High-resolution adiabatic scanning calorimetry and differential scanning calorimetry have been employed to study the thermal behavior of an organo-siloxane tetrapode reported to exhibit a biaxial nematic phase. No signature of the uniaxial to biaxial nematic phase transition could be retraced in sequential heating and cooling runs under different scanning rates, within the experimental resolution. The results obtained reveal that an extremely small heat should be involved in the uniaxial to biaxial nematic phase transition. The isotropic to uniaxial nematic transition at $318\pm 0.01\mathrm{K}$ is very stable, and it is weakly first order with a rather small latent heat of $0.20\pm 0.02\mathrm{J}∕\mathrm{g}$.

We have measured the shear force for short double-stranded DNA sequences pulled by either the $3^{\prime }{3}^{\prime }$ or $5^{\prime }{5}^{\prime }$ ends and find that the shear force is independent of the pulling technique. For the 50% GC sequences examined, the force is a linear function of DNA length up to 20 base pairs (bp); however, we show that, as predicted by deGennes, the shear force approaches an asymptotic value in the limit where the number of base pairs approaches infinity, where the shear force for a $32\mathrm{bp}$ sequence is within 5% of the asymptotic value of $61.4\mathrm{pN}$. Fits to deGennes’ theory suggest that the shear force is distributed over fewer than $10\mathrm{bp}$ at the end of the sequence, with the rest of the sequence experiencing negligible shear force. The single base pair rupture force and the ratio of the backbone spring constant to the base pair spring constant determined from fits of the data to deGennes’ theory are consistent with ab initio predictions.

The phase diagrams for lysozyme are calculated for two different precipitant salts, NaCl and NaSCN, using a potential of mean force that takes into account contributions from ion-dispersion forces [M. Boström et al., J. Phys. Chem. B 110, 24757 (2006)]. Our results are consistent with a recent perturbation theory calculation (referenced above) in that the phase diagram for lysozyme with NaCl is quite different than for lysozyme with NaSCN for the same molar concentration $\left(0.2\mathrm{M}\right)$. However, in contrast to the perturbation theory calculation, we find that the lysozyme phase diagram with NaCl has a metastable fluid-fluid coexistence curve and that the metastability gap in the case of NaSCN is much larger than predicted by perturbation theory.

In this paper, numerical simulation of calcium waves in a network of cells coupled together by a paracrine signaling is investigated. The model takes into account the long-range interaction between cells due to the action of extracellular messengers, which provide links between first-neighbor cells, but also on cells located far away from the excited cell. When considering bidirectional coupling, the long-range interaction influences neither the frequency nor the amplitude of oscillations, contrary to one-directional coupling. The long-range interaction influences the speed of propagation of ${\mathrm{Ca}}^{2+}$ waves in the network and induces enlargement of the transition zone before the steady regime of propagation is attained. We also investigate the long-range effects on the colonization of a given niche by a pathogenic microorganism signal on calcium wave propagation in the network.

We use a particle-based model of a swarm of interacting particles to explore analytically the conditions for the formation of vortexlike behavior. Our model uses pairwise interaction potentials to model weak long-range attraction and strong short-range repulsion with a dissipation function to align particle velocity vectors. We use the effective energy of the swarm as a Lyapunov function to prove convergence to a vortexlike state. Our analysis extends previous work which has relied purely on simulation to explore the formation and stability of vortexlike behavior through analytical rather than numerical methods.

In this Comment, we point out that the Euler-Lagrange equations, which are referred to as the general equilibrium shape equations presented by Zhang et al. [Phys. Rev. E 70, 051902 (2004)] are incorrect, along with equations derived from them. The correct equations are provided here and they are cross-checked using certain energy functions previously presented in the literature. Further, with the use of the correct equations, we present new numerical results, which for the values of the constants given by Zhang et al. do not give rise to the physical behavior observed for DNA by those authors. However, the correct equations can be consistent with sensible behavior for different values of the constants.

By means of LaSalle’s invariance principle, we propose an adaptive controller with the aim of stabilizing an unstable steady state for a wide class of nonlinear dynamical systems. The control technique does not require analytical knowledge of the system dynamics and operates without any explicit knowledge of the desired steady-state position. The control input is achieved using only system states with no computer analysis of the dynamics. The proposed strategy is tested on Lorentz, van der Pol, and pendulum equations.

We present gyrokinetic neoclassical simulations of tokamak plasmas with a self-consistent electric field using a fully nonlinear (full-$f$) continuum code TEMPEST in a circular geometry. A set of gyrokinetic equations are discretized on a five-dimensional computational grid in phase space. The present implementation is a method of lines approach where the phase-space derivatives are discretized with finite differences, and implicit backward differencing formulas are used to advance the system in time. The fully nonlinear Boltzmann model is used for electrons. The neoclassical electric field is obtained by solving the gyrokinetic Poisson equation with self-consistent poloidal variation. With a four-dimensional $\left(\psi ,\theta ,ϵ,\mu \right)$ version of the TEMPEST code, we compute the radial particle and heat fluxes, the geodesic-acoustic mode, and the development of the neoclassical electric field, which we compare with neoclassical theory using a Lorentz collision model. The present work provides a numerical scheme for self-consistently studying important dynamical aspects of neoclassical transport and electric field in toroidal magnetic fusion devices.

We report on the interaction of hydrogen atoms and molecules under high flux conditions with a cooled copper surface and its impact on gas phase densities and internal excitation of the molecules. These densities were measured by means of laser-induced fluorescence using tunable radiation sources in the vacuum-ultraviolet (vuv). While H atoms were detected by two-photon absorption laser-induced fluorescence, the necessary vuv radiation for the detection of rovibrationally excited ${\mathrm{H}}_2$ molecules in the electronic ground state were produced by stimulated anti-Stokes Raman scattering. The results reveal a strong loss mechanism of H atoms and the formation of rovibrationally excited ${\mathrm{H}}_2$ molecules due to surface interaction. The surface reaction probability of H atoms under high flux conditions on copper was estimated. Surface collisions are shown to have a profound influence on the density distribution of rovibrationally excited ${\mathrm{H}}_2$ molecules: The distributions follow lower temperatures and are less Boltzmann-like, i.e., the distributions of the internal excitation of ${\mathrm{H}}_2$ molecules differ more from thermodynamic equilibrium.

A structured composite of the negative index of refraction was fabricated by one layer of cross-I-shaped metal pairs. In this structure, the electric and magnetic inclusions were effectively integrated into one small unit. We varied the spacing of the cross pair to control the location of the magnetic resonance mode and their intercoupling with the electric mode. The frequency dependences of permittivity, permeability, and refractive indices with different gap widths of the pairs were systematically discussed by free-space measurement as well as numerical simulation. A spacing window dependent on the geometrical parameters was found in which the real part of the refractive index could have a negative value. The one-layer cross-pair pattern proposed in this work can be extended to three-dimensional structures with well-controlled interlayer coupling that will greatly facilitate the fabrication and measurement of negative-index materials in high frequencies.

The conditions for the propagation of modulated waves on a system of two coupled discrete nonlinear $LC$ transmission lines with negative nonlinear resistance are examined, each line of the network containing a finite number of cells. Our theoretical analysis shows that the telegrapher equations of the electrical transmission line can be reduced to a set of two coupled discrete complex Ginzburg-Landau equations. Using the standard linear stability analysis, we derive the expression for the growth rate of instability as a function of the wave numbers and system parameters, then obtain regions of modulational instability. Using numerical simulations, we examine the long-time dynamics of modulated waves in the line. This leads to the generation of nonlinear modulated waves which have the shape of a soliton for the fast and low modes. The effects of dissipative elements on the propagation are also shown. The analytical results are corroborated by numerical simulations.

We study a model short-range attractive fluid under shear. For this system, the strength of interparticle attractions strongly influences the equilibrium structural order. We find that shear monotonically decreases structural order regardless of the strength of the attractions. There is a strong correlation between shear-rate-dependent viscosity and a structural order metric, suggesting a structurally based constitutive equation. This correlation also holds for the Lennard-Jones fluid.

The statement of the title is shown by numerical simulation of homogeneously sheared assemblies of frictionless, nearly rigid beads in the quasistatic limit. Results coincide for steady flows at constant shear rate $\dot{\gamma }$ in the limit of small $\dot{\gamma }$ and static approaches, in which packings are equilibrated under growing deviator stresses. The internal friction angle $\phi$, equal to $5.76°\pm 0.22°$ in simple shear, is independent of average pressure $P$ in the rigid limit and stems from the ability of stable frictionless contact networks to form stress-induced anisotropic fabrics. No enduring strain localization is observed. Dissipation at the macroscopic level results from repeated network rearrangements, similar to the effective friction of a frictionless slider on a bumpy surface. Solid fraction $\Phi$ remains equal to the random close packing value $\simeq 0.64$ in slowly or statically sheared systems. Fluctuations of stresses and volume are observed to regress in the large system limit. Defining the inertial number as $I=\dot{\gamma }\sqrt{m/\left(aP\right)}$, with $m$ the grain mass and $a$ its diameter, both internal friction coefficient ${\mu }^{\ast }=\text{tan}\phi$ and volume $1/\Phi$ increase as powers of $I$ in the quasistatic limit of vanishing $I$, in which all mechanical properties are determined by contact network geometry. The microstructure of the sheared material is characterized with a suitable parametrization of the fabric tensor and measurements of coordination numbers.

We study the response of probe particles to weak constant driving in kinetically constrained models of glassy systems, and show that the probe’s response can be nonmonotonic and give rise to negative differential mobility: increasing the applied force can reduce the probe’s drift velocity in the force direction. Other significant nonlinear effects are also demonstrated, such as the enhancement with increasing force of the probe’s fluctuations away from the average path, a phenomenon known in other contexts as giant diffusivity. We show that these results can be explained analytically by a continuous-time random walk approximation where there is decoupling between persistence and exchange times for local displacements of the probe. This decoupling is due to dynamic heterogeneity in the glassy system, which also leads to bimodal distributions of probe particle displacements. We discuss the relevance of our results to experiments.

We describe dynamic modes that originate from shape and structure fluctuations in a droplet microemulsion system. The modes are decoupled by a contrast variation neutron scattering technique using the relative intermediate form factor method. The strategy of the method is analogous to the relative form factor method, which decouples the form and structure factors from the small-angle neutron scattering intensity [M. Nagao et al., Phys. Rev. E 75, 061401 (2007)]. First, we will briefly explain theoretical and experimental approaches to understanding neutron spin echo (NSE) data from droplet microemulsion systems. Then we will introduce the relative intermediate form factor method, which decouples shape and structure fluctuations. The concentration dependence of the droplet dynamics in a microemulsion system is used to elucidate the strengths of this method. The intermediate form and structure factors are successfully decoupled from an observed intermediate scattering function by NSE. The decay rate of the shape fluctuation modes linearly decreases, while the fluctuation amplitude increases as the droplet concentration increases. The first cumulant of the obtained intermediate structure factor shows a clear de Gennes narrowing behavior at a length scale corresponding to the interdroplet distance. However, in the high-momentum-transfer and longer-time regions, the first cumulant deviates from the intermediate structure factor. This result suggests the existence of other dynamic modes of structure fluctuations rather than the center-of-mass diffusion mode.

We report on an interesting formulation of a phase-field model which incorporates a description of individual phases and particles with preserved volume evolving in a system of multiple phases such that the interfacial energy decreases. In our model, an antiforcing free energy density is defined to fulfill constraints on selected volume fractions by counterbalancing phase changes. Phases are defined as regions with energy bearing boundaries that may differ in their physical states, i.e., the regions may be distinguished in structure (crystal transformations), in composition (alloys, mixtures of fluids), or in the orientation of the crystal lattice (grains). The method allows one to simulate the formation of equilibrium crystal shapes and of the migration of inert particles and phases in microstructures. We show two- and three-dimensional simulations of bubble ensembles and foam textures and demonstrate the excellent agreement of crystal morphology configurations with analytical results.

We establish an expression of the entropy-from-work theorem that is complementary to the one originally proposed by Talkner, Hanggi, and Morillo [Phys. Rev. E 77, 051131 (2008)]. In the original expression the final energy is fixed, whereas in the present expression the initial energy is fixed.

We present the derivation of the continuous-time equations governing the limit dynamics of discrete-time reaction-diffusion processes defined on heterogeneous metapopulations. We show that, when a rigorous time limit is performed, the lack of an epidemic threshold in the spread of infections is not limited to metapopulations with a scale-free architecture, as it has been predicted from dynamical equations in which reaction and diffusion occur sequentially in time.

The choice of free parameters in network models is subjective, since it depends on what topological properties are being monitored. However, we show that the maximum likelihood (ML) principle indicates a unique, statistically rigorous parameter choice, associated with a well-defined topological feature. We then find that, if the ML condition is incompatible with the built-in parameter choice, network models turn out to be intrinsically ill defined or biased. To overcome this problem, we construct a class of safely unbiased models. We also propose an extension of these results that leads to the fascinating possibility to extract, only from topological data, the “hidden variables” underlying network organization, making them “no longer hidden.” We test our method on World Trade Web data, where we recover the empirical gross domestic product using only topological information.

The entropy of a hierarchical network topology in an ensemble of sparse random networks, with “hidden variables” associated with its nodes, is the log-likelihood that a given network topology is present in the chosen ensemble. We obtain a general formula for this entropy, which has a clear interpretation in some simple limiting cases. The results provide keys with which to solve the general problem of “fitting” a given network with an appropriate ensemble of random networks.