VictorJuiz/thesis huggingface dataset:
Allosteric communication, assembly, and nucleotide hydrolysis in group II chaperonins

Protein function is dependent upon adoption of a native 3-D configuration whilst avoiding toxic conformations. Some proteins can fold spontaneously; however, the complexity of the proteome requires cellular cofactors called chaperones to ensure problematic proteins are natively folded. Chaperonins are a class of molecular chaperones that are universally conserved in all domains of life and contribute to the cellular proteostasis toolkit. They are 1-MDa complexes composed of two rings that undergo a dramatic conformational change with ATP hydrolysis to form an inner folding cavity. Chaperonins have significantly diverged in architecture, topology, and client repertoire so they are divided into two classes: group I and group II chaperonins. Group I chaperonins exist in prokarya whilst group II chaperonins are found in eukarya and archaea. All chaperonins help to orchestrate ATP-dependent client protein sequestration and refolding through encapsulation in the central folding cavity. This thesis is centered on enumerating the mechanism of a group II chaperonin found in M. Maripaludis (MmCpn), an archaeal methanogen. Biochemical and biophysical interrogation of structural moieties, chiefly the c-termini, were found to contribute to ATP hydrolysis, substrate re-folding, and complex integrity. New structural elements such as interfacial methionine fingers and electrostatic contacts were observed to undergo novel conformations, yielding new candidates for studying group II chaperonins in general. Electrostatic disruption of the c-termini allowed for dissection of multimeric states, including the long elusive single-ring species which could serve as a useful tool for understanding chaperonin biogenesis and function

Keywords: Medicine.
Advisor: Frydman Judith
Puglisi Joseph D.
Wakatsuki Soichi
An Ecology of Quotation and Quotability: Discourse in Annie Dillard's Pilgrim at Tinker Creek

Annie Dillard’s Pilgrim at Tinker Creek uses quotation and quotability to create a system of discourse founded in the messy ecological processes of consumption, digestion, and decomposition. Dillard quotes heavily from a myriad of sources, creating her narrating self as the processor and digester of a dialogic tangle of citationality. This overwhelming surge of discourse into the self leads to Dillard’s rich transcendence. At the same time as she quotes heavily, she unexpectedly denies easy quotability to her own text. Her prose is captivating but disrupts itself, preventing the reader from excising text out of context. This forces readers into more immersive and digestive meaning making and rejects the traditional Transcendentalist ethic of individualism, domination, and quotability. This process of discourse—of consumption through quotation, and decomposition and reconstruction through the intentional process of meaning-making beyond quotability—is an iterative, brutal, and ecological semiotic system that rejects Emerson’s clean microcosmic semiosis. Dillard's own observations of nature demonstrate this very ecological semiotic system of a tangled food web, with flesh and energy always being torn, eaten, destroyed, and reused. Dillard models a productive and discursive way to achieve transcendence and create meaning.

Keywords: English
Dillard, Annie
Pilgrim at Tinker Creek (Dillard, Annie)
Transcendentalism
Transcendentalism in literature
Citationality
Quotability
Quotation
Thoreau, Henry David, 1817-1862
Emerson, Ralph Waldo, 1803-1882
Emerson, Mary Moody, 1774-1863
Bakhtin, M. M. (Mikhail Mikhaĭlovich), 1895-1975
Foucault, Michel, 1926-1984
Digital humanities
Commonplace books
Fuller, Margaret, 1810-1850
Ecocriticism in literature
Ecocriticism
Semiotics and literature
Dialogism (Literary analysis)
Nonfiction
Feminist literary criticism
Creative nonfiction
Nature writers
Ecoliterature
Mysticism
Mysticism in literature
Lorde, 1996-
Text
Thesis
Advisor: Greif Mark
Ruttenburg Nancy
Anaesthetics : popular music and the flight from feeling

This dissertation argues that themes of self-dissolution, emotional emptiness, and empathetic absence are becoming increasingly central to contemporary English-language popular music. It historicizes this phenomenon by relating popular music's "flight from feeling" to late-twentieth and early-twenty-first century transitions in popular music production, drug culture, media, and labor. And it theorizes the aesthetic paradoxes that emerge when themes of nonfeeling are taken up by popular song, often understood as an art form preoccupied with describing, evoking, and producing emotion. This dissertation's three central chapters explore three registers of nonfeeling: dissociation (deprivation of sense of self), numbness (deprivation of sensation or emotion), and coldness (deprivation of empathy or affect). Its first chapter takes up three recent pop, hip-hop, and hyperpop songs that not only describe dissociation in their lyrics but also enact it texturally and formally, theorizing these songs' performances of self-dissolution by relating them to changing music production norms and to the alleged "death of the subject" in postmodern cultural production. Its second chapter traces a history of popular music's engagements with the word "numb," beginning with Pink Floyd's 1979 "Comfortably Numb" and concluding with Em Beihold's 2022 "Numb Little Bug." Its third chapter explores coldness as a metaphor, a sound, and an affect in popular music from the 1970s to the 2020s, arguing that although coldness once represented a term of condemnation directed at unfeeling lovers, it has increasingly become a value that popular songs attribute to their own lyric subjects. Its conclusion reflects on the uses and pleasures that nonfeeling offers these songs and that these songs offer their listeners, asking under what circumstances nonfeeling might come to feel good.

Keywords: Humanities and Sciences.
Music.
Advisor: Gill Denise
Kronengold Charles
Greif Mark
Hadlock Heather
Analyses of market structures

This paper contains three chapters which each develops a new economic model to investigate a question related to market structure. The first chapter develops a search-theoretic model of competing platforms that profit from targeted advertising to understand the impacts of policies, such as those on consumer data and platform interoperability, on this market's function. The second chapter, based on joint work with Darrell Duffie, investigates the welfare implications of the growing fragmentation of trade across lit exchanges. The third chapter investigates the optimal design of a market for trade of a financial asset

Keywords: Business.
Advisor: Sannikov Yuliy
Skrzypacz Andrzej
Duffie Darrell
Wilson Robert
An analysis of projection-based reduced order models and their application to supersonic flows

Computationally expensive physics simulations remain necessary and challenging in the engineering community. Applications that require many queries of the high dimensional model are particularly expensive, including design optimization and uncertainty quantification. Time-critical applications, such as model predictive control, cannot currently rely on high-fidelity simulations due to the time and storage requirements. Projection-based reduced order models (PROMs) offer a promising solution by approximating the full-order simulations while significantly reducing the computational complexity. This dissertation explores projection-based reduced order models (PROM) in fluid dynamics simulations. The objective is to develop a tool for analyzing and applying PROMs in computational fluid dynamics (CFD) problems. The PROM framework is implemented in the SU2 solver using the Least-Squares Petrov-Galerkin equations. Using this tool, a novel hyper-reduction method is investigated. Additionally, a comparative analysis between PROMs and a nonlinear autoencoder model using latent space systems identification is presented. The comparative analysis guides the selection of appropriate modeling approaches for different flow scenarios that contain shocks

Keywords: Engineering.
Aeronautics and Astronautics.
Advisor: Alonso Juan José
Farhat Charbel
Kochenderfer Mykel J.
Anomaly detection in X-ray physics

Anomaly detection is an important task for complex systems (e.g., industrial facilities, manufacturing, large-scale science experiments), where failures in a sub-system can lead to low yield, faulty products, or even damage to components. These systems produce too many signals for the system operators to monitor in real time. In addition, many of these signals are only interpretable by subject matter experts with years of experience. As a result, changes in system performance can require time-intensive consultations with experts to identify the underlying problem. For this reason, despite the wealth of data that these complex systems produce, labeled anomalies are typically rare (or even nonexistent) and expensive to acquire. Since there are no labels, the training data will inevitably be contaminated by anomalies. In Chapter 2, we introduce a fully automated, unsupervised beam-based diagnostic method for RF station fault detection at SLAC's Linac Coherent Light Source (LCLS). Our key contribution is the combination of high fidelity beam position monitoring data with bandwidth limited (and noisy) radio-frequency (RF) station diagnostic data to achieve highly accurate, nearly real time fault identification. In Chapter 3, we introduce coincident learning for anomaly detection (CoAD) and an unsupervised metric \hat{F}_\beta, that assumes and exploits that anomalies are coincident in two different slices of the input data. We present theoretical properties of our metric and demonstrate its performance on four data sets. In Chapter 4, we focus on a broader task of detecting any anomalous beam behavior at LCLS and develop the unsupervised Resilient Variational Autoencoder (ResVAE) model. We illustrate its resilience to contaminated training data and apply it to identifying anomalies in accelerator status at LCLS . In Chapter 5, we switch gears and address a problem in neural network pruning. We introduce a novel channel pruning approach for convolutional neural networks, called Soft Masking for cost-constrained Channel Pruning (SMCP), that is particularly suitable when pruning a large fraction of the network's channels. The core of our approach relies on regularly rewiring the network sparsity, through soft masking of the network weights, to minimize the accuracy drop for large pruning fractions. Our method outperforms prior works on both the ImageNet classification and PASCAL VOC detection datasets.

Keywords: Engineering.
Advisor: Darve Eric
Ermon Stefano
RatnerDaniel
Applications of absorption spectroscopy to the study of hypersonic flow conditions in ground test facilities

The hypersonic flight regime is a hostile one, characterized by significant thermal loading on vehicle structures. In order to fortify vehicle platforms and mission architectures employing these high speeds, experimental testing is crucial to better characterize the thermochemical processes prevalent behind the strong shock waves emblematic of hypersonic flight. As part of this effort, ground test facilities fulfill an important niche. These facilities simulate realistic hypersonic flight environments by generating high-speed, high-enthalpy flows in controlled environments. In this dissertation, laser absorption spectroscopy is leveraged to study several different hypersonic flows or relevant high-temperature conditions in three different types of ground test facilities. Spectroscopic targets include nitric oxide (NO), atomic nitrogen (N), atomic oxygen (O), molecular nitrogen (N2), and carbon monoxide (CO). The monitoring of these species permits the assessment of hypersonic-relevant phenomena, including chemical non-equilibrium, vibrational freezing, and electronic excitation. Three major experimental efforts underlie this dissertation. The first is the characterization of the hypersonic flows in the Caltech T5 Reflected Shock Tunnel. Spectroscopic measurements allowed for the determination of freestream temperature, composition, and flow velocity. These measurements were then extended into near-body flows behind the shock waves generated by cylinder and wedge test articles. The second study is the characterization of the NASA Ames Interaction Heating Facility (IHF), a 60 MW Arcjet used to study thermal protection systems (TPS). Spectroscopic investigation targets the determination of stagnation enthalpy, a crucial operational parameter. Finally, the third study utilizes an in-house Stanford shock tube to investigate nitrogen-chemistry electronic excitation and ionization, high-temperature processes relevant to lunar return trajectories.

Keywords: Engineering.
Mechanical Engineering.
Advisor: Hanson Ronald
Hara Ken
Urzay Lobo Javier
Applications of cooperative game theory to interpretable machine learning

Model-agnostic feature importance measures are central to the task of demystifying opaque or "black-box" machine learning models. The proliferation of such models within high-stakes decision making settings such as healthcare or banking necessitates the development of flexible and trustworthy approaches to the problem. With no ground truth feature importance to compare to, competing methods provide contrasting approaches and/or philosophies often with a claim of superiority. Some of the most popular recent approaches are adaptations of tools from cooperative game theory used in reward or cost sharing problems. In this document, we report on recent advances among such feature importance methods. In particular, we discuss a "data-centric" cohort-based framework for model-agnostic local feature importance using Shapley values. We propose a primary importance measure and explore several adaptations of that method better suited for specific use cases or data regimes. We analyze the properties and behaviors of these methods and apply them to a broad range of synthetic and real-world problem settings including voter registration and recidivism data. We then propose and discuss new methods for local importance aggregation and feature importance evaluation

Keywords: Humanities and Sciences.
Statistics.
Advisor: Owen Art B.
Palacios Roman Julia Adela
Taylor Jonathan E.
Applications of microlocal analysis in general relativity and inverse problems

This thesis consists of three parts: the first part serves as a brief introduction to microlocal analysis; the second part is the application of microlocal analysis in general relativity; the third part is the application of microlocal analysis in inverse problems. In the first part, we introduce various pseudodifferential operator algebras we will use as tools in our applications. These algebras include well-known ones such as classical, scattering and b￾algebras, and also relatively new ones such as 1-cusp (in fact, its semiclassical foliation version) and the one we construct for our wave propagation on Kerr(-de Sitter) spacetimes. In the second part, we prove a propagation estimate with arbitrarily small extra loss compared with the classical non-trapping propagation estimates using the algebra we constructed in Chapter 3. One of the major applications of estimates of this type is to linearized Einstein equations on the Kerr(-de Sitter) spacetimes. In the third part, we consider the injectivity of the X-ray transform on one forms and 2-tensors on asymptotically conic manifolds. This uses the algebra developed by Andras Vasy and Evangelie Zachos. This question is motivated by the boundary rigidity problem of asymptotically conic manifolds, we expect this injectivity result of the X-ray transform to be a linearization of it and serve as a key ingredient in the proof of this rigidity problem

Keywords: Engineering.
Advisor: Vasy András
Mazzeo Rafe
Ryzhik Leonid
Applying artificial intelligence to the sociological study of meaning

As artificial intelligence changes nearly every facet of modern society, we should not be surprised that it is changing how we do social science. By leveraging the power of machine learning and automated text analysis, researchers can analyze complex patterns from data and extract meaning from natural language at an unprecedented scale. However, the application of these tools to social scientific inquiry raises important issues concerning construct validity and the very nature of deductive social science. Throughout this dissertation, I examine the promises and pitfalls of applying these cutting-edge technologies specifically to the sociological study of meaning. In the first chapter, I provide a comprehensive review of popular automated text analysis methods and classify them according to the pre-analytic constructs they extract from text. In the following chapters, I present two original studies that use machine learning and automated text analysis to answer fundamental questions about culture and meaning. The first study asks: does everyday symbolic exchange contain sufficient information to effectively enculturate a tabula rasa learner? The second asks: does the way an individual understands their nation shape their immigration policy preferences? Via novel and rigorous applications of computational methods, I provide compelling evidence that supports the affirmative answers to both questions. Ultimately, this dissertation highlights the potential of machine learning and automated text analysis to produce sound social science research. However, it also underscores analytical concerns of which researchers should be mindful

Keywords: Humanities and Sciences.
Sociology.
Advisor: Goldberg Amir
Willer Robert Bartley
Freese Jeremy
Applying physical principles for reliable and precise human manipulation

When faced with complex design questions, it may seem natural to design complex devices. However, careful consideration of underlying physical principles can help lead to concise and simple solutions, which in turn can have higher impact. In this dissertation, we present two complimentary projects which illustrate this principle, focusing on human manipulation. The first project is the design, analysis, and utility evaluation of a two-finger force feedback haptic interface. It explores the utility of high-performance haptic feedback at the fingertips for interaction in teleoperated and virtual environments. The second project entailed the design and validation of a low-cost electricity-free device for automating the preparation of whole blood samples for pathology assessment. This device is a key part of our in-house low-cost pipeline for automatically diagnosing malaria, a preventable infectious disease that still kills hundreds of thousands of people per year.

Keywords: Engineering.
Mechanical Engineering.
Advisor: Cutkosky Mark R.
Prakash Manu
Salisbury J. Kenneth
Are National Parks Reserved for Certain Visitors? Effects of Timed-Entry Reservation Systems on the Demographic Composition of Arches National Park Visitors

Timed-entry reservation systems are an increasingly popular visitation management strategy at National Parks. Acquiring a reservation through these systems requires computer literacy, advance notice of work and family scheduling, and familiarity with national park policies. These characteristics are concentrated within particular demographic groups, and as such timed-entry systems create an inequitable barrier to national park visitation. Using a difference-in-differences regression model on survey data collected in 2015 and 2016 and data from the Recreation Information Database, I find preliminary evidence that the timed-entry system at Arches National Park resulted in an increase in median household income and educational attainment based on park visitors’ zip codes. Building on existing research which suggests that requiring reservations for campsites can have negative impacts on racial and socioeconomic diversity, I show that the pattern holds in national parks that implement reservation systems park-wide. This finding exists within the context of underrepresentation of marginalized groups in national park visitation and outdoor recreation more broadly. While timed-entry systems may protect the environmental assets of national parks, they make outdoor spaces less accessible and are contradictory to the mission of public lands.

Keywords: Public Policy Program
National parks and reserves
Public lands
Land use > Management
Race
Diversity, equity, and inclusion
Socioeconomic status
Accessibility
Environmental justice
Stanford University
Humanities and Sciences
Public Policy Program
Text
Thesis
Advisor: Cain Bruce
Art under a spell : gender, sexuality, and esotericism in Los Angeles

Art Under a Spell: Gender, Sexuality, and Esotericism in Los Angeles examines the roles of magic, altered states of consciousness, and other esoteric practices in the work of Cameron, Kenneth Anger, Curtis Harrington, Wallace Berman, and Steven Arnold. As the center of the burgeoning aerospace industry, psychedelic counterculture, and Hollywood, Los Angeles was uniquely positioned for their otherworldly ambitions. However, what unites these figures beyond geographic proximity are their shared desires to think expansively about identity and sexuality; their propensities toward secrecy and interiority; performative impulses; and ambitions to make the dreamlike worlds of their imaginations come alive. Drawing from rarely seen archival materials, queer and feminist theory, and cultural studies, this dissertation situates esotericism as a means through which these artists engage with and reconfigure conceptions of subjectivity, opting for marginality and social deviancy rather than visibility and legibility. This dissertation not only offers a deeper understanding of these artists, but also calls for methodologies that might embrace the irrational, magical, and hidden impulses within histories of postwar American art.

Keywords: Humanities and Sciences.
Art and Art History.
Advisor: Meyer Richard
Aberth Susan L.
Kwon Marci
Nemerov Alexander
Artificial intelligence and dynamic markets

Artificial Intelligence (AI) has been transforming digital and analog markets in the past few years. Will the current economic analysis apply to new decision-making technologies? In my dissertation, Artificial Intelligence and Dynamic Markets, I study this question from multiple perspectives. I model automated decision-makers, the markets they operate in, and the information structures of dynamic digital economies. Through this research, my aim is to enhance our understanding of the functioning of dynamic digital markets and identify the market structures that facilitate efficient AI adoption

Keywords: Business.
Advisor: Skrzypacz Andrzej
Kreps David M.
Ostrovsky Michael