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The purpose of this thesis is to explain how the change of the zero tolerance policy in Stockholm against graffiti has been affected by the different formulations of graffiti as a problem. The purpose is fulfilled by applying a dynamic frameanalysis on the processes of creating and changing the policy. The analysis begins in the 1980s and continues until present time. By using this kind of process study the thesis shows that it was the actions made by the supporters of the zero tolerance-policy which started the changing process. It also shows that the process has not yet ended and the policy is likely to be changed again within the next few years.

Staphylococcus aureus and methicillin resistant Staphylococcus aureus (MRSA) are important pathogens of humans and livestock, including dairy cows. In livestock it represents a concern for public health as it may act as a reservoir that can infect humans and provide a source of transferrable resistance genes. The divergent mecA gene, mecC, was first identified in dairy cows in the UK, and has since been detected in many species in continental Europe. However, limited data exists on the epidemiological characteristics or the transmission dynamics of bovine mecC MRSA in the UK. S. aureus Mobile Genetic Elements (MGEs) often encode virulence and antimicrobial resistance genes that can contribute to the pathogenicity of the strain. Acquisition or loss of MGEs and variations within the core genome are reported to play an important role in S. aureus host adaptation although the mechanisms underlying S. aureus host specificity are not fully understood. This study was undertaken to determine the antimicrobial resistance and bovine associated virulence features of S. aureus isolated from bovine milk. The first two chapters of this thesis comprise of an introduction and a description of the methods used. Chapter 3 describes bovine associated features in bulk tank milk S. aureus isolates. SaPI borne-vwb and sec_bovine were widespread. Further, genome analysis detected six new SaPIs harbouring these genes and a class of site-specific integrases that appear to be associated with ruminant derived isolates. Examination of the fnbpA gene identified host specific variations that may be used to distinguish bovine from human isolates. Chapter 4 presents data on the epidemiological characteristics of mecC MRSA at the cow level within a dairy herd. Data from a longitudinal study undertaken suggested that mecC MRSA infections were transient and may not be associated with clinical disease. The prevalence varied between 1.14%-5.07% during the one-year study period, while SNP based whole genome phylogeny revealed four possible chains of transmission. Chapter 5 details a survey conducted to detect the prevalence of MRSA in UK retail meat. No mecC MRSA were found however CC398 were found and compared to CC398 isolates from the bulk tank milk study. A phylogenetic study provided no evidence of a common lineage of livestock association MRSA colonising both cattle and pigs in the UK. Chapter 6 describes the characterisation of a novel Streptococcus species isolated from a mastitic cow from New Zealand. Genome sequencing and phenotypic studies revealed this isolate, originally thought to be Streptococcus uberis to be most closely related to Streptococcus pseudoporcinus.

This dissertation focuses on developing algorithms that generate tool paths for free-form surfaces based on accuracy of desired manufactured part. A manufacturing part is represented by mathematical curves and surfaces. Using the mathematical representation of the manufacturing part, we generate reliable and near optimal tool paths as well as cutter location (CL) data file for postprocessing. This algorithm includes two components. First is the forward-step function which determines maximum distance called forward- step between two cutter contact (CC) points with given tolerance. This function is independent of the surface type and is applicable to all continuous parametric surfaces that are twice differentiable. The second component is the side-step function which determines maximum distance called side-step between two adjacent tool paths with a given scallop height. This algorithm reduces manufacturing and computing time as well as the CC points while keeping the given tolerance and scallop height in the tool paths. Several parts, for which the CC points are generated using the proposed algorithm, are machined using a three axes milling machine. As part of the validation process, the tool paths generated during machining are analyzed to compare the machined part and the desired part.

This thesis explores the role of the media in voting behaviour in Turkey in terms of the 2010 constitutional referendum. The media is a very important tool for both providing information and entertainment for people in Turkey. Thus, it can be claimed that the media are very powerful and have a large influence on audiences. In this study, I seek to explore the media’s power over citizens’ political choices. In other words, this thesis aims to reveal the affect the media content has on voters. To achieve this goal, I have chosen to analyse the 2010 referendum because of its special characteristics, which differentiate it from other referendums and elections in Turkey. Although there are many studies which examine the media effects on voting in the literature, these generally concentrate on developed democracies. Furthermore, general elections and presidential elections are more common in the field. The number of studies searching for the media’s effect on referendum voting in Turkey is very limited. For this reason, I prioritise referendums and the media systems to provide a better understanding of the Turkish case, as a developing democratic country. In addition to this, media content and public opinion constitute the main data for the methodological part of the study. In order to identify the influence of the media in the 2010 referendum, I employ a three-step method including firstly, an analysis of the public opinion survey data to understand voter preferences; secondly, media content analysis to see the media coverage on the referendum issue and the salience of the referendum in the media and; as the third and final step of the analysis, I link the public opinion data and the media content. My contribution to the field is the analysis of the media effects on referendum voting with a systematic and an extensive methodological approach, which is supported by the analysis of the media system in Turkey, as an example of developing country. I expect to contribute a comprehensive analysis of the referendum voting in respect of the media nested with the voter preferences to the literature on politics in Turkey.

Master of Arts / Department of Modern Languages / Emma Betz / Using conversation analytic methodology, this paper examines the self-repair of actions in everyday German conversation, with focus given to the replacement of verbs and the subsequent effect on actions. While study has been done on the function of recycling repair within a turn (Fox, Hayashi, Jesperson, 1996) no research has been done on the function of verb replacement and its effect on talk. This paper shows that verb replacement is a strategy employed by speakers in order to either a) negotiate what type of action is preferred within a particular TCU or b) to invoke external forces to either deflect an action, or to make a particular action available to an interlocutor. This paper concludes by discussing the specific function of this particular type of repair and how it is useful in repairing problematic actions.

Les médias sociaux ont changé notre manière de communiquer entre individus, au sein des organisations et des communautés. La disponibilité de ces données sociales ouvre de nouvelles opportunités pour comprendre et influencer le comportement des utilisateurs. De ce fait, la fouille des médias sociaux connait un intérêt croissant dans divers milieux scientifiques et économiques. Dans cette thèse, nous nous intéressons spécifiquement aux utilisateurs de ces réseaux et cherchons à les caractériser selon deux axes : (i) leur expertise et leur réputation et (ii) les sentiments qu’ils expriment.De manière classique, les données sociales sont souvent fouillées selon leur structure en réseau. Cependant, le contenu textuel des messages échangés peut faire émerger des connaissances complémentaires qui ne peuvent être connues via la seule analyse de la structure. Jusqu’à récemment, la majorité des travaux concernant l’analyse du contenu textuel était proposée pour l’Anglais. L’originalité de cette thèse est de développer des méthodes et des ressources basées sur le contenu pour la fouille des réseaux sociaux pour la langue Française.Dans le premier axe, nous proposons d'abord d’identifier l'expertise des utilisateurs. Pour cela, nous avons utilisé des forums qui recrutent des experts en santé pour apprendre des modèles de classification qui servent à identifier les messages postés par les experts dans n’importe quel autre forum. Nous démontrons que les modèles appris sur des forums appropriés peuvent être utilisés efficacement sur d’autres forums. Puis, dans un second temps, nous nous intéressons à la réputation des utilisateurs dans ces forums. L’idée est de rechercher les expressions de confiance et de méfiance exprimées dans les messages, de rechercher les destinataires de ces messages et d’utiliser ces informations pour en déduire la réputation des utilisateurs. Nous proposons une nouvelle mesure de réputation qui permet de pondérer le score de chaque réponse selon la réputation de son auteur. Des évaluations automatiques et manuelles ont démontré l’efficacité de l’approche.Dans le deuxième axe, nous nous sommes focalisés sur l’extraction de sentiments (polarité et émotion). Pour cela, dans un premier temps, nous avons commencé par construire un lexique de sentiments et d’émotions pour le Français que nous appelons FEEL (French Expanded Emotion Lexicon). Ce lexique est construit de manière semi-automatique en traduisant et en étendant son homologue Anglais NRC EmoLex. Nous avons ensuite comparé FEEL avec les lexiques Français de la littérature sur des benchmarks de référence. Les résultats ont montré que FEEL permet d’améliorer la classification des textes Français selon leurs polarités et émotions. Dans un deuxième temps, nous avons proposé d’évaluer de manière assez exhaustive différentes méthodes et ressources pour la classification de sentiments en Français. Les expérimentations menées ont permis de déterminer les caractéristiques utiles dans la classification de sentiments pour différents types de textes. Les systèmes appris se sont montrés particulièrement efficaces sur des benchmarks de référence. De manière générale, ces travaux ont ouvert des perspectives prometteuses sur diverses tâches d’analyse des réseaux sociaux pour la langue française incluant: (i) combiner plusieurs sources pour transférer la connaissance sur les utilisateurs des réseaux sociaux; (ii) la fouille des réseaux sociaux en utilisant les images, les vidéos, les géolocalisations, etc. et (iii) l'analyse multilingues de sentiment. / Social Media has changed the way we communicate between individuals, within organizations and communities. The availability of these social data opens new opportunities to understand and influence the user behavior. Therefore, Social Media Mining is experiencing a growing interest in various scientific and economic circles. In this thesis, we are specifically interested in the users of these networks whom we try to characterize in two ways: (i) their expertise and their reputations and (ii) the sentiments they express.Conventionally, social data is often mined according to its network structure. However, the textual content of the exchanged messages may reveal additional knowledge that can not be known through the analysis of the structure. Until recently, the majority of work done for the analysis of the textual content was proposed for English. The originality of this thesis is to develop methods and resources based on the textual content of the messages for French Social Media Mining.In the first axis, we initially suggest to predict the user expertise. For this, we used forums that recruit health experts to learn classification models that serve to identify messages posted by experts in any other health forum. We demonstrate that models learned on appropriate forums can be used effectively on other forums. Then, in a second step, we focus on the user reputation in these forums. The idea is to seek expressions of trust and distrust expressed in the textual content of the exchanged messages, to search the recipients of these messages and use this information to deduce users' reputation. We propose a new reputation measure that weighs the score of each response by the reputation of its author. Automatic and manual evaluations have demonstrated the effectiveness of the proposed approach.In the second axis, we focus on the extraction of sentiments (emotions and polarity). For this, we started by building a French lexicon of sentiments and emotions that we call FEEL (French Expanded Emotions Lexicon). This lexicon is built semi-automatically by translating and expanding its English counterpart NRC EmoLex. We then compare FEEL with existing French lexicons from literature on reference benchmarks. The results show that FEEL improves the classification of French texts according to their polarities and emotions. Finally, we propose to evaluate different features, methods and resources for the classification of sentiments in French. The conducted experiments have identified useful features and methods in the classification of sentiments for different types of texts. The learned systems have been particularly efficient on reference benchmarks.Generally, this work opens promising perspectives on various analytical tasks of Social Media Mining including: (i) combining multiple sources in mining Social Media users; (ii) multi-modal Social Media Mining using not just text but also image, videos, location, etc. and (iii) multilingual sentiment analysis.

In this essay we use complex analysis, in particular modern residue calculus, to compute certain Riemann integrals. / I den har uppsatsen använder vi komplex analys, då särskilt modern residykalkyl, for att beräkna vissa Riemann-integraler.

国立情報学研究所で電子化したコンテンツを使用している。

The purposes of this research are (1) to bridge this gap of deficiency by developing a simple, precise and reproducible routine analytical technique by using attenuated total reflectance, and (2) to serve as an atlas for identification of renal calculi.