Design and management optimization of trickle irrigation systems using non-linear programming

A non-linear model is presented which optimizes the lay-out, as well as the design and management of trickle irrigation systems, to achieve maximum net benefit. The model consists of an objective function that maximizes profit at the farm level, subject to appropriate geometric and hydraulic constraints. It can be applied to rectangular shaped fields, with uniform or zero slope. The software used is the Gams-Minos package. The basic inputs are the crop-water-production function, the cost function and cost of system components, and design variables. The main outputs are the annual net benefit and pipe diameters and lengths. To illustrate the capability of the model, a sensitivity analysis of the annual net benefit for a citrus field is evaluated with respect to irrigated area, ground slope, micro-sprinkler discharge and shape of the field. The sensitivity analysis suggests that the greatest benefit is obtained with the smallest microsprinkler discharge, the greatest area, a square field and zero ground slope. The costs of the investment and energy are the components of the objective function that had the greatest effect in the 120 situations evaluated. (C) 1996 Academic Press Limited

Thermoeconomic analysis method for optimization of combined heat and power systems. Part I

This article presents a thermoeconomic analysis of cogeneration plants, applied as a rational technique to produce electric power and saturated steam. The aim of this new methodology is the minimum Exergetic Production Cost (EPC), based on the Second Law of Thermodynamics. The variables selected for the optimization are the pressure and the temperature of the steam leaving the boiler in the case of using steam turbine, and the pressure ratio, turbine exhaust temperature and mass flow in the case of using gas turbines. The equations for calculating the capital costs of the components and products are formulated as a function of these decision variables. An application of the method using real data of a multinational chemical industry located in São Paulo state is presented. The conditions which establish the minimum cost are presented as final output. (C) 2003 Elsevier Ltd. All rights reserved.

Structural health evaluation by optimization techinique and artificial neural network

This paper presents two different approaches to detect, locate, and characterize structural damage. Both techniques utilize electrical impedance in a first stage to locate the damaged area. In the second stage, to quantify the damage severity, one can use neural network, or optimization technique. The electrical impedance-based, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations, this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors, and therefore, it is able to detect the damage in its early stage. Optimization approaches must be used for the case where a good condensed model is known, while neural network can be also used to estimate the nature of damage without prior knowledge of the model of the structure. The paper concludes with an experimental example in a welded cubic aluminum structure, in order to verify the performance of these two proposed methodologies.

Antibiosis associated to Lactobacillus acidophilus growth .2. Optimization of some culture parameters in whey and soy milk medium

Whey supplemented with soy milk has been used as a low-cost alternative in the growth of Lactobacillus acidophilus for the production of antimicrobial compounds. Response Surface Metodology has been employed in order to study the effects of initial pH, incubation temperature and soy milk rate for supplementation in the production of antimicrobial substance. It has been observed that both tested microrganisms used (S. aureus and E. coli) were inhibited by antimicrobial substance produced by L. acidophilus. The results obtained with E. coli inhibition did not follow the employed statistical model. on the other hand, when the tested microorganism S. aureus was used, the best inhibition results have been obtained when L. acidophilus was incubated at 36.80 degrees C in whey with 5.6 initial pH and 31,90% (v/v) rate supplemented with soy milk. The analysed antimicrobial substances were nor acids neither hidrogen peroxid.

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.

Effects of biofertilizer rates on the structural, morphogenetic and productive characteristics of Piata grass

The objective of this study was to investigate the influence of different levels of biofertilizers from cattle and swine manure on the structural, morphogenetic and productive characteristics of Brachiaria brizantha cv. Piata. The experiment was arranged in a completely randomized factorial design with split plots. The plots were defined by eight treatments: two biofertilizers (cattle and swine), four levels (0, 100, 200 and 300 kg N.ha(-1)) and subplots by four different cutting periods. The cutting for plant uniformity was performed at 45 days after sowing at 15 cm above the soil surface. The biofertilizeres were applied in a single level, after the cutting of plants, in rates of 0, 0.23 and 0.19, 0.45 and 0.38, 0.68 and 0.57 liters pot(-1) for the biofertilizers from cattle and swine manure, respectively. These rates were also equivalent to levels of 0, 100, 200 and 300 kg N.ha(-1). There was no significant difference between the types of biofertilizers as there was no interaction between them and the different levels, hence both biofertilizers could be applied without any loss of nutrient intake by the plants used in this experiment. There was a significant difference between the production of green and dry matter, the leaf appearance rate, phyllochron, leaf and pseudostem elongation rates, number of green leaves, final leaf length, number and weight of tillers, according to the increase of nitrogen rates, following linear prediction model. Effect of the cutting periods was also observed, once the plants harvested during the summer presented greater performance of structural and morphogenetic characteristics.

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)

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.