103,259 research outputs found
Children's Health: Evaluating the Impact of Digital Technology. Final Report for Sunderland City Council.
No full textEXECUTIVE SUMMARY
The Children’s Health project sponsored by the City of Sunderland Digital Challenge project examined the impact of providing health-focused digital technologies to children aged 11-15 years, in terms of their usage and requirements of such technologies, and their subsequent behavioural changes.
The empirical study ran with three groups of six children over a period of seven weeks for each group. A console-based exercise game and an exercise-focused social website were used in the study and the focus was on opportunistic (unstructured/unplanned) exercise.
The emergent findings are:
• Data collected about physical activity must be more extensive than simple step counts.
• Data collection technologies for activities must be ubiquitous but invisible.
• Social interaction via technology is expected; positive messages reinforcing attainments of goals are valued; negative feedback is seen as demotivating.
• participants were very open to sharing information (privacy was not a concern).
• Authority figures have a significant impact on restricting adolescents’ use of technologies.
This document reports the how the study was conducted, analyses the findings and draws conclusions from these regarding how to use digital technologies to improve and/or maintain the physical activity levels of children throughout their adolescence and on into adulthood.
The appendices provide the detailed (anonymised) data collected during the study and the background literature review
Les constructions navales à Sunderland
No full textMerlat O. Les constructions navales à Sunderland. In: Annales de Géographie, t. 44, n°250, 1935. pp. 420-423
Contract accounting and costing in the Sunderland shipbuilding industry, 1818-1917
No full textBy the 1850s, Sunderland claimed to be the largest shipbuilding town in the world. This paper analyses the social, economic and organizational circumstances of the Sunderland shipbuilding industry and traces the development of contact accounting and costing in four of its firms
Letter, [Author unclear] to Paulina T. Merritt
No full textHandwritten letter to Paulina Merritt from an unknown author, October 1, 1876.
Backhouse (T.-W.)· — Observations of variable stars, made in the years 1866-1904. (Publications of West Hendon house Observatory , Sunderland, n° 3.)
No full textBackhouse (T.-W.)· — Observations of variable stars, made in the years 1866-1904. (Publications of West Hendon house Observatory , Sunderland, n° 3.). In: Bulletin astronomique, tome 23, 1906. p. 341
Waterjet and Creative Innovation in Higher Education
No full textThis chapter provides an in-depth exploration of the innovative integration of water-jet technology in art and design higher education, in the Glass and Ceramics Department at the University of Sunderland, UK. This was the first educational institution in the UK to acquire a waterjet specifically for research and artistic experimentation. Vanessa Cutler’s ground-breaking research pioneered a unique approach with waterjet technology, empowering undergraduate, postgraduate, and PhD students to directly integrate this advanced precision digital technology into their creative endeavours
Handwritten biographical information on Paulina T. McClung Merritt
No full textA handwritten biography of Paulina T. McClung Merritt by an unknown author, 1892.
Heterogeneous and tissue-specific regulation of effector T cell responses by IFN-gamma during Plasmodium berghei ANKA infection.
No full textIFN-γ and T cells are both required for the development of experimental cerebral malaria during Plasmodium berghei ANKA infection. Surprisingly, however, the role of IFN-γ in shaping the effector CD4(+) and CD8(+) T cell response during this infection has not been examined in detail. To address this, we have compared the effector T cell responses in wild-type and IFN-γ(-/-) mice during P. berghei ANKA infection. The expansion of splenic CD4(+) and CD8(+) T cells during P. berghei ANKA infection was unaffected by the absence of IFN-γ, but the contraction phase of the T cell response was significantly attenuated. Splenic T cell activation and effector function were essentially normal in IFN-γ(-/-) mice; however, the migration to, and accumulation of, effector CD4(+) and CD8(+) T cells in the lung, liver, and brain was altered in IFN-γ(-/-) mice. Interestingly, activation and accumulation of T cells in various nonlymphoid organs was differently affected by lack of IFN-γ, suggesting that IFN-γ influences T cell effector function to varying levels in different anatomical locations. Importantly, control of splenic T cell numbers during P. berghei ANKA infection depended on active IFN-γ-dependent environmental signals--leading to T cell apoptosis--rather than upon intrinsic alterations in T cell programming. To our knowledge, this is the first study to fully investigate the role of IFN-γ in modulating T cell function during P. berghei ANKA infection and reveals that IFN-γ is required for efficient contraction of the pool of activated T cells
Developing an AI algorithm to detect predictors of poor performance in a self-administered, web-based digital biomarker for Alzheimer’s Disease: proof of concept.
No full textAuthor List & Affiliations: Joe Butler, [email protected]; School of Psychology, University of Sunderland, Sunderland, UK. Helen McArdle Nursing and Care Research Institute, University of Sunderland, Sunderland, UK. Adewale Samuel Owobowale, [email protected]; School of Computer Science, University of Sunderland, Sunderland, UK Tamlyn J. Watermeyer; [email protected]; Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, College of Medicine & Veterinary Sciences; University of Edinburgh, Edinburgh, UK & Faculty of Health & Life Sciences, Northumbria University, Newcastle-Upon-Tyne, UK Sam Danso*; [email protected]; School of Computer Science, University of Sunderland, Sunderland, UK & Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, College of Medicine & Veterinary Sciences; University of Edinburgh, Edinburgh, UK
Mario Parra-Rodrigues*; [email protected] School of Psychology, University of Strathclyde, Glasgow, UK. Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, College of Medicine & Veterinary Sciences; University of Edinburgh, Edinburgh, UK.
*Co-Supervising authors
Background:
The Visual Short Term Memory Binding (VSTMBT) task is a gold-standard cognitive assessment for the identification of Alzheimer's Disease and associated risk factors, including during the preclinical stage. Previous work from our group (Butler, Watermeyer,...& Parra 2024) demonstrated in a small number (n=37) of healthy older adults that data collected using a web-based, self-administrated version of the task provides data comparable to that collected in laboratory conditions. Here we incorporated a machine learning (ML) approach to explore impacts of risk factors on this task in a larger digital dataset.
Methods:
Using data (n=359) collected from an online study incorporating the VSTMBT and lifestyle, psychological, and health data, we created a Binding Cost score which has shown to approximate AD-related neuropathology (Parra et al., 2024). This categorised participants as either strong-binders (SB – indicative of no pathology; 85.9% percent of the sample) or weak-binders (WB – indicative of pathology; 14.1%).
We trained three ML algorithms (Random Forest (RF), K-Nearest Neighbour (KNN) and Decision Tree (DT) by employing SMOTE technique to overcome the imbalance in group distribution. We applied a 10-fold cross-validation with hyper-parameter tuning to optimise the models based on the selected variables (including age, sex, education, BMI, loneliness, and existing-morbidities) to predict individual’s risk of cognitive impairment based on the groupings (SB vs WB). Models’ performances were examined on 20% of unseen test set.
Results:
Aside from existing morbidities, which were higher in weak binders (WB = 0.41 (sd+2=0.79); SB =0.22(sd+2=0.49); t=2.21; p=0.03), other measures did not differ between groups. Regarding performance of the ML models, RF achieved the best performance (accuracy: 91%; recall=91%; precision=91%; AUC=97%) compared to KNN (accuracy: 81%; recall=81%; precision=84%; AUC=91%) and DT (accuracy: 81%; recall=81%; precision=82%; AUC= 85%). Feature importance analysis of the RF model suggests mental health, BMI, and fatigue have the highest impact on the prediction model, while sex and multi-morbidity score have the least impact.
Conclusions:
The study underscores the potential of web-based cognitive assessments and ML for remote monitoring and early identification of AD risk factors, contributing to the advancement of accessible tools for early detection
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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