cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc1zrx6v
title: CCDC 1840228: Experimental Crystal Structure Determination

description: Related Article: Daniel E. Díaz, Leonel Llanos, Pablo Arce, Romina Lorca, Juan Guerrero, Juan Costamagna, Daniel Aravena, Guillermo Ferraudi, Allen Oliver, A. Graham Lappin, Luis Lemus|2018|Chem.-Eur.J.|24|13839|doi:10.1002/chem.201802290
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1z9bzl
title: CCDC 1826240: Experimental Crystal Structure Determination

description: Related Article: Emira Kahrović, Adnan Zahirović, Aleksandar Višnjevac, Irnesa Osmanković, Emir Turkušić, Harun Kurtagić|2018|Croat.Chem.Acta|91|195|doi:10.5562/cca3334
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1z9c0n
title: CCDC 1826241: Experimental Crystal Structure Determination

description: Related Article: Emira Kahrović, Adnan Zahirović, Aleksandar Višnjevac, Irnesa Osmanković, Emir Turkušić, Harun Kurtagić|2018|Croat.Chem.Acta|91|195|doi:10.5562/cca3334
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc23n510
title: CCDC 1955791: Experimental Crystal Structure Determination

description: Related Article: Norihisa Hoshino, Syunsaku Tamura, Tomoyuki Akutagawa|2020|Chem.-Eur.J.|26|2610|doi:10.1002/chem.201904553
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc21kdz0
title: CCDC 1893572: Experimental Crystal Structure Determination

description: Related Article: M. Shahwaz Ahmad, Mohd Khalid, M. Shahnawaz Khan, M. Shahid, Musheer Ahmad, Monika, Azaj Ansari, Mo Ashafaq|2020|New J.Chem.|44|7998|doi:10.1039/D0NJ00605J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc23z8x9
title: CCDC 1965521: Experimental Crystal Structure Determination

description: Related Article: Safaa Eldin H. Etaiw, Rabie S. Farag, Hassan Marie, Fatma A. Elsharqawy|2020|Solid State Sciences|102|106160|doi:10.1016/j.solidstatesciences.2020.106160
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc25q5hl
title: CCDC 2017309: Experimental Crystal Structure Determination

description: Related Article: Álvaro Martínez-Camarena, Matteo Savastano, José M. Llinares, Begoña Verdejo, Antonio Bianchi, Enrique García-España, Carla Bazzicalupi|2020|Inorg.Chem.Front.|7|4239|doi:10.1039/D0QI00912A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc25zfd0
title: CCDC 2025242: Experimental Crystal Structure Determination

description: Related Article: Akiko Hori, Hiroyuki Kobayashi, Genta Sakamoto, Hidetaka Yuge|2020|Polyhedron|192|114825|doi:10.1016/j.poly.2020.114825
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.5575442
title: Spatiotemporal analysis of plankton drivers in the Belgian part of the North Sea. Data, scripts and model output

description: This archive contains the input data, R scripts and final results of a mechanistic model that uses near real-time data from the Belgian Part of the North Sea (2011-2017) to quantify the relative contributions of the bottom-up and top-down drivers in phytoplankton dynamics. Input data are zooplankton and phytoplankton abundances, nutrients, Sea Surface Temperature (SST), photosynthetically active radiation (PAR); from the LifeWatch data and infrastructure, funded by Research Foundation - Flanders (FWO). Water temperature data for one of the locations was obtained from Flemish Banks Monitoring Network at https://meetnetvlaamsebanken.be/. The R scripts are presented in a R Markdown file that can be executed in the Blue-Cloud Zoo and Phytoplankton EOV products Vlab at https://blue-cloud.d4science.org/web/zoo-phytoplankton_eov, operated by D4Science.org, www.d4science.org (Assante et al., 2019).
DOI: 10.5281/zenodo.5575441
title: Spatiotemporal analysis of plankton drivers in the Belgian part of the North Sea. Data, scripts and model output

description: This archive contains the input data, R scripts and final results of a mechanistic model that uses near real-time data from the Belgian Part of the North Sea (2011-2017) to quantify the relative contributions of the bottom-up and top-down drivers in phytoplankton dynamics. Input data are zooplankton and phytoplankton abundances, nutrients, Sea Surface Temperature (SST), photosynthetically active radiation (PAR); from the LifeWatch data and infrastructure, funded by Research Foundation - Flanders (FWO). Water temperature data for one of the locations was obtained from Flemish Banks Monitoring Network at https://meetnetvlaamsebanken.be/. The R scripts are presented in a R Markdown file that can be executed in the Blue-Cloud Zoo and Phytoplankton EOV products Vlab at https://blue-cloud.d4science.org/web/zoo-phytoplankton_eov, operated by D4Science.org, www.d4science.org (Assante et al., 2019).
DOI: 10.5281/zenodo.7014406
title: Mapping mineralogical heterogeneities at the nm-scale by scanning electron microscopy in modern Sardinian stromatolites: Deciphering the origin of their laminations

description: These are the raw or processed data used for a paper published in Chemical Geology by Debrie et al. (2022), entitled "Mapping mineralogical heterogeneities at the nm-scale by scanning electron microscopy in modern Sardinian stromatolites: Deciphering the origin of their laminations", https://doi.org/10.1016/j.chemgeo.2022.121059 The data content is summarized in the List_description_of_data.xlsx file
description: {"references": ["https://doi.org/10.1016/j.chemgeo.2022.121059"]}
DOI: 10.5281/zenodo.7014405
title: Mapping mineralogical heterogeneities at the nm-scale by scanning electron microscopy in modern Sardinian stromatolites: Deciphering the origin of their laminations

description: These are the raw or processed data used for a paper published in Chemical Geology by Debrie et al. (2022), entitled "Mapping mineralogical heterogeneities at the nm-scale by scanning electron microscopy in modern Sardinian stromatolites: Deciphering the origin of their laminations", https://doi.org/10.1016/j.chemgeo.2022.121059 The data content is summarized in the List_description_of_data.xlsx file
description: {"references": ["https://doi.org/10.1016/j.chemgeo.2022.121059"]}
DOI: 10.5281/zenodo.5117799
title: GWTC-2.1: Deep extended-catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Sensitivity of search pipelines to simulated signals

description: Results of search pipelines (GSTLAL, MBTA, PYCBC, PYCBC BBH) used to identify candidates in GWTC-2.1 on a set of simulated signals corresponding to binary neutron star (BNS), neutron star black holes (NSBH), and binary black holes (BBH) signals. Additionally, we include a README file which provides information on how to read these files.
description: LIGO Laboratory and Advanced LIGO are funded by the United States National Science Foundation (NSF) as well as the Science and Technology Facilities Council (STFC) of the United Kingdom, the Max-Planck-Society (MPS), and the State of Niedersachsen/Germany for support of the construction of Advanced LIGO and construction and operation of the GEO600 detector. Additional support for Advanced LIGO was provided by the Australian Research Council. Virgo is funded, through the European Gravitational Observatory (EGO), by the French Centre National de Recherche Scientifique (CNRS), the Italian Istituto Nazionale di Fisica Nucleare (INFN) and the Dutch Nikhef, with contributions by institutions from Belgium, Germany, Greece, Hungary, Ireland, Japan, Monaco, Poland, Portugal, Spain.
DOI: 10.5281/zenodo.5148739
title: GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Candidate Data Release

description: Data associated with candidates in GWTC-2.1. These are gravitational-wave candidates from the first half of the third observing run (O3a) of the Advanced LIGO and Virgo detectors that pass a false alarm rate threshold of 2/day. We upload a tar file (search_data_GWTC2p1.tar.gz) containing all the data and a python notebook (search_data.ipynb) which provides description on how to use the files contained in the dataset.
description: LIGO Laboratory and Advanced LIGO are funded by the United States National Science Foundation (NSF) as well as the Science and Technology Facilities Council (STFC) of the United Kingdom, the Max-Planck-Society (MPS), and the State of Niedersachsen/Germany for support of the construction of Advanced LIGO and construction and operation of the GEO600 detector. Additional support for Advanced LIGO was provided by the Australian Research Council. Virgo is funded, through the European Gravitational Observatory (EGO), by the French Centre National de Recherche Scientifique (CNRS), the Italian Istituto Nazionale di Fisica Nucleare (INFN) and the Dutch Nikhef, with contributions by institutions from Belgium, Germany, Greece, Hungary, Ireland, Japan, Monaco, Poland, Portugal, Spain.
DOI: 10.7935/nfnt-hm34
title: LIGO Virgo strain data from observing run O3a (Apr 2019 - Sep 2019)
DOI: 10.6084/m9.figshare.20527995
title: ZnO paper.xlsx

description: The data shows the result of the analysis of different streams (Feed, Permeate, Retentate) from a system using ceramic membranes combined with photocatalytic nanoparticles for the treatment of surface water
DOI: 10.6084/m9.figshare.14660488.v1
title: Factors Affecting the Time to Publication in Ophthalmology Journals: A Comprehensive Bibliometric Analysis

description: There are currently no available aids for authors when selecting ophthalmology journals to submit their manuscripts. We aim to provide comprehensive data on the duration from submission to various stages of the publication process and assess factors influencing time to publication in ophthalmology journals. A list of ophthalmology journals was obtained from the 2019 Web of Science Journal Citation Report. Journal characteristics, such as five-year impact factor, number of authors per article, journal type, and number of multi-institutional articles, were collected. The dates of submission, acceptance, electronic and print publication for all articles published in an ophthalmology journal in 2019 were determined. In total, 56 journals and 8835 research articles were included. Of these articles, 3591 (40.6%) were open access and 4837 (54.7%) were multi-institutional. In 2019, most publications came from the United States of America (n = 1973), China (n = 1069) and Germany (n = 602). Significant associations were found between various predictors and a reduced mean number of days from submission to electronic publication: increased journal five-year impact factor (<i>p = </i>.026), more authors (<i>p = </i>.028), publishing in a hybrid journal (both open-access and subscription articles) versus an open-access journal (<i>p = </i>.021), and a reduced proportion of multi-institutional articles in a journal (<i>p = </i>.030). There is a wide variation in the time to acceptance and publication in ophthalmology journals. Authors can expect a shorter time to publication when publishing in high-impact journals.
DOI: 10.6084/m9.figshare.14660488
title: Factors Affecting the Time to Publication in Ophthalmology Journals: A Comprehensive Bibliometric Analysis

description: There are currently no available aids for authors when selecting ophthalmology journals to submit their manuscripts. We aim to provide comprehensive data on the duration from submission to various stages of the publication process and assess factors influencing time to publication in ophthalmology journals. A list of ophthalmology journals was obtained from the 2019 Web of Science Journal Citation Report. Journal characteristics, such as five-year impact factor, number of authors per article, journal type, and number of multi-institutional articles, were collected. The dates of submission, acceptance, electronic and print publication for all articles published in an ophthalmology journal in 2019 were determined. In total, 56 journals and 8835 research articles were included. Of these articles, 3591 (40.6%) were open access and 4837 (54.7%) were multi-institutional. In 2019, most publications came from the United States of America (n = 1973), China (n = 1069) and Germany (n = 602). Significant associations were found between various predictors and a reduced mean number of days from submission to electronic publication: increased journal five-year impact factor (<i>p = </i>.026), more authors (<i>p = </i>.028), publishing in a hybrid journal (both open-access and subscription articles) versus an open-access journal (<i>p = </i>.021), and a reduced proportion of multi-institutional articles in a journal (<i>p = </i>.030). There is a wide variation in the time to acceptance and publication in ophthalmology journals. Authors can expect a shorter time to publication when publishing in high-impact journals.
DOI: 10.5281/zenodo.7014618
title: The mere presence of a smartphone reduces basal attentional performance

description: This dataset contains the relevant data for the study “The mere presence of a smartphone reduces basal attentional performance”. The following variables are presented: Person: Numbering of the test subjects Gender: 1- male; 2- female Age: Age of the test subjects Question1 - Question10: The checked values by the test subjects of the questionnaire d-KV-SSS (German Short Version of the Smartphone Questionnaire) WithWithout: The conduction of the test in smartphone presence (with- 1) and out of smartphone presence (without- 2) <strong>Values of the attention test (d2-R):</strong> APValue: The attention performance value; a person's ability to focus their attention PTOValue: The “Processed target objects” value that indicates the speed of the test processing E% value: The Error % value, the accuracy of a test person in processing the d2-R ValidInvalid: Valid or invalid test performance SmartphoneDependenceSum: The summed-up values of the questionnaire (Question 1 to Question 10), thus the results of the questionnaire d-KV-SSS that indicate a possible tendency towards a smartphone dependency In our study, it was hypothesized that there is a lower attentional performance under smartphone presence. To test this hypothesis, three one-tailed ANOVAs were conducted with the presence and absence of the smartphone as the independent variable and one of the three given values of the d2-R (attention performance, speed value and error value) as the dependent variable. The total score of the d-KV-SSS (“SmartphoneDependenceSum”) indicates a tendency towards smartphone dependence. A one-factor ANOVA was used to examine the subjects' attention performance in connection with a tendency towards smartphone addiction. The presence or absence of the smartphone was the independent variable, and the attention performance score was the dependent variable.
DOI: 10.5281/zenodo.7014617
title: The mere presence of a smartphone reduces basal attentional performance

description: This dataset contains the relevant data for the study “The mere presence of a smartphone reduces basal attentional performance”. The following variables are presented: Person: Numbering of the test subjects Gender: 1- male; 2- female Age: Age of the test subjects Question1 - Question10: The checked values by the test subjects of the questionnaire d-KV-SSS (German Short Version of the Smartphone Questionnaire) WithWithout: The conduction of the test in smartphone presence (with- 1) and out of smartphone presence (without- 2) <strong>Values of the attention test (d2-R):</strong> APValue: The attention performance value; a person's ability to focus their attention PTOValue: The “Processed target objects” value that indicates the speed of the test processing E% value: The Error % value, the accuracy of a test person in processing the d2-R ValidInvalid: Valid or invalid test performance SmartphoneDependenceSum: The summed-up values of the questionnaire (Question 1 to Question 10), thus the results of the questionnaire d-KV-SSS that indicate a possible tendency towards a smartphone dependency In our study, it was hypothesized that there is a lower attentional performance under smartphone presence. To test this hypothesis, three one-tailed ANOVAs were conducted with the presence and absence of the smartphone as the independent variable and one of the three given values of the d2-R (attention performance, speed value and error value) as the dependent variable. The total score of the d-KV-SSS (“SmartphoneDependenceSum”) indicates a tendency towards smartphone dependence. A one-factor ANOVA was used to examine the subjects' attention performance in connection with a tendency towards smartphone addiction. The presence or absence of the smartphone was the independent variable, and the attention performance score was the dependent variable.
DOI: 10.6084/m9.figshare.19852873
title: Nevados Del Ruiz

description: ADTC-InSAR data for Nevados Del Ruiz
DOI: 10.6084/m9.figshare.19852873.v1
title: Nevados Del Ruiz

description: ADTC-InSAR data for Nevados Del Ruiz
DOI: 10.6084/m9.figshare.19854259
title: Hualca-hualca

description: ADTC-InSAR data for Hualca-hualca volcano
DOI: 10.6084/m9.figshare.19854259.v1
title: Hualca-hualca

description: ADTC-InSAR data for Hualca-hualca volcano
DOI: 10.6084/m9.figshare.19854262
title: Galeras

description: ADTC-InSAR data for Galeras volcano
DOI: 10.6084/m9.figshare.19854262.v1
title: Galeras

description: ADTC-InSAR data for Galeras volcano
DOI: 10.6084/m9.figshare.19854265
title: Reventador

description: ADTC-InSAR data for Reventador volcano
DOI: 10.6084/m9.figshare.19854265.v1
title: Reventador

description: ADTC-InSAR data for Reventador volcano
DOI: 10.6084/m9.figshare.19857496
title: Uturuncu

description: ADTC-InSAR data for Uturuncu volcano
DOI: 10.6084/m9.figshare.19857496.v1
title: Uturuncu

description: ADTC-InSAR data for Uturuncu volcano
DOI: 10.6084/m9.figshare.19857499.v1
title: Robledo

description: ADTC-InSAR data for Robledo volcano
DOI: 10.6084/m9.figshare.19857745
title: Llaima

description: ADTC-InSAR data for Llaima volcano
DOI: 10.6084/m9.figshare.19857499
title: Robledo

description: ADTC-InSAR data for Robledo volcano
DOI: 10.6084/m9.figshare.19857745.v1
title: Llaima

description: ADTC-InSAR data for Llaima volcano
DOI: 10.6084/m9.figshare.19857748
title: Copahue

description: ADTC-InSAR data for Copahue volcano
DOI: 10.6084/m9.figshare.19857748.v1
title: Copahue

description: ADTC-InSAR data for Copahue volcano
DOI: 10.6084/m9.figshare.19858801
title: LONLAT

description: Latitude and longitude for each of the volcanoes
DOI: 10.6084/m9.figshare.19858801.v1
title: LONLAT

description: Latitude and longitude for each of the volcanoes
DOI: 10.6084/m9.figshare.19858807
title: Cordón Caulle

description: ADTC-InSAR data for Cordón Caulle
DOI: 10.6084/m9.figshare.19858807.v1
title: Cordón Caulle

description: ADTC-InSAR data for Cordón Caulle
DOI: 10.6084/m9.figshare.19873789
title: Chaitén

description: ADTC-InSAR data for Chaitén volcano
DOI: 10.6084/m9.figshare.20085635
title: Corr__ADTC_InSAR.m

description: Script to estimate tropospheric correction with ADTC-InSAR in MATLAB
DOI: 10.6084/m9.figshare.20085635.v1
title: Corr__ADTC_InSAR.m

description: Script to estimate tropospheric correction with ADTC-InSAR in MATLAB
DOI: 10.6084/m9.figshare.20085638
title: Test data

description: Test interferogram to generate the tropospheric correction with ADTC-InSAR using the scripts Corr__ADTC_InSAR.py and Corr__ADTC-InSAR.m
DOI: 10.6084/m9.figshare.19873789.v1
title: Chaitén

description: ADTC-InSAR data for Chaitén volcano
DOI: 10.6084/m9.figshare.20085638.v1
title: Test data

description: Test interferogram to generate the tropospheric correction with ADTC-InSAR using the scripts Corr__ADTC_InSAR.py and Corr__ADTC-InSAR.m
DOI: 10.6084/m9.figshare.20085641
title: Corr__ADTC_InSAR.py

description: Script to estimate tropospheric correction with ADTC-InSAR in PYTHON
DOI: 10.6084/m9.figshare.20085641.v1
title: Corr__ADTC_InSAR.py

description: Script to estimate tropospheric correction with ADTC-InSAR in PYTHON
DOI: 10.6084/m9.figshare.20092556
title: README

description: Description of the ADTC-InSAR database and scripts
DOI: 10.6084/m9.figshare.20092556.v1
title: README

description: Description of the ADTC-InSAR database and scripts