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The United States is the world's largest oil consumer demanding about twenty five percent of the total world oil production. Whenever there are difficulties to supply the increasing quantities of oil demanded by the market, the price of oil escalates leading to what is known as oil price spikes or oil price shocks. The last oil price shock which was the longest sustained oil price run up in history, began its course in year 2004, and ended in 2008. This last oil price shock initiated recognizable changes in transportation dynamics: transit operators realized that commuters switched to transit as a way to save gasoline costs, consumers began to search the market for more efficient vehicles leading car manufactures to close 'gas guzzlers' plants, and the government enacted a new law entitled the Energy Independence Act of 2007, which called for the progressive improvement of the fuel efficiency indicator of the light vehicle fleet up to 35 miles per gallon in year 2020. The past trend of gasoline consumption will probably change; so in the context of the problem a gasoline consumption model was developed in this thesis to ascertain how some of the changes will impact future gasoline demand. Gasoline demand was expressed in oil equivalent million barrels per day, in a two steps Ordinary Least Square (OLS) explanatory variable model. In the first step, vehicle miles traveled expressed in trillion vehicle miles was regressed on the independent variables: vehicles expressed in million vehicles, and price of oil expressed in dollars per barrel. In the second step, the fuel consumption in million barrels per day was regressed on vehicle miles traveled, and on the fuel efficiency indicator expressed in miles per gallon. The explanatory model was run in EVIEWS that allows checking for normality, heteroskedasticty, and serial correlation. Serial correlation was addressed by inclusion of autoregressive or moving average error correction terms. Multicollinearity was solved by first differencing. The 36 year sample series set (1970-2006) was divided into a 30 years sub-period for calibration and a 6 year "hold-out" sub-period for validation. The Root Mean Square Error or RMSE criterion was adopted to select the "best model" among other possible choices, although other criteria were also recorded. Three scenarios for the size of the light vehicle fleet in a forecasting period up to 2020 were created. These scenarios were equivalent to growth rates of 2.1, 1.28, and about 1 per cent per year. The last or more optimistic vehicle growth scenario, from the gasoline consumption perspective, appeared consistent with the theory of vehicle saturation. One scenario for the average miles per gallon indicator was created for each one of the size of fleet indicators by distributing the fleet every year assuming a 7 percent replacement rate. Three scenarios for the price of oil were also created: the first one used the average price of oil in the sample since 1970, the second was obtained by extending the price trend by exponential smoothing, and the third one used a longtime forecast supplied by the Energy Information Administration. The three scenarios created for the price of oil covered a range between a low of about 42 dollars per barrel to highs in the low 100's. The 1970-2006 gasoline consumption trend was extended to year 2020 by ARIMA Box-Jenkins time series analysis, leading to a gasoline consumption value of about 10 millions barrels per day in year 2020. This trend line was taken as the reference or baseline of gasoline consumption. The savings that resulted by application of the explanatory variable OLS model were measured against such a baseline of gasoline consumption. Even on the most pessimistic scenario the savings obtained by the progressive improvement of the fuel efficiency indicator seem enough to offset the increase in consumption that otherwise would have occurred by extension of the trend, leaving consumption at the 2006 levels or about 9 million barrels per day. The most optimistic scenario led to savings up to about 2 million barrels per day below the 2006 level or about 3 millions barrels per day below the baseline in 2020. The "expected" or average consumption in 2020 is about 8 million barrels per day, 2 million barrels below the baseline or 1 million below the 2006 consumption level. More savings are possible if technologies such as plug-in hybrids that have been already implemented in other countries take over soon, are efficiently promoted, or are given incentives or subsidies such as tax credits. The savings in gasoline consumption may in the future contribute to stabilize the price of oil as worldwide demand is tamed by oil saving policy changes implemented in the United States.

The daytime serial drama, commercially known as the soap opera, has for a long time been diminished as an inferior artform, which previous research has connected to bias towards its historically predominantly female audience as well as its close relation to advertising. This thesis examines Guiding Light (original title The Guiding Light, CBS, 1937-1956, 1952-2009) and its transition from radio to television in the 1950s by using a historiographical approach through analysis of archive artefacts that cover the decade. The archive material, consisting of newspapers and magazines, have two parts to play: the first regarding the influence of the sponsor Procter & Gamble considering the soap opera’s status as a thriving advertisement vehicle of the time, and the second in the relationship between soap opera and its listeners/viewers throughout the era of transition. Throughout the years that it existed as a combination serial; both factors were seen to play a vital role in shaping the serial, both from an industry point-of-view, and as evident in its text. The two perspectives are often contradictory to one another but the co-existence of them is essential to the shaping of the soap opera’s history writing. Gender ties into both angles as the transition added to a growing social panic surrounding the housewife as a pillar for postwar US-American values.

This thesis consisted of experiments designed to explore the construct of attention and investigate the disruptive effects of psychotomimetics, with a specific focus on NMDA antagonists. Phencyclidine (PCP) was administered through a variety of treatment regimens in order to to determine the ability of inducing cognitive-specific disruptions in attentional functioning. The hypothesis that sub-chronic exposure to PCP would result in persistent attentional impairment was tested, using the 5-choice serial reaction time task (5-CSRTT). The 5-CSRTT assesses not only visuospatial attention, but also components of impulsivity, compulsivity, speed of processing and motivation. It was determined that an additional task-related intervention that increased the attentional load was required to elucidate attentional impairment following sub-chronic PCP treatment. The ability of rats to perform the modified version of the 5-CSRTT, known as the 5-choice continuous performance test (5C-CPT), was investigated. The 5C-CPT was implemented to provide a task that may have greater analogy to the human CPT, than the original 5-CSRTT. The consequence of dopaminergic D1 system activation was investigated. It was revealed that D1 partial agonism improved attentional performance in a baseline-dependent manner. Following successful acquisition of the task, it was shown that repeated PCP treatment induced cognitive disruption that was cognitive-specific, and not confounded by generalised response disruption. Furthermore, a partial attenuation of the PCP-induced performance disruption was achieved following administration of the D1 partial agonist, SKF 38393. Moreover, sub-chronic PCP treatment was shown to impair 5C-CPT performance in the drug-free state. However, an additional challenge that further increased the attentional load was needed to elucidate a performance deficit. This highlighted that sustained attention/vigilance is sensitive to persistent impairment following sub-chronic PCP administration in a manner consistent with deficits observed in schizophrenia patients. This prompted the investigation that tested the hypothesis that sub-chronic PCP treatment could induce enduring structural deficits in regions associated with attentional performance. Magnetic resonance imaging (MRI) was conducted, in conjunction with 5-CSRTT and pre-pulse inhibition (PPI). It was revealed that sub-chronic PCP treatment resulted in morphological brain abnormalities in brain regions associated with 5-CSRTT performance. This was coupled with deficits in sustained attentional performance following an increase in attentional load, yet PPI was unaffected. Taken together, these findings suggested sub-chronic PCP treatment impairs attentional functionality, an effect that dissociates between effortful and passive attentional processes.

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Die dreidimensionale Mikrostruktur, welche bei der Oberflächenkristallisation von Glaskeramiken entsteht, wird mittels einer neuartigen Methode zur Präparation von abgesenkten Probenoberflächen untersucht. Diese Initialkantensektionierungsmethode, welche auf der Erzeugung von Scharten in der Probenoberfläche und anschließender Glanzwinkelionenstrahlerosion basiert, erlaubt das rapide Freilegen von großflächigen Schichten in wohldefinierten Tiefen unterhalb der ursprünglichen Probenoberfläche. In dieser Dissertation werden mehrere Variationen der Technik durch Kombination von Laserablation, Ionenbreit- sowie Ionenfeinstrahlerosion untersucht und miteinander verglichen. Die in Bezug auf Schnittgeometrie und Probengüte relevanten, experimentellen Parameter werden bestimmt und bewertet. Ein Modell zur Beschreibung der zeitlichen Evolution der Probengeometrie während des Erosionsvorgangs wird auf Grundlage von Simulationen und analytischen Näherungen aufgestellt und mit experimentellen Ergebnissen verglichen. Schließlich wird die Initialkantensektionierungsmethode mit Elektronenrückstreubeugung kombiniert um Wachstumseffekte bei der Oberflächenkristallisation von Diopsid- und Ba2TiSi2O8-Fresnoitglaskeramiken zu untersuchen.:1 Introduction 1.1 Motivation 1.2 Aims and Objectives 2 Literature Review 2.1 Sample Preparation for Electron Backscatter Diffraction Studies 2.2 Serial Sectioning Methods 2.3 Microstructure Characterization of Glass Ceramics using EBSD 2.4 Interim Conclusion 3 Theory 3.1 Erosion of a Surface Under Ion Bombardment 3.1.1 Sputtering 3.1.2 Kinetic Theory of Surface Evolution 3.1.3 Numerical Simulation of Surface Erosion 3.1.4 Erosion of a Surface With Initial Notches 3.2 Electron Backscatter Diffraction 3.2.1 Measurement Principle 3.2.2 Representation of Orientations and Texture 4 Methods and Materials 4.1 Sample Preparation and Processing 4.2 Surface Metrology 4.3 Microstructure Analysis 4.4 Materials 5 Erosion of Surfaces With Initial Notches 5.1 Evaluation of Surface Processing Methods 5.1.1 Notch Creation 5.1.2 Terrace Formation by Glancing-Angle Ion Beam Erosion 5.2 Surface Properties in the Terrace Region 5.2.1 Terrace Roughness 5.2.2 Ion Beam Induced Amorphization 5.3 Evolution of Surface Geometry 5.3.1 Linear Model 5.3.2 Simulations 5.3.3 Experimental Results 5.4 Discussion 5.4.1 Sample Processing 5.4.2 Sample Quality 5.4.3 Kinetic Model of Surface Evolution 6 Depth-Resolved Microstructure Characterization Using Initial Notches 6.1 Diopside 6.2 Ba2TiSi2O8 fresnoite (BTS) 6.3 Discussion 6.3.1 Methodological Aspects of Initial Notch Sectioning 6.3.2 Microstructure Analysis on Surface-Crystallized Glass Ceramics 7 Summary and Outlook / Three-dimensional microstructures resulting from surface crystallization of glass ceramics are studied using a novel sample sectioning method. Based on the creation of notches on the sample surface and subsequent glancing-angle ion beam erosion, initial notch sectioning enables the rapid excavation of large subsurface layers at well-defined depths. In this thesis, several variations of this technique using different combinations of laser ablation, broad and focused ion beam erosion are realized and compared to each other. Relevant parameters controlling the section geometry and quality are determined. A model of the surface evolution kinetics is developed using simulations and analytical estimates, which is compared to experimental results. Finally, initial notch sectioning in combination with electron backscatter diffraction is applied to elucidate growth phenomena in the surface crystallization of diopside and Ba2TiSi2O8 fresnoite glass ceramics.:1 Introduction 1.1 Motivation 1.2 Aims and Objectives 2 Literature Review 2.1 Sample Preparation for Electron Backscatter Diffraction Studies 2.2 Serial Sectioning Methods 2.3 Microstructure Characterization of Glass Ceramics using EBSD 2.4 Interim Conclusion 3 Theory 3.1 Erosion of a Surface Under Ion Bombardment 3.1.1 Sputtering 3.1.2 Kinetic Theory of Surface Evolution 3.1.3 Numerical Simulation of Surface Erosion 3.1.4 Erosion of a Surface With Initial Notches 3.2 Electron Backscatter Diffraction 3.2.1 Measurement Principle 3.2.2 Representation of Orientations and Texture 4 Methods and Materials 4.1 Sample Preparation and Processing 4.2 Surface Metrology 4.3 Microstructure Analysis 4.4 Materials 5 Erosion of Surfaces With Initial Notches 5.1 Evaluation of Surface Processing Methods 5.1.1 Notch Creation 5.1.2 Terrace Formation by Glancing-Angle Ion Beam Erosion 5.2 Surface Properties in the Terrace Region 5.2.1 Terrace Roughness 5.2.2 Ion Beam Induced Amorphization 5.3 Evolution of Surface Geometry 5.3.1 Linear Model 5.3.2 Simulations 5.3.3 Experimental Results 5.4 Discussion 5.4.1 Sample Processing 5.4.2 Sample Quality 5.4.3 Kinetic Model of Surface Evolution 6 Depth-Resolved Microstructure Characterization Using Initial Notches 6.1 Diopside 6.2 Ba2TiSi2O8 fresnoite (BTS) 6.3 Discussion 6.3.1 Methodological Aspects of Initial Notch Sectioning 6.3.2 Microstructure Analysis on Surface-Crystallized Glass Ceramics 7 Summary and Outlook

Denna studie fokuserar på fankulturen kring tv-serien Dahmer – Monster: The Jeffrey Dahmer Story på TikTok. Studien ämnar att undersöka hur TikTok-videor romantiserar och sexualiserar skådespelaren Evan Peters, som spelar Jeffrey Dahmer i serien. Undersökningen analyserar representationen av karaktären i TikTok-videor och om dessa Dahmer-TikToks bidrar till romantiserandet av seriemördare generellt. Forskningen inkluderar en multimodal diskursanalys av visuellt material från TikTok samt en enkätundersökning för att samla in TikTok-användarnas attityder och uppfattningar. Enkätresultaten indikerar att majoriteten av respondenterna har stött på den typen av Dahmer-TikToks som undersöks, och en betydande andel tolkar dem som romantiserande eller sexualiserande. Undersökningen visar att den sociokulturella traditionen för hur människor betraktar seriemördare kan vara på väg att förändras på grund av spridningen av romantiserande och sexualiserande Dahmer-TikToks. Tv-serien och dess TikTok-trend har även gett upphov till en fankultur; användare skapar, delar och engagerar sig i romantiska videor om Dahmer för att följa trenden. Sammanfattningsvis belyser studien fenomenet av Dahmer-TikToks med sexuella, romantiska eller objektifierande anspelningar, och indikerar en potentiell förändring i samhällets diskurs kring seriemördare. / This study focuses on the fan culture surrounding the TV series Dahmer – Monster: The Jeffrey Dahmer Story on TikTok. It aims to investigate how TikTok videos romanticize and sexualize the actor Evan Peters, who plays Jeffrey Dahmer in the series. The study analyzes the representation of the character in TikTok videos and explores whether these Dahmer-TikToks contribute to the romanticization of serial killers in general. The research includes a multimodal discourse analysis of visual material from TikTok and a survey to gather TikTok users' attitudes and perceptions. The survey findings indicate that the majority of respondents have encountered the type of Dahmer-TikToks investigated, and a significant percentage interpret them as romanticizing or sexualizing. The study suggests that the socio-cultural tradition of how people view serial killers may be changing due to the distribution of romanticized and sexualized Dahmer-TikToks. The analysis aligns with the survey results, supporting the premise of the thesis. The TV series and its respective TikTok trend have also spawned a fan culture; users create, share, and engage with romantic videos of Dahmer. Overall, the study highlights the presence of videos with sexual, romantic, or objectifying elements related to Dahmer on TikTok and indicates a potential shift in societal discourse regarding serial killers.

In the last decades, computational models have become useful tools for studying biological neural networks. These models are typically constrained by either behavioural data from neuropsychological studies or by biological data from neuroscience. One model of the latter kind is the Bayesian Confidence Propagating Neural Network (BCPNN) - an attractor network with a Bayesian learning rule which has been proposed as a model for various types of memory. In this thesis, I have further studied the potential of the BCPNN in short-term sequential memory. More specifically, I have investigated if the network can be used to qualitatively replicate behaviours of immediate verbal serial recall, and thereby offer insight into the network-level mechanisms which give rise to these behaviours. The simulations showed that the model was able to reproduce various benchmark effects such as the word length and irrelevant speech effects. It could also simulate the bow shaped positional accuracy curve as well as some backward recall if the to-be recalled sequence was short enough. Finally, the model showed some ability to handle sequences with repeated patterns. However, the current model architecture was not sufficient for simulating the effects of rhythm such as temporally grouping the inputs or stressing a specific element in the sequence. Overall, even though the model is not complete, it showed promising results as a tool for investigating biological memory and it could explain various benchmark behaviours in immediate serial recall through neuroscientifically inspired learning rules and architecture. / Under de senaste årtionden har datorsimulationer blivit ett allt mer populärt verktyg för att undersöka biologiska neurala nätverk. Dessa modeller är vanligtvis inspirerade av antingen beteendedata från neuropsykologiska studier eller av biologisk data från neurovetenskapen. En modell av den senare typen är ett Bayesian Confidence Propagating Neural Network (BCPNN) - ett autoassociativt nätverk med en Bayesiansk inlärningsregel, vilket tidigare har använts för att modellera flera typer av minne. I det här examensarbetet har jag vidare undersökt om nätverket kan användas som en modell för sekventiellt korttidsminne genom att undersöka dess förmåga att replikera beteenden inom verbalt sekventiellt korttidsminne. Experimenten visade att modellen kunde simulera ett flertal viktiga nyckeleffekter såsom the word length effect och the irrelevant speech effect. Däröver kunde modellen även simulera den bågformade kurvan som beskriver andelen lyckade repetitioner som en funktion av position, och den kunde dessutom repetera korta sekvenser baklänges. Modellen visade också på viss förmåga att hantera sekvenser där ett element återkom senare i sekvensen. Den nuvarande modellen var däremot inte tillräcklig för att simulera effekterna som tillkommer av rytm, såsom temporär gruppering eller en betoning på specifika element i sekvensen. I sin helhet ser modellen däremot lovande ut, även om den inte är fullständig i sin nuvarande form, då den kunde simulera ett flertal viktiga nyckeleffekter och förklara dessa med hjälp av neurovetenskapligt inspirerade inlärningsregler.

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