Resting Heart Rate is Associated with Blood Pressure in Male Children and Adolescents

Objectives To analyze the association between resting heart rate and blood pressure in male children and adolescents and to identify if this association is mediated by important confounders. Study design Cross-sectional study carried out with 356 male children and adolescents from 8 to 18 years old. Resting heart rate was measured by a portable heart rate monitor according to recommendations and stratified into quartiles. Blood pressure was measured with an electronic device previously validated for pediatric populations. Body fatness was estimated by a dual-energy x-ray absorptiometry. Results Obese subjects had values of resting heart rate 7.8% higher than nonobese (P = .001). Hypertensive children and adolescents also had elevated values of resting heart rate (P = .001). When the sample was stratified in nonobese and obese, the higher quartile of resting heart rate was associated with hypertension in both groups of children and adolescents. Conclusions This study confirms the existence of a relationship between elevated resting heart rate and increased blood pressure in a pediatric population, independent of adiposity, ethnicity and age. (J Pediatr 2011; 158:634-7).

Niobium hydrogenation process Effect of temperature and cooling rate from the hydrogenation temperature

High-purity niobium powder can be produced via the hydrogenation and dehydrogenation processes The present work aimed at the effect of temperature and cooling rate conditions on the niobium hydrogenation process using hydrogen gas The hydrogen contents of the materials were evaluated by weight change and chemical analysis X ray diffraction (XRD) was performed to identify and determine the lattice parameters of the formed hydride phases No hydrogenation took place under isothermal conditions only during cooling of the materials Significant hydrogenation occurred in the 500 C and 700 C experiments leading to the formation of a beta NbH(x) single phase material (C) 2010 Elsevier Ltd All rights reserved

Screening of lipases for the synthesis of xylitol monoesters by chemoenzymatic esterification and the potential of microwave and ultrasound irradiations to enhance the reaction rate

Lipases from different sources, Pseudomonas fluorescens (AK lipase), Burkholderia cepacia (PS lipase), Penicillium camembertii (lipase G) and Porcine pancreas lipase (PPL), previously immobilized on epoxy SiO(2)-PVA, were screened for the synthesis of xylitol monoesters by esterification of the protected xylitol using oleic acid as acyl donor group. Among all immobilized derivatives, the highest esterification yield was achieved by P. camembertii lipase, showing to be attractive alternative to bulk chemical routes to satisfy increasing commercial demands. Further experiments were performed to determine the influence of fatty acids chain size on the reaction yield and the feasibility of using non-conventional heating systems (microwave and ultrasound irradiations) to enhance the reaction rate. (C) 2010 Elsevier B.V. All rights reserved.

Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration

The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

An algorithm for computerized automatic tuning of power system stabilizers

The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

NEX-LMS: A novel adaptive control scheme for harmonic sound quality control

This paper presents a novel adaptive control scheme. with improved convergence rate, for the equalization of harmonic disturbances such as engine noise. First, modifications for improving convergence speed of the standard filtered-X LMS control are described. Equalization capabilities are then implemented, allowing the independent tuning of harmonics. Eventually, by providing the desired order vs. engine speed profiles, the pursued sound quality attributes can be achieved. The proposed control scheme is first demonstrated with a simple secondary path model and, then, experimentally validated with the aid of a vehicle mockup which is excited with engine noise. The engine excitation is provided by a real-time sound quality equivalent engine simulator. Stationary and transient engine excitations are used to assess the control performance. The results reveal that the proposed controller is capable of large order-level reductions (up to 30 dB) for stationary excitation, which allows a comfortable margin for equalization. The same holds for slow run-ups ( > 15s) thanks to the improved convergence rate. This margin, however, gets narrower with shorter run-ups (<= 10s). (c) 2010 Elsevier Ltd. All rights reserved.

A novel multiobjective optimization algorithm based on bacterial chemotaxis

In this article a novel algorithm based on the chemotaxis process of Echerichia coil is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO. (C) 2009 Elsevier Ltd. All rights reserved.

A Constructive Genetic Algorithm for permutation flowshop scheduling

The general flowshop scheduling problem is a production problem where a set of n jobs have to be processed with identical flow pattern on in machines. In permutation flowshops the sequence of jobs is the same on all machines. A significant research effort has been devoted for sequencing jobs in a flowshop minimizing the makespan. This paper describes the application of a Constructive Genetic Algorithm (CGA) to makespan minimization on flowshop scheduling. The CGA was proposed recently as an alternative to traditional GA approaches, particularly, for evaluating schemata directly. The population initially formed only by schemata, evolves controlled by recombination to a population of well-adapted structures (schemata instantiation). The CGA implemented is based on the NEH classic heuristic and a local search heuristic used to define the fitness functions. The parameters of the CGA are calibrated using a Design of Experiments (DOE) approach. The computational results are compared against some other successful algorithms from the literature on Taillard`s well-known standard benchmark. The computational experience shows that this innovative CGA approach provides competitive results for flowshop scheduling; problems. (C) 2007 Elsevier Ltd. All rights reserved.

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine`s capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine`s potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification

This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved

Consolidation of elastic-plastic saturated porous media by the boundary element method

This paper presents a domain boundary element formulation for inelastic saturated porous media with rate-independent behavior for the solid skeleton. The formulation is then applied to elastic-plastic behavior for the solid. Biot`s consolidation theory, extended to include irreversible phenomena is considered and the direct boundary element technique is used for the numerical solution after time discretization by the implicit Euler backward algorithm. The associated nonlinear algebraic problem is solved by the Newton-Raphson procedure whereby the loading/unloading conditions are fully taken into account and the consistent tangent operator defined. Only domain nodes (nodes defined inside the domain) are used to represent all domain values and the corresponding integrals are computed by using an accurate sub-elementation scheme. The developments are illustrated through the Drucker-Prager elastic-plastic model for the solid skeleton and various examples are analyzed with the proposed algorithms. (c) 2008 Elsevier B.V. All rights reserved.

Anaerobic sequencing batch biofilm reactor applied to automobile industry wastewater treatment: Volumetric loading rate and feed strategy effects

This paper presents a technological viability study of wastewater treatment in an automobile industry by an anaerobic sequencing batch biofilm reactor containing immobilized biomass (AnSBBR) with a draft tube. The reactor was operated in 8-h cycles, with agitation of 400 rpm, at 30 degrees C and treating 2.0 L wastewater per cycle. Initially the efficiency and stability of the reactor were studied when supplied with nutrients and alkalinity. Removal efficiency of 88% was obtained at volumetric loading rate (VLR) of 3.09 mg COD/L day. When VLR was increased to 6.19 mg COD/L day the system presented stable operation with reduction in efficiency of 71%. In a second stage the AnSBBR was operated treating wastewater in natura, i.e., without nutrients supplementation, only with alkalinity, thereby changing feed strategy. The first strategy consisted in feeding 2.0 L batch wise (10 min), the second in feeding 1.0 L of influent batch wise (10 min) and an additional 1.0 L fed-batch wise (4 h), both dewatering 2.0 L of the effluent in 10 min. The third one maintained 1.0 L of treated effluent in the reactor, without discharging, and 1.0 L of influent was fed fed-batch wise (4 h) with dewatering 1.0 L of the effluent in 10 min. For all implemented strategies (VLR of 1.40, 2.57 and 2.61 mg COD/L day) the system presented stability and removal efficiency of approximately 80%. These results show that the AnSBBR presents operational flexibility, as the influent can be fed according to industry availability. In industrial processes this is a considerable advantage, as the influent may be prone to variations. Moreover, for all the investigated conditions the kinetic parameters were obtained from fitting a first-order model to the profiles of organic matter, total volatile acids and methane concentrations. Analysis of the kinetic parameters showed that the best strategy is feeding 1.0 L of influent batchwise (10 min) and 1.0 L fed-batch wise (4 h) in 8-h cycle. (c) 2007 Elsevier B.V. All rights reserved.

Fatigue behaviour of friction stir welded AA2024-T3 alloy: longitudinal and transverse crack growth

The fatigue crack growth properties of friction stir welded joints of 2024-T3 aluminium alloy have been studied under constant load amplitude (increasing-Delta K), with special emphasis on the residual stress (inverse weight function) effects on longitudinal and transverse crack growth rate predictions (Glinka`s method). In general, welded joints were more resistant to longitudinally growing fatigue cracks than the parent material at threshold Delta K values, when beneficial thermal residual stresses decelerated crack growth rate, while the opposite behaviour was observed next to K-C instability, basically due to monotonic fracture modes intercepting fatigue crack growth in weld microstructures. As a result, fatigue crack growth rate (FCGR) predictions were conservative at lower propagation rates and non-conservative for faster cracks. Regarding transverse cracks, intense compressive residual stresses rendered welded plates more fatigue resistant than neat parent plate. However, once the crack tip entered the more brittle weld region substantial acceleration of FCGR occurred due to operative monotonic tensile modes of fracture, leading to non-conservative crack growth rate predictions next to K-C instability. At threshold Delta K values non-conservative predictions values resulted from residual stress relaxation. Improvements on predicted FCGR values were strongly dependent on how the progressive plastic relaxation of the residual stress field was considered.

Influence of the Solvent Evaporation Rate on the Crystalline Phases of Solution-Cast Poly(Vinylidene Fluoride) Films

The influence of the solvent-evaporation rate on the formation of of. and P crystalline phases in solution-cast poly(vinylidene fluoride) (PVDF) films was systematically investigated. Films were crystallized from PVDF/N,N-dimethylformamide solutions with concentrations of 2.5, 5.0, 10, and 20 wt % at different temperatures. During crystallization, the solvent evaporation rate was monitored in situ by means of a semianalytic balance. With this system, it was possible to determine the evaporation rate for different concentrations and temperatures of the solution under specific ambient conditions (pressure, temperature, and humidity). Fourier-Transform InfraRed spectroscopy with Attenuated Total Reflectance revealed the P-phase content in the PVDF films and its dependence on previous evaporation rates. Based on the relation between the evaporation rate and the PVDF phase composition, a consistent explanation for the different amounts of P phase observed at the upper and lower sample surfaces is achieved. Furthermore, the role of the sample thickness has also been studied. The experimental results show that not only the temperature but also the evaporation rate have to be controlled to obtain the desired crystalline phases in solution-cast PVDF films. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 116: 785-791, 2010

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.