State Agent, Identity and the "New World Order" : Reconstructing Polish Defence Identity after the Cold War Era

National identity signifies and makes state s defence- and foreign policy behaviour meaningful. National consciousness is narrated into existence by narratives upon one s own exceptionalism and Otherness of the other nations. While national identity may be understood merely as a self-image of a nation, defence identity refers to the borders of Otherness and issues that have been considered as worth defending for. As national identities and all the world order models are human constructions, they may be changed by the human efforts as well; states and nations may deliberately promote communitarian or even cosmopolitan equality and tolerance without borders of Otherness. The main research question of the thesis is: How does Poland constitute herself as a nation and a state agent in the current world order and to what extent have contextual foreign and defence policy interactions changed the Polish defence identity during the post-Cold War era? The main empirical argument of the thesis is: Poland is a narrated idea of a Christian Catholic nation-state, which the Polish State, the Catholic Church of Poland, the Armed Forces of Poland as well as a majority of the Polish nation share. Polish defence identity has been almost impenetrable to contextual foreign and defence policy interactions during the post-Cold War era. While Christian religious ontology binds corporate Poland together, allowing her to survive any number of military and political catastrophes, it simultaneously brings her closer to the USA, raises tensions in the infidel EU-context, and restrains corporate Poland s pursuit of communitarian, or even cosmopolitan, global equality and tolerance. It is not the case that corporate Poland s foreign and defence policy orientation is instinctively Atlanticist by nature, as has been argued. Rather, it has been the State s rational project to overcome a habituated and reified fear of becoming geopolitically sandwiched between Russian and German Others by leaning on the USA; among the Polish nation, support for the USA has been declining since 2004. It is not corporate Poland either that has turned into a constructive European , as has been argued, but rather the Polish nation that has, at least partly, managed to emancipate itself from its habituation to a betrayal by Europe narrative, since it favours the EU as much as it favours NATO. It seems that in the Polish case a truly common European CFSP vis-à-vis Russia may offer a solution that will emancipate the Polish State from its habituated EU-sceptic role identity and corporate Poland from its narrated borders of Otherness towards Russia and Germany, but even then one cannot be sure whether any other perspective than the Polish one on a common stand towards Russia would satisfy the Poles themselves.

Gene flow from transgenic plant populations: models and applications for risk assessment

The future use of genetically modified (GM) plants in food, feed and biomass production requires a careful consideration of possible risks related to the unintended spread of trangenes into new habitats. This may occur via introgression of the transgene to conventional genotypes, due to cross-pollination, and via the invasion of GM plants to new habitats. Assessment of possible environmental impacts of GM plants requires estimation of the level of gene flow from a GM population. Furthermore, management measures for reducing gene flow from GM populations are needed in order to prevent possible unwanted effects of transgenes on ecosystems. This work develops modeling tools for estimating gene flow from GM plant populations in boreal environments and for investigating the mechanisms of the gene flow process. To describe spatial dimensions of the gene flow, dispersal models are developed for the local and regional scale spread of pollen grains and seeds, with special emphasis on wind dispersal. This study provides tools for describing cross-pollination between GM and conventional populations and for estimating the levels of transgenic contamination of the conventional crops. For perennial populations, a modeling framework describing the dynamics of plants and genotypes is developed, in order to estimate the gene flow process over a sequence of years. The dispersal of airborne pollen and seeds cannot be easily controlled, and small amounts of these particles are likely to disperse over long distances. Wind dispersal processes are highly stochastic due to variation in atmospheric conditions, so that there may be considerable variation between individual dispersal patterns. This, in turn, is reflected to the large amount of variation in annual levels of cross-pollination between GM and conventional populations. Even though land-use practices have effects on the average levels of cross-pollination between GM and conventional fields, the level of transgenic contamination of a conventional crop remains highly stochastic. The demographic effects of a transgene have impacts on the establishment of trangenic plants amongst conventional genotypes of the same species. If the transgene gives a plant a considerable fitness advantage in comparison to conventional genotypes, the spread of transgenes to conventional population can be strongly increased. In such cases, dominance of the transgene considerably increases gene flow from GM to conventional populations, due to the enhanced fitness of heterozygous hybrids. The fitness of GM plants in conventional populations can be reduced by linking the selectively favoured primary transgene to a disfavoured mitigation transgene. Recombination between these transgenes is a major risk related to this technique, especially because it tends to take place amongst the conventional genotypes and thus promotes the establishment of invasive transgenic plants in conventional populations.

Questions to Artificial Nature: A Philosophical Study of Interdisciplinary Models and their Functions in Scientific Practice

This thesis presents an interdisciplinary analysis of how models and simulations function in the production of scientific knowledge. The work is informed by three scholarly traditions: studies on models and simulations in philosophy of science, so-called micro-sociological laboratory studies within science and technology studies, and cultural-historical activity theory. Methodologically, I adopt a naturalist epistemology and combine philosophical analysis with a qualitative, empirical case study of infectious-disease modelling. This study has a dual perspective throughout the analysis: it specifies the modelling practices and examines the models as objects of research. The research questions addressed in this study are: 1) How are models constructed and what functions do they have in the production of scientific knowledge? 2) What is interdisciplinarity in model construction? 3) How do models become a general research tool and why is this process problematic? The core argument is that the mediating models as investigative instruments (cf. Morgan and Morrison 1999) take questions as a starting point, and hence their construction is intentionally guided. This argument applies the interrogative model of inquiry (e.g., Sintonen 2005; Hintikka 1981), which conceives of all knowledge acquisition as process of seeking answers to questions. The first question addresses simulation models as Artificial Nature, which is manipulated in order to answer questions that initiated the model building. This account develops further the "epistemology of simulation" (cf. Winsberg 2003) by showing the interrelatedness of researchers and their objects in the process of modelling. The second question clarifies why interdisciplinary research collaboration is demanding and difficult to maintain. The nature of the impediments to disciplinary interaction are examined by introducing the idea of object-oriented interdisciplinarity, which provides an analytical framework to study the changes in the degree of interdisciplinarity, the tools and research practices developed to support the collaboration, and the mode of collaboration in relation to the historically mutable object of research. As my interest is in the models as interdisciplinary objects, the third research problem seeks to answer my question of how we might characterise these objects, what is typical for them, and what kind of changes happen in the process of modelling. Here I examine the tension between specified, question-oriented models and more general models, and suggest that the specified models form a group of their own. I call these Tailor-made models, in opposition to the process of building a simulation platform that aims at generalisability and utility for health-policy. This tension also underlines the challenge of applying research results (or methods and tools) to discuss and solve problems in decision-making processes.

Expression and function of angiotensins in the regulation of intraocular pressure - an experimental study

Glaucoma is a multifactorial long-term ocular neuropathy associated with progressive loss of the visual field, retinal nerve fiber structural abnormalities and optic disc changes. Like arterial hypertension it is usually a symptomless disease, but if left untreated leads to visual disability and eventual blindness. All therapies currently used aim to lower intraocular pressure (IOP) in order to minimize cell death. Drugs with new mechanisms of action could protect glaucomatous eyes against blindness. Renin-angiotensin system (RAS) is known to regulate systemic blood pressure and compounds acting on it are in wide clinical use in the treatment of hypertension and heart failure but not yet in ophthalmological use. There are only few previous studies concerning intraocular RAS, though evidence is accumulating that drugs antagonizing RAS can also lower IOP, the only treatable risk factor in glaucoma. The main aim of this experimental study was to clarify the expression of the renin-angiotensin system in the eye tissues and to test its potential oculohypotensive effects and mechanisms. In addition, the possible relationship between the development of hypertension and IOP was evaluated in animal models. In conclusion, a novel angiotensin receptor type (Mas), as well as ACE2 enzyme- producing agonists for Mas, were described for the first time in the eye structures participating in the regulation of IOP. In addition, a Mas receptor agonist significantly reduced even normal IOP. The effect was abolished by a specific receptor antagonist. Intraocular, local RAS would thus to be involved in the regulation of IOP, probably even more in pathological conditions such as glaucoma though there was no unambiguous relationship between arterial and ocular hypertension. The findings suggest the potential as antiglaucomatous drugs of agents which increase ACE2 activity and the formation of angiotensin (1-7), or activate Mas receptors.

Oxidative stability of phytosterols in food models and foods

An important safety aspect to be considered when foods are enriched with phytosterols and phytostanols is the oxidative stability of these lipid compounds, i.e. their resistance to oxidation and thus to the formation of oxidation products. This study concentrated on producing scientific data to support this safety evaluation process. In the absence of an official method for analyzing of phytosterol/stanol oxidation products, we first developed a new gas chromatographic - mass spectrometric (GC-MS) method. We then investigated factors affecting these compounds' oxidative stability in lipid-based food models in order to identify critical conditions under which significant oxidation reactions may occur. Finally, the oxidative stability of phytosterols and stanols in enriched foods during processing and storage was evaluated. Enriched foods covered a range of commercially available phytosterol/stanol ingredients, different heat treatments during food processing, and different multiphase food structures. The GC-MS method was a powerful tool for measuring the oxidative stability. Data obtained in food model studies revealed that the critical factors for the formation and distribution of the main secondary oxidation products were sterol structure, reaction temperature, reaction time, and lipid matrix composition. Under all conditions studied, phytostanols as saturated compounds were more stable than unsaturated phytosterols. In addition, esterification made phytosterols more reactive than free sterols at low temperatures, while at high temperatures the situation was the reverse. Generally, oxidation reactions were more significant at temperatures above 100°C. At lower temperatures, the significance of these reactions increased with increasing reaction time. The effect of lipid matrix composition was dependent on temperature; at temperatures above 140°C, phytosterols were more stable in an unsaturated lipid matrix, whereas below 140°C they were more stable in a saturated lipid matrix. At 140°C, phytosterols oxidized at the same rate in both matrices. Regardless of temperature, phytostanols oxidized more in an unsaturated lipid matrix. Generally, the distribution of oxidation products seemed to be associated with the phase of overall oxidation. 7-ketophytosterols accumulated when oxidation had not yet reached the dynamic state. Once this state was attained, the major products were 5,6-epoxyphytosterols and 7-hydroxyphytosterols. The changes observed in phytostanol oxidation products were not as informative since all stanol oxides quantified represented hydroxyl compounds. The formation of these secondary oxidation products did not account for all of the phytosterol/stanol losses observed during the heating experiments, indicating the presence of dimeric, oligomeric or other oxidation products, especially when free phytosterols and stanols were heated at high temperatures. Commercially available phytosterol/stanol ingredients were stable during such food processes as spray-drying and ultra high temperature (UHT)-type heating and subsequent long-term storage. Pan-frying, however, induced phytosterol oxidation and was classified as a rather deteriorative process. Overall, the findings indicated that although phytosterols and stanols are stable in normal food processing conditions, attention should be paid to their use in frying. Complex interactions between other food constituents also suggested that when new phytosterol-enriched foods are developed their oxidative stability must first be established. The results presented here will assist in choosing safe conditions for phytosterol/stanol enrichment.

Valuation of reduced eutrophication in the Gulf of Finland : Choice experiment with attention to heterogeneous and discontinuous preferences and respondent uncertainty

Eutrophication of the Baltic Sea is a serious problem. This thesis estimates the benefit to Finns from reduced eutrophication in the Gulf of Finland, the most eutrophied part of the Baltic Sea, by applying the choice experiment method, which belongs to the family of stated preference methods. Because stated preference methods have been subject to criticism, e.g., due to their hypothetical survey context, this thesis contributes to the discussion by studying two anomalies that may lead to biased welfare estimates: respondent uncertainty and preference discontinuity. The former refers to the difficulty of stating one s preferences for an environmental good in a hypothetical context. The latter implies a departure from the continuity assumption of conventional consumer theory, which forms the basis for the method and the analysis. In the three essays of the thesis, discrete choice data are analyzed with the multinomial logit and mixed logit models. On average, Finns are willing to contribute to the water quality improvement. The probability for willingness increases with residential or recreational contact with the gulf, higher than average income, younger than average age, and the absence of dependent children in the household. On average, for Finns the relatively most important characteristic of water quality is water clarity followed by the desire for fewer occurrences of blue-green algae. For future nutrient reduction scenarios, the annual mean household willingness to pay estimates range from 271 to 448 and the aggregate welfare estimates for Finns range from 28 billion to 54 billion euros, depending on the model and the intensity of the reduction. Out of the respondents (N=726), 72.1% state in a follow-up question that they are either Certain or Quite certain about their answer when choosing the preferred alternative in the experiment. Based on the analysis of other follow-up questions and another sample (N=307), 10.4% of the respondents are identified as potentially having discontinuous preferences. In relation to both anomalies, the respondent- and questionnaire-specific variables are found among the underlying causes and a departure from standard analysis may improve the model fit and the efficiency of estimates, depending on the chosen modeling approach. The introduction of uncertainty about the future state of the Gulf increases the acceptance of the valuation scenario which may indicate an increased credibility of a proposed scenario. In conclusion, modeling preference heterogeneity is an essential part of the analysis of discrete choice data. The results regarding uncertainty in stating one s preferences and non-standard choice behavior are promising: accounting for these anomalies in the analysis may improve the precision of the estimates of benefit from reduced eutrophication in the Gulf of Finland.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

Joint Regression and Association Models for Repeated Categorical Responses

The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.

On linear order and computation : The expressiveness of interactive computations on linear orders and computations indexed by ordinals

We solve the Dynamic Ehrenfeucht-Fra\"iss\'e Game on linear orders for both players, yielding a normal form for quantifier-rank equivalence classes of linear orders in first-order logic, infinitary logic, and generalized-infinitary logics with linearly ordered clocks. We show that Scott Sentences can be manipulated quickly, classified into local information, and consistency can be decided effectively in the length of the Scott Sentence. We describe a finite set of linked automata moving continuously on a linear order. Running them on ordinals, we compute the ordinal truth predicate and compute truth in the constructible universe of set-theory. Among the corollaries are a study of semi-models as efficient database of both model-theoretic and formulaic information, and a new proof of the atomicity of the Boolean algebra of sentences consistent with the theory of linear order -- i.e., that the finitely axiomatized theories of linear order are dense.

Locality and order-invariant logics

Malli on logiikassa käytetty abstraktio monille matemaattisille objekteille. Esimerkiksi verkot, ryhmät ja metriset avaruudet ovat malleja. Äärellisten mallien teoria on logiikan osa-alue, jossa tarkastellaan logiikkojen, formaalien kielten, ilmaisuvoimaa malleissa, joiden alkioiden lukumäärä on äärellinen. Rajoittuminen äärellisiin malleihin mahdollistaa tulosten soveltamisen teoreettisessa tietojenkäsittelytieteessä, jonka näkökulmasta logiikan kaavoja voidaan ajatella ohjelmina ja äärellisiä malleja niiden syötteinä. Lokaalisuus tarkoittaa logiikan kyvyttömyyttä erottaa toisistaan malleja, joiden paikalliset piirteet vastaavat toisiaan. Väitöskirjassa tarkastellaan useita lokaalisuuden muotoja ja niiden säilymistä logiikkoja yhdistellessä. Kehitettyjä työkaluja apuna käyttäen osoitetaan, että Gaifman- ja Hanf-lokaalisuudeksi kutsuttujen varianttien välissä on lokaalisuuskäsitteiden hierarkia, jonka eri tasot voidaan erottaa toisistaan kasvavaa dimensiota olevissa hiloissa. Toisaalta osoitetaan, että lokaalisuuskäsitteet eivät eroa toisistaan, kun rajoitutaan tarkastelemaan äärellisiä puita. Järjestysinvariantit logiikat ovat kieliä, joissa on käytössä sisäänrakennettu järjestysrelaatio, mutta sitä on käytettävä siten, etteivät kaavojen ilmaisemat asiat riipu valitusta järjestyksestä. Määritelmää voi motivoida tietojenkäsittelyn näkökulmasta: vaikka ohjelman syötteen tietojen järjestyksellä ei olisi odotetun tuloksen kannalta merkitystä, on syöte tietokoneen muistissa aina jossakin järjestyksessä, jota ohjelma voi laskennassaan hyödyntää. Väitöskirjassa tutkitaan minkälaisia lokaalisuuden muotoja järjestysinvariantit ensimmäisen kertaluvun predikaattilogiikan laajennukset yksipaikkaisilla kvanttoreilla voivat toteuttaa. Tuloksia sovelletaan tarkastelemalla, milloin sisäänrakennettu järjestys lisää logiikan ilmaisuvoimaa äärellisissä puissa.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Damp building moulds: Assessment of sensitization in patients and studies into mechanisms of airway inflammation using experimental models

Exposure to water-damaged buildings and the associated health problems have evoked concern and created confusion during the past 20 years. Individuals exposed to moisture problem buildings report adverse health effects such as non-specific respiratory symptoms. Microbes, especially fungi, growing on the damp material have been considered as potential sources of the health problems encountered in these buildings. Fungi and their airborne fungal spores contain allergens and secondary metabolites which may trigger allergic as well as inflammatory types of responses in the eyes and airways. Although epidemiological studies have revealed an association between damp buildings and health problems, no direct cause-and-effect relationship has been established. Further knowledge is needed about the epidemiology and the mechanisms leading to the symptoms associated with exposure to fungi. Two different approaches have been used in this thesis in order to investigate the diverse health effects associated with exposure to moulds. In the first part, sensitization to moulds was evaluated and potential cross-reactivity studied in patients attending a hospital for suspected allergy. In the second part, one typical mould known to be found in water-damaged buildings and to produce toxic secondary metabolites was used to study the airway responses in an experimental model. Exposure studies were performed on both naive and allergen sensitized mice. The first part of the study showed that mould allergy is rare and highly dependent on the atopic status of the examined individual. The prevalence of sensitization was 2.7% to Cladosporium herbarum and 2.8% to Alternaria alternata in patients, the majority of whom were atopic subjects. Some of the patients sensitized to mould suffered from atopic eczema. Frequently the patients were observed to possess specific serum IgE antibodies to a yeast present in the normal skin flora, Pityrosporum ovale. In some of these patients, the IgE binding was partly found to be due to binding to shared glycoproteins in the mould and yeast allergen extracts. The second part of the study revealed that exposure to Stachybotrys chartarum spores induced an airway inflammation in the lungs of mice. The inflammation was characterized by an influx of inflammatory cells, mainly neutrophils and lymphocytes, into the lungs but with almost no differences in airway responses seen between the satratoxin producing and non-satratoxin producing strain. On the other hand, when mice were exposed to S. chartarum and sensitized/challenged with ovalbumin the extent of the inflammation was markedly enhanced. A synergistic increase in the numbers of inflammatory cells was seen in BAL and severe inflammation was observed in the histological lung sections. In conclusion, the results in this thesis imply that exposure to moulds in water damaged buildings may trigger health effects in susceptible individuals. The symptoms can rarely be explained by IgE mediated allergy to moulds. Other non-allergic mechanisms seem to be involved. Stachybotrys chartarum is one of the moulds potentially responsible for health problems. In this thesis, new reaction models for the airway inflammation induced by S. chartarum have been found using experimental approaches. The immunological status played an important role in the airway inflammation, enhancing the effects of mould exposure. The results imply that sensitized individuals may be more susceptible to exposure to moulds than non-sensitized individuals.

Simulations of dimensionally reduced effective theories of high temperature QCD

Quantum chromodynamics (QCD) is the theory describing interaction between quarks and gluons. At low temperatures, quarks are confined forming hadrons, e.g. protons and neutrons. However, at extremely high temperatures the hadrons break apart and the matter transforms into plasma of individual quarks and gluons. In this theses the quark gluon plasma (QGP) phase of QCD is studied using lattice techniques in the framework of dimensionally reduced effective theories EQCD and MQCD. Two quantities are in particular interest: the pressure (or grand potential) and the quark number susceptibility. At high temperatures the pressure admits a generalised coupling constant expansion, where some coefficients are non-perturbative. We determine the first such contribution of order g^6 by performing lattice simulations in MQCD. This requires high precision lattice calculations, which we perform with different number of colors N_c to obtain N_c-dependence on the coefficient. The quark number susceptibility is studied by performing lattice simulations in EQCD. We measure both flavor singlet (diagonal) and non-singlet (off-diagonal) quark number susceptibilities. The finite chemical potential results are optained using analytic continuation. The diagonal susceptibility approaches the perturbative result above 20T_c$, but below that temperature we observe significant deviations. The results agree well with 4d lattice data down to temperatures 2T_c.

Diagnostic Tests Based on Quantile Residuals for Nonlinear Time Series Models

This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

Models of Dispersal and Diversification

Ecology and evolutionary biology is the study of life on this planet. One of the many methods applied to answering the great diversity of questions regarding the lives and characteristics of individual organisms, is the utilization of mathematical models. Such models are used in a wide variety of ways. Some help us to reason, functioning as aids to, or substitutes for, our own fallible logic, thus making argumentation and thinking clearer. Models which help our reasoning can lead to conceptual clarification; by expressing ideas in algebraic terms, the relationship between different concepts become clearer. Other mathematical models are used to better understand yet more complicated models, or to develop mathematical tools for their analysis. Though helping us to reason and being used as tools in the craftmanship of science, many models do not tell us much about the real biological phenomena we are, at least initially, interested in. The main reason for this is that any mathematical model is a simplification of the real world, reducing the complexity and variety of interactions and idiosynchracies of individual organisms. What such models can tell us, however, both is and has been very valuable throughout the history of ecology and evolution. Minimally, a model simplifying the complex world can tell us that in principle, the patterns produced in a model could also be produced in the real world. We can never know how different a simplified mathematical representation is from the real world, but the similarity models do strive for, gives us confidence that their results could apply. This thesis deals with a variety of different models, used for different purposes. One model deals with how one can measure and analyse invasions; the expanding phase of invasive species. Earlier analyses claims to have shown that such invasions can be a regulated phenomena, that higher invasion speeds at a given point in time will lead to a reduction in speed. Two simple mathematical models show that analysis on this particular measure of invasion speed need not be evidence of regulation. In the context of dispersal evolution, two models acting as proof-of-principle are presented. Parent-offspring conflict emerges when there are different evolutionary optima for adaptive behavior for parents and offspring. We show that the evolution of dispersal distances can entail such a conflict, and that under parental control of dispersal (as, for example, in higher plants) wider dispersal kernels are optimal. We also show that dispersal homeostasis can be optimal; in a setting where dispersal decisions (to leave or stay in a natal patch) are made, strategies that divide their seeds or eggs into fractions that disperse or not, as opposed to randomized for each seed, can prevail. We also present a model of the evolution of bet-hedging strategies; evolutionary adaptations that occur despite their fitness, on average, being lower than a competing strategy. Such strategies can win in the long run because they have a reduced variance in fitness coupled with a reduction in mean fitness, and fitness is of a multiplicative nature across generations, and therefore sensitive to variability. This model is used for conceptual clarification; by developing a population genetical model with uncertain fitness and expressing genotypic variance in fitness as a product between individual level variance and correlations between individuals of a genotype. We arrive at expressions that intuitively reflect two of the main categorizations of bet-hedging strategies; conservative vs diversifying and within- vs between-generation bet hedging. In addition, this model shows that these divisions in fact are false dichotomies.