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Institute News

With communities across the nation experiencing a wave of COVID-19 infections, clinicians need effective tools that will enable them to aggressively and accurately treat each patient based on their specific disease presentation, health history, and medical risks.

A small energy harvesting device that can transform subtle mechanical vibrations into electrical energy could be used to power wireless sensors and actuators for use in anything from temperature and occupancy monitoring in smart environments, to biosensing within the human body.

TROY, N.Y. — The harsh conditions that equipment, satellites, and spacecraft are subject to in space pose significant challenges. Electronic systems must be protected from extreme heat and cold, while storage containers holding liquid propellants must be shielded from solar radiation.

A COVID-19 transmission model inspired by gas-phase chemistry is helping the Centers for Disease Control and Prevention (CDC) forecast COVID-19 deaths across the country.

Developed by Yunfeng Shi, an associate professor of materials science and engineering at Rensselaer Polytechnic Institute, and Jeff Ban, a professor of civil engineering at the University of Washington, the model uses fatality data collected by Johns Hopkins University and mobility data collected by Google to predict disease spread based on how much a population is moving within its community.

Anyone who has experienced a midafternoon energy slump or suffered from jetlag has felt the effects of their body’s circadian rhythm. This internal clock helps regulate many of our physiological processes, including sleep, metabolism, and even how the brain functions.

Researchers at Rensselaer Polytechnic Institute anticipate a future in which a combination of smart wearables and algorithms assess each person’s circadian rhythm and provide personalized feedback as to what light, sleep, and work schedule would be ideal for their particular internal clock.

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