Molecular-weight scaling of coexistence curves for monodisperse polymer solutions

The available data for the polymer volume fraction along the coexistence curves for monodisperse solutions of polystyrene in methylcyclohexane are used to derive the exponent z ≈ 0.61 such that the “correct” order parameter is only a function of ?M^Z (M is the polymer's molecular weight while ? is the reduced temperature). It is shown that a knowledge of the “correct” order parameter is unnecessary for a determination of z which is expected to be universal, i.e. independent of the polymer-solvent system.     

Solid-state photodimerization kinetics of alpha-trans-cinnamic acid to alpha-truxillic acid studied via solid-state NMR

The present work focuses on the topochemical photoconversion process in which alpha-trans-cinnamic acid becomes alpha-truxillic acid. This solid-state [2 + 2] cycloaddition reaction has previously been studied with X-ray diffraction, atomic force microscopy, and vibrational spectroscopy. However structural and kinetic details about the reaction are still debated. We present results from (13)C cross-polarization magic angle spinning solid-state NMR experiments that suggest that the Johnson, Mehl, Avrami, and Kolmogorov model of phase transformation kinetics can be applied to this system. The model elucidates parameters of the reaction, such as the nucleation rate, diffusion rate, and dimensionality of the reaction. From our data, it is concluded that this reaction follows one-dimensional growth with a decreasing nucleation rate.     

Rebalancing Multiple Assets with Mutual Price Impact

We find asymptotically optimal trading policies for long-term investors with constant relative risk aversion, in a multiple-assets market, where expected returns and covariances are constant, and the execution price of each asset is linear in the trading intensities of all assets. Trading toward the frictionless target is optimal, when the current portfolio differs from the target by a principal portfolio—an eigenvector of the inverse impact matrix times the covariance matrix. Optimal policies approach the frictionless target along nonlinear, power-shaped paths, trading faster in more liquid directions, while tolerating wider oscillations along less liquid directions.     

A method of proving non-unitarity of representations of p-adic groups I

In this paper we exhibit a new method of proving non-unitarity of representations, based on semi simplicity of unitarizable representations. Non-unitarity is proved for a half of all irreducible representations of classical p-adic groups whose infinitesimal character is the same as the infinitesimal character of a generalized Steinberg representation (as defined in Tadić, Am J Math 120:159–210, 1998). Only the Steinberg representation and its Aubert dual are expected to be unitary here. In this way we partially generalize a result of Casselman to the case of classical groups. Our argument is completely different from Casselman’s argument (which is hard to extend to this case). It requires a very limited knowledge of the inducing cuspidal representation.     

Microbial Baeyer-Villiger oxidation: stereopreference and substrate acceptance of cyclohexanone monooxygenase mutants prepared by directed evolution

[reaction: see text] An array of random mutants of cyclohexanone monooxygenase (CHMO) from Acinetobacter sp. NCIMB 9871 was screened against a library of structurally diverse ketones for modifications in the substrate acceptance profile and stereopreference of the enzymatic Baeyer-Villiger biooxidation. While the set of mutant biocatalysts was initially evolved for the enantiocomplementary oxidation of 4-hydroxycyclohexanone, improved and/or divergent stereoselectivities were observed for several substrates. In addition, expanded substrate acceptance to facilitate biotransformation of sterically demanding ketones was found.     

A continuation approach to mode-finding of multivariate Gaussian mixtures and kernel density estimates

This paper presents a novel method of multi-objective optimization by learning automata (MOLA) to solve complex multi-objective optimization problems. MOLA consists of multiple automata which perform sequential search in the solution domain. Each automaton undertakes dimensional search in the selected dimension of the solution domain, and each dimension is divided into a certain number of cells. Each automaton performs a continuous search action, instead of discrete actions, within cells. The merits of MOLA have been demonstrated, in comparison with a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and non-dominated sorting genetic algorithm II (NSGA-II), on eleven multi-objective benchmark functions and an optimal problem in the midwestern American electric power system which is integrated with wind power, respectively. The simulation results have shown that MOLA can obtain more accurate and evenly distributed Pareto fronts, in comparison with MOEA/D and NSGA-II.     

Transport in a disordered tight-binding chain with dephasing

We studied transport properties of a disordered tight-binding model (XX spin chain) in the presence of dephasing. Focusing on diffusive behaviour in the thermodynamic limit at high energies, we analytically derived the dependence of conductivity on dephasing and disorder strengths. As a function of dephasing, conductivity exhibits a single maximum at the optimal dephasing strength. The scaling of the position of this maximum with disorder strength is different for small and large disorders. In addition, we studied periodic disorder for which we found a resonance phenomenon, with conductivity having two maxima as a function of dephasing strength. If the disorder is non-zero only at a random fraction of all sites, conductivity is approximately the same as in the case of a disorder on all sites but with a rescaled disorder strength.