VictorJuiz/thesis huggingface dataset:
Quantitative dissection of pattern formation along the central dogma in the early fly embryos

The question of how a cell determines which cell fate it will adopt is at the heart of developmental biology. In most cases, morphogens control cell fates by directing cells to activate or repress downstream gene expression programs containing a specific subset of genes required for the desired cell function and morphology. Over the past few decades, this question has been dissected in great detail in several model organisms. One of the best-studied examples is the early embryo of the fruit fly, Drosophila melanogaster, whose cascade of gene expression network has been revealed by decades of hard work. Indeed, the fruit fly is one of the first organisms whose morphogens were identified using mutant screens pioneered by Christiane Nüsslein-Volhard and Eric Wieschaus. The identified morphogens revealed how the initial gradients of morphogens instruct cells at different positions along the embryo body axis to adopt different fates, such as those corresponding to legs or antennae, by activating differential transcriptional programs./nFor the past decade, this knowledge of classic developmental biology, which revealed great details about the underlying gene regulatory networks, has been under quantitative dissection via the development of a wide array of new experimental techniques. The accumulation of these quantitative data demands quantitative models to understand the underlying principles behind gene regulation. Ultimately, one of the dreams of developmental biologists is to have a predictive understanding of gene expression patterns solely from the patterns of input morphogens and the regulatory DNA sequences./nI believe that the field of developmental biology is at an exciting new phase where quantitative measurements meet theoretical modeling to unveil the molecular underpinnings of transcriptional and translational regulation. In my view, the dream of predictive developmental biology can only be achieved by an active dialogue between theoretical modeling that generates experimentally testable hypotheses and quantitative measurements to test these hypotheses./nMy dissertation is an attempt to contribute to this new phase of quantitative data meeting theoretical modeling by developing and characterizing molecular tools for quantitative measurements of gene expression following the central dogma (transcription and translation), and theoretical frameworks to understand and predict transcriptional regulation and protein pattern formation.

Advisor: Garcia, Hernan
Systems for Using Far Memory in Datacenters

Datacenter efficiency has become increasingly relevant, as the end of Moore's Law and Dennard scaling have caused CPU and memory performance to begin plateauing. Resource disaggregation is a recent datacenter design point, where server nodes share remote resources through a fast (usually RDMA-based) network, enabling greater execution flexibility and performance in datacenters. Remote or far memory--an instance of resource disaggregation--increases flexibility because nodes can access more memory than locally available. And performance in distributed applications can improve as RDMA provides high-performance access to shared state. This dissertation describes two networked systems that allow server nodes in a data center to leverage far memory./nFirst, WICkit is a framework and runtime for Where-Independent Code. WICs are a location-independent abstraction representing complex remote memory accesses, e.g., accessing a value in a hashmap. Without code changes, the WICkit runtime can execute WICs at the client, server, and SmartNIC CPU locations. As different locations provide different performance and resource trade-offs, WICkit allows users to flexibly choose the location when execution begins while obtaining comparable performance to location-specific systems./nSecond, Cluster Far Memory is a system that transparently allows existing jobs to access far memory. CFM includes a fast swapping mechanism and a far memory-aware job scheduler that enable far memory support at rack scale. Using CFM for memory-intensive workloads, a rack can improve its throughput on the order of 10% or more without increasing the total amount of memory in it.

Advisor: Shenker, Scott
Sources of Perceived Online Social Support: Adaptation of the Online Social Support Scale

In this study, I examined whether there were differences in online social support by source. The three sources were college friends, pre-college friends, and virtual friends. I adapted a measure of online social support in a sample of 500 undergraduate students who communicated with friends online. Psychometric analyses supported the reliability and validity of scores on the adapted measure. Analysis of variance results indicated a statistically significant effect of friend source on online social support scores, with a large effect size. Follow-up analyses indicated significant pairwise differences in scores between virtual friends and college friends as well as virtual friends and pre-college friends. There was a statistically significant positive correlation with a small effect size between length of friendship and online social support scores for college friends and virtual friends. Independent t-test results indicated that there were no statistically significant differences in total online social support scores between males and females, with negligible to small effect sizes. This dissertation contributes to the literature on online social support by offering an adapted measure of online social support by source.

Advisor: Worrell, Frank C
Topological Quantum Gravity of the Ricci Flow

In this thesis we construct a family of topological quantum gravity theories with the goal of finding a regime in which these theories' localization equations are Perelman's celebrated Ricci flow equations. The natural setting for these theories is a nonrelativistic N = 2 superspace in which the spacetime is foliated by leaves of constant time. The basis for this construction is a "primitive" topological theory involving the spatial metric and its corresponding spatial diffeomorphism invariance, with N = 2 BRST symmetry. The algebra of the BRST charges is chosen so that the localization equations derived from a BRST-invariant action are flow equations and the couplings in the action are chosen so that these flow equations take the exact form of Hamilton's Ricci flow equations. Gauging spatial diffeomorphisms and foliation-preserving time reparametrizations (initially in two separate steps, but later in a single sweeping step) leads us to a set of geometric constraints that produce three distinct classes of field content in the BRST multiplets involved. Notably, the superpotential of the gauged theory is precisely Perelman's F-functional and the role of his dilaton is played by our nonrelativistic lapse function. Perelman's Ricci flow equations are then obtained as localization equations from the gauged theory in the same way as Hamilton's were obtained from the primitive theory (up to an interesting reframing), satisfying our goal.

Advisor: Hořava, Petr
Signatures from Aspherical Kilonovae and Unconventional Tidal Disruption Events

Compact objects can produce a variety of distinct observable signatures due to their extreme properties. In particular, mergers and encounters involving compact objects can produce electromagnetic (EM) transients that probe these systems and inform broader astrophysical questions. This dissertation focuses on two categories of fast and bright electromagnetic transient: kilonovae (kNe) produced by black hole - neutron star (BH-NS) and neutron star - neutron star (NS-NS) mergers, and tidal disruption events (TDEs) produced when a star is tidally disrupted by a supermassive black hole (SMBH). The introductory chapter contains a brief summary of the basic physics of these transients. We then present Monte Carlo radiative transfer (MCRT) simulations that calculate the EM emission from aspherical kilonovae. Multidimensional kilonova models can aid efforts to detect and characterize these events. The second chapter presents two axisymmetric geometric models of aspherical ejecta: an ellipsoid and a torus. These generic models capture the simplest global deviations from sphericity. The third chapter examines the kilonova signatures from the tidal dynamical ejecta of a BH-NS merger. We study the hydrodynamic evolution of the ejecta and calculate the bolometric and broadband light curves. In the fourth chapter we take an interlude and consider a potential EM signature from a different category of compact object transient: the accretion-induced collapse (AIC) of white dwarfs. The MCRT calculation in this work is based on a now-outdated ejecta model, but provides a benchmark for other potential AIC signals. We close by studying the signatures from some atypical TDEs, which might exhibit extreme properties that uniquely probe SMBHs. The fifth chapter examines the new regime of ultra-deep TDEs, in which a star is disrupted on a highly penetrating encounter with a low-mass SMBH and the disrupted debris strongly self-intersects at first pericenter passage. We determine the encounter properties, then predict a novel observable and estimate the detection rate. In the sixth chapter we present a parameter study of the statistics and signatures of TDEs from binary SMBHs.

Advisor: Kasen, Daniel
Essays on Asset Pricing, Portfolio Choice, and International Finance

This dissertation investigates a number of topics in international finance and macroeconomics, with a particular emphasis on using and adapting tools from asset pricing to this context. Chapter 1, co-authored with Pierre-Olivier Gourinchas and Hélène Rey, starts by providing an overview of the structure of the international monetary and financial system. Chapter 2 zooms in on a specific and long-standing open issue that has received a lot of attention in the international finance literature: the international portfolio choice problem, which is concerned with how investors allocate their portfolio internationally. Despite this attention, the literature has only provided limited answers to this problem in terms of resolution methods and the generality of preferences, an issue that I aim to alleviate in this Chapter. Because of its generality, the framework of Chapter 2 lends itself to several applications and extensions. Chapter 3 focuses on one main application, in which I show that the model can reproduce a number of stylized facts about the structure and dynamics of the international financial system, and in particular the role of the United States, and of asset returns in this context. Finally, Chapter 4, co-authored with Pierre-Olivier Gourinchas and Hélène Rey, focuses on the secular decline in global real interest rates, another key theme in international finance and macroeconomics. We suggest that the world real rate of interest is likely to remain low or negative for an extended period of time, and discuss a number of possible explanations, an important one being the process of deleveraging of the balance sheets of investors.

Advisor: Gourinchas, Pierre-Olivier
Essays on the Politics of Solidarity in Multiracial America

This dissertation investigates how government policies influenced U.S. minority coalition formation in the 1960s and 1970s. I argue that the key to explaining this puzzle lies in ethnic elites’ strategic calculations, as influenced by historical legacies, policy changes, and variations. Chapter 2 examines why American minority mobilization emphasized race so much in the 1960s and 1970s. In leveraging the Chinese immigrant communities along the U.S.–Canadian border on the West Coast, I found that what makes the U.S. unique is its immigration and segregation policies. Chapter 3 investigates why Asian and Latin American national origin groups joined forces as Asian Americans and Latinos in the 1960s and 1970s. I explain the welfare state as an underappreciated mechanism that mobilized these intra-racial coalitions. Chapter 4 examines why inter-racial coalitions were rare or short-lived in the 1960s and 1970s. I found that although racial minority groups are often described collectively as people of color, their issues varied because they faced different policy challenges. Additionally, the misalignment of political agendas made coordinating actions among them difficult. Taken together, these three chapters highlight how combining a historical perspective and strategic analysis offers new insights into the contingent nature of minority coalition formation in the U.S. and beyond. The rich archival, organizational, and text data I assembled provide an example of how to undertake historical research on marginalized groups in a data-intensive way.

Advisor: Pierson, Paul
Lee, Taeku
Microscale tools for improved analytical sensitivity and throughput in single-cell immunoblotting

Proteins drive nearly all cellular processes, and direct quantitation of protein abundance from single-cells is essential to understanding heterogeneous cell states.1,2 Immunoassays are widely accepted tools for performing single-cell protein detection,3,4 but protein detection by immunoaffinity alone is insufficient for precision protein characterization, as proteins with similar bindingkineticscanhavedifferentbiologicalimpacts,includingindisease.5,6,7 Toprovideacross- validation tool for protein characterization, electrophoretic cytometry immunoassays have been developed to characterize proteins by both immunoaffinity and molecular-mass through electrophoresis.8,9 Central to these assays performance is a multifunctional gel matrix that acts as a protein sieving matrix during electrophoresis and a protein scaffolding matrix during in-gel immunoblotting. In-gel immunoblotting of target proteins is widely accomplished by diffusively-driven immunoprobing, yet, this detection strategy suffers from reduced probe access to in-gel immobilized proteins via size-exclusion partitioning. Specifically, reduced probe delivery to the gel matrix in which target proteins are immobilized both (i) adversely impacts equilibrium immunocomplex formation and thus protein detection sensitivity and (ii) extends overall assay run time.In this dissertation, to improve the analytical detection capabilities and improve assay throughput in electrophoretic cytometry assays, we present methods to enhance immunoprobe delivery to hydrogel matrices, we introduce an assay design to improve throughput in single-cell immunoblotting, and we investigate reengineered sample handling designs for reduced protein losses before immobilization. Overall, we apply fundamentals in materials science, transport and reaction phenomena, and engineering design principles for the advancement of targeted protein detection assays. We see these advancements as contributing to the broader goal of improving our understanding of cell- state in healthy and disease conditions.

Advisor: Herr, Amy E
Reasoning for Representations for Learning-based Control

Data-driven machine learning approaches offer great intelligence capabilities and can help solve many challenging control problems. However, the agnostic nature of the internal representations in the learning-based control (LbC) policies makes them difficult to apply on a broad basis. Since the LbC policies are generally optimized in an end-to-end manner based on specialized domain settings, they can fail, for unknown reasons, in domains with setting variations. Moreover, a lack of understanding of the underlying logics in LbC policies also limits the transferability of the learned knowledge to different tasks./nThis dissertation presents a series of works on reasoning for representations for LbC policies, including decomposition of LbC policies, and design of interpretable and transferable representations. The thread of this dissertation is based on the roles of the representations for LbC. Three major areas are covered in this dissertation. Three major representation reasoning areas are covered in this dissertation:: (I) inside the LbC policies, (II) at the interface of the LbC policies, and (III) outside the LbC policies./nFirst, within the parameterized LbC policies, the reasoning for learning representations is developed to capture subtle features in complex scenarios. A sophisticated neural network structure is applied online to infer the task context representations in a contact-aware way; this is followed by a comprehensive investigation on design and selection of representations. The presented representations include the Gaussian mixture model, the graph neural network, and a novel history-encoding representation; the applications range from robotic manipulation to autonomous driving to human intention inference./nIn regard to the challenge of knowledge transfer, we propose a policy decomposition approach to learn attribute-wise modules separately. We design two representation frameworks at the interface of the LbC policies for the decomposition and combination of attribute-wise modules. The proposed architecture, the cascade attribute networks (CANs), and parallel attribute networks (PANs) can transfer learned knowledge between tasks and efficiently produce sophisticated LbC policies by fusing learned attribute-wise modules./nVariation between the training and deployment domains is another major reason there are LbC policy failures. In the last part of the dissertation, we focus our investigation on representation reasoning for autonomous-driving policy transfer against vehicle dynamics variation and external dynamics disturbances. We leverage the interpretable kinematic-level representations to bridge the transferring domains. We propose two external adaptation modules—model agnostic meta learning (MAML) and disturbance-observer-based (DOB) robust controllers— to achieve one-shot or zero-shot adaptation of the kinematic-level representations to the deployment domain.

Advisor: Tomizuka, Masayoshi
“The Dream Upon the Water”: Music, Ecology, and Politics in Venice ca. 1848

When Italians took to their balconies during the early COVID-19 quarantine to play music and sing together as a conscious act of solidarity, they demonstrated how sound troubles the very notion of social distance. Similar instances punctuate the intertwined histories of music and politics in the Italian peninsula—histories built on the assumption that Italian music stimulates strong emotions that forge social and political bonds. Music has long played a crucial role in framing Italian identity: as “Southerners” Italians were naturally inclined toward song and the pursuit of sensual pleasures, which made them unfit for self-governance—an excuse often wielded to support the foreign governments ruling Italy. Throughout the nineteenth century Italians appealed to their northern neighbors for material and political support for the project of unifying as a European nation-state./nI examine how Venice—as both material and poetic space—mediated sound and politics around the period of the 1848 revolution and the subsequent Habsburg reconquest. The cultural products depicting Venice as watery, unmoored, and exotic have exerted an irresistible attraction for outsiders and yet (as ecocritic Serenella Iovino recently cautioned (2016)) also concealed a threat of ecological disaster. The long nineteenth century in Venice saw momentous changes to the city’s political ecology, which disrupted the ecosystem and initiated an alienation of the people from the lagoon that recent “high water” events in the city continue to highlight. I trace how music by composers such as Giuseppe Verdi and Gioachino Rossini contributed to this mystification of Venice. In writing sound into ecocriticism, I reconstruct a frictive process in which musical form, politics, and environment are mutually constitutive./nChapter 1 considers the essentially Venetian genre of the barcarolle in relation to the city’s natural geography and built environment, focusing on the practical and discursive changes effected when the first bridge to the mainland was erected in 1846. Chapter 2 examines the music performed at the concerts mounted to raise funds for the revolutionary cause in 1848 and the journalistic discourse around those performances, to show how music helped Venetians come together, spurring them to collective actions against the Habsburgs. Chapter 3 begins from the Habsburg reconquest in 1849 and the expected return to “normalcy” in public spaces, including the opera house. The chapter juxtaposes instances of music, noise, and (resistant) silence in the public square with scenes of surveillance, mishearing, and lapsed communication in Giuseppe Verdi’s 1851 opera Rigoletto, the first major premiere of the post-revolution period. Chapter 4 focuses on the Venetian premiere of Gioachino Rossini’s 1829 opera Guillaume Tell in 1856, teasing out the attitudes to the operatic past and to tradition revealed in public reactions to Rossini’s music a quarter-century after the peak of his success.

Advisor: Smart, Mary Ann
Subverting Relations of Power through Play: Youth Agency, Collaboration, and Sociopolitical Learning in Video Games

This research examines the ingenious activity, relationships, and power dynamics that mediate learning in the video game play of youth from non-dominant communities. Through extensive analyses of a multi-sited digital ethnography, the dissertation draws on data collected from a study on the everyday media practices of working-class families, as well as analyses of youth activity on a live-streaming platform called Twitch to analyze learning in playful contexts. The three-article dissertation highlights the importance of studying youth digital activities and phenomenon across media ecologies to understand how youth develop repertoires and dispositions. By drawing on a Cultural Historical Activity Theoretical (CHAT) framework, the three articles call attention to the generative possibilities of focusing on youth agency, ingenuity, and digital resistance to counter deficit approaches around the everyday media practices of youth. The first article of the dissertation examines how a Latino boy, Richard, draws on the relational expertise of a community of gamers to learn how to exploit glitches in the games he played. Specifically, the study shows how the focal child, learns to subvert video game system designs, and argues that by deviating from the norms of play, children from non-dominant communities, like Richard, can expand and transform the learning ecologies they participate in. The second article of the dissertation examines youth activity on a live-streaming platform, called Twitch, to analyze how race discourse mediates learning in gaming spaces. This article documents how youth engage, reproduce, and/or challenge race discourse that emerges in their digital play ecologies. Finally, the third article draws on “Learning by Observing and Pitching In” (LOPI) as an analytical frame to examine how children and adults in gaming communities work as a fluid ensemble to accomplish endeavors in their online activity. The article argues that online gaming spaces are organized in ways that support collaboration amongst adults and children and, as a result, can be leveraged to develop relational equity between adult educators and their students. Overall, the three-article dissertation study has implications for how we can design robust digital and hybrid learning ecologies that center play and youths' media interest-driven practices.

Advisor: Gutiérrez, Kris D.