Modelagem estocástica do índice de radiação ultravioleta na costa leste do nordeste do Brasil

The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (João Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period

Identificação e avaliação de propriedades de polissacarídeos sulfatados de diferentes fontes naturais que possibilitem sua aplicabilidade biotecnológica

Sulfated polysaccharides (SP) are widely distributed in animals and seaweeds tissues. These polymers have been studied in light of their important pharmacological activities, such as anticoagulant, antioxidant, antitumoral, anti-inflammatory, and antiviral properties. On other hand, SP potential to synthesize biomaterials like as nanoparticules has not yet been explored. In addition, to date, SP have only been found in six plants and all inhabit saline environments. However, the SP pharmacological plant activities have not been carrying out. Furthermore, there are no reports of SP in freshwater plants. Thus, do SP from marine plants show pharmacological activity? Do freshwater plants actually synthesize SP? Is it possible to synthesize nanoparticles using SP from seaweed? In order to understand this question, this Thesis was divided into tree chapters. In the first chapter a sulfated polysaccharide (SPSG) was successfully isolated from marine plant Halodule wrightii. The data presented here showed that the SPSG is a 11 kDa sulfated heterogalactan contains glucose and xylose. Several assays suggested that the SPSG possessed remarkable antioxidant properties in different in vitro assays and an outstanding anticoagulant activity 2.5-fold higher than that of heparin Clexane® in the aPTT test; in the next chapter using different tools such as chemical and histological analyses, energy-dispersive X-ray analysis (EDXA), gel electrophoresis and infra-red spectroscopy we confirm the presence of sulfated polysaccharides in freshwater plants for the first time. Moreover, we also demonstrate that SP extracted from E. crassipes root has potential as an anticoagulant compound; and in last chapter a fucan, a sulfated polysaccharide, extracted from the brown seaweed was chemically modified by grafting hexadecylamine to the polymer hydrophilic backbone. The resulting modified material (SNFuc) formed nanosized particles. The degree of substitution for hydrophobic chains of 1H NMR was approximately 93%. SNFfuc-TBa125 in aqueous media had a mean diameter of 123 nm and zeta potential of -38.3 ± 0.74 mV, measured bydynamic light scattering. Tumor-cell (HepG2, 786, H-S5) proliferation was inhibited by 2.0 43.7% at SNFuc concentrations of 0.05 0.5 mg/ mL and RAEC non-tumor cell line proliferation displayed inhibition of 8.0 22.0%. On the other hand, nanogel improved CHO and RAW non-tumor cell line proliferation in the same concentration range. Flow cytometric analysis revealed that this fucan nanogel inhibited 786 cell proliferation through caspase and caspaseindependent mechanisms. In addition, SNFuc blocks 786 cell passages in the S and G2-M phases of the cell cycle

Análise e classificação de imagens de lesões da pele por atributos de cor, forma e textura utilizando máquina de vetor de suporte

The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries