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Modern high energy physics describes natural phenomena in terms of quantum field theories (QFTs). The relevant calculations in QFTs aim at the evaluation of physical quantities, which often leads to the application of perturbation theory. In non-thermal theories these quantities emerge from, for example, scattering amplitudes. In high-temperature theories thermodynamical quantities, such as pressure, arise from the free energy of the system. The actual computations are often performed with Feynman diagrams, which visually illustrate multi-dimensional momentum (or coordinate) space integrals. In essence, master integrals are integral structures (within these diagrams) that can not be reduced to more concise or simpler integral representations. They are crucial in performing perturbative corrections to any system described by (any) QFT, as the diagrammatic structures reduce to linear combinations of master integrals. Traditional zero-temperature QFT relates the corresponding master integrals to multi-loop vacuum diagrams, which leads in practice to the evaluation of $d$-dimensional regularized momentum integrals. Upon transitioning to thermal field theory (TFT), the corresponding master integrals become multi-loop sum-integrals. Both the thermal and non-thermal master integral structures are explored at length, using $\overline{MS}$-scheme (Modified Minimal Subtraction) in the calculations. Throughout this thesis, a self-consistent methodology is presented for the evaluation of both types of master integrals, while limiting the calculations to one- and two-loop diagrams. However, the methods are easily generalized to more complex systems. The physical background of master integrals is introduced through a derivation of Feynman rules and diagrams for $\phi^4$ scalar field theory. Afterwards, the traditional $d$-dimensional master integral structures are considered, up to general two-loop structures with massive propagators. The evaluation strategies involve e.g. the Feynman parametrization and the Mellin-Barnes transform. The application of these results is demonstrated through the evaluation of three different diagrams appearing in the two-loop effective potential of the dimensionally reduced variant of the Standard model. The relevant thermal one-loop integral structures are introduced through the high-temperature expansion of a massive one-loop sum-integral (with a single massive propagator). The thermal multi-loop computations are predominantly considered with a methodology that decomposes the integrals into finite and infinite elements. Specifically, we demonstrate the removal of both the ultraviolet and infrared (UV and IR) divergences, and evaluate the remaining finite integral using the Fourier transform from momentum space back to coordinate space. The strategies are applied to multiple non-trivial diagrammatic structures arising from the Standard model.

To evaluate whether CMIP6 models provide good simulation in Arctic sea-ice extent, thickness, and motion, selected 6 CMIP6 models are EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, GFDL-ESM4, MPI-ESM1-2-HR, NORESM2-LM. For CMIP6 models and observations, seasonal cycle and the annual variation from 1979-2014 of sea-ice extent were studied, for sea-ice thickness and sea-ice motion, the Arctic is separated into three regions, geographical distribution, inter-annual variation from 1979-2014, seasonal cycle, and trend were studied. Then student t-test is used to evaluate whether the model output has a significant difference from observation, to select the best model(s). For sea-ice extent, EC-Earth3 is overestimating sea-ice extent, especially in winter, BCC-CSM2-MR model underestimates sea-ice extent, ACCESS-CM2, MPI-ESM1-2-HR, NorESM2-LM models perform the best. For sea-ice thickness, BCC-CSM2-MR underestimates sea-ice thickness, EC-Earth3, ACCESS-CM2, and NORESM2-LM models are overestimating sea-ice thickness. GFDL-ESM4 and MPI-ESM1-2-HR have the best performance at sea-ice thickness simulation. For sea-ice motion, the MPI-ESM1-2-HR model overestimates sea-ice drifting speed all year round, ACCESS-CM2 model tends to overestimate sea-ice drifting speed in summer for region1 and region2, in region3 ACCESS-CM2 model mostly overestimate sea-ice motion except winter months. NorESM2-LM model has the best performance overall, and ACCESS-CM2 has the second-best simulation for region1 and region2. EC-Earth3 also has a satisfactory simulation for sea-ice motion. Models and observation also agree on common results for sea-ice properties: Maximum sea-ice extent occurs in March, and minimum sea-ice extent occurs in September. There's a decreasing trend of sea-ice extent. The Central Arctic and Canadian Archipelago always have the thickest sea ice, followed by the East Siberian Sea, Laptev Sea, and Chukchi Sea, Beaufort Sea. East Greenland Sea, Barents Sea, Buffin Bay, and the Kara Sea always have the thinnest sea ice. There's a decreasing trend for sea-ice thickness according to models, sea-ice is thicker in the Chukchi Sea and the Beaufort Sea than in Laptev and East Siberian seas. Winter sea-ice thickness is higher than in summer, and sea-ice thickness has a more rapid decreasing rate in summer than in winter. Laptev and the East Siberian Sea have the most rapidly sea-ice thinning process. Sea-ice thickness has seasonal cycle that maximum usually occurs in May, and minimum sea-ice thickness happens in October. For sea-ice motion, there's an increasing trend of sea-ice motion, and summer sea-ice motion has faster sea-ice motion than winter, Chukchi Sea, and the Beaufort Sea has faster sea-ice motion than Laptev and the East Siberian Sea. Corresponding with the comparatively faster-thinning in the Laptev and the East Siberian Seas simulated by models, there's also a faster increasing rate in the Laptev and the East Siberian Sea.

While numerical weather forecasts have improved dramatically in recent decades, forecasting severe weather events remains a great challenge due to models being unable to resolve convection explicitly. Forecasters commonly utilize large-scale convective parameters derived from atmospheric soundings to assess whether the atmosphere has the potential to develop convective storms. These parameters are able to describe the environments in which thunderstorms occur but relate to actual thunderstorm events only probabilistically. Roine (2001) used atmospheric soundings and thunderstorm observations to assess which from a variety of stability indices were most successful in predicting thunderstorms in Finland, and found that Surface Lifted Index, CAPE and the Showalter index were most skillful based on the data set in question. This study aims to extend the assessment of thunderstorm predictors to atmospheric reanalyses, by utilising model pseudo-soundings. Reanalyses such as ERA-Interim use sophisticated data assimilation schemes to reconstruct past atmospheric conditions from historical observational data. In addition to a large sample size, this approach enables examining the use of other large-scale model parameters, which are hypothesized to be associated with convective initiation, as supplemental forecast parameters. Using lightning location data and ERA-Interim reanalysis fields for Finnish summers between 2002 and 2013, it is found that the Lifted Index (LI) based on the most unstable parcel in the lowest 300 hPa has the highest forecast skill among traditional stability indices. By combining this index with the dew point depression at 700 hPa and low-level vertical shear, its performance can be further slightly increased. Moreover, vertically integrated mass flux convergence between the surface and 500 hPa calculated from the ERA-I convergence seems to have high association with thunderstorm occurrence when used as a supplementary parameter. Finally, artificial neural networks (ANN) were developed for predicting thunderstorm occurrence, and their forecast skill compared to that of stability indices. The best ANN found, utilizing 11 parameters as input, clearly outperformed the best stability indices in a skill score test; achieving a True Skill Score of 0.69 compared to 0.61 with the most unstable Lifted Index. The results suggest that ANNs, due to their inherent nonlinearity, represent a promising tool for forecasting of deep, moist convection.

Paleoproterotzoic evaporitic rocks in the Central Lapland Greenstone Belt (CLGB) were discovered in 2016 as a result of relatively deep diamond core drilling (400-1100m) during a Ni-Cu-PGE ore exploration project. Evaporites occur as relatively flat successions. Highly soluble evaporites were probably initially preserved by active magmatism that enveloped these layers under extrusives or/and in between subvolcanic sills. Under the deformation the plastic behaviour of evaporites may have provided a platform that may have functioned as a slip surface for the prograding thrust faults. Plastic behaviour may also have prevented folding. Evaporites in the Central Lapland Greenstone Belt formed after the Great Oxidation Event, during the late stages of Lomagundi-Jatuli carbon isotope event. The discovered evaporites belong to the Savukoski Group rocks (2.2-2.05 Ga) that resemble a closing rift and the corresponding of a shallow sea environment, where evaporites are considered to have precipitated by oversaturation induced by anomalously high terrestrial influx that was enhanced by newly introduced oxic conditions. Age constraints for these deposits are provided by their relative position in the CLGB stratigraphy: 1. They postdate the appearance of fist black shales of the Matarakoski Formation in Kitinen and Siuliunpalo Formation in Pelkosenniemi (<2.2 Ga), and 2. they predate the ultramafic volcanic rocks of the Sattasvaara Formation in Kitinen and Kummitsoiva Formation in Pelkosenniemi (>2.05Ga). These conclusions are strengthened by carbon isotope results from carbonates. Evaporitic carbonates show elevated 13C values ranging from +4 to +14 ‰, with an average at +9 ‰. These values correlate well with the timing of the Paleoproterotzoic carbon excursion (2.2-2.06 Ga). The excursion has been addressed to extensive burial of organic carbon (Karhu & Holland, 1996). 34S values form a relative tight group between +5 -+8 ‰ (averaging +6.5 ‰) and are similar with the roughly coeval Paleoproterotzoic evaporitic anhydrites of the Onega Basin. The discovery of Paleoproterozoic evaporites foremostly adds a new rocktype into the bedrock of Finland as well as gives new insight to the crustal evolution in the CLGB.

Abstract This thesis explores the everyday spatial practices in the gentrified and micro-segregated Eastleigh, Nairobi. Gentrification is one of the most important aspects of urban studies, as well as social geography contributing to significant socioeconomic changes in many metropolitan cities in the world. Although the emerging empirical studies indicate socioeconomic impacts of gentrification, less research has been conducted to examine social and economic interaction in gentrified spaces in the Global South. Additionally, there are limited studies on how cultural diversity influences gentrification. In the case of a diversified neighbourhood, such as Eastleigh, assessing the effects of culture on gentrification is significant. Therefore, this study aimed to see by observing and interviewing residents, whether the developments in Eastleigh can be analysed and interpreted through the theoretical framework of gentrification and micro-segregation. The study used descriptive research to build on literature and graphics to collect data on gentrification indicators and socioeconomic interactions. The qualitative part of the study entailed observation, questionnaire survey, and key Informant interviews, while quantitative analysis was based on the graphical presentation of data. The outcomes of the study strongly suggest that an increase in the housing variables, the influx of wealthy population, increased employment, and shift in consumption trends are the significant indicators of ongoing gentrification in Eastleigh. The empirical studies indicate that social interactions in gentrified spaces appear to be marginalized due to cultural differences that have a strong impact on social and economic agents. The review made similar observations regarding social interactions between the new-comers and the long-time residents. The results of the study also found out that the reason for social and economic inequalities among the residents and the gentrifies was cultural differences which hindered access to social and economic services. However, since this study is one of the initial studies on gentrification in Eastleigh, Nairobi, more and in-depth studies are recommended

Dispersal is a significant characteristic of life history of many species. Dispersal polymorphisms in nature propose that dispersal can have significant effect on species diversity. Evolution of dispersal is one probable reason to speciation. I consider an environment of well-connected and separate living sites and study how connectivity difference between different sites can affect the evolution of a two-dimensional dispersal strategy. Two-dimensionality means that the strategy consists of two separate traits. Adaptive dynamics is a mathematical framework for analysis of evolution. It assumes small phenotypic mutations and considers invasion possibility of a rare mutant. Generally invasion of a sufficiently similar mutant leads to substitution of the former resident. Consecutive invasion-substitution processes can lead to a singular strategy where directional evolution vanishes and evolution may stop or result in evolutionary branching. First I introduce some fundamental elements of adaptive dynamics. Then I construct a mathematical model for studying evolution. The model is created from the basis of the Hamilton-May model (1977). Last I analyse the model using tools I introduced previously. The analysis predicts evolution to a unique singular strategy in a monomorphic resident population. This singularity can be evolutionarily stable or branching depending on survival probabilities during different phases of dispersal. After branching the resident population becomes dimorphic. There seems to be always an evolutionarily stable dimorphic singularity. At the singularity one resident specializes fully to the well-connected sites while the other resides both types of sites. Connectivity difference of sites can lead to evolutionary branching in a monomorphic population and maintain a stable dimorphic population.

The Hawk-Dove game has been used as a model of situations of conflict in diverse fields as sociology, politics, economics as well as animal behavior. The iterated Hawk-Dove game has several rounds with payoff in each round. The thesis is about a version of the iterated Hawk-Dove game with the additional new feature that each player can unilaterally decide when to quit playing. After quitting, both players return to the pool of temporally inactive players. New games can be initiated by random pairing of individuals from within the pool. The decision of quitting is based on a rule that takes into account the actions of oneself or one's opponent, or on the payoffs received during the last or previous rounds of the present game. In this thesis, the quitting rule is that a player quits if its opponent acts as a Hawk. The additional feature of quitting dramatically changes the game dynamics of the traditional iterated Hawk-Dove game. The aim of the thesis is to study these changes. To that end we use elements of dynamical systems theory as well as game theory and adaptive dynamics. Game theory and adaptive dynamics are briefly introduced as background information for the model I present, providing all the essential tools to analyze it. Game theory provides an understanding of the role of payoffs and the notion of the evolutionarily stable strategies, as well as the mechanics of iterated games. Adaptive dynamics provides the tools to analyze the behavior of the mutant strategy, and under what conditions it can invade the resident population. It focuses on the evolutionary success of the mutant in the environment set by the current resident. In the standard iterated Hawk-Dove game, always play Dove (all-Dove) is a losing strategy. The main result of my model is that strategies such as all-Dove and mixed strategy profiles that are also not considered as worthwhile strategies in the standard iterated Hawk-Dove game can be worthwhile when quitting and the pool are part of the dynamics. Depending on the relations between the payoffs, these strategies can be victorious.

In this thesis, we study epidemic models such as SIR and superinfection to demonstrate the coexistence as well as the competitive exclusion of all but one strain. We show that the strain that can keep its position under the worst environmental conditions cannot be invaded by any other strain when it comes to some models with a constant death rate. Otherwise, the optimization principle does not necessarily work. Nevertheless, Ackleh and Allen proved that in the SIR model with a density-dependent mortality rate and total cross-immunity the strain with the largest basic reproduction number is the winner in competitive exclusion. However, it must be taken into account that the conditions on the parameters used for the proof are sufficient but not necessary to exclude the coexistence of different pathogen strains. We show that the method can be applied to both density-dependent and frequency-dependent transmission incidence. In the latter half, we link the between and within-host models and expand the nested model to allow for superinfection. The introduction of the basic notions of adaptive dynamics contributes to simplifying our task of demonstrating the evolutionary branching leading to diverging dimorphism. The precise conclusions about the outcome of evolution will depend on the host demography as well as on the class of superinfection and the shape of transmission functions.

A distributed system is a collection of networked autonomous processing units which must work in a cooperative manner. Currently, large-scale distributed systems, such as various telecommunication and computer networks, are abundant and used in a multitude of tasks. The field of distributed computing studies what can be computed efficiently in such systems. Distributed systems are usually modelled as graphs where nodes represent the processors and edges denote communication links between processors. This thesis concentrates on the computational complexity of the distributed graph colouring problem. The objective of the graph colouring problem is to assign a colour to each node in such a way that no two nodes connected by an edge share the same colour. In particular, it is often desirable to use only a small number of colours. This task is a fundamental symmetry-breaking primitive in various distributed algorithms. A graph that has been coloured in this manner using at most k different colours is said to be k-coloured. This work examines the synchronous message-passing model of distributed computation: every node runs the same algorithm, and the system operates in discrete synchronous communication rounds. During each round, a node can communicate with its neighbours and perform local computation. In this model, the time complexity of a problem is the number of synchronous communication rounds required to solve the problem. It is known that 3-colouring any k-coloured directed cycle requires at least ½(log* k - 3) communication rounds and is possible in ½(log* k + 7) communication rounds for all k ≥ 3. This work shows that for any k ≥ 3, colouring a k-coloured directed cycle with at most three colours is possible in ½(log* k + 3) rounds. In contrast, it is also shown that for some values of k, colouring a directed cycle with at most three colours requires at least ½(log* k + 1) communication rounds. Furthermore, in the case of directed rooted trees, reducing a k-colouring into a 3-colouring requires at least log* k + 1 rounds for some k and possible in log* k + 3 rounds for all k ≥ 3. The new positive and negative results are derived using computational methods, as the existence of distributed colouring algorithms corresponds to the colourability of so-called neighbourhood graphs. The colourability of these graphs is analysed using Boolean satisfiability (SAT) solvers. Finally, this thesis shows that similar methods are applicable in capturing the existence of distributed algorithms for other graph problems, such as the maximal matching problem.

Finland and Estonia form a cross-border region in Europe. Unlike other cross-border regions, which share a land border with their neighbor, Finland and Estonia are separated by the Gulf of Finland. The distance is close enough to facilitate regular travel by ferry on a weekly or monthly basis, but for Estonian immigrants living in Finland, daily commutes are unlikely. Given that Finland is the top migration destination for Estonians, the cross-border region of Estonia-Finland poses an interesting case study. In this thesis, the integration and transnationalism of Estonians living in Finland are studied through a spatial mobility lens. First, a theoretical framework is proposed to facilitate empirical research. The framework jointly examines integration and transnationalism by partitioning them into separate domains: social, structural, cultural, civic & political, identity, and spatial. The aim of the framework is to narrow the socio-spatial gap in migration literature, by focusing on the interwoven nature of the social and spatial perspectives. Using data from a comprehensive survey about Estonian immigrants living in Finland, the proposed theoretical framework is operationalized for multiple correspondence analysis (MCA). Three MCA analyses are performed: 1) social integration with host society (Finland), 2) social transnationalism with the sending society (Estonia), and 3) spatial transnationalism between the host society (Finland) and the sending society (Estonia). MCA results show that transnationalism and integration vary both across and within domains. MCA results are connected to one another using correlation analysis and general linear model (GLM) analyses. Correlation analysis and GLM demonstrate that for the study population, integration in the host society and transnationalism with the sending society are inversely associated. This inverse relationship carries over into the spatial domain and can be seen based on which country an immigrant does certain activities (e.g., visiting family, working, accessing healthcare, enjoying leisure time). Immigrants with strong social connections to the host society are more likely to do activities in Finland whereas immigrants with strong social connections to the sending society are more likely to do activities in Estonia. Some immigrants exhibit a multilocal mobility pattern, in which they do activities equally in both Estonia and Finland.