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were constructed. The results will be compared with those for a charged scalar field [2]. The second part of the project involves computing the renormalized expectation value of the stress-energy tensor
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Organic quantum batteries: the development of high-performance energy storage devices (S3.5-MPS-Lidzey)
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Digitalising populations of structural systems using machine learning (S3.5-MAC-Dardeno)
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design of thermal management elements for fusion components. This framework foresees two building blocks: high-fidelity Computational Fluid Dynamics (CFD) simulations of boiling flows within complex
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BBSRC Yorkshire Bioscience DLA Programme: How do cells coordinate nutrient scavenging pathways?
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Zero-Knowledge for Quantum Proofs: Quantum Computation and Cryptographic Primitives (S3.5-COM-Abdolmaleki)
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Bugging Out: When AI loses the Plot – Detecting and Taming Hallucinations in LLM-Generated Code (S3.5-COM-Wang)
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Explainable and Causal AI for Visual Analytics in Regenerative and Climate-Smart Agriculture (C3.5-COM-Cruz Villa-Uriol)
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for fusion components. This framework foresees two building blocks: high-fidelity Computational Fluid Dynamics (CFD) simulations of boiling flows within complex geometry using opensource software and cutting
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Adversarial machine learning - Identification and prevention of cyber-physical attacks on infrastructure (S3.5-MAC-Champneys)