Space-borne synthetic aperture radar (SAR) observations can be used to measure structure and velocity within the Antarctic ice sheet. Most SAR missions to date have used L-band frequencies (1-2 GHz) but interest is now turning to lower-frequency P-band signals (around 430 MHz) because they have greater penetration of the ice. Both the University of Bath and BAS are currently involved in feasibility studies relating to P-band SAR design for future ESA satellites. P-band SARs in polar orbits such as the ESA BIOMASS satellite due to launch in 2014, have the potential to map out the three-dimensional structure of ice sheets. However, their signals will suffer from significant ionospheric effects including Faraday rotation, range defocusing, range delay and interferometric phase bias. The ionosphere must be taken into account in the system design but the necessary ionospheric measurements to do this do not currently exist. This project will deliver the measurements for the Antarctic region and lay the foundation for successful P-band SAR missions. This project involves equipment development, fieldwork and analysis. The objective of the fieldwork is to deploy modified GPS receiving equipment that will for the first time take measurements of total electron content (TEC), plasma velocity and ionospheric scintillation at remote locations across the Antarctic. To achieve this, eight new GPS receivers will be deployed to undertake long-term measurements in the auroral and polar-cap regions over a two year period. Additional data from lower Antarctic latitudes will be provided by international partners. The measurements will be used to develop a multi-scale model of the Antarctic ionosphere. This model will be a critical input to SAR design that will minimize the impact of the ionosphere on ice measurements for future satellite missions.

There is little doubt we must reduce greenhouse gas emissions to avoid catastrophic climate change. There is however, a disconnect between human activities and impact in energy and carbon externality. By monitoring energy use for a specific human activity, Ubicomp technologies may help us uncover this hidden impact. Our aim is to bring Computer Science, Economics, Carbon Profiling and Sociology together to explore the feasibility of identifying and informing people of 'critical moments in their daily activities that have carbon impact', so they can individually and collectively make savings. We will work with an actual community using a novel set of technological and cultural probes, involving embedded sensors, smartphone applications, aggregated 'crowdsourced' data and ethnographic field work, to deliver a richer understanding of behaviour that leads to lower carbon lifestyles, backed up by experimental data showing the impact of our intervention feeding this back to end-users. Our software, high level results, algorithms and models will be placed into the public domain and communicated through our programme of engagement, such as developing teaching materials with local schools.Our hypothesis is people are unaware of their direct and indirect energy usage and its associated climate change impact: this is a barrier to understanding how to achieve 'low carbon living' personally, as communities. During a 2 year feasibility study our objectives are to:1. Gather baseline data about energy use and associated carbon footprint that is personally attributable;2. Develop real-time models of financial and environmental tradeoffs for identifing opportunities for savings;3. Communicate opportunities for making savings back to individuals, enabling greater awareness and making it easy to chart the effect of household 'energy related experiments';4. Provide methods for comparing the usage against others in one's social network i) as an incentive, and ii) to raise awareness of low cost opportunities for collective action (such as ride-sharing);5. Create online resources and teaching materials to communicate our findings to a wider population beyond the study group.We have established links with Galloway Carbon Action Project (a community of 2,800) homes who have pledged us support and access to the three communities involved. This is a perfect complement for gathering real world data and findings from end-users and for communicating our findings and having a significant real-world impact. We also have links with local schools who are prepared to help us develop teaching materials, to help us communicate the key lessons to local communities.

Microwave Imaging (MI) has gained a great deal of attention among researchers over the past decade, mainly due to its potential use in breast cancer imaging. MI is seen as a safe, portable and low-cost alternative to existing imaging modalities. Due to the breast tissue properties at microwave frequencies, MI benefits from significantly higher contrast than other techniques. The great excitement about MI radar system is that, using a multi-static real aperture technique and sophisticated signal processing, it has sufficient resolution to be clinically useful and is far better than simple wavelength assumptions would estimate. Whilst to date MI has been mainly proposed for breast cancer detection, some recent reports have also speculated a use of MI in extremities imaging, diagnostics of lung cancer, brain imaging and cardiac imaging. Despite the interest in Microwave Imaging among researchers, it has not moved far beyond numerical simulations and very simple experimental works without clinical realisation. Bristol is among two research groups in the world who have clinical experience with Microwave Imaging.Compared with other medical imaging techniques, microwave imaging is still in its infancy. One historical reason for this might due to the fact that most microwave systems-devices originated in military applications, radar being an obvious example. In recent years however, due to the mobile/wireless revolution, we have witnessed unprecedented progress in high performance microwave hardware as well as computing power. This opens up a unique opportunity for development of microwave imaging systems. The goal of this Career Acceleration Fellowship project is to explore a novel direction in MI, Differential Microwave Imaging (DMI), in clinical applications reaching far beyond breast cancer detection. In Differential Microwave Imaging, the goal is to image temporal changes in tissue, and not the tissue itself. This somewhat limits usability of DMI as an imaging technique on one hand, but at the same time it opens up totally new applications where standard Microwave Imaging could not be applied. The idea of DMI came from the discovery during world's first clinical trial of microwave radar imaging system in Bristol in 2009. During the clinical trials it was realised that the Microwave Imaging system was extremely sensitive to any changes occurring during the scan. Following this up it was then discovered that the local change in tissue properties can easily be detected and precisely located. Moreover, it was shown that this change in local properties of tissues can even be detected in very dense and heterogeneous breast tissues. The project will focus on two applications, serving as Proof of Principle:1. Nanoparticle contrast-enhanced DMI for cancer detection The proposed work on 3D detection of nanoparticles is of great interest to researchers working in the cancer imaging field. DMI could find applications not only in cancer detection, but it could also be used to find and evaluate the effectiveness of new cancer biomarkers, track nanoparticle-labelled cells or monitor delivery of nanoparticles for hyperthermia treatment. 2. Functional brain imaging using DMI radar systemDMI, as a general method, is also a promising concept for functional brain imaging. Development of the DMI system for functional brain imaging is timely related to current research activities in neuroscience. Functional imaging is used to diagnose metabolic diseases and lesions (such as Alzheimer's disease or epilepsy) and also for neurological and cognitive psychology research. This novel interdisciplinary project connects the fields of electronic engineering, nanotechnology and medical physics. The proposed research project addresses one of the EPSRC strategic priorities: Towards next generation healthcare. High calibre of clinical collaborators will ensure that research outcomes are relevant to end users.

A concept of central importance in mathematics is that of symmetry. One used to think of symmetry as a property of geometric shapes, but in the 19th century Evariste Galois extended the concept of symmetry to algebraic objects, and today his insights are completely fundamental to pure mathematics. The underlying goal of this proposal, which is situated between Algebra, Number Theory, and Topology, relying also on techniques from Probability Theory and Additive Combinatorics, is to study symmetries of arithmetic and geometric objects. Number Theory is an ancient mathematical discipline with a rich history of over 2000 years, but also with spectacular developments in recent years. Some of the most impressive recent advances have happened in the area of Number Theory called Arithmetic Statistics: the groundbreaking contributions of Manjul Bhargava have been rewarded with a Fields Medal in 2014. The aim of Arithmetic Statistics is to understand the behaviour of arithmetic objects, such as (ray) class groups, in families. The birth of this area goes back to Gauss, who formulated some concrete conjectures concerning the behaviour of class groups of quadratic fields. It was given a huge boost in the 1980s, when Cohen and Lenstra proposed a general model that implied all the conjectures of Gauss, and more. Roughly speaking, they postulated that class groups of imaginary quadratic fields obey a probability distribution that assigns to a finite abelian group X a probability that is inverse proportional to the number of symmetries of X. This is, in fact, a very natural model for random algebraic objects. This was later generalised to other number fields by Cohen and Martinet, but in more general cases the probability distributions looked more mysterious. The Cohen-Lenstra-Martinet Heuristics have been used as a guiding principle in Arithmetic Statistics since then, and have found applications in many other areas, such as the theory of Elliptic Curves, in Combinatorics, and in Differential Geometry. This project will consist of a blend of theorems, conjectures, and computations. I will: - show that the original conjectures are false, as stated, - find the correct formulations, - put them on a more conceptual footing, by explaining the mysterious looking probability weights of Cohen-Martinet using a theory of commensurability of algebraic objects that I have been developing together with Hendrik Lenstra, - extend the scope of the heuristics, e.g. to ray class groups. Two other kinds of very basic objects whose symmetries one studies are finite sets and finite dimensional vector spaces. An old problem in Representation Theory, with applications to Number Theory and Differential Geometry, is to compare symmetries of sets with symmetries of vector spaces, and in particular to determine which symmetries of sets become isomorphic (essentially the same) when the sets are turned into vector spaces. There are two incarnations of this problem: one where the vector spaces are over a field of characteristic 0, e.g. over the real numbers, and one where they are vector spaces over a field of positive characteristic. In previous joint work with Tim Dokchitser we have solved the case of characteristic 0, thereby settling an over 60 year old problem. Using the techniques that we developed, and new ones, this project will settle the case of positive characteristic. Finally, I will also investigate symmetries of low-dimensional manifolds. These are the basic objects studied by modern geometry and topology, and it is an old and fruitful line of investigation to determine what one can say about the topology of the manifold from knowing its symmetries. In recent joint work with Aurel Page, I have introduced a new representation theoretic tool into the area, which I had worked on in number theoretic contexts. Using these new techniques, I am planning to shed more light on the connection between symmetries and the topology of the manifold.

This project addresses how environmental change affects the movement of sediment through rivers and into our oceans. Understanding the movement of suspended sediment is important because it is a vector for nutrients and pollutants, and because sediment also creates floodplains and nourishes deltas and beaches, affording resilience to coastal zones. To develop our understanding of sediment flows, we will quantify recent variations (1985-present) in sediment loads for every river on the planet with a width greater than 90 metres. We will also project how these river sediment loads will change into the future. These goals have not previously been possible to achieve because direct measurements of sediment transport through rivers have only ever been made on very few (<10% globally) rivers. We are proposing to avoid this difficulty by using a 35+ years of archive of freely available satellite imagery. Specifically, we will use the cloud-based Google Earth Engine to automatically analyse each satellite image for its surface reflectance, which will enable us to estimate the concentration of sediment suspended near the surface of rivers. In conjunction with other methods that characterise the flow and the mixing of suspended sediment through the water column, these new estimates of surface Suspended Sediment Concentration (SSC) will be used to calculate the total movement of suspended sediment through rivers. We then analyse our new database (which, with a five orders of magnitude gain in spatial resolution relative to the current state-of-the-art, will be unprecedented in its size and global coverage) of suspended sediment transport using novel Machine Learning techniques, within a Bayesian Network framework. This analysis will allow us to link our estimates of sediment transport to their environmental controls (such as climate, geology, damming, terrain), with the scale of the empirical analysis enabling a step-change to be obtained in our understanding of the factors driving sediment movement through the world's rivers. In turn, this will allow us to build a reliable model of sediment movement, which we will apply to provide a comprehensive set of future projections of sediment movement across Earth to the oceans. Such future projections are vital because the Earth's surface is undergoing a phase of unprecedented change (e.g., through climate change, damming, deforestation, urbanisation, etc) that will likely drive large transitions in sediment flux, with major and wide reaching potential impacts on coastal and delta systems and populations. Importantly, we will not just quantify the scale and trajectories of change, but we will also identify how the relative contributions of anthropogenic, climatic and land cover processes drive these shifts into the future. This will allow us to address fundamental science questions relating to the movement of sediment through Earth's rivers to our oceans, such as: 1. What is the total contemporary sediment flux from the continents to the oceans, and how does this total vary spatially and seasonally? 2. What is the relative influence of climate, land use and anthropogenic activities in governing suspended sediment flux and how have these roles changed? 3. How do physiographic characteristics (area, relief, connectivity, etc.) amplify or dampen sediment flux response to external (climate, land use, damming, etc) drivers of change and thus condition the overall response, evolution and trajectory of sediment flux in different parts of the world? 4. To what extent is the flux of sediment driven by extreme runoff generating events (e.g. Tropical Cyclones) versus more common, lower magnitude events? How will projected changes in storm frequency and magnitude affect the world's sediment fluxes in the future? 5. How will the global flux of sediment to the oceans change over the course of the 21st century under a range of plausible future environmental change scenarios?