cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2b6ns0
title: CCDC 2151362: Experimental Crystal Structure Determination

description: Related Article: Björn H. Greijer, Gustav Nestor, Jan E. Eriksson, Gulaim A. Seisenbaeva, Vadim G. Kessler|2022|Dalton Trans.|51|9511|doi:10.1039/D2DT00717G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b6nt1
title: CCDC 2151363: Experimental Crystal Structure Determination

description: Related Article: Björn H. Greijer, Gustav Nestor, Jan E. Eriksson, Gulaim A. Seisenbaeva, Vadim G. Kessler|2022|Dalton Trans.|51|9511|doi:10.1039/D2DT00717G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b6nv2
title: CCDC 2151364: Experimental Crystal Structure Determination

description: Related Article: Björn H. Greijer, Gustav Nestor, Jan E. Eriksson, Gulaim A. Seisenbaeva, Vadim G. Kessler|2022|Dalton Trans.|51|9511|doi:10.1039/D2DT00717G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.5794683
title: Four angle fused dataset for Ascidian embryo imaged via light sheet

description: Original dataset imaged and published here: <pre>DOI: 10.6084/m9.figshare.8235473.v1</pre> This dataset is provided as Raw dataset for training deep neural networks for segmentation tasks. The binary masks and the integer labels are provided separately.
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
description: {"references": ["Patrick Lemaire, Astec-Pm7 (Wild type Phallusia mammillata embryo, live SPIM imaging, stages 7-12), year = 2020"]}
DOI: 10.5281/zenodo.5794682
title: Four angle fused dataset for Ascidian embryo imaged via light sheet

description: Original dataset imaged and published here: <pre>DOI: 10.6084/m9.figshare.8235473.v1</pre> This dataset is provided as Raw dataset for training deep neural networks for segmentation tasks. The binary masks and the integer labels are provided separately.
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
description: {"references": ["Patrick Lemaire, Astec-Pm7 (Wild type Phallusia mammillata embryo, live SPIM imaging, stages 7-12), year = 2020"]}
DOI: 10.5281/zenodo.6676701
title: 3DPC of Chandebrito (Spain)

description: Location: here From this publication: https://link.springer.com/article/10.1007/s10346-019-01208-5 The 3D model of the area was obtained by using a technique that combines aerial photogrammetry from a UAS (González-Jorge et al. 2016) to obtain a complete point cloud of the study area and a terrestrial survey from a ground-based LiDAR to obtain a better accuracy of the critical areas, such as the unstable blocks. Some targets were added to the structure to facilitate the registration process. The photogrammetric flights were made using a Phantom 3 UAS equipped with a 12 Mpx digital camera (f/2.8, 94°). Flight height was about 87.5 m. 220 photographs were taken for the photogrammetric restitution, a step carried out with the photogrammetric suite Photoscan. After the restitution, the software allows exporting a 3D point cloud. It was levelled and scaled using a Global Navigation Satellite System Trimble R8, with which a horizontal and vertical accuracy of 1.97 and 3.24 cm, respectively, was obtained. The photogrammetric flights covered an area of 0.102 km2, with a ground resolution of 3.59 cm/px and a reprojection error of 0.886 px. With this process, a point cloud with 29 million points was obtained. LiDAR data acquisition was done using six scan stations to provide a coverage of the unstable blocks area. A Faro Focus 330X LiDAR was used for this survey, which has a resolution of 2 mm at 25 m (González-Jorge et al. 2018). Each point cloud has between 9 and 15 million points. Targets on the structure provide control points for the registration of the point clouds and for joining all the data in a single coordinate reference system. After registration, this resulting point cloud is again merged together with that one provided by the UAS. The point cloud provided by the UAS was used as reference because it was the most complete one. Distance histograms between the points of the reference point cloud and each LiDAR point cloud registered are provided by Fig. 3.1 in the Online Resource 1. As can be seen, the registration error is below 6 cm in almost all the registered LiDAR point clouds. Finally, a global and detailed point cloud from the structure and its surroundings was obtained (Fig. 2)
DOI: 10.5281/zenodo.6676700
title: 3DPC of Chandebrito (Spain)

description: Location: here From this publication: https://link.springer.com/article/10.1007/s10346-019-01208-5 The 3D model of the area was obtained by using a technique that combines aerial photogrammetry from a UAS (González-Jorge et al. 2016) to obtain a complete point cloud of the study area and a terrestrial survey from a ground-based LiDAR to obtain a better accuracy of the critical areas, such as the unstable blocks. Some targets were added to the structure to facilitate the registration process. The photogrammetric flights were made using a Phantom 3 UAS equipped with a 12 Mpx digital camera (f/2.8, 94°). Flight height was about 87.5 m. 220 photographs were taken for the photogrammetric restitution, a step carried out with the photogrammetric suite Photoscan. After the restitution, the software allows exporting a 3D point cloud. It was levelled and scaled using a Global Navigation Satellite System Trimble R8, with which a horizontal and vertical accuracy of 1.97 and 3.24 cm, respectively, was obtained. The photogrammetric flights covered an area of 0.102 km2, with a ground resolution of 3.59 cm/px and a reprojection error of 0.886 px. With this process, a point cloud with 29 million points was obtained. LiDAR data acquisition was done using six scan stations to provide a coverage of the unstable blocks area. A Faro Focus 330X LiDAR was used for this survey, which has a resolution of 2 mm at 25 m (González-Jorge et al. 2018). Each point cloud has between 9 and 15 million points. Targets on the structure provide control points for the registration of the point clouds and for joining all the data in a single coordinate reference system. After registration, this resulting point cloud is again merged together with that one provided by the UAS. The point cloud provided by the UAS was used as reference because it was the most complete one. Distance histograms between the points of the reference point cloud and each LiDAR point cloud registered are provided by Fig. 3.1 in the Online Resource 1. As can be seen, the registration error is below 6 cm in almost all the registered LiDAR point clouds. Finally, a global and detailed point cloud from the structure and its surroundings was obtained (Fig. 2)
DOI: 10.5281/zenodo.5227316
title: Noise to void model and results of denoising + segmentation using VollSeg

description: Noise to void model and results of denoising + segmentation using VollSeg
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5227315
title: Noise to void model and results of denoising + segmentation using VollSeg

description: Noise to void model and results of denoising + segmentation using VollSeg
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5211291
title: U-Net model trained on Ascadian embryo dataset of light sheet microscope

description: U-Net model trained using CARE package for doing semantic segmentation of Ascadian embryo
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5211290
title: U-Net model trained on Ascadian embryo dataset of light sheet microscope

description: U-Net model trained using CARE package for doing semantic segmentation of Ascadian embryo
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5227301
title: U-Net model for Arabidopsis segmentation in 3D

description: U-Net segmentation model to be used in Vollseg notebooks and scripts for 3D segmentation of Arabidopsis membrane datasets in 3D.
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5227300
title: U-Net model for Arabidopsis segmentation in 3D

description: U-Net segmentation model to be used in Vollseg notebooks and scripts for 3D segmentation of Arabidopsis membrane datasets in 3D.
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5227304
title: StarDist model for Arabidopsis using Resnet backbone

description: Stardist model for Arabidopsis using Resnet backbone to be used in conjugation with U-Net model in vollseg setting
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5227303
title: StarDist model for Arabidopsis using Resnet backbone

description: Stardist model for Arabidopsis using Resnet backbone to be used in conjugation with U-Net model in vollseg setting
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5217410
title: Test dataset with ground truth for segmentation models testing

description: Test dataset with ground truth for segmentation models testing
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5217409
title: Test dataset with ground truth for segmentation models testing

description: Test dataset with ground truth for segmentation models testing
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5217367
title: Binary segmentation images for 3D segmentation model training

description: Binary segmentation images for 3D segmentation model training
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.5281/zenodo.5217366
title: Binary segmentation images for 3D segmentation model training

description: Binary segmentation images for 3D segmentation model training
description: Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.
DOI: 10.25318/3310050501-eng
title: Business or organization expected impacts of labour-related obstacles over the next three months, second quarter of 2022

description: Business or organization expected impacts of labour-related obstacles over the next three months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2022.
DOI: 10.25318/3310050501-fra
title: Répercussions prévues des obstacles en matière de main-d’œuvre sur l'entreprise ou l'organisme au cours des trois prochains mois, deuxième trimestre de 2022

description: Répercussions prévues des obstacles en matière de main-d’œuvre sur l'entreprise ou l'organisme au cours des trois prochains mois, selon le Système de classification des industries de l’Amérique du Nord (SCIAN), l’effectif de l’entreprise, le type d’entreprise, l’activité de l'entreprise et le propriétaire majoritaire, deuxième trimestre de 2022.
DOI: 10.25318/3310050601-eng
title: Business or organization challenges with recruiting and retaining staff compared with 12 months ago, second quarter of 2022

description: Business or organization challenges with recruiting and retaining staff compared with 12 months ago, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2022.
DOI: 10.25318/3310050601-fra
title: Défis que l'entreprise ou l'organisme doit relever pour recruter du personnel et le maintenir en poste par rapport à il y a 12 mois, deuxième trimestre de 2022

description: Défis que l'entreprise ou l'organisme doit relever pour recruter du personnel et le maintenir en poste par rapport à il y a 12 mois, selon le Système de classification des industries de l’Amérique du Nord (SCIAN), l’effectif de l’entreprise, le type d’entreprise, l’activité de l'entreprise et le propriétaire majoritaire, deuxième trimestre de 2022.
DOI: 10.25612/p2bmw83ov21p
title: State of Housing (2022) - Data Archive

description: The State of Housing Report is a collection of data from various sources used in the 2022 Kinder Institute State of Housing Report
DOI: 10.25318/3310050701-eng
title: Business or organization expectations of how long supply chain obstacles will last, second quarter of 2022

description: Business or organization expectations of how long various obstacles will last, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2022.
DOI: 10.25318/3310050701-fra
title: Attentes de l'entreprise ou de l'organisme quant à la durée des obstacles liés à la chaîne d'approvisionnement, deuxième trimestre de 2022

description: Attentes de l'entreprise ou de l'organisme quant à la durée des obstacles liés à la chaîne d'approvisionnement, selon le Système de classification des industries de l’Amérique du Nord (SCIAN), l’effectif de l’entreprise, le type d’entreprise, l’activité de l'entreprise et le propriétaire majoritaire, deuxième trimestre de 2022.
DOI: 10.25318/3310050801-eng
title: Business or organization change in supply chain challenges over the last three months, second quarter of 2022

description: Business or organization change in supply chain challenges over the last three months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2022.
DOI: 10.25318/3310050801-fra
title: Manière dont les défis liés à la chaîne d’approvisionnement auxquels ont été confrontés les entreprises ou les organismes ont changé au cours des trois derniers mois, deuxième trimestre de 2022

description: Manière dont les défis liés à la chaîne d’approvisionnement auxquels ont été confrontés les entreprises ou les organismes ont changé au cours des trois derniers mois, selon le Système de classification des industries de l’Amérique du Nord (SCIAN), l’effectif de l’entreprise, le type d’entreprise, l’activité de l'entreprise et le propriétaire majoritaire, deuxième trimestre de 2022.
DOI: 10.25318/3310050901-eng
title: Business or organization expectations of change in supply chain challenges over the next three months, second quarter of 2022

description: Business or organization expectations of change in supply chain challenges over the next three months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2022.
DOI: 10.25318/3310050901-fra
title: Attentes des entreprises ou des organismes quant à la manière dont les défis liés à la chaîne d’approvisionnement changeront au cours des trois prochains mois, deuxième trimestre de 2022

description: Attentes des entreprises ou des organismes quant à la manière dont les défis liés à la chaîne d’approvisionnement changeront au cours des trois prochains mois, selon le Système de classification des industries de l’Amérique du Nord (SCIAN), l’effectif de l’entreprise, le type d’entreprise, l’activité de l'entreprise et le propriétaire majoritaire, deuxième trimestre de 2022.
DOI: 10.5281/zenodo.6678131
title: Metadata for Geospatial Mapping Tools, Indicators and Metrics for Fish Habitat in the Pacific Region

description: Metadata on geospatial tools, indicators, metrics and scoring benchmarks useful for assessing the status of threats to freshwater fish habitat in British Columbia
DOI: 10.5281/zenodo.6678130
title: Metadata for Geospatial Mapping Tools, Indicators and Metrics for Fish Habitat in the Pacific Region

description: Metadata on geospatial tools, indicators, metrics and scoring benchmarks useful for assessing the status of threats to freshwater fish habitat in British Columbia
DOI: 10.6084/m9.figshare.3761562.v2256
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.3886/e173183
title: Replication Data for: Suddenly Married: Joint Taxation and the Labor Supply of Same-Sex Married Couples After U.S. v. Windsor

description: Joint taxation can exacerbate the deadweight loss of taxation due to labor supply responses, but evidence is scarce. I estimate the labor supply effects and efficiency costs of joint taxation in the United States by leveraging tax variation created by federal same-sex marriage recognition following the 2013 United States v. Windsor Supreme Court ruling. I estimate significant compensated elasticities along the extensive, but not intensive, margin among both higher and lower earners. My findings suggest that joint taxation is less efficient and generates less tax revenue than individual taxation, and that lowering tax rates for secondary earners could improve efficiency.<br>
DOI: 10.3886/e173183v1
title: Replication Data for: Suddenly Married: Joint Taxation and the Labor Supply of Same-Sex Married Couples After U.S. v. Windsor

description: Joint taxation can exacerbate the deadweight loss of taxation due to labor supply responses, but evidence is scarce. I estimate the labor supply effects and efficiency costs of joint taxation in the United States by leveraging tax variation created by federal same-sex marriage recognition following the 2013 United States v. Windsor Supreme Court ruling. I estimate significant compensated elasticities along the extensive, but not intensive, margin among both higher and lower earners. My findings suggest that joint taxation is less efficient and generates less tax revenue than individual taxation, and that lowering tax rates for secondary earners could improve efficiency.<br>
DOI: 10.25919/ra2a-a306
title: Parkes observations for project P1153 semester 2022APRS_07

description: The ThunderKAT and MeerTRAP teams at the MeerKAT radio telescope have discovered a slow, pulsating radio source in the image and time domain data. We estimate a best fit period P = 75.88 s and period derivative Pdot = 2.9 x 10^-13 s/s. The source is seen to lie in the P-Pdot pulsar parameter phase space "death valley" where radio emission from neutron stars is not expected according to models in the literature. Single pulse analysis of MeerKAT data in the L- and UHF-bands reveals remarkable and unusual spectro-temporal properties, quite unlike anything seen in known radio neutron stars, with some pulses showing quasi-periodic sub-pulse components. We request 9 hours in the April 2022 semester to utilise the excellent ultra wide-band sensitivity of Parkes to study the pulse shape evolution and spectro-tempo-polarimetric properties of the source, probe the broadband nature and evolution of the sub-pulse components, and investigate any radius-to-frequency mapping, allowing us to characterise and/or distinguish it from other types of known neutron stars.
DOI: 10.34740/kaggle/dsv/3842889
title: Country Data
DOI: 10.5281/zenodo.6678327
title: Sensitivity_Data_NCI60_PSet

description: Pre-processed drug sensitivity data for NCI60 PSet.
DOI: 10.5281/zenodo.6678326
title: Sensitivity_Data_NCI60_PSet

description: Pre-processed drug sensitivity data for NCI60 PSet.
DOI: 10.5517/ccdc.csd.cc2b953y
title: CCDC 2153759: Experimental Crystal Structure Determination

description: Related Article: Pedro Delgado, Javier D. Martin-Romera, Cristina Perona, Rebecca Vismara, Simona Galli, Carmen R. Maldonado, Francisco J. Carmona, Natalia M. Padial, Jorge A. R. Navarro|2022|ACS Applied Materials and Interfaces|14|26501|doi:10.1021/acsami.2c06025
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bd5xv
title: CCDC 2156667: Experimental Crystal Structure Determination

description: Related Article: Björn H. Greijer, Gustav Nestor, Jan E. Eriksson, Gulaim A. Seisenbaeva, Vadim G. Kessler|2022|Dalton Trans.|51|9511|doi:10.1039/D2DT00717G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bkl1k
title: CCDC 2161848: Experimental Crystal Structure Determination

description: Related Article: Chengkun Yi, Lingfeng Wu, Liang Chen, Wenshan Ren|2022|Dalton Trans.|51|9241|doi:10.1039/D2DT00996J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.