Emission characteristics of a homologous series of bimesogenic liquid-crystal lasers.

In this study we have fabricated eight different liquid-crystal lasers using the same gain medium but different homologues from the bimesogenic series alpha-(2',4-difluorobiphenyl-4'-yloxy)-omega-(4-cyanobiphenyl-4'-yloxy)alkanes, whereby the number of methylene units in the spacer chain varied from n=5 to n=12. To quantify the performance of these lasers, the threshold energy and the slope efficiency were extracted from the input-output characteristics of each laser. A clear odd-even effect was observed when both the excitation threshold and the slope efficiency were plotted as a function of the number of methylene units in the spacer chain. In all cases, the bimesogen lasers for which n is even exhibit lower threshold energies and higher slope efficiencies than those for which n is odd. These results are then interpreted in terms of the macroscopic physical properties of the liquid-crystalline compounds. In accordance with a previous study [S. M. Morris, A. D. Ford, M. N. Pivnenko, O. Hadeler, and H. J. Coles, Phys. Rev. E. 74, 061709 (2006)], a combination of a large birefringence and high order parameters are found, in the most part, to correlate with low-threshold energy and high slope efficiency. This indicates that the threshold and slope efficiency are dominated by the host macroscopic properties as opposed to intermolecular interactions between the dye and the liquid crystal. However, certain differences in the slope efficiency could not be explained by the birefringence and order parameter values alone. Instead, we find that the slope efficiency is further increased by increasing the elastic constants of the liquid-crystal host so as to decrease the scattering losses incurred by local distortions in the director field under high-energy optical excitation.

A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series.

Understanding the regulatory mechanisms that are responsible for an organism's response to environmental change is an important issue in molecular biology. A first and important step towards this goal is to detect genes whose expression levels are affected by altered external conditions. A range of methods to test for differential gene expression, both in static as well as in time-course experiments, have been proposed. While these tests answer the question whether a gene is differentially expressed, they do not explicitly address the question when a gene is differentially expressed, although this information may provide insights into the course and causal structure of regulatory programs. In this article, we propose a two-sample test for identifying intervals of differential gene expression in microarray time series. Our approach is based on Gaussian process regression, can deal with arbitrary numbers of replicates, and is robust with respect to outliers. We apply our algorithm to study the response of Arabidopsis thaliana genes to an infection by a fungal pathogen using a microarray time series dataset covering 30,336 gene probes at 24 observed time points. In classification experiments, our test compares favorably with existing methods and provides additional insights into time-dependent differential expression.