Evolutionary Relationships of the Triatoma matogrossensis Subcomplex, the Endemic Triatoma in Central-Western Brazil, Based on Mitochondrial DNA Sequences

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill

This paper proposes a Fuzzy Goal Programming model (FGP) for a real aggregate production-planning problem. To do so, an application was made in a Brazilian Sugar and Ethanol Milling Company. The FGP Model depicts the comprehensive production process of sugar, ethanol, molasses and derivatives, and considers the uncertainties involved in ethanol and sugar production. Decision-makings, related to the agricultural and logistics phases, were considered on a weekly-basis planning horizon to include the whole harvesting season and the periods between harvests. The research has provided interesting results about decisions in the agricultural stages of cutting, loading and transportation to sugarcane suppliers and, especially, in milling decisions, whose choice of production process includes storage and logistics distribution. (C)2014 Elsevier B.V. All rights reserved.

A smooth evolutionary structural optimization procedure applied to plane stress problem

Topological optimization problems based on stress criteria are solved using two techniques in this paper. The first technique is the conventional Evolutionary Structural Optimization (ESO), which is known as hard kill, because the material is discretely removed; that is, the elements under low stress that are being inefficiently utilized have their constitutive matrix has suddenly reduced. The second technique, proposed in a previous paper, is a variant of the ESO procedure and is called Smooth ESO (SESO), which is based on the philosophy that if an element is not really necessary for the structure, its contribution to the structural stiffness will gradually diminish until it no longer influences the structure; its removal is thus performed smoothly. This procedure is known as "soft-kill"; that is, not all of the elements removed from the structure using the ESO criterion are discarded. Thus, the elements returned to the structure must provide a good conditioning system that will be resolved in the next iteration, and they are considered important to the optimization process. To evaluate elasticity problems numerically, finite element analysis is applied, but instead of using conventional quadrilateral finite elements, a plane-stress triangular finite element was implemented with high-order modes for solving complex geometric problems. A number of typical examples demonstrate that the proposed approach is effective for solving problems of bi-dimensional elasticity. (C) 2014 Elsevier Ltd. All rights reserved.

A mixed-integer quadratically-constrained programming model for the distribution system expansion planning

This paper presents a mixed-integer quadratically-constrained programming (MIQCP) model to solve the distribution system expansion planning (DSEP) problem. The DSEP model considers the construction/reinforcement of substations, the construction/reconductoring of circuits, the allocation of fixed capacitors banks and the radial topology modification. As the DSEP problem is a very complex mixed-integer non-linear programming problem, it is convenient to reformulate it like a MIQCP problem; it is demonstrated that the proposed formulation represents the steady-state operation of a radial distribution system. The proposed MIQCP model is a convex formulation, which allows to find the optimal solution using optimization solvers. Test systems of 23 and 54 nodes and one real distribution system of 136 nodes were used to show the efficiency of the proposed model in comparison with other DSEP models available in the specialized literature. (C) 2014 Elsevier Ltd. All rights reserved.

The influence of self-weight of elastic 2D structures in topology optimization via numerical technique Smooth Evolutionary Structural Optimization (SESO)

This paper deals with topology optimization in plane elastic-linear problems considering the influence of the self weight in efforts in structural elements. For this purpose it is used a numerical technique called SESO (Smooth ESO), which is based on the procedure for progressive decrease of the inefficient stiffness element contribution at lower stresses until he has no more influence. The SESO is applied with the finite element method and is utilized a triangular finite element and high order. This paper extends the technique SESO for application its self weight where the program, in computing the volume and specific weight, automatically generates a concentrated equivalent force to each node of the element. The evaluation is finalized with the definition of a model of strut-and-tie resulting in regions of stress concentration. Examples are presented with optimum topology structures obtaining optimal settings. (C) 2012 CIMNE (Universitat Politecnica de Catalunya). Published by Elsevier Espana, S.L.U. All rights reserved.

Comparative Chromosome Mapping of U2 snRNA and 5S rRNA Genes in Gymnotus Species (Gymnotiformes, Gymnotidae): Evolutionary Dynamics and Sex Chromosome Linkage in G. pantanal

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Building the sugarcane genome for biotechnology and identifying evolutionary trends

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evolutionary History of the PER3 Variable Number of Tandem Repeats (VNTR): Idiosyncratic Aspect of Primate Molecular Circadian Clock

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Undernutrition fetal programming: effects on kidney morphology, renal steroid and angiotensin receptors expression and urinary sodium excretion

Maternal undernutrition affects the foetal development, promoting renal alterations and adult hypertension. The present study investigates, in adult male rats, the effect of food restriction in utero on arterial blood pressure changes (AP), and its possible association with the number of nephrons, renal function and angiotensin II (AT1R/AT2R), glucocorticoid (GR) and mineralocorticoid (MCR) receptors expression. The daily food supply to pregnant rats was measured and one group (n=5) received normal quantity of food (NF) while the other group received 50% of that (FR50) (n=5). The AP was measured weekly. At 16 weeks of life, fractionator’s method was used to estimate glomeruli number in histological slices. The renal function was estimate by creatinine and lithium clearances. Blood and urine samples were collected to biochemical determination of creatinine, sodium, potassium and lithium. At 90th and 23rd days of life, kidneys were also processed to AT1R, AT2R, GR and MCR immunolocalization and for western blotting analysis. FR50 offspring shows a significant reduction in BW (FR50: 5.67 ± 0.16 vs. 6.84 ± 0.13g in NF, P<0.001) and increased AP from 6th to 12nd week (6thwk FR50: 149.1 ± 3.4 vs. 125.1 ± 3.2mmHg in NF, P<0.001and, 12ndwk FR50: 164.4 ± 4.9 vs. 144.0 ± 3.3 mmHg in NF, P=0.02). Expression of AT1R and AT2R were significantly decreased in FR50 (AT1, 59080 ± 2709 vs. 77000 ± 3591 in NF, P=0.05; AT2, 27500 ± 95.50 vs. 67870 ± 1509 in NF, P=0.001) while the expression of GR increased in FR50 (36090 ± 781.5 vs. 4446 ± 364.5 in NF, P=0.0007). The expression of MCR did not change significantly. We also verified a pronounced decrease in fractional urinary sodium excretion in FR50 offspring (0.03 ± 0.02 vs. 0.06 ± 0.04 in NF, p=0.03). This occurred despite unchanged creatinine clearance. The study led us to suggest that fetal undernutrition, with increased fetal exposure... (Complete abstract click electronic access below)

An evolutionary approach to improve connectivity prediction in mobile wireless sensor networks

Connectivity is the basic factor for the proper operation of any wireless network. In a mobile wireless sensor network it is a challenge for applications and protocols to deal with connectivity problems, as links might get up and down frequently. In these scenarios, having knowledge of the node remaining connectivity time could both improve the performance of the protocols (e.g. handoff mechanisms) and save possible scarce nodes resources (CPU, bandwidth, and energy) by preventing unfruitful transmissions. The current paper provides a solution called Genetic Machine Learning Algorithm (GMLA) to forecast the remainder connectivity time in mobile environments. It consists in combining Classifier Systems with a Markov chain model of the RF link quality. The main advantage of using an evolutionary approach is that the Markov model parameters can be discovered on-the-fly, making it possible to cope with unknown environments and mobility patterns. Simulation results show that the proposal is a very suitable solution, as it overcomes the performance obtained by similar approaches.

Integrated cutting machine programming and lot sizing in furniture industry

In this paper a mathematical model that combines lot-sizing and cutting-stock problems applied to the furniture industry is presented. The model considers the usual decisions of the lot sizing problems, as well as operational decisions related to the cutting machine programming. Two sets of a priori generated cutting patterns are used, industry cutting patterns and a class of n-group cutting patterns. A strategy to improve the utilization of the cutting machine is also tested. An optimization package was used to solve the model and the computational results, using real data from a furniture factory, show that a small subset of n-group cutting patterns provides good results and that the cutting machine utilization can be improved by the proposed strategy.

Evolutionary trends in Iridaceae: new cytogenetic findings from the New World

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fetal kidney programming by severe food restriction: effects on structure, hormonal receptor expression and urinary sodium excretion in rats

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Deriving vegetation indices for phenology analysis using genetic programming

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)