VictorJuiz/thesis huggingface dataset:
Flipping the Hemoglobin Switch and Discovering Regulators Involved in Fetal Hemoglobin Reactivation

The fetal to adult hemoglobin switch is a developmental process by which fetal hemoglobin becomes silenced after birth and replaced by adult hemoglobin. Diseases caused by defective or missing adult hemoglobin, such as Sickle Cell Disease or β-Thalassemia, can be ameliorated by reactivating fetal hemoglobin. We discovered that knockdown or knockout of β-globin, a subunit of adult hemoglobin, led to robust upregulation of γ-globin, a subunit of fetal hemoglobin. This phenomenon suggested that red blood cells have an inherent ability to upregulate fetal hemoglobin in the event that adult hemoglobin is lacking./nWe developed multiple gene-editing tools in an immortalized erythroid cell model to investigate the molecular mechanisms behind the increase in fetal hemoglobin. Time-course transcriptomics identified ATF4, a transcription factor, as a causal regulator of this response. Further analysis also converged upon downregulation of MYB and BCL11A, known repressors of γ-globin, described in detail in chapter 2. Further work in chapter 3 explores other possible fetal hemoglobin regulators as discovered by CRISPRi arrayed mediated knockdown experiments. This work furthers our understanding of fundamental mechanisms of gene regulation and how cellular and molecular events influence red blood cell differentiation.

Advisor: Corn, Jacob E
Risk-Sensitive Safety Analysis and Control for Trustworthy Autonomy

Methods for managing dynamical systems typically invoke one of two perspectives. In the worst-case perspective, the system is assumed to behave in the most harmful way; this perspective is used to provide formal safety guarantees. In the risk-neutral perspective, the system is assumed to behave as expected; this perspective is invoked in reinforcement learning and stochastic optimal control. While the worst-case perspective is useful for safety analysis, it can lead to unnecessarily conservative decisions, especially in settings where uncertainties are non-adversarial. The risk-neutral perspective is less conservative and useful for optimizing the system's performance on average. However, optimizing average performance is not guaranteed to protect against harmful outcomes and thus is not appropriate for safety-critical applications./nThis thesis consists of two parts. First, we present an analytical and computational toolkit for cancer modeling and management that we have developed with cancer biologists by invoking the worst-case perspective. In addition to providing biological insights about breast cancer and theoretical insights about switched systems, this work has motivated the need for new mathematical methods that facilitate less conservative but still protective control of dynamical systems./nTowards this aim, we have devised a risk-sensitive mathematical method for safety analysis that blends the worst-case and risk-neutral perspectives by leveraging the Conditional Value-at-Risk measure. The second part of this thesis presents the mathematical development of this risk-sensitive safety analysis method. We also show its practical application to evaluating the safety of urban water infrastructure, using a numerical example that has been developed in collaboration with water resources engineers.

Advisor: Tomlin, Claire
Na:tinixwe Education as a Site for (Re)newed Words and Worlds

By utilizing Indigenous, decolonial and most importantly Na:tinixwe methodologies, this dissertation documents the ongoing settler colonial history of schooling in Na:tinixwe, charts a community vision for the education of Na:tinixwe youth, and lastly documents ongoing praxis of these community visions. The Hoopa Valley Tribe, or Na:tinixwe (Hupa people), reside in the far reaches of Northern California. Na:tinixw (Hoopa Valley) has been our homeland since time immemorial. Before the time of major European contact, around the 1850s, the Na:tinixwe lived along the Trinity River in 12 different villages. Each village was composed of different family groups. They lived their lives in the traditional Na:tinixw way, which included distinct political, social and economic systems. Education was a life-long process guided by teaching from ninisa:n, the land, kisdiya:n, elders and kixuna:y, the spirit ancestors (Nelson, 1978). In 1893 the Hoopa Valley Indian School was established by the Bureau of Indian Affairs with the mission of teaching Na:tinixwe children how to be civilized, in the hopes of killing off all that made them Hupa through military bootcamp tactics (Nelson, 1978). One major part of this was to force them to speak English only and punish any use of Na:tinixwe Mixine:whe (Bushnell, 1968). This technique of Indigenous linguistic elimination was widely employed by government funded Indian schools and reflects an incredibly important piece of the settler colonial drive to eliminate its Indigenous population (Iyengar, 2014). Following the conversion of the boarding school to a public school, in the same location, Hupa language and knowledge continued to be suppressed and marginalized while settler curriculum remained at the center. Today like many other publicly funded schools serving Native American children across the nation, Hoopa Valley Elementary School and Hoopa Valley High School are “underperforming”, underfunded and understaffed. The majority of the teachers are non-Native and Na:tinixwe traditional knowledge is highly marginalized, if present at all within the curriculum. This dissertation brings together the voice and visions of the Na:tinixwe to chart (re)envisioned pathways and praxis for education in our community.

Advisor: Baquedano-López, Patricia
The Modernist Russian Lyric Thinks Through Classical Myth

This dissertation examines three modernist Russian poets’ engagement with ancient mythology to illuminate the conceptual effects of lyric poetry. In a series of close readings, I argue that these poets (Viacheslav Ivanov, Osip Mandelstam, Joseph Brodsky) deploy a variety of mythic material and modes (Dionysian revelry, epic quests, modern centaurs) in their writings in order to perform intellectual work (historiography, philosophical inquiry, deconstruction) and ultimately reveal the lyric genre’s constitutive devices (metaphor and sound patterning, apostrophe, metonymy) to be ancient technologies of thought./nIn the process, I demonstrate that these modernist Russian lyrics reckon with – and invite us to perform – a reflexive conceptual feat. Engaging with the conditions of their own emergence, reaching for their connections with the Hellenic past, the lyrical works of Ivanov, Mandelstam, and Brodsky explore the links between classical myth and modern poetic expression, exposing the power of the poetic word to unite the fragmentary, and to make mystical the mundane. By investigating how these works each enter a mythic mode, deploy a lyrical device by which the mythic mode is thought through, and then engender a resulting conceptual effect, this dissertation proposes connections stretching from classical antiquity to the twentieth century, from structuralist studies of myth to ecocriticism to new media studies./nWhile the affinity between ancient myth and poetic expression is a well-known feature of Russian lyric modernism, this dissertation examines how these lyrical works limn their own constitutive devices as technologies of human thought and apperception. Ivanov’s, Mandelstam’s, and Brodsky’s investments in antiquity adumbrates how lyric can reflexively pursue itself as both an object and medium of thought. In this way, the poems this dissertation examines conjure myth as a resource, and invite the reader to participate in the prevailing cognitive mode they represent.

Advisor: Golburt, Lyubov
Micro Scale Lithium Ion Battery Modeling with the Finite Element Method

Novel research is currently being performed on commercialization of higher capacity anode materials. Additionally, optimized battery technology for electric vehicles puts increasing demand on faster charging protocols. Both of these demands are theoretically very achievable today, but they inevitably have shortcomings of a decreased battery cycle life and a reduction in battery performance. The shortcomings can be attributed to large mechanical stresses and the rapid growth of corrosive aging mechanisms occurring at electrode-electrolyte interfaces. This dissertation will focus on the study of these unwanted phenomena at the battery's microstructural length scale to aid current research in lithium ion battery optimization. This dissertation combines various existing works to formulate the foundation for a complete multiphysics battery model with the incorporation of corrosive reactions hindering the life cycle and performance of the battery. The reactions that are considered include the formation and growth of the solid electrolyte interphase and plated lithium metal. We will illustrate the implications and limitations of common battery modeling methods with our more detailed microstructural model of a battery cell. We use the finite element method to solve the general governing equations and implement surface reaction kinetics via appropriate Butler-Volmer expressions. We use our model to illustrate the limitations of common experimental techniques, such as the Galvanostatic Intermittent Titration Technique and the Potentiostatic Intermittent Titration Technique, which are used to determine important material transport properties. We then demonstrate how small changes in electrode particle geometry can result in large changes on the mechanical stress and the reaction rates of unwanted chemical reactions. Lastly, we will calculate sensitivity measures through a global sensitivity analysis of the finite element material parameters. These results indicate which material parameters should be experimentally verified and used cautiously in battery modeling.

Advisor: Govindjee, Sanjay
History and Its Kind: The Charge of the Other in Black Gay Men's Literatures

This dissertation, “History and Its Kind: The Charge of the Other in Black Gay Men’s Literatures,” examines understudied queer relational forms, arguing that black gay genealogies arise from non-identitarian forms of being in common. The project is organized around overlooked experiences of what I call “kind-ness,” a term that intermingles erotic acts of affirmation with eccentric feelings of like-ness and belonging. I derive this formulation from Melvin Dixon’s poem, “Blood Positive,” which stages an intergenerational dialogue between the dead and the living: “We did nothing but worship our kind / When you love as we did you will know / there is no life but this / and history will not be kind.” The challenge to “love as we did” offers an immersive yet open-ended expression of concern, and also of reading. Reading for a minor category of the embrace – that is, a romance, a fetish, a hunger – scrambles our original categories of belonging and calls forth new intimate publics. In chapters on Melvin Dixon, James Baldwin, and Samuel Delany, I analyze representations of affiliative practices that remain minor in that they have rarely themselves become the site of political organizing or identitarian formation. Whether in a fetish for waste and fingernails (as in Delany’s work), or in an erotics of sibling and daddy play (as in Baldwin’s, Delany’s, and certain aspects of Dixon’s), these authors exhibit an intense focus on relational forms that allows me to locate historically contingent strategies of survival that affirm black queer life. I show how this body of literature negotiates stylistic and attitudinal shifts brought about by various social movements across the late twentieth century, and, in so doing, alters our sense of black and gay belonging. Reading for such minor forms of kind-ness, I argue, allows us to experience black gay genealogies otherwise.

Advisor: Ellis, Nadia
Time-Course Analysis and Clustering of Gene Expression Data

High-throughput time-course studies collect measurements from samples across time. In/nparticular, longer-duration high-throughput time-course studies are becoming more common, such as in the case of 16S sequencing of bacterial communities or single-cell mRNA sequencing of developmental lineages. A common focus of these studies is on significance/ntesting per gene. However, in many settings, particularly those studying developmental processes, large numbers of genes show temporal changes, and the relevant question is instead to classify genes into different types of temporal changes. We propose a mixture-model clustering method that estimates a functional spline model for the mean of the cluster, in/norder to cluster the temporal patterns of genes independent of scale. The model allows for/na wide range of likelihood models to suit a variety of data types. In addition, this clustering/nstrategy accounts for time-course data under different experimental conditions or developmental lineages, and it provides a method for evaluating, per cluster, significant differences in temporal patterns between conditions. This allows for an integrated analysis of differential expression analysis and clustering. We demonstrate the benefits of our method using simulated data. In addition, we explore several real data sets to illustrate both the context for and the application of the mixture model.

Advisor: Purdom, Elizabeth
Reactors: A Deterministic Model of Concurrent Computation for Reactive Systems

Actors have become widespread in programming languages and programming frameworks focused on parallel and distributed computing. While actors provide a more disciplined model for concurrency than threads, their interactions, if not constrained, admit nondeterminism. As a consequence, actor programs may exhibit unintended behaviors and are less amenable to rigorous testing. The same problem exists in other dominant concurrency models, such as threads, shared-memory models, publish-subscribe systems, and service-oriented architectures.We propose “reactors,” a new model of computation that combines synchronous-reactive principles with a sophisticated model of time to enable determinism while preserving much of the style and performance of actors. Reactors promote modularity and allow for distributed execution. The relationship that reactors establish between events across timelines allows for: 1. the construction of programs that react predictably to unpredictable external events; 2. the formulation of deadlines that grant control over timing; and 3. the preservation of a deterministic distributed execution semantics under quantifiable assumptions. We bring the deterministic concurrency and time-based semantics of reactors to the world of mainstream programming languages through Lingua Franca (LF), a polyglot coordination language with support (so far) for C, C++, Python, and TypeScript. In LF, program logic is given in one or more of those target languages, enabling developers to use familiar languages and integrate extensive libraries and legacy code. The main contributions of this work consist of a formalization of reactors, the implementation of an efficient runtime system for the execution of reactors, and the design and implementation of LF.

Advisor: Lee, Edward A
Latent Variable Models: Maximum Likelihood Estimation and Microbiome Data Analysis

Data analysis often involves modeling complex relationships among many variables, some of which are unobserved. This type of analysis is usually tackled by latent variable models, which are graphical models consisting of both observed variables and latent variables. In this work, we delve into the computational aspect and the application aspect of latent variable models. On the computational side, we unify and extend stochastic gradient based maximum likelihood estimation methods for latent variable models under a framework called Hierarchical Model Stochastic Gradient Descent (HMSGD). Numerical studies have shown that certain extensions are more computationally efficient compared to the Monte Carlo Expectation Maximization (MCEM) algorithm. On the application side, we develop a non-parametric graphical model for microbiome data, and apply the framework to analyze the statistical properties of rarefaction, a popular normalization technique in microbiome data analysis. We show that rarefaction helps guarantee validity of permutation inference. We introduce the sample rarefaction efficiency index as a preliminary data-driven indicator of statistical efficiency of rarefied data compared to original data. Using the nonparametric graphical model, we propose a rarefaction-based nonparametric statistical testing procedure, the combined correlation permutation test, to assess whether library sizes are associated with microbial compositions conditioning on the grouping variable of interest. Case studies have shown that such associations are not uncommon in practice.

Advisor: Fithian, William
de Valpine, Perry
Design, Fabrication, and Assembly of Multi-chip Walking Silicon Microrobots

Microrobots can someday be used as a tool to further expand investigative capabilities-- for example, archeologists could use them to research buried cities such as the one in Tiwanaku, Bolivia, or emergency response workers could send robots ahead in search-and-rescue operations. The anatomy of a microrobot can be broken down into its body, brain and power. Typically, each subsystem is fabricated using a different process, creating the need for multi-chip assembly. Microrobots in the literature are often assembled post-process using methods such as wire bonding, silver epoxy, and flip-chip bonding. These approaches tend to be time consuming, tedious and may even harm the devices. Additionally, not all of them provide the necessary mechanical robustness needed for a moving walking microrobot./nThis work presents a zero-insertion force (ZIF) socket as a solution to achieving robust electrical, and mechanical assembly of a walking silicon microrobot. The ZIF socket and body of the microrobot are composed of various micro-electro mechanical systems (MEMS) fabricated using a three-mask silicon-on-insulator (SOI) process. First, successful MEMS-MEMS assembly using a ZIF socket is presented, as well as important design considerations. Subsequently, proof-of-concept and first results for MEMS-CMOS assembly is shown, integrating a complimentary metal-oxide semiconductor (CMOS) chip into a ZIF socket. Finally, the full system design of a walking silicon microrobot (not yet fabricated) using the Single Chip micro Mote (SCµM) CMOS chip as a brain, and a solar cell chip (Zappy2) for power is introduced.

Advisor: Pister, Kristofer SJ
A Language-Based Approach to Smart Contract Engineering

Blockchain-based smart contracts have emerged as a popular means of enforcing agreements among a collection of parties without a prior assumption of trust. However, it has proven difficult to write correct contracts that are robust when operating in the adversarial environment of public blockchains. This thesis evaluates the ability of a domain-specific contract programming language to support the expression and systematic testing of practical smart contracts. We present the design, implementation, and evaluation of Quartz, a contract language based on the state machine model of execution./nThe design and evaluation of Quartz is grounded in a suite of case study smart contracts. These are intended to span a wide range of application scenarios and design patterns encountered in practice by contract developers. The language's implementation is organized around the translation of a contract to two targets: a formal specification expressed in TLA+ and an implementation expressed in Solidity. Through its support for model checking contract specifications, Quartz enables the discovery of implementation flaws identical to those that have compromised real-world smart contracts. Moreover, its generated Solidity code imposes at most minor execution overhead compared to equivalent handwritten code. Finally, we discuss Quartz's future potential to validate contracts against economic notions of correctness, which are often central concerns in contract design yet are not addressed by current verification techniques.

Advisor: Culler, David E
Katz, Randy H
Data-driven Approaches to Spectral Gamma-ray Source Detection and Identification

The ability to detect and identify gamma-ray sources by means of analyzing gamma-ray spectra is essential for nuclear safety and security, and accurately performing these tasks in environments with varying background radiation remains a challenge. One common approach to enhancing detection capabilities is directing research and development at novel detection materials and systems. Alternatively, detection sensitivity can be enhanced by making use of more sophisticated data processing methods on existing detection systems. Leveraging advances in data analysis methods, this dissertation introduces and characterizes novel data-driven approaches to spectral detection and identification. An emphasis is made on methods that can potentially be augmented with complementary non-radiological data (e.g., video streams), with the objective of enhancing performance by constraining models using information about the local environment./nTwo general data analysis methods are examined for both detection and identification: non-negative matrix factorization (NMF) and neural networks. When applied to gamma-ray spectra, NMF yields accurate and interpretable models of background and sources using relatively few parameters. Neural networks are considered for their flexibility in design, the significant amount of active research in the area, and the ease with which models can be augmented with additional data sources. For both the NMF and neural network models, detection and identification methods are introduced, the performance of each is evaluated relative to benchmarks from the literature, and an assessment on tradeoffs, specifically as they relate to practical considerations, is discussed. The methods introduced in this work provide improvements over the examined benchmarks, and each method can be applied to existing systems. Additionally, discussion is provided on the potential to extend each method further using complementary non-radiological data.

Advisor: Vetter, Kai
Surveying the global landscape of post-transcriptional regulation

At all stages of a messenger RNA’s lifecycle, it is covered in RNA-binding proteins. These proteins regulate an RNA transcript’s splicing and processing in the nucleus, its export from the nucleus into the cytoplasm, its localization and translation in the cytoplasm, and its eventual turnover and decay. Despite knowing the identities of roughly 700 RNA-binding proteins in budding yeast, the role in RNA regulation that many of these proteins perform remains unclear. Here we present two studies that are aimed at the functional characterization of proteins that regulate post-transcriptional gene expression. In the first study, we devised a high-throughput tethering assay for the characterization of proteins on a proteome-wide scale. This novel assay provides domain-level resolution for the functional regions of proteins and identifies their regulatory activity in a quantitative manner. In the second study, we characterized the yeast RNA-binding protein Mrn1p and found that it is a dynamic regulator of post-transcriptional regulation that functions through mRNA turnover. Mrn1p is especially important in linking cell wall biogenesis with mitochondrial homeostasis, and it regulates these two cellular compartments in a manner that is responsive to carbon source and cell stress. Together, we present two studies that provide new functional information about yeast RNA binding proteins, with broad implications for a better understanding of post-transcriptional gene expression.

Advisor: Ingolia, Nicholas T