VictorJuiz/thesis huggingface dataset:
Matching with interviews
Keywords: Economics.

This dissertation explores matching markets in which interviews take place before the final match is determined. Specifically, the discussion is framed in the context of the entry- and intermediate-level labor markets for medical doctors and surgeons in the United States. Recent debate in the medical literature has raised concerns about the pre-match interview process for residency and fellowship positions at US hospitals, and many market participants have expressed discontent with the process through which interviews are determined. However, little is known about the economics of this decentralized process. In this dissertation, I identify new sources of inefficiency in interview markets that are consistent with several of the concerns that have been raised in the medical literature. I also provide novel insights into market design interventions intended to address both these and related concerns. Moreover, I propose an adaptation of the concept of stability to the context of interview markets, and explore several of its implications
Mathematical and decision analytic modeling of interventions to mitigate infectious diseases from endemic to pandemic
Keywords: Management Science and Engineering.

Infectious diseases are responsible for millions of deaths globally each year. Difficult decisions must be made about how to allocate resources efficiently to treat infection, prevent transmission, and save lives while also mitigating the negative impacts of an outbreak. Mathematical and decision analytic modeling help inform decision makers about the most effective and most cost-effective interventions to prepare for and respond to infectious disease outbreaks. In this dissertation, I present novel applications of a variety of model types to assess interventions for recent disease outbreaks. I develop cutting edge methodological improvements for decision making amid an outbreak and provide critical evidence on how model structure could impact predicted intervention effectiveness. Specifically, I assess the cost-effectiveness of plague control interventions for the 2017 plague outbreak in Madagascar including expanded access to antibiotic treatment with doxycycline, mass distribution of doxycycline prophylaxis, and mass distribution of malathion -- alone and in combination. I focus on the trade-off between intervention timing and coverage levels as measured in terms of costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios. Subsequently, I provide a novel framework for rapid decision making and advancing methods for meta-modeling in the infectious disease context. I derive the simple decision rule using a compartmental model framework and net monetary benefit to assess cost-effectiveness and compare the performance of the simple decision rule to machine learning metamodels. During the COVID-19 pandemic, I estimated the impact of various mitigation strategies on COVID-19 transmission in a large U.S. urban jail. I develop a stochastic dynamic transmission model and use this model to estimate the effectiveness of three interventions undertaken by the jail -- depopulation, increased single celling, and asymptomatic testing -- in reducing the spread of COVID-19. Finally, I explicitly address how the choice of model can influence estimates of intervention effectiveness in the short and long term for an endemic disease. I consider four disease models with different permutations of socially connected network vs. unstructured contact (mass-action mixing) model and heterogeneous vs. homogeneous disease risk. I calibrate the models to the same long-term equilibrium disease prevalence and consider a simple intervention with varying levels of coverage and efficacy. For each type of model, I measure the rate of prevalence decline post-intervention, the long-term equilibrium prevalence, and the long-term effective reproduction ratio at equilibrium
me++: Finding Oneself in Computer Science
Keywords: computer science education
academic identity
culturally relevant pedagogy
introductory class
narrative as liberatory practice
Text
Thesis

In the university context, student experiences of courses, dorm life, and more affect how they discover where they belong. In that stream of thought, I followed five students taking CS 106A at Stanford to see how they made sense of their position within and relative to computer science, over the course of the quarter. In those interviews, I watched my participants make sense of their experiences, and co-construct knowledge with them. I saw how they were reflecting on their experiences to form a sense of where they belong in computer science, and at Stanford more generally. I propose a framework of three dimensions to capture their reflections: computer science (a) as a cultural milieu; (b) as a constellation of negotiated values; and (c) as an affective experience. As their positions within and relative to computer science evolved throughout the quarter, my participants relied on those three dimensions, in conjunction with one another, to make sense of their experiences in the course. These results problematize the static treatment of one’s position within and with respect to a discipline, and emphasize the importance of liberatory interview practices in qualitative studies of sensemaking. For educators, this work emphasizes the importance of curriculum construction in context—student-centered education requires a nuanced understanding of the student context.
Measurement and representation
Keywords: Political Science.

This dissertation consists of three papers under the topic of Measurement and Representation. The first paper is entitled QUESTIONING QUESTIONS IN THE LAW OF DEMOCRACY: WHAT THE DEBATE OVER VOTER ID LAWS' EFFECTS TEACHES ABOUT ASKING THE RIGHT QUESTIONS. The second paper is entitled BOLSTERING FAITH WITH FACTS: SUPPORTING INDEPENDENT REDISTRICTING COMMISSIONS WITH REDISTRICTING ALGORITHMS. The third paper is entitled REDISTRICTING AND NATIVE REPRESENTATION
A measure-theoretic approach to Bayesian hypothesis testing and inversion with geophysical data
Keywords: Geophysics.

Today, most geophysical hypothesis testing and inverse problems are formulated using conditional probability and Bayes' Theorem. In this dissertation, we argue that measure-theoretic principles provide a more natural alternative to hypothesis testing and inverse problems. First, we present the theory behind this measure-theoretic formulation of inverse problems. We also compare it to the conditional probability and conjunction of information inverse problem formulations. Then, we apply the hypothesis testing formulation to compare a numerical model of river delta sedimentation to laboratory experiments. This comparison quantitatively shows that the numerical delta model cannot capture the experimental channel dynamics. Finally, we apply the inversion formulation to determine the geological origins of a zone of fractured shale bedrock in the Rocky Mountains of Colorado. We invert electrical resistivity tomography data to estimate the dip angle of the fracture zone, which shows that two of the six proposed fracturing mechanisms are inconsistent with the data. Together, the theory and applications developed in this dissertation show that measure-theoretic formulations can help solve larger and more complicated Bayesian inference problems than existing methods
Measuring rapidity and momentum distributions of dipolar 1D quantum gases
Keywords: Applied Physics.

Quantum integrable systems such as Lieb-Liniger model are naturally characterized by the momenta of the long-lived quasi-particles, or rapidities. The mapping between rapidities and physical momenta is highly non-trivial in a strongly correlated system, and it is only until recently becoming experimentally accessible in strongly interacting cold atom setups. The observation of rapidity distributions provides a great opportunity to understand quantum near-integrable systems from both experiment and theory perspectives. In this dissertation, I present our work on characterizing the rapidity distribution of a Lieb-Liniger model augmented with long-range dipole-dipole interaction (DDI). This near-integrable system is realized with bosonic dysprosium quantum gases confined in quasi-one-dimensional (1D) waveguides. The contact interaction can be tuned via confinement-induced resonances, while the long-range DDI is controlled by dipole alignment fixed by the orientation of an external magnetic field. The rapidity distribution of dipolar 1D gases is revealed with a modified time-of-flight sequence, in which the system undergoes the evolution of 1D integrable dynamics, mapping rapidities onto measurable momenta. Our measurement near the hard-core boson limit shows a great agreement with the finite-temperature Lieb-Liniger theory. DDI has more significant effects with intermediate contact interaction strength, while the measurement is still in qualitative agreements with an Lieb-Liniger model that includes the short-range part of the DDI in the contact interaction strength. This result suggests the possibility of describing dipolar 1D gases with the Lieb-Liniger model
Mechanical force sensing drives extrusion of Enterovirus-A71-infected cells from colonic epithelial organoids
Keywords: Microbiology and Immunology.

Enterovirus A71 (EV-A71) can cause severe disease upon systemic infection, sometimes leading to severe neurological dysfunction. However, in most cases infection is limited to the gastrointestinal tract, where virus is amplified for transmission. In this work described in this thesis, we sought to utilize three-dimensional epithelial organoids generated from crypt stem cells of healthy patient colon tissue (colonoids) to investigate viral spread through the gastrointestinal epithelium, the tissue most relevant for viral transmission. Chapter 1 introduces the reader to the viral and tissue model systems relevant for this work. In Chapter 2, the generation and characterization of an apical-out, differentiated colonoid model for EV-A71 infection is described. Chapter 3 details the surprising phenomenon of whole-cell extrusion of virus-infected cells from intact colonoids, including the timing and frequencies of these events. Poliovirus-infected cells were also readily observed extruding from gastrointestinal organoids, suggesting this phenomenon occurs during infection with multiple Enterovirus species. Chapter 4 explores the mechanism for extrusion of EV-A71-infected cells and the identification of mechanical force-sensing ion channels as required for the removal of infected cells from organoids. Finally, in Chapter 5 we explore the potential benefits of extruding a virus-infected cell for both the virus and the host. We find the extruded cells themselves are infectious, capable of initiating new infections in both monolayers and colonoid cultures. These results suggest a novel mechanism for extrusion of live, virus-infected cells through mechanical cell compression forces. In the gastrointestinal tract, apically extruded cells are released into the lumen of the gut and eventually excreted in feces; therefore, extruded infected cells likely contribute to virus spread both throughout an infected host and between hosts
Mechanics of epithelial cell division
Keywords: Mechanical Engineering.

Epithelial cells undergo striking morphological changes during division to ensure proper segregation of genetic and cytoplasmic materials. These morphological changes occur despite dividing cells being mechanically restricted by neighboring cells, indicating the need for extracellular force generation. Beyond driving cell division itself, forces associated with division have been implicated in tissue-scale processes, including development, tissue growth, migration, and epidermal stratification. In this dissertation, I focus on understanding how dividing cells generate forces to drive the morphological changes necessary for cell division, in epithelial tissues and single-cell contexts. While forces generated by mitotic rounding are well understood, forces generated after rounding remain unknown. I identify two distinct stages of division force generation that follow rounding: (1) Protrusive forces along the division axis that drive division elongation, and (2) outward forces that facilitate postdivision spreading. Cytokinetic ring contraction of the dividing cell, but not activity of neighboring cells, generates extracellular forces that propel division elongation and contribute to chromosome segregation. Forces from division elongation are observed in epithelia across many model organisms. In the second part of my dissertation, I discuss improvements made to a custom-built atomic force microscope with side- and bottom-view imaging paths. I use this instrument to measure the mechanical properties of dividing cells. In summary, we find that cells generate extracellular forces to drive cell division, and this represents a universal mechanism in confining environments
A mechanism design perspective on firms and market power
Keywords: Economics.

Each chapter of this PhD dissertation develops new mechanism design techniques to study the following three economic problems relating to firms with market power: (i) optimal pricing and product design (Loertscher and Muir, 2021), (ii) optimal wage-setting and employment decisions (Loertscher and Muir, 2022), and (iii) optimal contracting by an input supplier and the decision of whether or not to offer a competing downstream product (Kang and Muir, 2022). The first chapter (Loertscher and Muir, 2021) considers the welfare implications of underpricing and rationing by a monopoly seller. These practices are considered something of a puzzle among economists. They are frequently observed in markets for perishable goods and often give rise to resale markets. This chapter develops a coherent model of these phenomena and deepens our understanding of the likely impact of policies such as the BOTS (Better Online Ticket Sales) Act, which reduces the efficiency of resale markets without banning them entirely. The second chapter of this dissertation (Loertscher and Muir, 2022) studies the implications of minimum wage policies when employers have market power. While the textbook model of a perfectly competitive market suggests that introducing a minimum wage can only reduce employment, it is well-known that imposing a minimum wage on a monopsony employer can increase employment. This chapter seeks to provide regulators with clearer guidance by showing how measures such as wage dispersion, efficiency wages and involuntary unemployment can be used to predict the implications of an increase in the minimum wage for employment. The third chapter (Kang and Muir, 2022) of this dissertation focuses on the antitrust implications of platforms that use their own marketplaces to sell in-house products. A natural example of such a platform is Amazon, which sells e-commerce and distribution services upstream, as well as its own private-label products downstream. In this chapter we adopt a mechanism design approach to characterize the optimal menu of contracts that dominant platform offer in upstream markets. Our main result then shows that consumers always benefit from the platform's decision to offer a competing product downstream. Consequently, antitrust laws prohibiting platforms from selling their own private-label products, such as those recently implemented in India, can harm consumers
Mechanisms of mutant huntingtin quality control and the impact on cellular proteostasis in Huntington's disease
Keywords: Biology.

Huntington's Disease is a neurodegenerative disorder characterized by a genetic mutation that expands a CAG trinucleotide repeat in exon 1 of the huntingtin gene resulting in a lengthened polyglutamine stretch. Importantly, the genetic neurodegenerative disorder Huntington's Disease shares key characteristics with other neurodegenerative diseases, including misfolded protein pathology and aberrant endolysosomal pathway function. While Huntington's Disease genetics pinpoints the underlying cause of disease, mechanisms of neurodegeneration and disease biology remain unclear. Many studies have highlighted a loss-of-function or gain-of-function caused by the mutant huntingtin protein, which has diverse cellular roles. However, rarely are both loss-of-function and gain-of-function aspects considered together. In this work, we aim to investigate altered huntingtin functions by comparing the in-cell protein-protein interactions of an exon 1 mutant huntingtin to exon 1 of the wild-type protein. We discover a gene set involved in the endolysosomal pathway that is highly specific to mutant huntingtin. We map endosomal interaction back to full-length huntingtin function, and show wild-type huntingtin and mutant huntingtin have fundamentally different interactions with endosomal membranes. These interactions highlight a novel VPS4 mediated protein quality control pathway we propose for regulating mutant huntingtin. Importantly, mutant huntingtin's altered endosomal interaction can be described by both a loss-of-wild-type-function and gain-of-mutant-function, which we correlate with widespread defects in endolysosomal pathway function. Ultimately, we propose a link between endolysosomal defects and the Huntington's Disease mutation, which provide mechanistic insight to disease relevant biology and inform potential therapeutic avenues
Mechanisms of neural communication predicted from computational modeling of healthy and pathological brain circuits
Keywords: Bioengineering.

The topics of memory processing and epilepsy are investigated through computational modeling with the overarching goal of predicting novel mechanisms that can be experimentally verified via a number of genetic, electrophysiological, and imaging methods. Specifically, we leveraged biophysically detailed and more abstract machine-learning inspired modeling approaches through the development of 1) a microcircuit model of hippocampal CA3 and 2) a novel computational pipeline that can infer and mine the higher-order organization of large-scale epileptic circuits built from single cells. Simulations from these computational models predicted a critical role for inhibitory plasticity to perform 'world inference learning' by filtering out irrelevant stimuli during circuit processes associated with spatial navigation, and predicted a novel functional cell type - the superhub cell - that preferentially emerges in the preseizure brain and can propagate excitatory activity downstream with high fidelity. Critically, as patients with epilepsy often exhibit cognitive comorbidities including memory dysfunction, deeper understanding of these topics has potential to drive more holistic strategies for intervention that include both seizure reduction and normalization of computational processes associated with memory
Mechanistic & spectroscopic studies on O2-activation and reactivity by coupled binuclear copper enzymes
Keywords: Chemistry.

Coupled binuclear copper (CBC) enzymes constitute a major family of O2-activating metalloenzymes that catalyze a wide range of oxidation and oxygenation reactions. The most predominant member of this enzyme family, tyrosinase (Ty) in its dicopper(I) reduced form (deoxy-Ty) binds O2 to form a μ-η2:η2-peroxide dicopper(II) intermediate (oxy-Ty) that can monooxygenate para-substituted monophenols to catechols, which in its native function constitutes the initial step in melanin biosynthesis in a wide range of organisms, from soil bacteria to humans. The mechanism of this important monooxygenation reaction has not been fully understood, with its key reaction intermediates remaining elusive. This thesis presents advancements in defining the monophenol monooxygenation mechanism of Ty by (i) trapping and spectroscopically characterizing key reaction intermediates, (ii) investigating their reactivity by kinetic methods, and (iii) correlating experimental results to quantum-mechanics/molecular-mechanics (QM/MM) calculations. Analysis of our experimental and computational results provides a molecular-level definition of the reaction coordinate for the monophenol monooxygenation reaction of Ty. This mechanism is different from the general paradigm based on previous model complex studies and provides new insights into how Nature employs Cu2O2 active sites to perform enzymatic catalysis
Mediatizing terrorism : a study of audiences' construction of violent events under datafied capitalism
Keywords: Communication.

This dissertation studies the circulation of transnational mobile media accounts of terror attacks in order to examine the intersection of violence, liberalism, anti-Muslim racism, and authoritarianism as it is transformed in the data-driven political economy of communication. The dissertation's central question asks: how is mediatized terrorism encountered, made sense of, and responded to by mobile audiences in datafied media? To answer, I use a new method for digital observation that collects screenshots from participants' mobile devices every five seconds for longitudinal studies. Through observation of U.S. mobile media users' reception of a wave of Daesh-linked terror attacks in Europe and North Africa in the spring of 2017, I identify four mediatized rituals responding to these attacks. One ritual, specific to far-right ecosystems, assimilates attacks and unrelated social conflict into an imagined future of what liberal pluralism portends, creating the possibility for offline action stoking cycles of violence. The other observed responses constitute a limited suite of individualized responses that are habituated by the data-driven political economy of mobile media. These findings contrast with prominent critiques of social media (e.g., polarization) by highlighting the distinct threat posed by ritual action in far-right mobile media. This analysis also adds nuance to disinformation frameworks that abstract users' construction of reality from their mediatized social contexts and cultural practices. The conclusion proposes developing a decolonial global media technology ethics based on these findings that mobilizes media against persistent orientalism and far-right authoritarianism in the global political landscape emerging under datafication
Memory Politics in Independent Kazakhstan: The Great Famine and National Identity
Keywords: Kazakhstan
Famines
Memory
Memory > Political aspects
Nazarbaev, Nursultan
Tokaev, K. K. (Kasymzhomart Kemelevich)
Central Asia
Kazakh-Russian relations
Text
Thesis

Stalin’s collectivization policies created a famine that killed around 1.5 million people in Soviet Kazakhstan from 1932 to 1933. However, the Kazakhstani state remains reluctant to incorporate the famine into official historical narratives and marginalizes public discourse about this period of history. This paper analyzes the evolution of official rhetoric about the 1932-33 famine from 1991 to today as a lens through which to understand elite-level political concerns behind national identity building in Kazakhstan. I find that an instrumental relationship to history and political expediency governs debates about the famine in Kazakhstan, including the desire to create a civic “Kazakhstani” national identity and concerns about Russia’s stake in Kazakhstan’s memory politics.