The Phoenix Takes Flight (PTF) research study will explore how community-based organisations delivering social prescribing initiatives can expand and grow within integrated care systems. PTF will work with an established social prescribing programme Phoenix Rising (supported by the Thriving Communities Fund), where existing third sector partners (The Gathering Fields, Green Close, Lancashire Wildlife Trust and Mandala Preston) are currently delivering an extensive programme of art, nature and movement activities in partnership with Lancashire and South Cumbria NHS Foundation Trust's Recovery College. The study will draw upon the learning of the partners who collectively have over 55 years' experience of delivery in this field and the research findings produced by Lancaster University in September 2020 https://greenclose.org/wp-content/uploads/2021/01/Phoenix_Project_Evaluation.pdf and also due in March 2022. PTF will draw upon a growing network of community partners delivering social prescribing in the area and explore the benefits and challenges of delivering community-based health support for a wide range of participants, examining how it can be embedded into integrated care systems, and how it can grow and flourish to enable access for those populations most in need of healthcare support. The study will use the existing network which the Phoenix and Phoenix Rising projects have grown to ensure a robust cross-section of health care providers, GP's, Social Prescribing link workers, patients and third sector organisations are involved from the study's inception through to its completion. PTF will bring these groups together to discuss the challenges and benefits of this work, to reflectively plan the development of the work and ultimately co-produce ideas and solutions that will enable the existing programme to become more scalable in terms of service offers and more likely to be sustainable to those in need of accessing such services - thereby ultimately to 'taking flight'. Co-production, patient voice and an open and inclusive approach to our research - informed by the knowledge of our partners - will ensure that we build an inclusive, solution-focussed outcome that will enable a collective approach to expanding social prescribing offers embedded within integrated care systems. It is our aim that the solutions provided through this research will help to tackle some of the many health inequalities existing in the North West of England.

Imagine a future where autonomous systems are widely available to improve our lives. In this future, autonomous robots unobtrusively maintain the infrastructure of our cities, and support people in living fulfilled independent lives. In this future, autonomous software reliably diagnoses disease at early stages, and dependably manages our road traffic to maximise flow and minimise environmental impact. Before this vision becomes reality, several major limitations of current autonomous systems need to be addressed. Key among these limitations is their reduced resilience: today's autonomous systems cannot avoid, withstand, recover from, adapt, and evolve to handle the uncertainty, change, faults, failure, adversity, and other disruptions present in such applications. Recent and forthcoming technological advances will provide autonomous systems with many of the sensors, actuators and other functional building blocks required to achieve the desired resilience levels, but this is not enough. To be resilient and trustworthy in these important applications, future autonomous systems will also need to use these building blocks effectively, so that they achieve complex technical requirements without violating our social, legal, ethical, empathy and cultural (SLEEC) rules and norms. Additionally, they will need to provide us with compelling evidence that the decisions and actions supporting their resilience satisfy both technical and SLEEC-compliance goals. To address these challenging needs, our project will develop a comprehensive toolbox of mathematically based notations and models, SLEEC-compliant resilience-enhancing methods, and systematic approaches for developing, deploying, optimising, and assuring highly resilient autonomous systems and systems of systems. To this end, we will capture the multidisciplinary nature of the social and technical aspects of the environment in which autonomous systems operate - and of the systems themselves - via mathematical models. For that, we have a team of Computer Scientists, Engineers, Psychologists, Philosophers, Lawyers, and Mathematicians, with an extensive track record of delivering research in all areas of the project. Working with such a mathematical model, autonomous systems will determine which resilience- enhancing actions are feasible, meet technical requirements, and are compliant with the relevant SLEEC rules and norms. Like humans, our autonomous systems will be able to reduce uncertainty, and to predict, detect and respond to change, faults, failures and adversity, proactively and efficiently. Like humans, if needed, our autonomous systems will share knowledge and services with humans and other autonomous agents. Like humans, if needed, our autonomous systems will cooperate with one another and with humans, and will proactively seek assistance from experts. Our work will deliver a step change in developing resilient autonomous systems and systems of systems. Developers will have notations and guidance to specify the socio-technical norms and rules applicable to the operational context of their autonomous systems, and techniques to design resilient autonomous systems that are trustworthy and compliant with these norms and rules. Additionally, developers will have guidance to build autonomous systems that can tolerate disruption, making the system usable in a larger set of circumstances. Finally, they will have techniques to develop resilient autonomous systems that can share information and services with peer systems and humans, and methods for providing evidence of the resilience of their systems. In such a context, autonomous systems and systems of systems will be highly resilient and trustworthy.