VictorJuiz/thesis huggingface dataset:
Missing in action [electronic resource] : agency, race, & recognition
Keywords: Philosophy.

In an 1883 address, Frederick Douglass outlined how the escalating criminalization of black people had become a key process for sustaining a racial caste system post-slavery, acutely observing the "general disposition in this country to impute crime to color." In this dissertation, I argue that the ongoing development of the "crime to color" relationship that Douglass emphasized raises important philosophical challenges for our understanding of how intentional action unfolds in the social sphere. Contending that philosophical accounts of human agency must incorporate an analysis of sociality and power, Missing in Action: Agency, Race, & Recognition proposes two interventions. First, I argue that the conceptual relationship between "criminality" and "blackness" is more than a problem of racist concept associations, and has instead become conflated and embedded in dominant U.S. discourses and understandings. I introduce "racial conflation" as a frame through which we can analyze the persistent yoking of the concepts, "blackness" and "criminality." Racial conflation triggers others' reconstruction of black action into criminal action, and conjures fictive intentions to rationalize those reconstructions. The problem of racial conflation does not merely reflect unjust, unfair, or untrue characterizations of black people, but is instead a matter of the structure of concepts themselves, making the relationship a foundational theoretical problem for philosophy of action. Second, I build on Hegel's theory of the sociality of intention and Maria Lugones' analysis of power and agency to propose a framework for intentional action that can account for racial conflation. I argue that the intentions of black agents are vacated by others and replaced with what I describe as "phantom intentions, " or explanations constructed through the logic of racial conflation. With a specific focus on cases of black women's agentic strategies, I enlist feminist of color theory and feminist epistemology to propose a methodological framework to more effectively theorize intentional action, arguing that we must not only ask "how much" agency are subjects granted in conditions of oppression, but also "what kind" of agencies are projected onto subjects so that these conditions of oppression are rendered legitimate?.
The mission project : teaching history and avoiding the past in California elementary schools
Keywords: Education.

This three-article dissertation specifically examines one challenging element of teaching history to young children: the representation of historical violence and adversity, using fourth grade curriculum and instruction surrounding the topic of Spanish colonization of California as a case study. This era, known as the Spanish mission period in California, is a violent and controversial historical period that is recommended by California's fourth grade level history/social science standards. The topic provides fertile ground for an in-depth study of how young children are introduced to the violent past in their early academic experiences. The data in the dissertation, drawn from textbooks, classroom instruction, and field trips to historic sites, illustrate ways in which formal education manages to avoid the violence of colonialism, presenting it instead as necessary progress. The third article presents data from an Indigenous (Ohlone) led museum of California colonial history, and presents a case in which educators are able to build a counternarrative to the dominant colonial story.
Modeling and approximating non-stationarities in stochastic systems
Keywords: Management Science and Engineering.

This dissertation consists of two parts, with a central focus on modeling and approximating non-stationarities in stochastic systems. The first part revolves around the statistical and stochastic modeling of the non-stationary arrivals that serve as inputs to such systems. The second part revolves around approximating performances for stochastic systems with non-stationary dynamics or non-stationary inputs.
Modeling Cardiac Dysfunction Associated with Mutation in N-alpha-Acetyltransferase 10 (NAA10) in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes
Keywords:  Department of Biology
cardiovascular models
human induced pluripotent stem cells
NAA10
cardiovascular disease
drug discovery
Thesis

N-terminal (Nt-) acetylation is a common cotranslational protein modification found in over 80% of human proteins. A recent study identified a variant (c.128 A > C; p.Tyr43Ser) of N-alpha acetyltransferase 10 (NAA10), the gene that encodes the catalytic subunit of the primary human Nt-acetylation catalyst, as the cause of a novel syndrome characterized by cardiac dysfunction and other severe clinical features. Variants of NAA10 have also been associated with Ogden syndrome, Lenz microphthalmia syndrome, and other serious disorders, but the mechanisms that support the severe and complex phenotypes observed in patients with NAA10-associated diseases have remained unclear. Human induced pluripotent stem cells (iPSCs) provide a unique platform for studying genetic human diseases because they can be created from the somatic cells of affected patients and, consequently, contain all of the genetic components associated with the disease phenotype. This study shows that when iPSCs were reprogrammed from the peripheral blood mononuclear cells (PBMCs) of patients carrying the Tyr43Ser NAA10 variant and were differentiated into cardiomyocytes (CMs), the iPSC-CMs displayed aberrations in calcium handling and action potential measurements (i.e., arrhythmia and prolonged QT intervals) that were consistent with the patients’ cardiac symptoms. Furthermore, the abnormalities could be rescued by using CRISPR/Cas9 and ssODN-mediated gene-editing technology to restore the normal NAA10 sequence, which confirmed that the Tyr43Ser mutation is necessary for the disease phenotype. These observations establish iPSC-CMs as a powerful tool for modeling the disease. Additional investigations with this disease model will improve patient diagnosis and treatment, enable screening for drugs that reverse the disease phenotype, and advance our understanding of the mechanisms underlying related cardiomyopathies.
Modeling differential effects of health interventions across a heterogeneous population
Keywords: Management Science and Engineering.

Populations comprising individuals with varying characteristics and needs presents a challenge to public health decision making, as people may benefit from (or be harmed by) policies to differing extents. This dissertation focuses on mathematical modeling approaches to assess the differential effects of public health interventions across heterogeneous populations and inform policy decisions. First, we develop a microsimulation model to project the impact of increased meat price on dietary consumption, obesity and mortality by sex and race. We find that increased meat price would likely reduce obesity prevalence for white males, black males, and black females, far more than for white females. We also identify black males as least likely to experience gains in life expectancy from such a price increase. Next, we create a dynamic compartmental model of the population, stratified by pain, opioid use, and opioid addiction status, to estimate the ten-year impact of 11 interventions in response to the US opioid epidemic. We find that policies that reduce the prescription opioid supply may increase heroin use and reduce quality of life in the short term, but in the long term could generate positive health benefits. Policies focused on treating addiction (or mitigating its impact) improve health without causing harm, but alone, these will not stem the epidemic. A portfolio of interventions will be needed for eventual mitigation. Finally, we offer a framework for categorizing health interventions according to the expected distribution of benefit and harm to aid decision makers in identifying tradeoffs between efficiency, equity, and harm avoidance.
Modeling, estimation, and control for navigation of flexible continuum robots
Keywords: Mechanical Engineering.

Continuum manipulators are robots with long, slender, and flexible bodies that can be deformed into smooth three-dimensional curves. Their snake-like shape and intrinsic compliance make continuum manipulators useful for applications that require movement through unstructured and constrained environments. Examples include search-and-rescue, confined space inspection, and minimally invasive surgery. This dissertation addresses navigation of a flexible continuum robot to a target location. Because of the body's flexibility, accurate mechanics-based models of continuum manipulator motion are sensitive to physical parameters that must be experimentally determined and may change with time. Further, contact with the environment which is often unknown, can significantly affect the accuracy of these models. Because of these difficulties, this thesis focuses on simple, empirical models that are coupled with conservative control methods that are robust to model inaccuracy. These techniques are demonstrated on three different continuum robots: a minimally invasive surgical instrument known as a steerable needle, and two types of soft continuum robots that grow from the tip. Contributions of the thesis include (1) a new estimation method for continuum robot state, (2) design, modeling, and control of a new soft continuum robot that extends by growing from its tip, and (3) a kinematic model and planner for interactions between a soft growing robot and its environment.
Modeling of turbulent mixing and combustion at transcritical conditions [electronic resource]
Keywords: Mechanical Engineering.

The simulation of transcritical real-fluid effects is crucial for many engineering applications, such as fuel injection and combustion in internal-combustion engines, rocket motors and gas turbines. In these systems, the liquid fuel is injected into the ambient gas at a pressure that exceeds its critical value, and the fuel jet will be heated to a supercritical temperature before combustion takes place. At elevated pressures, the mixture properties exhibit liquid-like densities and gas-like diffusivities, and the surface tension and enthalpy of vaporization approach zero. In this thesis, algorithms and modeling tools are developed for the prediction of supercritical and transcritical mixing and combustion. A diffuse-interface method is developed for simulating turbulent flows at transcritical conditions. Real-fluid thermodynamics is described efficiently using the cubic equation of state. Spurious pressure oscillations associated with fully conservative (FC) formulations are addressed by a double-flux model. An entropy-stable scheme that combines high-order non-dissipative and low-order dissipative finite-volume schemes is proposed to preserve the physical realizability of numerical solutions across large density gradients. The resulting algorithms are applied to a series of test cases to demonstrate the capability in simulations of problems that are relevant for multi-species transcritical turbulent flows. The developed quasi-conservative (QC) scheme is subsequently analyzed with the traditional FC scheme for multi-species mixing problems. Through numerical analysis, it is shown that mixing processes for isobaric systems follow the limiting cases of adiabatic and isochoric mixing models for FC and QC schemes, respectively, which is confirmed by several numerical test cases. An extension to the classical flamelet/progress variable approach is developed for transcritical combustion simulations. The novelty of the proposed approach lies in the ability to account for pressure and temperature variations from the baseline tabulated values in a thermodynamically consistent fashion. Application cases relevant to rocket combustors are performed to demonstrate the capability of the proposed approach in multidimensional transcritical combustion simulations. Finally, a finite-rate chemistry model is employed in conjunction with the developed diffuse-interface method for the prediction of diesel fuel injection and auto-ignition processes. Simulations of an ECN-relevant diesel-fuel injector are performed for both inert and reacting cases at multiple operating points. The performance of the presented numerical framework is demonstrated through comparisons with available experimental data.
Modeling the stimulus dependence of the visual reading circuitry and implications for diagnosing reading disability
Keywords: Psychology.

Reading is a complex task, involving the proper function and communication of multiple neural systems. Successful reading involves the ability to efficiently integrate visual signals with the sounds of speech and the language system; a reading disorder may stem from a deficit in any part of this circuitry. This body of work focuses on the visual portion of the reading circuitry, and advocates for assessing the reading circuitry broadly, and not just a localized region of the brain. This dissertation begins by describing the methods used to collect and analyze the data. The position sensitivity of the VOTRC is reported, along with reports of stimulus-dependence. The stimulus-dependence is analyzed at the level of the voxel, and quantifications of position sensitivity and stimulus-dependency are reported for the VOTRC as well as the visual areas throughout visual cortex. These experiments establish a framework for better understanding the neural mechanisms contributing to spatial sensitivity. Quantitative measurements such as these may be useful for the diagnosis and treatment of reading disorders with deficits in the visual reading circuitry. This dissertation concludes with a review of functional and structural measurements that may help parents and educators select remediation methods for the reading impaired, with the hopes of supporting societal aims of improving literacy.
The moderates' dilemma : obstacles to mobilization against islamist extremism
Keywords: Political Science.

Why do moderate majorities often fail to coordinate opposition to extremist minorities? Transnational and local movements acting in the name of radical Sunni Islamism are at the forefront of domestic and international security concerns, yet little is known about how moderate Muslims react to extremist violence explicitly justified in the name of a shared religious faith and the circumstances under which they mobilize against it. This manuscript offers an explanation for the microfoundations of mod- erate mobilization in Indonesia, the world's largest Muslim-majority country. Using original survey data, observational data, qualitative interviews and case studies, I find that moderates fear social shaming from radicals and their sympathizers for ex- pressing anti-violent viewpoints. These anticipated reputation costs lead some to hide moderate attitudes resulting in a failure of moderates to collectively condemn violence in line with their individual beliefs, a phenomenon I call the "Moderates' Dilemma." I show that the severity of this dilemma varies by an individual's sensitivity to reputation costs and uncertainty about support for violence. These findings have significant implications for countering violent extremism globally.
Modular microring arrays for versatile in vitro recording
Keywords: Materials Science and Engineering.

Electroactive cells such as neurons and myocytes enable all of the biological pro-cesses that allow us to do, sense, and think. Nondestructive in vitro recordings of these cells are critical to deciphering the fundamental processes underpinning all of human bi-ology, understanding and treating degenerative diseases such as epilepsy, and even dif-ferentiating patient-derived stem cells for tissue transplantation and personalized medi-cine. However, the recording quality of massively parallel electrode arrays continues to be bottlenecked by poor mechanical and electrochemical coupling between the cell and the recording electrode. A key breakthrough in the field has been moving beyond planar devices and toward three-dimensional nanostructures; however, most sub-micron elec-trodes suffer from prohibitively high impedances that limit their usefulness as a biologi-cal tool. Here, we describe a modular microelectrode that decouples the active electrode from the physical sealing mechanic to achieve a breakthrough combination of high leak re-sistance and low electrochemical impedance. These tuneable microring electrodes exhibit high sensitivity even at length scales below the size of a single neuron, and can electro-porate into mammalian neurons to obtain intracellular recordings. Moreover, they are the first chip-based devices capable of performing not only current clamp, but also voltage clamp experiments. This seal-promoting geometry can be combined with chemical func-tionalization to mimic cell-to-cell junctions at the electrode interface. Using protein pho-tolithography to selectively pattern N-cadherin onto our microring electrodes, we were able to achieve intracellular recordings from mouse cardiomyocytes without the aid of electroporation. These devices recorded intracellularly for over two continuous hours—the longest uninterrupted intracellular recording reported to date. By permitting truly non-perturbative recording, this platform will enable electrophysiologists to perform extend-ed recordings that are currently impossible with destructive patch clamp techniques.
Monetary policy uncertainty and its effects
Keywords: Economics.

This thesis consists of three chapters that study the effects of monetary policy uncertainty and deviations from rule-based policy. In the first chapter, I develop an extension of the standard New Keynesian model to monetary policy regime switching to study the impact of uncertainty around the future inflation target. First, I fully characterize how the responses of current inflation and output to inflation target uncertainty depend on the monetary policy rule. If monetary policy is passive, inflation may increase far beyond the anticipated increase in the inflation target, while a strong monetary response to expected inflation results in an immediate drop in the inflation rate. Next, I derive the optimal response of the central bank, which can be achieved by adjusting the current inflation target. A central bank unwilling to adjust the inflation target can optimally adjust other policy rule parameters and can often obtain comparatively similar welfare benefits. Finally, I examine the implications of a perfectly anticipated change in the inflation target and find it is likely to generate cyclical dynamics for inflation and output under a constant policy rule. An optimal time varying policy rule or uncertainty in the period of the inflation target change eliminates cyclical fluctuations and improves welfare. In the second chapter, I apply the New Keynesian model with regime switching of the policy rule to study other dimensions of monetary policy uncertainty. I find that expectations of a regime shift in the future affect current inflation stability in the direction of the expected policy shift, but paradoxically expectations of a shift to a sub-optimal regime may result in better outcomes under the current regime due to the asymmetric effect on output and inflation stability. Additionally, I find that the central bank's first best response is to completely eliminate the uncertainty and that regime switching can only be part of an optimal policy if eventually monetary policy converges to the optimal single regime policy. In the final chapter, I construct the differences between rule-based monetary policy for multiple interest rate rules and the actual interest rates for nine countries using real-time data available to policymakers at the time. I document that more rule-like policy is associated with greater economic stability. Additionally, I find evidence that the association between rule-like policy and greater economic stability is causal by examining the timing of the structural breaks and the changes in central bank policy, using vector autoregressions, and regression specifications relying on the temporal ordering of lagged deviations from the policy rules.
Monitoring bondline integrity via embedded piezoelectric sensors [electronic resource]
Keywords: Mechanical Engineering.

Monitoring the bondline integrity of adhesively bonded joints consists one of the most critical concerns in the design of aircraft structures up to date. Due to the lack of confidence on the integrity of the bondline both during fabrication and service, the industry standards and regulations require assembling the composites or even metallic structure using the inefficient "black-aluminum" approach, i.e. drill holes and use fasteners. Furthermore, state-of-the-art non-destructive evaluation (NDE) and structural health monitoring (SHM) approaches are not yet able to provide mature solutions on the issue of bondline integrity monitoring. Therefore, the objective of this work is the introduction and feasibility investigation of a novel bondline integrity monitoring method that is based on the use of piezoelectric sensors embedded inside adhesively bonded joints in order to provide an early detection of bondline degradation. The proposed approach incorporates: (i) micro-sensors embedded inside the adhesive layer leaving a minimal footprint on the material, (ii) numerical and analytical modeling of the electromechanical impedance (EMI) of the adhesive bondline, and (iii) EMI-based diagnostic algorithms for monitoring and assessing the bondline integrity. The literature review indicates that the key parameter to identify the kissing bond is the stiffness of the boundary layer of the bondline, a thin arbitrary layer between the adhesive and adherends. A simple theoretical model and a more comprehensive finite element model was developed to assess the impedance based method. The experimental validation and assessment of the proposed approach is achieved via the design and fabrication of prototype adhesively bonded lap-joints with embedded piezoelectric sensors and a series of mechanical tests under various static and dynamic (fatigue) loading conditions. The obtained results demonstrate the potential of the proposed approach in providing increased confidence on the use of adhesively bonded joints for aerospace structures. Based on the experimental validation, the detection algorithms is developed with the validation test to demonstrate the feasibility to predict the mechanical performance of the bonded joints using the impedance information from the embedded sensor. The optimal design for sensor is also studied with a preliminary exploration on monitoring the fabrication process of the bonded joints.