Bioprospecção química da esponja callyspongia vaginalis (Callyspongiidae)

Recently, marine organisms have attracted attention because of the complexity and potent biological activity from your secondary metabolites. Our planet has 80% it surface covered by oceans and seas, therefore, housing a wide number of different forms of life, among them, the sponges. These sessile and filtrating animals, according to numerous researches, come showing like true chemistry factories. The substances from these animals, sometimes show as news targets to therapeutics agents, and some countries has already use them for treatment of some diseases. Further of the secondary metabolites, the polysaccharides of marine origin also have been target of studies, because the presence of the sulfates groups in its molecules. Polysaccharides with differents biological activities have been related in a large number of researches. Actually, many studies show the sponges as source of promising medicine. These studies inspire new researches, because the few number of sponges species studied until now. Because of that, the present work shows the chemistry prospection of the sponge Callyspongia vaginalis. Chromatographic methods in silica gel allowed the isolations of two secondary metabolites: the known β- sitosterol and a ceramide, no reported in the genus Callyspongia, previously. The analysis of the their lipid extracts show different kinds of fatty acids with a variety of chain length (saponifiable fraction), and others metabolites like Lupenone and stigmasterol, also unprecedented in the genus. The Polysaccharide characterization and the elucidation of the secondary metabolites acquired through of chromatography analysis (CC, molecular exclusion) and spectrometric (NMR 1H and 13C, mass, IR), respectively and comparison with literature data

Sistema inteligente para detecção de manchas de óleo na superfície marinha através de imagens de SAR

Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents

Model-Driven requirements engineering process aided by ontologies and natural controlled languages

Researches in Requirements Engineering have been growing in the latest few years. Researchers are concerned with a set of open issues such as: communication between several user profiles involved in software engineering; scope definition; volatility and traceability issues. To cope with these issues a set of works are concentrated in (i) defining processes to collect client s specifications in order to solve scope issues; (ii) defining models to represent requirements to address communication and traceability issues; and (iii) working on mechanisms and processes to be applied to requirements modeling in order to facilitate requirements evolution and maintenance, addressing volatility and traceability issues. We propose an iterative Model-Driven process to solve these issues, based on a double layered CIM to communicate requirements related knowledge to a wider amount of stakeholders. We also present a tool to help requirements engineer through the RE process. Finally we present a case study to illustrate the process and tool s benefits and usage