cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4768071
title: Data for Bradter, Altringham, Kunin, Thom, O'Connell & Benton: Variable ranking and selection with random forest for unbalanced data. Environmental Data Science

description: The data are used in 'Bradter, Altringham, Kunin, Thom, O'Connell & Benton: Variable ranking and selection with random forest for unbalanced data. Environmental Data Science' and are described in the ReadMe file and in the manuscript and Supporting information.
DOI: 10.5281/zenodo.7337856
title: Data for Bradter, Altringham, Kunin, Thom, O'Connell & Benton: Variable ranking and selection with random forest for unbalanced data. Environmental Data Science

description: The data are used in 'Bradter, Altringham, Kunin, Thom, O'Connell & Benton: Variable ranking and selection with random forest for unbalanced data. Environmental Data Science' and are described in the ReadMe file and in the manuscript and Supporting information.
DOI: 10.5281/zenodo.7324628
title: Licitaciones y contrataciones del sector público en España (enero a octubre 2022)

description: Este documento es el resultado de la elaboración de la práctica “¿Cómo podemos capturar los datos de la web?” de la asignatura “Tipología y ciclo de vida de los datos” del " Máster en Ciencia de Datos” de la UOC. La práctica consiste en la selección de una fuente de datos y la recolección de información de la misma mediante técnicas de webscrapping. La información que se va a recolectar es la contratación del sector público en España, para ello se ha utilizado la página: https://contrataciondelestado.es/
DOI: 10.5281/zenodo.7324627
title: Licitaciones y contrataciones del sector público en España (enero a octubre 2022)

description: Este documento es el resultado de la elaboración de la práctica “¿Cómo podemos capturar los datos de la web?” de la asignatura “Tipología y ciclo de vida de los datos” del " Máster en Ciencia de Datos” de la UOC. La práctica consiste en la selección de una fuente de datos y la recolección de información de la misma mediante técnicas de webscrapping. La información que se va a recolectar es la contratación del sector público en España, para ello se ha utilizado la página: https://contrataciondelestado.es/
DOI: 10.6084/m9.figshare.21586857
title: DETERMINATION CUT-OFF POINTS OF BODY FAT DISTRIBUTION FOR DETECTION OF CARDIOMETABOLIC RISK.

description: Methods of easy and quick application that make it possible to know the magnitude of cardiometabolic risk factors in order to plan interventions effectively, minimizing the aggravations of chronic diseases and promoting people's health and quality of life are very important for prevention, diagnosis and treatment, since Brazilian public health cannot access routine exams for the entire population. The aim of this study was to determine cutoff points of body fat distribution to identify cardiometabolic risk factors and metabolic syndrome, as well as to compare their predictive capacity.
DOI: 10.6084/m9.figshare.21586857.v1
title: DETERMINATION CUT-OFF POINTS OF BODY FAT DISTRIBUTION FOR DETECTION OF CARDIOMETABOLIC RISK.

description: Methods of easy and quick application that make it possible to know the magnitude of cardiometabolic risk factors in order to plan interventions effectively, minimizing the aggravations of chronic diseases and promoting people's health and quality of life are very important for prevention, diagnosis and treatment, since Brazilian public health cannot access routine exams for the entire population. The aim of this study was to determine cutoff points of body fat distribution to identify cardiometabolic risk factors and metabolic syndrome, as well as to compare their predictive capacity.
DOI: 10.5281/zenodo.7338008
title: Data e-commerce AND intellectual property

description: Data e-commerce AND intellectual property
DOI: 10.5281/zenodo.7338007
title: Data e-commerce AND intellectual property

description: Data e-commerce AND intellectual property
DOI: 10.5281/zenodo.7336214
title: Evolució del preu de les matèries primeres

description: <strong>Després de la pandèmia del coronavirus, ens trobem en un procés inflacionari que afecta sobretot els preus de les matèries primeres o productes bàsics, els quals reflecteixen l’economia global, altament interconnectada. Especialment l’energia, es tracta d’una gran arma geopolítica que en moments d’inestabilitat pot ser, i està sent, molt rellevant.</strong> <strong>En aquest context, i amb la intenció d’estudiar indirectament l’economia mundial, s'han recollit dades dels preus de les matèries primeres en el rang de període dels últims vint anys.</strong> <strong>Per fer-ho, s’ha escollit la web IndexMundi, en concret per les matèries primeres https://www.indexmundi.com/commodities/, que es tracta d’un portal de dades que reuneix fets i estadístiques de múltiples fonts. </strong>
DOI: 10.5281/zenodo.7336213
title: Evolució del preu de les matèries primeres

description: <strong>Després de la pandèmia del coronavirus, ens trobem en un procés inflacionari que afecta sobretot els preus de les matèries primeres o productes bàsics, els quals reflecteixen l’economia global, altament interconnectada. Especialment l’energia, es tracta d’una gran arma geopolítica que en moments d’inestabilitat pot ser, i està sent, molt rellevant.</strong> <strong>En aquest context, i amb la intenció d’estudiar indirectament l’economia mundial, s'han recollit dades dels preus de les matèries primeres en el rang de període dels últims vint anys.</strong> <strong>Per fer-ho, s’ha escollit la web IndexMundi, en concret per les matèries primeres https://www.indexmundi.com/commodities/, que es tracta d’un portal de dades que reuneix fets i estadístiques de múltiples fonts. </strong>
DOI: 10.5517/ccdc.csd.cc285j66
title: CCDC 2090677: Experimental Crystal Structure Determination

description: Related Article: Maddalen Agirre, Tamara Bello, Jinxiu Zhou, María de Gracia Retamosa, Fernando P. Cossío|2022|J.Org.Chem.|87|14819|doi:10.1021/acs.joc.2c01230
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.cc285p8f
title: CCDC 2090834: Experimental Crystal Structure Determination

description: Related Article: Maddalen Agirre, Tamara Bello, Jinxiu Zhou, María de Gracia Retamosa, Fernando P. Cossío|2022|J.Org.Chem.|87|14819|doi:10.1021/acs.joc.2c01230
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.cc29k2ts
title: CCDC 2131585: Experimental Crystal Structure Determination

description: Related Article: Xiaofeng Qiao, Yuhan Lin, Di Huang, Hongwei Ji, Chuncheng Chen, Wanhong Ma, Jincai Zhao|2022|J.Org.Chem.|87|13627|doi:10.1021/acs.joc.2c01291
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.cc29k2vt
title: CCDC 2131586: Experimental Crystal Structure Determination

description: Related Article: Xiaofeng Qiao, Yuhan Lin, Di Huang, Hongwei Ji, Chuncheng Chen, Wanhong Ma, Jincai Zhao|2022|J.Org.Chem.|87|13627|doi:10.1021/acs.joc.2c01291
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.cc29k2wv
title: CCDC 2131587: Experimental Crystal Structure Determination

description: Related Article: Xiaofeng Qiao, Yuhan Lin, Di Huang, Hongwei Ji, Chuncheng Chen, Wanhong Ma, Jincai Zhao|2022|J.Org.Chem.|87|13627|doi:10.1021/acs.joc.2c01291
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.cc2b0b1r
title: CCDC 2145263: Experimental Crystal Structure Determination

description: Related Article: Laura G. Rodríguez, Ana Delgado, Carlos J. Ciudad, Véronique Noé, Josep Bonjoch, Ben Bradshaw|2022|J.Org.Chem.|87|15693|doi:10.1021/acs.joc.2c02205
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.cc2bb3tm
title: CCDC 2154680: Experimental Crystal Structure Determination

description: Related Article: Basavaraja D, Athira C S, Siddalingeshwar V. D, Ashitha K. T, Sasidhar B. Somappa|2022|J.Org.Chem.|87|13556|doi:10.1021/acs.joc.2c01063
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.cc2bc967
title: CCDC 2155808: Experimental Crystal Structure Determination

description: Related Article: Jiateng Wang, Yunqing Zhuang, Bingxue Yu, Xiaofeng Wang, Gehua Bi, Xin Huang, Weimin Zhang|2022|J.Org.Chem.|87|14870|doi:10.1021/acs.joc.2c01630
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.cc2bfs9w
title: CCDC 2158198: Experimental Crystal Structure Determination

description: Related Article: Rajesh R. Zalte, Alexey A. Festa, Leonid G. Voskressensky, Victor B. Rybakov|2022|CSD Communication|||
description: Related Article: Rajesh R. Zalte, Alexey A. Festa, Pavel V. Raspertov, Olga A. Storozhenko, Nikita E. Golantsov, Victor B. Rybakov, Alexey V. Varlamov, Leonid G. Voskressensky|2022|J.Org.Chem.|87|13663|doi:10.1021/acs.joc.2c01327
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.cc2bpfdw
title: CCDC 2165548: Experimental Crystal Structure Determination

description: Related Article: Victor B. Rybakov, Rajesh R. Zalte, Alexey A. Festa, Leonid G. Voskressensky|2022|CSD Communication|||
description: Related Article: Rajesh R. Zalte, Alexey A. Festa, Pavel V. Raspertov, Olga A. Storozhenko, Nikita E. Golantsov, Victor B. Rybakov, Alexey V. Varlamov, Leonid G. Voskressensky|2022|J.Org.Chem.|87|13663|doi:10.1021/acs.joc.2c01327
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.7338047
title: Self-propping exists in coal seam hydraulic fractures

description: This repository contains data used in "Self-propping exists in coal seam hydraulic fractures" submitted by R Li, CZ Qin, SW Wang, and JC Wang.
DOI: 10.5281/zenodo.7338046
title: Self-propping exists in coal seam hydraulic fractures

description: This repository contains data used in "Self-propping exists in coal seam hydraulic fractures" submitted by R Li, CZ Qin, SW Wang, and JC Wang.
DOI: 10.5281/zenodo.7126443
title: Top Quark Momentum Reconstruction Dataset

description: A set of Monte Carlo simulated events, for the evaluation of top quarks' (and their child particles') momentum reconstruction. The data is saved in HDF5 format, as sets of arrays with keys (as detailed below). There are 1.5M events, with approximately 700k in "train.h5", 200k in "valid.h5", 100k in "test.h5", and 500k in "test_large.h5". There are two versions of the data, the difference between them being whether or not (fast) detector simulation was performed. Those with the detector simulation have the "_delphes" suffix in their filenames. Both versions are produced from the same set of generator-level events. 13 TeV center-of-mass energy, fully hadronic top quark decays, simulated with Pythia8. Events are generated with leading top quark pT in [550,650] GeV. Where applicable, detector simulation is done using Delphes, with the ATLAS detector card. Clustering of particles/objects is done using the anti-kT algorithm, with \(R=0.8\). For the data without detector simulation, the inputs to clustering are the stable, visible final-state particles from Pythia8. For the data with detector simulation, the inputs are calorimeter towers (`Towers`) from Delphes. Each entry corresponds with a single jet. All jets are matched to a parton-level top quark within \(\Delta R =0.8\) Jets are required to have \(|\eta| &lt; 2, \; p_T &gt; 15 \text{ GeV}\) The 200 leading (highest \(p_T\)) jet constituent four-momenta are stored in Cartesian coordinates \((E,p_x,p_y,p_z)\), sorted by decreasing \(p_T\) and with with zero-padding for jets with fewer than 200 constituents. These are stored under the key `Pmu`. The number of non-zero jet constituents is stored under the key `Nobj`. The jet four-momentum is stored in Cartesian coordinates and in cylindrical coordinates \((p_T,\eta,\phi,m)\) under keys `jet_Pmu` and `jet_Pmu_cyl`, respectively. The truth (parton-level) four-momenta of the top quark, and the bottom quark and W-boson to which it decays, are stored in Cartesian coordinates in keys `truth_Pmu_0`, `truth_Pmu_1` and `truth_Pmu_2` respectively. In addition, these are stored together under the key `truth_Pmu`, with the corresponding PDG codes stored under the key `truth_Pdg`.
DOI: 10.5281/zenodo.7338129
title: Anomaly Detection Algorithm Performance

description: Anomaly detection algorithms performance metrics: AUC and Average precision; two sets of 298 + 13 algorithms; 9315 datasets.
DOI: 10.5281/zenodo.7338128
title: Anomaly Detection Algorithm Performance

description: Anomaly detection algorithms performance metrics: AUC and Average precision; two sets of 298 + 13 algorithms; 9315 datasets.
DOI: 10.5281/zenodo.2591594
title: Aversive imagery causes de novo fear conditioning (Open Data and Open Materials)

description: <strong>Open Data and Open Materials of: Mueller, E. M., Sperl, M. F. J., & Panitz, C. (2019). Aversive imagery causes de novo fear conditioning. <em>Psychological Science</em>, <em>30</em>(7), 1001–1015.</strong> In classical fear conditioning, neutral conditioned stimuli (CS) that have been paired with aversive physical unconditioned stimuli eventually trigger fear responses. Here, we test whether aversive mental images systematically paired with a CS may also cause de novo fear learning in the absence of any external aversive stimulation. In two experiments, <em>N</em>=45 and <em>N</em>=41 participants were first trained to produce aversive, neutral, or no imagery in response to one of three different visual imagery cues. In a subsequent imagery-based differential conditioning paradigm, each of the three cues systematically co-terminated with one of three different neutral faces. Although the face that was paired with the aversive imagery cue was never paired with aversive external stimuli or threat-related instructions, participants rated it as more arousing, unpleasant, and threatening and displayed relative fear bradycardia and fear-potentiated startle. These results could be relevant for the development of fear and related disorders without trauma.
description: Open Data and Open Materials of: Mueller, E. M., Sperl, M. F. J., & Panitz, C. (2019). Aversive imagery causes de novo fear conditioning. Psychological Science, 30(7), 1001–1015.
DOI: 10.5281/zenodo.2591593
title: Aversive imagery causes de novo fear conditioning (Open Data and Open Materials)

description: <strong>Open Data and Open Materials of: Mueller, E. M., Sperl, M. F. J., & Panitz, C. (2019). Aversive imagery causes de novo fear conditioning. <em>Psychological Science</em>, <em>30</em>(7), 1001–1015.</strong> In classical fear conditioning, neutral conditioned stimuli (CS) that have been paired with aversive physical unconditioned stimuli eventually trigger fear responses. Here, we test whether aversive mental images systematically paired with a CS may also cause de novo fear learning in the absence of any external aversive stimulation. In two experiments, <em>N</em>=45 and <em>N</em>=41 participants were first trained to produce aversive, neutral, or no imagery in response to one of three different visual imagery cues. In a subsequent imagery-based differential conditioning paradigm, each of the three cues systematically co-terminated with one of three different neutral faces. Although the face that was paired with the aversive imagery cue was never paired with aversive external stimuli or threat-related instructions, participants rated it as more arousing, unpleasant, and threatening and displayed relative fear bradycardia and fear-potentiated startle. These results could be relevant for the development of fear and related disorders without trauma.
description: Open Data and Open Materials of: Mueller, E. M., Sperl, M. F. J., & Panitz, C. (2019). Aversive imagery causes de novo fear conditioning. Psychological Science, 30(7), 1001–1015.
DOI: 10.5517/ccdc.csd.cc2bst65
title: CCDC 2168797: Experimental Crystal Structure Determination

description: Related Article: Chonghe Zhang, Junyi Wang, Zhenyang Lin, Qing Ye|2022|Inorg.Chem.|61|18275|doi:10.1021/acs.inorgchem.2c03111
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.cc2bst76
title: CCDC 2168798: Experimental Crystal Structure Determination

description: Related Article: Chonghe Zhang, Junyi Wang, Zhenyang Lin, Qing Ye|2022|Inorg.Chem.|61|18275|doi:10.1021/acs.inorgchem.2c03111
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.cc2bst87
title: CCDC 2168799: Experimental Crystal Structure Determination

description: Related Article: Chonghe Zhang, Junyi Wang, Zhenyang Lin, Qing Ye|2022|Inorg.Chem.|61|18275|doi:10.1021/acs.inorgchem.2c03111
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.cc2bst98
title: CCDC 2168800: Experimental Crystal Structure Determination

description: Related Article: Chonghe Zhang, Junyi Wang, Zhenyang Lin, Qing Ye|2022|Inorg.Chem.|61|18275|doi:10.1021/acs.inorgchem.2c03111
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.cc2bstb9
title: CCDC 2168801: Experimental Crystal Structure Determination

description: Related Article: Chonghe Zhang, Junyi Wang, Zhenyang Lin, Qing Ye|2022|Inorg.Chem.|61|18275|doi:10.1021/acs.inorgchem.2c03111
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.cc2bstcb
title: CCDC 2168802: Experimental Crystal Structure Determination

description: Related Article: Chonghe Zhang, Junyi Wang, Zhenyang Lin, Qing Ye|2022|Inorg.Chem.|61|18275|doi:10.1021/acs.inorgchem.2c03111
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.cc2bstdc
title: CCDC 2168803: Experimental Crystal Structure Determination

description: Related Article: Chonghe Zhang, Junyi Wang, Zhenyang Lin, Qing Ye|2022|Inorg.Chem.|61|18275|doi:10.1021/acs.inorgchem.2c03111
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.cc2bstfd
title: CCDC 2168804: Experimental Crystal Structure Determination

description: Related Article: Chonghe Zhang, Junyi Wang, Zhenyang Lin, Qing Ye|2022|Inorg.Chem.|61|18275|doi:10.1021/acs.inorgchem.2c03111
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.