VictorJuiz/thesis huggingface dataset:
Liquid geography : the Yalu River and the boundaries of Empire in East Asia, 1894-1945
Keywords: History.

This dissertation examines imperial Japan's efforts to transform and control the Yalu River boundary between Korea and Manchuria (Northeast China) during the period 1894-1945. Following the Japanese colonization of Korea in 1910, the Yalu River, together with the neighboring Tumen River, formed the longest formal, non-maritime border of the Japanese Empire until its dissolution in 1945. Yet despite the Yalu's strategic significance in the imperialist politics of early twentieth-century Northeast Asia, its modern history has been surprisingly overlooked. I address this historiographical gap while making three key interventions in the larger scholarship on borders, climate history, and Japanese imperialism. First, by drawing on archival materials in Japanese, Korean, Chinese, and English, I argue that dynamic environments like the Yalu are more than mere backdrops to border histories, but co-agents of border creation and contestation alongside local human residents. A focus on what I call the liquid geography of the Yalu border shows how the transnational flow of people, goods, and the river itself exposed the limits of the colonial state even while providing the material underpinnings for further imperial expansion. Second, in analyzing the river as an agent of history, I propose a new, seasonal approach to history. Controlling the movement of peoples and goods across the Yalu meant contending with winter ice, summer floods, and other aspects of a seasonally changing riparian geography. Third and finally, I challenge conventional understanding of the political unity of the Japanese empire in Asia. I show how the internal contradictions of Japan's imperial project, as well as its external challenges, were most glaringly exposed along fault lines like the Yalu River border.
The listener in language change
Keywords: Linguistics.

Language changes constantly, in ways that can be influenced by factors both language-internal, such as word frequency, and language-external, such as social organization and attitudes. A major challenge for linguistic theory is to give a unified explanation of these constraints on language change. In this dissertation, I argue that this challenge can be addressed by looking to spoken language perception, where passive but powerful perceptual biases give rise to many similar constraints on how listeners update the cognitive representations they draw upon for language use. I present an approach to language change in which perceptual biases in the listener play a central role. I ground this approach in an exemplar-based computational model, which is able to recreate empirically-observed general properties of sound change. I then test the approach by integrating experimentally-supported perceptual biases with computational modeling and novel corpus methods across two studies. In the first study, I apply the computational model to simulate word-frequency effects in sound change. I show that different word-frequency effects in different kinds of sound change follow from a single perceptual bias, whereby high-frequency words are recognized more easily than low-frequency words when acoustically ambiguous. In the second study, I extend the listener-based approach to the effect of improving interethnic social attitudes on the spread of lexical items across ethnic groups in New Zealand. Drawing on biases in the perception of 'other-accented' words, I make specific predictions for the spread of the tag "eh" from indigenous Māori to White Pākehā, which I test with novel corpus methods. Taken together, these two studies highlight how passive but powerful perceptual biases in the listener can give a unified explanation of different constraints on language change.
Living still : John F. Peto and the artist across time
Keywords: Art and Art History.

This dissertation focuses on turn-of-the-century American still life painter John F. Peto, who painted in near obscurity in his studio home on the New Jersey shore until his death in 1907. His strange, trompe l'oeil paintings obsessively depict old, discarded objects including books, doors, pipes, mugs, letters, photographs, and likenesses of Abraham Lincoln. In the decades after Peto's death, twenty-one of his paintings were passed off—some with forged signatures—as the work of his more successful contemporary, William Harnett. These paintings were only brought to light as Peto's work in 1947. My project rejects Peto's marginal status, taking him out of a limited temporal and genre context to suggest that he might radically exist across time. I consider the afterlife and predestiny of Peto's paintings as integral to his practice. Across my four chapters and conclusion, I explore Peto's philosophy of posthumous success, his historical confusion with Harnett and subsequent discovery, gender and authorship in Peto's photographic practice, Peto's obsession with the Civil War president Abraham Lincoln, and Peto's resurfacing in the work of Jasper Johns.
Living up to Responsibilities: UN Humanitarian Interventions and the Impact of R2P
Keywords:  Department of International Relations
United Nations
Responsibility to Protect
Human Rights
Security Council
Intervention
International Relations
Thesis

The Responsibility to Protect (R2P) doctrine, which was unanimously signed by UN member states in 2005, declared that states have a responsibility to protect their citizens from genocide, war crimes, ethnic cleansing, and crimes against humanity. R2P was revolutionary for the time given that previously the UN considered domestic state sovereignty as inviolable and was only allowed to intervene if the state threatened international peace and security. Fourteen years later, R2P has been invoked in humanitarian interventions in Libya and Côte d’Ivoire but has been ignored in other cases of mass atrocities such as in Syria. This thesis examines how R2P has changed the way the UN performs interventions in conflicts and whether it has succeeded in preventing and abating mass atrocities. Specifically, this thesis takes a quantitative approach in analyzing how R2P and other factors have affected how fast the UN intervenes in civil wars and then examines these causal mechanisms qualitatively using three case studies of Libya, Côte d’Ivoire, and Syria.
Local and global variation in the human gut microbiome
Keywords: Genetics.

We increasingly appreciate the role of microbes that live in our gut, collectively referred to as the gut microbiome, in modulating human health and disease. However, translating findings to the clinic has presented challenges, as many studies of the microbiome in health and disease are associational and therefore difficult to translate to meaningful therapies. This thesis focuses on using high-throughput whole-genome sequencing of our gut microbes and computational genomic tools to understand host-microbe dynamics on the strain-specific level, identify opportunities for concrete clinical interventions, investigate the efficacy of existing interventions, and turn our attention to populations who have not been comprehensively studied to establish a baseline for further inquiry toward the microbiome in health and disease. The work herein contributes to our understanding of the microbiome as an influencer of disease outcome and both suggests and informs future microbiome-targeted therapies.
Local structure-redox relationship in Li-excess layered oxides
Keywords: Materials Science and Engineering.

In the last decades, lithium-ion batteries (LIB) have significantly contributed to technological progress. Recently, Li-excess layered materials are attracting interest as a promising cathode material for the next generation, since they exhibit high energy densities and capacities significantly higher than commercially available cathode materials. Unlike conventional layered oxides where the only redox center is transition metal cations, an oxygen anion redox in the Li-excess layered material plays an important role to achieve high capacity. However, despite their promising performance, a deeper understanding about the origin and details of anion redox is necessary for commercialization. Understanding the state of the material is crucial as property of material is determined and can be changed by structure. I introduce various X-ray techniques to understand and analyze the structure of Li-excess materials. Rietveld refinement reveals an increase in structural distortion, including antisite defect, in the Li-excess material during anion redox. A strong correlation between structure distortion and anion redox is identified and suggested as a powerful indicator to estimate the existence of anion redox. Not only as an indicator, exact analysis of crystal structure and oxidation state suggest methods to understand the anion redox in Li-excess material. Anion redox can also be tuned by altering composition and crystal structure of Li-excess material. Different amount of Sn substitution in Li1-xIri-ySnyO3 material change the extent of anion redox. Operando X-ray absorption spectroscopy analysis support different electrochemical behaviors. XRD analysis confirmed a distortion in the crystal structure in the existence of oxygen redox. Density functional theory simulation predicts possible local structure as a result of distortion, which suggests multiple ways of oxygen oxidation in different situations. Not only doping for changing oxygen redox properties, changing the synthesis condition affect anion redox strongly. Different annealing temperature and partial oxygen pressure during synthesis do not affect transition metal redox property in Li2RuO3 material. However, difference in synthesis conditions only alters anion redox capacity. I confirm and suggest that crystal structure determine the anion redox property in the Li-excess material, which suggests that we can tune the oxygen redox in various methods, adjust doping or changing synthesis conditions. Over this thesis, systematic analysis of various Li-excess material will be revealed. Study on identifying the structure-property relation is suggested, and methods to control anion redox is verified. This study will suggest powerful and robust direction to understand the origin of anion redox in Li-excess materials. This study will also show a guideline for optimizing properties of cathode materials for next-generation batteries.
Localization and free energy asymptotics in disordered statistical mechanics and random growth models
Keywords: Mathematics.

This dissertation develops, for several families of statistical mechanical and random growth models, techniques for analyzing infinite-volume asymptotics. In the statistical mechanical setting, we focus on the low-temperature phases of spin glasses and directed polymers, wherein the ensembles exhibit localization which is physically phenomenological. We quantify this behavior in several ways and establish connections to properties of the limiting free energy. We also consider two popular zero-temperature polymer models, namely first- and last-passage percolation. For these random growth models, we investigate the order of fluctuations in their growth rates, which are analogous to free energy.
Long Live the Motherland: Chen Man’s Visual Language and New Imaginings of Chinese Womanhood
Keywords:  Stanford Global Studies
Stanford Global Studies
East Asian Studies
China
Chen Man
Fashion Photography
Media Studies
Gender Studies
Fashion
China
Thesis

Given the rising prominence and profitability of the fashion industry in China, this thesis offers a close analysis of images that illuminate shifting visions of women’s representation. The rise of the fashion industry is not simply due to economic changes in the post-Maoist era. It is instead a reflection of broader social and cultural shifts in how the nation and women’s place in it are defined. In taking these contexts seriously within the realm of women’s fashion, this thesis contributes to post-structuralist critique on the role of women in China.
This project answers the question: how do fashion images in popular Chinese media perpetuate narratives around women’s roles in China’s shifting socio-political climate? This question is examined through close analysis of images by Chinese fashion photographer Chen Man within the framework of existing critical theory, specifically post-structuralist feminist discourse on China.
While the focus of this study is centered around fashion and aesthetics since China’s Opening and Reform (1979), it also places Chen Man’s work in conversation with historical images of women in China. The purpose of this comparison is two-fold: (1) in order to demonstrate the direct mapping of fashion cultures onto theoretical framework, Chen Man’s work must be considered within the historical context of 20th century China’s shifting cultural landscape; (2) although fashion is an inherently global industry, the Communist Revolution in China transformed Chinese fashion into a state-mediated performance of nationalism. China’s fashion today cannot only be considered within the global fashion market framework but must also exist in relation to the specifically Chinese context.
Love as We Know It: A Consideration of Romance through the Lens of Trust in the Era of Technology
Keywords:  Department of Communication
Trust
Love
Violations
Recovery
Thesis

Trust and love are two peculiarities of the human nature that influence our social and interpersonal relationships. This paper is a literature review and synthesis of philosophies that considers what each phenomenon is, how they develop independently of one another, how they interact, and how trust and love may change over the course of a relationship. Considering love, the particular partnership type of consideration in this paper is romantic relationships. The purpose is to educate the current generation on how trust and love influence social and romantic interaction while also providing an exploration into the concepts themselves. Through this exploration, the paper also considers the implications of the expression in trust and love for members of the current generation, one that has been cultivated in an age of ever-present technology.
Low-cost unsteady discrete adjoint techniques for aeroacoustic optimization
Keywords: Aeronautics and Astronautics.

With the rapid growth of aircraft traffic and the new modes of transport such as Urban Air Mobility systems crowding the air space, aircraft noise is no longer a mere design constraint but an important factor to design and optimize for. Reducing aircraft noise however requires efficient coupling of simulation tools with design methods to be able to meet the stringent future aircraft noise requirements that allow for sustainable growth. Gradient-based design optimization based on adjoint method for sensitivity analysis offers a feasible design approach. Adjoint methods based on steady state physics have been widely in practice in industrial applications mainly for aerodynamic optimization so far. However, extending this approach to aeroacoustic optimization is not straightforward and not a common practice in industrial settings due the requirement of unsteady adjoint solutions that is prohibitively expensive. This dissertation presents temporal and spatial coarsening techniques for the computation of low-cost unsteady adjoints to obtain sensitivities for aeroacoustic shape optimization. The effects of the coarsening techniques on the accuracy of the gradients are analyzed by using different levels of temporal and spatial coarsening using multiple two dimensional and three dimensional test cases. Computational cost savings as well as reduction of memory storage requirements up to 10% of the base adjoint solutions are presented while maintaining reasonable accuracy in the gradients driving the optimization for these test cases. Finally, an extension to the temporal coarsening technique is proposed with non-uniform time stepping of adjoint solver based on the local flow truncation error estimates of the flow solver. The proposed extension is demonstrated to further improve the accuracy of the low-cost gradients providing motivations for the future directions of the work done in this thesis.
The LZ dark matter search and development of a new gas phase technique to characterize low level electron emission from electrode grids
Keywords: Physics.

Dark Matter is needed to explain many cosmological observations and therefore has been proposed for many decades, but it awaits direct detection. One of the most popular classes of dark matter candidates is Weakly Interacting Massive Particles (WIMPs), which have masses in the order of 100 GeV and couple to ordinary matter at weak scale. In WIMP direct detection experiments, we look for WIMPs being scattered by nuclei, a process which produces low energy (smaller than 100 keV) recoiling nuclei that can be observed. We are building LZ, a detector looking for WIMPs using liquid xenon in a dual-phase time projection chamber (TPC), at 4850 feet underground at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. LZ aims to achieve the world's highest sensitivity to find WIMPs via WIMP-nucleon interactions. After a brief discussion of dark matter and the LZ experiment, this dissertation presents the details of my study to solve the electron emission problem. The LZ TPC will consist of electrode grids and other metallic surfaces that can emit electrons when operated under voltage. Because the charge measurement in the LZ detector is sensitive to single electrons, electrons from the grids can be both a significant nuisance for data collection and a source of background at low-energies, limiting the sensitivity of the experiment for low-mass WIMPs. This has motivated us to develop a test detector to study how to reduce this background. The test detector consists of a pair of grids biased to high voltage and operated in xenon gas. The electric field between the grid causes the electrons to produce electroluminescence scintillation light that is measured by PMTs. This new technique is sensitive to single electrons emitted by the grids, allowing a measurement of emission currents as low as atto-amperes. We used this detector to study the properties of different grids and to determine what treatments can be done to reduce their electron emission. We found that passivation with citric acid reduces electron emission from stainless steel surfaces. This work was supervised by Professor Thomas Shutt and was completed in collaboration with members of the LZ collaboration and the SLAC LZ group.
Machine learning and control methodologies with applications to medical computing
Keywords: Electrical Engineering.

Machine Learning (ML) in adult healthcare has demonstrated significant benefits in a wide range of applications, and provides a proof-of-concept for extended work in pediatrics. In contrast, ML in pediatric healthcare is a relatively immature field with huge potential for improving quality of patient care. Tools built using a combination of unique data sources, with novel theoretical and practical approaches, provide significant benefits when delivered to the hospital via the Electronic Medical Record (EMR). Statistical analysis of detailed in-hospital datasets enable standardizing patient care and construct a sound foundation for data-driven and automated decision support systems. Similarly, machine learning methodologies enable predictive models to optimize patient outcomes, and create frameworks for analyzing variable importances to improve efficiency in resource-limited critical care environments. Beyond the EMR, continuous bedside monitors record physiological waveforms to track each patient's state throughout their hospitalization. These dense, real-time data enable continuous provision of results, alerts, and predictions, but require novel deep learning models and adaptations to process and interpret. Convolutional Neural Networks (CNNs) provide a structured framework for processing such data sources, which is powerful yet flexible enough to adapt to a wide range of applications. Both in and outside the hospital environment, wearable devices provide similar physiological data streams to the in-hospital monitors. Such devices and the Wireless Body-Area Networks (WBANs) they comprise support remote patient monitoring in the ``e-Health'' paradigm. These systems are supported and enabled by theoretical and practical developments in fundamental wireless communication and queuing theory, yet require particular considerations for application to patient monitoring and care. In this thesis, I present novel contributions to both theoretical models and practical applications for each of these three lines of research. Each of these either directly addresses or indirectly supports a specific use case in the pediatric hospital environment.
Machine learning and social science for fair and private data products
Keywords: Management Science and Engineering.

Technological innovations are fundamentally transforming information flow and social behavior. Digital platforms are increasingly embedded in established social systems highlighting the importance of developing fair and private machine learning approaches to managing these platforms. As social networks and social media data are increasingly leveraged for business and policy decisions, this thesis discusses work to develop methods for analyzing data privacy in attribute-rich network data, and to promote fair and equitable digital systems. Chapter 2 discusses work on privacy in digital systems. Privacy attacks in networked systems commonly leverage homophilous interactions, or what's commonly referred to as "birds of a feather flock together". While homophily describes a bias in attribute preferences for similar others, it gives limited attention to variability. We observe that attribute preferences can exhibit variation beyond what can be explained by models of homophily, and observe that this excess variation can induce a similarity among friends-of-friends on a network without requiring any similarity among friends. These findings offer an alternative perspective on network structure and attributes in general and prediction in particular, complicating the already difficult task of protecting privacy on social networks. Then, Chapter 3 examines node attribute prediction tasks more generally and provides a framework for distinguishing different types of prediction tasks as within-network, across-network, or across-layer tasks. This work highlights that methods aimed at across-network tasks are in fact evaluated on across-layer problems and have limited performance on across-network problems. Chapter 4 assesses novel uses of social media data to target regulatory enforcement efforts. This work provides a more cautionary perspective on the leading case that Yelp reviews are useful to target food safety inspections. This work highlights that prior results are sensitive to ``extreme imbalanced sampling'': extreme because the dataset was restricted from roughly 13k inspections to a sample of only 612 inspections with only extremely high or low inspection scores, and imbalanced by not accounting for class imbalance in the population. Finally, Chapter 5 studies the challenge of class imbalance more generally, comparing more standard approaches like Synthetic Minority Oversampling Technique to more modern approaches like Weighted Random Forest and Balanced Random Forest. Taken together, this thesis highlights the importance of understanding how new technologies intersect with existing consumer behavior and demonstrate the unique role of machine learning and social science research in the design and management of data products. As technology continues to promote instantaneous connectivity, there is a pressing need for analytical tools that facilitate secure and equal-opportunity platforms