VictorJuiz/thesis huggingface dataset:
Intercultural (Dis)Connections in the South Korean Rock Scene

This dissertation examines intercultural interactions between South Korean (hereafter Korean) musicians and foreign musicians in the underground rock scene in Seoul. It is based on ethnographic fieldwork conducted from 2016-2017, supported by the US Fulbright Junior Scholars program. This fieldwork included attending multiple concerts each week, as well as interviews, and analysis of media and promotional materials. In studying the intercultural interactions of local foreign musicians (mostly white, male, English teachers) and Korean musicians, I argue that a variety of markers, including place, genre, and nationality, are important parts of how individual musicians understand their connections and/or disconnections with other musicians. Foreign musicians in Korea employ a variety of ideologies and techniques to attempt to bridge perceived gaps between musicians./nThe first chapter lays the groundwork understandings of the context of underground rock and the term “foreigner” in the Korean context. I also explain how understanding intercultural interaction through the similarities and differences in what Roger Schank and Robert Abelson call “situational scripts” helps to illuminate why certain groups of musicians work well together, while others do not. The second chapter focuses on understandings of place in relation to Korean rock music, discussing the way that the US military presence influenced the formation of Itaewon and Haebangchon as “alien spaces” (Eun-Shil Kim) within Seoul. I also detail the origin of the punk scene in the 1990s in Hongdae, and the subsequent gentrification that has pushed music venues out of the neighborhood. The third chapter looks at punk musicians specifically, detailing how the performance scripts of punk music help to create unity within the scene, although admitting there are still points of conflict around behavior. The fourth chapter looks at a network cluster of musicians who do not find unity in their genre, and details the way that different understandings about the scripts of performance cause conflict and disconnection. The fluidity of this performance network means that the groups never situate themselves fully in one script or another, and a balance is harder to achieve. The fifth chapter looks at the situations in which connections are created: the after-party. Again, similarities and differences in the understandings of social scripts play a role in how musicians gain opportunities in the scene. Finally, the sixth chapter analyzes two foreigner-run initiatives meant to expand the reach and influence of the underground rock scene in Korea. These each display a different ideology of how foreigners should act. Throughout these chapters, I work to understand how musicians connect across intercultural interactions, and the ways they stay disconnected.

Advisor: Wade, Bonnie
Pushing the Helium Envelope: Signatures of Normal and Unusual Supernovae from Sub-Chandrasekhar Mass White Dwarf Explosions

Type Ia supernovae (SNe) are among the most common astrophysical transients, yet their progenitors are still unknown. Throughout this thesis we examine a specific pathway to these explosions – the double detonation explosion mechanism. In this scenario a white dwarf (WD) is able to explode below the Chandrasekhar mass limit through the aid of an accreted helium shell. An ignition of this helium can send a shock wave into the center of the WD which, upon convergence, can ignite the core causing a thermonuclear runaway resulting in a Type Ia-like explosion./nPrior to this work, the double detonation scenario was not favored as a mechanism for Type Ia SNe, as there was no strong observational evidence supporting it. The first part of this thesis is a calculation of observational predictions of double detonation explosions. We perform hydrodynamical simulations and radiative transport calculations in order to produce testable predictions for observers. In doing so we identify a population of SNe Type Ia that likely arise from the double detonation progenitor channel recognized by the relationship between their Si II velocity and peak luminosity, and characteristic early color evolution./nWhile the double detonation scenario has mainly been employed to model signatures of SNe Type Ia, requiring WD masses greater than ∼0.9 M⊙ and helium shell masses less than ∼0.01 M⊙, there exists a wide parameter space beyond these limits which allows for more peculiar transients. We examine these regions and relate low mass double detonations to Ca-rich transients by their properties in the nebular phase. We also determine the peculiar signatures of double detonations triggered by thick helium shells. In doing so this work accurately predicts the observable properties associated with these events, which were later seen in SN 2018byg, establishing the most direct evidence to date that there are multiple mechanisms through which WDs explode.

Advisor: Nugent, Peter
Kasen, Daniel
Structured Models for Vision-and-Language Reasoning

Vision-and-language tasks (such as answering a question about an image, grounding a referring expression, or following a natural language instruction to navigate through a visual environment) require jointly modeling and reasoning over the two modalities of image and text. We have witnessed significant progress in joint visual and linguistic reasoning, often through neural approaches trained with the help of larger datasets and more computation resources. However, is solving these vision-and-language tasks as simple as building models with more parameters and training them on more data? If not, how can we build better reasoning models that are data-efficient and generalize well?/nThis thesis provides an answer to the above question with structured models for vision-and-language reasoning – models with architectures that take into account the patterns and regularities in human language, visual scenes, and agents’ skills. We begin with the task of referring expression grounding, where we show that significantly better accuracy and generalization can be achieved by taking into account the compositional structures in these expressions with our proposed Compositional Modular Networks (CMNs) in Chapter 2. We further address the visual question answering task in Chapter 3 with the End-to-End Module Networks (N2NMNs) based on dynamic compositional modules that align with the reasoning steps in the questions. In Chapter 4, we extend our work on modular reasoning and propose the Stack Neural Module Networks (SNMNs) that automatically induce a proper module layout with interpretable reasoning steps. Beyond modular reasoning, we also propose to construct context-aware representations of the visual scene with Language-Conditioned Graph Networks (LCGNs) in Chapter 5 for relational reasoning, and address the problem of reading text in images for question answering with iterative pointer-augmented multimodal transformers in Chapter 6. Finally, we show that embodied tasks also require structured models, and propose the Speaker-Follower models for the navigational instruction following task in Chapter 7 with the pair of a speaker model and a follower model that complement each other. In all these scenarios, we show that by taking into account the structures in the tasks and the input modalities, our models perform and generalize significantly better than their unstructured counterparts.

Advisor: Darrell, Trevor
Do Managers Exploit Private Information about Their Firm’s Investor Base?

I investigate whether managers obtain and exploit private information about who is buying and selling their firm’s securities. To do so, I examine insider trading prior to activist investors’ disclosure of Schedule 13Ds. Schedule 13Ds are required when investors have acquired more than 5% of a firm’s shares, and they cause a significant price jump of approximately 6% upon disclosure. I find that insider purchases (sales) are abnormally high (low) in the days prior to the disclosure of Schedule 13Ds. Cross-sectionally, pre-disclosure insider purchases are higher when activist investors make larger trades, since they are more likely to be detected by insiders. Furthermore, the stock market fails to recognize that insiders trade ahead of the Schedule13D filings, reflected by the fact that pre-disclosure insider trading does not facilitate price discovery in the underlying firms. Finally, I show that pre-disclosure insider trading is predictive of the firm’s future stock and operating performance, consistent with managers exploiting private information when they expect it to generate greater profits. Taken together, my results show that managers obtain private information concerning their firm’s investor base and exploit it for personal gain.

Advisor: Even-Tov, Omri
Computational Approaches to Big Data and Deep Time in Ecology, Hydrology, and Geomorphology

Some of the most challenging problems in ecology, hydrology, and geomorphology arise from processes which play out over large spatial scales and long time intervals. High-resolution global digital elevation models are becoming available. They will allow problems of broad spatial extent to be addressed, but only if we can handle the enormous volume of data. Similarly, performance gains in computers now make it feasible to test more complex theory using computational models, but only if efficient techniques are used. In this dissertation I develop and demonstrate techniques for handling large geospatial raster datasets and rapidly modeling ecological and hydrological processes, producing results that are orders of magnitude more efficient than previous work. Notably, these techniques work on both high-performance machines and laptops. Finally, I apply the techniques to a challenging problem at the interface of ecology, evolution, climate, and geology.

Advisor: Harte, John
A syndemic exploration of sexual compulsivity among methamphetamine-using sexual minority men living with HIV

Sexual minority men (SMM) have historically been exposed to stressors that translate into poor social and health outcomes. Methamphetamine use is an outcome representing a powerful health disparity for SMM. Sexual compulsivity (SC) has been centered in SMM’s health research; however, its role in SMM’s methamphetamine use remains underdeveloped. Guided by syndemics theory, intersectionality, and revised stress and coping theory, the purpose of this mixed methods study is to contextualize the role of SC in the methamphetamine-using behaviors of SMM living with HIV. Data were collected from 2014-2019 through an RCT testing a positive affect intervention in San Francisco. Cross-sectional survey data (N= 129) were used for quantitative analyses and participants (n = 24) were purposively sampled to take part in semi-structured interviews for qualitative analyses. Narrative analysis revealed that most participants experienced adverse events as youths, specifically related to sexuality. Additionally, they reported that sex was related to methamphetamine initiation and subsequent use, and that methamphetamine was disruptive to relationships. Narrative analyses surfaced a sequential pattern of disconnection at foundational, relational, and recovery levels, revealing themes of negative affect, isolation, SC, depression, trauma, and other mental health issues across the life-course. Network analysis suggests two specific significant positive associations: between depression and negative affect and between PTSD and depression. Constructivist grounded theory analysis highlighted six themes regarding participants’ relationships with/on methamphetamine. Findings highlight the influence of life-long experiences of syndemically related psychosocial factors in the methamphetamine-using behaviors of SMM. Findings suggest peer-based interventions focus on holistic, integrated approaches to tend to SMM’s histories of adverse events and mental health issues, which diminish relational capabilities. SC should be understood as a potentially maladaptive coping strategy developed by SMM as a response to stigmatization and discrimination. Taken together, these findings can help inform cutting-edge methamphetamine use and mental health interventions for SMM.

Advisor: Organista, Kurt C
Paesaggi Corporei

Abstract/nPaesaggi Corporei/nby/nAntonio Juan Marcos Cavazos/nDoctor of Philosophy in Music/nUniversity of California, Berkeley/nProfessor Franck Bedrossian, Chair/nIn Paesaggi Corporei, I set to music four sonnets attributed to composer Antonio Vivaldi (1678-1741). These are the same sonnets which Vivaldi used as the basis for his series of violin concertos entitled The Four Seasons (1725). This song cycle was written for the French ensemble Les Folies Françoises, with the intention of performing each song as a prelude to each of The Four Seasons. The result is a concert program which mixes baroque and contemporary music, and is thematically unified by the sonnets. I composed the song cycle Paesaggi Corporei (Body Landscapes), with the same instrumentation used by Les Folies Françoises to play The Four Seasons: three first violins, three second violins, two violas, two cellos, one double bass, and continuo (Italian harpsichord and archlute). Additionally, all of these instruments are period instruments. In the pieces, the soprano sings and sometimes recites the sonnets./nThe string orchestra often has the function of articulating polyphonic textures that serve as a sonic metaphor to the notions of foliage and nature. The two violas often create the impression of movement in the middle register of the orchestra. Inspired by Vivaldi's masterpieces, I sometimes explored the possibilities of several violins playing as soloists. I highlight the archlute in a section of music for plucked strings which contributes to the timbral richness of the composition. The use of metal and wood mutes on the strings, as well as the use of prepared harpsichord also create timbral richness./nAs to the relationship between text and music, the intention of Paesaggi Corporei was to differentiate each season by setting each sonnet in a different way: sections that explore the phonemes of key words, sections where the text is read, or sections with an intimate and lyrical singing of text. Using the technique of “word painting,” I created sound images of certain words by manipulating their phonetic and rhythmic characteristics.

Advisor: Bedrossian, Franck
Scene Representations for View Synthesis with Deep Learning

In this dissertation, we investigate the question of how 3D scenes should be represented, such that the representation can be effectively estimated from standard photographs and can then be used to synthesize images of the same scene from novel unobserved viewpoints. Recovering photorealistic scene representations from images has been a longstanding goal of computer vision and graphics, and has typically been addressed using representations from standard computer graphics pipelines, such as triangle meshes, which are not particularly amenable to end-to-end optimization for maximizing the fidelity of rendered images. Instead, we advocate for the use of scene representations that are specifically well-suited to being used in differentiable deep learning pipelines. We explore the efficacy of various representations for view synthesis tasks including synthesizing local views around a single input image, extrapolating views around a pair of nearby input images, and interpolating novel views from a set of unstructured images. We present scene representations that succeed at the aforementioned tasks, which share two common properties: they represent scenes as volumes and that they avoid the poor scaling properties of regularly-sampled voxel grids by using compressed or parameter-efficient volume representations.

Advisor: Ng, Ren
Ramamoorthi, Ravi
Knowledge Systems for Material Sustainability

Making systems of production sustainable will require deep technological and societal change. This dissertation explores several facets of the relationships between scientific knowledge, society, and “green design”—a set of approaches for eliminating harmful chemical substances from material technologies. This is an interdisciplinary investigation based in science and technology studies (STS), drawing from scholarship in the sociology of knowledge and resource management, information studies, and design studies./nAn overarching challenge in green design is effectively cultivating and mobilizing scientific knowledge to enable technical change. This dissertation asks what systems could produce, test, verify, and organize scientific knowledge in ways that better meet the needs of a growing community of green design practitioners, advocates, and decision-makers. Scientific communities are increasingly turning to systems of shared and collectively governed knowledge resources—or knowledge commons. Using in-depth case studies I explore emerging knowledge commons in the domain of chemicals and environmental health. I investigate how a commons can be formed and sustained in this complex and politically contested arena; and whether (or how) such a commons can function as a stable site for producing “socially robust knowledge”—knowledge that has been tested and accepted as valid by a wide range of stakeholders./nAt the same time, the politics of green design are structured by dominant systems of knowledge and technological development, in which civil society is largely oblivious to the risks of material design choices and unable to actively participate in shaping alternatives. With a case study of the building sector, I examine how mobilizing science to inform green design necessarily involves making political and value-laden choices, even though these are rarely debated as such. Extending my analysis to the case of nanotechnology, I argue that green design should become more participatory—providing pathways for society to consciously shape material technologies for sustainability.

Advisor: Iles, Alastair
Finding Critical and Gradient-Flat Points of Deep Neural Network Loss Functions

Despite the fact that the loss functions of deep neural networks are highly non-convex,/ngradient-based optimization algorithms converge to approximately the same performance/nfrom many random initial points. This makes neural networks easy to train, which, combined with their high representational capacity and implicit and explicit regularization/nstrategies, leads to machine-learned algorithms of high quality with reasonable computational cost in a wide variety of domains./nOne thread of work has focused on explaining this phenomenon by numerically characterizing the local curvature at critical points of the loss function, where gradients are zero./nSuch studies have reported that the loss functions used to train neural networks have no/nlocal minima that are much worse than global minima, backed up by arguments from/nrandom matrix theory. More recent theoretical work, however, has suggested that bad/nlocal minima do exist./nIn this dissertation, we show that one cause of this gap is that the methods used to/nnumerically find critical points of neural network losses suffer, ironically, from a bad local/nminimum problem of their own. This problem is caused by gradient-flat points, where/nthe gradient vector is in the kernel of the Hessian matrix of second partial derivatives./nAt these points, the loss function becomes, to second order, linear in the direction of the/ngradient, which violates the assumptions necessary to guarantee convergence for secondorder critical point-finding methods. We present evidence that approximately gradient-flat/npoints are a common feature of several prototypical neural network loss functions.

Advisor: Bouchard, Kristofer E
DeWeese, Michael R
Local Operators and Quantum Chaos

A hypothesis is presented for the universal properties of operators evolving under Hamiltonian dynamics in many-body systems. The hypothesis states that successive Lanczos coefficients in the continued fraction expansion of the Green's functions grow linearly with rate $\alpha$ in generic systems, with an extra logarithmic correction in 1d. The rate $\alpha$ --- an experimental observable --- governs the exponential growth of operator complexity in a sense that is made precise. This exponential growth prevails beyond semiclassical or large-$N$ limits. Moreover, $\alpha$ upper bounds a large class of operator complexity measures, including the out-of-time-order correlator. As a result, a sharp bound is obtained on Lyapunov exponents $\lambda_L \leq 2 \alpha$, which complements and improves the known universal low-temperature bound $\lambda_L \leq 2 \pi T$. Our results are illustrated in paradigmatic examples such as non-integrable spin chains, the Sachdev-Ye-Kitaev model, and classical models. Finally hypothesis is used in in conjunction with the recursion method to develop a technique for computing diffusion constants.

Advisor: Moore, Joel
Interacting Ultracold Bosonic Atoms in Geometrically Frustrated Lattices

Geometric frustration is a phenomenon where local energy constraints cannot be simultaneously satisfied because of geometric reasons. This leads to a manifold of degenerate ground states in which ordering can be highly nontrivial and exotic phases of matter could emerge. In a kagome lattice, both interaction energies of spins and kinetic energies of particles can be frustrated. In the latter case, a single-particle band structure with a flat (dispersionless) energy band results./nIn this dissertation, we report our experimental studies of interacting bosonic systems in kagome lattices. Such studies are performed with a quantum simulator based on ultracold atoms in optical lattices. We describe upgrades and development of the apparatus that constructs optical kagome lattices in our experiment. We briefly discuss results of an experiment studying the Bose-Hubbard model in a trimerized kagome lattice. We then report the details of an experiment investigating the interplay of kinetic frustration and interactions by probing the band structure of an optical kagome lattice with interacting ultracold bosonic atoms. Finally, we propose experimental ideas for exploring the properties of the singular band touching point in the kagome flat band.

Advisor: Stamper-Kurn, Dan M
The Mechanical Properties of Spray-Formed Oxide Dispersion Strengthened Steel Alloy 14YWT

Next generation nuclear reactor concepts employ higher temperatures, harder neutron fluxes, and generally a more difficult material environment than the current fleet. This, in conjunction with economic demands for longer periods between outages and higher fuel utilization, require radiation-hardened materials capable of withstanding such conditions. Oxide dispersion strengthened (ODS) steel alloys are one such potential class of materials. These are induced to have nanostructures within their bulk which provide distinct advan- tages, but which also preclude the use of consolidation and joining techniques which would degrade or destroy the same features. Cold spraying is an additive technique which has been explored as a possible avenue toward efficiently creating bulk parts out of ODS-precursor feedstock, with superior efficiency and properties compared to other means of consolidation, most commonly hot extrusion./nThis work has assessed the mechanical properties of one very promising ODS alloy, 14YWT, as formed by the cold spray technique. Results were not promising: the samples were brittle and weak, while not completely free of some of the disadvantages of hot extru- sion. Additionally, the demands of the cold-spray process were determined to be distinctly limiting as to the formation of the feedstock material, with negative impacts on the quality of the nanostructuring that forms the unique and desirable feature of the alloy. Though additional material processing and quality control may be able to remediate some of these defects, this work concludes that cold spraying is not a suitable mechanism for consolidating ODS alloys.

Advisor: Hosemann, Peter M