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This thesis presents the results from seventeen collisionless merger simulations of massive early-type galaxies in an effort to understand the coalescence of supermassive black holes (SMBHs) in the context of the Final Parsec Problem. A review of the properties of massive early-type galaxies and their SMBHs is presented alongside a discussion on SMBH binary coalescence to motivate the initial conditions used in the simulations. The effects of varying SMBH mass and stellar density profiles in the progenitor initial conditions on SMBH coalescence was investigated. Differing mass resolutions between the stellar particles and the SMBHs for each physical realisation were also tested. The simulations were performed on the supercomputers Puhti and Mahti at CSC, the Finnish IT Centre for Science. SMBH coalescence was found to only occur in mergers involving SMBH binaries of equal mass, with the most rapid coalescence observed in galaxies with a steep density profile. In particular, the eccentricity of the SMBH binary was observed to be crucial for coalescence: all simulations that coalesced displayed an orbital eccentricity in excess of e=0.7 for the majority of the time for which the binary was bound. Simulations of higher mass resolution were found to have an increased number of stellar particles able to positively interact with the SMBH binary to remove orbital energy and angular momentum, driving the binary to coalescence. The gravitational wave emission from an equal mass SMBH binary in the final stages before merging was calculated to be within the detection limits required for measurement by pulsar timing arrays. Mergers between galaxies of unequal mass SMBHs were unable to undergo coalescence irrespective of mass resolution or progenitor density profile, despite the binary in some of these simulations displaying a high orbital eccentricity. It was determined that the stellar particles interacting with the SMBH binary were unable to remove the required orbital energy and angular momentum to bring the SMBHs to within the separation required for efficient gravitational wave emission. A trend between increasing mass resolution and increasing number of stellar particles able to remove energy from the SMBH binary was observed across all the simulation suites. This observation is of paramount importance, as three-body interactions are essential in removing orbital energy and angular momentum from the SMBH binary, thus overcoming the Final Parsec Problem. As such, it is concluded that the Final Parsec Problem is a numerical artefact arising from insufficient mass resolution between the stellar particles and the SMBHs rather than a physical phenomenon.

A myriad of different volatile organic compounds is emitted to the atmosphere through biogenic and anthropogenic pathways. In the atmosphere, they get oxidised forming products of lower volatility, which may then condense and contribute to the formation and growth of aerosol particles. Extremely low-volatility organic compounds (ELVOC) is a group of highly oxidised molecules that were recently observed in oxidation of biogenically emitted molecules, monoterpenes. It has been shown that ELVOCs from monoterpene oxidation in the atmosphere explain most of the aerosol growth rates in the boreal forest. In this work, I investigate the ELVOC formation from aromatic compounds, which are primarily emitted from anthropogenic sources. This thesis focuses on oxidation of benzene, a simplest aromatic molecule, although ELVOCs forming from toluene, naphthalene and phenol are also presented. The experimental work with all compounds, except phenol, was conducted in a flow tube at the Universtity of Helsinki, Finland, while in-depth study of benzene was performed in the chamber at Forschungszentrum Jülich GmbH, Germany. The oxidation products were detected using nitrate-based scheme chemical ionisation atmospheric pressure interface time-of-flight mass spectrometer (CI-APi-TOF). It was found that all four molecules in the reaction with a hydroxyl radical produced ELVOC. In case of benzene, the detected ELVOC monomers had maximum of 11 oxygen atoms, while dimers had up to 18. Toluene and naphthalene oxidation gained ELVOC monomers with maximum 10 oxygen atoms. The possibility of multiple reactions with the hydroxyl radical, however, could not be eliminated as the products of aromatic oxidation usually have higher reaction rate coefficients than their parent molecule. The average ELVOC molar yield in benzene oxidation was 3.7%, while in phenol case it was 1.5%, which suggested that primary OH attack and further autoxidation is an important pathway for ELVOC formation in oxidation of benzene. The study of the ELVOC – aerosol particle interactions in the chamber revealed that ELVOCs from aromatic precursors behave similarly to the ELVOCs formed from monoterpenes, rapidly condensing on the introduced aerosol particles. The organic fraction of the aerosols had similar O:C ratio to the total gas-phase ELVOC, indicating that ELVOCs were primary condensing species. The decreasing O:C ratio of aerosol phase with higher aerosol loading confirmed that ELVOCs are dominating aerosol growth at low aerosol loading. In this thesis, also a review of known chemical pathways of benzene oxidation is presented and some further steps towards ELVOC formation are suggested. Benzene oxidation pathways may serve as a model for studying the oxidation of other aromatic molecules. Substituted aromatic molecules are more reactive with the hydroxyl radical and are likely to yield more ELVOCs, which may be dominant factor in the aerosol growth in urban and industrialised areas.

The debate over antidepressants, especially SSRIs, has lasted for more than a decade, the controversy revolving mostly around their efficacy over placebo as a treatment of depression. Sure enough, one gets conflicting results depending on which primary outcome measure is chosen as that operationalizing 'treatment effect' and where to delimit its 'clinically significant' size. Moreover, including only published studies in an evidence base assumed wholly unbiased artificially inflates the efficacy claims being made. The stakes are high: depression is estimated as one of the costliest of all illnesses, accounting for as much as 12% of the global burden of disease. However, so far, the debate has been nitpicking in the sense of not seeing the forest for the trees; and the poor forestry may just end up killing more than the weight of the already hefty one eighth. What has not been pointed out prior, then, is that there is something more fundamentally wrong here; something only indirectly reflected in the multiple points of controversy, responsible for this and other debates akin to it resting in a state of stalemate and confusion. I argue that this something is the wrong statistical paradigm we've embraced in clinical guideline development. I make my case by identifying two classes of controversy in the antidepressant debate: those related with patient preference and those with model choice. I hint at how these issues could be resolved, if a better framework was adopted, yet cannot even hope to be resolved within the present paradigm. In terms of the first class of issues, I argue that we haven't been able to agree upon an appropriate operationalization of 'treatment effect', nor its threshold of 'clinically significant', nor 'severity of depression', because we have discounted decision theory and the incorporation of patient preference in treatment choice to go along with it. In terms of establishing the conclusions to a given operationalization of any of the above by the means of valid argument based on premises backed up by trustworthy evidence, there is next to nothing to cling on to in the present guidelines of depression. For valid argument, we require the language of decision theory; for a purposeful evidence base we require utilities and outcome measures so chosen as to be able to establish rational patient centered choice. We need predictions of all important treatment outcomes for a patient exchangeable with some subset of those in the evidence base, not parameter inferences of summary statistics of treatment effect, the size of which is interpreted from a vantage point dependent on arbitrary choices over the primary outcome measure and a cut-off value for clinical significance. In terms of the second class of issues, we haven't taken proper account of uncertainty in deriving the interval estimates for our already ill-founded meta-analytic summary effects either. What full probability model to entertain for one's inferences – how to account for publication bias, between trial heterogeneity, inconsistency, poor quality trials and the like – is a matter of subjective model choice. The seemingly 'objective' protocol having been applied across the board is based on classical fixed and random effects meta-analyses with a tacit assumption of zero bias. Applying such protocol means placing all our eggs in a broken basket. I show that at present the meta-analytic models endeared rest on false assumptions, yielding biased and overconfident interval estimates. Since the evidence statements depend on whether an arbitrarily chosen threshold value for reaching 'clinical significance' is included in the fallacious interval estimate inferred, the evidence statements, that in turn ground the recommendations of the guidelines, are fallacious, too. I show the 'subjectivity' of the allegedly 'objective' evidence statements by conditioning the inferences over meta-analytic summary statistics of treatment effect on a set of plausible candidate models none of which, importantly enough, can be considered 'objective' in the sense of dominating as model choices universally preferred over all the others. I apply the framework to an evidence base used in the leading guideline of depression treatment. I show how the flexibility of the Bayesian framework enables more credible meta-analytic models, and better evidence statements with more intuitive interpretations. The Bayesian paradigm also allows for merging the output from multiple candidate models in a model-averaged posterior predictive better calibrated for rational choice than any classical parameter estimator could ever hope to be. The antidepressant debate is therefore not only a singular case with problems particular to it, but rather one sad example of classical statistics, and the evidence based medicine movement it has hijacked, being unable to deal with decision nor uncertainty. What to measure, how, and where to draw threshold values cannot be answered without accounting for patient preference. Since parameter and model uncertainty are always present, this uncertainty needs to be accounted for one way or the other, the most plausible means so far offered being probability calculus, the coherent application of which requires assigning distributions to unknowns classical statistics treats as fixed. To be able to convincingly deal with both decision and uncertainty is a prerequisite for any viable framework steering the development of clinical guidelines that ultimately cannot help but concern decision under uncertainty, be the application to the treatment of depression, or any other ailment found in DSMIV, or ICD10, for that matter. The wrong paradigm is bankrupting us, placing a serious threat on the credibility of all applied medicine. Something needs to be done.

The sampling was done in 2013 during the Integrated Ocean Drilling Program Expedition 347 on two sites in the river Ångermanälven estuary in Sweden. The area has had the highest rate of uplift in Fennoscandia since the last glaciation. The area was freed from ice 10 500 years before present, after which the shore displacement has been notable. The sedimentation environment has changed considerably from an ice proximal setting, through open sea to a less exposed estuary. The varve deposition is an ongoing process in the estuary since several thousands of years, and it has been correlated to annual discharge, which makes the estuary interesting for palaeoenvironmental studies. The aim of the study was to analyze the changes in the grainsize distribution and to link these changes to the environmental changes. The initial subsampling was made in Bremen in 2014 and the analysis in the laboratory of the Department of Geosciences and Geography of the University of Helsinki in 2015. A method, in compliance to the ISO 13320:2009 standard, was used in the laser diffraction particle size analysis. Also the water content and loss-on-ignition (LOI) was determined from selected samples. The results were processed with the statistics program GRADISTAT 8.0. The resulting figures were compared between the sites and displayed as a function of depth. The sediment consists of varying silt and sand deposits, in which both regular and irregular changes were seen. Interpretations of the sedimentation environments were made and compared with the results of earlier studies. At least three sedimentary units were recognized. Within the upper organic rich silt unit, the point of maximum salinity of the Baltic Sea was recognized. Also the effects of the shoreline displacement, as a coarsening of the sediment, with the decreasing distance to the source of the material, were noted. The unit was interpreted to the brackish Litorina Sea stage. The middle unit was more varied and the relationship between the two sites was more complex. A finer sample resolution would have been needed for an accurate interpretation of this unit. However the interpretation was the fresh water stage of the Ancylus Lake. The lower sandy unit showed indications of a glaciofluvial environment and also the change of distance to the source of the material. The interpretation was a fresh water lake and an ice proximal setting. This study utilized material from the CISU-project funded by the Academy of Finland (resolution 281143).

Finnish society is rapidly becoming more diverse, which is also reflected in the housing preferences and choices. A growing group in the Finnish housing market is the children of immigrants also known as the second-generation. Second-generation successes and challenges in integrating into society have been a hot topic around Europe including in Finland. Despite the groups growing presence a little is known about their housing preferences or choices especially in the case of Finland. This thesis aims to study the housing preferences and choices of second-generation Somalis in Helsinki. The data of this research is based on fifteen semi-structured interviews of young second-generation Somalis between the ages of 25 and 29 and statistical data received from the City of Helsinki and Stat Finland that was visualized into thematic maps demonstrating the spatial distribution of Somali-speakers in Helsinki. This thesis is a part of the Helsinki Institute of Urban Regional Studies’s (Urbaria) project Housing& Migrants Immigrants, spatial capital, and urban housing diversity: A comparative study of non-native population groups in the Helsinki metropolitan area. The findings of this study highlighted how culture and religion affects the housing preferences and choices of second-generation Somalis and how this group is positioned between different cultural norms. The values of the interviewees are indicative of an ongoing assimilation process; however, the remaining importance of culture and religion prevents the full integration to Finnish housing culture. This is especially visible in relation to homeownership, which is a desired form of tenure for many but deemed as impossible to pursue in the current Finnish housing market as there are no Sharia-compliant mortgage options. Furthermore, the findings emphasized that the perception about the possibility of fulfilling one’s housing preferences had a major impact on the sense of belonging among the interviewees and the desire to build a life in Finland.

In recent decades, rapid urbanization together with industrialization has led to an increase in anthropogenic emissions, resulting in high air pollution concentrations and poor air quality particularly in developing countries, such as in China. Due to both the enhanced environmental and severe public health risks poor air quality is causing and the climate impacts of aerosols, it is of great interest to study and understand aerosol particles and their impact on our surroundings. Aerosols affect the radiative properties of the atmosphere and the surface energy balance. The impact of aerosols on the surface radiative fluxes of the urban surface energy balance is widely known, but the impact on the turbulent energy fluxes, which are important components in the energy balance, has until now remained unclear. To extend the knowledge of aerosol impacts on all the energy balance components, a simple urban land surface model (SUEWS) during the period of 2006-2009 is used, together with aerosol data, Aerosol Optical Depth (AOD), received from an AERONET station located in Beijing. With the use of commonly measured meteorological variables together with parameters defined for the study area of 1 km radius around a meteorological tower, the components of the urban surface energy balance are simulated by the model. For further data analysis, the data are divided into thermal seasons and pollutant categories according to the available AOD-data. Extreme polluted conditions are achieved during 24 % for the time of available AOD-data, additionally showing relatively less situations with poor air quality (8 %) in winter compared to 27 % observed in summer. The aim of this study is to analyse how much aerosol particles can modify the different surface energy balance components, particularly focusing on the turbulent fluxes. The model is evaluated against observed turbulent fluxes in the same tower, showing an overestimation of the sensible heat flux and an underestimation and a better model performance of the latent heat flux. Still, the diurnal behaviour of the fluxes is shown to be well reproduced by the model. The behaviour of the modelled components is further investigated, showing a clear monthly variation for almost all the fluxes contributing to the surface energy balance. The behaviour of the total energy balance is in general controlled by the wet (occurring from May to October) and dry periods, distinguishing the climate in Beijing. The sensible heat flux is the dominant flux in March, accounting for 59 % of the available energy, whereas during the wet periods, higher portion of the available energy is consumed by the turbulent latent heat flux (61 % in August). Adding the effect of aerosols, the results clearly show how the net radiative flux is decreased in poor air quality conditions, giving differences of 138 W/m2 in the median flux due to aerosol loading in the atmosphere. The main finding of this study is that aerosols also influence the turbulent fluxes, with largest aerosol impact on the sensible heat flux occurring during thermal spring (66 W/m2 difference between clean and polluted air conditions). Likewise, in summer, when the latent heat flux is the largest contributor for consuming the available energy, the influence of aerosols is most visible (25 W/m2 difference). This study highlights the importance of maintaining measurements of aerosol concentrations and characteristics of the pollutants over urban areas due to their influence not only on the radiative fluxes, but all the components of the surface energy balance, which can further alter the water circulation and give rise to other environmental risks. These findings can therefore be used in urban planning and issues related to water management and air pollution regulations.

Global warming is rapidly reducing the Arctic sea ice cover. Along with its major impacts in the Arctic, the sea ice loss is known to affect the climate in remote continental areas. In this thesis, the remote effects are studied by analysing data from experiments carried out using the ECHAM6 atmospheric general circulation model forced with simple sea ice concentration and sea surface temperature configurations. The European and Asian midlatitude winter responses of surface air temperature are investigated, together with anomalies of variables potentially affecting them: sea level pressure, thermal advection, adiabatic and diabatic heating and surface energy fluxes. Arctic sea ice loss was found to have contributed weakly to the European warming from the 1980s to the 2010s. With sea ice and sea surface temperature conditions projected for 2071–2100, the warming response was about 1 °C relative to the 1979–2008 climatology, despite a negative North Atlantic Oscillation phase response. In Asia, the model simulates slight cooling of about 0.5 °C east of the Urals in the past and in the eastern parts of the continent in the future. However, the cooling responses are overwhelmed by the warming effect of global forcings. The effects of internal variability are large, and the role of the thermodynamic processes and surface energy fluxes in the link between the Arctic and Eurasia is not very clear. However, the temperature responses are mostly consistent with previous research, even though the model does not capture the observed past changes well.

Air temperatures are commonly higher in urban environments compared to rural ones. The energy input of solar radiation and its storage in urban surfaces changes the way the surface interacts with the atmosphere through turbulent fluxes and mixing processes. The complexity of radiative properties combined with the effect of urban geometry makes the magnitude of the effect radiation has on the dynamics of boundary layer flow an important area of study. The aim of this study is to understand and quantify how much the radiative processes alter the flow field and turbulence in a real urban street canyon in Helsinki. The model used is the large-eddy simulation (LES) model PALM, which solves for the flow and the most relevant atmospheric scales that describe interactions between the surface and atmosphere. An additional library called RRTMG (Rapid Radiative Transfer Model for Global Models) is used in this study to provide the radiation input impacting the boundary layer flow. Two embedded surface models in PALM, USM (Urban Surface Model) and LSM (Land-Surface Model) are used to solve the local conditions for radiative balance based on the output of RRTMG. Two model runs are made (RRTMG On & RRTMG Off), both identical in terms of the large-scale forcing boundary conditions and land-use data, but with additional radiation input in RRTMG On. The results show that radiation alters the low level stratification of potential temperature, which leads to more unstable conditions. Near-surface air temperatures within the canyon were increased by 3.9 C on average. Horizontal wind speeds increased by 76 % close to the ground compared to RRTMG Off. RRTMG On also showed a change in the structure of the topographically forced canyon vortex, as the low wind conditions enabled the radiative effects to have a stronger effect in its forcing. The center of the vortex changed in location more towards the center of the canyon and the vertical motions on opposing sides of the street were strengthened by 0.15 m/s in both vertical directions. Additionally both mechanical and thermal turbulence production increased with RRTMG On, while the thermal production remained smaller by one magnitude compared to mechanical production within Mäkelänkatu. Higher wind speeds and their variance gave rise to increased mechanical production of turbulence and radiative effects increased the thermal production. More research is however needed to determine thermal turbulence's role in situations with different meteorological conditions or in other cities.

Chord is a distributed hash table solution that makes a set of assumptions about its performance and how that performance is affected when the size of the Chord network increases. This thesis studies those assumptions and the foundation they are based on. The main focus is to study how the Chord protocol performs in practice by utilizing a custom Chord protocol implementation written in Python. The performance is tested by measuring the length of lookup queries over the network and the cost of maintaining the routing invariants. Additionally, the amount of data being exchanged when a new Chord node joins the network and how data has been distributed over network in general is also measured. The tests are repeated using various different networks sizes and states. The measurements are used to formulate models and those models are then used to draw conclusions about the performance assumptions. Statistical measurements of quality are used to estimate the quality of the models. The Ukko high performance cluster is used for running the Chord networks and to execute the tests.

Substratum and environmental variables influence benthic algal species richness and community composition. Benthic habitats form complex connections within and between communities leading to unique water ecosystems. In order to better understand substratum relationships and the effects of environmental covariates towards microorganisms, this study focused on benthic diatoms in subarctic mountain ponds living in different substrata. Moreover, methodological choices are important for field survey in freshwater environments and thus in this study, we also compared sponge and brush sampling techniques to examine possible differences in benthic diatom species richness and community composition. We sampled 23 subarctic ponds between July and August 2022 in northern Fennoscandia. The samples were taken from stones and sediment. To analyse the differences between species richness for substrata and methods, we used paired Wilcoxon signed-rank test and paired t-test. In order to find out the most significant environmental variables influencing diatom species richness, we used generalized linear models (GLM). Differences in diatom community compositions were analysed using non-metric multidimensional scaling (NMDS), analysis of similarities (ANOSIM), and Jaccard similarity index. Finally in order to visualise the variation in community composition between stone and sediment samples explained by environmental variables, a redundancy analysis (RDA) was used. Benthic diatom species richness significantly differed between rock and sediment substrata where sediment was the most species rich substratum. Local environmental variables were influential towards diatom species richness, where water pH was the major determinant for both substrata. Diatom community composition did not differ significantly between rock and sediment substrata but was defined by environmental variables such as pond surface area and water pH having a strong influence on both substrata. No significant differences were found between sampling methods in terms of diatom species richness or community composition. Our results support the theory that sediment substratum contains the highest diatom species richness. Furthermore, the study highlights the importance of water pH on benthic diatoms regardless of substratum, supporting diatom reliability as bioindicators for water pH.