Synthesis of diisocyanides with phenolic groups and their polymerization to helically chiral poly(quinoxaline‐2,3‐diyl)s

The development of synthetic routes which lead to five new diisocyanide monomers with one or two phenolic groups is described. Their polymerization behavior is studied with Pd‐ and Ni‐based initiators, as well as under microwave irradiation. The polymerizability is mainly dominated by steric effects as is concluded from experiments using different protecting groups. Chiroptical properties of these new polymers are studied by CD‐spectroscopy. After deprotection, helically chiral poly(quinoxalin‐2,3‐diyl)s are obtained which display a Brønsted function attached to a stereolabile biaryl axis whose configuration should be influenced by the chiral polymer backbone. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2015 , 53, 1320–1329     

On the analysis of a dynamic evolutionary algorithm

Evolutionary algorithms are applied as problem-independent optimization algorithms. They are quite efficient in many situations. However, it is difficult to analyze even the behavior of simple variants of evolutionary algorithms like the (1+1) EA on rather simple functions. Nevertheless, only the analysis of the expected run time and the success probability within a given number of steps can guide the choice of the free parameters of the algorithms. Here static (1+1) EAs with a fixed mutation probability are compared with dynamic (1+1) EAs with a simple schedule for the variation of the mutation probability. The dynamic variant is first analyzed for functions typically chosen as example-functions for evolutionary algorithms. Afterwards, it is shown that it can be essential to choose the suitable variant of the (1+1) EA. More precisely, functions are presented where each static (1+1) EA has exponential expected run time while the dynamic variant has polynomial expected run time. For other functions it is shown that the dynamic (1+1) EA has exponential expected run time while a static (1+1) EA with a good choice of the mutation probability has polynomial run time with overwhelming probability.     

Bronze roman mirrors: the secret of brightness

The surface microchemical structure of high tin leaded bronze Roman mirrors has been studied by means of scanning electron microscopy combined with energy dispersive spectrometry (SEM-EDS), X-ray diffraction (XRD) and optical microscopy (OM) techniques. The results allowed understanding of the origin of their high chemical stability and silvery-lustrous appearance. Indeed, some areas of the selected Roman mirrors are still characterised by a highly reflective and silver coloured surface even though they have been buried in the soil for about 2000 years. The micro-chemical results obtained from these areas have revealed that the mirror surface was tin enriched via inverse-segregation phenomenon by tailoring the cooling parameters. Furthermore, the presence of tin could be likely enhanced via cycles of oxidation and selective copper corrosion processes, thus resulting in a tin surface enrichment as a semi-transparent amorphous-like tin oxide (SnO₂) film, as well as a copper depletion at the outer surfaces.     

Exploring interactions in high-dimensional genomic data: an overview of Logic Regression, with applications

Logic Regression is an adaptive regression methodology mainly developed to explore high-order interactions in genomic data. Logic Regression is intended for situations where most of the covariates in the data to be analyzed are binary. The goal of Logic Regression is to find predictors that are Boolean (logical) combinations of the original predictors. In this article, we give an overview of the methodology and discuss some applications. We also describe the software for Logic Regression, which is available as an R and S-Plus package.