We study the mechanical and thermodynamic properties of different traffic models for kinesin which are relevant in biological and experimental contexts. We find that motor-motor interactions play a fundamental role by enhancing the thermodynamic efficiency at maximum power of the motors, as compared to the noninteracting system, in a wide range of biologically compatible scenarios. We furthermore consider the case where the motor-motor interaction directly affects the internal chemical cycle and investigate the effect on the system dynamics and thermodynamics.

Random fields in nature often have, to a good approximation, Gaussian characteristics. For such fields, the number of maxima and minima are the same. Furthermore, the relative densities of umbilical points, topological defects which can be classified into three types, have certain fixed values. Phenomena described by nonlinear laws can, however, give rise to a non-Gaussian contribution, causing a deviation from these universal values. We consider a random surface, whose height is given by a nonlinear function of a Gaussian field. We find that, as a result of the non-Gaussianity, the density of maxima and minima no longer match and we calculate the relative imbalance between the two. We also calculate the change in the relative density of umbilics. This allows us not only to detect a perturbation, but to determine its size as well. This geometric approach offers an independent way of detecting non-Gaussianity, which even works in cases where the field itself can not be probed directly.

Lévy walks (LWs) are a popular stochastic tool to model anomalous diffusion and have recently been used to describe a variety of phenomena. We study the linear response behavior of this generic model of superdiffusive LWs in finite systems to an external force field under both stationary and nonstationary conditions. These finite-size LWs are based on power-law waiting time distributions with a finite-time regularization at ${\tau }_c$, such that the physical requirements are met to apply linear response theory and derive the power spectrum with the correct short frequency limit, without the introduction of artificial cutoffs. We obtain the generalized Einstein relation for both ensemble and time averages over the entire process time and determine the turnover to normal Brownian motion when the full system is explored. In particular, we obtain an exact expression for the long time diffusion constant as a function of the scaling exponent of the waiting time density and the characteristic time scale ${\tau }_c$.

We investigate generalized potentials for a mean-field density functional theory of a three-phase contact line. Compared to the symmetrical potential introduced in our previous article [Phys. Rev. E 85, 011120 (2012)], the three minima of these potentials form a small triangle located arbitrarily within the Gibbs triangle, which is more realistic for ternary fluid systems. We multiply linear functions that vanish at edges and vertices of the small triangle, yielding potentials in the form of quartic polynomials. We find that a subset of such potentials has simple analytic far-field solutions and is a linear transformation of our original potential. By scaling, we can relate their solutions to those of our original potential. For special cases, the lengths of the sides of the small triangle are proportional to the corresponding interfacial tensions. For the case of equal interfacial tensions, we calculate a line tension that is proportional to the area of the small triangle.

We deduce the mixing-demixing phase diagram for binary liquid mixtures in an electric field for various electrode geometries and arbitrary constitutive relation for the dielectric constant. By focusing on the behavior of the liquid-liquid interface, we produce simple analytic expressions for the dependence of the interface location on experimental parameters. We also show that the phase diagram contains regions where liquid separation cannot occur under any applied field. The analytic expression for the boundary “electrostatic binodal” line reveals that the regions' size and shape depend strongly on the dielectric relation between the liquids. Moreover, we predict the existence of an “electrostatic spinodal” line that identifies conditions where the liquids are in a metastable state. We finally construct the phase diagram for closed systems by mapping solutions onto those of an open system via an effective liquid composition. For closed systems at a fixed temperature and mixture composition, liquid separation occurs in a finite “window” of surface potential (or charge density). Higher potentials or charge densities counterintuitively destroy the interface, leading to liquid mixing. These results give valuable guides for experiments by providing easily testable predictions for how liquids behave in nonuniform electric fields.

We study the role of the control parameter triggering nematic order (temperature or concentration) on the dynamical behavior of a system of nanorods under shear. Our study is based on a set of mesoscopic equations of motion for the components of the tensorial orientational order parameter. We investigate these equations via a systematic bifurcation analysis based on a numerical continuation technique, focusing on spatially homogeneous states. Exploring a wide range of parameters we find, unexpectedly, that states with oscillatory motion can exist even under conditions where the equilibrium system is isotropic. These oscillatory states are characterized by a wagging motion of the paranematic director, and they occur if the tumbling parameter is sufficiently small. We also present full nonequilibrium phase diagrams in the plane spanned by the concentration and the shear rate.

We present a Monte Carlo study of the conformational properties of polymer chains in platelet nanocomposites. We find that high platelet orientation leads to an increase in chain confinement and to a substantial decrease in polymer entropy. The latter may be responsible for the observed aging of these systems in which the platelets gradually lose their orientation with time. As a test of our entropy-driven hypothesis, we suggest that aging could be substantially slowed down by the addition of small spherical nanoparticles. Using a generalized Stokes-Einstein relation, a calculation of the thermal random motion of the platelets predicts a fivefold increase in shear modulus during aging, in agreement with experimental observation on compatibilized layered silicate nanocomposites.

Nonmotile elongated bacteria confined in two-dimensional open microchannels can exhibit collective motion and form dense monolayers with nematic order if the cells proliferate, i.e., grow and divide. Using soft molecular dynamics simulations of a system of rods interacting through short range mechanical forces, we study the effects of the cell growth rate, the cell aspect ratio, and the sliding friction on nematic ordering and on pressure fluctuations in confined environments. Our results indicate that rods with aspect ratios $>$3.0 reach quasiperfect nematic states at low sliding friction. At higher frictions, the global nematic order parameter shows intermittent fluctuations due to sudden losses of order and the time intervals between these bursts are power-law distributed. The pressure transverse to the channel axis can vary abruptly in time and shows hysteresis due to lateral crowding effects. The longitudinal pressure field is on average correlated to nematic order, but it is locally very heterogeneous and its distribution follows an inverse power law, in sharp contrast with nonactive granular systems. We discuss some implications of these findings for tissue growth.

Locomotion in biological systems involves various gaits, and hysteresis appears when the gaits change in accordance with the locomotion speed. That is, the gaits vary at different locomotion speeds depending on the direction of speed change. Although hysteresis is a typical characteristic of nonlinear dynamic systems, the underlying mechanism for the hysteresis in gait transitions remains largely unclear. In this study, we construct a neuromechanical model of an insect and investigate the dynamic characteristics of its gait and gait transition. The simulation results show that our insect model produces metachronal and tripod gaits depending on the locomotion speed through dynamic interactions among the body mechanical system, the nervous system, and the environment in a self-organized manner. They also show that it undergoes the metachronal-tripod gait transition with hysteresis by changing the locomotion speed. We examined the hysteresis mechanism in the metachronal-tripod gait transition of insects from a dynamic viewpoint.

Infection dynamics have been studied extensively on complex networks, yielding insight into the effects of heterogeneity in contact patterns on disease spread. Somewhat separately, metapopulations have provided a paradigm for modeling systems with spatially extended and “patchy” organization. In this paper we expand on the use of multitype networks for combining these paradigms, such that simple contagion models can include complexity in the agent interactions and multiscale structure. Using a generalization of the Miller-Volz mean-field approximation for susceptible-infected-recovered (SIR) dynamics on multitype networks, we study the special case of epidemic fronts propagating on a one-dimensional lattice of interconnected networks—representing a simple chain of coupled population centers—as a necessary first step in understanding how macroscale disease spread depends on microscale topology. Applying the formalism of front propagation into unstable states, we derive the effective transport coefficients of the linear spreading: asymptotic speed, characteristic wavelength, and diffusion coefficient for the leading edge of the pulled fronts, and analyze their dependence on the underlying graph structure. We also derive the epidemic threshold for the system and study the front profile for various network configurations.

We investigate the frictional sliding of an incommensurate chain of interacting particles confined in between two nonlinear on-site substrate potential profiles in relative motion. We focus here on the class of Remoissenet-Peyrard parametrized potentials $V_{\mathrm{RP}}(x,s)$, whose shape can be varied continuously as a function of $s$, recovering the sine-Gordon potential as a particular case. The observed frictional dynamics of the system, crucially dependent on the mutual ratios of the three periodicities in the sandwich geometry, turns out to be significantly influenced also by the shape of the substrate potential. Specifically, variations of the shape parameter $s$ affect significantly and not trivially the existence and robustness of the recently reported velocity quantization phenomena [A. Vanossi et al., Phys. Rev. Lett. 97, 056101 (2006)], where the chain center-of-mass velocity to the externally imposed relative velocity of the sliders stays pinned to exact “plateau” values for wide ranges of the dynamical parameters.

We investigate the stochastic resonance of the stock prices in a finance system with the Heston model. The extrinsic and intrinsic periodic information are introduced into the stochastic differential equations of the Heston model for stock price by focusing on the signal power amplification (SPA). We find that for both cases of extrinsic and intrinsic periodic information a phenomenon of reverse resonance emerges in the behaviors of SPA as a function of the system and external driving parameters. Moreover, in both cases, a phenomenon of double reverse resonance is observed in the behavior of SPA versus the amplitude of volatility fluctuations, by increasing the cross correlation between the noise sources in the Heston model.

To predict the gaseous mass flow rate of microchannels, conventional analytical solutions based on the Navier-Stokes equation or volume diffusion hydrodynamics (bivelocity hydrodynamics) associated with first-order or second-order slip boundary condition are not very successful, especially in high-Knudsen-number flow. An analytical solution which agrees with experimental data to a Knudsen number of 50 is presented in this paper. To achieve this goal, a concept of effective volume diffusion is defined. Then, with a general slip boundary condition, the gaseous mass flow rate of microchannel is derived by solving the momentum equation of this effective volume diffusion hydrodynamics. Compared with six other analytical solutions and one group of numerical solutions of the linearized Boltzmann equation, this solution is validated by three groups of experimental data. The results not only illustrate an improvement of this solution compared with other analytical solutions but also show the importance of the effective volume diffusion hydrodynamics for compressible microfluids.

Lattice Boltzmann Modeling (LBM) simulations were performed on the dynamic behavior of liquid droplets on chemically striped patterned surfaces, ultimately with the aim to develop a predictive tool enabling reliable design of future experiments. The simulations accurately mimic experimental results, which have shown that water droplets on such surfaces adopt an elongated shape due to anisotropic preferential spreading. Details of the contact line motion such as advancing of the contact line in the direction perpendicular to the stripes exhibit pronounced similarities in experiments and simulations. The opposite of spreading, i.e., evaporation of water droplets, leads to a characteristic receding motion first in the direction parallel to the stripes, while the contact line remains pinned perpendicular to the stripes. Only when the aspect ratio is close to unity, the contact line also starts to recede in the perpendicular direction. Very similar behavior was observed in the LBM simulations. Finally, droplet movement can be induced by a gradient in surface wettability. LBM simulations show good semiquantitative agreement with experimental results of decanol droplets on a well-defined striped gradient, which move from high- to low-contact angle surfaces. Similarities and differences for all systems are described and discussed in terms of the predictive capabilities of LBM simulations to model direction wetting.

Communities are fundamental entities for the characterization of the structure of real networks. The standard approach to the identification of communities in networks is based on the optimization of a quality function known as modularity. Although modularity has been at the center of an intense research activity and many methods for its maximization have been proposed, not much is yet known about the necessary conditions that communities need to satisfy in order to be detectable with modularity maximization methods. Here, we develop a simple theory to establish these conditions, and we successfully apply it to various classes of network models. Our main result is that heterogeneity in the degree distribution helps modularity to correctly recover the community structure of a network and that, in the realistic case of scale-free networks with degree exponent $\gamma <2.5$, modularity is always able to detect the presence of communities.

Recently, experiments showed that forces on intruders dragged horizontally through dense, hydrostatic granular packings mainly depend on the local surface orientation and can be seen as the sum of the forces exerted on small surface elements. In order to understand such forces more deeply, we perform a two-dimensional soft-sphere molecular dynamics simulation, on a similar setup, of an intruder dragged through a 50–50 bi-disperse granular packing, with diameters $0.30$ and $0.34$ cm. We measure, for both circular and half-circle shapes, the forces parallel (drag) and perpendicular (lift) to the drag direction as functions of the drag speed, with $V=10.3$–309 cm/s, and intruder depths, with $D=3.75$–37.5 cm. The drag forces on an intruder monotonically increase with $V$ and $D$, and are larger for the circle. However, the lift force does not depend monotonically on $V$ and $D$, and this relationship is affected by the shape of the intruder. The vertical force was negative for the half-circle, but for a small range of $V$ and $D$, we measure positive lift. We find no sign change for the lift on the circle, which is always positive. The explanation for the nonmonotonic dependence is related to the decrease in contacts on the intruder as $V$ increases. This is qualitatively similar to supersonic flow detachment from an obstacle. The detachment picture is supported by simulation measurements of the velocity field around the intruder and force profiles measured on its surface.

The stability of nonvolatile thin liquid films and of sessile droplets is strongly affected by finite size effects. We analyze their stability within the framework of density functional theory using the sharp kink approximation, i.e., on the basis of an effective interface Hamiltonian. We show that finite size effects suppress spinodal dewetting of films because it is driven by a long-wavelength instability. Therefore nonvolatile films are stable if the substrate area is too small. Similarly, nonvolatile droplets connected to a wetting film become unstable if the substrate area is too large. This instability of a nonvolatile sessile droplet turns out to be equivalent to the instability of a volatile drop which can attain chemical equilibrium with its vapor.

The stochastic Eulerian-Lagrangian method (SELM) is used to simulate coarse-grained lipid membrane models under steady-state conditions and in shear flow. SELM is an immersed boundary method which combines the efficiency of particle-based simulations with the realistic solvent dynamics provided by fluctuating hydrodynamics. Membrane simulations in SELM are shown to give structural properties in accordance with equilibrium statistical mechanics and dynamic properties in agreement with previous simulations of highly detailed membrane models in explicit solvent. Simulations of sheared membranes are used to calculate surface shear viscosities and inter-monolayer friction coefficients. The membrane models are shown to be shear thinning under a wide range of applied shear rates.

Based on an exact analytical approach to describe scattering fidelity experiments [Köber et al., Phys. Rev. E 82, 036207 (2010)], we obtain an expression for the fidelity amplitude decay of quantum chaotic or diffusive systems under arbitrary Hermitian perturbations. This allows us to rederive previous separately obtained results in a simpler and unified manner, as is shown explicitly for the case of a global perturbation. The general expression is also used to derive a so far unpublished exact analytical formula for the case of a moving S-wave scatterer. In the second part of the paper, we extend a relation between fidelity decay and parametric level correlations from the universal case of global perturbations to an arbitrary combination of global and local perturbations. Thereby, the relation becomes a versatile tool for the analysis of unknown perturbations.

The relation of particle transport of relativistic particles in plasmas with high-amplitude isotropic sub-Larmor-scale magnetic turbulence to the spectra of radiation simultaneously produced by these particles is investigated both analytically and numerically. We have found that in the asymptotic regime of very small particle deflections, the pitch-angle diffusion coefficient is directly related to the spectrum of the emitted radiation. Moreover, this spectrum provides much information about the statistical properties of the underlying magnetic turbulence. The transition from small- to large-scale jitter to synchrotron radiation regimes as a function of turbulence properties has also been explored. These results can readily be used to diagnose laboratory and astrophysical plasmas.