398 research outputs found
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Characterization and evaluation data from the National Fruit Collection 2025_Cherry
No full textData are characterization and evaluation scores and measures collected during the curation of the National Fruit Collection (cherry collection). Data were largely collected in line with the published ECPGR Passport and Priority Descriptors for Cherry Genetic Resources with additional locally agreed descriptors. The dataset contains scores across 14 traits from 369 accessions
Data used in the article 'Effect of rare sugars on physical and sensory properties of doughs and biscuits'
Full text linkThis dataset contains data obtained from experimental work on the physical and sensory properties of doughs and biscuits elaborated with different sugars (e.g., sucrose, fructose, allulose, tagatose), where fructose, allulose, and tagatose were used for total sucrose replacement. The data was obtained using a Kenwood Mixer, a convection oven, a differential scanning calorimeter (DSC), a rheometer, a texture analyser, a moisture analyser, a water activity analyser, a calliper, and a Chroma meter (colour). The sensory analysis data was obtained from trained panellists from MMR Research Worldwide Ltd
Dataset supporting: Co-designing a research agenda for UK agroforestry using a multi-actor approach
Full text linkThese survey data were collected to identify research suggestions (questions) for in-field agroforestry in the UK. These suggestions were then used to create a list of high-priority research questions to make a research agenda (see Hood et al In Review for further information). The online survey was distributed via personal networks, mailing lists, and social media in October and November 2023. The survey was open to anyone working in industries relevant to agroforestry (e.g. farmers, tree nurseries, policy makers, researchers, foresters, NGOs). Respondents were invited to submit 1-4 research priorities each (see attached survey for further information). We also included demographic questions on respondents’ gender, age, current and previous roles, and experience of working in, studying, establishing, or managing different agroforestry systems
Dataset to support 'Rapid and accurate biological sex estimation by LAP-MALDI MS analysis of child teeth'
No full textThis dataset includes raw and processed data demonstrating the use of a new rapid workflow for estimating the biological sex of human individuals using liquid atmospheric-pressure matrix-assisted laser desorption/ionisation (LAP-MALDI) mass spectrometry (MS) and MS/MS analysis of amelogenin peptides. By applying a straightforward classification rule that leverages a panel of MS and MS/MS ion signals, it was also possible to estimate the biological sex of deciduous teeth.
All teeth were obtained from a single site (St. Oswald’s Priory, Gloucester, UK) and together with their skeletal remains curated by the Department of Archaeology at the University of Reading.
All MS and MS/MS analyses were conducted using a modified Synapt G2-Si (Waters, Wilmslow, UK) equipped with a custom-built atmospheric pressure MALDI source.
Raw data were processed with Mascot Distiller (Version 2.8.5.0, 64-bit; Matrix Science, London, UK) for automated peak picking, with each raw data file analysed using three different signal-to-noise ratios (S/N): 2, 10, and 50
Vocabulary learning for visually impaired learners
Full text linkThe dataset consists of second language learning data from 32 Saudi learners of English (16 visually impaired and 16 sighted, aged 16 to 20) at three time points. At Time 1, quantitative data were collected through an English vocabulary knowledge test, a target vocabulary pre-test, and a listening comprehension test. At Time 2, quantitative data were collected from a vocabulary post-test. At time 3, quantitative test data were collected from a vocabulary delayed post-test. Lastly, quantitative data were collected from a vocabulary final delayed post-test to assess the effect of repetition. All vocabulary tests were meaning recognition tests
Data supporting: 'Mental illness stigma exacerbates anhedonia in Major Depressive Disorder (MDD): A participatory qualitative study'
No full textClinical depression, or Major Depressive Disorder (MDD), is a common and serious condition in young people, often characterised by persistent sadness, loss of interest, and emotional numbness. In this age group, MDD can substantially affect academic performance, relationships, and overall life satisfaction. While depressive symptoms are well documented, the role of stigma in exacerbating them—particularly anhedonia, characterised by reduced pleasure, motivation, and social engagement and often resistant to treatment—remains insufficiently understood. Stigma may further diminish motivation and social participation, increasing isolation and emotional disconnection.
This qualitative study explored how mental illness stigma influences anhedonia in young people with clinical symptoms of MDD. A core feature of the study was its participatory design: a youth advisory group co-developed the interview guide, providing input throughout the research process to ensure relevance, sensitivity, and alignment with young people’s lived experiences. This approach enabled the study to centre youth voices and priorities at every stage.
The findings provide novel, youth-informed evidence that stigma compounds anhedonia by undermining motivation, disrupting emotional connection, and reinforcing social withdrawal. These results highlight stigma as a previously overlooked mechanism contributing to anhedonia and underscore the value of co-produced research that elevates young people’s perspectives in mental health studies.
The dataset includes participants’ demographic information alongside responses to questionnaires assessing depression symptoms, stigma, anhedonia, motivation, and social participation, providing a comprehensive overview of the sample and key variables
North Atlantic polar low tracks from September 2008 to May 2009 from WRF simulations at 50, 25 and 12.5 km grid spacings
No full textThis dataset contains:
1. The model configuration files of three simulations conducted with the Advanced Research Weather Research and Forecasting (WRF) Model with 50, 25 and 12.5 km grid spacings. The domain is the North Atlantic and the period covered is 2008-09 to 2009-05.
2. The tracks of polar lows in each simulation.
3. Statistics of the characteristics of the polar low tracks and associated fields
L2 listening development within an informal digital learning of English listening (IDLEL) context
Full text linkThis dataset first includes questionnaire data collected from Chinese undergraduate EFL learners (aged 18-21) on self-regulated L2 listening (N = 523), listening anxiety (N = 427), and listening self-efficacy (N = 435). These data were used to conduct confirmatory factor analyses (CFA) to validate the latent constructs of the three questionnaires. Additionally, to explore the relationships among self-regulation, self-efficacy, listening anxiety, L2 listening proficiency, and IDLEL engagement (i.e., frequency, duration, diversity, and strategy use), another group of English-major EFL learners (N= 130, aged 18-20) were recruited. The collected data includes: 1) participants’ L2 listening proficiency, assessed through listening comprehension tests administered at the pretest (Week 1, N = 130), post-test (Week 6, N = 91), and delayed post-test (Week 19, N = 60); 2) participants’ pretest (N = 130) and post-test (N = 91) responses to Likert-scale questionnaire items on listening self-regulation, listening anxiety, and listening self-efficacy; 3) participants’ weekly (N = 91)records in E-logs from Week 2 to Week 5, documenting the diversity, frequency, and duration of their engagement in IDLEL activities, as well as the strategies used during those activities
Dataset supporting a study of cognition, emotion regulation, and mental health in Parkinson’s Disease
No full textThis dataset contains anonymised data from 103 individuals diagnosed with Parkinson’s Disease (PD), collected as part of a remote study investigating the relationships between cognitive functioning, emotion regulation strategies, and mental health outcomes. Data include demographic and clinical variables (e.g., age, gender, ethnicity, education, age of diagnosis, illness duration, levodopa equivalent daily dose, motor and non-motor aspects of daily living, and global cognition; performance-based cognitive tasks (Trail Making Test, Digit Span, Go/No-Go), self-reported functional cognitive impairment, and validated questionnaires assessing anxiety, depression, mental wellbeing and both cognitive and behavioural emotion regulation strategies. Data were collected via video call and online survey platforms. The dataset has been fully de-identified and stored in .csv format. It may be of interest to researchers studying cognition-emotion interactions, executive functioning, or non-motor symptoms in PD
Dataset supporting: Identifying knowledge barriers to agroforestry adoption and co-designing solutions to them
Full text linkThese interviews were conducted to identify the perceived knowledge barriers impacting farmers who are interested in adopting in-field agroforestry in the UK. The interview results were then used to co-create solutions to these barriers and create an educational agenda for UK agroforestry (see Hood et al In Review for further information). The interviews were conducted in-person at 1:1 meetings and two workshops from September 2023 – February 2024. I interviewed 27 farmers in total. I used a perception matrix in the interviews, which contained twelve elements and eight constructs to identify perceived knowledge barriers to agroforestry adoption (see attached Interview Questions). This perception matrix was situated within a three-part interview that included farm characteristics, the perception matrix, and socio-economic demographic questions