VictorJuiz/thesis huggingface dataset:
Building informative priors for the subsurface with generative adversarial networks and graphs

Uncertainty quantification of flow in porous media in the subsurface is important for applications such as aquifer management, CO2 storage, hydrocarbon production and contaminant transport modeling. The main goal of this dissertation is to develop new approaches to build fast and geologically consistent priors for the subsurface. We first review the physics of computational sediment transport and the consequences for simulation in different depositional environments. A comparison of a data set of 110 modern analogs is made with a large number of Delft3D realizations of river deltas using the channel networks as a framework. Because of the prohibitive computational cost associated with using computational hydrodynamics on geological time scales, it is necessary to speed up such experiments significantly or to somehow extract the essence of the information. One possibility is to use the final output as training images. Thus, a Generative Adversarial Network, which is a modern family of generative machine learning models, is here trained using a data set of satellite images of river delta networks. These types of methods hold much promise for the future but are shown to have limitations when realizations need to be generated in data-dense environments. As an alternative to artifical neural networks, which require large amounts of training data, we propose a computationally cheaper and grid-free alternative, namely the framework of spectral graph theory. The mapped graph Laplacian spectrum is shown to hold strong discriminative power both for real and synthetic river deltas, digital rock samples and heterogeneous porous media. We argue that there should be done more research on generating such geological graphs directly based on prior distributions of more detailed geological patterns.

Keywords: Energy Resources Engineering.
Advisor: Mukerji Tapan
Caers Jef 
Kitanidis P. K. (Peter K.)
Building the Mothership: “School Bussing” on Public Transportation

This thesis is about the beautiful youth of San Francisco, specifically the youth of Sunnydale and Bayview-Hunters Point. It amplifies their voices, brilliance, and experiences taking public transportation to and from school.
Please copy and paste this URL into your browser to watch the full abstract on YouTube:
https://youtu.be/Ma6Xcxb1DiU
This thesis was finished during the 2020 Pandemic COVID 19. The author finished it under great duress and personal struggle. The author finished it while watching the world finally acknowledge the cries of Black and Brown folks around the world.
Black Lives Matter. Love Heals All. Change Must Come. Listen. Empower. Envision. Dream. Share. Speak. Stand. Sing. Be You. Love Difference. See HUMANITY.
Thank you for your time <3

Keywords: Science Technology and Society
education
students
Stanford University
racism
school
mothership
mothership connection
P-Funk
Parliament Funkadelic
Parliament Funk
Afrofuturism
bussing
gentrification
white flight
urban renewal
Japanese
Fillmore
Sunnydale
Bayview-Hunters Point
Bayview
San Francisco
Black Lives Matter
Black
white
Latin
Chinese
Filipino
Elderly
Children
Mothers
User Interface
design
love
empathy
empowerment
adolescent development
youth
music
singing
voice
elderly
senior citizen
generational divide
culture
cultural understanding
cultural competence
code switching
mixed kids
mixed children
mixed
multicultural
Thesis
Advisor: Shanks Michael
Camera systematics and three-point correlations in modern photometric galaxy surveys

The goal of modern cosmology, broadly speaking, is to understand the behavior of the Universe at large scales, including the evolution of dark matter and dark energy over cosmic time. In the context of the modern paradigm of a universe dominated by dark energy and cold dark matter (LCDM), the goal is to detect deviations from LCDM predictions (new physics), and in the absence of those, to infer the value of the LCDM parameters. Advances this endeavor will require both improved constraints on systematic errors in raw astronomical data as well as improved statistical methods for extracting cosmological information from galaxy catalogs. Toward these ends, the first half of this thesis discusses methods for improving our ability to make precise and accurate measurements of galaxies in the universe using astronomical CCD imaging cameras. The second half of this thesis discusses a novel application of a statistical probe of the cosmic web of dark matter, the galaxy three-point correlation function, to photometric galaxy surveys, that allows us to extract more information of cosmological interest from the observed galaxy distribution. Both lines of research discussed in this thesis will be useful in future analyses of data from upcoming optical galaxy surveys, including the Large Synoptic Survey Telescope.

Keywords: Physics.
Advisor: Roodman Aaron J. (Aaron Jay)
Kuo Chao-Lin (Physics professor) 
Wechsler Risa H. (Risa Heyrman)
Can We Predict the Returns of Crypto-Currencies?

In this thesis I investigate the extent to which we can predict the market outcomes of cryptocurrencies. I focus on the two currently most prominent cryptocurrencies: Bitcoin and Ethereum. In the first part of the thesis I investigate whether the price levels of Bitcoin and Ethereum satisfy the weak form of the Efficient Market Hypothesis. I find evidence of weak-form efficiency in the market for cryptocurrencies. In the second part of the thesis I ask whether cryptocurrencies are viewed as an hedging vehicle against the mainstream economy. To answer this question I explore the association between market outcomes for Bitcoin and Ethereum and the Yield Curve. I find limited evidence of an association between the cryptocurrencies market and the Yield Curve. In the third part of the thesis I ask whether the market for cryptocurrencies is driven by noise traders. To answer that I explore the association between market outcomes for cryptocurrencies and qualitative information from Google searches. I find evidence of strong predictability of the price and transaction volume of Bitcoin by indexized Google searches, suggesting that the fashionability and popularity of Bitcoin go hand in hand.

Keywords:  Public Policy Program
Stanford University
Humanities and Sciences
Public Policy Program
Bitcoin
Ethereum
Thesis
Advisor: Athey Susan
Can You, and Should You, Buy an Innovation Hub?

This paper offers some of the first empirical analysis on the impact of innovation hubs on firm and local performance. The Silicon Valley innovation hub is frequently cited as evidence for the success innovation hubs bring through spillover effects which boost local economies. I exploit Microsoft’s 1979 relocation from Albuquerque, New Mexico, to Bellevue, Washington, to analyze the effect of the Seattle innovation hub on its local economy. Using a difference-in-difference approach with quasi-synthetic controls, I find three main results. First, there is no strong evidence for Microsoft triggering the development of a Seattle innovation hub. Second, to the extent to which the Seattle Hub exists, it does not perform significantly better when looking at firm and local performance. Finally, there is evidence that innovation hubs incur higher rent that potentially constrains growth.

Keywords: Department of Economics
innovation hub
agglomeration
externalities
firm performance
urban economics
local performance
Microsoft
spillover effect
Thesis
Advisor: Bloom Nicholas
Capturing atomic-level mechanisms for membrane transport and signaling with biomolecular simulation

Proteins embedded in cell membranes translate a broad range of environmental cues---including the presence of nutrients, drugs, ions and photons---into molecular signals to induce appropriate cellular responses. Membrane proteins thus represent a control panel of the cell and constitute key drug targets for the treatment of a range of diseases. Designing medications to effectively modulate these proteins, however, remains exceedingly challenging and would benefit dramatically from an atomic-level understanding of how these proteins work. Here, I have used molecular dynamics (MD) simulations---which describe how every atom in a biological system evolves with high resolution in space and time---to reveal functional mechanisms for transporters and receptors, two essential classes of membrane proteins. This approach allowed us to address several long-standing questions in molecular biology. For example, we captured the complete process of substrate translocation through an alternating-access membrane transporter. These simulations, which revealed structural rearrangements in the protein that control substrate passage across the membrane as well as the driving forces underlying those transitions, suggest a structural foundation for the design of highly specific and more efficacious transporter-targeted medications. We also revealed the mechanism by which G protein--coupled receptors stimulate arrestins, intracellular regulators of cell signaling. By identifying atomic-level interactions at the GPCR--arrestin interface that drive arrestin activation, we provide a framework for designing drugs that could selectively block or stimulate arrestin signaling, thereby reducing unwanted side effects. In each study, we worked closely with our experimental collaborators to validate predictions derived from our computational results.

Advisor: Dror Ron
Fordyce Polly 
Kobilka Brian K.
Carbon monoxide gas diffusion electrolysis for the production of concentrated C2 products with high single-pass conversion

Anthropogenic climate change will cause irreparable damage to the environment if measures are not taken to abate the emissions of CO2. One way to drive emissions down is to valorize CO2 by using it as a carbon source for the synthesis of chemical feedstocks. The development of new technologies that produce chemicals from CO2 in a cost competitive and efficient way could put market pressure on existing fossil-derived petrochemicals and incentivize the capture of CO2 from concentrated point sources such as power plants. One attractive strategy for CO2 valorization is to use renewable energy to power the aqueous electrochemical reduction of CO2 and H2O to generate valuable C2+ chemical feedstocks such as ethylene, ethanol, propanol, and acetate. Unfortunately, the spontaneous reaction of CO2 and HO-- to form HCO3-- and CO32-- impedes the optimization of these systems. While the operation of CO2 reduction cells with alkaline electrolytes results in low total cell voltages, the super stoichiometric consumption of MOH in these systems represents a significant energy penalty. Furthermore, only low single-pass conversions have been achieved for CO2 electrolysis resulting in dilute product streams that are energy intensive to purify. Deconstructing CO2 reduction into two separate electrochemical steps may offer a path to overcome the challenges posed by direct electrochemical CO2 reduction. In this two-step process, CO2 is first converted to CO with a high temperature solid oxide electrolysis cell (SOEC), in which the reaction of CO2 and HO-- is avoided. The CO is subsequently reduced in a separate electrochemical cell to generate C2+ chemical feedstocks. While SOECs have recently been brought to market, relatively little is known about how to design an efficient CO electrolysis device that can achieve high single-pass conversions. For the first time, various cell configurations for CO electrolysis are evaluated and high single-pass conversions exceeding 80% are demonstrated corresponding to gas product streams which are greater than 24 vol% ethylene. Through device engineering liquid product streams that are greater than 1 M in sodium acetate are produced. Finally, an innovative deposition technique is developed to generate thick, highly active catalyst layers for CO reduction cathodes, resulting in improved device performance. The results obtained herein indicate the advantages of CO reduction over direct CO2 reduction. The exploration of various cell configurations informs future efforts to design and build larger scale CO electrolysis devices.

Keywords: Chemistry.
Advisor: Kanan Matthew William
Chidsey Christopher E. D. (Christopher Elisha Dunn)
Dai Hongjie
Catalyzing electrochemical oxygen reduction to form hydrogen peroxide : from catalyst development to device integration

Hydrogen peroxide (H2O2) is a highly valuable chemical with wide range of applications in industry such as paper bleaching, textile manufacturing and environmental protection. Currently, the industrial synthesis of H2O2 is through an energy intensive anthraquinone process, which requires large-scale and complex infrastructure. Electrochemical synthesis of H2O2 from oxygen reduction offers an attractive alternative route for onsite applications, while the efficiency of this process greatly depends on identifying cost-effective catalysts with high activity and selectivity. As several classes of catalysts have been reported or proposed by theory to be good candidates of the targeted reaction, here we focus our attention upon a metal-organic framework (MOF) and high-performance carbon catalysts for the perspective of both fundamental understanding and the high cost-efficiency. Catalytic systems whose properties can be systematically tuned via changes in synthesis conditions are highly desirable for applications in catalyst design and optimization, namely, the 2D conductive metal--organic framework (MOF) with M-N4 units (M = Ni, Cu) and a hexaaminobenzene (HAB) linker as a catalyst for the oxygen reduction reaction (ORR). By varying synthetic conditions, we synthesized two Ni-HAB catalysts with different crystallinities, resulting in a catalytic system with variable electrical conductivity, electrochemical activity and stability. We show that crystallinity has a positive impact on conductivity and demonstrate that this improved crystallinity/conductivity improves the ORR performance of our model system.

Keywords: Chemistry.
Advisor: Jaramillo Thomas Francisco 
Bao Zhenan 
Waymouth Robert M.
Celestial seductresses and hungry ghosts : preta narratives in early Indian Buddhism

In this dissertation I examine tales about the departed (Sanskrit: preta) composed in Sanskrit and Pāli from approximately the third century BCE to the sixth century CE. I argue that the body of the preta was essential to the construction of a Buddhist cosmology rooted in a socio-karmic discourse that is fundamentally physio-moral in nature. Through the body, I trace the transformation of the departed preta to the preta as a ghost constituting a separate realm of rebirth in the Buddhist cosmos. By telling stories about pretas, whose bodies are constituted by their prior actions and simultaneously restrict their ability to act toward soteriological goals, Buddhist authors created and illustrated their understanding of moral law of cause and effect. Additionally, the Buddhist saṅgha's claim to be able to transform abject preta bodies into divine ones allowed monks to elevate themselves as the superior mediators between humans and non-humans. While all men and women in these stories act immorally, their depiction is influenced by a social system that upheld the patriarchal householder structure and by a monastic institution that guarded itself against sensual desires and attachment to the body. For this reason, preta tales produce an ideological discourse of the body.

Keywords: Religious Studies.
Advisor: Harrison Paul M. (Paul Maxwell)
Kieschnick John
Gin Lum Kathryn 
McDaniel Justin
The cell biology of LRRK2 kinase activation and phosphorylation of Rab GTPases

LRRK2 kinase mutations cause familial Parkinson's disease and increased phosphorylation of a subset of Rab GTPases. Rab29 recruits LRRK2 to the trans-Golgi and activates it there, yet some of LRRK2's major Rab substrates are not on the Golgi. The second chapter of this thesis describes the cell biology of LRRK2 activation. Unlike other Rab family members, we show that Rab29 binds nucleotide weakly, is poorly prenylated, and is not bound to GDI in the cytosol; nevertheless, Rab29 only activates LRRK2 when it is membrane bound and GTP bound. Mitochondrially anchored, GTP-bound Rab29 is both a LRRK2 substrate and activator, and it drives accumulation of active LRRK2 and phosphorylated Rab10 on mitochondria. Importantly, mitochondrially anchored LRRK2 is much less capable of phosphorylating plasma membrane--anchored Rab10 than soluble LRRK2. These data support a model in which LRRK2 associates with and dissociates from distinct membrane compartments to phosphorylate Rab substrates; if anchored, LRRK2 can modify misdelivered Rab substrates that then become trapped there because GDI cannot retrieve them. Work in the third chapter examines Rab29's possible function and effector proteins. The data demonstrate that there are no significant Golgi structure or retrograde trafficking defects upon Rab29 depletion. Immunoprecipitation followed by mass spectrometry indicates that active Rab29 preferentially binds a calcium channel. Additionally, nucleotide free Rab29 preferentially binds to a GEF complex. These data suggest that Rab29 regulates calcium signaling at the Golgi and may be activated by a GEF complex that also activates Rab7.

Keywords: Biochemistry.
Advisor: Pfeffer Suzanne 
Harbury Pehr 
Rohatgi Rajat
Challenges in CT with photon counting detectors

With many attractive attributes including improved tissue characterization, reduced noise, and lower dose, photon counting detectors (PCDs) with multiple energy bins are being considered for clinical CT systems. A major problem with PCDs is the slow count rate, resulting in count rate loss and pulse pileup. Another challenge to PCDs with multiple energy bins is the large amount of projection data acquired that must be transferred in real time through slip rings to data storage subsystems, causing a bandwidth bottleneck problem. Our goal is to address these challenges with a dynamic bowtie filter, a pulse pileup modeling, and a compression algorithm for PCD projection data. A dynamic bowtie modulates flux distribution as a function of fan and view angles to reduce dose, scatter, and detector dynamic range. One approach, the piecewise-linear attenuator (Hsieh and Pelc, Med Phys 2013), consists of multiple wedges, each of which covers a different fan angle range and is moved in the axial direction to change the thickness seen in an axial slice. Our implementation of the filter with precision components and a control algorithm reduces the detected flux dynamic range to 42 for a chest and 25 for an abdomen, corresponding to a reduction factor of 5 and 11 from the object scans without the bowtie. The thickness profile of the piecewise-linear attenuator is proportional to wedge position and is sensitive to the precision of wedge control. Thus, we propose another dynamic bowtie design called a fluid-filled dynamic bowtie filter (FDBF), a two-dimensional array of small binary elements (filled or empty), that may be more reproducible due to digital control. On average, for simulated scans of chest, abdomen, and shoulder sections of an anthropomorphic phantom, the proposed FDBF reduces the maximum-count-rate required of a PCD to 1.2 Mcps/mm2, which is 55.8 and 3.3 times lower than the max-count-rate of the conventional bowtie and the piecewise-linear bowtie, respectively. For the pulse pileup effect, the performance of several analytical models are dependent on the assumptions used, including the assumed pulse shape which could differ from the actual one. From our sensitivity analysis of a pileup model by Taguchi et al. (Med Phys, 2010), the accuracy of some parameters such as the deadtime are more important than others, and they matter more with increasing count rate. For the bandwidth problem, we explored the use of data compression that could be performed prior to transmission through the slip ring. Utilizing the dependencies in the multi-energy data, our proposed compressor achieves an average compression ratio of 2.25:1 for lossless compression and 4.27:1 for lossy compression.

Keywords: Bioengineering.
Advisor: Pelc Norbert J. 
Glover Gary H.
Pauly John (John M.)
The character of animality : species difference and narrative form in American fiction, 1890-1970

The Character of Animality challenges the critical commonplace that literary character can only reveal fiction's inescapable anthropocentrism. I argue instead that twentieth-century American literature positions character as a vital tool for imagining consciousness and complex behavior beyond the human. In readings of Jack London, William Faulkner, Zora Neale Hurston, and Philip K. Dick, I uncover a century-long controversy over fiction's capacity to represent nonhuman animals, placing literary studies in direct conversation (or heated debate) with comparative psychology and the uneven behaviorism of its approach to animal life. When read together, the novel and the scientific discourse of animality both approach animal character as a set of strategies for representing the life of the mind under conditions of uncertainty, highlighting the shared limits of scientific empiricism and narratorial authority. For that reason, the possibility of fictionalizing animal minds informs the deep concerns of American literary history from the advent of Darwinian thought until the present day. Far from merely troubling the category of the human, the character systems of American novels offer a veritable poetics of species difference. Each of my four chapters describes a moment when animal character becomes more than a metaphor, colliding dramatically with the material reality of species. The first chapter reads Jack London's dogs and Upton Sinclair's pigs as the paradigmatic subjects of naturalist narration, registering the period's response to the taboo on animal sentience forming in the natural sciences. My second and third chapters jump forward to the interwar period that saw the blossoming of comparative psychology, showing that modernist fiction absorbs and revises the ambivalent anti-mentalism of the animal sciences through such characters as Faulkner's Benjy Compson and Hurston's talking buzzards. In my final chapter, I consider how literature engaged with midcentury cybernetics, arguing that Philip K. Dick and other writers borrow the ambivalent figure of the animal-machine to think the ethics of animal representation. At each juncture, I interrogate a different sense of likeness between character and animal, in the process re-opening the question of what it means for a character to resemble anything at all.

Advisor: McGurl Mark
Moya Paula M. L. 
Ngai Sianne 
Woloch Alex