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or joining thin-wall Titanium and Nickel alloys at high temperatures. Due to the unique material behaviours of these sheets and foils (0.1 mm to 0.5 mm thick), controlling variables in the forming process is
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season properties (e.g. number, intensity) for lead times ranging from one to approximately six months in the latest generation of dynamical seasonal and decadal forecast models. Seasonal forecasts
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expertise and facilities in electrochemistry, materials chemistry, advanced characterisation techniques (including a variety of spectroscopy, microscopy,) modelling and battery and fuel cell construction and
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of these sheets and foils (0.1 mm to 0.5 mm thick), controlling variables in the forming process is challenging. Characterising the mechanical behaviours of thin foils at elevated temperatures is crucial in
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the APE at each point of the North Atlantic using existing software and isolate the coastal values along the Eastern and Western boundaries to compute East-West differences, which will be then correlated
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satellites, with the potential for travel to test instrumentation in ideal locations. Additionally, the simulation work will focus on developing computational models to validate instrumentation and optimising
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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this, there are further sub-objectives during the investigation to achieve this goal: Predict thermal warpage effects on a supersonic intake at different flight times, coupled to a numerical model for the downstream
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to treat ulcerative colitis (UC) and Crohn's disease (CD), including tablets, suppositories, and enemas, are typically associated with adverse systemic effects. Nevertheless, the innovative encapsulation
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, multi-source learning is used to integrate diverse patient populations to build robust models, but having to protect sensitive information. Various modern ML paradigms are proposed to address the diverse