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  1. Upside-down jellyfish, Cassiopea , are prevalent in warm and shallow parts of the oceans throughout the world. They are unique among jellyfish in that they rest upside down against the substrate and extend their oral arms upwards. This configuration allows them to continually pull water along the substrate, through their oral arms, and up into the water column for feeding, nutrient and gas exchange, and waste removal. Although the hydrodynamics of the pulsation of jellyfish bells has been studied in many contexts, it is not clear how the presence or absence of the substrate alters the bulk flow patterns generated by Cassiopea medusae. In this paper, we use three-dimensional (3D) particle tracking velocimetry and 3D immersed boundary simulations to characterize the flow generated by upside-down jellyfish. In both cases, the oral arms are removed, which allows us to isolate the effect of the substrate. The experimental results are used to validate numerical simulations, and the numerical simulations show that the presence of the substrate enhances the generation of vortices, which in turn augments the upward velocities of the resulting jets. Furthermore, the presence of the substrate creates a flow pattern where the water volume within the bell is ejected withmore »each pulse cycle. These results suggest that the positioning of the upside-down jellyfish such that its bell is pressed against the ocean floor is beneficial for augmenting vertical flow and increasing the volume of water sampled during each pulse.« less
    Free, publicly-accessible full text available May 12, 2023
  2. null (Ed.)
    Understanding the dynamics of the spread of COVID-19 between connected communities is fundamental in planning appropriate mitigation measures. To that end, we propose and analyze a novel metapopulation network model, particularly suitable for modeling commuter traffic patterns, that takes into account the connectivity between a heterogeneous set of communities, each with its own infection dynamics. In the novel metapopulation model that we propose here, transport schemes developed in optimal transport theory provide an efficient and easily implementable way of describing the temporary population redistribution due to traffic, such as the daily commuter traffic between work and residence. Locally, infection dynamics in individual communities are described in terms of a susceptible-exposed-infected-recovered (SEIR) compartment model, modified to account for the specific features of COVID-19, most notably its spread by asymptomatic and presymptomatic infected individuals. The mathematical foundation of our metapopulation network model is akin to a transport scheme between two population distributions, namely the residential distribution and the workplace distribution, whose interface can be inferred from commuter mobility data made available by the US Census Bureau. We use the proposed metapopulation model to test the dynamics of the spread of COVID-19 on two networks, a smaller one comprising 7 counties in themore »Greater Cleveland area in Ohio, and a larger one consisting of 74 counties in the Pittsburgh–Cleveland–Detroit corridor following the Lake Erie’s American coastline. The model simulations indicate that densely populated regions effectively act as amplifiers of the infection for the surrounding, less densely populated areas, in agreement with the pattern of infections observed in the course of the COVID-19 pandemic. Computed examples show that the model can be used also to test different mitigation strategies, including one based on state-level travel restrictions, another on county level triggered social distancing, as well as a combination of the two.« less
  3. Synopsis Metachronal motion is used across a wide range of organisms for a diverse set of functions. However, despite its ubiquity, analysis of this behavior has been difficult to generalize across systems. Here we provide an overview of known commonalities and differences between systems that use metachrony to generate fluid flow. We also discuss strategies for standardizing terminology and defining future investigative directions that are analogous to other established subfields of biomechanics. Finally, we outline key challenges that are common to many metachronal systems, opportunities that have arisen due to the advent of new technology (both experimental and computational), and next steps for community development and collaboration across the nascent network of metachronal researchers.
  4. For organisms to have robust locomotion, their neuromuscular organization must adapt to constantly changing environments. In jellyfish, swimming robustness emerges when marginal pacemakers fire action potentials throughout the bell’s motor nerve net, which signals the musculature to contract. The speed of the muscle activation wave is dictated by the passage times of the action potentials. However, passive elastic material properties also influence the emergent kinematics, with time scales independent of neuromuscular organization. In this multimodal study, we examine the interplay between these two time scales during turning. A three-dimensional computational fluid–structure interaction model of a jellyfish was developed to determine the resulting emergent kinematics, using bidirectional muscular activation waves to actuate the bell rim. Activation wave speeds near the material wave speed yielded successful turns, with a 76-fold difference in turning rate between the best and worst performers. Hyperextension of the margin occurred only at activation wave speeds near the material wave speed, suggesting resonance. This hyperextension resulted in a 34-fold asymmetry in the circulation of the vortex ring between the inside and outside of the turn. Experimental recording of the activation speed confirmed that jellyfish actuate within this range, and flow visualization using particle image velocimetry validated the correspondingmore »fluid dynamics of the numerical model. This suggests that neuromechanical wave resonance plays an important role in the robustness of an organism’s locomotory system and presents an undiscovered constraint on the evolution of flexible organisms. Understanding these dynamics is essential for developing actuators in soft body robotics and bioengineered pumps.

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  5. Current quantum computer designs will not scale. To scale beyond small prototypes, quantum architectures will likely adopt a modular approach with clusters of tightly connected quantum bits and sparser connections between clusters. We exploit this clustering and the statically-known control flow of quantum programs to create tractable partitioning heuristics which map quantum circuits to modular physical machines one time slice at a time. Specifically, we create optimized mappings for each time slice, accounting for the cost to move data from the previous time slice and using a tunable lookahead scheme to reduce the cost to move to future time slices. We compare our approach to a traditional statically-mapped, owner-computes model. Our results show strict improvement over the static mapping baseline. We reduce the non-local communication overhead by 89.8% in the best case and by 60.9% on average. Our techniques, unlike many exact solver methods, are computationally tractable.
  6. We initiate a fine-grained study of the round complexity of Oblivious RAM (ORAM). We prove that any one-round balls-in-bins ORAM that does not duplicate balls must have either 𝛺(𝑁‾‾√) bandwidth or 𝛺(𝑁‾‾√) client memory, where N is the number of memory slots being simulated. This shows that such schemes are strictly weaker than general (multi-round) ORAMs or those with server computation, and in particular implies that a one-round version of the original square-root ORAM of Goldreich and Ostrovksy (J. ACM 1996) is optimal. We prove this bound via new techniques that differ from those of Goldreich and Ostrovksy, and of Larsen and Nielsen (CRYPTO 2018), which achieved an 𝛺(log𝑁) bound for balls-in-bins and general multi-round ORAMs respectively. Finally we give a weaker extension of our bound that allows for limited duplication of balls, and also show that our bound extends to multiple-round ORAMs of a restricted form that include the best known constructions.
  7. Body size is a key functional trait that is predicted to decline under warming. Warming is known to cause size declines via phenotypic plasticity, but evolutionary responses of body size to warming are poorly understood. To test for warming-induced evolutionary responses of body size and growth rates, we used populations of mosquitofish ( Gambusia affinis ) recently established (less than 100 years) from a common source across a strong thermal gradient (19–33°C) created by geothermal springs. Each spring is remarkably stable in temperature and is virtually closed to gene flow from other thermal environments. Field surveys show that with increasing site temperature, body size distributions become smaller and the reproductive advantage of larger body size decreases. After common rearing to reveal recently evolved trait differences, warmer-source populations expressed slowed juvenile growth rates and increased reproductive effort at small sizes. These results are consistent with an adaptive basis of the plastic temperature–size rule, and they suggest that temperature itself can drive the evolution of countergradient variation in growth rates. The rapid evolution of reduced juvenile growth rates and greater reproduction at a small size should contribute to substantial body downsizing in populations, with implications for population dynamics and for ecosystems inmore »a warming world.« less