cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15161/oar.it/30629
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.5281/zenodo.3988742
title: Data for "Incidence, clinical course and risk factor for recurrent PCR positivity in discharged COVID-19 patients in Guangzhou, China: a prospective cohort study"

description: Data for "Incidence, clinical course and risk factor for recurrent PCR positivity in discharged COVID-19 patients in Guangzhou, China: a prospective cohort study"
DOI: 10.5281/zenodo.3988741
title: Data for "Incidence, clinical course and risk factor for recurrent PCR positivity in discharged COVID-19 patients in Guangzhou, China: a prospective cohort study"

description: Data for "Incidence, clinical course and risk factor for recurrent PCR positivity in discharged COVID-19 patients in Guangzhou, China: a prospective cohort study"
DOI: 10.21227/xjzb-4y45
title: HUMAN4D: A Human-Centric Multimodal Dataset for Motions Immersive Media

description: We introduce HUMAN4D, a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system.nbsp;By capturing 2 female and 2 male professional actors performing various full-body movements and expressions, HUMAN4D provides a diverse set of motions and poses encountered as part of single- and multi-person daily, physical and social activities (jumping, dancing, etc.), along with multi-RGBD (mRGBD), volumetric and audio data.nbsp;Despite the existence of multi-view color datasets captured with the use of hardware (HW) synchronization, to the best of our knowledge, HUMAN4D is the first and only public resource that provides volumetric depth maps with high synchronization precision due to the use of intra- and inter-sensor HW-SYNC.nbsp;Moreover, a spatio-temporally aligned scanned and rigged 3D character complements HUMAN4D to enable joint research on time-varying and high-quality dynamic meshes.nbsp;We provide evaluation baselines by benchmarking HUMAN4D with state-of-the-art human pose estimation and 3D compression methods.nbsp;For the former, we apply 2D and 3D pose estimation algorithms both on single- and multi-view data cues.nbsp;For the latter, we benchmark open-source 3D codecs on volumetric data respecting online volumetric video encoding and steady bit-rates.nbsp;Furthermore, qualitative and quantitative visual comparison between mesh-based volumetric data reconstructed in different qualities showcases the available options with respect to 4D representations.nbsp;HUMAN4D is introduced to the computer vision and graphics research communities to enable joint research on spatio-temporally aligned pose, volumetric, mRGBD and audio data cues.The dataset and its code are available online.
DOI: 10.21227/t82t-qc67
title: HUMAN4D: A Human-Centric Multimodal Dataset for Motions Immersive Media

description: We introduce HUMAN4D, a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system.nbsp;By capturing 2 female and 2 male professional actors performing various full-body movements and expressions, HUMAN4D provides a diverse set of motions and poses encountered as part of single- and multi-person daily, physical and social activities (jumping, dancing, etc.), along with multi-RGBD (mRGBD), volumetric and audio data.nbsp;Despite the existence of multi-view color datasets captured with the use of hardware (HW) synchronization, to the best of our knowledge, HUMAN4D is the first and only public resource that provides volumetric depth maps with high synchronization precision due to the use of intra- and inter-sensor HW-SYNC.nbsp;Moreover, a spatio-temporally aligned scanned and rigged 3D character complements HUMAN4D to enable joint research on time-varying and high-quality dynamic meshes.nbsp;We provide evaluation baselines by benchmarking HUMAN4D with state-of-the-art human pose estimation and 3D compression methods.nbsp;For the former, we apply 2D and 3D pose estimation algorithms both on single- and multi-view data cues.nbsp;For the latter, we benchmark open-source 3D codecs on volumetric data respecting online volumetric video encoding and steady bit-rates.nbsp;Furthermore, qualitative and quantitative visual comparison between mesh-based volumetric data reconstructed in different qualities showcases the available options with respect to 4D representations.nbsp;HUMAN4D is introduced to the computer vision and graphics research communities to enable joint research on spatio-temporally aligned pose, volumetric, mRGBD and audio data cues.The dataset and its code are available online.
DOI: 10.17632/kfdfv9tmxg.3
title: Data for: Dynamic capital structure under changing market conditions in the oil industry: An empirical investigation

description: Data correspond to variables constructed for analyzing capital structure models within the oil industry. Raw data were retrieved from DataStream.
DOI: 10.21227/hk5f-5v47
title: HUMAN4D: A Human-Centric Multimodal Dataset for Motions Immersive Media

description: We introduce HUMAN4D, a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system.nbsp;By capturing 2 female and 2 male professional actors performing various full-body movements and expressions, HUMAN4D provides a diverse set of motions and poses encountered as part of single- and multi-person daily, physical and social activities (jumping, dancing, etc.), along with multi-RGBD (mRGBD), volumetric and audio data.nbsp;Despite the existence of multi-view color datasets captured with the use of hardware (HW) synchronization, to the best of our knowledge, HUMAN4D is the first and only public resource that provides volumetric depth maps with high synchronization precision due to the use of intra- and inter-sensor HW-SYNC.nbsp;Moreover, a spatio-temporally aligned scanned and rigged 3D character complements HUMAN4D to enable joint research on time-varying and high-quality dynamic meshes.nbsp;We provide evaluation baselines by benchmarking HUMAN4D with state-of-the-art human pose estimation and 3D compression methods.nbsp;For the former, we apply 2D and 3D pose estimation algorithms both on single- and multi-view data cues.nbsp;For the latter, we benchmark open-source 3D codecs on volumetric data respecting online volumetric video encoding and steady bit-rates.nbsp;Furthermore, qualitative and quantitative visual comparison between mesh-based volumetric data reconstructed in different qualities showcases the available options with respect to 4D representations.nbsp;HUMAN4D is introduced to the computer vision and graphics research communities to enable joint research on spatio-temporally aligned pose, volumetric, mRGBD and audio data cues.The dataset and its code are available online.
DOI: 10.17030/uclan.data.00000264
title: Code for seasonally specific models.
DOI: 10.21227/pgkw-m429
title: HUMAN4D: A Human-Centric Multimodal Dataset for Motions Immersive Media

description: We introduce HUMAN4D, a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system.nbsp;By capturing 2 female and 2 male professional actors performing various full-body movements and expressions, HUMAN4D provides a diverse set of motions and poses encountered as part of single- and multi-person daily, physical and social activities (jumping, dancing, etc.), along with multi-RGBD (mRGBD), volumetric and audio data.nbsp;Despite the existence of multi-view color datasets captured with the use of hardware (HW) synchronization, to the best of our knowledge, HUMAN4D is the first and only public resource that provides volumetric depth maps with high synchronization precision due to the use of intra- and inter-sensor HW-SYNC.nbsp;Moreover, a spatio-temporally aligned scanned and rigged 3D character complements HUMAN4D to enable joint research on time-varying and high-quality dynamic meshes.nbsp;We provide evaluation baselines by benchmarking HUMAN4D with state-of-the-art human pose estimation and 3D compression methods.nbsp;For the former, we apply 2D and 3D pose estimation algorithms both on single- and multi-view data cues.nbsp;For the latter, we benchmark open-source 3D codecs on volumetric data respecting online volumetric video encoding and steady bit-rates.nbsp;Furthermore, qualitative and quantitative visual comparison between mesh-based volumetric data reconstructed in different qualities showcases the available options with respect to 4D representations.nbsp;HUMAN4D is introduced to the computer vision and graphics research communities to enable joint research on spatio-temporally aligned pose, volumetric, mRGBD and audio data cues.The dataset and its code are available online.
DOI: 10.17632/kfdfv9tmxg.4
title: Data for: Dynamic capital structure under changing market conditions in the oil industry: An empirical investigation

description: Data correspond to variables constructed for analyzing capital structure models within the oil industry. Raw data were retrieved from DataStream.
DOI: 10.5281/zenodo.3989293
title: Low temperature selective growth of GaN single crystals on pre-patterned Si substrates_experimental dataset

description: This file contains the raw unprocessed experimental data for the results published in Jindřich Mach et al., <strong>Low temperature selective growth of GaN single crystals on pre-patterned Si substrates</strong>, Applied Surface Science, Volume 497, 16 August 2019, 143705.
description: This work was supported by the Technology Agency of the Czech Republic (Grant No. TE01020233), H2020 Twinning programme (project SINNCE, 810626), Grant Agency of the Czech Republic (grant 17-33767L), and MEYS CR (grant No. LQ1601 – CEITEC 2020). We also acknowledge the support by the Grant Agency of the Czech Republic (grant No. 17-21413S).
DOI: 10.5281/zenodo.3989292
title: Low temperature selective growth of GaN single crystals on pre-patterned Si substrates_experimental dataset

description: This file contains the raw unprocessed experimental data for the results published in Jindřich Mach et al., <strong>Low temperature selective growth of GaN single crystals on pre-patterned Si substrates</strong>, Applied Surface Science, Volume 497, 16 August 2019, 143705.
description: This work was supported by the Technology Agency of the Czech Republic (Grant No. TE01020233), H2020 Twinning programme (project SINNCE, 810626), Grant Agency of the Czech Republic (grant 17-33767L), and MEYS CR (grant No. LQ1601 – CEITEC 2020). We also acknowledge the support by the Grant Agency of the Czech Republic (grant No. 17-21413S).
DOI: 10.5281/zenodo.3988472
title: CLDF dataset derived from Gauchat et al.'s "Tableaux phonétiques des patois suisses romands" from 1925

description: Cite the source of the dataset as: Gauchat, L.; Jeanjaquet, J. & Tappolet, E. (1925): Tableaux phonétiques des patois suisses romands Attinger: Neuchâtel.
DOI: 10.5281/zenodo.3989406
title: Collector Droplet Behavior during Formation of Nanowire Junctions_experimental dataset

description: This file contains the raw unprocessed experimental data for the results published in Yanming Wang et al., Collector Droplet Behavior during Formation of Nanowire Junctions, J. Phys. Chem. Lett. 2020, 11, XXX, 6498–6504.
description: This research has been financially supported by the Grant Agency of the Czech Republic (16-16423Y), Technology Agency of the Czech republic (TN01000008), Ministry of Education, Youth and Sports of the Czech Republic under the projects CEITEC 2020 (LQ1601) and Ceitec Nano+ (CZ.02.01/0.0./.0.0./16_013/0001728 under the program OPVVV) and Horizon 2020 Research and Innovation Programme under the grant agreement no. 810626 (SINNCE). We acknowledge CzechNanoLab Research Infrastructure supported by MEYS CR (LM2018110). The simulations were performed at the Stanford Nano Shared Facilities supported by the National Science Foundation under award ECCS-1542152. Y.W. would like to acknowledge financial support from Toyota Research Institute.
DOI: 10.5281/zenodo.3989405
title: Collector Droplet Behavior during Formation of Nanowire Junctions_experimental dataset

description: This file contains the raw unprocessed experimental data for the results published in Yanming Wang et al., Collector Droplet Behavior during Formation of Nanowire Junctions, J. Phys. Chem. Lett. 2020, 11, XXX, 6498–6504.
description: This research has been financially supported by the Grant Agency of the Czech Republic (16-16423Y), Technology Agency of the Czech republic (TN01000008), Ministry of Education, Youth and Sports of the Czech Republic under the projects CEITEC 2020 (LQ1601) and Ceitec Nano+ (CZ.02.01/0.0./.0.0./16_013/0001728 under the program OPVVV) and Horizon 2020 Research and Innovation Programme under the grant agreement no. 810626 (SINNCE). We acknowledge CzechNanoLab Research Infrastructure supported by MEYS CR (LM2018110). The simulations were performed at the Stanford Nano Shared Facilities supported by the National Science Foundation under award ECCS-1542152. Y.W. would like to acknowledge financial support from Toyota Research Institute.
DOI: 10.7910/dvn/cf6ljr/n3kh8b
title: data file for Study 1_Mizrahi, Lemay, Maniaci, & Reis.tab

description: :unav
DOI: 10.7910/dvn/cf6ljr/bla5cz
title: data file for Study 2_Mizrahi, Lemay, Maniaci, & Reis.tab

description: :unav
DOI: 10.5281/zenodo.3985018
title: LanguageStructure/TuDeT v0.1

description: The pre-release v0.1 contains only a dozen sentences in each of the three languages: Akuntsú, Ka'apor, Mundurukú, and Tupinambá. The documentation is being prepared, including a mapping from UPOS (universal POS) to XPOS (language-specific POS).
DOI: 10.5281/zenodo.3985017
title: LanguageStructure/TuDeT v0.1

description: The pre-release v0.1 contains only a dozen sentences in each of the three languages: Akuntsú, Ka'apor, Mundurukú, and Tupinambá. The documentation is being prepared, including a mapping from UPOS (universal POS) to XPOS (language-specific POS).
DOI: 10.5281/zenodo.3989223
title: WASP-74b transit 2020-07-28

description: CMOS photometry fits frames for exoplanet WASP-74b transit. Location: Archodiko Avias Telescope Celestron EdgeHD 9.25 CMOS Camera: ASI183MM-Pro Filter: R Exposure: 30.0 Dark and Bias frames included.
DOI: 10.5281/zenodo.3989222
title: WASP-74b transit 2020-07-28

description: CMOS photometry fits frames for exoplanet WASP-74b transit. Location: Archodiko Avias Telescope Celestron EdgeHD 9.25 CMOS Camera: ASI183MM-Pro Filter: R Exposure: 30.0 Dark and Bias frames included.
DOI: 10.14272/njqguconxnpkie-uhfffaoysa-l.1
title: Dichlorido[1,1,3,3-Tetramethyl-2-(chinolin-8-yl)guanidin]eisen(II)
title: InChI=1S/C14H18N4.2ClH.Fe/c1-17(2)14(18(3)4)16-12-9-5-7-11-8-6-10-15-13(11)12;;;/h5-10H,1-4H3;2*1H;/q;;;+2/p-2

description: This dataset contains experimental data from a sample (InChI=1S/C14H18N4.2ClH.Fe/c1-17(2)14(18(3)4)16-12-9-5-7-11-8-6-10-15-13(11)12;;;/h5-10H,1-4H3;2*1H;/q;;;+2/p-2). The datasets from the following experiments are available: infrared absorption spectroscopy (IR) mass spectrometry (MS) elemental analysis (EA) X-ray diffraction (XRD)
DOI: 10.14272/njqguconxnpkie-uhfffaoysa-l/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/C14H18N4.2ClH.Fe/c1-17(2)14(18(3)4)16-12-9-5-7-11-8-6-10-15-13(11)12;;;/h5-10H,1-4H3;2*1H;/q;;;+2/p-2

description: dataset for infrared absorption spectroscopy (IR) IR (KBr): ṽ = 3040 (m), 3006 (m), 2949 (m), 2921 (m), 2887 (m), 2864 (m), 2794 (w), 1957 (w), 1922 (w), 1979 (w), 1848 (w), 1782 (w), 1556 (vs, ν(C=Ngua)), 1521 (vs, ν(C=Ngua)), 1499 (vs, ν(C=Ngua)), 1466 (vs), 1441 (s), 1415 (s), 1384 (vs), 1334 (s), 1272 (m), 1234 (m), 1161 (m), 1138 (m), 1101 (m), 1063 (m), 1017 (m), 962 (m), 923 (m), 901 (m), 831 (s), 814 (m), 784 (s), 754 (m), 699 (m), 654 (m), 630 (m), 582 (m), 542 (m), 477 (w), 455 (w), 434 (w) cm-1.
DOI: 10.14272/njqguconxnpkie-uhfffaoysa-l/chmo0000156
title: X-ray diffraction (XRD) ()
title: InChI=1S/C14H18N4.2ClH.Fe/c1-17(2)14(18(3)4)16-12-9-5-7-11-8-6-10-15-13(11)12;;;/h5-10H,1-4H3;2*1H;/q;;;+2/p-2

description: dataset for X-ray diffraction (XRD) Crystal system, space group: Monoclinic, P2(1)/c Unit cell dimensions:a = 7.9617(4) A alpha = 90 deg. b = 14.5303(7) A beta = 100.819(5) deg. c = 14.1157(7) A gamma = 90 deg. Volume: 1603.96(14) A^3 Z, Calculated density: 4, 1.528 Mg/m^3
DOI: 10.14272/njqguconxnpkie-uhfffaoysa-l/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/C14H18N4.2ClH.Fe/c1-17(2)14(18(3)4)16-12-9-5-7-11-8-6-10-15-13(11)12;;;/h5-10H,1-4H3;2*1H;/q;;;+2/p-2

description: dataset for mass spectrometry (MS) HR-MS ESI (+): m/z: calcd: 333.05694 [C14H18ClFeN4]+ found: 333.05618 [C14H18ClFeN4]+.
DOI: 10.14272/njqguconxnpkie-uhfffaoysa-l/chmo0001075
title: elemental analysis (EA) ()
title: InChI=1S/C14H18N4.2ClH.Fe/c1-17(2)14(18(3)4)16-12-9-5-7-11-8-6-10-15-13(11)12;;;/h5-10H,1-4H3;2*1H;/q;;;+2/p-2

description: dataset for elemental analysis (EA) berechnet: 45,56; 4,92; 15,18 gefunden: 45,6; 4,883; 14,83 gefunden: 45,5; 4,742; 15,04 Mittelwert: 45,55; 4,8125; 14,935 Abweichung [%]: -0,01; -0,1075; -0,245
DOI: 10.25592/uhhfdm.1426
title: Hamburg Corpus of Polish in Germany (HamCoPoliG)

description: Audio recordings of German/Polish bilingual and Polish monolingual adults (16-46 years). Recordings of semi-spontaneous data (3 topics) and renarration of a picture story. The Hamburg Corpus of Polish in Germany (HamCoPoliG) was compiled between July 2008 and June 2011 in the research project "Current Polish-German Bilingualism in Germany" (H8, principal investigator: Bernhard Brehmer), part of the Collaborative Research Centre "Multilingalism", funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) and hosted by the University of Hamburg. Czachor, Agnieszka (2012): Polish-German bilingual corpus: collecting and analysing written and spoken data for investigating contact-induced change. Submitted to: Schmidt, Thomas & Wörner, Kai (eds.): Multilingual Corpora and Multilingual Corpus Analysis. Hamburg Studies in Multilingualism (14). Amsterdam: Benjamins. <strong>CLARIN Metadata summary for Hamburg Corpus of Polish in Germany (HamCoPoliG) (CMDI-based)</strong> <strong>Title: </strong>Hamburg Corpus of Polish in Germany (HamCoPoliG)<br> <strong>Description: </strong>Audio recordings of German/Polish bilingual and Polish monolingual adults (16-46 years). Recordings of semi-spontaneous data (3 topics) and renarration of a picture story.<br> <strong>Publication date: </strong>2011-09-02<br> <strong>Data owner: </strong> Bernhard Brehmer, Institut für Slavistik / Von-Melle-Park 6 / D-20146 Hamburg, bernhard.brehmer@uni-hamburg.de<br> <strong>Contributors: </strong> Bernhard Brehmer, Institut für Slavistik / Von-Melle-Park 6 / D-20146 Hamburg, bernhard.brehmer@uni-hamburg.de (compiler)<br> <strong>Project: </strong> H8 "Current Polish-German Bilingualism in Germany", German Research Foundation (DFG)<br> <strong>Keywords: </strong> language attrition, adult bilingualism, cross-sectional data, simultaneous bilingualism, successive bilingualism, child L2 acquisition, adult L2 acquisition, L1 data, EXMARaLDA<br> <strong>Language: </strong> Polish (pol)<br> <strong>Size: </strong> 93 speakers (64 female, 29 male), 360 communications, 358 recordings, 2264 minutes, 358 transcriptions, 294663 words<br> <strong>Temporal Coverage: </strong> 2009-04-17/2010-12-17<br> <strong>Spatial Coverage: </strong> Max-Brauer-Allee 60, 22765 Hamburg, DE; Warszawa, PL<br> <strong>Genre: </strong> discourse<br> <strong>Modality: </strong> spoken
DOI: 10.5281/zenodo.3989601
title: Density-dependent natural selection mediates harvest-induced trait changes

description: Rapid life-history changes caused by size-selective harvesting are often interpreted as a response to direct harvest selection against a large body size. However, similar trait changes may result from a harvest-induced relaxation of natural selection for a large body size via density-dependent selection. Here, we show evidence of such density-dependent selection favouring large-bodied individuals at high population densities, in replicated pond populations of medaka fish. Harvesting, in contrast, selected medaka directly against a large body size and, in parallel, decreased medaka population densities. Five years of harvesting were enough for harvested and unharvested medaka populations to inherit the classically-predicted trait differences, whereby harvested medaka grew slower and matured earlier than unharvested medaka. We demonstrate that this life-history divergence was not driven by direct harvest selection for a smaller body size in harvested populations, but by density-dependent natural selection for a larger body size in unharvested populations.
DOI: 10.5281/zenodo.3989600
title: Density-dependent natural selection mediates harvest-induced trait changes

description: Rapid life-history changes caused by size-selective harvesting are often interpreted as a response to direct harvest selection against a large body size. However, similar trait changes may result from a harvest-induced relaxation of natural selection for a large body size via density-dependent selection. Here, we show evidence of such density-dependent selection favouring large-bodied individuals at high population densities, in replicated pond populations of medaka fish. Harvesting, in contrast, selected medaka directly against a large body size and, in parallel, decreased medaka population densities. Five years of harvesting were enough for harvested and unharvested medaka populations to inherit the classically-predicted trait differences, whereby harvested medaka grew slower and matured earlier than unharvested medaka. We demonstrate that this life-history divergence was not driven by direct harvest selection for a smaller body size in harvested populations, but by density-dependent natural selection for a larger body size in unharvested populations.
DOI: 10.5281/zenodo.3988193
title: Decomposing Effective Radiative Forcing due to Aerosol Cloud Interactions by Global Cloud Regimes

description: This data can be used to reconstruct ERF<sub>ACI</sub> when decomposed by global cloud regimes. Regime centroids are defined in the file ctd_GL_8309_43_o2.asc, provided in Tselioudis, George, et al, 2013.
description: {"references": ["Tselioudis, George, et al. \"Global weather states and their properties from passive and active satellite cloud retrievals.\" Journal of climate 26.19 (2013): 7734-7746."]}
DOI: 10.5517/ccdc.csd.cc22dyq5
title: CCDC 1919077: Experimental Crystal Structure Determination

description: Related Article: Zhangyuan Yan|2019|CSD Communication|||
description: Related Article: Zhangyuan Yan, Jialin Li, Geting Ye, Tao Chen, Meimei Li, Yanmin Liang, Yuhua Long|2020|RSC Advances|10|28560|doi:10.1039/D0RA05532H
DOI: 10.5517/ccdc.csd.cc23nbbg
title: CCDC 1955955: Experimental Crystal Structure Determination

description: Related Article: Gabrielle M. Risica, Veacheslav Vieru, Branford O. Wilkins, Trevor P. Latendresse, Joseph H. Reibenspies, Nattamai S. Bhuvanesh, Gregory P. Wylie, Liviu F. Chibotaru, Michael Nippe|2020|Angew.Chem.,Int.Ed.|59|13335|doi:10.1002/anie.202003759