Advanced wearable technology improves support for people with dementia and their caregivers
Peer-Reviewed Publication
Updates every hour. Last Updated: 27-Jun-2025 14:10 ET (27-Jun-2025 18:10 GMT/UTC)
Those receiving care then wore a GPS-based device (resembling a smartwatch) that also had an S.O.S. emergency calling function. Their caregivers downloaded a smartphone application that informed them of the location of their care recipient, set physical boundaries that triggered smartphone notifications when crossed and enabled immediate communication with care recipients who wandered.
By linking theoretical predictions with neutron experiments, researchers have found evidence for quantum spin ice in the material Ce2Sn2O7. Their findings, which may inspire the technology of tomorrow, such as quantum computers, have been published in the journal ‘Nature Physics’. The experiments were conducted at the Institut Laue-Langevin (ILL), taking advantage of the world’s most intense neutron beams and of an unparalleled state-of-the-art instrument suite. This work paves the way towards future unifications of theory and experiments, which is of particular interest for highly complex areas such as quantum physics and exotic states of matter. The findings also offer a wonderful playground for further exploration of quantum phenomena in materials with potential applications in quantum computing.
A research team led by Dr. Sofia Sheikh of the SETI Institute, in collaboration with the Characterizing Atmospheric Technosignatures project and the Penn State Extraterrestrial Intelligence Center, set out to answer a simple question: If an extraterrestrial civilization existed with technology similar to ours, would they be able to detect Earth and evidence of humanity? If so, what signals would they detect, and from how far away?
“One of the most satisfying aspects of this work was getting to use SETI as a cosmic mirror: what does Earth look like to the rest of the galaxy? And how would our current impacts on our planet be perceived,” said Sheikh. “While of course we cannot know the answer, this work allowed us to extrapolate and imagine what we might assume if we ever discover a planet, with, say, high concentrations of pollutants in its atmosphere."
Texas A&M researchers are developing a hybrid biomechanical physics-informed machine learning model. Their approach combines experimentally measured bone deformation data with governing physics and a robust machine learning framework, enabling precise, personalized predictions of mechanical stress in the bone. This innovation provides an efficient tool for patient-specific dental surgery planning, optimizing bone healing and ensuring long-term implant success.