The unzipping and rezipping of a double-stranded DNA molecule is carried out in the presence of two single-stranded binding proteins T4 gp32 and E. Coli SSB protein to determine the effect of the proteins on the stability of single- and double-stranded DNA. The proteins do not have a significant effect on unzipping, indicating that the two proteins do not destabilize the double-stranded DNA; however, both proteins inhibit rezipping. At protein concentrations where the rezipping force response is saturated, E. Coli SSB protein reduces the rezipping force to $5.5\pm 1.5\mathrm{pN}$, while T4 gp32 completely blocks rezipping on the time scale of the experiment.

Many empirical networks display an inherent tendency to cluster, i.e., to form circles of connected nodes. This feature is typically measured by the clustering coefficient (CC). The CC, originally introduced for binary, undirected graphs, has been recently generalized to weighted, undirected networks. Here we extend the CC to the case of (binary and weighted) directed networks and we compute its expected value for random graphs. We distinguish between CCs that count all directed triangles in the graph (independently of the direction of their edges) and CCs that only consider particular types of directed triangles (e.g., cycles). The main concepts are illustrated by employing empirical data on world-trade flows.

Granular flows due to simultaneous vertical and horizontal excitations of a flat-bottomed cylindrical pan are investigated using event-driven molecular dynamics simulations. In agreement with recent experimental results, we observe a transition from a solidlike state to a fluidized state in which circulatory flow occurs simultaneously in the radial and tangential directions. By going beyond the range of conditions explored experimentally, we find that each of these circulations reverses its direction as a function of the control parameters of the motion. We numerically evaluate the dynamical phase diagram for this system and show, using a simple model, that the solid-fluid transition can be understood in terms of a critical value of the radial acceleration of the pan bottom and that the circulation reversals are controlled by the phase shift relating the horizontal and vertical components of the vibrations. We also discuss the crucial role played by the geometry of the boundary conditions and point out a relationship of the circulation observed here and the flows generated in vibratory conveyors.

A high-pressure calorimetric experiment to test the validity of a water model’s prediction, regarding the behavior of the heat capacity in the liquid-liquid critical point and singularity-free scenarios, is proposed in this paper. The response of the specific heat at high pressure is different depending on the existence, or not, of a second critical point. If the model presents a second critical point, there is a nondivergent maximum in the specific heat at a temperature $T\sim T_c$ for any pressure $P>P_c$ ($T_c$ and $P_c$ being the temperature and pressure of the model’s second critical point). This maximum does not appear for the model with a singularity free scenario.

We present molecular dynamics simulations of a nanoscopic nematic twist cell confined within two bounding substrates with conflicting anchoring conditions. The results of our simulations show that the torque transmitted through the cell drops significantly below a certain critical cell’s thickness, thus confirming the predictions of the continuum Landau theory extrapolated down to the nanoscopic scale [F. Bisi, E. G. Virga, and G. E. Durand, Phys. Rev. E 70, 042701 (2004)].

Molecular orientation fluctuations in ferroelectric smectic liquid crystals produce space charges, due to the divergence of the spontaneous polarization. These space charges interact with mobile ions, so that one must consider the coupled dynamics of the orientation and ionic degrees of freedom. Previous theory and light scattering experiments on thin free-standing films of ferroelectric liquid crystals have not included this coupling, possibly invalidating their quantitative conclusions. We consider the most important case of very slow ionic dynamics, compared to rapid orientational fluctuations, and focus on the use of a short electric field pulse to quench orientational fluctuations. We find that the resulting change in scattered light intensity must include a term due to the quasistatic ionic configuration, which has previously been ignored. In addition to developing the general theory, we present a simple model to demonstrate the role of this added term.

We report the transition dipole strength of eumelanin (the principal human photoprotective pigment) in the ultraviolet and visible. We have used both theoretical (density functional) and experimental methods to show that eumelanin is not an unusually strong absorber amongst organic chromophores. This is somewhat surprising given its role as a photoprotectant, and suggests that the dark coloring in vivo (and in vitro) of the eumelanin pigment is a concentration effect. Furthermore, by observing the polymerization of a principle precursor (5,6-dihydroxyindole-2-carboxylic acid) into the full pigment, we observe that eumelanin exhibits a small amount $(\sim 20\%)$ of hyperchromism (i.e., the reaction process enhances the light absorption ability of the resultant macromolecule relative to its monomeric precursor). These results have significant implications for our understanding of the photophysics of these important functional biomolecules. In particular, they appear to be consistent with the recently proposed chemical disorder secondary structure model of eumelanins.

We investigate the normal form of a subcritical Hopf bifurcation subjected to time-delayed feedback control. Bifurcation diagrams which cover time-dependent states as well are obtained by analytical means. The computations show that unstable limit cycles with an odd number of positive Floquet exponents can be stabilized by time-delayed feedback control, contrary to incorrect claims in the literature. The model system constitutes one of the few examples where a nonlinear time delay system can be treated entirely by analytical means.

We find actual evidence, relying upon vorticity time series taken in a high-Reynolds-number atmospheric experiment, that to a very good approximation the surface boundary layer flow may be described, in a statistical sense and under certain regimes, as an advected ensemble of homogeneous turbulent systems, characterized by a log-normal distribution of fluctuating intensities. Our analysis suggests that the usual direct numerical simulations of homogeneous and isotropic turbulence, performed at moderate Reynolds numbers, may play an important role in the study of turbulent boundary layer flows, if supplemented with appropriate statistical information concerned with the structure of large-scale fluctuations.

The line emissions of ${\mathrm{OH}}^{*}$, Na, $\mathrm{Na}\text{−}{\mathrm{Ar}}^{*}$, and Ar are observed in stable and bright single bubble sonoluminescence (SBSL), which shows that the composition of the bubble consists of at least three parts: the vapor, droplets of the host liquid, and the gas dissolved in the host liquid. The observation of line emissions in SBSL demonstrates that it shares exactly the same spectra with multibubble sonoluminescences (MBSL). The experiments indicate that noble gas plays an important role in all line emissions of both SBSL and MBSL. The time resolved spectra of SBSL show that there is significant mass exchange between the inside and outside of the bubble. The time scale of the mass exchange ranges from less than $\frac{1}{10}\mathrm{s}$ to tens of seconds. The SBSL in sulfuric acid supports the argon rectification theory. Because stable SBSL in sulfuric acid can just be achieved within a narrow parameter range, only weak rectification is observed in our experiments.

The velocity autocorrelation function is derived from the mean-squared displacement measured on a colloidal suspension of particles with hard-sphere-like interactions. It decays to zero from below and follows a stretched exponential function of delay time for the thermodynamically stable suspension. For the metastable suspension a power-law decay emerges. The results are discussed in terms of the classical Lorentz gas and the model that describes diffusion confined to one dimension. With the aid of these models, the experimental results provide a characterization of the dynamical heterogeneities which are observed microscopically, and an explanation for the enhanced resistance to flow and diffusion usually found in undercooled fluids upon approaching the glass transition.

Parameters for orientational and inhomogeneous broadening are found from the line shape analysis of the Raman spectrum of the glass former $\alpha$-picoline during cooling from low-viscous to glassy state. The orientational phase loss time ${\tau }_{\mathrm{OPL}}$, extracted from the analysis, coincides with the $\alpha$ relaxation time at $T>T_A$, where $T_A$ is the temperature of transition from an Arrhenius-like to a non-Arrhenius behavior for the $\alpha$-relaxation time dependence on temperature. At lower temperatures ${\tau }_{\mathrm{OPL}}\left(T\right)$ continues the Arrhenius behavior, in contrast to the $\alpha$-relaxation time. The width of inhomogeneous broadening of the Raman line decreases noticeably as temperature increases in the temperature range $T_g<T<T_A$, approaching to zero at $T\sim T_A$. The findings evidence the transition of molecular dynamics from individual to cooperative at $T=T_A$.

The properties of the generalized survival probability, that is, the probability of not crossing an arbitrary location $R$ during relaxation, have been investigated experimentally (via scanning tunneling microscope observations) and numerically. The results confirm that the generalized survival probability decays exponentially with a time constant ${\tau }_s\left(R\right)$. The distance dependence of the time constant is shown to be ${\tau }_s\left(R\right)={\tau }_{s0}\exp [-R∕w\left(T\right)]$, where $w^2\left(T\right)$ is the material-dependent mean-squared width of the step fluctuations. The result reveals the dependence on the physical parameters of the system inherent in the prior prediction of the time constant scaling with $R∕L^{\alpha }$, with $L$ the system size and $\alpha$ the roughness exponent. The survival behavior is also analyzed using a contrasting concept, the generalized inside survival $S_{\mathrm{in}}(t,R)$, which involves fluctuations to an arbitrary location $R$ further from the average. Numerical simulations of the inside survival probability also show an exponential time dependence, and the extracted time constant empirically shows ${(R∕w)}^{\lambda }$ behavior, with $\lambda$ varying over 0.6 to 0.8 as the sampling conditions are changed. The experimental data show similar behavior, and can be well fit with $\lambda =1.0$ for $T=300\mathrm{K}$, and $0.5<\lambda <1$ for $T=460\mathrm{K}$. Over this temperature range, the ratio of the fixed sampling time to the underlying physical time constant, and thus the true correlation time, increases by a factor of $\sim {10}^3$. Preliminary analysis indicates that the scaling effect due to the true correlation time is relevant in the parameter space of the experimental observations.

The classical fluid dynamics boundary condition of no slip suggests that variation in the wettability of a solid should not affect the flow of an adjacent liquid. However, experiments and molecular dynamics simulations indicate that this is not the case. In this paper we show how flow over a solid substrate with variations of wettability can be described in a continuum framework using the interface formation theory developed earlier. Results demonstrate that a shear flow over a perfectly flat solid surface is disturbed by a change in its wettability, i.e., by a change in the chemistry of the solid substrate. The magnitude of the effect is shown to be proportional to $\cos {\theta }_1-\cos {\theta }_2$, where ${\theta }_1$ and ${\theta }_2$, are the equilibrium contact angles that a liquid-gas free surface would form with the two chemically different parts of the solid surface.

We have studied the conformational properties of a flexible end-grafted chain (length $N$) with a rigid side chain (length $S$) by means of Monte Carlo simulations. Depending on the lengths $N$ and $S$ and the branching site $b$, we observe a considerable straightening of the flexible backbone as quantified via the gyration tensor. For $b=N$, i.e., when attaching the side chain to the free end of the flexible backbone, the effect was strongest.

Commonly used dependence measures, such as linear correlation, cross-correlogram, or Kendall’s $\tau$, cannot capture the complete dependence structure in data unless the structure is restricted to linear, periodic, or monotonic. Mutual information (MI) has been frequently utilized for capturing the complete dependence structure including nonlinear dependence. Recently, several methods have been proposed for the MI estimation, such as kernel density estimators (KDEs), $k$-nearest neighbors (KNNs), Edgeworth approximation of differential entropy, and adaptive partitioning of the $XY$ plane. However, outstanding gaps in the current literature have precluded the ability to effectively automate these methods, which, in turn, have caused limited adoptions by the application communities. This study attempts to address a key gap in the literature—specifically, the evaluation of the above methods to choose the best method, particularly in terms of their robustness for short and noisy data, based on comparisons with the theoretical MI estimates, which can be computed analytically, as well with linear correlation and Kendall’s $\tau$. Here we consider smaller data sizes, such as 50, 100, and 1000, and within this study we characterize 50 and 100 data points as very short and 1000 as short. We consider a broader class of functions, specifically linear, quadratic, periodic, and chaotic, contaminated with artificial noise with varying noise-to-signal ratios. Our results indicate KDEs as the best choice for very short data at relatively high noise-to-signal levels whereas the performance of KNNs is the best for very short data at relatively low noise levels as well as for short data consistently across noise levels. In addition, the optimal smoothing parameter of a Gaussian kernel appears to be the best choice for KDEs while three nearest neighbors appear optimal for KNNs. Thus, in situations where the approximate data sizes are known in advance and exploratory data analysis and/or domain knowledge can be used to provide a priori insights into the noise-to-signal ratios, the results in the paper point to a way forward for automating the process of MI estimation.

At zero temperature, the elastic constants of a disordered network with bond-bending forces vanish at the geometric percolation point $p_c$, in contrast to networks with only central forces which lose the ability to withstand shear at a rigidity percolation point $p_r$. Moreover, the critical behavior of the modulus is different in the two cases. I report on extensive molecular dynamics simulations on a model system with central and bond-bending forces between the monomers over a range of temperatures $T$. The critical behavior of the shear modulus seems to be the same as that of a purely central-force network at finite $T$ and consistent with a long-standing conjecture of de Gennes.

We find that an amplitude death state and a spatiotemporally chaotic state coexist spontaneously in the Matthews-Cox equations and this coexistence is robust. Although the entire system is far from equilibrium, the domain wall between the two states is stabilized by a negative-feedback effect due to a conservation law. This is analogous to the phase separation in conserved systems that exhibit spinodal decompositions. We observe similar phenomena also in the Nikolaevskii equation, from which the Matthews-Cox equations were derived. A Galilean invariance of the former equation corresponds to the conservation law of the latter equations.

In this paper, we propose a cellular automata (CA) model for traffic flow in the framework of Kerner’s three-phase traffic theory. We mainly consider the velocity-difference effect on the randomization of vehicles. The presented model is equivalent to a combination of two CA models, i.e., the Kerner-Klenov-Wolf (KKW) CA model and the Nagel-Schreckenberg (NS) CA model with slow-to-start effect. With a given probability, vehicle dynamical rules are changed over time randomly between the rules of the NS model and the rules of the KKW model. Due to the rules of the KKW model, the speed adaptation effect of three-phase traffic theory is automatically taken into account and our model can show synchronized flow. Due to the rules of the NS model, our model can show wide moving jams. The effect of “switching" from the rules of the KKW model to the rules of the NS model provides equivalent effects to the “acceleration noise" in the KKW model. Numerical simulations are performed for both periodic and open boundaries conditions. The results are consistent with the well-known results of the three-phase traffic theory published before.