VictorJuiz/thesis huggingface dataset:
The Complexity of Countable Structures

We prove various results about the complexity of countable structures, both computable and arbitrary./nWe begin by investigating descriptions of countable structures in the infinitary logic Lω1ω. Given a countable structure A, we can find a sentence ϕ, a Scott sentence for A, which describes A up to isomorphism in the sense that A is the unique countable model of ϕ. We can assign a complexity, the Scott rank of A, to A; this is the quantifier complexity of the simplest Scott sentence. We investigate the Scott ranks of the models of a theory; we produce several new computable models of high Scott rank; we construct a computable group with no d-Σ2 Scott sentence; and we produce a first-order theory of Ulm type./nNext, we look at computable structures on a cone. If A is a natural structure—by which we mean an informal notion of a structure that might show up in the normal course of mathematics, and which was not constructed explicitly as a computability-theoretic counterexample—then arguments about A will generally relativize. So we can study natural structures by studying arbitrary structures relativized "on a cone". This gives us a way of making precise statements about the imprecise notion of a natural structure. We give a complete classification of the degrees of categoricity on a cone, and prove a number of results about degree spectra of relation on a cone./nThird, we investigate the deep connections between infinitary interpretations and functors. An interpretation of one structure A in another structure B induces a functor which produces copies of A from copies of B. Moreover, the interpretation induces a homomorphism from the automorphism group of B to the automorphism group of A. We show that this reverses: given a functor from B to A, or a homomorphism from the automorphism group of B to A, we can recover an interpretation. We consider the effective version of this, as well as the corresponding results for bi-interpretations./nFinally, we look at a number of different algebraic structures. We study the effectivization of extending automorphisms of fields to their algebraic closure, extending valuations to a field extension, and embedding valued fields into algebraically closed valued fields. We give a metatheorem for finding computable copies of various algebraic structures with an independence relation, such as differentially closed fields with δ-independence, with a computable basis. We show that there is a computable left-orderable group with no computable copy with a computable ordering.

Advisor: Montalban, Antonio
Silicon carbide technologies for interfacing with the nervous system

In the past couple of decades we have seen remarkable advances in the integration of biological systems with artificial ones. Our knowledge of both of these worlds has grown exponentially, and in particular our knowledge of the human body. In recent years we have been able to understand and treat diseases we never thought we would, and we have even been able to interface with the body to restore lost functions. Direct interaction with the human brain to read and write information to it has been achieved thanks to the development of neural probes. The work presented in this thesis focused on improving the performance of such probes in regards to their operational lifetime. This work begins with a description and demonstration of how silicon carbide technologies are suitable and compatible with neural probes, and is a better material choice for device insulation. Then, a fabrication method for silicon carbide based electrode arrays is presented, in which conductive silicon carbide is integrated with insulating silicon carbide to form an electrode architecture in which the only exposed material is the superior silicon carbide. Following this, in-vivo demonstration of these silicon carbide based electrode arrays is done by recording from the nervous system of an animal model

Advisor: Maharbiz, Michel M
A Framework for Integrating Statistical Modeling into a Culturally Competent Evaluation

In 2011, the American Evaluation Association published the Public Statement on Cultural Competence in Evaluation, highlighting the need for evaluators to take a culturally competent stance. While some may view this charge as primarily applicable to qualitative methods, evaluators with quantitative skillsets are critical contributors. Advances in quantitative techniques allow for statistical modeling to address nuanced questions appropriate to a culturally competent evaluation design; however, the link between cultural competence and statistical modeling remains unclear./nPrior research has discussed the need for an inquiry into if and how quantitative methods can help evaluators better respond to and engage with culture (Chouinard and Cousins, 2009). Chapter One of this dissertation responds to this need by reviewing 110 evaluation cases demonstrating culturally competent approaches and synthesizing their prevalence and use of quantitative methods. Findings discuss the predominant methods and purposes for integrating quantitative methods with culturally competent approaches. Furthermore, findings illustrate key themes for aligning quantitative practices with culturally competent approaches./nOne of the key themes from Chapter One highlighted the need for quantitative evaluation measures to better align with the cultural context of an evaluation. Therefore, Chapter Two outlines the Bear Assessment System process for creating, validating, and calibrating quantitative measures in a manner that complements a culturally competent evaluation approach. This process is explained through reflecting on the case of UC Berkeley’s Athletic Study Center evaluation in which quantitative measures of sense of belonging and self-reliance were created for both formative and summative purposes./nWhile Chapter Two explained how to create, validate, and calibrate quantitative measures, the literature still lacks a clear example of how to analyze measures to reflect cultural competence. Chapter Three extends the evaluation case presented in Chapter Two to demonstrate how an evaluator can apply the Latent Growth Item Response model (LG-IRM) to analyze longitudinal data with both statistical rigor and cultural competence.

Advisor: Wilson, Mark
Van Rheenen, Derek
Bad Timing: Cliffhangers and Historical Crisis in Nineteenth-Century Fiction

“Bad Timing: Cliffhangers and Historical Crisis in Nineteenth-Century Fiction” argues that the cliffhanger became central to the historical novel’s effort to represent historical crisis and change in the nineteenth century. In the wake of the French Revolution and Napoleonic Wars, the acceleration of technological, social, and political changes produced a general sense of historical disorientation – a sense that time itself was somehow out of joint. The historical novel sought to mediate this widespread sense of historical rupture by scrutinizing historical turning points and plotting more tangible relations between past and present, in an attempt to give coherence and meaning to bewildering historical changes. I argue that what we now call the cliffhanger was a key element of this project, because the cliffhanger offered a way to reproduce a sense of rupture and acceleration in the actual scene of reading. By dramatically halting the story to frame an imminent crisis, the cliffhanger offered an efficient means of isolating and analyzing narrative turning points. In chapters on the classical historical novel (Walter Scott), its mid-century re-configuration under the regime of realism (Charles Dickens), and its late-century heirs (the adventure fiction of Ballantyne, Haggard, and Stevenson), I argue that the cliffhanger represented a way for novelists in the nineteenth century to pose larger questions about the experience of historical time.

Advisor: Duncan, Ian
Excitatory Inputs to Starburst Amacrine Cells: Adaptation, Computations, Development

The retina in our eyes is full of tiny neuronal computers, cells with diversely elaborate dendritic arbors that transform, sort, and integrate information about light bouncing off of objects in the world. The focus of this dissertation was to understand how dendrites of one type of cell in the retina, called the starburst amacrine cell, perform computations on visual information. The starburst amacrine cell is a part of the retina’s “direction selective circuit”, a model system for studying the cellular and synaptic implementation of a neural computation. Within this circuit, the starburst amacrine cells are responsible for detecting the direction of motion in the environment—right, left, up, or down—and cueing downstream cells, which pass on this information about motion direction to the brain. To begin, Chapter I presents the recent advances in our understanding of how the direction selective circuit works. Then, the experimental investigations presented in this dissertation attempt to clarify three issues about starburst amacrine cells. First, I examined the precise role of starburst amacrine cells in the direction selective circuit by altering their response properties and investigating how the performance of the circuit changes (Chapter II). I found that perturbations to the excitatory inputs to starburst amacrine cells using either visual adaptation of the retina or a chemo-genetic manipulation substantially altered the computational output of the entire circuit. Second, I described how the cells’ excitatory synaptic inputs are organized and contribute to the cells’ computations (Chapter III). I discovered that the precise distribution of excitatory inputs to the starburst amacrine cells shapes the cells’ ability to detect motion direction. Because of the elaborate structure of the dendrites, this precise arrangement is necessary for the electrical signals coming at different times and onto different dendritic locations to be integrated together in a direction-dependent fashion. Third, I investigated the development of the excitatory inputs to starburst amacrine cells and starburst amacrine cells’ velocity tuning (Chapter IV). These preliminary experiments provide a framework for further inquiry in these areas. Together, these experiments reveal how anatomical wiring and electrical properties of neurons in the retina produce exquisite computational abilities.

Advisor: Feller, Marla B
Cortical and Striatal Circuits for Learning Adaptive Behaviors and Wireless Ultrasonic Implants for Interfacing with the Nervous System

Abstract/nCortical and Striatal Circuits for Learning Adaptive Behaviors and Wireless Ultrasonic Implants for Interfacing with the Nervous System/nby/nRyan M Neely/nDoctor of Philosophy in Neuroscience/nUniversity of California, Berkeley/nProfessor Jose M. Carmena, Chair/nBrain and nerve interface systems have shown early promise for alleviating a wide range of debilitating conditions. In the field of brain-machine interfaces (BMI), movement kinematics have been decoded from cortical neurons and used as a control signal for prosthetic devices. In the periphery, recent insights into the connection between nerves and organ systems has sparked new interest in the therapeutic potential of accessing and altering activity in peripheral nerves. Investigating fundamental mechanisms through which networks of neurons coordinate to produce adaptive responses can inform the design of next-generation nervous system interfaces. However, technological challenges must also be addressed before these systems are ready for widespread clinical adoption./nUsing a brain-machine interface paradigm, we trained rodents to volitionally modulate the activity of primary visual cortex (V1) neurons. This approach allowed us to observe the instrumental learning process in cortical networks directly, and define the relationship between neural activity and behavioral outcomes. Learning occurred in the absence of visual input, suggesting that modulations were internally driven. Similar to demonstrations of instrumental learning in other cortical areas, learning in V1 engaged and required activity in the striatum, suggesting that cortico-striatal circuits are an essential component for behaviorally-relevant adaptation of cortical outputs. Next, we investigated how factors affecting behavioral choice are represented by striatal neurons as rodents performed a two-alternative probabilistic switching task. We found a rich encoding of task parameters in the dorsomedial striatum both at the level of single neurons and neural populations. We observed activity related to animals’ confidence in the current state of the task, and found that confidence levels modulated the strength and timing of signals predicting behavioral choice. Finally, we sought to address the limitations of current methods for interfacing with the nervous system. We designed, built, and tested mm-scale wireless implants for recording electrical activity in peripheral nerves and muscles. This system, called neural dust, utilized ultrasonic backscatter as a scalable means for powering and communicating with miniaturized devices implanted deep in tissue. We showed that this system is capable of recording electroneurogram and electromyogram activity with high fidelity in living animals.

Advisor: Carmena, Jose M
Implementing Efficient, Portable Computations for Machine Learning

Computers are powerful tools which perform fast, accurate calculations over huge sets of data. However, many layers of abstraction are required to use computers for any given task. Recent advances in machine learning employ compute-intensive operations embedded in complex overall flows. Further, deployment of these systems must balance many concerns: accuracy, speed, energy, portability, and cost. Currently, for each target, a good implementation of the needed software layers requires many programmer-years of effort./nTo address this, we explore new tools and methods to amplify programmer effort for machine learning applications. In particular, we focus on portability and speed for machine learning operations, algorithms, and flows. Additionally, we wish to maintain accuracy and carefully control the complexity of the overall software system./nFirst, we motivate our approach with a case study in developing libHOG, which provides high-speed primitives for calculating image gradient histograms, where we achieve a 3.6X speedup over the state of the art. Next, in DenseNet, we enable previously prohibitively slow multiscale sliding window object detection using dense convolutional neural network features. Finally, we propose our Boda framework for implementing artificial neural network computations, based on metaprogramming, specialization, and autotuning. In Boda, we explore in depth the development of efficient convolution operations across various types of hardware. With only a few months of effort, we achieve speed within 2X of the highly-tuned vendor library on NVIDIA Graphics Processing Units (GPUs). Further, in only a few weeks, we achieve up to 30\% efficiency on Qualcomm mobile GPUs, where no vendor library exists.

Advisor: Keutzer, Kurt W
Remittance Fiction: Human Labor Export, Realism, and the Filipino Novel in English

“Remittance Fiction: Human Labor Export, Realism, and the Filipino Novel in English,” argues that anglophone writers became part of the worldwide dispersion of Filipinos through international educational exchange systems, and that their overseas literary production helped to reproduce the figure of the “overseas Filipino” as a subject and object of national development. Combining world-systems analysis with a rhetorically-oriented analysis of literary style, the dissertation pursues a double investigation. First, it constructs a genealogy of realism in the Philippine anglophone novel rooted in the twentieth-century evolution of the Philippines from an agricultural economy to a financialized economy built on labor export and migrant remittances. Second, it examines the conditions of this economic transformation through a formalist analysis of literary texts I call “remittance fiction,” that is, works produced out of the writer’s overseas experience and valorized at home as national literature./nEach chapter seeks to establish the dialectic between realism, nationalism, and the remaking of the Filipino by the state as “human capital,” by focusing on the literary remittances of Juan C. Laya, Edilberto K. Tiempo, N. V. M. Gonzalez, Nick Joaquin, Bienvenido N. Santos, Wilfrido D. Nolledo, and Ninotchka Rosca. Chapter 1 analyzes how Laya’s His Native Soil adapted the bildungsroman to develop a realist prose style capable of capturing the contradictory requirements of US-directed free trade under the commonwealth transition to independence. Chapter 2—through an analysis of Tiempo’s literary criticism, Joaquin’s The Woman Who Had Two Navels, and Gonzalez’s A Season of Grace and The Bamboo Dancers—examines the importation of New Criticism into the Philippines in the context of postwar import-substituting industrialization, a process enabled by the expatriate writer’s overseas training in creative writing through programs such as Paul Engle’s Iowa Writers’ Workshop and Wallace Stegner’s Stanford Creative Writing Program. Chapter 3 historicizes the increasing dominance of the historical novel after 1965 by situating Santos’s Villa Magdalena, Nolledo’s But for the Lovers, and Rosca’s State of War in relation to the decline of import-substitution and the rise of the new remittance economy under Ferdinand E. Marcos’s labor export program. Articulating the relations between literary and economic histories, the dissertation tells the story of how Filipino English writers imagined their relation to the nation, how the state itself envisioned them as nation-builders and transnational mediators, and how international cultural organizations provided the transpacific institutional matrix within which remittance fictions were produced and integrated into economic and literary world-systems defined by combined and uneven development.

Advisor: Butler, Judith
Lye, Colleen
Remodeling of the Retina Following Photoreceptor Degeneration That Enables Targeted Azobenzene Photosensitization

Azobenzene photoswitches confer light sensitivity onto retinal ganglion cells (RGCs) in blind mice, making these compounds promising candidates as vision-restoring drugs in humans with degenerative blindness. Remarkably, photosensitization manifests only in animals with photoreceptor degeneration and is absent in wild-type animals with intact rods and cones. While RGCs survive following photoreceptor death, they exhibit physiological changes, leading to heightened spontaneous activity and permissiveness to azobenzene photoswitch-reanimation. Here it is shown show that P2X receptors mediate photoswitch entry into RGCs where they associate with upregulated HCN channels, enabling light to control action potential firing. This remodeling is limited to morphologically identified OFF-RGCs, enabling selective and specific chemical photosensitization. This selectivity is not only for OFF-RGCs within a degenerated retina, but also displays selectivity within a focally degenerated retina, where photoreceptor death is non-uniform. Retinoic acid (RA), an important developmental morphogen, is also shown to be the signal that triggers pathophysiological retinal remodeling. Blocking RA signaling reduces remodeling and enhances light sensitivity in degenerating retinas. Enhancing RA signaling mimics pathophysiological remodeling in healthy retinas. A genetically-encoded fluorescent reporter shows increased RA signaling during degeneration. Identification of RA as the local, degeneration-dependent initiator of remodeling presents a new therapeutic opportunity for boosting low-level vision and performance of retinal prosthetics during degenerative blindness. Understanding the changes that occur in a degenerating retina and the signal for these changes has broad implications for disease-specific drug delivery.

Advisor: Kramer, Richard H
Local fishery, global commodity: Conflict, cooperation, and competition in Ghana’s coastal fisheries

A large body of research in recent decades has dramatically increased our understanding of the dynamics, challenges, and management approaches in marine fisheries commons. However, most of this research focuses on specific fisheries in a single subsector, outlining a series of recommendations to improve governance within a particular context. Yet, as most fisheries around the world do not occur within a closed context, but instead are diverse, cross-scale, dynamic, pluralistic, and resource-limited, many of these recommendations are ill-suited to their particular challenges. One of the best examples of these cross-scale resources challenges are the increasingly reported incidents between small-scale and industrial fishers. While small-scale fishers assert that conflict and competition with industrial vessels present some of the most persistent threats to fishing livelihoods, interactions are complex and may also include cooperative and compensatory dynamics. To illuminate these dynamics, I situate my case study in coastal Ghana, analyzing the characteristics, drivers, and consequences of industrial-small-scale incidents at sea. I employ both qualitative and quantitative methodologies, including key informant interviews, cross-sectional surveys, archival work, and spatial modeling. First, I use a historical database of incidents to understand the actors, characteristics, and drivers of incidents, situating them as a form of resource conflict. Further, I ground these incidents in conflict theory, outlining their contingent nature and pathways toward conflict and cooperation. Finally, I empirically assess the consequences of these incidents for small-scale fishing households and communities. Through these analyses, I aim to illuminate one of the least evidenced and theorized conjunctures in fisheries, yet one that profoundly affects the day to day lives of millions of fishers around the world.

Advisor: Brashares, Justin S.
O'Neill, Kate M.