Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Why are some kids fat? Newspapers round up junk food, too many sweets and eating too much, but are these the only things that are important? What about the skinny cross country winner who eats like a horse or the big rugby player who eats hardly anything? What controls their weight? Also, why do children eat too much? Is it because they're bored, the fridge is full of their favourite food, dad or mum has cooked some delicious chocolate cake or because 'they have nothing better to do'? Many things contribute to obesity. To prevent it, we must identify those that are most important. Doing this is the science of EPIDEMIOLOGY - a big word that comes from the Greek EPI meaning disease and DEMOS meaning populations. Epidemiologists compare populations with a condition, e.g.obesity, or a disease e.g.leukaemia with those without the problem. They collect data about things which they can measure and which may be important e.g. what and how much food is eaten. These are called VARIABLES. Epidemiologists use these variables in statistical tests, run on computers, to identify which ones increase (or decrease) the risk of getting disease. This type of study has resulted in anti-smoking campaigns and the recommended '5 pieces of fruit a day'. Because of the importance of their results, epidemiologists design studies carefully and use the best statistical tests available. One of the most common is LOGISTIC REGRESSION - a mouthful more easily referred to as LR. LR is powerful; it can tease out important factors from a complicated mass of data by estimating the effect of one variable when adjusted for the effects of all others. In addition to LR, epidemiologists investigate different methods of analysis. Just as a sick person might seek a 'second opinion' from another doctor, epidemiologists need tests that either confirm or question their results. At the moment, there is no easily available and generally accepted alternative to LR. This proposal aims to alter this by using one of the most exciting developments in computing in the last 10 years. This development is SUPPORT VECTOR MACHINE learning - another mouthful best referred to as SVM. Although SVM sounds like a gadget, it is not. It is a technique of training computers to tell the difference between things. In this case, we are interested in training the SVM to tell us the difference between diseased and non-diseased groups, but the method has also been used to tell faces, voices and handwriting apart. It does this by selecting features that are important in differentiating or classifying the groups. So, SVM, like LR, identifies variables associated with disease but in a completely different way. Having two tests, working in different ways, assists epidemiologists in the same way that an X-ray and MRI scan are more helpful to a doctor than two X-rays. We have already used SVM, not on obese children, or smoking adults, but on a new disease of meat chickens. We studied chickens because we are veterinarians interesting in protecting their health and that of people who eat them. We first heard of SVM at a meeting held to introduce epidemiologists to new methods in mathematics and computing and were awarded a small amount of money to begin collaboration. We have shown that SVM is a useful technique but we need to test it in the field and develop an easy way for epidemiologists to use it. So, we are going to develop a user-friendly SVM program. Whilst doing this, we will write about SVM, talk about it at meetings, try it out on different diseases and train other people to use and evaluate it. Computer scientists and veterinarians may seem a strange combination. It is! We have each had to learn new jargon, just to talk to each other...we even use the same words for completely different things.... But, if epidemiologists are to use the power of modern computing to help prevent disease, teams such as these are essential. They are also a lot of fun!

Terahertz (THz) device research and studies of THz phenomena in solid state systems require detection of THz waves and signals on the scale of few microns. These measurements present a major technological problem caused by diffraction of THz waves. The diffraction limit prevents the use of the recently developed THz spectroscopic instrumentation for studies of objects smaller than approximately a wavelength. Near-field surface probing methods have shown potential solutions in overcoming the diffraction limit. However all the existing THz near-field techniques exhibit another fundamental limitation due to significant perturbations in the electric field caused by the near-field probe. The probe invasiveness and a non-uniform frequency response across the THz spectrum prevent the use of the existing near-field probes for mapping of electric field distribution in THz devices. In addition, THz near-field imaging systems with spatial resolution better than ~1/20 of a wavelength suffer from a severe reduction in sensitivity.To mitigate these problems and to allow high spatial resolution studies with THz waves we propose to develop a THz imaging and spectroscopy system with a novel near-field probe. The probe concept exploits the non-invasive nature of the electro-optic detection method and utilizes an optical micro-resonator to enhance the detection sensitivity. The proposed electro-optic micro-resonator will be integrated into a fibre-coupled near-field probe. It will allow THz wave and signal probing with a spatial resolution of ~5 microns (~1/100 of the wavelength) and it will offer full spectroscopic capabilities in the THz range (0.1-2.0 THz). The novelty of this approach is in exploiting the optical cavity resonance for electro-optic detection of THz waves by an extremely small near-field probe. The goal of this research programme is to develop and build the THz near-field probing system and apply it in device research on the sub-wavelength scale. The proposed technology will expand the spectrum of THz studies to micrometre-scale objects. It will aid in the progress of THz device research and will facilitate studies of THz phenomena in physics, materials science and other disciplines.

Complex systems, like liquids made out of molecules, large molecules made out of atoms, lawn made out of grass, etc. are impossible to describe fully. In fact, such a description it is not even desirable, as one would be overwhelmed by information impossible to interpret. Typically, a few characteristics of the system, like density profiles, relative frequencies of inter-object distances, are of great importance. An effective way of treating such complex systems is to concentrate on the properties of these characteristics. In such an approach a system of equations describing the characteristics is derived in some ad hoc manner. The question is then: are the solutions of these equations still compatible with the originally considered complex system? In other words, do states of the complex system exist, which would give rise to these characteristics? As an example, if the effective equations predicted a negative density of particles, then the answer would be 'no'. For more complicated characteristics or collections of characteristics, one cannot expect the relations between them, which are usually in the form of inequalities, to be so obvious. The realizability and representability problems are to identify these conditions and to determine which putative characteristics can in fact be realized by a state of the underlying system.Realizability and representability arise repeatedly in different areas, thus they seem to be a very promising viewpoint on complex systems. It is also timely to attack these problems, due to a recent interest in these problems as in many different areas of statistical mechanics, like jamming, random packing, optimal packing in high dimensions, and heterogeneous materials, as well as in quantum chemistry. Progress is hindered by a lack of understanding of the underlying mathematical structure of these problems, both of which can be interpreted as high-dimensional truncated moment problems. Even the two dimensional case is already known to be very difficult. Ideally, one would obtain an approach which permits one to derive the microscopic interactions from macroscopic measurements.One can give a theoretical description of all inequalities for putative correlation functions characterizing realizability based on a general approach coming from the theory of truncated moment problems. This description is unfortunately so indirect that only a few conditions are known explicitly. It is a very hard problem to express further conditions in an explicit manner. Beside its practical importance this last question provides an important connection between the project and areas of pure mathematics.

What impact have local electric field fluctuations on neuronal activity? Recording extracellular action potential is one of the primary methods to study brain function in the living animal. Understanding and quantifying the effect of the local field potential on the transmembrane potential of neurones is crucial for determining whether and when a given synaptic input will cause neurones to initiate an action potential. Since the days of Hodgkin-Huxley and their equations, neuronal membrane and extended dendritic as well as axonal structures have been modelled using one-dimensional cable theory in combination with linear or nonlinear time, voltage- and ligand-gated membrane conductances. In this entire body of work a common assumption was that the extracellular potential (Ve) is uniform, i.e. it does not depend on space, and is constant in time. Both assumptions, however, are known to be wrong - otherwise one could not record action potentials from outside neurones - but were justified by arguing that contributions of a non-uniform Ve(x, t) could be neglected. We propose to study theoretically the effect of a non-uniform and dynamic Ve on different levels of neuronal complexity: (a) on a single, unbranched cable model of a neurone, (b) on hippocampal pyramidal neurones with realistic dendritic morphology and electrophysiological signature and (c) on a population of simplified cortical cells exhibiting typical morphology and activity. In the first two stages, existing simulators from Prof. Christof Koch's lab (California Institute of Technology, USA) will be implemented as well as experimentally measured spatial and temporal Ve distributions from electrode arrays from Prof. Gyorgy Buzsaki's lab (Rutgers, USA). Recent in vitro studies indicate that in hippocampus electric field effects play a crucial role on neuronal synchronization. Based on these results, in the third stage, a reduced model will help us study the same effects on a neuronal population where features of small-world dynamics and synchronization will be investigated. All our theoretical conclusions will be compared to detailed experimental measurements.What effects do large excursions of Ve (up to 10 mV/mm for hippocampal sharp waves) have on the spiking activity of individual hippocampal pyramidal neurones? Will the firing of the neurone become entrained to the electric field through direct, so-called ephaptic, effects? How are these phenomena reflected upon a population of neurones firing? Are these effects manifested differently on the typical oscillatory frequencies that are attributed to diverse behavioural states? These are just a few of the questions we seek to investigate with this proposal.