Orthologous and heterologous expression of a protein from Saccharomyces cerevisiae: Optimization for a biotechnological application

In this thesis (TFG) the results of the comparison between different methods to obtain a recombinant protein, by orthologous and heterologous expression, are exposed. This study will help us to identify the best way to express and purify a recombinant protein that will be used for biotechnology applications. In the first part of the project the goal was to find the best expression and purification system to obtain the recombinant protein of interest. To achieve this objective, a system expression in bacteria and in yeast was designed. The DNA was cloned into two different expression vectors to create a fusion protein with two different tags, and the expression of the protein was induced by IPTG or glucose. Additionally, in yeast, two promoters where used to express the protein, the one corresponding to the same protein (orthologous expression), and the ENO2 promoter (heterologous expression). The protein of interest is a NAD-dependent enzyme so, in a second time, its specific activity was evaluated by coenzyme conversion. The results of the TFG suggest that, comparing the model organisms, bacteria are more efficient than yeast because the quantity of protein obtained is higher and better purified. Regarding yeast, comparing the two expression mechanisms that were designed, heterologous expression works much better than the orthologous expression, so in case that we want to use yeast as expression model for the protein of interest, ENO2 will be the best option. Finally, the enzymatic assays, done to compare the effectiveness of the different expression mechanisms respect to the protein activity, revealed that the protein purified in yeast had more activity in converting the NAD coenzyme.

Mutual feedback in e-portfolio assessment : an approach to the netfolio system

Peer-reviewed

Analyzing Carbon Trade Permits in Optimization Framework

The threats caused by global warming motivate different stake holders to deal with and control them. This Master's thesis focuses on analyzing carbon trade permits in optimization framework. The studied model determines optimal emission and uncertainty levels which minimize the total cost. Research questions are formulated and answered by using different optimization tools. The model is developed and calibrated by using available consistent data in the area of carbon emission technology and control. Data and some basic modeling assumptions were extracted from reports and existing literatures. The data collected from the countries in the Kyoto treaty are used to estimate the cost functions. Theory and methods of constrained optimization are briefly presented. A two-level optimization problem (individual and between the parties) is analyzed by using several optimization methods. The combined cost optimization between the parties leads into multivariate model and calls for advanced techniques. Lagrangian, Sequential Quadratic Programming and Differential Evolution (DE) algorithm are referred to. The role of inherent measurement uncertainty in the monitoring of emissions is discussed. We briefly investigate an approach where emission uncertainty would be described in stochastic framework. MATLAB software has been used to provide visualizations including the relationship between decision variables and objective function values. Interpretations in the context of carbon trading were briefly presented. Suggestions for future work are given in stochastic modeling, emission trading and coupled analysis of energy prices and carbon permits.

Essays on pricing of risk and international linkage of Russian stock market

Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.

The role of alliance capabilities in alliance portfolio management

The question of why some firms perform better in managing their alliances has raised interest among scholars and managers. Whereas inter-firm factors influencing the alliance performance such as strategic fit between partners and the existence of complementarities have been studied extensively, research on firm-level antecedents is rather scarce. Therefore this study investigates the role of firm’s alliance capability in the alliance success equation. Particularly it analyses the specialized mechanisms and processes set up by firm in order to facilitate alliancerelated know-how leverage organization-wise. Evidence from a cross-industry sample of R&D intensive Finnish companies supports the fact that firms which have invested in institutionalizing alliance capabilities outperform their counterparts in alliance portfolio management. Results also suggest that firms need to adjust alliance management tools depending on the alliance portfolio size, prior experience with inter-firm partnerships and the strategic importance of alliances. Furthermore, absorptive capacity is found to be crucial for successful alliance management, its role being complementary to that of alliance capability. Finally, firms that have successful alliances also enjoy higher financial, market and innovation performance.

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications

Optimization of a heatset dryer

The objective of the thesis was to examine the possibilities in designing better performing nozzles for the heatset drying oven in Forest Pilot Center. To achieve the objective, two predesigned nozzle types along with the replicas of the current nozzles in the heatset drying oven were tested on a pilot-scale dryer. During the runnability trials, the pilot dryer was installed between the last printing unit and the drying oven. The two sets of predesigned nozzles were consecutively installed in the dryer. Four web tension values and four different impingement air velocities were used and the web behavior during the trial points was evaluated and recorded. The runnability in all trial conditions was adequate or even good. During the heat transfer trials, each nozzle type was tested on at least two different nozzle-to-surface distances and four different impingement air velocities. In a test situation, an aluminum plate fitted with thermocouples was set below a nozzle and the temperature measurement of each block was logged. From the measurements, a heat transfer coefficient profile for the nozzle was calculated. The performance of each nozzle type in tested conditions could now be rated and compared. The results verified that the predesigned simpler nozzles were better than the replicas. For runnability reasons, there were rows of inclined orifices on the leading and trailing edges of the current nozzles. They were believed to deteriorate the overall performance of the nozzle, and trials were conducted to test this hypothesis. The perpendicular orifices and inclined orifices of a replica nozzle were consecutively taped shut and the performance of the modified nozzles was measured as before, and then compared to the performance of the whole nozzle. It was found out, that after a certain nozzle-to-surface distance the jets from the two nozzles would collide, which deteriorates the heat transfer.

Optimization of energy in a pulp mill

This study presents examination of ways to increase power generation in pulp mills. The main purpose was to identify and verify the best ways of power generation growth. The literature part of this study presented operation of energy pulp mill departments, energy consumption and generation by the recovery and power boilers. The second chapter of this part described the main directions for increase of electricity generation rise of black liquor dry solid content, increase of main steam parameters, flue gas heat recovery technologies, feed water and combustion air preheating. The third chapter of the literature part presented possible technical, environment and corrosion risks appeared from described alternatives. In the experimental part of this study, calculations and results of possible models with alternatives was presented. The possible combinations of alternatives were generated in 44 `models of energy pulp mill. The target of this part was define extra electricity generation after alternatives using and estimate profitability of generated models. The calculations were made by computer programme PROSIM. In the conclusions, the results were estimated on the basis of extra electricity generation and equipment design data of models. The profitability of cases was verified by their payback periods and additional incomes.

Digital learner portfolio as a tool for inovating assessment in the European Higher Education Area

The present article comes from a doctoral thesis that turns on digital learner portfolio, which is an innovating methodology from the perspective of European Higher Education Area. First, the educative concept of eportfolio is described in the sense of its procedure and its structure, by means of the technological support of a platform of virtual campus. Second, it is shown the pedagogical model of an eportfolio that adapts subjects with an instrumental character to one organization based on tasks and reflections. This design of virtual learning environment is based on a teaching- learning methodology sustained in the activity of the student, which tries to give support to the management of his or her own process of learning and assessment. Finally, the article illustrates the experience of implementation of the first digital learner portfolios in the University of Barcelona and the Autonomous University of Barcelona, with the objective of reflecting about the pedagogical consequences that this assessment model with technological support has in a traditional higher education institution.

Investigating university students' adaptation to digital learner course portfolio

Digital learner portfolios are of growing importance in higher education as the sector seeks new teaching-learning-assessment methods which promote students" autonomy as managers of their own virtual learning environment. The purpose of this study was to analyse descriptively the undergraduate students" perceptions, attitudes and behaviour when using an eportfolio to support their learning and assessment in practice based courses at two traditional Spanish universities. The participants were 88 students, who were studying through a blended learning mode. Data were collected through questionnaires: a computer experience survey, another which examined the psychological, pedagogical and technological dimensions of eportfolios use. Further, an individual overall reflection was obtained from each student to help gain an understanding of their experiences of using the eportfolio. A mixed-method analysis was applied in order to study the impact of this technological innovation on students and their satisfaction. The results showed that the students had positive opinions and self-efficiency through the eportfolio as a tool to manage their learning and assessment during a semester, especially from the second month of use. However, the expected impact on their learning was not so significant. Nevertheless, the students emphasised that the eportfolio was valuable as a personal developmental learning tool.

ContinuousMultimodal Global Optimization with Differential Evolution-Based Methods

Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.

Experimental analysis of optimization techniques on the road passenger transportation problem

Analyzing the state of the art in a given field in order to tackle a new problem is always a mandatory task. Literature provides surveys based on summaries of previous studies, which are often based on theoretical descriptions of the methods. An engineer, however, requires some evidence from experimental evaluations in order to make the appropriate decision when selecting a technique for a problem. This is what we have done in this paper: experimentally analyzed a set of representative state-of-the-art techniques in the problem we are dealing with, namely, the road passenger transportation problem. This is an optimization problem in which drivers should be assigned to transport services, fulfilling some constraints and minimizing some function cost. The experimental results have provided us with good knowledge of the properties of several methods, such as modeling expressiveness, anytime behavior, computational time, memory requirements, parameters, and free downloadable tools. Based on our experience, we are able to choose a technique to solve our problem. We hope that this analysis is also helpful for other engineers facing a similar problem