News by Subject Technology & Engineering

Deep learning, a type of artificial intelligence, can boost the power of MRI in predicting attention deficit hyperactivity disorder (ADHD), according to a new study. Researchers said the approach could also have applications for other neurological conditions.

Thrips don't rely on lift in order to fly. Instead, the tiny insects rely on a drag-based flight mechanism, staying afloat in airflow velocities with a large ratio of force to wing size. Researchers have performed the first test of drag force on a thrip's wing under constant airflow in a bench-top wind tunnel and, drawing from microfabrication and nanomechanics, they created an experiment in which a thrip's wing was glued to a self-sensing microcantilever.

A new UNSW study has shown that using a drone to film hippos in Africa is an effective, affordable tool for conservationists to monitor the threatened species' population from a safe distance, particularly in remote and aquatic areas.

In the not too distant future, we can expect to see our skies filled with unmanned aerial vehicles delivering packages, maybe even people, from location to location. Researchers from The University of Texas and MIT, in collaboration with Akselos, and Aurora Flight Sciences, are developing 'digital twins' that combine computational models and machine learning to predict vehicle health and enable autonomous decision-making at the edge.

A Rutgers-led team of engineers has developed an automated way to produce polymers, making it much easier to create advanced materials aimed at improving human health. The innovation is a critical step in pushing the limits for researchers who want to explore large libraries of polymers, including plastics and fibers, for chemical and biological applications such as drugs and regenerative medicine through tissue engineering.

A specially conditioned liquid crystal polymer could be controlled with the power of light alone, with new potential applications in soft robotics.

Researchers in Finland are 'training' pieces of plastic to walk under the command of light. The method developed, published Dec. 4 in the journal Matter, is the first time a synthetic actuator 'learns' to do new 'tricks' based on its past experiences, without computer programming.

Computers can learn to find flares and other events in vast streams of solar images to help forecasters issue timely alerts, according to a new study in the Journal of Space Weather and Space Climate. The machine-learning technique, developed by CIRES and NOAA scientists, searches satellite data for features significant for space weather. Changing conditions on the Sun can affect various technologies on Earth, blocking radio communications, damaging power grids, and diminishing navigation system accuracy.