Design of laminated piezocomposite shell transducers with arbitrary fiber orientation using topology optimization approach

Sensor and actuator based on laminated piezocomposite shells have shown increasing demand in the field of smart structures. The distribution of piezoelectric material within material layers affects the performance of these structures; therefore, its amount, shape, size, placement, and polarization should be simultaneously considered in an optimization problem. In addition, previous works suggest the concept of laminated piezocomposite structure that includes fiber-reinforced composite layer can increase the performance of these piezoelectric transducers; however, the design optimization of these devices has not been fully explored yet. Thus, this work aims the development of a methodology using topology optimization techniques for static design of laminated piezocomposite shell structures by considering the optimization of piezoelectric material and polarization distributions together with the optimization of the fiber angle of the composite orthotropic layers, which is free to assume different values along the same composite layer. The finite element model is based on the laminated piezoelectric shell theory, using the degenerate three-dimensional solid approach and first-order shell theory kinematics that accounts for the transverse shear deformation and rotary inertia effects. The topology optimization formulation is implemented by combining the piezoelectric material with penalization and polarization model and the discrete material optimization, where the design variables describe the amount of piezoelectric material and polarization sign at each finite element, with the fiber angles, respectively. Three different objective functions are formulated for the design of actuators, sensors, and energy harvesters. Results of laminated piezocomposite shell transducers are presented to illustrate the method. Copyright (C) 2012 John Wiley & Sons, Ltd.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

NUTRITIONAL BALANCE, ESSENTIAL OIL AND WOOD PRODUCTION FROM Corymbia citriodora Hill & Johnson WITH SEWAGE SLUDGE AND MINERAL FERTILIZER APPLICATIONS

The Corymbia citriodora is one of the most important forest species in Brazil and the reason is the diversity of its use, because it produces good quality wood and the leaves may be used for essential oil production. Although, there are not many studies about species and the handling effect in the nutritional balance. This study aimed to evaluate the biomass production and nutrient balance in the conventional production of essential oil and wood of Corymbia citriodora with sewage sludge application. The experiment design established was the randomized blocks, with four replicates and two treatments: 1 - fertilization with 10 tons ha(-1) (dry mass) of sewage sludge, supplemented with K and B, and 2 - mineral fertilization. It was evaluated the aerial biomass production, the nutrient export of the leaves, the essential oil and wood production at four years old. The trees that received application of sewage sludge produced 20 % more leaves biomass than the trees with mineral fertilization, resulting in larger oil production. Besides, the trees with sewage sludge application produced 14.2 tons ha(-1) yr(-1) of woody biomass that was 27 % higher than the treatment with mineral fertilization. For both treatments the N balance was negative, but treatment with sewage sludge application (-45 kg ha(-1)) was four times lower than the observed on mineral fertilization treatment (-185 kg ha(-1)). It may be concluded in this paper that the application of sewage sludge benefits the production of leaves biomass, essential oil and wood, besides result better nutritional balance of the Corymbia citriodora production system.

Structure- and ligand-based drug design approaches for neglected tropical diseases

Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. Structure( SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.

Probabilistic crack growth analyses using a boundary element model: Applications in linear elastic fracture and fatigue problems

This paper addresses the numerical solution of random crack propagation problems using the coupling boundary element method (BEM) and reliability algorithms. Crack propagation phenomenon is efficiently modelled using BEM, due to its mesh reduction features. The BEM model is based on the dual BEM formulation, in which singular and hyper-singular integral equations are adopted to construct the system of algebraic equations. Two reliability algorithms are coupled with BEM model. The first is the well known response surface method, in which local, adaptive polynomial approximations of the mechanical response are constructed in search of the design point. Different experiment designs and adaptive schemes are considered. The alternative approach direct coupling, in which the limit state function remains implicit and its gradients are calculated directly from the numerical mechanical response, is also considered. The performance of both coupling methods is compared in application to some crack propagation problems. The investigation shows that direct coupling scheme converged for all problems studied, irrespective of the problem nonlinearity. The computational cost of direct coupling has shown to be a fraction of the cost of response surface solutions, regardless of experiment design or adaptive scheme considered. (C) 2012 Elsevier Ltd. All rights reserved.

Do changes in carbon allocation account for the growth response to potassium and sodium applications in tropical Eucalyptus plantations?

Understanding the underlying mechanisms that account for the impact of potassium (K) fertilization and its replacement by sodium (Na) on tree growth is key to improving the management of forest plantations that are expanding over weathered tropical soils with low amounts of exchangeable bases. A complete randomized block design was planted with Eucalyptus grandis (W. Hill ex Maiden) to quantify growth, carbon uptake and carbon partitioning using a carbon budget approach. A combination of approaches including the establishment of allometric relationships over the whole rotation and measurements of soil CO2 efflux and aboveground litterfall at the end of the rotation were used to estimate aboveground net production (ANPP), total belowground carbon flux and gross primary production (GPP). The stable carbon isotope (delta C-13) of stem wood alpha-cellulose produced every year was used as a proxy for stomatal limitation of photosynthesis. Potassium fertilization increased GPP and decreased the fraction of carbon allocated belowground. Aboveground net production was strongly enhanced, and because leaf lifespan increased, leaf biomass was enhanced without any change in leaf production, and wood production (P-W) was dramatically increased. Sodium application decreased the fraction of carbon allocated belowground in a similar way, and enhanced GPP, ANPP and P-W, but to a lesser extent compared with K fertilization. Neither K nor Na affected delta C-13 of stem wood alpha-cellulose, suggesting that water-use efficiency was the same among the treatments and that the inferred increase in leaf photosynthesis was not only related to a higher stomatal conductance. We concluded that the response to K fertilization and Na addition on P-W resulted from drastic changes in carbon allocation.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).