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and spatiotemporal scales, i.e., new forms of real-time automation of intelligent active grids including grid-forming converters, using distributed control and artificial intelligence (AI) based
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of cellular reprogramming by introducing scalable computational methods that streamline the discovery of reprogramming targets and control strategies. A key innovation of EdgeCR is its fine-grained control
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are believed to influence the coupling of the leaf to its surrounding air, whereas stomatal size, shape and distribution are assumed to determine the plant’s control on leaf gas exchange. Leaf spectral
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, the set-ups should subject liquid crystalline as well as isotropic liquids, which may be highly viscous and require temperature control, to static or oscillatory flow past strategically placed obstacles in
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data, including TPMS (Tire Pressure Monitoring System), high-speed wheel encoders, CAN (Controller Area Network) data, accelerometers, and acoustics data. Understanding of sensor technologies and their
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advanced grid-connected hardware architectures. · Implementing control loops for grid-connected power converters. · Developing gird-following and grid-forming functionalities
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different data collection methods and sensors used to gather road condition data, including TPMS (Tire Pressure Monitoring System), high-speed wheel encoders, CAN (Controller Area Network) data
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on these instruments. The focus areas include nano-imaging, nano-analysis, and in-situ process control for nano-fabrication. AINA’s multi-disciplinary team of experts in charged particle optics, mechanical engineers