VictorJuiz/thesis huggingface dataset:
Working on the Poor: Ambulance Labor in the Polarized City

What is the role of the 911 ambulance in the American city? The prevailing narrative provides a rather simple answer: to save and transport the critically ill and injured. This is not an incorrect description, but it is incomplete. The ambulance plays another role, one that is less known. Along with other frontline institutions like the prison and welfare office, I argue the ambulance is part of a poverty regulating regime that is focused less on the eradication of material suffering and more on the day-to-day management of its symptoms./nI draw on nearly two years of fieldwork (including 9 months working as a novice emergency medical technician) and over 100,000 medical records to reimagine the ambulance as an institution of poverty governance. Against somewhat common assumptions that this vehicle is absent or tardy in poor neighborhoods, my research demonstrates that the ambulance is actually a prevalent and busy institution in these areas. Not only are the poor more likely to experience life threatening crises, they are also more likely to summon the ambulance for so-called non-emergencies./nWhether by compressing lifeless chests on the streets or by transporting the publicly intoxicated into the hospital, ambulance crews daily transform the bodies and spaces of urban poverty. This work brings them in recurrent contact with the emergency department nurses and police officers who share their clientele. I show how these different workers often conflict over the management of subjects they generally see as burdensome. With “legit” ambulance calls being relatively rare, crews frequently struggle with police and nurses over “bullshit” work. These street-level relations, however, cannot be understood without considering the forces that control and coordinate labor from above. Neoliberal principles of organizational efficiency and flexibility have flooded poverty governing institutions throughout the American city, and the ambulance is no exception. The state often delegates paramedical operations to for-profit agencies that run on a fee-for-service model. This intensifies the exploitation of labor and exacerbates tense relations between crews and their clientele on the one hand and crews and their nurse and police counterparts on the other./nMy research advances a new framework for understanding the management of marginality: the labor theory of poverty governance. This model insists that we cannot understand how the poor are governed without understanding the labor process that generates and re-generates the poverty regulating state. This means accounting not only for the interactions between laborers and the subjects of their labor, but also the horizontal interactions amongst laborers and the vertical interactions between laborers and those who control and coordinate their work. This framework is novel in that it integrates three crucial dimensions of poverty regulation: the frontlines of governance, the horizontality of governance, and the verticality of governance.

Advisor: Burawoy, Michael
A Learning-Based Approach to Safety for Uncertain Robotic Systems

Robotic systems are becoming more pervasive, and have the potential to significantly improve human lives. However, for these benefits to be realized it is critical that the safe operation of these systems be guaranteed. Reachability analysis has proven to be an effective tool for providing safety certificates for dynamical systems, given a model of the system. A major challenge in assuring safety, is that systems often have uncertainty due to the hard-to-model complex physical interactions, or lack of knowledge of the behavior of external agents, on which safety may depend./nThis thesis uses Hamilton-Jacobi (HJ) reachability analysis to robustly guarantee safety for systems with uncertainty. In the presence of uncertainty there must be a balance between conservativeness as it pertains to safety and performance as it pertains to other system objectives, and we also account for this through reachability analysis. In addition, this thesis also explores methods for modifying the analysis as more data is collected from the robotics system, which ultimately allows for improved performance. This is referred to here as learning-based reachability analysis. The thesis concludes with a new HJ reachability formulation that enhances the learning-based analysis. The myriad of ideas presented throughout the thesis are demonstrated on various examples.

Advisor: Tomlin, Claire J
Bayesian Methods for Mortality Estimation

The development of mortality models is important in order to reconstruct historical processes, understand current patterns and predict future trends. Mortality models are particularly useful when the available data are sparse, unreliable or incomplete. Traditionally, mortality patterns in data-rich populations were used to observe mathematical or empirical regularities, which could be applied to data-sparse populations. However, as a wider variety of data have become available, the focus of model building has shifted to developing flexible models that perform well in a variety of contexts./nThis dissertation introduces Bayesian methods of mortality estimation in three contexts where the available data are imperfect. The first paper develops a method to estimate subnational mortality in situations with small populations and highly-variable data. The second paper develops a unified modeling framework to estimate and project neonatal mortality in all countries worldwide, including those with limited and poor-quality data. The third paper introduces a new dataset to study mortality inequalities in the United States, and develops methods to deal with the truncated and censored mortality information that is available. In all three contexts, the modeling approaches combine strengths from traditional demographic models, which capture mortality regularities across age, with the flexibility of Bayesian frameworks, which allow for multiple data sources to be incorporated, information to be shared across time and space, and uncertainty to be assessed.

Advisor: Goldstein, Joshua R
Independence, Amalgamation, and Trees

This thesis is concerned with developing a theory of model-theoretic tree properties. These properties are combinatorial properties of a formula or family or formulas that place strong constraints on the behavior of forking and dividing yet are compatible with certain forms of model-theoretic randomness. The most significant and intensively studied is \emph{the tree property}, whose negation characterizes the simple theories, and a successful theory for simple theories was developed by Hrushovski, Kim, Pillay, and others, in the late 90s and early 2000s. Motivated by parallels with simplicity theory, we introduce a theory of independence called \emph{Kim-independence} and present a structure theory for NSOP$_{1}$ theories in terms of it. This unifies and explains simplicity-like phenomena observed in several non-simple examples, such as existentially closed vector spaces with a bilinear form and $\omega$-free PAC fields. This machinery also gives a streamlined method for establishing that a given theory is NSOP$_{1}$ and for showing that certain generic constructions preserve NSOP$_{1}$. We also develop techniques for the manipulation of tree indiscernibles to address several questions concerning the syntax of the related model-theoretic tree properties TP$_{1}$, weak $k$-TP$_{1}$, and the associated cardinal invariants.

Advisor: Scanlon, Thomas
Volumetric Additive Manufacturing of Arbitrary Three-Dimensional Geometries in Photopolymer Materials

Additive manufacturing (AM) capabilities are rapidly expanding and AM is increasingly used for the production of end-use and multi-component parts. The field of AM now encompasses technologies that rely on a broad range of process physics, from which the ASTM has delineated 7 distinct categories. The term “3D printing” is often used synonymously with additive manufacturing to describe systems that build parts of custom 3D geometry on demand. While the final parts produced by 3D printing are three-dimensional, the printing processes typically rely on serial repetition of unit printing operations of dimensionality less than three. Three-dimensional parts are built up point-by-point or layer-by-layer./nThis thesis covers the design, implementation, and development of new methods for volumetric or volume-at-once additive manufacturing, where entire complex three-dimensional geometries are printed all together. After an introduction to the current state of additive manufacturing in Chapter 1, Chapter 2 presents a background and modeling of photopolymer chemistry, which is leveraged to develop the novel manufacturing methods discussed in detail in Chapters 3 and 4. In addition to development of the core operating principles behind these technologies, this thesis presents demonstrations of printed components and manufacturing capabilities. Potential applications spaces are discussed with proof-of-concept demonstrations in bioprinting and multi-process AM. These include printing of soft (~1-10kPa stiffness) hydrogel structures along with a demonstration of a novel “overprinting” capability that prints complex polymer geometries onto pre-manufactured metal components./nThe concluding chapter (5) discusses current capabilities and limitations of these novel processes and looks ahead toward further development directions.

Advisor: Taylor, Hayden K
Acquiring Diverse Robot Skills via Maximum Entropy Deep Reinforcement Learning

In this thesis, we study how maximum entropy framework can provide efficient deep reinforcement learning (deep RL) algorithms that solve tasks consistently and sample efficiently. This framework has several intriguing properties. First, the optimal policies are stochastic, improving exploration and preventing convergence to local optima, particularly when the objective is multimodal. Second, the entropy term provides regularization, resulting in more consistent and robust learning when compared to deterministic methods. Third, maximum entropy policies are composable, that is, two or more policies can be combined, and the resulting policy can be shown to be approximately optimal for the sum of the constituent task rewards. And fourth, the view of maximum entropy RL as probabilistic inference provides a foundation for building hierarchical policies that can solve complex and sparse reward tasks. In the first part, we will devise new algorithms based on this framework, starting from soft Q-learning that learns expressive energy-based policies, to soft actor-critic that provides simplicity and convenience of actor-critic methods, and ending with automatic temperature adjustment scheme that practically eliminates the need for hyperparameter tuning, which is a crucial feature for real-world applications where tuning of hyperparameters can be prohibitively expensive. In the second part, we will discuss extensions enabled by the inherent stochasticity of maximum entropy polices, including compositionality and hierarchical learning. We will demonstrate the effectiveness of the proposed algorithms on both simulated and real-world robotic manipulation and locomotion tasks.

Advisor: Levine, Sergey
Abbeel, Pieter
Topological Phase Transitions

The study of continuous phase transitions triggered by spontaneous symmetry breaking has brought/nrevolutionary ideas to physics. Recently, through the discovery of symmetry protected topological phases, it is realized that continuous quantum phase transition can also occur between states with the same symmetry but different topology. The subject of this dissertation is the phase transition between these symmetry protected topological states (SPTs). There are two main parts in this dissertation./nIn the first part we consider spatial dimension $d$ and symmetry group $G$ so that the cohomology group, $H^{d+1}(G,U(1))$, contains at least one $Z_{2n}$ or $Z$ factor. We show that the phase transition between the trivial SPT and the root states that generate the $ Z_{2n} $ or $Z$ groups can be induced on the boundary of a d+1 dimensional $G\times Z_2^T$-symmetric SPT by a $Z_2^T$ symmetry breaking field. Moreover we show these boundary phase transitions can be ``transplanted'' to d dimensions and realized in lattice models as a function of a tuning parameter. The price one pays is for the critical value of the tuning parameter there is an extra non-local (duality-like) symmetry. In the case where the phase transition is continuous, our theory predicts the presence of unusual (sometimes fractionalized) excitations corresponding to delocalized boundary excitations of the non-trivial SPT on one side of the transition. This theory also predicts other phase transition scenarios including first order transition and transition via an intermediate symmetry breaking phase./n/nIn the second part, we study the phase transition between bosonic topological phases protected by $Z_n\times Z_n$ in 1+1 dimensions. We find a direct transition occurs when $ n=2,3,4 $ and in all cases the critical point possesses two gap opening relevant operators: one leads to a Landau-forbidden symmetry breaking phase transition and the other to the topological phase transition. We also obtained a constraint($ c\geq1 $) on the central charge for general phase transitions between symmetry protected bosonic topological phases in 1+1D.

Advisor: Lee, Dung-Hai
Detonation Initiation, Propagation, and Suppression

Understanding the fundamental processes of detonation is essential for both energy and safety issues. The rapid energy conversion characteristic of detonation is significantly useful in industrial and military applications, such as detonation engines and high explosives. On the other side, this characteristic of detonation is not preferred in the field of safety engineering. Detonations with violent pressure waves frequently cause catastrophic human casualties and property damages./nThis dissertation presents theoretical and numerical studies on detonation initiation, propagation, and suppression. Multiple numerical tools are employed to study detonation phenomena: a toolbox to calculate the steady state homogeneous detonation properties, a simplified unsteady compressible solver for Lagrangian equations to simulate detonation behaviors as a primary stage, and a compressible multi-component reacting flow solver to perform transient simulations of the detonation phenomena in detail./nSeveral methods to predict the occurrence of detonation initiation and deflagration to detonation transition are developed. Transient and integral reactivity gradient methods are proposed and evaluated on the basis of the Zel'dovich gradient theory. Prediction models of detonation initiation developed from machine learning techniques are also presented. Potential applications of statistical learning models with the conventional numerical simulations are discussed./nEffects of fuel-stratification on detonation propagation are identified by detailed numerical simulations. Both the leading shock pressure and detonation propagation speed in the fuel-stratified layer are compared to the corresponding homogeneous Chapman-Jouguet detonation properties. The shock reflection and transmission theory, and the Zel'dovich-Neumann-Döring detonation structure model are employed to describe deficits or surpluses in properties of stratified detonation. The overall mechanism of stratified detonation propagations is also proposed./nDetonation suppression in water vapor concentration gradients is investigated by the transient numerical simulations with various water vapor concentrations and thicknesses of the gradient layer. From the simulations, three combustion modes are observed: 1) normal detonation propagation, 2) detonation mitigation and re-initiation, 3) detonation suppression. The separation of leading shock and reaction front is the main cause of a detonation suppression. A regime map for limits of each mode is introduced showing that the mode depends on the normalized ignition delay time including shock reflection effect and the ratio of the gradient layer thickness to the detonation induction length. The transient reactivity gradient is employed to understand the detonation re-initiation process after the mitigation of the initial detonation.

Advisor: Chen, Jyh-Yuan
Characterization of Substituted Radicals by Multi-Edge Femtosecond X-Ray Transient Absorption Spectroscopy

Femtosecond x-ray transient absorption spectroscopy is used in conjunction with selective bond breaking to characterize the electronic structures of substituted radicals. By utilizing the A band photodissociation of iodides, a series of carbon-centered radicals is produced and their frontier molecular orbitals are probed via core-level transitions by x-ray photons produced through high harmonic generation, whose limit has been extended to 390 eV with the apparatus detailed in the second chapter./nTwo types of substituted radicals are studied in this work to demonstrate substitution effects: halogenated radicals and alkyl substituted radicals. The third chapter focuses on the halogenated radicals, in particular ·CH2Cl and ·CH2Br, which are produced under ultraviolet radiation of CH2ICl and CH2IBr, respectively. The ·CH2Cl radical is probed via the carbon K edge and the chlorine L2,3 edges to reveal the electron withdrawing effect impacting different atoms in the photodissociation of CH2ICl. Core-level transitions in ·CH2Br are studied in comparison to ·CH3 and ·CH2Cl to understand possible stabilization of the frontier molecular orbital by π bonding and the strength of such stabilization. The fourth chapter turns to the alkyl substituted radicals, where the methyl, ethyl, isopropyl and tert-butyl radical are produced from methyl, ethyl, isopropyl and tert-butyl iodide, respectively. While the characteristic carbon 1s→σ*(C-I) transition takes place in the parent iodides at similar energies, the transition from carbon 1s to the frontier singly occupied molecular orbital differs drastically in the radicals. This can be explained by either a significant change in the carbon 1s orbital of the radicals because of methyl substitution or complications due to vibrational excitation. The results point to new directions for core-level theoretical investigations.

Advisor: Leone, Stephen R
Coupled Multiscale Modeling of Aortic Valve Tissue

Recent studies have uncovered the pivotal role that valvular interstitial cells play in the/naortic valve system. The valvular interstitial cells regulate the extracellular matrix, maintain/nhomeostasis, and modulate pathology, among other vital functions. The inherent connection/nbetween the aortic valve as an organ and its constituent cells may explain the shortcoming of/ntraditional biomechanical modeling, particularly when the goal is to understand the cause,/nevolution, treatment, and prevention of disease./nMultiscale modeling of aortic valves has recently emerged, but is relatively nascent and/nmuch is missing from the literature. Most notably is the lack of a coupled multiscale model of/nthe aortic valve, wherein the biomechanics of the aortic valve organ and its constituent cells/nimpact one another. In this work, we investigate a novel multiscale approach to modeling/naortic valve tissue that is coupled, i.e., biomechanical events occurring at disparate length/nscales are simultaneously captured./nWe begin by presenting a model of aortic valve tissue that explicitly accounts for the/ncollagen bers that make up its microstructure and is consistent with experimental data./nWe then apply this model in an FE2 (computational homogenization) framework to model/nthe aortic valve tissue as an organ and its constituent valvular interstitial cells. We show/nthe validity of such an approach and use it to argue the necessity of 3D multiscale modeling./nFinally, we apply the multiscale model to a calcied aortic valve to study the mechanical/nbehavior of the valvular interstitial cells in pathological tissue.

Advisor: Govindjee, Sanjay
Vital Signs: Rhythm, Image, and Voice in Russian Modernist Poetry and Theory 1905-1924

This dissertation focuses new critical attention on Russian modernism’s engagement with poetic form. Placing close-readings of poetic and theoretical texts in the context of rapid urbanization, the emergence of new technologies, and socialist revolution, it argues that it is precisely where modernist poets (Alexander Blok, Boris Pasternak, and Vladimir Mayakovsky) and formalist theorists (Boris Eikhenbaum, Viktor Shklovsky, and Yury Tynianov) are most interested in the nature and functioning of poetic language that they respond most urgently to the dramatic changes occurring in early-twentieth-century Russian society and public discourse. Contrary to common approaches to Russian modernism that view it primarily in terms of competing poetic schools and distinct periods, the three chapters of this dissertation aim to think across the theory/practice divide, highlighting the common impulses behind the diverse output of its central figures in order to arrive at a definition of modernism not through periodization or literary school but instead as a certain way of thinking about and through poetic form and its relation to society. Bringing Russian modernism into dialogue with contemporary Western theories of the lyric, old/new media, and the urban environment, the dissertation asks what the poetic and theoretical output of this period has to tell us about the functioning of poetry and its role in the world today.

Advisor: Ram, Harsha
Golburt, Lyubov
Race as a Dependent Variable: Three Papers on the Social Predictors of Racial Attribution and Identification in Brazil

Racial classification is relational, and it is constructed and contested as both an identity and as an ascribed category. In this three-part dissertation, I examine racial classification in São Paulo, Brazil, and argue that we can leverage survey data on racial classification to reach a more nuanced understanding of racial boundaries./nPaper 1: Because racial classification is relational, we must examine both sides of the relationship, and yet most studies on ascription do not consider the ways in which the ascriber’s traits matter for classificatory outcomes. Using a quasi-experimental design, I examine how statuses of both the classifier and of the person being classified matter for racial attribution. I find that high-status biographies paired with a racially ambiguous face have a higher likelihood of white (versus pardo) racial attribution. I also find that educational achievement is significantly predictive of seeing whiteness in others—irrespective of the phenotype, self-identification, or the social status of the person being classified./nPaper 2: Drawing on a large-scale survey linked to census-tract data, I examine how classification can operate asymmetrically across different racial boundaries. I compare the effects of various individual-level and neighborhood-level traits on the chances of having one’s racial identity contested by an observer. I show that social status does not have a uniform effect, mattering greatly for the boundary between white and pardo, and much less for the boundary between pardo and black. I also find that individuals living in richer or more educated neighborhoods—even when controlling for individual status—are more likely to be whitened, and less likely to have their white identities challenged./nPaper 3: In this paper, I demonstrate how we can leverage racial mismatch data to study the everyday impact of institutions (in this case, the police) on individual racial identity. With a combination of survey and census data, I show how self-reported contact with the police in the twelve months prior to the survey is associated with a lower chance of identifying as white, even when controlling for individual status and observed race. I also show how neighborhood characteristics can further shape racial identity: Proximity to a favela, the neighborhood rate of economically motivated crime, and the racial makeup of the neighborhood all have separate and independent effects on racial identity.

Advisor: Fourcade, Marion