cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14220594
title: Contrasting genetic differentiation of urban and rural populations of two grassland lepidopterans across Europe

description: This is a population genomic ddRADseq dataset including samples from several European populations of the butterfly Coenonympha pamphilus and the moth Chiasmia clathrata. This dataset includes the bioinformatics output files that were used in analyses of genetic population structure in the two species. The dataset includes also information about the sampling sites (coordinates, environmental variables used in the analyses), some derived data matrices produced by the analyses, and R-scripts that were used in key analyses of the data. These data are associated with a manuscript by the same authors, the working title of the manuscript being "Contrasting genetic differentiation of urban and rural populations of two grassland lepidopterans across Europe".
DOI: 10.5281/zenodo.14746130
title: Data from: Net primary productivity but not its remote sensing proxies predict mammal diversity in Andean-Amazonian rainforests

description: Dataset for the publication "Net primary productivity but not its remote sensing proxies predict mammal diversity in Andean-Amazonian rainforests"
DOI: 10.5281/zenodo.14746131
title: Data from: Net primary productivity but not its remote sensing proxies predict mammal diversity in Andean-Amazonian rainforests

description: Dataset for the publication "Net primary productivity but not its remote sensing proxies predict mammal diversity in Andean-Amazonian rainforests"
DOI: 10.15468/dl.4tz5mz
title: Occurrence Download

description: A dataset containing 89 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Berardius bairdii Stejneger, 1883",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 89 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004679-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9dwen3
title: Occurrence Download

description: A dataset containing 78277 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is ba482b53-07ed-4ca4-8981-5396d1a8a6fc",
 "BasisOfRecord is Specimen",
 "EventDate is less than or equal to 2025-01-02"
 ]
}

 The dataset includes 78277 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004678-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g3upwc
title: Occurrence Download

description: A dataset containing 151 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euphausia pacifica Hansen, 1911",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 151 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004680-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t93u2v
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Squalus brevirostris Tanaka, 1917",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 51 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004684-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25592/uhhfdm.15982
title: Trading-Off Health Safety, Civil Liberties, and Unemployment Based on Communication Strategies: The Social Dilemma in Fighting Pandemics

description: Data, Code, Questionnaire (in German)
description: All information to be treated as strictly confidential.
DOI: 10.25592/uhhfdm.15981
title: Trading-Off Health Safety, Civil Liberties, and Unemployment Based on Communication Strategies: The Social Dilemma in Fighting Pandemics

description: Data, Code, Questionnaire (in German)
description: All information to be treated as strictly confidential.
DOI: 10.15468/dl.f7heuq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Squalus griffini Phillipps, 1931",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004685-250123221155621/datasets/export for details.
DOI: 10.15468/dl.xfeptj
title: Occurrence Download

description: A dataset containing 872 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry MULTIPOLYGON Z(((2.41232 42.63364 0,2.40417 42.63345 0,2.39498 42.62991 0,2.40314 42.62359 0,2.41172 42.62928 0,2.41232 42.63364 0)))",
 "Geometry MULTIPOLYGON Z(((2.36936 42.6292 0,2.36524 42.62847 0,2.36537 42.62724 0,2.37198 42.62317 0,2.37606 42.62304 0,2.37807 42.62519 0,2.36936 42.6292 0)))",
 "Geometry MULTIPOLYGON Z(((2.37601 42.62254 0,2.37455 42.62244 0,2.37417 42.62159 0,2.37494 42.62102 0,2.37752 42.62112 0,2.37777 42.62197 0,2.37601 42.62254 0)))",
 "Geometry MULTIPOLYGON Z(((2.27541 42.65405 0,2.27164 42.64104 0,2.30099 42.63069 0,2.30906 42.64458 0,2.27541 42.65405 0)))",
 "Geometry MULTIPOLYGON Z(((2.23977 42.67326 0,2.23082 42.66974 0,2.21827 42.66481 0,2.19994 42.6576 0,2.23153 42.64599 0,2.25625 42.66972 0,2.23977 42.67326 0)))",
 "Geometry MULTIPOLYGON Z(((2.37988 42.63281 0,2.37627 42.62915 0,2.38091 42.62505 0,2.39035 42.62347 0,2.39635 42.62366 0,2.39953 42.62416 0,2.37988 42.63281 0)))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 872 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004686-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.748e58
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Squalus margaretsmithae Viana, Lisher & Carvalho, 2017",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004687-250123221155621/datasets/export for details.
DOI: 10.5281/zenodo.14746767
title: Codificación de los debates grabados de los estudiantes sobre los estereotipos de género en las actividades físicas artístico-expresivas

description: Se adjuntan las codificaciónes realizadas utlizando el sotware Nvivo 11 de los debates grabados por los estudiantes de cuarto curso de la mencion de Educacion Física del grado de Magisterio de Primaria de la Facultad de Educacion de la Universidad de Zaragoza (España).

Dichos debates grabados relataban lo experimentado con respecto a los estereotipos de género en las sesiones prácticas de la asignatura Actividades Físicas Artístico-Expresivas. En dichos debates exponían de forma individual sus experiencias y reflexiones. Fueron transcritos y analizados utilizando un sistema de categorias que se adjunta en el mismo documento tras la codificacion (Canales-Lacruz, I., & Lorente-Echeverría, S. (2024). Sistema de categorías para analizar los estereotipos de género de los estudiantes universitarios en tareas artístico-expresivas (Proyecto Agitando el avispero). Zenodo. https://doi.org/10.5281/zenodo.10847999)
DOI: 10.5281/zenodo.14746768
title: Codificación de los debates grabados de los estudiantes sobre los estereotipos de género en las actividades físicas artístico-expresivas

description: Se adjuntan las codificaciónes realizadas utlizando el sotware Nvivo 11 de los debates grabados por los estudiantes de cuarto curso de la mencion de Educacion Física del grado de Magisterio de Primaria de la Facultad de Educacion de la Universidad de Zaragoza (España).

Dichos debates grabados relataban lo experimentado con respecto a los estereotipos de género en las sesiones prácticas de la asignatura Actividades Físicas Artístico-Expresivas. En dichos debates exponían de forma individual sus experiencias y reflexiones. Fueron transcritos y analizados utilizando un sistema de categorias que se adjunta en el mismo documento tras la codificacion (Canales-Lacruz, I., & Lorente-Echeverría, S. (2024). Sistema de categorías para analizar los estereotipos de género de los estudiantes universitarios en tareas artístico-expresivas (Proyecto Agitando el avispero). Zenodo. https://doi.org/10.5281/zenodo.10847999)
DOI: 10.17028/rd.lboro.28284947
title: Supplementary information files for "The CURTAIN feasibility study: exploring a food-themed reminiscence theatre intervention to improve the nutrition of older adults living in residential care homes"

description: Supplementary files for article "The CURTAIN feasibility study: exploring a food-themed reminiscence theatre intervention to improve the nutrition of older adults living in residential care homes"Reminiscence theatre (RT), an applied drama technique, is an effective tool for improving health-related outcomes for older adults in clinical settings. However, no research has explored the potential for a food-themed RT intervention to improve the nutrition, health and wellbeing of this population. Therefore, the current study explored the feasibility and acceptability of such an intervention – the CURTAIN intervention – in residential care-homes. Two care-homes, their residents and staff were recruited to a cluster randomised crossover feasibility study with post-hoc interviews. Over two months, participants (n=42) took part in the CURTAIN activity and a control activity before consuming their lunch, with momentary hunger, activity/meal enjoyment, and food intake measured around each activity. Continuation to a full-scale trial was assessed against progression criteria for data-collection-sheet completion and residents’ enjoyment of the intervention. The intervention was highly enjoyed by residents (median score = 8/10), with only 1% of data-collection cells blank. Attrition rate was 5% and preliminary data suggest CURTAIN has the potential to improve residents’ appetite and energy intake. Aspects of evaluation design and recruitment strategy to optimise sample diversity require some amendments; however, overall, the CURTAIN intervention is feasible and acceptable to care-home residents and staff, and a full intervention evaluation is warranted.© The Authors, CC BY-NC-ND 4.0
DOI: 10.17028/rd.lboro.28284947.v1
title: Supplementary information files for "The CURTAIN feasibility study: exploring a food-themed reminiscence theatre intervention to improve the nutrition of older adults living in residential care homes"

description: Supplementary files for article "The CURTAIN feasibility study: exploring a food-themed reminiscence theatre intervention to improve the nutrition of older adults living in residential care homes"Reminiscence theatre (RT), an applied drama technique, is an effective tool for improving health-related outcomes for older adults in clinical settings. However, no research has explored the potential for a food-themed RT intervention to improve the nutrition, health and wellbeing of this population. Therefore, the current study explored the feasibility and acceptability of such an intervention – the CURTAIN intervention – in residential care-homes. Two care-homes, their residents and staff were recruited to a cluster randomised crossover feasibility study with post-hoc interviews. Over two months, participants (n=42) took part in the CURTAIN activity and a control activity before consuming their lunch, with momentary hunger, activity/meal enjoyment, and food intake measured around each activity. Continuation to a full-scale trial was assessed against progression criteria for data-collection-sheet completion and residents’ enjoyment of the intervention. The intervention was highly enjoyed by residents (median score = 8/10), with only 1% of data-collection cells blank. Attrition rate was 5% and preliminary data suggest CURTAIN has the potential to improve residents’ appetite and energy intake. Aspects of evaluation design and recruitment strategy to optimise sample diversity require some amendments; however, overall, the CURTAIN intervention is feasible and acceptable to care-home residents and staff, and a full intervention evaluation is warranted.© The Authors, CC BY-NC-ND 4.0
DOI: 10.15128/r1bz60cw31v
title: Shear banding as a cause of non-monotonic stress relaxation after flow cessation [dataset]

description: Recent flow cessation experiments on soft materials have shown a counter-intuitive non-monotonic relaxation of the shear stress: following the switch-off of a steady imposed shear flow, the stress initially decays before later increasing again. By simulating the soft glassy rheology model in a form extended to allow steady state shear banding, we show that the presence of shear bands prior to flow cessation can give rise to this phenomenon. We give a mechanistic understanding of the basic physics involved, in terms of (i) the decay of the shear bands after flow cessation, and (ii) the evolution of frustrated local stresses, governed by different time scales for plastic relaxation in each band. In particular, an elastic recoil in the unsheared band gives rise to negative local frustrated stresses, the slow release of which can cause an increase in macroscopic stress. Given that shear banding and frustrated local stresses arise widely across disordered soft solids, we argue that non-monotonic stress relaxation after flow cessation may occur in many different materials.
DOI: 10.15468/dl.dx6vtb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Squalus mahia Viana, Lisher & Carvalho, 2017",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004688-250123221155621/datasets/export for details.
DOI: 10.5281/zenodo.11167520
title: WOLO: Wilson Only Looks Once – Datasets

description: WOLO: Wilson Only Looks Once – Estimating ant body mass from reference-free images using deep convolutional neural networks

Abstract

Size estimation is a hard computer vision problem with widespread applications in quality control in manufacturing and processing plants, livestock management, and studies on animal behaviour. Typically, image-based size estimation is facilitated by either well-controlled imaging conditions, the provision of global cues, or both. Reference-free size estimation is challenging, because objects of vastly different sizes can appear identical if they are of similar shape. Here, we attempt to implement automated and reference-free body size estimation to facilitate large-scale experimental work in a key model species in sociobiology: the leaf-cutter ants. Leaf-cutter ants are a suitable testbed for reference-free size-estimation, because their workers differ vastly in both size and shape; in principle, it is therefore possible to infer body mass, a proxy for size, from relative body proportions alone. Inspired by earlier work by E.O. Wilson, who trained himself to discern ant worker size from visual cues alone, we used various deep learning techniques to achieve the same feat automatically, quickly, and at scale from a single reference image: Wilson Only Looks Once (WOLO). Utilizing over 3 million hand-annotated and computer-generated images, a set of deep neural networks---including regressors, classifiers, and detectors---were trained to estimate the body mass of ants from image cut-outs. The WOLO networks approximately matched human performance, measured for a small group of both experts and non-experts, but were about 1000 times faster. Further refinement may enable accurate, high-throughput, and non-intrusive body mass estimation at scale, and so eventually contribute to a more nuanced and comprehensive understanding of the complex division of labour that characterises polymorphic insect societies.

Datasets

This repository contains all (cropped) frame datasets for training and benchmarking. Refer to the WOLO GitHub page for usage and the manuscript for dataset details.

As the full-frame datasets are too large to host online permanently, please get in touch with the lead author (Fabian Plum) if you require access.
DOI: 10.5281/zenodo.11167521
title: WOLO: Wilson Only Looks Once – Datasets

description: WOLO: Wilson Only Looks Once – Estimating ant body mass from reference-free images using deep convolutional neural networks

Abstract

Size estimation is a hard computer vision problem with widespread applications in quality control in manufacturing and processing plants, livestock management, and studies on animal behaviour. Typically, image-based size estimation is facilitated by either well-controlled imaging conditions, the provision of global cues, or both. Reference-free size estimation is challenging, because objects of vastly different sizes can appear identical if they are of similar shape. Here, we attempt to implement automated and reference-free body size estimation to facilitate large-scale experimental work in a key model species in sociobiology: the leaf-cutter ants. Leaf-cutter ants are a suitable testbed for reference-free size-estimation, because their workers differ vastly in both size and shape; in principle, it is therefore possible to infer body mass, a proxy for size, from relative body proportions alone. Inspired by earlier work by E.O. Wilson, who trained himself to discern ant worker size from visual cues alone, we used various deep learning techniques to achieve the same feat automatically, quickly, and at scale from a single reference image: Wilson Only Looks Once (WOLO). Utilizing over 3 million hand-annotated and computer-generated images, a set of deep neural networks---including regressors, classifiers, and detectors---were trained to estimate the body mass of ants from image cut-outs. The WOLO networks approximately matched human performance, measured for a small group of both experts and non-experts, but were about 1000 times faster. Further refinement may enable accurate, high-throughput, and non-intrusive body mass estimation at scale, and so eventually contribute to a more nuanced and comprehensive understanding of the complex division of labour that characterises polymorphic insect societies.

Datasets

This repository contains all (cropped) frame datasets for training and benchmarking. Refer to the WOLO GitHub page for usage and the manuscript for dataset details.

As the full-frame datasets are too large to host online permanently, please get in touch with the lead author (Fabian Plum) if you require access.
DOI: 10.15468/dl.dbwt52
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Squalus albicaudus Viana, Carvalho & Gomes, 2016",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004689-250123221155621/datasets/export for details.
DOI: 10.15468/dl.hjt749
title: Occurrence Download

description: A dataset containing 169 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Chinese Taipei, China, Korea, Republic of)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Harpadon nehereus (Hamilton, 1822)"
 ]
}

 The dataset includes 169 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004690-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14744371
title: Tanzania Climate-Sensitive Waterborne Diseases Dataset for Predictive Machine Learning: A Comprehensive Five-Year Analysis of Health, Infrastructure, and Weather Data (2019–2023)

description: This dataset presents comprehensive field and environmental data collected from five districts in Tanzania, referred to as District 1, District 2, District 3, District 4, and District 5, over a five-year period (2019–2023). The dataset includes information on critical public infrastructure such as water sources, toilet quality, health facility locations, and waste management facilities. Additionally, data on waterborne disease cases were recorded, covering Typhoid fever, Amoebiasis/dysentery, Diarrhea (categorized by severity: no dehydration, some dehydration, and severe dehydration), Schistosomiasis, and intestinal worms. Complementary weather data with monthly frequency for the same five-year period was sourced from Copernicus.

The dataset underwent rigorous preprocessing, cleaning, and formatting to ensure usability and consistency. Each data point, such as a water source, was expanded to include a minimum of 60 entries to align with weather conditions over the 60 months. Furthermore, all location-revealing data has been anonymized to maintain privacy. This dataset provides a valuable resource for public health analysis and research on the relationships between infrastructure, environmental conditions, and health outcomes in Tanzania.
DOI: 10.5281/zenodo.14744372
title: Tanzania Climate-Sensitive Waterborne Diseases Dataset for Predictive Machine Learning: A Comprehensive Five-Year Analysis of Health, Infrastructure, and Weather Data (2019–2023)

description: This dataset presents comprehensive field and environmental data collected from five districts in Tanzania, referred to as District 1, District 2, District 3, District 4, and District 5, over a five-year period (2019–2023). The dataset includes information on critical public infrastructure such as water sources, toilet quality, health facility locations, and waste management facilities. Additionally, data on waterborne disease cases were recorded, covering Typhoid fever, Amoebiasis/dysentery, Diarrhea (categorized by severity: no dehydration, some dehydration, and severe dehydration), Schistosomiasis, and intestinal worms. Complementary weather data with monthly frequency for the same five-year period was sourced from Copernicus.

The dataset underwent rigorous preprocessing, cleaning, and formatting to ensure usability and consistency. Each data point, such as a water source, was expanded to include a minimum of 60 entries to align with weather conditions over the 60 months. Furthermore, all location-revealing data has been anonymized to maintain privacy. This dataset provides a valuable resource for public health analysis and research on the relationships between infrastructure, environmental conditions, and health outcomes in Tanzania.
DOI: 10.1285/i26113775n8
title: Apprendimento territoriale. Il caso del Gal Terra d'Arneo