VictorJuiz/thesis huggingface dataset:
Islamic identity and politics in Muslim-minority contexts
Keywords: Political Science.

Islamic identity has undergone profound changes over the twentieth century with the emergence of fundamentalist Islam. The rise of conservative Islam worldwide has generated unique challenges for different regions. Across three papers, this dissertation examines this change in Islamic identity and its implications for politics in the Muslim-minority contexts of sub-Saharan Africa and Europe. My work on sub-Saharan Africa examines the origins of Islamic conservatism on the continent while the work on Europe explores the institutional and societal responses to changing Islamic identity. In the first paper, "Arab Missionary Roots of Africa's Islamic Fundamentalism", I explore the emergence of Islamic fundamentalism in sub-Saharan Africa. I leverage cross-national and subnational evidence to link the rise of fundamentalism in Africa to repatriated graduates from Islamic universities in Egypt and Saudi Arabia. The second and third paper explore Islamic identity and politics in Europe. In the second paper, "Perceived Discrimination and Adolescent Muslim Integration", my co-author Vasiliki Fouka and I examine the impact of social stigmatization of Muslims in the UK, Germany, and Sweden. We use high frequency hate crime data alongside a longitudinal survey of immigrant adolescents to show that in months with greater anti-Muslim violence, Muslim adolescents report greater association with the majority identity, lower religiosity, and increased pro-integration attitudes. The final paper, "Political Secularism and Muslim Integration in the West", co-authored with Vasiliki Fouka, examines institutional efforts to curb Muslims' religious behavior. We study the landmark French law banning headscarves in schools. We find that the law reduced Muslim women's educational attainment with negative downstream effects on employment as well as intensified their identification with French and religious communities
Isogeny graphs, zero-cycles, and modular forms : computations over algebraic curves and surfaces
Keywords: Mathematics.

In the study of algebraic varieties over number fields or finite fields, there are many properties of these varieties that can be difficult to compute. This thesis discusses variants of the following three computational problems: (a) to compute an isogeny between two given supersingular elliptic curves; (b) to determine whether a zero-cycle on a product of elliptic curves is rationally equivalent to zero, and if so, to compute a rational equivalence; (c) to compute the space of cuspidal modular forms over a function field of genus greater than one. For each of these problems, we present algorithms that allow the problem to be solved in certain special cases, and prove results about these cases
Japan’s Economic Partnership Agreement Healthcare Worker Programs as a Tool for “Soft Diplomacy”
Keywords:  Stanford Global Studies
EPA
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Thesis

Japan is facing rapid depopulation and population ageing. With a shrinking domestic workforce and a growing share of elderly population in the country, Japan is expecting a huge shortage of manpower, especially in the expanding care sector. Prior to 2008, the Japanese healthcare labor market has been closed to immigrant workers. However, beginning in 2008, Japan started to accept Southeast Asian nurses and care workers under Economic Partnership Agreements (EPA) with three countries: Vietnam, Philippines, and Indonesia. Logically, one may suppose that this is a gesture of Japan opening its care market to foreign professionals. The scale of the acceptance of Southeast Asian nurses and care workers under EPA -- only a few hundred people per year -- is too small to have any measurable impact on the labor shortage of care workers” The minuscule scale of the EPA program has not expanded over a decade, and the fact that most foreign healthcare workers return to their home countries after participating in the program means that the EPA program is clearly not intended as a solution to the labor shortage. Moreover, although the program was implemented as an “Economic Partnership Agreement,” and despite the Japanese government insisting that acceptance of foreign nurses and care workers under EPA is designed to promote international economic cooperation, the program per se does not deliver substantial economic gains to any party involved. The thesis therefore attempts to answer the question: “why does Japan continue to accept Southeast Asian nurses and care workers under EPA?” Inspired by the patterns of Japan’s soft power foreign diplomacy in the latter half of the 20th century, the thesis finds a potential explanation for the continuation of the program: soft diplomacy, i.e. activities that help foster positive feelings among foreign citizens towards the country (Japan).
Kant and Rawls on the moral and political development of persons
Keywords: Philosophy.

My dissertation examines Kant's and Rawls's theories of the moral development of individuals within structured political communities. I reconstruct Kant's under-studied account of the emergence of reason I show how this account fits with his broader view of humankind's rational progress and the moral development of an individual. Next, I argue that Kant's anthropological and pedagogical writings influenced Rawls's early views on moral development explicated in his A Theory of Justice. In contrast to other commentators who have located Kant's influence on Rawls in his emphasis on the free and equal nature of human beings, my dissertation shows that Kant's anthropological theory of moral development is also at the core of Rawls's Kantian project. I also argue that the moral-psychological account Rawls develops in Part III of Theory sheds light on crucial aspects of Kant's practical philosophy, notably on Kant's emphasis on the need for one generation to provide the moral education of subsequent generations in order for stable moral development of humanity
K-Healthcare?: Medical Tourism and the Hallyu-ification of Korea’s National Healthcare System
Keywords:  Stanford Global Studies
Medical tourism
Nation-Branding
Korea (South)
Hallyu
Stanford Global Studies
East Asian Studies
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Thesis

The term “Hallyu” has collectively been defined as Korean popular culture. It is widely seen as a phenomenon with studies assessing the impact of South Korean culture on politics, international relations, and global media consumption. However, the continued efforts of the Korean government to utilize the “wave” in other economic industries outside cultural exports suggest that Hallyu is less a local product and has become a political and economic framework in which to expand South Korea’s “middle power” profile. The objective of this thesis is to provide grounds for studying medical tourism through geopolitical lenses as 1) country perception is a significant factor in choosing a medical destination and 2) the explicit aspirations of the Korean government to utilize the industry to build diplomatic relations, as seen in the successes of Hallyu, demand whether the medical tourism industry is a worthwhile investment.
Kinetic insights into the mechanism of influenza A virus membrane fusion
Keywords: Chemistry.

Host lipid composition influences many stages of the influenza A virus (IAV) entry process, including: initial binding of IAV to sialylated glycans, fusion between the viral envelope and the host membrane, and the formation of a fusion pore through which the viral genome is transferred into a target cell. In particular, target membrane cholesterol has been shown to preferentially associate with virus receptors and alter physical properties of the membrane like fluidity and curvature. These properties affect both IAV binding and fusion, which makes it difficult to isolate the role of cholesterol in IAV fusion from receptor binding effects. Here, I develop a new fusion assay that uses synthetic DNA-lipid conjugates as surrogate viral receptors to tether virions to target vesicles. To avoid the possibly perturbative effect of adding self-quenched concentrations of dye-labeled lipids or dye to the viral membrane and viral contents, I tether virions to lipid- or content-labeled target vesicles, and use fluorescence microscopy to detect individual, pH-triggered IAV membrane fusion events. Through this approach, I find that cholesterol in the target membrane enhances the efficiency of IAV lipid and content mixing, while the rate of both processes is independent of cholesterol composition. I also find that the single virus kinetics of IAV lipid mixing to target membranes with different cholesterol compositions is independent of receptor binding, suggesting that cholesterol-mediated spatial clustering of viral receptors within the target membrane does not significantly affect IAV hemifusion. Finally, I show that cholesterol decreases the fraction of content mixing events that result in content loss, which provides direct experimental evidence to support the hypothesis that the negative spontaneous curvature of cholesterol stabilizes pore formation in IAV entry and limits leakage following pore formation. This approach is a promising strategy for studying the single-virus lipid and content mixing kinetics of other enveloped viruses
Lagrangian cobordisms between enriched knot diagrams
Keywords: Mathematics.

In this dissertation, we present certain obstructions to the existence of Lagrangian cobordisms in $\R^4$ which depend only on the data of enriched diagrams of the boundaries. The goal is to explore the applications of holomorphic curve techniques to undercutting relations between enriched diagrams, which are dictated by the existence of Lagrangian cobordisms. We provide example applications such as the growing and shrinking of boundary knots of Lagrangians depending on the signs of crossings
Laplacian regularized stratified model fitting
Keywords: Electrical Engineering.

A large number of practical problems in optimization involve the fitting of models with categorical features. These problems arise in a variety of fields, such as machine learning, statistics, finance, medicine, and data analysis. A common and simple paradigm parameterizes the model by a parameter vector, and uses convex optimization to minimize an empirical loss on a training data set plus a regularization term that (hopefully) skews the model parameter toward one for which the model generalizes to out of sample data. In this dissertation, we discuss a framework of model fitting methods that depend on a number of categorical features. We build a model of some data that depends in an arbitrary way on these categorical features, by building a separate model for the data that take on each of the possible values of these categorical features. We call these models stratified models. Furthermore, we propose augmenting a basic stratified model fitting problem with an additional regularization term, Laplacian regularization, which encourages the parameters found for each value to be close to their neighbors on some specified weighted graph on the categorical values. We begin this dissertation with an early work on solving Laplacian regularized problems. We then define these models as Laplacian regularized stratified models, and propose an efficient distributed solution method based on the alternating direction method of multipliers (ADMM), which allows us to solve the Laplacian regularized stratified model fitting problem in a distributed fashion and at large scale, in spite of the model parameters being coupled due to the Laplacian regularization term. We then provide an extension of Laplacian regularized stratified models, where we show that if the model parameters vary smoothly over the graph Laplacian, then it can be well approximated by a linear combination of a small number of the Laplacian eigenvectors, which can drastically reduce the number of variables in the problem. Finally, we provide two examples: one example of fitting Laplacian regularized Gaussian models, and another, much larger example which brings the ideas of this paper together by fitting Laplacian regularized stratified risk and return models to used in a realistic quantitative finance setting
Large-scale simulation for embodied perception and robot learning
Keywords: Electrical Engineering.

Being able to perceive and interact with complex human environments is an important yet challenging problem in robotics for decades. Learning active perception and sensorimotor control by interacting with the physical world is cumbersome as existing algorithms are too slow to learn in real-time, and robots are fragile and costly. This has given rise to learning in simulation, and to make progress on this problem, efficient simulation infrastructure needs to be developed to support interactive and long-horizon tasks, and sample-efficient learning algorithms need to be developed to solve these tasks. In this dissertation, I present two lines of work contributing to these topics. The first line of work is to create large-scale, realistic, and interactive simulation environments, including Gibson Environment and iGibson. Gibson Environment is proposed for learning real-world perception for active agents. Gibson Environment is built from the real world and reflects its semantic complexity. It has a neural network-based renderer and a mechanism named ``Goggle" to ensure no need to further domain adaptation before deployment of results in the real world. Gibson Environment significantly improves pixel-level realism over existing simulation environments. To build upon Gibson Environment and improve the physical realism of the simulation, I propose iGibson, a simulation environment to develop robotic solutions for interactive tasks in large-scale realistic scenes. The simulated scenes are replicas of 3D scanned real-world homes, aligning the distribution of objects and layout to those of the real world. Novel long horizon problems including interactive navigation and mobile manipulation can be defined in this environment, and I show evidence that solutions can be transferred to the real world. The second line of work studies reinforcement learning (RL) for long-horizon robotics problems enabled by the interactive simulation environments. First, I introduce the interactive navigation problem and associated metrics. I leverage model-free RL algorithms to solve the proposed interactive navigation problems. Second, to solve challenging tasks in fully interactive simulation environments and improve sample efficiency of RL, I propose ReLMoGen, a framework to integrate motion generation into RL. I propose to lift the action space from joint control signals to motion generation subgoals. By lifting the action space and leveraging sampling-based motion planners, I can efficiently use RL to solve complex long-horizon tasks that existing RL methods cannot solve in the original action space
Las Historias Explosivas: Resisting Justice in Ricardo Piglia’s La ciudad ausente
Keywords: Department of English
Ricardo Piglia
Post-dictatorship
Postdictatorial Latin American fiction
Neoliberalism
Post-dictatorship justice
Transitional justice
Critical legal studies
Storytelling
Testimony
Walter Benjamin
Paolo Freire
Cyborg theory
Wai Chee Dimock
Narrative resistance
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Thesis

Argentine post-dictatorship can be characterized by a series of legal actions to exculpate the dictatorship's accused, from the Ley de punto final of 1986 to the presidential pardons of 1990. From within this overarching narrative of reconciliation, Ricardo Piglia's La ciudad ausente tells the story of a storytelling machine, Elena, whose stories form a sort of resistance to state control—resistance, in particular, to the narrative that justice had already been served. Drawing on Wai Chee Dimock's theory of justice's residues, Walter Benjamin's theory of storytellers, and Paolo Freire's Pedagogy of the Oppressed, this thesis builds on Idelber Avelar's analysis in The Untimely Present to examine the role of storytelling within La ciudad ausente, and suggests that it may serve as a means of resistance to the narrative of achieved justice. This analysis of La ciudad ausente thus provides an example of the inadequacies of legal justice, and the importance of alternative strategies for achieving restitution and moving forward.
Lay beliefs about self-identity: the case of gender
Keywords: Psychology.

The current dissertation contains three series of studies that revealed laypeople's nuanced, meticulous, and early-emerging attentiveness to gender membership, gender self-identification, and gender roles and norms in their personal and social life. Specifically, the studies together suggest that laypeople's conceptualizations of gender seem to display a rather sophisticated structure that (1) allows for simultaneous and separate judgments about gender membership; (2) considers the distinct influences of one's internal sense of gender, gender roles ascribed by society, and the physical forms stereotypically associated with different gender groups; and (3) demonstrates remarkable variability across individuals, cultural and historical contexts, and one's own life span
Layout automation for analog and mixed-signal circuits using digital place-and-route tools
Keywords: Electrical Engineering.

Today's analog and mixed-signal (AMS) layout flow requires long manual iterations and does not leverage computing resources for data-driven optimization. This issue is further compounded by the explosion of design rules and layout-dependent effects. We present an AMS layout generation flow that leverages digital place-and-route tools, amortizes setup cost with reusable primitives, and prunes layout candidates using time-efficient layout quality surrogates. We also analyze layout-dependent effects and parasitics and investigate unique challenges and mitigation strategies associated with using digital place-and-route tools for AMS circuits. These insights are validated with a generated 4x time-interleaved successive approximation analog-to-digital converter, a StrongARM comparator, and a voltage-controlled oscillator (VCO) in 16 nm FinFET CMOS. Silicon measurement results of the VCO closely track the simulation, showing only 6% in maximal oscillation frequency degradation from its manual counterpart, verifying the methodology from netlist to silicon
Learning determinants of nucleosome positioning from sequence-based models of cell-free DNA
Keywords: Genetics.

The human genome exists in cells as chromatin, a vastly complex 3D macromolecule with multiple hierarchical scales of structural and functional organization. Nucleosomes, small, radially symmetric protein octamers ~10-20nm in diameter, are the fundamental unit of chromatin organization from which higher order chromatin structures are derived. Nucleosomes act like passive beads on a string, controlled both by their own sterics and by higher-order processes such as TF binding and chromatin remodeling. This work centers on the relationship between nucleosomes and the DNA sequences they bind, measured using the mapping coordinates of (largely nucleosome bound) fragments of DNA isolate from blood plasma. In the first half, we develop a model called cfDNA-DeepNuc, which is a fully dense convolutional neural network trained to predict nucleosome occupancy from DNA sequence. We use the model as a basis to study the sequence determinants of nucleosomes positioning, identifying patterns that both coincide with and that extend beyond existing knowledge of nucleosome sequence determinants. In the second half, we present an approach to measuring chromatin state (i.e., enhancer accessibility) from cell-free DNA fragmentation patterns, and demonstrate proof of principle for providing estimates of tissue signal strength in a series of in silico titration and subsampling experiments. Our work is intended to highlight cell-free DNA fragmentation patterns as a functional genomic signal providing insight on genome structure and function, and to highlight the promise of using functional genomic annotation priors for the analysis of cell-free DNA in liquid biopsies
Learning, fast and slow : computation, plasticity and metaplasticity in a neural circuit
Keywords: Bioengineering.

Memory—--the ability to transform transient information into a more persistent form---is a fundamental property of neural systems, allowing them to learn from experience. Memories are stored in a variety of substrates, from persistent neural activity to changes in synaptic weights. Experience may even alter the interactions of the molecular networks that support synaptic weight changes themselves. The processes by which memories are stored, maintained and transformed are dynamical, resulting from the interplay of the substrate elements across spatial and temporal scales, fast and slow. Here I use mathematical and computational methods to investigate the dynamics of the storage of a long-term memory during synaptic plasticity, the transfer of long-term memory between synaptic sites during systems consolidation, and the tuning of the rules for inducing synaptic plasticity as a result of metaplasticity. I perform a conceptual unification of short-term and long-term memory, which have long been considered unrelated phenomena, by demonstrating that the consolidation of graded long-term memories in persistent synaptic weight changes is conceptually analogous to the storage of graded memories in persistent neural activity in short-term (working) memory, both processes being described by line attractor dynamics and the operation of temporal integration. Finally, I propose biologically plausible mechanisms for a newly discovered form of metaplasticity that each generate associative synaptic plasticity rules tuned to different features of the correlation structure of inputs to a neuron