To meet expected demand, the world will need to produce 50 percent more food in 2050 than it did in 2012. While similar growth rates have been achieved in the past, future growth faces the additional pressure of climate change and the need for reduced chemical inputs. Sustainably enhancing agricultural production is therefore a major challenge facing the sector. A valuable source of traits for disease resistance and abiotic stress tolerance resides in thousands of living wild crop relatives. Accessing these traits for plant breeding, however, is limited by "genetic drag", where low levels of genetic exchange (recombination) means that both desirable and undesirable "wild traits" are introduced and can be difficult to separate. Boosting recombination overcomes genetic drag allowing access to diverse germplasm, as well as increasing the efficiency of traditional breeding programs, helping generate the new combinations of traits required for crop improvement in fewer generations. Recombination can be increased in plants 8-fold by knocking out anti-recombinase genes. However, establishing multigene knockouts in every breeding program is not practical, approaches used to generate mutants may preclude cultivation in tightly (GMO) regulated environments and the mutations introduced can reduce fertility, so wild type alleles must be restored prior to cultivation. Transiently increasing recombination without modification of the recombination machinery itself would solve these problems. To achieve this goal, we will use high-throughput screening assays to identify small molecule inhibitors of key recombination suppressing proteins that can be used to transiently boost recombination in a wide variety of crop species. To identify inhibitors, we will design targeted compound libraries for screening based on molecules identified in large biomedical drug screens that inhibit human orthologs of our target proteins. In addition, virtual screening of large compound libraries will be used to identify further compounds of interest for testing. We will also identify and/or develop plant versions of peptides known to boost recombination in mammalian systems. Once identified, delivery of recombination boosting small-molecules will be optimised for use in crops. This will be initially be undertaken in Brassica and barley, covering a dicot crop closely related to the model plant Arabidopsis, and a key grain crop, both with well-developed cytological tools. Another route for crop development is to incorporate the traits and diversity of two genomes into a single individual - known as allopolyploidy. Allopolyploid plants are common in agriculture (e.g. wheat and cotton) as their fixed hybrid nature usually results in improved agricultural traits. Despite their potential, previous attempts to generate new allopolyploid crops have failed as they tend to have genomic instability and low fertility due to recombination between the two sub-genomes. Two interacting genes have recently been implicated in suppressing this inter-genomic recombination and we will assess the potential to use/modify these genes, and others in the same pathway, to engineer a stable meiosis in new allopolyploids. If successful we will use this approach to generate new genetically stable allopolyploid Brassica and pasture grasses. This multi-disciplinary project, draws on expertise of the Fellow and Project Partners in molecular plant science, phenomics, plant breeding, polyploidy, medicinal chemistry and biochemistry to modify recombination in plants for accelerated plant breeding, helping to develop the high nutrition, climate ready and disease resistant crops needed to meet future food needs. The final three years of the project will involve product development in collaboration with breeding companies to optimise delivery and effectiveness during plant breeding and establishment of a start-up company to commercialise the product(s) developed.

This research project will be based in the area of combinatorial optimisation, with a particular focus on algorithmic graph theory and heuristics. Problems within this field are known to have many real-world applications in areas such as transportation, logistics, timetabling, and manufacturing. Many of these problems are also known to be NP-hard, and therefore require the use of heuristic and approximate methods. This PhD project will focus on designing, implementing, and testing a range of algorithms in this problem area, focusing on specific problems that will be decided upon in the early stages of the studentship. In doing this, we will seek to deepen our understanding of the problem area and, where appropriate, make connections to other graph-theoretical problems and results. During this PhD, the student will research several methods for tackling combinatorial optimisation problems, including integer programming, heuristics, and metaheuristics. Such techniques will then be implemented for this problem. There will also be opportunities to learn how to interrogate online mapping and graphing APIs to collect and exploit real-world data. There will be a significant element of coding in these projects (most likely C++ and Python) and the student will become experienced in running large scale experiments and statistically analysing results. More generally, the student will become experienced in critical thinking, complex problem solving, and correct decision-making. They will develop the research skills needed to dig deeply into the literature in order to find credible and relevant information. All of these skills are highly transferrable inside and outside of academia, particularly in areas of analytics and data science. The proposed studentship involves a combination of both theoretical and experimental work. Theoretical results will be derived via a thorough review of the literature, mathematical thought, and supervisory discussions. Significant results will be documented through publication with the student named as first author, helping to develop their research portfolio. Upon completion, the desired aim is for the student to have achieved at least one journal publication in addition to their thesis. Opportunities to teach in tutorial sessions will also be provided. A compulsory taught element of the programme will also be provided by NATCOR, a series of week-long residential courses taught at different UK universities. These will be used to introduce the student to important research skills and methods and will help to advance and broaden their knowledge in the field. The student will also attend international conferences, where they will present their work to their peers. The student will also be encouraged to seek publications during their PhD. This will aid the improvement of their writing skills and allow them to gain experience in revising and defending work. From a mathematical and data science perspective, the ubiquitous nature of graphs and networks in the modern world, together with our desire to understand and learn from them, makes this a very important area of study. We expect this studentship to result in at least one paper to be published in a 4-star journal, plus additional output in conference proceedings. Seminars and conference presentations will also be given by the student as the research progresses

We are trying to develop new drugs that will improve tumour killing in currently used imuno- and chemotherapy. The complement system is the body’s first line of defence against disease, able to kill invading bacteria and foreign cells. Cancer cells have on their surface protecting proteins, called regulators, which allow them to ‘hide’ from complement attack and survive. The factors that enable cancer cells to make large amounts of these regulators are not known but it is clear that if tumours could be prevented from making regulators then complement would much more efficiently kill the tumour. We propose to identify the factors controlling production of complement regulators and develop ways of reducing their production in tumours. We also suggest developing a new strategy for design of drugs that specifically activate on tumour surface and prevent production of the protective regulators. As a consequence, tumours will be more efficiently killed by complement that activates in imuno- and chemotherapy. The strategies will first be developed in cancer cells in the test-tube, the potential drugs then tested for therapeutic effect on human tumours in mouse animal model. Though here modelled in neuroblastoma, the strategy may be of much broader relevance to tumour therapy.

This project aims to: (a) Evaluate the utility of social media communications for tension and cohesion monitoring within local communities, and (b) Evaluate the role of positive social media narratives in curtailing spikes in negative narratives in the aftermath of an event. The objectives of the project are: 1) To identify a series of events in Wales around which on and offline tension and cohesion monitoring can be deployed; 2) To use social media monitoring techniques to gather information on tension and cohesion around these events (recording both negative narratives, and the positive narratives that tend to occur in the aftermath of events); 3) To compare the data generated from social media with conventional terrestrial tension and cohesion monitoring outcomes; 4) To analyse the dynamics of positive social media narratives in the aftermath of an event, and the impact this has on type and duration of the spike in negative social media narratives 5) To interview members of the local community, police, local government and third sector organisations to gather perceptions of both on and offline tension and cohesion monitoring outcomes. 6) To develop a Community Tension and Cohesion Monitoring Dashboard for use by community cohesion teams and coordinators.

Security at airports now commonly involves full body scanners and new regulations in the UK will require all air-passengers to undergo a full body scan by 2022 as part of the standard security process before boarding an aircraft. Such scanners work by viewing the body at colours not visible to the human eye. These colours occur at so called millimetre wavelengths and in most cases light at this colour in generated in the same way as the optical light we see as humans - heat. Most clothing is transparent to light at millimetre wavelengths whereas many objects that could pose a security risk are not. The heat from our body is a natural source of millimetre light and objects hidden under clothing can block this light from view creating a shadow of the object. However, millimetre wave light is difficult to detect and requires special cameras. The technology in airports to date is not sensitive enough to measure the natural millimetre wave light produced by our body heat but instead illuminates each person with millimetre wave light and measures reflections. This is similar to using a flash on a camera when taking a photograph in a dark room. This process is slow and requires each person to be stationary while the image is taken. Each person takes around 15-20 seconds to be imaged in this way and due to the insensitivity of the system an additional manual search is often required. Moving to a requirement where 100% of passengers are screened in this manner, an increase in the time and cost of security protocols at airports are inevitable. Using technology originally developed for astronomy, we propose a solution to this problem. We have developed a millimetre wave camera based on superconducting detectors that has the capability of performing the required security imaging while a person simply walks past the camera. In most cases the person would be unaware of this system in the same way we have become unconscious to CCTV at airports. The key to this technology are ultra-sensitive millimetre wave detectors that do not require the "flash" used in current scanners and can work in video mode. The detectors gain their sensitivity by working at extremely low temperatures, in fact, only a fraction of a degree above absolute zero - the coldest temperature physically possible. Realising such a camera in a busy airport may seem impossible but modern technology makes reaching such temperatures routine. To prove this, in November 2018, our group took a generic version of our millimetre-wave camera to Cardiff airport where we conducted a number of successful trials imaging people in a typical airport environment. Our system was able to easily detect a mock gun concealed under a thick coat and was even proven in conjunction with artificial intelligence systems that could recognise and highlight this forbidden object. Such imaging naturally raises concerns regarding privacy and safety. In our system, the image of the person being screened shows up as a silhouette preserving modesty. Furthermore, with no requirement for illumination, our system is completely passive making it the same as taking a normal photograph or video of the person being screened. This project will address several issues preventing the commercial adoption of this new technology. We wish to adapt our generic camera to enable 24-hour automated operation as well as the ability to image a person from four viewpoints creating a compete security scan as a person walks past. We will also develop new detector arrays providing improved sensitivity to detecting potential concealed threats. We will also develop new electronics that will reduce the overall cost of our system while enhancing performance to meet the challenges of rapid screening in a modern airport. The overall aim is to produce a full body scanner that is, cheaper, faster, more convenient and overall safer than the technology currently used.