Tourism, recreation, fishing, marine aquaculture, and many other economic activities depend on the diverse marine ecosystems globally. However, a combination of factors such as global warming, ocean acidification, and increment of cyclones in recent years have led to the aggravating degradation of natural reefs, one of the most varied marine ecosystems on Earth. Artificial reefs (AR) are widely used for habitat restoration, ecological development, and coastline protection. Concrete is the most successful AR material, but it generates substantial CO2 emissions, has high contamination, and has low bio-receptivity. Botanical concrete developed by author during PhD study is based on the concept of a circular economy with 100% responsible use of waste materials and its carbon negative and non-toxic characteristics provide exciting potential in building the green infrastructure in ocean. This research aims to enhance the durability, bioreceptivity and versatility of wood-waste-based botanical concrete to create a green route for the design of the new generation of multifunctional eco-friendly AR for coastal protection and coral restoration. Based on nutrition, water quality and settlement substrate test in marine environment (lab-level) the raw materials are selected. Followed by formation design through advanced simulation, Computed Tomography scanning and experiments on durability and mechanical performance, and life cycle assessment, the prototype of AR will be tailored to achieve optimal density for easy installation, high resilience in storms, superior capability for coral larval settlement and biodiversity. The results will revolutionize the way in which ARs are made and boost the efficient use of recycled resources and alleviate climate change by moving into a clean circular blue economy. The project will contribute to the EU’s sustainable blue economy strategies, including decarbonization, circular economy, biodiversity, climate adaptation, and sustainable food.

About one-fifth of the world's greenhouse gas emissions come from agriculture. Much of this relates to livestock used for animal-based foods. Rather than arguing for increased efficiency, MidWay probes the concept of sufficiency to explore its potential for reducing human impacts on Earth's biosphere while preserving overall welfare, i.e., its potential for defining a 'middle way' between 'too little' and 'too much'. To do this, MidWay studies the cases of meat and milk in China. While meat was always a high-status product, milk was historically considered a 'barbarian' food, and most Chinese were intolerant to it. Both products were scarcely consumed in Chinese history but have boomed in popularity over the past 40 years. While often thought about as a change of consumer preferences, it has taken a concerted effort by the Chinese government and domestic and international actors to make both products integral to Chinese food practices. Seeing China as a strategic research site to ask questions about the supply and demand of animal foods, the MidWay project hypothesises that what has made meat and milk integral to Chinese food practices might also be 'otherwise', i.e., opening up a possibility for a future disembedding of meat and milk from food practices. Thus, using a constructivist inspired lens, MidWay makes use of practice theory and 'systems of provision' to study the normalisation of animal foods in China, particularly since 1978, with China's opening up. The ultimate objective is to probe the concept of sufficiency as a useful organising principle to achieve reduced consumption - highlighted through the sub-objectives of understanding how meat and milk have been rendered desirable in China. Perspectives that show how food is connected to social, technical and cultural variables, and the system that provides food, are lacking internationally and could lead to changes through facilitating a multifaceted policy response.

The goal of the TECTONIC project is to alleviate the challenging problem of hot-spots in 3D stacked chip-multiprocessors by employing a software-hardware based combined approach. With the stagnation in process technology scaling new emerging memory technologies are investigated. Promise of better scalability with reduced static leakage makes Non-volatile memories (NVM) as the potential candidates to replace conventional SRAM. However, many of the proposed NVM technologies are sensitive to heat, that raised up the issue of reliability. Considering heat dissipation as an exclusive issue of hardware will not be the appropriate approach towards finding out the solutions, as running-application has direct impacts on on-chip thermal imbalance. Hence, TECTONIC will manage the on-chip temperature and eliminate hot-spots by leveraging application specific knowledge extracted at compile time in combination with new hardware mechanisms for distributing computational work and memory accesses for even heat distribution while maintaining high performance.

Recent severe heatwaves and prolonged drought negatively affect agricultural crop fitness and biomass, threatening global food security. Therefore, there is an urgent need to enhance crop resilience against environmental stress to reduce crop loss. The cell wall is of key interest here due to its role as the primary barrier against environmental stress. However, improving crop tolerance via cell wall manipulation remains challenging due to plasticity, which determines the wall's ability to alter its shape, composition, and viscoelasticity (stiffness and viscosity). Plasticity seems to be modulated by the cell wall integrity (CWI) maintenance mechanism. A mechanism that continuously monitors the functional integrity of cell walls by utilizing a wide range of CWI sensors to sense damages in the cell wall and initiate wall remodeling. Any impairment in the CWI triggers adaptive responses, including the production of phytohormones. Abscisic acid (ABA) is one of the key phytohormones that regulate plant adaptive responses against abiotic stresses. Although the potential of the CWI maintenance mechanism modulating cell wall plasticity via ABA signaling has been proposed, the underlying mechanism remains largely unexplored. Therefore, investigating interactions between these processes may lead to the development of novel strategies to improve plant tolerance against abiotic stress. In this project, I will investigate the relationship between changes in ABA and cell wall viscoelasticity controlled by the CWI maintenance mechanism. I will also identify and characterize novel components of the CWI maintenance mechanism responsible for the induction of ABA production. Furthermore, the knowledge produced here will facilitate the identification of corresponding orthologs in commercial crops that can be used to develop strategies to improve crop performance.

The aim of this project is to develop efficient real-time optimal control (RTOC) for the carbon dioxide (CO2) heat pump as a part of a building energy supply system and validate its reliability experimentally. This is necessary to increase the system efficiency. For a high system efficiency with CO2 heat pumps for heating purpose, a low water return temperature from building heating systems is crucially important. However, this is still difficult to achieve due to well-established heating solutions and control strategies that are not suitable for CO2 heat pumps. CO2 is considered as one natural refrigerant, which has the merit of nonflammability, non-toxicity, and low price when compared with traditional refrigerants. Current well-functioning control methods are developed for heat pumps based on HFCs. Current RTOCs have the disadvantage of large computational load, which makes them difficult to operate with real building energy systems. Furthermore, experimental validations for the developed RTOC cannot be conducted due to lack of advanced experimental conditions. A reliable and experimental-validated RTOC for CO2 heat pump systems is urgently needed. This project will be developed by combining my scientific expertise on RTOCs with advanced experimental conditions with the CO2 heat pump for residential heating use at the host laboratory. Model-based predictive control (MPC) will be used to develop the RTOC. Machine learning methods will be used to develop the non-linear system model. Further, the RTOC with multiplexed optimization strategy (MOS) will be implemented in simulation environment. After the reliability of the developed RTOC in simulation environment is validated, the RTOC will be tested in experimental conditions. Finally, the reliability of the developed RTOC will be validated in experimental conditions. This project will bring new knowledge and theories to develop the RTOC for CO2 heat pump systems and will help me become an independent researcher.