Nature of band-gap states in V-doped TiO2 revealed by resonant photoemission

Band-gap states in V-doped TiO2 have been studied by photoemission spectroscopy over a range of photon energies encompassing the Ti 3p and V 3p core thresholds. The states show resonant enhancement at photon energies significantly higher than found for Ti 3d states introduced into TiO2 by oxygen deficiency or alkalimetal adsorbates. This demonstrates that the gap states relate to electrons trapped on dopant V cations rather than host Ti cations

Food safety vulnerability: Neighbourhood determinants of non-compliant establishments in England and Wales

This paper utilises logistic regression to identify ecological determinants of non-compliant food outlets in England and Wales. We consider socio-demographic, urbanness and business type features to better define vulnerable populations based on the characteristics of the area within which they live. We find a clear gradient of association between deprivation and non-compliance, with outlets in the most deprived areas 25% less likely (OR = 0.75) to meet hygiene standards than those in the least deprived areas. Similarly, we find outlets located in conurbation areas have a lower probability of compliance (OR = 0.678) than establishments located in rural and affluent areas. Therefore, individuals living in these neighbourhoods can be considered more situationally vulnerable than those living in rural and non-deprived areas. Whilst comparing compliance across business types, we find that takeaways and sandwich shops (OR = 0.504) and convenience retailers (OR = 0.905) are significantly less likely to meet hygiene standards compared to restaurants. This is particularly problematic for populations who may be unable to shop outside their immediate locality. Where traditional food safety interventions have failed to consider the prospect of increased risk based on proximity to unsafe and unhygienic food outlets, we re-assess the meaning of vulnerability by considering the type of neighbourhoods within which non-compliant establishments are located. In-lieu of accurate foodborne illness data, we recommend prioritised inspections for outlets in urban and deprived areas. Particularly takeaways, sandwich shops and small convenience retailers

Application of Machine Learning Algorithms to Predict Body Condition Score from Liveweight Records of Mature Romney Ewes

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The Effect of Herbage Availability and Season of Year on the Rate of Liveweight Loss during Weighing of Fasting Ewe Lambs

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Predictors of postprandial glycaemia, insulinaemia and insulin resistance in adolescents

Postprandial glycaemia and insulinaemia are important risk factors for type 2 diabetes. The prevalence of insulin resistance in adolescents is increasing, but it is unknown how adolescent participant characteristics such as BMI, waist circumference, fitness and maturity offset may explain responses to a standard meal. The aim of the present study was to examine how such participant characteristics affect the postprandial glycaemic and insulinaemic responses to an ecologically valid mixed meal. Data from the control trials of three separate randomised, crossover experiments were pooled, resulting in a total of 108 participants (52 boys, 56 girls; age: 12.5±0.6 y; BMI: 19.05±2.66 kg·m-2). A fasting blood sample was taken for the calculation of fasting insulin resistance, using the HOMA-IR model. Further capillary blood samples were taken before and 30-, 60- and 120-min after a standardised lunch, providing 1.5 g.kg-1 body mass of carbohydrate, for the quantification of blood glucose and plasma insulin total area under the curve (tAUC). Hierarchical multiple linear regression demonstrated significant predictors for plasma insulin tAUC were waist circumference, physical fitness and HOMA-IR (F(3, 98)=36.78, p<.001, Adj. R2=.515). The variance in blood glucose tAUC was not significantly explained by the predictors used (F(7, 94)=1.44, p=.198). Significant predictors for HOMA-IR were BMI and maturity offset (F(2, 102)=14.06, p<.001, Adj. R2=.021). In summary, the key findings of the study are that waist circumference, followed by physical fitness, best explained the insulinemic response to an ecologically valid standardised meal in adolescents. This has important behavioural consequences because these variables can be modified

Effect of exercise duration on postprandial glycaemic and insulinaemic responses in adolescents

High-intensity intermittent exercise (HIIE) is a potential intervention to manage hyperglycaemia and insulin resistance in adolescents. The aim of this study was to determine the optimum duration of HIIE to reduce postprandial glycaemic and insulinaemic responses in adolescents and the longevity of the response. Thirty-nine participants (12.4 ± 0.4 year) completed a 30- and 60-min exercise trial (Loughborough Intermittent Shuttle Test) and a rested control trial in a randomised crossover design. Capillary blood samples were taken at baseline, immediately and 1-h post-exercise; and 30, 60 and 120 min following a standardised lunch (day one) and a standardised breakfast 24-h post-exercise. Plasma insulin total area under the curve (tAUC) following lunch was lower following 60-min HIIE (21,754 ± 16,861 pmol·L−1 × 120 min, p = 0.032) and tended to be lower following 30-min HIIE (24,273 ± 16,131 pmol·L−1 × 120 min, p = 0.080), when compared with the resting condition (26,931 ± 21,634 pmol·L−1 × 120 min). Blood glucose concentration was lower 1-h post-exercise following 30-min HIIE (3.6 ± 0.6 mmol·L−1) when compared to resting (4.1 ± 0.9 mmol·L−1, p = 0.001). Blood glucose and plasma insulin concentration did not differ across trials on day two. Shorter bouts of HIIE (30-min), as well as a 60-min bout, reduced the postprandial insulinaemic response to lunch, an ecologically valid marker of insulin sensitivity. As the beneficial effects of HIIE were limited to 3 h post-exercise, adolescents are recommended to engage daily HIIE to enhance metabolic health

The effect of nutrition and body condition of triplet-bearing ewes during late pregnancy on the behaviour of ewes and lambs

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Mammary Gland Structures Are Not Affected by an Increased Growth Rate of Yearling Ewes Post-Weaning but Are Associated with Growth Rates of Singletons

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Effect of football activity and physical fitness on information processing, inhibitory control and working memory in adolescents

Background: Whilst an acute bout of exercise has been shown to enhance subsequent cognition, including in adolescents, the effects of team games (of which Football is the most popular) has received little attention. Therefore, this study examined: the effect of an acute bout of outdoor Football activity on information processing, inhibitory control, working memory and circulating brain-derived neurotrophic factor (BDNF) in adolescents; the effect of physical fitness on cognition and; the moderating effect of physical fitness on the acute exercise responses. Methods: Following familiarisation, 36 adolescents (16 girls) took part in two trials (60-min Football and 60-min seated rest) separated by 7-d in a counterbalanced, crossover design. Information processing and inhibitory control (Stroop Test), and working memory (Sternberg Paradigm) were assessed 30-min before exercise/rest and immediately, 45- and 90-min post-exercise/rest. Capillary blood samples were obtained before exercise/rest and up to 120-min post-exercise/rest. The median split of distance covered on the MSFT was used to divide the group into high- and low-fit groups. Results: Performance on the cognitive function tasks was similar between Football and seated rest (trial*time interactions; all p > .05). However, the high-fit group had overall quicker response times on both levels of the Stroop Task and all three levels of the Sternberg Paradigm (main effect of fitness; all p  .05). Conclusion: The present study shows that higher levels of physical fitness are beneficial for cognitive function and provides novel evidence that an ecologically valid, and popular, form of exercise is beneficial for working memory following exercise, in high-fit participants only

Predicting Food Safety Compliance for Informed Food Outlet Inspections: A Machine Learning Approach

Consumer food environments have transformed dramatically in the last decade. Food outlet prevalence has increased, and people are eating food outside the home more than ever before. Despite these developments, national spending on food control has reduced. The National Audit Office report that only 14% of local authorities are up to date with food business inspections, exposing consumers to unknown levels of risk. Given the scarcity of local authority resources, this paper presents a data-driven approach to predict compliance for newly opened businesses and those awaiting repeat inspections. This work capitalizes on the theory that food outlet compliance is a function of its geographic context, namely the characteristics of the neighborhood within which it sits. We explore the utility of three machine learning approaches to predict non-compliant food outlets in England and Wales using openly accessible socio-demographic, business type, and urbanness features at the output area level. We find that the synthetic minority oversampling technique alongside a random forest algorithm with a 1:1 sampling strategy provides the best predictive power. Our final model retrieves and identifies 84% of total non-compliant outlets in a test set of 92,595 (sensitivity = 0.843, specificity = 0.745, precision = 0.274). The originality of this work lies in its unique and methodological approach which combines the use of machine learning with fine-grained neighborhood data to make robust predictions of compliance