VictorJuiz/thesis huggingface dataset:
The use of a low-latency key-value store for implementing a scalable and high-performance graph database

This dissertation presents the design, implementation, and evaluation of TorcDB, a high performance graph database system that inherits its ability to scale from a generic key-value store. The key-value store, RAMCloud, is an in memory and low latency distributed storage system that provides the necessary features for scaling, including fault-tolerance, automatic data distribution, and distributed transactions, without assuming anything about the type of data stored by clients. TorcDB achieves high performance using RAMCloud by carefully laying out data and translating traversals into a read and write schedule that minimizes query latency. Using this approach, TorcDB is able to achieve competitive and often better performance than the state of the art in graph database systems today. Evaluated on a large scale social network workload, TorcDB is able to achieve an overall 50th percentile latency of 246us for update queries, 139us for short read queries, and 4.6ms for complex analytical queries.

Keywords: Electrical Engineering.
Advisor: Rosenblum Mendel 
Ousterhout John K. 
Prabhakar Balaji
Useful thermal effects in electrochemical systems

Redox reactions with high entropy changes can be used to make effective refrigerators and heat engines. This work demonstrates electrochemical systems that harvest heat energy (with efficiency > 60% of Carnot) and can provide effective cooling (at power > 0.5W/cm^3). A key advantage is that electromigration and mass advection in electrolytes can be optimized separately to decouple charge, entropy, and heat transport in ways that aren't possible with solid-state thermoelectrics. While these devices are a long way from any practical use, they might inform or inspire other researchers working towards hydrofluorocarbon-free refrigeration or energy harvesting.

Keywords: Chemical Engineering.
Advisor: Cargnello Matteo
Majumdar Arunava 
Chueh William
Using seawater to transition offshore energy production from petroleum to clean energy

The most abundant material on our planet, seawater, could help us to build a bridge between the fossil fuel industry and human-timescale renewable energy resources. In this thesis, I show that seawater can enhance oil recovery from porous media and store electrical energy. Therefore, seawater unlocks clean offshore energy storage hubs. This report shows that seawater (1) can alter the wettability of carbonate porous media towards more water-wet conditions that are favorable for oil recovery and (2) can store chemical energy after oil removal from porous media. Specifically, my work demonstrates that seawater enhances oil recovery from carbonate fields and offshore petroleum reservoirs could become underground porous electrodes of a giant redox flow battery. With this proposal, I use seawater as a base material for the design of the injection water and add ions that help to detach oil from the rock. I enable seawater as injection fluid to increase oil recovery by wettability alteration adding ions that have been proved to help oil recovery. The mean water contact angle of the ganglia showed a 28% contact angle reduction from an oil-wet to a water-wet system when using a tuned seawater composition with high salinity in a tertiary displacement. The wettability alteration might not be as drastic as simplified ion compositions or diluted seawater, but it potentially provides a more economically efficient solution. In this way, I contribute to enhanced oil recovery and with an eye toward the economics involved in tuning the seawater to make it an injection fluid that alters wettability. I induced potential on a connate salinity and seawater salinity brines cell set-up to transfer sulfide reverting the redox reaction and therefore storing energy. Hence, a seawater ion-exchange cell could be considered as one of the most attractive candidate applications for offshore large-scale energy storage and chemical ionic tuning. Despite the fact that a seawater-battery has lesser gravimetric and volumetric energy density, natural underground reservoir electrodes have the size to make large scale energy storage possible.

Keywords: Energy Resources Engineering.
Advisor: Kovscek Anthony R. (Anthony Robert)
Using sequencing to analyze exotic circulating nucleic acids in primates and transplantation immunity of a sea squirt

High throughput sequencing allows the accurate quantification of millions to billions of biomolecules at a time. I have looked to answer questions across a range of biological fields by building analysis pipelines for this data, utilizing high-performance computing infrastructure, and applying techniques from machine learning. In the last decade, studies of circulating nucleic acids in humans have yielded noninvasive tests of fetal chromosome abnormalities and signatures of rejection events in transplant recipients. Here I describe how circulating nucleic acids also have microbial and viral signatures which allow us to detect pathogens in a hypothesis-free manner, to identify highly divergent and novel microbes in humans, to characterize the microbiome of non-human primates, and to unveil disease dynamics and changes in the immune system in individuals living with HIV. Another area I've researched relates to the immune system of sea squirts, or tunicates, the sister group of vertebrates and are separated about 400 million years from us. The tunicate Botryllus schlosseri is a colonial organism with a natural allogeneic fusion reaction that produces chimeras, and therefore serves as a model system for transplantation. Here I used deep sequencing to present a molecular, genetic and cellular description of the process of resorption of unstable chimeras, characterization of the haematopoietic system, and molecular, cellular and morphological changes during development of this fascinating organism.

Keywords: Physics.
Advisor: Quake Stephen Ronald 
Chu Steven
Weissman Irving L.
Using the Global Decarbonization Movement to Create a Socioeconomically Equitable World

The International Panel on Climate Change estimates that over the next three decades the global economy must invest $2 trillion per year into decarbonizing the infrastructure that supports our society. Using existing business models for community energy, this massive wave of investment can simultaneously be used to alleviate socioeconomic inequities that exist in developed nations like the United States. Deploying community energy projects successfully requires a particular emphasis on community engagement as our team learned while building a community co-design framework on the Hawaiian island of Moloka’i. We learned that physical models of the island and in-person role play of business model specifics motivate residents to share culturally relevant requests for project specifications. Executing on these specifications as a renewable energy developer facilitates resident’s emotional ownership of a project and stimulates a more socioeconomically equitable society while reducing carbon emissions.

Keywords: Renewable energy
social equity
socioeconomic equity
environmental justice
Hawaii
community engagement
community
Thesis
UV and IR properties of quantum gravity from amplitudes

We state the motivation of our work on quantum gravity using modern amplitudes techniques, and give a brief review of basics of amplitudes, including the spinor-helicity formalism, unitarity cuts, and relations between graviton amplitudes and gluon amplitudes. After this introduction, we review our work investigating the ultraviolet behavior of the 2-loop 4-graviton amplitude using generalized unitarity cuts in dimensional regularization in -2\epsilon$ dimensions. We find a surprisingly simple dependence on the renormalization scale, which is the physical quantity we should focus on, for graviton amplitudes at 2-loop level. Since every simple result needs a simple derivation, we re-derive this simple renormalization scale dependence of the 2-loop graviton amplitude using the unitarity-cut method directly in 4-dimensional spacetime. This method relates the renormalization scale dependence to discontinuities of the amplitudes and elucidates the physics within. Last, we review our work on the infrared, or long-distance, properties of quantum gravity by studying the first quantum correction to the bending angles of massless projectiles with different spins, using 1-loop scattering amplitudes. Our calculation of the bending angle for gravitons, in particular, completes this line of research. The difference between the quantum corrections to the bending angles of different massless projectiles indicates a violation of the classical equivalence principle at the quantum level.

Keywords: Physics.
Advisor: Dixon Lance Jenkins
Kallosh Renata
Schuster Philip Christian
Validating a Multifactorial Autism Mouse Model: The Combinatorial Effects of CHD8 Haploinsufficiency and Prenatal Inflammation

Although the incidence of Autism spectrum disorder (ASD) has been on the rise in recent decades, its etiology is not well understood. Its risk factors are diverse, being both environmental and genetic. Among the many genetic factors, chromodomain helicase DNA binding protein 8 (CHD8) is one of the most common alterations identified in individuals with ASD. However, the mutations in CHD8 alone are not sufficient to cause ASD, and there are no other single gene causes of autism, suggesting a combinatorial etiology. As such, it is important to study how an environmental challenge may modulate a pre-existing genetic risk. Previous studies have strongly implicated infections in the pregnant mother as one of the most common non-genetic risks. In experimental models, eliciting an immune activation that simulates infection is known as maternal immune activation (MIA). In mice, MIA alone is sufficient to produce behavioral features reminiscent of ASD in offspring. CHD8 was initially identified due to its role in immune cell regulation, and the present research speculates that mutations in CHD8 may “interact” with MIA to alter neurodevelopmental outcomes. The present research project focuses on validating a mouse model of CHD8 partial loss of function with the intent of using this model with MIA to study combinatorial effects on fetal brain development. Mice were bred to generate offspring with one mutated allele of Chd8 and were challenged with an MIA immunogen (LPS). Experimental offspring trended toward delays in development, increased anxiety, and loss of preference in interacting with a novel social stimulus. These findings emphasize the complex etiology of ASD; it is important to understand how multiple factors produce unique combinatorial phenotypes in the development of this condition.

Keywords:  Department of Biology
Biology
Neuroimmunity
CHD8
maternal immune activation (MIA)
lipopolysaccharide (LPS)
autism spectrum disorder (ASD)
neuroimmunity
combinatorial
risk factors
hypoactivity
Thesis
Advisor: Palmer Theo D.
Heller H. Craig
Validating models of a physical system with experiments : electrostatic actuators in electrolytes

The construction and validation of models for systems is essential to engineering. This requires accurate mathematical representations of relevant processes, parameter and/or state estimation in order to inform models, high quality experiments with which to validate these models, and a formal evaluation of the ability of model's to explain a physical system. Typically, an individual research project in the context of academia focuses on one or two of these steps. In the work done in this thesis, we perform these steps in concert, and apply it to the case of an electrostatic comb-drive actuator in electrolytes. Electrostatic comb-drive actuators in electrolytes have many potential applications. Two applications, in particular, are found in literature. The most commonly cited is characterizing the mechanical properties of diverse structures at small scales. In particular, biological cells. The mechanical properties of cells are critical to their health, and can be implied by observing their behavior in response to external forcing. Electrostatic comb-drive actuators in conducting liquids also have potential in microfluidic systems. In particular, they can be used in microfluidic systems designed for drug delivery, and the mechanical manipulation of cells. Maximizing the utility of these devices for such applications requires robust methods for operating electrostatic actuators in electrolytes, and the creation of accurate models for these devices. Electrostatic actuators are typically operated with DC voltages. In electrolytes, an ionic shield forms on the actuator surface's under the influence of DC voltages, preventing motion. Previous studies discovered that this effect could be overcome by applying AC voltages with sufficiently high frequencies. Lumped circuit models were subsequently developed that accurately captured the general behavior of electrostatic actuators with comb-drive and parallel plate configurations respectively. However, these models had limited quantitative accuracy at low and intermediate frequencies of the AC signal. We develop models of the comb-drive actuator in electrolytes that are accurate over a wide range of frequencies, and that will facilitate accurate control of these actuators in both the context of deforming cells, and of actuation in microfluidic systems. We also develop a method of parameter estimation that simultaneously performs optimization and uncertainty quantification, and allows us to comment on the generalizability, informativeness, and best fit of our models, with respect to the physical system.

Keywords: Mechanical Engineering.
Advisor: Iaccarino Gianluca 
Mani Ali (Professor of mechanical engineering) 
Pruitt Beth
Validation of a protein biomarker panel for early hepatocellular carcinoma detection at the Point-of-Care

Hepatocellular carcinoma (HCC) composes about 80% of liver cancer cases, which is the second leading cause of cancer-related deaths worldwide. Majority of HCC burden is present in developing countries where hepatitis B virus (HBV) vaccination is inadequate and transmission of hepatitis C virus (HCV) is prevalent. In addition, HCC is an escalating problem in the US where liver cancer rates doubled over the last three decades due to chronic HCV infection, diabetes, and obesity. Most patients become chronically infected, progress to fibrosis and cirrhosis, and finally develop HCC. Current detection methods include ultrasound and alpha-fetoprotein (AFP) serum assay. These methods lack adequate sensitivity to catch early stage HCC, and many patients get diagnosed at later stages, resulting in suboptimal prognosis and low survival rates (< 10%). It is therefore imperative to develop a sensitive and specific multiplexed method for early HCC detection in high-risk patients. Early detection leads to early treatment, resulting in better patient prognosis and survival. We will discuss how giant magnetoresistive (GMR) sensor arrays can be used to develop a protein biomarker panel for early detection of HCC in high-risk cirrhotic patients. We show that the diagnostic power of our biomarker panel can exceed that of AFP alone. We also demonstrate significant improvement to diagnostic performance (AUC = 0.89) when combining our biomarker panel assay results with imaging results and clinically available information, including age and ethnicity. Given high prevalence of HCC in developing countries, we also designed and built an automated point-of-care GMR sensor platform to perform rapid, relatively inexpensive, and user-friendly assays. We demonstrate potential use of this platform for disease detection. By relaxing current limitations imposed by training, technical skills, time, and resources, the GMR sensor platform can bring affordable healthcare to a broader audience and extend medical technology to disadvantaged parts of the world.

Keywords: Bioengineering.
Advisor: Wang Shan X. 
Cochran Jennifer R. 
Utz Paul
Valuation of distributed energy resources based on consumption data

The electric grid is undergoing fundamental changes. The most well known is taking place at the central nodes of the grid, where new utility scale solar and wind generation plants are increasing the share of energy produced by renewable and intermittent sources. An equally profound though less mature transformation is underway at the peripheral nodes of the grid with the increasing adoption by residential consumers of distributed energy resources (DERs) like rooftop solar, energy storage, and electric vehicles. Whether solar and storage technologies make the leap from eager, early adopters to a mass presence will be determined by how well they align with the needs of residential consumers. This study develops models for the drivers and impacts of widespread adoption of rooftop solar and storage in the residential sector. We take the electricity consumption history of households, as recorded by their smart meters, as the best measure of their primary needs and wants. In the first section of this study, we characterize the effect of pricing policies on the distribution of household electricity cost savings from net-zero sized solar and storage technologies under time-varying prices. We also model and estimate the additional value that coordination services that aggregate resources can provide to households. In the second section, we develop a model for a peer-to-peer rental market for rooftop solar and energy storage. The market rental price, quantity, and participation rate are characterized for varying levels of DER adoption. We find that direct subsidies are a cheaper way to increase adoption if enabling the peer-to-peer market increases distribution grid costs by more than a few percent. In the third and final section, we develop a method to quantify the resilience value that rooftop solar can provide to residential neighborhoods in the aftermath of natural disasters. As a case study, we apply this method to single family homes in San Carlos subjected to an earthquake based on the 1906 San Francisco event. We evaluate the cost and effect of a policy intervention to ensure more geographically uniform resilience, finding that a relatively small nudge can have a significant impact on improving resilience for all households.

Advisor: Rajagopal Ram 
Kiremidjian Anne S. (Anne Setian) 
Majumdar Arunava
Vape Tricks: An Overview of E-Cigarette Industry Marketing and Analysis of Adolescents' and Young Adults' Memories of Advertisement Messages

A summary of e-cigarette advertising techniques, messages, and media, and analysis of cross-sectional data from a larger longitudinal study regarding adolescent and young adult use and perceptions of tobacco products.

Keywords:  Department of Medicine
Community Health and Prevention Research
Stanford Prevention Research Center
Stanford School of Medicine
Thesis
Advisor: Halpern-Felsher Bonnie
Velocity model building using shape optimization applied to level sets

As oil and gas extraction becomes more advanced, exploration becomes increasingly focused on imaging near or under complex salt geology, which necessitates detailed velocity models with sharp interfaces. Current state-of-the-art practices include the use of Full-Waveform Inversion (FWI). However, this type of approach can result in salt body models that lack the sharp interfaces characteristic of this type of geobody. This is typically due to the computational expense of using increasingly high frequencies in the data. These interfaces can be elegantly tracked as sharp boundaries using the level sets of an implicit surface. Used in conjunction with shape optimization, one can invert for salt boundaries that fit recorded data in a FWI style objective function that is parameterized in terms of both the implicit surface and a background velocity model. While this addition of the implicit surface requires more model parameters, radial basis functions can be used to create a sparse parameterization of it, which can hasten convergence of the inversion. The implicit surface also allows for embedding information about the certainty of different salt boundary regions by means of its initialization. This information allows for intelligent guidance of the inversion based on interpreter input, which can help the inversion avoid local minima. The result of testing this inversion workflow on a 3D Gulf of Mexico dataset shows that it can be a useful tool for refining salt models, as the seismic images produced from the final model shows clearer and more consistent features below the updated salt area.

Keywords: Geophysics.
Advisor: Biondi Biondo
Beroza Gregory C. (Gregory Christian) 
Clapp Robert G. (Robert Graham)
Viral outrage : victims and villains of our contemporary moral discourse

Viral outrage--the piling up of online condemnation in response to offensive remarks--is a common expression of moral judgment in the digital age. Whereas moral outrage has traditionally served a valuable social function, expressing group values and inhibiting deviant behavior, the exponential dynamics of Internet postings make this expression of legitimate individual outrage appear excessive and unjust. Across nine studies (N=5,377), we address two questions: 1) How do outside observers evaluate individuals who contribute to viral outrage? 2) Is viral outrage effective in convincing observers that an offender is blameworthy? In Studies 1-5, participants saw racist, sexist, or unpatriotic posts with accompanying expressions of outrage, and formed impressions of a single commenter. We demonstrate that the same individual outrage that would be praised in isolation was more likely to be viewed as bullying when echoed online by a multitude of similar responses, as viral outrage elicited greater sympathy towards the initial offender. In Studies 6-9, participants were again presented with offensive posts and accompanying expressions of outrage, but in contrast to the previous studies, evaluated the offender rather than individual commenters. As more people expressed outrage, observers believed it was more normative to express condemnation, but also felt that the outrage was excessive, thus inspiring both more outrage and more sympathy towards the offender. Greater outrage increased condemnation towards the offender; greater sympathy decreased it. These two processes operated in opposition and suppressed one another. The exponential nature of online moral outrage may significantly alter how outrage is elicited, expressed, and perceived, raising the question of how best to respond to injustice in the digital age.

Keywords: Psychology.
Advisor: Monin Benoît
Markus Hazel Rose 
Tsai Jeanne Ling