In an article published in Communications Physics, researchers from the Université libre de Bruxelles and the Institute for Quantum Optics and Quantum Information in Vienna present a new framework for describing physics relative to quantum reference frames, unveiling the importance of previously unrecognised “extra particles”. 

During the preliminary design phase of flapping-wing micro air vehicles (FWMAVs), there currently exists a deficiency in rapid prediction method for the aerodynamic characteristics of flexible flapping wings. A novel aerodynamic prediction method for flexible flapping wings has recently achieved significant breakthroughs. This method innovatively employs conical surface to mimic wing deformation, combined with an unsteady panel method for aerodynamic force computation, enabling rapid and accurate prediction of both aerodynamic characteristics and control moments of flexible flapping wings.

Both biotic factors (microbial biomass and leaf nutrients) and abiotic factors (climate, soil properties, and elevation) play important roles in shaping how sensitive forest soil respiration (Q₁₀) is to temperature changes. By analyzing 766 soil Q₁₀ values from forests around the world, researchers found that microbial biomass carbon is the strongest single predictor, with plant traits like leaf phosphorus content also having a clear impact. The findings highlight the need to consider both biotic and abiotic influences when managing forests and improving carbon cycle models in a warming climate.

For decades, aerospace engineers have confronted the life-threatening challenge of reigniting aircraft engines in high-altitude, low-pressure environments. Traditional spark ignition systems, limited by short discharge time and low energy efficiency, consistently fail to ignite lean kerosene-air mixtures in some difficult conditions. Although, gliding arc plasma ignitor offers improvements, its dependence on external gas sources prevents compatibility with combustor wide flight envelopes. This critical bottleneck has impeded next-generation aerospace propulsion systems.

Performance of Global Navigation Satellite Systems (GNSS) in providing positioning, velocity estimation, and timing services in urban environments often suffers significant degradation due to multipath effects and Non-Line-of-Sight signal reception. Traditional Fault Detection and Exclusion methods face technical bottlenecks, including high computational complexity and insufficient exclusion accuracy caused by the complex and diverse nature of fault modes. This study proposed a novel fault detection and correction method for Doppler-observable-based velocity estimation: GS-LASSO (Grouping-Sparsity Least Absolute Shrinkage and Selection Operator). Experiment results demonstrated that the GS-LASSO method could provide high-precision velocity estimates at the decimeter-per-second (dm/s) level in complex urban environments with limited computational resources.