Degradation of detergent (linear alkylbenzene sulfonate) in an anaerobic stirred sequencing-batch reactor containing granular biomass

This study aimed to determine the efficiency of an anaerobic stirred sequencing-batch reactor containing granular biomass for the degradation of linear alkylbenzene sulfonate (LAS), a surfactant present in household detergent. The bioreactor was monitored for LAS concentrations in the influent, effluent and sludge, pH, chemical oxygen demand, bicarbonate alkalinity, total solids, and volatile solids. The degradation of LAS was found to be higher in the absence of co-substrates (53%) than in their presence (24-37%). Using the polymerase chain reaction and denaturing gradient gel electrophoresis (PCR/DGGE), we identified populations of microorganisms from the Bacteria and Archaea domains. Among the bacteria, we identified uncultivated populations of Arcanobacterium spp. (94%) and Opitutus spp. (96%). Among the Archaea, we identified Methanospirillum spp. (90%), Methanosaeta spp. (98%), and Methanobacterium spp. (96%). The presence of methanogenic microorganisms shows that LAS did not inhibit anaerobic digestion. Sampling at the last stage of reactor operation recovered 61 clones belonging to the domain bacteria. These represented a variety of phyla: 34% shared significant homology with Bacteroidetes, 18% with Proteobacteria, 11% with Verrucomicrobia, 8% with Fibrobacteres, 2% with Acidobacteria, 3% with Chlorobi and Firmicutes, and 1% with Acidobacteres and Chloroflexi. A small fraction of the clones (13%) were not related to any phylum. Published by Elsevier Ltd.

Experimental study of a Tollmien-Schlichting wave interacting with a shallow 3D roughness element

The paper is devoted to an experimental study of the effect of a shallow 3D roughness element on the evolution of a 2D Tollmien-Schlichting wave in a Blasius boundary layer. The experiments were carried out under controlled disturbance conditions on an airfoil section which could provide a long run with zero pressure gradient flow. A pneumatically driven slit source was used to introduce the Tollmien-Schilichting wave upstream of the lower branch of the neutral stability curve. A few wavelengths downstream, the T-S wave interacts with a cylindrical roughness element. The height of the roughness was slowly oscillating in time, which allows a continuous measurement of the T-S wave response downstream the roughness. The oscillation frequency was approximately 1500 times lower than the frequency of the studied Tollmien-Schlichting wave and therefore, behaved as a steady roughness with respect to the T-S wave. Hot wire anemometry was used to measure wall normal profiles and spanwise scans close to the maximum of the eigenfunction of the T-S wave. The oscillation of the roughness and the synchronization of all-equipments permitted the use of ensemble average techniques. Two different amplitudes of T-S waves with a non-dimensional frequency of F120E-06 were studied. They show a strong amplification of the disturbances in a small spanwise wave number range. The analysis of the wall normal T-S profiles suggests the growth of oblique modes.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms

In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (C) 2009 Elsevier B.V. All rights reserved.

Recycling Krylov subspaces for efficient large-scale electrical impedance tomography

Electrical impedance tomography (EIT) captures images of internal features of a body. Electrodes are attached to the boundary of the body, low intensity alternating currents are applied, and the resulting electric potentials are measured. Then, based on the measurements, an estimation algorithm obtains the three-dimensional internal admittivity distribution that corresponds to the image. One of the main goals of medical EIT is to achieve high resolution and an accurate result at low computational cost. However, when the finite element method (FEM) is employed and the corresponding mesh is refined to increase resolution and accuracy, the computational cost increases substantially, especially in the estimation of absolute admittivity distributions. Therefore, we consider in this work a fast iterative solver for the forward problem, which was previously reported in the context of structural optimization. We propose several improvements to this solver to increase its performance in the EIT context. The solver is based on the recycling of approximate invariant subspaces, and it is applied to reduce the EIT computation time for a constant and high resolution finite element mesh. In addition, we consider a powerful preconditioner and provide a detailed pseudocode for the improved iterative solver. The numerical results show the effectiveness of our approach: the proposed algorithm is faster than the preconditioned conjugate gradient (CG) algorithm. The results also show that even on a standard PC without parallelization, a high mesh resolution (more than 150,000 degrees of freedom) can be used for image estimation at a relatively low computational cost. (C) 2010 Elsevier B.V. All rights reserved.

Microstructure and texture assessment of Al-Mn-Fe-Si (3003) aluminum alloy produced by continuous and semicontinuous casting processes

Aluminum sheets are currently produced by the direct-chill process (DC). The need for low-cost aluminum sheets is a challenge for the development of new materials produced by the twin roll caster (TRC) process. It is expected that sheets produced from these different casting procedures will differ in their microstructure. These differences in microstructure and in the crystallographic texture have great impact on sheet mechanical properties and formability. The present study investigated microstructure and evaluated texture of two strips of Al-Mn-Fe-Si (3003) aluminum alloy produced by TRC and by hot-rolling processes. It was possible to notice that the microstructure, morphology, and grain size of the TRC sample were more homogenous than those found in hot-rolled samples. Both strips, obtained by the two processes, showed strong texture gradient across the thickness.

Real time optimization (RTO) with model predictive control (MPC)

This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.

Improving the tracking capability of adaptive filters via convex combination

As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.

Coarse-grid higher order finite-difference time-domain algorithm with low dispersion errors

Higher order (2,4) FDTD schemes used for numerical solutions of Maxwell`s equations are focused on diminishing the truncation errors caused by the Taylor series expansion of the spatial derivatives. These schemes use a larger computational stencil, which generally makes use of the two constant coefficients, C-1 and C-2, for the four-point central-difference operators. In this paper we propose a novel way to diminish these truncation errors, in order to obtain more accurate numerical solutions of Maxwell`s equations. For such purpose, we present a method to individually optimize the pair of coefficients, C-1 and C-2, based on any desired grid size resolution and size of time step. Particularly, we are interested in using coarser grid discretizations to be able to simulate electrically large domains. The results of our optimization algorithm show a significant reduction in dispersion error and numerical anisotropy for all modeled grid size resolutions. Numerical simulations of free-space propagation verifies the very promising theoretical results. The model is also shown to perform well in more complex, realistic scenarios.

Jointly multi-user detection and channel estimation with genetic algorithm

This work aims at proposing the use of the evolutionary computation methodology in order to jointly solve the multiuser channel estimation (MuChE) and detection problems at its maximum-likelihood, both related to the direct sequence code division multiple access (DS/CDMA). The effectiveness of the proposed heuristic approach is proven by comparing performance and complexity merit figures with that obtained by traditional methods found in literature. Simulation results considering genetic algorithm (GA) applied to multipath, DS/CDMA and MuChE and multi-user detection (MuD) show that the proposed genetic algorithm multi-user channel estimation (GAMuChE) yields a normalized mean square error estimation (nMSE) inferior to 11%, under slowly varying multipath fading channels, large range of Doppler frequencies and medium system load, it exhibits lower complexity when compared to both maximum likelihood multi-user channel estimation (MLMuChE) and gradient descent method (GrdDsc). A near-optimum multi-user detector (MuD) based on the genetic algorithm (GAMuD), also proposed in this work, provides a significant reduction in the computational complexity when compared to the optimum multi-user detector (OMuD). In addition, the complexity of the GAMuChE and GAMuD algorithms were (jointly) analyzed in terms of number of operations necessary to reach the convergence, and compared to other jointly MuChE and MuD strategies. The joint GAMuChE-GAMuD scheme can be regarded as a promising alternative for implementing third-generation (3G) and fourth-generation (4G) wireless systems in the near future. Copyright (C) 2010 John Wiley & Sons, Ltd.

In Vitro and In Vivo Evaluation of Lyophilized Bioprosthetic Valve

Freeze-drying of biological tissues allows for dry storage and gamma ray sterilization, which may improve their use as a medical prosthesis. The objective of this study was to evaluate the rehydration characteristics and hydrodynamic performance of prosthetic valves before and after lyophilization. Two size 23 bovine pericardium aortic valve prostheses from different manufacturers were evaluated in a Shelhigh (Union, NJ, USA) pulse duplicator (80 ppm, 5 L/min) before and after lyophilization. Flow and transvalvular pressure gradient were registered in vitro and in vivo, and images of opening and closing of the prosthesis were obtained in the pulse duplicator in a digital camera. Rehydration was evaluated by comparison of dry valve weight with valve weight after 15 min, and 1, 24, 48, and 72 h in saline solution, inside the pulse duplicator. In vivo performance was assessed by surgical implantation in Santa Ines young male sheep in the pulmonary position after 30 min rehydration with 0.9% saline. Transvalvular pressure gradient and flow measurements were obtained immediately after implantation and 3 months after surgery when valves were explanted. Captured images showed a change in the profile opening and closing of valve prosthesis after lyophilization. The gradient measured (in vitro) in two valves was 17.08 +/- 0.57 and 18.76 +/- 0.70 mm Hg before lyophilization, and 34.24 +/- 0.59 and 30.40 +/- 0.97 mm Hg after lyophilization. Rehydration of both lyophilized valves was approximately 82%. Drying changed the profile of the opening and closing of valve prostheses, and increased on average by 83% the gradient in vitro tests. The result of the in vivo tests suggests maintaining pressure levels of the animal with the lyophilized prostheses within acceptable levels.

Study of copper electrodeposition mechanism from a strike alkaline bath prepared with 1-hydroxyethane-1,1-diphosphonic acid through cyclic voltammetry technique

Copper strike baths are extensively used in metal plating industry as they present the ability to plate adherent copper layers on less-noble metal substrates such as steel and zinc die castings. However, in the last few years, due to environmental controls and safety policies for operators, the plating industry has been interested in replacing the toxic cyanide copper strike baths with environmentally friendly baths. A broad bibliographic review showed that the published papers, referring to the new nontoxic copper strike baths, are patents, having little or no emphasis focused on electrodeposition mechanisms. Therefore, it was decided to study the copper electrodeposition mechanism from a strike alkaline bath prepared with one of the most nontoxic chelating agents cited in many patents which is the 1-hydroxyethane-1,1-diphosphonic acid, known as HEDP. This acid forms very stable water soluble complexes with Cu(2+) ions, thus cupric sulfate was used for preparing the plating bath. The results obtained through a cyclic voltammetry technique showed that Cu(2+) ion reduction to Cu from an HEDP electrodeposition bath occurs via a direct reduction reaction without a formation of Cu(+) intermediates. (C) 2010 Elsevier Ltd. All rights reserved.

Predicting the columnar-to-equiaxed transition for a distribution of nucleation undercoolings

A deterministic mathematical model for steady-state unidirectional solidification is proposed to predict the columnar-to-equiaxed transition. In the model, which is an extension to the classic model proposed by Hunt [Hunt JD. Mater Sci Eng 1984;65:75], equiaxed grains nucleate according to either a normal or a log-normal distribution of nucleation undercoolings. Growth maps are constructed, indicating either columnar or equiaxed solidification as a function of the velocity of isotherms and temperature gradient. The fields A columnar and equiaxed growth change significantly with the spread of the nucleation undercooling distribution. Increasing the spread Favors columnar solidification if the dimensionless velocity of the isotherms is larger than 1. For a velocity less than 1, however, equiaxed solidification is initially favored, but columnar solidification is enhanced for a larger increase in the spread. This behavior was confirmed by a stochastic model, which showed that an increase in the distribution spread Could change the grain structure from completely columnar to 50% columnar grains. (c) 2008 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Endophytic bacteria in long-term in vitro cultivated axenic pineapple microplants revealed by PCR-DGGE

In vitro propagated plants are believed to be free of microbes. However, after 5 years of in vitro culture of pineapple plants, without evidence of microbial contamination, the use of culture-independent molecular approach [classifying heterogeneous nucleic acids amplified via universal and specific 16S rRNA gene by polymerase chain reaction (PCR)], and further analysis by denaturing gradient gel electrophoresis (DGGE) revealed endophytic bacteria in roots, young and mature leaves of such plants. The amplification of 16S rRNA gene (Bacteria domain) with the exclusion of the plant chloroplast DNA interference, confirmed the presence of bacterial DNA, from endophytic microorganisms within microplant tissues. PCR-DGGE analysis revealed clear differences on bacterial communities depending on plant organ. Group-specific DGGE analyses also indicated differences in the structures of Actinobacteria, Alphaproteobacteria and Betaproteobacteria communities in each part of plants. The results suggest the occurrence of a succession of bacterial communities colonizing actively the microplants organs. This study is the first report that brings together evidences that pineapple microplants, previously considered axenic, harbor an endophytic bacterial community encompassing members of Actinobacteria, Alphaproteobacteria and Betaproteobacteria group which is responsive to differences in organs due to plant development.

Measuring Hydraulic Conductivity to Wilting Point Using Polymer Tensiometers in an Evaporation Experiment

The polymer tensiometer is a novel instrument to measure soil water pressure heads from saturation to permanent wilting conditions. We used tensiometers of this type in an experiment to determine the hydraulic properties of evaporating soil samples in the laboratory. Relative errors in the hydraulic conductivity function in the wet part were high due to the relatively low accuracy of the pressure transducers, resulting in a large uncertainty in the hydraulic gradient and therefore in the calculated hydraulic conductivity. In the dry part, the error related to this accuracy was on the same order of magnitude as the error related to balance accuracy. Therefore, the method can be assumed adequate for measuring soil hydraulic properties except under very wet conditions. In our experiments, relative error and bias increased significantly at pressure heads less negative than -1 m.