In Patients With Acute Myocardial Infarction, the Impact of Hyperglycemia as a Risk Factor for Mortality Is Not Homogeneous Across Age-Groups

OBJECTIVE To assess the impact of hyperglycemia in different age-groups of patients with acute myocardial infarction (AM I). RESEARCH DESIGN AND METHODS A total of 2,027 patients with AMI were categorized into one of five age-groups: <50 years (n = 301), >= 50 and <60 (n = 477),>= 60 and <70 (n = 545), >= 70 and <80 (n = 495), and years (n = 209). Hyperglycemia was defined as initial glucose >= 115 mg/dL. RESULTS The adjusted odds ratios for hyperglycemia predicting hospital mortality in groups 1-5 were, respectively, 7.57 (P = 0.004), 3.21 (P 0.046), 3.50 (P = 0.003), 3.20 (P < 0.001.), and 2.16 (P = 0.021). The adjusted P values for correlation between glucose level (as a continuous variable) and mortality were 0.007, <0.001, 0.043, <0.001, and 0.064. The areas under the ROC curves (AUCs) were 0.785, 0.709, 0.657, 0.648, and 0.613. The AUC in group 1 was significantly higher than those in groups 3-5. CONCLUSIONS The impact of hyperglycemia as a risk factor for hospital mortality in AMI is more pronounced in younger patients.

Influence of Genomic Ancestry on the Distribution of SLCO1B1, SLCO1B3 and ABCB1 Gene Polymorphisms among Brazilians

The frequency distribution of SNPs and haplotypes in the ABCB1, SLCO1B1 and SLCO1B3 genes varies largely among continental populations. This variation can lead to biases in pharmacogenetic studies conducted in admixed populations such as those from Brazil and other Latin American countries. The aim of this study was to evaluate the influence of self-reported colour, geographical origin and genomic ancestry on distributions of the ABCB1, SLCO1B1 and SLCO1B3 polymorphisms and derived haplotypes in admixed Brazilian populations. A total of 1039 healthy adults from the north, north-east, south-east and south of Brazil were recruited for this investigation. The c.388A>G (rs2306283), c.463C>A (rs11045819) and c.521T>C (rs4149056) SNPs in the SLCO1B1 gene and c.334T>G (rs4149117) and c.699G>A (rs7311358) SNPs in the SLCO1B3 gene were determined by Taqman 5'-nuclease assays. The ABCB1 c.1236C>T (rs1128503), c.2677G>T/A (rs2032582) and c.3435C>T (rs1045642) polymorphisms were genotyped using a previously described single-base extension/termination method. The results showed that genotype and haplotype distributions are highly variable among populations of the same self-reported colour and geographical region. However, genomic ancestry showed that these associations are better explained by a continuous variable. The influence of ancestry on the distribution of alleles and haplotype frequencies was more evident in variants with large differences in allele frequencies between European and African populations. Design and interpretation of pharmacogenetic studies using these transporter genes should include genomic controls to avoid spurious conclusions based on improper matching of study cohorts from Brazilian populations and other highly admixed populations.

Six-element circuit for maximum power point tracking in photovoltaic-motor systems with variable-frequency drives

A low-cost circuit was developed for stable and efficient maximum power point (MPP) tracking in autonomous photo voltaic-motor systems with variable-frequency drives (VFDs). The circuit is made of two resistors, two capacitors, and two Zener diodes. Its input is the photovoltaic (PV) array voltage and its output feeds the proportional-integral-derivative (PID) controller usually integrated into, the drive. The steady-state frequency-voltage oscillations induced by the circuit were treated in a simplified mathematical model, which was validated by widely characterizing a PV-powered centrifugal pump. General procedures for circuit and controller tuning were recommended based on model equations. The tracking circuit presented here is widely applicable to PV-motor system with VFDs, offering an. efficient open-access technology of unique simplicity. Copyright (C) 2010 John Wiley & Sons, Ltd.

A comparative evaluation of polymerization stress data obtained with four different mechanical testing systems

Objectives. The null hypothesis was that mechanical testing systems used to determine polymerization stress (sigma(pol)) would rank a series of composites similarly. Methods. Two series of composites were tested in the following systems: universal testing machine (UTM) using glass rods as bonding substrate, UTM/acrylic rods, "low compliance device", and single cantilever device ("Bioman"). One series had five experimental composites containing BisGMA:TEGDMA in equimolar concentrations and 60, 65, 70, 75 or 80 wt% of filler. The other series had five commercial composites: Filtek Z250 (3M ESPE), Filtek A110 (3M ESPE), Tetric Ceram (Ivoclar), Heliomolar (Ivoclar) and Point 4 (Kerr). Specimen geometry, dimensions and curing conditions were similar in all systems. sigma(pol) was monitored for 10 min. Volumetric shrinkage (VS) was measured in a mercury dilatometer and elastic modulus (E) was determined by three-point bending. Shrinkage rate was used as a measure of reaction kinetics. ANOVA/Tukey test was performed for each variable, separately for each series. Results. For the experimental composites, sigma(pol) decreased with filler content in all systems, following the variation in VS. For commercial materials, sigma(pol) did not vary in the UTM/acrylic system and showed very few similarities in rankings in the others tests system. Also, no clear relationships were observed between sigma(pol) and VS or E. Significance. The testing systems showed a good agreement for the experimental composites, but very few similarities for the commercial composites. Therefore, comparison of polymerization stress results from different devices must be done carefully. (c) 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

Stabilization for an ensemble of half-spin systems

Feedback stabilization of an ensemble of non interacting half spins described by the Bloch equations is considered. This system may be seen as an interesting example for infinite dimensional systems with continuous spectra. We propose an explicit feedback law that stabilizes asymptotically the system around a uniform state of spin +1/2 or -1/2. The proof of the convergence is done locally around the equilibrium in the H-1 topology. This local convergence is shown to be a weak asymptotic convergence for the H-1 topology and thus a strong convergence for the C topology. The proof relies on an adaptation of the LaSalle invariance principle to infinite dimensional systems. Numerical simulations illustrate the efficiency of these feedback laws, even for initial conditions far from the equilibrium. (C) 2011 Elsevier Ltd. All rights reserved.

New approach for power transformer protection based on intelligent hybrid systems

A power transformer needs continuous monitoring and fast protection as it is a very expensive piece of equipment and an essential element in an electrical power system. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can mislead the conventional protection affecting the power system stability negatively. This study proposes the development of a new algorithm to improve the protection performance by using fuzzy logic, artificial neural networks and genetic algorithms. An electrical power system was modelled using Alternative Transients Program software to obtain the operational conditions and fault situations needed to test the algorithm developed, as well as a commercial differential relay. Results show improved reliability, as well as a fast response of the proposed technique when compared with conventional ones.

A New Method of Current Switching for Linear Wide-Range Measurement Systems

This new and general method here called overflow current switching allows a fast, continuous, and smooth transition between scales in wide-range current measurement systems, like electrometers. This is achieved, using a hydraulic analogy, by diverting only the overflow current, such that no slow element is forced to change its state during the switching. As a result, this approach practically eliminates the long dead time in low-current (picoamperes) switching. Similar to a logarithmic scale, a composition of n adjacent linear scales, like a segmented ruler, measures the current. The use of a linear wide-range system based on this technique assures fast and continuous measurement in the entire range, without blind regions during transitions and still holding suitable accuracy for many applications. A full mathematical development of the method is given. Several computer realistic simulations demonstrated the viability of the technique.

Progress in the mathematical theory of quantum disordered systems

We review recent progress in the mathematical theory of quantum disordered systems: the Anderson transition, including some joint work with Marchetti, the (quantum and classical) Edwards-Anderson (EA) spin-glass model and return to equilibrium for a class of spin-glass models, which includes the EA model initially in a very large transverse magnetic field. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4770066]

Kinetic and growth parameters of Arthrospira (Spirulina) platensis cultivated in tubular photobioreactor under different cell circulation systems

Arthrospira platensis was cultivated in tubular photobioreactor in order to evaluate growth and biomass production at variable photosynthetic photon flux density (PPFD?=?60, 120, and 240?mu mol photons m-2?s-1) and employing three different systems for cell circulation, specifically an airlift, a motor-driven pumping and a pressurized system. The influence of these two independents variables on the maximum cell concentration (Xm), cell productivity (Px), nitrogen-to-cell conversion factor (YX/N), photosynthetic efficiency (PE), and biomass composition (total lipids and proteins), taken as responses, was evaluated by analysis of variance. The statistical analysis revealed that the best combination of responses' mean values (Xm?=?4,055?mg?L-1, Px?=?406?mg?L-1?day-1, YX/N?=?5.07?mg?mg-1, total lipids?=?8.94%, total proteins?=?30.3%, PE?=?2.04%) was obtained at PPFD?=?120?mu mol photons m-2?s-1; therefore, this light intensity should be considered as the most well-suited for A. platensis cultivation in this photobioreactor configuration. The airlift system did not exert any significant positive statistical influence on the responses, which suggests that this traditional cell circulation system could successfully be substituted by the others tested in this work. Biotechnol. Bioeng. 2012; 109:444450. (c) 2011 Wiley Periodicals, Inc.

Entropy Production in Nonequilibrium Systems at Stationary States

We present a stochastic approach to nonequilibrium thermodynamics based on the expression of the entropy production rate advanced by Schnakenberg for systems described by a master equation. From the microscopic Schnakenberg expression we get the macroscopic bilinear form for the entropy production rate in terms of fluxes and forces. This is performed by placing the system in contact with two reservoirs with distinct sets of thermodynamic fields and by assuming an appropriate form for the transition rate. The approach is applied to an interacting lattice gas model in contact with two heat and particle reservoirs. On a square lattice, a continuous symmetry breaking phase transition takes place such that at the nonequilibrium ordered phase a heat flow sets in even when the temperatures of the reservoirs are the same. The entropy production rate is found to have a singularity at the critical point of the linear-logarithm type.

Investigating Smart Sampling as a population initialization method for Differential Evolution in continuous problems

Recently, researches have shown that the performance of metaheuristics can be affected by population initialization. Opposition-based Differential Evolution (ODE), Quasi-Oppositional Differential Evolution (QODE), and Uniform-Quasi-Opposition Differential Evolution (UQODE) are three state-of-the-art methods that improve the performance of the Differential Evolution algorithm based on population initialization and different search strategies. In a different approach to achieve similar results, this paper presents a technique to discover promising regions in a continuous search-space of an optimization problem. Using machine-learning techniques, the algorithm named Smart Sampling (SS) finds regions with high possibility of containing a global optimum. Next, a metaheuristic can be initialized inside each region to find that optimum. SS and DE were combined (originating the SSDE algorithm) to evaluate our approach, and experiments were conducted in the same set of benchmark functions used by ODE, QODE and UQODE authors. Results have shown that the total number of function evaluations required by DE to reach the global optimum can be significantly reduced and that the success rate improves if SS is employed first. Such results are also in consonance with results from the literature, stating the importance of an adequate starting population. Moreover, SS presents better efficacy to find initial populations of superior quality when compared to the other three algorithms that employ oppositional learning. Finally and most important, the SS performance in finding promising regions is independent of the employed metaheuristic with which SS is combined, making SS suitable to improve the performance of a large variety of optimization techniques. (C) 2012 Elsevier Inc. All rights reserved.

A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal-Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient. (C) 2012 Elsevier B.V. All rights reserved.

Chains of Infinite Order, Chains with Memory of Variable Length, and Maps of the Interval

We show how to construct a topological Markov map of the interval whose invariant probability measure is the stationary law of a given stochastic chain of infinite order. In particular we characterize the maps corresponding to stochastic chains with memory of variable length. The problem treated here is the converse of the classical construction of the Gibbs formalism for Markov expanding maps of the interval.

OPTIMIZATION AND CONTROL OF A CONTINUOUS POLYMERIZATION REACTOR

This work studies the optimization and control of a styrene polymerization reactor. The proposed strategy deals with the case where, because of market conditions and equipment deterioration, the optimal operating point of the continuous reactor is modified significantly along the operation time and the control system has to search for this optimum point, besides keeping the reactor system stable at any possible point. The approach considered here consists of three layers: the Real Time Optimization (RTO), the Model Predictive Control (MPC) and a Target Calculation (TC) that coordinates the communication between the two other layers and guarantees the stability of the whole structure. The proposed algorithm is simulated with the phenomenological model of a styrene polymerization reactor, which has been widely used as a benchmark for process control. The complete optimization structure for the styrene process including disturbances rejection is developed. The simulation results show the robustness of the proposed strategy and the capability to deal with disturbances while the economic objective is optimized.