VictorJuiz/thesis huggingface dataset:
Rasch and Rationality: Scale typologies as applied to Item Response Theory

This dissertation consists of three papers on a central topic: the application of scale type theory to the Rasch and 2PL models. Each paper uses a different framework or set of frameworks for defining a typology of scales./nIn the first paper, I begin the analysis of scale types through the Stevens (1946) typology. I introduce the notion of difference scales using a formalization of this typology. In applying this formalization to the Rasch and 2PL models, I discuss alternate paradigms for conceptualizing the restrictive assumptions of the Rasch model./nIn the second paper, I apply the Suppes (1958) typology to the two IRT models. The conclusions here echo and reinforce those of the first chapter. In the second half of this paper, I examine other perspectives on connecting scale type theory and the Rasch model, focusing on the case of additive conjoint measurement theory./nThe first two papers consider the scale types of the odds and logit forms of the models separately. In the third paper, I look at typologies in which the model form is not a factor. The first of these is the axiomatic system of Hölder (1901), which identifies two types of quantities: magnitudes, and points on a line. The second is the homogeneity-uniqueness typology of Narens and Luce (1986), which classifies scales by the types of choices that are possible during the process of numeral assignment./nTogether, the three papers form an argument for considering psychometric properties behaving as predicted by the Rasch model as having the scale type of ratio scale attributes, while those that behave as predicted by the 2PL model have the scale type of interval scale attributes.

Advisor: Wilson, Mark R
Engineered Bio-inspired Geometrically Complex Water-repellent Surfaces and Their Applications

In nature, various plants and animals exhibit promising structurally-defined functionalities. Many discoveries of efficient water-repellent surfaces in nature have promoted research into engineering bio-inspired artificial structures with superhydrophobicity, due to their huge potential impacts on various applications, such as water-repellency, self-cleaning, condensation acceleration, and drag reduction. In particular, Nelumbo nucifera (lotus leaf), has been extensively studied in an effort to replicate its excellent superhydrophobic and low water adhesive characteristics./nAccording to the inspiration driven from the lotus leaf, the stable combination of chemical modification (e.g. hydrophobic fluoro-silane treatment) and increased surface roughness (e.g. increasing levels of structural hierarchy) is the most important factor to obtain efficient water-repellency. However, most existing manufacturing techniques using a lithographic or molding approach have typically involved only one, or occasionally two, length-scales of roughness, and have not been successful enough to mimic the complex geometries of a biological epidermis, such as the lotus leaf or taro leaf./nIn this research, in order to achieve a closer resemblance to the Nelumbo nucifera and to obtain even better water-repellent performance, we will introduce various manufacturing breakthroughs and in-depth investigations into novel micro- and nano- manufacturing processes for bio-inspired geometrically complex structures. This research on efficient water-repellency makes extensive contributions in the field of wettability, e.g. microfabrication research, biomimetics, and related fundamental wettability theories .

Advisor: Taylor, Hayden
From Pen to Podcast: Facilitating Critical Moral Reasoning and Critical Consciousness Through Constructing Narratives of Personal Conflicts

This mixed methods study investigated 10th grade students' shifts in reasoning between handwritten narratives of personal conflicts and their production of digital podcast versions of the same conflicts. Specifically, shifts in perspective, resolution, domains of social reasoning, domain coordination, and storytelling elements were compared. This study was implemented as a curriculum intervention with 32 participants in a public high school in British Columbia. Analyzing multiple narrative constructions of the same personal conflict, but within different mediums, is conceptualized as a way of stimulating and bringing into view developmental transformations, including the development of critical moral reasoning and critical consciousness. Key findings include a significant decrease in victim perspectives in the podcast format, and an increase in the use of the conventional domain in students’ resolutions of their conflicts in the podcast format. The type of characters included in students' conflicts changed between narrative and podcast, and students arrived at different types of conclusions. The podcast is proposed as a storytelling format that can target specific critical moral reasoning and critical consciousness components, such as transactive reasoning, heteroglossia, and making connections between personal and societal struggles. Implications for educators include how to identify emerging critical moral reasoning and critical consciousness skills within students' podcasts, as well as barriers that students may face in the process of coming to critical conclusions.

Advisor: Nucci, Larry
Sterponi, Laura
Singularities in U (2)-invariant 4d Ricci flow

Firstly, we analyze the steady Ricci soliton equation for a certain class of metrics on complex line bundles over K\"ahler-Einstein manifolds of positive scalar curvature. We show that these spaces admit a non-collapsed steady gradient Ricci soliton metric. In the four (real-) dimensional case, this yields a new family of non-collapsed steady Ricci solitons on the complex line bundles $O(-k)$, $k \geq 3$, over $\mathbb{C}P^1$. These solitons are $U(2)$-invariant, non-K\"ahler, and asymptotic to the the quotient of the four dimensional Bryant soliton by $\Z_k$. As a byproduct of our work we also find Taub-Nut like Ricci solitons on $\R^4$ and demonstrate a new proof for the existence of the Bryant soliton./nSecondly, we investigate the formation of singularities in four dimensional $U(2)$-invariant Ricci flow and show that the Eguchi-Hanson space can occur as a blow-up limit. In particular, we prove that starting from a class of asymptotically cylindrical $U(2)$-invariant initial metrics on $TS^2$, a Type II singularity modeled on the Eguchi-Hanson space develops in finite time and the only possible blow-up limits are (i) the Eguchi-Hanson space, (ii) the flat $\R^4 / \Z_2$ orbifold, (iii) the 4d Bryant soliton quotiented by $\Z_2$, and (iv) the shrinking cylinder $\R \times \R P^3$. It also follows from our work that in four dimensional Ricci flow an embedded two dimensional sphere of any self-intersection number $k \in \Z$ may collapse to a point in finite time and thereby produce a singularity. For $|k|\geq 3$ the singularities we construct are of Type II, yielding a new infinite family of Type II singularities. Numerical simulations indicate that their blow-up limits are the four dimensional steady Ricci solitons described above.

Advisor: Bamler, Richard
Wilkening, Jon
Bayesian experiment design and estimation for probabilistic modeling of biological systems

Computational models have emerged as a key tool to study and characterize the behavior of biological systems. In order to accurately describe biological systems, computational models need to capture inherently complex features of biological behavior, such as nonlinear and probabilistic dynamics. Probabilistic models of biological systems can account for our lack of knowledge in model structure or parameters (uncertainty), as well as the physical sources of probabilistic behavior leading to heterogeneity./nUncertainty quantification and optimal experiment design frameworks play a key role in the development of probabilistic models for biological systems, as they can enable system learning from informative experimental data by improving the accuracy of model structures and parameter estimates. Despite the extensive implementation of uncertainty quantification and experimental design frameworks in complex engineering systems, their application in biological systems has been lagging. This is because of their high computational cost, which can be further exacerbated when accounting for the large number of parameters and cellular constituents that characterize biological models. There is a need for computationally efficient tools that can capture complex biological properties to enable learning of biological systems in a systematic manner./nIn this thesis, we present novel uncertainty quantification and optimal experiment design tools that can capture complex traits of biological behavior, namely uncertainty, heterogeneity, nonlinearities, and large numbers of parameters and cellular constituents. More specifically, we introduce novel surrogate modeling methods for fast propagation of sources of uncertainty and heterogeneity, which enable the application of uncertainty quantification and optimal experiment design tools in biological systems. Subsequently, we introduce novel Bayesian methods for the estimation of genome-scale model parameters from noisy, sparse, and incomplete biological datasets. Additionally, we introduce computationally efficient methods to design experiments that yield informative data to refine parameter estimates and model structures in an offline and online manner (i.e., in the course of an experiment). The contributions of this thesis will create new opportunities for seamless implementation of uncertainty quantification and optimal experiment design for systematic and hypothesis-based modeling in biological systems.

Advisor: Mesbah, Ali
Computational Tools for Immune Repertoire Characterization and Primer Set Design

The enormous decrease in the cost of genomic sequencing over the past two decades has enabled researchers to revisit previously unaddressable questions in sequence analysis. However, this boom of genomic information has introduced new sets of problems that often demand computationally efficient methods. In this work, we describe computational tools for two such settings involving large-scale genomic data: 1) estimating copy number and allelic variation in two highly complex gene families, and 2) selective sequencing of a target genome in a complex DNA sample./nWe first describe a method that takes short reads from high-throughput sequencing and characterizes both copy number and allelic variation in the IGHV and TRBV loci. These two loci can vary extensively between individuals in copy number and contain genes that are highly similar, making their analysis technically challenging. Additionally, we have conducted the first study of a globally diverse sample of hundreds of individuals in these two loci from over a hundred populations. In addition to providing insight into the different evolutionary paths of the IGHV and TRBV loci, our results are also important to the adaptive immune repertoire sequencing community, where the lack of frequencies of common alleles and copy number variants is hampering existing analytical pipelines./nIn our second problem setting, we describe SOAPswga, an optimized and parallelized pipeline for primer design in the context of selective amplification. Unlike previous heuristic-based methods, SOAPswga uses machine learning methods to evaluate both individual primers and primer sets. Additionally, rather than brute force search for primer sets, such as in predecessor methods, SOAPswga uses branch-and-bound principles to pursue only the most promising sets. These optimizations, including the parallelization of each step, allow for a huge decrease in runtime from the order of weeks to minutes. We also discuss the results of our pipeline applied to the selective amplification of Mycobacterium tuberculosis in a sample of human blood. Lastly, we expand on the importance of this work, and in general, its potential usefulness to any setting consisting of targeted sequencing.

Advisor: Song, Yun S
Measuring Generalization and Overfitting in Machine Learning

Due to the prevalence of machine learning algorithms and the potential for their decisions to profoundly impact billions of human lives, it is crucial that they are robust, reliable, and understandable. This thesis examines key theoretical pillars of machine learning surrounding generalization and overfitting, and tests the extent to which empirical behavior matches existing theory. We develop novel methods for measuring overfitting and generalization, and we characterize how reproducible observed behavior is across differences in optimization algorithm, dataset, task, evaluation metric, and domain./nFirst, we examine how optimization algorithms bias machine learning models towards solutions with varying generalization properties. We show that adaptive gradient methods empirically find solutions with inferior generalization behavior compared to those found by stochastic gradient descent. We then construct an example using a simple overparameterized model that corroborates the algorithms’ empirical behavior on neural networks./n/nNext, we study the extent to which machine learning models have overfit to commonly reused datasets in both academic benchmarks and machine learning competitions. We build new test sets for the CIFAR-10 and ImageNet datasets and evaluate a broad range of classification models on the new datasets. All models experience a drop in accuracy, which indicates that current accuracy numbers are susceptible to even minute natural variations in the data distribution. Surprisingly, despite several years of adaptively selecting the models to perform well on these competitive benchmarks, we find no evidence of overfitting. We then analyze data from the machine learning platform Kaggle and find little evidence of substantial overfitting in ML competitions. These findings speak to the robustness of the holdout method across different data domains, loss functions, model classes, and human analysts./nOverall, our work suggests that the true concern for robust machine learning is distribution shift rather than overfitting, and designing models that still work reliably in dynamic environments is a challenging but necessary undertaking.

Advisor: Recht, Benjamin
Demmel, James
Advanced imaging methods unveil new mechanisms transcriptional regulation in the context of nuclear organization

It has long been appreciated that organization of macromolecules within the cell is paramount to proper cellular function. As the number of tools in the molecular and cell biologist’s toolbox grows, the list of ways cells achieve organization also grows. This is especially true for the process of transcription and its regulation, where the fundamental questions remain a challenge to address, but where a convergence of genetic, genomic, structural and imaging techniques offer the possibility of answers. The proper loading of an RNA polymerase on a gene requires the coordinated action of hundreds of proteins and other macro molecules, as well as cellular genome to be maintained in a topologically permissive state; yet as a system, gene regulation requires interactions to be dynamic enough to respond to the changing needs of the cell in response to internal and external ques. How a cell constructs a system that is, on the one hand robust, and on the other hand flexible remains a challenge to answer./nIn Chapter 1 of this thesis, we will introduce the study of transcription regulation as a general topic, and discuss a number of fluorescence imaging techniques that have fundamentally changed the our understanding of transcription regulation. Chapter 2 will focus on one particular aspect of cellular organization which has recently come into vogue—that of membraneless compartment formation through liquid-liquid phase separation. A thorough investigation of the literature, particularly in light of the experiments which we foreshadow and introduce in more depth in Chapter 3, suggests that much more work is needed before phase separation as a means of biological organization can become a general paradigm. Chapter 3 presents a particularly poignant example of the issues raised in Chapter 2. Using Herpes Simplex Virus as a model system because of its ability to form compartments in the nucleus, we demonstrate that recruitment of Pol II and other proteins can be explained through the availability of nonspecific binding sites rather than phase separation. Lastly, Chapter 4 will present technical findings on the optimal fluorescent dyes to use for in vivo labeling of proteins for imaging applications./nIn summary, this dissertation underscores the way in which new imaging techniques reveal new biological principles and challenge old models. It will be of great interest to watch these ideas and techniques mature beyond the work presented in this dissertation.

Advisor: Darzacq, Xavier
Tjian, Robert
Mitochondrial Segregation in Budding Yeast Gametogenesis

Cellular differentiation involves remodeling cellular architecture to transform one cell type into another. An important and conserved cellular differentiation program is gametogenesis, the process by which sexually reproducing organisms produce gametes. Gametogenesis involves specialized cell division as well as extensive cellular remodeling. Here, we investigated mitochondrial dynamics during gametogenesis in budding yeast to determine how regulators of meiotic differentiation act to control organelle morphogenesis. We found that mitochondria detach from the plasma membrane during meiosis II in a temporally controlled manner. Mitochondrial detachment is regulated by the induction of a transcription factor, Ndt80, which promotes the activation of a protein kinase, Ime2. Ime2 induces mitochondrial detachment by promoting the destruction of the mitochondria-endoplasmic reticulum-cortex anchor (MECA), which normally attaches mitochondria to the plasma membrane. Destruction of MECA involves Ime2-dependent phosphorylation and proteolysis that target both known subunits of the complex. We next investigated the fate of the mitochondrial network after its detachment. Consistent with previous studies, we found that the detached mitochondria gained associations with meiotic nuclei. By light and electron microscopy, we determined that the association between mitochondria and the nucleus is a developmentally regulated membrane contact site. Formation of the nucleus-mitochondria contact site required Ndt80 but not Ime2, indicating that the contact site is potentiated prior to destruction of MECA. We analyzed the potential involvement of two known ER-mitochondria tethers, ERMES and Ltc1/Lam6, but our data disfavor their potential roles in this process. Instead, novel factors are likely responsible for generating the nucleus-mitochondria contact site. Our study defines key mechanisms that coordinate mitochondrial morphogenesis with the landmark events of meiosis. Further, our work demonstrates that cells can developmentally regulate tethering to induce organelle remodeling.

Advisor: Ünal, Elçin
The Alchemy of Medicine: Making Doctors, Knowledge, and Drugs in Treaty-Port Shanghai, 1915-1927

This project investigates not the inexplicable cures that healed the sick in early 20th-century China, but the transformations in the hierarchies of knowledge on which Western medical authority was based. I look at simultaneously existing paradigms of authority surrounding doctors of Western medicine, scientific medical knowledge, and Chinese herbal medicine in the print media of 1920s Shanghai./nThe historical confluence of challenges to Chinese medicine and the rise of Western medicine are the backdrop of this story. The fall of the last dynasty in 1911 prompted Chinese reformers to question their guiding paradigms in all areas of life, including language and politics, science and medicine. Intellectuals like Liang Qichao condemned traditional Chinese culture, which was seen as weakening China in the face of foreign imperialism. Chinese medicine however, was not completely repudiated. For all the harsh criticism of Chinese theories of knowing the body based on concepts like yin yang, and methods of diagnosis such as pulse reading, in areas of treatment, herbal and mineral especially, doctors and patients still viewed their native medicine as retaining some value. For prior to the rise of medical schools in the mid-19th century and lab-based biomedicine in the mid-20th century, doctors of Western medicine – often portrayed as charlatans hawking unproven nostrums – struggled to respond effectively to diseases. I ask how Chinese doctors of Western medicine in Shanghai made a case for themselves as figures of authority at a time when Western medicine was ascendant yet could not offer reliable cures for many of the major diseases of the time./nDrawing on professional medical journals, popular newspapers, and legal regulations, I show how physicians presented themselves as ethical professionals; how medical journals turned subjective experience into objective scientific knowledge; and the ways professional, popular, and state reporting transformed authoritative herbs into efficacious drugs. The forms of institutional organization and knowledge production that created this medical authority simultaneously produced a whole host of tensions: between professional ethics and medical entrepreneurship; scientific knowledge that was locally contingent but sought to be globally coherent; and between authentic and commodified indigenous medicine. I argue that a particular formation of Sino-Western medicine, knowledge production, and the market in Republican Shanghai resulted in print media restructuring hierarchies of knowledge production to hinge less on asserting the inherent qualities of medical experts, knowledge, or drugs, and more on articulating the institutional processes that validated claims as an expert physician, producer of medical knowledge, and purveyor of effective medical treatments.

Advisor: Yeh, Wen-hsin
Learning to Hear: Modern Poetry's Acoustic Educations

In the lived day-to-day of literature classrooms and poetry seminars, the line between literal and figurative calls to “hear” can be notoriously hard to decipher. More often than not, the “ears” that are called upon are less metaphorical than metonymic, actual organs of audition undistinguished in language from the complex physiological and neurological processes they can potentially enable. Their repeated solicitation not only suggests but actively promotes a relationship between poetry and sound from which some readers are, by nature, excluded. This project asks what we truly need to know about hearing, language, and human physiology in order to consider new possibilities for communication about sound with respect to poetry. What do we need to change about our critical and pedagogical practice? By interrogating the hearing and learning processes of several literary figures whose lives, communities, and readerships owed much to public and personal conceptions of their “ears,” this project examines how our beliefs about hearing (born of our respective experiences with sound) impact what we think language can do. The acoustic educations formative to modern poetry, it argues, are no different from our own. What the readings of this project embody is a form of attention that might be called “distance listening”: a mode of listening and critical analysis that interrogates and makes apparent individual capacities to perceive and imagine highly particularized acoustic conditions. These are conditions not merely of learned speech but also of temporally located environments, bodies, texts, and spaces. Ultimately, this project seeks to know how we can recognize the labor and forms of access that precede individual imaginative acts. A robust and diverse readership for poetry, it contends, relies heavily on the willingness of hearing poets, scholars, and educators to resist simply seeking out or subsisting on a community of sympathetic ears.

Advisor: Falci, Eric