Effects of calcining conditions on the microstructure of sugar cane waste ashes (SCWA): Influence in the pozzolanic activation

in this paper a study of calcining conditions on the microstructural features of sugar cane waste ash (SCWA) is carried out. For this purpose, some microparticles (< 90 mu m) of sugar cane straw ash and sugar cane bagasse ash of samples calcined at 800 degrees C and 1000 are studied by combining the bright field and the dark field images with the electron diffraction patterns in the transmission electron microscopy (TEM). It is appreciated that the morphology and texture of these microparticles change when silicon or calcium are present. Furthermore, it is observed that iron oxide (magnetite Fe(3)O(4)) is located in the calcium-rich particles. The microstructural information is correlated with the results of a kinetic-diffusive model that allows the computing of the kinetic parameters of the pozzolanic reaction (mainly the reaction rate constant). The results show that the sugar cane wastes ash calcined at 800 and 1000 degrees C have properties indicative of high pozzolanic activity. The X-ray diffraction patterns, the TEM images and the pozzolanic activity tests show the influence of different factors on the activation of these ashes. (c) 2008 Elsevier Ltd. All rights reserved.

Geophysical investigation using resistivity and GPR methods: a case study of a lubricant oil waste disposal area in the city of Ribeiro Preto, So Paulo, Brazil

Geophysics has been shown to be effective in identifying areas contaminated by waste disposal, contributing to the greater efficiency of soundings programs and the installation of monitoring wells. In the study area, four trenches were constructed with a total volume of about 25,000 m(3). They were almost totally filled with re-refined lubricating oil waste for approximately 25 years. No protection liners were used in the bottoms and laterals of the disposal trenches. The purpose of this work is to evaluate the potential of the resistivity and ground penetrating radar (GPR) methods in characterizing the contamination of this lubricant oil waste disposal area in Ribeiro Preto, SP, situated on the geological domain of the basalt spills of the Serra Geral Formation and the sandstones of the Botucatu Formation. Geophysical results were shown in 2D profiles. The geophysical methods used enabled the identification of geophysical anomalies, which characterized the contamination produced by the trenches filled with lubricant oil waste. Conductive anomalies (smaller than 185 Omega m) immediately below the trenches suggest the action of bacteria in the hydrocarbons, as has been observed in several sites contaminated by hydrocarbons in previously reported cases in the literature. It was also possible to define the geometry of the trenches, as evidenced by the GPR method. Direct sampling (chemical analysis of the soil and the water in the monitoring well) confirmed the contamination. In the soil analysis, low concentrations of several polycyclic aromatic hydrocarbons (PAHs) were found, mainly naphthalene and phenanthrene. In the water samples, an analysis verified contamination of the groundwater by lead (Pb). The geophysical methods used in the investigation provided an excellent tool for environmental characterization in this study of a lubricant oil waste disposal area, and could be applied in the study of similar areas.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

Image indexing and retrieval using an ART-2A neural network architecture

Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Decolourisation of real textile waste using electrochemical techniques: Effect of electrode composition

The present paper presents the study of the decolourisation of real textile effluent by constant current electrolysis in a flow-cell using a DSAO type material. The effect of using different anode materials (Ti/Ru0.3Ti0.7O2; Ti/Ir0.3Ti0.7O2; Ti/RuxSn1-xO2, where X = 0.1, 0.2 or 0.3) on the efficiency of colour removal is discussed. Attempts to perform galvanostatic oxidation (40 and 60 mA cm(-2)) on the as-received effluent demonstrate that colour removal and total organic carbon (TOC) removal are limited. In this case the greatest degree of colour removal is achieved when anode containing 90% SnO2 is used. If the conductivity of the effluent is increased by adding NaCl (0.1 mol L-1) appreciable colour/TOC removal is observed. The efficiencies of colour and TOC removal are discussed in terms of the energy per order (E-EO/kWhm(-3) order(-1)) and energy consumption (E-C/kW h kg(-1) TOC), respectively. Finally, the extent of colour removal is compared to consent levels presented in the literature. (C) 2008 Elsevier B.V. All rights reserved.

Structure and Applications of a Rhamnolipid Surfactant Produced in Soybean Oil Waste

Soybean oil soapstock was utilized as an alternative carbon source for the production of rhamnolipids by Pseudomonas aeruginosa LBI strain. The chemical composition and properties of the rhamnolipid mixture obtained were determined to define its potential applications. The chemical characterization of the rhamnolipid has revealed the presence of ten different homologues. The monorhamnolipid RhaC(10)C(10) and the dirhamnolipid Rha(2)C(10)C(10) were the main components of the mixture that showed predominance of 44% and 29%, respectively, after 144-h of cultivation. The biosurfactant was able to form stable emulsions with several hydrocarbons and showed excellent emulsification for soybean oil and chicken fat (100%). The rhamnolipid removed 67% of crude oil present in sand samples and presented antimicrobial activity against Bacillus cereus and Mucor miehei at 64 mu g/mL and inhibition of Neurospora crassa, Staphylococcus aureus, and Micrococcus luteus at 256 mu g/mL. The results demonstrated that the rhamnolipid produced in soybean oil soapstock can be useful in environmental and food industry applications.