Our research with the particle physics rolling grant at Sheffield attempts to progress understanding of some of the most important questions concerning the origins and make-up of the Universe. One of these big questions is to understand what gives fundamental particles their mass. Part of our work on the huge ATLAS experiment at the Large Hadron Collider (LHC) at CERN in Geneva is aimed at this question, in particular to see if the famous Higgs Boson particle exists. The best theories we have to explain particle mass predict that it should be there. We will play a key role in analysing the vast amount of data soon expected to make this exciting discovery. Another search at ATLAS will be to determine if the so-called supersymmetry (SUSY) theory is correct. This is our best prospect for understanding how particles interact at high energy and itself predicts a new class of particles. The concept states that for every known fundamental particle there exists a super-partner particle. We worked for many years developing the key silicon technology now installed in ATLAS to search for these particles. Now we are ready with our software to play a key role in analysing the data that will hopefully discover that they exist. One of the implications of SUSY theory is the likelihood that the most stable new particle, the so-called lightest supersymmetric particle (LSP), probably is very abundant throughout the Universe, making up about 25% of its mass. This would easily explain one of the big mysteries in physics, the so-called Dark Matter seen by astronomers from its gravitational effects on stars and galaxies. Our group has pioneered techniques to search directly for dark matter particles in the laboratory and is participating in a new multi-national venture, EURECA. This will build a tonne-sized device using low temperature superconductors to perform a new search. We will contribute to the key aspect of how to shield the experiment from natural background particles, like muons. Another mystery in the Universe are the strange properties of its most abundant particle, the neutrino. This has only recently been found to have a small mass and to readily change form between three different 'flavours' while propagating through space. Details of this are not fully understood but it is known that if properly unravelled it might answer another big question, why there is so little anti-matter in the Universe. We are working on these questions through participation in the big international T2K neutrino beam experiments in Japan. We are building a key component of the detectors and will, within two years, start to analyse the data to unravel these issues. T2K probably will not do a full job, so we have instigated in the UK work on a new neutrino detector concept, based on liquid argon, contributing to the FJNE programme. We plan to build test devices to enable the next generation of neutrino experiments to follow T2K. This is linked also to our work on accelerator technology, MICE, where we are building test beam targets. This is a vital step towards the ultimate facility, a neutrino factory. We are working on key technology for this within the UKNF project. Finally, much of the hardware and computer code developed for these fundamental studies have great relevance well outside our main research. There are many examples, involving projects with a dozen UK companies. For instance, our work with Corus Ltd. on new techniques for neutron detection, has allowed development of new monitors to detect illicit transport of nuclear materials at ports. This will continue now and broaden into medical applications. Our dark matter work has produced a new national facility for underground science, the Boulby laboratory. Here we have started a new project on climate change, SKY, to explore the effect of comic rays on cloud formation.

Domestic burglary is a high volume crime affecting many households. As well as substantial financial loss and damage to property, it causes high levels of anxiety about the possibility of being burgled. Surveys documenting public priorities about crime place burglary at the top. Burglar alarms and other security devices in principle deter potential burglars. Insurance premiums are discounted when a fully operating burglar alarm exists in the home due to claims about the effectiveness of burglar alarms and other security devices in the marketing literature, but no systematic research studies have been undertaken to assess their effectiveness in different areas, accommodation types and occupants' characteristics. The research proposed is precisely concerned with such an assessment. The primary research question is: Which burglary security devices work for whom and in what context? This study will identify the individual and combined security devices that offer cost-effective burglary protection to (a) the population in England and Wales overall; (b) specific population subgroups according to their socio-economic attributes; (c) the residents of Wales, each of the nine English regions and area types according to population socio-demographic profile and density; and (d) area types and population subgroups plausible combinations. The urgency to gain insights about the cost-effectiveness of burglary devices for tailor-made preventive interventions cannot be exaggerated: at a time of massive public spending cuts and declining disposable incomes the latest Home Office figures show a 14% annual increase in domestic burglary in 2010/11 after an extended (fifteen years) period of falls (Chaplin et al. 2011). The Department for Communities and Local Government (2012) has recently highlighted the need of research evidence on cost-effective burglary security devices to inform the on-going deliberation on national building regulation for minimum standards for security in homes. The proposed research will: -Make a major scientific contribution with immediate and high societal and economic impact. Its theoretical and methodological advancements will inform future research developments in criminology. The current gap in knowledge impedes cost-effective burglary prevention not just in the UK but across the world at a time that wasteful financial decisions are unaffordable. -Engage throughout with high level research users in the public sector and civil society organisations and inform national and international guidelines on burglary prevention. The research results will be regularly conveyed to users in the private sector (the security and insurance industry) who however will not contribute to their development to avoid conflict of interest. -Analyse two decades of a formidable existing data source, the British Crime Survey (BCS). The BCS is a large and complex dataset with currently some 40,000 respondents annually that exists in the public domain, and has been run for three decades. Yet, relative to both data generation cost and its impeccable quality, it has been extremely under-explored. -Employ innovative research techniques for the deeper exploitation of the BCS, including the Security Impact Assessment Tool, pioneered by the co-applicants with ESRC support to assess the effectiveness of car security devices, as well as the multivariate multilevel logit modelling, to investigate the effect of context on trends of related crime types. -Build the national skills base in the analysis of large and complex datasets and expand the limited secondary data analysis capacity in criminology via actively seeking to employ a full time researcher from disciplines (mathematics, statistics, sciences or engineering) beyond traditional BCS users. Therefore the proposed research fits the ESRC-SDAI call specification. The co-applicants' theoretical, methodological and policy contribution to date ensure its successful delivery.

In the past, when the majority of people were born, lived and died in the same locality where everybody knew each other, there was no need for biometrics. However, nowadays, with the society moving rapidly towards Digital Economy, and the people mobility within the country and across borders reaching unprecedented levels, efficient, robust and effective ways of recognising and verifying individuals automatically, based on biometrics, is emerging as an essential requirement and element of the fabric of the information infrastructure. Identity verification is required to facilitate commerce, and remote working, to enable access to remote services and physical sites in smart cities, as well as contributing to a safer society by fighting crime and terrorism through automatic surveillance. In this context face biometrics is a preferred biometric modality, as it can be captured unobtrusively, even without subjects' being aware of being monitored and potentially recognised. It is also the modality used by humans and thus, when needed, it supports a seamless transition and cooperation between machine and human face recognition. Although face biometrics is beginning to be deployed in several sectors, it is currently limited to applications where a strict control can be imposed on the process of face image capture (frontal face recognition in controlled lighting). However, automatic face recognition in uncontrolled scenarios is an unsolved problem because of the variability of face appearance in images captured in different poses, with diverse expressions, under changing illumination. Furthermore, the image variability is aggravated by degradation phenomena such as noise, blur and occlusion. The project will develop unconstrained face recognition technology, which is robust to a range of degradation factors, for applications in the Digital Economy and in a world facing global security issues, as well as demographic changes. The approach adopted will endeavour to devise novel machine learning solutions, which combine the technique of deep learning with sophisticated prior information conveyed by 3D face models. The scientific challenge will be to develop a face image representation, which is invariant to various imaging factors. This will necessitate gaining better understanding of the effect of natural face appearance variations and face image degradation phenomena on face image representation. The work will be carried out by a multidisciplinary team constituted by three academic partners, University of Surrey, Imperial College London and University of Stirling, which has extensive experience in biometrics and face modelling, and jointly possesses the necessary expertise, including psychology of human face perception. The research direction will be regularly reappraised and if necessary revised, with steering provided by a team of external experts representing the biometrics industry, government agencies, and potential users of the unconstrained face recognition technology. The progress of the project will be measured by extensive evaluations of the solutions developed using challenging benchmarking tests devised by the biometrics community and compared with evolving commercial offerings.

The proposal has been designed to explore a novel and holistic approach which will engage experts across the full spectrum of their skills-base, through a suite of short-term research activities that are linked in theme and approach, yet are highly adventurous and in areas highly speculative in nature, aiming to provide an effective means for better and non-invasive human monitoring for security applications. Prior studies have shown that human odours can provide relevant biological information about their 'sender' and a key target of this approach is the fusion of the analysis of this type of olfactory communication with associated physiological and behavioural indications. This shows advantages particularly when the other two major 'senses', i.e. the visual and acoustic, are functionally restricted, most frequently the case in security screening. The interdisciplinary approach proposed addresses the detection of human 'fear' - focusing on fear pheromone as a key physiological indicator and correlating the information with human abnormal behaviour. Although simple to describe in these terms, real success envisaged is only possible when factors across the spectrum from the chemical, physical, engineering to the social sciences and psychology are effectively integrated, rather than viewed in isolation. The work will target as an outcome being able to determine the viability and efficacy of such an integrated approach to the detection of these human alarm signals: applied in assessing the stress status of an individual and interpreting this in a security-critical context. The application domain will allow addressing the feasibility of novel methods based on this approach for the rapid and accurate identification of criminal or terrorist suspects in public areas, e.g. at airports, railway stations or approaching the London Olympics, with minimum disruption to routine operations.

Domestic burglary is a high volume crime affecting many households. As well as substantial financial loss and damage to property, it causes high levels of anxiety about the possibility of being burgled. Surveys documenting public priorities about crime place burglary at the top. Burglar alarms and other security devices in principle deter potential burglars. Insurance premiums are discounted when a fully operating burglar alarm exists in the home due to claims about the effectiveness of burglar alarms and other security devices in the marketing literature, but no systematic research studies have been undertaken to assess their effectiveness in different areas, accommodation types and occupants' characteristics. The research proposed is precisely concerned with such an assessment. The primary research question is: Which burglary security devices work for whom and in what context? This study will identify the individual and combined security devices that offer cost-effective burglary protection to (a) the population in England and Wales overall; (b) specific population subgroups according to their socio-economic attributes; (c) the residents of Wales, each of the nine English regions and area types according to population socio-demographic profile and density; and (d) area types and population subgroups plausible combinations. The urgency to gain insights about the cost-effectiveness of burglary devices for tailor-made preventive interventions cannot be exaggerated: at a time of massive public spending cuts and declining disposable incomes the latest Home Office figures show a 14% annual increase in domestic burglary in 2010/11 after an extended (fifteen years) period of falls (Chaplin et al. 2011). The Department for Communities and Local Government (2012) has recently highlighted the need of research evidence on cost-effective burglary security devices to inform the on-going deliberation on national building regulation for minimum standards for security in homes. The proposed research will: -Make a major scientific contribution with immediate and high societal and economic impact. Its theoretical and methodological advancements will inform future research developments in criminology. The current gap in knowledge impedes cost-effective burglary prevention not just in the UK but across the world at a time that wasteful financial decisions are unaffordable. -Engage throughout with high level research users in the public sector and civil society organisations and inform national and international guidelines on burglary prevention. The research results will be regularly conveyed to users in the private sector (the security and insurance industry) who however will not contribute to their development to avoid conflict of interest. -Analyse two decades of a formidable existing data source, the British Crime Survey (BCS). The BCS is a large and complex dataset with currently some 40,000 respondents annually that exists in the public domain, and has been run for three decades. Yet, relative to both data generation cost and its impeccable quality, it has been extremely under-explored. -Employ innovative research techniques for the deeper exploitation of the BCS, including the Security Impact Assessment Tool, pioneered by the co-applicants with ESRC support to assess the effectiveness of car security devices, as well as the multivariate multilevel logit modelling, to investigate the effect of context on trends of related crime types. -Build the national skills base in the analysis of large and complex datasets and expand the limited secondary data analysis capacity in criminology via actively seeking to employ a full time researcher from disciplines (mathematics, statistics, sciences or engineering) beyond traditional BCS users. Therefore the proposed research fits the ESRC-SDAI call specification. The co-applicants' theoretical, methodological and policy contribution to date ensure its successful delivery.