The UK has an unparalleled tradition of longitudinal birth cohort and panel studies that track generations of babies (and their families) from birth throughout the lifespan. The cohorts span over 70 years. The 1946 British Cohort Study and the 1958 National Child Development Study have been following the lives of over 20,000 people born in England, Scotland and Wales. These studies have been tracking study participants' height, weight, health, school performance, social class, deviance (e.g. bullying others, crime behaviours), and their later employment and relationship histories, health, life satisfaction and so on. Another study began in 1970; and then others in the 1990s and 2000s, including twin cohort studies, which can assess the relative importance of genetic and environmental influence on child development. Taken together, this research has made major contributions to UK health, education, economic and social policy, and to our understanding of individual development across the life course. The recent ESRC Longitudinal Studies Strategic Review noted that advances in longitudinal studies in other countries - including Japan - are now opening up key opportunities for rigorous international comparative studies on a wide range of issues including comparisons of life-course trajectories to better understand how environmental circumstances and policy can affect development trajectories, health and other outcomes. The Review also, however, noted that there is currently a lack of the right mix of skills and mentoring in quantitative 'know-how' to make these sorts of comparative analyses possible. More specifically, The Review highlighted the need for data harmonization to enhance international comparative research and improve its methodological foundations. This application aims to create sustainable international collaborations between UK and Japanese researchers to enable high-quality applications for future UKRI-JSPS bilateral research calls, as well as high quality peer-reviewed journal articles. We aim to bring together UK and Japanese researchers who are examining risk pathways to inform detection and prevention, fitting well with the ESRC's priority to understand social factors involved in mental health. To this end, we will utilise the pump-priming funds to (i) have a UK team deliver two workshops in Japan on data harmonisation and the estimation of developmental trajectories. We envisage that these workshops will act as a forum to begin a dialogue about wider harmonisation possibilities within existing cohort studies. (ii) The Japanese researchers will come to the UK to showcase existing projects and papers that arise from these workshops.

We are already experiencing the impacts of climate change. In recent years, more intense storms, particularly in northern, central and eastern Europe, the Americas and South and East Asia, have led to an increase in extreme erosion events. For example the tails of Atlantic hurricanes have hit Europe for the first time (e.g. Storm Eleanor, Storm Eberhard). The impact of these erosion hazards are of global importance because they are wide ranging, costly and of critical importance to the vulnerability of assets. During the last 50 years nearly one-third of the world's arable land has been lost by erosion, causing an annual cost to global GDP of $8BN. In the UK for example, erosion causes £336M a year in extra flood damage, are a considerable source of water pollution totalling costs of £238M a year, and increase the costs of water treatment and maintenance of drainage networks by £132M a year. They cause considerable damage to critical infrastructure such as roads and electricity pylons, and account for 25% of valid subsidence insurance claims. In Fukushima, erosion is the major cause of wash-off of radiocaesium to rivers and streams, and ultimately to the Pacific Ocean. Thus creating resilient, sustainable infrastructure depends on accurate prediction of the future risks of more extreme erosion hazards. Yet at present, soil erosion models for river catchments perform poorly in predicting erosion rates in extreme, high intensity storms. Japan has been experiencing these types of storm events for many decades, predominantly during the monsoon season, (the so called "guerrilla rains") e.g. Typhoon Hagibis during the Rugby World Cup caused damage totalling >$15BN and killed 98 people. The Japanese National Research Institute for Earth Science and Disaster Prevention and the University of Tsukuba has world-leading laboratory and field infrastructure to monitor the impacts of these events on erosion. This project brings together the highly complementary expertise of these partners with the state-of-the-art modelling tools at the University of Liverpool. Through a set of novel, integrated field, rainfall-simulation and numerical experiments, the partnership will produce novel understanding of the controls of erosion dynamics in high intensity rainfall, and the development of more realistic models that will enable global scientists to better forecast the impacts of extreme erosion events. Together we will develop the ideas, datasets and modelling tools to facilitate a major step-forward in understanding high-magnitude erosion events, both through the direct activities of this proposal, and by creating a long-lasting partnership. The outputs will include: - Scientific insights into erosion during extreme, high rainfall intensity storms, and how this might change as a result of climate projections - A quantitative predictive modelling framework that provides much needed accurate forecasts of erosion hazards, that can be applied to assess future erosion risk to critical infrastructure - A long-lasting world-leading partnership in erosion monitoring and prediction, and a spring-board for new links and scientific discovery with global researchers

The continued releases of radioactive material from the earthquake-damaged Fukushima Dai-ichi nuclear power station in Japan, with the risks to water, coastal environments, agricultural land, animals and human health have drawn international concern. The incident, together with the Chernobyl disaster a generation earlier, has highlighted the importance of being able to detect, measure and monitor radiation in our environment. This is no easy challenge - the amounts of radioactivity are often low (relative to controlled medical or industrial settings) or highly dispersed through soils, sediments and water. There is also a considerable background radiation all around us, not only from the legacy of human nuclear technology but from natural minerals, gases (eg. radon, a major problem in some regions), cosmic and solar sources. On the other hand, this radioactivity is used widely by earth and environmental scientists to date rocks, monitor sediment movement and geomorphological changes, or the growth rates and life histories of plants and animals. If we are to measure environmental radioactivity, not just to help clean-up and recovery after an accidental release but also to monitor sites, prevent releases and support the safe operation and decommissioning of nuclear facilities (as well as support that range of scientific research needs), then we need continuous improvement of sensors which can detect and quantify radiation sources to higher resolution, lower detection thresholds and shorter measurement times. The current generation of sensors is based on mechanical collimators, a technology similar to the 'pixellated' image sensors in digital cameras, in which the radiation arriving at any point on the surface is used to build up a 2D image of the radiation source. Nuclear physicists at the University of Liverpool have recently developed a new approach for detection of gamma radiation called Compton-geometry imaging. In this approach, two sensors are placed one in front of the other and the measurement is based on the scattering of radiation between them. The technique is powerful because the position of the radiation source is located by mathematically reconstructing the origin of many scattering events, rather than by the physical position of the incident radiation on the collimator surface. This 'electronic' collimation can resolve the position of the source with much greater accuracy and sensitivity than mechanical collimation, has the advantage of being able to locate the source in 3D, and yields smaller, lighter detector equipment with potential savings in measurement time. Currently, only two other research groups in the world are working with this technology. The objective of this proposal is to understand how this powerful new technology can be optimised for environmental gamma radioactivity measurements. Research so far has focused on the development of prototype Compton cameras for industrial and medical applications, which present very different challenges to the environmental conditions described earlier. By combining a world leading expertise in device development in close collaboration with academic and industry end-users in environmental science and engineering, this Technology Proof-of-Concept proposal aims to develop design criteria, optimised system specifications, and a first prototype for a Compton camera which we intend will set a benchmark for the next generation of environmental radioactivity sensors. Imagine being able to locate a radioactive substance beneath the ground and monitor how it moves with changes in water flow or sediment movement. Or to watch, using a portable device, in real-time how plants and animals take up radioactive materials from contaminated soils and move them into the food chain. Star Trek science? Perhaps for now, but the environmental Compton camera that is the long-term goal of this research project moves us a significant step closer towards that vision.

Complex system often exhibit a dynamics that can be regarded as superpositionof several dynamics on different time scales.A simple example is a Brownian partice that moves in an inhomogeneousenvironment which exhibits temperature fluctuations in space and time on a relatively large scale. There is a superposition of two relevant stochastic processes,a fast one given by the velocity of the particle and a much slower onedescribing changes in the environment. It has become common to call thesetypes of systems 'superstatistical' since they consist of a superposition of twostatistics, a fast one as described by ordinary statistical mechanicsand a much slower one describing changes of the environment. The superstatistics is very general and has been recently applied to a variety of complex systems, including hydrodynamicturbulence, pattern forming nonequilibrium systems, solar flares, cosmic rays,wind velocity fluctuations, hydro-climatic fluctuations, share price evolution,random networks and random matrix theory.The aim of the research proposal is twofold.On the theoretical side, the aim is to develop a generalisedstatistical mechanics formalism that describes a large variety of complexsystems of the above type in an effective way. Rather thantaking into account every detail of the complex system, one seeksfor an effective description with few relevant variables. For thisthe methods of thermodynamics are generalised:One starts with more general entropy functionsthat take into account changes of the environment(or, in general, large-scale fluctuations of a relevant system parameter) as well. An extended theory also takes into account how fast the local system relaxes to equilibrium,thus describing finite time scale separation effects.On the applied side, the aim is to apply the above theory to a large variety of time series generated by different complexsystems (pattern forming granular gases, brain activityduring epileptic seizures, earthquake activity in Japan and California, evolutionof share price indices, velocity differences in turbulent flows).It will be investigated which superstatistical phenomena are universal(i.e. independent of details of the complex system studied) and whichare specific to a particular system. Possible universality classeswill be extracted directly from the data. Application-specific modelswill be developed to explain the observed probability distributionsof the slowly varying system parameters.