911 resultados para MINIMIZING EARLINESS


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The quality of environmental studies depends on the utilization of adequate sampling protocol and analytical method for obtaining reliable results and minimizing analytical uncertainties. In order to demonstrate the applicability of INAA for determining chemical element composition of invertebrates, this work evaluated sample representativeness in terms of subsampling and sample size. Br, Co, Fe, K, Na, Sc and Zn could be determined in very small samples despite increasing of analytical uncertainties. Special attention should be directed to invertebrate species with small structures because of the high chemical variation observed among different sample sizes tested.

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The aim of this study was to assess the effect of leucine supplementation on elements of the ubiquitin proteasome system (UPS) in rat skeletal muscle during immobilization. This effect was evaluated by submitting the animals to a leucine supplementation protocol during hindlimb immobilization, after which different parameters were determined, including: muscle mass; cross-sectional area (CSA); gene expression of E3 ligases/deubiquitinating enzymes; content of ubiquitinated proteins; and rate of protein synthesis. Our results show that leucine supplementation attenuates soleus muscle mass loss driven by immobilization. In addition, the marked decrease in the CSA in soleus muscle type I fibers, but not type II fibers, induced by immobilization was minimized by leucine feeding. Interestingly, leucine supplementation severely minimized the early transient increase in E3 ligase [muscle ring finger 1 (MuRF1) and muscle atrophy F-box (MAFbx)/atrogin-1] gene expression observed during immobilization. The reduced peak of E3 ligase gene expression was paralleled by a decreased content of ubiquitinated proteins during leucine feeding. The protein synthesis rate decreased by immobilization and was not affected by leucine supplementation. Our results strongly suggest that leucine supplementation attenuates muscle wasting induced by immobilization via minimizing gene expression of E3 ligases, which consequently could downregulate UPS-driven protein degradation. It is notable that leucine supplementation does not restore decreased protein synthesis driven by immobilization. Muscle Nerve 41: 800-808, 2010

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It has been previously reported that carbohydrate (CHO) mouth rinse can improve exercise performance. The proposed mechanism involves increased activation of brain regions believed to be responsible for reward/motivation and motor control. Since strength-related performance is affected by central drive to the muscles, it seems reasonable to hypothesize that the positive CNS response to oral CHO sensing may counteract the inhibitory input from the muscle afferent pathways minimizing the drop in the central drive. The purpose of the current study was to test if CHO mouth rinse affects maximum strength and strength endurance performance. Twelve recreationally strength-trained healthy males (age 24.08 +/- 2.99 years; height 178.09 +/- 6.70 cm; weight 78.67 +/- 8.17 kg) took part in the study. All of the tests were performed in the morning, after an 8 h overnight fasting. Subjects were submitted to a maximum strength test (1-RM) and a strength endurance test (six sets until failure at 70% of 1-RM), in separate days under three different experimental conditions (CHO mouth rinse, placebo-PLA mouth rinse and control-CON) in a randomized crossover design. The CHO mouth rinse (25 ml) occurred before every attempt in the 1-RM test, and before every set in the endurance strength test. Blood glucose and lactate were measured immediately before and 5 min post-tests. There were no significant differences in 1-RM between experimental conditions (CHO 101 +/- 7.2 kg; PLA 101 +/- 7.4 kg; CON 101 +/- 7.2 kg; p = 0.98). Furthermore, there were no significance between trial differences in the number of repetitions performed in each set (p = 0.99) or the total exercise volume (number of repetitions x load lifted [kg]) (p = 0.98). A main effect for time (p < 0.0001) in blood lactate concentration was observed in both tests (1-RM and strength endurance). Blood glucose concentration did not differ between conditions. In conclusion, CHO mouth rinse does not affect maximum strength or strength endurance performance.

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This paper presents a small-area CMOS current-steering segmented digital-to-analog converter (DAC) design intended for RF transmitters in 2.45 GHz Bluetooth applications. The current-source design strategy is based on an iterative scheme whose variables are adjusted in a simple way, minimizing the area and the power consumption, and meeting the design specifications. A theoretical analysis of static-dynamic requirements and a new layout strategy to attain a small-area current-steering DAC are included. The DAC was designed and implemented in 0.35 mu m CMOS technology, requiring an active area of just 200 mu m x 200 mu m. Experimental results, with a full-scale output current of 700 mu A and a 3.3 V power supply, showed a spurious-free dynamic range of 58 dB for a 1 MHz output sine wave and sampling frequency of 50 MHz, with differential and integral nonlinearity of 0.3 and 0.37 LSB, respectively.

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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.

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This paper deals with the traditional permutation flow shop scheduling problem with the objective of minimizing mean flowtime, therefore reducing in-process inventory. A new heuristic method is proposed for the scheduling problem solution. The proposed heuristic is compared with the best one considered in the literature. Experimental results show that the new heuristic provides better solutions regarding both the solution quality and computational effort.

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We consider a class of two-dimensional problems in classical linear elasticity for which material overlapping occurs in the absence of singularities. Of course, material overlapping is not physically realistic, and one possible way to prevent it uses a constrained minimization theory. In this theory, a minimization problem consists of minimizing the total potential energy of a linear elastic body subject to the constraint that the deformation field must be locally invertible. Here, we use an interior and an exterior penalty formulation of the minimization problem together with both a standard finite element method and classical nonlinear programming techniques to compute the minimizers. We compare both formulations by solving a plane problem numerically in the context of the constrained minimization theory. The problem has a closed-form solution, which is used to validate the numerical results. This solution is regular everywhere, including the boundary. In particular, we show numerical results which indicate that, for a fixed finite element mesh, the sequences of numerical solutions obtained with both the interior and the exterior penalty formulations converge to the same limit function as the penalization is enforced. This limit function yields an approximate deformation field to the plane problem that is locally invertible at all points in the domain. As the mesh is refined, this field converges to the exact solution of the plane problem.

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Compliant mechanisms can achieve a specified motion as a mechanism without relying on the use of joints and pins. They have broad application in precision mechanical devices and Micro-Electro Mechanical Systems (MEMS) but may lose accuracy and produce undesirable displacements when subjected to temperature changes. These undesirable effects can be reduced by using sensors in combination with control techniques and/or by applying special design techniques to reduce such undesirable effects at the design stage, a process generally termed ""design for precision"". This paper describes a design for precision method based on a topology optimization method (TOM) for compliant mechanisms that includes thermal compensation features. The optimization problem emphasizes actuator accuracy and it is formulated to yield optimal compliant mechanism configurations that maximize the desired output displacement when a force is applied, while minimizing undesirable thermal effects. To demonstrate the effectiveness of the method, two-dimensional compliant mechanisms are designed considering thermal compensation, and their performance is compared with compliant mechanisms designs that do not consider thermal compensation. (C) 2010 Elsevier B.V. All rights reserved.

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Sensors and actuators based on piezoelectric plates have shown increasing demand in the field of smart structures, including the development of actuators for cooling and fluid-pumping applications and transducers for novel energy-harvesting devices. This project involves the development of a topology optimization formulation for dynamic design of piezoelectric laminated plates aiming at piezoelectric sensors, actuators and energy-harvesting applications. It distributes piezoelectric material over a metallic plate in order to achieve a desired dynamic behavior with specified resonance frequencies, modes, and enhanced electromechanical coupling factor (EMCC). The finite element employs a piezoelectric plate based on the MITC formulation, which is reliable, efficient and avoids the shear locking problem. The topology optimization formulation is based on the PEMAP-P model combined with the RAMP model, where the design variables are the pseudo-densities that describe the amount of piezoelectric material at each finite element and its polarization sign. The design problem formulated aims at designing simultaneously an eigenshape, i.e., maximizing and minimizing vibration amplitudes at certain points of the structure in a given eigenmode, while tuning the eigenvalue to a desired value and also maximizing its EMCC, so that the energy conversion is maximized for that mode. The optimization problem is solved by using sequential linear programming. Through this formulation, a design with enhancing energy conversion in the low-frequency spectrum is obtained, by minimizing a set of first eigenvalues, enhancing their corresponding eigenshapes while maximizing their EMCCs, which can be considered an approach to the design of energy-harvesting devices. The implementation of the topology optimization algorithm and some results are presented to illustrate the method.

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This work deals with the problem of minimizing the waste of space that occurs on a rotational placement of a set of irregular two dimensional polygons inside a two dimensional container. This problem is approached with an heuristic based on simulated annealing. Traditional 14 external penalization"" techniques are avoided through the application of the no-fit polygon, that determinates the collision free area for each polygon before its placement. The simulated annealing controls: the rotation applied, the placement and the sequence of placement of the polygons. For each non placed polygon, a limited depth binary search is performed to find a scale factor that when applied to the polygon, would allow it to be fitted in the container. It is proposed a crystallization heuristic, in order to increase the number of accepted solutions. The bottom left and larger first deterministic heuristics were also studied. The proposed process is suited for non convex polygons and containers, the containers can have holes inside. (C) 2009 Elsevier Ltd. All rights reserved.

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This work deals with the problem of minimizing the waste of space that occurs on a rotational placement of a set of irregular bi-dimensional items inside a bi-dimensional container. This problem is approached with a heuristic based on Simulated Annealing (SA) with adaptive neighborhood. The objective function is evaluated in a constructive approach, where the items are placed sequentially. The placement is governed by three different types of parameters: sequence of placement, the rotation angle and the translation. The rotation applied and the translation of the polygon are cyclic continuous parameters, and the sequence of placement defines a combinatorial problem. This way, it is necessary to control cyclic continuous and discrete parameters. The approaches described in the literature deal with only type of parameter (sequence of placement or translation). In the proposed SA algorithm, the sensibility of each continuous parameter is evaluated at each iteration increasing the number of accepted solutions. The sensibility of each parameter is associated to its probability distribution in the definition of the next candidate.

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There is an increasing need to treat effluents contaminated with phenol with advanced oxidation processes (AOPs) to minimize their impact on the environment as well as on bacteriological populations of other wastewater treatment systems. One of the most promising AOPs is the Fenton process that relies on the Fenton reaction. Nevertheless, there are no systematic studies on Fenton reactor networks. The objective of this paper is to develop a strategy for the optimal synthesis of Fenton reactor networks. The strategy is based on a superstructure optimization approach that is represented as a mixed integer non-linear programming (MINLP) model. Network superstructures with multiple Fenton reactors are optimized with the objective of minimizing the sum of capital, operation and depreciation costs of the effluent treatment system. The optimal solutions obtained provide the reactor volumes and network configuration, as well as the quantities of the reactants used in the Fenton process. Examples based on a case study show that multi-reactor networks yield decrease of up to 45% in overall costs for the treatment plant. (C) 2010 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

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The procedure for online process control by attributes consists of inspecting a single item at every m produced items. It is decided on the basis of the inspection result whether the process is in-control (the conforming fraction is stable) or out-of-control (the conforming fraction is decreased, for example). Most articles about online process control have cited the stoppage of the production process for an adjustment when the inspected item is non-conforming (then the production is restarted in-control, here denominated as corrective adjustment). Moreover, the articles related to this subject do not present semi-economical designs (which may yield high quantities of non-conforming items), as they do not include a policy of preventive adjustments (in such case no item is inspected), which can be more economical, mainly if the inspected item can be misclassified. In this article, the possibility of preventive or corrective adjustments in the process is decided at every m produced item. If a preventive adjustment is decided upon, then no item is inspected. On the contrary, the m-th item is inspected; if it conforms, the production goes on, otherwise, an adjustment takes place and the process restarts in-control. This approach is economically feasible for some practical situations and the parameters of the proposed procedure are determined minimizing an average cost function subject to some statistical restrictions (for example, to assure a minimal levelfixed in advanceof conforming items in the production process). Numerical examples illustrate the proposal.

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We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

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Since the computer viruses pose a serious problem to individual and corporative computer systems, a lot of effort has been dedicated to study how to avoid their deleterious actions, trying to create anti-virus programs acting as vaccines in personal computers or in strategic network nodes. Another way to combat viruses propagation is to establish preventive policies based on the whole operation of a system that can be modeled with population models, similar to those that are used in epidemiological studies. Here, a modified version of the SIR (Susceptible-Infected-Removed) model is presented and how its parameters are related to network characteristics is explained. Then, disease-free and endemic equilibrium points are calculated, stability and bifurcation conditions are derived and some numerical simulations are shown. The relations among the model parameters in the several bifurcation conditions allow a network design minimizing viruses risks. (C) 2009 Elsevier Inc. All rights reserved.