VictorJuiz/thesis huggingface dataset:
Ultrafast Manipulation of Magnetic Order with Electrical Pulses

During the last 30 years spintronics has been a very rapidly expanding field leading to lots of new interesting physics and applications. As with most technology-oriented fields, spintronics strives to control devices with very low energy consumption and high speed. The combination of spin and electronics inherent to spintronics directly tackles energy efficiency, due to the non-volatility of magnetism. However, speed of operation of spintronic devices is still rather limited (~nanoseconds), due to slow magnetization precessional frequencies./nUltrafast magnetism (or opto-magnetism) is a relatively new field that has been very active in the last 20 years. The main idea is that intense femtosecond laser pulses can be used in order to manipulate the magnetization at very fast time-scales (~100 femtoseconds). However, the use of femtosecond lasers poses great application challenges such as diffraction limited optical spot sizes which hinders device density, and bulky and expensive integration of femtosecond lasers into devices./nIn this thesis, our efforts to combine ultrafast magnetism and spintronics are presented. First, we show that the magnetization of ferrimagnetic GdFeCo films can be switched by picosecond electronic heat current pulses. This result shows that a non-thermal distribution of electrons directly excited by laser is not necessary for inducing ultrafast magnetic dynamics./nThen, we fabricate photoconductive switch devices on a LT-GaAs substrate, to generate picosecond electrical pulses. Intense electrical pulses with 10ps (FWHM) duration and peak current up to 3A can be generated and delivered into magnetic films. Distinct magnetic dynamics in CoPt films are found between direct optical heating and electrical heating./nMore importantly, by delivering picosecond electrical pulses into GdFeCo films, we are able to deterministically reverse the magnetization of GdFeCo within ~10ps. This is more than one order of magnitude faster than any other electrically controlled magnetic switching. Our results present a fundamentally new switching mechanism electrically, without requirement for any spin polarized current or spin transfer/orbit torques. Our discovery that ultrafast magnetization switching can be achieved with electrical pulses will launch a new frontier of spintronics science and herald a new generation of spintronic devices that operate at high speed with low energy consumption./nAt last, to push ultrafast spintronics to practical use, ultrafast switching of a ferromagnetic film is desired. By exploiting the exchange interaction between GdFeCo and ferromagnetic Co/Pt layer, we achieved ultrafast (sub 10ps) switching of ferromagnetic film with a single laser pulse. This result will open up the possibility to control ferromagnetic materials at ultrafast time scale, critical for practical applications.

Advisor: Martin, Lane
Bokor, Jeffrey
A Subset of Octopaminergic Neurons that promotes Feeding Initiation in Drosophila melanogaster

In order for animals to achieve metabolic hometostasis and maintain fitness, it is/ncrucial for them to make appropriate feeding decisions and precisely execute feeding/nbehaviors. Animals make feeding decisions based on various factors including their/nphysiological needs and palatability of the food source. Despite of their importance,/nneural and molecular mechanisms underpinning the integration of these internal and/nexternal information have yet to be fully elucidated. In addition, octopamine, an/nequivalent of mammalian norepinephrine, has been suggested to regulate feeding/nbehavioral responses in invertebrates. However, how octopamine modulates feeding/nbehavior has been unclear. Utilizing Drosophila melanogaster as a model system, I/nsought to examine the neural and molecular mechanisms underlying octopaminergic/nfeeding modulation in this thesis./nIn specific, I investigated the role of a subset of octopaminergic neurons, the/nOA-VPM4 cluster, in sucrose acceptance behavior. Thermogenetic activation of Gal4/nlines containing OA-VPM4 promoted proboscis extension to sucrose, while optogenetic/ninactivation reduced extension. Anatomically, the presynaptic terminals of OA-VPM4/nare in close proximity to the presynaptic terminals of sugar-responsive gustatory/nsensory neurons. Moreover, RNAi knockdown of a specific class of octopamine/nreceptor, OAMB, selectively in sugar-sensing gustatory neurons decreased the/nbehavioral response to sucrose. By calcium imaging experiments, I found that/napplication of octopamine potentiates sensory responses to sucrose in satiated flies./nPreliminary results from the experiments investigating functional connectivity/nbetween sensory neurons and OA-VPM4 suggest that OA-VPM4 is likely an/nupstream modulator of the sensory neurons. Taken together, these findings suggest a/nmodel by which OA-VPM4 promotes feeding behavior by modulating the activity of/nsensory neurons.

Advisor: Scott, Kristin
Building Energy Modeling and Control Methods for Optimization and Renewables Integration

This dissertation presents techniques for the numerical modeling and control of building systems, with an emphasis on thermostatically controlled loads. The primary objective of this work is to address technical challenges related to the management of energy use in commercial and residential buildings. This work is motivated by the need to enhance the performance of building systems and by the potential for aggregated loads to perform load following and regulation ancillary services, thereby enabling the further adoption of intermittent renewable energy generation technologies. To increase the generalizability of the techniques, an emphasis is placed on recursive and adaptive methods which minimize the need for customization to specific buildings and applications./nThe techniques presented in this dissertation can be divided into two general categories: modeling and control. Modeling techniques encompass the processing of data streams from sensors and the training of numerical models. These models enable us to predict the energy use of a building and of sub-systems, such as a heating, ventilation, and air conditioning (HVAC) unit. Specifically, we first present an ensemble learning method for the short-term forecasting of total electricity demand in buildings. As the deployment of intermittent renewable energy resources continues to rise, the generation of accurate building-level electricity demand forecasts will be valuable to both grid operators and building energy management systems. Second, we present a recursive parameter estimation technique for identifying a thermostatically controlled load (TCL) model that is non-linear in the parameters. For TCLs to perform demand response services in real-time markets, online methods for parameter estimation are needed. Third, we develop a piecewise linear thermal model of a residential building and train the model using data collected from a custom-built thermostat. This model is capable of approximating unmodeled dynamics within a building by learning from sensor data./nControl techniques encompass the application of optimal control theory, model predictive control, and convex distributed optimization to TCLs. First, we present the alternative control trajectory (ACT) representation, a novel method for the approximate optimization of non-convex discrete systems. This approach enables the optimal control of a population of non-convex agents using distributed convex optimization techniques. Second, we present a distributed convex optimization algorithm for the control of a TCL population. Experimental results demonstrate the application of this algorithm to the problem of renewable energy generation following./nThis dissertation contributes to the development of intelligent energy management systems for buildings by presenting a suite of novel and adaptable modeling and control techniques. Applications focus on optimizing the performance of building operations and on facilitating the integration of renewable energy resources.

Advisor: Moura, Scott J
Racial/Ethnic Disparities in Preterm Birth in an Intergenerational Cohort of Mothers and Babies in California: The Role of Neighborhood Disinvestment

Background/nPreterm birth in the U.S. is higher than other comparable countries. Babies born preterm are at higher risk of life-threatening complications in their first days as well as a range of health and educational problems over the life course. Despite recent declines in preterm birth, significant racial/ethnic disparities persist. A growing body of literature suggests conditions in the places where people live, especially during critical time periods of development, may be playing a fundamental role in shaping the development of maternal health, and disparities in birth outcomes in the subsequent generation. However, this literature is limited by cross-sectional neighborhood and health data and incomplete definition and measurement of complex historical and economic processes that shape neighborhood environments. The overarching goals of this study are 1) to expand current measurement of neighborhood contexts to capture historical and economic processes of structural marginalization that have shaped them, and to assess the relationship between these expanded measures and preterm birth 2) to develop and apply a framework informed by structural marginalization to catalyze a next-generation practice of Maternal and Child Health./nMethod/nThe Life Course Social Context database, which contains geocoded birth records linked between mothers and babies in California, provides a unique opportunity to assess the relationship between neighborhood-level exposures experienced at two different stages of a mother’s life course (early childhood and adulthood) and preterm birth in the next generation. Using these data and other census measures, we construct histories of neighborhood poverty going back to 1970 and examine associations between these neighborhood poverty histories and preterm birth. Next, we assess the relationship between structural neighborhood inequality and preterm birth and preterm birth disparities, using measures of income inequality, racial/ethnic inequality and a combined measure of income and racial/ethnic inequality. Finally, we develop a conceptual model for understanding the broader context in which inequities in birth outcomes arise and provide case examples and lessons for future development of a next-generation MCH practice that will address the root causes of inequities in birth outcomes./nSignificance/nClearer understanding of complex neighborhood processes and how they shape health through generations is vital for the development of targeted and impactful public health programs. The development and assessment of new measures that approximate structural forces underlying neighborhood conditions shaping health over the life course will help direct the scope and scale of policy and practice efforts aimed at improving health and reducing inequities in birth outcomes. This study aims to contribute to more complete definition, measurement, and intervention for historical and structural forces that shape neighborhood conditions.

Advisor: Mujahid, Mahasin S
Traffic: On the Displacement of Art in Early Twentieth-Century France

This dissertation is about the image and the reality of traffic in early twentieth-century France, from the late 1890s to the mid-1930s. It comprises three chapters, each of which centers on a different artist’s encounter with the emergence of the modern traffic system: Camille Pissarro’s Boulevards Montmartre and Avenues de l’Opéra series of 1897-98, Le Corbusier’s first projects in and around Paris between 1917-1923, and Fernand Léger’s “object-drawings” of 1928-33. Together, these chapters shed light on the emergence of a new scene of modernization three decades after Baron Haussmann’s first campaign of urban renovations, from which would result the transformation, not simply of the old core of central Paris, but of the road network in its entirety, encompassing city and country alike. Tracking the development of the traffic system in broad strokes, from the policing of the street in the moment of the Dreyfus Affair to the planning of the first autoroutes in the late 1920s and early ’30s, my dissertation asks how the modernization of street traffic came to be seen as a natural and normal aspect of the human environment, and how, in turn, artists, architects, and other advocates of modernism sought to grapple with the contradictions of the new infrastructural landscape.

Advisor: Clark, Timothy J.
System-Aware Optimization for Machine Learning at Scale

New computing systems have emerged in response to the increasing size and complexity of modern datasets. For best performance, machine learning methods must be designed to closely align with the underlying properties of these systems./nIn this thesis, we illustrate the impact of system-aware machine learning through the lens of optimization, a crucial component in formulating and solving most machine learning problems. Classically, the performance of an optimization method is measured in terms of accuracy (i.e., does it realize the correct machine learning model?) and convergence rate (after how many iterations?). In modern computing regimes, however, it becomes critical to additionally consider a number of systems-related aspects for best overall performance. These aspects can range from low-level details, such as data structures or machine specifications, to higher-level concepts, such as the tradeoff between communication and computation./nWe propose a general optimization framework for machine learning, CoCoA, that gives careful consideration to systems parameters, often incorporating them directly into the method and theory. We illustrate the impact of CoCoA in two popular distributed regimes: the traditional cluster-computing environment, and the increasingly common setting of on-device (federated) learning. Our results indicate that by marrying systems-level parameters and optimization techniques, we can achieve orders-of-magnitude speedups for solving modern machine learning problems at scale. We corroborate these empirical results by providing theoretical guarantees that expose systems parameters to give further insight into empirical performance.

Advisor: Jordan, Michael I
Culler, David
Herpesviral regulation of the RAE-1 family of NKG2D ligands

Natural Killer (NK) cells are essential for control of viral infection and cancer. NK cells express NKG2D, an activating receptor that directly recognizes NKG2D ligands. These are expressed at low level on healthy cells, but are induced by stresses like infection and transformation. The physiological events that drive NKG2D ligand expression during infection are still poorly understood. Given the observation that the mouse cytomegalovirus (MCMV) encoded protein m18 is necessary and sufficient to drive expression of the RAE-1 family of NKG2D ligands I investigate m18, how it induces NKG2D ligand expression, and how the biology of NKG2D ligand regulation relates to the biology of herpesviruses. I demonstrate that RAE-1 is transcriptionally repressed by histone deacetylase inhibitor 3 (HDAC3) in healthy cells, and m18 relieves this repression by directly interacting with Casein Kinase II and preventing it from activating HDAC3. Accordingly, I found that HDAC inhibiting proteins from human herpesviruses induce human NKG2D ligand ULBP-1. Thus my findings indicate that virally mediated HDAC inhibition can act as a signal for the host to activate NK-cell recognition. Additionally, I characterize two unique proteins produced from the m18 ORF, and demonstrate tone of them is necessary and sufficient to induce the expression of RAE-1 ligands. Finally, I investigate a similarity between the reactivation control promoters of y-herpesviruses and NKG2D ligands, and investigate the potential of a drug that blocks NKG2D ligand induction to block y-herpesvirus reactivation.

Advisor: Coscoy, Laurent
Competition, Entrepreneurship, and Innovation

What kind of market structure promotes innovation and growth? This dissertation delves into the relationship between market power, innovation, and returns. On one hand, competition exerts downward pressure on costs and provides incentives for efficient organization of production. On the other, the Schumpeterian hypothesis suggests that monopolist rents are necessary to encourage technological disruption. I study the effects of competition in two distinct settings: the acquisition of early-staged high-growth startups and horizontal mergers between public companies./nIn Chapter 1, Catering Innovation: Entrepreneurship and the Acquisition Market, I study the role of the financial market of acquisitions on an inventor's decision to begin a new venture and his or her subsequent innovation. After documenting its increasing importance as the dominant exit path for entrepreneurs, I test a novel catering theory of innovation: Does the market structure of potential acquirers have a measurable impact on inventors' start-up decisions? I construct a new dataset of early stage start-ups using the uniquely broad coverage of CrunchBase and VentureXpert data. I disambiguate and match the resulting data to employment data from LinkedIn and to the entire universe of patent data. Using the prior citation history of entrepreneurs for exogenous variation, I construct a formal proxy variable and employ the Heckman selection model to establish causality. I find that a one standard deviation increase in acquirer market concentration decreases the inventor's propensity to become an entrepreneur by 4%. This first result suggests that fragmented markets are appealing entry markets. My main finding is that a one standard deviation increase in acquirer concentration and market size increases the quality of patents, as measured by citations per patent, and the catering of entrepreneurs, as measured by technological overlap with potential acquirers. The magnitudes suggest that 5-16% of entrepreneurial innovation can be attributed to the influence of acquisition markets, particularly in the information technology and biotechnology industries./nIn Chapter 2, Market Power in Mergers and Acquisitions, I explore the value implications of market power changes in public mergers and acquisitions. Using a large sample of horizontal mergers from 1980 to 2012, I provide evidence that a significant portion of merger announcement returns are explained by changes in market power resulting from the merger. I find that a 0.1 expected increase in product market concentration leads to a 2.3% increase in cumulative abnormal returns over a three day period. In the long-run, mergers with high expected changes in market power revert to pre-announcement levels. My results suggest the "announcement effect" in M&A is due to misplaced market power expectations by investors.

Advisor: Malmendier, Ulrike
Morse, Adair
Towards Automated Online Schema Evolution

Schema evolution studies the issue of moving a database from one version of its schema to a new updated schema. Traditionally, database administrators perform these tasks offline and they involve large amounts of manual labor and custom scripting. In today’s world where databases power many 24/7 online services, schema evolution can no longer be an offline process. Furthermore, application requirements change much more rapidly today, causing more frequent changes in database schemas. Because of these trends, it is critical for database administrators to have automated tools to evolve database schemas in an online fashion that does not disrupt the foreground services./nThis thesis attempts to explore ways an administrator might automate this pro- cess and provide some insight into building tools to help make this process easier, faster and more reliable. The thesis makes the following contributions. First, it provides a complete system implementation, Ratchet, that a database administrator can use to perform efficient schema evolution on supported platforms (PostgreSQL). The system uses various techniques such as improved fine-grained locking and a delayed- copy strategy to improve its schema evolution performance. Second, it analyzes the characteristics of schema evolution for a five-year period for Wikimedia, one of the most widely used websites. Third, using Ratchet, the thesis recreates five years of schema evolution automatically. Finally, the thesis provides a mechanism of rollback in schema evolution.

Advisor: Brewer, Eric
Minority Models: Masochism, Masculinity, and the Machine in Asian American Cultural Politics

As W.E.B. DuBois asked African Americans in The Souls of Black Folk, “How does it feel to be the problem?”, Vijay Prashad asked Asian Americans in The Karma of Brown Folk, “How does it feel to be the solution?” That is, what are the affective and ethical repercussions of being positioned as “model minority” in the U.S. racial system? In response, this dissertation aims to develop a queer theory of Asian American masochism, gesturing to a cultural politics intertwined with this racial position, negotiated through a masochistic attachment to the figure of the machine. My dissertation, Minority Models: Masochism, Masculinity, and the Machine in Asian American Cultural Politics, analyzes the masochistic performance of masculine Asian American cultural production in the co-constitution of Asianness and machineness in Asian American identity from 1982 to the present day./nThrough the study of Asian American literature and theater, the political histories of Asian American critique, as well as new media forms like video games and comics, I argue that masculine Asian American cultural production places Asian American masculinity and mechanization into a symbiotic relationship in its articulations of Asian American identity. My work asks: what are the affective and ethical repercussions of being positioned as “model minority” in the U.S. racial system? One answer, this text suggests, lies in masochistic pleasure, wherein reception of pain and penetrability become sources of both pleasure and moral legitimacy. Building upon prior scholarship that models Asian American subject formation within a rubric of melancholic lack—such as Anne Cheng’s Melancholy of Race and David Eng’s Racial Castration—I gesture towards revising such models in favor of the pleasures of masochism. I argue that Asian American cultural production generates affective and ethical meaning from masochism as a moral economy, source of pleasure, and avenue for imagining racial form beyond human boundaries.

Advisor: Steen, Shannon
Lye, Colleen