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Food as Bridge: Belonging and Transnationalism in the Culinary Culture of Chinese Immigrants in Early 20th-Century Chicago
No full textThis thesis discusses how early 20th-century Chinese immigrants in the United States negotiated their belonging through culinary culture, focusing on the Chinese American community in Chicago. While Asian American scholarship predominantly centers on coastal cities like San Francisco and New York, Chicago offers a unique perspective as a significant hub for Chinese immigration. Utilizing artifacts from the Chinese American Museum of Chicago (CAMOC)—including menus, dishware, restaurant advertisements, and imported items from China—I explore how culinary practices facilitated cultural preservation, adaptation, and a transnational connection with the homeland amidst exclusionary laws and social marginalization. By analyzing culinary practices as symbols of both adaptation and preservation, this study investigates how Chinese immigrants settled in the host society and defended against the stigmatization fueled by anti-Chinese hostility. Drawing on Hobsbawm and Ranger's concept of invented tradition and Homi Bhabha's notion of hybridity, this paper situates CAMOC’s culinary collections within the socio-political landscape of early Chinese American communities in Chicago. Interpreting these culinary artifacts as primary sources, this paper contributes to current discussions on the formation and transformation of the diasporic community's belonging amidst shifting cultural dynamics and ongoing connections to their homeland
Mid-Infrared Mercury Telluride Nanoparticles: From Microscopic Properties to Photodiode Performance
Get PDFMidwave infrared detection has many uses, typically stemming from the sensing of vibrational structures, as in biological imaging or molecular spectroscopy, or the sensing of blackbody radiation, as in thermal imaging. Different infrared detector technologies each have their drawbacks. Bolometers are an inexpensive approach suffering from slow response speed and low frequency noise. InSb detectors generally require cryogenic cooling. Both InSb and HgCdTe detectors are prohibitively expensive for many applications.Solution-processed materials are hoped to allow for vast improvements on the cost of infrared photon detectors with minimal losses to performance, expanding the range of feasible application. The most promising of these material approaches for use in the mid-infrared appears to be HgTe colloidal quantum dots. So far, the highest performing detectors of these are photovoltaics. This work focuses on the development of a circuit model for mid-infrared HgTe colloidal quantum dot photodiodes in order to investigate the limits of their performance in terms of measurable properties of the quantum dot material.Specifically, this work presents significant improvements in detector external quantum efficiency through the incorporation of quantum dots with an improved synthesis and the management of leakage current with a guard ring. It presents a performant top-illuminated architecture and presents a detailed analysis of the temperature dependence of circuit model parameters, relating them to the dominant recombination mechanisms present in the dot material.</p
A Generalized Mediation Analysis of Intergenerational Income Elasticity (IGE)
Get PDFThis study systematically examines the determinants and pathways of intergenerational income elasticity (IGE) in China, highlighting the explanatory power of parental occupations. Using data from the China Family Panel Studies (CFPS) (2010–2022), we employ decomposition frameworks and layered mediation analysis to disentangle the complex mechanisms underlying income persistence. The findings reveal that parental income alone explains a limited portion of income mobility, while parental occupations emerge as significant independent contributors, even after controlling for education, urban-rural status, and regional economic conditions. Through mediation analysis, education years, industry selection, and social capital are identified as key channels through which parental occupations influence child income. The results underscore the importance of addressing structural advantages embedded in occupational hierarchies, suggesting that policy interventions should extend beyond educational improvements to include targeted measures addressing occupational barriers and inherited advantages
When Nigeria Speaks: The Divergent Paths of #BringBackOurGirls and #EndSARS
Get PDFThis thesis explores the divergent trajectories of two major Nigerian social movements, #BringBackOurGirls and #EndSARS, which relied heavily on digital platforms but experienced differing international reach and domestic engagement levels. This research investigates how resource mobilization, framing, and political opportunity interact to shape movement outcomes through a comparative case study approach and thematic analysis of secondary sources. The analysis reveals that while both movements leveraged digital tools to amplify their causes, they succeeded in different arenas. #BringBackOurGirls gained widespread international attention through elite endorsements and emotionally powerful messaging, whereas #EndSARS formed deep grassroots participation through youth-led organizing. These contrasting trajectories reflect how each movement strategized its framing, mobilized resources, and navigated political opportunities. By synthesizing multiple social movement theories and applying them to a non-Western context, this research contributes to a deeper understanding of contemporary activism. It highlights the value of multi-framework analysis in capturing the dynamics of activism in Nigeria
Land of the Censored, Home of the Silenced: How Trump’s Immigration Crackdowns Undermine the Virtues of American Higher Education
Get PDFPresident Donald Trump began his second term in January of 2025, and one of his main priorities was to crack down on immigration. In pursuit of this, he has taken multiple measures to increase deportation, the revocation of visas, and the detainment of noncitizens–regardless of status, criminal background, or legality. As a result, universities across the nation are experiencing unforeseen consequences regarding the free speech, safety, and security of their international students, as well as broader threats to their university culture. Using interviews and news monitoring, I explore how Trump’s immigration crackdowns impact higher education on a micro and macro scale, including individual emotions and behaviors, departmental changes, and the nature of resistance to his efforts. Focusing in on the University of Chicago, I explore how a university famously known for free expression is responding to these rapid changes, giving voice to international students and how they respond to this administration in real time. These findings shed light on the future of international talent in American higher education, and consequences of the Trump administration’s crackdowns, including brain drain, revenue decline, the loss of university culture, and broader threats to democracy at large
Dynamic brain connectivity predicts emotional arousal during naturalistic movie-watching
Get PDFHuman affective experience varies along the dimensions of valence (positivity or negativity) and arousal (high or low activation). It remains unclear how these dimensions are represented in the brain and whether the representations are shared across different individuals and diverse situational contexts. In this study, we first utilized two publicly available functional MRI datasets of participants watching movies to build predictive models of moment-to-moment emotional arousal and valence from dynamic functional brain connectivity. We tested the models by predicting emotional arousal and valence both within and across datasets. Our results revealed a generalizable arousal representation characterized by the interactions between multiple large-scale functional networks. The arousal representation generalized to two additional movie-watching datasets with different participants viewing different movies. In contrast, we did not find evidence of a generalizable valence representation. Taken together, our findings reveal a generalizable representation of emotional arousal embedded in patterns of dynamic functional connectivity, suggesting a common underlying neural signature of emotional arousal across individuals and situational contexts. We have made our model and analysis scripts publicly available to facilitate its use by other researchers in decoding moment-to-moment emotional arousal in novel datasets, providing a new tool to probe affective experience using fMRI
The End of History and U.S. Commercial Shipbuilding
Get PDFWhy did the United States, during the unipolar moment, act against its long-term strategic interest by choosing not to invest in its commercial shipbuilding industry? This decision is especially puzzling considering that China, the United States’ current peer competitor and potential naval adversary, started publicly investing in and emphasizing the strategic importance of its sector during the same time. I argue that the United States’ adherence to and belief in a liberal foreign policy during the unipolar moment is chiefly to blame. Believing that China could rise without challenging its security, the United States discounted the risk of a security competition and naval conflict with it in the future. As a result, the U.S. had no reason to be concerned with China’s growing dominance of commercial shipbuilding or invest in its uncompetitive commercial sector. This only changed after the United States recognized both the threat China would pose to its security and the challenges its industrial base would face supporting a protracted, large-scale conventional war
Gray Zone Tactic Choice: Understanding How and Why States Utilize Sub-Limited Warfare
No full textStates constantly pursue their aims or attempt to weaken one another without resorting to conventional war. To do this, they employ different types of sub-limited operations to manipulate or weaken a defender state. This thesis examines these operations as deliberately selected tactics that can elicit different perceptions and responses in international politics. Specifically, it asks whether two variables, target scope and confrontation history, influence whether a state uses a kinetic or non-kinetic operation type. By analyzing an original data set of Iranian sub-limited operation usage between 2010 to 2024, and two historical case studies, this thesis finds suggestive evidence that states are most likely to use kinetic mechanisms against narrow targets within adversaries with whom they have a high confrontation history
Taiwan Foreign Direct Investment Effects on ASEAN and Pacific Island Emigration
No full textIt costs a lot to look this pretty. This thesis explores how Taiwanese Foreign Direct Investment (FDI) serves as a tool of economic statecraft, influencing migration flows from states within the Association of South East Asian Nations (ASEAN) and Pacific Island states. Situated within the frameworks of Soft Power and Smart Power attraction, the study examines Taiwan’s use of economic engagement to establish strategic influence in regions with limited formal diplomatic recognition. Using datasets from 2013 to 2021, the analysis employs OLS regression to assess the relationship between Taiwanese FDI and migration to Taiwan, controlling for variables such as diplomatic status, net migration, GDP, population, natural disasters, economic recessions, and Chinese Belt and Road Initiative (BRI) investment. Findings show that Taiwanese FDI significantly increases migration, indicating the development of social and institutional linkages over time. According to Irene S. Wu's emigration rubric, migration is the strongest variable for Soft Power. The results contribute to understanding Taiwan's regional influence and the role of economic engagement in non-coercive diplomacy in ASEAN and Pacific Island states
A Data-Driven Approach for Patient Selection for Xenotransplant Human Clinical Trials
No full textThe demand for transplant organs surpasses supply, with xenotransplantation offering a potential solution to this shortage. Successful investigational transplants of genetically edited pig kidneys into brain-dead recipients and expanded access cases involving living human recipients suggest that the first human clinical trials are imminent. This dissertation focuses on patient selection for the initial trials. In Chapter 1, using the benchmark of 2-year survival of non-human primates in pre-clinical studies, we develop a tool that can identify individual wait-listed patients predicted to have a shorter life expectancy than with a xenotransplant, utilizing Random Survival Forest, DeepSurv and Cox Proportional-Hazards models. We find that it is hard to identify patients that reach clinical equipoise unless the expected xenograft survival exceeds two years. Few patients would benefit based on survival alone and potential beneficiaries are spread across more than 200 transplant centers. Several incentives could allow more patients to reach equipoise. Keeping patients inactive on the waitlist while they have a functioning xeno-kidney provides a modest incentive, while giving patients with failed xenografts the same or even more priority as prior living donors would represent a potent driver for participation in trials. We are able, however, to identify phenotypes that have high mortality and low transplant rates in the current allocation system that could serve as acceptable candidates. In Chapter 2, we extend this framework to jointly model decisions about who should receive a xenograft, when to proceed, and under which incentive scheme. We develop an individual-level optimal stopping model that captures the decision process of a forward-looking patient who evaluates whether to accept or decline allo- and xeno-offers over time. The model is structured as a two-stage problem: the first covers choices after initial waitlisting, and the second applies if the patient reenters the list following xenograft failure. Incentive mechanisms, such as awarding additional priority points after xenograft failure, are embedded in the second stage, influencing the value of rejoining the waitlist and shaping the initial acceptance decision. To capture heterogeneity, we represent patient health with high-dimensional covariates that integrate demographic, clinical, and socioeconomic factors, enabling individualized outcome predictions. For computation, we implement GPU-accelerated backward induction to efficiently evaluate large state spaces. We also employ classification analysis to identify patient characteristics most predictive of benefiting from xenografts. In Chapter 3, we examine the current eligibility criteria for initial xenotransplant clinical trials and apply them to patient-level data using Scientific Registry of Transplant Recipients decision aid and the Estimated Post-Transplant Survival score. We then compare this framework with our proposed approach