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Haughn and colleagues develop gust rejection controllers and overcome challenges of computationally expensive modeling and expansive distributed sensing networks. With only three pressure tap sensors, small fixed wing uncrewed aerial vehicles could extend into more complex urban environments.
Wang and colleagues design a flowmeter composed of a liquid crystal-filled nested capillary which demonstrates thermal stability and high sensitivity. The device measures air flow via its cooling effect resulting in a measurable spectrum shift in whispering gallery modes.
Mochou Yang and colleagues describe a a ghost imaging framework based on laser mode speckle pattern which improves imaging quality at low sampling rate. The feasibility of this method is demonstrated in a turbid water environment.
A research team from the High-Tech Industry Unit at TNO reports a method to identify satellites using retroreflecting tags with spectral signatures mounted on these satellites. The approach reduces the complexity of the observation system and does not require any power sources on board.
Mohammad Omid Bagheri and colleagues introduce a metasurface-enhanced millimetre-wave radar system designed for near-field biosensing. Their device adapts to the properties of the skin-device interface, providing heightened diagnostic precision in wearable healthcare monitoring applications.
X-ray computed tomography is a widely used technique for non-invasively visualizing the interior of the human body. A. Ben Yahuda and colleagues report a technique for incorporating scattered radiation data in Computed Tomography scans to improve image resolution and minimize radiation exposure for patients.
Stanley Cheung and co-authors introduce co-integrated III-V/Si memristors with fundamental photonic building blocks used in both communication and computing applications. This allows a path towards realizing low-loss, non-volatile optical elements with near-zero static power consumption.
Guillaume Dion and co-authors present the gait pattern recognition micro-electromechanical sensor. The effective coupling between sensing and computing capabilities allows in-sensor processing for robust, secure and low-power data analysis.
Thieben et al report a 3D human-scale magnetic particle imaging scanner, which allows for real-time 3D, multi-contrast imaging with compelling sensitivity and spatial resolution. The use of a medical tracer with appropriate dosages facilitates potential clinical usage.
Jiashuo Shi and colleagues build an integrated camera capable of tracking objects of interest. They use optical computing to arrange molecules in the liquid crystal mask for enhanced distinction between the object and background.
Real-time, low-cost, and wireless mechanical vibration monitoring is necessary for industrial, environmental, and biomedical applications. Here, Dajun Zhang and colleagues report a passive,ss metamaterial-based device which substantially improves the sensitivity of wireless vibration measurement methods when attached to vibrating surfaces.
Ce Zhang and colleagues report a novel system based on a software-defined radio to measure and control the vibrations of an exotic nanomechanical graphene resonator. This system will be helpful for the nanomechanical measurements with small signals and modulations.
Yi-Te Huang and colleagues demonstrate a microactuator driven by a spin-current volume effect. Alternating current and external magnetic field generates mechanical resonances in the amorphous magnetic film TbFeCo layered with non-magnetic metal.
Ran Xiao, Jiaheng Li and colleagues report the fabrication of architected microlattice nasopharyngeal swabs, which can effectively release the collected load without the need for dilution. The method was demonstrated able to improve the accuracy of Covid19 rapid tests.
Modelling waste biorefining processes can be difficult due to variability of feedstocks, making process optimization challenging. To address these uncertainties, Ji Gao and colleagues introduced a reinforcement learning-based framework, using a model anaerobic digestion process to demonstrate their control methods.
Adolfo Perrusquia and colleagues propose a machine learning-based framework to unveil the hidden intentions of drones, without relying on explicit behavioral features. This framework can distinguish drone’s malicious intentions from naïve intentions, enhancing our ability to effectively identify potential threats posed by drones.
Chung, Quirk and colleagues present a lightweight active back exosuit to assist workers when lifting. Testing in a simulated one-hour order picking task demonstrates the device has practical usability and reduces back muscle effort by 18%.