Innovations in Gastric Cancer Surgery During Early Minimally Invasive Era and Future Perspectives
With continuing revelations in tumor biology and the emergence of artificial intelligence, new horizons for surgical innovation are opening. At the center of this transformative journey stands the innovative surgeon, driven by passion, guided by data, and steadfast in the commitment to patient safety and quality of life.
Reut El‐On, Young‐Woo Kim
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Discovery of the reward function for embodied reinforcement learning agents. [PDF]
Lu R +12 more
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Abstract Electrification of distillation offers a promising route to reducing scope‐1 emissions from one of the chemical industry's most energy‐intensive unit operations. However, conventional adiabatic columns are dynamically inflexible: Long, energy‐intensive start‐ups make shutdown and restart impractical under variable electricity prices and ...
Samuel Mercer, Michael Baldea
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Challenges and enablers in fluidization technology
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
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Artificial intelligence-driven optimal charging strategy for EV with integrated power quality enhancement in electric power grids. [PDF]
K S, C M.
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Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization
Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son +4 more
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Techno-economic analysis of a power-to-hydrogen system in heavy industries with and without national incentives. [PDF]
Marouani I +5 more
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Dynamic-layer transformer-based reinforcement learning for observation-constrained multi-agent roundup scenarios. [PDF]
Li X, Xu N, Chi Q, Chen H.
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Deep Learning-Based Dynamic Time Division ISAC Beamforming for Vehicular Networks. [PDF]
Lim J, So J.
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