In this proposal, I want to develop optimisation frameworks that will use smart card and mobility-as-a-service subscription data to address strategic (transit route network design problem) and (if time allows) tactical (frequency setting and timetabling) public transport planning problems. The use of public transportation is decreasing all around the UK, except London, every year. Last year, more than 80% of the distances are travelled by private cars in Britain. There may be many reasons for the lack of enthusiasm for public transport, e.g. poor connections, infrequent service or high cost. Making public transport again the main mode of transport is important for many reasons. First, the UK's zero carbon emission by 2050 pledge requires to use more energy-efficient modes. More than 16% of the emissions in the UK are from private cars. Second, cars waste road space, they need almost eight times more space per passenger compared to busses. Excessive private car use is one of the biggest reasons for traffic congestion we experience every day. We need to find ways to move mode choice from private to public transport. One way of altering user behaviour from private to public transport could be frameworking mobility as a service (MaaS) and provide packages that could provide different options to users. MaaS is not a new concept and is in use of different forms all around the world. However, these systems either are just a design concept a platform that provides multiple options and unified payment method for any trip to its users or only allows subscription packages that allow users to access mass public transport modes. In this project, in addition to smart card data, I will be able to work with a subscription-based MaaS data that provides mass and personal public transport (e.g. bikesharing, carsharing, ride-hailing, shared ride-hailing, dial-a-ride) to its users together. Intelligent transportation systems (ITP) applications help us monitor and control public transport system. We also use the collected ITP data to analyse and improve those systems. However, the existing classical models are usually not capable of utilising the mass data produced by the ITP systems every day. We need to develop better methods to deal with high precision data. In this proposal, I aim to develop models that will improve public transport planning by using smart card and MaaS subscription data. In my approach, in addition to mass public transit lines, I want to consider personal public transport options in the development of public transport network design and (if time allows) frequency setting and timetabling problems. With the advancement in mobile technologies and trend towards sharing economy, we see more personal public transport modes in cities. They are encouraged by especially the big cities to provide alternative modes of transportation to their dwellers. We see more people use these transport modes every day. Considering all types of public transportation modes in designing transit route networks could provide better public transport plans for limited resources and eventually increase average welfare for the urban dwellers living in these cities.

It is increasingly evident that a net zero transition will be resource intensive. For example, per megawatt (MW) of installed capacity (electricity supply ~1000 homes), a single onshore wind turbine uses 3 tonnes (t) of copper (Cu), 0.75 t of manganese (Mn), 0.5 t of chromium (Cr) and nickel (Ni), 0.1 t of molybdenum (Mo) and smaller amounts of rare earth elements (REEs) (~15 kg). Solar photovoltaic (PV) devices have similar Cu requirements but offshore wind turbines use significantly more Cu (x2.5) and REEs (x10). Scaling up, ~140 Mt of critical metals will be utilised by renewable energy (wind/solar/geothermal) technologies and the energy storage devices required for a <1.5 degreeC climate change future. Thus there is growing concern about security of supply of critical elements. In 2022, the UK government published its first Critical Minerals Strategy and will review the stability and security of critical mineral supply chains by the end of 2023. There has been much less consideration of the challenges we now face in protecting our soils and waters and indeed human health. Extraction of mineral resources is not only water intensive in areas that are already water-stressed but it inevitably generates waste materials. Past/current practices have already produced >280 gigatonnes (Gt) - this equates to a cube that is 6 km high! These are often uncurtailed and dispersal by wind and water results in contamination spread and expansive exposure for proximal populations. The contaminated dusts and waters contain a wide range of potentially toxic elements (PTEs), e.g. arsenic (As), lead (Pb), nickel (Ni), boron (B), molybdenum (Mo) which naturally co-occur within the mined materials. Individually, there are well-documented impacts upon human health, e.g. As is known to cause various cancers, Pb is known to affect brain development especially in children, but the cumulative effective of exposures to complex PTE mixtures is unknown. The focus of this proposal is on copper (Cu) mining because (i) Cu is required across all low-carbon technologies; (ii) it is the gateway to co-occurring critical metals such as Mo, Re, Te, REEs; (iii) Cu mining wastes constitute almost half of all tailing wastes; (iv) these wastes contain the complex PTE mixtures that we need to study. Chile is by far the largest producer of Cu in the world and it also has more than 740 registered tailings areas, many of which are improperly managed and are impacting soil, water, food and human health, especially of indigenous communities. We therefore propose a new international partnership between the Sustainable Minerals Institute-International Centre of Excellence-Chile (SMI-ICE-Chile) and the University of Edinburgh (UoE) to bring together SMI-ICE-Chile's excellence in research, innovation and technological/capacity transfer in the mining industry of Chile and South America and Edinburgh's world-class research facilities and our complementary expertise. Taking advantage of SMI-ICE-Chile's active projects, we will use a novel, holistic and integrated approach to address a key gap in understanding regarding PTE mixtures that will underpin assessments for ecological and human health risk as well as future work on sustainable waste treatment and critical metal recovery. By jointly engaging with the International Institute for Environmental Studies (IIES), we will enhance the long-term sustainability of our partnership and open up potential avenues for wider international collaboration and funding. In particular, we aim to facilitate discussions across the UK-Chile-Canada-Australia nexus which will be paramount to securing an environmentally sustainable supply of critical minerals in the future. By building on our experience of delivering scientific progress that also has positive socio-economic impact, we will also ensure a culturally aware provision of a better quality of life for indigenous communities.

Drugs against infectious diseases have transformed human and animal health and saved millions of lives. Nevertheless, their widespread use and misuse has led to the emergence of antimicrobial resistance (AMR) that poses a potentially catastrophic threat to public health and animal husbandry. There a several routes by which a pathogen can become resistant to a drug. One of the principal routes, and a focus of this project, is by single point mutations in genomic regions that code for proteins and result in a change in the protein's sequence of amino acids. These types of mutations are called Single Nucleotide Polymorphisms (SNPs). Advances in genome sequencing means there are now large collections of sequences from a range of pathogens where SNPs have been identified and can be associated with drug resistance. This project aims to capitalise on this wealth of data, combined with the recent advances made to accurately model protein structures, to develop a new AI-based tool to predict the effect of SNPs that could lead to resistance and have yet to be observed. By modelling how pathogens mutate to avoid the effect of drugs, we can better predict how infections will respond to specific drugs and may be able to design drugs that have longer clinical use. As well as directly benefiting those working to develop the next generation of drugs, it also benefits those managing prescribing routines and in surveillance, identifying new emerging resistance that can be acted on before it becomes widespread within a population. The project brings together a group of international experts from the University of Queensland (Australia) and the London School of Hygiene & Tropical Medicine (LSHTM, UK) who have complementary expertise in AI, drug resistance and bacterial pathogen genomics. The project has several key objectives: Objective 1: Develop a Natural Language Processing (NLP)-based AI tool for predicting SNPs causing resistance trained on features derived from the large collections of pathogen genome data where mutations associated with drug resistance have been identified. Objective 2: Validate and apply the newly developed methodologies to specific pathogens including Salmonella Typhiand Klebsiella pneumoniae (WHO priority pathogens) that gives opportunity for real-world validation and the ability to give insights into resistance mechanisms. Objective 3: Knowledge Exchange of AI applied to AMR though two UK-led workshops. This will enhance the collaborative network, establish design criteria for the AI tool based on user needs, and provide a pathway to translating the tools into real-world use. In addition, exchanges of researchers between the UK and Australian groups will enhance capacity and capabilities of both teams. This project envisions an AI-powered solution to help pre-empt the impact of drug resistance mutations, addressing the urgent need to combat the growing threat of AMR. The validated new computational tools will help in developing better drugs and, in conjunction with complementary technologies, aid in deciding drug treatment regimens and in resistance surveillance. It will enable a UK-led international partnership that will place the groups involved at the forefront of research in this field.

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.

Transducers are devices that can convert electrical energy into mechanical energy and vice versa. They are widely used in non-destructive testing to generate acoustic signals in test materials and to detect changes in the acoustic signal as it travels enabling material properties to be determined. The application areas for transducers in non-destructive testing are diverse and range from locating cracks in metal structures to diagnosing disease in humans. Transducers are typically made from single crystals such as quartz or ceramics. Recently it has been shown that a much wider range of materials can be used in transducers if they are miniaturised down to a nanometre scale. In fact, it has been shown that electrical energy can be converted to mechanical energy in biological membranes. Further, strategies to greatly increase the size of this effect have also been identified. These findings are very exciting as they pave the way for development of tiny transducers that could be used in the human body without posing any risk of toxicity, thus having tremendous potential for application in medicine. The work proposed in this Fellowship is centred on the development of nano-sized transducers made from phospholipids, which are the main type of fat found in membrane of biological cells. A huge area of application for the nano-transducers proposed is in medical imaging which presents a number of challenges. In practice, the nano-transducers could be used to remotely probe tissue properties and used in an imaging system to aid the diagnosis of disease. There is also a growing need for new imaging systems capable of remotely studying cells and tissues in the body to support the development of emerging therapies that use human cells to treat currently incurable conditions, such as Parkinson's disease and spinal injury, as well as chronic conditions including diabetes and heart disease. The hope is that by introducing new healthy cells into the body they will help to restore the function of injured or diseased cells. To ensure these therapies have a positive effect it is important that the location and behaviour of introduced cells are tracked once in the body. This is a challenging problem which current technologies are struggling to address. The work proposed in this Fellowship will address the above challenges. The approach that will be taken is different from other workers particularly as it will involve the development of transducers made from organic material. A major part of the proposed work will be designing and fabricating the nano-transducers. The phospholipids the nano-transducers will be composed of will be formed into bubbles called liposomes. Due to the natural link between the electrical and mechanical properties of liposomes it will be possible to use them as tiny acoustic sources. Strategies to increase the size of the acoustic signal produced will be developed based on modification of the liposome composition, shape and size. Another part of this Fellowship will be the development of a suitable imaging system using the nano-transducers that can be used to produce diagnostic images of the body. Also by controllably decorating the liposomes with specific biological molecules the nano-transducers will be able to target certain cell types enabling them to act as beacons to locate cells in the body. The final part of the work will be centred on demonstrating the capability of the new imaging system using tissue phantoms that mimic the human body. In particular, the ability to detect tumours, electrical activity in the brain and track cells used in therapy will be investigated. Overall, the success of this work will deliver a new medical imaging modality that could be implemented readily within clinical pathways at the point of care. This would have a significant impact on healthcare and enable new therapies to become available for clinical use and thus contribute to the health and wealth of society.