Lehigh University researcher Hannah Dailey is leading a new international collaboration to improve predictions of how bone fractures heal. Supported by the U.S. National Science Foundation and the Swiss National Science Foundation, the four-year project partners with the AO Research Institute Davos (ARI) to develop computational models that combine mechanical factors—such as implant stiffness and loading patterns—with biological processes that vary from patient to patient. Using ARI’s extensive imaging library documenting fracture healing in sheep, the team will build probabilistic models capable of forecasting how recovery will progress. The models will ultimately be integrated into ARI’s online training platform to help surgeons understand how implant choices and rehabilitation strategies influence healing. Long term, the goal is to enable patient-specific simulations that help clinicians identify complications earlier and make more informed treatment decisions.

A research paper by scientists at Nankai University presents a monolithic synaptic device that replicates and integrates tactile sensing and neuromorphic processing functions for in-sensor computing.

As part of an effort to better evaluate how pre-weaned calf and stocker calf treatments influence feedlot performance, Daniel Rivera, associate professor of animal science with the University of Arkansas System Division of Agriculture and Paul Beck, a professor and extension specialist for beef nutrition with Oklahoma State University’s department of animal and food sciences, published a summary of research on the topic in a special issue of Applied Animal Sciences, the American Registry of Professional Animal Scientists' official journal.