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Denne oppgaven undersøker forholdet mellom det Bysantinske Riket og Petsjenegerne. Den undersøker Steppetradisjonen og den Bysantinske diplomatiske tradisjonen, og bruker dem for å vise at tiden Petsjenegerne brukte på de Pontiske steppene kan deles inn i to perioder. Den første perioden kjennetegnes med fredelige forhold og aktivt bysantinsk diplomati for å beholde freden og for å forsikre at Petsjenegerne var villig til å hjelpe bysantinerne mot andre politiske rivaler dersom det var nødvendig. Samtidig ble Petsjenegerne rikelig belønnet for tjenestene de gjorde for bysantinerne og mottok ofte gaver fra bysantinerne. Petsjenegerne og bysantinerne hadde derfor et forhold som tjente dem begge. Den andre perioden kjennetegnes med dårligere forhold og til slutt fiendtligheter. Dette var et resultat av økt ytre press satt på Petsjenegerne. Dette tvang Petsjenegerne mer mot sørvest og nærmere Bysants. I tillegg ser vi en endring i bysantinsk diplomati, som ikke lenger ser nytten i en allianse med Petsjenegerne. Derfor var ikke fred med Bysants ikke lenger mulig for Petsjenegerne som var avhengige av en kilde til prestisje og rikdom for å sikre samholdet til Petsjenegerne. This thesis will examine the relationship between the Byzantine Empire and the Pechenegs. It examines the Steppe Tradition and the Byzantine diplomatic tradition and uses them to demonstrate that the time the Pechenegs spent on the Pontic steppe can be divided into two periods. The first period is characterized by peaceful relations, accompanied by active Byzantine diplomacy to ensure peace and that the Pechenegs were willing to help the Byzantines against other political rivals in the area. At the same time, the Pechenegs were well rewarded for doing tasks for the Byzantines and received annual gifts from them. Thus, the Pechenegs and Byzantines created a relationship that was beneficial for both. The second period is characterized by the deterioration of Byzantine relations with the Pechenegs and in the end open hostility. This was caused by increased external pressure on the Pechenegs forcing the polity further southwestwards towards Byzantine lands. In addition, Byzantine diplomacy no longer favored an alliance with the Pechenegs. Thus, peace between the Pechenegs and Byzantines were no longer possible, as the Pechenegs needed a source of wealth and prestige in order to ensure the cohesion of their polity.

High-doses of anabolic–androgenic steroids (AAS) is efficient for building muscle mass, but pose a risk of cardiovascular side effects. Little is known of the effect of AAS on vasculature, but previous findings suggest unfavorable alterations in vessel walls and vasoreactivity. Here, long-term effect of AAS on vascular function and morphology were examined in male weightlifters, and in a mimicking animal model. Arterial elasticity and morphology were tested with ultrasound, pulse wave velocity (PWV) and carotid intima media thickness (cIMT) in 56 current male AAS users, and 67 non-exposed weightlifting controls (WLC). Female mice were treated with testosterone for 14 days and echocardiography were applied to evaluate vascular function and morphology. Male AAS users had higher PWV (p = 0.044), reduced carotid artery compliance (p = 0.0005), and increased cIMT (p = 0.041) compared to WLC. Similar functional changes were found in the ascending aorta of mice after 7- (p = 0.043) and 14 days (p = 0.001) of testosterone treatment. This animal model can be used to map molecular mechanisms responsible for complications related to AAS misuse. Considering the age-independent stiffening of major arteries and the predictive power of an increase in PWV and cIMT, the long-term users of AAS are at increased risk of severe cardiovascular events.

This thesis explores the use of deep learning and variational inference in Carbon Capture and Storage (CCS) monitoring. It consists of an introductory part and three scientific papers. The first chapter introduces CCS and techniques for monitoring of such sites from both a marine and subsurface perspective. The next chapter introduces the basic concepts of deep learning. Further, an introduction to Bayesian neural networks and variational inference as tools for assessing uncertainty in deep models is presented. The last chapter of the introductory part presents how dropout in a neural network can approximate variational inference and different variational auto-encoder models. In part two, three papers are presented that use variational inference to obtain uncertainty estimates in different applications. The first paper presents an algorithm that probabilistically classifies time series from a marine environment to determine if it arise from a CCS leakage incident and uses a Bayesian decision rule to optimally decide whether to initiate costly actions. The second paper presents a novel variational auto-encoder model for probabilistic reconstruction of flow fields given sparse measurements. The last paper presents a variational auto-encoder for reservoir monitoring. The proposed variational auto-encoder can both reconstruct the above zone monitoring interval (AZMI) pressure and classify the flux rate of the CO2 leakage given only the sparse observations from the AZMI wells. Doktorgradsavhandling

Aim: Skeletal muscle is a heterogeneous tissue containing several different cell types, and only about 40%‐50% of the cell nuclei within the tissue belong to myofibres. Existing technology, attempting to distinguish myonuclei from other nuclei at the light microscopy level, has led to controversies in our understanding of the basic cell biology of muscle plasticity. This study aims at demonstrating that an antibody against the protein pericentriolar material 1 (PCM1) can be used to reliably identify myonuclei on histological cross sections from humans, mice and rats. Methods: Cryosections were labelled with a polyclonal antibody against PCM1. The specificity of the labelling for myonuclei was verified using 3D reconstructions of confocal z‐stacks triple‐labelled for DNA, dystrophin and PCM1, and by co‐localization with nuclear mCherry driven by the muscle‐specific Alpha‐Actin‐1 promoter after viral transduction. Results: The PCM1 antibody specifically labelled all myonuclei, and myonuclei only, in cryosections of muscles from rats, mice and men. Nuclei in other cell types including satellite cells were not labelled. Both normal muscles and hypertrophic muscles after synergist ablation were investigated. Conclusion: Pericentriolar material 1 can be used as a specific histological marker for myonuclei in skeletal muscle tissue without relying on counterstaining of other structures or cumbersome and subjective analysis of nuclear positioning.