cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr35381.v3
title: Survey of Consumer Attitudes and Behavior, January 2006
title: Version 3

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter. The surveys conducted in 2006 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, and other durables. Also explored in this survey were respondents' types of savings and financial investments, loan use, family income, general feelings and retirement planning. Other topics in this series typically include ownership, lease, and use of automobiles, respondents' use of personal computers at home and in the office, and respondents' familiarity with and use of the Internet. Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this survey series is to forecast changes in aggregate consumer behavior.
description: The data are not weighted, however, this collection contains four weight variables; WT (HOUSEHOLD HEAD WEIGHT), WT_HH (HOUSEHOLD WEIGHT), WT_ADHD (ADULT HEAD WEIGHT), and WT_AD (ADULT WEIGHT) that must be used in any analysis. For more information on weights and sampling please visit the Surveys of Consumers Web site, and refer to the documentation on Sample Design, and the section on Sample Weights.
description: National sampling of dwelling units selected by area probability sampling.
description: Datasets: DS1: Survey of Consumer Attitudes and Behavior, January 2006
description: Persons aged 18 years or older living in households with telephones within the United States. Smallest Geographic Unit: Census division
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the P.I. Codebook.Additional information on the Survey of Consumers can be found by visiting the Surveys of Consumers Web site.
DOI: 10.48567/dtte-j705
title:  Year of Polar Prediction in the Southern Hemisphere: WRF forecast model netCDF output from AMPS, 2022.
DOI: 10.5281/zenodo.7562790
title: FINTA/CINTA/GESTA/FIESTA Datasets

description: FINTA/CINTA/GESTA/FIESTA datasets and neural network weights
description: {"references": ["J. H. Legarreta, L. Petit, P.-M. Jodoin, and M. Descoteaux, \"Generative sampling in tractography using autoencoders (GESTA),\" Apr. 2022. https://arxiv.org/abs/2204.10891", "F. Dumais et al., \"FIESTA: Autoencoders for accurate fiber segmentation in tractography,\" Dec. 2022. https://arxiv.org/abs/2212.00143", "J. H. Legarreta et al., \"Filtering in tractography using autoencoders (FINTA),\" Medical Image Analysis, vol. 72, p. 102126, Aug. 2021, doi: https://doi.org/10.1016/j.media.2021.102126.", "J. H. Legarreta, L. Petit, P.-M. Jodoin, and M. Descoteaux, \"Clustering in Tractography Using Autoencoders (CINTA),\" in Computational Diffusion MRI (CDMRI) Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshop, 2022, vol. 13722, pp. 125\u2013136. doi: https://doi.org/10.1007/978-3-031-21206-2_11."]}
DOI: 10.5281/zenodo.7586608
title: Identifying environmentally-comparable cities across the globe for urban ecology studies

description: Defining a comprehensive and quantitative framework for comparing urban areas is a priority for conducting research in urban ecology and related fields. In this study, we use unsupervised learning on a matrix of climate- and human-related features to estimate the number of groups explaining the characteristics of ~6,000 cities across the globe. Using estimates of city-level stability within clusters, we estimate that cities can be clustered in 5–7 clusters, with 6 being the most likely and stable number of groups. Groups of cities are primarily defined by climatic and geographical features (e.g. elevation), with population-level and land use parameters being less relevant for structuring cities. City clusters generally correspond with a continental-based partitioning. However, geographic distances between cities do not necessarily reflect their position in the examined multivariate space. The analytical framework presented in this paper can be extended to accounting for alternative features to describing cities and their characteristics. We implement an online web application for comparing cities across the globe based on the results presented in this study. This application is expected to inform decisions on where to sample populations or species in cities with either similar or divergent climatic conditions.
DOI: 10.5281/zenodo.7562789
title: FINTA/CINTA/GESTA/FIESTA Datasets

description: FINTA/CINTA/GESTA/FIESTA datasets and neural network weights
description: {"references": ["J. H. Legarreta, L. Petit, P.-M. Jodoin, and M. Descoteaux, \"Generative sampling in tractography using autoencoders (GESTA),\" Apr. 2022. https://arxiv.org/abs/2204.10891", "F. Dumais et al., \"FIESTA: Autoencoders for accurate fiber segmentation in tractography,\" Dec. 2022. https://arxiv.org/abs/2212.00143", "J. H. Legarreta et al., \"Filtering in tractography using autoencoders (FINTA),\" Medical Image Analysis, vol. 72, p. 102126, Aug. 2021, doi: https://doi.org/10.1016/j.media.2021.102126.", "J. H. Legarreta, L. Petit, P.-M. Jodoin, and M. Descoteaux, \"Clustering in Tractography Using Autoencoders (CINTA),\" in Computational Diffusion MRI (CDMRI) Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshop, 2022, vol. 13722, pp. 125\u2013136. doi: https://doi.org/10.1007/978-3-031-21206-2_11."]}
DOI: 10.5281/zenodo.7586607
title: Identifying environmentally-comparable cities across the globe for urban ecology studies

description: Defining a comprehensive and quantitative framework for comparing urban areas is a priority for conducting research in urban ecology and related fields. In this study, we use unsupervised learning on a matrix of climate- and human-related features to estimate the number of groups explaining the characteristics of ~6,000 cities across the globe. Using estimates of city-level stability within clusters, we estimate that cities can be clustered in 5–7 clusters, with 6 being the most likely and stable number of groups. Groups of cities are primarily defined by climatic and geographical features (e.g. elevation), with population-level and land use parameters being less relevant for structuring cities. City clusters generally correspond with a continental-based partitioning. However, geographic distances between cities do not necessarily reflect their position in the examined multivariate space. The analytical framework presented in this paper can be extended to accounting for alternative features to describing cities and their characteristics. We implement an online web application for comparing cities across the globe based on the results presented in this study. This application is expected to inform decisions on where to sample populations or species in cities with either similar or divergent climatic conditions.
DOI: 10.6084/m9.figshare.20459118
title: Supplemental file 3b_EC_Biomarker.csv

description: DEG and highly expressed genes in endothelial cells between large and small rat mesenteric arteries
DOI: 10.6084/m9.figshare.20459118.v3
title: Supplemental file 3b_EC_Biomarker.csv

description: DEG and highly expressed genes in endothelial cells between large and small rat mesenteric arteries
DOI: 10.6084/m9.figshare.20459118.v2
title: Supplemental file 3b_EC_Biomarker.csv

description: DEG and highly expressed genes in endothelial cells between large and small rat mesenteric arteries
DOI: 10.6084/m9.figshare.21961172
title: Compiled trait data and serological state of Argentinean birds against WNV and SLEV

description: Imputed data of Argentinean birds tested for WNV and SLEV neutralizing antibodies and their compiled traits by specie (body mass, clutch size, migratory status, diet type, nest type, nest, height)
DOI: 10.6084/m9.figshare.21961172.v1
title: Compiled trait data and serological state of Argentinean birds against WNV and SLEV

description: Imputed data of Argentinean birds tested for WNV and SLEV neutralizing antibodies and their compiled traits by specie (body mass, clutch size, migratory status, diet type, nest type, nest, height)
DOI: 10.6084/m9.figshare.21969425
title: Dataset of WNV, SLEV infection rates and traits by specie

description: Dataframe for NMDS analysis according birds seroprevalence and their ecological and life history traits
DOI: 10.6084/m9.figshare.21969425.v1
title: Dataset of WNV, SLEV infection rates and traits by specie

description: Dataframe for NMDS analysis according birds seroprevalence and their ecological and life history traits
DOI: 10.5281/zenodo.7586357
title: Policies used in "Deep reinforcement learning for the olfactory search POMDP: a quantitative benchmark"

description: Policies used in the paper "Deep reinforcement learning for the olfactory search POMDP: a quantitative benchmark". They can be tested using the software "OTTO-benchmark" available at https://github.com/auroreloisy/otto-benchmark.
DOI: 10.5281/zenodo.7586356
title: Policies used in "Deep reinforcement learning for the olfactory search POMDP: a quantitative benchmark"

description: Policies used in the paper "Deep reinforcement learning for the olfactory search POMDP: a quantitative benchmark". They can be tested using the software "OTTO-benchmark" available at https://github.com/auroreloisy/otto-benchmark.
DOI: 10.6084/m9.figshare.20459142
title: Supplemental file 3_EC_ALL_LgVSmall.csv

description: All genes identified in rat mesenteric artery endothelial cells in large and small mesenteric arteries
DOI: 10.6084/m9.figshare.20459142.v2
title: Supplemental file 3_EC_ALL_LgVSmall.csv

description: All genes identified in rat mesenteric artery endothelial cells in large and small mesenteric arteries
DOI: 10.6084/m9.figshare.20459142.v3
title: Supplemental file 3_EC_ALL_LgVSmall.csv

description: All genes identified in rat mesenteric artery endothelial cells in large and small mesenteric arteries
DOI: 10.5066/p9u6ksbj
title: MODFLOW-NWT simulations of regional groundwater flow under mining and pre-mining scenarios near the Mesabi Iron Range within the St. Louis River Basin, northeastern Minnesota

description: The U.S. Geological Survey developed two steady-state finite-difference regional groundwater-flow models using the MODFLOW-NWT computer code. These models simulate flow in the area of historical iron mining on and around the portion of the Mesabi Iron Range that is in the St. Louis River basin in northeastern Minnesota. The models are composed of 8 layers each; the upper four representing unconsolidated glacial sediments and the lower 4 representing bedrock. Horizontal boundary flows for these models are the results of a 2-dimensional analytic element groundwater-flow model of the entire St. Louis River Basin documented here: https://doi.org/10.3133/sir20195033 and available here: https://doi.org/10.5066/P9KUJ0L3. This archive contains two simulations. The mining model simulates groundwater flow under current iron-mining land use, being calibrated to average hydrologic conditions during calendar years 1995-2015. The premining simulation is identical to the mining simulation except that all iron-mining features are removed. It represents a scenario where modern conditions exist but iron mining does not. The models were used to explore the effects of modern iron mining on hydrology in the St. Louis River basin. This USGS data release contains all of the input and output files for the simulations described in the associated model documentation report (https://doi.org/10.3133/sir20225124).
DOI: 10.5517/ccdc.csd.cc1jxy4j
title: CCDC 1427988: Experimental Crystal Structure Determination

description: Related Article: Yupian Deng, Xuxue Zhang, Chuan Liu, Song Cao|2021|Tetrahedron|81|131804|doi:10.1016/j.tet.2020.131804
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.cc1phd0l
title: CCDC 1563919: Experimental Crystal Structure Determination

description: Related Article: A. N’aitOusidi, M.Y. Ait Itto, A. Auhmani, M. Loubidi, A. Riahi, J.-C. Daran, M. Esseffar, Carol A. Parish|2021|Tetrahedron|78|131830|doi:10.1016/j.tet.2020.131830
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.cc251cj4
title: CCDC 1997315: Experimental Crystal Structure Determination

description: Related Article: Eugeny Ivakhnenko, Vasily Malay, Galina Romanenko, Oleg Demidov, Pavel Knyazev, Andrey Starikov, Vladimir Minkin|2021|Tetrahedron|79|131841|doi:10.1016/j.tet.2020.131841
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.cc251ck5
title: CCDC 1997316: Experimental Crystal Structure Determination

description: Related Article: Eugeny Ivakhnenko, Vasily Malay, Galina Romanenko, Oleg Demidov, Pavel Knyazev, Andrey Starikov, Vladimir Minkin|2021|Tetrahedron|79|131841|doi:10.1016/j.tet.2020.131841
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.cc25r739
title: CCDC 2018320: Experimental Crystal Structure Determination

description: Related Article: Kai-Kai Wang, Yan-Li Li, Ying-Jie Lv, Rong-Hua Shen, Wei Zhao, Rongxiang Chen|2021|Tetrahedron|77|131766|doi:10.1016/j.tet.2020.131766
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.cc25y59m
title: CCDC 2024030: Experimental Crystal Structure Determination

description: Related Article: Subhash P. Chavan, Dinesh B. Kalbhor, Rajesh G. Gonnade|2021|Tetrahedron|80|131773|doi:10.1016/j.tet.2020.131773
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.cc25ymlc
title: CCDC 2024473: Experimental Crystal Structure Determination

description: Related Article: Eugeny Ivakhnenko, Vasily Malay, Galina Romanenko, Oleg Demidov, Pavel Knyazev, Andrey Starikov, Vladimir Minkin|2021|Tetrahedron|79|131841|doi:10.1016/j.tet.2020.131841
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.cc20m6kf
title: CCDC 1865504: Experimental Crystal Structure Determination

description: Related Article: Eugeny Ivakhnenko, Vasily Malay, Galina Romanenko, Oleg Demidov, Pavel Knyazev, Andrey Starikov, Vladimir Minkin|2021|Tetrahedron|79|131841|doi:10.1016/j.tet.2020.131841
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.cc267n48
title: CCDC 2033139: Experimental Crystal Structure Determination

description: Related Article: Maoyuan Zhang, Zengbing Xu, Dabin Shi|2021|Tetrahedron|79|131861|doi:10.1016/j.tet.2020.131861
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.cc269l6b
title: CCDC 2035001: Experimental Crystal Structure Determination

description: Related Article: Stephen G. Davies, Ai M. Fletcher, Paul M. Roberts, Cameron E. Taylor, James E. Thomson|2021|Tetrahedron|79|131860|doi:10.1016/j.tet.2020.131860
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.cc26bkkp
title: CCDC 2035942: Experimental Crystal Structure Determination

description: Related Article: Yuliya F. Polienko, Natalia M. Kuprikova, Dmitriy A. Parkhomenko, Yuriy V. Gatilov, Elena I. Chernyak, Igor A. Kirilyuk|2021|Tetrahedron|81|131915|doi:10.1016/j.tet.2020.131915
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.cc26bklq
title: CCDC 2035943: Experimental Crystal Structure Determination

description: Related Article: Yuliya F. Polienko, Natalia M. Kuprikova, Dmitriy A. Parkhomenko, Yuriy V. Gatilov, Elena I. Chernyak, Igor A. Kirilyuk|2021|Tetrahedron|81|131915|doi:10.1016/j.tet.2020.131915
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.cc26bkmr
title: CCDC 2035944: Experimental Crystal Structure Determination

description: Related Article: Yuliya F. Polienko, Natalia M. Kuprikova, Dmitriy A. Parkhomenko, Yuriy V. Gatilov, Elena I. Chernyak, Igor A. Kirilyuk|2021|Tetrahedron|81|131915|doi:10.1016/j.tet.2020.131915
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.cc26bkns
title: CCDC 2035945: Experimental Crystal Structure Determination

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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.cc26h4pk
title: CCDC 2040348: Experimental Crystal Structure Determination

description: Related Article: Conor Dean, Stefan Roesner, Sundaram Rajkumar, Guy J. Clarkson, Matthew Jones, Michael Shipman|2021|Tetrahedron|79|131836|doi:10.1016/j.tet.2020.131836
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.cc26h4ql
title: CCDC 2040349: Experimental Crystal Structure Determination

description: Related Article: Conor Dean, Stefan Roesner, Sundaram Rajkumar, Guy J. Clarkson, Matthew Jones, Michael Shipman|2021|Tetrahedron|79|131836|doi:10.1016/j.tet.2020.131836
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.cc26h4rm
title: CCDC 2040350: Experimental Crystal Structure Determination

description: Related Article: Conor Dean, Stefan Roesner, Sundaram Rajkumar, Guy J. Clarkson, Matthew Jones, Michael Shipman|2021|Tetrahedron|79|131836|doi:10.1016/j.tet.2020.131836
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.cc26h4sn
title: CCDC 2040351: Experimental Crystal Structure Determination

description: Related Article: Conor Dean, Stefan Roesner, Sundaram Rajkumar, Guy J. Clarkson, Matthew Jones, Michael Shipman|2021|Tetrahedron|79|131836|doi:10.1016/j.tet.2020.131836
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.