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predict interaction effects. Unlike robot-specific neural network models, the proposed approach aims to learn a universal representation of local interactions (fluid-structure, robot-robot, robot-object
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, electrochemical storage, energy conversion, and controllable loads. • Generation of normal, disturbed, and degraded operating scenarios taking into account different network configurations. • Integration
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-fidelity modeling approaches combining simulations of different fidelity levels, ranging from RANS calculations to high-fidelity LES, possibly associated with various levels of geometric or physical
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to explain the observed matter-antimatter asymmetry in the universe. The SM is therefore likely a low-energy limit of a more complex theory, and the Higgs field is one of the most useful tools for determining
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cross-border network — the Upper Rhine Biodiversity Cluster — to share knowledge. This work will lead to analytical tools, action plans, training for professionals, and exhibitions for the general public