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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/. 

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. 

Miniaturized fluorescence microscopes (miniscopes) enable imaging of calcium events from a large population of neurons in freely behaving animals. Traditionally, miniscopes have only been able to record from a single fluorescence wavelength. Here, we present an open-source dual-channel miniscope that simultaneously records two wavelengths in freely behaving animals. To enable simultaneous acquisition of two fluorescent wavelengths, we incorporated two CMOS sensors into a single miniscope. To validate our dual-channel miniscope, we imaged hippocampal CA1 region that co-expressed a dynamic calcium indicator (GCaMP) and a static nuclear signal (dTomato) while mice ran on a linear track. Our results suggest that, even when neurons were registered across days using dTomato signals, hippocampal spatial coding changes over time. In conclusion, our dual-channel miniscope enables imaging of two fluorescence wavelengths with minimal cross-talk between the two channels, opening the doors to a multitude of previously inaccessible experimental possibilities. 

Abstract We find the scaling limits of a general class of boundary-to-boundary connection probabilities and multiple interfaces in the critical planar FK-Ising model, thus verifying predictions from the physics literature. We also discuss conjectural formulas using Coulomb gas integrals for the corresponding quantities in general critical planar random-cluster models with cluster-weight$${q \in [1,4)}$$ $q\in [1,4)$. Thus far, proofs for convergence, including ours, rely on discrete complex analysis techniques and are beyond reach for other values ofqthan the FK-Ising model ($$q=2$$ $q=2$). Given the convergence of interfaces, the conjectural formulas for other values ofqcould be verified similarly with relatively minor technical work. The limit interfaces are variants of$$\text {SLE}_\kappa $$ ${\text{SLE}}_{\kappa }$curves (with$$\kappa = 16/3$$ $\kappa =16/3$for$$q=2$$ $q=2$). Their partition functions, that give the connection probabilities, also satisfy properties predicted for correlation functions in conformal field theory (CFT), expected to describe scaling limits of critical random-cluster models. We verify these properties for all$$q \in [1,4)$$ $q\in [1,4)$, thus providing further evidence of the expected CFT description of these models.