cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc1pfh5s
title: CCDC 1562095: Experimental Crystal Structure Determination

description: Related Article: Jacek Chrzanowski,  Dorota Krasowska,  Malgorzata Urbaniak, Leslaw Sieron,  Patrycja Pokora- Sobczak,  Oleg M. Demchuk, and Jozef Drabowicz|2018|Eur.J.Org.Chem.|2018|4614|doi:10.1002/ejoc.201800698
DOI: 10.5517/ccdc.csd.cc1pfh6t
title: CCDC 1562096: Experimental Crystal Structure Determination

description: Related Article: Jacek Chrzanowski,  Dorota Krasowska,  Malgorzata Urbaniak, Leslaw Sieron,  Patrycja Pokora- Sobczak,  Oleg M. Demchuk, and Jozef Drabowicz|2018|Eur.J.Org.Chem.|2018|4614|doi:10.1002/ejoc.201800698
DOI: 10.5517/ccdc.csd.cc1pfh7v
title: CCDC 1562097: Experimental Crystal Structure Determination

description: Related Article: Jacek Chrzanowski,  Dorota Krasowska,  Malgorzata Urbaniak, Leslaw Sieron,  Patrycja Pokora- Sobczak,  Oleg M. Demchuk, and Jozef Drabowicz|2018|Eur.J.Org.Chem.|2018|4614|doi:10.1002/ejoc.201800698
DOI: 10.14284/421
title: Bulk carbon and nitrogen, and amino acid-specific carbon stable isotope data of major production sources and biomass-important consumers in Maldivian coral reef fish food webs

description: Dataset focuses on six major production sources supporting coral-reef food-webs in the Maldives, using two types of stable isotope data (bulk carbon and nitrogen, and compound-specific [essential amino acid-specific] carbon stable isotope) of species widely considered to align with a particular trophic guild together with respective production sources or end members of each pathway.
description: The corals, sponge, macroalgae and sea cucumber were collected by hand during SCUBA diving. Pelagic production sources (diurnal and nocturnal plankton) were collected with a plankton net (500 mm aperture, 150 µm mesh) towed at the sea surface at a steady speed of 3 knots for 20 min along the reef edge. The diurnal plankton was sampled at most sites in the inner- and outer-atoll, whereas the nocturnal plankton sampling was confined to two adjacent reefs in the outer-atoll, and two reef sites (Vabbinfaru and Ihuru) in the inner-atoll due to limited access. Most fishes were collected with a Hawaiian sling except the Caesionidae spp from the outer-atoll which were collected by Maldivian fishermen. Carbon and nitrogen bulk stable isotopes of macroalgae, plankton and ground samples (fish white muscle tissues) were analyzed EA-IRMS. Amino acids-specific stable isotope analysis of selected ground samples: AA fractions were analysed by GC/C/IRMS to generate the chromatography of the five essential amino acids (δ13C-EAAs of Valine [Val], Leucine [Leu], Threonine [Thr], Phenylalanine [Phe] and Lysine [Lys]).
DOI: 10.6084/m9.figshare.13089857
title: BD_moral injury_initial.sav

description: Moral injury among physicians during the COVID-19 pandemic
DOI: 10.6084/m9.figshare.13089857.v1
title: BD_moral injury_initial.sav

description: Moral injury among physicians during the COVID-19 pandemic
DOI: 10.21227/64ke-c966
title: Cloud benchmarking and performance analysis of an HPC application in Amazon EC2

description: Computing has revolutionized the way computational resources are delivered by making them available on-demand and at a low cost. Consistent with the democratization of technology in this era of globalization, it has made computing power and data storage more affordable and accessible than ever before. The existence of hundreds of cloud providers today attests to the massive success of cloud computing. We performed a feasibility study in the category of HPC in the cloud. It consisted of porting a CFD simulation from a Cray XC40 supercomputer (Beskow) to Amazon Cloud using the tool ParallelCluster and running a set of benchmarks to help us understand the results. We find the performance of our target application is 1.17 times better in the cloud, and we show strong scaling up to 2304 processes. This dataset shows the results in both the Amazon Web Services Cloud environment and Beskow for:the OSU benchmarks for all the collective MPI routines (in the form of plots and a pdf file with tables)the NAS benchmarks in shared memory and for up to 8 nodesParaview solution files for the problem we tackleComparison plots between the performance on Beskow and the AWS EC2 clusterStrong scaling results
DOI: 10.21227/y7z0-1j27
title: Cloud benchmarking and performance analysis of an HPC application in Amazon EC2

description: Computing has revolutionized the way computational resources are delivered by making them available on-demand and at a low cost. Consistent with the democratization of technology in this era of globalization, it has made computing power and data storage more affordable and accessible than ever before. The existence of hundreds of cloud providers today attests to the massive success of cloud computing. We performed a feasibility study in the category of HPC in the cloud. It consisted of porting a CFD simulation from a Cray XC40 supercomputer (Beskow) to Amazon Cloud using the tool ParallelCluster and running a set of benchmarks to help us understand the results. We find the performance of our target application is 1.17 times better in the cloud, and we show strong scaling up to 2304 processes. This dataset shows the results in both the Amazon Web Services Cloud environment and Beskow for:the OSU benchmarks for all the collective MPI routines (in the form of plots and a pdf file with tables)the NAS benchmarks in shared memory and for up to 8 nodesParaview solution files for the problem we tackleComparison plots between the performance on Beskow and the AWS EC2 clusterStrong scaling results
DOI: 10.21227/p2ex-y744
title: Model1

description: LR
DOI: 10.5281/zenodo.3819952
title: Data of the article "Efficient spin torques in antiferromagnetic CoO/Pt quantified by comparing field- and current- induced switching"

description: Data for experimental transport measurements and analytical calculations for the article "Efficient spin torques in antiferromagnetic CoO/Pt quantified by comparing field- and current- induced switching" (https://arxiv.org/abs/2003.05923)
description: The authors thank H. Meerfor skillful technical assistanceand insightful discussions. L.B acknowledges the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreements ARTES number 793159. L.B., R.L., and M.K. acknowledge support from the Graduate School of Excellence Materials Science in Mainz (MAINZ) DFG 266, the DAAD (Spintronics network, Project No. 57334897) and all groups from Mainz acknowledge that this work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -TRR 173 –268565370 (projects A01, A03, A11, B02, and B12). R.L. and M.K. acknowledge financial support from the Horizon 2020 Framework Programme of the European Commission under FET-Open grant agreement no. 863155 (s-Nebula). This work was also supported by ERATO "Spin Quantum Rectification Project" (Grant No. JPMJER1402) and the Grant-in-Aid for Scientific Research on Innovative Area, 11"Nano Spin Conversion Science" (Grant No. JP26103005), Grant-in-Aid for Scientific Research (C) (Grant No. JP20K05297) from JSPS KAKENHI, Japan. R.L. acknowledges the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement FAST number 752195.
DOI: 10.5281/zenodo.3819951
title: Data of the article "Efficient spin torques in antiferromagnetic CoO/Pt quantified by comparing field- and current- induced switching"

description: Data for experimental transport measurements and analytical calculations for the article "Efficient spin torques in antiferromagnetic CoO/Pt quantified by comparing field- and current- induced switching" (https://arxiv.org/abs/2003.05923)
description: The authors thank H. Meerfor skillful technical assistanceand insightful discussions. L.B acknowledges the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreements ARTES number 793159. L.B., R.L., and M.K. acknowledge support from the Graduate School of Excellence Materials Science in Mainz (MAINZ) DFG 266, the DAAD (Spintronics network, Project No. 57334897) and all groups from Mainz acknowledge that this work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -TRR 173 –268565370 (projects A01, A03, A11, B02, and B12). R.L. and M.K. acknowledge financial support from the Horizon 2020 Framework Programme of the European Commission under FET-Open grant agreement no. 863155 (s-Nebula). This work was also supported by ERATO "Spin Quantum Rectification Project" (Grant No. JPMJER1402) and the Grant-in-Aid for Scientific Research on Innovative Area, 11"Nano Spin Conversion Science" (Grant No. JP26103005), Grant-in-Aid for Scientific Research (C) (Grant No. JP20K05297) from JSPS KAKENHI, Japan. R.L. acknowledges the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement FAST number 752195.
DOI: 10.5281/zenodo.4084747
title: Labella_et_al_2020_IJCIS_DATASET

description: This dataset contains the underlying data for the following publication: <strong>Labella, Á., Koasidis, K., Nikas, A., Arsenopoulos, A., & Doukas, H. (2020). APOLLO: A Fuzzy Multi-criteria Group Decision-Making Tool in Support of Climate Policy. <em>International Journal of Computational Intelligence Systems</em>, <em>13</em>(1), 1539-1553, https://doi.org/10.2991/ijcis.d.200924.002.</strong> Full details of methods used to create the dataset and provided within this publication.
DOI: 10.5281/zenodo.4084746
title: Labella_et_al_2020_IJCIS_DATASET

description: This dataset contains the underlying data for the following publication: <strong>Labella, Á., Koasidis, K., Nikas, A., Arsenopoulos, A., & Doukas, H. (2020). APOLLO: A Fuzzy Multi-criteria Group Decision-Making Tool in Support of Climate Policy. <em>International Journal of Computational Intelligence Systems</em>, <em>13</em>(1), 1539-1553, https://doi.org/10.2991/ijcis.d.200924.002.</strong> Full details of methods used to create the dataset and provided within this publication.
DOI: 10.21227/pex3-h590
title: Cloud benchmarking and performance analysis of an HPC application in Amazon EC2

description: Computing has revolutionized the way computational resources are delivered by making them available on-demand and at a low cost. Consistent with the democratization of technology in this era of globalization, it has made computing power and data storage more affordable and accessible than ever before. The existence of hundreds of cloud providers today attests to the massive success of cloud computing. We performed a feasibility study in the category of HPC in the cloud. It consisted of porting a CFD simulation from a Cray XC40 supercomputer (Beskow) to Amazon Cloud using the tool ParallelCluster and running a set of benchmarks to help us understand the results. We find the performance of our target application is 1.17 times better in the cloud, and we show strong scaling up to 2304 processes. This dataset shows the results in both the Amazon Web Services Cloud environment and Beskow for:the OSU benchmarks for all the collective MPI routines (in the form of plots and a pdf file with tables)the NAS benchmarks in shared memory and for up to 8 nodesParaview solution files for the problem we tackleComparison plots between the performance on Beskow and the AWS EC2 clusterStrong scaling results
DOI: 10.21227/cwmv-h463
title: BaselineAvg

description: missing data is replaced by the average of the 10 nearest neighborsprediction is just the averages from 2017
DOI: 10.21949/1520083
title: Maricopa County Regional Work Zone Data Exchange (WZDx) v3.0 Feed Sample
DOI: 10.21227/t0aj-fk67
title: Raw data of positioning experiment and tracking experiment

description: Raw data of positioning experiment and tracking experiment for "A Laser-Guided Solution to Manipulate Mobile Robot Arm Terminals within a Large Workspace"
DOI: 10.6084/m9.figshare.12967901
title: Supplementary material 1

description: This dataset is part of the paper "Spatial and temporal variation of the diet of the flag tetra Hyphessobrycon heterorhabdus (Characiformes: Characidae) in streams of the Eastern Amazon", by Benone et al.<br>
DOI: 10.6084/m9.figshare.12967901.v1
title: Supplementary material 1

description: This dataset is part of the paper "Spatial and temporal variation of the diet of the flag tetra Hyphessobrycon heterorhabdus (Characiformes: Characidae) in streams of the Eastern Amazon", by Benone et al.<br>
DOI: 10.6084/m9.figshare.12827420
title: Training and testing dataset

description: Training and testing dataset for ANN VTKEL model.
DOI: 10.6084/m9.figshare.12827420.v2
title: Training and testing dataset

description: Training and testing dataset for ANN VTKEL model.
DOI: 10.6084/m9.figshare.12827420.v1
title: Training and testing dataset

description: Training and testing dataset for ANN VTKEL model.
DOI: 10.18112/openneuro.ds003325.v1.0.0
title: In vivo T1w MRI of a TDP-43 knock-in mouse model of ALS-FTD
DOI: 10.21227/57th-yy47
title: Raw data of positioning experiment and tracking experiment

description: Raw data of positioning experiment and tracking experiment for "A Laser-Guided Solution to Manipulate Mobile Robot Arm Terminals within a Large Workspace"
DOI: 10.6084/m9.figshare.13090070.v1
title: Provenance of Carboniferous sandstones in the central and southern parts of the Pennine Basin, UK: evidence from detrital zircon ages

description: U-Pb data of detrital zircon.
DOI: 10.6084/m9.figshare.13090070
title: Provenance of Carboniferous sandstones in the central and southern parts of the Pennine Basin, UK: evidence from detrital zircon ages

description: U-Pb data of detrital zircon.
DOI: 10.6084/m9.figshare.13090046
title: Influence of environmental factors on the behaviour of the owl monkey Aotus lemurinus in a Northern-Andes mountain forest (Quindío, Colombia)

description: All data analysed and The R script<br>
DOI: 10.6084/m9.figshare.13090046.v1
title: Influence of environmental factors on the behaviour of the owl monkey Aotus lemurinus in a Northern-Andes mountain forest (Quindío, Colombia)

description: All data analysed and The R script<br>
DOI: 10.6084/m9.figshare.13090025
title: Visaul_Textual_features_data

description: This pickle files consists of features of Visual and textual entities from VTKEL* dataset.
DOI: 10.25345/c5zn2h
title: MassIVE MSV000086283 - HST2 interactors and HST2 phosphorylation
title: From yeast cells expressing Flag-Hst2, soluble (cytosolic) fractions were collected. Cells expressing untagged Hst2 served as control. IP was performed on both experimantal and conrol samples with Anti-Flag agarose beads. Flag-Hst2 and bound proteins were precipitated und purified running a short SDS-gel. LFQ was used to identify binding partners and search for S, T, and Y phosphorylation were performed separately.
DOI: 10.6084/m9.figshare.13056488
title: visual_textual_features_data

description: To generate the training and testing dataset, please download the pickle files of visual-textual features.
DOI: 10.6084/m9.figshare.13056488.v2
title: visual_textual_features_data

description: To generate the training and testing dataset, please download the pickle files of visual-textual features.
DOI: 10.6084/m9.figshare.13056488.v1
title: visual_textual_features_data

description: To generate the training and testing dataset, please download the pickle files of visual-textual features.
DOI: 10.5517/ccdc.csd.cc1pprjn
title: CCDC 1570042: Experimental Crystal Structure Determination

description: Related Article: Dong Ding, Guohao Zhu, Xuefeng Jiang|2018|Angew.Chem.,Int.Ed.|57|9028|doi:10.1002/anie.201804788
description: Related Article: Hao Ouyang, Dan Yuan, Kun Nie, Yong Zhang, Yingming Yao, Dongmei Cui|2018|Inorg.Chem.|57|9028|doi:10.1021/acs.inorgchem.8b01046
DOI: 10.5517/ccdc.csd.cc1pprkp
title: CCDC 1570043: Experimental Crystal Structure Determination

description: Related Article: Dong Ding, Guohao Zhu, Xuefeng Jiang|2018|Angew.Chem.,Int.Ed.|57|9028|doi:10.1002/anie.201804788
description: Related Article: Hao Ouyang, Dan Yuan, Kun Nie, Yong Zhang, Yingming Yao, Dongmei Cui|2018|Inorg.Chem.|57|9028|doi:10.1021/acs.inorgchem.8b01046
DOI: 10.5517/ccdc.csd.cc1pprlq
title: CCDC 1570044: Experimental Crystal Structure Determination

description: Related Article: Dong Ding, Guohao Zhu, Xuefeng Jiang|2018|Angew.Chem.,Int.Ed.|57|9028|doi:10.1002/anie.201804788
description: Related Article: Hao Ouyang, Dan Yuan, Kun Nie, Yong Zhang, Yingming Yao, Dongmei Cui|2018|Inorg.Chem.|57|9028|doi:10.1021/acs.inorgchem.8b01046
DOI: 10.6084/m9.figshare.13087922.v1
title: R0190_20170829a_videos

description: Rat 0190, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13087922
title: R0190_20170829a_videos

description: Rat 0190, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13089026
title: Bicultural Self-Construal and Career Planning: A Study of Taiwan

description: Raw qualitative data of interviews of 18 undergraduates going to enter the career market. Data are analysed through the ground theory approach to find out the relationship between self-construals and career planning of the young adults in Taiwan.
DOI: 10.6084/m9.figshare.13089026.v2
title: Bicultural Self-Construal and Career Planning: A Study of Taiwan

description: Raw qualitative data of interviews of 18 undergraduates going to enter the career market. Data are analysed through the ground theory approach to find out the relationship between self-construals and career planning of the young adults in Taiwan.
DOI: 10.6084/m9.figshare.13089026.v3
title: Bicultural Self-Construal and Career Planning: A Study of Taiwan

description: Raw qualitative data of interviews of 18 undergraduates going to enter the career market. Data are analysed through the ground theory approach to find out the relationship between self-construals and career planning of the young adults in Taiwan.
DOI: 10.5281/zenodo.4088315
title: Input data for the Monin-Obukhov Similarity Theory (MOST) benchmark

description: This is the input data used in Wakebench MOST benchmark.
DOI: 10.5281/zenodo.4088314
title: Input data for the Monin-Obukhov Similarity Theory (MOST) benchmark

description: This is the input data used in Wakebench MOST benchmark.
DOI: 10.5281/zenodo.3985160
title: Hathi: An MCDM-based Approach for the Capacity Planning of Cloud-hosted DBMS — Data Sets

description: These data sets provide supplemental material for the paper "Hathi: An MCDM-based Approach for<br> the Capacity Planning of Cloud-hosted DBMS" submitted to the 13th IEEE/ACM International<br> Conference on Utility and Cloud Computing.
description: The research leading to these results has received funding from the Federal Ministry of Education and Research of Germany under grant agreement 01IS18068 (SORRIR).
DOI: 10.5281/zenodo.3985159
title: Hathi: An MCDM-based Approach for the Capacity Planning of Cloud-hosted DBMS — Data Sets

description: These data sets provide supplemental material for the paper "Hathi: An MCDM-based Approach for<br> the Capacity Planning of Cloud-hosted DBMS" submitted to the 13th IEEE/ACM International<br> Conference on Utility and Cloud Computing.
description: The research leading to these results has received funding from the Federal Ministry of Education and Research of Germany under grant agreement 01IS18068 (SORRIR).
DOI: 10.21227/dx3x-2746
title: Cloud benchmarking and performance analysis of an HPC application in Amazon EC2

description: Computing has revolutionized the way computational resources are delivered by making them available on-demand and at a low cost. Consistent with the democratization of technology in this era of globalization, it has made computing power and data storage more affordable and accessible than ever before. The existence of hundreds of cloud providers today attests to the massive success of cloud computing. We performed a feasibility study in the category of HPC in the cloud. It consisted of porting a CFD simulation from a Cray XC40 supercomputer (Beskow) to Amazon Cloud using the tool ParallelCluster and running a set of benchmarks to help us understand the results. We find the performance of our target application is 1.17 times better in the cloud, and we show strong scaling up to 2304 processes. This dataset shows the results in both the Amazon Web Services Cloud environment and Beskow for:the OSU benchmarks for all the collective MPI routines (in the form of plots and a pdf file with tables)the NAS benchmarks in shared memory and for up to 8 nodesParaview solution files for the problem we tackleComparison plots between the performance on Beskow and the AWS EC2 clusterStrong scaling results
DOI: 10.5281/zenodo.4088324
title: GENEA Challenge 2020 submitted BVH files

description: This Zenodo repository contains all BVH files for the evaluation study submitted by the participants of the GENEA Challenge 2020.
DOI: 10.25345/c5tv1z
title: MassIVE MSV000086284 - Synechococcus Sp. RS9916 Lyase Isomerase MpeV Characterization
title: This project sought to characterize the function and order of modification for Synechococcus lyase-isomerase MpeV.
DOI: 10.5281/zenodo.4088356
title: Usability Evaluation Process for Domain-Specific Languages - Documents and survey data

description: Usability Evaluation Process for Domain-Specific Languages - Documents and survey data
DOI: 10.5281/zenodo.3962211
title: Usability Evaluation Process for Domain-Specific Languages - Documents and survey data

description: Usability Evaluation Process for Domain-Specific Languages - Documents and survey data
DOI: 10.5281/zenodo.4088390
title: Supplementary Material for "Kinetic Analysis of the Hydrolysis of Pentose-1-phosphates through Apparent Nucleoside Phosphorolysis Equilibrium Shifts"

description: This is the external Supplementary Information for our publication "Kinetic Analysis of the Hydrolysis of Pentose-1-phosphates through Apparent Nucleoside Phosphorolysis Equilibrium Shifts". The .pdf file contains the Supplementary Information: author contributions, experimental procedures, derivation of equations and supplementary items. The .zip file contains the raw data and metadata for all items (supplementary and main text) and the calculations. Like most publications, this one builds on previous work. The Python code used for spectral unmixing is available on this platform (10.5281/zenodo.3243376) and has been described in our previous publications (10.3390/mps2030060, 10.5281/zenodo.3333469, 10.1002/cbic.202000204, 10.5281/zenodo.3723806 ). Further applications of this method can be found in our recent article in <em>Adv. Synth. Catal.</em> (10.1002/adsc.201901230) and its supporting material (10.5281/zenodo.3568858), as well as a preprint (10.26434/chemrxiv.12993416.v1) and its supporting material (10.5281/zenodo.4043929).