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University of Liverpool

University of Liverpool

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2,941 Projects, page 1 of 589
  • Funder: European Commission Project Code: 101209607
    Funder Contribution: 276,188 EUR

    Integration with wave energy convertors (WECs) has been a promising solution to lowering the levelized cost of energy of floating offshore wind turbines (FOWTs) by sharing the platform and mooring systems. The synergy effects of wind-wave integrated floating energy systems (IFES) can be achieved to improve the power performance and motion stability, which requires a proper combination of FOWT and WECs. This project aims to construct an optimization design framework for cost-effective, high-efficiency and stabilized wind-wave IFES based on artificial intelligence (AI) techniques by: i) developing a fully coupled modelling methodology for considering the aero-hydro-servo-elastic effects; ii) developing a real-time hybrid testing method overcoming the conflicts between different scaling laws to validate the numerical model; iii) understanding the interaction mechanism between WECs and FOWT under different environmental loads and operating states; iv) developing a novel machine learning model to efficiently predict dynamic responses of IFES by introducing signal processing algorithms into convolutional neural network and bidirectional long-short term memory model with attention mechanism; v) determining Pareto solution sets using improved non-dominated sorting genetic algorithm. The outcome of this research will help to facilitate the development of offshore wind and wave energy resources in deep sea areas. This project will benefit offshore engineering industry by providing a novel machine learning model for dynamic response prediction based on limited wind and wave data input. The research will also promote the multi-disciplinary integration by covering a wide range knowledge areas including aerodynamics, intelligent control, hydrodynamics, structural dynamics, and computer science. The interdisciplinary knowledge and innovative research skills of the postdoctoral fellowship will be significantly improved after carrying out this challenging and meaningful project.

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  • Funder: European Commission Project Code: 276909
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  • Funder: UK Research and Innovation Project Code: G0601549
    Funder Contribution: 316,927 GBP

    My research is aimed at understanding the development of the nervous system at the molecular level. I am particularly interested in a group of complex glycoproteins, heparan sulphate proteoglycans (HSPGs). My research uses the nematode Caenorhabditis elegans as a simplistic genetic model. Understanding neuronal development is one of the fundamental questions in biology as neurons control actions from movement to autonomous functions such as heart beat and breathing, and our ability to sense, think and remember. The adult human brain has over hundred billion neurons which each make connections with an average of 1000 target cells, yet mistakes happen very rarely. Neuron migration and formation of neuronal connections during development are genetically determined and dictate the wiring of the entire nervous system, yet the molecular mechanisms are still poorly understood. HSPGs are present in cell membranes and in the extracellular space between cells. HSPGs mediate interactions of cells with their environment and play critical roles in regulating development and homeostasis. In the nervous system HSPGs guide migrating neurons and their processes, and control functions involved in learning and memory. C. elegans contains homologues of key genes involved in human neuronal development. A simplified model is expected to improve understanding of HSPGs in normal cellular communication. Understanding normal development will provide novel insights into mechanisms that underlie cancer, degenerative neuronal diseases such as Alzheimer’s and Parkinson’s, and regeneration after injury.

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  • Funder: UK Research and Innovation Project Code: EP/V518505/1
    Funder Contribution: 13,333 GBP

    Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

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  • Funder: UK Research and Innovation Project Code: G1002402
    Funder Contribution: 410,245 GBP

    In the UK, declining levels of physical activity are contributing to an epidemic of obesity and alarming increases in preventable conditions such as cardiovascular disease and diabetes. Previous efforts to promote physical activity have largely failed. However, a powerful motivator for an active lifestyle, already present in many households, has been overlooked. 1 in 4 households in the UK own dogs, yet despite having a furry pal ready to ‘go walkies‘, some owners still do not walk their dogs or walk them only rarely. This study by researchers at the University of Liverpool will examine the aspects of the human-dog relationship that cause some people to walk their dogs, and others not. It will use a combination of face-to-face interviews with dog owners, observational studies and questionnaire surveys. A key focus will be the involvement of children in activities with dogs that may prevent childhood obesity. If all dog owners walked for at least 30 minutes every day, they would meet recommended physical activity guidelines. Many dogs would also live much healthier and happier lives. This study will inform the best methods to motivate walking that is beneficial to the health of both people and dogs.

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