Monitoring vital signs is essential in healthcare, and although there are currently several ways of doing so, either at the hospital environment or at home, conventional devices pose different challenges to their users, being bulky and uncomfortable, often complicated to operate by non-experts, and extremely expensive. With the Internet-of-Things (IoT)-driven device connectivity and technological advancements, as cellular connectivity is replaced by other types of wireless communications like Bluetooth, the fast-growing market of connected wearables also plays an important role in the emerging market of remote patient monitoring, since wearable devices also enable a hands-free operation and continuous recording of useful data. Integrating sensors for body temperature, breathing rate and cardiac activity directly on textiles would eliminate the inconvenience of uncomfortable hardware directly in contact with the human skin. This is very important in the case of electrocardiography, particularly when performed continuously, which requires the prolonged use of gel electrolytes to reduce the resistance between the skin and the electrode, often causing allergies and skin irritation. In addition to measuring temperature, cardiac activity and breathing rate, wearable sensors can also be used to track a person's body movements, which can also find applications in different fields, such as physiotherapy and rehabilitation. For instance, gait patterns can provide a lot of information about a patient's health. Moreover, these body movements and wasted body heat are often underestimated as a means to generate energy to power wearable devices. This project aims to innovative develop graphene-based and self-powered vital signs sensors fully integrated on textiles and with wireless communication capabilities. Such sensors offer a comfortable and almost imperceptible way of continuous monitoring, as opposed to heavy and bulky equipment currently in use for the same purpose. Exposed to external stimuli, such as mechanical deformations or variations in temperature, the conductivity of these textiles will change in a predictable way, and this will be explored for sensing purposes. Furthermore, these conducting textiles will also be used as electrodes for electrocardiography. A self-contained and environmentally friendly energy source based on a triboelectric nanogenerator, capable of harvesting energy from the movements of the user, will also be developed using similar materials and methods. This innovative approach of building the sensors directly on textiles will put the UK in the forefront in the field of continuous vital sign monitoring and remote healthcare and has the potential to generate numerous business opportunities. Allied to self-monitoring and self-care, with the rise of remote health monitoring there is an increasing need of practical and convenient vital sign monitoring devices with sensors that can be self-powered, easily integrated with conventional electronics and wireless communications, and simply operated in the palm of our hands, for instance, using a mobile phone. To ensure that this project is carried out successfully, a team comprising the PI, 2 postgraduate research students (PGRS) and one experienced postdoctoral research associate (PDRA) will be assembled, and will work closely with two industrial partners with expertise in the textile industry, (Centexbel, Belgium and Heathcoat, UK), and two academic partners from Skoltech, Russia, with expertise in electronics and wireless communications, and UCL, UK, with expertise in data processing, ideal to complement the expertise in materials, nanotechnology and physics of the team at Exeter.

We can use intricately controlled assemblies of metals carved into structures on the scale of a billionth of a metre, to funnel and concentrate light into tiny volumes of space. This 'nano-optics' allows us to access for the first time small numbers of molecules and atoms moving around in real time. Even more interesting we can start to use light to control the movement of molecules and atoms, since it can produce strong forces directly at the nanoscale. In this research, we plan to use our new-found ability to concentrate on a whole range of physical phenomena that underlie devices at the heart of healthcare, information technology, and energy production. For instance we can watch how lithium ions move into and out of a small fragment of battery, and how the deformations of the atomic lattice are produced, which is what determines how long batteries last and how much energy they can store. Another project uses light to move gold atoms around inside larger carbon-based molecules, to control what colour they absorb at, and what molecules they can sense. Further projects build wallpapers constructed from tiny flipping components that produce colour changes on demand, the precursor to walls that change colour at the flick of a switch or display images or text on the side of lorries. Underpinning all this are serious advances in learning how to build such structures reliably, so anyone can make use of our new ideas. We understand very little about what happens when we put molecules inside such compressed nano-cavities for light, and these fundamentals will open up new areas. This research also crucially helps us understand what new properties we can create, and predicts how to improve them best. This will lay open many of the new technologies of the next century.

The Programme is organised into two themes. Research theme one will develop new computer vision algorithms to enable efficient search and description of vast image and video datasets - for example of the entire video archive of the BBC. Our vision is that anything visual should be searchable for, in the manner of a Google search of the web: by specifying a query, and having results returned immediately, irrespective of the size of the data. Such enabling capabilities will have widespread application both for general image/video search - consider how Google's web search has opened up new areas - and also for designing customized solutions for searching. A second aspect of theme 1 is to automatically extract detailed descriptions of the visual content. The aim here is to achieve human like performance and beyond, for example in recognizing configurations of parts and spatial layout, counting and delineating objects, or recognizing human actions and inter-actions in videos, significantly superseding the current limitations of computer vision systems, and enabling new and far reaching applications. The new algorithms will learn automatically, building on recent breakthroughs in large scale discriminative and deep machine learning. They will be capable of weakly-supervised learning, for example from images and videos downloaded from the internet, and require very little human supervision. The second theme addresses transfer and translation. This also has two aspects. The first is to apply the new computer vision methodologies to `non-natural' sensors and devices, such as ultrasound imaging and X-ray, which have different characteristics (noise, dimension, invariances) to the standard RGB channels of data captured by `natural' cameras (iphones, TV cameras). The second aspect of this theme is to seek impact in a variety of other disciplines and industry which today greatly under-utilise the power of the latest computer vision ideas. We will target these disciplines to enable them to leapfrog the divide between what they use (or do not use) today which is dominated by manual review and highly interactive analysis frame-by-frame, to a new era where automated efficient sorting, detection and mensuration of very large datasets becomes the norm. In short, our goal is to ensure that the newly developed methods are used by academic researchers in other areas, and turned into products for societal and economic benefit. To this end open source software, datasets, and demonstrators will be disseminated on the project website. The ubiquity of digital imaging means that every UK citizen may potentially benefit from the Programme research in different ways. One example is an enhanced iplayer that can search for where particular characters appear in a programme, or intelligently fast forward to the next `hugging' sequence. A second is wider deployment of lower cost imaging solutions in healthcare delivery. A third, also motivated by healthcare, is through the employment of new machine learning methods for validating targets for drug discovery based on microscopy images

Energy systems are vitally important to the future of UK industry and society. However, the energy trilemma presents many complex interconnected challenges. Current integrated energy systems modelling and simulation techniques suffer from a series of shortcomings that undermine their ability to develop and inform improved policy and planning decisions, therefore preventing the UK realising huge potential benefits. The current approach is characterised by high level static models which produce answers or predictions that are highly subject to a set of critical simplifying assumptions and therefore cannot be relied upon with a high degree of confidence. They are unable to provide sufficiently accurate or detailed, integrated representations of the physics, engineering, social, spatial temporal or stochastic aspects of real energy systems. They also struggle to generate robust long term plans in the face of uncertainties in commercial and technological developments and the effects of climate change, behavioural dynamics and technological interdependencies. The aim of the Centre for Energy Systems Integration (CESI) is to address this weakness and reduce the risks associated with securing and delivering a fully integrated future energy system for the UK. This will be achieved through the development of a radically different, holistic modelling, simulation and optimisation methodology which makes use of existing high level tools from academic, industry and government networks and couples them with detailed models validated using full scale multi vector demonstration systems. CESI will carry out uncertainty quantification to identify the robust messages which the models are providing about the real world, and to identify where effort on improving models should be focused in order to maximise learning about the real world. This approach, and the associated models and data, will be made available to the energy community and will provide a rigorous underpinning for current integrated energy systems research, so that future energy system planning and policy formulation can be carried out with a greater degree of confidence than is currently possible. CESI is a unique partnership of five research intensive universities and underpinning strategic partner Siemens (contribution value of £7.1m to the centre) The Universities of Newcastle, Durham, Edinburgh, Heriot-Watt and Sussex have a combined RCUK energy portfolio worth over £100m. The centre will have a physical base as Newcastle University which will release space for the centre in the new £60m Urban Sciences Building. This building will contain world-class facilities from which to lead international research into digitally enabled urban sustainability and will also be physically connected to a full scale instrumented multi vector energy system. The building will feature an Urban Observatory, which will collect a diverse set of data from across the city, and a 3D Decision Theatre which will enable real-time data to be analysed, explored and the enable the testing of hypotheses. The main aim of CESI's work is to develop a modular 'plug-n-play' environment in which components of the energy system can be co-simulated and optimised in detail. With no technology considered in isolation, considering sectors as an interlinked whole, the interactions and rebound effects across technologies and users can be examined. The methodology proposed is a system architect concept underpinned by a twin track approach of detailed multi-vector, integrated simulation and optimisation at various scales incorporating uncertainty, coupled with large scale demonstration and experimental facilities in order to test, validate and evaluate solutions and scenarios. A System Architect takes a fully integrated, balanced, long term, transparent approach to energy system planning unfettered by silos and short term thinking.

Silicon photonics is the manipulation of light (photons) in silicon-based substrates, analogous to electronics, which is the manipulation of electrons. The development cycle of a silicon photonics device consists of three stages: design, fabrication, and characterisation. Whilst design and characterisation can readily be done by research groups around the country, the fabrication of silicon photonics devices, circuits and systems requires large scale investments and capital equipment such as cleanrooms, lithography, etching equipment etc. Based at the Universities of Southampton and Glasgow, CORNERSTONE 2.5 will provide world-leading fabrication capability to silicon photonics researchers and the wider science community. Whilst silicon photonics is the focus of CORNERSTONE 2.5, it will also support other technologies that utilise similar fabrication processes, such as MEMS or microfluidics, and the integration of light sources with silicon photonics integrated circuits, as well as supporting any research area that requires high-resolution lithography. The new specialised capabilities available to researchers to support emerging applications in silicon photonics are: 1) quantum photonics based on silicon-on-insulator (SOI) wafers; 2) programmable photonics; 3) all-silicon photodetection; 4) high efficiency grating couplers for low energy, power sensitive systems; 5) enhanced sensing platforms; and 6) light source integration to the silicon nitride platform. Access will be facilitated via a multi-project-wafer (MPW) mechanism whereby multiple users' designs will be fabricated in parallel on the same wafer. This is enabled by the 8" wafer-scale processing capability centred around a deep-UV projection lithography scanner installed at the University of Southampton. The value of CORNERSTONE 2.5 to researchers who wish to use it is enhanced by a network of supporting companies, each providing significant expertise and added value to users. Supporting companies include process-design-kit (PDK) software specialists (Luceda Photonics), reticle suppliers (Compugraphics, Photronics), packaging facilities (Tyndall National Institute, Bay Photonics, Alter Technologies), a mass production silicon photonics foundry (CompoundTek), an epitaxy partner for germanium-on-silicon growth (IQE), fabrication processing support (Oxford Instruments), an MPW broker (EUROPRACTICE), a III-V die supplier (Sivers Semiconductors) and promotion and outreach partners (Photonics Leadership Group, EPIC, CSA Catapult, CPI, Anchored In). Access to the new capabilities will be free-of-charge to UK academics in months 13-18 of the project, and 75% subsidised by the grant in months 19-24. During the 2-year project, we will also canvas UK demand for the capability to continue to operate as an EPSRC National Research Facility, and if so, to establish a Statement of Need.