Food drying is a common process for preserving many types of food, including fruits and meat; however, drying can alter the food’s quality and nutritional value. In recent years, researchers have developed precision techniques that use optical sensors and AI to facilitate more efficient drying. A new study from the University of Illinois Urbana-Champaign discusses three emerging smart drying techniques, providing practical information for the food industry.

A research team led by Professor Chuyang Tang, Chair Professor from the Department of Civil Engineering, Faculty of Engineering at the University of Hong Kong (HKU), has developed a novel nanofiltration membrane using natural silk, which could revolutionise the process of water purification or treatment.

Researchers from Princeton University and the University of Arizona have created a simulation that maps underground water on a continental scale. The result of three years’ work studying groundwater from coast to coast, the findings plot the unseen path that each raindrop or melted snowflake takes before reemerging in freshwater streams, following water from land surface to depths far below and back up again, emerging up to 100 miles away, after spending from 10 to 100,000 years underground.

Researchers at the University of Virginia’s School of Engineering and Applied Science and School of Education and Human Development will use AI-powered video analysis technology to help teachers improve the quality of their mathematics instruction under a new $1.4 million grant. 

In Physics of Fluids, researchers in China focus on enhancing the aerodynamic performance of autonomous vehicles by reducing drag induced by externally mounted sensors such as cameras and light detection and ranging instruments. After establishing an automated computational platform, they combined the experimental design with a substitute model and an optimization algorithm to improve the structural shapes of AV sensors. They then performed simulations of both the baseline and optimized models. After optimizing the design, researchers found a 3.44% decrease in the total aerodynamic drag of an AV.

Researchers from HHMI's Janelia Research Campus and collaborators have developed a new AI method that produces sharp microscopy images throughout a thick biological sample without using adaptive optics, adding additional hardware, or taking more images.