cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7008298
title: U.S. cities increasingly integrate justice into climate planning and create policy tools for climate justice (Diezmartínez & Short Gianotti, 2022) - Data and code

description: This repository contains datasets and coding corresponding to the journal article titled "U.S. cities increasingly integrate justice into climate planning and create policy tools for climate justice". We include: DataRegressionAnalysis.csv CSV file with data used for regression analysis. This file can be used directly to run R code provided in this repository. QualitativeCodingResults.nvp NVivo project with all results for the qualitative coding of urban climate action plans. This file also contains all climate action plans analyzed in this research. QualitativeCodingResults_Summary.xlsx Excel file with a results summary for the qualitative coding of urban climate action plans. RegressionAnalysis.Rmd Rmd file with R code used for regression analysis. RegressionAnalysis_KnitOutput.html Knit output from R code with regression analysis results, html format. RegressionAnalysis_KnitOutput.pdf Knit output from R code with regression analysis results, PDF format.
DOI: 10.5439/1025152
title: ARM: AOS: condensation particle counter

description: AOS: condensation particle counter
DOI: 10.5439/1025259
title: ARM: Aerosol Observing System (AOS): aerosol data, 1-min, mentor-QC applied

description: Aerosol Observing System (AOS): aerosol data, 1-min, mentor-QC applied
DOI: 10.5439/1025303
title: ARM: Tandem Differential Mobility Analyzer: size-resolved concentrations

description: Tandem Differential Mobility Analyzer: size-resolved concentrations
DOI: 10.5439/1150275
title: ARM: Tandem Differential Mobility Analyzer Aerosol Particle Sizer

description: Tandem Differential Mobility Analyzer Aerosol Particle Sizer
DOI: 10.5439/1511037
title: SGP Merged Aerosol Size Distribution (CPC+SMPS+APS)

description: Five years (2009-2013) of data from three instruments at the SGP site were merged in order to create a new aerosol size distribution dataset. Data from the scanning mobility particle sizer (SMPS), part of the TDMA system, were combined with size distribution data from the aerodynamic particle sizer (APS). The merged size distribution from those two instruments spanned the diameter (mobility) size range between ~12 nm and ~14 μm with 215 bins (Collins 2010). Total aerosol number concentrations from a TSI 3010 condensation particle counter (CPC) were then used to adjust and constrain the SMPS+APS size distributions and to extend the size distribution down to ~7 nm. Collins, D: Tandem Differential Mobility Analyzer/Aerodynamic Particular Sizer (APS) Handbook. DOE ARM Climate Research Facility. DOE/SC-ARM-TR-090, 2010.
DOI: 10.5284/1016098
title: Stepping stones to the Neolithic? Islands, maritime connectivity and the 'western seaways' of Britain, 5000-3500 BC
DOI: 10.6084/m9.figshare.15797838.v1
title: DOSE AST supplementary file data

description: Full dataset of included studies, details about the interventions in those studies, details about the outcomes and results, and the data used in the Cochrane Review analyses, including differences between the included study trial reporting and review analysis and assumptions made in the review.
DOI: 10.6084/m9.figshare.15752415
title: DOSE-AST ROB2 consensus data file.xlsm

description: Risk of bias 2 consensus judgments and overviews for all results included in the Cochrane systematic review (domains and signalling questions)
DOI: 10.17632/vftc7kg6ty.2
title: Test Instances for the Prize-Collecting Generalized MST Problem

description: Test instances for the Prize-Collecting Generalized Minimum Spanning Tree Problem. The instances have the form mXXXXn, where m is the number of clusters, n is the number of nodes and XXXXn is the name of the problem in TSPLIB (REINELT, 1991). We modified the instances for the GMST problem, provided by the authors Paolo Toth and Albert Einstein F. Muritiba. We added a value of prize, pseudo-randomly generated in the range [0, 10], for every node in the previous instances. We also provide the best known solution of each instance for the PC-GMST problem in a separate file. Reading a GTP file: --------------------- 1. First data is the number of nodes, n. 2. The 2n other lines give the x and y coordinates of each node. 3. A data gives the number of clusters, m. 4. The following is reapeated m times: - the number of nodes in the first cluster, m1. - the node number of the m1 nodes. - the number of nodes in the first cluster, m2. - the node number of the m2 nodes. - .... 5. m numbers of nodes (possibly the centers of the clusters). 6. A validating number set to -999. 7. n prize values in the range [0, 10], one for each node. 8. A validating number set to -999. Euclidean distance (REINELT, 1991): --------------------- Let x[i] and y[i] be the coordinates of node i. The distance between two points i and j must be computed as follows: xd = x[i] - x[j]; yd = y[i] - y[j]; dij = (int) ( sqrt( xd*xd + yd*yd ) + 0.5 ); where sqrt is the C square root function. Reference: ----------- REINELT, G. TSPLIB-- A Traveling Salesman Problem Library. ORSA Journal on Computing, v. 3, n. 4, p. 376, 1991.
DOI: 10.21415/t5b88z
title: SamtaleBank Danish Sam2 Corpus
DOI: 10.5255/ukda-sn-6614-2
title: Understanding Society: Wave 1, 2009-2010
DOI: 10.5281/zenodo.3360259
title: Comparison of artificial hands developed in years 1980-2019

description: File contains comparison of artificial hands developed in years 1980-03.2019. That was the basis for the review article "An Artificial Hand - Current State of Knowledge in Designing and Forecasting Changes" and includes following features: - article title in which device is described, - hand name, - publication year, - overall hand design, - thumb properties, - number of degrees of motion - number of all moving joints and its axis with not considered transmission and actuation system (DOF includes that) - type of actuator, - number of actuators, - transmission type, - available forces/torques, - operating speed, - sensors, - additional information. All the hands were searched in google schollar with phrases "artificial hand" and "robotic hand". There are included these articles/devices which were available with University access.
DOI: 10.5281/zenodo.6812547
title: ACIA500: a 500 m annual cropping intensity dataset for monsoon Asia based on MODIS data

description: This dataset provides 500m-grid crop intensity map of monsoon Asia (some countries) from 2001 to 2021. *** Updated crop intensity map for 2021 *** The data file is in “.tif" format *** Temporal Resolution: Yearly *** Pixel size: 500 m *** Projection information: EPSG: 4326 The map boundary employed in this database does not imply the expression of any opinion whatsoever on the part of us concerning the legal status of any country, territory, city or area or its authorities, or concerning the delimitation of its frontiers or boundaries.
DOI: 10.5281/zenodo.6494267
title: Description and quality metadata files for four spatial landmark datasets

description: The files define the description and quality metadata of the spatial landmark datasets from camptocamp.org defined here. Two ISO standards ISO 19115-1:2014 and ISO 19157:2013, recommanded by the INSPIRE Directive for the dissemination of spatial data and the reporting of data quality are used.
DOI: 10.5281/zenodo.6494268
title: Description and quality metadata files for four spatial landmark datasets

description: The files define the description and quality metadata of the spatial landmark datasets from camptocamp.org defined here. Two ISO standards ISO 19115-1:2014 and ISO 19157:2013, recommanded by the INSPIRE Directive for the dissemination of spatial data and the reporting of data quality are used.
DOI: 10.5281/zenodo.6501691
title: Description and quality metadata files for four spatial landmark datasets

description: The files define the description and quality metadata of the spatial landmark datasets from camptocamp.org defined here. Two ISO standards ISO 19115-1:2014 and ISO 19157:2013, recommanded by the INSPIRE Directive for the dissemination of spatial data and the reporting of data quality are used.
DOI: 10.5281/zenodo.6636472
title: Description and quality metadata files for four spatial landmark datasets

description: The files define the description and quality metadata of the spatial landmark datasets from camptocamp.org defined here. Two ISO standards ISO 19115-1:2014 and ISO 19157:2013, recommanded by the INSPIRE Directive for the dissemination of spatial data and the reporting of data quality are used.
DOI: 10.17632/jtzpkhw3mk.1
title: Mental Health in Indian metro cities: 2020

description: The data used in the study was collected from 1,275 persons aged 21-60 years randomly selected  from the list of mobile phone users in the six Class 1 metropolitan cities of India—viz. Bengaluru, Chennai, Delhi, Kolkata, Mumbai and Hyderabad. Depression Anxiety Stress Scale (DASS) version 21 was administered to the study participants apart from collecting information on socio-demographic and economic characteristics.
The survey was undertaken in August-September 2020 during the first wave of COVID in India.
DOI: 10.17632/rw4zjr4dzj.1
title: Platelet-Rich Plasma and  Uterine Wound Healing 

description: study was performed to investigate the effect of intramyometrial injection of autologous platelet rich plasma on uterine wound healing among women undergoing prelabor primary cesarean section (CS).
DOI: 10.17632/32zydvmzjd.1
title: Douglas-fir and Norway spruce tree-ring data from three sites in Slovenia

description: Data consists of two files:
1. TRW-chronologies-raw-std-res.xlsx - contains tree-ring widths in raw and standardised form
2. All-sites-dug-spru-pointer years.xlsx
In files DF stands for Douglas fir and NS for Norway spruce
DOI: 10.17632/2kk4c3ctzg.1
title: A unique skin phenotype resulting from heterozygous deletion of six keratin genes 

description: Pachyonychia congenita (PC) is a rare autosomal dominant disorder featuring palmoplantar keratoderma, nail dystrophy, oral leukokeratosis, follicular cysts and natal teeth. PC is caused by mutations in KRT6A, KRT6B, KRT6C, KRT16 or KRT17 genes. Here we aimed to identify the genetic basis of an atypical PC case. We conducted whole exome sequencing (WES) in affected individual and his healthy parents. This data set includes the WES analysis results.
DOI: 10.17632/rwdbymndmj.1
title: cAMP-Protein Kinase A and Stress-Activated MAP signaling mediate transcriptional control of autophagy in fission yeast. Source images for main and supplementary figures.

description: Source images for main article and supplementary figures of the article entitled "cAMP-Protein Kinase A and Stress-Activated MAP signaling mediate transcriptional control of autophagy in fission yeast" by Armando Jesús Pérez-Díaz, Beatriz Vázquez-Marín, Jero Vicente-Soler, Francisco Prieto-Ruiz, Teresa Soto, Alejandro Franco, José Cansado* and Marisa Madrid*
DOI: 10.17632/9krjdj44p5.1
title: The protease DDI2 regulates NRF1 activation in response to Cadmium toxicity 

description: Raw immunoblot data
DOI: 10.17632/cm8pxdt5pm.1
title: Identification of Pathogenic Immune Cell Subsets in Checkpoint Inhibitor-induced Myocarditis

description: Immune checkpoint inhibitors (ICIs) are monoclonal antibodies used widely to activate the immune system against tumor cells. Despite their therapeutic benefits, ICIs are known to cause immune-related adverse events (irAE) such as myocarditis, a rare but serious side effect with up to 50% mortality. To identify pathogenic immune subset(s) responsible for ICI myocarditis and other irAE, we performed single cell mass cytometry (CyTOF) on peripheral blood mononuclear cells from patients and controls with irAE including four patients with ICI myocarditis.
DOI: 10.17632/cm8pxdt5pm.2
title: Identification of Pathogenic Immune Cell Subsets in Checkpoint Inhibitor-induced Myocarditis

description: Immune checkpoint inhibitors (ICIs) are monoclonal antibodies used widely to activate the immune system against tumor cells. Despite their therapeutic benefits, ICIs are known to cause immune-related adverse events (irAE) such as myocarditis, a rare but serious side effect with up to 50% mortality. To identify pathogenic immune subset(s) responsible for ICI myocarditis and other irAE, we performed single cell mass cytometry (CyTOF) on peripheral blood mononuclear cells from patients and controls with irAE including four patients with ICI myocarditis.
DOI: 10.17632/htx484fv8p.1
title: Study by N. Bouftas et al., Cyclin B3 implements timely vertebrate  oocyte arrest for fertilization, original data

description: Original scans of western blots used to mount the figures in Bouftas et al, Cyclin B3 implements timely vertebrate  oocyte arrest for fertilization
DOI: 10.5281/zenodo.6483784
title: Matching results between landmark in different sources and landmark in a referenced dataset (BDTOPO)

description: The four datasets represent the results of a two sequentials processus. The first processus consists on a automatic matching between landmark in different sources and landmark in a referenced dataset (french national topographic data: BDTOPO). Then the links 1:1 are manually validated by experts in the second processus. The four different datasets and the BDTOPO dataset are archived here. The data matching algorithm is described in this paper. Each file represents the result matching for features belonging to a data source with: - the name of file depending on the data source - the column "id_source" corresponds to the identifier of the landmark in data source - the column "types_of_matching_results" describes the type of matching result: « 1:0 »: means that a landmark from a data source (e.g. Camptocamp) has no homologue landmark in BDTOPO « 1:1 validated »: means that a homologous feature exist in BDTOPO and the link was validated « 1:1 non validated »: means that the matching link was not validated « without candidates »: represents the non-matched landmarks because there are no candidates in BDTOPO or because the landmark in data source is far away from its homologous in BDTOPO « uncertain »: uncertainty cases are complex cases where any decision is taken by the data matching algorithm - the column "id_candidat" corresponds to the identifier of the landmark in BDTOPO if and only if there is a validated matching link - the column "samal" corresponds to the Samal distance The matching results are obtained using an ontology application named OOR. These specific results are obtained using the version of OOR V1.0.1 which is an improved version and contains new concepts compared to the first release 1.0.0. The new version of OOR (i.e. 1.0.1) will be released by the end of May 31 2022. The new link will be added here. This archive is released for transparency and reproducibility purposes.
DOI: 10.5281/zenodo.6483785
title: Matching results between landmark in different sources and landmark in a referenced dataset (BDTOPO)

description: The four datasets represent the results of a two sequentials processus. The first processus consists on a automatic matching between landmark in different sources and landmark in a referenced dataset (french national topographic data: BDTOPO). Then the links 1:1 are manually validated by experts in the second processus. The four different datasets and the BDTOPO dataset are archived here. The data matching algorithm is described in this paper. Each file represents the result matching for features belonging to a data source with: - the name of file depends on the data source - id_source corresponds to the identify of the landmark in data source - types_of_matching_results describes the type of result matching : « 1:0 » means that a landmark from a data source (e.g. Camptocamp) has no homologue landmark in BDTOPO « 1:1 validated » means that a homologous feature exist in BDTOPO and the link was validated « 1:1 non validated » means that the matching link was not validated « without candidates » represents the non-matched landmarks because there are no candidates in BDTOPO or because the landmark in data source is far away from its homologous in BDTOPO « uncertain » : uncertainty cases are complex cases where any decision is taken by the data matching algorithm - id_bdtopo corresponds to the identify of the landmark in BDTOPO if and only if there is a validated matching link <br>
DOI: 10.5281/zenodo.6491156
title: Matching results between landmark in different sources and landmark in a referenced dataset (BDTOPO)

description: The four datasets represent the results of a two sequentials processus. The first processus consists on a automatic matching between landmark in different sources and landmark in a referenced dataset (french national topographic data: BDTOPO). Then the links 1:1 are manually validated by experts in the second processus. The four different datasets and the BDTOPO dataset are archived here. The data matching algorithm is described in this paper. Each file represents the result matching for features belonging to a data source with: - the name of file depending on the data source - the column "id_source" corresponds to the identifier of the landmark in data source - the column "types_of_matching_results" describes the type of matching result: « 1:0 »: means that a landmark from a data source (e.g. Camptocamp) has no homologue landmark in BDTOPO « 1:1 validated »: means that a homologous feature exist in BDTOPO and the link was validated « 1:1 non validated »: means that the matching link was not validated « without candidates »: represents the non-matched landmarks because there are no candidates in BDTOPO or because the landmark in data source is far away from its homologous in BDTOPO « uncertain »: uncertainty cases are complex cases where any decision is taken by the data matching algorithm - the column "id_candidat" corresponds to the identifier of the landmark in BDTOPO if and only if there is a validated matching link - the column "samal" corresponds to the Samal distance The matching results are obtained using an ontology application named OOR. These specific results are obtained using the version of OOR V1.0.1 which is an improved version and contains new concepts compared to the first release 1.0.0. The new version of OOR (i.e. 1.0.1) will be released by the end of May 31 2022. The new link will be added here. This archive is released for transparency and reproducibility purposes.
DOI: 10.5281/zenodo.6518363
title: Matching results between landmark in different sources and landmark in a referenced dataset (BDTOPO)

description: The four datasets represent the results of a two sequentials processus. The first processus consists on a automatic matching between landmark in different sources and landmark in a referenced dataset (french national topographic data: BDTOPO). Then the links 1:1 are manually validated by experts in the second processus. The four different datasets and the BDTOPO dataset are archived here. The data matching algorithm is described in this paper. Each file represents the result matching for features belonging to a data source with: - the name of file depending on the data source - the column "id_source" corresponds to the identifier of the landmark in data source - the column "types_of_matching_results" describes the type of matching result: « 1:0 »: means that a landmark from a data source (e.g. Camptocamp) has no homologue landmark in BDTOPO « 1:1 validated »: means that a homologous feature exist in BDTOPO and the link was validated « 1:1 non validated »: means that the matching link was not validated « without candidates »: represents the non-matched landmarks because there are no candidates in BDTOPO or because the landmark in data source is far away from its homologous in BDTOPO « uncertain »: uncertainty cases are complex cases where any decision is taken by the data matching algorithm - the column "id_candidat" corresponds to the identifier of the landmark in BDTOPO if and only if there is a validated matching link - the column "samal" corresponds to the Samal distance The matching results are obtained using an ontology application named OOR. These specific results are obtained using the version of OOR V1.0.1 which is an improved version and contains new concepts compared to the first release 1.0.0. The new version of OOR (i.e. 1.0.1) will be released by the end of May 31 2022. The new link will be added here. This archive is released for transparency and reproducibility purposes.
DOI: 10.5281/zenodo.6481338
title: Alignment between type of landmark in different sources and the concept in the spatial reference objects ontology

description: The five datasets represent a manually alignment between the landmark type of five different datasets archived here and a common vocabulary extracted from an application ontology defined for mountain rescue purposes, named Ontology of landmarks (OOR). Each file represents the alignment for features belonging to a data source with the same OOR ontology. For example, the type «bivouac» from camptocamp.org source is aligned with the uri http://purl.org/choucas.ign.fr/oor#abri of the corresponding class «Shelter » in the ontology of landmark. The alignments models can be considered as a ground truth data. The alignments results are obtained using an ontology application named OOR. These specific results are obtained using the version of OOR V1.0.1 which is an improved version and contains new concepts compared to the first release 1.0.0. The new version of OOR (i.e. 1.0.1) will be released by the end of May 31 2022. The new link will be added here. This archive is released for transparency and reproducibility purposes.
description: version 1.1: fix for Alignment_POI_BDTOPO_OOR.csv file the inconsistency of column separation <br> version 1.2: add double quote to properly escape
DOI: 10.5281/zenodo.6481339
title: Alignment between type of landmark in different sources and the concept in the spatial reference objects ontology

description: The five datasets represent a manually alignment between the landmark type of five different datasets archived here and a common vocabulary extracted from an application ontology defined for mountain rescue purposes, named Ontology of landmarks (OOR). Each file represents the alignment for features belonging to a data source with the same OOR ontology. For example, the type «bivouac» from camptocamp.org source is aligned with the uri http://purl.org/choucas.ign.fr/oor#abri of the corresponding class «Shelter » in the ontology of landmark. The alignments models can be considered as a ground truth data. The alignments results are obtained using an ontology application named OOR. These specific results are obtained using the version of OOR V1.0.1 which is an improved version and contains new concepts compared to the first release 1.0.0. The new version of OOR (i.e. 1.0.1) will be released by the end of May 31 2022. The new link will be added here. This archive is released for transparency and reproducibility purposes.