Encapsulating sustainability principles for structural design of buildings

Adaptive re-use of buildings is seen by many as a key mechanism for developing a sustainable urban environment. How many buildings are actually designed with adaptive re-use as one of the requirements? This paper is concerned with how new building designs can take into account the future need for renovation, revamp and retrofit. At the outset of a building project, one cannot know for sure what modifications will be needed in the future. However, there are considerations that can be incorporated into the initial design and construction that will facilitate future renovations. Likewise there are practices that are undertaken now that will make renovations more difficult in the future. This preparation for the future re-use of buildings is an area of sustainability that has not received much attention. Examples of buildings that were originally designed with future modifications incorporated illustrate that long term thinking can lead to long term gain. There are also barriers to the long view. Economic drivers favour short term gain. The costs are levied up-front but the return on investment is many years later. The paper finishes with two case studies that demonstrate a long term sustainable approach

A brief introduction to recent developments in population-based structural health monitoring

This is the final version. Available from the publisher via the DOI in this record.One of the main problems in data-based Structural Health Monitoring (SHM), is the scarcity of measured data corresponding to damage states in the structures of interest. One approach to solving this problem is to develop methods of transferring health inferences and information between structures in an identified population—Population-based SHM (PBSHM). In the case of homogenous populations (sets of nominally-identical structures, like in a wind farm), the idea of the form has been proposed which encodes information about the ideal or typical structure together with information about variations across the population. In the case of sets of disparate structures—heterogeneous populations—transfer learning appears to be a powerful tool for sharing inferences, and is also applicable in the homogenous case. In order to assess the likelihood of transference being meaningful, it has proved useful to develop an abstract representation framework for spaces of structures, so that similarities between structures can formally be assessed; this framework exploits tools from graph theory. The current paper discusses all of these very recent developments and provides illustrative examplesEngineering and Physical Sciences Research Council (EPSRC

A data-centric approach to generative modelling for 3D-printed steel.

The emergence of additive manufacture (AM) for metallic material enables components of near arbitrary complexity to be produced. This has potential to disrupt traditional engineering approaches. However, metallic AM components exhibit greater levels of variation in their geometric and mechanical properties compared to standard components, which is not yet well understood. This uncertainty poses a fundamental barrier to potential users of the material, since extensive post-manufacture testing is currently required to ensure safety standards are met. Taking an interdisciplinary approach that combines probabilistic mechanics and uncertainty quantification, we demonstrate that intrinsic variation in AM steel can be well described by a generative statistical model that enables the quality of a design to be predicted before manufacture. Specifically, the geometric variation in the material can be described by an anisotropic spatial random field with oscillatory covariance structure, and the mechanical behaviour by a stochastic anisotropic elasto-plastic material model. The fitted generative model is validated on a held-out experimental dataset and our results underscore the need to combine both statistical and physics-based modelling in the characterization of new AM steel products

A data-centric approach to generative modelling for 3D-printed steel.

The emergence of additive manufacture (AM) for metallic material enables components of near arbitrary complexity to be produced. This has potential to disrupt traditional engineering approaches. However, metallic AM components exhibit greater levels of variation in their geometric and mechanical properties compared to standard components, which is not yet well understood. This uncertainty poses a fundamental barrier to potential users of the material, since extensive post-manufacture testing is currently required to ensure safety standards are met. Taking an interdisciplinary approach that combines probabilistic mechanics and uncertainty quantification, we demonstrate that intrinsic variation in AM steel can be well described by a generative statistical model that enables the quality of a design to be predicted before manufacture. Specifically, the geometric variation in the material can be described by an anisotropic spatial random field with oscillatory covariance structure, and the mechanical behaviour by a stochastic anisotropic elasto-plastic material model. The fitted generative model is validated on a held-out experimental dataset and our results underscore the need to combine both statistical and physics-based modelling in the characterization of new AM steel products

Changes in ponderal index and body mass index across childhood and their associations with fat mass and cardiovascular risk factors at age 15

Background: Little is known about whether associations between childhood adiposity and later adverse cardiovascular health outcomes are driven by tracking of overweight from childhood to adulthood and/or by vascular and metabolic changes from childhood overweight that persist into adulthood. Our objective is to characterise associations between trajectories of adiposity across childhood and a wide range of cardiovascular risk factors measured in adolescence, and explore the extent to which these are mediated by fat mass at age 15. Methods and Findings: Using data from the Avon Longitudinal Study of Parents and Children, we estimated individual trajectories of ponderal index (PI) from 0-2 years and BMI from 2-10 years using random-effects linear spline models (N = 4601). We explored associations between PI/BMI trajectories and DXA-determined total-body fat-mass and cardiovascular risk factors at 15 years (systolic and diastolic blood pressure, fasting LDL-and HDL-cholesterol, triglycerides, C-reactive protein, glucose, insulin) with and without adjustment for confounders. Changes in PI/BMI during all periods of infancy and childhood were associated with greater DXA-determined fat-mass at age 15. BMI changes in childhood, but not PI changes from 0-2 years, were associated with most cardiovascular risk factors in adolescence; associations tended to be strongest for BMI changes in later childhood (ages 8.5-10), and were largely mediated by fat mass at age 15. Conclusion: Changes in PI/BMI from 0-10 years were associated with greater fat-mass at age 15. Greater increases in BMI from age 8.5-10 years are most strongly associated with cardiovascular risk factors at age 15, with much of these associations mediated by fat-mass at this age. We found little evidence supporting previous reports that rapid PI changes in infancy are associated with future cardiovascular risk. This study suggests that associations between early overweight and subsequent adverse cardiovascular health are largely due to overweight children tending to remain overweight

Physical activity attitudes, intentions and behaviour among 18-25 year olds: a mixed method study

Peer reviewedPublisher PD

Ferumoxytol-enhanced MRI in patients with prior cardiac transplantation.

Objectives: Ultra-small superparamagnetic particles of iron oxide (USPIO)-enhanced MRI can detect cellular inflammation within tissues and may help non-invasively identify cardiac transplant rejection. Here, we aimed to determine the normal reference values for USPIO-enhanced MRI in patients with a prior cardiac transplant and examine whether USPIO-enhanced MRI could detect myocardial inflammation in patients with transplant rejection. Methods: Ten volunteers and 11 patients with cardiac transplant underwent T2, T2* and late gadolinium enhancement 1.5T MRI, with further T2* imaging at 24 hours after USPIO (ferumoxytol, 4 mg/kg) infusion, at baseline and 3 months. Results: Ten patients with clinically stable cardiac transplantation were retained for analysis. Myocardial T2 values were higher in patients with cardiac transplant versus healthy volunteers (53.8±5.2 vs 48.6±1.9 ms, respectively; p=0.003). There were no differences in the magnitude of USPIO-induced change in R2* in patients with transplantation (change in R2*, 26.6±7.3 vs 22.0±10.4 s-1 in healthy volunteers; p=0.28). After 3 months, patients with transplantation (n=5) had unaltered T2 values (52.7±2.8 vs 52.12±3.4 ms; p=0.80) and changes in R2* following USPIO (29.42±8.14 vs 25.8±7.8 s-1; p=0.43). Conclusion: Stable patients with cardiac transplantation have increased myocardial T2 values, consistent with resting myocardial oedema or fibrosis. In contrast, USPIO-enhanced MRI is normal and stable over time suggesting the absence of chronic macrophage-driven cellular inflammation. It remains to be determined whether USPIO-enhanced MRI may be able to identify acute cardiac transplant rejection. Trial registration number: NCT02319278349 (https://clinicaltrials.gov/ct2/show/NCT02319278) Registered 03.12.2014 EUDraCT 2013-002336-24

Body image, body dissatisfaction and weight status in south asian children: a cross-sectional study

Background Childhood obesity is a continuing problem in the UK and South Asian children represent a group that are particularly vulnerable to its health consequences. The relationship between body dissatisfaction and obesity is well documented in older children and adults, but is less clear in young children, particularly South Asians. A better understanding of this relationship in young South Asian children will inform the design and delivery of obesity intervention programmes. The aim of this study is to describe body image size perception and dissatisfaction, and their relationship to weight status in primary school aged UK South Asian children. Methods Objective measures of height and weight were undertaken on 574 predominantly South Asian children aged 5-7 (296 boys and 278 girls). BMI z-scores, and weight status (underweight, healthy weight, overweight or obese) were calculated based on the UK 1990 BMI reference charts. Figure rating scales were used to assess perceived body image size (asking children to identify their perceived body size) and dissatisfaction (difference between perceived current and ideal body size). The relationship between these and weight status were examined using multivariate analyses. Results Perceived body image size was positively associated with weight status (partial regression coefficient for overweight/obese vs. non-overweight/obese was 0.63 (95% CI 0.26-0.99) and for BMI z-score was 0.21 (95% CI 0.10-0.31), adjusted for sex, age and ethnicity). Body dissatisfaction was also associated with weight status, with overweight and obese children more likely to select thinner ideal body size than healthy weight children (adjusted partial regression coefficient for overweight/obese vs. non-overweight/obese was 1.47 (95% CI 0.99-1.96) and for BMI z-score was 0.54 (95% CI 0.40-0.67)). Conclusions Awareness of body image size and increasing body dissatisfaction with higher weight status is established at a young age in this population. This needs to be considered when designing interventions to reduce obesity in young children, in terms of both benefits and harms