Digital games have extraordinary economic, social and cultural impact. The industry is one of the fastest-growing in the world, larger than film or music, with revenues expected to increase from $138 billion in 2018 to $180 billion by 2021. 2.6 billion people worldwide play digital games (21 million in the UK), with an average age of 35 and equal numbers of females and males. The Wellcome Trust-sponsored game Senua's Sacrifice, made in the UK, won 5 Baftas for its interactive and educational portrayal of psychosis. The UK games industry is a global leader - UK game sales are valued at £4.3bn with 12,000 people directly employed. The games industry is innovative and hungry for innovation - recent research breakthroughs in Artificial Intelligence (AI) and Machine Learning (ML) have arisen through games research undertaken at Google DeepMind in the UK. Rolls Royce makes better jet engines using 3D technology pioneered in games. Games are leading the "data and AI revolution" of HM Government's 2017 Industrial Strategy. Games have become a massive lever for social good through applied games for health, education, and science. The mobile game Pokémon Go added 144 billion steps to physical activity in the US alone. The Alzheimer's Research-funded Sea Hero Quest game collected data equivalent to 9,400 years of dementia lab data within 6 months. The EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence (IGGI) first received funding in 2014, and has since been a huge success: raising the level of research innovation in games, with the highest-possible ratings in our EPSRC mid-term review. The next phase of IGGI will inject 60+ PhD-qualified research leaders and state of the art research advances into the UK games industry. The two core themes of IGGI are: (1) Intelligent Games: increasing the flow of research into games. IGGI PhD research in topics such as AI, data science, and design will empower the UK games industry to create more innovative and entertaining games. IGGI research has already enhanced the experience for millions of game players. IGGI will create engaging AI agents that are enjoyable to interact with, tackling fundamental challenges for the future of work and society that go beyond games. IGGI will spearhead new AI techniques that augment human creativity by automatically 'filling in the details' of human sketches. (2) Game Intelligence: increasing the use of intelligence from games to achieve scientific and social goals. Every action in a digital game can be logged, creating huge data sets for behavioural science. For example, current IGGI students have assessed traits such as IQ, agreeableness, or attention from large game datasets. IGGI students will investigate more intelligent, adaptive games for education and to improve mental health. IGGI will maximize the enormous opportunity for scientific and social impact from games by laying the research groundwork for further data-driven applied games for health, science, and education. IGGI will massively advance these research themes, and train 60+ PhD students to be future research leaders. To accomplish this, our updated training programme and 60+ research supervisors will provide students with rigorous training and hands-on experience in AI, programming, game design, research methods, and data science, with end user and industry engagement from day one. Recruiting and empowering a diverse student cohort to promote equality, diversity, and inclusion through games, IGGI will drive positive culture change in industry and academia. Students will work with leading UK experts to co-create and disseminate standards for responsible games innovation. Directly working with the UK games industry through placements, workshops, game development challenges, and an annual conference, they will advance research knowledge and translate it into social, cultural and economic impact.

Passive non-neuronal brain cells called astrocytes have emerged as a critical yet grossly understudied part of brain machinery. Atrocytes take up released neurotransmitters, maintain ionic homeostasis of the extracellular space, and generate a variety of molecular signlas that regulate neural circuit activity. However, the emerging difference between animal and human astroglia in their morphology and physiology threatens the harm-benefit ratio of animal preparations in this important field of neuroscience and neurology. In this respect, realistic computational models of astroglia and astroglia-neuronal networks could provide hypothesis testing, mechanistic physiological insights, and an inter-species knowledge transfer that are unattainable in animal experiments. Exploring such models ought to minimise animal experimentation with no loss of knowledge, yet the methodology to create the corresponding modelling environment is only beginning to emerge. Thus, the present project aims to combine an experimental methodological approach, on the one hand, and open-access computer-simulation platforms, on the other, that would shift the weight of knowledge-based glial research from animals to human tissue preparations and realistic computational models. This will be achieved through the three objectives: (i) to establish working experimental protocols for up-to-date studies of human astroglia in organised brain tissue, making them a commonly accessible, viable alternative to animal brain tissue research strategies, (ii) to create an open-access computational platform that enables exploratory investigation of realistic biophysical models of astroglia, thus reducing similarly aimed experimental trials in animals, and (iii) to generate an experimental data library adaptable for the functional comparison of animal and human astroglia, thus providing a guidance on potentially implausible extrapolation of animal data to human brain astroglia.

Cardiovascular diseases, associated with stroke, heart failure, and end-stage renal disease, caused more than 30% of deaths worldwide. As of 2020, 19 million estimated deaths globally are attributed to cardiovascular diseases, which is an increase of 18.7% to that of 2010. Atherosclerosis is the common pathology that leads to this considerable amount of deaths. To treat atherosclerosis, the most common treatment is stenting, where its clinical efficacy resulted into millions of it implanted every year. A problem in this treatment however is the occurrence of restenosis, or the re-narrowing of the blood vessel due to adverse reaction of the body to the stent material. Methods to diagnose this condition however are invasive, have limited clinical outcomes and are done only when the patient is already feeling the symptoms. In addition, some of the implantable devices that diagnose this condition have limited battery-life and require even more surgeries for replacements. By integrating sensors with the stents (smart stents) early symptoms of restenosis can be detected by monitoring the blood fluid dynamics in the implanted area. Our study aims to create a smart stent making use of a new type of stretchable piezoelectric active sensor and radio frequency identification (RFID) technology in combination with artificial intelligence (AI)-based data processing and analytics.