In this Brief Report we investigate the multiscale hydrodynamical response of a liquid as a function of mixture composition. This is done via a series of molecular dynamics simulations in which the wave-vector-dependent viscosity kernel is computed for three mixtures, each with 7–15 different compositions. We observe that the viscosity kernel is dependent on composition for simple atomic mixtures for all the wave vectors studied here; however, for a molecular mixture the kernel is independent of composition for large wave vectors. The deviation from ideal mixing is also studied. Here it is shown that the Lorentz-Berthelot interaction rule follows ideal mixing surprisingly well for a large range of wave vectors, whereas for both the Kob-Andersen and molecular mixtures large deviations are found. Furthermore, for the molecular system the deviation is wave-vector dependent such that there exists a characteristic correlation length scale at which the ideal mixing goes from underestimating to overestimating the viscosity.

In a recent paper by Valleriani et al. [Phys. Rev. E 83, 042903 (2011)], a simple model for the translation of messenger RNA (mRNA) is presented. Using this model, the protein translational ratio $r$, defined as the ratio of protein translation rate ${\omega }_{\mathrm{tl}}$ from mRNA to protein degradation rate ${\omega }_p$, is obtained. The key point in obtaining the translational ratio $r$ is to get the protein translation rate ${\omega }_{\mathrm{tl}}$. In Valleriani et al.'s paper, ${\omega }_{\mathrm{tl}}$ is obtained as the mean value of the measured translation rate, which is the ratio of the synthesized protein number to the mRNA lifetime. However, in experiments, different methods might be used to obtain the value of ${\omega }_{\mathrm{tl}}$. Therefore, to apply Valleriani et al.'s model to more general experiments, in this Comment three methods to obtain the translation rate ${\omega }_{\mathrm{tl}}$, and consequently the translational ratio $r$, are presented. Based on one of the methods which might be employed in most of the experiments, we find that the translational ratio $r$ decays exponentially with mRNA length in prokaryotic cells, and decays reciprocally with mRNA length in eukaryotic cells. This result is slight different from that which was obtained in Valleriani et al.'s paper.

We present an experimental study of the transition to turbulence in a plane Poiseuille flow. Using a well-controlled perturbation, we analyze the flow by using extensive particle image velocimetry and flow visualization (using laser-induced fluorescence) measurements, and use the deformation of the mean velocity profile as a criterion to characterize the state of the flow. From a large parametric study, four different states are defined, depending on the values of the Reynolds number and the amplitude of the perturbation. We discuss the role of coherent structures, such as hairpin vortices, in the transition. We find that the minimal amplitude of the perturbation triggering transition scales asymptotically as ${\text{Re}}^{-1}$.

Highly collimated MeV electron beam guiding has been observed along the target surface following the interaction of bulk target irradiation by femtosecond laser pulses at relativistic intensities. The beam quality is shown to depend critically on the laser contrast: With a ns prepulse, the generated electron beam is well concentrated and intense, while a high laser contrast produces divergent electron beams. In the case of large preplasma scale lengths, tunable guiding and acceleration of the target surface electrons is achieved by changing the laser incident angle. By expanding the preplasma scale length to several hundred micrometers, we obtained MeV spectrum-peaked electron beams with a 100 pC per laser pulse and divergence angles of only 3${}^{\circ }$. This technique suggests a stable method of injection of elections into a variety of accelerator designs.

We introduce and investigate a multiscale model for the propagation of rupture fronts in friction. Taking advantage of the correlation length for the motion of individual contacts in elastic theory, we introduce collective contacts which can be characterized by a master equation approach. The problem of the dynamics of a chain of those effective contacts under stress is studied. We show that it can be reduced to an analog of the Frenkel-Kontorova model. In some limits this allows us to derive analytical solutions for kinks describing the rupture fronts. Numerical simulations are used to study more complex cases.

In this paper we study the jamming transition in complex adaptive networks. We introduce an adaptation mechanism that modifies the weight of the communication channels in order to delay the congestion onset. Adaptivity takes place locally as it is driven by each node of the network. Surprisingly, regardless of the structural properties of the backbone topology, e.g., its degree distribution, the adaptive network can reach optimal functioning provided it allows a reciprocal distribution of the weights. Under this condition, the optimal functioning is achieved through an extensive network reshaping ending up in a highly reciprocal weighted network whose critical onset of congestion is delayed up to its maximum possible value. We also show that, for a given network, the reciprocal weighting obtained from adaptation produce optimal static configurations.

We present general methods to exactly calculate mean first-passage quantities on self-similar networks defined recursively. In particular, we calculate the mean first-passage time and the splitting probabilities associated to a source and one or several targets; averaged quantities over a given set of sources (e.g., same-connectivity nodes) are also derived. The exact estimate of such quantities highlights the dependency of first-passage processes with respect to the source-target distance, which has recently revealed to be a key parameter in characterizing transport in complex media. We explicitly perform calculations for different classes of recursive networks [finitely ramified fractals, scale-free (trans)fractals, nonfractals, mixtures between fractals and nonfractals, nondecimable hierarchical graphs] of arbitrary size. Our approach unifies and significantly extends the available results in the field.

We show experimentally that two semiconductor lasers mutually coupled via a passive relay fiber loop exhibit chaos synchronization at zero lag, and study how this synchronized regime is lost as the lasers’ pump currents are increased. We characterize the synchronization properties of the system with high temporal resolution in two different chaotic regimes, namely, low-frequency fluctuations and coherence collapse, identifying significant differences between them. In particular, a marked decrease in synchronization quality develops as the lasers enter the coherence collapse regime. Our high-resolution measurements allow us to establish that synchronization loss is associated with bubbling events, the frequency of which increases with increasing pump current.

We scrutinize the reliability of covariant and Gram-Schmidt Lyapunov vectors for capturing hydrodynamic Lyapunov modes (HLMs) in one-dimensional Hamiltonian lattices. We show that, in contrast with previous claims, HLMs do exist for any energy density, so that strong chaos is not essential for the appearance of genuine (covariant) HLMs. In contrast, Gram-Schmidt Lyapunov vectors lead to misleading results concerning the existence of HLMs in the case of weak chaos.

The transition from subcritical to supercritical stationary periodic patterns is described by the one-dimensional cubic-quintic Ginzburg-Landau equation $A_t=\mu A+A_{xx}+i(a_1{\left|A\right|}^2{A}_x+a_2{A}^2{A}_x^{*}{)+b|A|}^{2}A-{\left|A\right|}^{4}A$, where $A(x,t)$ represents the pattern amplitude and the coefficients $\mu$, $a_1$, $a_2$, and $b$ are real. The conditions for Eckhaus instability of periodic solutions are determined, and the resulting spatially modulated states are computed. Some of these evolve into spatially localized structures in the vicinity of a Maxwell point, while others resemble defect states. The results are used to shed light on the behavior of localized structures in systems exhibiting homoclinic snaking during the transition from subcriticality to supercriticality.

Nonlinear propagation of fast and slow magnetosonic perturbation modes in an ultrarelativistic, ultracold, degenerate (extremely dense) electron positron (EP) plasma (containing ultrarelativistic, ultracold, degenerate electron and positron fluids) has been investigated by the reductive perturbation method. The Alfvén wave velocity is modified due to the presence of the enthalpy correction in the fluid equations of motion. The degenerate EP plasma system (under consideration) supports the Korteweg–de Vries (KdV) solitons, which are associated with either fast or slow magnetosonic perturbation modes. It is found that the ultrarelativistic model leads to compressive (rarefactive) electromagnetic solitons corresponding to the fast (slow) wave mode. There are certain critical angles, ${\theta }_c$, at which no soliton solution is found corresponding to the fast wave mode. For the slow mode, the magnetic-field intensity affects both the soliton amplitude and width. It is also illustrated that the basic features of the electromagnetic solitary structures, which are found to exist in such a degenerate EP plasma, are significantly modified by the effects of enthalpy correction, electron and positron degeneracy, magnetic-field strength, and the relativistic effect. The applications of the results in a pair-plasma medium, which occurs in many astrophysical objects (e.g., pulsars, white dwarfs, and neutron stars) are briefly discussed.

Microdiffusion in a (2 + 1)-dimensional liquid with flexible long longitudinal chain bundles, formed by negatively charged dusts suspended in a low-pressure Ar gaseous discharge, is investigated. With increasing time scale $\tau$, the transverse hopping dominated displacement induces the transition from the sub- to the superdiffusion of the single dust, and the growth of spatial displacement correlation of two dusts, which suppresses their relative diffusion. The rise time of displacement correlation increases with dust separation. The bond breaking around the hopping cluster boundary is the main source for long time relative diffusion and causes the presence of the multiple shoulders in the fat tails of the non-Gaussian relative displacement histograms. The stronger longitudinal coupling than the transverse coupling strongly enhances the motion correlation over much larger separation, and suppresses the bond-breaking rate and the relative diffusion of the longitudinal dust pairs.

In a chain of mutually coupled oscillators, the coupling threshold for synchronization between the outermost identical oscillators decreases when a type of impurity (in terms of parameter mismatch) is introduced in the inner oscillator(s). The outer oscillators interact indirectly via dynamic relaying, mediated by the inner oscillator(s). We confirm this enhancing of critical coupling in the chaotic regimes of the Lorenz system, in the Rössler system in the absence of coupling delay, and in the Mackey-Glass system with delay coupling. The enhancing effect is experimentally verified in the electronic circuit of Rössler oscillators.

A low density binary mixture of granular gases is considered within the Boltzmann kinetic theory. One component, the intruders, is taken to be dilute with respect to the other, and thermal segregation of the two species is described for a special solution to the Boltzmann equation. This solution has a macroscopic hydrodynamic representation with a constant temperature gradient and is referred to as the Fourier state. The thermal diffusion factor characterizing conditions for segregation is calculated without the usual restriction to Navier-Stokes hydrodynamics. Integral equations for the coefficients in this hydrodynamic description are calculated approximately within a Sonine polynomial expansion. Molecular dynamics simulations are reported, confirming the existence of this idealized Fourier state. Good agreement is found for the predicted and simulated thermal diffusion coefficient, while only qualitative agreement is found for the temperature ratio.

The way sensory microcircuits manage cellular response correlations is a crucial question in understanding how such systems integrate external stimuli and encode information. Most sensory systems exhibit heterogeneities in terms of population sizes and features, which all impact their dynamics. This work addresses how correlations between the dynamics of neural ensembles depend on the relative size or density of excitatory and inhibitory populations. To do so, we study an apparently symmetric system of coupled stochastic differential equations that model the evolution of the populations’ activities. Excitatory and inhibitory populations are connected by reciprocal recurrent connections, and both receive different stimuli exhibiting a certain level of correlation with each other. A stability analysis is performed, which reveals an intrinsic asymmetry in the distribution of the fixed points with respect to the threshold of the nonlinearities. Based on this, we show how the cross correlation between the population responses depends on the density of the inhibitory population, and that a specific ratio between both population sizes leads to a state of zero correlation. We show that this so-called asynchronous state subsists, despite the presence of stimulus correlation, and most importantly, that it occurs only in asymmetrical systems where one population outnumbers the other. Using linear approximations, we derive analytical expressions for the root of the cross-correlation function and study how the asynchronous state is impacted by the model's parameters. This work suggests a possible explanation for why inhibitory cells outnumber excitatory cells in the visual system.

Human heart rate variability, in the form of time series of intervals between heart beats, shows complex, fractal properties. Recently, it was demonstrated many times that the fractal properties vary from point to point along the series, leading to multifractality. In this paper, we concentrate not only on the fact that the human heart rate has multifractal properties but also that these properties depend on the time scale in which the multifractality is measured. This time scale is related to the frequency band of the signal. We find that human heart rate variability appears to be far more complex than hitherto reported in the studies using a fixed time scale. We introduce a method called multiscale multifractal analysis (MMA), which allows us to extend the description of heart rate variability to include the dependence on the magnitude of the variability and time scale (or frequency band). MMA is relatively immune to additive noise and nonstationarity, including the nonstationarity due to inclusions into the time series of events of a different dynamics (e.g., arrhythmic events in sinus rhythm). The MMA method may provide new ways of measuring the nonlinearity of a signal, and it may help to develop new methods of medical diagnostics.

The critical exponents were measured for absorbing phase transitions in the conserved lattice gas (CLG) model on a simple cubic lattice. The correlation-length exponent calculated from the dynamic exponent obtained by finite-size scaling and from the mean spreading distance was consistently found to be ${\nu }_{\perp }=0.631\pm 0.02$, which yields a positive specific heat exponent $\alpha =2-d{\nu }_{\perp }$ on a pure system. The pure fixed point should, thus, be unstable if the Harris criterion established in equilibrium systems is applicable to the nonequilibrium absorbing phase transitions of the CLG model. However, this prediction is in contradiction with recent simulation results.

We show that an exact solution of the generalized Langevin equation (GLE) for the autocorrelations of a many-body classical system can be given in an exponential functionality (EF) form. As a consequence, the power spectrum of the correlation has a Lorentzian functionality, i.e., is represented by an infinite sum of Lorentzian functions corresponding to the eigenmodes of the considered correlation. By means of the simple derivation of the GLE by M. H. Lee [Phys. Rev. B 26, 2547 (1982)], we also show that, in practical cases of interest to experimental spectroscopies, possible approximations of the EF are related to a reduction of the relevant dynamical variables via a restriction of the dimensions of the orthogonalized space onto which the dynamics of the system is projected.