VictorJuiz/thesis huggingface dataset:
Topics in statistical learning with a focus on large-scale data
Keywords: Statistics.

The widespread of modern information technologies to all spheres of society leads to a dramatic increase of data flow, including the formation of "big data" phenomenon. Big data are data on a massive scale in terms of volume, intensity, and complexity that exceed the ability of traditional statistical methods and standard tools. When the size of the data becomes extremely large, it may be too long to run the computing task, and even infeasible to store all of the data on a single computer. Therefore, it is necessary to turn to distributed architectures and scalable statistical methods. Big data vary in shape and call for different approaches. One type of big data is the tall data, i.e., a very large number of samples but not too many features. Chapter 1 describes a general communication-efficient algorithm for distributed statistical learning on this type of big data. Our algorithm distributes the samples uniformly to multiple machines, and uses a common reference data to improve the performance of local estimates. Our algorithm enables potentially much faster analysis, at a small cost to statistical performance. Another type of big data is the wide data, i.e., too many features but a limited number of samples. It is also called high-dimensional data, to which many classical statistical methods are not applicable. Chapter 2 discusses a method of dimensionality reduction for high-dimensional classification. Our method partitions features into independent communities and splits the original classification problem into separate iv smaller ones. It enables parallel computing and produces more interpretable results. For unsupervised learning methods like principle component analysis and clustering, the key challenges are choosing the optimal tuning parameter and evaluating method performance. Chapter 3 proposes a general cross-validation approach for unsupervised learning methods. This approach randomly partitions the data matrix into K unstructured folds. For each fold, it fits a matrix completion algorithm to the rest K − 1 folds and evaluates the prediction on the hold-out fold. Our approach provides a unified framework for parameter tuning in unsupervised learning, and shows strong performance in practice.
Topology optimization of thermo-elastically damped MEMS resonators
Keywords: Mechanical Engineering.

Micro-electromechanical systems (MEMS) resonators are becoming evermore ubiquitous. The main loss mechanism in these devices is thermo-elastic dissipation (TED). In this thesis a finite element model is developed to simulate TED behavior and a topology optimization scheme is established to modify the internal structure of the resonator in an effort to reduce damping. Each element of the resonant structure is a variable of density between 0 (void) and 1 (solid). The gradients of these variables are calculated and are used to solve a strictly convex subset of the problem using the method of moving asymptotes. The element densities of the model are updated iteratively until an optimal topology is formed. The algorithm proves to be effective at mitigating the effects of TED. Optimal devices have an improvement in quality factor of nearly 10x. Devices are fabricated in single crystal silicon and tested using a lock-in amplifier. The constituent loss modes are able to be quantified experimentally and there is good agreement between modeled and tested devices. This topology optimization algorithm and other tools can be used to improve all types of MEMS resonators.
Touching heroes [electronic resource] : the homeric construction of intimacy
Keywords: Classics.

This dissertation examines the poetics of intimacy in the Iliad and the Odyssey and demonstrates that they employ an observable system when constructing close contact. It does so by first defining 'intimacy' as those moments of extreme physical and emotional closeness between characters, which it situates in archaic Greek epic. It then breaks down these encounters into their three essential elements: stance, physical connection, and verbal intercourse. Together, they make an interaction 'intimate.' Each of these elements is treated in its own chapter, which allows my dissertation to examine all the phrases and formulas that constitute them, as well as their various shades of meaning and thematic implications. Characters do not just stand near one another and touch each other with gesture and speech, they use a variety of stances and actions that, in turn, produce a myriad of effects and associations. They also make themselves vulnerable. My dissertation establishes the fullness of Homer's intimate poetics and, in doing so, brings to light the ambiguity of intimacy inherent to this system. Whether on the battlefield or at home, the poet's description of interaction links care and violence in surprising and disturbing ways.
Toward the generation of pure forebrain glutamatergic and spinal cholinergic neurons
Keywords:  Department of Biology
Neurodegenerative
induced neuronal cell
pluripotent
cholinergic
glutamatergic
neuron
Thesis

Current practices for disease modeling or drug screening for neurodegenerative genetic diseases rely on human immortalized cell lines or animal models that do not accurately represent the progression of the disease or capture the effects drugs will have in clinical trials. Human neurons induced from stem cells have been shown to accurately capture the effects the drugs will have on the diseases neurons and can serve as a reliable model for the progression of these (Jiménez-Moreno et al., 2017; Jungverdorben et al., 2017). However, current methods for obtaining human neurons for drug testing and disease modeling involve converting readily available cell types such as fibroblasts and blood cells into induced pluripotent stem cells and subsequently differentiating into neurons. These methods often involve multiple lengthy and complicated combinations of morphogens or growth factors and produce neurons at a very low efficiency. Our lab previously reported a facile and rapid method to produce induced neuronal (iN) cells by overexpressing a proneural transcription factor, NGN2, in human embryonic stem cells and induced pluripotent stem cells (Zhang et al., 2013).To determine the neuronal subtypes at a single cell level, we first performed single cells RNA-sequencing (scRNA-seq) for human embryonic stem cells, day 4 and day 28 iN cells. Two transcription factors (ISL1 and PHOX2B) were found to be upregulated in a subpopulation of iN cells which are positive for cholinergic markers such as SLC18A3 and SLC5A7. Immunofluorescence staining of ISL1 and PHOX2B confirmed the scRNA-seq results. We further confirmed overexpression of ISL1 and/or PHOX2B in Ngn2 derived iN cells is sufficient to upregulate in cholinergic genes. The cholinergic fate was partially removed by forcing the induced neurons into a frontal brain neuronal fate that showed an increase in glutamatergic markers. Through this research we have shown that ISL1 and PHOX2B are important regulators of cholinergic cell fate and can be overexpressed or removed to give the desired neuronal cell fate.
Towards a holistic language for engineering synthetic morphogenesis [electronic resource]
Keywords: Bioengineering.

Biological patterns form in a distributed manner through self-assembly and have the capacity to self-heal. The ability to engineer synthetic morphogenesis will advance our way of patterning. Here, I develop a language to facilitate the engineering of synthetic morphogenesis. This language is motivated by an exercise to design and grow a yinyang-like pattern from a single \textit{Escherichia coli} cell. The language consists of the abstraction and implementation of functions for engineering the curvature, texture, and reliability of cell lineage borders. These border functions are realized holistically, as an emergent consequence of cell physical properties such as growth rate and cell shape, as opposed to an explicit genetic system. I used the border functions to design and grow two-dimensional phases of the moon, pacmans with different size mouths, and a yinyang-like pattern. The holistic language facilitates the engineering of more complex synthetic morphogenesis than previously achieved and serves as a foundation for expanding our ability to engineer synthetic patterns.
Towards a Mexican Indigenous Party? A Study of Ethnic Party Formation and Indigenous Mobilization in 20th Century Mexico
Keywords:  Center for Latin American Studies
Stanford Center for Latin American Studies
Latin American Studies
Mexico
Indigenous issues
ethnic parties
Indigenous mobilization
20th Century Mexico
Thesis

In absolute numbers, Mexico is the country in the Western Hemisphere with the largest number of Indigenous peoples. Depending on the definition used, between ten and slightly more than twenty percent of Mexico, a nation of nearly 120 million, is Indigenous. At the same time, Mexico’s Indigenous population has historically been among the most marginalized of the country’s citizens. More than seventy percent live in poverty while also facing persistent discrimination in a nation that has historically lionized its Indigenous roots while neglecting the needs of its contemporary Indigenous population. Despite these factors, Indigenous movements and organizations in Mexico have never coalesced to form a cohesive, viable, national-level Indigenous movement, nor an ethnic political party organized around Indigenous identity and issues. This paper will explore the question of why this has been the case. This paper assesses the question through a comparative approach that considers the theory of ethnic party formation and the factors that allowed such parties to form in other Latin American countries. It then explores the nature of the relationship between Indigenous groups and the federal government in Mexico, how that relationship evolved over the last century, and how institutional and organizational factors affected the relationship and the organization of Indigenous groups themselves. It also discusses whether, given that Mexico’s Indigenous population has not thus far organized into an ethnic political party, whether this is something that should happen.
Towards clinically viable neural prostheses through innovations in neuroscience, decoders, and interfaces
Keywords: Electrical Engineering.

Millions of people in the United States live with paralysis due to spinal cord injury or neurological diseases. The motor impairment limits the patients' independence and in some cases the ability to communicate. Brain-computer interfaces (BCIs) translate signals from the brain into useful control signals, manipulating end-effectors such as computer cursors or robotic arms. BCIs can help restore lost motor capabilities and improve the quality of life for people with paralysis. Intracortical BCIs (iBCIs) have shown promising results in clinical trials, making them the prime candidate as an assistive device for people with severe paralysis, such as tetraplegia. However, for most applications iBCIs need further improvements to be suitable for clinical use. In this dissertation, I aimed to advance the main three components of the iBCI system: the neural interface, the user estimation decoding algorithm, and the user interface. I advanced the three components using multidisciplinary tools from neuroscience, statistics, and engineering. I believe that the studies which comprise this dissertation are a step forward towards the goal of clinical viability of iBCIs.
Towards Fairness in the Wild: Controlling Disparities in Machine Learning Systems with Human Interaction
Keywords:  Department of Computer Science
artificial intelligence
bias
fairness
machine learning
human interaction
Thesis

The problem of fairness in machine learning (ML) systems has become increasingly important as algorithmic decision making is permeating society, from social media applications with billions of users to the criminal justice system. We consider two aspects of fairness in ML systems that have received relatively little attention in the literature. First, many real-world ML systems are “online” and are fed data continuously over time, resulting in an amplification of initial disparities. Second, the particular demographic groups we often seek to be fair across depend on specific case-settings, and are not sufficient in capturing all possible groups that may suffer from an unfair system. We therefore present two new methods of understanding fairness in machine learning systems that interact with humans: 1. We develop a technique based on distributionally robust optimization to control for losses faced by minority groups at each time step of an online ML system, and we demonstrate improvements in minority group satisfaction in a real-world text autocomplete task, and 2. We demonstrate a clustering algorithm that groups data by a model’s expected loss, allowing human users to determine which high-loss groups present fairness concerns for the particular system. Together, these approaches allow us to address fairness in ML systems as not only just a small number of high-stakes fairness cases, but also as an inherently social problem.
Towards industry-ready high-order overset methods on modern hardware
Keywords: Aeronautics and Astronautics.

While computational fluid dynamics (CFD) has enabled a significant reduction in wind tunnel testing during the aircraft design process, the methods used in industry have largely stagnated in recent years. Traditional CFD methods are not well suited to vortex-dominated flows or flows where boundary layer transition and separation play a key role. In addition, the nature of modern high-performance computing (HPC) hardware has changed in recent years, requiring a fundamental shift in algorithm development to fully utilize the computing power available on modern clusters. This thesis presents the development of an overset CFD solver to tackle the above problems. First, the artificial boundary (AB) overset approach is presented, including a new interpolation method developed to reduce the error inherent in inter-grid interpolation. Numerical analysis and experiments are presented to show that the AB approach is more accurate and efficient than traditional methods. The second part of this thesis presents a new overset hole-cutting algorithm to reduce the overhead associated with moving overset grids. Based upon a direct cut approach, the algorithm was developed specifically to handle curved grids and to leverage the massive parallelism available on GPUs. The method is shown to be fast and robust enough to be applicable to large-scale problems of industrial interest. Finally, two large-scale, 3D, unsteady, compressible Navier--Stokes simulations are presented on both static and dynamic overset grids: the Taylor--Green vortex breakdown, and the flow around static and spinning golf balls. The Taylor--Green results are shown to agree extremely well with an `exact' solution, even on dynamic overset grids. A review of previous literature on golf ball flow physics is also presented, with the present results shown to agree well with a variety of both experimental and computational studies.
Towards Ultracold Strontium Atoms
Keywords:  Department of Physics
AMO
Physics
Quantum
Ultracold
Strontium
Thesis

Ultracold atoms give physicists a system dominated by quantum mechanical effects with considerable experimental control, and as such are used for quantum simulation and precision measurement experiments. In order to get atoms down to ultracold temperatures (nanokelvin), many different techniques and stages are required. In this thesis, we present two different developments towards obtaining ultracold strontium for precision measurement purposes. We frequency lock three lasers used in the laser cooling process to a strontium cell. We explore painted potential evaporative cooling techniques and calculate the micromotion for different modulation frequencies.
Towards understanding human strategies for encoding robot manipulation skills
Keywords: Aeronautics and Astronautics.

Enabling robots to perform tasks in unstructured, human environments has been a long standing vision of roboticists for decades. Some mobile platforms are already operating in these environments, such as autonomous robot vacuums and telepresence robots. In industrial settings, robots perform many manipulation tasks such as welding and handling and transporting objects, however, in these settings, the environment is very structured and the position and orientation of obstacles and work pieces are known with high accuracy. In unstructured human environments, few practical applications of robots performing manipulation tasks exist yet, especially for constrained motion, assembly-type tasks that require forming contact relationships to perform the task. Due to uncertainty in object poses and geometry in unstructured environments, it is essential that the robot complies with object constraints to perform the task and ensure safe operation. This thesis presents work towards developing compliant, human-inspired manipulation skills in task space for robots operating in unstructured environments that are able to accommodate uncertainty and adapt to environmental perturbations. To develop a framework for programming compliant manipulation primitives, we study how humans use contact relationships and compliance while performing insertion-type tasks in a haptic simulation environment. The analysis from the haptic simulation experiments motivates subsequent studies in the physical environment of how humans use contact force information to perform a basic constrained task and combine several primitives for a more complex task. We use insights gleaned from the human experiments to develop robot contact primitives to perform basic tasks and networks of contact primitives to encode more complex skills. The robot skills are encoded at the task level, which inherently enables robot skills to be transferable between robot platforms. Additionally, we use the operational space whole body control architecture which enables handling task and whole body motion coordination while in contact under various constraints within a unified and general form. The contact primitives are developed for tasks where the robot has already firmly grasped an object and uses contact sensing, not relying on any visual information. This thesis also presents work on developing perception primitives using vision-based algorithms to grasp objects and identify visual features to parameterize motion primitives for manipulating simple constrained objects.
Towns in Transition: Kern County, CA as a Case Study for Justice Considerations in Decarbonization
Keywords:  Earth Systems
earth systems
Bill Lane Center
American West
Kern County
renewable energy
oil and gas production
politics
public opinion
environmental justice
environmental policy
Thesis

The 2016 presidential election revealed the political power of discourse surrounding the collapse of coal towns. In my research, I investigate the future of towns reliant on another geopolitically potent fossil fuel resource: oil. Kern County, California has some of the oldest oilfields in the nation, and typically supplies about 75% of the oil consumed in California. Unstable oil prices have caused county budget crises and plagues of unemployment. At the same time, the statewide policy push toward renewable energy has jumpstarted the solar sector in Kern County. My research takes an ethnographic and economic perspective in order to understand how the two energy industries interact in the community. The goal of the project is to build a better understanding of the cultural effects of these industries, both for academic purposes and concerned citizenry. Through a range of interviews with stakeholders from the oil and solar industries, local government and social impact sector, themes emerged surrounding the normalcy of boom-bust cycles, solar as an economic growth area non-competitive with oil, cultural resentment tied to energy policy, and complicated environmental and equity issues. Some indicators, such as the fairly comparable nature and distribution of work in oil and solar, support the idea that solar can help pave the way for smooth local transitions in a decarbonizing economy. Other considerations, such as complicated property tax schemes, reveal challenges that merit more policy attention as we move toward further decarbonization. Finally, I examine how both these social and economic indicators fulfill the goals of justice in the transition to a low carbon economy. To do so, I examine the Kern County case study under three emerging frameworks: energy justice, just transition, and climate policy equity.
Tracing the Arctic regions : exploring ice and time in nineteenth-century photographs of Greenland
Keywords: Art and Art History.

"Tracing The Arctic Regions: Exploring Ice and Time in Nineteenth-Century Photographs of Greenland" is a study of a single, rare photographic book. Created by the American marine painter, William Bradford, The Arctic Regions was a lavish publication that paired the artist's narrative of an audacious art expedition to Greenland with 141 photographs taken to document the journey. This dissertation treats these images both as traces of real things—the people, animals, and ice that existed on the western coast of Greenland in the summer of 1869—and as expressions of how nineteenth-century Americans understood natural history and their place on its lengthening arc. Case studies of specific photographs show how images of a world that seemed strange and remote helped Americans to understand their home environments and the rights of others living within them. With attention to distant and often-marginalized subjects, "Tracing The Arctic Regions" is a study of how different kinds of looking—close looking, past looking, and environmental looking—can generate new perspectives in art history in an age of changing climate.