Keratinase production by new strain of Bacillus Amyloliquefaciens: Application of statistical experimental design for optimization of keratinase production

Feathers are rich in amino acids and can be employed as a dietary protein supplement for animal feed. Microbial degradation is an alternative technology for improving the nutritional value of feathers. Other potential applications of keratinase include use in the leather industry, detergents and medicine as well as the pharmaceutical for the treatment of acne, psoriasis and calluses. A new keratinolytic enzyme production bacterium was isolated from a poultry processing plant. To improve keratinase yield, statistically based experimental designs were applied to optimize three significant variables: temperature, substrate concentration (feathers) and agitation speed. Response surface methodology demonstrated an increase in keratinolytic activity at temperature, agitation speed and substrate concentration of 26.6°C, 150 rpm and 2%, respectively. Liquid chromatography revealed the release of amino acids in the Bacillus amyloliquefaciens culture broth, thereby demonstrating the potential of feather meal in the animal feed industry. © Global Science Publications.

Selection of desulfurizing agents and optimization of operational variables in hot metal desulfurization

The growing demand for steels with tighter compositional specifications led the Companhia Siderúrgica Nacional (CSN) to develop more efficient processes. To solve this problem this paper aims to identify the operational variables more impacting in the desulfurization process, specifically in torpedo car, as well as its causes and solutions. Then select and test, with laboratorial and industrial tests, desulfurizing agents based of CaC 2, CaO, CaCO3, and Mg to assess the cost per quantity of product desulfurized. The mixture with best results was not that one with highest content of CaC2. It is believed that this mixture showed better efficiency because of the increased agitation of the bath, produced by the releasing of gas from compound CaCO3 present in this mixture. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A heuristic algorithm based on multi-assignment procedures for nurse scheduling

This paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses' preferences and minimize the violation of soft constraints. This paper presents a new deterministic heuristic algorithm, called MAPA (multi-assignment problem-based algorithm), which is based on successive resolutions of the assignment problem. The algorithm has two phases: a constructive phase and an improvement phase. The constructive phase builds a full schedule by solving successive assignment problems, one for each day in the planning period. The improvement phase uses a couple of procedures that re-solve assignment problems to produce a better schedule. Given the deterministic nature of this algorithm, the same schedule is obtained each time that the algorithm is applied to the same problem instance. The performance of MAPA is benchmarked against published results for almost 250,000 instances from the NSPLib dataset. In most cases, particularly on large instances of the problem, the results produced by MAPA are better when compared to best-known solutions from the literature. The experiments reported here also show that the MAPA algorithm finds more feasible solutions compared with other algorithms in the literature, which suggest that this proposed approach is effective and robust. © 2013 Springer Science+Business Media New York.

Penalty-based nonlinear solver for optimal reactive power dispatch with discrete controls

The optimal reactive dispatch problem is a nonlinear programming problem containing continuous and discrete control variables. Owing to the difficulty caused by discrete variables, this problem is usually solved assuming all variables as continuous variables, therefore the original discrete variables are rounded off to the closest discrete value. This approach may provide solutions far from optimal or even unfeasible solutions. This paper presents an efficient handling of discrete variables by penalty function so that the problem becomes continuous and differentiable. Simulations with the IEEE test systems were performed showing the efficiency of the proposed approach. © 1969-2012 IEEE.

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.

Optimization of the surimi production from Mechanically Recovered Fish Meat (MRFM) using response surface methodology

The by-products generated from industrial filleting of tilapia surimi can be used for the manufacture of surimi. The surimi production uses large amounts of water, which generates a wastewater rich in organic compounds (lipids, soluble proteins and blood). Optimizing the number of washing cycles will contribute to a more sustainable production. A mathematical model of mechanically recovered tilapia meat (Oreochromis niloticus) for the processing of surimi (minced fish washing cycles and tapioca starch addition) based on two quality parameters (texture and moisture) was constructed by applying the response surface methodology (RSM). Each factor had an important effect on the moisture and texture of surimi. This study found that the optimal formulation for producing the best surimi using the by-products of tilapia filleting in manufacturing fish burger were the addition of 10% tapioca starch and three minced fish washing cycles. A microstructural evaluation supported the findings of the mathematical model. Practical Applications: The use of mechanically recovered fish meat (MRFM) for the production of surimi enables the utilization of the by-products of filleting fish. However, the inferior quality of the surimi produced from MRFM in relation to that produced with fillets necessitates the addition of starch; secondly, surimi production consumes a large volume of water. RSM provides a valuable means for optimizing the number of washing cycles and starch amounts utilized in fish burger production. Tapioca starch, widely produced in Brazil, has desirable characteristics (surface sheen, smooth texture, neutral taste and clarity in solution) for use in MRFM-produced surimi. © 2013 Wiley Periodicals, Inc.

Lipase production by Botryosphaeria ribis EC-01 on soybean and castorbean meals: Optimization, immobilization, and application for biodiesel production

The effects of soybean and castorbean meals were evaluated separately, and in combinations at different ratios, as substrates for lipase production by Botryosphaeria ribis EC-01 in submerged fermentation using only distilled water. The addition of glycerol analytical grade (AG) and glycerol crude (CG) to soybean and castorbean meals separately and in combination, were also examined for lipase production. Glycerol-AG increased enzyme production, whereas glycerol-CG decreased it. A 24 factorial design was developed to determine the best concentrations of soybean meal, castorbean meal, glycerol-AG, and KH2PO4 to optimize lipase production by B. ribis EC-01. Soybean meal and glycerol-AG had a significant effect on lipase production, whereas castorbean meal did not. A second treatment (22 factorial design central composite) was developed, and optimal lipase production (4,820 U/g of dry solids content (ds)) was obtained when B. ribis EC-01 was grown on 0.5 % (w/v) soybean meal and 5.2 % (v/v) glycerol in distilled water, which was in agreement with the predicted value (4,892 U/g ds) calculated by the model. The unitary cost of lipase production determined under the optimized conditions developed ranged from US$0.42 to 0.44 based on nutrient costs. The fungal lipase was immobilized onto Celite and showed high thermal stability and was used for transesterification of soybean oil in methanol (1:3) resulting in 36 % of fatty acyl alkyl ester content. The apparent K m and V max were determined and were 1.86 mM and 14.29 μmol min -1 mg-1, respectively. © 2013 Springer Science+Business Media New York.

A hybrid image restoration algorithm based on Projections onto Convex Sets and Harmony Search

Image restoration is a research field that attempts to recover a blurred and noisy image. Since it can be modeled as a linear system, we propose in this paper to use the meta-heuristics optimization algorithm Harmony Search (HS) to find out near-optimal solutions in a Projections Onto Convex Sets-based formulation to solve this problem. The experiments using HS and four of its variants have shown that we can obtain near-optimal and faster restored images than other evolutionary optimization approach. © 2013 IEEE.

Comparative analysis of strut-and-tie models using Smooth Evolutionary Structural Optimization

The strut-and-tie models are widely used in certain types of structural elements in reinforced concrete and in regions with complexity of the stress state, called regions D, where the distribution of deformations in the cross section is not linear. This paper introduces a numerical technique to determine the strut-and-tie models using a variant of the classical Evolutionary Structural Optimization, which is called Smooth Evolutionary Structural Optimization. The basic idea of this technique is to identify the numerical flow of stresses generated in the structure, setting out in more technical and rational members of strut-and-tie, and to quantify their value for future structural design. This paper presents an index performance based on the evolutionary topology optimization method for automatically generating optimal strut-and-tie models in reinforced concrete structures with stress constraints. In the proposed approach, the element with the lowest Von Mises stress is calculated for element removal, while a performance index is used to monitor the evolutionary optimization process. Thus, a comparative analysis of the strut-and-tie models for beams is proposed with the presentation of examples from the literature that demonstrates the efficiency of this formulation. © 2013 Elsevier Ltd.

Particle swarm optimization aplicada ao planejamento da expansão de sistemas de transmissão

Pós-graduação em Engenharia Elétrica - FEIS

Global optimization using a genetic algorithm with hierarchically structured population

This paper applies a genetic algorithm with hierarchically structured population to solve unconstrained optimization problems. The population has individuals distributed in several overlapping clusters, each one with a leader and a variable number of support individuals. The hierarchy establishes that leaders must be fitter than its supporters with the topological organization of the clusters following a tree. Computational tests evaluate different population structures, population sizes and crossover operators for better algorithm performance. A set of known benchmark test problems is solved and the results found are compared with those obtained from other methods described in the literature, namely, two genetic algorithms, a simulated annealing, a differential evolution and a particle swarm optimization. The results indicate that the method employed is capable of achieving better performance than the previous approaches in regard as the two criteria usually employed for comparisons: the number of function evaluations and rate of success. The method also has a superior performance if the number of problems solved is taken into account. (C) 2013 Elsevier B.V. All rights reserved.

Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas

Hepatocellular carcinoma (HCC) is a primary tumor of the liver. After local therapies, the tumor evaluation is based on the mRECIST criteria, which involves the measurement of the maximum diameter of the viable lesion. This paper describes a computed methodology to measure through the contrasted area of the lesions the maximum diameter of the tumor by a computational algorithm 63 computed tomography (CT) slices from 23 patients were assessed. Non-contrasted liver and HCC typical nodules were evaluated, and a virtual phantom was developed for this purpose. Optimization of the algorithm detection and quantification was made using the virtual phantom. After that, we compared the algorithm findings of maximum diameter of the target lesions against radiologist measures. Computed results of the maximum diameter are in good agreement with the results obtained by radiologist evaluation, indicating that the algorithm was able to detect properly the tumor limits A comparison of the estimated maximum diameter by radiologist versus the algorithm revealed differences on the order of 0.25 cm for large-sized tumors (diameter > 5 cm), whereas agreement lesser than 1.0cm was found for small-sized tumors. Differences between algorithm and radiologist measures were accurate for small-sized tumors with a trend to a small increase for tumors greater than 5 cm. Therefore, traditional methods for measuring lesion diameter should be complemented with non-subjective measurement methods, which would allow a more correct evaluation of the contrast-enhanced areas of HCC according to the mRECIST criteria.

Chemometric optimization of solid-liquid extraction with low-temperature partition (SLE-LTP) for determination of persistent organic pollutants in Caiman yacare eggs

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Discovering promising regions to help global numerical optimization algorithms

We have developed an algorithm using a Design of Experiments technique for reduction of search-space in global optimization problems. Our approach is called Domain Optimization Algorithm. This approach can efficiently eliminate search-space regions with low probability of containing a global optimum. The Domain Optimization Algorithm approach is based on eliminating non-promising search-space regions, which are identifyed using simple models (linear) fitted to the data. Then, we run a global optimization algorithm starting its population inside the promising region. The proposed approach with this heuristic criterion of population initialization has shown relevant results for tests using hard benchmark functions.

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.