Polymerization of Bisacrylic Monomers within a Liquid-Crystalline Smectic B Solvent

Abstract

A smectic B (S,) solvent may provide a very highly ordered, and possibly oriented, host medium for polymerization processes. Photochemical polymerizations of two bisacrylic monomers were therefore carried out in a S_B medium. The process conditions were chosen on the basis of a preliminary study of the monomer-solvent binary system carried out by differential scanning calorimetry (D.S.C.), optical microscopy and X-ray diffraction. The polymerization was then studied by D.S.C. at different reaction times. These measurements showed clearly that there is a point along the reaction path at which the growing polymer chains start segregating from the solvent and the mesomorphic bulk no longer acts as a reaction solvent but only as a reservoir for the ponomer. The polymer chains from that point keep growing only upon or between the faces of the S_B layers. Electron microscopy observations showed that the morphology of the final polymer is affected by this interlayer process.     

Organic–inorganic interpenetrating polymer networks and hybrid polymer materials prepared by frontal polymerization

Novel polyacrylamide‐based hydrogels containing 3‐(trimethoxysilyl)propyl methacrylate and/or tetraethoxy silane were synthesized by means of frontal polymerization, using ammonium persulfate as initiator, N,N′‐methylene bisacrylamide as crosslinking agent and dimethyl sulfoxide as solvent. The obtained samples were treated at pH of 2 or 5 to induce the sol–gel reaction and evaluate their swelling behavior in the conditions. The occurrence of this reaction was assessed by solid‐state NMR. Moreover, the thermal properties of the dry materials were studied by differential scanning calorimetry and thermal gravimetric analysis, and their water‐contact angles were measured. It was found that the amount of Si affects the extent of swelling and the hydrophilicity of the resulting materials. © 2013 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2013 , 51, 4618–4625     

Portfolio management under sudden changes in volatility and heterogeneous investment horizons

We analyze the implications for portfolio management of accounting for conditional heteroskedasticity and sudden changes in volatility, based on a sample of weekly data of the Dow Jones Country Titans, the CBT-municipal bond, spot and futures prices of commodities for the period 1992–2005. To that end, we first proceed to utilize the ICSS algorithm to detect long-term volatility shifts, and incorporate that information into PGARCH models fitted to the returns series. At the next stage, we simulate returns series and compute a wavelet-based value at risk, which takes into consideration the investor's time horizon. We repeat the same procedure for artificial data generated from semi-parametric estimates of the distribution functions of returns, which account for fat tails. Our estimation results show that neglecting GARCH effects and volatility shifts may lead to an overestimation of financial risk at different time horizons. In addition, we conclude that investors benefit from holding commodities as their low or even negative correlation with stock and bond indices contribute to portfolio diversification.     

On numerical errors and turbulence modeling in tip vortex flow prediction

The accuracy of tip vortex flow prediction in the near‐field region is investigated numerically by attempting to quantify the shortcomings of the turbulence models and the flow solver. In particular, some turbulence models can produce a ‘numerical diffusion’ that artificially smears the vortex core. Low‐order finite differencing techniques of the convective and pressure terms of the Navier–Stokes equations and inadequate grid density and distribution can also produce the same adverse effect. The flow over a wing and the near‐wake with the wind tunnel walls included was simulated using 2.5 million grid points. Two subset problems, one using a steady, three‐dimensional analytical vortex, and the other, a vortex obtained from experiment and propagated downstream, were also devised in order to make the study of vortex preservation more tractable. The method of artificial compressibility is used to solve the steady, three‐dimensional, incompressible Navier–Stokes equations. Two one‐equation turbulence models (Baldwin–Barth and Spalart–Allmaras turbulence models), have been used with the production term modified to account for the stabilizing effect of the nearly solid body rotation in the vortex core. Finally, a comparison between the computed results and experiment is presented. Published in 1999 by John Wiley & Sons, Ltd.     

Parsimonious Optimization of Multitask Neural Network Hyperparameters

Neural networks are rapidly gaining popularity in chemical modeling and Quantitative Structure–Activity Relationship (QSAR) thanks to their ability to handle multitask problems. However, outcomes of neural networks depend on the tuning of several hyperparameters, whose small variations can often strongly affect their performance. Hence, optimization is a fundamental step in training neural networks although, in many cases, it can be very expensive from a computational point of view. In this study, we compared four of the most widely used approaches for tuning hyperparameters, namely, grid search, random search, tree-structured Parzen estimator, and genetic algorithms on three multitask QSAR datasets. We mainly focused on parsimonious optimization and thus not only on the performance of neural networks, but also the computational time that was taken into account. Furthermore, since the optimization approaches do not directly provide information about the influence of hyperparameters, we applied experimental design strategies to determine their effects on the neural network performance. We found that genetic algorithms, tree-structured Parzen estimator, and random search require on average 0.08% of the hours required by grid search; in addition, tree-structured Parzen estimator and genetic algorithms provide better results than random search.     

X-ray crystallography at macromolecular resolution: A solution of the phase problem

The problem of crystal structure analysis at macromolecular resolution is tackled using notions borrowed from small-angle solution-scattering studies. The mathematical procedure - essentially a pattern recognition approach - consists of generating all the phase combinations compatible with the data and screening them: the critical steps are the choice of the “pattern” and of the criteria which preside the “recognition”. Two strategies are adopted. One is based upon use of the histogram of the electron density maps, a function more dependent on chemical composition than on physical structure: the histograms of samples of different structure and similar chemical composition are compared in search for similarity. The other strategy operates on the electron density maps and involves the principle of maximum smoothness. From the practical viewpoint, one single parameter, (Δp)⁴, is found to play an outstanding role in the two cases. Algorithms are worked out, implemented on the computer and tested using a variety of lipid-water phases. The comparison of samples of different structure and similar chemical composition is found to provide a powerful screening criterion. The principle of maximum smoothness is also of great help, at least to the extent that the electron density distribution is a fairly smooth function, devoid of sharp peaks (associated with heavy atoms). The practical aspects of the algorithms are discussed, as well as their possible application to crystallographic problems of more general interest.     

Phenolic Characterization and Neuroprotective Properties of Grape Pomace Extracts

Vitis vinifera (grape) contains various compounds with acknowledged phytochemical and pharmacological properties. Among the different parts of the plant, pomace is of particular interest as a winemaking industry by-product. A characterization of the water extract from grape pomace from Montepulciano d’Abruzzo variety (Villamagna doc) was conducted, and the bioactive phenolic compounds were quantified through HPLC-DAD-MS analysis. HypoE22, a hypothalamic cell line, was challenged with an oxidative stimulus and exposed to different concentrations (1 µg/mL⁻¹ mg/mL) of the pomace extract for 24, 48, and 72 h. In the same conditions, cells were exposed to the sole catechin, in a concentration range (5–500 ng/mL) consistent with the catechin level in the extract. Cell proliferation was investigated by MTT assay, dopamine release through HPLC-EC method, PGE₂ amount by an ELISA kit, and expressions of neurotrophin brain-derived neurotrophic factor (BDNF) and of cyclooxygenase-2 (COX-2) by RT-PCR. The extract reverted the cytotoxicity exerted by the oxidative stimulus at all the experimental times in a dose-dependent manner, whereas the catechin was able to revert the oxidative stress-induced depletion of dopamine 48 h and 72 h after the stimulus. The extract and the catechin were also effective in preventing the downregulation of BDNF and the concomitant upregulation of COX-2 gene expression. In accordance, PGE₂ release was augmented by the oxidative stress conditions and reverted by the administration of the water extract from grace pomace and catechin, which were equally effective. These results suggest that the neuroprotection induced by the extract could be ascribed, albeit partially, to its catechin content.