Optimization of osmotic dehydration of papaya followed by air-drying

FERNANDES, Fabiano A. N. et al. Optimization of Osmotic Dehydration of Papaya of followed by air-drying. Food Research Internation, v. 39, p. 492-498, 2006.

Multi-objective ant colony optimization for requirements selection

The selection of a set of requirements between all the requirements previously defined by customers is an important process, repeated at the beginning of each development step when an incremental or agile software development approach is adopted. The set of selected requirements will be developed during the actual iteration. This selection problem can be reformulated as a search problem, allowing its treatment with metaheuristic optimization techniques. This paper studies how to apply Ant Colony Optimization algorithms to select requirements. First, we describe this problem formally extending an earlier version of the problem, and introduce a method based on Ant Colony System to find a variety of efficient solutions. The performance achieved by the Ant Colony System is compared with that of Greedy Randomized Adaptive Search Procedure and Non-dominated Sorting Genetic Algorithm, by means of computational experiments carried out on two instances of the problem constructed from data provided by the experts.

Optimization of lipase production from yeasts strains isolated from olive mil wastewater

Dissertação submetida à Universidade de Lisboa, Faculdade de Ciências para a obtenção do Grau de Mestre em Microbiologia Aplicada.

Optimization and improvement of NSCU 1.0. Universal Functional Tester produced by Evoleo Technologi

The aim of the project was to improve an existing testing machine that is produced by the company EVOLEO Technologies. New conceptions of each part have been invented in order to produce an innovative unit that combines optimal segments from the old construction with the new, improved ones. The machine is meant to be testing different kind of devices that use specific elements like: buttons, knobs, monitors. The main purpose is to create various concepts of components that could be changed in order to lower the cost, weight or to simplify the operating process. Figure 1. shows the already existing discussed device.

Probabilistic design optimization of horizontal axis wind turbine rotors

Considerable interest in renewable energy has increased in recent years due to the concerns raised over the environmental impact of conventional energy sources and their price volatility. In particular, wind power has enjoyed a dramatic global growth in installed capacity over the past few decades. Nowadays, the advancement of wind turbine industry represents a challenge for several engineering areas, including materials science, computer science, aerodynamics, analytical design and analysis methods, testing and monitoring, and power electronics. In particular, the technological improvement of wind turbines is currently tied to the use of advanced design methodologies, allowing the designers to develop new and more efficient design concepts. Integrating mathematical optimization techniques into the multidisciplinary design of wind turbines constitutes a promising way to enhance the profitability of these devices. In the literature, wind turbine design optimization is typically performed deterministically. Deterministic optimizations do not consider any degree of randomness affecting the inputs of the system under consideration, and result, therefore, in an unique set of outputs. However, given the stochastic nature of the wind and the uncertainties associated, for instance, with wind turbine operating conditions or geometric tolerances, deterministically optimized designs may be inefficient. Therefore, one of the ways to further improve the design of modern wind turbines is to take into account the aforementioned sources of uncertainty in the optimization process, achieving robust configurations with minimal performance sensitivity to factors causing variability. The research work presented in this thesis deals with the development of a novel integrated multidisciplinary design framework for the robust aeroservoelastic design optimization of multi-megawatt horizontal axis wind turbine (HAWT) rotors, accounting for the stochastic variability related to the input variables. The design system is based on a multidisciplinary analysis module integrating several simulations tools needed to characterize the aeroservoelastic behavior of wind turbines, and determine their economical performance by means of the levelized cost of energy (LCOE). The reported design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity. The presented technology is applied to the design of a 5-MW HAWT rotor to be used at sites of wind power density class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing the mean and standard deviation of the LCOE. Airfoil shapes, spanwise distributions of blade chord and twist, internal structural layup and rotor speed are optimized concurrently, subject to an extensive set of structural and aeroelastic constraints. The effectiveness of the multidisciplinary and robust design framework is demonstrated by showing that the probabilistically designed turbine achieves more favorable probabilistic performance than those of the initial baseline turbine and a turbine designed deterministically.

Madeira wine vinification process: analysis and control

The present study was done in collaboration with J. Faria e Filhos company, a Madeira wine producer, and its main goal was to fully characterize three wines produced during 2014 harvest and identify possible improving points in the winemaking process. The winemaking process was followed during 4 weeks, being registered the amounts of grapes received, the fermentation temperatures, the time at which fermentation was stopped and evolution of must densities until the fortification time. The characterization of musts and wines was done in terms of density, total and volatile acidity, alcohol content, pH, total of polyphenol, organic acids composition, sugars concentration and the volatile profile. Also, it was developed and validated an analytical methodology to quantify the volatile fatty acids, namely using SPME-GC-MS. Briefly, the following key features were obtained for the latter methodology: linearity (R2=0.999) e high sensitivity (LOD =0.026-0.068 mg/L), suitable precision (repeatability and reproducibility lower than 8,5%) and good recoveries (103,11-119,46%). The results reveal that fermentation temperatures should be controlled in a more strictly manner, in order to ensure a better balance in proportion of some volatile compounds, namely the esters and higher alcohols and to minimize the concentration of some volatiles, namely hexanoic, octanoic and decanoic acids, that when above their odours threshold are not positive for the wine aroma. Also, regarding the moment to stop the fermentation, it was verified that it can be introduced changes which can also be benefit to guarantee the tipicity of Madeira wine bouquet.

Bioconversion of agro-industrial wastes for the production of fibrinolytic enzyme from Bacillus halodurans IND18: Purification and biochemical characterization

Background: Agro-wastes were used for the production of fibrinolytic enzyme in solid-state fermentation. The process parameters were optimized to enhance the production of fibrinolytic enzyme from Bacillus halodurans IND18 by statistical approach. The fibrinolytic enzyme was purified, and the properties were studied. Results: A two-level full factorial design was used to screen the significant factors. The factors such as moisture, pH, and peptone were significantly affected enzyme production and these three factors were selected for further optimization using central composite design. The optimum medium for fibrinolytic enzyme production was wheat bran medium containing 1% peptone and 80% moisture with pH 8.32. Under these optimized conditions, the production of fibrinolytic enzyme was found to be 6851 U/g. The fibrinolytic enzyme was purified by 3.6-fold with 1275 U/mg specific activity. The molecular mass of fibrinolytic enzyme was determined by sodium dodecyl sulphate polyacrylamide gel electrophoresis, and it was observed as 29 kDa. The fibrinolytic enzyme depicted an optimal pH of 9.0 and was stable at a range of pH from 8.0 to 10.0. The optimal temperature was 60°C and was stable up to 50°C. This enzyme activated plasminogen and also degraded the fibrin net of blood clot, which suggested its potential as an effective thrombolytic agent. Conclusions: Wheat bran was found to be an effective substrate for the production of fibrinolytic enzyme. The purified fibrinolytic enzyme degraded fibrin clot. The fibrinolytic enzyme could be useful to make as an effective thrombolytic agent.

Thermotolerant fermenting yeasts for simultaneous saccharification fermentation of lignocellulosic biomass

Lignocellulosic biomass is the most abundant renewable source of energy that has been widely explored as second-generation biofuel feedstock. Despite more than four decades of research, the process of ethanol production from lignocellulosic (LC) biomass remains economically unfeasible. This is due to the high cost of enzymes, end-product inhibition of enzymes, and the need for cost-intensive inputs associated with a separate hydrolysis and fermentation (SHF) process. Thermotolerant yeast strains that can undergo fermentation at temperatures above 40°C are suitable alternatives for developing the simultaneous saccharification and fermentation (SSF) process to overcome the limitations of SHF. This review describes the various approaches to screen and develop thermotolerant yeasts via genetic and metabolic engineering. The advantages and limitations of SSF at high temperatures are also discussed. A critical insight into the effect of high temperatures on yeast morphology and physiology is also included. This can improve our understanding of the development of thermotolerant yeast amenable to the SSF process to make LC ethanol production commercially viable.

Ultrasound and microwave assisted extraction of ergosterol from Agaricus bisporus L.: optimization through response surface methodology

There is scientific evidence demonstrating the benefits of mushrooms ingestion due to their richness in bioactive compounds such as mycosterols, in particular ergosterol [I]. Agaricus bisporus L. is the most consumed mushroom worldwide presenting 90% of ergosterol in its sterol fraction [2]. Thus, it is an interesting matrix to obtain ergosterol, a molecule with a high commercial value. According to literature, ergosterol concentration can vary between 3 to 9 mg per g of dried mushroom. Nowadays, traditional methods such as maceration and Soxhlet extraction are being replaced by emerging methodologies such as ultrasound (UAE) and microwave assisted extraction (MAE) in order to decrease the used solvent amount, extraction time and, of course, increasing the extraction yield [2]. In the present work, A. bisporus was extracted varying several parameters relevant to UAE and MAE: UAE: solvent type (hexane and ethanol), ultrasound amplitude (50 - 100 %) and sonication time (5 min-15 min); MAE: solvent was fixed as ethanol, time (0-20 min), temperature (60-210 •c) and solid-liquid ratio (1-20 g!L). Moreover, in order to decrease the process complexity, the pertinence to apply a saponification step was evaluated. Response surface methodology was applied to generate mathematical models which allow maximizing and optimizing the response variables that influence the extraction of ergosterol. Concerning the UAE, ethanol proved to be the best solvent to achieve higher levels of ergosterol (671.5 ± 0.5 mg/100 g dw, at 75% amplitude for 15 min), once hexane was only able to extract 152.2 ± 0.2 mg/100 g dw, in the same conditions. Nevertheless, the hexane extract showed higher purity (11%) when compared with the ethanol counterpart ( 4% ). Furthermore, in the case of the ethanolic extract, the saponification step increased its purity to 21%, while for the hexane extract the purity was similar; in fact, hexane presents higher selectivity for the lipophilic compounds comparatively with ethanol. Regarding the MAE technique, the results showed that the optimal conditions (19 ± 3 min, 133 ± 12 •c and 1.6 ± 0.5 g!L) allowed higher ergosterol extraction levels (556 ± 26 mg/100 g dw). The values obtained with MAE are close to the ones obtained with conventional Soxhlet extraction (676 ± 3 mg/100 g dw) and UAE. Overall, UAE and MAE proved to he efficient technologies to maximize ergosterol extraction yields.

Optimization of microwave-assisted extration of phenolic compounds from tomao by full factorial design coupled with response surface methodology

Tomato (Lycopersicon esculentum Mill.), apart from being a functional food rich in carotenoids, vitamins and minerals, is also an important source of phenolic compounds [1 ,2]. As antioxidants, these functional molecules play an important role in the prevention of human pathologies and have many applications in nutraceutical, pharmaceutical and cosmeceutical industries. Therefore, the recovery of added-value phenolic compounds from natural sources, such as tomato surplus or industrial by-products, is highly desirable. Herein, the microwave-assisted extraction of the main phenolic acids and flavonoids from tomato was optimized. A S-Ieve! full factorial Box-Behnken design was implemented and response surface methodology used for analysis. The extraction time (0-20 min), temperature (60-180 "C), ethanol percentage (0-100%), solidlliquid ratio (5-45 g/L) and microwave power (0-400 W) were studied as independent variables. The phenolic profile of the studied tomato variety was initially characterized by HPLC-DAD-ESIIMS [2]. Then, the effect of the different extraction conditions, as defined by the used experimental design, on the target compounds was monitored by HPLC-DAD, using their UV spectra and retention time for identification and a series of calibrations based on external standards for quantification. The proposed model was successfully implemented and statistically validated. The microwave power had no effect on the extraction process. Comparing with the optimal extraction conditions for flavonoids, which demanded a short processing time (2 min), a low temperature (60 "C) and solidlliquid ratio (5 g/L), and pure ethanol, phenolic acids required a longer processing time ( 4.38 min), a higher temperature (145.6 •c) and solidlliquid ratio (45 g/L), and water as extraction solvent. Additionally, the studied tomato variety was highlighted as a source of added-value phenolic acids and flavonoids.

Optimization of ultrasound-assisted extraction to obtain mycosterols from Agaricus bisporus L. by response surface methodology and comparison with conventional Soxhlet extraction

Ergosterol, a molecule with high commercial value, is the most abundant mycosterol in Agaricus bisporus L. To replace common conventional extraction techniques (e.g. Soxhlet), the present study reports the optimal ultrasound-assisted extraction conditions for ergosterol. After preliminary tests, the results showed that solvents, time and ultrasound power altered the extraction efficiency. Using response surface methodology, models were developed to investigate the favourable experimental conditions that maximize the extraction efficiency. All statistical criteria demonstrated the validity of the proposed models. Overall, ultrasound-assisted extraction with ethanol at 375 W during 15 min proved to be as efficient as the Soxhlet extraction, yielding 671.5 ± 0.5mg ergosterol/100 g dw. However, with n-hexane extracts with higher purity (mg ergosterol/g extract) were obtained. Finally, it was proposed for the removal of the saponification step, which simplifies the extraction process and makes it more feasible for its industrial transference.

Microwave-assisted extraction of phenolic acids and flavonoids and production of antioxidant ingredients from tomato: a nutraceutical-oriented optimization study

The production of natural extracts requires suitable processing conditions to maximize the preservation of the bioactive ingredients. Herein, a microwave-assisted extraction (MAE) process was optimized, by means of response surface methodology (RSM), to maximize the recovery of phenolic acids and flavonoids and obtain antioxidant ingredients from tomato. A 5-level full factorial Box-Behnken design was successfully implemented for MAE optimization, in which the processing time (t), temperature (T), ethanol concentration (Et) and solid/liquid ratio (S/L) were relevant independent variables. The proposed model was validated based on the high values of the adjusted coefficient of determination and on the non-significant differences between experimental and predicted values. The global optimum processing conditions (t=20 min; T=180 ºC; Et=0 %; and S/L=45 g/L) provided tomato extracts with high potential as nutraceuticals or as active ingredients in the design of functional foods. Additionally, the round tomato variety was highlighted as a source of added-value phenolic acids and flavonoids.

Carrier Selection for Multi-commodity Flow Optimization in Cooperative Environments

Part 18: Optimization in Collaborative Networks

I. Quantal effects in biochemical cooperativity and a proposed mechanism for the differentiation of calcium signaling in synaptic plasticity. II. Evolutionary algorithms for the optimization of methods in computational chemistry

In Part 1 of this thesis, we propose that biochemical cooperativity is a fundamentally non-ideal process. We show quantal effects underlying biochemical cooperativity and highlight apparent ergodic breaking at small volumes. The apparent ergodic breaking manifests itself in a divergence of deterministic and stochastic models. We further predict that this divergence of deterministic and stochastic results is a failure of the deterministic methods rather than an issue of stochastic simulations.

Ergodic breaking at small volumes may allow these molecular complexes to function as switches to a greater degree than has previously been shown. We propose that this ergodic breaking is a phenomenon that the synapse might exploit to differentiate Ca$^{2+}$ signaling that would lead to either the strengthening or weakening of a synapse. Techniques such as lattice-based statistics and rule-based modeling are tools that allow us to directly confront this non-ideality. A natural next step to understanding the chemical physics that underlies these processes is to consider \textit{in silico} specifically atomistic simulation methods that might augment our modeling efforts.

In the second part of this thesis, we use evolutionary algorithms to optimize \textit{in silico} methods that might be used to describe biochemical processes at the subcellular and molecular levels. While we have applied evolutionary algorithms to several methods, this thesis will focus on the optimization of charge equilibration methods. Accurate charges are essential to understanding the electrostatic interactions that are involved in ligand binding, as frequently discussed in the first part of this thesis.

Optimization of Enzymes Inactivation in High Pressure Processes

The demand of highest quality foods in terms of taste and their properties preservation without the use of additives is constantly increasing. Consequently, new approaches to food processing have been developed, as for example high-pressure technology which has proven to be very valuable because it allows to maintain good properties of food like some vitamins and, at the same time, to reduce some undesirable bacteria. This technology avoids the use of high temperatures during the process (not like Pasteurization), which may have adverse effect on some nutritional properties of the food, its flavour, etc. The models for some enzymatic inactivations, which depend on the pressure and temperature profiles are presented. This work deals with the optimization of the inactivation of certain enzymes when high pressure treatment on food processing is applied. The optimization algorithms will minimize the inactivation not only of a certain isolated enzyme but also to several enzymes that can be involved simultaneously in the high-pressure process.