NATURAL PRODUCT SUBSTITUTION PATTERN AND SKELETAL RECOGNITION METHOD

This work describes a methodology for identification of skeletal types of diterpenes based on data base with 1500 compounds isolated from Asteraceae. One program named BOTOCSYS was built with the codification of the compounds and their botanical sources. An example of identification of a new substance is given.

Multiwavelength electronic speckle pattern interferometry for surface shape measurement

Profilometry by electronic speckle pattern interferometry with multimode diode lasers is both theoretically and experimentally studied. The multiwavelength character of the laser emission provides speckled images covered with interference fringes corresponding to the surface relief in single-exposure processes. For fringe pattern evaluation, variations of the phase-stepping technique are investigated for phase mapping as a function of the number of laser modes. Expressions for two, three, and four modes in four and eight stepping are presented, and the performances of those techniques are compared in the experiments through the surface shaping of a flat bar. The surface analysis of a peach points out the possibility of applying the technique in the quality control of food production and agricultural research. (c) 2007 Optical Society of America.

X chromosome heterochromatic pattern and nucleolar synthesis in pupal ovaries of Aedes aegypti

C-banding and silver-staining techniques were used to examine pupal ovaries of Aedes aegypti from Sao Jose do Rio Preto (Brazil). Silver staining in ovary cystocytes showed two basic patterns relative to the nucleolar morphology: viz (1) a single, compact small body; and (2) multiple bodies encompassing large nuclear areas. These two types of cystocytes were present in the ratio of 7:1, which is the same as the number of nurse cells and oocytes, respectively, in each follicle. This suggests the possibility of eventually using such a nucleolar morphological difference to recognize both cell types in developmental stages before emergence. Silver nitrate staining in metaphase chromosomes revealed centromeric bands on all six chromosomes. The C-banding pattern in metaphase chromosomes showed an intercalary band in one of the X arms, as described previously in other populations. In ovary cystocytes (pachytene stage) this C-positive band seemed to consist of two chromomeres. Phase contrast microscopy showed that the nucleolus was associated with the distal chromomere of this intercalary C-band, indicating that the nucleolus organizer region was located in that part of the heterochromatic band.

The changing pattern of analgesic and anti-inflammatory drug use in cleft lip and palate repair

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Pattern recognition theory in nonlinear signal processing

A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.