cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16879573.v3
title: Gender differences in the induction of negative emotions by loss- versus gain-framed images accompanying a nutrition message

description: Health personnel’s preference for loss-framed health messages is attributed to occupational factors, but it could owe to gender. The majority of health workers are women, more susceptible to negative emotions than men. Here, we tested whether there are gender biases in processes whereby gain- and loss-framed messages induce negative emotions in the task of assessing a poster with nutritional recommendations to reduce risks associated with COVID-19. Using images of a smiling family indoors versus transportation of a coffin, we found among workers at a hospital in Lima, Peru that loss-frame, compared to gain-frame, robustly increased the negative emotions of women, but not those of men. Findings entailing positive emotions and adherence behavior are still needed to challenge the occupational interpretation.<br>
DOI: 10.6084/m9.figshare.16910878.v1
title: InundationExtent_Hurricane_Florence_UAVSAR_V2.0.zip

description: The 2018 Hurricane Florence produced heavy rainfall and subsequent record-setting riverine flooding in North Carolina, USA. NASA/JPL collected daily high-resolution (about 5 meters) full-polarized L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data between September 18th and 23rd. Here, we use UAVSAR data to construct a flood inundation detection framework through a combination of polarimetric decomposition method and a Random Forest classifier. Validation of the established model with compiled ground references shows that the incorporation of linear polarizations with polarimetric decomposition and terrain variables significantly enhances the accuracy of inundation classification, and the Kappa statistic increases to 91.4% from 64.3% with linear polarizations alone. This data set contains inundation extent information of four UAVSAR flight lines (i.e., 13510, 31509, 32023 and 35303) with at least four days’ observations from Sep 18 to Sep 23, corresponding to the area covering the Neuse, Cape Fear, and Lumbee Rivers as well as their tributaries in Eastern North Carolina
DOI: 10.6084/m9.figshare.16910902
title: Beta Diversity of Plant-Pollinator Interactions in Anthropogenic Landscapes

description: Data are of plant-pollinator interactions from twenty-one sites in the Dublin region of Ireland (Figure 1) sampled four times between 5 May and 20 August 2018 at monthly intervals. Plants and pollinators were sampled along a 2m x 1km transect within each 1.5km radius site, with sub-sections of the transect allocated proportionately to all land cover types comprising more than 1% of the selected site (e.g. pasture, arable, continuous urban fabric; see Figure S1 Legend). Transects in residential areas were positioned along the boundary between pavements and residential gardens, so that 1m of the transect width was located in gardens and the other 1m was located on pavements and road verges. Transect locations were chosen using a random number generator to select points, and transect sections were located as close as possible to those points. Where land cover types were particularly dominant within a site, a maximum transect section length of 250m was walked, with multiple transects of the same land cover walked across multiple locations. Flowers were sampled by noting every flowering species on the outward walk of the transect and then counting the floral units of each species on the return walk. A floral unit was defined as an individual flower or collection of flowers that an insect of 5 mm body length could walk between (see Baldock et al. 2015, Supplementary Material Table S4) and comprised a single capitulum for Asteraceae, a secondary umbel for Apiaceae and a single flower for most other taxa. Grasses, sedges and wind-pollinated forbs were not sampled. Flower-visitor interactions were quantified by walking along each transect and recording every insect on flowers up to 1m either side of the transect line to a height of 2m, where appropriate, e.g. along hedgerows. An attempt was made to net all bees and hoverflies (Syrphidae), which were frozen and later identified to species. All other flower visiting insects were recorded at the family level (Coleoptera, Diptera, Lepidoptera). Bees and hoverflies were identified using Falk (2015) and Stubbs & Falk (2002) respectively, with identifications checked by taxonomists (See Acknowledgements). Plants were identified using Rose & O’Reilly (2006) and the phone application Plantnet (available at: https://identify.plantnet-project.org/), 85% to species and the rest to genus or morpho species. Sampling for flower visitors and their interactions took place between 09:00 and 19:00 hours on dry, warm, non-windy days.
DOI: 10.6084/m9.figshare.16910878.v2
title: InundationExtent_Hurricane_Florence_UAVSAR_V2.0.zip

description: The 2018 Hurricane Florence produced heavy rainfall and subsequent record-setting riverine flooding in North Carolina, USA. NASA/JPL collected daily high-resolution (about 5 meters) full-polarized L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data between September 18th and 23rd. Here, we use UAVSAR data to construct a flood inundation detection framework through a combination of polarimetric decomposition method and a Random Forest classifier. Validation of the established model with compiled ground references shows that the incorporation of linear polarizations with polarimetric decomposition and terrain variables significantly enhances the accuracy of inundation classification, and the Kappa statistic increases to 91.4% from 64.3% with linear polarizations alone. This data set contains inundation extent information of four UAVSAR flight lines (i.e., 13510, 31509, 32023 and 35303) with at least four days’ observations from Sep 18 to Sep 23, corresponding to the area covering the Neuse, Cape Fear, and Lumbee Rivers as well as their tributaries in Eastern North Carolina
DOI: 10.6084/m9.figshare.16910764
title: Plowman et al Dominant Mutant Phenotype Data

description: PEAKS data of keratins and keratin associated proteins from mass spectral label free quantitation of wool derived from wild-type and dominant mutant twin pairs of lambs in "Wool fiber curvature is correlated with abundance of K38 and specific keratin associated proteins."
DOI: 10.6084/m9.figshare.16910764.v1
title: Plowman et al Dominant Mutant Phenotype Data

description: PEAKS data of keratins and keratin associated proteins from mass spectral label free quantitation of wool derived from wild-type and dominant mutant twin pairs of lambs in "Wool fiber curvature is correlated with abundance of K38 and specific keratin associated proteins."
DOI: 10.6084/m9.figshare.16910878.v3
title: InundationExtent_Hurricane_Florence_UAVSAR_V2.0

description: The 2018 Hurricane Florence produced heavy rainfall and subsequent record-setting riverine flooding in North Carolina, USA. NASA/JPL collected daily high-resolution (about 5 meters) full-polarized L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data between September 18th and 23rd. Here, we use UAVSAR data to construct a flood inundation detection framework through a combination of polarimetric decomposition method and a Random Forest classifier. Validation of the established model with compiled ground references shows that the incorporation of linear polarizations with polarimetric decomposition and terrain variables significantly enhances the accuracy of inundation classification, and the Kappa statistic increases to 91.4% from 64.3% with linear polarizations alone. This data set contains inundation extent information of four UAVSAR flight lines (i.e., 13510, 31509, 32023 and 35303) with at least four days’ observations from Sep 18 to Sep 23, corresponding to the area covering the Neuse, Cape Fear, and Lumbee Rivers as well as their tributaries in Eastern North Carolina
DOI: 10.6084/m9.figshare.16910878.v4
title: InundationExtent_Hurricane_Florence_UAVSAR_V2.0

description: The 2018 Hurricane Florence produced heavy rainfall and subsequent record-setting riverine flooding in North Carolina, USA. NASA/JPL collected daily high-resolution (about 5 meters) full-polarized L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data between September 18th and 23rd. Here, we use UAVSAR data to construct a flood inundation detection framework through a combination of polarimetric decomposition method and a Random Forest classifier. Validation of the established model with compiled ground references shows that the incorporation of linear polarizations with polarimetric decomposition and terrain variables significantly enhances the accuracy of inundation classification, and the Kappa statistic increases to 91.4% from 64.3% with linear polarizations alone. This data set contains inundation extent information of four UAVSAR flight lines (i.e., 13510, 31509, 32023 and 35303) with at least four days’ observations from Sep 18 to Sep 23, corresponding to the area covering the Neuse, Cape Fear, and Lumbee Rivers as well as their tributaries in Eastern North Carolina
DOI: 10.25952/9g6z-mm73
title: Airfields of the Commonwealth

description: This dataset was created as part of Daniel J. Leahy's 2018 Bachelor of Arts with Honours project investigating the archaeology of airfields utilised by schools of the Empire Air Training Scheme during the Second World War. Sites include those in Australia, Canada, New Zealand, Zimbabwe (formerly Southern Rhodesia) and South Africa. Similar sites utilised by the British Flying Training Schools in the United States have also been included.<br>
Each site is recorded by its latitude, longitude, and UTM coordinates in the standard of the World Geodetic System 1984 (WGS-84). A raw text (CSV) file has been included as well as a PDF document of how this data was formatted to appear as Appendix A in Leahy's 2018 Honours thesis.
description: This dataset was created as part of Daniel J. Leahy's 2018 Bachelor of Arts with Honours project investigating the archaeology of airfields utilised by schools of the Empire Air Training Scheme during the Second World War. Sites include those in Australia, Canada, New Zealand, Zimbabwe (formerly Southern Rhodesia) and South Africa. Similar sites utilised by the British Flying Training Schools in the United States have also been included.<br>
Each site is recorded by its latitude, longitude, and UTM coordinates in the standard of the World Geodetic System 1984 (WGS-84). A raw text (CSV) file has been included as well as a PDF document of how this data was formatted to appear as Appendix A in Leahy's 2018 Honours thesis.
DOI: 10.5281/zenodo.5635390
title: Scientific names used for the South American sea lion in peer-review papers (2010-2020)

description: The valid specific name of the South American sea lion was controversial for many years since <em>Otaria flavescens</em> (Shaw, 1800) and <em>Otaria byronia</em> (de Blainville, 1820) were the disputing designations. The present database summarizes the use of both names in peer-reviewed papers obtain in Google Scholar for the period 2010-2020.
DOI: 10.5281/zenodo.5635389
title: Scientific names used for the South American sea lion in peer-review papers (2010-2020)

description: The valid specific name of the South American sea lion was controversial for many years since <em>Otaria flavescens</em> (Shaw, 1800) and <em>Otaria byronia</em> (de Blainville, 1820) were the disputing designations. The present database summarizes the use of both names in peer-reviewed papers obtain in Google Scholar for the period 2010-2020.
DOI: 10.6084/m9.figshare.16910905.v1
title: Data of Inflammatory Parameters after Anti-coagulant among Moderate, Severe, and Critically Ill COVID-19 Patients

description: This dataset consists of 331 enrolled patients for a study entitled "The Improvement of Inflammatory Markers and Disease Progression among Moderate, Severe, and Critically Ill COVID-19 Patients: A Study from Two-Second Referral Hospitals in Surabaya, Indonesia". We recorded baseline characteristics and laboratory parameters in three timeframes of evaluation.
DOI: 10.5281/zenodo.5635445
title: Rock physics models of gas hydrate bearing sediments – the classification, simulation workflow, and challenges

description: This study reviews the rock physics models for simulating the elastic properties of gas hydrate bearing sediments. Considering that it is confusing to select the appropriate model for a specific study from the various models, we classify the models into five categories according to different principles. We also summarize a general workflow of the modeling process, elaborate the possible models in each step and bring up the potential sources of uncertainties. Besides, we explicate the general problems of the current models and raise several potential research directions. This study provides us a clear view of the rock physics models, the associated uncertainties, as well as the general modeling workflow of gas hydrate bearing sediments, and also provides some implications for future studies.
DOI: 10.5281/zenodo.5635444
title: Rock physics models of gas hydrate bearing sediments – the classification, simulation workflow, and challenges

description: This study reviews the rock physics models for simulating the elastic properties of gas hydrate bearing sediments. Considering that it is confusing to select the appropriate model for a specific study from the various models, we classify the models into five categories according to different principles. We also summarize a general workflow of the modeling process, elaborate the possible models in each step and bring up the potential sources of uncertainties. Besides, we explicate the general problems of the current models and raise several potential research directions. This study provides us a clear view of the rock physics models, the associated uncertainties, as well as the general modeling workflow of gas hydrate bearing sediments, and also provides some implications for future studies.
DOI: 10.6084/m9.figshare.16910164.v2
title: Depth-dependent drivers of soil microbial necromass carbon across Tibetan alpine grasslands

description: This dataset is composed of plant carbon input and and soil physicochemical<i> </i>properties (soil temperature, soil moisture, pH, microbial biomass carbon)<i>, </i>and soil microbial necromass carbon of 36 sites on the Tibetan Plateau.<br><br>
DOI: 10.25919/f35d-0v60
title: Parkes observations for project P1141 semester 2021OCTS_01

description: Radio giant pulses (GPs) have been observed since the discovery of the Crab pulsar more than 50 years ago. Nevertheless the origins of this apparently irregular form of radio emission are still not understood. While their characteristics indicate the existence of a coherent emission mechanism, the search for an incoherent emission component via multi-wavelength correlation studies provides one way to identify potential emission regions in the magnetosphere of the pulsar. With the present proposal, we address the radio GP emission from PSR J0540-6919 (the Crab twin) and seek to search for a correlation with its X-ray emission. A recent study of this kind for the Crab pulsar proved to be successful (Enoto et al.\,2021). Our proposed study is to the best of our knowledge the first of its kind together with the Neutron Star Interior Composition ExploreR (NICER) for this particular source and will shed light on the question of whether correlations with X-ray emission are a characteristic of ordinary pulsars with radio GP emission. Such knowledge will be useful in unraveling whether there are different populations of radio GPs in the case of ordinary and millisecond pulsars.
DOI: 10.25345/c5cp0t
title: MassIVE MSV000088291 - B metadata-massive datasets upload-2021-11-1
title: Screening and identifying PAs of chinese medicines based on UHPLC-Q-Exactive mass spectrometry
DOI: 10.5281/zenodo.5635466
title: Base de datos del Mapeo Sistemático - Adicción a los videojuegos en linea y conductas agresivas

description: Base de datos con la lista de los articulos utilizados para la elaboracion del articulo sobre mapeo sistematico de adiccion a los videojuegos en linea y conductas agresivas.
DOI: 10.5281/zenodo.5635465
title: Base de datos del Mapeo Sistemático - Adicción a los videojuegos en linea y conductas agresivas

description: Base de datos con la lista de los articulos utilizados para la elaboracion del articulo sobre mapeo sistematico de adiccion a los videojuegos en linea y conductas agresivas.
DOI: 10.3886/e139681
title: Promises and pitfalls of using computer vision to make inferences about landscape preferences: Evidence from an urban-proximate park system (data and code)

description: We compare preferences for landscape features derived through a computer vision algorithm (Google Cloud Vision) used to analyze social media photographs with preferences derived through a traditional on-site intercept survey. We surveyed visitors in Boulder Open Space and Mountain Parks lands in Colorado (USA) in May and June, 2018. We downloaded all Flickr photographs within Boulder Open Space and Mountain Parks lands from 2004 - 2018, and ran the photographs through Google Cloud Vision to get up to 10 labels for each image. We compare the content in Flickr photographs to the features that visitors say positively impacted their experience on surveys.<br><br>This paper is currently under review.<br><br><b>Contents of this repository:</b><br><br><b>GoogleVision: </b><br>Contains raw data exported from Google Vision, as well as a codebook for how we coded each label to match the landscape categories we asked about in the survey. Also contains a full database connecting the Google Vision labels and presence/absence of each feature to the Flickr data.<br><br><b>Code:</b><br>Contains one R script that makes the maps and runs spatial cluster analysis, and one R script that does all the data cleaning and analysis for the Flickr and survey data. You will need to download the contents in the GoogleVision, shapefiles, and survey folders to run this code. This folder also contains a Python script that we used to download Flickr data within Boulder through the Flickr API, and another R script used only to generate table E.1 in the supplementary material.<br><br><b>Shapefiles: </b><br>Contains all the spatial data needed to reproduce maps and run R code. This includes OSMP trails, trailheads, lands, landscape character areas, survey locations, and coordinates of Flickr points.<br><br><b>Survey:</b><br>Contains the data from a visitor survey in Boulder OSMP lands from May and June 2018 (in a CSV), as well as a codebook to interpret the data, and the survey instrument.<br><br>
description: Response Rates: 84.3% response rate to the visitor survey; 81.6% response rate after non-usable surveys were removed.
description: Presence of Common Scales: Several Likert-type scales were used in the visitor survey.
description: We distributed surveys at 18 Boulder Open Space and Mountain Parks trailheads in May and June 2018. We selected locations using a stratified sampling approach based on the six OSMP landscape character areas, combined with a spatial cluster analysis of geotagged Flickr data to determine the most popular locations in the parks.<br>
description: Visitors to Boulder's Open Space and Mountain Parks lands.
description: on-site questionnaire; web scraping;
DOI: 10.3886/e139681v1
title: Promises and pitfalls of using computer vision to make inferences about landscape preferences: Evidence from an urban-proximate park system (data and code)

description: We compare preferences for landscape features derived through a computer vision algorithm (Google Cloud Vision) used to analyze social media photographs with preferences derived through a traditional on-site intercept survey. We surveyed visitors in Boulder Open Space and Mountain Parks lands in Colorado (USA) in May and June, 2018. We downloaded all Flickr photographs within Boulder Open Space and Mountain Parks lands from 2004 - 2018, and ran the photographs through Google Cloud Vision to get up to 10 labels for each image. We compare the content in Flickr photographs to the features that visitors say positively impacted their experience on surveys.<br><br>This paper is currently under review.<br><br><b>Contents of this repository:</b><br><br><b>GoogleVision: </b><br>Contains raw data exported from Google Vision, as well as a codebook for how we coded each label to match the landscape categories we asked about in the survey. Also contains a full database connecting the Google Vision labels and presence/absence of each feature to the Flickr data.<br><br><b>Code:</b><br>Contains one R script that makes the maps and runs spatial cluster analysis, and one R script that does all the data cleaning and analysis for the Flickr and survey data. You will need to download the contents in the GoogleVision, shapefiles, and survey folders to run this code. This folder also contains a Python script that we used to download Flickr data within Boulder through the Flickr API, and another R script used only to generate table E.1 in the supplementary material.<br><br><b>Shapefiles: </b><br>Contains all the spatial data needed to reproduce maps and run R code. This includes OSMP trails, trailheads, lands, landscape character areas, survey locations, and coordinates of Flickr points.<br><br><b>Survey:</b><br>Contains the data from a visitor survey in Boulder OSMP lands from May and June 2018 (in a CSV), as well as a codebook to interpret the data, and the survey instrument.<br><br>
description: Response Rates: 84.3% response rate to the visitor survey; 81.6% response rate after non-usable surveys were removed.
description: Presence of Common Scales: Several Likert-type scales were used in the visitor survey.
description: We distributed surveys at 18 Boulder Open Space and Mountain Parks trailheads in May and June 2018. We selected locations using a stratified sampling approach based on the six OSMP landscape character areas, combined with a spatial cluster analysis of geotagged Flickr data to determine the most popular locations in the parks.<br>
description: Visitors to Boulder's Open Space and Mountain Parks lands.
description: on-site questionnaire; web scraping;
DOI: 10.6084/m9.figshare.16910995
title: Velocity, attenuation and permeability of S-wave in Indiana limestone

description: Velocity, the quality factor, and permeability of S-wave in water-saturated Indiana limestone<br>
DOI: 10.6084/m9.figshare.16910995.v1
title: Velocity, attenuation and permeability of S-wave in Indiana limestone

description: Velocity, the quality factor, and permeability of S-wave in water-saturated Indiana limestone<br>