Sequential Injection Analysis (SIA) for Arsenic Speciation by Capillary Electrophoresis Hyphenated to Inductively Coupled Plasma Sector Field Mass Spectrometry (CE-ICP-SFMS)

Sequential injection analysis (SIA) is proposed for managing microvolumes of sample and arsenic species solutions for speciation analysis by capillary electrophoresis focusing on the reduction of hazardous waste residues. An electronically controlled hydrodynamic injector was projected to introduce microvolumes of solutions prepared by SIA into the CE capillary with precision better than 2%. The determination of arsenite, arsenate, monomethylarsonic acid, dimethylarsinic acid, and arsenobetaine was performed from 50 mu L volumes of lyophilized urine and extract of shrimp with the system hyphenated to inductively coupled plasma mass spectrometry (CE-ICP-SFMS).

Sequential production of amylolytic and lipolytic enzymes by bacterium strain isolated from petroleum contaminated soil

Amylases and lipases are highly demanded industrial enzymes in various sectors such as food, pharmaceuticals, textiles, and detergents. Amylases are of ubiquitous occurrence and hold the maximum market share of enzyme sales. Lipases are the most versatile biocatalyst and bring about a range of bioconversion reactions such as hydrolysis, inter-esterification, esterification, alcoholysis, acidolysis, and aminolysis. The objective of this work was to study the feasibility for amylolitic and lipolytic production using a bacterium strain isolated from petroleum contaminated soil in the same submerged fermentation. This was a sequential process based on starch and vegetable oils feedstocks. Run were performed in batchwise using 2% starch supplemented with suitable nutrients and different vegetable oils as a lipase inducers. Fermentation conditions were pH 5.0; 30 degrees C, and stirred speed (200 rpm). Maxima activities for amyloglucosidase and lipase were, respectively, 0.18 and 1,150 U/ml. These results showed a promising methodology to obtain both enzymes using industrial waste resources containing vegetable oils.

A state-space modeling approach for active structural acoustic control

The demands for improvement in sound quality and reduction of noise generated by vehicles are constantly increasing, as well as the penalties for space and weight of the control solutions. A promising approach to cope with this challenge is the use of active structural-acoustic control. Usually, the low frequency noise is transmitted into the vehicle`s cabin through structural paths, which raises the necessity of dealing with vibro-acoustic models. This kind of models should allow the inclusion of sensors and actuators models, if accurate performance indexes are to be accessed. The challenge thus resides in deriving reasonable sized models that integrate structural, acoustic, electrical components and the controller algorithm. The advantages of adequate active control simulation strategies relies on the cost and time reduction in the development phase. Therefore, the aim of this paper is to present a methodology for simulating vibro-acoustic systems including this coupled model in a closed loop control simulation framework that also takes into account the interaction between the system and the control sensors/actuators. It is shown that neglecting the sensor/actuator dynamics can lead to inaccurate performance predictions.

Experimental investigation on adaptive robust controller designs applied to a free-floating space manipulator

This paper aims to formulate and investigate the application of various nonlinear H(infinity) control methods to a fiee-floating space manipulator subject to parametric uncertainties and external disturbances. From a tutorial perspective, a model-based approach and adaptive procedures based on linear parametrization, neural networks and fuzzy systems are covered by this work. A comparative study is conducted based on experimental implementations performed with an actual underactuated fixed-base planar manipulator which is, following the DEM concept, dynamically equivalent to a free-floating space manipulator. (C) 2011 Elsevier Ltd. All rights reserved.

Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

Anaerobic treatment of sulfate-rich wastewater in an anaerobic sequential batch reactor (AnSBR) using butanol as the carbon source

Biological sulfate reduction was studied in a laboratory-scale anaerobic sequential batch reactor (14 L) containing mineral coal for biomass attachment. The reactor was fed industrial wastewater with increasingly high sulfate concentrations to establish its application limits. Special attention was paid to the use of butanol in the sulfate reduction that originated from melamine resin production. This product was used as the main organic amendment to support the biological process. The reactor was operated for 65 cycles (48 h each) at sulfate loading rates ranging from 2.2 to 23.8 g SO(4)(2-)/cycle, which corresponds to sulfate concentrations of 0.25, 0.5,1.0, 2.0 and 3.0 g SW(4)(2-)L(-1). The sulfate removal efficiency reached 99% at concentrations of 0.25, 0.5 and 1.0 g SO(4)(2-)L(-1). At higher sulfate concentrations (2.0 and 3.0 g SO(4)(2-)L(-1)), the sulfate conversion remained in the range of 71-95%. The results demonstrate the potential applicability of butanol as the carbon source for the biological treatment of sulfate in an anaerobic batch reactor. (C) 2011 Elsevier Ltd. All rights reserved.

Sequential decision making with partially ordered preferences

This paper presents new insights and novel algorithms for strategy selection in sequential decision making with partially ordered preferences; that is, where some strategies may be incomparable with respect to expected utility. We assume that incomparability amongst strategies is caused by indeterminacy/imprecision in probability values. We investigate six criteria for consequentialist strategy selection: Gamma-Maximin, Gamma-Maximax, Gamma-Maximix, Interval Dominance, Maximality and E-admissibility. We focus on the popular decision tree and influence diagram representations. Algorithms resort to linear/multilinear programming; we describe implementation and experiments. (C) 2010 Elsevier B.V. All rights reserved.

Infinite horizon MPC with non-minimal state space feedback

In the MPC literature, stability is usually assured under the assumption that the state is measured. Since the closed-loop system may be nonlinear because of the constraints, it is not possible to apply the separation principle to prove global stability for the Output feedback case. It is well known that, a nonlinear closed-loop system with the state estimated via an exponentially converging observer combined with a state feedback controller can be unstable even when the controller is stable. One alternative to overcome the state estimation problem is to adopt a non-minimal state space model, in which the states are represented by measured past inputs and outputs [P.C. Young, M.A. Behzadi, C.L. Wang, A. Chotai, Direct digital and adaptative control by input-output, state variable feedback pole assignment, International journal of Control 46 (1987) 1867-1881; C. Wang, P.C. Young, Direct digital control by input-output, state variable feedback: theoretical background, International journal of Control 47 (1988) 97-109]. In this case, no observer is needed since the state variables can be directly measured. However, an important disadvantage of this approach is that the realigned model is not of minimal order, which makes the infinite horizon approach to obtain nominal stability difficult to apply. Here, we propose a method to properly formulate an infinite horizon MPC based on the output-realigned model, which avoids the use of an observer and guarantees the closed loop stability. The simulation results show that, besides providing closed-loop stability for systems with integrating and stable modes, the proposed controller may have a better performance than those MPC controllers that make use of an observer to estimate the current states. (C) 2008 Elsevier Ltd. All rights reserved.

Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

The procedure of on-line process control by attributes, known as Taguchi`s on-line process control, consists of inspecting the mth item (a single item) at every m produced items and deciding, at each inspection, whether the fraction of conforming items was reduced or not. If the inspected item is nonconforming, the production is stopped for adjustment. As the inspection system can be subject to diagnosis errors, one develops a probabilistic model that classifies repeatedly the examined item until a conforming or b non-conforming classification is observed. The first event that occurs (a conforming classifications or b non-conforming classifications) determines the final classification of the examined item. Proprieties of an ergodic Markov chain were used to get the expression of average cost of the system of control, which can be optimized by three parameters: the sampling interval of the inspections (m); the number of repeated conforming classifications (a); and the number of repeated non-conforming classifications (b). The optimum design is compared with two alternative approaches: the first one consists of a simple preventive policy. The production system is adjusted at every n produced items (no inspection is performed). The second classifies the examined item repeatedly r (fixed) times and considers it conforming if most classification results are conforming. Results indicate that the current proposal performs better than the procedure that fixes the number of repeated classifications and classifies the examined item as conforming if most classifications were conforming. On the other hand, the preventive policy can be averagely the most economical alternative rather than those ones that require inspection depending on the degree of errors and costs. A numerical example illustrates the proposed procedure. (C) 2009 Elsevier B. V. All rights reserved.

Animated solid model of the lung constructed from unsynchronized MR sequential images

This work discusses a 4D lung reconstruction method from unsynchronized MR sequential images. The lung, differently from the heart, does not have its own muscles, turning impossible to see its real movements. The visualization of the lung in motion is an actual topic of research in medicine. CT (Computerized Tomography) can obtain spatio-temporal images of the heart by synchronizing with electrocardiographic waves. The FOV of the heart is small when compared to the lung`s FOV. The lung`s movement is not periodic and is susceptible to variations in the degree of respiration. Compared to CT, MR (Magnetic Resonance) imaging involves longer acquisition times and it is not possible to obtain instantaneous 3D images of the lung. For each slice, only one temporal sequence of 2D images can be obtained. However, methods using MR are preferable because they do not involve radiation. In this paper, based on unsynchronized MR images of the lung an animated B-Repsolid model of the lung is created. The 3D animation represents the lung`s motion associated to one selected sequence of MR images. The proposed method can be divided in two parts. First, the lung`s silhouettes moving in time are extracted by detecting the presence of a respiratory pattern on 2D spatio-temporal MR images. This approach enables us to determine the lung`s silhouette for every frame, even on frames with obscure edges. The sequence of extracted lung`s silhouettes are unsynchronized sagittal and coronal silhouettes. Using our algorithm it is possible to reconstruct a 3D lung starting from a silhouette of any type (coronal or sagittal) selected from any instant in time. A wire-frame model of the lung is created by composing coronal and sagittal planar silhouettes representing cross-sections. The silhouette composition is severely underconstrained. Many wire-frame models can be created from the observed sequences of silhouettes in time. Finally, a B-Rep solid model is created using a meshing algorithm. Using the B-Rep solid model the volume in time for the right and left lungs were calculated. It was possible to recognize several characteristics of the 3D real right and left lungs in the shaded model. (C) 2007 Elsevier Ltd. All rights reserved.

Social behaviour of collared peccaries (Pecari tajacu) under three space allowances

Captive breeding of peccaries is on the increase in neotropical countries. Few studies, however, have reported behavioural responses of wild animals under farmed conditions. Therefore, the aim of this study was to evaluate the effects of space allowance on the occurrence of social behaviour patterns on farmed collared peccary (Pecan tajacu). We observed three herds of collared peccaries each containing eight acquainted individuals. Using a 3 x 3 Latin square design, herds were allocated, in a random order, to one of the three experimental enclosures, each with a different size. 375, 750 and 1,500 m(2) of total available area, each with three wooden shelters. We recorded all the occurrences of selected positive and agonistic behavioural patterns that occurred 90 min before and during feeding Enclosure size had a significant effect on agonistic patterns of peccaries during feeding, in that more agonistic behaviour was observed in smaller spaces We also found that shelter usage increased as space decreased Differing space allowances, however, did not have an effect on the occurrence of positive interactions that were more frequent before compared to during feeding. We concluded that enclosure size had an effect on the expression of agonistic be and the use of shelters by collared peccaries Thus, animal welfare can be improved by adopting at least 187 5 m(2) per peccary. In addition, our study also confirmed the importance of shelter areas in collared peccary husbandry.

Performance of a multi-level TDR system exposed to tropical field conditions - A time-space comparison with tensiometry

Time-domain reflectometry (TDR) is an important technique to obtain series of soil water content measurements in the field. Diode-segmented probes represent an improvement in TDR applicability, allowing measurements of the soil water content profile with a single probe. In this paper we explore an extensive soil water content dataset obtained by tensiometry and TDR from internal drainage experiments in two consecutive years in a tropical soil in Brazil. Comparisons between the variation patterns of the water content estimated by both methods exhibited evidences of deterioration of the TDR system during this two year period at field conditions. The results showed consistency in the variation pattern for the tensiometry data, whereas TDR estimates were inconsistent, with sensitivity decreasing over time. This suggests that difficulties may arise for the long-term use of this TDR system under tropical field conditions. (c) 2008 Elsevier B.V. All rights reserved.

Does using stepwise variable selection to build sequential path analysis models make sense?

Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.

Biomarkers of selenium status in the amazonian context: Blood, urine and sequential hair segments

Selenium (Se) is an essential element and deficit or excess of dietary Se is associated with health disorders. Relatively elevated Se levels have been reported in the Brazilian Amazon, where there are also important annual variations in the availability of different foods. The present study was conducted among six riparian communities of the Tapajos River to evaluate seasonal variations in blood and sequential hair cm Se concentrations, and to examine the relationships between Se in blood and hair, and blood and urine. Two cross-sectional studies were conducted, at the descending water (DWS, n = 259) and the rising water (RWS, n = 137) seasons, with repeated measures for a subgroup (n = 112). Blood Se (B-Se), hair Se (H-Se) and urine Se (U-Se) were determined. Match-paired analyses were used for seasonal comparisons and the method of best fit was used to describe the relationships between biomarkers. B-Se levels presented a very large range (142-2447 mu g/l) with no overall seasonal variation (median 284 and 292 mu g/l, respectively). Sequential analysis of 13 cm hair strands showed significant variations over time: Se concentrations at the DWS were significantly lower compared with the rising water season (medians: 0.7 and 0.9 mu g/g; ranges: 0.2-4.3 mu g/g and 0.2-5.4 mu g/g, respectively). At both seasons, the relationships between B-Se and H-Se were linear and highly significant (r(2) = 67.9 and 63.6, respectively), while the relationship between B-Se and U-Se was best described by a sigmoid curve. Gender, age, education and smoking did not influence Se status or biomarker relationships. Variations in H-Se suggest that there may be seasonal availability of Se sources in local food. For populations presenting a large range and/or elevated Se exposure, sequential analyses of H-Se may provide a good reflection of variations in Se status.

QUADRANT-SEARCHING: A NEW TECHNIQUE TO REDUCE THE SEARCH SPACE OF THE INVERSE PROBLEM OF EIT USING BEM TO THE DIRECT PROBLEM

The image reconstruction using the EIT (Electrical Impedance Tomography) technique is a nonlinear and ill-posed inverse problem which demands a powerful direct or iterative method. A typical approach for solving the problem is to minimize an error functional using an iterative method. In this case, an initial solution close enough to the global minimum is mandatory to ensure the convergence to the correct minimum in an appropriate time interval. The aim of this paper is to present a new, simple and low cost technique (quadrant-searching) to reduce the search space and consequently to obtain an initial solution of the inverse problem of EIT. This technique calculates the error functional for four different contrast distributions placing a large prospective inclusion in the four quadrants of the domain. Comparing the four values of the error functional it is possible to get conclusions about the internal electric contrast. For this purpose, initially we performed tests to assess the accuracy of the BEM (Boundary Element Method) when applied to the direct problem of the EIT and to verify the behavior of error functional surface in the search space. Finally, numerical tests have been performed to verify the new technique.