A new AI-powered tool has reduced astronomers’ workload by 85% - filtering through thousands of data alerts to identify the few genuine signals caused by supernovae (powerful explosions from dying stars). The findings have been published today (10 Sept) in The Astrophysical Journal. 

Whether helping create an alloy that can withstand the withering conditions of Venus in partnership with NASA or collaborating with the National Energy Technology Laboratory (NETL) to develop a portable sensor that can identify rare earth elements (REE), the University of Pittsburgh Swanson School of Engineering’s Paul Ohodnicki is fueling innovative research while solving problems both in space and right here on Earth. R&D World has recognized Ohodnicki and his team of collaborators with 2025 R&D 100 Awards, this year for two emerging technologies: VulcanAlloy and eMission Critical Sensor.

The electronic nose works by analyzing volatile organic compounds (VOCs) or groups of chemicals that can evaporate with ease and release potentially harmful gases — an example of this is smog. The e-nose is designed to detect the presence of a strong, unpleasant odor in food that bacteria has contaminated past the point of human consumption.

The National Comprehensive Cancer Network (NCCN)—an alliance of leading cancer centers devoted to patient care, research, and education—hosts a Policy Summit exploring where artificial intelligence (AI) currently stands as a tool for improving cancer care, and where it may be going in the future. 

Researchers led by Noah Cowan at Johns Hopkins University have secured NIH funding to probe how animals alternate between "explore" (sensing) and "exploit" (task-oriented) behaviors in uncertain environments, using the weakly electric glass knifefish as  a model. The team includes researchers from four universities who will integrate their expertise in neuroscience, math, engineering, and machine learning to build on 2023 findings in  Nature Machine Intelligence that revealed the explore/exploit pattern across species from amoebas to humans. The project aims to decode decision triggers, with implications for robotics and medicine.