Kinetic, thermodynamic properties, and optimization of barley hydration

The hydration kinetics of five barley cultivars was studied at six different temperatures ranging from 10 to 35 ºC for 32 hours applying the Peleg model. Response Surface was used to describe dynamic of the process and identify the hydration time for each cultivar. The activation energy (Ea), enthalpy (ΔH*), entropy (ΔS*), and Gibbs free energy (ΔG*) were estimated from the adjusted parameters and Arrhenius equation. Temperature had significant effect on the hydration of the five cultivars. At low temperatures, the stabilization time for hydration was faster. Peleg constants K1 and K2 decreased with increasing temperature. The cultivar BRS BRAU showed the lowest value of initial absorption rate (R0 = 0.149 kg.h-1) at 10 ºC, while the cultivar BRS BOREMA had the highest value of R0 (0.367 kg.h-1 at 35 ºC). The equilibrium moisture content (Me) increased with increasing temperature. The cultivars BRS CAUE and BRS BRAU showed the lowest values of Ea, ΔH*, ΔS* showed negative values, and ΔG* increased with increasing temperature, confirming the effect of temperature on hydration.

Microencapsulation of babassu coconut milk

The objective of this study was to obtain babassu coconut milk powder microencapsulated by spray drying process using gum Arabic as wall material. Coconut milk was extracted by babassu peeling, grinding (with two parts of water), and vacuum filtration. The milk was pasteurized at 85 ºC for 15 minutes and homogenized to break up the fat globules, rendering the milk a uniform consistency. A central composite rotatable design with a range of independent variables was used: inlet air temperature in the dryer (170-220 ºC) and gum Arabic concentration (10-20%, w/w) on the responses: moisture content (0.52-2.39%), hygroscopicity (6.98-9.86 g adsorbed water/100g solids), water activity (0.14-0.58), lipid oxidation (0.012-0.064 meq peroxide/kg oil), and process yield (20.33-30.19%). All variables influenced significantly the responses evaluated. Microencapsulation was optimized for maximum process yield and minimal lipid oxidation. The coconut milk powder obtained at optimum conditions was characterized in terms of morphology, particle size distribution, bulk and absolute density, porosity, and wettability.

Optimization of the HS-SPME-GC/MS technique for determining volatile compounds in red wines made from Isabel grapes (Vitis labrusca)

Abstract Brazilian wine production is characterized by Vitis labrusca grape varieties, especially the economically important Isabel cultivar, with over 80% of its production destined for table wine production. The objective of this study was to optimize and validate the conditions for extracting volatile compounds from wine with the solid-phase microextraction technique, using the response surface method. Based on the response surface analysis, it can be concluded that the central point values maximize the process of extracting volatile compounds from wine, i.e., an equilibrium time of 15 minutes, an extraction time of 35 minutes, and an extraction temperature of 30 °C. Esters were the most numerous compounds found under these extraction conditions, indicating that wines made from Isabel cultivar grapes are characterized by compounds that confer a fruity aroma; this finding corroborates the scientific literature.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Alkaline Protease from a Non-toxigenic Vibrio sp.(V26) and its Applications

The thesis presents a detailed account of the alkaline protease produced by Vibrio sp.(V26) a mangrove isolate,and the application of this enzyme in different fields.The protease producer strain was identified on the basis of biochemical characteristice,putative virulence traits and 16S rRNA gene sequencing.The purification and characterization of the protease has been carried out. Along with this, an attempt has been made to identifiy the protease gene. The physical parameters as well as the media components influencing protease production were optimized using Response Surfce Methodology(RSM).The scale up of the application of the protease from Vibrio sp.(V26) in the dissociation of cells in animal cell culture,in the recovery of silver from used X-ray films as well as an ingredient in commercial detergents were investigated.

Lipase from marine Aspergillus awamori BTMFW032: Production, partial purification and application in oil effluent treatment

Marine fungus BTMFW032, isolated from seawater and identified as Aspergillus awamori, was observed to produce an extracellular lipase, which could reduce 92% fat and oil content in the effluent laden with oil. In this study, medium for lipase production under submerged fermentation was optimized statistically employing response surface method toward maximal enzyme production. Medium with soyabean meal- 0.77% (w/v); (NH4)2SO4-0.1 M; KH2PO4-0.05 M; rice bran oil-2% (v/v); CaCl2-0.05 M; PEG 6000-0.05% (w/v); NaCl-1% (w/v); inoculum-1% (v/v); pH 3.0; incubation temperature 35 8C and incubation period-five days were identified as optimal conditions for maximal lipase production. The time course experiment under optimized condition, after statistical modeling, indicated that enzyme production commenced after 36 hours of incubation and reached a maximum after 96 hours (495.0 U/ml), whereas maximal specific activity of enzyme was recorded at 108 hours (1164.63 U/mg protein). After optimization an overall 4.6- fold increase in lipase production was achieved. Partial purification by (NH4)2SO4 precipitation and ion exchange chromatography resulted in 33.7% final yield. The lipase was noted to have a molecular mass of 90 kDa and optimal activity at pH 7 and 40 8C. Results indicated the scope for potential application of this marine fungal lipase in bioremediation.

Plasma polymerization of C[subscript 4]F[subscript 8] thin film on high aspect ratio silicon molds

High aspect ratio polymeric micro-patterns are ubiquitous in many fields ranging from sensors, actuators, optics, fluidics and medical. Second generation PDMS molds are replicated against first generation silicon molds created by deep reactive ion etching. In order to ensure successful demolding, the silicon molds are coated with a thin layer of C[subscript 4]F[subscript 8] plasma polymer to reduce the adhesion force. Peel force and demolding status are used to determine if delamination is successful. Response surface method is employed to provide insights on how changes in coil power, passivating time and gas flow conditions affect plasma polymerization of C[subscript 4]F[subscript 8].

The importance of temperature and moisture to the egg-laying behaviour of a pest slug, Deroceras reticulatum

Oviposition behaviour is important when modelling the population dynamics of many invertebrates. The numbers of eggs laid are frequently used to describe fecundity, but this measure may differ significantly from realised fecundity. Oviposition has been shown to be important when describing the dynamics of slug populations, which are important agricultural pests. The numbers of eggs laid by Deroceras reticulatum and their viability were measured across a range of 16 temperature (4, 10, 15 and 23 degrees C) by moisture (33%, 42%, 53% and 58% by dry soil weight) experimental combinations. A fitted quadratic response surface model was used to estimate how D. reticulatum adjusted its egg laying to the surrounding temperature and moisture conditions, with most eggs being laid at a combination of 53% soil moisture and 18 degrees C. The number and proportion of viable eggs also covaried with temperature and moisture, suggesting that D. reticulatum may alter their investment in reproduction to maximise their fitness. We have shown that the number of viable eggs differs from the total number of eggs laid by D. reticulatum. Changes in egg viability with temperature and moisture may also be seen in other species and should be considered when modelling populations of egg-laying invertebrates.

Fitting models for the joint action of two drugs using SAS(R)

Combinations of drugs are increasingly being used for a wide variety of diseases and conditions. A pre-clinical study may allow the investigation of the response at a large number of dose combinations. In determining the response to a drug combination, interest may lie in seeking evidence of synergism, in which the joint action is greater than the actions of the individual drugs, or of antagonism, in which it is less. Two well-known response surface models representing no interaction are Loewe additivity and Bliss independence, and Loewe or Bliss synergism or antagonism is defined relative to these. We illustrate an approach to fitting these models for the case in which the marginal single drug dose-response relationships are represented by four-parameter logistic curves with common upper and lower limits, and where the response variable is normally distributed with a common variance about the dose-response curve. When the dose-response curves are not parallel, the relative potency of the two drugs varies according to the magnitude of the desired effect and the models for Loewe additivity and synergism/antagonism cannot be explicitly expressed. We present an iterative approach to fitting these models without the assumption of parallel dose-response curves. A goodness-of-fit test based on residuals is also described. Implementation using the SAS NLIN procedure is illustrated using data from a pre-clinical study. Copyright © 2007 John Wiley & Sons, Ltd.

Modelling climate impact on floods with ensemble climate projections

The evidence provided by modelled assessments of future climate impact on flooding is fundamental to water resources and flood risk decision making. Impact models usually rely on climate projections from global and regional climate models (GCM/RCMs). However, challenges in representing precipitation events at catchment-scale resolution mean that decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs. Here the impacts on projected high flows of differing ensemble approaches and application of Model Output Statistics to RCM precipitation are evaluated while assessing climate change impact on flood hazard in the Upper Severn catchment in the UK. Various ensemble projections are used together with the HBV hydrological model with direct forcing and also compared to a response surface technique. We consider an ensemble of single-model RCM projections from the current UK Climate Projections (UKCP09); multi-model ensemble RCM projections from the European Union's FP6 ‘ENSEMBLES’ project; and a joint probability distribution of precipitation and temperature from a GCM-based perturbed physics ensemble. The ensemble distribution of results show that flood hazard in the Upper Severn is likely to increase compared to present conditions, but the study highlights the differences between the results from different ensemble methods and the strong assumptions made in using Model Output Statistics to produce the estimates of future river discharge. The results underline the challenges in using the current generation of RCMs for local climate impact studies on flooding. Copyright © 2012 Royal Meteorological Society

Simple uncertainty frameworks for selecting weighting schemes and interpreting multimodel ensemble climate change experiments

Future climate change projections are often derived from ensembles of simulations from multiple global circulation models using heuristic weighting schemes. This study provides a more rigorous justification for this by introducing a nested family of three simple analysis of variance frameworks. Statistical frameworks are essential in order to quantify the uncertainty associated with the estimate of the mean climate change response. The most general framework yields the “one model, one vote” weighting scheme often used in climate projection. However, a simpler additive framework is found to be preferable when the climate change response is not strongly model dependent. In such situations, the weighted multimodel mean may be interpreted as an estimate of the actual climate response, even in the presence of shared model biases. Statistical significance tests are derived to choose the most appropriate framework for specific multimodel ensemble data. The framework assumptions are explicit and can be checked using simple tests and graphical techniques. The frameworks can be used to test for evidence of nonzero climate response and to construct confidence intervals for the size of the response. The methodology is illustrated by application to North Atlantic storm track data from the Coupled Model Intercomparison Project phase 5 (CMIP5) multimodel ensemble. Despite large variations in the historical storm tracks, the cyclone frequency climate change response is not found to be model dependent over most of the region. This gives high confidence in the response estimates. Statistically significant decreases in cyclone frequency are found on the flanks of the North Atlantic storm track and in the Mediterranean basin.

Multivariant optimization, validation, and application of capillary electrophoresis for simultaneous determination of polyphenols and phenolic acids in Brazilian wines

A method for the simultaneous determination of the stilbene resveratrol, four phenolic acids (syringic, coumaric, caffeic, and gallic acids), and five flavonoids (catechin, rutin, kaempferol, myricetin, and quercetin) in wine by CE was developed and validated. The CE electrolyte composition and instrumental conditions were optimized using 2(7-3) factorial design and response surface analysis, showing sodium tetraborate, MeOH, and their interaction as the most influential variables. The optimal electrophoretic conditions, minimizing the chromatographic resolution statistic values, consisted of 17 mmol/L sodium tetraborate with 20% methanol as electrolyte, constant voltage of 25 kV, hydrodynamic injection at 50 mbar for 3 s, and temperature of 25 degrees C. The R(2) values for linearity varied from 0.994 to 0.999; LOD and LOQ were 0.1 to 0.3 mg/L and 0.4 to 0.8 mg/L, respectively. The RSDs for migration time and peak area obtained from ten consecutive injections were less than 2% and recoveries varied from 97 to 102%. The method was applied to 23 samples of inexpensive Brazilian wines, showing wide compositional variation.

Técnicas de avaliação da confiabilidade em estruturas de concreto armado

Neste trabalho é dado ênfase à inclusão das incertezas na avaliação do comportamento estrutural, objetivando uma melhor representação das características do sistema e uma quantificação do significado destas incertezas no projeto. São feitas comparações entre as técnicas clássicas existentes de análise de confiabilidade, tais como FORM, Simulação Direta Monte Carlo (MC) e Simulação Monte Carlo com Amostragem por Importância Adaptativa (MCIS), e os métodos aproximados da Superfície de Resposta( RS) e de Redes Neurais Artificiais(ANN). Quando possível, as comparações são feitas salientando- se as vantagens e inconvenientes do uso de uma ou de outra técnica em problemas com complexidades crescentes. São analisadas desde formulações com funções de estado limite explícitas até formulações implícitas com variabilidade espacial de carregamento e propriedades dos materiais, incluindo campos estocásticos. É tratado, em especial, o problema da análise da confiabilidade de estruturas de concreto armado incluindo o efeito da variabilidade espacial de suas propriedades. Para tanto é proposto um modelo de elementos finitos para a representação do concreto armado que incorpora as principais características observadas neste material. Também foi desenvolvido um modelo para a geração de campos estocásticos multidimensionais não Gaussianos para as propriedades do material e que é independente da malha de elementos finitos, assim como implementadas técnicas para aceleração das avaliações estruturais presentes em qualquer das técnicas empregadas. Para o tratamento da confiabilidade através da técnica da Superfície de Resposta, o algoritmo desenvolvido por Rajashekhar et al(1993) foi implementado. Já para o tratamento através de Redes Neurais Artificias, foram desenvolvidos alguns códigos para a simulação de redes percéptron multicamada e redes com função de base radial e então implementados no algoritmo de avaliação de confiabilidade desenvolvido por Shao et al(1997). Em geral, observou-se que as técnicas de simulação tem desempenho bastante baixo em problemas mais complexos, sobressaindo-se a técnica de primeira ordem FORM e as técnicas aproximadas da Superfície de Resposta e de Redes Neurais Artificiais, embora com precisão prejudicada devido às aproximações presentes.

Estudo do impacto da variabilidade de resinas alquídicas nas propriedades de tintas

Este trabalho de conclusão tem como tema a relação entre as especificações de resinas alquídicas e de tintas preparadas com estas resinas, com foco nas características de teor de sólidos e viscosidade, fazendo uso das técnicas projeto de experimentos, superfície de resposta e análise de regressão. O objetivo principal é o estudo dos limites de especificação ideais para a resina alquídica, de forma que os lotes de tinta apresentem propriedades dentro da especificação já ao final do processamento, reduzindo a incidência de lotes fabris com necessidade de ajuste. Como conseqüência, temos redução de retrabalho e lead time fabril, adequação de custo de produtos, maior qualidade intrínseca e maior confiança na sistemática de desenvolvimento, produção e controle de qualidade. Inicialmente, foi realizada uma revisão bibliográfica sobre a tecnologia de tintas e resinas alquídicas, conceitos de controle de qualidade, planejamento de experimentos, análise por superfície de resposta e análise de regressão. Na seqüência, foi conduzido o estudo de caso, realizado na empresa Killing S.A. Tintas e Adesivos, planta localizada na cidade de Novo Hamburgo. Os resultados experimentais indicaram modelos de regressão polinomial válidos para as propriedades avaliadas. Foram tomadas as propriedades teor de sólidos e viscosidade Copo Ford #2 da mistura A+B como parâmetros para análise dos limites de especificação da resina alquídica, onde se comprovou que a variabilidade atualmente permitida é excessiva. A aplicação dos modelos de regressão indicou novos limites de especificação para a resina alquídica, mais estreitos, viabilizando a obtenção de tintas com propriedades especificadas.

Supplementation of sugarcane bagasse with rice bran and sugarcane molasses for shiitake (Lentinula edodes) spawn production

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