VictorJuiz/thesis huggingface dataset:
Understanding and harnessing psychological and social forces to improve healthcare

Relative to the attention paid to biological forces, little attention has been spent trying to understand how psychological and social forces can be harnessed as tools for healing inside the doctor's office. By helping care teams realize that they can use biological, psychological, and social interventions to help their patients, we can expand providers' healing arsenal. In this dissertation, I design, implement, and assess four studies to help us better understand and leverage psychological and social forces in healthcare. Together, these studies demonstrate how psychological and social forces matter with placebo treatment (chapter 2), without treatment (chapter 3), with active treatment (chapter 3), and how they can be leveraged at scale (chapter 4). Findings from these studies demonstrate that: 1) patient beliefs are a previously-overlooked variable influencing the effects of open-label placebo treatments; 2) provider assurance alone can have a healing effect, even without the presence of medication or treatment; 3) instilling the mindset that minor, non-life threatening side effects are a sign that treatment is working can improve treatment experience and outcomes in children undergoing oral immunotherapy for life-threatening food allergies, and; 4) care teams are receptive to a training designed to help them harness psychological and social forces in clinical practice. Together, these studies use a variety of methods and research settings to demonstrate that psychological and social forces in the healthcare encounter can be systematically unpacked, manipulated, and studied, and then deliberately leveraged to improve healthcare. The overall goal of this research is to bring us closer to realizing the promise of the biopsychosocial model of health by underscoring the impact of psychological and social forces on patient health outcomes and implementing novel techniques for using these forces in practice

Keywords: Psychology.
Advisor: Crum Alia
Dweck Carol S.
Zaki Jamil
Understanding catalyst structure-performance relationships through precise synthesis and in situ characterization

Heterogeneous catalysis will play an important role in facilitating chemical reactions with sustainable energy conversion and environmental applications. The performance of a catalyst can be affected by many different physical, chemical, and electronic properties of the material. The relationships between these properties and catalytic reactivity are not well-understood and as a result, the design of high-performance catalysts has been a significant challenge. In this dissertation, we synthesize catalysts using precise methods, including atomic layer deposition (ALD) and colloidal nanocrystal synthesis. By analyzing the properties of these controlled catalytic materials during reaction using in situ methods, we understand the relationships between structure and performance. This strategy is applied to the study of several catalytic systems for sustainable energy and environmental processes. One promising pathway towards the long-term production of fuels and chemicals is through the catalytic conversion of syngas to higher oxygenates. Several classes of catalysts have emerged as promising candidates for direct higher oxygenate synthesis from syngas: rhodium-based materials, mixed Fischer-Tropsch and methanol synthesis metals, and alternatives to pure metals. In the first part of this dissertation, we study the properties of one example catalyst from each of these classes. The last two studies in this dissertation highlight general design strategies and principles in the study of heterogeneous catalysts. We show the importance of impurity control in achieving the desired catalytic performance, a factor that is often overlooked in catalyst design. Finally, we develop a procedure combining ALD and colloidal nanocrystal synthesis that can be used to study metal-support interaction in a wide variety of catalyst systems. Throughout this dissertation, emphasis is placed on structure-performance relationships, controlled catalyst synthesis using atomically precise methods, and in situ characterization. We show how an understanding of the effects of physical and chemical catalyst properties on reactivity can be used to intelligently design higher performance catalysts. Precise synthesis methods play an important role in elucidating these structure-performance relationships and in enabling the synthesis of catalytic materials with the desired nanoscale properties. Characterization of catalyst structures are further enabled by in situ methods, which allow active sites and surface characteristics to be identified. The results in this dissertation contribute to and provide guidance for the design, synthesis, and characterization of high-performance heterogeneous catalysts

Keywords: Chemical Engineering.
Advisor: Bent Stacey
Bare Simon
Cargnello Matteo
UNDERSTANDING CHRONIC TRAUMATIC ENCEPHALOPATHY IN THE NATIONAL FOOTBALL LEAGUE: THE IMPLICATIONS OF PUBLIC DISMISSAL AND MEDIA CONVERSATION OF THE DISEASE

Chronic traumatic encephalopathy, more commonly referred to as CTE, has been a critical health issue in the National Football League that has received insufficient attention. The neurodegenerative disease is caused by repeated head trauma, often sustained through impact collisions and concussions from football. Despite increased research on CTE in the early part of the 21st century, it has taken almost two decades for the NFL to begin to acknowledge and act towards the issue. This research explores how and why the NFL was able to dismiss the disease for so long, the long-term implications for player health and safety, and steps moving forward given the league’s monopolistic influence over the sport as well as strong media influence. By comparing the NFL to Robert Proctor’s work on the tobacco industry and the long-term effects of smoking, as well as taking into account literature from Fainaru-Wada and Fainaru as well as Oriard, it is apparent that the NFL’s handling of CTE is based on business motives and reputation, even going as far as the league doing a complete turnaround in their messaging, as seen through the media analysis outlined in Table 1 of this paper. It is evident that there needs to be a structural shift in policy, accountability, and awareness tactics in order to manage and prevent CTE in the NFL and the harsh consequences of the disease. By taking a holistic approach through science, technology, and society, the politics of the league can shift, and ethics can be reinforced to realign league priorities around CTE.

Keywords:  Department of Science
Science Technology and Society
chronic traumatic encephalopathy
CTE
National Football League (NFL)
concussion
media conversation
neurodegenerative brain disease
health technology
machine learning
policy
Thesis
Advisor: Freese Jeremy
Understanding control of lithium morphology in lithium metal batteries

Directing the morphology of lithium metal deposits during electrodeposition is crucial to the development of safe, high energy density batteries with robust cycle life for application in emerging energy storage technologies including electric vehicles. Towards this end, mechanistic insight is imperative to understand the relationship between electrolytes, additives, cycling conditions, and resulting lithium morphologies. Relevant background and motivating information for the work to be presented in this dissertation is discussed in Chapter 1, including a brief discussion of batteries, electrochemical characterization, and materials characterization techniques. In Chapter 2, results of a systematic study which reveals the links between electrolyte composition, initial solid electrolyte interphase (SEI) formation, and a highly controlled columnar morphology of electrodeposited lithium metal is presented. A suite of electrochemical characterizations, X-ray photoelectron spectroscopy, small and wide-angle synchrotron X-ray scattering, and scanning electron microscopy was used to draw insights concerning the underlying mechanisms of HF additive-induced columnar lithium formation and these insights can help guide the development of future electrolyte additive design and rational formation cycling protocols for lithium metal batteries. Chapter 3 focuses on the role of applied mechanical pressure in enhancing the cycling performance of lithium metal batteries, and the combined effects of electrolyte additives and stack pressure. Results from experiments on anode-free cells as well as both anode and cathode symmetric cells over a range of applied pressures and pressure application methods help shed light on precisely how mechanical pressure modulates cycling behavior and reaffirms the importance of a wholistic approach to designing and engineering lithium metal batteries for practical applications. This dissertation concludes with Chapter 4 in which a brief overall conclusion of the work is followed by some future perspectives and research ideas within the lithium metal battery space

Keywords: Materials Science and Engineering.
Advisor: Chueh William
Toney Michael Folsom
Cui Yi
Understanding, prevention, and management of vaccine-preventable communicable diseases and associated health outcomes

Communicable diseases remain a threat to population health in the United States and globally. This dissertation focuses on HPV and SARS-CoV-2, viruses that can lead to considerable morbidity. This, coupled with widespread concerns about vaccine efficacy and safety, highlights the need for further study of the prevention and management of illnesses caused by these viruses. The objective of this dissertation is to further our knowledge of HPV and SARS-CoV-2 by identifying drivers of vaccine uptake and exploring how these infections may lead to health outcomes of interest. In the first part of this dissertation, we apply an environment-wide association approach to identify drivers of HPV vaccine initiation among adolescents in the United States. In the second part, we conduct a systematic review of studies examining persistent symptoms among COVID-19 patients and present a series of methodological recommendations to guide future research. Finally, we explore the association between obesity and COVID-19 pneumonia, a condition which has been linked to lung scarring and persistent symptoms such as difficulty breathing. These chapters demonstrate how diverse methodological approaches and datasets can be leveraged to reduce the burden of morbidity caused by communicable diseases

Keywords: Epidemiology.
Advisor: Sainani Kristin
Bendavid Eran
Odden Michelle
Understanding the degradation of perovskite solar cells and engineering methods for improved stability

Within approximately a decade of their invention, organic-inorganic metal perovskite solar cells have reached power conversion efficiencies of 25%, which rival the market-dominant c-Si solar panels. The impressive power conversion efficiencies are attributable to its unique defect-tolerant optoelectronic properties. However, there is still much to be investigated with respect to the stability and lifetime of perovskites, which limits the path to commercialization. Perovskites are susceptible to degradation from many environmental stressors including heat, moisture, and UV light. To reach device lifetimes of greater than 10 years, which is necessary for perovskites to be competitive with other photovoltaic technologies, perovskite solar cells must be effectively encapsulated between two glass panels to prevent any ingress of moisture which causes premature failure. In this dissertation, I will discuss findings on the fundamentals of thermal degradation mechanisms in encapsulated perovskite solar cells. Based on these findings, a novel encapsulation scheme that reduces the thermal load of the solar cell is tested and evaluated in accelerated aging conditions of damp heat, dry heat, and outdoor aging. The development of an open-air plasma-deposition process for thin film moisture barriers is then presented as part of a cost-effective encapsulation scheme. The performance of the moisture barrier is assessed using both accelerated aging of perovskite solar cells and optical calcium testing to measure water vapor transmission rates through the barrier. Finally, capabilities for measuring the mechanical properties of ultra-thin (sub 10 nm) fluorosilane films which are used as an anti-fouling, hydrophobic coating for moisture-sensitive electronic devices, including perovskite solar cells are presented. From these measurements, insights are made regarding the influence of chemical precursor structure on the mechanical properties and durability of the film

Keywords: Materials Science and Engineering.
Advisor: Dauskardt R. H. (Reinhold H.)
McIntyre Paul Cameron
Salleo Alberto
Understanding the interactions between text and visualizations

Visualizations and text are commonly used together in various applications, ranging from communicative documents to interactive tools for analyzing and exploring data. However, much about the relationship between visualizations and text remains unexplored. This thesis specifically focuses on three problems related to communicating the connections between the two representations and ways to surface these connections to address the problems. We begin by asking how readers integrate information between visualizations and text when the two representations emphasize different aspects of the underlying data. Through a user study, we find that readers can miss information presented in the text because they rely more on the visualizations for their takeaways. Based on the study results, we provide guidelines for authoring effective visualization-text pairs that doubly emphasize intended aspects of the underlying data. Identifying references between visualizations and text, which are often also spatially separated, is a mentally taxing process. The cognitive burden disrupts the flow of reading as readers traverse back and forth between visualizations and text in an attempt to mentally link their contents. We present an interactive document reader that extends existing PDF documents based on automatically extracted references between visualizations and text. Specifically, it facilitates document reading by highlighting the references and dynamically positioning visualizations close to relevant text. Our user study shows that the interface helps readers integrate visualizations into their flow of reading by helping them identify references more quickly and more accurately. When using a natural language interface for visualizations, users are often not informed about how the system operated on a visualization based on its interpretation of a text query. This lack of transparency leads users to question the system because they cannot easily verify the correctness of its outputs. We present a chart question answering system that generates visual explanations that clarifies how it used an input question and a visualization to obtain an answer. A user study reveals that our visual explanations significantly improve transparency and achieve levels of trust close to human-generated explanations

Advisor: Agrawala Maneesh
Landay James A.
Setlur Vidya
Unequal Aid: The Disproportionate Effect of Stay-at-Home Orders during the COVID-19 Pandemic by Income and Race

This paper investigates the effects of COVID-19 stay-at-home orders on new case and death numbers by county in the United States. Although a large body of past literature describes the pandemic’s effect on financial and physical health, there is a gap in our understanding of how government policies influenced individual COVID-19 outcomes. This paper utilizes a multiple fixed-effects regression approach as introduced by Correia (2016) to predict the average treatment effect of these government mandates on new COVID-19 cases and deaths by week. Ultimately, we conclude that the COVID-19 stay-at-home orders disproportionately aided high-income and predominantly White communities, while case and death rates rose after these mandates for low-income and predominantly Black communities. This paper largely supports the understanding that financial and human crises affect vulnerable communities the most, and it raises important policy implications for government aid during these crises.

Keywords: Department of Economics
COVID-19
shelter-in-place
stay-at-home
multiple fixed effects
disproportionate effects
income
race
Thesis
Advisor: Bhattacharya Jay
Unpacking the education production function : essays on teaching, parenting, and measurement in emerging contexts

This dissertation consists of three essays that investigate topics concerning the three main characters in the education production function-the teacher, the parent, and the student. All three essays speak to modes of learning that have a broad reach and leverage novel sources of data to inform implementation, policymaking, and future research. The first chapter of this dissertation brings experimental evidence to the problem of improving parental execution, i.e. taking action with their children, in mobile education. The second chapter of this dissertation presents quasi-experimental evidence to answer an age-old question-how does faculty research affect student learning? The third chapter of this dissertation concerns the estimation of student models using large sparse data from online learning

Keywords: Education.
Advisor: Bettinger Eric
Loeb Susanna
Athey Susan
Unsupervised Learning for Discovery in 2D & 3D Scenes: Towards Unbiased Understanding of Biomedical Images

While in recent years artificial intelligence has made impressive strides in many fields, the bulk of this progress has been limited to supervised methods and tasks with an abundance of labeled data. However, in many real-world domains, labeling may be burdensome or near impossible, and on the extreme end, annotations of interest may lie beyond the extent of human knowledge. Unsupervised learning, which broadly involves training machine learning models to encode information from unlabeled data, is then particularly promising as a means to address these problems. It has the potential to discover new objects and structures in 2D & 3D scenes beyond what humans can recognize. Such promise is especially exciting for discovery in the biomedical domain. Biological data can be vastly complex, and as new technologies help us collect more complicated data, there is increasing opportunity for unsupervised learning to help scientists turn observations into insights, shedding new perspectives on the underlying unknowns behind human health. In my thesis, I both establish unsupervised learning methods that expand the state-of-the-art in deep learning as well as apply my methods on real-world, cutting-edge biological data.

Keywords:  Department of Computer Science
machine learning
deep learning
unsupervised learning
differential geometry
Thesis
Advisor: Yeung Serena
Chiu Wah
Upstream oil production, ambient air pollution, and adverse birth outcomes in California

An estimated 17.6 million United States residents live within 1.6 km (1 mile) of an active oil or gas well, including 2.1 million Californians. Prior research has found associations between exposure to unconventional natural gas production and a range of adverse health impacts, including preterm birth (delivery at < 37 weeks of gestation). However, there has been less attention to conventional oil and gas production, which is predominant in California. In this dissertation, my objectives were to examine how exposure to upstream oil production in California affects ambient air quality and the risk of spontaneous preterm birth. In Chapter 1, my colleagues and I examined the association between exposure to oil and gas wells and risk of preterm birth among gestating parents in the San Joaquin Valley, California. We conducted a case-control study, a classic epidemiological design, using data on 225,000 births delivered between 1998 and 2011. We found increased odds of preterm birth with high exposure to wells in the first and second trimesters for births delivered at ≤31 weeks (aORs, 1.08--1.14). In stratified analyses, the associations were confined to births to Hispanic and non-Hispanic Black parents and to parents with ≤12 years of educational attainment. In Chapter 2, we investigated the effects of upstream oil and gas production on ambient air quality throughout California. We constructed a panel dataset with daily measurements of five routinely monitored air pollutants from 314 U.S. EPA air quality monitors between 2006 and 2019. We leveraged daily changes in wind direction as an exogenous source of variation and controlled for geographic, meteorological, seasonal, and time-trending factors that may influence air quality. We observed higher concentrations of air pollutants within 4 km of wells in preproduction and 2 km of producing wells. Finally, in Chapter 3 we built on our earlier findings and leveraged a matched-sibling design to determine whether, among births to the same parent, higher exposure to upstream oil and gas production increased preterm birth risk. We obtained data for approximately 1.5 million births to 660,000 parents across California. The results indicate that that higher exposure to preproduction wells and production volume was associated with increased preterm birth risk. This dissertation contributes to understanding of environmental drivers of preterm birth and how upstream oil and gas production affects the environment and health. .

Advisor: Burke Marshall
Shaw Gary
Baiocchi Michael
Cullen Mark R.
Using CDK4/6 inhibitors to identify novel regulators of the RB pathway

The initiation of cell division is a fundamental cellular process that integrates a large number of intra- and extra-cellular inputs. In mammalian cells, D-type cyclins (cyclin D1, D2, and D3, together "cyclin D") couple these inputs to the decision to initiate DNA replication. Increased levels of cyclin D promote cell cycle progression by activating cyclin-dependent kinases 4 and 6 (CDK4/6), which in turn phosphorylate and inactivate the retinoblastoma protein (RB) to drive cell cycle entry. Accordingly, increased levels and activity of cyclin D and their associated kinases are strongly linked to unchecked cell proliferation and tumor development. Despite this central role in cell cycle progression, the mechanisms regulating cyclin D levels remain incompletely understood. Here, we identify AMBRA1 as the main regulator of cyclin D protein degradation. We first identified AMBRA1 in a genome-wide CRISPR/Cas9 loss-of-function screen investigating the genetic basis of response to chemical CDK4/6 inhibition. AMBRA1 loss results in high protein levels of cyclin D in cells and in mice. These high levels of cyclin D reshuffle the cyclin-CDK complexes active in G1 to promote proliferation and increase tolerance to CDK4/6 inhibition. AMBRA1 loss also promotes the development of lung adenocarcinoma in mouse models, and low levels of AMBRA1 correlate with worse survival in lung adenocarcinoma patients. We then identified the mechanistic link between AMBRA1 and cyclin D . AMBRA1 acts as a substrate receptor for the Cullin 4 E3 ligase complex to promote ubiquitylation and proteasomal degradation of the three D-type cyclins. Thus, AMBRA1 is a previously unrecognized regulator of the cell cycle, directly limiting cyclin D protein levels and thereby influencing the development of cancer as well as the response of cancer cells to CDK4/6 inhibitors

Advisor: Sage Julien
Attardi Laura
Jackson Peter K. (Peter Kent)
Skotheim Jan