Deuterium NMR Study of Orientational Order in Cellulosic Network Microfibers

Deuterium NMR was used to investigate the orientational order in a composite cellulosic formed by liquid crystalline acetoxypropylcellulose (A PC) and demented nematic 4'-penty1-4-cyanobiphenyl (5CB-4 alpha d(2)) with the per centage of 85% A PC by weight Three forms of the composite including electro spun microfibers, thin film and bulk samples were analyzed The NMR results initially suggest two distinct scenarios, one whet e the 503-alpha d(2), is confined to small droplets with dimensions smaller than the magnetic coherence length and the other where the 503-alpha d(2) molecules arc aligned with the A PC network chains Polarized optical microscopy (POW from thin film samples along with all the NMR results show the presence of 5CB-alpha d(2) droplets in the composite systems with a nematic wetting layer at the APC-5CB-alpha d(2) interface that experiences and order disorder transition driven by the polymer network N-I transition The characterization of the APC network I-N transition shows a pronounced subcritical behavior within a heterogeneity scenario.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

Caracterização por optical coherence tomography (OCT) de placas coronárias sujeitas a cutting balloon: contributo das técnicas bidiomensional e tridimensional

Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular - Área de especialização: Intervenção cardiovascular