cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.t2budb
title: Occurrence Download

description: A dataset containing 38392 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Oenothera glazioviana Micheli, Oenothera laevifolia de Vries, Oenothera rubritincta R.R.Gates, Oenothera lata de Vries, Oenothera lamarckiana de Vries, 1901, Oenothera gigantea C.Huber, Oenothera tardiflora R.R.Gates, Oenothera blandina de Vries, Oenothera glazioviana var. azorica Rostaski, Oenothera bipartita Lutz, Oenothera liquida de Vries, Oenothera vrieseana H.Lév., Oenothera fatua de Vries, Oenothera scintillans de Vries, Oenothera semilata de Vries, Oenothera pallescens de Vries, Onagra nanella (de Vries) Mac Dougal, Oenothera leptocarpa Greene, Oenothera plicatula Lutz, Oenothera sublinearis de Vries, Oenothera lamarkiana, Oenothera candicans de Vries, Oenothera oblonga de Vries, Oenothera nanella de Vries, Oenothera cana de Vries, Oenothera brevistylis de Vries, Oenothera fusiformis Munz & I.M.Johnst., Oenothera aberrans Lutz, Oenothera glazioviana f. glazioviana, Oenothera pulla de Vries, Onagra laevifolia de Vries, Oenothera militaris de Vries, Oenothera tarda de Vries, Oenothera rubrinervis de Vries, Oenothera rubrinervoides R.R.Gates, Oenothera vana de Vries, Oenothera albida de Vries, Oenothera hamata de Vries, Oenothera oxypetala de Vries, Oenothera subovata de Vries, Oenothera erythrosepala var. azorica Rostanski, Oenothera gigas de Vries, Oenothera simplex de Vries, Oenothera elliptica de Vries, Oenothera superflua de Vries, Oenothera scindens de Vries, Oenothera spathulata de Vries, Oenothera multiflora var. elliptica R.R.Gates, Oenothera multiflora R.R.Gates, Onagra erythrosepala Borbás, Oenothera glazioviana var. glazioviana, Oenothera crassifolia var. leptocarpa (Greene) H.Lév., Onagra nanella (de Vries) MacDougal, Onagra rubrinervis (de Vries) MacDougal, Onagra rubrinervis (de Vries) Mac Dougal, Onagra gigas (de Vries) MacDougal, Onagra gigas (de Vries) Mac Dougal, Oenothera suaveolens f. erythrocephala (Borbás) Jáv., Oenothera biennis f. erythrosepala (Borbás) Jáv., 1924, Oenothera suaveolens f. erythrosepala (Borbás) Munz, Oenothera suaveolens f. erythrosepala (Borbás) Jáv., Oenothera grandiflora subsp. erythrocephala (Borbás) Á.Löve & D.Löve, Oenothera erythrosepala (Borbás) Borbás, Oenothera grandiflora subsp. erythrosepala (Borbás) Á.Löve & D.Löve)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 38392 records from 518 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010375-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48579/pro/zsyxyf
title: Campagne acoustique Roscoff Juillet 2020

description: Le projet ACaPELA (ACoustique PELagique) est un projet porté par le MNHN (Station marine de Dinard) et réalisé en collaboration avec l’IRD (UMR LEMAR) et PatriNat (OFB-CNRS-MNHN). Ce projet R&D a pour objectif de développer et valider la méthodologie de surveillance DCSMM pour l’évaluation de l’état écologique des populations et peuplements de poissons et céphalopodes (PCs) des milieux pélagiques côtiers, c’est-à-dire les espèces pélagiques ou bentho-pélagiques fréquentant la colonne d’eau (le pelagos) dans les zones dont la bathymétrie est comprise entre 0 et 40 m (zones dites côtières). Les protocoles d’échantillonnages proposés consistent à combiner l’utilisation de deux technologies d’acoustiques actives complémentaires, orientées verticalement : un sondeur large bande (Simrad EK80, 70, 120 et 200 kHz) et un sonar multifaisceaux (Simrad M3, 500 kHz). Cette campagne a été réalisée dans le cadre du projet ACaPELA, en Juillet 2020, à bord du bateau de station Néomysis. Cette campagne a permis de réaliser des radiales acoustiques en baie de Morlaix, au départ de Roscoff, avec un focus sur les zones de petits fonds et le gradient côte-large. Ces enregistrements ont été complétés avec des enregistrements CTD (Conductivity-Depth-Temperature) à des points clefs identifiés au préalables. Des pêches sur détection ont également été réalisées à l’aide d’un chalut méso-pélagique.
DOI: 10.15468/dl.mvxgcy
title: Occurrence Download

description: A dataset containing 937 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Osteoglossum Cuvier, 1829"
 ]
}

 The dataset includes 937 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010377-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wpj25y
title: Occurrence Download

description: A dataset containing 744 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus bungeana Zucc. ex Endl."
 ]
}

 The dataset includes 744 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010378-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48579/pro/3fqugn
title: Campagne acoustique Marseille Août 2020

description: Le projet ACaPELA (ACoustique PELagique) est un projet porté par le MNHN (Station marine de Dinard) et réalisé en collaboration avec l’IRD (UMR LEMAR) et PatriNat (OFB-CNRS-MNHN). Ce projet R&D a pour objectif de développer et valider la méthodologie de surveillance DCSMM pour l’évaluation de l’état écologique des populations et peuplements de poissons et céphalopodes (PCs) des milieux pélagiques côtiers, c’est-à-dire les espèces pélagiques ou bentho-pélagiques fréquentant la colonne d’eau (le pelagos) dans les zones dont la bathymétrie est comprise entre 0 et 40 m (zones dites côtières). Les protocoles d’échantillonnages proposés consistent à combiner l’utilisation de deux technologies d’acoustiques actives complémentaires, orientées verticalement : un sondeur large bande (Simrad EK80, 70, 120 et 200 kHz) et un sonar multifaisceaux (Simrad M3, 500 kHz). Cette campagne a été réalisée dans le cadre du projet ACaPELA, en Août 2020, à bord du bateau Cro-Magnon, de l'association Septentrion. Cette campagne a permis de réaliser des radiales acoustiques aux alentours de Marseille, avec un focus sur les zones le gradient côte-large et l'impact des zones de non-pêche. Ces enregistrements ont été complétés avec des enregistrements CTD (Conductivity-Depth-Temperature) à des points clefs identifiés au préalables. Des plongées et enregistrements vidéos ont également été effectués de manière complémentaire
DOI: 10.15468/dl.x5zwyq
title: Occurrence Download

description: A dataset containing 1992 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus caribaea Morelet"
 ]
}

 The dataset includes 1992 records from 196 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010379-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3eu4vy
title: Occurrence Download

description: A dataset containing 2899 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus massoniana Lamb."
 ]
}

 The dataset includes 2899 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010380-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11174782
title: Dataset of adaptive Children-Robot Interaction for Education based on Autonomous Multimodal Users' Readings

description: # Dataset of adaptive Children-Robot Interaction for Education based on Autonomous Multimodal Users’ Readings 

## Background

This dataset is generated from multiple interactions between a Social Robot (NAO) and 5th grade students from a private school in São Paulo, Brazil. 

In the interaction, the robot approached the content that teachers were approaching at the time with the participants students about the wasting system in Brazil.

The measures here are the readings that the R-CASTLE system did for each answer the students gave to the questions the robot asked. 

For more information about how these measures were collected, please refer to this thesis at:  https://doi.org/10.11606/T.55.2020.tde-31082020-093935

Since the goal of the R-CASTLE is to provide autonomous adaptation, we built a ground-truth dataset based on human feedback of an expert in education operating the robot in loco. The person was teleoperating the robot to change its behaviour (or not) according to observed values of the participants as Face Gaze, Facial emotion displayed, Number of spoken words, the correctness of the answer (based on pre-defined answers), and the time students took to answer. These measures are the 5th columns of this csv file. The evaluator could decide to increase (1), maintain (0), or decrease (-1) the level of difficulties of the following questions depending on the mentioned observed measures. This is the human true label, stored in the 6th column.   

## Description:Each row of this file is a tuple of the autonomous reading the robot made in the 5 first columns, plus the true label in the 6th row (True Value) and the Final Crisp Value using fuzzy classification in the 7th row (Final Crisp Value).

Deviations (integer): number of face deviations of the participant during the question answering identified by the system.

EmotionCount (integer): a balance between "good" and "bad" emotions (good - bad) identified by the system.

NumberWord (integer): number of words comprised in the sentence the participant gave.

SucRate/Ans/RWa: (between 0 and 1, where 0 is completely wrong and 1 is completely right): The success rate of the participant’s answer to that question, based on the expected answer programmed by their teachers.

Time2ans (float): The time spent to answer the question since the robot has finished the question until the end of the participant’s speech in seconds.

True Value (-1, 0, 1): Ground-truth value. Value of adaptation chosen by the human observing the interaction if the system needed to decrease, maintain, or increase the level of difficulty of asked questions.    

Final Crisp Value (float): value of calculated fuzzy output based on the implementations in the paper: https://doi.org/10.1145/3395035.3425201

## Creators Daniel Tozadore: dtozadore@gmail.comRoseli Romero: rafrance@icmc.usp.br

## License: [Creative Commons Licenses](https://creativecommons.org/share-your-work/cclicenses/)
DOI: 10.5281/zenodo.11174781
title: Dataset of adaptive Children-Robot Interaction for Education based on Autonomous Multimodal Users' Readings

description: # Dataset of adaptive Children-Robot Interaction for Education based on Autonomous Multimodal Users’ Readings 

## Background

This dataset is generated from multiple interactions between a Social Robot (NAO) and 5th grade students from a private school in São Paulo, Brazil. 

In the interaction, the robot approached the content that teachers were approaching at the time with the participants students about the wasting system in Brazil.

The measures here are the readings that the R-CASTLE system did for each answer the students gave to the questions the robot asked. 

For more information about how these measures were collected, please refer to this thesis at:  https://doi.org/10.11606/T.55.2020.tde-31082020-093935

Since the goal of the R-CASTLE is to provide autonomous adaptation, we built a ground-truth dataset based on human feedback of an expert in education operating the robot in loco. The person was teleoperating the robot to change its behaviour (or not) according to observed values of the participants as Face Gaze, Facial emotion displayed, Number of spoken words, the correctness of the answer (based on pre-defined answers), and the time students took to answer. These measures are the 5th columns of this csv file. The evaluator could decide to increase (1), maintain (0), or decrease (-1) the level of difficulties of the following questions depending on the mentioned observed measures. This is the human true label, stored in the 6th column.   

## Description:Each row of this file is a tuple of the autonomous reading the robot made in the 5 first columns, plus the true label in the 6th row (True Value) and the Final Crisp Value using fuzzy classification in the 7th row (Final Crisp Value).

Deviations (integer): number of face deviations of the participant during the question answering identified by the system.

EmotionCount (integer): a balance between "good" and "bad" emotions (good - bad) identified by the system.

NumberWord (integer): number of words comprised in the sentence the participant gave.

SucRate/Ans/RWa: (between 0 and 1, where 0 is completely wrong and 1 is completely right): The success rate of the participant’s answer to that question, based on the expected answer programmed by their teachers.

Time2ans (float): The time spent to answer the question since the robot has finished the question until the end of the participant’s speech in seconds.

True Value (-1, 0, 1): Ground-truth value. Value of adaptation chosen by the human observing the interaction if the system needed to decrease, maintain, or increase the level of difficulty of asked questions.    

Final Crisp Value (float): value of calculated fuzzy output based on the implementations in the paper: https://doi.org/10.1145/3395035.3425201

## Creators Daniel Tozadore: dtozadore@gmail.comRoseli Romero: rafrance@icmc.usp.br

## License: [Creative Commons Licenses](https://creativecommons.org/share-your-work/cclicenses/)
DOI: 10.5281/zenodo.14795429
title: Effects of Parental Beliefs and Practices on Young Children's Pre-literacy: The Case of China

description: This study investigates the impact of parental beliefs and practices on pre-literacy among young children in China. A self-report survey of 1,060 kindergarten parents from mainland China was conducted, controlling for demographic and socioeconomic factors.
DOI: 10.5281/zenodo.14795430
title: Effects of Parental Beliefs and Practices on Young Children's Pre-literacy: The Case of China

description: This study investigates the impact of parental beliefs and practices on pre-literacy among young children in China. A self-report survey of 1,060 kindergarten parents from mainland China was conducted, controlling for demographic and socioeconomic factors.
DOI: 10.3886/e156901
title: Data and Code for: The COVID-19 Pandemic Disrupted Both School Bullying and Cyberbullying

description: One-fifth of U.S. high school students report being bullied each year. We use internet search data for real-time tracking of bullying patterns as COVID-19 disrupted in-person schooling. We first show that, pre-pandemic, internet searches contain useful information about actual bullying behavior. We then show that searches for school bullying and cyberbullying dropped 30-35 percent as schools shifted to remote learning in spring 2020. The gradual return to in-person instruction starting in fall 2020 partially returns bullying searches to pre-pandemic levels. This rare positive effect may partly explain recent mixed evidence on the pandemic's impact on students' mental health and well-being.
description: All Google users in the United States. Smallest Geographic Unit: U.S. States
DOI: 10.3886/e156901v1-166021
title: Data and Code for: The COVID-19 Pandemic Disrupted Both School Bullying and Cyberbullying

description: One-fifth of U.S. high school students report being bullied each year. We use internet search data for real-time tracking of bullying patterns as COVID-19 disrupted in-person schooling. We first show that, pre-pandemic, internet searches contain useful information about actual bullying behavior. We then show that searches for school bullying and cyberbullying dropped 30-35 percent as schools shifted to remote learning in spring 2020. The gradual return to in-person instruction starting in fall 2020 partially returns bullying searches to pre-pandemic levels. This rare positive effect may partly explain recent mixed evidence on the pandemic's impact on students' mental health and well-being.
description: All Google users in the United States. Smallest Geographic Unit: U.S. States
DOI: 10.15468/dl.qkssxk
title: Occurrence Download

description: A dataset containing 62382 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Poecilia"
 ]
}

 The dataset includes 62382 records from 399 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010382-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28334696
title: Raw data of Assessment of physico-chemical properties of ginger genotypes in Salyan, Nepal.xlsx

description: Ginger (Zingiber officinale) is an important spice crops which is known for its good nutritive and medicinal values. It is cultivated in Nepal from a long period of time. The production of the ginger in Nepal is increasing and with the increasing production, the export of the commodity is also increasing. To meet the standard of international market, the quality of the ginger should be better. For this genotype with better physico-chemical properties is required. For this, an experiment will be carried out in Salyan district of Nepal. This study aims to identify the genotypes with higher physico-chemical properties. The experiment will be conducted in a Completely Randomized Design with one factor as genotypes. The genotypes used in the experiment are ZI-9721 (kapukot ginger-1), ZI-0515, ZI-1025, ZI-1027, ZI-1303 and ZI-1620. These genotypes are under different trials and research in NARC. Thus the experiment consists of 6 treatments replicated 4 times resulting in 24 experimental units laid out in a complete randomized design (CRD). The ginger rhizomes will be collected, washed, dried and grinded, then passed through different test in laboratory for physical and biochemical analysis. At different stages of experiment the relevant data required for analysis and comparison are recorded. In the experiment, Weight of the ginger rhizomes, Size of rhizomes, Bulk density, Meat : peel ratio, Moisture content, Dry recovery percentage, Oleoresin content, Essential oil content, Crude fibre content, and pH content of the rhizomes will be calculated. The data recorded will be arranged and entered in the MS-Excel and will be analyzed by using statistical software R-Studio Version 4.2. The inference will be drawn at 5% level of signficances and mean comparisons of above-mentioned parameters will be done by using DMRT (Duncan's Multiple Range Test).
DOI: 10.6084/m9.figshare.28334696.v1
title: Raw data of Assessment of physico-chemical properties of ginger genotypes in Salyan, Nepal.xlsx

description: Ginger (Zingiber officinale) is an important spice crops which is known for its good nutritive and medicinal values. It is cultivated in Nepal from a long period of time. The production of the ginger in Nepal is increasing and with the increasing production, the export of the commodity is also increasing. To meet the standard of international market, the quality of the ginger should be better. For this genotype with better physico-chemical properties is required. For this, an experiment will be carried out in Salyan district of Nepal. This study aims to identify the genotypes with higher physico-chemical properties. The experiment will be conducted in a Completely Randomized Design with one factor as genotypes. The genotypes used in the experiment are ZI-9721 (kapukot ginger-1), ZI-0515, ZI-1025, ZI-1027, ZI-1303 and ZI-1620. These genotypes are under different trials and research in NARC. Thus the experiment consists of 6 treatments replicated 4 times resulting in 24 experimental units laid out in a complete randomized design (CRD). The ginger rhizomes will be collected, washed, dried and grinded, then passed through different test in laboratory for physical and biochemical analysis. At different stages of experiment the relevant data required for analysis and comparison are recorded. In the experiment, Weight of the ginger rhizomes, Size of rhizomes, Bulk density, Meat : peel ratio, Moisture content, Dry recovery percentage, Oleoresin content, Essential oil content, Crude fibre content, and pH content of the rhizomes will be calculated. The data recorded will be arranged and entered in the MS-Excel and will be analyzed by using statistical software R-Studio Version 4.2. The inference will be drawn at 5% level of signficances and mean comparisons of above-mentioned parameters will be done by using DMRT (Duncan's Multiple Range Test).
DOI: 10.15468/dl.tysb9u
title: Occurrence Download

description: A dataset containing 2041 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus parviflora Siebold & Zucc."
 ]
}

 The dataset includes 2041 records from 178 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010385-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26506315
title: Data for the manuscript Egg Shape Type Mediates Acceptance Thresholds in Host Species with Different Rates of Antiparasitic Egg Rejection.

description: Data for the manuscript Egg Shape Type Mediates Acceptance Thresholds in Host Species with Different Rates of Antiparasitic Egg Rejection.
DOI: 10.6084/m9.figshare.26506315.v1
title: Data for the manuscript Egg Shape Type Mediates Acceptance Thresholds in Host Species with Different Rates of Antiparasitic Egg Rejection.

description: Data for the manuscript Egg Shape Type Mediates Acceptance Thresholds in Host Species with Different Rates of Antiparasitic Egg Rejection.
DOI: 10.15468/dl.wfyhug
title: Occurrence Download

description: A dataset containing 18364 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus rigida Mill."
 ]
}

 The dataset includes 18364 records from 304 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010386-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0175671.10fu
title: SH0175671.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.