VictorJuiz/thesis huggingface dataset:
Activist Responsibility and Social Platforms: Analyzing Billie Jean King's Furtherance of Women's Athletics Through Liberal Feminism
Keywords:  Department of Communication.
feminism
second-wave feminism
women's athletics
activist responsibility
disadvantaged social groups
Title IX
Billie Jean King
Stanford University Department of Communication
Thesis

This thesis addresses whether members of disadvantaged social groups who have access to an influential platform bear an activist responsibly for their respective community. In answering this overarching question, this thesis focuses on athletics as the platform in discussion and feminism as the mode of advocacy. Through analysis of hegemonic gender ideology in the American public sphere, brief history of women's athletics to the 1970s, and contention between second-wave feminism and women's athletics in the early years of Title IX, research supports the need for prominent female athletes to further feminist causes. Billie Jean King's relationship with both movements sheds light on the struggles faced by each, and an interview conducted for this thesis reaffirms athletes' unique social affordances and consequent social responsibility.
Advances in magnetic resonance imaging near metal
Keywords: Electrical Engineering.

It is estimated that 2.4% of the US population has an artificial hip or knee as of 2010, and the prevalence of metallic implants continues to grow. Current imaging evaluation of complications near implants relies on X-Ray, which has limited contrast in soft tissues and thus limited sensitivity for early disease. Magnetic Resonance Imaging (MRI) is a safe medical imaging modality known for its excellent soft tissue contrast, which could be a useful tool for accurate, early and non-invasive assessment of complications. However, severe magnetic field variations induced by metal often render conventional MRI techniques non-diagnostic near the implants. Multi-spectral imaging (MSI) techniques resolve metal-induced field perturbations, but they suffer from long scan times that delay their widespread clinical adoption, and residual frequency-encoding artifacts that cause resolution loss close to the metal. This dissertation focuses on techniques to improve MRI near metal in terms of scan efficiency, artifact correction and delineation of implants. First, a signal model of MSI was introduced to compactly represent the signal distribution in the spectral dimension and enable accelerations of MSI scans. The model-based reconstruction was demonstrated to provide 3-fold acceleration beyond conventional acceleration techniques including parallel imaging and partial Fourier reconstruction. Next, a deep-learning-based reconstruction was presented to reduce the reconstruction times of optimization-based reconstruction and improve the reconstructed image quality of accelerated imaging near metal. Then, the frequency-encoding artifacts induced by metal, including signal hyper-intensities, signal oscillations and resolution loss, were analyzed and alternating-gradient MSI acquisitions were introduced to correct these artifacts. Finally, a method for susceptibility mapping inside signal voids was presented to delineate the geometry and material of metallic implants.
Advancing ab initio electronic structure theory and computational methods for excited state molecular dynamics
Keywords: Chemistry.

Photochemistry studies chemical reactions caused by absorption of light. Developing theoretical and computational tools for photochemistry will not only help better understand photochemical processes such as photosynthesis and vision, but can also provide guidelines about how molecular photodevices can be better designed. Therefore, the goal of my graduate research is to develop a set of computational tools for studying photochemical processes. Physical systems have a hierarchical structure, i.e. basic particles like nuclei and electrons interact leading to the formation of molecules, and molecules interact and change conformations giving rise to chemical reactions. Naturally, the corresponding theoretical methods should also follow this hierarchy. At the bottom level, we need molecular integrals to describe different types of interactions between basic particles. I introduced the automated code engine (ACE) that generates optimized codes for computing integrals on the graphical processing units, and developed several variants of tensor hyper-contraction (THC) approximations. ACE reduces the computational prefactor of integral evaluations whereas THC reduces the formal scaling. On top of the integrals, we then need electronic structure methods to describe the energies and forces for a molecule at any given nuclear configuration; including electron correlation is the key to having an accurate description. Here, I first developed single reference THC-MP2 to capture the dynamic correlations, and then developed multi-reference THC-CASPT2 method to incorporate static correlations simultaneously. These methods were later generalized to THC-MSPT2 to enable descriptions for excited states and conical intersections, both are critical for photochemistry. Finally, given the electronic structure methods, we then need methods to explore the potential energy surfaces. In particular, critical point search methods locate the important configurations (e.g. Franck-Condon point, conical intersections), while molecular dynamics methods generate trajectories describing how the molecules move and interact with each other. By interfacing the electronic structure methods that I developed with the geomeTRIC geometry optimizer and G-AIMS non-adiabatic dynamics framework, a complete toolbox for understanding photochemistry is provided.
Advancing utilization of positron emission tomography for quantifying fluid transport and CO₂ trapping in geologic porous media
Keywords: Energy Resources Engineering.

Accurate observations and descriptions of the role of heterogeneity on water and CO2 transport and immobilization in porous and fractured geologic media are important for understanding and modeling multiphase conditions present in geologic carbon storage reservoirs. The growth in in-situ imaging has lead to remarkable advancements in understanding and quantification of this complex fluid transport behavior. Despite these advancements, commonly used imaging and experimental methods such as clinical computed tomography, micro computed tomography, nuclear magnetic resonance, and optical imaged micromodels each have limitations. Each modality faces individual challenges with observing fluid advection, dispersion, and diffusion, in 3D geologic porous media. In this work, micro-positron emission tomography (micro-PET), in combination with other imaging methods, is utilized to study a number of challenging transport problems in earth science.
Advancing x-ray diffuse scattering to probe protein dynamics
Keywords: Biochemistry.

Proteins are frequently characterized as molecular machines, with atomic-level motions driving biological function. Past decades have witnessed a dramatic increase in the tools available to probe these dynamics, but few methods enable us to resolve these collective motions with high spatial resolution. This dissertation investigates the potential of x-ray diffuse scattering from protein crystals to meet this critical need. Specifically, I review the models of correlated disorder that have previously been suggested to account for this signal and describe algorithms for processing the diffuse scattering in experimental diffraction data. These models and algorithms are applied to dissect the physical origins of the diffuse scattering observed from three protein crystals. Though considerable progress is still required for the analysis of diffuse scattering to become a routine biophysical method for studying protein dynamics, the framework and findings described in this dissertation make concrete steps toward that end.
Aerodynamic interactions in arrays of vertical-axis wind turbines
Keywords: Mechanical Engineering.

Understanding the aerodynamic interactions between turbines in a wind farm is essential for maximizing power generation. In contrast to horizontal-axis wind turbines (HAWTs), for which wake interactions between turbines in arrays must be minimized to prevent performance losses, vertical-axis wind turbines (VAWTs) in arrays have demonstrated beneficial interactions that can result in net power output greater than that of turbines in isolation. These synergistic interactions have been observed in previous numerical simulations, laboratory experiments, and field work. This dissertation builds on previous work by identifying the aerodynamic mechanisms that result in beneficial turbine-turbine interactions and providing insights into potential wind farm optimization. The experimental data presented indicates increased power production of downstream VAWTs when positioned offset from the wake of upstream turbines. Comparison with three-dimensional, three-component flow measurements demonstrates that this enhancement is due to flow acceleration adjacent to the upstream turbine, which increase the incident freestream velocity on appropriately positioned downstream turbines. A low-order model combining potential flow and actuator disk theory accurately captures this effect. Laboratory and field experiments were used to validate the model's predictive capabilities, and an evolutionary algorithm was deployed to investigate array optimization. Furthermore, changes in upstream turbine performance are related to variations in the surrounding flow field due to the presence of the downstream rotor. Finally, three-dimensional vortex interactions behind pairs of VAWTs are observed to replenish momentum in the array's wake. These effects are described along with their implications for wind farm design.
Affective influences on consumer decision making under uncertainty
Keywords: Business.

This dissertation investigates various affective influences on decision making under risk and uncertainty. The first essay of the dissertation shows that the relationship between physiological arousal and risk-taking is more nuanced than previously found. The results demonstrate that lower levels of physiological arousal increase sensitivity to expected values of risky prospects, leading to more adaptive decisions, instead of increasing or decreasing risk seeking across the board. The second essay of the dissertation elucidates how anticipated guilt can lead to choices of uncertain options over certain ones, establishing how choosing uncertain outcomes can serve as a guilt reduction mechanism. Finally, the third essay investigates neural affective correlates of consumer disengagement from consumption episodes that have uncertain rewards that are known only as they unfold over time and exhibits how data from a neural focus group can improve forecasts of market-level behavior.
Aggregated Model Spaces
Keywords:  Department of Computer Science
Machine Learning
Privacy
Knowledge Aggregation
Computer Science
Thesis

In many practical applications, machine learning is divided over multiple agents, where each agent learns a different task and/or learns from a different dataset. We present Aggregated Model Spaces (AMS), a framework for learning a global model by aggregating local learnings performed by each agent. Our approach forgoes sharing of data between agents, makes no assumptions on the distribution of data across agents, and requires minimal communication between agents. We empirically validate our techniques on MNIST experiments and discuss how AMS can generalize to a wide range of problem settings, including federated averaging and catastrophic forgetting. We believe our framework to be among the first to lay out a general methodology for “combining” distinct models.
Algorithmic mirrors : an examination of how personalized recommendations can shape self-perceptions and reinforce gender stereotypes
Keywords: Communication.

With the growing prevalence of algorithmic decision-making, scholars have become increasingly concerned about algorithmic bias, or discriminatory differences in algorithmic decisions based one's identity. The present study examines that the extent that algorithmic bias can affect perceptions of the self, as well as the extent that one's understanding of the system moderates this effect. A total of 117 women were randomly assigned to receive a personalized recommendation for a stereotypical "feminine" (i.e., nurse, librarian) or "masculine" career (i.e., lawyer, chief executive) ostensibly based on their Facebook activity. Participants' a priori beliefs about the system's objectivity, personal data collection, and certainty about how the system worked were measured before they received their recommendation. Participant's self-perceptions of masculinity, leadership ability, and self-confidence were measured after they received their recommendation, along with their beliefs about the cause of the recommendation. Women who received a stereotypical feminine career recommendation reported lower masculinity, lower leadership ability, and lower self-confidence than women who received a stereotypical masculine career. Additionally, women who received a masculine career recommendation and believed the recommendation was based on internal characteristics (i.e., internal locus) were more likely to report greater leadership ability than women who received the same recommendation but believed the recommendation was based on external factors (i.e., external locus). The likelihood of making internal locus signal attributions for their recommendation was greater for people who more actively use Facebook and who believed the system was more objective. Together, the dissertation findings suggest that people's self-perceptions can be influenced by algorithmic recommendations, and this effect is magnified by one's understanding of the system.
Algorithms for real-time time-dependent density functional theory and calculation of phase diagrams for two-dimensional phase-change materials
Keywords: Mechanical Engineering.

Two-dimensional materials have found use in a wide range of engineering applications, owing in part to their unique properties not found in the bulk and their potential to enable fabrication of devices that approach atomic sizes. The inherently quantum mechanical nature of 2D materials can be treated using density functional theory (DFT)-based methods, with some limitations that can in principle be addressed with the time-dependent formulation of DFT, known as time-dependent density functional theory (TDDFT). Here, we explore the use of DFT and TDDFT for applications of 2D materials, with two primary focuses: (1) the implementation and analysis of numerical integration schemes for time-domain TDDFT and associated applications to 2D and bulk materials properties and (2) the application of ground-state DFT to the study of thermodynamic properties of 2D materials that undergo structural phase transformations under electrostatic gating. Towards focus 1, we have implemented a variety of implicit and explicit integration schemes in the context of plane-wave real-time TDDFT and assessed the accuracy, stability, and computational cost of these methods. We find that for plane-waves, high-order explicit multi-step methods, including Adams-Bashforth and Adams-Bashforth-Moulton methods, outperform commonly-used methods including Crank-Nicolson and Runge-Kutta. We have developed a code, called rt-tddft, as an extension to the popular Quantum ESPRESSO code, which will enable researchers performing ground-state plane-wave DFT calculations to immediately benefit from our time-domain integration schemes. The code is written in object-oriented Fortran and is designed using object-oriented design patterns and built-in testing. We also apply the code to a new time-domain formulation of the adiabatic connection fluctuation-dissipation theorem (ACFDT) to compute electron correlation energies, an application especially relevant to van der Waals interactions in 2D materials systems. Towards focus 2, we have developed modeling methods to predict the phase transformation properties and phase diagrams of electrostatically-gated 2D materials. Using DFT-based calculations, we are able to predict the critical charge and critical voltage required to induce a structural phase transformation in a variety of 2D materials, and also determine how these critical values change with temperature. Using these methods, we are able to map out detailed phase diagrams for different 2D materials systems. In addition, we study the potential to use the electrostatic gating mechanism to absorb heat from the surroundings, an effect we term the electrostaticaloric effect. The methods we develop are useful for a variety of realistic engineering applications, including the use of 2D materials for applications in phase-change memory, controllable atomic-scale heat absorbers, and atomic sensors.
American-Russian Cultural Encounter in Siberia (1918-1920)
Keywords:  Stanford Global Studies
Stanford University
Stanford Global Studies
Center for Russian
East European
and Eurasian Studies
Thesis

From August 1918 to April 1920, over 9,500 American soldiers and aid workers were in Siberia as part of the Allied intervention in the Russian Civil War. Half of these soldiers came from the Phillippines, and half from the temporary Army base at Camp Fremont, CA in present day Menlo Park and Stanford University. The soldiers in Siberia had a neutral military mission, guarded the Trans-Siberian railroad, and lived in close proximity to local Russians. Consequently, there was an American-Russian cultural encounter, recorded in dozens articles, diaries, letters, and notes of Americans who were in Siberia.
Through everyday close contact, Americans evidenced more understanding of Russians. They remembered the generosity and hospitality of their hosts, the humbling experience of communicating in another language, and the differences and similarities in rituals like Easter celebrations, weddings, and going to the banya. American society plunged into the depths of the first Red Scare and America and Russia grew further apart. However, in contrast to their society back home, American soldiers and volunteer workers in Siberia bridged the gap in cultural understanding through their experiences, resulting in a shift in their perceptions of Russian identities, in communicating and building relationships with Russians, and in observing and participating in Russian rituals. In contrast to what has been called a civilizational or imperial lens, and a dialogue of superiority and inferiority, Americans displayed increasingly positive impressions of Russians the closer they were to them, while negatively perceived differences were greatest when encounters were brief or at a distance.
An Analysis of The Indian Solar Experiment
Keywords:  Program in International Relations
Indian solar experiment
Program in International Relations
Energy
Thesis

The Indian government under Prime Minister Narendra Modi has set a target to reach 100GW of solar power by the year 2022. Currently, India produces less than 15GW of solar power. This means that India needs to increase its solar output nearly seven fold: growth so rapid that it seems implausible, but cannot be ruled out as impossible. This rapid planned expansion of solar energy is known as the Indian solar initiative. In order to better analyze the future of the Indian solar initiative this thesis will examine three case studies: the first the demonetization movement of 2016, the second a comparison of India’s most successful solar parks, and the third, the China-India trade relationship. Each three of these case studies can teach something new as it applies to the solar initiative. This paper will attempt to broadly conclude that the solar experiment, while on track and currently poised for success at the 100GW solar target, the initiative will require that the trade relationship with China remain constant, that federal oversight is matched with corporate involvement, and that, above all, the price of solar power remains affordable. Additionally, while this thesis argues in the demonetization case study that the Modi Administration has the ability to take unprecedented action when deemed ‘necessary’ on projects of large size and scale, that the administration is not adequately equipped to handle the extremely difficult implementation costs that exist for projects of this scale. These are a few of the factors that can elucidate some clarity on the future of the Indian solar experiment, and that will be explored in the chapters below.
An analysis of variants present in patients with Juvenile Idiopathic Arthritis
Keywords:  Department of Biology
Biology
Computation Biology
Thesis

Juvenile Idiopathic Arthritis (JIA) is a complex genetic disease characterized by chronic inflammation of the joints. The primary molecular phenotypes include a 40-fold increase in proinflammatory cytokines such as IL-1β and IL-6. A computational analysis was conducted on a cohort of 18 patient exomes, 14 of which were accompanied with exomes of unaffected parents and siblings. Compared to a healthy control population, the patients had an enrichment of single nucleotide variants in ATN1, ZDBF2, and TNRC18 genes. A large fraction (5/14) of the patients also showed de novo variants in SIRPα, which regulates immune response suppression and phagocytosis inhibition, explaining many hallmark phenotypes of JIA.
An Exploration of Cell Cycle Regulation Mechanisms Using Myb-RFP and Polo-GFP Transgene Interactions in Drosophila melanogaster
Keywords:  Department of Biology
Biology
Molecular Genetics
Cancer Genetics
Thesis

According to the National Cancer Institute, approximately 40% of people in the US will be diagnosed with cancer at some point in their lives. As cancer has become one of the most prevalent and harmful diseases that humans face today, it has also become an area of intense research. Cancer forms through aggressive, unchecked cell division, which is often a product of the cell cycle going unregulated or being improperly regulated. The dREAM complex, or Drosophila RBF, E2F2, and Myb complex, provides essential regulation of the cell cycle during Drosophila melanogaster (fruit fly) development. The DREAM (dimerization partner (DP), RB- like, E2F and MuvB) complex in humans functions analogously, and therefore mutations in DREAM proteins are linked to many different forms of cancer in humans, making the Drosophila dREAM model of great significance in cancer research. One of the most important regulatory targets of the Drosophila dREAM complex in regards to proper cell cycle control is polo, a gene that encodes a protein kinase necessary for spindle formation and therefore proper cell cycle progression. Although it is established that polo is a target of dREAM complex regulation, the specific role that different dREAM proteins play in this regulation is not well understood. This research aims to determine how Myb, a dREAM complex activator, is able to regulate polo expression in the wing disc of third instar larvae Drosophila melanogaster. Specifically, we are asking if, in a Myb-null background, turning Myb back on later in development in the wing discs of third instar larvae will turn polo expression back on. To answer this research question, we have used a GAL4 driver system in a Myb-null background to create tissue-specific expression of Myb-RFP in varying types of wing disc cells. We then used confocal imaging to determine the resulting Polo-GFP levels in third instar wing discs. Our results demonstrate that Myb’s regulatory relationship with polo can vary in different types of cells and at different times during normal development within the wing disc, which raises future questions about how differences between cell types might play a role in this complex regulatory relationship.