Young Prof Honored by Forbes Trillions of atoms in motion could take the form of a new cancer drug or a bendable phone. At the quantum scale, “atoms vibrate, combine, and pile up in very complicated ways,” says UVM chemist Michael Ruggiero. For his remarkable work in better understanding how these subtle, but very specific, motions of atoms influence the bulk properties of materials people can use, the UVM assistant professor was selected as one of Forbes’ “30-Under-30” leaders in science, their “annual list chronicling the brashest entrepreneurs across the United States and Canada.” In his Discovery Hall laboratory, Ruggiero and his students hit materials with a powerful laser to tease out the quantum mechanics of molecules. Then they take what they learn in these real-world materials and model their motions on a supercomputer. “We go from the very basic to the very applied,” Ruggiero says. For example, with insights he gains about the motions of specific molecules, he’s working to help pharmaceutical companies better understand how materials may be interacting to degrade a medication. “The kind of work we do could lead to drugs with a longer shelf life,” he says. Other examples of where Ruggiero's research program aims to help: improving the ability of semiconductors to work in flexible displays, and better understanding the mechanical properties of gas storage materials for improved hydrogen fuel cells.
HELPING CATCH ANXIETY AND DEPRESSION EARLY
Anxiety and depression are surprisingly common among young children—as many as one in five kids suffer from one of them, starting as early as the preschool years. But it can be hard to detect these conditions, known as “internalizing disorders,” because the symptoms are so inward-facing that parents, teachers, and doctors often fail to notice them. A new tool developed by UVM biomedical engineer Ryan McGinnis and Ellen McGinnis, UVM clinical psychologist, and colleagues in the Department of Psychiatry at the University of Michigan promises to better screen children for internalizing disorders, catching them early enough to be treated. Their innovative approach was having children in a test group wear motion sensors as they completed a “mood induction task,” a common research method designed to elicit specific behaviors and feelings such as anxiety. Typically, trained researchers would watch a video of the task and score the child’s behavior and speech during the task to diagnose internalizing disorders. In the new study, the wearable motion sensor monitored movement and a machine learning algorithm analyzed that movement to distinguish between children with anxiety or depression and those without. After processing the movement data, the algorithm identified differences in the way the two groups moved that could be used to separate them, identifying children with internalizing disorders with 81 percent accuracy—better than the standard parent questionnaire. The work was published in the journal PLOS ONE.
LEFT, WILLIAM MCDOWELL; ABOVE, SALLY MCCAY; BELOW LEFT, ARMAN ZHENIKEYEV/GETTY IMAGES
“
SAFE SKIES UVM’S Spatial Analysis Laboratory, pioneers in using drones to assess emergencies and natural disasters, joins an international team providing expertise as the Federal Aviation Administration examines regulation of unmanned aerial systems, AKA drones. As part of the FAA’s Alliance for System Safety of UAS through Research Excellence, the UVM team will research the use of drones in disaster situations, providing the agency with data for their safe operations in times of disaster.
I N Q U I RY 2 0 2 0
5
