The results of their research were published in the journal Artificial Intelligence in Agriculture under the title “Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression.”

Researchers at Argonne have discovered that superconducting nanowire photon detectors can also be used as highly accurate particle detectors, and they have found the optimal nanowire size for high detection efficiency.

Entanglement – linking distant particles or groups of particles so that one cannot be described without the other – is at the core of the quantum revolution changing the face of modern technology. While entanglement has been demonstrated in very small particles, new research from the lab of University of Chicago Pritzker School of Molecular Engineering (UChicago PME) Prof. Andrew Cleland is thinking big, demonstrating high-fidelity entanglement between two acoustic wave resonators.

With the exponential rise in drone activity, safely managing low-flying airspace has become challenging — especially in highly populated areas. Just last month an unauthorized drone collided with a ‘Super Scooper’ aircraft above the Los Angeles wildfires, grounding the aircraft for several days and hampering the firefighting efforts.

Traditional radar systems are powerful but cannot effectively detect low-flying aircraft below 400 feet. While the Federal Aviation Administration (FAA) has some regulations to manage small, unmanned aircraft systems (UAS) or drones, tracking and safety can be problematic – especially in congested or restricted airspaces. BYU researchers may have the solution.

Using a network of small, low-cost radars, engineering professor Cammy Peterson and her colleagues have built an air traffic control system for drones that can effectively and accurately track anything in an identified low-altitude airspace.