Evaluation of mechanical, physical and thermal performance of cement-based tiles reinforced with vegetable fibers

The objective of this work was to analyze mechanical, physical and thermal performance of roofing tiles produced with several formulations of cement-based matrices reinforced with sisal and eucalyptus fibers. The physical properties of the tiles were more influenced by the fiber content of the composite than by the type of reinforcement. The type of the fiber was the main variable for the achievement of the best results of mechanical properties. Exposure to tropical climate has caused a severe reduction in the mechanical properties of the composites. After approximately four months of age under external weathering the toughness of the vegetable fiber-cement fell to 53-68% of the initial toughness at 28 days of age. The thermal performance showed that roofing tiles reinforced with vegetable fiber are acceptable as substitutes of asbestos-cement sheets. (c) 2006 Elsevier Ltd. All rights reserved.

Towards improving cluster-based feature selection with a simplified silhouette filter

This paper proposes a filter-based algorithm for feature selection. The filter is based on the partitioning of the set of features into clusters. The number of clusters, and consequently the cardinality of the subset of selected features, is automatically estimated from data. The computational complexity of the proposed algorithm is also investigated. A variant of this filter that considers feature-class correlations is also proposed for classification problems. Empirical results involving ten datasets illustrate the performance of the developed algorithm, which in general has obtained competitive results in terms of classification accuracy when compared to state of the art algorithms that find clusters of features. We show that, if computational efficiency is an important issue, then the proposed filter May be preferred over their counterparts, thus becoming eligible to join a pool of feature selection algorithms to be used in practice. As an additional contribution of this work, a theoretical framework is used to formally analyze some properties of feature selection methods that rely on finding clusters of features. (C) 2011 Elsevier Inc. All rights reserved.

Aerosol inorganic composition at a tropical site: Discrepancies between filter-based sampling and a semi-continuous method

The concentrations of the water-soluble inorganic aerosol species, ammonium (NH4+), nitrate (NO3-), chloride (Cl-), and sulfate (SO42-), were measured from September to November 2002 at a pasture site in the Amazon Basin (Rondnia, Brazil) (LBA-SMOCC). Measurements were conducted using a semi-continuous technique (Wet-annular denuder/Steam-Jet Aerosol Collector: WAD/SJAC) and three integrating filter-based methods, namely (1) a denuder-filter pack (DFP: Teflon and impregnated Whatman filters), (2) a stacked-filter unit (SFU: polycarbonate filters), and (3) a High Volume dichotomous sampler (HiVol: quartz fiber filters). Measurements covered the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). Analyses of the particles collected on filters were performed using ion chromatography (IC) and Particle-Induced X-ray Emission spectrometry (PIXE). Season-dependent discrepancies were observed between the WAD/SJAC system and the filter-based samplers. During the dry season, when PM2.5 (D-p <= 2.5 mu m) concentrations were similar to 100 mu g m(-3), aerosol NH4+ and SO42- measured by the filter-based samplers were on average two times higher than those determined by the WAD/SJAC. Concentrations of aerosol NO3- and Cl- measured with the HiVol during daytime, and with the DFP during day- and nighttime also exceeded those of the WAD/SJAC by a factor of two. In contrast, aerosol NO3- and Cl- measured with the SFU during the dry season were nearly two times lower than those measured by the WAD/SJAC. These differences declined markedly during the transition period and towards the cleaner conditions during the onset of the wet season (PM2.5 similar to 5 mu g m(-3)); when filter-based samplers measured on average 40-90% less than the WAD/SJAC. The differences were not due to consistent systematic biases of the analytical techniques, but were apparently a result of prevailing environmental conditions and different sampling procedures. For the transition period and wet season, the significance of our results is reduced by a low number of data points. We argue that the observed differences are mainly attributable to (a) positive and negative filter sampling artifacts, (b) presence of organic compounds and organosulfates on filter substrates, and (c) a SJAC sampling efficiency of less than 100%.

Agro-Based Biocomposites for Industrial Applications

Leaf fibers are fibers that run lengthwise through the leaves of most monocotyledonous plants such as pineapple, banana, etc. Pineapple (Ananas comosus) and Banana (Musa indica) are emerging fiber having a very large potential to be used for composite materials. Over 150,000 ha of pineapple and over 100,000 ha of banana plantations are available in Brazil for the fruit production and enormous amount of agricultural waste is produced. This residual waste represents one of the single largest sources of cellulose fibers available at almost no cost. The potential consumers for this fiber are pulp and paper, chemical feedstock, textiles and composites for the automotive, furniture and civil construction industry.