Perfusion imaging allows us to measure the vital role played by delivery of blood to the brain in keeping it supplied with nutrients and removal of waste. Any deviations of the blood supply from normal can be a sign of disease. In particular early and subtle changes in perfusion might mark regions of the brain which are affected by degenerative diseases such as dementia before other imaging signs become obvious. The technology exists and is increasingly widely available to image perfusion quickly and safely using Magnetic Resonance Imaging. Thus perfusion Magnetic Resonance Imaging could be a valuable tool in the understanding of dementias, as well as the diagnosis and monitoring of patients with dementia. The challenge that remains is making sufficiently specific measurements of subtle changes in blood supply that would be needed to make the technology truly useful for patients. This project addresses that problem in three ways: > Automated removal of errors associated with imperfect measurement, for example due to motion of the patient. > Methods to control for differences between patients due to their individual brain structure, allowing blood supply measurements to be compared between individuals or from a patient to a population of similar healthy adults. These methods remove uncertainties introduced by other differences between the brain's of individuals that are not related to perfusion. > Generation of personalised reference perfusion images for an individual patient against which their measured perfusion can be compared to detect changes specific to that individual. The methods and tools that are to be generated in this project will enable perfusion Magnetic Resonance Imaging to be used more effectively in the UK-wide effort to understand dementia and in the search for new and effective treatments. Ultimately the work done in this project will enable perfusion Magnetic Resonance Imaging to become a valuable clinical tool that can be used in the diagnosis and monitoring of individual patients with dementia.

The security threat level from international terrorism, introduced by the UK Security Service, has been classified as either "severe" or "critical" for much of its six-year history, and currently remains as "substantial" (source: MI5 web site). Part of the risk posed by terrorist threats involves potential releases of air-borne chemical, biological, radiological or nuclear (CBRN) material into highly populated urbanised areas. Smoke from industrial accidents within or in the vicinity of urban areas also pose risks to health and can cause widespread disruption to businesses, public services and residents. The Buncefield depot fire of 2005 resulted in the evacuation of hundreds of homes and closure of more than 200 schools and public buildings for two days; consequences would have been much more severe if prevailing meteorological conditions had promoted mixing or entrainment of the smoke plume into the urban canopy. In both these scenarios it is crucial to be able to model, quickly and reliably, dispersion from localised sources through an urban street network in the short range, where the threat to human health is greatest. However, this is precisely where current operational models are least reliable because our understanding and ability to model short-range dispersion processes is limited. The contribution that DIPLOS will make is: (i) to fill in the gaps in fundamental knowledge and understanding of key dispersion processes, (ii) to enable those processes to be parametrized for use in operational models, and (iii) to implement them into an operational model, evaluate the improvement and apply the model to a case study in central London. Most of the existing research on urban dispersion has focused on air quality aspects, with sources being extensive and distributed in space. Scientifically, the proposed research is novel in focusing on localized releases within urban areas, and on dispersion processes at short range. Through a combination of fundamental studies using wind tunnel experiments and high resolution supercomputer simulations, extensive data analysis and development of theoretical and numerical models, DIPLOS will contribute to addressing this difficult and important problem from both a scientific research and a practical, operational perspective.

The proposed multidisciplinary network for Decarbonizing Transport through Electrification (DTE) will bring together research expertise to address the challenges of interactions between energy networks, future electric vehicle charging infrastructure ( including roadside wireless charging, the shift to autonomous vehicles), electric and hybrid aircraft and electrification of the rail network. The DTE network will bring together industry, academia and the public sector to identify the challenges limiting current implementation of an electrified, integrated transport system across the automotive, aerospace and rail sectors. The network will develop and sustain an interdisciplinary team to solve these challenges, leveraging external funding from both public and private sectors, aiming to be become self sustainable in future and growing to establish an International Conference. The network will be inclusive, with a focus EDI and mechanisms to support colleagues such as early career researchers. The DTE network will address low-carbon transport modes (road, rail and airborne) alongside associated electricity infrastructures to support existing and deliver future mobility needs, treating these as an integrated system embedded within the electricity energy vector with the goal of decarbonising the transport sector. It will explore drivers for change within the transport system including technology innovation, individual mobility needs and economic requirements for change alongside environmental and social concerns for sustainability and consider the role, social acceptance and impact of policies and regulations to result in emissions reduction. The network has three key "Work Streams" focusing on: (i) vehicular technologies; (ii) charging infrastructure; (iii) energy systems. These will be underpinned by cross-cutting themes around large scale data analysis and human factors. The network also has a dedicated Work Stream on people-based activities to enable us to widen our dissemination and impact across other communities. The outcome of the DTE network is expected to transform current practices and research in the decarbonization of transport (considering a number of different perspectives).