Size at birth and growth in childhood are thought to be important stages of development in our lifespan and are known to be important to the risk of infant and childhood health and development problems. Over recent years these important phases of early development have also been linked to our risk of illness in later life, particularly diabetes and coronary heart disease. South Asian populations are known to be at particular risk of diabetes (2 - 4 fold higher) and coronary heart disease (50 - 80% higher) and this may be due to them having a tendency for more fat compared to lean mass. At birth, South Asian babies are generally smaller and lighter but recent studies show that like South Asian adults, they have more fat than White British individuals. This greater fatness for a given weight could be very important to the risk of diabetes and coronary heart disease but so far the reasons for it are not very clear. It is possible that being diabetic during pregnancy, which is more common in South Asian women, 'overfeeds' the infant leading to greater fatness at birth and possibly throughout life. If this is true then later generations would also overfeed their infants during pregnancy and a cycle of poor health and development could be set in motion. This continuation of risk could be made worse by the changes in environment and lifestyle experienced by South Asians who migrate to the UK such as the availability of high energy diets, a culture of less exercise and rising rates of obesity. How patterns of growth from birth to childhood differ in South Asian and White British children could also affect differences in health between these two groups in relation to childhood infections and other childhood health problems and could even affect how well children do in school. However research in this area has often used poorly designed studies with too few participants to give accurate results. Using data and information from the Born in Bradford birth cohort study I will: 1.Look at whether how much a woman weighs at the start of pregnancy, how much weight she gains during pregnancy, her glucose (sugar) levels in pregnancy and whether she develops gestational diabetes, affect how much her child weighs and how fat they are at birth and also at age 4/5 years. I will look at whether the effect of any of these measurements is different depending on whether the mother and child are of Pakistani or White British origin. 2.Describe patterns of growth and differences in adiposity and blood pressure in UK born Pakistani origin children and UK born White British children 3.Look at whether different patterns of growth in UK born Pakistani origin and UK born White British children result in different rates of childhood infection and hospital admissions between these two groups. I will also look at whether different patterns of growth affect how well the children do in school. 4.Find out whether weight and fatness at birth and in childhood is different depending on whether parents and grandparents of Pakistani infants are born in the UK or South Asia. To do this I will combine existing information from the BiB cohort with new information collected for the first time as part of this proposal. I will train and support school nurses in Bradford to collect skinfold measurements (used to estimate fatness) and blood pressure alongside the height and weight measurements recorded for all reception age children in the UK, including good coverage in Bradford. These measurements will be collected over 2 consecutive school years (2013/2014 and 2014/2015) and will involve approximately 8000 children. Cord blood samples for the whole BiB cohort will be used to compare fat mass in Pakistani and White British infants at birth (approx 9000 samples). In addition I will merge information from routine health and education systems with the existing BiB data.

Imagine a future where autonomous systems are widely available to improve our lives. In this future, autonomous robots unobtrusively maintain the infrastructure of our cities, and support people in living fulfilled independent lives. In this future, autonomous software reliably diagnoses disease at early stages, and dependably manages our road traffic to maximise flow and minimise environmental impact. Before this vision becomes reality, several major limitations of current autonomous systems need to be addressed. Key among these limitations is their reduced resilience: today's autonomous systems cannot avoid, withstand, recover from, adapt, and evolve to handle the uncertainty, change, faults, failure, adversity, and other disruptions present in such applications. Recent and forthcoming technological advances will provide autonomous systems with many of the sensors, actuators and other functional building blocks required to achieve the desired resilience levels, but this is not enough. To be resilient and trustworthy in these important applications, future autonomous systems will also need to use these building blocks effectively, so that they achieve complex technical requirements without violating our social, legal, ethical, empathy and cultural (SLEEC) rules and norms. Additionally, they will need to provide us with compelling evidence that the decisions and actions supporting their resilience satisfy both technical and SLEEC-compliance goals. To address these challenging needs, our project will develop a comprehensive toolbox of mathematically based notations and models, SLEEC-compliant resilience-enhancing methods, and systematic approaches for developing, deploying, optimising, and assuring highly resilient autonomous systems and systems of systems. To this end, we will capture the multidisciplinary nature of the social and technical aspects of the environment in which autonomous systems operate - and of the systems themselves - via mathematical models. For that, we have a team of Computer Scientists, Engineers, Psychologists, Philosophers, Lawyers, and Mathematicians, with an extensive track record of delivering research in all areas of the project. Working with such a mathematical model, autonomous systems will determine which resilience- enhancing actions are feasible, meet technical requirements, and are compliant with the relevant SLEEC rules and norms. Like humans, our autonomous systems will be able to reduce uncertainty, and to predict, detect and respond to change, faults, failures and adversity, proactively and efficiently. Like humans, if needed, our autonomous systems will share knowledge and services with humans and other autonomous agents. Like humans, if needed, our autonomous systems will cooperate with one another and with humans, and will proactively seek assistance from experts. Our work will deliver a step change in developing resilient autonomous systems and systems of systems. Developers will have notations and guidance to specify the socio-technical norms and rules applicable to the operational context of their autonomous systems, and techniques to design resilient autonomous systems that are trustworthy and compliant with these norms and rules. Additionally, developers will have guidance to build autonomous systems that can tolerate disruption, making the system usable in a larger set of circumstances. Finally, they will have techniques to develop resilient autonomous systems that can share information and services with peer systems and humans, and methods for providing evidence of the resilience of their systems. In such a context, autonomous systems and systems of systems will be highly resilient and trustworthy.

Autonomous systems, such as medical systems, autonomous aerial and road vehicles, and manufacturing and agricultural robots, promise to extend and expand human capacities. But their benefits will only be harnessed if people have trust in the human processes around their design, development, and deployment. Enabling designers, engineers, developers, regulators, operators, and users to trace and allocate responsibility for the decisions, actions, failures, and outcomes of autonomous systems will be essential to this ecosystem of trust. If a self-driving car takes an action that affects you, you will want to know who is responsible for it and what are the channels for redress. If you are a doctor using an autonomous system in a clinical setting, you will want to understand the distribution of accountability between you, the healthcare organisation, and the developers of the system. Designers and engineers need clarity about what responsibilities fall on them, and when these transfer to other agents in the decision-making network. Manufacturers need to understand what they would be legally liable for. Mechanisms to achieve this transparency will not only provide all stakeholders with reassurance, they will also increase clarity, confidence, and competence amongst decision-makers. The research project is an interdisciplinary programme of work - drawing on the disciplines of engineering, law, and philosophy - that culminates in a methodology to achieve precisely that tracing and allocation of responsibility. By 'tracing responsibility' we mean the process of tracking the autonomous system's decisions or outcomes back to the decisions of designers, engineers, or operators, and understanding what led to the outcome. By 'allocating responsibility' we mean both allocating role responsibilities to different agents across the life-cycle and working out in advance who would be legally liable and morally responsible for different system decisions and outcomes once they have occurred. This methodology will facilitate responsibility-by-design and responsibility-through-lifecycle. In practice, the tracing and allocation of responsibility for the decisions and outcomes of AS is very complex. The complexity of the systems and the constant movement and unpredictability of their operational environments makes individual causal contributions difficult to distinguish. When this is combined with the fact that we delegate tasks to systems that require ethical judgement and lawful behaviour in human beings, it also gives rise to potential moral and legal responsibility gaps. The more complex and autonomous the system is, the more significant the role that assurance will play in tracing and allocating responsibility, especially in contexts that are technically and organisationally complex. The research project tackles these challenges head on. First, we clarify the fundamental concepts of responsibility, the different kinds of responsibility in play, the different agents involved, and where 'responsibility gaps' arise and how they can be addressed. Second, we build on techniques used in the technical assurance of high-risk systems to reason about responsibility in the context of uncertainty and dynamism, and therefore unpredictable socio-technical environments. Together, these strands of work provide the basis for a methodology for responsibility-by-design and responsibility-through-lifecycle that can be used in practice by a wide range of stakeholders. Assurance of responsibility will be achieved that not only identifies which agents are responsible for which outcomes and in what way throughout the lifecycle, and explains how this identification is achieved, but also establishes why this tracing and allocation of responsibility is well-justified and complete.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Birth weight reflects intrauterine growth and wellbeing and is recognised globally as an indicator of perinatal and infant health. A number of studies have suggested that occupation, air pollution and chlorination by-products in drinking water may be associated with low birth weight/intra uterine growth retardation (Nieuwenhuijsen et al 2000, Sram et al 2005, Farrow et al 1998, Chia et al 2004, Rylander and Kallen 2005), but the evidence is inconclusive, partly as a result of limited exposure assessments in the epidemiological studies that have been conducted. A large prospective birth cohort study is required to provide conclusive evidence about the link between occupation, chlorination by-products and air pollution on birth weight. The overall aim of this study is to bring together a multi-disciplinary team of physicians, epidemiologists, geneticists, environmental scientists, social scientists and statistical modellers to build capacity and lay the ground work for further studies to investigate the relationship, if any, between occupational factors, traffic related air pollution and chlorination disinfection by-products (DBPs) in drinking water and intra uterine growth retardation/low birth weight, taking into account known potential confounders such as smoking and ethnicity in the Born in Bradford study of 10,000 pregancies. The main focus of the work is the collection of information for the validation of exposure estimates, together with the initiation of data collection for the exposure modelling and preparing a strategy for linking them to health data.