VictorJuiz/thesis huggingface dataset:
Uncertainty and policy design for sustainable energy systems
Keywords: Management Science and Engineering.

Decarbonizing the electricity sector will require a massive increase in variable solar and wind generation. Maintaining the stability of that future grid will require new sources of flexibility to keep supply and demand in balance without relying on traditional fossil-fired generation. Battery-based storage and flexible demand are two promising sources of flexibility that could each play a large role in future electricity grids. New policies are necessary to support the growth and value of these resources, and to integrate them into existing markets, because they work very differently from the traditional electricity generators that markets were originally designed to coordinate. This dissertation contributes to ongoing policy discussions by identifying how policy and market design can efficiently support the growth of each of these up-and-coming resources. In doing so, it advances our knowledge of exactly how these resources can most effectively provide value to the electricity grid. This dissertation begins with a novel taxonomy of uncertainty analysis approaches available to macro-energy systems modeling and includes a summation of best-practice advice that is applied in the following chapters. The third chapter examines the design of Demand Response (DR) programs, which could provide flexibility to the electricity grid through programs that incentivize customers to reduce or shift their electricity usage. It examines the implications of several common DR program design parameters for the system value and customer experience, revealing which parameters may severely limit the value of DR, and which offer smart tradeoffs between utility and customer outcomes. Results show that advance notice requirements as well as duration, total-time and total energy limits could be valuable tools for providing good system value while minimizing customer impacts. DR program designers should avoid creating programs with poor reliability and time-of- day limits, as these can significantly reduce system value. The fourth chapter examines the economic outcomes, as well as greenhouse gas and criteria air pollutant emissions resulting from grid-scale lithium-ion battery storage across three different Independent System Operators in the US. It identifies situations where smart policy can support the growth of this industry and its value to society and shows that the financial attractiveness of batteries varies greatly by region. The frequency regulation (FR) market currently drives the profitability of batteries. Results suggest that policy supporting learning-by-doing and attractive financing terms can help batteries remain financially attractive despite expected declines in FR prices. Finally, it shows that batteries can increase the net emissions of the electricity system, but studies that do not incorporate ancillary services into battery dispatch decisions may not correctly estimate the magnitude of this effect
(Un)changing inequality : economic life, social movements, and policymaking during years of inflation in urban Brazil, 1944-1978
Keywords: History.

This dissertation is a study of inflation and inequality in urban Brazil from 1944-1978. Examining the feedback loop among economic life, social movements, and policymaking, it analyzes how different people experienced inflation, the social movements they formed to protest against it, and how some policies enacted to address it helped exacerbate inequality. The first half features chapters about the unequal lived experience of the high cost of living in the 1940s and the public protest campaigns carried out by women and students in Rio de Janeiro in the 1940s and 1950s. The second half examines the American consulting firm Klein & Saks' 1954 mission that studied why food prices were so high in urban Brazil; the wage policy in 1964's PAEG that reduced workers' wages as a way to fight inflation; and the anti-inflation advertising campaigns in 1973 and 1977 that blamed urban women, shopkeepers, and consumers for inflation. Integrating methods from social, cultural, and intellectual history with those from economic history and political economy, while using an array of qualitative and quantitative primary sources, this dissertation makes several arguments. First, we cannot understand urban Brazilians' lived experience from the 1940s-1970s without appreciating the degree to which inflation influenced their daily lives, and how this varied by socioeconomic status and gender. Second, analyzing the women- and student-led social movements in the 1940s and 1950s not only enhances our knowledge of these groups' agency and political action but also of their successes and failures in influencing policymakers. Finally, we have an incomplete conception of both the range of policy options available to policymakers and the results of policies that scholars have overlooked. Ultimately, this dissertation contributes to our understanding of state-society relations, political legitimacy, and the persistence of inequality in Brazil, and it provides lessons for countries today and in the future facing economic imbalances
Uncovering molecular innovation in the malaria plastid organelle through forward genetics
Keywords: Molecular and Cellular Physiology.

Plasmodium parasites and related apicomplexans are important human pathogens with major global burdens. These parasites represent a highly divergent and understudied branch of eukaryotes, and as such often defy the expectations set by model organisms. One striking example of unique apicomplexan biology is the apicoplast, an essential but non-photosynthetic plastid derived from a secondary (eukaryote-eukaryote) endosymbiosis. Endosymbioses are a major driver of molecular and cellular innovation, and biogenesis of the four-membrane apicoplast poses a unique challenge requiring evolution of new machinery. As such, apicoplast biogenesis pathways represent a hot spot for cellular innovation, yet few molecular players have been identified. To discover organellar pathways with evolutionary and biomedical significance, we conducted a mutagenesis screen for essential apicoplast biogenesis genes in P. falciparum using a novel fluorescent reporter and a chemical rescue that permits conditional disruption of the apicoplast. We identified fourteen gene candidates, and validated that six are specifically essential for apicoplast biogenesis. Three validated genes had no previous functional annotation, including a triosephosphate isomerase (TIM)-barrel which we show is derived from a core metabolic enzyme but evolved a new activity for its role in apicoplast biogenesis. We also validate a CaaX protease and bacteriocin processing (CPBP) gene, which based on gene annotations was expected to function as a CaaX protease in the eukaryotic post-prenylation processing pathway. However, we unexpectedly find that it does not act as a eukaryotic CaaX protease, but is instead derived from a cyanobacterial gene and likely performs a conserved chloroplast function that has been retained for complex plastid biogenesis. Altogether, our screen identified both unknown and unexpected genes, highlighting the abundance of molecular innovation in apicoplast biogenesis pathways. Furthermore, this proof-of-concept screen enables future expansion to a genome-scale screen, allowing broad discovery of these unique and essential pathways
Understanding and harnessing psychological and social forces to improve healthcare
Keywords: Psychology.

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
Understanding catalyst structure-performance relationships through precise synthesis and in situ characterization
Keywords: Chemical Engineering.

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
UNDERSTANDING CHRONIC TRAUMATIC ENCEPHALOPATHY IN THE NATIONAL FOOTBALL LEAGUE: THE IMPLICATIONS OF PUBLIC DISMISSAL AND MEDIA CONVERSATION OF THE DISEASE
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

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.
Understanding control of lithium morphology in lithium metal batteries
Keywords: Materials Science and Engineering.

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
Understanding, prevention, and management of vaccine-preventable communicable diseases and associated health outcomes
Keywords: Epidemiology.

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
Understanding the degradation of perovskite solar cells and engineering methods for improved stability
Keywords: Materials Science and Engineering.

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
Unequal Aid: The Disproportionate Effect of Stay-at-Home Orders during the COVID-19 Pandemic by Income and Race
Keywords: Department of Economics
COVID-19
shelter-in-place
stay-at-home
multiple fixed effects
disproportionate effects
income
race
Thesis

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.
Unpacking the education production function : essays on teaching, parenting, and measurement in emerging contexts
Keywords: Education.

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
Unsupervised Learning for Discovery in 2D & 3D Scenes: Towards Unbiased Understanding of Biomedical Images
Keywords:  Department of Computer Science
machine learning
deep learning
unsupervised learning
differential geometry
Thesis

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.