Malware (short for "malicious software") refers to any software that perform malicious activities, such as stealing information (e.g., spyware) and damaging systems (e.g., ransomware). Malware authors constantly update their attack strategies to evade detection of antivirus systems, and automatically generate multiple variants of the same malware that are harder to recognize than the original. Traditional malware detection methods relying on manually defined patterns (e.g., sequences of bytes) are time consuming and error prone. Hence, academic and industry researchers have started exploring how Machine Learning (ML) can help in detecting new, unseen malware types. In this context, explaining ML decisions is fundamental for security analysts to verify correctness of a certain decision, and develop patches and remediations faster. However, it has been shown that attackers can induce arbitrary, wrong explanations in ML systems; this is achieved by carefully modifying a few bytes of their malware. This project, XAdv ("X" for explanation, and "Adv" for adversarial robustness), aims to design "robust explanations" for malware detection, i.e., explanations of model decisions which are easy to understand and visualize for security analysts (to support faster verification of maliciousness, and development of patches), and which are trustworthy and reliable even in presence of malware evolution over time and evasive malware authors. Moreover, this project will explore how robust explanations can be used to automatically adapt ML-based malware detection models to new threats over time, as well as to integrate domain knowledge from security analysts' feedback from robust explanations to improve detection accuracy.

Nuclear power is arguably the only option for large-scale baseload electricity generation that is compatible with the UK Government's commitment to an 80% reduction in greenhouse gas emissions by 2050. The safe operation of current and future generations of nuclear reactors requires the development and refinement of materials to be used in the construction of reactors and in materials (glass and glass-ceramic wasteforms) to be used for the long-term safe disposal of radioactive wastes. The inevitable irradiation of such materials with energetic particles such as neutrons and alpha particles can have extremely deleterious effects on their structural strength and even their physical dimensions. Ballistic effects cause atoms to be knocked off their normal positions creating vacant sites (vacancies) and displaced atoms (interstitials). Nuclear reactions induced by neutron irradiation can create alpha particles (which are just helium nuclei) causing a build-up of helium gas in these materials. Helium has very little solubility in most materials and will generally combine with vacancies (or accumulate in other regions of lower than average electron-density) to form bubbles. These can have very significant unwanted effects on the properties of the materials by, for instance, building up at the boundaries between grains in polycrystalline materials and making them much more brittle and likely to fracture. Bubbles will also result in highly undesirable changes to the physical dimensions of components. The high temperatures at which reactors operate, and to which wasteforms will be subjected for the first 500 years-or-so of storage, can greatly exacerbate these problems, particularly in the reactor materials by enabling the vacancies, interstitials and helium atoms to combine in different ways and form extended defects such as voids, dislocations and stacking faults. This project aims to explore systematically the effects that varying the amount of displacement damage, the helium concentration and the temperature has on the damage that develops in a range of structural materials and wasteforms. Different combinations of these parameters pertain to different types of material (both structural and wasteforms), different reactors and even different locations within a reactor. In addition, aspects of the waste glasses, such as alkali content and the presence of glass ceramic interfaces will also be varied in order to determine their role in the development of bubbles and other defects. The project exploits the unique attributes of the MIAMI facility (constructed with EPSRC funding) that permit the ion irradiation of thin foils of materials in-situ within a transmission electron microscope. By varying the ion energy, the ratio of injected helium to the amount of displacement damage can be varied over the range of values relevant to reactor and wasteform materials without the necessity of using two separate ion beams. The ability to irradiate at a range of temperatures from -150 to +1000 degrees Celsius means the that the entire relevant parameter space (helium content, damage and temperature) can be explored. In this way, transmission electron microscopy (and also electron energy-loss spectroscopy for the nuclear glasses) will be used to build up a comprehensive dataset of the form and structure of defects (defect morphologies) resulting from the various combinations of these parameters. The main aim is then to develop a phenomenological picture of the processes occurring. For the structural materials, the dataset will be calibrated and validated by comparisons with neutron-irradiated materials which will give the dataset greater power to predict defect morphologies likely to result under reactor conditions. Finally, through collaboration with computer modellers, we will seek to obtain a fundamental understanding of the underlying physical processes which drive the behaviour of these materials under irradiation.

The VisitorBox project will produce a toolkit that combines physical ideation cards with a mobile app and web-based idea repository to enable heritage organisations to rapidly generate and share ideas for new visitor experiences. This Follow-on Fund project addresses the 'Digital Transformations in the Arts and Humanities' theme and will forge impact through commercialization and knowledge exchange. It builds on research undertaken by the project team as well as research and impact collaborations with our external partners. These partners are chosen from different segments of the regional and national heritage economy; they represent curators and collection managers with differing training backgrounds, all keen to harness digital technologies to enhance access to and engagement with their collection assets. VisitorBox presents an unanticipated pathway to impact that has emerged from the AHRC international network Data - Asset - Method (DAM network: AH/J006963/1). This network identified the barriers that prevent our stakeholders operating in the culture economy from accessing digital technologies. The main barrier is the stakeholders' lack of an overview of available technologies, and their low confidence and expertise to experiment with such technologies, especially at the early stages of design and prototyping. The network findings align in particular with our experience of collaborating with partners in the heritage sector, including in the context of three EU-funded projects. We want to bring to bear our knowledge and the expertise gained through the network to overcome the barriers of harnessing digital technologies in this specific sector. Our aim is to respond to one explicit demand of our heritage partners in the domain of visitor engagement, which is their key means of intellectual and commercial exploitation: to have access to their own design and prototyping exploration tools and so scale up the impact of our research and consultancy. Researchers and partners (including the Nottingham Castle and Galleries, the National Videogame Arcade, the D.H. Lawrence Birthplace Museum, Nottingham's UNESCO City of Literature, and the National Trust) will work together as co-producers of VisitorBox. The tool-set will consist of a set of ideation cards. These physical playing cards represent individual design concepts, technologies, user types, and visiting activities; the cards encapsulate comprehensive engagement design and humanities thinking, reflected in the rules for playing them. The cards will allow players (e.g. curators) to produce new ideas quickly but without compromising on methodological depth. Alongside the card deck VisitorBox will include a mobile app, allowing players to scan individual cards or card combinations to capture ideas and curatorial trajectories in digital form. Players will be able to upload these digital ideas to an interactive website, the VisitorBox repository, and share them with their colleagues, or with trusted partners. Users will also be able to gain access to a rich set of digital resources that will support project refinement and execution. The project will evidence the value of the toolkit through co-production with our partners in six design workshops and additional piloting with twenty national and international heritage organisations. Feedback from these activities will inform the development of a sustainable business model for VisitorBox. We will promote VisitorBox along with our business plan at high-profile sectoral events in Europe and the US, and within the teaching programme of a leading US HE organisation. The project will be led by an early-career researcher - Dr Ben Bedwell - to establish him as a research leader at the interface of Computer Science and the Humanities. The project team has a strong track record of developing challenge-driven technologies for arts and humanities practitioners; it involves the lead investigators of the DAM network, Lorenz and Benford.

Indoor scenario has emerged as one of the most congested, contested, and competitive wireless environments. With the need of resilient Internet of Everything (IoE) and Fourth Industrial Revolution (Industry 4.0) infrastructures, we expect to connect thousands of devices within a confined indoor environment, interfering to each other and contending for limited electromagnetic spectrum. While the growing demand for data traffic meets confined space and congested spectrum, it creates a clear and present technical challenge, and opportunities for innovation. The research objective of this proposal is to investigate new fundamental communication models and schemes, which dynamically program and customize indoor wireless propagation environments for enhanced wireless communication. This objective is attained by integrating the physics of wave-chaotic dynamics, the mathematics of random matrix theory, the engineering of reconfigurable electromagnetic surfaces, and the computing power of adiabatic quantum annealer. The proposed work consists of three components: (1) rigorous mathematical model for the statistical analysis of wave physics in complex confined indoor environment; (2) the configuration and control of wave chaos using reconfigurable intelligent surfaces; (3) Quantum-enabled, ultra-fast large-scale optimization of reconfigurable intelligent surface configuration.

Mesoscale Convective Systems (MCSs) are among the most powerful storms in the world, and in many places are the dominant cause of hazards such as high winds, lightning, flash flooding and tornadoes. Across the tropics, MCSs account for 80% of extreme rainfall days. They result from thunderstorms that organize into a single large complex hundreds of km wide, which travel across the land for hours, in some cases days, causing extraordinary downpours along their path. They are particularly prevalent in certain "hotspot" regions including Northern Argentina and India, West and Central Africa, and the US Great Plains, where a combination of warm, moist air and favourable winds support their development. In these hotspot regions, an understanding of how MCSs will change as the world warms is urgently needed in order to build climate-resilient homes, roads, bridges and dams. Conventional climate models lack sufficient spatial resolution to realistically simulate these storms. There has however been a revolution in high-resolution climate models over the past 5 years, enabled by increasing computer power. New "Convection Permitting Models" (CPMs) can represent MCSs and are starting to deliver improved predictions and better understanding of how MCSs respond to their environment. We know that spatial patterns in vegetation and soil humidity affect air temperature, moisture and wind flows, and that these changes can affect where (or indeed whether) a powerful MCS develops. For example, contrasts between tropical forests and deserts control surface temperature differences across the continents, creating MCS hotspot regions through favourable wind conditions. Those surface temperature differences are already increasing due to global warming, and have been implicated in a tripling of the most intense West African MCSs over just 35 years, contributing to a dramatic rise in flash flooding there. We also know that the land surface affects individual MCS tracks. Evidence, again from West Africa, shows that MCSs are steered away from the saturated soils created by previous storms. This feedback makes predicting the track of a hazardous storm easier, though we do not know how strong the effect is in other regions of the world. This project will focus on how MCSs are affected by patterns of soil moisture and vegetation, through analysis of both satellite observations and CPMs. The work will discover how strong land effects are across the different hotspots of the world, and what processes are key to determining that strength. Experiments with a CPM will identify the surface patch sizes, ranging from 10s to many 100s km, which have the biggest impact on MCSs. Satellite data will be analysed to detect how MCS intensity and lifetime have been affected in regions with recent land use change (e.g. irrigation, deforestation, urbanisation). The work will explore how, as the world warms, and contrasts between wet and dry areas get stronger, the feedback between soil moisture patchiness and MCSs is changing. This matters because the feedback may amplify trends towards more extreme rain and longer gaps between storms. Identified observation-based relationships between the land and MCSs will also be used to scrutinise theoretical understanding and to evaluate the fast-emerging next generation of CPMs. This will include analysis of the world's first year-long global simulation from a land-atmosphere-ocean CPM able to capture the kilometre-scale motions within MCSs. Overall, the project will make substantial advances in understanding of how the land affects this powerful type of storm, with observations and model studies from across the world. The results will provide underpinning knowledge to improve prediction of storm hazards, informing decision making across weather to climate change time-scales.