Characterization of carboxylated nanolatexes by capillary electrophoresis

Poly(styrene-co-acrylic acid) (St/AA) and poly(styrene-co-methacrylic acid) (St/MA) nanolatexes with different acid contents were prepared by emulsion copolymerization and were analyzed by capillary electrophoresis (CE) and by laser doppler velocimetry (LDV). Due to the intrinsic differences in the methodologies, CE (separative technique) and LDV (zetametry, nonseparative technique) lead to very different electrophoretic mobility distributions. Beyond these differences, the variation of the electrophoretic mobility is a complex and nonlinear function of the hydrodynamic radius, the ionic strength, and the zeta potential. To gain better insight on the influence of the ionic strength and the acid content on the electrophoretic behavior of the nanolatexes, the electrophoretic mobility data were changed into surface charge densities using the O'Brien, White, and Ohshima modeling. This approach leads to the conclusion that the surface charge density is mainly controlled at high ionic strength (～50 mM) by the adsorption of anionic surfactants coming from the sample. On the contrary, at low ionic strength, and/or in the presence of neutral surfactant in the electrolyte, the acid content was the main parameter controlling the surface charge density of the nanolatexes.     

Building custom polysaccharides in vitro with an efficient, broad-specificity xyloglucan glycosynthase and a fucosyltransferase

The current drive for applications of biomass-derived compounds, for energy and advanced materials, has led to a resurgence of interest in the manipulation of plant polymers. The xyloglucans, a family of structurally complex plant polysaccharides, have attracted significant interest due to their intrinsic high affinity for cellulose, both in muro and in technical applications. Moreover, current cell wall models are limited by the lack of detailed structure-property relationships of xyloglucans, due to a lack of molecules with well-defined branching patterns. Here, we have developed a new, broad-specificity "xyloglucan glycosynthase", selected from active-site mutants of a bacterial endoxyloglucanase, which catalyzed the synthesis of high molar mass polysaccharides, with complex side-chain structures, from suitable glycosyl fluoride donor substrates. The product range was further extended by combination with an Arabidopsis thaliana α(1→2)-fucosyltransferase to achieve the in vitro synthesis of fucosylated xyloglucans typical of dicot primary cell walls. These enzymes thus comprise a toolkit for the controlled enzymatic synthesis of xyloglucans that are otherwise impossible to obtain from native sources. Moreover, this study demonstrates the validity of a chemo-enzymatic approach to polysaccharide synthesis, in which the simplicity and economy of glycosynthase technology is harnessed together with the exquisite specificity of glycosyltransferases to control molecular complexity.     

PPA-SiO_2 catalyzed efficient synthesis of polyhydroquinoline derivatives through Hantzsch multicomponent condensation under solvent-free conditions

Silica gel-supported polyphosphoric acid（PPA-SiO₂） was found to be an efficient catalyst for the one-pot four-component Hantzsch condensation reaction of aryl aldehydes,dimedone,ethyl acetoacetate and ammonium acetate to afford the corresponding polyhydroquinoline derivatives in high yields.The main advantages of the present approach are short reaction times,clean reaction profiles,simple experimental and workup procedures.     

IDSite: An accurate approach to predict P450-mediated drug metabolism

Accurate prediction of drug metabolism is crucial for drug design. Since a large majority of drugs metabolism involves P450 enzymes, we herein describe a computational approach, IDSite, to predict P450-mediated drug metabolism. To model induced-fit effects, IDSite samples the conformational space with flexible docking in Glide followed by two refinement stages using the Protein Local Optimization Program (PLOP). Sites of metabolism (SOMs) are predicted according to a physical-based score that evaluates the potential of atoms to react with the catalytic iron center. As a preliminary test, we present in this paper the prediction of hydroxylation and O-dealkylation sites mediated by CYP2D6 using two different models: a physical-based simulation model, and a modification of this model in which a small number of parameters are fit to a training set. Without fitting any parameters to experimental data, the Physical IDSite scoring recovers 83% of the experimental observations for 56 compounds with a very low false positive rate. With only 4 fitted parameters, the Fitted IDSite was trained with the subset of 36 compounds and successfully applied to the other 20 compounds, recovering 94% of the experimental observations with high sensitivity and specificity for both sets.     

Dynamics of pistachio oils by proton nuclear magnetic resonance relaxation dispersion

A number of pistachio oils were selected in order to test the efficacy of nuclear magnetic resonance relaxation dispersion (NMRD) technique in the evaluation of differences among oils (1) obtained from seeds subjected to different thermal desiccation processes, (2) retrieved from seeds belonging to the same cultivar grown in different geographical areas and (3) produced by using seed cultivars sampled in the same geographical region. NMRD measures relaxation rate values which are related to the dynamics of the chemical components of complex food systems. Results not only allowed to relate kinematic viscosity to relaxometry parameters but also were successful in the differentiation among the aforementioned oils. In fact, from the one hand, the larger the kinematic viscosity, the faster the rotational motions appeared as compared to the translational ones. On the other hand, relaxation rate curves (NMRD) varied according to the oxidative stresses and chemical composition of each sample. The present study showed for the first time that NMRD is a very promising technique for quick evaluations of pistachio oil quality without the need for time-consuming chemical manipulations.     

Bilinear optimality constraints for the cone of positive polynomials

For a proper cone \({{\mathcal K}\subset\mathbb{R}^n}\) and its dual cone \({{\mathcal K}^*}\) the complementary slackness condition \({\langle{\rm {\bf x}},{\rm {\bf s}}\rangle=0}\) defines an n-dimensional manifold \({C({\mathcal K})}\) in the space \({{\mathbb R}^{2n}}\) . When \({{\mathcal K}}\) is a symmetric cone, points in \({C({\mathcal K})}\) must satisfy at least n linearly independent bilinear identities. This fact proves to be useful when optimizing over such cones, therefore it is natural to look for similar bilinear relations for non-symmetric cones. In this paper we define the bilinearity rank of a cone, which is the number of linearly independent bilinear identities valid for points in \({C({\mathcal K})}\) . We examine several well-known cones, in particular the cone of positive polynomials \({{\mathcal P}_{2n+1}}\) and its dual, and show that there are exactly four linearly independent bilinear identities which hold for all \({({\rm {\bf x}},{\rm {\bf s}})\in C({\mathcal P}_{2n+1})}\), regardless of the dimension of the cones. For nonnegative polynomials over an interval or half-line there are only two linearly independent bilinear identities. These results are extended to trigonometric and exponential polynomials. We prove similar results for Müntz polynomials.     

An adaptive network based fuzzy inference system–auto regression–analysis of variance algorithm for improvement of oil consumption estimation and policy making: The cases of Canada,United Kingdom,and South Korea

This paper presents an adaptive network based fuzzy inference system (ANFIS)–auto regression (AR)–analysis of variance (ANOVA) algorithm to improve oil consumption estimation and policy making. ANFIS algorithm is developed by different data preprocessing methods and the efficiency of ANFIS is examined against auto regression (AR) in Canada, United Kingdom and South Korea. For this purpose, mean absolute percentage error (MAPE) is used to show the efficiency of ANFIS. The algorithm for calculating ANFIS performance is based on its closed and open simulation abilities. Moreover, it is concluded that ANFIS provides better results than AR in Canada, United Kingdom and South Korea. This is unlike previous expectations that auto regression always provides better estimation for oil consumption estimation. In addition, ANOVA is used to identify policy making strategies with respect to oil consumption. This is the first study that introduces an integrated ANFIS–AR–ANOVA algorithm with preprocessing and post processing modules for improvement of oil consumption estimation in industrialized countries.     

Antimicrobial graphene polymer (PVK-GO) nanocomposite films

The first report on the fabrication and application of a nanocomposite containing poly-N-vinyl carbazole (PVK) polymer and graphene oxide (GO) as an antimicrobial film was demonstrated. The antimicrobial film was 90% more effective in preventing bacterial colonization relative to the unmodified surface. More importantly, the nanocomposite thin film showed higher bacterial toxicity than pure GO-modified surface.     

On the fractional derivatives of radial basis functions: Theories and applications

The paper provides the fractional integrals and derivatives of the Riemann‐Liouville and Caputo type for the five kinds of radial basis functions, including the Powers, Gaussian, Multiquadric, Matérn, and Thin‐plate splines, in one dimension. It allows to use high‐order numerical methods for solving fractional differential equations. The results are tested by solving two test problems. The first test case focuses on the discretization of the fractional differential operator while the second considers the solution of a fractional order differential equation.     

Dynamics of a hybrid vibro-impact oscillator: canonical formalism

Nonlinear Dynamics - Hybrid vibro-impact (HVI) oscillations is a strongly nonlinear dynamical regime that involves both linear oscillations and collisions under periodic, impulsive, or stochastic...