Most of our responses to the COVID-19 pandemic are focused on the immediate needs of affected countries and populations and their swift economic recovery. In developing countries, where the effects of climate change are now made even worse by COVID-19, there is a lot of appetite for making this recovery sustainable and equitable. Specifically, we need to understand how COVID-19 has affected local people's ability to withstand droughts, floods and sea-level rise and the prospects for adapting to and mitigating climate change in these countries. However, the data and knowledge on how to achieve this are lacking. This project will invite local community members as well as practitioners from government, development, private sector and community-based organizations in Rwanda and Malawi - two countries simultaneously affected by the pandemic and climate change - to participate in interviews, focus groups and surveys on this topic. Participants from local communities will also be asked to produce video stories of their experiences of COVID-19 and climate change in order to put a human face on both crises and ensure local voices are heard at the highest levels of government in both countries. The findings of this research will inform the work of the Malawian and Rwandan ministries responsible for health, climate change and environment (key project partners). This will be achieved through a range of products and events, including reports, journal articles, a documentary, an interactive website and case-study leaflets. We will hold two simultaneous end-of-project workshops with online participation from the UK, during which all stakeholders will be able to discuss and exchange their experiences and inform policy development. The project's ultimate aim is to ensure that the way these countries plan and carry out their recovery after COVID-19 is environmentally sustainable and socially equitable, so that it does not harm the climate or the most vulnerable people.

The total primary energy supply in Sri Lanka has increased substantially and the electricity demand growth is also recorded as 6% per annum. These growths during the last decade has created a considerable local impact in terms of energy supply security, air pollution, environmental pollution, water scarcity, damage to national heritage and having a direct impact on human life in particular. As a result of three decade-long internal conflict, the lack of development in infrastructure facilities within the Northern Province and the Eastern Province of Sri Lanka have created enormous gap compare to the Southern part of the country. This has directly affected to skill labour availability in the conflict affected areas and created a living standard deference. Aligning Sri Lanka with Goal 7 of the Sustainable Development Goals (SDGs) of the UN, it is expected to reduce country’s dependence on fossil fuels to below 50% of the primary energy supply by 2030. The skill shortage is act as a barrier for archiving expected sustainable goals. As Sri Lanka have enormous potential to generate the required energy supply form renewable energy resources, it is highly critical to identify and address the existing skill level gaps with regards to renewable energy generation. As the outcome of this project five training centres will be developed across the country ( Northern, Eastern, Southern, Western and Central Provinces of Sri Lanka) and eLearning materials are expected to developed for provide training to three main categorise groups, which has listed in its Report on “Skill and Occupational Needs of Renewable Energy 2011” various kinds of skill requirements for different renewable energy sector. It is expected that THREE -LANKA project will contribute for developing skills levels in all the categorise groups in Sri Lanka starting from students, graduate engineers to project managers in the field of Renewable technologies.

SUPER will train 15 doctoral Fellows as transdisciplinary leaders to develop and promote sustainable, equitable physical activity and sports that prioritise both human and planetary health in the face of world finite resources and a changing climate. The network will bring together sports and physical activity industries, organisations and practitioners with leading researchers and experts across fields such as sports & behaviour sciences, human health, education, social science, planetary health, circular economy, environmental sciences and sustainable development to conduct empirical research and cascading skill-building with the following objectives: Objective 1: Establish the theoretical and evidence base as well as a research roadmap on the impact of sports and physical activity on planetary health, resources and climate and, conversely, the impact of climate change on sports and physical activity. This, to support policy, practice and novel solutions. Objective 2: Develop novel solutions for sports and physical activity policy, infrastructures, equipment, practices and promotion that bring co-benefits by simultaneously increasing population resilience to climate change equitably and lowering the impact on the planet and planetary limits. Objective 3: Test and demonstrate these novel solutions in key sectors through living labs: Health Care, Professional and Amateur Sports, School/Education, Urban Design, Workplace/Occupational Health. Objective 4: Provide evidence-based guidance and scientific support to future generations and all stakeholders who promote, manage, or use sports and physical activity: industry, practitioners, organisations, policymakers, funders, and the public, on making sports and physical activity sustainable and equitable. Objective 5: Build capacity for future generations and among the sports and physical activity industry, organisations and practitioners for developing innovative, sustainable and circular solutions and practiceTBD

D.Rad grounds radicalisation in perceptions of injustice which lead to grievance, alienation and polarisation. Based on a rigorous, cross-national survey of the drivers (injustice, grievance, alienation, polarisation) that can generate violent extremism, it uses innovative machine learning, discourse analysis and social psychology approaches to test projects, tools and dissemination strategies, emphasising the experiences of young people and socially excluded communities, and offering policy and practical recommendations. It will meet challenges posed for radicalisation research by developing online and offline interventions to promote agency, resolution and resilience. D.Rad will benefit from an exceptional breadth of backgrounds. The project spans national contexts including the UK, France, Italy, Germany, Poland, Hungary, Finland, Slovenia, Bosnia, Serbia, Kosovo, Israel, Iraq, Jordan, Turkey, Georgia, Austria, and several minority nationalisms. It bridges academic disciplines ranging from political science and cultural studies to social psychology and artificial intelligence. This will involve three core objectives, supplemented by secondary aims: 1. Detect Trends: D.Rad aims to identify the actors, networks, and wider social contexts driving radicalisation, especially in the emerging context of everyday polarisation over mundane issue in micro-spatial environments, in order to base interventions in evidence grounded in contemporary data and methodologies. 2. Resolve Drivers: D.Rad aims to understand the online and offline drivers that turn grievance, alienation and polarisation into radicalisation, so that policies can more effectively target underlying problems of social exclusion. 3. Re-integration and Inclusion: D.Rad aims to understand how individuals affected by grievance, alienation and polarisation can be re-integrated into the established polity or social groups, without compromising personal or collective liberties.

Before high voltage plant fails there is generally a period when degradation of the insulation system occurs, this may be a number of years. The key to improving the assessment of the equipment condition and life expectancy lies in identifying and characterising the stages of degradation. It is widely recognised that the degradation phase, irrespective of the cause, results in small sparks being generated at the site(s) of degradation. These electric sparks are generally referred to as partial discharges(PD). The characteristics of the sparks are influenced by the materials and stresses at the fault site. Improvement in their detection and characterisation will provide information on the location, nature, form and extent of degradation.The current detection process is severely compromised in practical on-site testing. These PD pulses are extremely small and hence, irrespective of the particular strategy being applied to detect them(electrical or acoustic), detection equipment must be very sensitive. In the field, this makes it prone to the influence or external interference or 'noise' from the surrounding environment and electrical/mechanical infrastructure. At best, this results in data corruption and compromises the efficiency of the condition assessment. At worst, it stops the technique from being of any use as the 'noise' signal exceeds the level of partial discharge activity.To solve the problems associated with noise a number of methods have been tried such as: screening and filtering, the application of analogue band-pass filtering, matched filters, polarity discrimination circuitry, time-windowed methods and digital filters. Each of these is, however, applicable to only certain types of noiseIn a recent study the author compared the matched filter, the traditional filter and the Discrete Wavelet Transform (DWT) in PD measurement denoising and has proven DWT provides the best solution in practical measurement when strong noise is in presence. Furthermore, DWT is the only method which allows reconstruction of the PD pulse.Having evolved from the Fourier Transform(FT), WT is particularly designed to analyse transient, irregular and non-periodic signals. Ideally, if a wavelet can be selected to match the PD pulse shape, the PD pulse could be extracted from any strong noise signals. Though the WT generates more information than the FT, it is inherently more complex than the FT and involves procedures dependent on the shape of the signals to be extracted from noisy data, the record length and the sampling rate. Dr. Zhou in the Insulation Diagnostics Group at the GCU was the first to study the optimal selection of the most appropriate wavelets, the optimal number of levels and level-dependent thresholding algorithm for automatic PD pulse extraction from electrically noisy environments using DWT. This innovative work has been proved to be effective in a number of measurement platforms. However, the application of DWT still requires significant experience at the moment when pulses of different shapes exist. The proposed research is to build on the experience and success already gained at GCU and to develop a methodology which allows the DWT to be applied to various PD measurement systems irrespective of their mechanism and bandwidth for PD data denoising and PD pulse reconstruction and classification.The outcome of the proposed research will be algorithms which can identify all types of transient pulses contained in data under analysis and present them separately in time domain. This would allow the identification and classification of various PD activities from PD measurements and production of phi-q-n diagrams which, in conjunction with pulse shapes, provides significantly improved means for plant diagnosis.