Deep reinforcement learning (DRL) has emerged as a transformative approach in the realm of fluid dynamics, offering a data-driven framework to tackle the intrinsic complexities of active flow control.
Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
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