Experiments on vibrated fluids confined in cylindrical and cuboidal containers were performed under the reduced gravity conditions of a parabolic flight. The results constitute a systematic quantitative investigation of the vibroequilibria effect, which refers to the reorientation of vibrated fluids in response to the inhomogeneous oscillatory velocity field and the accompanying dynamic pressure. This effect is amplified in microgravity where the restoring force of gravity is small or absent. Here the vibrations are transmitted via a pair of piezoelectric ceramics and a cantilever beam, excited in a resonant mode. The first and second resonances exhibit different types of motion and lead to different types of vibroequilibria surfaces, one with a dip or crater in the interior and the other flattened compared to the unforced reference experiment. The general tendency for interfaces to orient more perpendicular, on average, to the vibrational axis is confirmed. In the case of water in a cuboidal container, a quantitative comparison is made with vibroequilibria theory and with direct simulations of the Navier-Stokes equations. The good agreement confirms the predictions of vibroequilibria theory and suggests the capacity of this phenomenon to manipulate and position fluids in space environments through the choice of frequency and resonant mode.

Motivated by the challenges of uncertainty quantification for coarse-grained (CG) molecular dynamics, we investigate the role of perturbation theory in model reduction of classical systems. In particular, we consider the task of coarse-graining rigid bodies in the context of generalized multipole potentials that have controllable levels of accuracy relative to their atomistic counterparts. We show how the multipole framework yields a hierarchy of models that systematically connects a CG “point molecule” approximation to the exact dynamics. We use these results to understand when and how the CG models fail to describe atomistic dynamics at the trajectory level and develop asymptotic error estimates for approximate molecular potential energies. Implications for other model-reduction strategies are also discussed. Key findings of this work are that (i) omitting rotational energy introduces significant error when coarse-graining and (ii) attention to symmetry can improve accuracy of “point-molecule” approximations. Analytical derivations and numerical results support these conclusions. Relevance to nonrigid bodies is also discussed.

How long does a diffusing molecule spend in a close vicinity of a confining boundary or a catalytic surface? This quantity is determined by the boundary local time, which plays thus a crucial role in the description of various surface-mediated phenomena, such as heterogeneous catalysis, permeation through semipermeable membranes, or surface relaxation in nuclear magnetic resonance. In this paper, we obtain the probability distribution of the boundary local time in terms of the spectral properties of the Dirichlet-to-Neumann operator. We investigate the short-time and long-time asymptotic behaviors of this random variable for both bounded and unbounded domains. This analysis provides complementary insights onto the dynamics of diffusing molecules near partially reactive boundaries.

We present an exponential mode analysis of the dynamical processes determining the time behavior of the Kubo velocity autocorrelation function (KVAF) of fluid para-${\mathrm{H}}_2$, as obtained by ring polymer molecular dynamics simulations at various fluid densities. The mechanisms contributing to the decay of the KVAF are thoroughly characterized at a slightly supercritical temperature, in a density interval ranging from the critical point to the fluid-solid transition. We show that the quantum nature of the system does not influence the specific phenomena and decay channels through which a loss in velocity correlation takes place, since these are the same as found in classical fluids. Similarly, a dynamical crossover is observed with increasing density, signaling the onset of a transverse-like dynamics like in classical systems. We also investigate the effect of density on the processes contributing to the most relevant property of a quantum fluid, namely, the large values of the total and zero-point kinetic energy arising through the Heisenberg uncertainty principle.

We develop a framework based on discrete-time Markov chains (MCs) to model the Brazilian air transport market networks. Our results suggest that in this market, economic activity explains the centralities of the airports and the players' choices. Periods of economic prosperity affect the air transport networks and they move from a hub-and-spoke topology towards a mixed point-to-point and hub-and-spoke topology. Furthermore, we use the MC transition and stationary probabilities to build geographical subgraphs that reveal (1) the most important routes, (2) the stability of these routes, (3) the most important flights, and (4) the airlines' specific market niches.

The analysis and characterization of human mobility using population-level mobility models is important for numerous applications, ranging from the estimation of commuter flows in cities to modeling trade flows between countries. However, almost all of these applications have focused on large spatial scales, which typically range between intracity scales and intercountry scales. In this paper, we investigate population-level human mobility models on a much smaller spatial scale by using them to estimate customer mobility flow between supermarket zones. We use anonymized, ordered customer-basket data to infer empirical mobility flow in supermarkets, and we apply variants of the gravity and intervening-opportunities models to fit this mobility flow and estimate the flow on unseen data. We find that a doubly-constrained gravity model and an extended radiation model (which is a type of intervening-opportunities model) can successfully estimate 65%–70% of the flow inside supermarkets. Using a gravity model as a case study, we then investigate how to reduce congestion in supermarkets using mobility models. We model each supermarket zone as a queue, and we use a gravity model to identify store layouts with low congestion, which we measure either by the maximum number of visits to a zone or by the total mean queue size. We then use a simulated-annealing algorithm to find store layouts with lower congestion than a supermarket's original layout. In these optimized store layouts, we find that popular zones are often in the perimeter of a store. Our research gives insight both into how customers move in supermarkets and into how retailers can arrange stores to reduce congestion. It also provides a case study of human mobility on small spatial scales.

This paper continues the series of our works devoted to the liquid-gel phase transition in lipid membranes. Previously we described a variation of area per lipid, membrane thickness, and diffusion coefficient at the temperature-driven liquid-gel phase transition in bilayers. Here we expand the application of our analytic model approach to include a description of the lipid tilt and also extend the investigation to include Langmuir and self-assembled monolayers. The theory describes tilt formation at the temperature-driven liquid-gel phase transition in bilayers and the pressure-driven phase transition in Langmuir monolayers. Neither uniform tilt nor liquid-gel phase transition is found in self-assembled monolayers chemically bonded to the substrate.

The mechanisms of atrial fibrillation (AF) are poorly understood, resulting in disappointing success rates of ablative treatment. Different mechanisms defined largely by different atrial activation patterns have been proposed and, arguably, this dispute has slowed the progress of AF research. Recent clinical evidence suggests a unifying mechanism of local drivers based on sustained reentrant circuits in the complex atrial architecture. Here, we present a percolation inspired computational model showing spontaneous emergence of AF that strongly supports, and gives a theoretical explanation for, the clinically observed diversity of activation. We show that the difference in surface activation patterns is a direct consequence of the thickness of the discrete network of heart muscle cells through which electrical signals percolate to reach the imaged surface. The model naturally follows the clinical spectrum of AF spanning sinus rhythm, paroxysmal AF, and persistent AF as the decoupling of myocardial cells results in the lattice approaching the percolation threshold. This allows the model to make the prediction that, for paroxysmal AF, reentrant circuits emerge near the endocardium, but in persistent AF they emerge deeper in the bulk of the atrial wall. If experimentally verified, this may go towards explaining the lowering ablation success rate as AF becomes more persistent.

In contrast with the conventionally observed mechanism of stochastic resonance (SR) wherein the level of additive noise is systematically varied with a fixed set-point parameter, in this work we report the emergence of the SR phenomena in an electrochemical system maintaining the same level of noise and varying the parametric distance from a homoclinic bifurcation inherent to the system. The experimental system involves the corrosion of a metal disk in an acidic medium under potentiostatic conditions. The applied potential is used as a control parameter and the anodic current generated during the electrodissolution of the metal is the accessible system variable. In the presence of noise, it was observed that the system was able to enhance its output's fidelity with a weak subthreshold input signal when the set point was kept at an optimal parametric distance from the bifurcation. Numerical simulations were performed on a model for this system to corroborate the experimental observations. This type of SR may be critical in scenarios where a biological entity has control only on its sensory parameters and not on the environmental noise amplitude.

Thermal management has made considerable progress in the past decade for the emerging field of thermal metamaterials. However, two severe problems still handicap the development of thermal metamaterials. That is, thermal conductivities should be singular and uncommon as required by corresponding theories. To solve these problems, here we establish the theory of dipole-assisted thermotics. By tailoring the thermal dipole moment, thermal invisibility can be achieved without the requirements of singular and uncommon thermal conductivities. Furthermore, finite-element simulations and laboratory experiments both validate the theoretical analyses. The performance of the dipole-driven scheme is excellent in both two and three dimensions, and in both steady and transient states. Dipole-assisted thermotics not only offers a distinct mechanism to achieve thermal invisibility, but also has potential applications in thermal management such as infrared signature reduction, thermal protection, and infrared camouflage.

In this article, we revisit random site and bond percolation in a square lattice, focusing primarily on the behavior of entropy and the order parameter. In the case of traditional site percolation, we find that both the quantities are zero at $p=0$, revealing that the system is in the perfectly ordered and in the disordered state at the same time. Moreover, we find that entropy with $1-p$, which is the equivalent counterpart of temperature, first increases and then decreases again, but we know that entropy with temperature cannot decrease. However, bond percolation does not suffer from either of these two problems. To overcome this, we propose an alternative definition for site percolation where we occupy sites to connect bonds and we measure cluster size by the number of bonds connected by occupied sites. This resolves all the problems without affecting any of the existing known results.

Combinatorial analysis of a certain abstraction of RNA structures has been studied to investigate their statistics. Our approach regards the backbone of secondary structures as an alternate sequence of paired and unpaired sets of nucleotides, which can be described by a random matrix model. We obtain the generating function of the structures using the Hermitian matrix model with the Chebyshev polynomial of the second kind and analyze the statistics with respect to the number of stems. To match the experimental findings of the statistical behavior, we consider the structures in a grand canonical ensemble and find a fugacity value corresponding to an appropriate number of stems.

We investigate the phase transition properties of the polymer-Potts model, a chain composed of monomers with magnetic degrees of freedom, with the motivation to study the conformation and mark switching dynamics of chromatin. By the mean-field approximation, we find that the phase transition between the swollen-disordered state and the compact-ordered state is discrete; it is first order as in the long-range Potts model, but with a significantly larger jump in magnetization (i.e., mark coherence) upon the ordering transition. The results imply how small changes in epigenetic writer concentrations can lead to a macroscopic switching of the chromatin state, suggesting a simple mechanism of discrete switching observed, for instance, in cell differentiation.

In contrast to conservative systems, in nonlinear media with gain and loss the dynamics of localized topological structures exhibit many unique features that can be controlled externally. We propose a robust mechanism to perform topological transformations changing characteristics of dissipative vortices and their complexes in a controllable way. We show that a properly chosen potential carries out the evolution of dissipative structures to regime with spontaneous transformation of the topological excitations or drives generation of vortices with control over the topological charge.

The dynamics of chaotic Hamiltonian systems such as the kicked rotor continues to guide our understanding of transport and localization processes. The localized states of the quantum kicked rotor decay due to decoherence effects if subjected to noise. The associated quantum diffusion increases monotonically as a function of a parameter characterizing the noise distribution. In this Rapid Communication, for the atom-optics Lévy kicked rotor, the quantum diffusion displays nonmonotonic behavior as a function of a parameter characterizing the Lévy distribution. The optimal diffusion rates are experimentally obtained using an ultracold cloud of rubidium atoms in a pulsed optical lattice. The parameters for optimal diffusion rates are obtained analytically and show a good agreement with our experimental and numerical results. The nonmonotonicity is shown to be a quantum effect that vanishes in the classical limit.

Social dilemmas are situations wherein individuals choose between selfish interest and common good. One example of this is the vaccination dilemma, in which an individual who vaccinates at a cost protects not only himself but also others by helping maintain a common good called herd immunity. There is, however, a strong incentive to forgo vaccination, thus avoiding the associated cost, all the while enjoying the protection of herd immunity. To analyze behavioral incentives in a vaccination-dilemma setting in which an optional treatment is available to infected individuals, we combined epidemiological and game-theoretic methodologies by coupling a disease-spreading model with treatment and an evolutionary decision-making model. Extensive numerical simulations show that vaccine characteristics are more important in controlling the treatment adoption than the cost of treatment itself. The main effect of the latter is that expensive treatment incentivizes vaccination, which somewhat surprisingly comes at a little cost to society. More surprising is that the margin for a true synergy between vaccine and treatment in reducing the final epidemic size is very small. We furthermore find that society-centered decision making helps protect herd immunity relative to individual-centered decision making, but the latter may be better in establishing a novel vaccine. These results point to useful policy recommendations as well as to intriguing future research directions.

We reduce a one-dimensional model of an active segment (AS), which is used, for instance, in the description of contraction-driven cell motility, to a zero-dimensional model of an active particle (AP) characterized by two internal degrees of freedom: position and polarity. Both models give rise to hysteretic force-velocity relations showing that an active agent can support two opposite polarities under the same external force and that it can maintain the same polarity while being dragged by external forces with opposite orientations. This double bistability results in a rich dynamic repertoire which we illustrate by studying static, stalled, motile, and periodically repolarizing regimes displayed by an active agent confined in a viscoelastic environment. We show that the AS and AP models can be calibrated to generate quantitatively similar dynamic responses.

In this work we studied the differences in flight kinematics and aerodynamics that could relate to differences in wing morphologies of a dragonfly and a damselfly. The damselflies and dragonflies normally fly with the fore wing or hind wing in the lead, respectively. The wing of the damselfly is petiolate, which means that the wing root is narrower than that of the dragonfly. The influence of the biological morphology between the damselfly and the dragonfly on their hovering strategies is worthy of clarification. The flight motions of damselflies and dragonflies in hovering were recorded with two high-speed cameras; we analyzed the differences between their hovering motions using computational fluid dynamics. The distinct mechanisms of the hovering flight of damselflies (Matrona cyanoptera) and dragonflies (Neurothemis ramburii) with different phase lags between fore and hind wings were deduced. The results of a comparison of the differences of wing phases in hovering showed that the rotational effect has an important role in the aerodynamics; the interactions between fore and hind wings greatly affect their vortex structure and flight performance. The wake of a damselfly sheds smoothly because of slender petiolation; a vertical force is generated steadily during the stage of wing translation. Damselflies hover with a longer translational phase and a larger flapping amplitude. In contrast, the root vortex of a dragonfly impedes the shedding of wake vortices in the upstroke, which results in the loss of a vertical force; the dragonfly hence hovers with a large amplitude of wing rotation. These species of Odonata insects developed varied hovering strategies to fit their distinct biological morphologies.