cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/cc3813af5af3d0fec4bbede185a94cb6
title: Barn Tower Meteorological Station at Harvard Forest since 2015

description: The Barn Tower (40 m) was installed in 2009 to support meteorological and phenological measurements and to provide a relay point for the Harvard Forest field wireless network. A wind instrument was later installed at the top of the tower to provide continuous measurements of wind speed and direction.
DOI: 10.17894/ucph.1e91d0f0-3e01-4a32-9b05-0471b347f29a
title: Raw seqs for "Rapid loss of endogenous DNA in pig bone buried in five different environments"
DOI: 10.21227/5srq-3c28
title: DATASET FOR COMPLEXITY ANALYSIS OF VVC ENCODING AND DECODING

description: While the next generation video compression standard, Versatile Video Coding (VVC), provides a superior compressing efficiency, its computational complexity dramatically increases. This dataset provides a thoroug analisis on complexity of both encoder and decoder of VVC Test Model 6.0. Encoding and decoding operations have been performed for six video sequences of 720p, 1080p, and 2160p resolutions, and under Low-Delay (LD), Random-Access (RA), and All-Intra (AI) conditions (a total of 320 encoding/decoding operations). All operations were analyzed with Intel VTune 2019 and results of these analysis are collected and reported in this dataset, in csv files. Moreover complexity of encoding and decoding operation have been categorized into six coding/decoding classes and details of each test video sequence have been reported through 4 tables in Tabulated_Report.docx.This dataset serves as suplementary material for our paper "Complexity Analysis of Next-Generation VVC Encoding and Decoding", which is under review.
DOI: 10.21227/hxkm-2q16
title: Dynamic assessment and prediction of equipment status in 220kV substations by big data and AI technology

description: The current paper aims to present new hybrid model of fault classification based on implementing the principle of data reduction for Dissolved Gas Analysis data (DGA) of power transformers by using the combination (subsets) of set (C-set) method and the unsupervised FCM clustering algorithm. We used Multiclass Support Vector Machine (MCSVM) for performing the final classification. Bearing in mind the compactness of DGA data, C-set method is employed for dividing the data samples according to their fault types into multiple groups without repetition. FCM algorithm is adopted for samples pre-selection process by obtaining the cluster centers of each C-set class in order to reduce the dimensionally size of the DGA data set and the uncertainty of the transformer condition monitoring. Then, 1-vs-1 MCSVM method with linear kernel, has been used to carry out the fault diagnosis and perform the final classification. The proposed model diagnosis obtained accuracy, is 88.9%. Our proposed model has been compared with other soft computing techniques and traditional models. The proposed experimental model results revealed high performance in classifying transformer faults, improving the fault identification accuracy and shortening the computing time. Our new model is straightforward and accurate, suggesting good prospect of use in engineering practice.
DOI: 10.21227/xx3e-6851
title: COMPLEXITY ANALYSIS OF VVC ENCODING AND DECODING

description: While the next generation video compression standard, Versatile Video Coding (VVC), provides a superior compressing efficiency, its computational complexity dramatically increases. This dataset provides a thoroug analisis on complexity of both encoder and decoder of VVC Test Model 6.0. Encoding and decoding operations have been performed for six video sequences of 720p, 1080p, and 2160p resolutions, and under Low-Delay (LD), Random-Access (RA), and All-Intra (AI) conditions (a total of 320 encoding/decoding operations). All operations were analyzed with Intel VTune 2019 and results of these analysis are collected and reported in this dataset, in csv files. Moreover complexity of encoding and decoding operation have been categorized into six coding/decoding classes and details of each test video sequence have been reported through 4 tables in Tabulated_Report.docx.This dataset serves as suplementary material for our paper "Complexity Analysis of Next-Generation VVC Encoding and Decoding", which is under review.
DOI: 10.5281/zenodo.3628142
title: Data from: Predictive mapping of the global power system using open data

description: Three primary global data outputs from the research: <strong>grid.gpkg:</strong> Vectorized predicted distribution and transmission line network, with existing OpenStreetMap lines tagged in the 'source' column <strong>targets.tif:</strong> Binary raster showing locations predicted to be connected to distribution grid. <strong>lv.tif:</strong> Raster of predicted low-voltage infrastructure in kilometres per cell. This data was created with code in the following three repositories: https://github.com/carderne/gridfinder https://github.com/carderne/predictive-mapping-global-power https://github.com/carderne/access-estimator Full steps to reproduce are contained in this file: https://github.com/carderne/predictive-mapping-global-power/blob/master/README.md The data can be visualized at the following location: https://gridfinder.org
DOI: 10.5519/qd.swib669z
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (347 records)
DOI: 10.6084/m9.figshare.11719470.v10
title: Simulated significant wave height (3-hourly, 150a) from FIO-ESM v2.0 abrupt-4xCO2 experiment r1i1p1f1

description: Simulated significant wave height (3-hourly, 150a) from FIO-ESM v2.0 abrupt-4xCO2 experiment (CO2 abruptly quadrupled and then held constant) r1i1p1f1, which is branch from Jan 1, 301 of piControl experiment. The grid, named gx1v6, is the displaced pole (the North Pole displaced to the Greenland) grid with 1.1 degree in longitude and 0.27-0.54 degree in latitude.
DOI: 10.7910/dvn/zbomxx/4dtpck
title: 2015 American Family Survey.tab

description: :unav
DOI: 10.7910/dvn/zbomxx/ecr9rf
title: American-Family-Landscape-Topline-Final.pdf

description: :unav
DOI: 10.7910/dvn/zbomxx/eqhs4e
title: American-Family-Survey_Final-Report.pdf

description: :unav
DOI: 10.7910/dvn/zbomxx/yhmbft
title: American-Family-Survey-Codebook.pdf

description: :unav
DOI: 10.7910/dvn/cajwwb/jqmkml
title: AFS2016Report.pdf

description: :unav
DOI: 10.7910/dvn/cajwwb/mcszss
title: 2016-AFS-Codebook.pdf

description: :unav
DOI: 10.7910/dvn/cajwwb/sazwji
title: 2016 American Family Survey - Copy.tab

description: :unav
DOI: 10.7910/dvn/cajwwb/yg9lpp
title: 2016-American-Family-Survey-Topline-Final.pdf

description: :unav
DOI: 10.17632/kb7ry8xsvs.1
title: Mendeley Supplementary Table 1

description: Table that displays the cost, sensitivity and specificity for each of the diagnostic tests.
DOI: 10.25345/c5k405
title: MassIVE MSV000084842 - Chemical profiling of Helleborus odorus subsp. cyclophyllus.
title: Chemical profiling of Helleborus odorus subsp. cyclophyllus.
DOI: 10.5281/zenodo.3627952
title: Project dataset: predicting traffic volumes and congestion in road networks equipped with ANPR cameras

description: https://github.com/ppintosilva/anpr-predict
description: Cast id integers to factors in spatial data and rename columns to match flow data.
DOI: 10.7910/dvn/gkmkou/2hqfxo
title: AFS-Report-2017_Full_Embargoed.pdf

description: :unav
DOI: 10.7910/dvn/gkmkou/fu35bt
title: AFS 2017.tab

description: :unav
DOI: 10.7910/dvn/gkmkou/nhh3mp
title: 2017-American-Family-Survey-Topline.pdf

description: :unav
DOI: 10.7910/dvn/gkmkou/xhppdf
title: 2017-Codebook.pdf

description: :unav
DOI: 10.7910/dvn/i3lupc/3zag4m
title: 2018-Codebook.pdf

description: :unav
DOI: 10.7910/dvn/i3lupc/c4t6wm
title: Data for Release 2018.tab

description: :unav
DOI: 10.7910/dvn/i3lupc/esfimd
title: publicreport2018 (1).pdf

description: :unav
DOI: 10.7910/dvn/i3lupc/exm8xq
title: 2018Toplines.pdf

description: :unav
DOI: 10.7910/dvn/u3hwrg/i3kims
title: 2019 AFS Data.tab

description: :unav
DOI: 10.7910/dvn/u3hwrg/eqjmwh
title: 2019 AFS Topline.pdf

description: :unav
DOI: 10.7910/dvn/u3hwrg/klaz3a
title: 2019 AFS Codebook.pdf

description: :unav
DOI: 10.7910/dvn/u3hwrg/onoowj
title: AFS Final Report_Sep_2019 (1).pdf

description: :unav
DOI: 10.5281/zenodo.3627953
title: CaLiGraph - A Large-Scale Semantic Knowledge Graph compiled from Wikipedia Categories and List Pages

description: CaLiGraph is a large-scale semantic knowledge graph with a rich ontology which is compiled from the DBpedia ontology, and Wikipedia categories & list pages. For more information, visit http://caligraph.org Information about uploaded files:<br> (all files are b-zipped and in the n-triple format)<br> <br> caligraph-metadata.nt.bz2<br> Metadata about the dataset which is described using void vocabulary. caligraph-ontology.nt.bz2<br> Class definitions, property definitions, restrictions, and labels of the CaLiGraph ontology. caligraph-ontology_dbpedia-mapping.nt.bz2<br> Mapping of classes and properties to the DBpedia ontology. caligraph-ontology_provenance.nt.bz2<br> Provenance information about classes (i.e. which Wikipedia category or list page has been used to create this class). caligraph-instances_types.nt.bz2<br> Definition of instances and (non-transitive) types. caligraph-instances_transitive-types.nt.bz2<br> Transitive types for instances (can also be induced by a reasoner). caligraph-instances_labels.nt.bz2<br> Labels for instances. caligraph-instances_relations.nt.bz2<br> Relations between instances derived from the class restrictions of the ontology (can also be induced by a reasoner). caligraph-instances_dbpedia-mapping.nt.bz2<br> Mapping of instances to respective DBpedia instances. caligraph-instances_provenance.nt.bz2<br> Provenance information about instances (e.g. if the instance has been extracted from a Wikipedia list page). dbpedia_caligraph-instances.nt.bz2<br> Additional instances of CaLiGraph that are not in DBpedia.<br> ! This file is no part of CaLiGraph but should rather be used as an extension to DBpedia. The triples use the DBpedia namespace and can thus be used to directly extend DBpedia. ! dbpedia_caligraph-types.nt.bz2<br> Additional types of CaLiGraph that are not in DBpedia.<br> ! This file is no part of CaLiGraph but should rather be used as an extension to DBpedia. The triples use the DBpedia namespace and can thus be used to directly extend DBpedia. ! dbpedia_caligraph-relations.nt.bz2<br> Additional relations of CaLiGraph that are not in DBpedia.<br> ! This file is no part of CaLiGraph but should rather be used as an extension to DBpedia. The triples use the DBpedia namespace and can thus be used to directly extend DBpedia. ! <strong>Changelog</strong> v1.0.6 Fixed a bug in the ontology creation step that led to a substantially lower amount of sub-type relationships than actually exist. The new version provides a richer type hierarchy that also leads to an increased amount of types for resources. v1.0.5 Fixed a bug that has declared CaLiGraph predicates as subclasses of owl:Predicate instead of being of the type owl:Predicate.
DOI: 10.7910/dvn/htl8aj/12ccpp
title: Favoring Co-Partisans Dataset.tab

description: :unav
DOI: 10.7910/dvn/htl8aj/ep2bdw
title: Favoring Co-partisans Individual Level Analysis.do

description: :unav
DOI: 10.7910/dvn/htl8aj/eqpfzj
title: Favoring Co-partisans.do

description: :unav
DOI: 10.7910/dvn/htl8aj/xids3t
title: Favoring Co-Partisans Individual Level Dataset.tab

description: :unav
DOI: 10.21227/sz90-xe66
title: DATASET FOR COMPLEXITY ANALYSIS OF VVC ENCODING AND DECODING

description: While the next generation video compression standard, Versatile Video Coding (VVC), provides a superior compressing efficiency, its computational complexity dramatically increases. This dataset provides a thoroug analisis on complexity of both encoder and decoder of VVC Test Model 6.0. Encoding and decoding operations have been performed for six video sequences of 720p, 1080p, and 2160p resolutions, and under Low-Delay (LD), Random-Access (RA), and All-Intra (AI) conditions (a total of 320 encoding/decoding operations). All operations were analyzed with Intel VTune 2019 and results of these analysis are collected and reported in this dataset, in csv files. Moreover complexity of encoding and decoding operation have been categorized into six coding/decoding classes and details of each test video sequence have been reported through 4 tables in Tabulated_Report.docx.This dataset serves as suplementary material for our paper "Complexity Analysis of Next-Generation VVC Encoding and Decoding", which is under review.
DOI: 10.17632/hb9h79fjh3.1
title: Data for: Rare or overlooked? The distribution of Hairy Jointgrass in north coast New South Wales, Australia, and implications for its conservation status.

description: A probability distribution map of suitable habitat for the threatened grass Arthraxon hispidus in north coast New South Wales, Australia, developed using maximum entropy (MaxEnt) modelling.
DOI: 10.5281/zenodo.3628320
title: UK National Crystallography Service benchmark experiment 1

description: Data part of a bench-marking experiment. Data collected at Advanced Light Source, beamline 12.2.1 sample: 'challenging' sum formula: C13 H6 F5 N Wavelength: 0.7288 Angstrom Temperature: 100K Data integrated with SAINT
DOI: 10.5281/zenodo.3628321
title: UK National Crystallography Service benchmark experiment 1

description: Data part of a bench-marking experiment. Data collected at Advanced Light Source, beamline 12.2.1 sample: 'challenging' sum formula: C13 H6 F5 N Wavelength: 0.7288 Angstrom Temperature: 100K Data integrated with SAINT
DOI: 10.21227/5dbp-7c96
title: Twitter Sentiment Analysis Data

description: Each database (*.db) contain three columns. First column: date and time of the tweet, second column: tweet, third column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live[1]. The last column, viz. sentiment score, is not the score estimated by the model. The LSTM model is still in the pre-alpha phase. Therefore, to make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. The sentiment scores produced by our model will be made public after the project is completely open-sourced.####status/latest addition: Jan 26, 2020####Tweets containing the term "samsung": 1.20 million-plusTweets containing the term "facebook": 0.77 million-plusTweets containing the term "android": 0.88 million-plusTweets containing the term "oneplus": 15 thousand-plusTweets containing the term "messi": 225 thousand-plusTweets containing the term "housefull 4": 346 thousand-plusTweets containing the term "the joker": 1 million-plusTweets containing the term "iphone 11": 2 million-plus##################References:[1]https://sentiment.live/ [2]https://textblob.readthedocs.io/en/dev/
DOI: 10.21227/838q-hw29
title: Twitter Sentiment Analysis Data

description: Each database (*.db) contain three columns. First column: date and time of the tweet, second column: tweet, third column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live[1]. The last column, viz. sentiment score, is not the score estimated by the model. The LSTM model is still in the pre-alpha phase. Therefore, to make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. The sentiment scores produced by our model will be made public after the project is completely open-sourced.####status/latest addition: Jan 26, 2020####Tweets containing the term "samsung": 1.20 million-plusTweets containing the term "facebook": 0.77 million-plusTweets containing the term "android": 0.88 million-plusTweets containing the term "oneplus": 15 thousand-plusTweets containing the term "messi": 225 thousand-plusTweets containing the term "housefull 4": 346 thousand-plusTweets containing the term "the joker": 1 million-plusTweets containing the term "iphone 11": 2 million-plus##################References:[1]https://sentiment.live/ [2]https://textblob.readthedocs.io/en/dev/
DOI: 10.5281/zenodo.3627767
title: Dynamic Ligand Impacts on Dissolved Iron Distributions in a Global Ocean Biogeochemical Model

description: Annual mean CESM ocean output files on the coarse resolution gx3v7 grid.<br> Archived here in support of the paper submitted to JAMES by<br> Sherman et al. "Dynamic Ligand Impacts on Dissolved Iron Distributions in a<br> Global Ocean Biogeochemical Model". gdev.450 = dynamic ligand<br> gdev.457 = constant ligand = 1 nM<br> gdev.460 = implicit ligand gdev.458 = dynamic ligand + Sol Fe Depo X3<br> gdev.459 = constant ligand = 1 nM + Sol Fe Depo X3<br> gdev.461 = implicit ligand + Sol Fe Depo X3
DOI: 10.5281/zenodo.3627768
title: Dynamic Ligand Impacts on Dissolved Iron Distributions in a Global Ocean Biogeochemical Model

description: Annual mean CESM ocean output files on the coarse resolution gx3v7 grid.<br> Archived here in support of the paper submitted to JAMES by<br> Sherman et al. "Dynamic Ligand Impacts on Dissolved Iron Distributions in a<br> Global Ocean Biogeochemical Model". gdev.450 = dynamic ligand<br> gdev.457 = constant ligand = 1 nM<br> gdev.460 = implicit ligand gdev.458 = dynamic ligand + Sol Fe Depo X3<br> gdev.459 = constant ligand = 1 nM + Sol Fe Depo X3<br> gdev.461 = implicit ligand + Sol Fe Depo X3
DOI: 10.6084/m9.figshare.11719989
title: Candidate genes involved in the defunctionalization and refunctionalization of the urinary bladder induced by bladder anuria and reperfusion

description: <b>Supplementary Table S1: </b>Demographic data of the 44 patients who received dialysis prior to kidney transplantation.<b>Supplementary Table S2: </b>Primer sets used for the quantitative RT-PCR.<br><b>Supplementary Table S3: </b>List of top and bottom KEGG pathways that were significantly up-regulated and down-regulated from the control to the defunctionalized group and from the defunctionalized to the refunctionalized group in the rabbit DNA microarray analysis stratified with Z-scores of the parametric analysis of gene-set enrichment higher than three.<br><b>Supplementary Table S4:</b> Comparison of the changes in the relative gene expression level of collagens among the rabbit bladder DNA microarray, rabbit bladder RT-PCR, and human bladder RT-PCR of the control and defunctionalized groups and the defunctionalized and refunctionalized groups.<br>
DOI: 10.6084/m9.figshare.11719989.v1
title: Candidate genes involved in the defunctionalization and refunctionalization of the urinary bladder induced by bladder anuria and reperfusion

description: <b>Supplementary Table S1: </b>Demographic data of the 44 patients who received dialysis prior to kidney transplantation.<b>Supplementary Table S2: </b>Primer sets used for the quantitative RT-PCR.<br><b>Supplementary Table S3: </b>List of top and bottom KEGG pathways that were significantly up-regulated and down-regulated from the control to the defunctionalized group and from the defunctionalized to the refunctionalized group in the rabbit DNA microarray analysis stratified with Z-scores of the parametric analysis of gene-set enrichment higher than three.<br><b>Supplementary Table S4:</b> Comparison of the changes in the relative gene expression level of collagens among the rabbit bladder DNA microarray, rabbit bladder RT-PCR, and human bladder RT-PCR of the control and defunctionalized groups and the defunctionalized and refunctionalized groups.<br>
DOI: 10.5281/zenodo.3556400
title: Chip-based soliton microcomb module using a hybrid semiconductor laser

description: <strong>Data for the paper Chip-based soliton microcomb module using a hybrid semiconductor lase</strong>
DOI: 10.5281/zenodo.3556401
title: Chip-based soliton microcomb module using a hybrid semiconductor laser

description: <strong>Data for the paper Chip-based soliton microcomb module using a hybrid semiconductor lase</strong>
DOI: 10.5281/zenodo.3626806
title: FastText and Word2Vec Spanish Medical Embeddings

description: [Plan TL/medicine/word embeddings] Word embeddings generated from Spanish corpora that include: (a) the full-text in Spanish available in Scielo.org (until December/2018), (b) all articles from the following Wikipedia categories: Pharmacology, Pharmacy, Medicine and Biology (during December/2018) and (c) the concatenation of the previous two corpora. To generate the word embedding two different approaches were used: Word2Vec and fastText. For more information, we refer to the corresponding article: https://www.aclweb.org/anthology/W19-1916/
description: Funded by the Plan de Impulso de las Tecnologías del Lenguaje (Plan TL).
description: {"references": ["Soares F, Villegas M, Gonzalez-Agirre A, Krallinger M, Armengol-Estap\u00e9 J. Medical Word Embeddings for Spanish: Development and Evaluation. InProceedings of the 2nd Clinical Natural Language Processing Workshop 2019 Jun (pp. 124-133)."]}
DOI: 10.5281/zenodo.3627789
title: Promotion of sleep health in police officers

description: The file contains the data used for the article with the same name, sent for publication on PLoSOne. Data were corrected for some typos.
DOI: 10.5281/zenodo.3627790
title: Promotion of sleep health in police officers

description: The file contains the data used for the article with the same name, sent for publication on PLoSOne.
DOI: 10.5286/isis.e.rb2010756
title: Inelastic Neutron Scattering studies on R2CoRuO6 (R = La, Y)

description: The double perovskite compound La2CoRuO6 shows an antiferromagnetic ordered (AFM) ground state with propagation vector (½ 0 ½). On the other hand, Y2CoRuO6 shows antiparallel arrangements of Co and Ru sublattices leading to a ferrimagnetic ground state. It is rather fascinating to observe that La2CoRuO6 and Y2CoRuO6 compounds show different magnetic structures despite having similar crystal structure. It is therefore pertinent to study the magnitude and sign of the interactions J1 and J2 and one would expect J2 &gt; J1 and J1 &gt; J2 in La and Y compounds respectively. The magnetic excitation spectra obtained from inelastic neutron scattering experiment well below the magnetic transition temperature can be quite useful to estimate the magnetic exchange interactions. We therefore propose to investigate spin wave in La2CoRuO6 and Y2CoRuO6 using inelastic neutron scattering study on MERLIN/MARI
DOI: 10.5286/isis.e.rb2010756-1
title: Inelastic Neutron Scattering studies on R2CoRuO6 (R = La, Y)

description: The double perovskite compound La2CoRuO6 shows an antiferromagnetic ordered (AFM) ground state with propagation vector (½ 0 ½). On the other hand, Y2CoRuO6 shows antiparallel arrangements of Co and Ru sublattices leading to a ferrimagnetic ground state. It is rather fascinating to observe that La2CoRuO6 and Y2CoRuO6 compounds show different magnetic structures despite having similar crystal structure. It is therefore pertinent to study the magnitude and sign of the interactions J1 and J2 and one would expect J2 &gt; J1 and J1 &gt; J2 in La and Y compounds respectively. The magnetic excitation spectra obtained from inelastic neutron scattering experiment well below the magnetic transition temperature can be quite useful to estimate the magnetic exchange interactions. We therefore propose to investigate spin wave in La2CoRuO6 and Y2CoRuO6 using inelastic neutron scattering study on MERLIN/MARI