A swimming microorganism stirs the surrounding fluid, creating a flow field that governs not only its locomotion and nutrient uptake, but also its interactions with other microorganisms and the environment. Despite its fundamental importance, capturing this flow field and unraveling its biological implications remains a challenge. Here, we report direct, time-resolved measurements of the three-dimensional (3D) flow field generated by a single, free-swimming microalga, Chlamydomonas reinhardtii, a model organism for microbial locomotion and flagellar dynamics. Supported by hydrodynamic modeling and simulations, our measurements resolve how established two-dimensional (2D) flow features such as in-plane vortices and the stagnation point emerge from and shape the full algal flow in 3D. Moreover, we reveal unexpected low-Reynolds-number flow phenomena including micron-sized vortex rings and periodically recurring translating vortices and uncover topological changes in the underlying flow structure associated with the puller-to-pusher transition of an alga. Biologically, access to the 3D flow field enables rigorous quantification of the alga’s energy expenditure, as well as its swimming and feeding efficiency, improving the precision of these physiological metrics. Taken together, our study demonstrates rich vortex dynamics in inertialess flows and shows their influence on microbial motility. The work also introduces an experimental method for mapping the fluid environment sculpted by beating flagella.
BACKGROUND:Implicit neural representation (INR), particularly in combination with hash encoding, has recently emerged as a promising approach for computed tomography (CT) image reconstruction. However, directly applying INR techniques to 3D dental cone-beam computed tomography (CBCT) with a truncated field of view (FOV) is challenging. During the training process, if the FOV does not fully encompass the patient's head, a discrepancy arises between the measured projections and the forward projections computed within the truncated domain. This mismatch leads the network to estimate attenuation values inaccurately, producing severe artifacts in the reconstructed images. PURPOSE:This study aims to develop a computationally efficient INR-based reconstruction framework that leverages multi-resolution hash encoding for 3D dental CBCT with a truncated FOV. METHODS:To mitigate truncation artifacts, we train the network over an expanded reconstruction domain that fully encompasses the patient's head. For computational efficiency, we adopt an adaptive training strategy that uses a multi-resolution grid: finer resolution levels and denser sampling inside the truncated FOV, and coarser resolution levels with sparser sampling outside. To maintain consistent input dimensionality of the network across spatially varying resolutions, we introduce an adaptive hash encoder that selectively activates the lower-level features of the hash hierarchy for points outside the truncated FOV. RESULTS:The proposed method with an extended FOV effectively mitigates truncation artifacts. Compared with a naive domain extension, using fixed resolution levels and a fixed sampling rate, the adaptive strategy reduces computational time by 60% for an image volume of 800 × 800 × 600 $800\, \times \, 800\, \times \, 600$ , while preserving the peak signal-to-noise ratio (PSNR) within the truncated FOV. CONCLUSIONS:We propose an INR-based reconstruction framework for 3D dental CBCT with a truncated FOV, effectively reducing truncation artifacts and training cost.
Bacterial swimming is well characterized in uniform liquids at rest. The natural habitat of bacterial swimmers, however, is often dominated by moving fluids and interfaces, resulting in shear flows that may strongly alter bacterial navigation strategies. Here, we study how fluid shear flow affects the swimming motility of the soil bacterium Pseudomonas putida, a bacterial swimmer that moves in a versatile pattern composed of three different swimming modes, where the flagella may push, pull, or wrap around the cell body (multi-mode swimmer). We introduce a computer automated cell tracking and swimming mode detection tool to show that shear induced alignment depends on the swimming mode, while motility and proximity to surfaces counteract the alignment effect. Moreover, filament wrapping becomes less efficient with increasing shear stress. Numerical simulations of realistic swimmer geometries complement our experimental results, providing more detailed mechanistic insights into movement patterns of bacterial swimmers in a shear flow.
It is known that there exist theoretical limits on the mass of compact objects in general relativity. One is the Buchdahl limit for an object with an arbitrary equation-of-state, which turns out to be the limit for an object with a uniform density. Another one is the causal limit that is stronger than the Buchdahl limit and is related to the speed of sound inside an object. Similar theoretical limits on the mass of compact objects in deformed Hořava-Lifshitz (HL) gravity are found in this paper. Interestingly, both the uniform density limit and the sound speed limit curves converge with the horizon curve at its minimum, where a black hole becomes extremal, i.e., M=q, considering the Kehagias-Sfetsos vacuum, which is an asymptotically flat solution in the HL gravity.
Broad mobility restrictions can help control infectious disease spread, but their socioeconomic costs and the variation in transmission risks by mobility purpose, age group, and spatial connectivity highlight the need for targeted approaches. In this study, we developed an age-structured SEIR metapopulation model for COVID-19 across Seoul's 25 districts, integrating mobile phone-derived origin-destination data. We stratified mobility by age (0-19, 20-59, 60+) and purpose: residential (H), school/work (W), and other non-routine (O). Using 2024 mobility data as a baseline and incorporating pandemic-period (2020-2021) mobility deviations, we investigated counterfactual strategies under various targeting scenarios. Our results showed that W restrictions among adults aged 20-59 produced the highest per-capita reductions in infection. Spatial clustering based on population-adjusted W inflows showed that high-inflow central business districts corresponded to the fast-spreading districts identified in the simulations. Targeting W flows into and within this cluster consistently reduced epidemic size across uncertain seeding locations. Furthermore, weekday-inclusive schedules outperformed weekend-only restrictions. Overall, our findings suggest that although citywide restrictions achieve larger reductions, strategically targeting routine school/work mobility among adults aged 20-59 within fast-spreading clusters can provide substantial epidemiological benefits while reducing broader socioeconomic disruption.
