VictorJuiz/thesis huggingface dataset:
Precaution in the private interest
Keywords: Political Science.

What determines how the regulation of risk changes over time? This dissertation develops and tests a theory to explain regulatory change at both national and international levels of governance. Beginning with the observation that the regulation of risk centers on a problem of asymmetric information between the regulator and the party being regulated, I proceed to elucidate how this informational asymmetry informs the regulatory institutions that are implemented, as well as the regulatory outcomes that result. In particular, I show how producers of potentially dangerous products leverage their informational advantages in order to acquire regulations that push their less profitable products off the market in favor of more profitable alternatives. Surprisingly, precautionary institutions intended to make regulatory standards more responsive to science and new information end up helping these producers use information to their advantage. Notably, because producers' ability to win favorable regulations results from their informational, as opposed to their political, influence, producers have been as successful at winning preferential regulatory outcomes at the international level as they have at the national one. My findings have implications for global welfare as well as for scholars' theoretical understanding of the conditions under which national and international bodies do and do not produce divergent outcomes.
Predicting droplet breakup in a concentrated emulsion flowing in a microfluidic system
Keywords: Mechanical Engineering.

In recent years, droplet microfluidics has been increasingly popular in chemistry and biology where biological or chemical samples are encapsulated in nL-pL droplets. Some typical applications are using droplet microfluidics as a flow cytometer, as a drug discovery platform, for nanoparticle synthesis, and for tissue engineering. Unlike solid wells in multi-well plates, droplets are prone to instabilities at the liquid--liquid interface. They can undergo coalescence or break-up, and compromise the accuracy of the assay. While coalescence has been avoided by using appropriate stabilizers, the break-up of droplets—especially those within a concentrated emulsion—remains a limiting factor affecting the throughput of the assay, in particular during droplet content interrogation step. Unfortunately, previous studies on single droplet break-up cannot provide a thorough explanation as to why droplets break in highly concentrated emulsion flow in confined space. Furthermore, most present literature studies emulsion interactions and rheology in the macro-scale and don't study droplet-droplet interactions and individual droplet break-up within a highly concentrated emulsion flowing in a confined space. Thus, this work aims to study the physics of droplet break-up in a highly concentrated emulsion flowing into a narrow constriction. This work is categorized into three parts: (1) Quantify the droplet break-up probability at various flow parameters, channel geometries, and emulsion properties (2) Study the effects of drop pair interactions in a highly concentrated emulsion flow that leads to droplet break-up (3) Study the effects of drop shapes in a highly concentrated emulsion flow that leads to droplet break-up For the first part, the statistics of droplet break-up within a highly concentrated emulsion entering a narrow constriction at various flow parameters, channel geometries, and emulsion properties. It was found that there exist a scaling law for the break-up probability at various capillary number. For the second part, the drop pair interactions as they enter the narrow constriction are studied. It was found that the relative drop pair locations as the drops are entering the narrow constriction is a dominant factor in determining the drop break-up outcome. Three regimes were found where drops will either have a break, not break, and bistable outcome. For the third part, the drop shape as they enter the narrow constriction are studied. It was found that there are a diverse range of drop shapes occurring as the drops are entering the narrow constriction. This leads to drastically different stress balances for each individual drops as they enter the narrow constriction. For this part, a machine learning model and training strategy is proposed to describe droplet shapes and predict its break-up outcome accurately. In conclusion, this work represents a critical step towards the understanding of the physics governing drop instability in a highly concentrated emulsions flowing into a narrow constriction
Preliminary design of a hybrid motor for small-satellite propulsion
Keywords: Aeronautics and Astronautics.

Small-satellites are a low-cost, low-risk option for an increasing number of applications, including Earth observation and interplanetary exploration. However, their ranges of operation are limited by their ability to carry out critical maneuvers in space and could be further expanded with high-performance micropropulsion systems. Hybrid motors are a type of chemical propulsion option that utilize propellants stored in two different phases, typically a solid fuel and a liquid or gaseous oxidizer. For a small-satellite, a hybrid system would be better suited for rapid, large Delta-v maneuvers than electric thrusters. They have restart and throttling capabilities, and their inherent design makes them safer and more cost-efficient than hydrazine-based liquid engines. The delivered specific impulse is comparable to conventional bipropellant systems (300--350 s). As a result, they are a prime candidate for in-space applications requiring long-term propellant storage and low gross mass. However, with no flight heritage, the technology readiness level of small-scale hybrid motors remains low, and the fundamental understanding and modeling of the combustion phenomena is still immature. To be considered more consistently in system trade studies, the accuracy of preliminary design models and performance estimations must be improved. This thesis work provides a framework for consistent preliminary design analyses to further compare and assess the capabilities of small-scale hybrid motors. Fuel selection and other design choices are discussed. The benefits of using an optimization scheme to determine the best operational parameters are outlined. To improve the quantitative results, it was established that two parameters require further investigation: the solid fuel regression rate and the characteristic velocity c* efficiency. To further improve our understanding of hybrid combustion phenomena, an experimental setup was designed to measure the performance of a small-scale motor using gaseous oxygen and solid polymethylmethacrylate (PMMA). To calculate the instantaneous characteristic velocity, the total mass flow rate expelled during the hotfire must be determined. This requires an accurate measurement of the fuel regression rate in space and time. A non-intrusive, easy-to-implement, and low-cost measurement technique was developed using an optically clear fuel and a high-resolution camera, providing temporally and spatially resolved data. More than 60 hotfires were carried out to validate the method and collect data for a wide range of conditions including varying motor geometry and oxidizer mass flow rates. Experimental investigations led to multiple findings that can further advance our ability to design efficient hybrid motors. In particular, the injection scheme⁠—rarely discussed in regression rate modeling⁠—was found to have a large impact on the fuel regression rate and motor stability. Nozzle erosion and c* efficiency were also measured and guidelines to influence them are outlined.
Preminger's doubt : close analysis and film aesthetics in the aftermath of old Hollywood
Keywords: Art and Art History.

I find something quietly unsettling in three unloved works by the aging (read "declining") Hollywood filmmaker Otto Preminger. In Harm's Way (1965), Skidoo (1968), and Tell Me That You Love Me, Junie Moon (1970). These three films may at once appear somewhat unremarkable. They do not announce their strangeness with the kind of disjunctive experimentation like so many late 60s-early 70s films of the America's "New" Hollywood. But in them, Old Hollywood persisted, perhaps beyond the reach of its moment. In this project, I bring an art historical attentiveness and responsiveness to the study of film, and I find the doubts of the late 60s-early 70s quietly lurking in this rather unexpected place. "Preminger's Doubt: Close Analysis and Film Aesthetics in the Aftermath of Old Hollywood" is a project about the strangeness and inexhaustibility of the single work of art within and against its historical and aesthetic context. I show how three films forcefully probe a felt uncertainty in the aftermath of the Hollywood studio system, when the look and feel of American films—and American culture at large—were rapidly changing. Each work, in its own way, is attuned to a sense of vast institutional collapse, sensitive not only to Hollywood's fading memory of itself but also to the uncertain aftermaths of their contemporary moment—how Junie Moon's failure to follow relates to a waning of interest in NASA after the Apollo moon landing, how In Harm's Way's delayed credits sequence figures an uncertain world after the explosion of the atomic bomb, how Skidoo's widescreen aesthetics suggests a strange continuity between the older medium of film and the younger medium of television in the late 60s. But more than this, my dissertation finds an affinity between these films and the demands of close analysis. These films challenge us to connect—or meaningfully detach—certain moments, gestures, and images across the unfolding texture of the single work. At other times, they suggest parallels only to leave them open to doubt rather than neatly resolved.
Preschool enrollment and mothers' labor market outcomes in Brazil
Keywords: Mothers Employment
Mothers Earnings
Mothers Work Hours
Preschool
Public Policy
Work and Family
Gender-Gaps in the Labor Market
Stanford Graduate School of Education International Comparative Education
Thesis

I analyze the increase in financing early childhood education in Brazil by FUNDEB in 2006 and the establishment of compulsory preschool enrollment by Constitutional Amendment #59 in 2009 to understand its effects on preschool enrollment and mothers’ labor outcomes measured by their probability of working, hours worked and earnings. I provide empirical evidence of mothers’ responsiveness to changes in compulsory preschool enrollment and financing preschool. I hypothesize that FUNDEB and the establishment of Amendment #59 positively affected preschool enrollment. Then I hypothesize that this increase thus positively affected mothers' labor market outcomes. Through a difference-in-differences analysis, I exploit geographic variation across time and states in preschool enrollment. I compare the labor outcome of mothers of preschoolers with those of mothers with older children. Individual-level data (mothers and children) and aggregate data (families) come from the Brazilian National Household Survey (PNAD). Results indicate that the establishment of both FUNDEB and Amendment #59 positively increased preschool enrollment of 4 and 5 year old children compared to 6 and 7 year olds enrolling in primary education. Results also indicate that higher preschool enrollment positively affected mothers of preschoolers’ probability to work. However, that increase did not affect mothers’ earnings and hours worked, as these effects are not statistically significant.
Prescription Drug Expenditures, New Drug Launches, and Disease-specific Mortality
Keywords:  Department of Economics
Department of Economics
pharmaceutical innovation
healthcare
drug expenditures
R&amp;D
mortality
prescription drugs
drug prices
Thesis

This paper explores the relationship between disease-level prescription drug expenditures, the availability of FDA-approved prescription drugs, disease-level scientific R&D expenses, and disease-specific mortality. Leveraging prescription drug data from the national Medical Expenditures Panel Survey, mortality data from the Center for Disease Control, research expenditures data from the NIH, and drug launch data from the FDA, I develop a number of fixed effects regression models to assess how movements in drug launches, disease-level research, and disease-level expenditures impact mortality as a health endpoint. This research elucidates how various movements in pharmaceutical innovation can predict changes in mortality rates. This paper also aims to understand the impact of new drug launches across time and resolve whether mortality trends are more significantly related to drug launches in a previous year than in a current year – the former of which suggests that drug launches drive movements in mortality rather than the reverse. Analysis of a time lagged innovation variable estimates that a 1% increase in the cumulative available prescription drugs on the market yields a 0.25% decrease in mortality rates for individuals above the age of 65 and a 0.37% decrease in mortality rate for individuals below the age of 65. Analysis of disease-level NIH R&D data shows that a 1% increase in research spending yields a 0.59% decrease in mortality rate for individuals older than 65.
Pricing, spending, and shortages in US biopharmaceutical markets
Keywords: Health Research and Policy.

In this era of national concern about the availability and affordability of prescription drugs, policymaking is moving quickly, although critical gaps persist in the supporting evidence base. This dissertation is a collection of three essays written on economic and policy issues related to biopharmaceutical markets in the United States. The first chapter, "Price Elasticity of Demand for Prescription Drugs: Evidence from Medicare Part D's Low-Income Subsidy Program, " measures consumers' behavioral response to changes in the out-of-pocket price of prescription drugs by tracking Medicare Part D beneficiaries as they change Low-Income Subsidy status. In my second chapter, titled "Spending on Unapproved Drugs and Impact of the FDA Unapproved Drugs Initiative on Drug Utilization in the US, " I quantify spending on and utilization of certain marketed, unapproved prescription drugs for Medicare patients in the US and estimate how utilization changes when previously unapproved drugs gain FDA approval. In my third chapter, titled "Biopharmaceutical Market Shortages: Causes and Cures, " I explore primary causes of shortages in the biopharmaceutical space, with a particular focus on how forces at work in common generic sterile injectable drug shortages may be applicable to biologics; I also evaluate potential avenues for strategic regulatory reforms to prevent or mitigate shortages, examining proposed policy and non-policy solutions that could help address the factors contributing to biopharmaceutical shortages in the US.
Principled algorithms for finding local minima
Keywords: Management Science and Engineering.

Convex optimization is the cornerstone of continuous optimization, but many real problems arising in machine learning and operations research are nonconvex. This two part thesis explores my work developing principled algorithms for finding local minima of nonconvex functions. Part I: The complexity of finding stationary points of nonconvex functions. For a long time, it was known that gradient descent achieved an $\epsilon^{-2}$ rate for finding stationary points of unconstrained nonconvex functions, but better rates for first-order methods were unknown. We show that, using an algorithm that judiciously utilizes Nesterov's accelerated gradient descent, it is possible to improve this rate to $\epsilon^{-7/4}$ rate for functions with Lipschitz first and second derivatives. Adding Lipschitz third derivatives improves this rate to $\epsilon^{-5/3}$. Moreover, we provide almost matching lower bounds to prove that (i) finding a stationary point is easier for convex functions and (ii) acceleration in nonconvex optimization requires assumptions beyond smoothness. Part II: Interior point methods for nonconvex optimization. The second part of this thesis focuses on an interior point method (IPM) for optimization problems with nonconvex constraints. The work of Wachter and Biegler suggests that infeasible-start interior point methods (IPMs) developed for linear programming cannot be adapted to nonlinear optimization without significant modification, i.e., using a two-phase or penalty method. We propose an IPM that, by careful initialization and updates of the slack variables, is guaranteed to find a first-order certificate of local infeasibility, local optimality or unboundedness of the (shifted) feasible region. Our proposed algorithm differs from other IPM methods for nonconvex programming because we reduce primal feasibility at the same rate as the barrier parameter. This gives an algorithm with more robust convergence properties and closely resembles successful algorithms from linear programming. Comparisons with IPOPT on a subset of CUTEst problems indicate less frequent failures and superior performance for detecting infeasibility. Finally, we develop a highly simplified version of our IPM method with nonconvex constraints that obtains an $\epsilon$-scaled KKT point in $\epsilon^{-7/4}$ iterations. This provides the first proof that IPMs with nonconvex constraints have a polynomial runtime in
Probing the groove epitope on HIV-1 GP41 for sensitivity to neutralizing antibodies
Keywords: Biochemistry.

The Human Immunodeficiency Virus (HIV) has been a public health scourge since its appearance in the early 1980s. Having spread its way from sub-Saharan Africa across the world, now 1 in 200 people living on earth is infected with the virus. Because there is currently no cure, everyone infected with HIV will progress to Acquired Immunodeficiency Syndrome (AIDs), where they will succumb to an AIDs-related illness. Our growing understanding of the molecular mechanisms of the HIV virus has greatly aided the development of new therapeutics. HIV is a membrane virus containing only one viral protein on its surface, the envelope glycoprotein (Env). Env is responsible for mediating the fusion of the viral membrane with the membrane of the target cell. Antibodies towards Env block membrane fusion and prevent infection. Because HIV mutates rapidly resulting in a diverse array of clinical isolates, strategies aimed at eliciting neutralizing antibodies have failed. This is due to these antibodies being strain-specific and unable to provide protection against the many clinical isolates. The recent discovery of broadly neutralizing antibodies has re-invigorated the search for a vaccine. These antibodies target conserved regions on Env and thus are able to provide protection against a diverse range of clinical isolates. This dissertation focuses on our findings characterizing the most conserved region of Env, the groove region of the gp41 N-heptad repeat. We first design and validate new mimetics of the N-heptad repeat. Second, we use these mimetics to select for monoclonal antibodies. Third, we immunize guinea pigs to test whether these mimetics are capable of eliciting neutralizing antibodies. Finally, we investigate strategies for improving the potency of N-heptad repeat antibodies through the use of drug combinations. Together, these finding suggest that antibodies towards the groove epitope, though weakly neutralizing, may be a viable vaccine strategy.
Probing the physics of AGN feedback with high resolution X-ray spectroscopy
Keywords: Physics.

Active galactic nuclei (AGN) significantly impact the evolution of their host galaxies, as they can prevent star formation by either expelling large fractions of gas with wide-angle outflows, or by heating up the halo gas with jets. However, how the AGN energy is transferred to the galaxy in either of these feedback modes is still not known. My dissertation research involves novel applications of modern inference techniques to high resolution X-ray spectra in order to gain new insights into the physical processes behind AGN feedback. First, our improved Bayesian framework for the self-consistent modelling of deep spectra from nearby AGN with X-ray detected outflows is introduced. For the first time we are able to perform robust model selection, while keeping all of the parameter space open. We applied our approach to a new, deep Chandra High Energy Transmission Grating observation of the Seyfert-1 galaxy NGC 4051, where we successfully mapped multiple absorbing components moving at a few 1000 km/s. We obtained one of the tightest outflow density constraints to date, thereby measuring the wind's impact on the galaxy. Second, our unprecedented measurements of the gas turbulent velocities in the cores of 13 nearby giant elliptical galaxies are presented. These new constraints were obtained by statistically combining resonant scattering and direct line broadening, studied with deep XMM-Newton Reflection Grating Spectrometer observations. This allowed us to explore the precise nature of the hot gas motions in massive galaxies and constrain models of AGN feedback in these objects. Then, a successful application of our resonant scattering analysis to the first X-ray microcalorimeter observation, the Hitomi Perseus Cluster spectrum, is discussed. This analysis allowed us to place constraints on the hot gas turbulence in a galaxy cluster that are independent of direct line width measurements. This technique can also provide unique clues to the three dimensional structure of the gas velocity field when statistical uncertainties are minimized. Both of the presented analyses will naturally extend to new data sets from the upcoming high spectral resolution X-ray missions, such as XRISM, ATHENA, Arcus, and Lynx.
Probing the Pragmatic Information Encoded in Neural Networks’ Word Embedding Space
Keywords:  Symbolic Systems Program
Scalar Implicature
Neural Network Models
Word Embeddings
Pragmatics
Symbolic Systems Program
Thesis

It is frequently argued that natural language understanding models relying on deep learning techniques are not likely to admit of analytic understanding, for people cannot explicitly tell which piece of semantics, pragmatics, or other linguistic knowledge these models are able to understand and utilize. In this project, different pre-trained word embeddings as well as different neural network architectures have been explored. We specifically analyze the performance of predicting the implicature strength ratings of some on Switchboard corpus of telephone dialogues. The results provide evidence that multiple hand-mined contextual features previously identified as influencing inference strength become less significant when we include the neural network predictions as the new indicator and that the neural model can capture such qualitative effects, from which we come to the conclusion that at least some of the pragmatic information has already been encoded in the pre-trained word vectors and the neural network is able to learn this knowledge to predict human inference strength judgments for sentences with some.