Dans les tokamaks, les instabilités nommées ELMs (pour ``Edge Localized Modes'') génèrent des relaxations quasi-périodiques du plasma, potentiellement néfastes pour le divertor d'ITER. Une méthode de contrôle des ELMs prévue pour ITER est l'application de Perturbations Magnétiques Résonantes (RMPs), capables de mitiger ou supprimer les ELMs dans les tokamaks existants. Afin d'améliorer la compréhension de l'interaction entre les ELMs, les RMPs et les écoulements du plasma et de réaliser des prédictions fiables pour ITER, la simulation non-linéaire des ELMs et des RMPs est réalisée avec le code de MHD réduite JOREK, en géométrie réaliste. Les effets bi-fluides diamagnétiques, la friction poloidale néoclassique, une source de rotation parallèle et les RMPs ont été ajoutés dans JOREK pour simuler la pénétration des RMP en prenant en compte la réponse cohérente du plasma. Dans un premier temps, la réponse du plasma aux RMPs (sans ELMs) est étudiée dans le cas des tokamaks JET, MAST et ITER, pour des paramètres réalistes. Ensuite, la dynamique cyclique des ELMs (sans RMPs) est modélisée pour la première fois en géométrie réaliste. La compétition entre la stabilisation du plasma par la rotation diamagnétique et sa déstabilisation par la source de chaleur induit la reconstruction cyclique du piédestal. Enfin la mitigation et la suppression des ELMs sont obtenues pour la première fois dans nos simulations. Le couplage non-linéaire des RMPs avec des modes instables du plasma induit une activité MHD continue à la place des violentes relaxations d'ELMs. Au-delà d'un seuil de perturbation magnétique, la suppression totale des ELMs est également observée. / The growth of plasma instabilities called Edge Localized Modes (ELMs) in tokamaks results in the quasi-periodic relaxations of the edge plasma, potentially harmful for the divertor in ITER. One of the promising ELM control methods planned in ITER is the application of external resonant magnetic perturbations (RMPs), already efficient for ELM mitigation/suppression in current tokamak experiments. However a better understanding of the interaction between ELMs, RMPs and plasma flows is needed to make reliable predictions for ITER. In this perspective, non-linear modeling of ELMs and RMPs is done with the reduced MHD code JOREK, in realisitic geometry including the X-point and the Scrape-Off Layer. The two-fluid diamagnetic drifts, the neoclassical friction, a source of parallel rotation and RMPs have been implemented to simulate the RMP penetration consistently with the plasma response. As a first step, the plasma response to RMPs (without ELMs) is studied for JET, MAST and ITER realistic plasma parameters and geometry. Then the cyclic dynamics of the ELMs (without RMPs) is modeled for the first time in realistic geometry. After an ELM crash, the diamagnetic rotation is found to be instrumental to stabilize the plasma and to model the cyclic reconstruction and collapse of the plasma pressure profile. Last the ELM mitigation and suppression by RMPs is observed for the first time in modeling. The non-linear coupling of the RMPs with unstable modes is found to induce a continuous MHD activity in place of a large ELM crash, resulting in the mitigation of the ELMs. Over a threshold in magnetic perturbation, the full ELM suppression is also observed.

This master thesis will discuss elements of using celebrity in marketing communication. Theory will cover basic communication process, Elaboration Likelihood Model, and meaning transfer model but main focus will be in discussing various celebrity selection theories, identifying different risks involved in using celebrities in marketing communication and investigating ways how to utilize celebrities to enhance the communication. Several examples are included to provide connection to real life use of celebrities.

The purpose of this investigation is to determine whether or not Denton County gained or lost from the construction of Lake Dallas from the tax valuation standpoint.

This thesis deals with fraud detection in a real-world environment with datasets coming from Svenska Handelsbanken. The goal was to investigate how well machine learning can classify fraudulent transactions and how new additional features affected classification. The models used were EFSVM, RUTSVM, CS-SVM, ELM, MLP, Decision Tree, Extra Trees, and Random Forests. To determine the best results the Mathew Correlation Coefficient was used as performance metric, which has been shown to have a medium bias for imbalanced datasets. Each model could deal with high imbalanced datasets which is common for fraud detection. Best results were achieved with Random Forest and Extra Trees. The best scores were around 0.4 for the real-world datasets, though the score itself says nothing as it is more a testimony to the dataset’s separability. These scores were obtained when using aggregated features and not the standard raw dataset. The performance measure recall’s scores were around 0.88-0.93 with an increase in precision by 34.4%-67%, resulting in a large decrease of False Positives. Evaluation results showed a great difference compared to test-runs, either substantial increase or decrease. Two theories as to why are discussed, a great distribution change in the evaluation set, and the sample size increase (100%) for evaluation could have lead to the tests not being well representing of the performance. Feature aggregation were a central topic of this thesis, with the main focus on behaviour features which can describe patterns and habits of customers. For these there were five categories: Sender’s fraud history, Sender’s transaction history, Sender’s time transaction history, Sender’shistory to receiver, and receiver’s history. Out of these, the best performance increase was from the first which gave the top score, the other datasets did not show as much potential, with mostn ot increasing the results. Further studies need to be done before discarding these features, to be certain they don’t improve performance. Together with the data aggregation, a tool (t-SNE) to visualize high dimension data was usedto great success. With it an early understanding of what to expect from newly added features would bring to classification. For the best dataset it could be seen that a new sub-cluster of transactions had been created, leading to the belief that classification scores could improve, whichthey did. Feature selection and PCA-reduction techniques were also studied and PCA showedgood results and increased performance. Feature selection had not conclusive improvements. Over- and under-sampling were used and neither improved the scores, though undersampling could maintain the results which is interesting when increasing the dataset. / Denna avhandling handlar om upptäcka bedrägerier i en real-world miljö med data från Svenska Handelsbanken. Målet var att undersöka hur bra maskininlärning är på att klassificera bedrägliga transaktioner, och hur nya attributer hjälper klassificeringen. Metoderna som användes var EFSVM, RUTSVM, CS-SVM, ELM, MLP, Decision Tree, Extra Trees och Random Forests. För evaluering av resultat används Mathew Correlation Coefficient, vilket har visat sig ha småttt beroende med hänsyn till obalanserade datamängder. Varje modell har inbygda värden för attklara av att bearbeta med obalanserade datamängder, vilket är viktigt för att upptäcka bedrägerier. Resultatmässigt visade det sig att Random Forest och Extra Trees var bäst, utan att göra p-test:s, detta på grund att dataseten var relativt sätt små, vilket gör att små skillnader i resultat ej är säkra. De högsta resultaten var cirka 0.4, det absoluta värdet säger ingenting mer än som en indikation om graden av separation mellan klasserna. De bäst resultaten ficks när nya aggregerade attributer användes och inte standard datasetet. Dessa resultat hade recall värden av 0,88-0,93 och för dessa kunde det synas precision ökade med 34,4% - 67%, vilket ger en stor minskning av False Positives. Evluation-resultaten hade stor skillnad mot test-resultaten, denna skillnad hade antingen en betydande ökning eller minskning. Två anledningar om varför diskuterades, förändring av evaluation-datan mot test-datan eller att storleksökning (100%) för evaluation har lett till att testerna inte var representativa. Attribute-aggregering var ett centralt ämne, med fokus på beteende-mönster för att beskriva kunders vanor. För dessa fanns det fem kategorier: Avsändarens bedrägerihistorik, Avsändarens transaktionshistorik, Avsändarens historik av tid för transaktion, Avsändarens historik till mottagaren och mottagarens historik. Av dessa var den största prestationsökningen från bedrägerihistorik, de andra attributerna hade inte lika positiva resultat, de flesta ökade inte resultaten.Ytterligare mer omfattande studier måste göras innan dessa attributer kan sägas vara givande eller ogivande. Tillsammans med data-aggregering användes t-SNE för att visualisera högdimensionsdata med framgång. Med t-SNE kan en tidig förståelse för vad man kan förvänta sig av tillagda attributer, inom klassificering. För det bästa dataset kan man se att ett nytt kluster som hade skapats, vilket kan tolkas som datan var mer beskrivande. Där förväntades också resultaten förbättras, vilket de gjorde. Val av attributer och PCA-dimensions reducering studerades och PCA-visadeförbättring av resultaten. Over- och under-sampling testades och kunde ej förbättrade resultaten, även om undersampling kunde bibehålla resultated vilket är intressant om datamängden ökar.

Almsjukan är en vissnesjukdom orsakad av invasiva skadesvampar i släktet Ophiostoma. På grund av almsjukan är svenska almar kritiskt hotade och nya metoder att skydda almar behövs därför akut. Biologisk kontroll är en lovande strategi mot trädsjukdomar som almsjukan, men det behövs mer kunskap innan metoden kan tillämpas i praktiken. Endofytsvampar som lever inuti växter utan att orsaka symptom har visat sig kunna forma trädets motståndskraft. I tidigare in vitro studier har en endofytsvamp i släktet Fusarium uppvisat kemisk antagonism mot almsjukepatogener i odling på standardagar. I denna studie undersöktes om samma reaktion även uppkommer när svampar odlas på agar som berikats med almbarkextrakt som innehåller bl.a. fenoliska substanser. I in vitro tester med Fusarium-svampen och två Ophiostoma-isolater upptäcktes att den antagonistiska reaktionen fanns kvar trots almkemikalier, vilket antyder att reaktionen kan vara stabil även inuti almar. Resultaten tyder på att almens kemikalier kan förstärka Fusarium-svampens antagonism mot den aggressivare patogenen, O. novo-ulmi. Studien bekräftar därför Fusarium endofytens potential i biokontroll av almsjukan.

The study examined the frequent frames adopted by the CDC in the communication of the Covid-19 vaccine and how it impacts vaccine uptake through quantitative content analysis. The study builds on the framing theory and elaboration likelihood model. This study’s content collected 327 posts by the CDC on covid-19 vaccinations from December 2020- December 2022. A research randomizer was used to choose 200 posts as the final sample from the data that had been gathered. 122 posts out of the 200 total posts that the randomizer tallied were pertinent to the research questions for the study. It was found that the predominant framing strategy adopted by the CDC was the gain framing strategy, which outlined the benefits of being vaccinated. This is encouraging since, as advocates of health communication, we must understand that emphasizing the benefits of adopting a recommended action has a greater chance of having a positive impact.

Technology is changing the structure and dynamics of how humans communicate. Channels of communication are also used for attempts at persuasion, but until now persuasion that (if accepted) would promote the adoption of misinformation could not spread as readily through historical information channels. With the advent of the Internet and World Wide Web this has changed dramatically. In this dissertation it is argued that modern digital communication media such as YouTube, in confluence with what theories of persuasion have to say about how humans deal with persuasion, may create a situation in which misinformation may spread and be accepted on a large scale. The research in this dissertation explores this notion by presenting a group of 120 adolescents who are familiar with the Web with such a misinforming persuasive message. The purpose of which is to determine whether they accept the misinformation presented in the Web-context or are sceptical of it. Different manipulations were done to the persuasive message, known to increase the likelihood of persuasion. The research found that, for this group of participants, no attempt to increase uncritical acceptance of a persuasive message made a statistical difference between different groupings of participants. When intended behaviour was measured in addition to attitude towards the misinformation, participants were even less persuaded. The results are interesting as a starting point for further study, but its generalizability and certain design features must be called into question / Psychology / M.A. (Psychology)

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Sun-exposed broad leaved deciduous trees have a great species diversity of epiphytic lichens. In Europe, these trees have decreased dramatically in number as wooded pastures have become overgrown with trees and bushes, and broad leaved deciduous stands have been replaced by planted coniferous trees. These are the main reasons for many lichens depending on deciduous trees being red-listed. Epiphytic lichens in overgrown areas could benefit from conservation thinning, but few studies have been performed on how this type of cutting affects the lichens. In a previous study, the presence of red-listed epiphytic lichens in a broad leaved deciduous forest was examined. After the study, thinning of trees and bushes was made. Here we study the effects of this thinning on Lobaria pulmonaria. We tested possible factors that may affect the growth of L. pulmonaria, and if there were any differences in incidence and vitality of the lichen between managed and unmanaged stands. Since Dutch elm disease and ash dieback are well spread in the area, we wanted to see if they also affected the growth of L. pulmonaria. There were no differences in incidence and growth between managed and unmanaged stands. The results were unexpected since other studies show that, for instance, increased sun exposure often has a great effect on the growth of lichens. Many elms and ashes were dead or dying and had a significant negative effect on the change of number of lobes and the lobe surface. The diseases of the trees can thus be assumed to be the greatest cause of why the lichens in the managed stand did not benefit from thinning.

Baigiamojo darbo tikslas – sukurti šalutinių priemonių stiprinimo modelį VDU įtikinimo komunikacijos procese. Darbą sudaro trys pagrindinės dalys: teorinės literatūros analizė, tyrimo rezultatų analizė ir projektinio modelio sukūrimas. Teorinėje darbo dalyje analizuojama įtikinimo komunikacija, įsigilinimo tikimybės modelis, šalutinės priemonės komunikacijoje. Analitinėje baigiamojo darbo dalyje pateikiami ir analizuojami tyrimo rezultatai, gauti atlikus apklausą, siekiant nustatyti šalutinių priemonių – aukštųjų mokyklų logotipų ir šaltinių patikimumo (informacijos apie aukštąsias mokyklas pateikimo atžvilgiu) – lygį. Projektinėje darbo dalyje sukurti šalutinių priemonių stiprinimo modeliai VDU įtikinėjimo komunikacijoje. / The aim of this final work is to create a model of peripheral cues strengthen in VMU persuasive communication process. The paper consists of three main parts: theoretical analysis, analysis of survey and developing a model. The theoretical part analyzes the persuasive communication, Elaboration Likelihood Model (ELM), peripheral cues in communication. The analytical part of work provides an analysis of results of the study carried out of survey. The main aim of survey was to rate the level of peripheral cues (logos of high schools and source credibility). Design work develops models of peripheral cues strengthen in VMU persuasive communication process.