Diferentes classificadores na predição de classes de solos em mapeamento digital.

ABSTRACT: The study had as objective to develop techniques for digital soil mapping with support of main parameters of relief descriptors, of geologic map and pedological map pre-existing of Dois Córregos (SP, BRAZIL) sheet (1:50,000 scale), using data mining techniques. It was built a database from digital topographic and thematic, and data from soils and geology. Were calculate geomorphometric slope, curvature in plan and in profile and diagonal distance of the drainage area of study. These parameters and the geological map units were crossed through georeferencing the pedological map, enabling the construction of a matrix relating soil mapping units with original caption and simplified legend to the topography and geology parameters of reference areas.. This matrix was analyzed by three different techniques of machine learning, decision trees, k-NN and Naive Bayes, who predicted the soil mapping units. We evaluated soil mapping units accuracy individually and overall maps accuracy. Our results demonstrate that increasing number of records for training the algorithm increased the individual mapping units accuracy and maps. The decision tree algorithms and k-NN had the highest accuracy in both types of legend, but low in relation to training maps.SBSR 2011

Acute phase proteins in canine lymphoma during antineoplastic chemotherapy

The lymphoma is the main hematopoietic tumor in dogs and it is characterized by the proliferation of cells from lymphoid tissue, histiocytes and its precursors. Animals with lymphoma often show changes in biochemical and hematological parameters such as non-regenerative normochromic normocytic anemia, hemolytic anemia, hypocalcaemia and monoclonal gammopathy. The development of tumor can cause alterations in serum concentrations of acute phase proteins (APPs), consequent of hepatocytes stimulus by cytokines of inflammatory action. This study aimed to quantify and qualify APPs in dogs with lymphoma, at diagnosis time and during the time of chemotherapy sessions. After syneresis, centrifugation and fractioning the serum samples of 10 healthy and 10 dogs with lymphomas, the proteins fractions were separated by polyacrilamide gel electrophoresis (SDS-PAGE) and its concentrations were determined by computer densitometry. Between 18 and 30 proteins were separated by eletrophoresis, with molecular weights ranging from 18 to 245 kDa (kilodaltons). The alpha-1-glicoprotein acid (AGP) and transferrin serum concentration showed significantly higher in dogs with lymphoma, when compared with healthy dogs at diagnosis. The alpha-1-antitripsin (AAT) serum concentrations showed significantly higher in healthy dogs, when compared with dogs with lymphoma at diagnosis. The dogs with lymphoma the albumin did not appear as negative APP. On the other hand, transferrin appeared as positive AAP at diagnosis time and during the chemotherapy sessions. Healthy dogs had AAT serum concentrations significantly higher when compared to dogs with lymphoma at diagnosis. So, in this trial, it is suggested that this protein has been shown as a negative APP in the dogs with lymphoma. These dogs presented significantly higher AGP serum concentrations, in relation to healthy dogs at diagnosis, evidencing this protein APP positive behavior in neoplasm