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From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

Proceedings of the National Academy of Sciences of the United States of America
The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational dat...

[Intelligent fault diagnosis of medical equipment based on long short term memory network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In order to solve the current problems in medical equipment maintenance, this study proposed an intelligent fault diagnosis method for medical equipment based on long short term memory network(LSTM). Firstly, in the case of no circuit drawings and un...

Micrometer-sized electrically programmable shape-memory actuators for low-power microrobotics.

Science robotics
Shape-memory actuators allow machines ranging from robots to medical implants to hold their form without continuous power, a feature especially advantageous for situations where these devices are untethered and power is limited. Although previous wor...

Inverse mechano-electrical reconstruction of cardiac excitation wave patterns from mechanical deformation using deep learning.

Chaos (Woodbury, N.Y.)
The inverse mechano-electrical problem in cardiac electrophysiology is the attempt to reconstruct electrical excitation or action potential wave patterns from the heart's mechanical deformation that occurs in response to electrical excitation. Becaus...