Beyond disposal: redefining biodegradable plastics as high-value resources for carbon neutrality
Peer-Reviewed Publication
Updates every hour. Last Updated: 2-Apr-2026 02:16 ET (2-Apr-2026 06:16 GMT/UTC)
Some of the 3D digital models created by researchers to depict lost neighborhoods in Columbus, Ohio, tell a clear story by placing the “ghosts” of houses that were demolished for freeway construction atop the roadways now occupying that land. But by talking to the people who lived in these communities, scientists are filling in historic gaps that technology can’t fill, adding trees, cars, people, photographs and life stories to the digitized infrastructure that was an initial focus of the work. The research team has published an update on the Ghost Neighborhoods of Columbus project in the International Journal of Digital Humanities, reporting on the technology workflow, including solutions to bottlenecks they’ve encountered, and acknowledging a slow start to community engagement that hums along nicely these days. The team aims to put both the digital work and story collection on a faster track.
Researchers have identified key components in large language models (LLMs) that play a critical role in ensuring these AI systems provide safe responses to user queries. The researchers used these insights to develop and demonstrate AI training techniques that improve LLM safety while minimizing the “alignment tax,” meaning the AI becomes safer without significantly affecting performance.
A new study reviews how machine learning (ML) is being used to help communities recover critical infrastructure after natural hazards such as earthquakes, floods, and hurricanes. The research synthesizes global studies and shows that ML can support recovery by characterizing recovery trends, predicting recovery times, and optimizing recovery schedules. The authors also identify key challenges, such as limited data availability, and outline future directions for building more resilient infrastructure systems using ML.
Cryopreservation is not a new technology, but there is still much to explore and perfect in the field. Current methods use slow freezing, a method that is conducive to ice formation, cell dehydration and an increase in cryoprotective agents (CPAs). These are not ideal circumstances for achieving immaculately cryopreserved cells. Researchers from the University of Tokyo use vitrification, a process that transforms a substance into a noncrystalline solid by rapid cooling. This cooling yields favorable outcomes in biological samples, even those that are typically difficult to freeze and thaw successfully. Despite challenges within this method, the future of regenerative medicine research may be greatly, and positively, impacted by the use of vitrification for cell cryopreservation.