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.

Improved effective charge density in MOS capacitors with PECVD SiOxNy dielectric layer obtained at low RF power

In this work SiOxNy films are produced and characterized. Series of samples were deposited by the plasma enhanced chemical vapor deposition (PECVD) technique at low temperatures from silane (SiH4), nitrous oxide (N2O) and helium (He) precursor gaseous mixtures, at different deposition power in order to analyze the effect of this parameter on the films structural properties, on the SiOxNy/Si interface quality and on the SiOxNy effective charge density. In order to compare the film structural properties with the interface (SiOxNy/Si) quality and effective charge density, MOS capacitors were fabricated using these films as dielectric layer. X-ray absorption near-edge spectroscopy (XANES), at the Si-K edge, was utilized to investigate the structure of the films and the material bonding characteristics were analyzed through Fourier transform infrared spectroscopy (FTIR). The MOS capacitors were characterized by low and high frequency capacitance (C-V) measurements, in order to obtain the interface state density (D-it) and the effective charge density (N-ss). An effective charge density linear reduction for decreasing deposition power was observed, result that is attributed to the smaller amount of ions present in the plasma for low RF power. (C) 2008 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.

Distributed power control algorithm for multiple access systems based on Verhulst model

In this paper the continuous Verhulst dynamic model is used to synthesize a new distributed power control algorithm (DPCA) for use in direct sequence code division multiple access (DS-CDMA) systems. The Verhulst model was initially designed to describe the population growth of biological species under food and physical space restrictions. The discretization of the corresponding differential equation is accomplished via the Euler numeric integration (ENI) method. Analytical convergence conditions for the proposed DPCA are also established. Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations. The simulation results are compared with two other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal of Uykan and Koivo. Under estimated errors conditions, the proposed DPCA exhibits smaller discrepancy from the optimum power vector solution and better convergence (under fixed and adaptive convergence factor) than the classic and sigmoidal DPCAs. (C) 2010 Elsevier GmbH. All rights reserved.

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.

Local search multiuser detection

In this work, a wide analysis of local search multiuser detection (LS-MUD) for direct sequence/code division multiple access (DS/CDMA) systems under multipath channels is carried out considering the performance-complexity trade-off. It is verified the robustness of the LS-MUD to variations in loading, E(b)/N(0), near-far effect, number of fingers of the Rake receiver and errors in the channel coefficients estimates. A compared analysis of the bit error rate (BER) and complexity trade-off is accomplished among LS, genetic algorithm (GA) and particle swarm optimization (PSO). Based on the deterministic behavior of the LS algorithm, it is also proposed simplifications over the cost function calculation, obtaining more efficient algorithms (simplified and combined LS-MUD versions) and creating new perspectives for the MUD implementation. The computational complexity is expressed in terms of the number of operations in order to converge. Our conclusion pointed out that the simplified LS (s-LS) method is always more efficient, independent of the system conditions, achieving a better performance with a lower complexity than the others heuristics detectors. Associated to this, the deterministic strategy and absence of input parameters made the s-LS algorithm the most appropriate for the MUD problem. (C) 2008 Elsevier GmbH. All rights reserved.

Postural control during kneeling

Postural control was studied when the subject was kneeling with erect trunk in a quiet posture and compared to that obtained during quiet standing. The analysis was based on the center of pressure motion in the sagittal plane (CPx), both in the time and in the frequency domains. One could assume that postural control during kneeling would be poorer than in standing because it is a less natural posture. This could cause a higher CPx variability. The power spectral density (PSD) of the CPx obtained from the experimental data in the kneeling position (KN) showed a significant decrease at frequencies below 0.3 Hz compared to upright (UP) (P < 0.01), which indicates less sway in KN. Conversely, there was an increase in fast postural oscillations (above 0.7 Hz) during KN compared to UP (P < 0.05). The root mean square (RMS) of the CPx was higher for UP (P < 0.01) while the mean velocity (MV) was higher during KN (P < 0.05). Lack of vision had a significant effect on the PSD and the parameters estimated from the CPx in both positions. We also sought to verify whether the changes in the PSD of the CPx found between the UP and KN positions were exclusively due to biomechanical factors (e.g., lowered center of gravity), or also reflected changes in the neural processes involved in the control of balance. To reach this goal, besides the experimental approach, a simple feedback model (a PID neural system, with added neural noise and controlling an inverted pendulum) was used to simulate postural sway in both conditions (in KN the pendulum was shortened, the mass and the moment of inertia were decreased). A parameter optimization method was used to fit the CPx power spectrum given by the model to that obtained experimentally. The results indicated that the changed anthropometric parameters in KN would indeed cause a large decrease in the power spectrum at low frequencies. However, the model fitting also showed that there were considerable changes also in the neural subsystem when the subject went from standing to kneeling. There was a lowering of the proportional and derivative gains and an increase in the neural noise power. Additional increases in the neural noise power were found also when the subject closed his eyes.

Model for facilities or vendors location in a global scale considering several echelons in the Chain

The facilities location problem for companies with global operations is very complex and not well explored in the literature. This work proposes a MILP model that solves the problem through minimization of the total logistic cost. Main contributions of the model are the pioneer carrying cost calculation, the treatment given to the take-or-pay costs and to the international tax benefits such as drawback and added value taxes in Brazil. The model was successfully applied to a real case of a chemical industry with industrial plants and sales all over the world. The model application recommended a totally new sourcing model for the company.

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.

Thermodynamic information system for diagnosis and prognosis of power plant operation condition

A thermodynamic information system for diagnosis and prognosis of an existing power plant was developed. The system is based on an analytic approach that informs the current thermodynamic condition of all cycle components, as well as the improvement that can be obtained in the cycle performance by the elimination of the discovered anomalies. The effects induced by components anomalies and repairs in other components efficiency, which have proven to be one of the main drawbacks in the diagnosis and prognosis analyses, are taken into consideration owing to the use of performance curves and corrected performance curves together with the thermodynamic data collected from the distributed control system. The approach used to develop the system is explained, the system implementation in a real gas turbine cogeneration combined cycle is described and the results are discussed. (C) 2011 Elsevier Ltd. All rights reserved.

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.

Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.