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Development and validation of an AI-driven blood glucose prediction system for pilots based on continuous glucose monitoring
Abstract During flight, pilots are exposed to unique environmental factors such as low air pressure, acceleration, and psychological stress, which can lead to altered glucose metabolism that poses a threat to flight safety. Traditional fingerstick blood glucose monitoring has drawbacks such as the need for intermittent readings, time-consuming procedures, and passive monitoring.
[2502.00622] Strengthening Generative Robot Policies through Predictive World Modeling
arXiv:2502.00622 (cs) View PDF HTML (experimental) Comments: Subjects: Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG) Cite as: arXiv:2502.00622 [cs.RO] (or arXiv:2502.00622v1 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2502.00622 Submission history From: Haocheng Yin [ view email] [v1] Sun, 2 Feb 2025 01:21:19 UTC (38,012 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Connected Papers Toggle Connected...
A SiC Photo-Conductive Switch-Based Pulse Generator with Nanoseconds and High Voltage for Liver Cancer Cells Ablation Therapy
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