Social Money: Literary Engagements with Economics in Early Modern English Drama

This thesis investigates the impact of economic philosophy and history on sixteenth- and seventeenth-century English drama. It focuses primarily on the ways in which emergent mercantilist theories, new labour models, and changing class structures informed literary production. The significant influence exerted on the English public by financial developments during the early modern period suggests that economic concerns were of preeminent relevance to public discourse. As a result, playwrights cognizant of these worries produced plays that incorporated the distinctive language and character of economic thought and engaged their audiences through tableaus representative of select aspects of London’s financial landscape. In my first chapter, I use historical studies of Jacobean England’s engagement with slavery to read Shakespeare’s The Tempest as a political debate over the delineations among slaves, servants, and subjects within English institutions of servitude. Chapter Two examines Walter Mountfort’s The Launching of the Mary as a piece of early modern economic propaganda, with particular emphasis on its confluence of economic dialogue and the use of the female body as political imagery. Chapter Three is a rereading of Shakespeare’s 1 Henry VI; I argue that the play, which has chiefly been read as a dramatization of political history, is also an allegorical and moralized narrative of England’s transition from feudalism to mercantilism. Chapter Four addresses the personifications of greed in the medieval morality plays Everyman and The Castle of Perseverance and in Marlowe’s The Jew of Malta, with specific attention paid to the models of ideological morality and institutional discipline promoted by these displays. The considerable perspectives offered by economic criticism produce meaningful engagements with these plays and their literary, historical, and philosophical frameworks

Deep Representation of a Normal Map for Screen-Space Fluid Rendering

We propose a novel method for addressing the problem of efficiently generating a highly refined normal map for screen-space fluid rendering. Because the process of filtering the normal map is crucially important to ensure the quality of the final screen-space fluid rendering, we employ a conditional generative adversarial network (cGAN) as a filter that learns a deep normal map representation, thereby refining the low-quality normal map. In particular, we have designed a novel loss function dedicated to refining the normal map information, and we use a specific set of auxiliary features to train the cGAN generator to learn features that are more robust with respect to edge details. Additionally, we constructed a dataset of six different typical scenes to enable effective demonstrations of multitype fluid simulation. Experiments indicated that our generator was able to infer clearer and more detailed features for this dataset than a basic screen-space fluid rendering method. Moreover, in some cases, the results generated by our method were even smoother than those generated by the conventional surface reconstruction method. Our method improves the fluid rendering results via the high-quality normal map while preserving the advantages of the screen-space fluid rendering methods and the traditional surface reconstruction methods, including that of the computation time being independent of the number of simulation particles and the spatial resolution being related only to image resolution

Ultra-Processed Food Intakes Are Associated with Depression in the General Population: The Korea National Health and Nutrition Examination Survey

Depression is the most common mental illnesses worldwide. The consumption of ultra-processed food (UPF) has increased globally due to its affordability and convenience; however, only a few studies have investigated the link between UPF intake and depression in the general population. We investigated the associations between UPF and depression using the Korea National Health and Nutrition Examination Survey. A total of 9463 individuals (4200 males and 5263 females) aged above 19 years old participated in this study. The prevalence of depression was identified using the Patient Health Questionnaire-9. Dietary intake was assessed through a 24-h recall interview. The percentage of energy from UPFs was ascertained based on the NOVA classification. The associations between the quartile ranges of UPF intake and depression were estimated using logistic regression models. Individuals in the highest quartile had a 1.40 times higher likelihood of having depression, with marginal significance (95% confidence intervals (CIs) = 1.00–1.96). In a sex-specific stratification, only females demonstrated a significant association (odds ratio (OR) = 1.51, 95% CI 1.04–2.21), even after adjusting for confounders (p-value for trend = 0.023). Our findings revealed a significant association between higher UPF intake and depression among females but not among males in the Korean general population

Benchmarking Material Use Efficiency for Building Projects

Reducing the quantities of engineered materials provides a significant opportunity to mitigate the environmental impacts caused by material production and processing. Although the efficient use of materials in building construction has been emphasized, there has been little attention given to measuring the material use efficiency (MUE) of a project. This research fulfills this gap by using data envelopment analysis (DEA) as a benchmarking tool to generate an overall perspective on the MUE and to further compare its efficiency with that of peer projects, thereby promoting enhanced efficiency through target setting. In this research, MUE was measured by adopting the quantities of a variety of materials consumed during construction as input variables and the floor area of a built facility as an output variable. To generate a reliable MUE performance, a stepwise variable selection process was applied and then the performance was ranked based on evaluating cross-efficiency. In addition, clustering analysis and DEA were fused to enable a more realistic target to be set for each input, thereby determining practical targets for each underperforming project. It is anticipated that the proposed MUE benchmarking model would enable projects to recognize the gap with the best-performing projects and help them determine the targets to focus on to become efficient

Simplified Deterioration Modeling for Highway Sign Support Systems

Road sign support systems are not usually well managed, because bridges and pavements have budget and maintenance priority while the sign boards and sign supports are considered miscellaneous items. The authors of this paper developed a simple deterioration prediction model and a repair priority list for sign support systems. For asset management risk analysis, data were collected from the Connecticut Department of Transportation (CTDOT) asset management database. Asset ages, repair history, installation and repair costs, and other administrative information were collected. While there were many advanced and complicated structural deterioration prediction models, the Weibull function was used in this research because it is a simple probability distribution function that has been widely used in reliability theory. Assuming that the primary factors of the deterioration prediction are age and initial installation quality, the repair priority list was developed based on the risk analysis of the assets. Asset risks were calculated based on the deterioration prediction model and traffic impacts of the failure

Designing a public engagement process for long-term urban park development project.

Gathering public consensus about long-term urban open space development is more difficult than ever, even though public engagement is crucial for sustainable long-term policymaking. Routine evaluation of public awareness is important for retaining project momentum and designing appropriate public engagement processes for the future. This study focuses on the Yongsan Park Development Project, which has been in progress for more than three decades. An online survey of 2,000 respondents was conducted and analyzed to evaluate the current public awareness and ask questions about respondents' expectations for public engagement. The results of this study reveal that 1) a hybrid methodology is needed to effectively approach different age groups; 2) an online survey can offer new insights for projects that repurpose U.S. army base and military sites into urban open spaces; 3) the survey results will enable us to design a better public participation process that is appropriate for post-pandemic society, in which virtual meetings and socially distanced communications are part of the new norm