Nitric oxide release using natural rubber latex as matrix

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A low-cost 3D reconstruction system using a single-shot projection of a pattern matrix

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Binding of extracellular matrix proteins to Paracoccidioides brasiliensis

Adhesion to extracellular matrix (ECM) proteins plays a crucial role in invasive fungal diseases. ECM proteins bind to the surface of Paracoccidioides brasiliensis yeast cells in distinct qualitative patterns. Extracts from Pb18 strain, before (18a) and after animal inoculation (18b), exhibited differential adhesion to ECM components. Pb18b extract had a higher capacity for binding to ECM components than Pb18a. Laminin was the most adherent component for both samples, followed by type I collagen, fibronectin, and type IV collagen for Pb18b. A remarkable difference was seen in the interaction of the two extracts with fibronectin and their fragments. Pb18b extract interacted significantly with the 120-kDa fragment. Ligand affinity binding assays showed that type I collagen recognized two components (47 and 80 kDa) and gp43 bound both fibronectin and laminin. The peptide 1 (NLGRDAKRHL) from gp43, with several positively charged amino acids, contributed most to the adhesion of P. brasiliensis to Vero cells. Synthetic peptides derived from peptide YIGRS of laminin or from RGD of both laminin and fibronectin showed the greatest inhibition of adhesion of gp43 to Vero cells. In conclusion, this work provided new molecular details on the interaction between P. brasiliensis and ECNI components. (c) 2006 Elsevier SAS. All rights reserved.

Metronidazole release using natural rubber latex as matrix

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Métodos numéricos para resolução de equações diferenciais ordinárias lineares baseados em interpolação por spline

In this work we have elaborated a spline-based method of solution of inicial value problems involving ordinary differential equations, with emphasis on linear equations. The method can be seen as an alternative for the traditional solvers such as Runge-Kutta, and avoids root calculations in the linear time invariant case. The method is then applied on a central problem of control theory, namely, the step response problem for linear EDOs with possibly varying coefficients, where root calculations do not apply. We have implemented an efficient algorithm which uses exclusively matrix-vector operations. The working interval (till the settling time) was determined through a calculation of the least stable mode using a modified power method. Several variants of the method have been compared by simulation. For general linear problems with fine grid, the proposed method compares favorably with the Euler method. In the time invariant case, where the alternative is root calculation, we have indications that the proposed method is competitive for equations of sifficiently high order.

Modeling and analysis of artificial neural networks applied in operations research

Artificial neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements. Systems based on artificial neural networks have high computational rates due to the use of a massive number of these computational elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving problems related to operations research. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

The minimization of open stacks problem: A review of some properties and their use in pre-processing operations

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)