The aim of the proposed research is to systematically investigate feasibility and performance of collaborative perception in a network of connected autonomous cars in order to create a reliable and highly accurate perception of the state of a subject autonomous vehicle, e.g., its location, as well as the surrounding environment. The research will build on the top of existing techniques that autonomous vehicles currently apply for the above-mentioned purposes addressing their shortcomings in terms of accuracy and reliability without needing expensive on-board sensory and computing resources. To this end, the research will investigate alternative approach of using off-board information that can be made available through V2X communications and integrate them in a robust manner to deal with potential disruptions of communication systems, potentially into a novel perception layer on a Local Dynamic Map (LDM) system. The research is directly related to a number of EPSRC research areas: Artificial Intelligence Technologies, Robotics and information systems

Metabolism requires O2 and produces CO2 as a by-product. The amount of dissolved CO2 controls the acidity (pH) of our body fluids including blood. Many physiological processes are sensitive to pH, thus efficient control of the amount of dissolved CO2 in blood is a critical homoeostatic function. Special mechanisms exist to measure the amount of dissolved CO2 in blood ?if there is too much we breathe faster to drive off the excess, if there is too little we breathe less frequently. While there is evidence that CO2 is detected indirectly as pH, we have discovered a new molecular mechanism for the direct detection of CO2 ?CO2 binds to a type of channel called connexin 26 (Cx26), and in doing so causes it to open and release a chemical called ATP that activates neurons. Cx26 is sensitive to CO2 in exactly the physiological range required ?our normal levels of dissolved CO2 are at the mid-point of channel activation. Cx26 can thus respond to both increases and decreases in dissolved CO2. Cx26 is present in the correct areas of the brain to help control breathing. Our programme seeks to develop the genetic tools to analyze with great rigour the contributions of Cx26 to the measurement of CO2 and the control of breathing. Use of these tools will not only enable us to establish the causal link between Cx26 and behaviour, but also to determine the tissues, regions and cell types that are important for the detection of CO2. We also wish to understand the mechanism by which CO2 binds to the channel to change its conformation and cause it to open. We shall mix and match portions of CO2-sensitive and non-CO2-sensitive connexins to endow a previously non-sensitive connexin with CO2 sensitivity. This will tell us which part of the protein is important. We shall then identify the precise amino acid involved by mutating single amino acids in the critical region of the molecule. In parallel with this we shall use an analytical technique called NMR spectroscopy to directly and definitively test one possible way that CO2 could bind to the protein. Our proposal has the potential to transform understanding of how the brain senses CO2. This is likely to be important in understanding how CO2-sensing may be altered during pathologies such as congestive heart failure and chronic obstructive pulmonary disease.

This project is the first to systematically investigate the introduction of counterterrorism within Health and Social care across Europe. The longstanding separation of medicine and care from policing/intelligence in liberal societies has been superseded in the era of Countering Violent Extremism (CVE). This study explores the political, economic and discursive mechanisms behind this dramatic policy shift, as well as the consequences for medical ethics and society. The project makes a major research contribution by exploring the integration of counterterrorism within caregiving professions as an effect of neoliberalism, through a methodologically pluralist approach. The project also contributes to research on policy diffusion by tracing the spread of deradicalisation programs between member states and EU institutions, with special attention paid to uptake by Europe’s small states. The first stage of the project operates at the European policy level. Data analysis is performed on political, economic and social data from all member states to determine the extent to which neoliberalism affects CVE implementation. Policy diffusion dynamics are then illuminated through Critical Discourse Analysis of institutional speeches, policies, and the work of the EU's Radicalisation Awareness Network (RAN), which attempts to standardise counter-radicalisation practice in Europe. The second stage of the project explores the local implementation of counter-radicalisation in health and social care sectors of the UK; France; Norway; Finland; Croatia; and Lithuania. Interviews and site visits enable the research to investigate standardisation and variation in CVE practice within Health and Social Care. The final stage of the project embarks on participant research with persons referred to CVE programs, creating a documentary film which highlights the competing visions of care, security and medical ethics at play within European counterterrorism.

When the HIV epidemic was recognised in the 1980s, vast amounts of work were undertaken to reveal the networks of sexual encounters through which HIV could spread. Knowing this allowed scientists to develop accurate predictions of the way the epidemic would grow. Given the current risks of pandemic influenza, it is necessary to collect similar information on the types of personal interaction which can lead to the spread of influenza or other airborne infections. We have developed a simple anonymous questionnaire which we wish to distribute to homes in the UK -- as well as developing a web-based questionnaire. The results of this survey will provide a picture of the types, duration and number of social contacts per person in the UK. This data will then enable us to create a far more accurate mathematical model which will be used to predict the spread of influenza in the UK, identify the most at-risk sections of the community, and help to inform policy makers and public-health organisations about the best way to control any outbreaks.