cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5558087
title: Analysis of Whistler-Mode and Z-Mode Emission in the Juno Primary Mission

description: This is the supporting data set for the paper by the same title published in AGU JGR Space Physics. <strong>Key Points:</strong> Jovian whistler-mode chorus and Z-mode intensity distributions are surveyed and analyzed at the end of the Juno primary mission Bursty low frequency whistler mode emission implies electrons energies exceeding 100 keV Jovian whistler mode chorus and Z-mode intensity are parametrically fit to frequency, M-shell, and mag-latitude. <strong>Abstract</strong> At the end of the Juno primary mission we report observations of whistler mode chorus and Z-mode emission. The Juno orbits are evolving and much better coverage of the whistler mode chorus source region has resulted since the earlier surveys. Bursty chorus emission extending to ~30° latitude and to frequencies less than the lower hybrid frequency near the source region imply high electron energies (&gt;100 keV). Average chorus intensity levels peak at ~10-3 nT2 near M-shell of 8-9 and magnetic latitude of ~5°. Z-mode emission is identified at higher latitudes generally near and inward of the Io torus with intensity levels as much as two orders of magnitude higher than Z-mode emissions observed at Saturn. Inferred source regions for the Z-mode are consistent with the inner edge of the Io torus and with auroral field lines that may also support Jovian kilometric and decametric emission. Parametric fitting functions are evaluated for both whistler mode chorus and Z-mode, describing wave intensity as a function of frequency, magnetic latitude, and M-shell. Both whistler mode and Z-mode waves may have significant impact on electron scattering and acceleration at Jupiter as recent models indicate.
DOI: 10.5281/zenodo.5663848
title: Analysis of Whistler-Mode and Z-Mode Emission in the Juno Primary Mission

description: This is the supporting data set for the paper by the same title published in AGU JGR Space Physics, 10.1029/2021JA029885 <strong>Key Points:</strong> Jovian whistler-mode chorus and Z-mode intensity distributions are surveyed and analyzed at the end of the Juno primary mission Bursty low frequency whistler mode emission implies electrons energies exceeding 100 keV Jovian whistler mode chorus and Z-mode intensity are parametrically fit to frequency, M-shell, and mag-latitude. <strong>Abstract</strong> At the end of the Juno primary mission we report observations of whistler mode chorus and Z-mode emission. The Juno orbits are evolving and much better coverage of the whistler mode chorus source region has resulted since the earlier surveys. Bursty chorus emission extending to ~30° latitude and to frequencies less than the lower hybrid frequency near the source region imply high electron energies (&gt;100 keV). Average chorus intensity levels peak at ~10<sup>-3</sup> nT<sup>2</sup> near M-shell of 8-9 and magnetic latitude of ~5°. Z-mode emission is identified at higher latitudes generally near and inward of the Io torus with intensity levels as much as two orders of magnitude higher than Z-mode emissions observed at Saturn. Inferred source regions for the Z-mode are consistent with the inner edge of the Io torus and with auroral field lines that may also support Jovian kilometric and decametric emission. Parametric fitting functions are evaluated for both whistler mode chorus and Z-mode, describing wave intensity as a function of frequency, magnetic latitude, and M-shell. Both whistler mode and Z-mode waves may have significant impact on electron scattering and acceleration at Jupiter as recent models indicate.
description: Version 1.1.0 contains updated file descriptions and an additional data file.
DOI: 10.5281/zenodo.5558086
title: Analysis of Whistler-Mode and Z-Mode Emission in the Juno Primary Mission

description: This is the supporting data set for the paper by the same title published in AGU JGR Space Physics, 10.1029/2021JA029885 <strong>Key Points:</strong> Jovian whistler-mode chorus and Z-mode intensity distributions are surveyed and analyzed at the end of the Juno primary mission Bursty low frequency whistler mode emission implies electrons energies exceeding 100 keV Jovian whistler mode chorus and Z-mode intensity are parametrically fit to frequency, M-shell, and mag-latitude. <strong>Abstract</strong> At the end of the Juno primary mission we report observations of whistler mode chorus and Z-mode emission. The Juno orbits are evolving and much better coverage of the whistler mode chorus source region has resulted since the earlier surveys. Bursty chorus emission extending to ~30° latitude and to frequencies less than the lower hybrid frequency near the source region imply high electron energies (&gt;100 keV). Average chorus intensity levels peak at ~10<sup>-3</sup> nT<sup>2</sup> near M-shell of 8-9 and magnetic latitude of ~5°. Z-mode emission is identified at higher latitudes generally near and inward of the Io torus with intensity levels as much as two orders of magnitude higher than Z-mode emissions observed at Saturn. Inferred source regions for the Z-mode are consistent with the inner edge of the Io torus and with auroral field lines that may also support Jovian kilometric and decametric emission. Parametric fitting functions are evaluated for both whistler mode chorus and Z-mode, describing wave intensity as a function of frequency, magnetic latitude, and M-shell. Both whistler mode and Z-mode waves may have significant impact on electron scattering and acceleration at Jupiter as recent models indicate.
description: Version 1.1.0 contains updated file descriptions and an additional data file.
DOI: 10.6084/m9.figshare.22241608
title: 22Rv1_AR_1nM-DHT_rep1

description: 22Rv1_AR_1nM-DHT_rep1
DOI: 10.6084/m9.figshare.22241608.v1
title: 22Rv1_AR_1nM-DHT_rep1

description: 22Rv1_AR_1nM-DHT_rep1
DOI: 10.6084/m9.figshare.22241617
title: 22Rv1_AR_1nM-DHT_rep2

description: 22Rv1_AR_1nM-DHT_rep2
DOI: 10.6084/m9.figshare.22241617.v1
title: 22Rv1_AR_1nM-DHT_rep2

description: 22Rv1_AR_1nM-DHT_rep2
DOI: 10.5517/ccdc.csd.cc2bzhd7
title: CCDC 2174259: Experimental Crystal Structure Determination

description: Related Article: xianliechen chen|2022|CSD Communication|||
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.cc2djt0s
title: CCDC 2220685: Experimental Crystal Structure Determination

description: Related Article: Mohabul Mondal|2022|CSD Communication|||
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.cc2djtf6
title: CCDC 2220698: Experimental Crystal Structure Determination

description: Related Article: Rafael Stieler, Diogo Seibert Lüdtke, Eric Francis Lopes|2022|CSD Communication|||
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.cc2djtrj
title: CCDC 2220708: Experimental Crystal Structure Determination

description: Related Article: Tingyung Hsu|2022|CSD Communication|||
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.cc2djxql
title: CCDC 2220800: Experimental Crystal Structure Determination

description: Related Article: Abdelkader Tabbiche|2022|CSD Communication|||
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.cc2dk1qr
title: CCDC 2220924: Experimental Crystal Structure Determination

description: Related Article: Callum L. Paisley-Gunn, Adam Stewart, Jonathan M. White|2022|CSD Communication|||
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.cc2dk4qv
title: CCDC 2221017: Experimental Crystal Structure Determination

description: Related Article: Ren Pengzhou|2022|CSD Communication|||
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.cc2dk6z5
title: CCDC 2221087: Experimental Crystal Structure Determination

description: Related Article: Ren Pengzhou|2022|CSD Communication|||
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.cc2dk74c
title: CCDC 2221092: Experimental Crystal Structure Determination

description: Related Article: Ren Pengzhou|2022|CSD Communication|||
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.cc2dk7mv
title: CCDC 2221107: Experimental Crystal Structure Determination

description: Related Article: Ren Pengzhou|2022|CSD Communication|||
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: 10.6084/m9.figshare.22241629
title: 22Rv1_AR_100nM-DHT_rep1

description: 22Rv1_AR_100nM-DHT_rep1
DOI: 10.6084/m9.figshare.22241629.v1
title: 22Rv1_AR_100nM-DHT_rep1

description: 22Rv1_AR_100nM-DHT_rep1
DOI: 10.6084/m9.figshare.22241635
title: 22Rv1_AR_100nM-DHT_rep2

description: 22Rv1_AR_100nM-DHT_rep2
DOI: 10.6084/m9.figshare.22241635.v1
title: 22Rv1_AR_100nM-DHT_rep2

description: 22Rv1_AR_100nM-DHT_rep2
DOI: 10.6084/m9.figshare.22241641
title: 22Rv1_AR_ENZ3w_1nM-DHT_rep1

description: 22Rv1_AR_ENZ3w_1nM-DHT_rep1
DOI: 10.6084/m9.figshare.22241641.v1
title: 22Rv1_AR_ENZ3w_1nM-DHT_rep1

description: 22Rv1_AR_ENZ3w_1nM-DHT_rep1
DOI: 10.6084/m9.figshare.22241647.v1
title: 22Rv1_AR_ENZ3w_1nM-DHT_rep2

description: 22Rv1_AR_ENZ3w_1nM-DHT_rep2
DOI: 10.6084/m9.figshare.22241647
title: 22Rv1_AR_ENZ3w_1nM-DHT_rep2

description: 22Rv1_AR_ENZ3w_1nM-DHT_rep2
DOI: 10.6084/m9.figshare.22241659
title: 22Rv1_AR_EtOH_rep1

description: 22Rv1_AR_EtOH_rep1
DOI: 10.6084/m9.figshare.22241659.v1
title: 22Rv1_AR_EtOH_rep1

description: 22Rv1_AR_EtOH_rep1
DOI: 10.6084/m9.figshare.22241662.v1
title: 22Rv1_AR_EtOH_rep2

description: 22Rv1_AR_EtOH_rep2
DOI: 10.6084/m9.figshare.22241662
title: 22Rv1_AR_EtOH_rep2

description: 22Rv1_AR_EtOH_rep2
DOI: 10.34740/kaggle/dsv/5135074
title: Nifty-50 & Nifty Future 50 Dataset
DOI: 10.6084/m9.figshare.22148957
title: 3rdpub-data.csv

description: Data was collected from first-year students in the faculty of information technology and communication studies of the University of Professional Studies in Accra to determine the motivators students' behavioural intentions and actual use of learning management systems.
DOI: 10.6084/m9.figshare.22148957.v1
title: 3rdpub-data.csv

description: Data was collected from first-year students in the faculty of information technology and communication studies of the University of Professional Studies in Accra to determine the motivators students' behavioural intentions and actual use of learning management systems.
DOI: 10.6084/m9.figshare.22241665
title: 22Rv1_FOXA1_Dex_rep1

description: 22Rv1_FOXA1_Dex_rep1
DOI: 10.6084/m9.figshare.22241665.v1
title: 22Rv1_FOXA1_Dex_rep1

description: 22Rv1_FOXA1_Dex_rep1
DOI: 10.5519/qd.64t7tjhj
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (2872 records)
DOI: 10.6084/m9.figshare.22241674
title: 22Rv1_FOXA1_Dex_rep2

description: 22Rv1_FOXA1_Dex_rep2
DOI: 10.6084/m9.figshare.22241674.v1
title: 22Rv1_FOXA1_Dex_rep2

description: 22Rv1_FOXA1_Dex_rep2
DOI: 10.5281/zenodo.7712853
title: Datasets and codes for De Lorm et al. 2023: Optimising the automated recognition of individual animals to support population monitoring

description: Reliable estimates of population size and demographic rates are central to assessing the status of threatened species. However, obtaining individual-based demographic rates requires long-term data, which is often costly and difficult to collect. Photographic data offer an inexpensive, non-invasive method for individual-based monitoring of species with unique markings, and could therefore increase available demographic data for many species. However, selecting suitable images and identifying individuals from photographic catalogues is prohibitively time-consuming. Automated identification software can significantly speed up this process. Nevertheless, automated methods for selecting suitable images are lacking, as are studies comparing the performance of the most prominent identification software packages. In this study, we develop a framework that automatically selects images suitable for individual identification, and compare the performance of three commonly used identification software packages; Hotspotter, I<sup>3</sup>S-Pattern, and WildID. As a case study, we consider the African wild dog <em>Lycaon pictus</em>, a species whose conservation is limited by a lack of cost-effective large-scale monitoring. To evaluate intra-specific variation in the performance of software packages, we compare identification accuracy between two populations (in Kenya and Zimbabwe) that have markedly different coat colouration patterns. The process of selecting suitable images was automated using Convolutional Neural Nets that crop individuals from images, filter out unsuitable images, separate left and right flanks, and remove image backgrounds. Hotspotter had the highest image-matching accuracy for both populations. However, the accuracy was significantly lower for the Kenyan population (62%), compared to the Zimbabwean population (88%). Our automated image pre-processing has immediate application for expanding monitoring based on image-matching. However, the difference in accuracy between populations highlights that population-specific detection rates are likely and may influence certainty in derived statistics. For species such as the African wild dog, where monitoring is both challenging and expensive, automated individual recognition could greatly expand and expedite conservation efforts.
DOI: 10.5281/zenodo.7712852
title: Datasets and codes for De Lorm et al. 2023: Optimising the automated recognition of individual animals to support population monitoring

description: Reliable estimates of population size and demographic rates are central to assessing the status of threatened species. However, obtaining individual-based demographic rates requires long-term data, which is often costly and difficult to collect. Photographic data offer an inexpensive, non-invasive method for individual-based monitoring of species with unique markings, and could therefore increase available demographic data for many species. However, selecting suitable images and identifying individuals from photographic catalogues is prohibitively time-consuming. Automated identification software can significantly speed up this process. Nevertheless, automated methods for selecting suitable images are lacking, as are studies comparing the performance of the most prominent identification software packages. In this study, we develop a framework that automatically selects images suitable for individual identification, and compare the performance of three commonly used identification software packages; Hotspotter, I<sup>3</sup>S-Pattern, and WildID. As a case study, we consider the African wild dog <em>Lycaon pictus</em>, a species whose conservation is limited by a lack of cost-effective large-scale monitoring. To evaluate intra-specific variation in the performance of software packages, we compare identification accuracy between two populations (in Kenya and Zimbabwe) that have markedly different coat colouration patterns. The process of selecting suitable images was automated using Convolutional Neural Nets that crop individuals from images, filter out unsuitable images, separate left and right flanks, and remove image backgrounds. Hotspotter had the highest image-matching accuracy for both populations. However, the accuracy was significantly lower for the Kenyan population (62%), compared to the Zimbabwean population (88%). Our automated image pre-processing has immediate application for expanding monitoring based on image-matching. However, the difference in accuracy between populations highlights that population-specific detection rates are likely and may influence certainty in derived statistics. For species such as the African wild dog, where monitoring is both challenging and expensive, automated individual recognition could greatly expand and expedite conservation efforts.
DOI: 10.6084/m9.figshare.22241683
title: 22Rv1_FOXA1_DHT_rep1

description: 22Rv1_FOXA1_DHT_rep1
DOI: 10.6084/m9.figshare.22241683.v1
title: 22Rv1_FOXA1_DHT_rep1

description: 22Rv1_FOXA1_DHT_rep1
DOI: 10.5281/zenodo.7671289
title: O perfil discente de ingressantes nas graduações de Biblioteconomia no Brasil entre 2017 e 2021

description: Foram coletados dados no sítio do Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (Inep), a partir dos registros do Censo da Educação Superior, sobre o perfil das pessoas ingressantes cursos de Biblioteconomia brasileira, no período de 2017 a 2021. Estes dados foram organizados em uma única tabela para melhor visualização, bem como alterada a nomenclatura dos campos para melhor compreensão, mantendo o formato CSV para serem utilizados e reutilizados por qualquer software estatístico, livre ou proprietário. Este conjunto de dados permanecerá disponível na plataforma Zenodo a qual possui controle de versão e backup na própria plataforma. Data were collected at the site of the National Institute for Educational Studies and Research Anísio Teixeira (Inep), from the records of the Higher Education Census, on the profile of people entering the Brazilian Library Sciences, from 2017 to 2021. These data were Organized in a single table for better view, as well as the field nomenclature for better understanding, maintaining the CSV format to be used and reused by any statistical, free or owner software. This data set will remain available on the Zenodo platform which has version and backup control on the platform itself
description: Alternative Title: The Student Profile of Entrantes in Library Graduations in Brazil between 2017 and 2021
description: {"references": ["Instituto Nacional de Estudos e Pesquisas Educacionais An\u00edsio Teixeira. Censo da Educa\u00e7\u00e3o Superior. 2022"]}
DOI: 10.5281/zenodo.7352181
title: O perfil discente de ingressantes nas graduações de Biblioteconomia no Brasil entre 2017 e 2021

description: Foram coletados dados no sítio do Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (Inep), a partir dos registros do Censo da Educação Superior, sobre o perfil das pessoas ingressantes cursos de Biblioteconomia brasileira, no período de 2017 a 2021. Estes dados foram organizados em uma única tabela para melhor visualização, bem como alterada a nomenclatura dos campos para melhor compreensão, mantendo o formato CSV para serem utilizados e reutilizados por qualquer software estatístico, livre ou proprietário. Este conjunto de dados permanecerá disponível na plataforma Zenodo a qual possui controle de versão e backup na própria plataforma. Data were collected at the site of the National Institute for Educational Studies and Research Anísio Teixeira (Inep), from the records of the Higher Education Census, on the profile of people entering the Brazilian Library Sciences, from 2017 to 2021. These data were Organized in a single table for better view, as well as the field nomenclature for better understanding, maintaining the CSV format to be used and reused by any statistical, free or owner software. This data set will remain available on the Zenodo platform which has version and backup control on the platform itself
description: Alternative Title: The Student Profile of Entrantes in Library Graduations in Brazil between 2017 and 2021
description: {"references": ["Instituto Nacional de Estudos e Pesquisas Educacionais An\u00edsio Teixeira. Censo da Educa\u00e7\u00e3o Superior. 2022"]}
DOI: 10.6084/m9.figshare.22241692.v1
title: 22Rv1_FOXA1_DHT_rep2

description: 22Rv1_FOXA1_DHT_rep2
DOI: 10.6084/m9.figshare.22241692
title: 22Rv1_FOXA1_DHT_rep2

description: 22Rv1_FOXA1_DHT_rep2
DOI: 10.34740/kaggle/dsv/5135119
title: Nifty-50 & Nifty Future 50 Dataset
DOI: 10.6084/m9.figshare.22241704
title: 22Rv1_FOXA1_ENZ3w_Dex_rep1

description: 22Rv1_FOXA1_ENZ3w_Dex_rep1
DOI: 10.6084/m9.figshare.22241704.v1
title: 22Rv1_FOXA1_ENZ3w_Dex_rep1

description: 22Rv1_FOXA1_ENZ3w_Dex_rep1
DOI: 10.6084/m9.figshare.22241710.v1
title: 22Rv1_FOXA1_ENZ3w_Dex_rep2

description: 22Rv1_FOXA1_ENZ3w_Dex_rep2
DOI: 10.6084/m9.figshare.22241713
title: 22Rv1_FOXA1_ENZ3w_EtOH_rep1

description: 22Rv1_FOXA1_ENZ3w_EtOH_rep1
DOI: 10.6084/m9.figshare.22241713.v1
title: 22Rv1_FOXA1_ENZ3w_EtOH_rep1

description: 22Rv1_FOXA1_ENZ3w_EtOH_rep1
DOI: 10.6084/m9.figshare.22241719
title: 22Rv1_FOXA1_ENZ3w_EtOH_rep2

description: 22Rv1_FOXA1_ENZ3w_EtOH_rep2
DOI: 10.6084/m9.figshare.22241719.v1
title: 22Rv1_FOXA1_ENZ3w_EtOH_rep2

description: 22Rv1_FOXA1_ENZ3w_EtOH_rep2
DOI: 10.6084/m9.figshare.22241734
title: 22Rv1_FOXA1_EtOH_rep1

description: 22Rv1_FOXA1_EtOH_rep1
DOI: 10.6084/m9.figshare.22241734.v1
title: 22Rv1_FOXA1_EtOH_rep1

description: 22Rv1_FOXA1_EtOH_rep1
DOI: 10.24385/138x-yw95
title: Database of foodstuffs and food systems in Africa, 1497-1840
DOI: 10.34740/kaggle/dsv/5135146
title: NSE-Scripts-Data
DOI: 10.6084/m9.figshare.22241737
title: 22Rv1_FOXA1_EtOH_rep2

description: 22Rv1_FOXA1_EtOH_rep2
DOI: 10.6084/m9.figshare.22241737.v1
title: 22Rv1_FOXA1_EtOH_rep2

description: 22Rv1_FOXA1_EtOH_rep2