Phase-field-crystal (PFC) models constitute a field theoretical approach to solidification, melting, and related phenomena at atomic length and diffusive time scales. One of the advantages of these models is that they naturally contain elastic excitations associated with strain in crystalline bodies. However, instabilities that are diffusively driven towards equilibrium are often orders of magnitude slower than the dynamics of the elastic excitations, and are thus not included in the standard PFC model dynamics. We derive a method to isolate the time evolution of the elastic excitations from the diffusive dynamics in the PFC approach and set up a two-stage process, in which elastic excitations are equilibrated separately. This ensures mechanical equilibrium at all times. We show concrete examples demonstrating the necessity of the separation of the elastic and diffusive time scales. In the small-deformation limit this approach is shown to agree with the theory of linear elasticity.

Molecular dynamics simulations of the Lennard-Jones model are used to study phase transitions at a smooth surface. Our motivation is the observation that the existence of an attractive wall facilitates crystallization. To investigate how this wall influences phase transitions, the strength of wall-particle interaction is varied in our studies. We find that the phase behavior depends on the strength parameter α, i.e., the ratio between wall-particle and the particle-particle attraction strength. Three critical values of the ratio, namely, ${\alpha }_p$, ${\alpha }_w$, and ${\alpha }_c$, are used to define the qualitative nature of the phase behaviors at a smooth surface. Some interesting phenomena due to the increase of α are observed. First, a set of close-packed planes, i.e., $\left\{111\right\}$ planes in fcc structures or $\left\{0001\right\}$ planes in hcp structures, are “rotated” from intersecting to parallel to the wall when α = ${\alpha }_p$; second, the layering phase transition close to the wall antecedes that of the bulk when α = ${\alpha }_w$. Finally, the first-order phase transition in the first two layers is supplanted by a continuous phase transition when α = ${\alpha }_{\mathrm{c}}$, which to some extent can be treated as a quasi-two-dimensional process. We find that bulk freezing always discontinuously occurs through a first-order phase transition, and seems to be isolated from the freezing process occurring close to the attractive surfaces. Moreover, during the heating process, we observe minimal dependence at a strongly attractive surface.

Turnover is a typical intermittent body movement while asleep. Exploring its behavior may provide insights into the mechanisms and management of sleep. However, little is understood about the dynamic nature of turnover in healthy humans and how it can be modified in disease. Here we present a detailed analysis of turnover signals that are collected by accelerometry from healthy elderly subjects and age-matched patients with neurodegenerative disorders such as Parkinson's disease. In healthy subjects, the time intervals between consecutive turnover events exhibit a well-separated bimodal distribution with one mode at ⩽10 s and the other at ⩾100 s, whereas such bimodality tends to disappear in neurodegenerative patients. The discovery of bimodality and fine temporal structures (⩽10 s) is a contribution that is not revealed by conventional sleep recordings with less time resolution (≈30 s). Moreover, we estimate the scaling exponent of the interval fluctuations, which also shows a clear difference between healthy subjects and patients. We incorporate these experimental results into a computational model of human decision making. A decision is to be made at each simulation step between two choices: to keep on sleeping or to make a turnover, the selection of which is determined dynamically by comparing a pair of random numbers assigned to each choice. This decision is weighted by a single parameter that reflects the depth of sleep. The resulting simulated behavior accurately replicates many aspects of observed turnover patterns, including the appearance or disappearance of bimodality and leads to several predictions, suggesting that the depth parameter may be useful as a quantitative measure for differentiating between normal and pathological sleep. These findings have significant clinical implications and may pave the way for the development of practical sleep assessment technologies.

We study in detail the cooperative action of small groups of KIF1A motors in its monomeric (single-headed) form within an arrangement relevant to vesicle traffic or membrane tube extraction. It has been recently shown that under these circumstances, the presence of a finite dwell time in the motor cycle contributes to remarkably enhance collective force generation [D. Oriola and J. Casademunt, Phys. Rev. Lett. 111, 048103 (2013)]. We analyze this mechanism in detail by means of a two-state noise-driven ratchet model with hard-core repulsive interactions. We obtain staircase-shaped velocity-force curves and show that motors self-organize in clusters with a nontrivial force distribution that conveys a large part of the load to the central motors. Under heavy loads, large clusters adopt a synchronic mode of totally asymmetric steps. We also find a dramatic increase of the collective efficiency with the number of motors. Finally, we complete the study by addressing different interactions that impose spatial constraints such as rigid coupling and raft-induced confinement. Our results reinforce the hypothesis that the specificity of KIF1A to axonal vesicular transport may be deeply related to its high cooperativity.

Diffusive processes on nonplanar substrates are deeply relevant for cellular function and transport and increasingly used to probe and characterize the behavior of proteins in membranes. We present analytical and numerical analyses of in-plane diffusion of discrete particles on curved geometries reflecting various generic motifs in biology and explore, in particular, the effect that the shape of the substrate has on the characteristic time scales of diffusive processes. To this end, we consider both collective measures (the relaxation of concentration profiles towards equilibrium) and single-particle measures (escape rates and first passage times of individual diffusing molecules): the first relevant for the correct interpretation of FRAP experiments in curved environments; the second, for single-particle tracking probes. Each of these measures is sensitively affected by the morphology of the substrate, and we find that the exit rate out of a domain is not uniquely set by the size of its boundary, illustrating the general principle we reveal: By varying the shape of a substrate, Nature can control the diffusive time scales in a microenvironment without changing the bare substrate properties.

We study the conditions under which species interaction, as described by continuous versions of the competitive Lotka-Volterra model (namely the nonlocal Kolmogorov-Fisher model, and its differential approximation), can support the existence of localized states, i.e., patches of species with enhanced population surrounded in niche space by species at smaller densities. These states would arise from species interaction, and not by any preferred niche location or better fitness. In contrast to previous works we include only quadratic nonlinearities, so that the localized patches appear on a background of homogeneously distributed species coexistence, instead of on top of the no-species empty state. For the differential model we find and describe in detail the stable localized states. For the full nonlocal model, however, competitive interactions alone do not allow the conditions for the observation of self-localized states, and we show how the inclusion of additional facilitative interactions leads to the appearance of them.

The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

Many studies have shown that we can gain additional information on time series by investigating their accompanying complex networks. In this work, we investigate the fundamental topological and fractal properties of recurrence networks constructed from fractional Brownian motions (FBMs). First, our results indicate that the constructed recurrence networks have exponential degree distributions; the average degree exponent $\langle \lambda \rangle$ increases first and then decreases with the increase of Hurst index $H$ of the associated FBMs; the relationship between $H$ and $\langle \lambda \rangle$ can be represented by a cubic polynomial function. We next focus on the motif rank distribution of recurrence networks, so that we can better understand networks at the local structure level. We find the interesting superfamily phenomenon, i.e., the recurrence networks with the same motif rank pattern being grouped into two superfamilies. Last, we numerically analyze the fractal and multifractal properties of recurrence networks. We find that the average fractal dimension $\langle d_B\rangle$ of recurrence networks decreases with the Hurst index $H$ of the associated FBMs, and their dependence approximately satisfies the linear formula $\langle d_B\rangle \approx 2-H$, which means that the fractal dimension of the associated recurrence network is close to that of the graph of the FBM. Moreover, our numerical results of multifractal analysis show that the multifractality exists in these recurrence networks, and the multifractality of these networks becomes stronger at first and then weaker when the Hurst index of the associated time series becomes larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst index $H=0.5$ possesses the strongest multifractality. In addition, the dependence relationships of the average information dimension $\langle D\left(1\right)\rangle$ and the average correlation dimension $\langle D\left(2\right)\rangle$ on the Hurst index $H$ can also be fitted well with linear functions. Our results strongly suggest that the recurrence network inherits the basic characteristic and the fractal nature of the associated FBM series.

A dynamical model of the Swift-Hohenberg type is proposed to describe the formation of twelvefold quasipattern as observed, for instance, in optical systems. The model incorporates the general mechanisms leading to quasipattern formation and does not need external forcing to generate them. Besides quadratic nonlinearities, the model takes into account an angular dependence of the nonlinear couplings between spatial modes with different orientations. Furthermore, the marginal stability curve presents other local minima than the one corresponding to critical modes, as usual in optical systems. Quasipatterns form when one of these secondary minima may be associated with harmonics built on pairs of critical modes. The model is analyzed numerically and in the framework of amplitude equations. The results confirm the importance of harmonics to stabilize quasipatterns and assess the applicability of the model to other systems with similar generic properties.

By applying an out-of-phase actuation at the boundaries of a uniform chain of granular particles, we demonstrate experimentally that time-periodic and spatially localized structures with a nonzero background (so-called dark breathers) emerge for a wide range of parameter values and initial conditions. We demonstrate a remarkable control over the number of breathers within the multibreather pattern that can be “dialed in” by varying the frequency or amplitude of the actuation. The values of the frequency (or amplitude) where the transition between different multibreather states occurs are predicted accurately by the proposed theoretical model, which is numerically shown to support exact dark breather and multibreather solutions. Moreover, we visualize detailed temporal and spatial profiles of breathers and, especially, of multibreathers using a full-field probing technology and enable a systematic favorable comparison among theory, computation, and experiments. A detailed bifurcation analysis reveals that the dark and multibreather families are connected in a “snaking” pattern, providing a roadmap for the identification of such fundamental states and their bistability in the laboratory.

This paper investigates the dynamics of the Townsend discharge in nitrogen in narrow gaps. To provide stability of discharge in a broad range of current, we apply a plane-parallel structure, one of the electrodes of which is made of a high-resistivity gallium arsenide. The results of experiments are analyzed in the framework of theory [Yu. P. Raizer et al., Tech. Phys. 51, 185 (2006)], which considers the dynamics of discharge in short nitrogen-filled gaps of similar structures. According to the theory, a key parameter of discharge dynamics is time $\vartheta$ that defines the rate of discharge response to perturbations. In our work, time $\vartheta$ is experimentally found by analyzing the noise spectrum of the discharge glow in the stable and spatially uniform state of the structure. This characteristic time depends linearly on the discharge gap width, which corroborates conclusions based on the standard model of Townsend discharge. However, its values are substantially shorter compared to those predicted by theory. The relationship between $\vartheta$ and experimentally observed critical current density for the oscillatory instability, $j_{\text{cr}}$, is applied to find the discharge negative differential resistance for a set of parameters of the discharge gap.

This paper deals with the solution of the spherically symmetric time-dependent Hartree-Fock approximation applied to nuclear giant monopole resonances in the small amplitude regime. The problem is spatially unbounded as the resonance state is in the continuum. The practical requirement to perform the calculation in a finite-sized spatial region yields an artificial boundary, which is not present physically. The question of how to ensure the boundary does not interfere with the internal solution, while keeping the overall calculation time low is studied. Here we propose an absorbing boundary condition scheme to handle the conflict. The derivation, via a Laplace transform method, and implementation is described. An inverse Laplace transform required by the absorbing boundaries is calculated using a method of nonlinear least squares. The accuracy and efficiency of the scheme is tested and results presented to support the case that they are an effective way of handling the artificial boundary.

A solid-fluid boundary condition for the lattice Boltzmann (LB) method, which retains the simplicity of the bounce-back method and leads to positive definite populations similar to the diffusive boundary condition, is presented. As a refill algorithm, it is proposed that quasi-equilibrium distributions be used to model distributions at fluid nodes uncovered due to solid movement. The method is tested for flow past an impulsively started cylinder and demonstrates considerable enhancement in the accuracy of the unsteady force calculation at moderate and high Reynolds numbers. Furthermore, via simulations, we show that momentum exchange procedure used in LB to compute forces is not Galilean invariant. A modified momentum exchange procedure is proposed to reduce the errors due to violation of Galilean invariance.

The translocation time of a polymer through a pore under the influence of an external field depends on a number of parameters, the most important of which are the field strength, the interaction with the pore, and the confinement entropy. Experimentally, the translocation is dominated either by the driving force (electrophoretic regime) or by the entropy of confinement or pore interaction (barrier dominated regime). In this Rapid Communication we study a simple model for polymer translocation, loosely based on the asymmetric exclusion process, which shows that it is possible to have what experimentally would be interpreted as barrier dominated, even where there is no barrier to translocation. This effective barrier is interpreted as being due to collaborative effects between the monomers forming the polymer chain.

We study the dynamics of the nematic liquid crystal kickback effect upon removal of a primary electric field and its amplification by a perpendicular secondary electric field resulting in the formation of domains with a reverse director orientation. Using computational fluid dynamics, we show that the domain formation is a robust phenomenon that takes place also in the complex case of multiple irregular random Freedericksz domains in three dimension as they appear in a realistic experimental situation. We propose domain switching by kickback amplification as a tool for self-insertion of shell-like inhomogeneities into an otherwise perfectly uniform director field configuration.

The guidance of human sperm cells under confinement in quasi-2D microchambers is investigated using a purely physical method to control their distribution. Transport property measurements and simulations are performed with diluted sperm populations, for which effects of geometrical guidance and concentration are studied in detail. In particular, a trapping transition at convex angular wall features is identified and analyzed. We also show that highly efficient microratchets can be fabricated by using curved asymmetric obstacles to take advantage of the spermatozoa specific swimming strategy.

The Richtmyer-Meshkov instability of interfaces separating elastic-plastic materials from vacuum (heavy-light configuration) is studied by means of computational techniques. A fully Eulerian multimaterial algorithm that solves consistently the Euler equations and the time evolution of the deformations in the material is applied to three distinct materials (copper, aluminum, and stainless steel). If a perfectly plastic constitutive relation is considered, an empirical law is computed that relates the long-term perturbation amplitude of the interface, its maximum growth rate, the initial density, and the yield stress of the material. It is shown that this linear relation can be extended to materials that follow more complex plastic behavior which can account for rate dependency, hardening, and thermal softening, and to situations in which small-perturbation theory is no longer valid. In effect, the yield stress computed from measurements of the long-term amplitude and maximum growth rate closely matches the von Mises stress found at the interface of solid materials for a wide range of cases with different initial parameters.