Intracellular transport of large cargoes, such as organelles, vesicles, or large proteins, is a complex dynamical process that involves the interplay of adenosine triphosphate–consuming molecular motors, cytoskeleton filaments, and the viscoelastic cytoplasm. In this work we investigate the motion of pigment organelles (melanosomes) driven by myosin-V motors in Xenopus laevis melanocytes using a high-spatio-temporal resolution tracking technique. By analyzing the obtained trajectories, we show that the melanosomes mean-square displacement undergoes a transition from a subdiffusive to a superdiffusive behavior. A stochastic theoretical model, which explicitly considers the collective action of the molecular motors, is introduced to generalize the interpretation of our data. Starting from a generalized Langevin equation, we derive an analytical expression for the mean square displacement, which also takes into account the experimental noise. By fitting theoretical expressions to experimental data we were able to discriminate the exponents that characterize the passive and active contributions to the dynamics and to estimate the “global” motor forces correctly. Then, our model gives a quantitative description of active transport in living cells with a reduced number of parameters.

Time series of increments can be created in a number of different ways from a variety of physical phenomena. For example, in the phenomenon of volatility clustering—well-known in finance—magnitudes of adjacent increments are correlated. Moreover, in some time series, magnitude correlations display asymmetry with respect to an increment’s sign: the magnitude of $\left|x_i\right|$ depends on the sign of the previous increment $x_{i-1}$. Here we define a model-independent test to measure the statistical significance of any observed asymmetry. We propose a simple stochastic process characterized by a an asymmetry parameter $\lambda$ and a method for estimating $\lambda$. We illustrate both the test and process by analyzing physiological data.

A condition for the synchronizability of a pair of extended systems governed by partial differential equations (PDEs), coupled through a finite set of variables, is commonly the existence of internal synchronization or internal coherence in each system separately. The condition was previously illustrated in a forced-dissipative system and is here extended to Hamiltonian systems using an example from particle physics. Full synchronization is precluded by Liouville’s theorem. A form of synchronization weaker than “measure synchronization” is manifest as the positional coincidence of coherent oscillations (“breathers” or “oscillons”) in a pair of coupled scalar field models in an expanding universe with a nonlinear potential, and does not occur with a variant of the model that does not exhibit oscillons.

Channel widths and spacing in latticelike hierarchical transport networks are optimized to achieve maximum extraction of gas or electrical charge from nanoporous energy-storage materials during charge and discharge cycles of specified duration. To address a range of physics, the effective transport diffusivity is taken to vary as a power, $m$, of channel width. Optimal channel widths and spacing in all levels of the hierarchy are found to increase in a power-law manner with normalized system size, facilitating the derivation of closed-form approximations for the optimal dimensions. Characteristic response times and ratios of channel width to spacing are both shown to vary by the factor $2/m$ between successive levels of any optimal hierarchy. This leads to fractal-like self-similar geometry, but only for $m=2$. For this case of quadratic dependence of diffusivity on channel width, the introduction of transport channels permits increases in system size on the order of ${10}^4$, ${10}^8$, and ${10}^{10}$, without any reduction in extraction efficiency, for hierarchies having 1, 2 and, 8 levels, respectively. However, we also find that for a given system size there is an optimum number of hierarchical levels that maximizes extraction efficiency.

Spatial distributions of ${\text{H}}_{\alpha }$, ${\text{H}}_{\beta }$, and the near-uv continuum emission from the ${\text{H}}_2$ $a{{}^3\Sigma }_g^{+}$ state are measured and compared with a model for low-current electrical discharges in ${\text{H}}_2$ at high $E/N$ and low $Nd$, where $E$ is the spatially uniform electric field, $N$ is the gas density, and $d$ is the electrode separation. Data are analyzed for $300\text{Td}<E/N<45\text{kTd}$, $d=0.04\text{m}$, and $2\times {10}^{21}<N<2.6\times {10}^{22}{\text{m}}^{-3}$. $\left(1\text{Td}={10}^{-21}\text{V}{\text{m}}^2\right)$ The excitation is produced by electrons and by hydrogen atoms and molecules with mean energies from 5 to 1500 eV. Electron-induced emission, dominant at low $E/N$ and low pressures, is distinguished by its buildup toward the anode. Excitation of ${\text{H}}_{\alpha }$ by fast H atoms dominates at high $E/N$ and increases toward the cathode. The observed ${\text{H}}_{\alpha }$ emission at low $E/N$ is normalized to previous experiments to yield absolute experimental excitation coefficients for all $E/N$ and $Nd$. Small adjustments of model parameters yield good agreement with ${\text{H}}_{\alpha }$ data. Cross sections are derived for excitation of the ${\text{H}}_2$ near-uv continuum by H atoms. Spatial and pressure dependencies of ${\text{H}}_{\alpha }$ and ${\text{H}}_2$ near-uv emissions agree well with a model in which reactions of ${\text{H}}_2^{+}$, ${\text{H}}_3^{+}$, and ${\text{H}}^{+}$ ions with ${\text{H}}_2$ lead to fast H atoms and ${\text{H}}_2$ molecules, which then excite H atoms or ${\text{H}}_2$ molecules.

A granular cluster, placed on a staircase setup, is brought into motion by vertical shaking. Molecular dynamics simulations show that the system goes through three phases. After a rapid initial breakdown of the cluster, the particle stream organizes itself in the form of a shock wave moving down the steps of the staircase. As this wave becomes diluted, it transforms into a more symmetric flow, in which the particles move not only downwards but also toward the top of the staircase. This series of events is accurately reproduced by a dynamical model in which the particle flow from step to step is modeled by a flux function. To explain the observed scaling behavior during the three stages, we study the continuum version of this model (a nonlinear partial differential equation) in three successive limiting cases. (i) The first limit gives the correct $t^{-1/3}$ decay law during the rapid initial phase, (ii) the second limit reveals that the transient shock wave is of the Burgers type, with the density of the wave front decreasing as $t^{-1/2}$, and (iii) the third limit shows that the eventual symmetric flow is a slow diffusive process for which the density falls off as $t^{-1/3}$ again. For any finite number of compartments, the system finally reaches an equilibrium distribution with a bias toward the lower compartments. For an unbounded staircase, however, the $t^{-1/3}$ decay goes on forever and the distribution becomes increasingly more symmetric as the dilution progresses.

In this work, we discuss the general phase behavior of short tubelike flexible polymers. The geometric thickness constraint is implemented through the concept of the global radius of curvature. We use sophisticated Monte Carlo sampling methods to simulate small bead-stick polymer models with Lennard-Jones interaction among nonbonded monomers. We analyze energetic fluctuations and structural quantities to classify conformational pseudophases. We find that the tube thickness influences the thermodynamic behavior of simple tubelike polymers significantly, i.e., for a given temperature, the formation of secondary structures strongly depends on the tube thickness.

The phase-resetting curve (PRC) describes the response of a neural oscillator to small perturbations in membrane potential. Its usefulness for predicting the dynamics of weakly coupled deterministic networks has been well characterized. However, the inputs to real neurons may often be more accurately described as barrages of synaptic noise. Effective connectivity between cells may thus arise in the form of correlations between the noisy input streams. We use constrained optimization and perturbation methods to prove that the PRC shape determines susceptibility to synchrony among otherwise uncoupled noise-driven neural oscillators. PRCs can be placed into two general categories: type-I PRCs are non-negative, while type-II PRCs have a large negative region. Here we show that oscillators with type-II PRCs receiving common noisy input synchronize more readily than those with type-I PRCs.

We study counting statistics of number of transitions in a stochastic process. For mesoscopic systems, a path integral formulation for the counting statistics has already been derived. We here show that it is also possible to derive the similar path integral formulation without the assumption of mesoscopic systems. It has been clarified that the saddle point method for the path integral is not an approximation, but a valid procedure in the present derivation. Hence, a variational principle in the counting statistics is naturally derived. In order to obtain the variational principle, we employ many independent replicas of the same system. In addition, the Euler-Maclaurin formula is used in order to connect the discrete and continuous properties of the system.

We study the relaxation dynamics of the bid-ask spread and of the midprice after a sudden variation of the spread in a double auction financial market. We find that the spread decays as a power law to its normal value. We measure the price reversion dynamics and the permanent impact, i.e., the long-time effect on price, of a generic event altering the spread and we find an approximately linear relation between immediate and permanent impact. We hypothesize that the power-law decay of the spread is a consequence of the strategic limit order placement of liquidity providers. We support this hypothesis by investigating several quantities, such as order placement rates and distribution of prices and times of submitted orders, which affect the decay of the spread.

Oscillating fields can make domain patterns change into various types of structures. Numerical simulations show that concentric-ring domain patterns centered at a strong defect are observed under a rapidly oscillating field in some cases. The concentric-ring pattern appears near the threshold of spatially uniform patterns in high-frequency cases. The threshold is theoretically estimated and the theoretical threshold is in good agreement with numerical one in a high-frequency region. The theoretical analysis gives also good estimations of several characteristics of domain patterns for high frequencies.

Interactions of dispersive shock waves (DSWs) and rarefaction waves (RWs) associated with the Korteweg–de Vries equation are shown to exhibit multiphase dynamics and isolated solitons. There are six canonical cases: one is the interaction of two DSWs that exhibit a transient two-phase solution but evolve to a single-phase DSW for large time; two tend to a DSW with either a small amplitude wave train or a finite number of solitons, which can be determined analytically; two tend to a RW with either a small wave train or a finite number of solitons; finally, one tends to a pure RW.

Using simulations, we construct the effective dynamics in metabasin space for a Lennard-Jones glass former. Metabasins are identified via a scheme that measures transition rates between inherent structures and generates clusters of inherent structures by drawing in branches that have the largest transition rates. This construction is fundamentally different from the stochastic approach based on molecular-dynamics trajectories. The effective dynamics in this metabasin space is shown to be Markovian but to differ significantly from the simplest trap models. We specifically show that retaining information about the connectivity in this metabasin space is crucial for reproducing the slow dynamics observed in this system.

Based on a considerable amount of experimental evidence for lateral organization of lipid membranes which share astonishingly similar features in the presence of different inclusions, we use a hybrid self-consistent field theory (SCFT)/density-functional theory (DFT) approach to deal with bilayer membranes embedded by nanosized inclusions and explain experimental findings. Here, the hydrophobic inclusions are simple models of hydrophobic drugs or other nanoparticles for biomedical applications. It is found that lipid/inclusion-rich domains are formed at moderate inclusion concentrations and disappear with the increase in the concentration of inclusions. At high inclusion content, chaining of inclusions occurs due to the effective depletion attraction between inclusions mediated by lipids. Meanwhile, the increase in the concentration of inclusions can also cause thickening of the membrane and the distribution of inclusions undergoes a layering transition from one-layer structure located in the bilayer midplane to two-layer structure arranged into the two leaflets of a bilayer. Our theoretical predictions address the complex interactions between membranes and inclusions suggesting a unifying mechanism which reflects the competition between the conformational entropy of lipids favoring the formation of lipid- and inclusion-rich domains in lipids and the steric repulsion of inclusions leading to the uniform dispersion.

We study the effects of conformity, the tendency of humans to imitate locally common behaviors, in the evolution of cooperation when individuals occupy the vertices of a graph and engage in the one-shot prisoner’s dilemma or the snowdrift game with their neighbors. Two different graphs are studied: rings (one-dimensional lattices with cyclic boundary conditions) and scale-free networks of the Barabási-Albert type. The proposed evolutionary-graph model is studied both by means of Monte Carlo simulations and an extended pair-approximation technique. We find improved levels of cooperation when evolution is carried on rings and individuals imitate according to both the traditional payoff bias and a conformist bias. More importantly, we show that scale-free networks are no longer powerful amplifiers of cooperation when fair amounts of conformity are introduced in the imitation rules of the players. Such weakening of the cooperation-promoting abilities of scale-free networks is the result of a less biased flow of information in scale-free topologies, making hubs more susceptible of being influenced by less-connected neighbors.

A system of agents moving along a road in both directions is studied numerically within a cellular-automata formulation. An agent steps to the right with probability $q$ or to the left with $1-q$ when encountering other agents. Our model is restricted to two agent types, traffic-rule abiders $\left(q=1\right)$ and traffic-rule ignorers $\left(q=1/2\right)$, and the traffic flow, resulting from the interaction between these two types of agents, which is obtained as a function of density and relative fraction. The risk for jamming at a fixed density, when starting from a disordered situation, is smaller when every agent abides by a traffic rule than when all agents ignore the rule. Nevertheless, the absolute minimum occurs when a small fraction of ignorers are present within a majority of abiders. The characteristic features for the spatial structure of the flow pattern are obtained and discussed.

We investigate a special class of coupled nonlinear superluminal solitons arising from the interaction of an intense linearly polarized electromagnetic pulse with a cold plasma. These modulated envelope structures are obtained as numerical solutions of the classic Akhiezer-Polovin model equations [Sov. Phys. JETP 3, 696 (1956)]. We also present a multiple time scale perturbation analysis in the small amplitude limit that provides a close analytic description of these nonlinear solutions.

Recent experiments using proton backlighting of laser-foil interactions provide unique opportunities for studying magnetized plasma instabilities in laser-produced high-energy-density plasmas. Time-gated proton radiograph images indicate that the outer structure of a magnetic field entrained in a hemispherical plasma bubble becomes distinctly asymmetric after the laser turns off. It is shown that this asymmetry is a consequence of pressure-driven, resistive magnetohydrodynamic (MHD) interchange instabilities. In contrast to the predictions made by ideal MHD theory, the increasing plasma resistivity after laser turn-off allows for greater low-mode destabilization $\left(m>1\right)$ from reduced stabilization by field-line bending. For laser-generated plasmas presented herein, a mode-number cutoff for stabilization of perturbations with $m>\sim {\left[8\pi \beta \left(1+D_m{k}_{\perp }^2{\gamma }_{\text{max}}^{-1}\right)\right]}^{1/2}$ is found in the linear growth regime. The growth is measured and is found to be in reasonable agreement with model predictions.

We describe a method for evolving the projected Gross-Pitaevskii equation (PGPE) for an interacting Bose gas in a harmonic-oscillator potential, with the inclusion of a long-range dipolar interaction. The central difficulty in solving this equation is the requirement that the field is restricted to a small set of prescribed modes that constitute the low-energy $c$-field region of the system. We present a scheme, using a Hermite-polynomial-based spectral representation, which precisely implements this mode restriction and allows an efficient and accurate solution of the dipolar PGPE. We introduce a set of auxiliary oscillator states to perform a Fourier transform necessary to evaluate the dipolar interaction in reciprocal space. We extensively characterize the accuracy of our approach and derive Ehrenfest equations for the evolution of the angular momentum.

Information search is closely related to the first-passage property of diffusing particle. The physical properties of diffusing particle is affected by the topological structure of the underlying network. Thus, the interplay between dynamical process and network topology is important to study information search on complex networks. Designing an efficient method has been one of main interests in information search. Both reducing the network traffic and decreasing the searching time have been two essential factors for designing efficient method. Here we propose an efficient method based on biased random walks. Numerical simulations show that the average searching time of the suggested model is more efficient than other well-known models. For a practical interest, we demonstrate how the suggested model can be applied to the peer-to-peer system.