperature, Water Vapor, and Clouds in the Tropical Tropopause Layer

description: This is a NetCDF file that holds monthly anomalies for predictors and target variables used in "Interannual Variability of Zonal Mean Temperature, Water Vapor, and Clouds in the Tropical Tropopause Layer".
DOI: 10.6084/m9.figshare.24954024
title: employee & patient satisfaction in CHC

description: specific factors of employee satisfaction—such as compensation, supervision, and work environment—potentially influence patient satisfaction.
DOI: 10.6084/m9.figshare.24954024.v1
title: employee & patient satisfaction in CHC

description: specific factors of employee satisfaction—such as compensation, supervision, and work environment—potentially influence patient satisfaction.
DOI: 10.5281/zenodo.10465365
title: Galaxy masked catalog and Galaxy pixel/shell skymap
DOI: 10.5281/zenodo.10465366
title: Galaxy masked catalog and Galaxy pixel/shell skymap
DOI: 10.5281/zenodo.10465264
title: Extending Refactoring Detection to Kotlin: A Dataset and Comparative Study

description: This page serves as supplementary material for the article Extending Refactoring Detection to Kotlin: A Dataset and Comparative Study. In detail, we offer a downloadable dataset in JSON format, comprising 2,043 instances of refactoring instances covering 21 distinct refactoring types. These refactorings are applied within 200 commits across 10 Kotlin repositories and are manually validated by the authors of the paper. 

Results.json: The results as a single JSON file.





Overview of JSON Template: Each entry in this file provides details about commits, including their SHA-1 hash, GitHub URL, and an exhaustive list of refactorings identified in that specific commit. Refactorings are defined by their type (e.g., 'RenameClass') and are accompanied by detailed descriptions of the refactoring. Additionally, the entry specifies the tools that detected the refactoring, such as 'RefDetect' and 'KotlinRMiner.' The validation field indicates whether the refactoring was confirmed, using 'TP' for true positive and 'FP' for false positive. Optional comments and validator information may be also included.



AllCommits.zip: The Results for each repository in a single JSON file.

Times.xlsx: The Excel file containing the time taken by each tool (RefDetect and KotlinMiner) to identify refactoring in each commit.

Results.xlsx: The Excel file contains precision, recall, and F-score metrics for all identified refactoring types.
DOI: 10.5281/zenodo.10465265
title: Extending Refactoring Detection to Kotlin: A Dataset and Comparative Study

description: This page serves as supplementary material for the article Extending Refactoring Detection to Kotlin: A Dataset and Comparative Study. In detail, we offer a downloadable dataset in JSON format, comprising 2,043 instances of refactoring instances covering 21 distinct refactoring types. These refactorings are applied within 200 commits across 10 Kotlin repositories and are manually validated by the authors of the paper. 

Results.json: The results as a single JSON file.





Overview of JSON Template: Each entry in this file provides details about commits, including their SHA-1 hash, GitHub URL, and an exhaustive list of refactorings identified in that specific commit. Refactorings are defined by their type (e.g., 'RenameClass') and are accompanied by detailed descriptions of the refactoring. Additionally, the entry specifies the tools that detected the refactoring, such as 'RefDetect' and 'KotlinRMiner.' The validation field indicates whether the refactoring was confirmed, using 'TP' for true positive and 'FP' for false positive. Optional comments and validator information may be also included.



AllCommits.zip: The Results for each repository in a single JSON file.

Times.xlsx: The Excel file containing the time taken by each tool (RefDetect and KotlinMiner) to identify refactoring in each commit.

Results.xlsx: The Excel file contains precision, recall, and F-score metrics for all identified refactoring types.
DOI: 10.34740/kaggle/ds/4267519
title: ⚡Swiss Energy Balance Dataset from 1980-2022:🌿
DOI: 10.3886/e196881
title: Firm Survival and the Rise of the Factory

description: This is the replication package for the paper "Firm Survival and the Rise of the Factory" by Thor Berger and Vinzent Ostermeyer. The paper is published in the Economic History Review.
description: Swedish manufacturing firms/establishments.
description: For more information regarding the underlying data, visit https://www.historicalmanufacturingcensus.se/.
DOI: 10.3886/e196881v1
title: Firm Survival and the Rise of the Factory

description: This is the replication package for the paper "Firm Survival and the Rise of the Factory" by Thor Berger and Vinzent Ostermeyer. The paper is published in the Economic History Review.
description: Swedish manufacturing firms/establishments.
description: For more information regarding the underlying data, visit https://www.historicalmanufacturingcensus.se/.
DOI: 10.5519/qd.ftqa16tj
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (93 records)
DOI: 10.5281/zenodo.10465618
title: Molecular Dynamics Results for Crystalline Gold

description: LAMMPS: Molecular Dynamics Results for Crystalline Gold
DOI: 10.5281/zenodo.10465619
title: Molecular Dynamics Results for Crystalline Gold

description: LAMMPS: Molecular Dynamics Results for Crystalline Gold
DOI: 10.5519/qd.wfuk9dta
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (2513 records)
DOI: 10.5281/zenodo.3232907
title: Sri Ksetra (HMA) Digitised Paper Archive (Version 3)

description: This is the current version of a digitised excavation archive, deriving from archaeological investigations at Sri Ksetra (HMA) in Burma (Myanmar) carried out 2014-16. It comprises: excavation records, artefact illustrations, section drawings, plans, maps, artefact data, sample data, field notes and accompanying indexes.
DOI: 10.5281/zenodo.3232908
title: Sri Ksetra (HMA) Digitised Paper Archive (Version 3)

description: This is the current version of a digitised excavation archive, deriving from archaeological investigations at Sri Ksetra (HMA) in Burma (Myanmar) carried out 2014-16. It comprises: excavation records, artefact illustrations, section drawings, plans, maps, artefact data, sample data, field notes and accompanying indexes.
DOI: 10.34740/kaggle/dsv/7351762
title: Balochi Language to English Translation Dataset
DOI: 10.5519/qd.qoxhqdr7
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (57 records)
DOI: 10.6084/m9.figshare.24954144
title: DATA FOR ATRESIA BILIER

description: data description not more than 500 words
DOI: 10.5281/zenodo.10463648
title: HiTAB-Chicago: HeIght map of Trees And Buildings for the city of Chicago

description: The vertical dimensions of urban morphology, specifically the heights of buildings and trees, exert significant influence on wind flow fields in urban street canyons and the thermal properties of urban fabric, subsequently affecting the microclimate, noise levels, and air quality. Despite their importance, these critical attributes are less commonly available and rarely utilized in urban climate models compared to planar land use and land cover data. In our study, we explicitly mapped the height of trees and buildings (HiTAB) across the city of Chicago at 1-meter spatial resolution, using a data fusion approach. This approach integrates high-precision LiDAR cloud point data, building footprint inventory, and multi-band satellite images. Specifically, the digital terrain and surface models were first created from the LiDAR dataset to calculate the height of surface objects, while the rest of the datasets were used to delineate trees and buildings. We validated the derived height information against the existing building database in downtown Chicago and the Meter-scale Urban Land Cover map from the Environmental Protection Agency, respectively. Given their high spatial resolution, the height maps will enhance the parameterization process in physical-based models ranging from the simplest slab urban canopy model to the much-sophisticated computational fluid dynamics model. In addition, the datasets can also inform data-driven urban models to achieve higher resolution and lower uncertainties. Moreover, our method can be extended to other urban regions, benefiting from the growing availability of high-resolution urban informatics globally. Ultimately, these datasets can substantially contribute to future studies on hyper-local weather dynamics, urban heterogeneity, morphology, and planning, providing a more comprehensive understanding of urban environments.
DOI: 10.5281/zenodo.10463647
title: HiTAB-Chicago: HeIght map of Trees And Buildings for the city of Chicago

description: The vertical dimensions of urban morphology, specifically the heights of buildings and trees, exert significant influence on wind flow fields in urban street canyons and the thermal properties of urban fabric, subsequently affecting the microclimate, noise levels, and air quality. Despite their importance, these critical attributes are less commonly available and rarely utilized in urban climate models compared to planar land use and land cover data. In our study, we explicitly mapped the height of trees and buildings (HiTAB) across the city of Chicago at 1-meter spatial resolution, using a data fusion approach. This approach integrates high-precision LiDAR cloud point data, building footprint inventory, and multi-band satellite images. Specifically, the digital terrain and surface models were first created from the LiDAR dataset to calculate the height of surface objects, while the rest of the datasets were used to delineate trees and buildings. We validated the derived height information against the existing building database in downtown Chicago and the Meter-scale Urban Land Cover map from the Environmental Protection Agency, respectively. Given their high spatial resolution, the height maps will enhance the parameterization process in physical-based models ranging from the simplest slab urban canopy model to the much-sophisticated computational fluid dynamics model. In addition, the datasets can also inform data-driven urban models to achieve higher resolution and lower uncertainties. Moreover, our method can be extended to other urban regions, benefiting from the growing availability of high-resolution urban informatics globally. Ultimately, these datasets can substantially contribute to future studies on hyper-local weather dynamics, urban heterogeneity, morphology, and planning, providing a more comprehensive understanding of urban environments.
DOI: 10.34740/kaggle/dsv/7351993
title: Forex Exchange Rates Since 2004 (Updated Daily)
DOI: 10.34740/kaggle/dsv/7352012
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.34740/kaggle/dsv/7352043
title: Top Spotify Songs in 73 Countries (Daily Updated)
DOI: 10.34740/kaggle/dsv/7352052
title: Full TMDB Movies Dataset 2023 (930K Movies)
DOI: 10.17617/4.e7
title: Desmarestia dudresnayi genome assembly

description: Chromosome-level assembly of the monoicous species Desmarestia dudresnayi. The following files are available:
DOI: 10.34740/kaggle/dsv/7352049
title: SF Housing Production Soars Since 2005