The double Caldeira-Leggett model: Derivation and solutions of the master equations, reservoir-induced interactions and decoherence

In this paper we analyze the double Caldeira-Leggett model: the path integral approach to two interacting dissipative harmonic oscillators. Assuming a general form of the interaction between the oscillators, we consider two different situations: (i) when each oscillator is coupled to its own reservoir, and (ii) when both oscillators are coupled to a common reservoir. After deriving and solving the master equation for each case, we analyze the decoherence process of particular entanglements in the positional space of both oscillators. To analyze the decoherence mechanism we have derived a general decay function, for the off-diagonal peaks of the density matrix, which applies both to common and separate reservoirs. We have also identified the expected interaction between the two dissipative oscillators induced by their common reservoir. Such a reservoir-induced interaction, which gives rise to interesting collective damping effects, such as the emergence of relaxation- and decoherence-free subspaces, is shown to be blurred by the high-temperature regime considered in this study. However, we find that different interactions between the dissipative oscillators, described by rotating or counter-rotating terms, result in different decay rates for the interference terms of the density matrix. (C) 2010 Elsevier B.V. All rights reserved.

Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations

The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

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.

Improved maximum-likelihood estimation in a regression model with general parametrization

We analyse the finite-sample behaviour of two second-order bias-corrected alternatives to the maximum-likelihood estimator of the parameters in a multivariate normal regression model with general parametrization proposed by Patriota and Lemonte [A. G. Patriota and A. J. Lemonte, Bias correction in a multivariate regression model with genereal parameterization, Stat. Prob. Lett. 79 (2009), pp. 1655-1662]. The two finite-sample corrections we consider are the conventional second-order bias-corrected estimator and the bootstrap bias correction. We present the numerical results comparing the performance of these estimators. Our results reveal that analytical bias correction outperforms numerical bias corrections obtained from bootstrapping schemes.

Estimation and prediction of parameters and breeding values in soybean using REML/BLUP and Least Squares

The aim of this study was to compare REML/BLUP and Least Square procedures in the prediction and estimation of genetic parameters and breeding values in soybean progenies. F(2:3) and F(4:5) progenies were evaluated in the 2005/06 growing season and the F(2:4) and F(4:6) generations derived thereof were evaluated in 2006/07. These progenies were originated from two semi-early, experimental lines that differ in grain yield. The experiments were conducted in a lattice design and plots consisted of a 2 m row, spaced 0.5 m apart. The trait grain yield per plot was evaluated. It was observed that early selection is more efficient for the discrimination of the best lines from the F(4) generation onwards. No practical differences were observed between the least square and REML/BLUP procedures in the case of the models and simplifications for REML/BLUP used here.

Computational evaluation of flexural toughness of FRC and fracture properties of plain concrete

In this paper, a computational tool concerning the computation of flexural and fracture toughness of cement based composites is presented. Firstly, RILEM`s (Reunion Internationale des Laboratoires d`Essais de Materiaux) recommendations related to the analysis of FRC in three-point bend tests are discussed in their relevant aspects regarding the computational implementations. The determination of other mechanical properties such as the Young modulus has been added to the program. Taking this into account, a new formulation based on displacements is used. In the second part of the paper, the determination of fracture properties of concrete, such as the fracture energy, G(F) , and the fracture toughness, K-IC(S), is discussed regarding the computational strategies used in the implementations. Several features whereby anterior data can be reanalyzed, obtained from other standards and recommendations, have been incorporated into the program, therefore allowing comparative studies and back analysis activities.

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.

Stability and in vitro penetration study of rutin incorporated in a cosmetic emulsion through an alternative model biomembrane

Rutin is employed as antioxidant and to prevent the capillary fragility and, when incorporated in cosmetic emulsions, it must target the action site. In vitro cutaneous penetration studies through human skin is the ideal situation, however, there are difficulties to obtain and to maintain this tissue viability. Among the membrane models, shed snake skin presents itself as pure stratum corneum, providing barrier function similar to human and it is obtained without the animal sacrifice. The objectives of this research were the development and stability evaluation of a cosmetic emulsion containing rutin and propylene glycol (penetration enhancer) and the evaluation or rutin in vitro cutaneous penetration and retention from the emulsion, employing an alternative model biomembrane. Emulsion was developed with rutin and propylene glycol, both at 5.0% w/w. Active substance presented on the formulation was quantified by a validated spectrophotometric method at 361.0 nm. Rutin Rutin cutaneous penetration and retention was performed in vertical diffusion cells with shed snake skin of Crotalus durissus, as alternative model biomembrane, and distilled water and ethanol 99.5% (1:1), as receptor fluid. The experiment was conducted for six hours, at 37.0 +/- 0.5 degrees C with constant stirring of 300 rpm. Spectrophotometry at 410.0 nm, previously validated, determined the active substance after cutaneous penetration/ retention. Emulsion did not promote rutin cutaneous penetration through C. durissus skin, retaining 0.931 +/- 0.0391 mu g rutin/mg shed snake skin. The referred formulation was chemically stable for 30 days after stored at 25.0 +/- 2.0 degrees C, 5.0 +/- 0.5 degrees C and 45.0 +/- 0.5 degrees C. In conclusion, it has not been verified the active cutaneous penetration through the model biomembrane, but only its retention on the Crotalus durissus stratum corneum, condition considered stable for 30 days.

Derivation and external validation of a simple prediction model for the diagnosis of type 2 Diabetes Mellitus in the Brazilian urban population

A risk score model was developed based in a population of 1,224 individuals from the general population without known diabetes aging 35 years or more from an urban Brazilian population sample in order to select individuals who should be screened in subsequent testing and improve the efficacy of public health assurance. External validation was performed in a second, independent, population from a different city ascertained through a similar epidemiological protocol. The risk score was developed by multiple logistic regression and model performance and cutoff values were derived from a receiver operating characteristic curve. Model`s capacity of predicting fasting blood glucose levels was tested analyzing data from a 5-year follow-up protocol conducted in the general population. Items independently and significantly associated with diabetes were age, BMI and known hypertension. Sensitivity, specificity and proportion of further testing necessary for the best cutoff value were 75.9, 66.9 and 37.2%, respectively. External validation confirmed the model`s adequacy (AUC equal to 0.72). Finally, model score was also capable of predicting fasting blood glucose progression in non-diabetic individuals in a 5-year follow-up period. In conclusion, this simple diabetes risk score was able to identify individuals with an increased likelihood of having diabetes and it can be used to stratify subpopulations in which performing of subsequent tests is necessary and probably cost-effective.

Total Pancreatectomy: Porcine Model for Inducing Diabetes - Anatomical Assessment and Surgical Aspects

Background: The swine is an essential model for carrying out preclinical research and for teaching complex surgical procedures. There is a lack of experimental models describing anatomical and surgical aspects of total pancreatectomy in the pig. Materials and Methods: The experiments were performed on 10 white male swine weighing 27-33 kg. The animals were premedicated with midazolam (0.4 mg/kg, i.m.) and ketamine (4 mg/kg, i.m.). Anesthesia was induced with propofol (1-2 mg/kg, i.v.) and was maintained with propofol and fentanyl (0.3 mg and 0.1 mu g/kg/min, respectively, i.v.). The surgical period ranged from 44 to 77 min. The pancreas anatomy, and the main arterial, venous and pancreatic duct anatomy were assessed. Results: The pancreas anatomy was composed of 3 lobes, the `splenic`, `duodenal` and `connecting` lobe which is attached to the anterior portion of the portal vein. The splenic artery and the junction of the splenic vein and portal vein were divided. The left gastric artery was dissected and separated from its origin at the splenic artery. The head of the pancreas is disposed in a C shape. The pancreas was dissected and liberated from the right portion of the portal vein and the infrahepatic vena cava. The pancreas was separated from the duodenum preserving the pancreaticoduodenal artery, then we performed the total pancreatectomy preserving the duodenum, common bile duct and spleen. Conclusion: Total pancreatectomy with duodenum, bile duct and spleen preservation in the pig is feasible and an important instrument for research purposes and teaching surgical technique. Copyright (C) 2010 S. Karger AG, Basel

Study of the pozzolanic reaction kinetics in sugar cane bagasse-clay ash/calcium hydroxide system: kinetic parameters and pozzolanic activity

This paper presents a study of the pozzolanic reaction kinetics between calcium hydroxide and a mixture of sugar cane bagasse with 20 and 30% of clay, burned at 800 and 1000 degrees C (SCBCA) by electrical conductivity measurements. A kinetic-diffusive model produced in previous studies by some of the authors was used. The model was fitted to the experimental data, which allowed the computation of the kinetic parameters of the pozzolanic reaction (reaction rate constant and free energy of activation) that rigorously characterised the pozzolanic activity of the materials. The results show that SCBCA demonstrated reactivity and good pozzolanic qualities in the range 800-1000 degrees C.

On the efficiency of data representation on the modeling and characterization of complex networks

Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.

Disruption of Saccharomyces cerevisiae by Plantaricin 149 and investigation of its mechanism of action with biomembrane model systems

The action of a synthetic antimicrobial peptide analog of Plantaricin 149 (Pln149a) against Saccharomyces cerevisiae and its interaction with biomembrane model systems were investigated. Pln149a was shown to inhibit S. cerevisiae growth by more than 80% in YPD medium, causing morphological changes in the yeast wall and remaining active and resistant to the yeast proteases even after 24 h of incubation. Different membrane model systems and carbohydrates were employed to better describe the Pln149a interaction with cellular components using circular dichroism and fluorescence spectroscopies, adsorption kinetics and surface elasticity in Langmuir monolayers. These assays showed that Pln149a does not interact with either mono/polysaccharides or zwitterionic LUVs, but is strongly adsorbed to and incorporated into negatively charged surfaces, causing a conformational change in its secondary structure from random-coil to helix upon adsorption. From the concurrent analysis of Pln149a adsorption kinetics and dilatational surface elasticity data, we determined that 2.5 mu M is the critical concentration at which Pln149a will disrupt a negative DPPG monolayer. Furthermore, Pln149a exhibited a carpet-like mechanism of action, in which the peptide initially binds to the membrane, covering its surface and acquiring a helical structure that remains associated to the negatively charged phospholipids. After this electrostatic interaction, another peptide region causes a strain in the membrane, promoting its disruption. (C) 2009 Elsevier B.V. All rights reserved.

STABILITY ANALYSIS WITH APPLICATIONS OF A TWO-DIMENSIONAL DYNAMICAL SYSTEM ARISING FROM A STOCHASTIC MODEL FOR AN ASSET MARKET

We analyze the stability properties of equilibrium solutions and periodicity of orbits in a two-dimensional dynamical system whose orbits mimic the evolution of the price of an asset and the excess demand for that asset. The construction of the system is grounded upon a heterogeneous interacting agent model for a single risky asset market. An advantage of this construction procedure is that the resulting dynamical system becomes a macroscopic market model which mirrors the market quantities and qualities that would typically be taken into account solely at the microscopic level of modeling. The system`s parameters correspond to: (a) the proportion of speculators in a market; (b) the traders` speculative trend; (c) the degree of heterogeneity of idiosyncratic evaluations of the market agents with respect to the asset`s fundamental value; and (d) the strength of the feedback of the population excess demand on the asset price update increment. This correspondence allows us to employ our results in order to infer plausible causes for the emergence of price and demand fluctuations in a real asset market. The employment of dynamical systems for studying evolution of stochastic models of socio-economic phenomena is quite usual in the area of heterogeneous interacting agent models. However, in the vast majority of the cases present in the literature, these dynamical systems are one-dimensional. Our work is among the few in the area that construct and study analytically a two-dimensional dynamical system and apply it for explanation of socio-economic phenomena.

Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.