Heavy-light mesons on a lattice

Several excited states of Ds and Bs mesons have been discovered in the last six years: BaBar, Cleo and Belle discovered the very narrow states D(s0)*(2317)+- and D(s1)(2460)+- in 2003, and CDF and DO Collaborations reported the observation of two narrow Bs resonances, B(s1)(5830)0 and B*(s2)(5840)0 in 2007. To keep up with experiment, meson excited states should be studied from the theoretical aspect as well. The theory that describes the interaction between quarks and gluons is quantum chromodynamics (QCD). In this thesis the properties of the meson states are studied using the discretized version of the theory - lattice QCD. This allows us to perform QCD calculations from first principles, and "measure" not just energies but also the radial distributions of the states on the lattice. This gives valuable theoretical information on the excited states, as we can extract the energy spectrum of a static-light meson up to D wave states (states with orbital angular momentum L=2). We are thus able to predict where some of the excited meson states should lie. We also pay special attention to the order of the states, to detect possible inverted spin multiplets in the meson spectrum, as predicted by H. Schnitzer in 1978. This inversion is connected to the confining potential of the strong interaction. The lattice simulations can also help us understand the strong interaction better, as the lattice data can be treated as "experimental" data and used in testing potential models. In this thesis an attempt is made to explain the energies and radial distributions in terms of a potential model based on a one-body Dirac equation. The aim is to get more information about the nature of the confining potential, as well as to test how well the one-gluon exchange potential explains the short range part of the interaction.

Carbon dioxide and methane exchange between a boreal pristine lake and the atmosphere

Lakes serve as sites for terrestrially fixed carbon to be remineralized and transferred back to the atmosphere. Their role in regional carbon cycling is especially important in the Boreal Zone, where lakes can cover up to 20% of the land area. Boreal lakes are often characterized by the presence of a brown water colour, which implies high levels of dissolved organic carbon from the surrounding terrestrial ecosystem, but the load of inorganic carbon from the catchment is largely unknown. Organic carbon is transformed to methane (CH4) and carbon dioxide (CO2) in biological processes that result in lake water gas concentrations that increase above atmospheric equilibrium, thus making boreal lakes as sources of these important greenhouse gases. However, flux estimates are often based on sporadic sampling and modelling and actual flux measurements are scarce. Thus, the detailed temporal flux dynamics of greenhouse gases are still largely unknown. ----- One aim here was to reveal the natural dynamics of CH4 and CO2 concentrations and fluxes in a small boreal lake. The other aim was to test the applicability of a measuring technique for CO2 flux, i.e. the eddy covariance (EC) technique, and a computational method for estimation of primary production and community respiration, both commonly used in terrestrial research, in this lake. Continuous surface water CO2 concentration measurements, also needed in free-water applications to estimate primary production and community respiration, were used over two open water periods in a study of CO2 concentration dynamics. Traditional methods were also used to measure gas concentration and fluxes. The study lake, Valkea-Kotinen, is a small, humic, headwater lake within an old-growth forest catchment with no local anthropogenic disturbance and thus possible changes in gas dynamics reflect the natural variability in lake ecosystems. CH4 accumulated under the ice and in the hypolimnion during summer stratification. The surface water CH4 concentration was always above atmospheric equilibrium and thus the lake was a continuous source of CH4 to the atmosphere. However, the annual CH4 fluxes were small, i.e. 0.11 mol m-2 yr-1, and the timing of fluxes differed from that of other published estimates. The highest fluxes are usually measured in spring after ice melt but in Lake Valkea-Kotinen CH4 was effectively oxidised in spring and highest effluxes occurred in autumn after summer stratification period. CO2 also accumulated under the ice and the hypolimnetic CO2 concentration increased steadily during stratification period. The surface water CO2 concentration was highest in spring and in autumn, whereas during the stable stratification it was sometimes under atmospheric equilibrium. It showed diel, daily and seasonal variation; the diel cycle was clearly driven by light and thus reflected the metabolism of the lacustrine ecosystem. However, the diel cycle was sometimes blurred by injection of hypolimnetic water rich in CO2 and the surface water CO2 concentration was thus controlled by stratification dynamics. The highest CO2 fluxes were measured in spring, autumn and during those hypolimnetic injections causing bursts of CO2 comparable with the spring and autumn fluxes. The annual fluxes averaged 77 (±11 SD) g C m-2 yr-1. In estimating the importance of the lake in recycling terrestrial carbon, the flux was normalized to the catchment area and this normalized flux was compared with net ecosystem production estimates of -50 to 200 g C m-2 yr-1 from unmanaged forests in corresponding temperature and precipitation regimes in the literature. Within this range the flux of Lake Valkea-Kotinen yielded from the increase in source of the surrounding forest by 20% to decrease in sink by 5%. The free water approach gave primary production and community respiration estimates of 5- and 16-fold, respectively, compared with traditional bottle incubations during a 5-day testing period in autumn. The results are in parallel with findings in the literature. Both methods adopted from the terrestrial community also proved useful in lake studies. A large percentage of the EC data was rejected, due to the unfulfilled prerequisites of the method. However, the amount of data accepted remained large compared with what would be feasible with traditional methods. Use of the EC method revealed underestimation of the widely used gas exchange model and suggests simultaneous measurements of actual turbulence at the water surface with comparison of the different gas flux methods to revise the parameterization of the gas transfer velocity used in the models.

Modelling boreal forest CO2 exchange and seasonality

Man-induced climate change has raised the need to predict the future climate and its feedback to vegetation. These are studied with global climate models; to ensure the reliability of these predictions, it is important to have a biosphere description that is based upon the latest scientific knowledge. This work concentrates on the modelling of the CO2 exchange of the boreal coniferous forest, studying also the factors controlling its growing season and how these can be used in modelling. In addition, the modelling of CO2 gas exchange at several scales was studied. A canopy-level CO2 gas exchange model was developed based on the biochemical photosynthesis model. This model was first parameterized using CO2 exchange data obtained by eddy covariance (EC) measurements from a Scots pine forest at Sodankylä. The results were compared with a semi-empirical model that was also parameterized using EC measurements. Both of the models gave satisfactory results. The biochemical canopy-level model was further parameterized at three other coniferous forest sites located in Finland and Sweden. At all the sites, the two most important biochemical model parameters showed seasonal behaviour, i.e., their temperature responses changed according to the season. Modelling results were improved when these changeover dates were related to temperature indices. During summer-time the values of the biochemical model parameters were similar at all the four sites. Different control factors for CO2 gas exchange were studied at the four coniferous forests, including how well these factors can be used to predict the initiation and cessation of the CO2 uptake. Temperature indices, atmospheric CO2 concentration, surface albedo and chlorophyll fluorescence (CF) were all found to be useful and have predictive power. In addition, a detailed simulation study of leaf stomata in order to separate physical and biochemical processes was performed. The simulation study brought to light the relative contribution and importance of the physical transport processes. The results of this work can be used in improving CO2 gas exchange models in boreal coniferous forests. The meteorological and biological variables that represent the seasonal cycle were studied, and a method for incorporating this cycle into a biochemical canopy-level model was introduced.

Search for a Fermiophobic Higgs Boson Decaying into Diphotons in p p-bar Collisions at sqrt{s} = 1.96 TeV

A search for a narrow diphoton mass resonance is presented based on data from 3.0 fb^{-1} of integrated luminosity from p-bar p collisions at sqrt{s} = 1.96 TeV collected by the CDF experiment. No evidence of a resonance in the diphoton mass spectrum is observed, and upper limits are set on the cross section times branching fraction of the resonant state as a function of Higgs boson mass. The resulting limits exclude Higgs bosons with masses below 106 GeV at a 95% Bayesian credibility level (C.L.) for one fermiophobic benchmark model.

Search for a Fermiophobic Higgs Boson Decaying into Diphotons in pp̅ Collisions at √s=1.96 TeV

A search for a narrow diphoton mass resonance is presented based on data from 3.0 fb^{-1} of integrated luminosity from p-bar p collisions at sqrt{s} = 1.96 TeV collected by the CDF experiment. No evidence of a resonance in the diphoton mass spectrum is observed, and upper limits are set on the cross section times branching fraction of the resonant state as a function of Higgs boson mass. The resulting limits exclude Higgs bosons with masses below 106 GeV at a 95% Bayesian credibility level (C.L.) for one fermiophobic benchmark model.

UV-induced NOy emissions in gas-exchange chambers enclosing Scots pine shoots: an analysis on their origin and significance

It is essential to have a thorough understanding of the sources and sinks of oxidized nitrogen (NOy) in the atmosphere, since it has a strong influence on the tropospheric chemistry and the eutrophication of ecosystems. One unknown component in the balance of gaseous oxidized nitrogen is vegetation. Plants absorb nitrogenous species from the air via the stomata, but it is not clear whether plants can also emit them at low ambient concentrations. The possible emissions are small and difficult to measure. The aim of this thesis was to analyse an observation made in southern Finland at the SMEAR II station: solar ultraviolet radiation (UV) induced NOy emissions in chambers measuring the gas exchange of Scots pine (Pinus sylvestris L.) shoots. Both measuring and modelling approaches were used in the study. The measurements were performed under noncontrolled field conditions at low ambient NOy concentrations. The chamber blank i.e. artefact NOy emissions from the chamber walls, was dependent on the UV irradiance and increased with time after renewing the Teflon film on chamber surfaces. The contribution of each pine shoot to the total NOy emissions in the chambers was determined by testing whether the emissions decrease when the shoots are removed from their chambers. Emissions did decrease, but only when the chamber interior was exposed to UV radiation. It was concluded that also the pine shoots emit NOy. The possible effects of transpiration on the chamber blank are discussed in the summary part of the thesis, based on previously unpublished data. The possible processes underlying the UV-induced NOy emissions were reviewed. Surface reactions were more likely than metabolic processes. Photolysis of nitrate deposited on the needles may have generated the NOy emissions; the measurements supported this hypothesis. In that case, the emissions apparently would consist mainly of nitrogen dioxide (NO2), nitric oxide (NO) and nitrous acid (HONO). Within studies on NOy exchange of plants, the gases most frequently studied are NO2 and NO (=NOx). In the present work, the implications of the emissions for the NOx exchange of pine were analysed with a model including both NOy emissions and NOy absorption. The model suggested that if the emissions exist, pines can act as an NOx source rather than a sink, even under relatively high ambient concentrations.

Characterization of Ion-Exchange Fibers for Controlled Drug Delivery

Increasing attention has been focused on methods that deliver pharmacologically active compounds (e.g. drugs, peptides and proteins) in a controlled fashion, so that constant, sustained, site-specific or pulsatile action can be attained. Ion-exchange resins have been widely studied in medical and pharmaceutical applications, including controlled drug delivery, leading to commercialisation of some resin based formulations. Ion-exchangers provide an efficient means to adjust and control drug delivery, as the electrostatic interactions enable precise control of the ion-exchange process and, thus, a more uniform and accurate control of drug release compared to systems that are based only on physical interactions. Unlike the resins, only few studies have been reported on ion-exchange fibers in drug delivery. However, the ion-exchange fibers have many advantageous properties compared to the conventional ion-exchange resins, such as more efficient compound loading into and release from the ion-exchanger, easier incorporation of drug-sized compounds, enhanced control of the ion-exchange process, better mechanical, chemical and thermal stability, and good formulation properties, which make the fibers attractive materials for controlled drug delivery systems. In this study, the factors affecting the nature and strength of the binding/loading of drug-sized model compounds into the ion-exchange fibers was evaluated comprehensively and, moreover, the controllability of subsequent drug release/delivery from the fibers was assessed by modifying the conditions of external solutions. Also the feasibility of ion-exchange fibers for simultaneous delivery of two drugs in combination was studied by dual loading. Donnan theory and theoretical modelling were applied to gain mechanistic understanding on these factors. The experimental results imply that incorporation of model compounds into the ion-exchange fibers was attained mainly as a result of ionic bonding, with additional contribution of non-specific interactions. Increasing the ion-exchange capacity of the fiber or decreasing the valence of loaded compounds increased the molar loading, while more efficient release of the compounds was observed consistently at conditions where the valence or concentration of the extracting counter-ion was increased. Donnan theory was capable of fully interpreting the ion-exchange equilibria and the theoretical modelling supported precisely the experimental observations. The physico-chemical characteristics (lipophilicity, hydrogen bonding ability) of the model compounds and the framework of the fibrous ion-exchanger influenced the affinity of the drugs towards the fibers and may, thus, affect both drug loading and release. It was concluded that precisely controlled drug delivery may be tailored for each compound, in particularly, by choosing a suitable ion-exchange fiber and optimizing the delivery system to take into account the external conditions, also when delivering two drugs simultaneously.

Society by Numbers : Studies on Model-Based Explanations in the Social Sciences

The aim of this dissertation is to provide conceptual tools for the social scientist for clarifying, evaluating and comparing explanations of social phenomena based on formal mathematical models. The focus is on relatively simple theoretical models and simulations, not statistical models. These studies apply a theory of explanation according to which explanation is about tracing objective relations of dependence, knowledge of which enables answers to contrastive why and how-questions. This theory is developed further by delineating criteria for evaluating competing explanations and by applying the theory to social scientific modelling practices and to the key concepts of equilibrium and mechanism. The dissertation is comprised of an introductory essay and six published original research articles. The main theses about model-based explanations in the social sciences argued for in the articles are the following. 1) The concept of explanatory power, often used to argue for the superiority of one explanation over another, compasses five dimensions which are partially independent and involve some systematic trade-offs. 2) All equilibrium explanations do not causally explain the obtaining of the end equilibrium state with the multiple possible initial states. Instead, they often constitutively explain the macro property of the system with the micro properties of the parts (together with their organization). 3) There is an important ambivalence in the concept mechanism used in many model-based explanations and this difference corresponds to a difference between two alternative research heuristics. 4) Whether unrealistic assumptions in a model (such as a rational choice model) are detrimental to an explanation provided by the model depends on whether the representation of the explanatory dependency in the model is itself dependent on the particular unrealistic assumptions. Thus evaluating whether a literally false assumption in a model is problematic requires specifying exactly what is supposed to be explained and by what. 5) The question of whether an explanatory relationship depends on particular false assumptions can be explored with the process of derivational robustness analysis and the importance of robustness analysis accounts for some of the puzzling features of the tradition of model-building in economics. 6) The fact that economists have been relatively reluctant to use true agent-based simulations to formulate explanations can partially be explained by the specific ideal of scientific understanding implicit in the practise of orthodox economics.

Zebrafish as a model of Parkinson's disease

Parkinson’s disease (PD) is the second most common neurodegenerative disease among the elderly. Its etiology is unknown and no disease-modifying drugs are available. Thus, more information concerning its pathogenesis is needed. Among other genes, mutated PTEN-induced kinase 1 (PINK1) has been linked to early-onset and sporadic PD, but its mode of action is poorly understood. Most animal models of PD are based on the use of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). MPTP is metabolized to MPP+ by monoamine oxidase B (MAO B) and causes cell death of dopaminergic neurons in the substantia nigra in mammals. Zebrafish has been a widely used model organism in developmental biology, but is now emerging as a model for human diseases due to its ideal combination of properties. Zebrafish are inexpensive and easy to maintain, develop rapidly, breed in large quantities producing transparent embryos, and are readily manipulated by various methods, particularly genetic ones. In addition, zebrafish are vertebrate animals and results derived from zebrafish may be more applicable to mammals than results from invertebrate genetic models such as Drosophila melanogaster and Caenorhabditis elegans. However, the similarity cannot be taken for granted. The aim of this study was to establish and test a PD model using larval zebrafish. The developing monoaminergic neuronal systems of larval zebrafish were investigated. We identified and classified 17 catecholaminergic and 9 serotonergic neuron populations in the zebrafish brain. A 3-dimensional atlas was created to facilitate future research. Only one gene encoding MAO was found in the zebrafish genome. Zebrafish MAO showed MAO A-type substrate specificity, but non-A-non-B inhibitor specificity. Distribution of MAO in larval and adult zebrafish brains was both diffuse and distinctly cellular. Inhibition of MAO during larval development led to markedly elevated 5-hydroxytryptamine (serotonin, 5-HT) levels, which decreased the locomotion of the fish. MPTP exposure caused a transient loss of cells in specific aminergic cell populations and decreased locomotion. MPTP-induced changes could be rescued by the MAO B inhibitor deprenyl, suggesting a role for MAO in MPTP toxicity. MPP+ affected only one catecholaminergic cell population; thus, the action of MPP+ was more selective than that of MPTP. The zebrafish PINK1 gene was cloned in zebrafish, and morpholino oligonucleotides were used to suppress its expression in larval zebrafish. The functional domains and expression pattern of zebrafish PINK1 resembled those of other vertebrates, suggesting that zebrafish is a feasible model for studying PINK1. Translation inhibition resulted in cell loss of the same catecholaminergic cell populations as MPTP and MPP+. Inactivation of PINK1 sensitized larval zebrafish to subefficacious doses of MPTP, causing a decrease in locomotion and cell loss in one dopaminergic cell population. Zebrafish appears to be a feasible model for studying PD, since its aminergic systems, mode of action of MPTP, and functions of PINK1 resemble those of mammalians. However, the functions of zebrafish MAO differ from the two forms of MAO found in mammals. Future studies using zebrafish PD models should utilize the advantages specific to zebrafish, such as the ability to execute large-scale genetic or drug screens.

Dietary modulation of β-catenin signalling in an experimental model of colon cancer

Colorectal cancer is among the major cancers and one of the leading causes of cancer-related deaths in Western societies. Its occurrence is strongly affected by environmental factors such as diet. Thus, for preventative strategies it is vitally important to understand the mechanisms that stimulate adenoma growth and development towards accelerated malignancy or, in contrast, attenuate them to remain in quiescence for periods as long as decades. The main objective of this study was to investigate whether diet is able to modulate β-catenin signalling related to the promotion or prevention of intestinal tumourigenesis in an animal model of colon cancer, the Min/+ mouse. A series of dietary experiments with Min/+ mice were performed where fructo-oligosaccharide inulin was used for tumour promotion and four berries, bilberry (Vaccinium myrtillus), lingonberry (Vaccinium vitis-idaea), cloudberry (Rubus chamaemorus) and white currant (Ribes x pallidum), were used for tumour prevention. The adenomas (Apc-/-) and surrounding normal-appearing mucosa (Apc+/-) were investigated separately due to their mutational and functional differences. Tumour promotive and preventive diets had opposite effects on β-catenin signalling in the adenomas that was related to the different adenoma growth effects of dietary inulin and berries. The levels of nuclear β-catenin and cyclin D1 combined with size of the adenomas in the treatment groups suggests that diets induced differences in the cancerous process. Adenomas progressing to malignant carcinomas are most likely found in the sub-groups having the highest levels of β-catenin. On the other hand, adenomas staying quiescent for a long period of time are most probably found in the cloudberry or white currant diet groups. The levels of membranous E-cadherin and β-catenin increased as the adenomas in the inulin diet group grew, which could be a result of the overall increase in the protein levels of the cell. Therefore, the increasing levels of membranous β-catenin in Min/+ mice adenomas would be undesirable, due to the simultaneous increase in oncogenic nuclear β-catenin. We propose that the decreased amount of membranous β-catenin in benign adenomas of berry groups also means a decrease in the nuclear pool of β-catenin. Tumour promotion, but not the tumour prevention, influenced β-catenin signalling already in the normal appearing mucosa. Inulin-induced tumour promotion was related to β-catenin signalling in Min/+ mice, and in WT mice changes were also visible. The preventative effects of berries in the initiation phase were not mediated by β-catenin signalling. Our results suggest that, in addition to the number, size, and growth rate of adenomatous polyps, the signalling pattern of the adenomas should be considered when evaluating preventative dietary strategies.

Topological Quantum Computation - An Analysis of an Anyon Model Based on Quantum Double Symmetries

There exists various suggestions for building a functional and a fault-tolerant large-scale quantum computer. Topological quantum computation is a more exotic suggestion, which makes use of the properties of quasiparticles manifest only in certain two-dimensional systems. These so called anyons exhibit topological degrees of freedom, which, in principle, can be used to execute quantum computation with intrinsic fault-tolerance. This feature is the main incentive to study topological quantum computation. The objective of this thesis is to provide an accessible introduction to the theory. In this thesis one has considered the theory of anyons arising in two-dimensional quantum mechanical systems, which are described by gauge theories based on so called quantum double symmetries. The quasiparticles are shown to exhibit interactions and carry quantum numbers, which are both of topological nature. Particularly, it is found that the addition of the quantum numbers is not unique, but that the fusion of the quasiparticles is described by a non-trivial fusion algebra. It is discussed how this property can be used to encode quantum information in a manner which is intrinsically protected from decoherence and how one could, in principle, perform quantum computation by braiding the quasiparticles. As an example of the presented general discussion, the particle spectrum and the fusion algebra of an anyon model based on the gauge group S_3 are explicitly derived. The fusion algebra is found to branch into multiple proper subalgebras and the simplest one of them is chosen as a model for an illustrative demonstration. The different steps of a topological quantum computation are outlined and the computational power of the model is assessed. It turns out that the chosen model is not universal for quantum computation. However, because the objective was a demonstration of the theory with explicit calculations, none of the other more complicated fusion subalgebras were considered. Studying their applicability for quantum computation could be a topic of further research.

Synthesis, Reactivity and Biological Activity of 17β-HSD1 Inhibitors Based on a Thieno[2,3-d]pryrimidin-4(3H)-one Core

Breast cancer is the most common cancer in women in Western countries. In the early stages of development most breast cancers are hormone-dependent, and estrogens, especially estradiol, have a pivotal role in their development and progression. One approach to the treatment of hormone-dependent breast cancers is to block the formation of the active estrogens by inhibiting the action of the steroid metabolising enzymes. 17beta-Hydroxysteroid dehydrogenase type 1 (17beta-HSD1) is a key enzyme in the biosynthesis of estradiol, the most potent female sex hormone. The 17beta-HSD1 enzyme catalyses the final step and converts estrone into the biologically active estradiol. Blocking 17beta-HSD1 activity with a specific enzyme inhibitor could provide a means to reduce circulating and tumour estradiol levels and thus promote tumour regression. In recent years 17beta-HSD1 has been recognised as an important drug target. Some inhibitors of 17beta-HSD1 have been reported, however, there are no inhibitors on the market nor have clinical trials been announced. The majority of known 17beta-HSD1 inhibitors are based on steroidal structures, while relatively little has been reported on non-steroidal inhibitors. As compared with 17beta-HSD1 inhibitors based on steroidal structures, non-steroidal compounds could have advantages of synthetic accessibility, drug-likeness, selectivity and non-estrogenicity. This study describes the synthesis of large group of novel 17beta-HSD1 inhibitors based on a non-steroidal thieno[2,3-d]pyrimidin-4(3H)-one core. An efficient synthesis route was developed for the lead compound and subsequently employed in the synthesis of thieno[2,3-d]pyrimidin-4(3H)-one based molecule library. The biological activities and binding of these inhibitors to 17beta-HSD1 and, finally, the quantitative structure activity relationship (QSAR) model are also reported. In this study, several potent and selective 17beta-HSD1 inhibitors without estrogenic activity were identified. This establishment of a novel class of inhibitors is a progressive achievement in 17beta-HSD1 inhibitor development. Furthermore, the 3D-QSAR model, constructed on the basis of this study, offers a powerful tool for future 17beta-HSD1 inhibitor development. As part of the fundamental science underpinning this research, the chemical reactivity of fused (di)cycloalkeno thieno[2,3-d]pyrimidin-4(3H)-ones with electrophilic reagents, i.e. Vilsmeier reagent and dimethylformamide dimethylacetal, was investigated. These findings resulted in a revision of the reaction mechanism of Vilsmeier haloformylation and further contributed to understanding the chemical reactivity of this compound class. This study revealed that the reactivity is dependent upon a stereoelectronic effect arising from different ring conformations.

Discovering hidden structures in molecular data using a Bayesian partition model approach

Advancements in the analysis techniques have led to a rapid accumulation of biological data in databases. Such data often are in the form of sequences of observations, examples including DNA sequences and amino acid sequences of proteins. The scale and quality of the data give promises of answering various biologically relevant questions in more detail than what has been possible before. For example, one may wish to identify areas in an amino acid sequence, which are important for the function of the corresponding protein, or investigate how characteristics on the level of DNA sequence affect the adaptation of a bacterial species to its environment. Many of the interesting questions are intimately associated with the understanding of the evolutionary relationships among the items under consideration. The aim of this work is to develop novel statistical models and computational techniques to meet with the challenge of deriving meaning from the increasing amounts of data. Our main concern is on modeling the evolutionary relationships based on the observed molecular data. We operate within a Bayesian statistical framework, which allows a probabilistic quantification of the uncertainties related to a particular solution. As the basis of our modeling approach we utilize a partition model, which is used to describe the structure of data by appropriately dividing the data items into clusters of related items. Generalizations and modifications of the partition model are developed and applied to various problems. Large-scale data sets provide also a computational challenge. The models used to describe the data must be realistic enough to capture the essential features of the current modeling task but, at the same time, simple enough to make it possible to carry out the inference in practice. The partition model fulfills these two requirements. The problem-specific features can be taken into account by modifying the prior probability distributions of the model parameters. The computational efficiency stems from the ability to integrate out the parameters of the partition model analytically, which enables the use of efficient stochastic search algorithms.

Homogeneous model theory of metric structures

This thesis studies homogeneous classes of complete metric spaces. Over the past few decades model theory has been extended to cover a variety of nonelementary frameworks. Shelah introduced the abstact elementary classes (AEC) in the 1980s as a common framework for the study of nonelementary classes. Another direction of extension has been the development of model theory for metric structures. This thesis takes a step in the direction of combining these two by introducing an AEC-like setting for studying metric structures. To find balance between generality and the possibility to develop stability theoretic tools, we work in a homogeneous context, thus extending the usual compact approach. The homogeneous context enables the application of stability theoretic tools developed in discrete homogeneous model theory. Using these we prove categoricity transfer theorems for homogeneous metric structures with respect to isometric isomorphisms. We also show how generalized isomorphisms can be added to the class, giving a model theoretic approach to, e.g., Banach space isomorphisms or operator approximations. The novelty is the built-in treatment of these generalized isomorphisms making, e.g., stability up to perturbation the natural stability notion. With respect to these generalized isomorphisms we develop a notion of independence. It behaves well already for structures which are omega-stable up to perturbation and coincides with the one from classical homogeneous model theory over saturated enough models. We also introduce a notion of isolation and prove dominance for it.

Tiedon jakaminen tiimityössä

Knowledge-sharing in a teamwork The study examines the link between knowledge-sharing that takes place in a team and the dimensions and objectives of the team s activities. The question the study poses is: How does knowledge-sharing in a team relate to the team s activities? The exchange of knowledge is examined using knowledge-sharing networks and the conversion model, which describes the process of knowledge formation. The answer to the question is sought through four empirical articles describing the activities of a team from the viewpoint of quality, fairness, power related to knowledge management, and performance. One of the articles used in the study describes the role of networks in work life more generally. It attempts to shed light on the manner in which team-related networks operate as part of a more extensive structure of organizational networks. Finland is one of the most eager users of teamwork, if numbers are used as a yardstick. About half of all Finnish wage earners worked in teams in 2009, and comparisons show that the use of teams in Finland is above the EU average. This study focuses on so-called semi-autonomous teams, which carry out permanent work tasks. In such teams, tasks are interdependent, and teams are jointly responsible for ensuring that the work is done. Team members may also, at least to some extent, agree between themselves on how the tasks are carried out and are able to take part in the decision-making process. Such teamwork makes knowledge-sharing an important element for the team s activities. Knowledge and knowledge-sharing have become a major resource, allowing organizations to operate and even compete in today s increasingly competitive markets. A single team or a single organization cannot, however, possess all the knowledge required for carrying out the tasks assigned to it. Although it is difficult to copy the knowledge generated in an organization, it is important to share the knowledge within and between organizations. External links supply teams and organizations with important knowledge that allows them to keep their operations up-to-date and their structures well-functioning. In fact, knowledge provides teams and organizations with an intangible resource that improves their capacity to interact with their environment and to adjust to it. For this reason, it is important to examine both the internal and external knowledge-sharing taking place in a team. The findings of the study show that in terms of quality, fairness, performance and the knowledge management issues concerning a team, its social network structure is both internally and externally connected with its activities. A team structure that is internally coherent and at the same time open to external contacts, is, with certain restrictions, connected with the quality, fairness, and performance of the team. The restrictions concern differences between procedural and interactional justice, public and private sectors, and the team leaders and ordinary team members. The role of the team leader is closely connected with the management of networks that are considered valuable. The results of the study indicate that teamwork is supervisor-dominated. Thus, teamwork does not substantially strengthen the influence of individual employees as players in knowledge-transfer networks. However, ordinary team members possess important peer contacts inside the organization. Teamwork clearly allows employees to interact in a democratic manner, and here the transfer of tacit knowledge plays an important role. Keywords: teamwork, knowledge-sharing, social networks, organization