New occurrence of a macro B-chromosome in Astyanax scabripinnis paranae (Pisces, Characiformes, Characidae)

Cytogenetic studies performed on 17 specimens (11 females and six males) of Astyanax scabripinnis paranae from the Cascatinha stream showed that this population has 2n = 50 chromosomes (8M + 22SM + 10ST + 10A), two chromosome pairs with NORs and conspicuous C-band positive blocks in the terminal position of the long arm of five chromosome pairs. Three females presented 2n = 51 chromosomes and the extra chromosome was a large metacentric similar in size and morphology to the first chromosome pair in the karyotype. This accessory chromosome was entirely heterochromatic in C-banded metaphases, which permitted its classification as a supernumerary chromosome. Some aspects related to the morphology of such macro B-chromosomes are discussed.

Towards an intelligent graphical interface for linear programming modelling

The increase of computing power of the microcomputers has stimulated the building of direct manipulation interfaces that allow graphical representation of Linear Programming (LP) models. This work discusses the components of such a graphical interface as the basis for a system to assist users in the process of formulating LP problems. In essence, this work proposes a methodology which considers the modelling task as divided into three stages which are specification of the Data Model, the Conceptual Model and the LP Model. The necessity for using Artificial Intelligence techniques in the problem conceptualisation and to help the model formulation task is illustrated.

Optimality conditions for pareto nonsmooth nonconvex programming in banach spaces

In this paper, we consider a vector optimization problem where all functions involved are defined on Banach spaces. We obtain necessary and sufficient criteria for optimality in the form of Karush-Kuhn-Tucker conditions. We also introduce a nonsmooth dual problem and provide duality theorems.

Design of microirrigation systems in sloping lands using linear programming

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

VAr planning using genetic algorithm and linear programming

A combined methodology consisting of successive linear programming (SLP) and a simple genetic algorithm (SGA) solves the reactive planning problem. The problem is divided into operating and planning subproblems; the operating subproblem, which is a nonlinear, ill-conditioned and nonconvex problem, consists of determining the voltage control and the adjustment of reactive sources. The planning subproblem consists of obtaining the optimal reactive source expansion considering operational, economical and physical characteristics of the system. SLP solves the optimal reactive dispatch problem related to real variables, while SGA is used to determine the necessary adjustments of both the binary and discrete variables existing in the modelling problem. Once the set of candidate busbars has been defined, the program implemented gives the location and size of the reactive sources needed, if any, to maintain the operating and security constraints.

On the solution of mathematical programming problems with equilibrium constraints

Mathematical programming problems with equilibrium constraints (MPEC) are nonlinear programming problems where the constraints have a form that is analogous to first-order optimality conditions of constrained optimization. We prove that, under reasonable sufficient conditions, stationary points of the sum of squares of the constraints are feasible points of the MPEC. In usual formulations of MPEC all the feasible points are nonregular in the sense that they do not satisfy the Mangasarian-Fromovitz constraint qualification of nonlinear programming. Therefore, all the feasible points satisfy the classical Fritz-John necessary optimality conditions. In principle, this can cause serious difficulties for nonlinear programming algorithms applied to MPEC. However, we show that most feasible points do not satisfy a recently introduced stronger optimality condition for nonlinear programming. This is the reason why, in general, nonlinear programming algorithms are successful when applied to MPEC.

Extra̧ão de Macro e Micronutrientes Pela Parte Aérea de Erva-Doce EM Fuņão de Calagem e Aduba̧ão com Esterco de Cama de Frango

A greenhouse experiment was conducted in the Soil Science Department of the Botucatu College of Agricultural Sciences (UNESP), Brazil, using a Dark Red Latosol in 25 L pots. The soil was limed to 50 and 70% of base saturation; and doses 0, 10, 20, 30 and 40 t ha-1 of chicken manure were applied, in December of 1999. The experimental design was completely randomized blocks with a factorial arrangement 5x2, 10 treatments and three replications. This work was carried to evaluate leaf number, height plants, fresh and dry weight by aerial part of sweet fennel, and macronutrients and micronutrients removal. The organic fertilization affected the accumulation of N, P, K, S, B and Mn; liming affected the nutrient uptake, except for the Ca, Mg, S and Fe; the interaction of factors affected K, Mg and Mn.

Dynamic programming approach for road centerline extraction from digital images

This paper presents a dynamic programming approach for semi-automated road extraction from medium-and high-resolution images. This method is a modified version of a pre-existing dynamic programming method for road extraction from low-resolution images. The basic assumption of this pre-existing method is that roads manifest as lines in low-resolution images (pixel footprint> 2 m) and as such can be modeled and extracted as linear features. On the other hand, roads manifest as ribbon features in medium- and high-resolution images (pixel footprint ≤ 2 m) and, as a result, the focus of road extraction becomes the road centerlines. The original method can not accurately extract road centerlines from medium- and high- resolution images. In view of this, we propose a modification of the merit function of the original approach, which is carried out by a constraint function embedding road edge properties. Experimental results demonstrated the modified algorithm's potential in extracting road centerlines from medium- and high-resolution images.

Gonad development in females of fiddler crab Uca rapax (Crustacea, Brachyura, Ocypodidae) using macro and microscopic techniques

The morphology of the ovaries in Uca rapax (Smith, 1870) was described based on macroscopic and microscopic analysis. Females were collected in Itamambuca mangrove, Ubatuba, state of São Paulo, Brazil. In the laboratory, 18 females had their ovaries removed and prepared for histology. Each gonad developmental stage was previously determined based on external and macroscopic morphology and afterwards each stage was microscopically described. The ovaries of U. rapax showed a pronounced macroscopic differentiation in size and coloration with the maturation of the gonad, with six ovarian developmental stages: immature, rudimentary, developing, developed, advanced and spent. During the vitellogenesis, the amount of oocytes in secondary stage increases in the ovary, resulting in a change in coloration of the gonad. Oogonias, primary oocytes, secondary oocytes and follicular cells were histologically described and measured. In female's ovaries of U. rapax the modifications observed in the oocytes during the process of gonad maturation are similar to descriptions of gonads of other females of brachyuran crustaceans. The similarities are specially found in the morphological changes in the reproductive cells, and also in the presence and arrange of follicle cells during the process of ovary maturation. When external morphological characteristics of the gonads were compared to histological descriptions, it was possible to observe modifications that characterize the process in different developmental stages throughout the ovarian cycle and, consequently, the macroscopic classification of gonad stages agree with the modifications of the reproductive cells.

A multi-objective programming approach for the optimal operation of distributed generation considering uncertainty

Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.

Challenges of programming apprentice

The present article describes the challenges programming apprentices face and identifies the elements and processes that set them apart from experienced programmers. And also explains why a conventional programming languages teaching approach fails to map the programming mental model. The purpose of this discussion is to benefit from ideas and cognitive philosophies to be embedded in programming learning tools. Cognitive components are modeled as elements to be handled by the apprentices in tutoring systems while performing a programming task. In this process a mental level solution (the mental model of the program) and an implementation level solution (the program) are created. The mapping between these representations is a path followed by the student explicitly in this approach. © 2011 IEEE.

NCAP embedded using structured programming

This paper presents a network node embedded based on IEEE 1451 standard developed using structured programming to access the transducers in the WTIM. The NCAP was developed using Nios II processor and uClinux, a embedded operating system developed to features restricted hardware. Both hardware and software have dynamics features and they can be configured based in the application features. Based in this features, the NCAP was developed using the minimum components of hardware and software to that being implemented in remote environment like central point of data request. Many NCAP works are implemented with an object oriented structure. This is different from the surrounding implementations. In this project the NCAP was developed using structured programming. The tests of the NCAP were made using a ZigBee interface between NCAP and WTIM and the system demonstrated in areas of difficult access for long period of time due to need for low power consumption. © 2012 IEEE.

Optimal reactive power dispatch using stochastic chance-constrained programming

Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage stochastic optimization model is first formulated under the presumption that the load demand can be modeled as specified random parameters. A second stochastic chance-constrained model is presented considering uncertainty on the demand and the equivalent availability of shunt reactive power compensators. Simulations on six-bus and 30-bus test systems are used to illustrate the validity and essential features of the proposed models. This simulations shows that the proposed models can prevent to the power system operator about of the deficit of reactive power in the power system and suggest that shunt reactive sourses must be dispatched against the unavailability of any reactive source. © 2012 IEEE.

Condutividade elétrica da solução nutritiva e acúmulo de macro e micronutrientes no cultivo de crisântemo

The study of growth and uptake of nutrients is important to determine the times of increased demand in order to schedule the fertigation. The present research was developed with the objective of evaluating the effects of different levels of electrical conductivity on growth and accumulation of nutrients in chrysanthemum plants under greenhouse conditions. The electrical conductivity levels on the applied solution were 1.42, 1.65, 1.89, 2.13 and 2.36 dS m-1 (bud vegetative stage); 1.71, 1.97, 2.28, 2.57 and 2.85 dS m-1 (bud stage). The dry mass of the aerial portion of the plant and the contents of macronutrients and micronutrients were determined every 14 days. The nutrient accumulation in chrysanthemum plant showed similar trend as compared to dry matter accumulation. The nutrients presented the following order of absorption: K>N>Ca>Mg>P>S (1425, 892, 184, 150, 110 and 59 mg plant-1) and Fe>Zn>B>Mn>Cu (2254, 2219, 1725, 1287, 210 μg plant-1). The content of most nutrients increased with increase in electrical conductivity of the solution, without salt effect up to EC of 2.85 dS m-1.

A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems

This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.