cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4750612
title: Physiological activity during a virtual reality serious game – a dataset of ECG and EDA signal

description: The data was collected during an experimental study aimed at testing the ability of a virtual reality simulator to evoke certain affective states. The data was collected using the BITalino device and the EDA and ECG sensors.
description: This work was supported by the Polish National Centre for Research and Development under the grant "Bioadaptable training simulator for critical infrastructure operators – research and preparation for implementation" (project number POIR.01.01.01-00-1131/17; the Smart Growth Operational Programme, sub-measure 1.1.1) received by Nano Games sp. z o.o
description: {"references": ["Da Silva, H. P., Guerreiro, J., Louren\u00e7o, A., Fred, A. L., & Martins, R. (2014, January). BITalino: A novel hardware framework for physiological computing. In PhyCS (pp. 246-253)."]}
DOI: 10.6084/m9.figshare.14301257.v2
title: Data of: Cellulose in secondary xylem of Cactaceae: chemical composition and anatomical distribution

description: Raw dara from the infrared spectra of twenty-five species of Cactaceae with which the cristallinity indexes were obtained.
DOI: 10.5517/ccdc.csd.cc26c9xt
title: CCDC 2036666: Experimental Crystal Structure Determination

description: Related Article: Kaikai Niu, Ling Ding, Pan Zhou, Yanke Hao, Yuxiu Liu, Hongjian Song, Qingmin Wang|2021|Green Chemistry|23|3246|doi:10.1039/D1GC00861G
DOI: 10.6084/m9.figshare.13889885
title: Data from "Convergent recovery across western U.S. watersheds: Long-term monitoring reveals convergent patterns of recovery from mining contamination across four western U.S. watersheds"

description: Supporting water chemistry data and locational information from the article "<b>Convergent recovery across western U.S. watersheds: Long-term monitoring reveals convergent patterns of recovery from mining contamination across four western U.S. watersheds</b>" published in <i>Freshwater Science</i>, https://doi.org/10.1086/714575. <br>The information consists of 8 files providing supporting information on:<br><br>1. (SI) Supplemental information published with the main article, consisting of 4 figures:<b> Fig. S1:</b> Representative photographs; <b>Fig S2:</b> Stream discharge plots; <b>Fig S3:</b> Contributions of different metals to the cumulative criterion units (CCU) at impacted sites; and <b>Fig. S4:</b> Long-term changes in total macroinvertebrate abundance.<br>2. "<b>SI-Western_Watersheds_Stream_Recovery.kml</b>" Provides coordinates of study sites, and allows viewing site locations overlain on imagey of the watersheds for environmental context. Viewable in programs such as QGIS and Google Earth. <br><br><b>3. SI-assumptions for estimating metals exposures.pdf </b>Supplemental Information on Methods for Estimating Metals Exposures and calculate cumulative criteria units (CCUs)<br>4. <b>SI-Arkansas_R_CCU.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Arkansas River, Colorado study area.<br>5. <b>SI-ClarkForkRiver-CCU.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Clark Fork River, Montana study area.<br>6. <b>SI-Leviathan_CCU.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Leviathan Mine, California study area.<br>7. <b>SI-BigDeerCreek.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Big Deer Creek, Idaho study area.<br>8. <b>SI-Hydrological characteristics.xlsx</b>. Flat file with flow statistics for the streams from all 4 study units matched with chemistry values.<br><br>
DOI: 10.6084/m9.figshare.13889885.v2
title: Data from "Convergent recovery across western U.S. watersheds: Long-term monitoring reveals convergent patterns of recovery from mining contamination across four western U.S. watersheds"

description: Supporting water chemistry data and locational information from the article "<b>Convergent recovery across western U.S. watersheds: Long-term monitoring reveals convergent patterns of recovery from mining contamination across four western U.S. watersheds</b>" published in <i>Freshwater Science</i>, https://doi.org/10.1086/714575. <br>The information consists of 8 files providing supporting information on:<br><br>1. (SI) Supplemental information published with the main article, consisting of 4 figures:<b> Fig. S1:</b> Representative photographs; <b>Fig S2:</b> Stream discharge plots; <b>Fig S3:</b> Contributions of different metals to the cumulative criterion units (CCU) at impacted sites; and <b>Fig. S4:</b> Long-term changes in total macroinvertebrate abundance.<br>2. "<b>SI-Western_Watersheds_Stream_Recovery.kml</b>" Provides coordinates of study sites, and allows viewing site locations overlain on imagey of the watersheds for environmental context. Viewable in programs such as QGIS and Google Earth. <br><br><b>3. SI-assumptions for estimating metals exposures.pdf </b>Supplemental Information on Methods for Estimating Metals Exposures and calculate cumulative criteria units (CCUs)<br>4. <b>SI-Arkansas_R_CCU.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Arkansas River, Colorado study area.<br>5. <b>SI-ClarkForkRiver-CCU.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Clark Fork River, Montana study area.<br>6. <b>SI-Leviathan_CCU.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Leviathan Mine, California study area.<br>7. <b>SI-BigDeerCreek.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Big Deer Creek, Idaho study area.<br>8. <b>SI-Hydrological characteristics.xlsx</b>. Flat file with flow statistics for the streams from all 4 study units matched with chemistry values.<br><br>
DOI: 10.6084/m9.figshare.13889885.v1
title: Data from "Convergent recovery across western U.S. watersheds: Long-term monitoring reveals convergent patterns of recovery from mining contamination across four western U.S. watersheds"

description: Supporting water chemistry data and locational information from the article "<b>Convergent recovery across western U.S. watersheds: Long-term monitoring reveals convergent patterns of recovery from mining contamination across four western U.S. watersheds</b>" published in <i>Freshwater Science</i>, https://doi.org/10.1086/714575. <br>The information consists of 7 files providing supporting information on:<br><br>1. "<b>SI-Western_Watersheds_Stream_Recovery.kml</b>" Provides coordinates of study sites, and allows viewing site locations overlain on imagey of the watersheds for environmental context. Viewable in programs such as QGIS and Google Earth. <br><br><b>2. SI-assumptions for estimating metals exposures.pdf </b>Supplemental Information on Methods for Estimating Metals Exposures and calculate cumulative criteria units (CCUs)<br>3. <b>SI-Arkansas_R_CCU.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Arkansas River, Colorado study area.<br>4. <b>SI-ClarkForkRiver-CCU.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Clark Fork River, Montana study area.<br>5. <b>SI-Leviathan_CCU.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Leviathan Mine, California study area.<br>6. <b>SI-BigDeerCreek.xlsx</b> Provides stream chemistry data and formulas used to calculate CCUs for the Big Deer Creek, Idaho study area.<br>7. <b>SI-Hydrological characteristics.xlsx</b>. Flat file with flow statistics for the streams from all 4 study units matched with chemistry values.<br><br>
DOI: 10.25919/q74v-gf94
title: Perennial ryegrass as a possible source of gluten contamination in cereal crops

description: Data files of discovery proteomics of Lolium perenne. Data files of relative quantitation of gluten-like peptides in perennial ryegrass versus wheat.
DOI: 10.15144/s4wc77
title: DustCOMM data of improved representation of the global dust cycle using observational constraints on dust properties and abundance
DOI: 10.5517/ccdc.csd.cc26fnr2
title: CCDC 2038924: Experimental Crystal Structure Determination

description: Related Article: Ferdinand Lédée, Pierre Audebert, Gaëlle Trippé-Allard, Laurent Galmiche, Damien Garrot, Jérôme Marrot, Jean-Sébastien Lauret, Emmanuelle Deleporte, Claudine Katan, Jacky Even, Claudio Quarti|2021|Materials Horizons|8|1547|doi:10.1039/D0MH01904F
DOI: 10.5517/ccdc.csd.cc26l296
title: CCDC 2043157: Experimental Crystal Structure Determination

description: Related Article: Daniil A. Bardonov, Pavel D. Komarov, Valeriya I. Ovchinnikova, Lada N. Puntus, Mikhail E. Minyaev, Ilya E. Nifant’ev, Konstantin A. Lyssenko, Vladislav M. Korshunov, Ilya V. Taidakov, Dmitrii M. Roitershtein|2021|Organometallics|40|1235|doi:10.1021/acs.organomet.1c00022
DOI: 10.5517/ccdc.csd.cc26l2b7
title: CCDC 2043158: Experimental Crystal Structure Determination

description: Related Article: Daniil A. Bardonov, Pavel D. Komarov, Valeriya I. Ovchinnikova, Lada N. Puntus, Mikhail E. Minyaev, Ilya E. Nifant’ev, Konstantin A. Lyssenko, Vladislav M. Korshunov, Ilya V. Taidakov, Dmitrii M. Roitershtein|2021|Organometallics|40|1235|doi:10.1021/acs.organomet.1c00022
DOI: 10.5517/ccdc.csd.cc26l2c8
title: CCDC 2043159: Experimental Crystal Structure Determination

description: Related Article: Daniil A. Bardonov, Pavel D. Komarov, Valeriya I. Ovchinnikova, Lada N. Puntus, Mikhail E. Minyaev, Ilya E. Nifant’ev, Konstantin A. Lyssenko, Vladislav M. Korshunov, Ilya V. Taidakov, Dmitrii M. Roitershtein|2021|Organometallics|40|1235|doi:10.1021/acs.organomet.1c00022
DOI: 10.5517/ccdc.csd.cc26lwk8
title: CCDC 2043940: Experimental Crystal Structure Determination

description: Related Article: Haiyan Yu, Jun Ying, Chenxi Sun, Liang Jin, Aixiang Tian, Xiuli Wang|2021|New J.Chem.|45|7942|doi:10.1039/D1NJ00887K
DOI: 10.5281/zenodo.4420353
title: Professor

description: <strong>Targeted Chemometrics Investigations of Source-, Age- and Gender-Dependencies of Oral Cavity Malodorous Volatile Sulphur Compounds</strong> Halitosis is a highly distressing, socially-unaesthetic condition, with a very high incidence amongst the adult population. It predominantly arises from excessive oral cavity volatile sulphur compound (VSC) concentrations, which have either oral or extra-oral etiologies (90-95 and 5-10% of cases, respectively). However, reports concerning age- and gender-related influences on the patterns and concentrations of these malodorous agents remain sparse; therefore, this study’s first objective was to explore the significance and impact of these potential predictor variables. Moreover, because non-oral etiologies for halitosis may represent avatars of serious extra-oral diseases, the second objective was to distinguish between etiology- (source-) dependent patterns of oral cavity VSCs. Oral cavity VSC determinations were performed on 116 healthy human participants using a non-stationary gas chromatographic facility. Participants were grouped according to age band and gender. Statistical analyses of VSC level data acquired featured both univariate/correlation and multivariate (MV) approaches. Factorial analysis-of-variance and MV analyses revealed that the levels of all VSCs monitored were independent of both age and gender. Principal component analysis (PCA) and an agglomerative hierarchal clustering strategy demonstrated that VSC predictor variables were partitioned into two components, the first arising from orally-sourced H<sub>2</sub>S and CH<sub>3</sub>SH, the second from extra-orally-sourced (CH<sub>3</sub>)<sub>2</sub>S alone (58 and 35% of total PCA variance respectively). In conclusion, oral cavity VSC concentrations appear not to be significantly influenced by age band and gender. Furthermore, (CH<sub>3</sub>)<sub>2</sub>S may serve as a valuable biomarker for selected extra-oral conditions.
DOI: 10.25919/11aw-mr15
title: Parkes observations for project P574 semester 2021APRS_02

description: We request time to observe 260 pulsars regularly in order to provide the accurate ephemerides necessary for the detection and characterisation of gamma-ray pulsars with the Fermi satellite. The main science goals are to increase the number of known gamma-ray pulsars (both radio-loud and radio-quiet), to determine accurate pulse profiles, and to characterise their high energy (phase-resolved) spectra. In the radio, the observations will also allow us to investigate: neutron stars and pulsar emission via detecting glitches and determining pulse timing parameters; and the ISM via measuring and monitoring dispersion measures, Faraday rotation measures, and scintillation. To date, we are (co-)authors on over 90 papers arising from the collaboration and P574 data, including three which use UWL observations. The data have contributed to the PhD theses of students from Bordeaux, Manchester, Oxford, Stanford, and Swinburne.
DOI: 10.17632/4v677hrk4s.1
title: Data for: Dynamical Significance of the Tanlu Fault Zone in the Destruction of the North China Craton: The Evidence Provided by the Three-dimensional Magnetotelluric Array Study

description: Three-dimensional resistivity model produced by ModEM inversion
DOI: 10.17632/gx57kwjhpp.1
title: Data for: Instrumental mass fractionation during sulfur isotope analysis by secondary ion mass spectrometry in natural and synthetic glasses

description: Supplementary spreadsheets containing the sulfur isotope data collected from glasses by SIMS (spreadsheet1), a comparison between sulfur contents of the glasses measured by SIMS and EPMA (spreadsheet2), and the starting composition of the experimental glasses used in the study (spreadsheet3). Tables presented in the manuscript are also provided as an excel spreadsheet for easy access.
DOI: 10.25919/pd9x-3540
title: Parkes observations for project P1021 semester 2021APRS_04

description: We propose to continue our observations of PSR J1653-45, a 951-ms pulsar in a long, 1.5-yr orbit, which experiences apparent eclipses whose nature have yet to be fully understood. Binary pulsars are valuable objects of scientific study, allowing for multiple applications including tests of gravity, probes of the neutron star equation of state, and fossil records of stellar evolution. Long spin-period pulsars in binary systems are generally much rarer than faster-spinning `recycled’ pulsars, and represent an under-explored region of pulsar binary evolution. Based upon previous Parkes and ATCA proposals, our understanding of this pulsar has significantly increased. We have detected the pulsar in previously unexplored regions of its orbit, localised its position, and have constrained the start of the eclipse, such that a targeted campaign in the 2021APRS semester (during which the next eclipse is expected) will provide the breakthrough needed to solve and understand this pulsar. We therefore propose a high-cadence campaign with observations at least 1.4 times more sensitive than any previously recorded with Parkes during the eclipse. These observations will constrain the end of the eclipse and ensure that we detect the pulsar as early and often as possible, leading to a phase connected timing solution which will unlock the pulsar’s scientific potential. Through this, we hope to gain a greater understanding of this pulsar’s properties (as well as those of its companion) and how it fits into this under-explored class of unrecycled pulsar binaries.
DOI: 10.5281/zenodo.4750716
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.6084/m9.figshare.14394596
title: Underwater acoustic wave gauge and ADCP measurements

description: This is the Underwater acoustic wave gauge measurements and comparison with ADCP measurements. Experiment conducted on the Gelendzhik test site, February 1-10, 2021. Data for the paper in the journal "Journal of Geophysical Research: Oceans"
DOI: 10.6084/m9.figshare.14394596.v1
title: Underwater acoustic wave gauge and ADCP measurements

description: This is the Underwater acoustic wave gauge measurements and comparison with ADCP measurements. Experiment conducted on the Gelendzhik test site, February 1-10, 2021. Data for the paper in the journal "Remote Sensing"
DOI: 10.17608/k6.auckland.14576037
title: Technophobia dataset

description: This is a dataset on "technophobia" a socio-psychological construct, which is experienced by consumers who feel overloaded by the complexity of technology-related products. The dataset was used in the publications below and is available for use in replication and extension studies. <br><br>Sinkovics, Rudolf R., Barbara Stöttinger, Bodo B. Schlegelmilch, and Sundaresan Ram (2002), "Reluctance to use technology-related products: Development of a technophobia scale," Thunderbird International Business Review, 44 (4), 477-494. https://doi.org/10.1002/tie.10033<br><br>Salzberger, Thomas and Rudolf R. Sinkovics (2006), "Reconsidering the problem of data equivalence in international marketing research: Contrasting approaches based on CFA and the Rasch model for measurement," International Marketing Review, 23 (4), 390-417. https://doi.org/10.1108/02651330610678976<br><br>
DOI: 10.15144/s4rp4z
title: DustCOMM data of size-resolved contributions of each of the world’s main dust source regions to the global cycle of desert dust
DOI: 10.5517/ccdc.csd.cc26m769
title: CCDC 2044270: Experimental Crystal Structure Determination

description: Related Article: Daniil A. Bardonov, Pavel D. Komarov, Valeriya I. Ovchinnikova, Lada N. Puntus, Mikhail E. Minyaev, Ilya E. Nifant’ev, Konstantin A. Lyssenko, Vladislav M. Korshunov, Ilya V. Taidakov, Dmitrii M. Roitershtein|2021|Organometallics|40|1235|doi:10.1021/acs.organomet.1c00022
DOI: 10.5517/ccdc.csd.cc26m77b
title: CCDC 2044271: Experimental Crystal Structure Determination

description: Related Article: Daniil A. Bardonov, Pavel D. Komarov, Valeriya I. Ovchinnikova, Lada N. Puntus, Mikhail E. Minyaev, Ilya E. Nifant’ev, Konstantin A. Lyssenko, Vladislav M. Korshunov, Ilya V. Taidakov, Dmitrii M. Roitershtein|2021|Organometallics|40|1235|doi:10.1021/acs.organomet.1c00022
DOI: 10.5517/ccdc.csd.cc26m78c
title: CCDC 2044272: Experimental Crystal Structure Determination

description: Related Article: Daniil A. Bardonov, Pavel D. Komarov, Valeriya I. Ovchinnikova, Lada N. Puntus, Mikhail E. Minyaev, Ilya E. Nifant’ev, Konstantin A. Lyssenko, Vladislav M. Korshunov, Ilya V. Taidakov, Dmitrii M. Roitershtein|2021|Organometallics|40|1235|doi:10.1021/acs.organomet.1c00022
DOI: 10.5517/ccdc.csd.cc26pd6j
title: CCDC 2046347: Experimental Crystal Structure Determination

description: Related Article: Dongxu Yi, Jinju Ma, Hao Wu, Kaikai Zhu, Kai Wang, Rui Cao, Pengyu Zhang, Tao Li, Baozeng Ren|2021|J.Chem.Thermodynamics|159|106474|doi:10.1016/j.jct.2021.106474
DOI: 10.5517/ccdc.csd.cc26pfgt
title: CCDC 2046386: Experimental Crystal Structure Determination

description: Related Article: Pavel S. Kulyabin, Vyatcheslav V. Izmer, Georgy P. Goryunov, Mikhail I. Sharikov, Dmitry S. Kononovich, Dmitry V. Uborsky, Jo Ann M. Canich, Alexander Z. Voskoboynikov|2021|Dalton Trans.|50|6170|doi:10.1039/D1DT00645B
DOI: 10.5517/ccdc.csd.cc26pfhv
title: CCDC 2046387: Experimental Crystal Structure Determination

description: Related Article: Pavel S. Kulyabin, Vyatcheslav V. Izmer, Georgy P. Goryunov, Mikhail I. Sharikov, Dmitry S. Kononovich, Dmitry V. Uborsky, Jo Ann M. Canich, Alexander Z. Voskoboynikov|2021|Dalton Trans.|50|6170|doi:10.1039/D1DT00645B
DOI: 10.5517/ccdc.csd.cc26pfjw
title: CCDC 2046388: Experimental Crystal Structure Determination

description: Related Article: Pavel S. Kulyabin, Vyatcheslav V. Izmer, Georgy P. Goryunov, Mikhail I. Sharikov, Dmitry S. Kononovich, Dmitry V. Uborsky, Jo Ann M. Canich, Alexander Z. Voskoboynikov|2021|Dalton Trans.|50|6170|doi:10.1039/D1DT00645B
DOI: 10.5517/ccdc.csd.cc23tl6r
title: CCDC 1961004: Experimental Crystal Structure Determination

description: Related Article: Xiao Xiao, Bingxuan Shao, Jingyi Li, Zehui Yang, Yin-Jie Lu, Fei Ling, Weihui Zhong|2021|Chem.Commun.|57|4690|doi:10.1039/D1CC00989C
DOI: 10.34740/kaggle/ds/1322166
title: Academy awards dataset (oscars)
DOI: 10.5281/zenodo.4750718
title: CONUS NG-IDF Dataset

description: The <strong>NG-IDF data sets</strong> are developed for characterizing extreme events relevant to hydrologic design over water years 1951‒2013, at a 1/16th-degree (~6 km) resolution for over 200,000 locations across the conterminous United States (CONUS). The data sets are prepared in comma-separated value (.csv) format. <strong>The data sets include:</strong> <strong>list_location.csv</strong> <strong>Content:</strong> geographic <strong>c</strong>oordinates and (snow parameterization) cluster ID of 207,173 locations over the CONUS land surfaces. <strong>Dimension</strong>: 207,173 (<strong>R</strong>ows) x 3 (Columns) <strong>Format</strong>: <strong>C</strong>1: Latitude; <strong>C</strong>2: Longitude; <strong>C</strong>3: cluster ID (ranging from 1‒5) <strong>IDF/</strong> <strong>Content:</strong> discrete IDF values, i.e. magnitude of extreme events, corresponding to different event durations and returned periods, driven by different hydrometeorological mechanisms (i.e., rain, snowmelt, and rain-on-snow [ROS]) <strong>Dimension</strong>: 207,173 (Rows) x 9 (Columns) <strong>Format</strong>: C1: Latitude; C2: Longitude; C3‒9 (unit: mm): IDF values corresponding to return periods of 2 , 5, 10, 25, 50, 100, and 500 year <strong>trend/</strong> <strong>Content</strong>: Sen's slope of Mann-Kendall trend in annual maximum series driven by different hydrometeorological mechanisms over water years 1951‒2013 <strong>Dimension</strong>: 207,173 (<strong>R</strong>ows) x 3 (Columns) <strong>Format</strong>: <strong>C</strong>1: Latitude; <strong>C</strong>2: Longitude; C3:Trend. Unit is mm/year for all files but ROS_freq.csv that has a unit of # of events per year. <strong>Dom-Driver/</strong> <strong>Content</strong>: Dominant driving mechanism of extreme W events with different durations (24, 48 and 72 hours) and return periods (10, 50, and 100 years) <strong>Dimension</strong>: 207,173 (<strong>R</strong>ows) x 3 (Columns) <strong>Format</strong>: <strong>C</strong>1: Latitude; <strong>C</strong>2: Longitude; C3: Dominant driver IDs (1=rainfall, 2=ROS, 3=melt). <strong>risk/</strong> <strong>Content</strong>: Design risk associated with PREC-IDF estimated 100-year extreme events <strong>Dimension</strong>: 207,173 (<strong>R</strong>ows) x 3 (Columns) <strong>Format</strong>: <strong>C</strong>1: Latitude; <strong>C</strong>2: Longitude; C3: Bias (%) in PREC-IDF estimated extremes relative to NG-IDF <strong>SI/</strong> <strong>Content</strong>: Seasonality of annual maximum W events with 24-, 48-, and 72-hr durations <strong>Dimension</strong>: 207,173 (<strong>R</strong>ows) x 4 (Columns) <strong>Format</strong>: <strong>C</strong>1: Latitude; <strong>C</strong>2: Longitude; C3: Mean data (=1 if Oct 1); C4: Seasonality index <strong>Abbreviations used in folder/file names:</strong> W = water reaching the land surface during rain, snowmelt, and ROS events P = precipitation R = rainfall ROS = rain-on-snow M = snowmelt
DOI: 10.6084/m9.figshare.14576055
title: data and calculations.xlsx

description: quarterly data for the period from Q1 2000 to Q1 2020 on domestic and foreign Russian macroeconomic indicators
DOI: 10.6084/m9.figshare.14576055.v1
title: data and calculations.xlsx

description: quarterly data for the period from Q1 2000 to Q1 2020 on domestic and foreign Russian macroeconomic indicators