In this project we will build an artificial intelligence (AI)-based image analysis tool called "MechanoAI-tool" trained to identify changes in vascular smooth muscle cell (SMC) shape and structure in response to changes in the stiffness of the surface the cells are plated on. Being able to easily identify these changes in SMC shape is important because vascular SMCs are the cell types that make up the walls of blood vessels and control blood flow to our organs by contracting or relaxing. This contraction or relaxation depends on a number of signals which includes the mechanical factors acting on the cell such as stiffness or stretch. However, as we age, our vessels become stiffer and the way vascular SMCs respond changes, which together can impact blood flow to vital organs. Measuring how vascular SMCs respond to stiffness changes is a good indicator of ageing. However, many methods for studying stiffness responses require complex genetic techniques and expensive microscopes which act as barriers to entry for many research groups. We think that image analysis of vascular SMC responses under simple phase contrast microscopy, which is cheap and widely available, will provide an accessible, and robust way to test whether any given SMCs respond appropriately to stiffness changes or not. However, interpreting the changes on a simple phase contrast microscope is not easy and we will therefore develop an AI-based image analysis tool to identify normal vs abnormal responses quickly and reliably. These findings and the Mechano-AI-tool that we develop could be used to predict biological properties of vascular SMCs by any research group world-wide and have applications in SMC biology, ageing and vascular disease research.

Since the realisation of Bose-Einstein condensation of ultracold atoms in 1995, experiments on ultracold atoms have allowed us to explore and understand many aspects of many-body physics, i.e. understanding the consequences of quantum mechanics with large numbers of interacting particles. This is important because such many-body physics is responsible for effects such as superconductivity, superfluidity, and magnetism. In addition, understanding this physics is necessary to be able to exploit quantum behaviour for computing or communication technologies. Even with the impressive capabilities these experiments have shown, there remain phenomena that have been challenging to realise with the short-range interactions between atoms confined using fixed patterns of lasers. Recently, experiments with cold atoms in optical cavities (i.e. placed between high quality mirrors that trap light) have provided an extra set of tools for how to engineer many-body physics. In particular, experiments using cavities supporting multiple cavity modes have vastly broadened what states can be explored. Light in the cavity can affect atoms in the same way as an external laser, but crucially allows feedback of the motion and state of the atom on the cavity light. This gives controllable cavity-mediated quantum interactions between atoms, where we can change the range and structure of how atoms interact. Building on our collaboration with the only group in the world to have realised such experiments, we will develop the theoretical methods and approaches that are required to understand these experiments. While our work is driven by the exciting developments in these specific systems, the methods we will develop have far wider application. A key feature of these experiments is that because they involve light, they generally require understanding the effects of light leaking out of the mirrors, and of driving by external lasers to balance this. The light that escapes plays a key role, allowing us to monitor the experimental system, and potentially introduce quantum feedback. This means that the methods we need are those of the field of "many-body open quantum systems". This field seeks to understand how to describe quantum systems that are affected by noise, loss, and external driving. As such, this field is crucial to understanding how quantum technologies operate in the real world. To maximise the possibilities arising from these new "Multimode Cavity QED" experiments, our key objectives are: Developing theoretical methods (including numerical techniques) for modelling many-body open quantum systems. Understanding the quantum dynamics in the spin-glass states that can be realised in experiment, including finding how to optimise their performance as "associative memories" (where one can input a corrupted version of a memory, and have the system recover the corrected version). Determining how superconducting pairing can be realised and controlled using atoms in a multimode cavity, and whether this can be used to study "exotic" forms of superconductivity, such as those which may explain high-temperature superconductivity. The methods we will develop to achieve these goals will find widespread application across a range of many-body open quantum systems, thus supporting a broad range of experimental and theoretical researchers.

The proposal draws on work to better understand conditions facing British businesses by the universities of Nottingham and Stanford, who established the Decision Maker Panel (DMP) in partnership with the Bank of England (Bank) in 2016. This was funded by the ESRC through standard grants from 2017 - 2022 and it is recognized within HM Government as essential data infrastructure. To date, DMP has been essential to gaining a better understanding of the effects of Brexit, Covid and the Ukraine war during a period of enormous economic, geo-political and social change, delivering actionable insights for policymakers at the highest levels of government. It has delivered policy-focused research that is an essential resource for the Bank of England, HM Treasury, 10 Downing St and the Cabinet Office, Office for National Statistics (ONS) and the Office for Budget Responsibility (OBR) since 2016. It has received the ESRC Celebrating Impact Prize (second prize) 2021, it was described by the Deputy National Statistician as 'a game changer for business surveys', and 'world leading' 4* impact case study by REF2021. The ability to maintain a large, representative survey of senior business executives and to address the impacts and longer term effects of economic disruptions has made it vital infrastructure for policy. It maintains a corpus of questions that provide longitudinal quantitative information on business conditions, expectations and uncertainty and has the flexibility to adapt survey questions to new conditions as they emerge e.g. during Covid. The DMP has developed into a strategic data asset that we have made accessible to researchers beyond the core DMP team. In this proposal we will i) gather data from key decision makers in business; ii) provide a delivery plan to analyze the data for actionable insights; and iii) make the data available to other researchers. We will build capacity in survey data collection and analysis that sustains and expands economic and societal impact. The grant will support ongoing data collection of DMP data making it: > One of the largest business surveys in the UK, which is maintained by minimizing attrition and continuously recruiting new firms. > A regular source of information to businesses, journalists and academics through monthly letters sent to all the participants and the website www.decisionmakerpanel.co.uk > An essential input to Bank of England Policy Committees (MPC, FPC), HM Treasury, BEIS and OBR drawing on DMP research analysis to support the actions and communication of policy The research we undertake will address six vital questions: 1. What are the effects of Brexit on employment, investment, R&D, productivity growth, trade, prices, and wages of UK firms? 2. What are the uncertainty impacts of the COVID pandemic on firms? 3. How will firms respond to the resurgence of inflation? 4. How will investment growth policies announced in several Budgets and fiscal statements incentivize UK firms? 5. What effects will climate change make to firm investment and risk exposure? 6. What effect does CEO leadership have on performance? We draw on a highly-experienced established team of international researchers that have created a 'world-leading' survey to address We draw on a highly-experienced established team of international researchers that have created 'world-leading' surveys to address similar policy related research since 2016 in collaboration with the Bank of England, HM Government and the Office for National Statistics. Drawing on senior academics from Nottingham and Stanford we offer benefits to academics and users of the research through academic papers in top five economics journals, blogs, podcasts and media outputs, impact for policy making. We will create a publicly accessible dataset and build capacity in survey design and analysis by training a new cohort of early career researchers, giving them opportunities for secondment and career advancement.

Mobility systems are on the brink of revolution as they suffer from an overloaded infrastructure causing users' dissatisfaction, pollution, increased inequality, health dangers. In London alone, exposure to NO2 accounts for 5900 fatalities/year, with healthcare costs of 1.4BGBP/year. For these reasons, the UK Government identified Future Mobility as one of the four Grand Challenges. At the same time, the advent of new forms of mobility and big data provides remarkable opportunities. In this context, Intermodal Mobility -- where different modes of transport provide complementary services -- is a promising paradigm, as it combines efficient long-distance transport with last-mile services. However, their operation has resulted in equally many challenges. Most notably, transportation authorities struggle to understand how new mobility solutions should be integrated within the existing infrastructure, how to orchestrate and regulate them in a cohesive way, and how to identify those that will ultimately improve equitability and reduce system-wide congestion. At its core, these challenges stems from the fact that privately-owned mobility providers often have objectives that are misaligned with those of the transportation authority (e.g., maximise profit vs minimise congestion/inequity), and result in competing with existing modes of transport as opposed to complementing them. To address these challenges, COSMO aims to develop mathematical models to describe the competition between mobility providers, to analyse these models, and to exploit them to design optimisation-based and cooperation-inducing subsidies to reconcile the providers interest with that of improving equitability, minimising congestion, or a combination thereof. More in details, the first component will deliver a threefold set of cohesive contributions: i) the development of a concise game-theoretic model for competition between different mobility providers, ii) the study of the resulting equilibria, and iii) the design of efficient equilibrium computing algorithms. Building atop the first, the second component will leverage recent breakthroughs in optimization and game theory to design optimization-based cross-subsidies that trade-off between maximising equitability and minimising congestion/emissions. These two components will culminate in the release of an open-access algorithmic suite, whose effectiveness will be tested on synthetic and real-world case studies on US cities and the Borough of Greenwich, shared and developed jointly with project partners. In the spirit of this call, the research will be carried out in close collaboration with leaders in smart mobility (Dr. Pavone, Stanford University & NVIDIA Research) and transportation (Dr. Osorio, HEC Montreal & Google Research), with whom a number of networking activities have been co-designed including an extended visit at Stanford University and HEC Montreal, daily visits and invited talks at NVIDIA Research and Google Research.

All population fluctuate in size from year to year. An understanding of the causes of these changes in size is helpful when managing and conserving populations and has interested biologists for more than three centuries. Until recently, understanding changes in population size, i.e. population dynamics, has concentrated on investigating the changes in numbers alone, ignoring differences between individuals. Over the last few years there has been an increasing realisation that differences between individuals in age but also in traits like body size or condition crucially affect the way populations respond to changes in the environment over time. In addition, biologists have realised that evolutionary change can happen much faster than had previously been appreciated and that ecological and evolutionary change can happen simultaneously. This means that an ability to understand population dynamics, necessary to predict and manage populations, may require understanding of the way traits change in response to ecological and evolutionary pressures. Understanding dynamics may therefore require insight into how ecological and evolutionary processes are linked. Because all ecological and evolutionary change is determined by differences in birth and death rates between groups of individuals, we can use data on the survival and fertility rates of individuals living within a population to marry changes in trait distributions to changes in population size. This is what we will do in this grant. What will the work we do deliver? Take a concrete example: harvesting large individuals from a population will affect more than just the numbers of adults: it will alter the way the animals compete for resources, allowing smaller individuals greater access, perhaps allowing them to grow or reproduce more; it is also likely to alter average reproductive rates as larger individuals may reproduce more, or give rise to higher quality offspring. Harvesting will also alter the selection pressure on individuals, making it more beneficial to mature earlier and at a smaller size. Thus harvesting's effects are more profound than simply the removal of some individuals leaving all others unchanged. We expect that our work will allow us to understand how (1) selectively removing specific individuals from a population is likely to impact the dynamics of the population, and (2) how different types environments lead to changes in the distribution of traits like body size. This will provide some information on how we might expect changes in the climate to influence both the evolution of traits like body size, as well as fluctuations in population size. The approach we will take has never been applied to animals. We will use data from four contrasting animal species / a monogamous bird, the silvereye; free-living Soay sheep; group-living meerkats; and laboratory populations of soil mites. These systems have been chosen because previous research has provided a good understanding of many aspects of their ecology, because detailed data exist and because they have very different life histories and ecologies. By investing a range of species simultaneously, we will also be able to get a feeling for the generality of our conclusions and the degree to which we need to develop joint understanding of the way numbers and traits vary.