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The glass transition temperature (Tg) is one of the most important properties of polymeric materials. In order to reveal whether the scissors effect, i.e., the Fox&ndash, Flory relationship between Tg and the average molecular weight between crosslinking points (Mc), reported only in one case for polymer conetworks so far, is more generally effective or valid only for a single case, a series of poly(methyl methacrylate)-l-polyisobutylene (PMMA-l-PIB) conetworks was prepared and investigated. Two Tgs were found for the conetworks by DSC. Fox&ndash, Flory type dependence between Tg and Mc of the PMMA component (Tg = Tg,&infin, &minus, K/Mc) was observed. The K constants for the PMMA homopolymer and for the PMMA in the conetworks were the same in the margin of error. AFM images indicated disordered bicontinuous, mutually nanoconfined morphology with average domain sizes of 5&ndash, 20 nm, but the correlation between Tg and domain sizes was not found. These new results indicate that the macrocrosslinkers act like molecular scissors (scissors effect), and the Tg of PMMA depend exclusively on the Mc in the conetworks. Consequently, these findings mean that the scissors effect is presumably a general phenomenon in nanophase-separated polymer conetworks, and this finding could be utilized in designing, processing, and applications of these novel materials.

Para tentar medir e prever a “saúde financeira” de empresas, pode-se usar os chamados modelos de previsão de insolvência, construídos com apoio em técnicas estatísticas e aplicados para analisar índices econômico-financeiros selecionados, obtidos a partir dos demonstrativos contábeis. A partir da metade dos anos 90, questões tais como o aparecimento de novas técnicas de modelagem, a crescente importância da gerência do risco de crédito e as condições econômicas vigentes trouxeram de volta o interesse pela análise e previsão da insolvência de empresas. O objetivo deste artigo é descrever um método para elaboração de modelos de previsão de insolvência, fundamentado em técnicas estatísticas, e ilustrá-lo através de uma aplicação empírica a uma amostra de empresas comerciais e industriais brasileiras, empregando dados para o período de 1996 a 2000. It may happen that firms collapse irrespective of their financial statements being published in a regular basis and being prepared according to professional accounting standards and statutory requirements. The relationship between accounting data and business failure therefore deserves ongoing and expert attention. Bankruptcy prediction refers to the search for applicable models or procedures allowing to anticipate convincing signals of future problems.This paper proposes an empirical model for bankruptcy prediction that proceeds in two-stages: the first seeks to select appropriate predictors; the second employs discriminant analysis to classify successful and bankrupt firms. Empirical information has been collected from accounting data published by the Brazilian equivalent of SEC and refers to the period 1996 / 2000. Considering comparable figures reported in the literature, retained models obtain quite good hit ratios. For the selected time period, accounting data may be considered a convenient empirical support to predict bankruptcy in the Brazilian context.