VictorJuiz/thesis huggingface dataset:
Health System Efforts to Address Health Related Social Needs: Implications for Public Health, Health Services Use, and Quality Outcomes

Health systems face increasing pressure to improve population health by addressing health related social needs such as adequate housing, transportation, or food insecurity. Current evidence around these initiatives is still nascent. One common intervention to address health related social needs is case management. There is need to better understand the holistic impacts of case management, the role of specific case management program components, and the effects of social needs interventions implemented as distinct activities. The three papers that comprise this dissertation examine social needs interventions from different angles. The first paper uses a rigorously designed, large-scale health and social needs case management program to identify whether case management services improved vaccination rates in the wake of the Covid-19 pandemic. The second paper builds on the same case management program to understand whether housing deposits, a unique program benefit, impacted health services use. The third paper analyzes whether hospital activities to address social needs are associated with better quality of care. Collectively, these papers suggest that health system efforts to address social needs hold promise yet may require continued tailoring for specific patient populations and local communities.

Advisor: Brewster, Amanda L
Nonparametric Methods for High-Dimensional Data Analysis

Modern biomedical studies generate high-dimensional data, meaning that the number of variables collected is equal to or larger than the number of observations. Examples are numerous, including single-cell transcriptome analyses and clinical trials. The dimensions of these data often prevent the use of traditional statistical methods: the theory motivating their application is no longer applicable. New procedures must be developed for express use in these contexts to ensure trustworthy inference. This dissertation delves into two topics in high-dimensional statistics, the first being covariance matrix estimator selection. Motivated by the need to nonparametrically identify an optimal estimator of the covariance matrix for a given dataset, we propose a cross-validated estimator selection procedure and investigate its finite-sample and high-dimensional asymptotic performance. Our theoretical results, supported by empirical evidence, demonstrate that this procedure selects the optimal estimator asymptotically. Here, optimality is defined in terms of a Frobenius-norm-based risk. Applications are myriad, though we focus on improving exploratory analyses in single-cell transcriptome analyses. The second topic, born of the need to reliably uncover biomarkers that predict clinical trial patients’ response to novel therapies, is treatment effect modifier discovery. Treatment effect modifiers are pre-treatment covariates that influence the effect of a treatment on an outcome. While many approaches exist for identifying these effect modifiers in traditional asymptotic settings, few developments have been made for high-dimensional data. We propose a nonparametric framework for defining parameters measuring treatment effect modification, deriving accompanying estimators, and establishing these estimators’ asymptotic properties. We derive several such parameters and estimators using our methodology, and assess these estimators’ empirical performance through comprehensive simulation studies and real clinical trial data analyses.

Advisor: Dudoit, Sandrine
Essays in Empirical Macroeconomics

In this dissertation, I explore the consumption smoothing behavior of households. A key problem at the core of much of economics is how households allocate consumption over time and across states of the world: Do they borrow in lean times and save in good times? Do they save when young and dis-save when old? Do they account for future changes in income and adjust consumption right away? Studying consumption behavior at retirement and delinquencies during unemployment, I find that households cut their consumption substantially at the onset of retirement and that the sensitivity of delinquencies to unemployment appears to mostly be driven by a lack of liquidity during unemployment. Together, these results suggest that households exhibit a large degree of sensitivity to current income, a component largely ignored by state-of-the-art consumption models.

Advisor: Nakamura, Emi
Mountains and rivers: rare events in noisy systems and the forces that shape them

Rare events are ubiquitous in noisy complex systems throughout the physical sciences and to large extent determine their function and regulation. Dissipative outside forces often work hand in hand with equilibrium structure to shape the mechanism and frequency of such improbable fluctuations, but little is known about how to codify the influence of non-equilibrium on reaction rates and their mechanisms. In the last quarter century we have seen paradigm shifting breakthroughs in reaction rate theory that have allowed for the study of rare transitions in complex many particle systems. At the same time, development of the statistical mechanics of trajectories has revolutionized how we study the behavior, response and functional limits of systems away from equilibrium. Here, we develop a trajectory theory of how reaction rates respond to nonequilibrium forces, allowing us both to probe how non-equilibrium systems regulate their function, and leverage optimally designed forces to sample reaction rates from finite time driven trajectories for the first time.

Advisor: Limmer, David
Bustamante, Carlos
Towards an Optimal Cosmological Detection of Neutrino Mass with Bayesian Inference

High-precision measurements of large-scale cosmic structure are expected to revolutionize our understanding of fundamental physics, for example by the quantifying neutrino mass and elucidating the nature of dark energy. This dissertation tackles various of the challenges that must be faced in order to optimally extract information from cosmological surveys, taking a particular interest in neutrino mass./nMassive neutrinos suppress the growth of cosmic structure on small scales, where gravity is nonlinear. It is currently an urgent task to determine how to maximally retrieve information in the nonlinear regime, as a traditional power spectrum analysis is no longer optimal. We start by using simulations to investigate the amount of information regarding neutrino mass present in cosmic structure. We find that while there is in principle a lot of information, only a small fraction will be measurable by upcoming surveys such as DESI and LSST. This motivates the need to perform a combined analysis with other cosmological tracers, such as the cosmic microwave background, and galaxy peculiar velocities. We thus develop a Bayesian forward modeling framework to combine field-level inference with galaxy peculiar velocities as a means to optimally extract information./nAdditionally, various numerical challenges arise due to the nonlinear effects of gravity. For example, computing the covariance matrices required for likelihood-based analyses becomes challenging, in particular due to the super-sample covariance effect. Moreover, the inference often involves non-trivial posterior surfaces which are plagued by volume effects such as the Look-Elsewhere Effect. This is particularly prevalent when searching for evidence of exotic new models. In the latter chapters of the dissertation we provide methods to solve both of these problems./nAll put together, this dissertation provides the ingredients for the cosmology community to move closer to an optimal measurement of neutrino mass and other cosmological parameters.

Advisor: Seljak, Uros
Singular Alternating Matrices over Rings of Integers

Let K be a number field with ring of integers O. Consider the set of n x n alternating matrices with fixed rank, r/nThe principal ideas behind the proof were first introduced in a paper of Katznelson where the problem of counting matrices is reduced to one of counting lattice points. Because our matrices have entries in O rather than being restricted to the set of rational integers, the lattices of Katznelson are replaced in the present work with O-modules. The generalization from the rational numbers to K renders the standard tools of lattice-theory less directly applicable, and we rely on the Minkowski map and novel arguments to, at various turns, reduce to the lattice case, or abstract results from lattices to O-modules. Ancillary results in our work include a new formula for the discriminant of a torsion-free O-module in terms of its pseudo-basis and a novel structure theorem about the set of alternating matrices whose rows lie in a specified O-module.

Advisor: Matchett Wood, Melanie
Ribet, Ken
Deep Generative Modeling for Single-Cell Omics Data

Single-cell omics technologies have transformed our ability to take high-throughput measurements of the molecular contents of individual cells. Applications of these technologies broadly aim to resolve the molecular mechanisms that underlie cell-to-cell variability and identify the intrinsic and extrinsic factors that cause cells to take on particular states. For immunology, these technologies offer unprecedented resolution to characterize immune cell states and associated regulatory mechanisms in contexts ranging from development to antigen response dynamics to disease./nA central object used for analyzing single-cell data is a computational representation of cells that can be queried to extract biological insights. In this dissertation, I first describe methodology for learning cell state representations using deep generative models, a class of probabilistic generative models that make use of neural networks to learn the underlying distribution of the data. In particular, I present Total Variational Inference (totalVI), a model that enables general purpose analysis of paired single-cell transcriptomic and proteomic data by learning a representation that accounts for the technical characteristics of the data. In addition, I detail Velocity Variational Inference (veloVI) for the analysis of transcriptional dynamics from snapshot single-cell RNA-sequencing data. Underlying these models is a unified framework for probabilistic modeling and analysis of single-cell omics data (scvi-tools), which I also describe./nNext, I detail the application of these computational tools to disentangle the heterogeneity of CD8+ T cells in the context of response to acute viral infection. CD8+ T cells are a critical component of the adaptive immune system and contribute to the defense against intracellular pathogens and cellular processes gone awry. Here I describe axes of CD8+ T cell diversity that can effectively distinguish activation state versus differentiation state and help resolve lineage relationships of T cell subsets.

Advisor: Streets, Aaron
Yosef, Nir
Development of Late Transition Metal Catalysts for the Hydroamination of Unactivated Alkenes

The following dissertation discusses the development of ruthenium and iridium catalysts for the intermolecular hydroamination of unstrained and unconjugated alkenes with amines. These reactions involved the direct addition of the N–H bond of derivatives of 2-aminopyridine to unactivated terminal alkenes and the remote addition of the N–H bond of derivatives of 2-aminopyridine to unactivated disubstituted alkenes. These reactions occurred with high chemo- and regioselectivity to install the amino group at the subterminal position of an aliphatic chain. Experimental and computational mechanistic studies have shed light on the mechanism of these reactions and common side pathways during catalytic hydroamination./nChapter 1 provides an overview of the hydroamination of alkenes catalyzed by late transition metals. This review includes information regarding the importance and the challenges of catalytic hydroamination, representative examples of catalytic hydroamination of different classes of alkenes, including vinylarenes, conjugated dienes and trienes, strained alkenes as well as unactivated alkenes, and the mechanisms of those reactions. Discussion of photocatalytic hydroamination of alkenes and the future of catalytic hydroamination is also included in this chapter./nChapter 2 describes the development of ruthenium-catalyzed hydroamination of unactivated terminal alkenes. A cationic ruthenium complex catalyzes the intermolecular hydroamination of a variety of unactivated terminal alkenes with 2-aminopyridine as an ammonia surrogate. Detailed mechanistic studies show that this reaction occurs by a new mechanism comprising initial formation of an imine by oxidative amination, followed by reduction of the imine./nChapter 3 describes the development of iridium-catalyzed enantioselective hydroamination of unactivated terminal alkenes. A combination of a specific iridium precatalyst containing a monodentate, labile ethylene ligand and NaBArF catalyzes enantioselective hydroaminations with equimolar amounts of a 2-aminopyridine and unactivated alkenes containing a wide range of functional groups. This catalytic system suppresses competing side reactions, such as the isomerization of the terminal alkene and the racemization of the product of hydroamination./nChapter 4 describes the development of iridium-catalyzed remote hydroamination of unactivated disubstituted alkenes to place the amino group at the unactivated subterminal carbon of an alkyl chain. The electronic properties of the substituent on the aminopyridine and the development of a new ligand are critical to the high regioselectivity and reaction rates of the reaction.

Advisor: Hartwig, John F.
Essays on Field Experiments in Behavioral Economics

This dissertation contributes to the literature of using field experiments to test and develop theories of consumer behavior. In Chapter One, my coauthors and I partner with the YMCA to analyze how public recognition for exercise affects consumer's utility. We find that while it motivates positive behavior change, it creates highly unequal payments, with low performers losing a lot of utility from having their exercise habits publicly shared. In Chapter Two, my coauthor and I use an online shopping experiment to study how consumers (mis)react to sales taxes. We find evidence consistent with the theory that consumers using heterogeneous rules of thumb to compute the opaque tax when the stakes are low, but using costly mental effort at higher stakes. The results allow us to differentiate between various economic theories of limited attention. In Chapter Three, my coauthor and I partner with an online apparel retailer to study the consequences of offering a one-time price discount to consumers, with a particular focus on consumer beliefs. We find that the net effect was no significant difference in revenue, order frequency or profit from the two groups in our experiment. We further find that price discounts do not change the perceived value of the brand or quality of the product, which contradicts many existing economic theories.

Advisor: Taubinsky, Dmitry
Pulsed Electroluminescent Devices for Emission Across Energy and Length Scales

Unusual device architectures may open up unexpected opportunities for optoelectronic devices. For example, the range of luminescent materials that can be easily integrated in light-emitting devices is often limited by material processing and band alignment issues. This hinders the development of electroluminescent devices at extreme wavelengths and the use of electroluminescence spectroscopy as an analytical technique. In this thesis, I explore an unconventional scheme of electrically-driven light emission based on pulsed metal-oxide-semiconductor capacitor devices. This concept can be used to produce electroluminescence from a wide range of materials including bulk semiconductors, two-dimensional semiconductors, colloidal quantum dots, organic molecules, and more. The performance of this light-emitting device is studied through simulation and experiment, and practical characterization is undertaken with different alternating-current driving schemes. By scaling the device, low voltage operation of these devices is further demonstrated. The device not only achieves emission spanning the near-ultraviolet to near-infrared energy spectrum, but also offers a straightforward avenue towards achieving electroluminescence from materials with different physical compositions and length scales spanning single particles to thick films. As a result of the scalable fabrication approach, miniaturized arrays of many different color light-emitting devices can be easily created on a monolithic substrate. The potential of this device platform for spectroscopic applications is illustrated by spectral imaging demonstrations which combine compressive sensing-based algorithms with highly multicolored and multiplexed light-emitting arrays.

Advisor: Javey, Ali
High Performance Hybrid Switched-Capacitor Converters for Aerospace Applications

Innovations within power electronics are necessary to enable future electric aircraft and space exploration. In these aerospace applications, power converters must be light-weight, efficient and reliable. Conventional, inductor-based, power electronics tend to be heavy, and have high switch stress making them difficult to implement in these applications. In this thesis, hybrid switched-capacitor converters are explored as they utilize energy-dense capacitors as the primary energy storage element, and also decrease the voltage stress of the switches. The basics of hybrid switched-capacitor converters are covered, with a focus on why these topologies are suitable for aerospace applications. Next, the losses of the capacitors, the main building block of these converters, are characterized and a model is proposed which allows for simple loss estimation. Then, the design and flight qualification of a hybrid switched-capacitor converter is discussed, showcasing a converter with high efficiency, power density and reliable control. Moreover, the safe control of hybrid switched-capacitor converters during shutdown is described, with a model proposed which allows designers to understand the shutdown of the converter and trade-offs in different shutdown techniques. Hybrid switched-capacitor converters are motivated for their use in harsh space environments, where radiation effects make designing high performance converters challenging. Two different converters designed for space applications are then described, utilizing techniques such as partial power processing to minimize passive component mass. Overall, this thesis showcases the design of several high performance hybrid switched-capacitor converters, but also introduces models and comparison frameworks to allow future designers to better understand the design and operation of hybrid switched-capacitor converters in aerospace applications.

Advisor: Pilawa-Podgurski, Robert
Evaluating Climate Change Impacts on Water Resources and Food Systems – A Global Perspective with Insights from Africa and California.

This dissertation focuses on evaluating the hydrological impacts of climate change on water and food systems through integrated assessment models at various scales (global, country, and regional). The first chapter explores the future of global food self-sufficiency analysis in the 21st century under sustainable intensification of agriculture. By integrating biophysical, hydrological, climate, and societal models, the study considers factors such as sustainability, diet changes, population growth, agricultural intensification, and climate to project future scenarios. The findings reveal a concerning trend, indicating a probable decline in global food self-sufficiency within the middle-of-the-road and business-as-usual trajectories. In the second chapter, the focus shifts to Africa, a region experiencing high levels of food insecurity due to climate change and population growth. By assessing the impact of irrigation expansion on agricultural productivity and climate adaptation, the study highlights the limitations of irrigation alone in achieving food self-sufficiency. Under a 3°C warmer climate, Africa's total food production would only be sufficient to feed 1.35 billion people, while the population is projected to reach 3.5 billion. This underscores the need for additional strategies beyond irrigation alone to achieve food self-sufficiency, such as cropland expansion or increased reliance on imports. At a regional level, the third chapter employs Earth system models to assess the vulnerability of California's water-food nexus to changing snow regimes due to climate change. With a majority of snow monitoring sites showing declines in snowpack depths and earlier snowmelt onset, the study highlights the potential consequences of declining snowmelt on water availability for crop production, raising concerns about food security in a region already grappling with increased demand. This dissertation provides a comprehensive understanding of the complex dynamics influencing global food security. The findings emphasize the importance of sustainable practices, the limitations of irrigation expansion in addressing food deficits in Africa, and the vulnerability of water resources to declining snowpack in California. These insights contribute valuable knowledge for policymakers and stakeholders in formulating effective strategies to ensure a sustainable and secure food future for the global population.

Advisor: D'Odorico, Paolo