VictorJuiz/thesis huggingface dataset:
The hybrid mobile instrument : recoupling the haptic, the physical, and the virtual

The decoupling of the "controller" from the "synthesizer" is one of the defining characteristic of digital musical instruments (DMIs). While this allows for much flexibility, this "demutualization" (as Perry Cook termed) sometimes results in a loss of intimacy between the performer and the instrument. In this thesis, we introduce a framework to craft "mutualized" DMIs by leveraging the concepts of augmented mobile device, hybrid instrument design, and skill transfer from existing performer technique. Augmented mobile instruments combine commodity mobile devices with passive and active elements that can take part in the production of sound (e.g., resonators, exciter, etc.), while adding new affordances to the device and changing its form and overall aesthetics. Screen interfaces can be designed to facilitate skill transfer, accelerating the learning and the mastery of such instruments. Hybrid instrument design mutualizes physical and "physically-informed" virtual elements, taking advantage of recent progress in physical modeling and digital fabrication. This design ethos allows physical/acoustical elements to be substituted with virtual/digital ones and vice versa (as long as it is physically possible). A set of tools to design hybrid mobile instruments is introduced and evaluated. Overall, we demonstrate how this approach can help digital luthiers to think about DMI design "as a whole" in order to create mutualized instruments. Through a series of case studies, we discuss aesthetic and design implications when making such hybrid instruments.

Keywords: Music.
Advisor: Chafe Chris 
Smith Julius O. (Julius Orion) 
Wang Ge
Wright Matthew
Hybrid PSO - adjoint-gradient Procedure for Well Control Optimization

Compositional simulation is commonly applied to evaluate enhanced oil recovery and carbon storage processes. Compositional simulation is expensive because the models may include multiple components along with complex phase behavior. Thus, when compositional systems are optimized, the optimization algorithms must be robust and efficient. In this work, we assess different procedures for well control optimization in oil-gas compositional systems. The optimization algorithms considered include a standalone adjoint-gradient-based method, a standalone particle swarm optimization (PSO) procedure, and several hybridizations of these two approaches. We introduce and evaluate two criteria for switching from PSO to adjoint-gradient-based optimization in the hybrid procedures. These approaches are referred to as deterministic switching, where we switch after a specified number of PSO iterations, and adaptive switching, where the algorithmic switch is based on PSO performance. All methods are implemented and run within Stanford’s Unified Optimization Framework (UOF).
The performance of the standalone and hybrid procedures is assessed for two example cases involving well control optimization in Gaussian and channelized geological models. The time-varying bottom-hole well pressures are treated as the optimization variables, and net present value (NPV) is optimized. Each method under consideration is run at least nine times to account for the stochastic nature of PSO and the sensitivity to the initial guess in the adjoint-gradient method. This allows us to draw meaningful conclusions on the relative performance of the various procedures. The two example cases presented in this study demonstrate that the hybrid PSO-adjoint-gradient procedure utilizing adaptive switching outperforms the standalone algorithms in terms of average optimal NPV. By plotting the average optimal NPV versus computational effort for the different methods, we can construct a Pareto front. For both cases, the Pareto-optimal procedures include standalone PSO (which provides lower average NPV but requires less computation) and the hybrid PSO-adjoint-gradient method using adaptive switching. The latter gives higher average NPV but at the cost of increased computational effort.

Keywords:  Energy Resources Engineering
School of Earth Energy &amp; Environmental Sciences
Energy Resources Engineering
Production optimization
well control optimization
Particle swarm optimization
Adjoint-gradient optimization
Hybrid optimization
Reservoir simulation
Compositional simulation.
Thesis
Advisor: Durlofsky Louis
Padhye Nikhil
Hydroxychloroquine use and adverse events in Lupus pregnancy: A Stanford Experience

Background: Relatively recently, women with lupus would be advised against pregnancy. However, with improved diagnosis and management, complicated SLE and history of any organ involvement is not a strict contraindication for future pregnancy. As the literature providing evidence for the safety of hydroxychloroquine (HCQ) use during pregnancy in women with lupus grows, it has become increasingly important to evaluate the changes this intervention has introduced in regard to adverse events in pregnancy.
Aim: To evaluate the association between HCQ use and preterm birth (PTB) and preeclampsia (PE) in pregnant women with lupus.
Methods: A retrospective cohort of 129 pregnancies from 110 women with lupus was formed from 2000-2017 from a single center, Stanford Healthcare. Lupus diagnosis was evaluated and confirmed via medical record review. Data were collected regarding demographics, lupus disease, current pregnancy, delivery, and reproductive history characteristics. HCQ exposure was determined by care plan, physician notes, and prescriptions. Use of low dose aspirin (ASA), a secondary exposure, was also collected during chart review. Logistic regression was used to estimate odds ratios and 95% confidence intervals adjusting for potential confounders.
Results: Due to the limited sample size, statistical analyses were underpowered. However, the association between HCQ use during pregnancy and preeclampsia and preterm birth appeared protective in unadjusted and adjusted analyses accounting for maternal age and race, renal involvement, and antiphospholipid antibody positivity and syndrome (crude OR for HCQ-PTB=0.6, 95% CI=0.3-1.4 crude OR for HCQ-PE=0.4, 95% CI=0.2-1.1). Observed effects were not consistent in ASA analyses, for example the crude OR for ASA-PTB was 1.5, 95% CI (0.6-4.1) and the crude OR for ASA-PE was 0.6 95% CI (0.2-2.1).
Conclusion: While our study does suggest protective effects with HCQ use during pregnancy against preeclampsia and preterm birth in women with lupus, our sample size limitations hindered our ability to fully investigate potential effect modification by parity. Additional research is required to achieve sufficient power to adequately investigate effect modification by factors such as antiphospholipid antibodies (aPL) and antiphospholipid syndrome (APS).

Keywords:  Department of Health Research & Policy
Systemic lupus erythematosus
SLE
lupus
preeclampsia
preterm birth
hydroxychloroquine
plaquenil
Department of Health Research &amp; Policy
Stanford University
Stanford School of Medicine
Obstetrics
Gynecology
Rheumatology
Thesis
Advisor: Simard Julia
Chaichian Yashaar
Hypothesis testing using multiple data splitting

Data splitting, a tool that is well studied and commonly used for estimation problems such as assessing prediction error, can also be useful in testing problems where a portion of the data can be allocated to make the testing problem easier in some sense, say by estimating or even eliminating nuisance parameters, dimension-reduction, etc.. In single or multiple testing problems that include a large number of parameters, there can be a dramatic increase of power by reducing the number of parameters tested, particularly when the number of non-null parameters is relatively sparse. While there is some loss of power associated with testing on only a fraction of the available data, carefully selecting a test statistic may in turn improve power, though it remains unclear whether the reduction of the number of parameters under consideration can outweigh the loss of power from splitting the data. To combat the inherent loss of power seen with data splitting, methods of combining inference across several splits of the data are developed. The power of these methods is compared with the power of full data tests, as well as tests using only a single split of the data.

Keywords: Statistics.
Advisor: Romano Joseph P.
Taylor Jonathan E. 
Tibshirani Robert
Identification of biogenesis factors and drug targets in the apicoplast proteome of malaria parasites

Malaria, caused by apicomplexan parasites of the genus Plasmodium, is a devastating disease of global importance, with over 200 million yearly cases leading to more than 400,000 annual deaths. Emerging resistance to current frontline treatments necessitates continued identification of new, parasite-specific drug targets with mechanisms-of-action orthogonal to current treatments. One key source of novel targets is the apicoplast, a nonphotosynthetic, 4-membraned plastid that performs critical metabolic functions throughout the parasite life cycle. Apicoplast maintenance and biogenesis are essential processes and validated drug targets, but our limited molecular understanding of apicoplast organelle biology has hindered the discovery and development of chemotherapies that exploit these unique pathways for antiparasitic treatment. The work described in this dissertation addresses two aspects related to identifying and drugging apicoplast biogenesis factors. First, the full complement of apicoplast-localized proteins is poorly characterized, and this lack of a reliable apicoplast proteome has limited our ability to mechanistically interrogate the most novel aspects of apicoplast biogenesis. Using a combination of proximity biotinylation-based mass spectrometry and machine learning, I report a high-confidence apicoplast proteome that is rich in novel and essential functions. Critically, many of these novel proteins are parasite-specific and will likely yield new insights into mechanisms of apicoplast biogenesis. Second, even given a high-confidence proteome, methods for prioritizing the most promising candidates for drug discovery efforts are limited. This is especially so given the context that some inhibitors of apicoplast biogenesis cause an undesirable "delayed-death" phenotype resulting in a slow onset-of-action that limits the clinical utility of these drugs. Using a chemical biology approach designed to selectively disrupt apicoplast protein import, I show that this particular biogenesis pathway appears to avoid the delayed-death phenotype. This suggests that targeting apicoplast protein import may yield clinically useful antimalarials and that protein-level conditional tools are valuable resources for characterizing apicoplast biogenesis pathways. Altogether, the results of these studies will facilitate detailed investigation of the mechanisms and chemical inhibition of apicoplast biogenesis.

Keywords: Microbiology and Immunology.
Advisor: Yeh Ellen
Boothroyd John C. 
Carette Jan
Grossman Arthur (Arthur R.) 
Kirkegaard Karla
Identification of genetic modifiers of neurodegenerative diseases using CRISPR-Cas9 screens

Neurodegenerative diseases, such as Alzheimer's disease and Amyotrophic lateral sclerosis (ALS), pose one of the greatest risks to human health. Progress towards medical interventions is hindered by a lack of understanding of the underlying cellular and molecular causes of these diseases. In this work, I describe novel CRISPR-Cas9 screening approaches in human cells and primary neurons to understand neurodegenerative diseases. Through genome-wide CRISPR-Cas9 knockout screens in human cells, I describe hundreds of genetic modifiers of the toxic dipeptide repeat proteins (DPRs) associated with the C9orf72 repeat expansion, the most common cause of ALS. The genetic modifiers discovered in the human genome-wide screens are validated in the first reported CRISPR-Cas9 knockout screen in primary mouse neurons. Together, these screens revealed a novel therapeutic target for ALS, the ER resident protein TMX2. Additionally, I describe the development of a rapid genome-wide phenotypic screens for substrate specific regulators of phagocytosis, a process recently implicated in Alzheimer's disease. By conducting eight human genome-wide CRISPR knockout screens for regulators of phagocytosis of distinct substrates, I describe the discovery of a novel universal phagocytosis regulator, the previously-uncharacterized gene NHLRC2. Lastly I show that the previously-uncharacterized Alzheimer's disease-associated gene TM2D3 can selectively influence the phagocytosis of A aggregates. Together this work describes a novel approach to studying neurodegenerative diseases using human genome-wide knockout screens to reveal the cellular mechanisms and potential therapeutic targets for neurodegenerative diseases.

Keywords: Genetics.
Advisor: Bassik Michael 
Gitler Aaron D. 
Li Jin (Billy) 
Urban Alexander E.
Identification of novel regulators of the long interspersed nuclear element-1 retrotransposon in humans

First identified by Barbara McClintock in Zea mays, transposable elements are now recognized not only as parasitic DNA, the spread of which in the genome must be controlled by the host, but also as major players in genome evolution and regulation. The most abundant and only currently autonomously active transposable element in the human genome, LINE-1, contributes to inter- and intragenic variation within the human population. In addition, LINE-1 sequences can regulate transcriptional programs in cis and trans as well as lead to the mobilization of other cellular mRNAs, including other transposons. Here I address how cells defend against LINE-1 mobile activity, as well as explore the extent to which LINE-1 sequences are transcribed in adult human somatic tissues. Chapter 1 provides a short historical introduction to the identification of transposable elements and the biology of the LINE-1 transposon. In chapter 2, I describe our high-throughput screening approaches to identify key regulators of LINE-1 transposition. In addition to classifying regulators as acting through sequence dependent or independent mechanisms, we also identify the HUSH complex as a major regulator of LINE-1 activity in human cancer cells. In chapter 3, I use adult somatic tissue expression measurements from GTEx consortium to identify and describe somatic LINE-1 expression. We find tissue specific L1 expression, and further leverage publicly available ENCODE data to identify potential regulators of L1 transcription. In chapter 4 I discuss our findings from our screen and tissue-level expression analysis, with a focus on remaining unanswered questions. Taken together, these chapters improve our understanding host/LINE-1 interactions in human cells and tissues.

Keywords: genetics) degree committee member.
Genetics.
Advisor: Bassik Michael 
Fire Andrew Zachary 
Villeneuve Anne
Identifying bias in human and machine decisions

Many suspect that decisions in employment, college admissions, lending, and the criminal justice system are systematically biased against certain groups. To date, efforts to provide statistical support for these concerns are often hampered by subtle statistical flaws that are known to affect popular tests for discrimination. The first part of this dissertation introduces these tests and their flaws, before proposing two new statistical tests for discrimination. The threshold test uses a hierarchical Bayesian model to identify the standards that decision-makers apply to different protected groups, while risk-adjusted regression aims to determine whether observed differences in treatment are justified by legitimate policy goals. Decisions aided by machine learning algorithms have also come under scrutiny for bias. As humans use machines to inform more and more consequential decisions, it is becoming crucial to understand how bias might occur in algorithmic systems. The study of identifying bias in algorithmic decisions is young, and many of the initial approaches suffer from the same statistical limitations as tests for bias in human decisions. The second part of this dissertation explores these approaches to algorithmic fairness, demonstrates their deficiencies, and provides a framework for the development of fair algorithmic decisions. Throughout this dissertation we apply our methods to large datasets from the US criminal justice system, studying citizens' interactions with the police and defendants' interactions with the courts. Despite this criminal justice focus, our work is applicable to studying bias in any domain, whether the decisions are made by humans or algorithms.

Advisor: Bernstein Michael S.
Goel Sharad
Jurafsky Dan
Identifying the Role of Early Sex Hormone Exposure in the Development of Social Behavior in Astatotilapia burtoni

Far from simply mediating sexual development and reproduction, steroid sex hormones play a large role in the regulation of complex social behaviors across species. Several studies have elucidated how sex steroid hormones (i.e., androgens and estrogens) can increase adult male sexual and aggressive behaviors. But just how sex steroid hormones influence the onset of social behavior in both sexes during early ontogeny remains to be established. Here, we use the African cichlid fish Astatotilapia burtoni, to investigate how early sex hormone exposure influences the transition from gregarious shoaling behavior to aggressive chasing behavior in juveniles. Three equally sized groups of eggs from the same brood were separated and immersed into aquarium water containing a known concentration of androgen, estrogen, or control (dimethyl sulfoxide or DMSO) shortly after fertilization. At three time points up to two months after fertilization, the movements of six fish from each treatment group were video recorded to map their individual positions over time. We found that fish in the androgen-treated group shoaled (measured by the mean similarity between trajectories) significantly less than those in the estrogen- and DMSO-treated groups at the latter two time points, suggesting that early androgen exposure has an organizational effect in the brain that facilitates a premature transition to aggressive behavior from shoaling behavior. As all vertebrates—including humans—share many of the same sex hormones and associated receptors with A. burtoni, these results might inform our understanding of how differential prenatal sex hormone exposure could influence social behavior later in life.

Keywords:  Department of Biology
Biology
Astatotilapia burtoni
Testosterone
Estradiol
Shoaling
Aggression
Development
Organizational Effect
Thesis
Advisor: Fernald Russell
Heller Horace Craig
Ignition delay time measurements for distillate and synthetic jet fuels

As alternatives to traditional petroleum-based fuels are increasingly sought after, the National Jet Fuel Combustion Program (NJFCP) was established to streamline the evaluation and certification of these fuels. The current mandate is for the replacements of traditional fuels to be equally safe and to provide better environmental performance [1]. These so-called "drop-in" jet fuels refer to hydrocarbon fuels that deliver identical combustion performance and are produced from non-petroleum sources [2]. Following the mandate delivered by the NJFCP for alternative fuels, this study aims to improve the traditionally phenomenological understanding of combustion performance by making connections between fuel properties and the chemical composition of fuels. The ignition delay time is an important measure of the combustion performance of fuels, as it is an integrated measure of the fuels' physical and chemical properties, such as volatility, diffusivity, and chemical reactivity. Consequently, it is a very useful validation target in chemical kinetic modeling and has implications in practical aviation phenomena such as, among others, lean blowout, cold-start ignition and altitude relight. Shock tubes are well-suited for ignition delay time measurements, as they provide a well-defined time zero and a quasi-constant temperature and pressure test region behind the reflected shocks. All experiments in this thesis were performed on the Stanford Flexible Application Shock Tube (FAST). Reactive gas mixtures were prepared with equivalence ratios of 1 ± 0.05, and mixed in the shock tube driven section to avoid fuel loss attributed to non-idealities in the jet fuel vapor. Changes in the fuel mole fraction during mixing and ignition were monitored using laser absorption diagnosis at 3.39 µm. The ignition delay time is defined in this study by the onset of emission from electronically excited OH radicals at 306 nm. Ignition delay times were measured in the temperature range of 1200-1500 K and at 4 atm pressure for five distillate jet fuels from refineries around the US (termed geographical fuels), and for six synthetic jet fuels with varying cetane numbers ranging from 30-55 (termed CN fuels). The ignition delay times for A1-3 and C1-9 jet fuels were also measured at 1300 K and at 4 atm. The dependence of combustion properties on fuel chemical composition were investigated using the ignition delay times for these fuels. In particular, the key role that the degree of branching in the jet fuel molecular structure plays in the combustion kinetics and performance is discussed.

Keywords: Mechanical Engineering.
Advisor: Hanson Ronald
Imagining, building, and understanding the next-generation battery

Harnessing electricity marked the beginning of the industrial revolution; making it portable completely transformed modern society. Battery technology has largely enabled the conveniences of social connectivity and mobile services we enjoy today. However, current batteries are rapidly approaching their fundamental limits. To make a lasting impact in emerging applications such as electric vehicles and grid-scale energy storage, better batteries that can store more energy in a safe manner need to be developed. Innovations and breakthroughs in such technologies require a synergistic and interdisciplinary combination of materials design (chemistry, engineering) and fundamental characterization (materials science, physics). In my Ph.D., I demonstrate successful examples within these two major thrusts, which will not only bring practical applications in the short-term, but also establish fundamental insights that are necessary to facilitate long-term solutions. Chapters 1, 2, and 3 focus on the first major thrust of this dissertation: materials design. Chapters 1 and 2 are an introduction to batteries. In chapter 1, I detail the history, working mechanisms, and limitations of the current state-of-the-art batteries based on lithium chemistry. In chapter 2, I provide an overview of the two most relevant candidates for next-generation battery anode materials: silicon and lithium metal. Intrinsic failure modes, previous solutions, and remaining challenges will be discussed. Chapter 3 summarizes my graphene cage design to stabilize the silicon anode. With such a design (patent pending), the long-standing obstacles have been addressed. Chapters 4, 5, and 6 explore the second major thrust of this dissertation: fundamental discovery. In chapter 4, I explain the key fundamental working principles of the transmission electron microscope (TEM), a powerful characterization technique that can enable atomic-level observations with both structural and chemical information. In chapter 5, I discuss the in situ TEM studies that revealed the nanoscale corrosion and passivation mechanisms of lithium metal. In chapter 6, I highlight the breakthrough cryogenic electron microscopy technique I pioneered for use in battery materials. Finally in chapter 7, I conclude with the implications of my Ph.D. work and comment on the exciting future directions that can be pursued in the future.

Keywords: Materials Science and Engineering.
Advisor: Cui Yi
Bao Zhenan 
Sinclair Robert (Materials scientist)