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We consider the Cahn-Hilliard equation, which models phase separation in binary fluids, on the two-dimensional torus in the presence of advection by a given background shear flow, satisfying certain conditions and of sufficiently large amplitude. By exploiting the resulting enhanced dissipation for the linearized operator, we prove that, with well-prepared data, the solution converges asymptotically at large times to the solution of a one-dimensional Cahn-Hilliard equation, obtained by projecting the full equation in the direction orthogonal to the shear in a suitable sense. This result rigorously justifies the observed phenomenon of striation in the concentration field. 

Signal recognition particle (SRP), a universally conserved protein-targeting machine, cotranslationally recognizes signal sequences of nascent endomembrane proteins and engages the SRP receptor (SR) at the endoplasmic reticulum (ER) membrane to unload the translating ribosome. The mechanism of membrane-associated steps in this pathway remains unclear. Here, we address this question using pre–steady-state and single-molecule fluorescence measurements. SR induces release of the signal sequence from SRP and detachment of the SRP guanosine triphosphatase (GTPase) domain from the ribosome. Despite the dissolution of these contacts, SR acts as a tether to stabilize SRP association with the ribosome. Guanosine 5′-triphosphate (GTP) hydrolysis in the SRP-SR complex abolishes this stabilizing effect to facilitate ribosome-nascent chain complex (RNC) release from SRP. The ER membrane selectively promotes a prehandover conformation of the RNC-SRP-SR complex, in which delayed GTP hydrolysis optimizes the transition from targeting to translocation. Our findings provide a high-resolution model for key steps during cargo handover at the ER and highlight the critical role of fine-tuned GTPase activity in the SRP pathway. 

This study investigates the atomization process in Respimat® Soft MistTM Inhalers (SMIs) using a validated Volume of Fluid (VOF)-to-Discrete Phase Model (DPM) to simulate the transition from colliding liquid jets to aerosolized droplets. Key parameters, including colliding jet inlet velocity, surface tension, and liquid viscosity, were systematically varied to analyze their impact on the atomization, i.e., aerosolized droplet size distributions. The VOF-to-DPM simulation results indicate that higher jet inlet velocities enhance ligament fragmentation, producing finer and more uniform droplets while reducing total atomized droplet mass. The relationship between surface tension and atomization performance in colliding jet atomization is not monotonic. Reducing surface tension plays a complex dual role in the atomization process. On the one hand, lower surface tension enhances the likelihood of liquid jet breakup into a liquid sheet, leading to the formation of smaller ligaments under the same airflow conditions and shear forces. This increases the probability of generating more secondary droplets. On the other hand, reduced surface tension also destabilizes the liquid surface shape, decreasing the formation of fine, high-sphericity droplets in regimes where surface tension is a dominant force. Viscosity also influences atomization through complex mechanisms, i.e., lower viscosity reduces resistance to ligament breakup but promotes droplet interactions and coalescence, while higher viscosity suppresses ligament fragmentation, generating larger droplets and reducing atomization efficiency. The validated VOF-to-DPM framework provides critical insights for enhancing the performance and efficiency of inhalation therapies. Future work will incorporate nozzle geometry, jet impingement angles, and surfactant effects to better understand and optimize the atomization process in SMIs, focusing on achieving preferred droplet size distributions and emitted doses for enhanced drug delivery efficiency in human respiratory systems. 

Abstract Tracheal stenosis, a severe airway narrowing, poses significant challenges in respiratory function and often necessitates surgical intervention to restore proper airflow. This study aims to demonstrate how computational fluid dynamics (CFD) can provide a non-invasive, efficient, and highly individualized approach to assist surgeons in modeling and planning various surgical strategies for treatment. The CFD-based approach in this study provides significant advantages, including reduced time and cost, and the ability to analyze complex pulmonary airflow characteristics that are difficult to investigate using in vitro and in vivo studies. This research compares three tracheal geometries: a diseased airway with tracheal stenosis and two post-surgical configurations from different surgical plans. Simulations were conducted under four inhalation flow rates, i.e., rest (6 L/min), normal (30 L/min), moderate (60 L/min), and intensive exercise (120 L/min), to evaluate the impact of surgical outcomes on pulmonary airflow dynamics. The upper airway, modeled with a mouth inlet diameter of 20 mm, exhibited average velocities of 0.32, 1.59, 3.18, and 6.37 m/s, corresponding to the respective flow rates. The laminar model was used for the rest flow rate, while the shear stress transport (SST) k-ω model was applied to simulate turbulence with higher inhalation flow rates. The results revealed substantial improvements in flow parameters following surgery. The stenotic geometry exhibited extreme resistance, with pressure drops increasing from 1.96 Pa at rest to 318.9 Pa under intensive flow, and high wall shear stress (WSS) values peaking at 330.8 Pa. Surgical Plan 1 reduced pressure drops by up to 47% and WSS by 97%, while Surgical Plan 2 achieved even greater reductions, with pressure drops lowered by 45% and WSS reduced to 2.54 Pa under high flow rates. Localized flow disturbances, such as uneven airflow distribution among lung lobes, were also alleviated post-surgery. In the diseased airway, the right lower lobe received up to 40% of the total flow, causing severe imbalances. Surgical Plan 2 achieved the most uniform distribution, with all lobes receiving 13%-29% of airflow across all flow rates, ensuring effective oxygenation and minimizing risks of overdistension or under-perfusion. These findings suggest that the CFD-based approach employed in this study can effectively model surgical outcomes, providing surgeons with a fast, detailed, and non-invasive tool for tailoring procedures to individual patient needs. 

Point-Based Neural Rendering (PBNR) is emerging as a promising class of rendering techniques, which are permeating all aspects of society, driven by a growing demand for real-time, photorealistic rendering in AR/VR and digital twins. Achieving real-time PBNR on mobile devices is challenging. This paper proposes MetaSapiens, a PBNR system that for the first time delivers real-time neural rendering on mobile devices while maintaining human visual quality. MetaSapiens combines three techniques. First, we present an efficiencyaware pruning technique to optimize rendering speed. Second, we introduce a Foveated Rendering (FR) method for PBNR, leveraging humans’ low visual acuity in peripheral regions to relax rendering quality and improve rendering speed. Finally, we propose an accelerator design for FR, addressing the load imbalance issue in (FR-based) PBNR. Our evaluation shows that our system achieves an order of magnitude speedup over existing PBNR models without sacrificing subjective visual quality, as confirmed by a user study. The code and demo are available at: https://horizonlab.org/metasapiens/.