STRUCTURE AND BIFURCATION OF PULLBACK ATTRACTORS IN A NON-AUTONOMOUS CHAFEE-INFANTE EQUATION

The Chafee-Infante equation is one of the canonical infinite-dimensional dynamical systems for which a complete description of the global attractor is available. In this paper we study the structure of the pullback attractor for a non-autonomous version of this equation, u(t) = u(xx) + lambda(xx) - lambda u beta(t)u(3), and investigate the bifurcations that this attractor undergoes as A is varied. We are able to describe these in some detail, despite the fact that our model is truly non-autonomous; i.e., we do not restrict to 'small perturbations' of the autonomous case.

Assessment of Pharmaceutical Equivalence: Difference Test or Equivalence Test?

Pharmaceutical equivalence is an important step towards the confirmation of similarity and Interchangeability among pharmaceutical products, particularly regarding those that win not be tested for bioequivalence. The aim of this paper is to compare traditional difference testing to two one-side equivalence tests in the assessment of pharmaceutical equivalence, by means of equivalence studies between similar, generic and reference products of acyclovir cream, atropine sulfate injection, meropenem for injection, and metronidazole injection. All tests were performed in accordance with the Brazilian Pharmacopeia or the United States Pharmacopeia. All four possible combinations of results arise in these comparisons of difference testing and equivalence testing. Most of the former did not show significant difference, whereas the latter presented similarity. We concluded that equivalence testing is more appropriate than difference testing, what can make it a useful tool to assess pharmaceutical equivalence in products that will not be tested for bioequivalence.

Predicting the connectivity of primate cortical networks from topological and spatial node properties

Abstract Background The organization of the connectivity between mammalian cortical areas has become a major subject of study, because of its important role in scaffolding the macroscopic aspects of animal behavior and intelligence. In this study we present a computational reconstruction approach to the problem of network organization, by considering the topological and spatial features of each area in the primate cerebral cortex as subsidy for the reconstruction of the global cortical network connectivity. Starting with all areas being disconnected, pairs of areas with similar sets of features are linked together, in an attempt to recover the original network structure. Results Inferring primate cortical connectivity from the properties of the nodes, remarkably good reconstructions of the global network organization could be obtained, with the topological features allowing slightly superior accuracy to the spatial ones. Analogous reconstruction attempts for the C. elegans neuronal network resulted in substantially poorer recovery, indicating that cortical area interconnections are relatively stronger related to the considered topological and spatial properties than neuronal projections in the nematode. Conclusion The close relationship between area-based features and global connectivity may hint on developmental rules and constraints for cortical networks. Particularly, differences between the predictions from topological and spatial properties, together with the poorer recovery resulting from spatial properties, indicate that the organization of cortical networks is not entirely determined by spatial constraints.