Cross-validation of methods used for analysis of MTBE and other gasoline components in groundwater.

Head space gas chromatography with flame-ionization detection (HS-GC-FID), ancl purge and trap gas chromatography-mass spectrometry (P&T-GC-MS) have been used to determine methyl-tert-butyl ether (MTBE) and benzene, toluene, and the ylenes (BTEX) in groundwater. In the work discussed in this paper measures of quality, e.g. recovery (94-111%), precision (4.6 - 12.2%), limits of detection (0.3 - 5.7 I~g L 1 for HS and 0.001 I~g L 1 for PT), and robust-ness, for both methods were compared. In addition, for purposes of comparison, groundwater samples from areas suffering from odor problems because of fuel spillage and tank leakage were analyzed by use of both techniques. For high concentration levels there was good correlation between results from both methods.

Fish colonization of artificial reefs in a large Neotropical reservoir: material type and successional changes

Artificial reefs have barely been used in Neotropical reservoirs (about five studies in three reservoirs), despite their potential as a fishery management tool to create new habitats and also to understand fish ecology. We experimentally assessed how reef material (ceramic, concrete, and PVC) and time modulated fish colonization of artificial reefs deployed in Itaipu Reservoir, a large reservoir of the mainstem Parana´ River, Brazil. Fish richness, abundance, and biomass were significantly greater in the reef treatments than at control sites. Among the experimental reefs, ceramic followed by the concrete treatments were the materials most effectively colonized, harboring the majority of the 13 fish species recorded. Although dependent on material type, many of the regularities of ecological successions were also observed in the artificial reefs, including decelerating increases in species richness, abundance, mean individual size, and species loss rates with time and decelerating decreases of species gain and turnover rates. Species composition also varied with material type and time, together with suites of life history traits: more equilibrium species (i.e., fishes of intermediate size that often exhibit parental care and produce fewer but larger offspring) of the Winemiller-Rose model of fish life histories prevailed in later successional stages. Overall, our study suggests that experimental reefs are a promising tool to understand ecological succession of fish assemblages, particularly in tropical ecosystems given their high species richness and low seasonality

Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

Simple method for mass production of polypyrrole/carbon nanotubes hybrid artificial muscle

Large scale preparation of hybrid electrical actuators represents an important step for the production of low cost devices. Interfacial polymerization of polypyrrole in the presence of multi-walled carbon nanotubes represents a simple technique in which strong interaction between components is established, providing composite materials with potential applications as actuators due to the synergistic interaction between the individual components, i.e., fast response of carbon nanotubes, high strain of polypyrrole, and diversity in the available geometry of resulting samples.

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.

Hydrographic and hydrogeological basin of Entre-Ribeiros: probable recharge zone delimitation and environmental impact assessment

The probable recharge zone delimitation of Entre-Ribeiros Basin (Northwest of the state of Minas Gerais / Brazil) is proposed in this study. The delimitation is based upon stratigraphy, geomorphology, geo-environmental domains and hydrogeology studies. Combining the recharge zone map with the land use variation between 1975 and 2008, the occupation trends of possible recharge zones are identified. Concluding, the environmental impacts for this basin are discussed.

Technical and economic analysis of replacing artificial lighting system to induction of photoperiod effect in begonia's seedlings in greenhouse

The type of artificial light used for inducing photoperiod effect in begonia's seedlings at greenhouse has fundamental importance in the growth and development of these plants and directly reflects in the electrical energy consumption used in this production process. The objective of this research was to analyze the technical and economic feasibility of replacing the current technology of artificial lighting used by the producers (incandescent lamps), by the technology of discharge lamps with the purpose of inducing photoperiod in a greenhouse. The analysis results indicate that the discharge lamp of 32 W Tubular Fluorescent discharge lamp was the one that presented the lower peak demand and lower average energy consumption of 85.01% compared to incandescent filament lamp of 100 W that is the technology of bigger consumption and currently used by the producer.

Technical evaluation of artificial ligthing systems for broiler houses

The spatial distribution of illuminance and the electric consumption of artificial lighting system is one of the main problems related to broiler production. Therefore, the aim of this study was to evaluate the spatial distribution of luminance level and energy efficiency of different lighting systems for broiler houses. Six types of lamps were tested in two different configurations to find the minimum illuminance of 20 and 5 lux. The tested lamps were incandescent (IL) 100 W, compact fluorescent (CFL) 34 W, mixed (ML) 160 W, sodium vapor (SVL) 70 W, T8 fluorescent tube (T8 FTL) 40 W and T5 fluorescent tube (T5 FTL) 28 W. The first four were evaluated with and without reflective light fixture and the latter two without light fixture. It was observed that the tested system with light fixtures negatively affected the spatial distribution of illuminance inside the house. The systems composed by IL and ML without light fixture led to better results in meeting the minimum illuminance of 20 lux and 5 lux, respectively. T5 FTL presented the lowest energy demand.

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.

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.

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.