Role and regulatory mechanisms of heat shock factor 2

Protein homeostasis is essential for cells to prosper and survive. Various forms of stress, such as elevated temperatures, oxidative stress, heavy metals or bacterial infections cause protein damage, which might lead to improper folding and formation of toxic protein aggregates. Protein aggregation is associated with serious pathological conditions such as Alzheimer’s and Huntington’s disease. The heat shock response is a defense mechanism that protects the cell against protein-damaging stress. Its ancient origin and high conservation among eukaryotes suggest that the response is crucial for survival. The main regulator of the heat shock response is the transcription factor heat shock factor 1 (HSF1), which induces transcription of genes encoding protective molecular chaperones. In vertebrates, a family of four HSFs exists (HSF1-4), with versatile functions not only in coping with acute stress, but also in development, longevity and cancer. Thus, knowledge of the HSFs will aid in our understanding on how cells survive suboptimal circumstances, but will also provide insights into normal physiological processes as well as diseaseassociated conditions. In this study, the function and regulation of HSF2 have been investigated. Earlier gene inactivation experiments in mice have revealed roles for HSF2 in development, particularly in corticogenesis and spermatogenesis. Here, we demonstrate that HSF2 holds a role also in the heat shock response and influences stress-induced expression of heat shock proteins. Intriguingly, DNA-binding activity of HSF2 upon stress was dependent on the presence of intact HSF1, suggesting functional interplay between HSF1 and HSF2. The underlying mechanism for this phenomenon could be configuration of heterotrimers between the two factors, a possibility that was experimentally verified. By changing the levels of HSF2, the expression of HSF1-HSF2 heterotrimer target genes was altered, implementing HSF2 as a modulator of HSF-mediated transcription. The results further indicate that HSF2 activity is dependent on its concentration, which led us to ask the question of how accurate HSF2 levels are achieved. Using mouse spermatogenesis as a model system, HSF2 was found to be under direct control of miR-18, a miRNA belonging to the miR-17~92 cluster/Oncomir-1 and whose physiological function had remained unclear. Investigations on spermatogenesis are severely hampered by the lack of cell systems that would mimic the complex differentiation processes that constitute male germ cell development. Therefore, to verify that HSF2 is regulated by miR-18 in spermatogenesis, a novel method named T-GIST (Transfection of Germ cells in Intact Seminiferous Tubules) was developed. Employing this method, the functional consequences of miR-18-mediated regulation in vivo were demonstrated; inhibition of miR- 18 led to increased expression of HSF2 and altered the expression of HSF2 target genes Ssty2 and Speer4a. Consequently, the results link miR-18 to HSF2-mediated processes such as germ cell maturation and quality control and provide miR-18 with a physiological role in gene expression during spermatogenesis.Taken together, this study presents compelling evidence that HSF2 is a transcriptional regulator in the heat shock response and establishes the concept of physical interplay between HSF2 and HSF1 and functional consequences thereof. This is also the first study describing miRNA-mediated regulation of an HSF.

Recovery and refining of manganese as by-product from hydrometallurgical processes

The consumption of manganese is increasing, but huge amounts of manganese still end up in waste in hydrometallurgical processes. The recovery of manganese from multi-metal solutions at low concentrations may not be economical. In addition, poor iron control typically prevents the production of high purity manganese. Separation of iron from manganese can be done with chemical precipitation or solvent extraction methods. Combined carbonate precipitation with air oxidation is a feasible method to separate iron and manganese due to the fast kinetics, good controllability and economical reagents. In addition the leaching of manganese carbonate is easier and less acid consuming than that of hydroxide or sulfide precipitates. Selective iron removal with great efficiency from MnSO4 solution is achieved by combined oxygen or air oxidation and CaCO3 precipitation at pH > 5.8 and at a redox potential of > 200 mV. In order to avoid gypsum formation, soda ash should be used instead of limestone. In such case, however, extra attention needs to be paid on the reagents mole ratios in order to avoid manganese coprecipitation. After iron removal, pure MnSO4 solution was obtained by solvent extraction using organophosphorus reagents, di-(2-ethylhexyl)phosphoric acid (D2EHPA) and bis(2,4,4- trimethylpentyl)phosphinic acid (CYANEX 272). The Mn/Ca and Mn/Mg selectivities can be increased by decreasing the temperature from the commonly used temperatures (40 –60oC) to 5oC. The extraction order of D2EHPA (Ca before Mn) at low temperature remains unchanged but the lowering of temperature causes an increase in viscosity and slower phase separation. Of these regents, CYANEX 272 is selective for Mn over Ca and, therefore, it would be the better choice if there is Ca present in solution. A three-stage Mn extraction followed by a two-stage scrubbing and two-stage sulfuric acid stripping is an effective method of producing a very pure MnSO4 intermediate solution for further processing. From the intermediate MnSO4 some special Mn- products for ion exchange applications were synthesized and studied. Three types of octahedrally coordinated manganese oxide materials as an alternative final product for manganese were chosen for synthesis: layer structured Nabirnessite, tunnel structured Mg-todorokite and K-kryptomelane. As an alternative source of pure MnSO4 intermediate, kryptomelane was synthesized by using a synthetic hydrometallurgical tailings. The results show that the studied OMS materials adsorb selectively Cu, Ni, Cd and K in the presence of Ca and Mg. It was also found that the exchange rates were reasonably high due to the small particle dimensions. Materials are stable in the studied conditions and their maximum Cu uptake capacity was 1.3 mmol/g. Competitive uptake of metals and acid was studied using equilibrium, batch kinetic and fixed-bed measurements. The experimental data was correlated with a dynamic model, which also accounts for the dissolution of the framework manganese. Manganese oxide micro-crystals were also bound onto silica to prepare a composite material having a particle size large enough to be used in column separation experiments. The MnOx/SiO2 ratio was found to affect significantly the properties of the composite. The higher the ratio, the lower is the specific surface area, the pore volume and the pore size. On the other hand, higher amount of silica binder gives composites better mechanical properties. Birnesite and todorokite can be aggregated successfully with colloidal silica at pH 4 and with MnO2/SiO2 weight ratio of 0.7. The best gelation and drying temperature was 110oC and sufficiently strong composites were obtained by additional heat-treatment at 250oC for 2 h. The results show that silica–supported MnO2 materials can be utilized to separate copper from nickel and cadmium. The behavior of the composites can be explained reasonably well with the presented model and the parameters estimated from the data of the unsupported oxides. The metal uptake capacities of the prepared materials were quite small. For example, the final copper loading was 0.14 mmol/gMnO2. According to the results the special MnO2 materials are potential for a specific environmental application to uptake harmful metal ions.

Impersonal trust within the organization: what, how and why?

It has been shown in organizational settings that trust is a crucial factor in different kinds of outcomes, and consequently, building employee trust in the employer is a goal for all kinds of organizations. Although it is recognized that trust in organizations operates on multiple levels, at present there is no clear consensus on the concept of trust within the organization. One can have trust in particular people (i.e. interpersonal trust) or in organized systems (i.e. impersonal trust). Until recently organizational trust has been treated mainly as an interpersonal phenomenon. However, the interpersonal approach is limited. Scholars studying organizational trust have thus far focused only on specific dimensions of impersonal trust, and none have taken a comprehensive approach. The first objective in this study was to develop a construct and a scale encompassing the impersonal element of organizational trust. The second objective was to examine the effects of various HRM practices on the impersonal dimensions of organizational trust. Moreover, although the “black box” model of HRM is widely studied, there have been only a few attempts to unlock the box. Previous studies on the HRM-performance link refer to trust, and this work contributes to the literature in considering trust an impersonal issue in the relationship between HRM, trust, and performance. The third objective was thus to clarify the role of impersonal trust in the relationship between HRM and performance. The study is divided into two parts comprising the Introduction and four separate publications. Each publication addresses a distinct sub-question, whereas the Introduction discusses the overall results in the light of the individual sub-questions. The study makes two major contributions to the research on trust. Firstly, it offers a framework describing the construct of impersonal trust, which to date has not been clearly articulated in the research on organizational trust. Secondly, a comprehensive, psychometrically sound, operationally valid scale for measuring impersonal trust was developed. In addition, the study makes an empirical contribution to the research on strategic HRM. First, it shows that HRM practices affect impersonal trust and the contribution is to consider the HRM-trust link in terms of impersonal organizational trust. It is shown that each of the six HRM practices in focus is connected to impersonal trust. A further contribution lies in unlocking the black box. The study explores the impersonal element of organizational trust and its mediating role between HRM practices and performance. The result is the identification of the path by which HRM contributes to performance through the mediator of impersonal trust. It is shown that the effect on performance of HRM designed specifically to enhance employees’ impersonal trust in the organization is positive.

Solving Challenging Real-World Scheduling Problems

This work contains a series of studies on the optimization of three real-world scheduling problems, school timetabling, sports scheduling and staff scheduling. These challenging problems are solved to customer satisfaction using the proposed PEAST algorithm. The customer satisfaction refers to the fact that implementations of the algorithm are in industry use. The PEAST algorithm is a product of long-term research and development. The first version of it was introduced in 1998. This thesis is a result of a five-year development of the algorithm. One of the most valuable characteristics of the algorithm has proven to be the ability to solve a wide range of scheduling problems. It is likely that it can be tuned to tackle also a range of other combinatorial problems. The algorithm uses features from numerous different metaheuristics which is the main reason for its success. In addition, the implementation of the algorithm is fast enough for real-world use.

Notes on Emerging Technologies

This dissertation considers the impact of technology foresight in innovation within the context of a technology driven development. The main hypothesis made was that by using different methods of foresight in the industry level significant value could be created. The question was approached through a case study in portable fuel cell technology. The theoretical background of the study draws from Innovation, Product Development, Management of Technology, and Technology Foresight. The connection within the topics is made by analyzing foresight, not in a policy view as often done in Europe, but in a micro-level. Focusing mostly on how a technology driven development scenario could be analyzed. The study is based on a bibliometric, extrapolation and patent analysis within the context of a case study. In addition, a large two-year Delphi study was conducted. The study was finalized with a scenario work on the future possibilities of the case study technology. Original publications also consider several methodological issues. In the context of the case study, the study questions the practicality of establishing a portable fuel cell technology in Finland showing several impractical assumptions has been made. In a more conceptual level, the study makes notions on two underlying factors: policy-push technologies and growth of data. Policy-push questions in which level a policy effort towards a single technology is practical. The European foresight effort is more directed towards policy decisions in contrast to US foresight, which is to some extent corporate driven. Although the policy-based foresight has produced significant results in the European context, policy led efforts towards a single technology are challenging. Growth of data argues on the challenges produced by the large-scale application of quantitative measures of foresight. Bibliometric studies and trend extrapolations have been taken advantage of the increasing number of databases made available, and used these as the basis for forecasts. However, the relationship with actual development and quantitative evidence is still unproven.

Broadband excitation in the system identification of active magnetic bearing rotor systems

One of the targets of the climate and energy package of the European Union is to increase the energy efficiency in order to achieve a 20 percent reduction in primary energy use compared with the projected level by 2020. The energy efficiency can be improved for example by increasing the rotational speed of large electrical drives, because this enables the elimination of gearboxes leading to a compact design with lower losses. The rotational speeds of traditional bearings, such as roller bearings, are limited by mechanical friction. Active magnetic bearings (AMBs), on the other hand, allow very high rotational speeds. Consequently, their use in large medium- and high-speed machines has rapidly increased. An active magnetic bearing rotor system is an inherently unstable, nonlinear multiple-input, multiple-output system. Model-based controller design of AMBs requires an accurate system model. Finite element modeling (FEM) together with the experimental modal analysis provides a very accurate model for the rotor, and a linearized model of the magneticactuators has proven to work well in normal conditions. However, the overall system may suffer from unmodeled dynamics, such as dynamics of foundation or shrink fits. This dynamics can be modeled by system identification. System identification can also be used for on-line diagnostics. In this study, broadband excitation signals are adopted to the identification of an active magnetic bearing rotor system. The broadband excitation enables faster frequency response function measurements when compared with the widely used stepped sine and swept sine excitations. Different broadband excitations are reviewed, and the random phase multisine excitation is chosen for further study. The measurement times using the multisine excitation and the stepped sine excitation are compared. An excitation signal design with an analysis of the harmonics produced by the nonlinear system is presented. The suitability of different frequency response function estimators for an AMB rotor system are also compared. Additionally, analytical modeling of an AMB rotor system, obtaining a parametric model from the nonparametric frequency response functions, and model updating are discussed in brief, as they are key elements in the modeling for a control design. Theoretical methods are tested with a laboratory test rig. The results conclude that an appropriately designed random phase multisine excitation is suitable for the identification of AMB rotor systems.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

Software Test Process Development

In this thesis, the components important for testing work and organisational test process are identified and analysed. This work focuses on the testing activities in reallife software organisations, identifying the important test process components, observing testing work in practice, and analysing how the organisational test process could be developed. Software professionals from 14 different software organisations were interviewed to collect data on organisational test process and testing‐related factors. Moreover, additional data on organisational aspects was collected with a survey conducted on 31 organisations. This data was further analysed with the Grounded Theory method to identify the important test process components, and to observe how real‐life test organisations develop their testing activities. The results indicate that the test management at the project level is an important factor; the organisations do have sufficient test resources available, but they are not necessarily applied efficiently. In addition, organisations in general are reactive; they develop their process mainly to correct problems, not to enhance their efficiency or output quality. The results of this study allows organisations to have a better understanding of the test processes, and develop towards better practices and a culture of preventing problems, not reacting to them.

Making Sense of Shared Leadership. A case study of leadership processes and practices without formal leadership structure in the team context

Leadership is essential for the effectiveness of the teams and organizations they are part of. The challenges facing organizations today require an exhaustive review of the strategic role of leadership. In this context, it is necessary to explore new types of leadership capable of providing an effective response to new needs. The presentday situations, characterized by complexity and ambiguity, make it difficult for an external leader to perform all leadership functions successfully. Likewise, knowledge-based work requires providing professional groups with sufficient autonomy to perform leadership functions. This study focuses on shared leadership in the team context. Shared leadership is seen as an emergent team property resulting from the distribution of leadership influence across multiple team members. Shared leadership entails sharing power and influence broadly among the team members rather than centralizing it in the hands of a single individual who acts in the clear role of a leader. By identifying the team itself as a key source of influence, this study points to the relational nature of leadership as a social construct where leadership is seen as social process of relating processes that are co-constructed by several team members. Based on recent theoretical developments concerned with relational, practice-based and constructionist approaches to the study of leadership processes, this thesis proposes the study of leadership interactions, working processes and practices to focus on the construction of direction, alignment and commitment. During the research process, critical events, activities, working processes and practices of a case team have been examined and analyzed with the grounded theory –approach in the terms of shared leadership. There are a variety of components to this complex process and a multitude of factors that may influence the development of shared leadership. The study suggests that the development process of shared leadership is a common sense -making process and consists of four overlapping dimensions (individual, social, structural, and developmental) to work with as a team. For shared leadership to emerge, the members of the team must offer leadership services, and the team as a whole must be willing to rely on leadership by multiple team members. For these individual and collective behaviors to occur, the team members must believe that offering influence to and accepting it from fellow team members are welcome and constructive actions. Leadership emerges when people with differing world views use dialogue and collaborative learning to create spaces where a shared common purpose can be achieved while a diversity of perspectives is preserved and valued. This study also suggests that this process can be supported by different kinds of meaning-making and process tools. Leadership, then, does not reside in a person or in a role, but in the social system. The built framework integrates the different dimensions of shared leadership and describes their relationships. This way, the findings of this study can be seen as a contribution to the understanding of what constitutes essential aspects of shared leadership in the team context that can be of theoretical value in terms of advancing the adoption and development process of shared leadership. In the real world, teams and organizations can create conditions to foster and facilitate the process. We should encourage leaders and team members to approach leadership as a collective effort that the team can be prepared for, so that the response is rapid and efficient.

From Fluid Dynamics to Human Psychology.What Drives Financial Markets Towards Extreme Events

For decades researchers have been trying to build models that would help understand price performance in financial markets and, therefore, to be able to forecast future prices. However, any econometric approaches have notoriously failed in predicting extreme events in markets. At the end of 20th century, market specialists started to admit that the reasons for economy meltdowns may originate as much in rational actions of traders as in human psychology. The latter forces have been described as trading biases, also known as animal spirits. This study aims at expressing in mathematical form some of the basic trading biases as well as the idea of market momentum and, therefore, reconstructing the dynamics of prices in financial markets. It is proposed through a novel family of models originating in population and fluid dynamics, applied to an electricity spot price time series. The main goal of this work is to investigate via numerical solutions how well theequations succeed in reproducing the real market time series properties, especially those that seemingly contradict standard assumptions of neoclassical economic theory, in particular the Efficient Market Hypothesis. The results show that the proposed model is able to generate price realizations that closely reproduce the behaviour and statistics of the original electricity spot price. That is achieved in all price levels, from small and medium-range variations to price spikes. The latter were generated from price dynamics and market momentum, without superimposing jump processes in the model. In the light of the presented results, it seems that the latest assumptions about human psychology and market momentum ruling market dynamics may be true. Therefore, other commodity markets should be analyzed with this model as well.

Modeling of electrolyte sorption – from phase equilibria to dynamic separation systems

In this thesis, general approach is devised to model electrolyte sorption from aqueous solutions on solid materials. Electrolyte sorption is often considered as unwanted phenomenon in ion exchange and its potential as an independent separation method has not been fully explored. The solid sorbents studied here are porous and non-porous organic or inorganic materials with or without specific functional groups attached on the solid matrix. Accordingly, the sorption mechanisms include physical adsorption, chemisorption on the functional groups and partition restricted by electrostatic or steric factors. The model is tested in four Cases Studies dealing with chelating adsorption of transition metal mixtures, physical adsorption of metal and metalloid complexes from chloride solutions, size exclusion of electrolytes in nano-porous materials and electrolyte exclusion of electrolyte/non-electrolyte mixtures. The model parameters are estimated using experimental data from equilibrium and batch kinetic measurements, and they are used to simulate actual single-column fixed-bed separations. Phase equilibrium between the solution and solid phases is described using thermodynamic Gibbs-Donnan model and various adsorption models depending on the properties of the sorbent. The 3-dimensional thermodynamic approach is used for volume sorption in gel-type ion exchangers and in nano-porous adsorbents, and satisfactory correlation is obtained provided that both mixing and exclusion effects are adequately taken into account. 2-Dimensional surface adsorption models are successfully applied to physical adsorption of complex species and to chelating adsorption of transition metal salts. In the latter case, comparison is also made with complex formation models. Results of the mass transport studies show that uptake rates even in a competitive high-affinity system can be described by constant diffusion coefficients, when the adsorbent structure and the phase equilibrium conditions are adequately included in the model. Furthermore, a simplified solution based on the linear driving force approximation and the shrinking-core model is developed for very non-linear adsorption systems. In each Case Study, the actual separation is carried out batch-wise in fixed-beds and the experimental data are simulated/correlated using the parameters derived from equilibrium and kinetic data. Good agreement between the calculated and experimental break-through curves is usually obtained indicating that the proposed approach is useful in systems, which at first sight are very different. For example, the important improvement in copper separation from concentrated zinc sulfate solution at elevated temperatures can be correctly predicted by the model. In some cases, however, re-adjustment of model parameters is needed due to e.g. high solution viscosity.

Modelling of combustion and sorbent reactions in three-dimensional flow environment of a circulating fluidized bed furnace

This thesis presents a three-dimensional, semi-empirical, steady state model for simulating the combustion, gasification, and formation of emissions in circulating fluidized bed (CFB) processes. In a large-scale CFB furnace, the local feeding of fuel, air, and other input materials, as well as the limited mixing rate of different reactants produce inhomogeneous process conditions. To simulate the real conditions, the furnace should be modelled three-dimensionally or the three-dimensional effects should be taken into account. The only available methods for simulating the large CFB furnaces three-dimensionally are semi-empirical models, which apply a relatively coarse calculation mesh and a combination of fundamental conservation equations, theoretical models and empirical correlations. The number of such models is extremely small. The main objective of this work was to achieve a model which can be applied to calculating industrial scale CFB boilers and which can simulate all the essential sub-phenomena: fluid dynamics, reactions, the attrition of particles, and heat transfer. The core of the work was to develop the model frame and the required sub-models for determining the combustion and sorbent reactions. The objective was reached, and the developed model was successfully used for studying various industrial scale CFB boilers combusting different types of fuel. The model for sorbent reactions, which includes the main reactions for calcitic limestones, was applied for studying the new possible phenomena occurring in the oxygen-fired combustion. The presented combustion and sorbent models and principles can be utilized in other model approaches as well, including other empirical and semi-empirical model approaches, and CFD based simulations. The main achievement is the overall model frame which can be utilized for the further development and testing of new sub-models and theories, and for concentrating the knowledge gathered from the experimental work carried out at bench scale, pilot scale and industrial scale apparatus, and from the computational work performed by other modelling methods.

GAMS MINLP Solver comparisons and some improvements to the AlphaECP algorithm

I doktorsavhandlingen undersöks förmågan att lösa hos ett antal lösare för optimeringsproblem och ett antal svårigheter med att göra en rättvis lösarjämförelse avslöjas. Dessutom framläggs några förbättringar som utförts på en av lösarna som heter GAMS/AlphaECP. Optimering innebär, i det här sammanhanget, att finna den bästa möjliga lösningen på ett problem. Den undersökta klassen av problem kan karaktäriseras som svårlöst och förekommer inom ett flertal industriområden. Målet har varit att undersöka om det finns en lösare som är universellt snabbare och hittar lösningar med högre kvalitet än någon av de andra lösarna. Det kommersiella optimeringssystemet GAMS (General Algebraic Modeling System) och omfattande problembibliotek har använts för att jämföra lösare. Förbättringarna som presenterats har utförts på GAMS/AlphaECP lösaren som baserar sig på skärplansmetoden Extended Cutting Plane (ECP). ECP-metoden har utvecklats främst av professor Tapio Westerlund på Anläggnings- och systemteknik vid Åbo Akademi.