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A novel CSC MOS structure disentangles interface and shallow trap effects in AOS transistors, revealing distinct trap regimes and their time-dependent contributions to conductance loss.
Robots can now navigate complex, dynamic environments by intelligently pushing obstacles and interacting with their surroundings, not just avoiding them.
A novel explainable power modeling framework achieves state-of-the-art prediction accuracy and generalization on diverse workloads with negligible hardware overhead, unlike opaque black-box models.