Theory for the nonequilibrium dynamics of flexible chain molecules: relaxation to equilibrium of pentadecane from an all-trans conformation

We extend to nonequilibrium processes our recent theory for the long time dynamics of flexible chain molecules. While the previous theory describes the equilibrium motions for any bond or interatomic separation in (bio)polymers by time correlation functions, the present extension of the theory enables the prediction of the nonequilibrium relaxation that occurs in processes, such as T-jump experiments, where there are sudden transitions between, for example, different equilibrium states. As a test of the theory, we consider the ``unfolding'' of pentadecane when it is transported from a constrained all-trans conformation to a random-coil state at thermal equilibrium. The time evolution of the mean-square end-to-end distance after release of the constraint is computed both from the theory and from Brownian dynamics (BD) simulations. The predictions of the theory agree very well with the BD simulations. Furthermore, the theory produces enormous savings in computer time. This work is a starting point for the application of the new method to nonequilibrium processes with biological importance such as the helix-coil transition and protein folding.Comment: 11 pages total, including 2 Postscript figures; submitted to Journal of Chemical Physic

Interaction driven metal-insulator transition in strained graphene

The question of whether electron-electron interactions can drive a metal to insulator transition in graphene under realistic experimental conditions is addressed. Using three representative methods to calculate the effective long-range Coulomb interaction between $\pi$-electrons in graphene and solving for the ground state using quantum Monte Carlo methods, we argue that without strain, graphene remains metallic and changing the substrate from SiO$_2$ to suspended samples hardly makes any difference. In contrast, applying a rather large -- but experimentally realistic -- uniform and isotropic strain of about $15\%$ seems to be a promising route to making graphene an antiferromagnetic Mott insulator.Comment: Updated version: 6 pages, 3 figure

The role of electron-electron interactions in two-dimensional Dirac fermions

The role of electron-electron interactions on two-dimensional Dirac fermions remains enigmatic. Using a combination of nonperturbative numerical and analytical techniques that incorporate both the contact and long-range parts of the Coulomb interaction, we identify the two previously discussed regimes: a Gross-Neveu transition to a strongly correlated Mott insulator, and a semi-metallic state with a logarithmically diverging Fermi velocity accurately described by the random phase approximation. Most interestingly, experimental realizations of Dirac fermions span the crossover between these two regimes providing the physical mechanism that masks this velocity divergence. We explain several long-standing mysteries including why the observed Fermi velocity in graphene is consistently about 20 percent larger than the best values calculated using ab initio and why graphene on different substrates show different behavior.Comment: 11 pages, 4 figure

Pinning control of fractional-order weighted complex networks

In this paper, we consider the pinning control problem of fractional-order weighted complex dynamical networks. The well-studied integer-order complex networks are the special cases of the fractional-order ones. The network model considered can represent both directed and undirected weighted networks. First, based on the eigenvalue analysis and fractional-order stability theory, some local stability properties of such pinned fractional-order networks are derived and the valid stability regions are estimated. A surprising finding is that the fractional-order complex networks can stabilize itself by reducing the fractional-order q without pinning any node. Second, numerical algorithms for fractional-order complex networks are introduced in detail. Finally, numerical simulations in scale-free complex networks are provided to show that the smaller fractional-order q, the larger control gain matrix D, the larger tunable weight parameter , the larger overall coupling strength c, the more capacity that the pinning scheme may possess to enhance the control performance of fractional-order complex networks

Partitioning of Poly(amidoamine) Dendrimers between n-Octanol and Water

Dendritic nanomaterials are emerging as key building blocks for a variety of nanoscale materials and technologies. Poly(amidoamine) (PAMAM) dendrimers were the first class of dendritic nanomaterials to be commercialized. Despite numerous investigations, the environmental fate, transport, and toxicity of PAMAM dendrimers is still not well understood. As a first step toward the characterization of the environmental behavior of dendrimers in aquatic systems, we measured the octanol−water partition coefficients (logK_(ow)) of a homologous series of PAMAM dendrimers as a function of dendrimer generation (size), terminal group and core chemistry. We find that the logKow of PAMAM dendrimers depend primarily on their size and terminal group chemistry. For G1-G5 PAMAM dendrimers with terminal NH_2 groups, the negative values of their logK_(ow) indicate that they prefer to remain in the water phase. Conversely, the formation of stable emulsions at the octanol−water (O/W) interface in the presence of G6-NH_2 and G8-NH_2 PAMAM dendrimers suggest they prefer to partition at the O/W interface. In all cases, published studies of the cytotoxicity of Gx-NH_2 PAMAM dendrimers show they strongly interact with the lipid bilayers of cells. These results suggest that the logKow of a PAMAM dendrimer may not be a good predictor of its affinity with natural organic media such as the lipid bilayers of cell membranes

Density functional theory of inhomogeneous liquids. I. The liquid-vapor interface in Lennard-Jones fluids

A simple model is proposed for the direct correlation function (DCF) for simple fluids consisting of a hard-core contribution, a simple parametrized core correction, and a mean-field tail. The model requires as input only the free energy of the homogeneous fluid, obtained, e.g., from thermodynamic perturbation theory. Comparison to the DCF obtained from simulation of a Lennard-Jones fluid shows this to be a surprisingly good approximation for a wide range of densities. The model is used to construct a density functional theory for inhomogeneous fluids which is applied to the problem of calculating the surface tension of the liquid-vapor interface. The numerical values found are in good agreement with simulation

Semantic analysis of field sports video using a petri-net of audio-visual concepts

The most common approach to automatic summarisation and highlight detection in sports video is to train an automatic classifier to detect semantic highlights based on occurrences of low-level features such as action replays, excited commentators or changes in a scoreboard. We propose an alternative approach based on the detection of perception concepts (PCs) and the construction of Petri-Nets which can be used for both semantic description and event detection within sports videos. Low-level algorithms for the detection of perception concepts using visual, aural and motion characteristics are proposed, and a series of Petri-Nets composed of perception concepts is formally defined to describe video content. We call this a Perception Concept Network-Petri Net (PCN-PN) model. Using PCN-PNs, personalized high-level semantic descriptions of video highlights can be facilitated and queries on high-level semantics can be achieved. A particular strength of this framework is that we can easily build semantic detectors based on PCN-PNs to search within sports videos and locate interesting events. Experimental results based on recorded sports video data across three types of sports games (soccer, basketball and rugby), and each from multiple broadcasters, are used to illustrate the potential of this framework