cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25345/c5ks60
title: MassIVE MSV000083686 - Essential Role for CAND2 in Normal Cardiac Electrical and Mechanical Function
title: Jameson HS, Hucker WJ, Hanley A, Barraza M, Hall AW, Udeshi N, Svinkina T, Herndon CN, Schenone M, Retournard A, Ye J, Clauss S, Leyton-Mange JS, Parsons VA, Mina J, Bapat A, Tucker NR, Mills RW, Carr SA, Milan DJ, Ellinor PT. 2019. The genetic basis of atrial fibrillation (AF), the most common heart rhythm disturbance, has been well established. The underlying molecular mechanisms by which genetic variants contribute to the progression of AF however, remains unclear. Here we report that CAND2 , a muscle- and cardiac-specific protein known to inhibit the poly-ubiquitination of myogenin in skeletal muscle through disruption of the Skp1-cullin-F-box (SCF) protein complex, and identified as a susceptibility locus for AF, supports proper function of the cardiac ubiquitin proteasome system. We show loss of CAND2 leads to increased ubiquitination of sarcomeric substrates in vitro, with decreased expression of the corresponding protein, increased susceptibility to AF, and the development of dilated cardiomyopathy (DCM) in vivo. Together, these results identify a novel role for CAND2 in cardiovascular sarcomere stability and provide a detailed mechanistic understanding of how this AF risk locus contributes to the pathogenesis of cardiovascular diseases.
DOI: 10.18739/a2gq6r21h
title: Ablation stake data from Chamberlin Glacier, Arctic National Wildlife Refuge, Alaska, 2016-2017
DOI: 10.21227/8qth-xp91
title: NSGA-III

description: This paper presents a fast and open source extension based on the NSGA-II code stored in the repository of the Kanpur Genetic Algorithms Laboratory (KanGAL) and the adjustment of the selection operator. It slightly modifies existing well-established genetic algorithms for many-objective optimization called the NSGA-III, the adaptive NSGA-III (A-NSGA-III), and the efficient adaptive NSGA-III, (A$^2$-NSGA-III). The proposed method is tested on a range of benchmark problems and showcases notable performance improvement.NSGA-II and NSGA-III are frequently employed as a reference for a comparative evaluation of new evolutionary algorithms.However, the latter is proprietary and many researchers have been forced to implement it from scratch with lower performance. Our NSGA-III variations consider static and dynamic reference points where individuals in the first front are contemplated to obtain extreme points that are neither negatives nor repeated. Those algorithms resolve binary and real, constrained and non-constrained Multi-Objective and Many-objective problems. Additionally, when efficient adaptive NSGA-III is employed to solve the Car-Side Impact problem and the Water problem, we find not only visually well-distributed solutions, but also in terms of the Hyper-volume metric compared to the A-NSGA-III and the NSGA-III.
DOI: 10.21227/cybx-en36
title: NSGA-III

description: This paper presents a fast and open source extension based on the NSGA-II code stored in the repository of the Kanpur Genetic Algorithms Laboratory (KanGAL) and the adjustment of the selection operator. It slightly modifies existing well-established genetic algorithms for many-objective optimization called the NSGA-III, the adaptive NSGA-III (A-NSGA-III), and the efficient adaptive NSGA-III, (A$^2$-NSGA-III). The proposed method is tested on a range of benchmark problems and showcases notable performance improvement.NSGA-II and NSGA-III are frequently employed as a reference for a comparative evaluation of new evolutionary algorithms.However, the latter is proprietary and many researchers have been forced to implement it from scratch with lower performance. Our NSGA-III variations consider static and dynamic reference points where individuals in the first front are contemplated to obtain extreme points that are neither negatives nor repeated. Those algorithms resolve binary and real, constrained and non-constrained Multi-Objective and Many-objective problems. Additionally, when efficient adaptive NSGA-III is employed to solve the Car-Side Impact problem and the Water problem, we find not only visually well-distributed solutions, but also in terms of the Hyper-volume metric compared to the A-NSGA-III and the NSGA-III.
DOI: 10.25345/c5g04c
title: MassIVE MSV000083687 - Bone collagen from Pacific salmonid species contains differences allowing for peptide mass fingerprinting for easy identification
title: MS/MS spectra of archaeological (Oncorhynchus) and modern (Salmo salar) bone collagen.
DOI: 10.5281/zenodo.2641140
title: afshin-aero/360dataset: First release

description: A Taxonomy and Dataset for 360-degree videos
DOI: 10.5281/zenodo.2641141
title: afshin-aero/360dataset: First release

description: A Taxonomy and Dataset for 360-degree videos
DOI: 10.7910/dvn/2dcd6n
title: Replication Data for "Can Transitional Justice Improve the Quality of Representation in New Democracies?"

description: Replication Data for "Can Transitional Justice Improve the Quality of Representation in New Democracies?" We include the panel dataset of transitional justice (file: tj_data_panel.csv), which codes positive and negative lustration events in post-transitional and post-conflict regimes. We also include the party-level data for replication (file: data.csv), which includes information on the parties of the countries of interest that were reported by the DALP project (see https://sites.duke.edu/democracylinkage/), the cross-sectional measure of severity of transitional justice, and other covariates of interest.
DOI: 10.5517/ccdc.csd.cc203v00
title: CCDC 1850731: Experimental Crystal Structure Determination

description: Related Article: Jinzhen Lu, Ruchika Ojha, Alan M. Bond, Lisandra L. Martin|2019|Cryst.Growth Des.|19|2712|doi:10.1021/acs.cgd.8b01841
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.cc20mnlx
title: CCDC 1865939: Experimental Crystal Structure Determination

description: Related Article: Arnab Ghosh, Rajeev Hegde, Vitthal B. Makane, Balasubramanian Sridhar, Haridas B. Rode, Siddappa A. Patil, Ramesh B. Dateer|2019|Org.Biomol.Chem.|17|4440|doi:10.1039/C9OB00527G
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.cc20qj1b
title: CCDC 1868681: Experimental Crystal Structure Determination

description: Related Article: Igor Huskić, Novendra Novendra, Dae-Woon Lim, Filip Topić, Hatem M. Titi, Igor V. Pekov, Sergey V. Krivovichev, Alexandra Navrotsky, Hiroshi Kitagawa, Tomislav Friščić|2019|Chemical Science|10|4923|doi:10.1039/C8SC05088K
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.2640918
title: Frictionless Tabular Data Package for GC-MS Rose scent profile data for Data published in Nature genetics, June, 2018 & Science, July 2015

description: This dataset, in the form of a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holds the measurements of 35 known metabolites(all annotated with resolvable CHEBI identifiers and InChi strings), measured by gas chromatography mass-spectrometry (GC-MS) in one Rose cultivars (all annotated with resolvable NCBITaxonomy Identifiers) and one organism part (annotated with resolvable Plant Ontology identifiers). The quantitation types are annotated with resolvable STATO terms. The measurements over these metabolites, which were made in 2 distinct experiments, were extracted from: a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018 a supplementary material table available as a pdf from 'Biosynthesis of monoterpene scent compounds in roses' by Magnard et al, Science 03 Jul 2015 identified by the following doi: https://doi.org/10.1126/science.aab0696. This dataset is used to demonstrate how to make data Findable, Accessible, Discoverable and Interoperable (FAIR)and how Frictionless Tabular Data Package representations can be easily mobilised for reanalysis and data science.It is associated to the following project: https://github.com/proccaserra/rose2018ng-notebook with all the necessaryinformation, executable code and tutorials in the form of Jupyter notebooks.
description: {"references": ["https://doi.org/10.1038/s41588-018-0110-3", "https://doi.org/10.1126/science.aab0696"]}
DOI: 10.5281/zenodo.2640919
title: Frictionless Tabular Data Package for GC-MS Rose scent profile data for Data published in Nature genetics, June, 2018 & Science, July 2015

description: This dataset, in the form of a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holds the measurements of 35 known metabolites(all annotated with resolvable CHEBI identifiers and InChi strings), measured by gas chromatography mass-spectrometry (GC-MS) in one Rose cultivars (all annotated with resolvable NCBITaxonomy Identifiers) and one organism part (annotated with resolvable Plant Ontology identifiers). The quantitation types are annotated with resolvable STATO terms. The measurements over these metabolites, which were made in 2 distinct experiments, were extracted from: a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018 a supplementary material table available as a pdf from 'Biosynthesis of monoterpene scent compounds in roses' by Magnard et al, Science 03 Jul 2015 identified by the following doi: https://doi.org/10.1126/science.aab0696. This dataset is used to demonstrate how to make data Findable, Accessible, Discoverable and Interoperable (FAIR)and how Frictionless Tabular Data Package representations can be easily mobilised for reanalysis and data science.It is associated to the following project: https://github.com/proccaserra/rose2018ng-notebook with all the necessaryinformation, executable code and tutorials in the form of Jupyter notebooks.
description: {"references": ["https://doi.org/10.1038/s41588-018-0110-3", "https://doi.org/10.1126/science.aab0696"]}
DOI: 10.5281/zenodo.2641310
title: Alaska bearded and spotted seal example dataset analysis

description: Demonstration of the Whole Tale "tale" BagIt-RO export format.  This Tale demonstrates end-to-end Whole Tale capabilities including registering and accessing externally published data, customization of the computational environment via repo2docker, analysis, visualization, and publishing. This is based on tutorial material developed by Josh London and Devin Johnson in support of a training     course at the NOAA Fisheries Protected Species Assessment Workshop in La Jolla, California, USA. See https://jmlondon    .github.io/crwexampleakbs/analysis.html for more details.

This example uses the following dataset:

Michael Cameron, Josh London, Kathy Frost, Alex Whiting, and Peter Boveng. Satellite Telemetry Dataset (Raw): Juvenile Bearded and Spotted Seals, 2004-2006, Kotzebue, Alaska. Research Workspace. 10.24431/rw1k118
DOI: 10.5281/zenodo.2641311
title: Alaska bearded and spotted seal example dataset analysis

description: Demonstration of the Whole Tale "tale" BagIt-RO export format.  This Tale demonstrates end-to-end Whole Tale capabilities including registering and accessing externally published data, customization of the computational environment via repo2docker, analysis, visualization, and publishing. This is based on tutorial material developed by Josh London and Devin Johnson in support of a training     course at the NOAA Fisheries Protected Species Assessment Workshop in La Jolla, California, USA. See https://jmlondon    .github.io/crwexampleakbs/analysis.html for more details.

This example uses the following dataset:

Michael Cameron, Josh London, Kathy Frost, Alex Whiting, and Peter Boveng. Satellite Telemetry Dataset (Raw): Juvenile Bearded and Spotted Seals, 2004-2006, Kotzebue, Alaska. Research Workspace. 10.24431/rw1k118
DOI: 10.5517/ccdc.csd.cc20qj2c
title: CCDC 1868682: Experimental Crystal Structure Determination

description: Related Article: Igor Huskić, Novendra Novendra, Dae-Woon Lim, Filip Topić, Hatem M. Titi, Igor V. Pekov, Sergey V. Krivovichev, Alexandra Navrotsky, Hiroshi Kitagawa, Tomislav Friščić|2019|Chemical Science|10|4923|doi:10.1039/C8SC05088K
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.cc20qj3d
title: CCDC 1868683: Experimental Crystal Structure Determination

description: Related Article: Igor Huskić, Novendra Novendra, Dae-Woon Lim, Filip Topić, Hatem M. Titi, Igor V. Pekov, Sergey V. Krivovichev, Alexandra Navrotsky, Hiroshi Kitagawa, Tomislav Friščić|2019|Chemical Science|10|4923|doi:10.1039/C8SC05088K
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.cc20qj4f
title: CCDC 1868684: Experimental Crystal Structure Determination

description: Related Article: Igor Huskić, Novendra Novendra, Dae-Woon Lim, Filip Topić, Hatem M. Titi, Igor V. Pekov, Sergey V. Krivovichev, Alexandra Navrotsky, Hiroshi Kitagawa, Tomislav Friščić|2019|Chemical Science|10|4923|doi:10.1039/C8SC05088K
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.cc20qj5g
title: CCDC 1868685: Experimental Crystal Structure Determination

description: Related Article: Igor Huskić, Novendra Novendra, Dae-Woon Lim, Filip Topić, Hatem M. Titi, Igor V. Pekov, Sergey V. Krivovichev, Alexandra Navrotsky, Hiroshi Kitagawa, Tomislav Friščić|2019|Chemical Science|10|4923|doi:10.1039/C8SC05088K
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.cc20whcs
title: CCDC 1873465: Experimental Crystal Structure Determination

description: Related Article: V. Ganga Reddy, T. Srinivasa Reddy, Steven H. Privér, Yutao Bai, Shweta Mishra, Donald Wlodkowic, Nedaossadat Mirzadeh, Suresh Bhargava|2019|Inorg.Chem.|58|5988|doi:10.1021/acs.inorgchem.9b00281
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: 10.18739/a2bz6178m
title: Meteorological data from Chamberlin Glacier, Arctic National Wildlife Refuge, Alaska, 2016-2017
DOI: 10.5281/zenodo.2640872
title: Frictionless Tabular data package for GC-MS data from Rose Genome article published in Nature genetics, June, 2018

description: This dataset, in the form of a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holds the measurements of 61 known metabolites (all annotated with resolvable CHEBI identifiers and InChi), measured by gas chromatography mass-spectrometry (GC-MS) in 6 different Rose cultivars (all annotated with resolvable NCBITaxId) and 3 organism parts (all annotated with resolvable Plant Ontology identifiers). The data was extracted from a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018. This dataset is used to demonstrate how to make data Findeable, Accessible, Discoverable and Interoperable(FAIR) and how Tabular Data Package representations can be easily mobilized for re-analysis and data science. It is associated to the following project available from github at: https://github.com/proccaserra/rose2018ng-notebook with all necessary information and Jupyter notebooks.
description: {"references": ["https://doi.org/10.1038/s41588-018-0110-3"]}
DOI: 10.5281/zenodo.2640873
title: Frictionless Tabular data package for GC-MS data from Rose Genome article published in Nature genetics, June, 2018

description: This dataset, in the form of a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holds the measurements of 61 known metabolites (all annotated with resolvable CHEBI identifiers and InChi), measured by gas chromatography mass-spectrometry (GC-MS) in 6 different Rose cultivars (all annotated with resolvable NCBITaxId) and 3 organism parts (all annotated with resolvable Plant Ontology identifiers). The data was extracted from a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018. This dataset is used to demonstrate how to make data Findeable, Accessible, Discoverable and Interoperable(FAIR) and how Tabular Data Package representations can be easily mobilized for re-analysis and data science. It is associated to the following project available from github at: https://github.com/proccaserra/rose2018ng-notebook with all necessary information and Jupyter notebooks.
description: {"references": ["https://doi.org/10.1038/s41588-018-0110-3"]}
DOI: 10.18739/a27659f58
title: Carnivore Creek discharge and suspended sediment concentration, Alaska, 2015-2018
DOI: 10.5281/zenodo.2641157
title: AEROARMS Control-based local optimization methods for planning

description: This package allows to perform a Dynamic (Re-)Planning within the Set-Based Task-Priority Inverse-Kinematics (SBTP-IK) framework. It is ROS-based and it is provided to work with the Kinova Jaco2 7DOFs but it is can be easily adapted to another robot system changing the files describing the robot kinematics such as Denvait Hartenberg parameters.

The proposed approach is based on merging control-based local optimization methods inside the planning algorithms. For the experiments, a fixed-based 7 DOFs manipulator has been considered in two different scenarios. In the first case, a static environment has been considered. In the second one, the user places an obstacle on the manipulator’s path in real-time. Thus, a re-planning results necessary to manage this change in the environment.
DOI: 10.5281/zenodo.2641158
title: AEROARMS Control-based local optimization methods for planning

description: This package allows to perform a Dynamic (Re-)Planning within the Set-Based Task-Priority Inverse-Kinematics (SBTP-IK) framework. It is ROS-based and it is provided to work with the Kinova Jaco2 7DOFs but it is can be easily adapted to another robot system changing the files describing the robot kinematics such as Denvait Hartenberg parameters.

The proposed approach is based on merging control-based local optimization methods inside the planning algorithms. For the experiments, a fixed-based 7 DOFs manipulator has been considered in two different scenarios. In the first case, a static environment has been considered. In the second one, the user places an obstacle on the manipulator’s path in real-time. Thus, a re-planning results necessary to manage this change in the environment.
DOI: 10.18739/a23j3912w
title: CTD casts (conductivity, temperature, depth) in Lake Peters, Arctic National Wildlife Refuge, Alaska, 2015
DOI: 10.5281/zenodo.2641291
title: Polyoxygenated Cyclohexene Derivatives from the Roots of Monanthotaxis trichocarpa

description: Original NMR data and NMReDATA files of the 4 new compounds published in the article entitled Polyoxygenated Cyclohexene Derivatives from the Roots of <em>Monanthotaxis trichocarpa in J. Nat Prod. </em><strong>2019</strong>
DOI: 10.14469/hpc/5496
title: Co(II)-Tetraphenylporphyrin, doublet, S4 symmetry, flat Ph, optimised as saddle=4, 7-3294.488667, DG = 61.

description: Gaussian Calculation
DOI: 10.5281/zenodo.2640900
title: VOT19 Challenge RGBD

description: Dataset for the VOT19 RGBD Challenge.
DOI: 10.6092/unibo/amsacta/6151
title: CATCH-EyoU. Intervention in Schools. Methodology Evaluation and Main Results. EXTRACT Portugal

description: WP9 of the CATCH-EyoU project proposes a school-based socially innovative intervention that involves students and teachers. It examines how young people engage in social issues having local and European relevance, combining a participatory approach, community analysis, and structured dialogue with public authorities. 
The dataset contains the national report with the main results of the implementation of this intervention in the Portuguese contexts. The transcriptions and analyses of qualitative data (focus groups, interviews) contained in the report serves as the underlying data of the following scientific paper accepted for publication in the journal “Psicologia di Comunità” (https://www.francoangeli.it/riviste/Sommario.aspx?IDRivista=139&lingua=it):
Joana Cruz, Carla Malafaia, Filipe Piedade, José Eduardo Silva, Isabel Menezes (2019). Promoting European active citizenship: A participatory intervention towards the politicisation of youth social concerns. Psicologia di comunità. 

The data has been collected from an upper secondary school in Portugal, involved in the WP9 EU citizenship education intervention.
This data is made available for open access in compliance with H2020 Program regulation, following the guidelines stipulated by the Data Management Plan adopted by the CATCH-EyoU research project.
DOI: 10.18739/a2zs2kc8c
title: Geochemical and stable isotope composition data from precipitation, runoff, snow and ice collected in Lake Peters watershed, Arctic Wildlife Refuge, Alaska, 2015-2018
DOI: 10.18739/a2v11vk4j
title: Meteorological data from the Lake Peters watershed, Arctic National Wildlife Refuge, Alaska, 2015-2018