The health benefits of diet and physical activity are well established. However, the environment influences these behaviours and hence health risk. Previous research has examined the role of the environment using people's addresses but this misses where people go, when they go, and what they do. This means that the interplay between environmental exposures and personal behaviours is missed. We address this gap using existing timestamped measures of physical activity, location and diet from a large population-based cohort of over 10,000 adults in England. Using AI methods including autonomous agents acting on a knowledge graph, we will combine location and geospatial data to quantify personal dynamic environmental exposures to support epidemiological analysis of the cohort. Results will be relevant to local authorities, including more detailed understanding of how people use space and the duration and timing of health-related exposures. Long term, this research could facilitate real-time nudges of health behaviours using smartphones.

Many aspects of a child or young person's life can affect their mental health. If someone has a serious mental health problem their general practitioner (GP) may refer them to mental health (psychiatry) services for assessment and treatment by professionals. Mental health services are stretched so often intervene late, leaving people to suffer unnecessarily with problems that therefore may last longer, be more severe, or be harder to treat. Early warning signs of mental health problems may be noticed by the person themselves or by others (e.g. school staff, social workers). Many things can suggest a mental health problem, such as difficult early experiences, bullying, changes in behaviour, poor school attendance or grades, or risk-taking. Not all who experience one or more of these will have a mental health problem, so we need to take them together to spot patterns that show who is developing problems and may need professional help. However, this information (data) is stored in different places, e.g. by schools, GPs and social workers and so it may be impossible to spot problems early. Some researchers have joined data from two or more sources to find patterns suggesting mental health problems. Their success indicates good potential in this approach, but they have not made a practical difference for two main reasons: 1) the models are not yet accurate enough, probably because they omit many factors that can lead to problems; 2) the results cannot be used directly to help young people as they are based on anonymous data. We will develop a system that can be used by health, education, or social workers to identify adolescents showing early signs of mental health problems, to offer them help sooner. At the same time we want to provide better anonymous data for research into predicting mental health problems. Data must be held securely (most likely in the NHS), and only people involved in a person's care should be able to see it, but we need to understand how best to do this. To use data for research while protecting privacy it will be anonymised, removing anything that directly identifies a person (e.g. name, address, date of birth, NHS number) and access will be restricted to approved researchers. But we do not yet know what technical problems there may be in linking the databases, or what data the system will need in order to detect people showing early signs of a problem. The final challenge is how to make this work within the NHS, schools, and social care settings to enable earlier identification of young sufferers of mental health problems. Over the next year, we want to tackle these challenges by creating a group including mental health researchers, psychologists, schools, the NHS, councils, computer scientists, security experts, mathematicians, people who provide services, and policy makers, many of whom are doing ground-breaking work in other areas. We want to turn their attention to jointly solving these problems. We must involve young people, their carers, and people with lived experience: it is their data and we need to understand their views. We would like their help thinking about which professionals can see their data, and what should happen when a young person is thought to be developing mental health problems. We will hold workshops about these questions. We also have permission to create an initial data set with data from health, social services, and education. We will anonymise these, and practise linking and analysing them. These will help us understand the challenges, so that our final plan will be more detailed and likely to succeed. In the future we want to test if a computer program makes it easier to identify mental health problems and offer young people treatments earlier, and if they get better quicker because of this. This might have a range of benefits including helping with school, relationships, home life, and getting jobs or into university, and we want to test this theory.

Cloud computing promises to revolutionise how companies, research institutions and government organisations, including the National Health Service (NHS), offer applications and services to users in the digital economy. By consolidating many services as part of a shared ICT infrastructure operated by cloud providers, cloud computing can reduce management costs, shorten the deployment cycle of new services and improve energy efficiency. For example, the UK government's G-Cloud initiative aims to create a cloud ecosystem that will enable government organisations to deploy new applications rapidly, and to share and reuse existing services. Citizens will benefit from increased access to services, while public-sector ICT costs will be reduced. Security considerations, however, are a major issue holding back the widespread adoption of cloud computing: many organisations are concerned about the confidentiality and integrity of their users' data when hosted in third-party public clouds. Today's cloud providers struggle to give strong security guarantees that user data belonging to cloud tenants will be protected "end-to-end", i.e. across the entire workflow of a complex cloud-hosted distributed application. This is a challenging problem because data protection policies associated with applications usually require the strict isolation of certain data while permitting the sharing of other data. As an example, consider a local council with two applications on the G-Cloud: one for calculating unemployment benefits and one for receiving parking ticket fines, with both applications relying on a shared electoral roll database. How can the local council guarantee that data related to unemployment benefits will never be exposed to the parking fine application, even though both applications share a database and the cloud platform? The focus of the CloudSafetNet project is to rethink fundamentally how platform-as-a-service (PaaS) clouds should handle security requirements of applications. The overall goal is to provide the CloudSafetyNet middleware, a novel PaaS platform that acts as a "safety net", protecting against security violations caused by implementation flaws in applications ("intra-tenant security") or vulnerabilities in the cloud platform itself ("inter-tenant security"). CloudSafetyNet follows a "data-centric" security model: the integrity and confidentiality of application data is protected according to data flow policies -- agreements between cloud tenants and the provider specifying the permitted and prohibited exchanges of data between application components. It will enforce data flow policies through multiple levels of security mechanisms following a "defence-in-depth" strategy: based on policies, it creates "data compartments" that contain one or more components and isolate user data. A small privileged kernel, which is part of the middleware and constitutes a trusted computing base (TCB), tracks the flow of data between compartments and prevents flows that would violate policies. Previously such information flow control (IFC) models have been used successfully to enhance programming language, operating system and web application security. To make such a secure PaaS platform a reality, we plan to overcome a set of research challenges. We will explore how cloud application developers can express data-centric security policies that can be translated automatically into a set of data flow constraints in a distributed system. An open problem is how these constraints can be tied in with trusted enforcement mechanisms that exist in today's PaaS clouds. Addressing this will involve research into new lightweight isolation and sand-boxing techniques that allow the controlled execution of software components. In addition, we will advance software engineering methodology for secure cloud applications by developing new software architectures and design patterns that are compatible with compartmentalised data flow enforcement.

This programme brings together teams from Herriot Watt University, the University of Cambridge, the University of Westminster and Durham University: providing a multidisciplinary focus on the research needed to enable and underpin radical measures to decarbonise the UK's road freight transport sector. The researchers are augmented by a consortium of 22 industrial partners, drawn from users, suppliers and participants in the road logistics sector. These industrial members provide advice and guidance as well as a rapid route to prototyping and implementation of solutions. The first 5-year programme, conducted by the same team, laid the foundations and showed that radical measures are necessary to hit the UK Government's CO2 reduction targets. It also showed that integration between logistics solutions, vehicle technology, and policy measures is essential. This experience has shaped the design of the proposed programme. The new research programme will run for 5 years and has three themes: (i) data collection and management, (ii) logistics systems, and (iii) vehicle technology. A portfolio of 23 projects spans the themes. The first strand of projects (funded mainly by EPSRC), will focus on reducing barriers to promising strategic, deep decarbonisation technologies and solutions. These projects will create and integrate new data, new modelling tools and decision support systems, to create new insights about technological and logistical solutions, compelling arguments for their early adoption and recommendations for the necessary policy measures. Driven by a desire to model and then quantify the benefits of radical logistics options, the models will be developed and validated with data from real freight operations by the industrial partners, collected by novel automated means. Alternative vehicle fuels and power trains and ways of significantly reducing energy consumption will be investigated. The second strand of projects (funded mainly by EPSRC and industry) will focus on extending and optimising the capabilities of promising technologies and on increasing their impact when applied to decarbonisation of road freight. Applied research into the dynamics of logistics mode decisions and testing of novel logistics options such as horizontal collaboration, co-loading and reorganisation of logistics infrastructure, will be enabled by tools developed in the first strand. Technologies developed in the first 5 years of the Centre for Sustainable Road Freight (SRF) will be tested in two separate full-scale field trials with consortium partners, funded by InnovateUK. Road-mapping will provide a mechanism for corporates, government departments and researchers to build a common view of the future. The projects in the third strand (funded by Energy Technologies Institute) will focus on implementation of tools and practices that offer immediate impact. These include novel and powerful software systems for industry to use in data collection and for vehicle characterisation and fleet decarbonisation. Research into the drivers of strategy and policy will, likewise identify the most powerful ways to influence adoption of technologies and logistics solutions. The Road Freight Systems Living Laboratory ('Living Lab') is the central integrating element of the SRF's five-year research programme. Almost every project in the Centre will be part of it. The Living Lab will provide a test bed to measure and model freight operations; to develop technical and logistical interventions based on real-time logistics data; to test the interventions in simulation; to develop decision support tools (several based on work done in the first 5 years of the SRF) and eventually to implement and trial the tools and systems in practice. The Living Lab will be based on an integrated software and data platform that is currently being built by the research team and industry partners.

The uneven ways that civil liberties, work, labour and health have all been impacted over the last 18 months as we have all turned to digital technologies to sustain previous ways of life, has not only shown us the extent of inequalities across all societies as they are cut through with gender, ethnicity, age, opportunities, class, geolocation; it has also led many organisations and businesses across all three sectors to question those values they previously supported. Capitalising on this moment of reflection across industry, the public and third sectors; we explore the possibility of imagining and building a future that takes different core values and practices as central, and works in very different ways. As the roles of organisations and businesses across all industry, the public and third sectors changes, what is now taken up as core values and ethos will be crucial in defining the future. INCLUDE+ will build a knowledge community around in/equalities in digital society that will comprise industry, academia, the public and third sectors. Responding to the Equitable Digital Society theme, we ask how we can design, co-create and realise digital services and infrastructures to support inclusion and equality in ways that enable all people to thrive. Focusing on the three connected strands of wellbeing, precarity, and civic culture; we address structural inequalities as they emerge through our research, investigating them through whole system approaches that includes the generation of outputs that comprise of new systems, services and practices to be taken up by organisations. More than this, our knowledge community will be underpinned by empirical, co-curation and participatory led research that will produce real interventions into those structural inequalities. These interventions will be taken up by organisations, responded to and considered, enabling the wider knowledge community to critically assess them in relation to the values they purport to promote. Fed by secondments and supported through smaller exploratory and escalator funds, our knowledge community will not only grow through traditional networking activities such as workshops, annual conferences, academic outputs and further funding; it will also grow through the development of interdisciplinary methods, knowledge exchange practices, and mentorship, which the secondment package will promote. In so doing, we structure our N+ around participatory research practices, people development and knowledge exchange, aiming to grow our network through the development and growth of people and good practice. INCLUDE+ is led by a highly experienced cross-disciplinary team incorporating Management and Business Studies, Computing, Social Sciences, Media and Communication and Legal Studies. Each Investigator brings vibrant international networks; active research projects feeding the Network+; and long experience of impact generation across policy and research. With support from organisations like the International Labour Organisation, Law Commission, Cabinet Office, and Equality and Human Rights Commission as well as the existing DE community, we will develop from and with existing research, extend this work and impact beyond it. Our partner organisations cut across industry, the public and third sectors and include (for example) Lego; NHS AI Lab; Space2; mHabitat; Leeds, Cambridgeshire and Swansea Councils; PeopleDotCom; Ditchley; 5Rights; EAMA; DataKind and IBM. We have designed the Network+ to enable a whole system approach that is genuinely exciting and innovative not just because of scalability, transference and scope, but also because of the commitment to people development, knowledge exchange and interdisciplinary practice that will also shape future research