White oval squid (Sepioteuthis lessoniana sp. 2), known locally as shiro-ika, are medium-sized squids naturally distributed in the Indian and western Pacific oceans, flittering in and out of a wide range of different habitats – from shallow seagrass beds, over coral reefs, to depths of 100m along coastal environments. In such biodiverse zones, the squids encounter predators of all sizes and shapes, from seabirds flying overhead to sharks, tuna, and other cephalopods prowling under the sea.

Such a variety of threats calls for a large repertoire of survival strategies. Researchers from the Okinawan Institute of Science and Technology (OIST) have previously discovered how shiro-ika change color when moving between different shades of substrate – and now, the same team has painted a full picture of how the cephalopod employs a sophisticated range of camouflaging strategies to adapt to different environments and threats. “The wide variety of visual strategies used by the squid is surprisingly complex, especially considering that squid have traditionally been regarded as spending most of their lives in the open water column,” explains former OIST Visiting Researcher Dr. Ryuta Nakajima, “This discovery suggests that squid have a deeper behavioral relationship with the ocean floor than previously thought.”

Researchers from Kelson Marine in Portland, Maine and the University of Maine developed a new tool that provides detailed economic analyses for kelp farmers and reveals strategies for reducing the cost of farmed seaweed. The tool incorporates many different factors from a farming scenario, including site specific-ocean and meteorological conditions, species-specific crop characteristics and growth, workboat types and sizes, labor structures, operational technology, local shore-side infrastructure, maintenance schedules and more. By resolving the comprehensive impact on the bottom line and the multitude of tradeoffs associated with specific operational and farm design decisions, the tool provides unique insight into the implications of cost-saving alternatives.

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.