Determination of neutral polymorphisms (frameworks) of the human beta globin gene in beta thalassaemias by PCR/DGGE

Purpose: Considering the importance of type beta thalassaemias as hereditary syndromes of high significance in different populations of Mediterranean origin and, by extension, in the Brazilian population, the objective of the present study was to determine by PCR/DGGE the gene structures responsible for neutral polymorphisms (frameworks) observed in the human beta globin gene associated with the mutations responsible for type beta thalassaemias in a sample of the Brazilian population and, more specifically, of the population of the State of São Paulo. Patients and methods: Thirty individuals with beta thalassaemic mutations were analyzed: 22 mutations were in codon 39 (C->T), 5 in IVS1-110 (G->A), 2 in IVS1-6 (T->C) and 1 in IVS1-1 (G->A). DNA was extracted and selective amplification was performed by PCR extending from position IVS1 nt 46 to IVS2 nt 126 (474 pb). The product was then analyzed by polyacrylamide gel electrophoresis on a denaturing 10-60% urea/formamide gradient. Results: The results demonstrated that, as expected, the mutations responsible for type beta thalassaemia observed in this population are of Mediterranean origin, with 73% distribution represented by codon 39,17% by IVS1-110, 7% by IVS1-6 and 3% by IVS1-1. In turn, framework distribution seems to indicate a higher frequency of Fr 1-1 in codon 39 and IVS1-110, of Fr 1-3 in IVS1-6 and of Fr 1-2 in IVS1-1. Conclusions: These results permit us to conclude that gene amplification by PCR followed by DGGE is an appropriate method for the separation of DNA molecules that differ even by a single base change and therefore can be utilized to detect the alterations observed in the human beta globin gene. This methodology shows that, using only a pair of primers, it is possible to define the frameworks that are observed in the beta globin gene.

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.

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.

Influence of thermal and mechanical cycling on the flexural strength of ceramics with titanium or gold alloy frameworks

Objectives: The aim of this study was to evaluate the effect of thermal and mechanical cycling alone or in combination, on the flexural strength of ceramic and metallic frameworks cast in gold alloy or titanium. Methods: Metallic frameworks (25 mm × 3 mm × 0.5 mm) (N = 96) cast in gold alloy or commercial pure titanium (Ti cp) were obtained using acrylic templates. They were airborne particle-abraded with 150 μm aluminum oxide at the central area of the frameworks (8 mm × 3 mm). Bonding agent and opaque were applied on the particle-abraded surfaces and the corresponding ceramic for each metal was fired onto them. The thickness of the ceramic layer was standardized by positioning the frameworks in a metallic template (height: 1 mm). The specimens from each ceramic-metal combination (N = 96, n = 12 per group) were randomly assigned into four experimental fatigue conditions, namely water storage at 37 °C for 24 h (control group), thermal cycling (3000 cycles, between 4 and 55 °C, dwell time: 10 s), mechanical cycling (20,000 cycles under 10 N load, immersion in distilled water at 37 °C) and, thermal and mechanical cycling. A flexural strength test was performed in a universal testing machine (crosshead speed: 1.5 mm/min). Data were statistically analyzed using two-way ANOVA and Tukey's test (α = 0.05). Results: The mean flexural strength values for the ceramic-gold alloy combination (55 ± 7.2 MPa) were significantly higher than those of the ceramic-Ti cp combination (32 ± 6.7 MPa) regardless of the fatigue conditions performed (p < 0.05). Mechanical and thermo-mechanical fatigue decreased the flexural strength results significantly for both ceramic-gold alloy (52 ± 6.6 and 53 ± 5.6 MPa, respectively) and ceramic-Ti cp combinations (29 ± 6.8 and 29 ± 6.8 MPa, respectively) compared to the control group (58 ± 7.8 and 39 ± 5.1 MPa, for gold and Ti cp, respectively) (p < 0.05) (Tukey's test). While ceramic-Ti cp combinations failed adhesively at the metal-opaque interface, gold alloy frameworks exhibited a residue of ceramic material on the surface in all experimental groups. Significance: Mechanical and thermo-mechanical fatigue conditions decreased the flexural strength values for both ceramic-gold alloy and ceramic-Ti cp combinations with the results being significantly lower for the latter in all experimental conditions. © 2007 Academy of Dental Materials.

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.

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.

Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

Bilevel approach for optimal location and contract pricing of distributed generation in radial distribution systems using mixed-integer linear programming

In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.

DESIGN OF MICROIRRIGATION SYSTEMS IN SLOPING LANDS USING LINEAR PROGRAMMING

Quando a área a ser irrigada apresenta um elevado gradiente de declive na direção das linhas de derivação, uma opção de dimensionamento é o uso de tubulações com vários diâmetros para economizar no custo e também para manter a variação de pressão dentro dos limites desejados. O objetivo deste trabalho foi desenvolver um modelo de programação linear para dimensionar sistemas de irrigação por microaspersão com linhas de derivação com mais de um diâmetro e operando em declive, visando a minimização do custo anualizado da rede hidráulica e do custo anual com energia elétrica, além de assegurar que a máxima variação de carga hidráulica na linha será respeitada. Os dados de entrada são: configuração da rede hidráulica do sistema de irrigação, custo de todos os componentes da rede hidráulica e custo da energia. Os dados de saída são: custo anual total, diâmetro da tubulação em cada linha do sistema, carga hidráulica em cada ponto de derivação e altura manométrica total. Para ilustrar a potencialidade do modelo desenvolvido, ele foi aplicado em um pomar de citros no Estado de São Paulo, Brasil. O modelo demonstrou ser eficiente no dimensionamento do sistema de irrigação quanto à obtenção da uniformidade de emissão desejada. O custo anual com bombeamento deve ser considerado no dimensionamento de sistemas de irrigação por microaspersão porque ele gera menores valores de custo anual total quando comparado com a mesma alternativa que não considera aquele custo.