cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24356395
title: Supplementary Material for: Telomere length among Chinese aged 75+ years

description: Introduction: Telomere length (TL) is generally regarded as a biomarker of aging. TL, which is influenced by sociodemographic factors, has been shown to be inversely associated with morbidity. However, most studies examined the youngest old and whether the findings can be extended to older individuals is less clear. Further, few studies have examined these questions in Chinese older adults. This cross-sectional study examined TL and its associated factors in Chinese aged 75+ years in Hong Kong. Methods: Participants were from the Mr. and Ms. Osteoporosis cohort. A structured interview on sociodemographic factors and physical measurement was conducted. Frailty and sarcopenia status were respectively determined by Fried’s criteria and Asian Working Group for Sarcopenia definition. TL was measured by a molecular inversion probe - quantitative PCR (MIP-qPCR) assay and expressed as a novel telomere / a single copy reference gene (T/S) ratio. Adjusted binary logistic regressions were used to examine the associations between TL and the presence of multimorbidity, age-related diseases, frailty and sarcopenia. Results: Among 555 participants (mean age 83.6±3.8 years, 41.3% women), the mean T/S ratio was 1.01±0.20. Males had a lower T/S ratio (0.97±0.20) compared with females (1.07±0.18) (p&lt;0.001). A lower education level was related to a longer TL (p=0.016). Being a current smoker was related to a shorter TL (p=0.007). TL was not significantly different across categories of age, subjective socioeconomic status, drinking status, physical activity level and body mass index (p&gt;0.05). There were no associations between TL and the presence of multimorbidity, diabetes, stroke, cardiovascular diseases, cognitive impairment, frailty and sarcopenia. Conclusion: Among Chinese aged 75+ years, males had shorter TL compared with females. TL was not associated with age-related diseases, frailty and sarcopenia in this age group. TL may not be a biological marker of aging among older individuals.
DOI: 10.6084/m9.figshare.22817414.v1
title: The genome assembly of <em>Helwingia omeiensis</em>

description: The assembled haplotype genomes and the predicted gene structure of <em>Helwingia omeiensis</em>.
DOI: 10.6084/m9.figshare.24550936
title: U-Pb and XRD data of the Eastern Southern Alps - Curzi et al. Tectonics.

description: This item includes U-Pb and XRD data.
DOI: 10.6084/m9.figshare.24550936.v1
title: U-Pb and XRD data of the Eastern Southern Alps - Curzi et al. Tectonics.

description: This item includes U-Pb and XRD data.
DOI: 10.57754/fdat.3q119-kxk41
title: NoSta-D -- Korpus von Nicht-Standardvarietäten des Deutschen
title: NoSta-D -- A corpus of non-standard varieties of German

description: Corpus of different varieties of German. The subcorpora are subsets of other corpora, specified in parentheses: 1.) historical data (Anselm Corpus), chat data (Dortmund Chat Corpus), learner data (Falko), spoken data (BeMaTaC), literary prose (Kafka); 2.) newspaper texts (TüBa-D/Z). The subcorpora chat, spoken data, prose, and newspaper consist of approximately 5,000 tokens each, historical data of 1,000 tokens, and learner data of 2,900 tokens.
Each subcorpus is annotated with the following information: token and sentence boundaries; normalization; POS tags and dependency relations;  named entities; coreference. 
description: Legal ownership:
Seminar für Sprachwissenschaft, Universität Tübingen (Tüba-D/Z);
Public domain (Kafka);
Simone Schultz-Balluff & Klaus-Peter Wegera (Anselm Corpus);
Michael Beißwenger & Angelika Storrer (Dortmund Chat Corpus);
Institut für deutsche Sprache und Linguistik, HU Berlin (Falko; BaMaTaC); and
Anke Lüdeling, Stefanie Dipper, Marc Reznicek, Burkhard Dietterle (Annotations).
DOI: 10.57754/fdat.kdqzp-82076
title: German Word/Tag Embeddings (Syntactic)

description: Word and tag embeddings trained on TüDP-D/W and TüPP-D/Z using Wang2Vec.
description: Required software: extension of the original word2vec (https://code.google.com/p/word2vec/) using different architectures.
Available at https://github.com/wlin12/wang2vec
DOI: 10.17630/4b3da43a-857b-45de-805d-1e0e69b95167
title: Organic Light-emitting Diodes for Biomedical Applications (thesis data)

description: Thesis data deposited in txt. format
DOI: 10.5281/zenodo.10117555
title: Companion documents of the article entitled "State of the art of research towards sustainable power electronics" from the workgroup CEPPS, research group SEEDS, CNRS, France.

description: These documents accompany the article "State of the art of research towards sustainable power electronics", produced by members of the CEPPS working group, part of the SEEDS research group. These documents include: a list of keywords for bibliographic queries; a list of articles extracted; a list of journals, conferences and key players in the field; and a review of indicators.
DOI: 10.5281/zenodo.10117556
title: Companion documents of the article entitled "State of the art of research towards sustainable power electronics" from the workgroup CEPPS, research group SEEDS, CNRS, France.

description: These documents accompany the article "State of the art of research towards sustainable power electronics", produced by members of the CEPPS working group, part of the SEEDS research group. These documents include: a list of keywords for bibliographic queries; a list of articles extracted; a list of journals, conferences and key players in the field; and a review of indicators.
DOI: 10.5281/zenodo.8375648
title: Daphnia behavioural data and MFC field data

description: The uploaded files contain several datasets.
The Daphnia calibration dataset contains the data obtained from Daphnia behavioural experiments with the use of salt. Videos were taken every hour for 30 seconds of 5 individuals.
dumpMfcVeniceCertosaS3_2019-10.csv contains field data obtained from 5 MFCs. The file contains the timestamps, energy accumulated per MFC and their total energy accumulated—data collected in Venice Lagoon.
Millstatt_Mussel_Data contains the mussel behavioural data from Lake Millstatt in Austria (2022). It contains the x y coordinates of the top valve of a Zebra Mussel. The data was taken as a calibration of the valve movement in reaction to a sudden disturbance (in this case, a heavy rock).
DOI: 10.5281/zenodo.8375647
title: Daphnia behavioural data and MFC field data

description: The uploaded files contain several datasets.
The Daphnia calibration dataset contains the data obtained from Daphnia behavioural experiments with the use of salt. Videos were taken every hour for 30 seconds of 5 individuals.
dumpMfcVeniceCertosaS3_2019-10.csv contains field data obtained from 5 MFCs. The file contains the timestamps, energy accumulated per MFC and their total energy accumulated—data collected in Venice Lagoon.
Millstatt_Mussel_Data contains the mussel behavioural data from Lake Millstatt in Austria (2022). It contains the x y coordinates of the top valve of a Zebra Mussel. The data was taken as a calibration of the valve movement in reaction to a sudden disturbance (in this case, a heavy rock).
DOI: 10.5281/zenodo.10117726
title: Strategic crisis management in the EU: reference list

description: This dataset includes all the bibliographic references from the SAPEA evidence review report 'Strategic crisis management in the EU'.
DOI: 10.5281/zenodo.10117725
title: Strategic crisis management in the EU: reference list

description: This dataset includes all the bibliographic references from the SAPEA evidence review report 'Strategic crisis management in the EU'.
DOI: 10.5281/zenodo.4455612
title: A quantum magnetic analogue to the critical point of water

description: Specific heat data for SrCu2(BO3)2 with pressure and magnetic fields and iPEPS results for specific heat, correlation length and dimer correlations
DOI: 10.5281/zenodo.4455613
title: A quantum magnetic analogue to the critical point of water

description: Specific heat data for SrCu2(BO3)2 with pressure and magnetic fields and iPEPS results for specific heat, correlation length and dimer correlations
DOI: 10.5281/zenodo.10117796
title: Tensile test results for 3D printed unidirectional composites reinforced with continuous fibres
DOI: 10.5281/zenodo.10117795
title: Tensile test results for 3D printed unidirectional composites reinforced with continuous fibres
DOI: 10.5281/zenodo.10053508
title: A German Language Labeled Dataset of Tweets

description: Our dataset contains 8,048 German language tweets related to Jewish life from a four-year timespan. 
The dataset consists of 18 samples of tweets with the keyword "Juden" or "Israel." The samples are representative samples of all live tweets (at the time of sampling) with these keywords respectively over the indicated time period. Each sample was annotated by two expert annotators using an Annotation Portal that visualizes the live tweets in context. We provide the annotation results based on the agreement of two annotators, after discussing discrepancies (Jikeli et al. 2022: 3-6). 
 Overall, 335 tweets (4%) were labelled as antisemitic following the IHRA Working Definition of Antisemitism. 1345 tweets (17 %) come from 2019, 1364 tweets (17 %) from 2020, 2639 tweets (33 %) from 2021 and 2700 tweets (34 %) from 2022. 
About half of the tweets, a total of 4,493 tweets (56 %) come from queries with the keyword "Juden," which is representative of a continuous time period from January 2019 to December 2022: 864 tweets (19 %) come from 2019, 891 tweets (20 %) from 2020, 1364 tweets (30 %) from 2021 and 1374 (31 %). 148 out of the 4493 tweets, so 3% from the query with "Juden" are antisemitic. 
The other part of the tweets, a total of 3,555 (44 %)  results of queries with the keyword "Israel". 481 tweets (14 %) of the keywords containing Israel stem from 2019, 473 (13 %) come from 2020, 1275 tweets (36 %) from 2021 and 1326 tweets (37 %) are from 2022. Out of all tweets from the "Israel" query, 187 (5 %)  are antisemitic. 
The csv file contains diacritics and special characters of the German language (e.g., "ä", "ü", "ö", "ß"), which should be taken into account when opening it with anything other than a text editor. 
Acknowledgements 
This work used Jetstream2 at Indiana University through allocation HUM200003 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.  
We are grateful for the support of Indiana University's Observatory on Social Media (OSoMe) (Davis et al. 2016) and the contributions and annotations of all team members in our Social Media & Hate Research Lab at Indiana University's Institute for the Study of Contemporary Antisemitism, especially Grace Bland, Elisha S. Breton, Kathryn Cooper, Robin Forstenhäusler, Sophie von Máriássy, Mabel Poindexter, Jenna Solomon, Clara Schilling, Emma Shriberg and Victor Tschiskale.
DOI: 10.5281/zenodo.10053509
title: A German Language Labeled Dataset of Tweets

description: Our dataset contains 8,048 German language tweets related to Jewish life from a four-year timespan. 
The dataset consists of 18 samples of tweets with the keyword "Juden" or "Israel." The samples are representative samples of all live tweets (at the time of sampling) with these keywords respectively over the indicated time period. Each sample was annotated by two expert annotators using an Annotation Portal that visualizes the live tweets in context. We provide the annotation results based on the agreement of two annotators, after discussing discrepancies (Jikeli et al. 2022: 3-6). 
 Overall, 335 tweets (4%) were labelled as antisemitic following the IHRA Working Definition of Antisemitism. 1345 tweets (17 %) come from 2019, 1364 tweets (17 %) from 2020, 2639 tweets (33 %) from 2021 and 2700 tweets (34 %) from 2022. 
About half of the tweets, a total of 4,493 tweets (56 %) come from queries with the keyword "Juden," which is representative of a continuous time period from January 2019 to December 2022: 864 tweets (19 %) come from 2019, 891 tweets (20 %) from 2020, 1364 tweets (30 %) from 2021 and 1374 (31 %). 148 out of the 4493 tweets, so 3% from the query with "Juden" are antisemitic. 
The other part of the tweets, a total of 3,555 (44 %)  results of queries with the keyword "Israel". 481 tweets (14 %) of the keywords containing Israel stem from 2019, 473 (13 %) come from 2020, 1275 tweets (36 %) from 2021 and 1326 tweets (37 %) are from 2022. Out of all tweets from the "Israel" query, 187 (5 %)  are antisemitic. 
The csv file contains diacritics and special characters of the German language (e.g., "ä", "ü", "ö", "ß"), which should be taken into account when opening it with anything other than a text editor. 
Acknowledgements 
This work used Jetstream2 at Indiana University through allocation HUM200003 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.  
We are grateful for the support of Indiana University's Observatory on Social Media (OSoMe) (Davis et al. 2016) and the contributions and annotations of all team members in our Social Media & Hate Research Lab at Indiana University's Institute for the Study of Contemporary Antisemitism, especially Grace Bland, Elisha S. Breton, Kathryn Cooper, Robin Forstenhäusler, Sophie von Máriássy, Mabel Poindexter, Jenna Solomon, Clara Schilling, Emma Shriberg and Victor Tschiskale.
DOI: 10.57754/fdat.g2bsd-bk147
title: Tübinger Partiell Geparstes Korpus des Deutschen/Schriftsprache
title: Tübingen Partially Parsed Corpus of Written German

description: TüPP-D/Z is a collection of articles from the taz newspaper ("die tageszeitung") which have been automatically annotated with clause structure, topological fields, and chunks, in addition to more low level annotation including parts of speech and morphological ambiguity classes.  All texts have been processed automatically, starting from paragraph, sentence and token segmentation. Word forms include information about some regular types of named entities,  including dates, telephone numbers, and number/unit combinations.
DOI: 10.5281/zenodo.10117852
title: Native metabolomics with E.coli CutA and Isosepiapterin
DOI: 10.5281/zenodo.10117853
title: Native metabolomics with E.coli CutA and Isosepiapterin
DOI: 10.5285/c7db6003-1f72-4e69-b0b4-ec4b0aa4763c
title: Evidence of strong diffusion of radiation belt electrons in satellite data, and numerical simulations of strong diffusion using the BAS-RBM 2D.

description: The data set contains ephemera for the Van Allen Probes A satellite (VAP-A) and the Polar Operational Environmental Satellites (POES) m01 and n19 for the period 2013-03-17 to 2013-03-18. Chorus wave intensities calculated from data from the VAP-A EMFISIS instrument and trapped and precipitating electron fluxes calculated from the POES MEPED instruments are included in order to demonstrate the existence of conditions producing strong diffusion of electrons. Electron fluxes and phase space densities from simulations of strong diffusion performed using the BAS-RBM 2D are also include. This material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-19-1-7039. Richard Horne and Sarah Glauert were also supported by the Natural Environment Research Council (NERC) grant NE/V00249X/1 (Sat-Risk) and National and Public Good activity grant NE/R016445/1. Giulio Del Zanna acknowledges support from STFC (UK) via the consolidated grant to the astrophysics group at DAMTP, University of Cambridge (ST/T000481/1). Jay Albert acknowledges support from NASA Grant No. 80NSSC20K1270.
description: The POES electron fluxes were calculated using the proton contamination correction method from Peck et al. (2015). The raw POES MEPED data and ephemera were accessed via https://ngdc.noaa.gov/stp/satellite/poes/dataaccess.html. The chorus wave power was calculated as the wave power outside the plasmapause in 10 frequency bands between the lower hybrid resonance frequency and the electron gyrofrequency. The VAP-A ephemera and EMFISIS data were accessed via https://emfisis.physics.uiowa.edu/Flight/RBSP-A/L4/. The simulated electron fluxes and phase space densities are the output of the BAS-RBM 2D.
description: The satellite data was taken by the POES MEPED instruments, and the VAP EMFISIS instrument. The simulations were performed using the BAS-RBM 2D version 2.1.
description: Values of -1e+31 in the VAP-A chorus wave power represent times when no data was recorded.
DOI: 10.6084/m9.figshare.24551182
title: Data and Code

description: This folder includes code and data
DOI: 10.6084/m9.figshare.24551182.v1
title: Data and Code

description: This folder includes code and data
DOI: 10.5281/zenodo.10077629
title: 6DAPose - Synthetic Assembly Pose Dataset

description: 6DAPose dataset contains an object assembly in an ordered manner following its  assembly steps.  Each dataset contains 431 simulated view samples of the assembly for each assembly step. For each view sample, RGB and Depth Image, Segmentation map, ground truth values for 6D object pose and camera pose and model information are recorded following the BOP format . There are two datasets representing a 3-step fidget gear assembly and a 4-step Nema17 gear reducer assembly.
DOI: 10.5281/zenodo.10077630
title: 6DAPose - Synthetic Assembly Pose Dataset

description: 6DAPose dataset contains an object assembly in an ordered manner following its  assembly steps.  Each dataset contains 431 simulated view samples of the assembly for each assembly step. For each view sample, RGB and Depth Image, Segmentation map, ground truth values for 6D object pose and camera pose and model information are recorded following the BOP format . There are two datasets representing a 3-step fidget gear assembly and a 4-step Nema17 gear reducer assembly.
DOI: 10.5281/zenodo.10101329
title: Dataset numismàtic de monedes de l'imperi romà

description:  Aquest dataset és una col·lecció de dades numismàtic sobre les monedes de l'imperi Romà, obtingudes de el lloc web numismatics (OCRE).
El dataset obtingut conté les següents variables:

OcreReference: Identificador únic de la moneda a la base de dades numismatics.org.
Date: Data en què es va encunyar la moneda.
oType: Tipus de moneda (per exemple, Head of Caracalla, Bust of Caracalla, etc.).
rType:Tipus de revers de la moneda (per exemple, Hercules, Serapis, Mars, etc.).
authority:Autoritat que va emetre la moneda ((per exemple, Caralla, Septimius Severus, etc.).
denomination:Denominació de la moneda (per exemple,Denarius, Aureus, etc.).
material:Material amb què està feta la moneda (per exemple, plata, bronze, or).
objectType:Tipus d'objecte (per exemple, moneda, medalla, etc.).
manufacture: Fabricant de la moneda
mint: Ceca en què es va encunyar la moneda.
Region:Regió geogràfica en què es va encunyar la moneda.
DOI: 10.5281/zenodo.10101330
title: Dataset numismàtic de monedes de l'imperi romà

description:  Aquest dataset és una col·lecció de dades numismàtic sobre les monedes de l'imperi Romà, obtingudes de el lloc web numismatics (OCRE).
El dataset obtingut conté les següents variables:

OcreReference: Identificador únic de la moneda a la base de dades numismatics.org.
Date: Data en què es va encunyar la moneda.
oType: Tipus de moneda (per exemple, Head of Caracalla, Bust of Caracalla, etc.).
rType:Tipus de revers de la moneda (per exemple, Hercules, Serapis, Mars, etc.).
authority:Autoritat que va emetre la moneda ((per exemple, Caralla, Septimius Severus, etc.).
denomination:Denominació de la moneda (per exemple,Denarius, Aureus, etc.).
material:Material amb què està feta la moneda (per exemple, plata, bronze, or).
objectType:Tipus d'objecte (per exemple, moneda, medalla, etc.).
manufacture: Fabricant de la moneda
mint: Ceca en què es va encunyar la moneda.
Region:Regió geogràfica en què es va encunyar la moneda.
DOI: 10.5281/zenodo.10117902
title: Dataset numismàtic de monedes de l'imperi romà

description:  Aquest dataset és una col·lecció de dades numismàtic sobre les monedes de l'imperi Romà, obtingudes de el lloc web numismatics (OCRE).
El dataset obtingut conté les següents variables:

OcreReference: Identificador únic de la moneda a la base de dades numismatics.org.
Date: Data en què es va encunyar la moneda.
oType: Tipus de moneda (per exemple, Head of Caracalla, Bust of Caracalla, etc.).
rType:Tipus de revers de la moneda (per exemple, Hercules, Serapis, Mars, etc.).
authority:Autoritat que va emetre la moneda ((per exemple, Caralla, Septimius Severus, etc.).
denomination:Denominació de la moneda (per exemple,Denarius, Aureus, etc.).
material:Material amb què està feta la moneda (per exemple, plata, bronze, or).
objectType:Tipus d'objecte (per exemple, moneda, medalla, etc.).
manufacture: Fabricant de la moneda
mint: Ceca en què es va encunyar la moneda.
Region:Regió geogràfica en què es va encunyar la moneda.
DOI: 10.5281/zenodo.3716032
title: PAN14 Author Identification: Verification

description: We provide you with a training corpus that comprises a set of author verification problems in several languages/genres. Each problem consists of some (up to five) known documents by a single person and exactly one questioned document. All documents within a single problem instance will be in the same language and best efforts are applied to assure that within-problem documents are matched for genre, register, theme, and date of writing. The document lengths vary from a few hundred to a few thousand words.


More information: Link
DOI: 10.5281/zenodo.3716033
title: PAN14 Author Identification: Verification

description: We provide you with a training corpus that comprises a set of author verification problems in several languages/genres. Each problem consists of some (up to five) known documents by a single person and exactly one questioned document. All documents within a single problem instance will be in the same language and best efforts are applied to assure that within-problem documents are matched for genre, register, theme, and date of writing. The document lengths vary from a few hundred to a few thousand words.


More information: Link
DOI: 10.17031/6551f6438d26c
title: PHEG Update_1958_2021

description: Excel file containing CPR data for area 44N to 63N, -13W to 11E, 1958 to 2021, sample level data (each sample being 1 row, equating to approx. 10 nautical miles of tow, 3m3 of filtered seawater), for CPR PLET taxa. For each taxa, values indicate abundance (according to standard CPR methodology, see Richardson et al. 2006, Prog in Oceanog 68. 27-74), zero values are absence of taxon - all taxa have been counted since 1958. The excel file consists of samples in rows, with the following information in columns - A: sample id B:midpoint of sample latitude in decimal degrees C:midpoint of sample longitude in decimal degrees D:midpoint of sample local date and time E:sample year F: sample month G: Phytoplankton Colour Index H-:taxa.