In the realm of infrastructure maintenance, a novel approach to detecting concrete bridge damage has emerged. Researchers have developed an automated detection method using an enhanced version of the YOLO (You Only Look Once) algorithm, augmented with Vision Transformers. This advancement aims to improve the accuracy and efficiency of identifying structural defects in bridges, particularly those captured by drones under challenging real-world conditions. The study, published in Engineering, highlights the potential of this technology to enhance bridge inspection processes.

A new review published in Engineering explores the advancements in hand–eye coordination technology for agricultural robots, highlighting their potential to address labor shortages and enhance efficiency in complex farming tasks. The study examines various configurations of hand–eye systems, calibration methods, and control strategies, emphasizing the importance of accurate target perception and collision-free handle. While significant progress has been made, ongoing challenges such as maintaining calibration accuracy and replicating human dexterity remain. The findings suggest that continued innovation in hand–eye coordination could play a crucial role in the future development of smart agriculture.

A new study published in Engineering offers detailed insights into the potential areas for high-yield finfish mariculture. By integrating advanced physiological models with the spatiotemporal heterogeneity of marine environments, researchers have mapped suitable and high-yield areas for 27 commercial finfish species under current and future climate scenarios. The findings indicate that finfish mariculture could play a significant role in global food security as suitable areas are projected to increase by 2050.

A new study published in Engineering offers a novel approach to addressing environmental challenges in coal mining by integrating the treatment of coal mine goafs, utilization of coal-based solid waste, and sequestration of CO₂ through mineralization. This method not only enhances the mechanical properties of filling materials but also significantly increases CO₂ sequestration capacity, providing a sustainable solution for the coal industry.

This study published in Engineering offers new insights into the impact of alcoholic liver disease (ALD) on post-transplant outcomes in patients with hepatocellular carcinoma (HCC) and hepatitis B virus (HBV) infection. Researchers found that ALD significantly increases the risk of HBV reactivation and worsens survival outcomes following liver transplantation. Using advanced machine learning techniques, the study identified key metabolic factors associated with HBV reactivation and developed a novel risk stratification index to better predict patient outcomes. The findings highlight the importance of considering ALD in the management of liver transplant recipients with HBV-related HCC.

Researchers have developed a new hybrid earthquake early warning system called HEWFERS, which leverages advanced machine learning techniques and seismological principles to provide real-time predictions of ground shaking intensity. The system integrates a domain-informed variational autoencoder, a feed-forward neural network, and Gaussian process regression to offer both on-site and regional early warnings. Validated with a large database of ground motion records, HEWFERS demonstrates enhanced accuracy and reliability in seismic risk mitigation.

Designing flexible electronics has long been constrained by the limits of two-dimensional printing. 

RNAi technologies have been exploited to control viruses, pests, oomycetes and fungal phytopathogens that cause disasters in host plants, including many agronomically significant crops. However, it is unclear what process mediates RNA uptake by fungi. Here, the authors utilized live-cell imaging technology combined with molecular biology experiments to demonstrate that exogenous RNA is indiscriminately absorbed by Verticillium dahliae, the notorious plant pathogenic fungus. The uptake of exogenous RNA by fungal cells is predominantly mediated through endocytosis. This study not only provides a new theoretical foundation for applying trans-kingdom RNA interference technology in crop protection but also lays the groundwork for research and applications of exogenous RNA in plant-fungi interaction systems.

Lead-free antiferroelectric materials hold promise as alternatives to lead-containing dielectrics, but the challenge of irreversible room-temperature phase transitions in sodium niobate (NaNbO₃) has hindered their application. This work innovatively employs a tin (Sn) and cerium (Ce) co-doping strategy, successfully achieving precise control over the phase structure of NaNbO₃. The study found that the sample with x=0.04 exhibits reversible electric-field-induced ferroelectric/antiferroelectric (AFE ⇄ FE) phase transitions at room temperature, displaying the characteristic double hysteresis loops and a positive strain of 0.38%. The team also clarified the key mechanism involving Sn²⁺/Ce³⁺ occupying A-sites and Sn⁴⁺/Ce⁴⁺ occupying B-sites through atmosphere-controlled sintering. This work paves a new avenue for the design and application of high-performance lead-free antiferroelectric materials.