Evaluation of serological tests for the diagnosis of Neospora caninum infection in dogs: Optimization of cut off titers and inhibition studies of cross-reactivity with Toxoplasma gondii

Diagnosis of Neospora caninum infection in dogs is based on serological assays such as the indirect fluorescent antibody test (IFAT) and enzyme-linked immunosorbent assays (ELISA). This study evaluated two serological tests (IFAT and ELISA) for the detection of IgG antibodies to N. caninum in 300 serum samples of dogs through the optimization of cut off titers by using the two-graph receiveroperating characteristic (TG-ROC) curve. In addition, the identification of major cross-reactive antigens with Toxoplasma gondii was investigated by inhibition ELISA and immunoblotting (IB) assays. IFAT and ELISA results showed 74% agreement, with a good negative concordance (P-neg=0.83), but a poor positive concordance (P-pos=0.42). The great majority (86%) of sera with positive concordant results (IFAT+/ELISA+) recognized at least two out of three N. caninum immunodominant antigens, particularly the 29-32 and 35-37 kDa bands. Optimization of cut off titers in IFAT and ELISA was performed considering the reactivity to at least two out of three N. caninum immunodominant antigens as infection markers, obtaining a titer of 50 for IFAT and 200 for ELISA. Seropositivity to N. caninuin was significantly associated with T gondii-seropositive samples, particularly in ELISA (55.4%). Inhibition ELISA curves for N. caninum showed a partial heterologous inhibition, indicating some degree of cross-reactivity between N. caninum and T gondii antigens. Inhibition IB assays showed a moderate heterologous inhibition for N. caninum antigens above 45-50 kDa. These results indicate that ELISA should be used critically when crude tachyzoite antigen preparations are employed, due to possible cross-reactivity with other related parasites as T gondii. Also, the cut off dilution of 1:50 in IFAT showed to be the most appropriated for N. caninum serology in dogs. Therefore, we suggest that N. caninum immunodominant antigens, specially the 17 and 29-32 kDa proteins, should be selected markers in serological assays for canine neosporosis. (c) 2006 Elsevier B.V. All rights reserved.

Optimization of the Transesterification Reaction in Biodiesel Production and Determination of Density and Viscosity of Biodiesel/Diesel Blends at Several Temperatures

Waste frying oil has been used to optimize the production of biodiesel. Biodiesel was prepared through sodium ethoxide catalyzed methanolysis from the transesterification of recycled waste frying oil. Optimization of the transesterification reaction for biodiesel production was carried out by means of statistical analyses using ANOVA. The optimum conditions for reaction were the following: a oil methanol mole ratio of 1:9, temperature of 50 degrees C, catalyst mass fraction of 0.9 %, and reaction time of 40 min, which enabled a yield of 98.7 % determined by gas chromatography/mass spectrometry (GC/MS) analysis. The density and viscosity of biodiesel/diesel blends have been determined as a function of composition at several temperatures.

A GEP-ISFG collaborative study on the optimization of an X-STR decaplex: data on 15 Iberian and Latin American populations

In a collaborative work carried out by the Spanish and Portuguese ISFG Working Group (GEP-ISFG), a polymerase chain reaction multiplex was optimized in order to type ten X-chromosome short tandem repeats (STRs) in a single reaction, including: DXS8378, DXS9902, DXS7132, DXS9898, DXS6809, DXS6789, DXS7133, GATA172D05, GATA31E08, and DXS7423. Using this X-decaplex, each 17 of the participating laboratories typed a population sample of approximately 200 unrelated individuals (100 males and 100 females). In this work, we report the allele frequencies for the ten X-STRs in 15 samples from Argentina (Buenos Aires, CA(3)rdoba, Rio Negro, Entre Rios, and Misiones), Brazil (SA o pound Paulo, Rio de Janeiro, Parana, and Mato Grosso do Sul), Colombia (Antioquia), Costa Rica, Portugal (Northern and Central regions), and Spain (Galicia and Cantabria). Gene diversities were calculated for the ten markers in each population and all values were above 56%. The average diversity per locus varied between 66%, for DXS7133, and 82%, for DXS6809. For this set of STRs, a high discrimination power was obtained in all populations, both in males (a parts per thousand yen1 in 5 A- 10(5)) and females (a parts per thousand yen1 in 3 A- 10(9)), as well as high mean exclusion chance in father/daughter duos (a parts per thousand yen99.953%) and in father/mother/daughter trios (a parts per thousand yen99.999%). Genetic distance analysis showed no significant differences between northern and central Portugal or between the two Spanish samples from Galicia and Cantabria. Inside Brazil, significant differences were found between Rio de Janeiro and the other three populations, as well as between SA o pound Paulo and Parana. For the five Argentinean samples, significant distances were only observed when comparing Misiones with Entre Rios and with Rio Negro, the only two samples that do not differ significantly from Costa Rica. Antioquia differed from all other samples, except the one from Rio Negro.

Analytical optimization of spread and change of exponential decay of generalized Wannier functions in one dimension

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Characterization, feasibility and optimization of Agaricus subrufescens growth based on chemical elements on casing layer

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Combining genetic algorithm and simulated annealing: A molecular geometry optimization study

We introduce a new hybrid approach to determine the ground state geometry of molecular systems. Firstly, we compared the ability of genetic algorithm (GA) and simulated annealing (SA) to find the lowest energy geometry of silicon clusters with six and 10 atoms. This comparison showed that GA exhibits fast initial convergence, but its performance deteriorates as it approaches the desired global extreme. Interestingly, SA showed a complementary convergence pattern, in addition to high accuracy. Our new procedure combines selected features from GA and SA to achieve weak dependence on initial parameters, parallel search strategy, fast convergence and high accuracy. This hybrid algorithm outperforms GA and SA by one order of magnitude for small silicon clusters (Si6 and Si10). Next, we applied the hybrid method to study the geometry of a 20-atom silicon cluster. It was able to find an original geometry, apparently lower in energy than those previously described in literature. In principle, our procedure can be applied successfully to any molecular system. © 1998 Elsevier Science B.V.

Optimization procedures in the design of continuous induction hardening and tempering installations for magnetic steel bars

An inverse problem concerning the industrial process of steel bars hardening and tempering is considered. The associated optimization problem is formulated in terms of membership functions and, for the sake of comparison, also in terms of quadratic residuals; both geometric and electromagnetic design variables have been considered. The numerical solution is achieved by coupling a finite difference procedure for the calculation of the electromagnetic and thermal fields to a deterministic strategy of minimization based on modified Flctcher and Reeves method. © 1998 IEEE.

Bound constrained smooth optimization for solving variational inequalities and related problems

Variational inequalities and related problems may be solved via smooth bound constrained optimization. A comprehensive discussion of the important features involved with this strategy is presented. Complementarity problems and mathematical programming problems with equilibrium constraints are included in this report. Numerical experiments are commented. Conclusions and directions of future research are indicated.

Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning

In this article we describe a feature extraction algorithm for pattern classification based on Bayesian Decision Boundaries and Pruning techniques. The proposed method is capable of optimizing MLP neural classifiers by retaining those neurons in the hidden layer that realy contribute to correct classification. Also in this article we proposed a method which defines a plausible number of neurons in the hidden layer based on the stem-and-leaf graphics of training samples. Experimental investigation reveals the efficiency of the proposed method. © 2002 IEEE.

RAPD optimization for genetic studies with Citrulus lanatus and Sesamum indicum genotypes

The Random Amplified Polymorphic DNA (RAPD) technique is powerful for DNA polymorphism determinations and is widely used in research involving different organisms, but it is known that RAPD can be affected by many factors that may result in false positive bands and non-reproducible assays. In this study, we analyzed the effect of several factors such as DNA template, primer and Taq DNA polymerase concentrations to optimize and standardize the RAPD technique for further genetic studies with Citrulus lanattus and Sesamum indicum L. The best combination of DNA, Taq DNA polymerase enzyme and primer concentrations in RAPD amplification procedures for sesame and watermelon genotypes was established.

Optimization of multipulse converters with delta and Y-differential connections

This work presents a study regarding the optimization of multipulse converters. A general expression for the connection (Δ or Y) for both 12 and 18-pulses is obtained and describes the output voltages on the secondary windings, depending on the voltage reference from the primary. These generalized expressions allows choosing different ratios between input and output voltages and as result an optimum operation point for the converter can be calculated. Considering Δ-connected converters the optimum point occurs when the magnetic core of the autotransformer processes 18% and 17% of the output power for 12 and 18-pulses, respectively. For Y-connected converters the optimum point occurs when the kVA rating is 13% and 18% for 12 and 18-pulses, respectively. Based on these results magnetic elements can be calculated and designed leading to a great weight and volume reduction and also to lower costs and losses. Finally an analysis is made to improve the kVA rating of the transformers for 12 and 18 pulses converters. © 2009 IEEE.

Lower-semicontinuity and optimization of convex functionals

The result that we treat in this article allows to the utilization of classic tools of convex analysis in the study of optimality conditions in the optimal control convex process for a Volterra-Stietjes linear integral equation in the Banach space G([a, b],X) of the regulated functions in [a, b], that is, the functions f : [a, 6] → X that have only descontinuity of first kind, in Dushnik (or interior) sense, and with an equality linear restriction. In this work we introduce a convex functional Lβf(x) of Nemytskii type, and we present conditions for its lower-semicontinuity. As consequence, Weierstrass Theorem garantees (under compacity conditions) the existence of solution to the problem min{Lβf(x)}. © 2009 Academic Publications.

Power flow optimization for grid connected inverter using evolutionary algorithm and additional control loop

In this work it is proposed to validate an evolutionary tuning algorithm in plants composed by a grid connected inverter. The optimization aims the tuning of the slopes of P-Ω and Q-V curves so that the system is stable, damped and minimum settling time. Simulation and experimental results are presented to prove the feasibility of the proposed approach. However, experimental results demonstrate a compromising effect of grid frequency oscillations in the active power transferring. In addition, it was proposed an additional loop to compensate this effect ensuring a constant active power flow. © 2011 IEEE.

Application of an iterative method and an evolutionary algorithm in fuzzy optimization

This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.