EXPOSURE TO EXTREME HEAT EVENTS AND CHRONIC RESPIRATORY DISEASES AMONG A NATIONALLY REPRESENTATIVE SAMPLE OF THE UNITED STATES POPULATION

Previous studies have shown that extreme weather events are on the rise in response to our changing climate. Such events are projected to become more frequent, more intense, and longer lasting. A consistent exposure metric for measuring these extreme events as well as information regarding how these events lead to ill health are needed to inform meaningful adaptation strategies that are specific to the needs of local communities. Using federal meteorological data corresponding to 17 years (1997-2013) of the National Health Interview Survey, this research: 1) developed a location-specific exposure metric that captures individuals’ “exposure” at a spatial scale that is consistent with publicly available county-level health outcome data; 2) characterized the United States’ population in counties that have experienced higher numbers of extreme heat events and thus identified population groups likely to experience future events; and 3) developed an empirical model describing the association between exposure to extreme heat events and hay fever. This research confirmed that the natural modes of forcing (e.g., El Niño-Southern Oscillation), seasonality, urban-rural classification, and division of country have an impact on the number extreme heat events recorded. Also, many of the areas affected by extreme heat events are shown to have a variety of vulnerable populations including women of childbearing age, people who are poor, and older adults. Lastly, this research showed that adults in the highest quartile of exposure to extreme heat events had a 7% increased odds of hay fever compared to those in the lowest quartile, suggesting that exposure to extreme heat events increases risk of hay fever among US adults.

Spectral graph theory with applications to quantum adiabatic optimization

In this dissertation I draw a connection between quantum adiabatic optimization, spectral graph theory, heat-diffusion, and sub-stochastic processes through the operators that govern these processes and their associated spectra. In particular, we study Hamiltonians which have recently become known as ``stoquastic'' or, equivalently, the generators of sub-stochastic processes. The operators corresponding to these Hamiltonians are of interest in all of the settings mentioned above. I predominantly explore the connection between the spectral gap of an operator, or the difference between the two lowest energies of that operator, and certain equilibrium behavior. In the context of adiabatic optimization, this corresponds to the likelihood of solving the optimization problem of interest. I will provide an instance of an optimization problem that is easy to solve classically, but leaves open the possibility to being difficult adiabatically. Aside from this concrete example, the work in this dissertation is predominantly mathematical and we focus on bounding the spectral gap. Our primary tool for doing this is spectral graph theory, which provides the most natural approach to this task by simply considering Dirichlet eigenvalues of subgraphs of host graphs. I will derive tight bounds for the gap of one-dimensional, hypercube, and general convex subgraphs. The techniques used will also adapt methods recently used by Andrews and Clutterbuck to prove the long-standing ``Fundamental Gap Conjecture''.

Jiao Tong: A Grounded Theory of Chinese International Students' Transition to American Tertiary Education

University students are more globally mobile than ever before, increasingly receiving education outside of their home countries. One significant student exchange pattern is between China and the United States; Chinese students are the largest population of international students in the U.S. (Institute of International Education, 2014). Differences between Chinese and American culture in turn influence higher education praxis in both countries, and students are enculturated into the expectations and practices of their home countries. This implies significant changes for students who must navigate cultural differences, academic expectations, and social norms during the process of transition to a system of higher education outside their home country. Despite the trends in students’ global mobility and implications for international students’ transitions, scholarship about international students does not examine students’ experiences with the transition process to a new country and system of higher education. Related models were developed with American organizations and individuals, making it unlikely that they would be culturally transferable to Chinese international students’ transitions. This study used qualitative methods to deepen the understanding of Chinese international students’ transition processes. Grounded theory methods were used to invite the narratives of 18 Chinese international students at a large public American university, analyze the data, and build a theory that reflects Chinese international students’ experiences transitioning to American university life. Findings of the study show that Chinese international students experience a complex process of transition to study in the United States. Students’ pre-departure experiences, including previous exposure to American culture, family expectations, and language preparation, informed their transition. Upon arrival, students navigate resource seeking to fulfill their practical, emotional, social, intellectual, and ideological needs. As students experienced various positive and discouraging events, they developed responses to the pivotal moments. These behaviors formed patterns in which students sought familiarity or challenge subsequent to certain events. The findings and resulting theory provide a framework through which to better understand the experiences of Chinese international students in the context of American higher education.