This proposal brings together a critical mass of scientists from the Universities of Cardiff, Lancaster, Liverpool and Manchester and clinicians from the Christie, Lancaster and Liverpool NHS Hospital Trusts with the complementary experience and expertise to advance the understanding, diagnosis and treatment of cervical, oesophageal and prostate cancers. Cervical and prostate cancer are very common and the incidence of oesophageal is rising rapidly. There are cytology, biopsy and endoscopy techniques for extracting tissue from individuals who are at risk of developing these diseases. However the analysis of tissue by the standard techniques is problematic and subjective. There is clearly a national and international need to develop more accurate diagnostics for these diseases and that is a primary aim of this proposal. Experiments will be conducted on specimens from all three diseases using four different infrared based techniques which have complementary strengths and weaknesses: hyperspectral imaging, Raman spectroscopy, a new instrument to be developed by combining atomic force microscopy with infrared spectroscopy and a scanning near field microscope recently installed on the free electron laser on the ALICE accelerator at Daresbury. The latter instrument has recently been shown to have considerable potential for the study of oesophageal cancer yielding images which show the chemical composition with unprecedented spatial resolution (0.1 microns) while hyperspectral imaging and Raman spectroscopy have been shown by members of the team to provide high resolution spectra that provide insight into the nature of cervical and prostate cancers. The new instrument will be installed on the free electron laser at Daresbury and will yield images on the nanoscale. This combination of techniques will allow the team to probe the physical and chemical structure of these three cancers with unprecedented accuracy and this should reveal important information about their character and the chemical processes that underlie their malignant behavior. The results of the research will be of interest to the study of cancer generally particularly if it reveals feature common to all three cancers. The infrared techniques have considerable medical potential and to differing extents are on the verge of finding practical applications. Newer terahertz techniques also have significant potential in this field and may be cheaper to implement. Unfortunately the development of cheap portable terahertz diagnositic instruments is being impeded by the weakness of existing sources of terahertz radiation. By exploiting the terahertz radiation from the ALICE accelerator, which is seven orders of magnitude more intense that conventional sources, the team will advance the design of two different terahertz instruments and assess their performance against the more developed infrared techniques in cancer diagnosis. However before any of these techniques can be used by medical professionals it is essential that their strengths and limitations of are fully understood. This is one of the objectives of the proposal and it will be realised by comparing the results of each technique in studies of specimens from the three cancers that are the primary focus of the research. This will be accompanied by developing data basis and algorithms for the automated analysis of spectral and imaging data thus removing subjectivity from the diagnostic procedure. Finally the team will explore a new approach to monitoring the interactions between pathogens, pharmaceuticals and relevant cells or tissues at the cellular and subcellular level using the instruments deployed on the free electron laser at Daresbury together with Raman microscopy. If this is successful, it will be important in the longer term in developing new treatments for cancer and other diseases.

A major part of the diagnosis of any disease but particularly various forms of cancer, is obtained though a biopsy. This involves removing a small sample of tissue, or a few cells, from the patient. These samples, either tissue or cells are then examined by a pathologist looking down an optical microscope. In most cases the sample is stained with a combination of dyes to help gain some contrast. In most cases, based upon visual inspection of the sample a diagnosis is made. This process if far from ideal since it relies on the expertise of the clinician concerned as is subject to intra in inter observer error. Recently a number of proof of concept studies have shown that molecular spectroscopic techniques such as infrared and Raman are capable of distinguishing diseased from non diseased cells and tissue based upon the inherent chemistry contained within the cells. The UK is at the forefront of these developments but there are many hurdles that need to be overcome if this technology is to move from the proof of concept stage through the translational stage and into the clinical setting. It is the belief of the academic community that we are much more likely to overcome these hurdles if we pool our resources, bring in both industrial and clinical partners and work on these generic problems together. This application is for funding to support such a network of partners for the next three years.

Imagine a future where autonomous systems are widely available to improve our lives. In this future, autonomous robots unobtrusively maintain the infrastructure of our cities, and support people in living fulfilled independent lives. In this future, autonomous software reliably diagnoses disease at early stages, and dependably manages our road traffic to maximise flow and minimise environmental impact. Before this vision becomes reality, several major limitations of current autonomous systems need to be addressed. Key among these limitations is their reduced resilience: today's autonomous systems cannot avoid, withstand, recover from, adapt, and evolve to handle the uncertainty, change, faults, failure, adversity, and other disruptions present in such applications. Recent and forthcoming technological advances will provide autonomous systems with many of the sensors, actuators and other functional building blocks required to achieve the desired resilience levels, but this is not enough. To be resilient and trustworthy in these important applications, future autonomous systems will also need to use these building blocks effectively, so that they achieve complex technical requirements without violating our social, legal, ethical, empathy and cultural (SLEEC) rules and norms. Additionally, they will need to provide us with compelling evidence that the decisions and actions supporting their resilience satisfy both technical and SLEEC-compliance goals. To address these challenging needs, our project will develop a comprehensive toolbox of mathematically based notations and models, SLEEC-compliant resilience-enhancing methods, and systematic approaches for developing, deploying, optimising, and assuring highly resilient autonomous systems and systems of systems. To this end, we will capture the multidisciplinary nature of the social and technical aspects of the environment in which autonomous systems operate - and of the systems themselves - via mathematical models. For that, we have a team of Computer Scientists, Engineers, Psychologists, Philosophers, Lawyers, and Mathematicians, with an extensive track record of delivering research in all areas of the project. Working with such a mathematical model, autonomous systems will determine which resilience- enhancing actions are feasible, meet technical requirements, and are compliant with the relevant SLEEC rules and norms. Like humans, our autonomous systems will be able to reduce uncertainty, and to predict, detect and respond to change, faults, failures and adversity, proactively and efficiently. Like humans, if needed, our autonomous systems will share knowledge and services with humans and other autonomous agents. Like humans, if needed, our autonomous systems will cooperate with one another and with humans, and will proactively seek assistance from experts. Our work will deliver a step change in developing resilient autonomous systems and systems of systems. Developers will have notations and guidance to specify the socio-technical norms and rules applicable to the operational context of their autonomous systems, and techniques to design resilient autonomous systems that are trustworthy and compliant with these norms and rules. Additionally, developers will have guidance to build autonomous systems that can tolerate disruption, making the system usable in a larger set of circumstances. Finally, they will have techniques to develop resilient autonomous systems that can share information and services with peer systems and humans, and methods for providing evidence of the resilience of their systems. In such a context, autonomous systems and systems of systems will be highly resilient and trustworthy.