Determination of copper at wide range concentrations using instrumental features of high-resolution continuum source flame atomic absorption spectrometry

This work describes a method to determine Cu at wide range concentrations in a single run without need of further dilutions employing high-resolution continuum source flame atomic absorption spectrometry. Different atomic lines for Cu at 324.754 nm, 327.396 nm, 222.570 nm, 249.215 nm and 224.426 nm were evaluated and main figures of merit established. Absorbance measurements at 324.754 nm, 249.215 nm and 224.426 nm allows the determination of Cu in the 0.07 - 5.0 mg L-1, 5.0 - 100 mg L-1 and 100 - 800 mg L-1 concentration intervals respectively with linear correlation coefficients better than 0.998. Limits of detection were 21 µg L-1, 310 µg L-1 and 1400 µg L-1 for 324.754 nm, 249.215 nm and 224.426 nm, respectively and relative standard deviations (n = 12) were £ 2.7%. The proposed method was applied to water samples spiked with Cu and the results were in agreement at a 95% of confidence level (paired t-test) with those obtained by line-source flame atomic absorption spectrometry.

Soluble tissue sugar content and leaf blast severity in response to the application of calcinated serpentinite as a silicon source in irrigated rice

A field experiment conducted with the irrigated rice cultivar BRS Formoso, to assess the efficiency of calcinated serpentinite as a silicon source on grain yield was utilized to study its effect on leaf blast severity and tissue sugar levels. The treatments consisted of five rates of calcinated serpentinite (0, 2, 4, 6, 8 Mg.ha-1) incorporated into the soil prior to planting. The leaf blast severity was reduced at the rate of 2.96% per ton of calcinated serpentinite. The total tissue sugar content decreased significantly as the rates of serpentinite applied increased (R² = 0.83). The relationship between the tissue sugar content and leaf blast severity was linear and positive (R² = 0.81). The decrease in leaf blast severity with increased rates of calcinated serpentinite was also linear (R²= 0.96) and can be ascribed to reduced sugar level.

Decomposition of corn and soybean residues under field conditions and their role as inoculum source

Necrotrophic parasites of above-ground plant parts survive saprophytically, between growing seasons in host crop residues. In an experiment conducted under field conditions, the time required in months for corn and soybean residues to be completely decomposed was quantified. Residues were laid on the soil surface to simulate no-till farming. Crop debris of the two plant species collected on the harvesting day cut into pieces of 5.0cm-long and a 200g mass was added to nylon mesh bags. At monthly intervals, bags were taken to the laboratory for weighing. Corn residues were decomposed within 37.0 months and those of soybean, within 34.5 months. Hw main necrotrophic fungi diagnosed in the corn residues were Colletotrichum gramicola, Diplodia spp. and Gibberella zeae, and those in soybeans residues were Cercospora kikuchii, Colletotrichum spp, Glomerella sp. and Phomopsis spp. Thus, those periods shoulb be observed in crop rotation aimed at to eliminating contaminated residues and, consequently, the inoculum from the cultivated area.

Rainfall erosivity for the State of Rio de Janeiro estimated by artificial neural network

The Artificial Neural Networks (ANNs) are mathematical models method capable of estimating non-linear response plans. The advantage of these models is to present different responses of the statistical models. Thus, the objective of this study was to develop and to test ANNs for estimating rainfall erosivity index (EI30) as a function of the geographical location for the state of Rio de Janeiro, Brazil and generating a thematic visualization map. The characteristics of latitude, longitude e altitude using ANNs were acceptable to estimating EI30 and allowing visualization of the space variability of EI30. Thus, ANN is a potential option for the estimate of climatic variables in substitution to the traditional methods of interpolation.

Determination of the influence of the variation of reducing and non-reducing sugars on coffee quality with use of artificial neural network

The present study aimed at evaluating the use of Artificial Neural Network to correlate the values resulting from chemical analyses of samples of coffee with the values of their sensory analyses. The coffee samples used were from the Coffea arabica L., cultivars Acaiá do Cerrado, Topázio, Acaiá 474-19 and Bourbon, collected in the southern region of the state of Minas Gerais. The chemical analyses were carried out for reducing and non-reducing sugars. The quality of the beverage was evaluated by sensory analysis. The Artificial Neural Network method used values from chemical analyses as input variables and values from sensory analysis as output values. The multiple linear regression of sensory analysis values, according to the values from chemical analyses, presented a determination coefficient of 0.3106, while the Artificial Neural Network achieved a level of 80.00% of success in the classification of values from the sensory analysis.

Environmental adaptation of the source of the subbasin of Rico Stream, Monte Alto - SP, Brazil

The aim of this study was to define the photographic patterns that represent the use and occupation of the landcover of the "spring" of the Rico Stream subbasin, located at Monte Alto, state of São Paulo (SP), Brazil, for environmental adaptation regarding the Brazilian Forest Law. The mapping was performed using remote sensing techniques and visual interpretation of the World View image, followed by the digitalization of the net of drainage and vegetation (natural and agricultural) at the AutoCad software with documents and field work. The study area has 2141.53 ha and the results demonstrated that the main crop is sugarcane with 546.34 ha, followed by 251.22 ha of pastures, 191.71 ha of perennial crops, 57.31 ha of Eucalyptus and 49.52 ha of onion, confirming the advance of sugarcane culture in the region. The region has 375.04 ha of areas of permanent preservation (APPs), and of this area it was found that only 72.17 ha (19.24%) has arboreal vegetation or natural forest, and 302.87 ha of these areas need to be enriched and reforested with native vegetation from the region, according to the current legislation. The data of the area enable future proposals of models for environmental adaptation to the microbasin according to the current environmental legislation.

Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop

Precision irrigation seeks to establish strategies which achieve an efficient ratio between the volume of water used (reduction in input) and the productivity obtained (increase in production). There are several studies in the literature on strategies for achieving this efficiency, such as those dealing with the method of volumetric water balance (VWB). However, it is also of great practical and economic interest to set up versatile implementations of irrigation strategies that: (i) maintain the performance obtained with other implementations, (ii) rely on few computational resources, (iii) adapt well to field conditions, and (iv) allow easy modification of the irrigation strategy. In this study, such characteristics are achieved when using an Artificial Neural Network (ANN) to determine the period of irrigation for a watermelon crop in the Irrigation Perimeter of the Lower Acaraú, in the state of Ceará, Brazil. The Volumetric Water Balance was taken as the standard for comparing the management carried out with the proposed implementation of ANN. The statistical analysis demonstrates the effectiveness of the proposed management, which is able to replace VWB as a strategy in automation.

Dosagem de folatos maternos e fetais, séricos e eritrocitários em malformações por defeito de fechamento do tubo neural no feto

Objetivos: avaliar os níveis de folatos maternos e fetais gestações com malformações por defeitos de fechamento do tubo neural (DFTN). Métodos: o estudo foi do tipo caso-controle, no qual 14 casos de fetos com DFTN (grupo estudo) e 14 casos de fetos com outras malformações (grupo controle) foram estudados em gestantes de baixo risco para DFTN. Propusemo-nos a dosar o ácido fólico, na sua forma total e metilada, nos compartimentos fetal e materno, utilizando dosagens séricas e tissulares (eritrocitárias), assim como o volume corpuscular médio, o hematócrito e a hemoglobina. As coletas foram realizadas imediatamente antes da interrupção da gestação. Os resultados nos dois grupos foram comparados pelo teste t de Student, método de amostras pareados pela idade gestacional. Resultados: não se encontrou diferença nas taxas de folatos fetais e nos parâmetros hematológicos dos fetos, entre os dois grupos. Por outro lado, taxas anormalmente baixas de folatos foram encontradas nos eritrócitos das mães portadoras de fetos com DFTN, tanto para as formas totais(293,9 ng/mL contra 399,1 ng/mL no grupo controle, p=0,01) quanto para as formas metiladas (201,9 ng/mL contra 314,0 ng/mL para o grupo controle, p=0,02). Os folatos séricos maternos não se mostraram diferentes nos grupos estudo e controle. Conclusão: este estudo demonstrou que há uma menor taxa de folatos intratissulares, nas mães de fetos acometidos por DFTN, porém com taxas de folatos séricos semelhantes em relação ao grupo controle.

Folato, vitamina B12 e ferritina sérica e defeitos do tubo neural

Objetivo: verificar os níveis de folatos, vitamina B12 e ferritina em pacientes cujos fetos apresentaram defeitos de tubo neural (DTN). O folato sangüíneo e a vitamina B12 atuam como cofatores para as enzimas envolvidas na biossíntese do DNA. A interrupção deste processo pode impedir o fechamento do tubo neural. A suplementação vitamínica contendo folato pode reduzir as taxas de ocorrência de defeitos de tubo neural, embora exista a preocupação de que esta prevenção possa mascarar a deficiência de vitamina B12. Métodos: dosagens de vitamina B12 e ferritina pelo método de enzimaimunoensaio com micropartículas e a dosagens de ácido fólico pelo método de captura iônica (IMx ABBOTT). Resultados: a porcentagem de gestantes com deficiência de vitamina B12 (níveis séricos < 150 pg/ml) foi de 11,8%. Não houve nenhum caso de deficiência de folato (níveis séricos < 3,0 ng/ml). A prevalência de gestantes com deficiência nos estoques de ferro foi de 47,1% (níveis séricos < 12 ng/ml). Conclusões: com os resultados encontrados neste estudo (prevalência de 11,8% de deficientes em vitamina B12 e 0% de deficiência de folato), sugerimos que a suplementação se realize após a determinação da vitamina B12 sérica.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Potencial de transdiferenciação neural das células-tronco mesenquimais da medula óssea de equino

Os primeiros estudos demonstrando o potencial de trandiferenciação neural das células-tronco mesenquimais (CTMs) provenientes da medula óssea (MO) foram conduzidos em camundogos e humanos no início da década de 2000. Após esse período, o número de pesquisas e publicações com o mesmo propósito tem aumentado, mas com raros ou escassos estudos na espécie equina. Nesse sentindo, o objetivo desse trabalho foi avaliar o potencial in vitro da transdiferenciação neural das CTMs provenientes da MO de equinos utilizando-se dois protocolos: P1 (forksolin e ácido retinóico) e P2 (2-βmecarptoetanol). Após a confirmação das linhagens mesenquimais, pela positividade para o marcador CD90 (X=97,94%), negatividade para o marcador CD34 e resposta positiva a diferenciação osteogênica, as CTMs foram submetidas a transdiferenciação neural (P1 e P2) para avaliação morfológica e expressão dos marcadores neurais GFAP e β3 tubulina por citometria de fluxo. Os resultados revelaram mudanças morfológicas em graus variados entre os protocolos testados. No protocolo 1, vinte quatro horas após a incubação com o meio de diferenciação neural, grande proporção de células (>80%) apresentaram morfologia semelhante a células neurais, caracterizadas por retração do corpo celular e grande número de projeções protoplasmáticas (filopodia). Por outro lado, de forma comparativa, já nos primeiros 30 minutos após a exposição ao antioxidante β-mercaptoetanol (P2) as CTMs apresentaram rápida mudança morfológica caracterizada principalmente por retração do corpo celular e menor número de projeções protoplasmáticas. Também ficou evidenciado com o uso deste protocolo, menor aderência das células após tempo de exposição ao meio de diferenciação, quando comparado ao P1. Com relação a análise imunofenotípica foi observado uma maior (P<0,001) expressão dos marcadores GFAP e β3 tubulina ao término do P2 quando comparado ao P1. A habilidade das CTMs em gerar tipos celulares relacionados a linhagem neural é complexa e multifatorial, dependendo não só dos agentes indutores, mas também do ambiente no qual estas células são cultivadas. Desta forma um maior número de estudos é necessário para o melhor entendimento do processo de transdiferenciação neural a partir de CTMs de equinos.

Classification of antimicrobial resistance using artificial neural networks and the relationship of 38 genes associated with the virulence of Escherichia coli isolates from broilers

Avian pathogenic Escherichia coli (APEC) is responsible for various pathological processes in birds and is considered as one of the principal causes of morbidity and mortality, associated with economic losses to the poultry industry. The objective of this study was to demonstrate that it is possible to predict antimicrobial resistance of 256 samples (APEC) using 38 different genes responsible for virulence factors, through a computer program of artificial neural networks (ANNs). A second target was to find the relationship between (PI) pathogenicity index and resistance to 14 antibiotics by statistical analysis. The results showed that the RNAs were able to make the correct classification of the behavior of APEC samples with a range from 74.22 to 98.44%, and make it possible to predict antimicrobial resistance. The statistical analysis to assess the relationship between the pathogenic index (PI) and resistance against 14 antibiotics showed that these variables are independent, i.e. peaks in PI can happen without changing the antimicrobial resistance, or the opposite, changing the antimicrobial resistance without a change in PI.

Heat Source Estimation with the Conjugate Gradient Method in Inverse Linear Diffusive Problems

In this work, we present the solution of a class of linear inverse heat conduction problems for the estimation of unknown heat source terms, with no prior information of the functional forms of timewise and spatial dependence of the source strength, using the conjugate gradient method with an adjoint problem. After describing the mathematical formulation of a general direct problem and the procedure for the solution of the inverse problem, we show applications to three transient heat transfer problems: a one-dimensional cylindrical problem; a two-dimensional cylindrical problem; and a one-dimensional problem with two plates.

Detection of Horizontal Two-Phase Flow Patterns Through a Neural Network Model

One of the main problems related to the transport and manipulation of multiphase fluids concerns the existence of characteristic flow patterns and its strong influence on important operation parameters. A good example of this occurs in gas-liquid chemical reactors in which maximum efficiencies can be achieved by maintaining a finely dispersed bubbly flow to maximize the total interfacial area. Thus, the ability to automatically detect flow patterns is of crucial importance, especially for the adequate operation of multiphase systems. This work describes the application of a neural model to process the signals delivered by a direct imaging probe to produce a diagnostic of the corresponding flow pattern. The neural model is constituted of six independent neural modules, each of which trained to detect one of the main horizontal flow patterns, and a last winner-take-all layer responsible for resolving when two or more patterns are simultaneously detected. Experimental signals representing different bubbly, intermittent, annular and stratified flow patterns were used to validate the neural model.