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.

Robust model predictive controller with output feedback and target tracking

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

A mechanistic kinetic model for phenol degradation by the Fenton process

The objective of this paper is to develop and validate a mechanistic model for the degradation of phenol by the Fenton process. Experiments were performed in semi-batch operation, in which phenol, catechol and hydroquinone concentrations were measured. Using the methodology described in Pontes and Pinto [R.F.F. Pontes, J.M. Pinto, Analysis of integrated kinetic and flow models for anaerobic digesters, Chemical Engineering journal 122 (1-2) (2006) 65-80], a stoichiometric model was first developed, with 53 reactions and 26 compounds, followed by the corresponding kinetic model. Sensitivity analysis was performed to determine the most influential kinetic parameters of the model that were estimated with the obtained experimental results. The adjusted model was used to analyze the impact of the initial concentration and flow rate of reactants on the efficiency of the Fenton process to degrade phenol. Moreover, the model was applied to evaluate the treatment cost of wastewater contaminated with phenol in order to meet environmental standards. (C) 2009 Elsevier B.V. All rights reserved.

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.

Valve friction and nonlinear process model closed-loop identification

Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.

Network of phase-locking oscillators and a possible model for neural synchronization

In order to model the synchronization of brain signals, a three-node fully-connected network is presented. The nodes are considered to be voltage control oscillator neurons (VCON) allowing to conjecture about how the whole process depends on synaptic gains, free-running frequencies and delays. The VCON, represented by phase-locked loops (PLL), are fully-connected and, as a consequence, an asymptotically stable synchronous state appears. Here, an expression for the synchronous state frequency is derived and the parameter dependence of its stability is discussed. Numerical simulations are performed providing conditions for the use of the derived formulae. Model differential equations are hard to be analytically treated, but some simplifying assumptions combined with simulations provide an alternative formulation for the long-term behavior of the fully-connected VCON network. Regarding this kind of network as models for brain frequency signal processing, with each PLL representing a neuron (VCON), conditions for their synchronization are proposed, considering the different bands of brain activity signals and relating them to synaptic gains, delays and free-running frequencies. For the delta waves, the synchronous state depends strongly on the delays. However, for alpha, beta and theta waves, the free-running individual frequencies determine the synchronous state. (C) 2011 Elsevier B.V. All rights reserved.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

Validation of a root water uptake model to estimate transpiration constraints

Experimental results obtained from a greenhouse trial with common bean (Phaseolus vulgaris L) plants performed to test model hypotheses regarding the onset of limiting hydraulic conditions and the shape of the transpiration reduction curve in the falling rate phase are presented. According to these hypotheses based on simulations with an upscaled single-root model, the matric flux potential at the onset of limiting hydraulic conditions is as a function of root length density and potential transpiration rate, while the relative transpiration in the falling rate phase equals the relative matric flux potential. Transpiration of bean plants in water stressed pots with four different soils was determined daily by weighing and compared to values obtained from non-stressed pots. This procedure allowed determining the onset of the falling rate phase and corresponding soil hydraulic conditions. At the onset of the falling rate phase, the value of matric flux potential M(I) showed to differ in order of magnitude from the model predicted value for three out of four soils. This difference between model and experiment can be explained by the heterogeneity of the root distribution which is not considered by the model. An empirical factor to deal with this heterogeneity should be included in the model to improve predictions. Comparing the predictions of relative transpiration in the falling rate phase using a linear shape with water content, pressure head or matric flux potential, the matric flux potential based reduction function, in agreement with the hypothesis, showed the best performance, while the pressure head based equation resulted in the highest deviations between observed and predicted values of relative transpiration rates. (C) 2010 Elsevier B.V. All rights reserved.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Adapting the CROPGRO perennial forage model to predict growth of Brachiaria brizantha

Warm-season grasses are economically important for cattle production in tropical regions, and tools to aid in management and research of these forages would be highly beneficial. Crop simulation models synthesize numerous physiological processes and are important research tools for evaluating production of warm-season grasses. This research was conducted to adapt the perennial CROPGRO Forage model to simulate growth of the tropical species palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. Xaraes] and to describe model adaptation for this species. In order to develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation and partitioning during a 2-year experiment with Xaraes palisadegrass in Piracicaba, SP, Brazil. Starting with parameters for the bahiagrass (Paspalum notatum Flugge) perennial forage model, dormancy effects had to be minimized, and partitioning to storage tissue/root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area (SLA) and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield per cycle was 3573 kg ha(-1), with a RMSE of 538 kg DM ha(-1) (D-Stat = 0.838, simulated/observed ratio = 1.028). The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of palisadegrass and can be used to simulate growth. (C) 2010 Elsevier B.V. All rights reserved.

Body composition and quality of life (QoL) of the elderly offered by the ""University Third Age`` (UTA) in Brazil

The investigation of the factors that interfere in the well-being of the elderly and their QoL can provide theoretical and methodological subsidies in structuring actions and policies in the health area, in order to fulfill the needs of that population. In this descriptive transversal study, body composition and QoL of elderly women at the UTA program in Piracicaba (Sao Paulo, Brazil) were verified. The participants were 81 women from UTA, and the general levels of physical activity were evaluated, as well as body weight (BW), height, and bodymass index (BMI). The waist circumference (WC) was measured at the level of the umbilical scar and the body composition by impedance (BIA 310e). QoL was verified by means of WHOQOL-Bref and statistical analysis developed with the SAS program. The decrease of weight, height, BMI, and fat-free mass (FFM) was observed among the several age groups, although with no significant difference. The average levels of the general QoL scores and physical, psychological and environmental domains decreased in higher age groups, but social domains showed the opposite result. This fact can be a particular characteristic of the UTA group, and factors the influence such behavior are yet to be studied. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Influence of a probiotic soy product on fecal microbiota and its association with cardiovascular risk factors in an animal model

Background: Previous work showed that daily ingestion of an aqueous soy extract fermented with Enterococcus faecium CRL 183 and Lactobacillus helveticus 416, supplemented or not with isoflavones, reduced the total cholesterol and non-HDL-cholesterol levels, increased the high-density lipoprotein (HDL) concentration and inhibited the raising of autoantibody against oxidized low-density lipoprotein (ox-LDL Ab) and the development of atherosclerotic lesions. Objective: The aim of this study was to characterize the fecal microbiota in order to investigate the possible correlation between fecal microbiota, serum lipid parameters and atherosclerotic lesion development in rabbits with induced hypercholesterolemia, that ingested the aqueous soy extract fermented with Enterococcus faecium CRL 183 and Lactobacillus helveticus 416. Methods: The rabbits were randomly allocated to five experimental groups (n = 6): control (C), hypercholesterolemic (H), hypercholesterolemic plus unfermented soy product (HUF), hypercholesterolemic plus fermented soy product (HF) and hypercholesterolemic plus isoflavone-supplemented fermented soy product (HIF). Lipid parameters and microbiota composition were analyzed on days 0 and 60 of the treatment and the atherosclerotic lesions were quantified at the end of the experiment. The fecal microbiota was characterized by enumerating the Lactobacillus spp., Bifidobacterium spp., Enterococcus spp., Enterobacteria and Clostridium spp. populations. Results: After 60 days of the experiment, intake of the probiotic soy product was correlated with significant increases (P < 0.05) on Lactobacillus spp., Bifidobacterium spp. and Enterococcus spp. and a decrease in the Enterobacteria population. A strong correlation was observed between microbiota composition and lipid profile. Populations of Enterococcus spp., Lactobacillus spp. and Bifidobacterium spp. were negatively correlated with total cholesterol, non-HDL-cholesterol, autoantibodies against oxidized LDL (ox-LDL Ab) and lesion size. HDL-C levels were positively correlated with Lactobacillus spp., Bifidobacterium spp., and Enterococcus spp. populations. Conclusion: In conclusion, daily ingestion of the probiotic soy product, supplemented or not with isoflavones, may contribute to a beneficial balance of the fecal microbiota and this modulation is associated with an improved cholesterol profile and inhibition of atherosclerotic lesion development.

Acute care surgeon South American model

Background In the World Health Organization book by Murray and Lopez (The Global Burden of Disease), the authors make the point that there are major regional differences across the world for death from injury. In the European market economies, injuries accounted for 6% of all deaths, of which the majority were the result of road traffic accidents. In stark contrast, in Latin America and the Caribbean, injuries account for 12-13% of all deaths, and most of these are the result of violence. An estimated 30% of all male deaths are from external causes, and road traffic accidents are the number two cause of death. Within South American countries, trauma is the second most common cause of death in Columbia, Venezuela, Ecuador, and Brazil. In other South American countries, it is the third or fourth most common cause of death. If one examines the Disability Adjusted Life Years, South America is the third highest in the world. Death from injury primarily affects people in the middle- and low-income group. Traffic accidents and suicide are the main causes of trauma in the high-income population. South America is made up of developing and poor countries that have trauma as a very important cause of death and disability. Methods The author has reviewed information on injury from the World Health Organization, Pan American Health Organization, and Brazilian Health Ministry. In addition, a search of injury was performed through MEDLINE. Results and Conclusions The results of this review show that trauma is a major public health problem in South America. At the present time, there is a lack of statewide system development. In addition, there are difficulties in training surgeons to cope with these problems.

The role of interleukin-6, endothelins, and apoptotic genes in small bowel transplantation, in a swine model of ischemia and reperfusion injury

IRI is closely related to sepsis in ITx setting. Complete understanding of the mechanisms involved in IRI development may improve outcomes. Ortothopic ITx without immunosuppression was performed in order to characterize IRI-associated mucosal damage. Twenty pigs underwent ITx. Two groups were assigned to different CI times: G1: 90 min and, G2: 180 min. Euro-Collins was used as preservation solution. Jejunal fragments were collected at donor laparotomy, 30 min, and 3 days after reperfusion. IRI assessment involved: histopathologic analysis, quantification of MPO-positive cells through immunohistochemical studies, quantification of epithelial apoptotic cells using TUNEL staining, and quantification of IL-6, ET-1, Bak, and Bcl-XL genes expression by RT-PCR. Neutrophilic infiltration increased in a similar fashion in both groups, but lasted longer in G2. Apoptosis detected by TUNEL staining increased and anti-apoptotic gene Bcl-XL expression decreased significantly in G1, 3 days after surgery. Endothelin-1 and IL-6 genes expression increased 30 min after the procedure and returned to baseline 3 days after surgery. In conclusion, IL-6 and ET-1 are involved precociously in the development of intestinal IRI. Apoptosis was more frequently detected in G1 grafts by TUNEL-staining and by RT-PCR.