O Laboratório didático de química e a educação a distância: investigação preliminar de uma atividade prática

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Conhecimentos presentes na disciplina de análise nos cursos de licenciatura em Matemática no Brasil

Pós-graduação em Educação Matemática - IGCE

Drying of persimmon: Mathematical model for diffusivity as a simultaneous function of moisture content and shrinkage

Fresh persimmon has a high moisture content (about 85% wet basis) making it highly perishable and requiring adequate drying conditions to obtain an acceptable dehydrated product. Drying kinetics of persimmon cv. Rama Forte was studied in a fixed bed dryer at temperatures ranging from 50 to 80 degreesC and air velocity of 0.8 m/s. Shrinkage during drying was described by a linear correlation with respect to water content. Evaluation of effective diffusivity as a function of moisture content, with undergoing shrinkage during drying was based on Fourier series solution of Fick's diffusion equation. Effective diffusivity values at moisture contents between 0.09 - 4.23 kg water/kg dry matter were found to be in the range of 2.6 x 10(-10) m(2)/s to 5.4 x 10(-10) m(2)/s, and its dependence on air drying temperature was represented by an Arrhenius type equation. Activation energy increased with decreasing water content in persimmons.

A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements

The accurate identification of the nitrogen content in plants is extremely important since it involves economic aspects and environmental impacts, Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification in plants involves a lot of non-linear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought SPAD index using artificial neural networks (ANN). The network acts as identifier of relationships among, crop varieties, fertilizer treatments, type of leaf and nitrogen content in the plants (target). So, nitrogen content can be generalized and estimated and from an input parameter set. This approach can form the basis for development of an accurate real time system to predict nitrogen content in plants.

Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks

The accurate identification of the nitrogen content in crop plants is extremely important since it involves economic aspects and environmental impacts. Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification involves a lot of nonlinear parametes and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought spectral reflectance of plant leaves using artificial neural networks. The network acts as identifier of relationships among pH of soil, fertilizer treatment, spectral reflectance and nitrogen content in the plants. So, nitrogen content can be estimated and generalized from an input parameter set. This approach can be form the basis for development of an accurate real time nitrogen applicator.

Theoretical Approximations Between Brazilian and Spanish Authors' Production in the Field of Knowledge Organization in the Production of Journals on Information Science in Brazil

This work identifies and analyzes literature about knowledge organization (KO), expressed in scientific journals communication of information science (IS). It performs an exploratory study on the Base de Dados Referencial de Artigos de Periodicos em Ciência da Informacio (BRAPCI, Reference Database of Journal Articles on Information Science) between the years 2000 and 2010. The descriptors relating to "knowledge organization" are used in order to recover and analyze the corresponding articles and to identify descriptors and concepts which integrate the semantic universe related to KO. Through the analysis of content, based on metrical studies, this article gathers and interprets data relating to documents and authors. Through this, it demonstrates the development of this field and its research fronts according to the observed characteristics, as well as noting the transformation indicative in the production of knowledge. The work describes the influences of the Spanish researchers on Brazilian literature in the fields of knowledge and information organization. As a result, it presents the most cited and productive authors, the theoretical currents which support them, and the most significant relationships of the Spanish-Brazilian authors network. Based on the constant key-words analysis in the cited articles, the co-existence of the French conception current and the incipient Spanish influence in Brazil is observed. Through this, it contributes to the comprehension of the thematic range relating to KO, stimulating both criticism and self-criticism, debate and knowledge creation, based on studies that have been developed and institutionalized in academic contexts in Spain and Brazil.

Temperature and water content influence on thermophysical properties of coffee extract

Specific heat, thermal conductivity, thermal diffusivity, and density of coffee extract were experimentally determined in the range of 0.49 to 0.90 (wet basis) water content and at temperatures varying from 30 to 82 degreesC. Thermal conductivity and specific heat were measured by means of the same apparatus- a cell constituted of two concentric cylinders - operating at steady and unsteady state, respectively. The thermal diffusivity was measured by the well-known Dickerson's method and density was determined by picnometry. The results obtained were used to derive mathematical models for predicting these properties as a function of concentration and temperature.