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The following master thesis analyzes to which extent streaming services in particularNetflix influence the German television landscape and how this discourse is covered inGerman newspapers.The work shows that online streaming services with their non-linear content have animpact on German television. The theoretical base of the work is the critical discourseanalysis by the German linguist Siegfried Jäger. His work analyzes relevant socialdiscourses with its own method based on the theory of the French philosopher MichelFoucault. The present thesis refers to Netflix as a streaming service and analyzes theaspect of how it influences the television landscape since its introduction on the Germanmarket in 2014. For deeper understanding before conducting the critical discourse aninitial analysis of the German television market is presented. The base of the analysisare newspaper articles. Furthermore, the relevant aspects of the publishing landscape inGermany are introduced to provide the reader with relevant background knowledge.Moreover, the thesis contains an analysis of newspaper articles from three leadingnewspapers in Germany: Süddeutsche Zeitung, BILD Zeitung and taz, die tageszeitung(following referred to as taz). 15 representative articles were chosen and afterwardsanalyzed with the method of critical discourse analysis. The results of all threenewspapers on the Netflix discourse are compared to each other. In conclusion, thework shows that the influence of streaming services, especially Netflix on Germantelevision is stronger then expected. And even if television is still seen as the leadingmedium in Germany, public as well as private broadcasters have to be aware of the newcompetitor on the market and adapt to constant changes especially in the online segment.

In 2012, mandatory effluent quality standards were established in Canada as part of the Wastewater Systems Effluent Regulations (WSER) with compliance deadlines starting in 2020. Maintaining the treatment process efficacy to meet these new stringent discharge regulations is extremely challenging at treatment facilities that treat wastewater from multiple industries due to the high variation in the composition of the incoming feed to the process. In this work, application of two new analytical tools, PeCOD® and Liquid Chromatography-Organic Carbon Detection (LC-OCD), for measurement and characterization of industrial wastewater organic pollution respectively, has been investigated. Organic pollution is commonly measured as Chemical Oxygen Demand via the dichromate method (CODCr) which requires 2-3 hours to complete. Thus this method is not suitable for applications that require rapid and frequent pollution monitoring. The Photoelectrochemical Oxygen Demand (peCOD) is an alternative parameter of organic pollution that can be measured in approximately 15 minutes via a method that utilizes the high oxidation potential of UV-irradiated TiO2 nano-particulates. Herein peCOD suitability to replace CODCr for analysis of industrial wastewater was investigated. The results indicated that for both untreated (i.e. incoming) and treated (i.e. effluent) industrial wastewater samples, peCOD results are lower than CODCr results. However, for the effluent samples, the two methods’ results are strongly correlated. Containing hard to oxidize materials (i.e. macromolecules) and high concentrations of chloride and nitrogenous compounds were identified as potential causes of difference between the results of the two methods. When there is variation in the composition of the incoming wastewater to a treatment process, information about the wastewater composition is required for process optimization. Thus optimization cannot be based solely on bulk measurements of organic pollution (e.g. COD). In this study, a novel combination of LC-OCD analysis with Design-Of-Experiments (DOE) methods was used to optimize the Fenton Advanced Oxidation (AO) treatment conditions in terms of chemical reagent concentrations, to develop statistical models of the process, and to identify potential mechanisms of COD removal. / Thesis / Master of Applied Science (MASc) / Many industrial facilities do not treat their wastewater on-site and instead ship it to specialized treatment facilities. Ensuring that the treated effluent meets the stringent discharge regulations is a challenging task for such facilities as the composition of the incoming feed to the treatment process changes with each shipment. In this work, application of two new analytical tools, PeCOD® and Liquid Chromatography-Organic Carbon Detection (LC-OCD), for measurement and characterization of industrial wastewater organic pollution respectively, has been investigated. The conventional method of measuring organic pollution, Chemical Oxygen Demand (COD), requires 2-3 hours to complete. Herein the suitability of an alternative parameter, Photoelectrochemical Oxygen Demand (peCOD), that can be measured in approximately 15 minutes for replacing COD analysis in industrial wastewater plants was investigated. Implementation of effective treatment processes that are operated at their optimum conditions is required to meet the stringent discharge regulations. Advanced Oxidation (AO) is an effective method of industrial wastewater treatment. Herein, optimum AO treatment conditions were studied via application of the LC-OCD analysis for organic pollution characterization.

In this thesis, we study three periodic-review, finite-horizon inventory systems in the presence of supply and demand uncertainties. In the first part of the thesis, we study a multi-period single-station problem in which supply uncertainty is modeled by partial supply. Formulating the problem under a robust optimization (RO) framework, we show that solving the robust counterpart is equivalent to solving a nominal problem with a modified deterministic demand sequence. In particular, in the stationary case the optimal robust policy follows the quasi-(s, S) form and the corresponding s and S levels are theoretically computable. In the second part of the thesis, we extend the RO framework to a multi-period multi-echelon problem. We show that for a tree structure network, decomposition applies so that the optimal single-station robust policy remains valid for each echelon in the tree. Furthermore, if there are no setup costs in the network, then the problem can be decomposed into several uncapacitated single-station problems with new cost parameters subject to the deterministic demands. In the last part of the thesis, we consider a periodic-review Assemble-To-Order (ATO) system with multiple components and multiple products, where the inventory replenishment for each component follows an independent base-stock policy and product demands are satisfied according to a First-Come-First-Served (FCFS) rule. We jointly consider the inventory replenishment and component allocation problems in the ATO system under stochastic component replenishment lead times and stochastic product demands. The problems are formulated under the stochastic programming (SP) framework, which are difficult to solve exactly due to a large number of scenarios. We use the sample average approximation (SAA) algorithms to find near-optimal solutions, which accuracy is verified by the numerical experiment results. / Thesis / Doctor of Philosophy (PhD)

In recent years, the electrification of technology that is traditionally powered by fossil fuels has become a popular means to reduce greenhouse gases (GHG). Although the intentions are well founded, the strain on the electrical grid is seldom taken into consideration. When there is increased load on the grid, it is typically met by fossil fuel peaking power plants or additional fossil fuel infrastructure. Depending on the electrical generation technology deployed and the power plant efficiency, electrification can result in an increase in GHG emissions. To make better informed decisions for GHG reductions, policy makers and engineers are in need of smart energy systems, such as the Integrated Community Energy and Harvesting (ICE-Harvest) system. ICE-Harvest systems work with and can respond to changes on the electrical grid, providing demand response. The system creates electrical demand when renewable generation sources are available, reduces demand when fossil fuel generation is present, and can offset centralized generation using distributed combined heat and power resources. In this thesis, steps to design a micro-thermal network (MTN) for the ICE-Harvest system are outlined and different operational strategies are explored that respond to grid behaviour in real time. How fast the thermal network reacts to grid level variations is defined as the response time. The physical response of the thermal network is a temperature set point change. A design map was developed presenting multiple parameters that contribute to the response time, the trade-offs between them, and the corresponding temperature difference achievable. Through developing models in the equation-based object-oriented software Dymola, the viability for real time temperature set point changes in micro-thermal networks was explored. The MTN and the energy transfer stations (ETSs) that transfer energy between the thermal network and the buildings have been modeled. Yearly system simulations were conducted to analyze the corresponding performance of the MTN in terms of electrical requirements and overall GHG emissions. An operational range of the system was presented demonstrating the flexibility of the ICE-Harvest system. The simulation results have identified the ICE-Harvest system as a viable means to provide demand response to the grid and to reduce GHG emissions. Future work and recommendations will be made to improve the response of the system and further reduce electrical consumption and GHG emissions. / Thesis / Master of Science in Mechanical Engineering (MSME)

Thesis advisor: Ruth Langer / This dissertation creates a Jewish theology of asceticism focused on articulating the ideals toward which Jewish observant life is directed, a method for reflecting on the ‘ends’ of a Jewish life well lived in relationship to practice. I apply this theological asceticism to an analysis of Jewish liturgical prayer (tefilat keva), arguing that it is a desire-forming practice that causes practitioners to reimagine human flourishing and what leads to true satisfaction. My approach to this topic is modeled on a careful analysis and evaluation of the Anglican theologian Sarah Coakley’s “new asceticism” in light of Charles Taylor’s “maximal demand.” I augment Coakley’s definition of asceticism to fit a Jewish theological anthropology articulated by Rabbi Israel Salanter. I then apply this ascetic discourse to the study of the daily practice of liturgy. The Jewish liturgical asceticism I develop draws together elements from the Catholic James Fagerberg’s liturgical theology, the Presbyterian theologian James K. A. Smith’s theories about how liturgy forms a social-imaginary, and R. Israel Salanter’s teachings on the formation of desire (ta’avah) through the practice of hitpa’alut. The dissertation ends with an application of this method for theologically reflecting on the desire forming power of a daily prayer life through a close reading of elements of the weekday morning service, shacharit. This dissertation offers a Jewish theological account of the formative power of liturgical prayer on human desire. It also creates an approach for thinking more broadly about desire formation as a key component in the ideal goals of a normative Jewish lifestyle. This theological project will benefit communities of practice looking to better understand the wisdom of their inherited spiritual practices, educators and communal rabbis looking to commend traditional Jewish ways of life, Jewish theologians looking for an approach to discussing the ideals within Jewish life in a way that stays rooted in practice, and scholars of Jewish liturgy who are looking for methods for studying liturgy as a formative act and not merely an historical text. / Thesis (PhD) — Boston College, 2022. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Theology.

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Yes / What has generated the unprecedented fascination with the Internet? What future lies ahead for computing as the Internet and its associated infrastructure expand? Will the network be able to cope with rising demands for carrying capacity and response speed? Will it change the way scientists, designers, artists, computer professionals, and home users work in the future? These are some of the wideranging questions being asked about the Internet and World Wide Web.

This thesis aims to forecast aircraft demand in the aerospace and defense industry, specifically aircraft orders and deliveries. Orders are often placed by airline companies with aircraft manufacturers, and then suddenly canceled due to changes in plans. Therefore, at some point during the three-year lead time, the number of orders placed and realized deliveries may be quite different. As a result, orders and deliveries are very difficult to predict and are influenced by many different factors. Among these factors are past trends, macroeconomic indicators as well as aircraft sales measures. These predictor variables were analyzed thoroughly, then used with time series and multiple regression forecasting methods to develop different forecasts for quarterly and annual orders and deliveries. The relative accuracies of forecasts were measured and compared through the use of Theil’s U statistic. Finally, a linear program was used to aggregate multiple forecasts to develop an optimal combination of all forecasts. In conclusion, the methods employed in this thesis are quite effective and produce a wholesome aggregate forecast with an error that is generally quite low for a forecasting task as challenging as this one.

Physical inactivity is a major contributor to increased disease prevalence and reduced quality of life. Measuring behavioral economic demand for exercise may enable more effective physical activity intervention development. In study one, we developed the leisure-time-as-price exercise purchase task (LT-EPT), wherein participants (n = 175) indicate hypothetical likelihood to trade leisure time for access to exercise time. We observed weak to moderate correlations between demand indices (Q1%, α, BP1, and Pmax) generated from the LT-EPT and self-reported leisure and exercise time, demonstrating initial validation of the LT-EPT. In study two, we examine the effect of episodic future thinking (EFT; vivid, personalized prospection of future events) in adults not meeting physical activity guidelines (n = 127) on demand for exercise and delay discounting (sensitivity to delayed rewards). We observed reduced delay discounting in participants randomized to engage in EFT, but no difference between EFT and health information thinking (HIT) controls. In study three, we further examined the effect of EFT on demand for exercise in adults with type 2 diabetes and obesity participating in a 24-week randomized controlled trial (n = 71). All participants engaged in a multicomponent behavioral intervention focused on weight loss and glycemic control; additionally, participants were randomized to engage in EFT or HIT thrice daily beginning in week 3. We measured demand for exercise and delay discounting (among other outcomes) at weeks 0, 8, and 24, observing no differences between EFT or HIT groups in demand indices (Q1%, α) or delay discounting at any time point. In conclusion, early evidence suggests that the LT-EPT may be a valid method to measure behavioral economic demand for exercise; however, EFT may not be an effective intervention to increase demand for exercise. / Doctor of Philosophy / Physical inactivity poses a significant threat to our well-being, contributing to increased disease rates and a diminished quality of life. This dissertation details a novel method to measure how people value exercise and the effect of a behavioral intervention to increase exercise valuation. In the first study, we introduce the leisure-time-as-price exercise purchase task (LT-EPT), a tool designed to gauge individuals' willingness to trade leisure time for exercise time (i.e., exercise demand). Initial results show promising correlations between LT-EPT metrics and self-reported leisure and exercise time, providing a foundation for its potential as a valuable measurement tool. The second study examines the impact of episodic future thinking (EFT), a technique involving vivid and personalized visualization of future events, on exercise demand. While participants engaging in EFT showed increased preference for larger, delayed rewards over smaller, sooner rewards (i.e., reduced delay discounting), no significant difference was found between EFT and the health information thinking (HIT) control in terms of exercise demand. The third study expands our investigation to adults with type 2 diabetes and obesity undergoing a 24-week intervention. All participants engaged in a comprehensive behavioral program, while half were randomized to engage in EFT or HIT three times per day. No discernible differences were observed in exercise demand or delay discounting at any measurement point. In summary, our findings suggest that the LT-EPT may be a valid measure of exercise demand. However, the effectiveness of EFT in increasing demand for exercise remains inconclusive. These insights contribute to the ongoing efforts to develop more targeted and impactful interventions for promoting physical activity and improving overall health.