Researchers from Wuhan University have developed a new Uncertainty-Aware Filtering (UAF) algorithm that significantly enhances spacecraft autonomous navigation in deep-space environments characterized by weak gravity, strong perturbations, and limited prior knowledge, which is published in the Chinese Journal of Aeronautics (https://doi.org/10.1016/j.cja.2025.103971). The method shows clear advantages over conventional Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) approaches and has been validated using simulations of China’s Tianwen-2 mission to asteroid 311P/PANSTARRS.

Quantum computing offers a promising pathway for accelerating large-scale scientific simulations, but applying it to computational fluid dynamics remains difficult. A new quantum TLFS-LBM framework reported in the Chinese Journal of Aeronautics (https://doi.org/10.1016/j.cja.2026.104176) introduces a fractional-step correction, a coordinate-based streaming matrix, and a multi-circuit strategy to enable practical incompressible-flow simulations on non-uniform meshes and complex boundaries while reducing quantum-circuit resource demands.

With the rapid advancement of pulsed power electronics, electric vehicles, avionic systems, and renewable energy grids, dielectric capacitors have emerged as indispensable components due to their ultrahigh power density and ultrafast charge–discharge rates. Traditional lead-based dielectric ceramics, however, pose severe environmental and health hazards during their fabrication, usage, and disposal. Sodium bismuth titanate (Bi_0.5Na_0.5TiO₃, BNT)-based lead-free relaxor ferroelectric ceramics have attracted increasing attention as promising alternatives owing to the large spontaneous polarization induced by the Bi³⁺ 6s² lone-pair electron configuration and their broad operational temperature stability arising from diffuse phase transitions. Nevertheless, challenges remain in coordinating polarization response, dielectric breakdown strength (E_b), and relaxation behavior across different operational voltages. Therefore, developing field-tailored multiscale design strategies is essential to meet growing performance demands in diverse electrostatic energy storage applications.

Small target detection and tracking in UAV remote sensing images are key tasks in fields such as security patrols and traffic monitoring. Recently, a framework called the Cropped Target Detection and Tracking Framework, through cropping and random sampling strategies, significantly improves real-time performance while ensuring small target positioning accuracy and tracking robustness, which is published in the Chinese Journal of Aeronautics.

Early warning alone cannot stop an outbreak. A new Perspective in Science Bulletin examines why signals from emerging infectious diseases can fail to trigger timely public health action, and proposes a practical pathway linking rapid verification, context-sensitive risk assessment, predefined action triggers and operational readiness.

Vascular topology and hemodynamics define tissue perfusion boundaries, providing essential information for surgical margin planning, vessel preservation, and postoperative functional assessment. Scientists in China developed PAATAM, a real-time photoacoustic tracking and mapping strategy that fuses vascular geometry and signal-intensity features to estimate six-degree-of-freedom handheld probe motion. The method reconstructs globally consistent panoramic 3D vascular maps with 99.67% registration accuracy, opening new avenues for photoacoustic surgical navigation and functional vascular assessment.

This study aims to develop a medical “dry laboratory” model that treats healthcare data as the primary research subject and employs computational science and AI as core methodologies. Based on the practice of a large tertiary hospital, we present a construction framework featuring a full-cycle model spanning data cultivation, governance, value extraction, and ecological feedback—transforming medical data from a static resource into a living asset. Innovatively, the “dry laboratory” was integrated into the residency training rotation to systematically cultivate data literacy. Practice has shown that the framework establishes the “dry laboratory” as a digital research entity, creating a closed-loop system that integrates clinical practice with data analytics, significantly enhancing the usability of multimodal data and enabling scalable training in data competence. In conclusion, the medical “dry laboratory” represents a new digital research paradigm distinct from traditional wet laboratories. Its implementation provides a reference framework and introduces an integrated “dry-wet” research model combining wet-lab experiments with data cultivation, demonstrating significant value for enhancing medical innovation, cultivating interdisciplinary talent, and advancing smart healthcare.

The high-entropy ferroelectric fillers/polymer nanocomposites achieve ultra-high U_dis values of 8.7 J cm^-3 at 150 °C and 5.9 J cm^-3 at 200 °C, while maintaining an η of over 90%.