VictorJuiz/thesis huggingface dataset:
The Barn and the Beast: The Queerness of Child-Animal Figurations in Scandinavian Literature and Culture

This dissertation takes as its starting point my own fascination, as well as a broader cultural fascination, with what I call child-animal figurations. I use the phrase “child-animal figurations” to refer to the range of relationships and associations between children and animals that are as prevalent in art and literature as they are in everyday life. Though these figurations are often considered “natural,” this dissertation argues that child-animal figurations can be highly charged sites for testing the limits of development, subjectivity, power, and species. I make this argument through analysis of several examples of Scandinavian literature and a Finnish documentary film. Scandinavian literature and culture offer a rich context in which to test hypotheses about child-animal figurations, not least because children and “nature”—including animals—enjoy special statuses in the Nordic countries, both in the figural traditions and in contemporary social realities. Drawing on scholarship in children’s literature, childhood studies, animal studies, and queer studies, this dissertation suggests that Scandinavian child-animal figurations provide new and critical insight for how we interpret narratives, including the all-important narrative of how—or whether—to grow up./nThe first chapter considers the critical relationship among childhood, animals, and citizenship in two canonical Scandinavian children’s texts. Drawing on Kathryn Bond Stockton’s notions of the “the child queered by innocence” and “sideways growth,” I argue the protagonists in these texts can be understood as queer child figures whose non-normative development, facilitated by the animal, presents a surprising deviation from the nation-building agendas otherwise laid out in the texts. The second chapter examines autobiographical works about childhood by three twentieth-century Norwegian authors, whose texts suggest that animals are not only good to think with but to remember with as well. I argue that the autobiographical child can be understood not only as a figure of the author’s interior or of her past, but also as a version of “sideways growth” (Stockton) in the form of a text. The third and final chapter engages with examples that test the limits of species and subjectivity, including Tove Jansson’s Moomin series, which I read through a posthumanist lens (against the grain of the humanism that dominates Jansson scholarship), and the documentary film Hobbyhorse Revolution, in which I read the Finnish girl on her hobbyhorse as a cyborg in the sense put forth by Donna Haraway. In concluding the dissertation, I argue that the common notion of the “competent child” does not go far enough in explaining what makes the Nordic child a fascinating figure, and I propose the figure of the Nordic queer child as a necessary complement to the “competent” or “autonomous” child.

Advisor: Sandberg, Mark B
A THz-Driven Electron Gun

This thesis presents the development of a THz-driven electron gun and associated beam characterization assembly. The THz gun is a 2 cell electroformed copper structure and uses a copper tip field emission cathode. The cells operate in the pi mode at 110.081 GHz and are designed to be powered by a 110 GHz gyrotron oscillator. For 500 kW of input power, the gun is expected to produce bunches of electrons accelerated to a peak energy of 365 keV. Electromagnetic simulations predict the fields on the surface of the cathode will reach 3.9 GV/m for this input power, resulting in 51 fC bunches. The beam is accelerated over a distance of 1.6 mm in the two cells./nThe gun structure and characterization assembly are designed to operate over a range of input powers beyond the nominal operating point of 500 kW. The electron beam characterization assembly consists of a focusing solenoid, a dipole-based energy spectrometer, an on-axis microchannel plate detector, and a Faraday cup. The setup is designed to measure the energy spread, beam size, and current to characterize the gun performance. Each element in the assembly was custom designed for this setup and the expected energy range of the beam. The expected performance is based on modeling of the electromagnetic performance of the cells and 3D particle simulations of the beam dynamics and transport./nFabricated gun cells were cold tested and an extensive study of cell tuning was performed. Several copper tip structures were successfully tuned using mechanical compression. This is the first demonstration of the mechanical tuning of individual W-band accelerator cavities. The effects of plating and etching were also studied. Further electromagnetic and particle modeling was performed to characterize the expected performance of the fabricated and tuned structures. One set of tuned cells was incorporated into the full assembly and cold tested under vacuum. The cell resonances occur at their expected frequencies and the performance is preserved after cycling between air and vacuum.

Advisor: Nanni, Emilio A
Van Bibber, Karl A
Incipient Anomaly Detection with Ensemble Learning

Anomaly detection techniques are important in system health monitoring applications (e.g., fault detection and disease diagnosis). By recognizing suspicious patterns in data, anomaly detection models can tell whether system has degraded from the normal operating condition into a faulty or diseased state. To avoid unnecessary losses, it is desirable to have a way to identify incipient anomalies, i.e. to detect potential problems in their early stages of development. In buildings, early detection of incipient faults can help reduce maintenance and repair costs, save energy, and enhance occupant comfort. In healthcare, if incipient diseases can be discovered early, effective treatments can be applied and can prevent diseases from progressing into more severe stages./nHowever, it is difficult to accurately identify incipient anomalies while at the same time not incurring into too many false alarms. Incipient anomalies present milder deviations compared to severe ones, and are difficult to detect and diagnose due to their close resemblance to normal operating conditions. Anomaly detection approaches based on supervised Machine Learning (ML) rely on high-quality labeled data to build accurate classifiers. However, the lack of incipient anomaly examples in the training data can pose severe risks to anomaly detection methods that are built upon ML techniques, because these anomalies can be easily mistaken as normal operating conditions./nEnsemble learning is widely applied in ML to improve model performance and to mitigate decision risks. In ensemble approaches, predictions from a diverse set of learners are combined to obtain a joint decision with lower bias and variance. Recently, various methods have been explored in literature for estimating prediction uncertainties using ensemble learning. To address this challenge of incipient anomalies, I propose in this dissertation to utilize the uncertainty information available from ensemble learning to identify potential misclassified incipient anomalies. We will show that ensemble learning methods can give improved performance on incipient anomalies and identify common pitfalls in these models through extensive experiments on two real-world applications—detection of chiller faults and diagnosing diabetic retinopathy diseases. A theoretical analysis that compares the two popular strategies for extracting uncertainty information will also be given. We will also discuss how to design more effective ensemble models for detecting incipient anomalies.

Advisor: Sangiovanni-Vincentelli, Alberto
South Vietnam: A Social, Cultural, Political History, 1963 to 1967

This dissertation explores the putative autocratic legacy of President Ngô Đình Diệm among South Vietnamese and the dynamic nature of South Vietnam’s social, cultural, and political development during the so-called interregnum period, 1963 to 1967. The years between President Ngô Đình Diệm’s First Republic government, from 1955 to 1963, and President Nguyễn Văn Thiệu’s Second Republic government, from 1967 to 1975, demarcate this distinct but misunderstood period of national development. Previously, under the leadership of President Ngô Đình Diệm and his family, domineering conservative Catholics who exhibited much enmity for Western influence amid an escalating civil war, South Vietnam experienced better security conditions, but its citizens enjoyed fewer personal freedoms and had less civic independence. The overthrow of Ngô Đình Diệm’s government engendered watershed changes. South Vietnam experienced deteriorating security conditions, but citizens enjoyed more individual freedoms and had greater civic independence. Driven by elite and non-elite domestic actors, this shift impacted various aspects of society, from sports and female gender norms to politics and the performing arts. Whereas most literature portrays the 1963 coup against Ngô Đình Diệm as throwing the country into complete chaos and engendering widespread failure for multiple years, this work highlights the coup as a point of departure for a new and creative phase of national innovation, reinventing the mid-1960s as a creative and generative phase of South Vietnamese history. An overwhelming majority of extant South Vietnamese press materials published between November 1963 and September 1967 support this study.

Advisor: Zinoman, Peter
Developing Learning Analytics to Promote Knowledge Integration in a Technology-enhanced Learning Environment

In a context where classrooms are becoming increasingly enhanced with technology, a research priority is to develop learning analytics and teacher dashboards that support pedagogical actions that leverage students’ ideas as learning resources. While the field of learning analytics has made remarkable advances in developing and applying cutting edge technologies to support teaching and learning (e.g. machine learning-based predictive analytics), more progress is needed to connect these advances to the complex task of providing teachers with insight into student thinking (Baker et al., 2020). Additionally, the widespread adoption of the Next Generation Science Standards (NGSS) and the increased use of data-generating technologies in K-12 science classrooms makes the need for learning analytics that align with research- and theory-based pedagogy especially important. Taken together, this situation calls for the development of learning analytics and pedagogical supports that align with the current education reform efforts and leverage the unique perspectives and practices of teachers and students. My dissertation project addresses this situation by investigating the research question of how to develop and evaluate learning analytics and pedagogical supports that assist diverse teachers in supporting their students to build on their developing ideas towards integrated science knowledge./nSpecifically, this design-based dissertation project uses mixed methods to develop learning analytics that support teachers in investigating their students’ developing understanding of complex ideas about energy and matter transformation in photosynthesis. Using the knowledge integration (KI) pedagogical framework, I: (a) developed an online inquiry science unit on photosynthesis; (b) developed analytics to reveal student thinking by analyzing system-logged data associated with student-generated artifacts using natural language processing and machine learning techniques; and (c) developed and refined a teacher dashboard, called the Teacher Action Planner./nWhile this dissertation project primarily focuses on a middle school science classroom using a technology-enhanced learning environment, the resulting development strategy and products have broad application across disciplinary domains, instructional contexts, and teacher and student populations.

Advisor: Linn, Marcia F
Optimization Frameworks for Fair Data-Driven Decision Making

This thesis investigates the problem of fair statistical learning. We argue that critical notions of fairness can be represented by independence constraints on certain random variables, and take the approach of approximating independence by bounding moments. We propose a hierarchical Fair Optimization (FO) framework for generalized fair decision-making, prove desirable statistical properties, and extend the framework to a number of settings, ranging from supervised learning to unsupervised learning and hypothesis testing./n/nAlgorithmic decision-making has steadily gained in prominence as more data is produced and computing resources become more abundant. However, it has been observed that these can often reflect, and perpetuate, biases apparent in the training data. To that end, we construct the FO framework as a general approach to statistical decision-making under fairness constraints. The framework revolves around bounding the moments between a ``score" function underlying the decision-making process and predefined ``protected" attributes. We prove that this framework is consistent and will thus asymptotically provide fair decision rules, and provide non-asymptotic bounds on how quickly the framework approaches truly fair decision-making rules. We also provide experimental results that show the efficacy of the FO hierarchy on a variety of datasets, and use it to construct fair, automated one-time and sequential dosage mechanisms for morphine and heparin./n/nNovel, adversarial notions of fairness are then defined for the problem of dimensionality reduction of data, and a Semidefinite Programming (SDP) relaxation of the FO hierarchy is defined that controls these notions. we provide experimental analysis, including a case study on insurance rate-setting that allows for mechanisms that are fair with respect to legally-motivated age restrictions. Similarly, we extend fairness to the problem of hypothesis testing, and make the connection between fairness and robustness in this realm. This is actuated in the form of a distributionally-robust dynamic watermarking scheme to detect attacks on dynamical systems. Finally, we extend the intuitions of data-dependent regularization underlying the FO hierarchy to design a data-dependent regularizer that promotes robustness in classifiers in the low-data regime when data lies in a low-dimensional manifold.

Advisor: Aswani, Anil J
Enabling Multi-Zone Impedance Measurements for Higher Resolution Trans-Endothelial Electrical Resistance (TEER), and Single-Cell Viscoelastic Analysis.

The spatial and temporal resolution improvements of current and future biological assays are crucial elements in our advance toward single-cell assays, by which we dissect population-level averages to better understand disease progression and treatment. In this dissertation, spatial and temporal resolution improvements are demonstrated for two platforms by implementing a multi-zone measurement approach. For the first platform, we implement a multi-zone trans-endothelial electrical resistance (mz-TEER) continuous measurement within a microfluidic platform. This has enabled us to measure four distinct TEER zones within a single sample versus measuring one bulk TEER value. This work opens the door to questions of hetero- and homogeneity, and crosstalk between the cells on each of the respective zones. I will discuss how our results, using MCF-7GFP cell monolayers, showed that we are capable of monitoring these zones independently, and provide important future objectives for biologically relevant experiments, and improvements to the platform. Secondly, using the knowledge gained from developing mz-TEER, I then aimed to improve another impedance-based microfluidic platform developed in our lab previously, visco node-pore-sensing (viscoNPS) which is capable of measuring the viscoelastic properties of single cells at a single user-defined frequency. With an improvement similar to mz-TEER, we enhanced this platform by adding multi-zone measurement capabilities supported through the development of custom hardware and software, enabling each cell to be tested at up to four user defined frequencies.

Advisor: Sohn, Lydia L
Assessing indicators of population size and causes of extinction in late Quaternary megafauna

Megafauna are ecologically important. They are ecosystem engineers that substantially modify modern ecosystems, and likely did so for prehistoric ecosystems prior to the Late Quaternary extinction (LQE) event as well. The LQE resulted in the loss of ~65% of all large mammals during an age of global climate change and human population expansion. This means that understanding the causes and ecological impacts of megafauna preceding, during, and following the LQE is important for better understanding megafauna ecology and conservation today./nTo further this understanding, here I 1) explore the developing body of indicators used for inferring historic and prehistoric megafauna abundances; 2) investigate the environmental conditions surrounding human arrival and megafauna extirpation in Brazil, and; 3) test how sensitive the Sporormiella megafauna indicator is to temperature and humidity, as these factors could confound megafaunal population-size estimates based on Sporormiella abundances./nThe first chapter reviews the many different population-size indicators used in megafauna paleoecology. and finds all have their pros and cons regarding their applicabilities towards reconstructing megafauna populations depending on the depositional environment and other taphonomic factors. A widely used indicator of relative megafauna population size is the abundance of the dung fungus Sporormiella in sediment records, despite the need for more taphonomic work necessary to more robustly relate spore abundance to megafauna abundance./nThe second chapter untangles the relationship between climate, vegetation changes, human population growth, and megafauna decline surrounding the LQE in Brazil as a case study. I found that combinations of anthropogenic, climatic, and vegetational changes are likely implicated as causal factors, but the tree factors vary in their importance for different regions of Brazil. However, human population growth prior to the megafauna extirpation stands out as most notable./nThe third chapter reports results of an experiment that tested the effects of temperature and relative humidity on Sporormiella growth. I found that humidity above 89% does not notably affect Sporormiella growth but temperature in the range of 10-40 o C is important./nIn sum, this means that there is room for development of megafauna indicators, nuances between how different LQE causes can be distinguished at finer spatial scales, and reason to suggest that past climate change may bias Sporormiella -based reconstructions of megafauna populations.

Advisor: Barnosky, Anthony D
Explorations of spin excitations and dynamics in homonuclear and heteronuclear spin-1 atomic gases

Ultracold atomic system provides us a versatile platform to address problems ranging from quasi-particle excitations supported by a variety of ground states, to cold collisions which could lead to a precise determination of interatomic molecular potential, and to atomtronics focusing on atomic analogues of electronic components. In this dissertation, I describe our efforts in exploring a wide topic range by our \Rb Bose Einstein condensate (BEC) machine and \Li - \Rb mixture machine, including magnons, which are collective spin excitations supported by Rb F = 1 ferromagnetic BEC ground state, cold elastic collisions between Li and Rb co-trapped in a spherical quadrupole trap, and Li spin dynamics in a spin bath formed by Rb.

Advisor: Stamper-Kurn, Dan
Development and Application of Bond Cleavage Strategies and A Unified Strategy Toward the Synthesis of Reverse-Prenylated Indole Alkaloids

The following dissertation discusses the development and applications of bond cleavage strategies in organic synthesis. The main focus of this work will be directed toward the diversification of unstrained saturated aza-cycles through C–C bond cleavage/functionalization. Another focus of the dissertation will be directed toward the total syntheses of reverse-prenylated indole alkaloids which feature a bicyclo[2.2.2]diazaoctane core./nChapter 1 describes our initial efforts toward the deconstructive functionalization of cyclic amines. A method for the deconstructive fluorination of cyclic amines by coupling Csp3¬–Csp3 bond cleavage with Csp3¬–F bond formation was developed. This method has been applied to the late-stage diversification of peptides to arrive at novel fluorinated peptides and mechanistic insight also led to the development of a catalytic gem-difluorination of enamides./nChapter 2 describes our efforts to arrive at a general method for deconstructive diversification of saturated cyclic amines. Notably, the combination of silver salts and persulfate oxidant allowed access to versatile halogen containing acyclic amine derivatives by sequential C(sp3)–N and C(sp3)–C(sp3) bond cleavage followed by C(sp3)–X bond formation. The alkyl halides formed in this process are versatile synthetic intermediates that can be used for a variety of processes such as skeletal remodeling, peptide diversification, and ring contraction./nChapter 3 details our efforts toward the mild peripheral functionalization of cyclic amines by leveraging inherently strained systems. Specifically, using visible light, we effect a Norrish–Yang reaction, generating N-fused bicyclo -hydroxy--lactams. The inherent strain embedded in these heterocycles can be exploited to achieve mild cross-couplings arriving at peripherally functionalized saturated aza-cycles. Notably, this work represents the first palladium catalyzed C–C cleavage/functionalization of -hydroxy--lactams./nChapter 4 describes our efforts toward the synthesis of secondary metabolites isolated from Penicillium and Aspergillus species which feature a bicyclo[2.2.2]diazaoctane core. Our unified approach resulted in the syntheses of (+)-VM55599, preparaherquamide, and premalbrancheamide as well as provide access to ketomalbrancheamide which can be elaborated to malbrancheamides B, C, stephacidin A, notoamides F, I and R, aspergamide B, and waikialoid A. Key to the success of this strategy was leveraging a common intermediate facilitated a divergent approach and forging the pentacyclic indole skeleton through a one-pot Hoffmann rearrangement followed by Fischer indole synthesis.

Advisor: Sarpong, Richmond
Alternative lengthening of telomeres in a human stem cell-derived system

Alternative lengthening of telomeres (ALT) is a DNA recombination pathway which grants replicative immortality in approximately 10% of all cancers. Despite the high prevalence of ALT in cancer, the genetics and mechanism by which cells activate this pathway are largely not understood. A major challenge in dissecting ALT is the extremely low frequency of ALT induction in genetically tractable human cell systems. Guided by the genetic lesions that have been associated with ALT from cancer sequencing studies, we genetically engineered primary human cells to deterministically induce ALT. Using this system, we demonstrate that disruption of the p53 and Rb pathways in combination with ATRX loss-of-function is, in a cell type-specific manner, sufficient to induce all hallmarks of ALT and results in functional immortalization. We demonstrate that ALT can be induced in the presence of telomerase, is neither dependent on telomere shortening nor crisis, but is rather the consequence of epigenetic changes induced by differentiation of ATRX-deficient cells.

Advisor: Hockemeyer, Dirk