Phase Equilibrium and Optimization Tools: Application for Enhanced Structured Lipids for Foods

Solid-liquid phase equilibrium modeling of triacylglycerol mixtures is essential for lipids design. Considering the alpha polymorphism and liquid phase as ideal, the Margules 2-suffix excess Gibbs energy model with predictive binary parameter correlations describes the non ideal beta and beta` solid polymorphs. Solving by direct optimization of the Gibbs free energy enables one to predict from a bulk mixture composition the phases composition at a given temperature and thus the SFC curve, the melting profile and the Differential Scanning Calorimetry (DSC) curve that are related to end-user lipid properties. Phase diagram, SFC and DSC curve experimental data are qualitatively and quantitatively well predicted for the binary mixture 1,3-dipalmitoyl-2-oleoyl-sn-glycerol (POP) and 1,2,3-tripalmitoyl-sn-glycerol (PPP), the ternary mixture 1,3-dimyristoyl-2-palmitoyl-sn-glycerol (MPM), 1,2-distearoyl-3-oleoyl-sn-glycerol (SSO) and 1,2,3-trioleoyl-sn-glycerol (OOO), for palm oil and cocoa butter. Then, addition to palm oil of Medium-Long-Medium type structured lipids is evaluated, using caprylic acid as medium chain and long chain fatty acids (EPA-eicosapentaenoic acid, DHA-docosahexaenoic acid, gamma-linolenic-octadecatrienoic acid and AA-arachidonic acid), as sn-2 substitutes. EPA, DHA and AA increase the melting range on both the fusion and crystallization side. gamma-linolenic shifts the melting range upwards. This predictive tool is useful for the pre-screening of lipids matching desired properties set a priori.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

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.

An Array Recursive Least-Squares Algorithm With Generic Nonfading Regularization Matrix

We present a novel array RLS algorithm with forgetting factor that circumvents the problem of fading regularization, inherent to the standard exponentially-weighted RLS, by allowing for time-varying regularization matrices with generic structure. Simulations in finite precision show the algorithm`s superiority as compared to alternative algorithms in the context of adaptive beamforming.

A sensor array based on mass and capacitance transducers for the detection of adulterated gasolines

The simultaneous use of different sensors technologies is an efficient method to increase the performance of chemical sensors systems. Among the available technologies, mass and capacitance transducers are particularly interesting because they can take advantage also from non-conductive sensing layers, such as most of the more interesting molecular recognition systems. In this paper, an array of quartz microbalance sensors is complemented by an array of capacitors obtained from a commercial biometrics fingerprints detector. The two sets of transducers, properly functionalized by sensitive molecular and polymeric films, are utilized for the estimation of adulteration in gasolines, and in particular to quantify the content of ethanol in gasolines, an application of importance for Brazilian market. Results indicate that the hybrid system outperforms the individual sensor arrays even if the quantification of ethanol in gasoline, due to the variability of gasolines formulation, is affected by a barely acceptable error. (C) 2009 Elsevier B.V. All rights reserved.

Title Model for Computer Networks Optimization

The TCP/IP architecture was consolidated as a standard to the distributed systems. However, there are several researches and discussions about alternatives to the evolution of this architecture and, in this study area, this work presents the Title Model to contribute with the application needs support by the cross layer ontology use and the horizontal addressing, in a next generation Internet. For a practical viewpoint, is showed the network cost reduction for the distributed programming example, in networks with layer 2 connectivity. To prove the title model enhancement, it is presented the network analysis performed for the message passing interface, sending a vector of integers and returning its sum. By this analysis, it is confirmed that the current proposal allows, in this environment, a reduction of 15,23% over the total network traffic, in bytes.

Optimization of the Topology of Electric Energy Distribution Networks by Using Algorithm Inspired on Ant Behaviors

An algorithm inspired on ant behavior is developed in order to find out the topology of an electric energy distribution network with minimum power loss. The algorithm performance is investigated in hypothetical and actual circuits. When applied in an actual distribution system of a region of the State of Sao Paulo (Brazil), the solution found by the algorithm presents loss lower than the topology built by the concessionary company.

Optimization and Complexity Reduction of Switch-Reconfigured Antennas Using Graph Models

This letter addresses the optimization and complexity reduction of switch-reconfigured antennas. A new optimization technique based on graph models is investigated. This technique is used to minimize the redundancy in a reconfigurable antenna structure and reduce its complexity. A graph modeling rule for switch-reconfigured antennas is proposed, and examples are presented.

Using Reverberation to Improve Range and Elevation Discrimination for Small Array Sound Source Localization

Sound source localization (SSL) is an essential task in many applications involving speech capture and enhancement. As such, speaker localization with microphone arrays has received significant research attention. Nevertheless, existing SSL algorithms for small arrays still have two significant limitations: lack of range resolution, and accuracy degradation with increasing reverberation. The latter is natural and expected, given that strong reflections can have amplitudes similar to that of the direct signal, but different directions of arrival. Therefore, correctly modeling the room and compensating for the reflections should reduce the degradation due to reverberation. In this paper, we show a stronger result. If modeled correctly, early reflections can be used to provide more information about the source location than would have been available in an anechoic scenario. The modeling not only compensates for the reverberation, but also significantly increases resolution for range and elevation. Thus, we show that under certain conditions and limitations, reverberation can be used to improve SSL performance. Prior attempts to compensate for reverberation tried to model the room impulse response (RIR). However, RIRs change quickly with speaker position, and are nearly impossible to track accurately. Instead, we build a 3-D model of the room, which we use to predict early reflections, which are then incorporated into the SSL estimation. Simulation results with real and synthetic data show that even a simplistic room model is sufficient to produce significant improvements in range and elevation estimation, tasks which would be very difficult when relying only on direct path signal components.

S/MIMO MC-CDMA Heuristic Multiuser Detectors Based on Single-Objective Optimization

This paper analyzes the complexity-performance trade-off of several heuristic near-optimum multiuser detection (MuD) approaches applied to the uplink of synchronous single/multiple-input multiple-output multicarrier code division multiple access (S/MIMO MC-CDMA) systems. Genetic algorithm (GA), short term tabu search (STTS) and reactive tabu search (RTS), simulated annealing (SA), particle swarm optimization (PSO), and 1-opt local search (1-LS) heuristic multiuser detection algorithms (Heur-MuDs) are analyzed in details, using a single-objective antenna-diversity-aided optimization approach. Monte- Carlo simulations show that, after convergence, the performances reached by all near-optimum Heur-MuDs are similar. However, the computational complexities may differ substantially, depending on the system operation conditions. Their complexities are carefully analyzed in order to obtain a general complexity-performance framework comparison and to show that unitary Hamming distance search MuD (uH-ds) approaches (1-LS, SA, RTS and STTS) reach the best convergence rates, and among them, the 1-LS-MuD provides the best trade-off between implementation complexity and bit error rate (BER) performance.

OPTIMIZATION OF THE TREATMENT PROCESS FOR RESIDUAL WATER FROM A BEER INDUSTRY

The optimization of the treatment process for residual waters from a brewery operating under the modality of an anaerobic reactor and activated sludge combination was studied in two phases. In the first stage, lasting for six months, the characteristics and parameters of the plant operation were analyzed, wherein a diversion rate of more than 50% to aerobic treatment, the use of two aeration tanks and a high sludge production prevailed. The second stage comprised four months during which the system worked under the proposed operational model, with the aim of improving the treatment: reduction of the diversion rate to 30% and use of only one aeration tank At each stage, TSS, VSS and COD were measured at the entrance and exit of the anaerobic reactor mid the aeration tanks. The results were compared with the corresponding design specifications and the needed conditions were applied to reduce the diversion rate towards the aerobic process through monitoring the volume and concentration of the affluent, while applying the strategic changes in reactor parameters needed to increase its efficiency. A diversion reduction from 53 to 34% was achieved, reducing the sludge discharge generated in the aerobic system from 3670mg TSS/l. with two aeration tanks down to 2947mf TSS/l using one tank keeping the same relation VSS:TSS (0.55) and an efficiency of total removal of 98% in terms of COD.

A generalized multi-period mean-variance portfolio optimization with Markov switching parameters

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (C) 2008 Elsevier Ltd. All rights reserved.

MULTIVARIATE STATISTICAL METHOD IN OPTIMIZATION OF PROTEIN EXTRACTION FROM SOYBEAN FLOUR WITH DAIRY WHEY

The aim objective of this project was to evaluate the protein extraction of soybean flour in dairy whey, by the multivariate statistical method with 2(3) experiments. Influence of three variables were considered: temperature, pH and percentage of sodium chloride against the process specific variable ( percentage of protein extraction). It was observed that, during the protein extraction against time and temperature, the treatments at 80 degrees C for 2h presented great values of total protein (5.99%). The increasing for the percentage of protein extraction was major according to the heating time. Therefore, the maximum point from the function that represents the protein extraction was analysed by factorial experiment 2(3). By the results, it was noted that all the variables were important to extraction. After the statistical analyses, was observed that the parameters as pH, temperature, and percentage of sodium chloride, did not sufficient for the extraction process, since did not possible to obtain the inflection point from mathematical function, however, by the other hand, the mathematical model was significant, as well as, predictive.

Method development and optimization for the determination of selenium in bean and soil samples using hydride generation electrothermal atomic absorption spectrometry

The present investigation is the first part of an initiative to prepare a regional map of the natural abundance of selenium in various areas of Brazil, based on the analysis of bean and soil samples. Continuous-flow hydride generation electrothermal atomic absorption spectrometry (HG-ET AAS) with in situ trapping on an iridium-coated graphite tube has been chosen because of the high sensitivity and relative simplicity. The microwave-assisted acid digestion for bean and soil samples was tested for complete recovery of inorganic and organic selenium compounds (selenomethionine). The reduction of Se(VI) to Se(IV) was optimized in order to guarantee that there is no back-oxidation, which is of importance when digested samples are not analyzed immediately after the reduction step. The limits of detection and quantification of the method were 30 ng L(-1) Se and 101 ng L(-1) Se, respectively, corresponding to about 3 ng g(-1) and 10 ng g(-1), respectively, in the solid samples, considering a typical dilution factor of 100 for the digestion process. The results obtained for two certified food reference materials (CRM), soybean and rice, and for a soil and sediment CRM confirmed the validity of the investigated method. The selenium content found in a number of selected bean samples varied between 5.5 +/- 0.4 ng g(-1) and 1726 +/- 55 ng g(-1), and that in soil samples varied between 113 +/- 6.5 ng g(-1) and 1692 +/- 21 ng g(-1). (C) 2011 Elsevier B.V. All rights reserved.

Physical Stability Assessment and Sensory Optimization of a Dairy-Free Emulsion Using Response Surface Methodology

Desserts made with soy cream, which are oil-in-water emulsions, are widely consumed by lactose-intolerant individuals in Brazil. In this regard, this study aimed at using response surface methodology (RSM) to optimize the sensory attributes of a soy-based emulsion over a range of pink guava juice (GJ: 22% to 32%) and soy protein (SP: 1% to 3%). WHC and backscattering were analyzed after 72 h of storage at 7 degrees C. Furthermore, a rating test was performed to determine the degree of liking of color, taste, creaminess, appearance, and overall acceptability. The data showed that the samples were stable against gravity and storage. The models developed by RSM adequately described the creaminess, taste, and appearance of the emulsions. The response surface of the desirability function was used successfully in the optimization of the sensory properties of dairy-free emulsions, suggesting that a product with 30.35% GJ and 3% SP was the best combination of these components. The optimized sample presented suitable sensory properties, in addition to being a source of dietary fiber, iron, copper, and ascorbic acid.