EurekAlert! News by Subject: Tech & Engineering - News by Subject: Tech & Engineering

Tech & Engineering

Updates every hour. Last Updated: 18-Dec-2025 11:11 ET (18-Dec-2025 16:11 GMT/UTC)

A new wave in disaster financing: Parametric insurance for tsunami

Tohoku University
Peer-Reviewed Publication

Tsunami are rare, yet incredibly devasting disasters. How can we use science to design supportive tsunami insurance plans that are cost-effective?

Journal: npj Natural Hazards

Generalizable gait analysis for clinical applications using generative AI and musculoskeletal simulation

University of Tsukuba
Peer-Reviewed Publication

Gait assessment plays a critical role in the diagnosis and management of neurological disorders. Although AI-based models offer the potential to enhance the objectivity and accessibility of clinical gait analysis, most existing models are limited by their dependence on specific patient populations and sensor configurations, largely due to the scarcity of diverse clinical datasets. In a recent study, researchers from IBM Research, Cleveland Clinic, and University of Tsukuba addressed this limitation by developing a novel framework that integrates synthetic gait data generated by generative AI with physics-based musculoskeletal simulation. This approach supports the development of scalable and generalizable gait analysis models applicable across heterogeneous patient groups and sensor environments.

Journal: Nature Communications

Quad bike deaths are dropping, but experts say more action required

University of Sydney
Peer-Reviewed Publication

An Australian study of workplace deaths related to quad bike use has found that safety measures work best with government support to encourage uptake and use of safety devices.

Journal: Australian and New Zealand Journal of Public Health

Advances in metal halide perovskite scintillators for x-ray detection

Shanghai Jiao Tong University Journal Center
Peer-Reviewed Publication

The relentless pursuit of advanced X-ray detection technologies has been significantly bolstered by the emergence of metal halides perovskites (MHPs) and their derivatives, which possess remarkable light yield and X-ray sensitivity. This comprehensive review delves into cutting-edge approaches for optimizing MHP scintillators performances by enhancing intrinsic physical properties and employing engineering radioluminescent (RL) light strategies, underscoring their potential for developing materials with superior high-resolution X-ray detection and imaging capabilities. We initially explore into recent research focused on strategies to effectively engineer the intrinsic physical properties of MHP scintillators, including light yield and response times. Additionally, we explore innovative engineering strategies involving stacked structures, waveguide effects, chiral circularly polarized luminescence, increased transparency, and the fabrication of flexile MHP scintillators, all of which effectively manage the RL light to achieve high-resolution and high-contrast X-ray imaging. Finally, we provide a roadmap for advancing next-generation MHP scintillators, highlighting their transformative potential in high-performance X-ray detection systems.

Journal: Nano-Micro Letters

Global trends in herbal tea research reveal antioxidant focus and emerging collaboration

Maximum Academic Press

A research team has revealed key trends, research hotspots, and emerging collaborations in herbal tea research over the past two decades.

Journal: Beverage Plant Research

AI breakthrough unlocks 'new' materials to replace lithium-ion batteries

New Jersey Institute of Technology
Peer-Reviewed Publication

Researchers from New Jersey Institute of Technology (NJIT) have used artificial intelligence to tackle a critical problem facing the future of energy storage: finding affordable, sustainable alternatives to lithium-ion batteries.

The NJIT team successfully applied generative AI techniques to rapidly discover new porous materials capable of revolutionizing multivalent-ion batteries. These batteries, using abundant elements like magnesium, calcium, aluminum and zinc, offer a promising, cost-effective alternative to lithium-ion batteries, which face global supply challenges and sustainability issues.

Journal: Cell Reports

SFU researchers develop a new tool that brings blender-like lighting control to any photograph

Simon Fraser University
Peer-Reviewed Publication

Lighting plays a crucial role when it comes to visual storytelling. Whether it’s film or photography, creators spend countless hours, and often significant budgets, crafting the perfect illumination for their shot. But once a photograph or video is captured, the illumination is essentially fixed. Adjusting it afterward, a task called “relighting,” typically demands time-consuming manual work by skilled artists.

While some generative AI tools attempt to tackle this task, they rely on large-scale neural networks and billions of training images to guess how light might interact with a scene. But the process is often a black box; users can’t control the lighting directly or understand how the result was generated, often leading to unpredictable outputs that can stray from the original content of the scene. Getting the result one envisions often requires prompt engineering and trial-and-error, hindering the creative vision of the user.

In a new paper to be presented at this year's SIGGRAPH conference in Vancouver, researchers in the Computational Photography Lab at SFU offer a different approach to relighting. Their work, “Physically Controllable Relighting of Photographs”, brings explicit control over lights, typically available in Computer Graphics software such as Blender or Unreal Engine, to image and photo editing.