VictorJuiz/thesis huggingface dataset:
Generalization of Anderson's theorem for disordered superconductors

The real world is imperfect, and disorder is an inherent feature of condensed matter systems. Whether or not the associated physical effects are of consequence for the properties we are interested in is a separate question. For example, conventional superconductors exhibit a robustness of the critical temperature and energy gap to non-magnetic impurities. This can be understood through Anderson's "theorem" of pairing exact time-reversed states; however, the theorem is not applicable to unconventional superconductors, such as the cuprates, with a sign-changing order parameter where the dirty limit is not well-defined. Moreover, the perturbative and effective medium approximations typically employed to treat the suppression of superconductivity are only valid under certain assumptions about the disorder ensemble and coherence length. While the simultaneous treatment of disorder and interactions typically requires numerical methods without uncontrolled approximations, there are interesting questions that emerge if we restrict ourselves to an exact treatment of disorder within BCS theory. The first part of the thesis focuses on the effect of disorder on the mean-field transition temperature Tc. In particular, we argue that mean-field Tc is always increased in the presence of disorder independent of order parameter symmetry, disorder strength, and spatial dimension. This can be understood through an analogy with Lifshitz tails is disordered semiconductors where rare regions conducive to bound states produce exponential tails in the density of states. While this is valid as a strict mathematical statement, the physical content only becomes relevant for short-coherence length superconductors. We then revisit the conventional wisdom that the overdoped cuprate phase diagram can be described entirely by dirty d-wave BCS theory. An extensive mutual inductance experiment probing the superconducting dome and overdoped quantum critical point has provided compelling evidence for a vanishing superfluid stiffness as Tc --> 0 in the ultra-clean limit. The drop in superfluid density without the usual signatures of pair-breaking disorder suggests a simple mean-field approach is at least partially incomplete. To address the applicability of dirty d-wave BCS theory in the overdoped regime, we compute the superfluid density for various disorder ensembles that are microscopically motivated by the chemistry of the cuprates. We find that the disorder models can capture some features observed the experiments, but typically require unrealistically high impurity concentrations. The latter part of this thesis involves other projects on strongly correlated systems including computations for thermal conductivity and spin susceptibility for chiral p-wave models of strontium ruthenate 214, a DMRG study of the t1-t2-J1-J2 model on a 4-leg ladder, and a phenomenological model of twisted bilayer graphene.

Keywords: Physics.
Advisor: Kivelson Steven 
Hwang Harold Yoonsung
Raghu Srinivas
Generative Bayesian networks for conceptual aircraft design

Conceptual aircraft design, with its basis in engineering design, is an open-ended problem in which human designers synthesize solutions to meet a set of requirements. This open-ended prob- lem inherently necessitates an iteration process combining creation and testing. Designers approach these problems with their intuition, experience, and knowledge of physics to achieve this iteration process. However, future aircraft design requirements break away from traditional norms, leaving the seasoned human designer with little intuition. This work devises an architecture by taking cues from how human designers lead design pro- cesses. This architecture also becomes an iterative design loop with creation and testing. A prob- abilistic model, the generative Bayesian Network, suggests candidate designs for the architecture. The generative Bayesian Network decomposes the problem into physical components and finds the interactions between them, as a systems design. The generative Bayesian Network learns examples from a combination of historical data and generations analyzed with SUAVE, an aircraft conceptual design tool. SUAVE is especially suited for this process since it possesses the ability to analyze and optimize numerous types of aircraft. This architecture enables a human designer to consider concepts and configurations they might have otherwise not considered. Four test cases examine the effectiveness of this architecture that combines SUAVE with a gen- erative Bayesian Network. First, a simple beam design illustrates how multiple valid solutions may be found. Next, are two cases, that design with differing levels of complexity to compare against an existing medium-range airliner. Finally, an ultra-long-range aircraft is designed with mission requirements unprecedented today. The architecture returns feasible design concepts prepared for more in-depth design studies and development.

Keywords: Aeronautics and Astronautics.
Advisor: Alonso Juan José
Kochenderfer Mykel J.
Kroo Ilan
Genomic and transcriptional signatures of Epstein-Barr virus-associated malignancies

Epstein-Barr Virus (EBV) is causally associated with the development of malignancies across multiple tissue types. In transplant recipients, EBV can cause an aggressive spectrum of malignancies called post-transplant lymphoproliferative disorder (PTLD). Traditionally, it is thought that immunosuppression is the precipitating factor in the development of PTLD; however, only a small portion of transplant recipients develop PTLD. Here, we describe how EBV genome diversity, immune response, and cellular pathways contribute to development of EBV-associated malignancies, including PTLD. In chapter 2, we discuss how PTLD-associated variations potentially alter the immune response. We sequenced the EBV genome from transplant recipients with and without PTLD to determine which variations are unique to PTLD patients. We identified 15 novel PTLD-associated non-synonymous variations, including eight in EBNA3C. Then, we used NetMHC and NetMHCII to predict how these PTLD-associated variations alter the binding of EBV-derived peptides to HLA-A, -B, and -DR molecules. In chapter 3, we address the cellular pathways involved in EBV-oncogenesis. We conducted an integrative, multi- cohort meta-analysis of three gene expression datasets from PTLD, gastric cancer, and Hodgkin's lymphoma containing EBV-positive (EBV+) and EBV-negative (EBV-) tumor samples. We identified an EBV+ tumor gene signature that represents a network of genes that are commonly expressed in EBV infected cells across various cancers. Using siRNA and RNA-seq, we determined that one of the genes in the EBV+ tumor gene signature, C21orf91, regulates the expression of genes involved in NF-kB and Type I interferon signaling. Future directions of this work are summarized in chapter 4.

Advisor: Martinez Olivia
Bhatt Ami (Ami Siddharth) 
Davis Mark M. 
Khatri Purvesh
Genomic characterization of CHD8 with implications for autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by restricted social interaction, impaired verbal and non-verbal communication, and repetitive behavior. ASD is estimated to affect 24.8 million people worldwide and is diagnosed in about 1.7% of children in the United States. It is well established that ASD has a strong genetic component with evidence of allelic and locus heterogeneity. Yet, the underlying genetic cause of ASD is unknown for at least 70% of cases. Recently, largescale exome sequencing studies of ASD patients from unaffected parents have led to the discovery of candidate genes based on de novo loss-of-function mutations that carry large biological effects and high risk for ASD. Currently, mutations in several chromatin regulators have been causally linked to human neurodevelopmental and psychiatric disorders, such as ASD and schizophrenia. One such chromatin remodeler, chromodomain helicase DNA binding protein 8 (CHD8), is associated with 12 mutated alleles, consisting of nonsense mutations or frameshift insertions/deletions that confer a haploinsufficient phenotype. CHD8 has been established as one of the most frequently mutated genes in ASD. CHD8 is thought to use the energy of ATP hydrolysis to catalyze structural changes in chromatin, allowing transcription factors to access their cognate binding sites, replace histones with histone variants, and reposition nucleosomes on a DNA template to tightly control gene expression. CHD8, a member of the CHD6-9 subfamily of CHD chromatin remodelers, exhibits a diverse range of functions in transcriptional regulation. Ectopic expression studies have indicated that CHD8 suppresses p53-dependent activation and apoptosis. It has also been found to regulate the Wnt signaling pathway by repressing β- catenin target genes. Previous chromatin immunoprecipitation (ChIP) experiments have shown that CHD8 binds to the promoters of approximately 2000 active genes that are enriched for H3K4me2 and H3K4me3 marks. In addition, CHD8 has been shown to interact with CTCF, with members of the MLL1 transcription activation complex, and with elongating RNA Polymerase II (RNAPII). CHD7, which causes CHARGE syndrome, a condition characterized by abnormal development of the neural crest, has also been shown to interact with CHD8. This thesis covers a brief overview of where the field of autism is now, an in-depth analysis of the genomic characterization of CHD8 and the role that it plays during the early stages of neurogenesis, and characterization of a CHD8 haploinsufficient mouse model that is able to recapitulate some of the autism phenotypes in vivo.

Keywords: Stem Cell Biology and Regenerative Medicine.
Advisor: Crabtree Gerald R. 
Jackson Peter K. (Peter Kent) 
Palmer Theo
Geometric and structural inference on shape collections

Shapes are all around us, and relationships between them are understood intuitively. These relationships are often analyzed by means of using different similarity metrics. These similarity metrics provide understanding about the salient features of a set of shapes, providing pointers to what the similarities on a set of shapes are, and how they are different from other shapes. With increased availability of three-dimensional data, the need for understanding different shape modalities and unifying information obtained from them becomes crucial. This thesis delves deep into how shape geometry and shape structure can be used as similarity metrics to analyze shape relationships. This is followed by real-world applications of obtaining these similarity-based shape relationships. The similarity of shape geometry is shown to be useful in obtaining shape correspondences on pairs of shapes and shape collections. Structural similarity on shape collections, provide different kinds of structural priors, which are useful in completing partial shapes. This thesis work has pioneered shape correspondences between nonisometric shapes. While shape matching on isometric pairs of shapes is a well-studied problem, most real-world shape pairs and collections are nonisometric in nature, and this is a crucial problem to solve. An novel consideration that we introduce on computing maps on shape collections, is the notion of modularity. While consistency is an important consideration that is already in use, coupling it with modularity makes the correspondence computation process much quicker. While these two problems involve using shape geometry as a cornerstone to solve real world correspondences, we also shape structure as an important similarity metric, and use it to complete real scans. Here, we discuss two different paradigms in shape completion. We introduce structure-aware shape templates, that can be useful in performing shape completion. To this effect, we provide a template-based optimization approach, which is coupled with a multi-view CNN to infer the structure of complete and partial point clouds. This is shown to be useful in partial scan completion, scene completion and segmentation tasks. In addition to this retrieval-based shape completion technique, we also provide a surface reconstruction technique on point clouds that utilizes topological structure of the shape. This surface completion technique is unique in the fact that it provides a handle on solving the hard combinatorial topology-aware optimization problem. As these techniques are more general in nature, they can be useful in spheres which are even removed from shape similarity understanding. This is discussed in the concluding segment of the thesis, along with directions for future research.

Keywords: Electrical Engineering.
Advisor: Guibas Leonidas J. 
Boyd Stephen P. 
Weissman Tsachy
Geometric sensitivity, wake dynamics, and machine learning turbulence modeling on a skewed bump

A flow is considered geometrically sensitive if a slight perturbation to the geometry results in a major change to the flow structure. This work examines the flow over a wall-mounted, skewed bump, which exhibits geometric sensitivity. The bump is three-dimensional and has elliptical cross-sections with axis ratio of 4/3, and the geometry is modified by placing the bump at different angles with respect to the freestream. A combined experimental and computational approach is used to study the bump flow. The distinguishing features are a large separation bubble and longitudinal vortex structures in the wake. The wake has a quasi-periodic shedding cycle that is examined with Spectral Proper Orthogonal Decomposition (SPOD) and conditional averaging. Experiments are done to examine how the flow changes when the bump surface is rough. Reynolds Averaged Navier-Stokes (RANS) simulations have poor accuracy in this flow, and a method is developed to improve RANS accuracy using machine learning.

Keywords: Mechanical Engineering.
Advisor: Eaton John K. 
Dabiri John O. (John Oluseun)
Elkins Christopher J.
Geospatial Analysis of Near-Term Potential for Bioenergy with Carbon Capture and Storage (BECCS) in the United States

Bioenergy with carbon capture and storage (BECCS) is a negative emissions technology (NET) that may play a crucial role in climate change mitigation. BECCS relies on the capture and sequestration of carbon dioxide (CO2) following bioenergy production to remove and reliably sequester atmospheric CO2. Previous BECCS deployment assessments have largely overlooked the potential lack of spatial co-location of suitable storage basins and biomass availability, in the absence of long-distance biomass and CO2 transport. These conditions could constrain the near-term technical deployment potential of BECCS due to social and economic barriers that exist for biomass and CO2 transport. This study combines published biomass production data, published storage capacity data, and newly calculated injectivity estimates at high spatial resolution to assess the near-term deployment opportunities for BECCS in the U.S.
If the total biomass resource available in the U.S. was mobilized for BECCS, an estimated 370-400 Mt CO2 yr-1 of negative emissions could be supplied in 2020. Of the total available biomass, the technical potential of negative emissions from biomass that has co-located biomass and suitable storage sites is 100-110 Mt CO2 yr-1. In 2040, under the assumption that significant quantities of dedicated energy crop production materialize, the total BECCS potential increases to 360-630 Mt CO2 yr-1. Meeting this technical potential would require large-scale deployment of BECCS technology. Over 1000 counties have the technical potential for near-term BECCS, although approximately half of the technical potential is available in the 200 counties with the highest biomass potential across the U.S. If efficient methods for collecting and transporting biomass are developed, this could result in fewer and larger projects, thus decreasing the number of injection wells by nearly a fifth. Specifically, the Illinois basin, Gulf region, and western North Dakota have the greatest potential for near-term BECCS deployment. The high-resolution spatial assessment conducted in this study can inform near-term opportunities that minimize social and economic barriers to BECCS deployment.

Keywords: School of Earth Energy &amp; Environmental Sciences
Department of Energy Resources Engineering
Thesis
Advisor: Benson Sally M.
Ge/SiGe quantum confined stark effect waveguide modulator for optical interconnects

The improved performance of computer systems has been realized by downscaling the integrated circuit minimum feature sizes. However, interconnection through wires is becoming increasingly difficult such that the signal I/O rate cannot keep up with the growth of computational performance. Optical interconnects provide a promising solution to this on-chip interconnect bottleneck. To meet the energy requirement, a system with an off-chip laser and Si-compatible on-chip modulators and detectors appears to be the most probable approach. Among Si compatible modulators, Ge/SiGe quantum-confined Stark effect (QCSE) modulators are the best approach to meet both the speed and power targets. This thesis proposed and investigated a 3-dimensional (3D) taper design for Ge/SiGe quantum well waveguide modulators on a Si waveguide to improve the coupling efficiency between the Si bus waveguide and the SiGe devices. We showed by simulations the superiority of the 3D tapers for coupling due to its better maintenance of the fundamental mode. We then demonstrated the fabrication of 3D tapers through grayscale lithography using a Heidelberg Maskless Aligner. When comparing the performance of modulators coupled by 3D tapers and 2D tapers, we showed that 3D tapers can lead to a coupling enhancement by a factor of 4. These 3D tapers combined with the Ge/SiGe QCSE waveguide modulators pave the way to on-chip, integrated modulators and detectors for optical interconnects.

Keywords: Electrical Engineering.
Advisor: Harris J. S. (James Stewart)
Kamins Theodore I.
Miller D. A. B.
Getting cereus about roots: Tracking dynamic plant-microbe interactions in the A. thaliana root system

The symbiotic relationships that bacteria form with plant roots have far-reaching effects on plant physiology. Analysis of symbiotic interactions yield valuable information about the impact of bacteria in the rhizosphere, the interface of plant-soil interactions. Current research has focused on the location and interactions of specific plant and bacterial species to gain insights into effects of their association. My research uses an engineered integrative and conjugative element (ICE) to label bacteria isolated from the roots of the model plant Arabidopsis thaliana with a green fluorescent protein. Fluorescence imagining is then used to visualize bacterial colonization in the roots of wild type and mutant plants. Using this approach, we found that a soil isolate of Bacillus cereus stably colonizes the root tip of both wild type and mutant A. thaliana. Although the bacteria do not significantly affect plant growth, this strain may be useful as an engineered probiotic in the future because it stably colonizes of the root tip of A. thaliana.

Keywords:  Department of Biology
Biology
rhizosphere
plant roots
Bacillus cereus
Bacillus subtilis
ICEBs1
photosynthesis mutations
Thesis
Advisor: Dinneny José
Long Sharon
Getting into the Weeds: Competition and Cheating in the Washington State Marijuana Market

To sustain profitability, firms strive to gain any edge over their competitors: sometimes even acting illegally. This paper looks into the effect of the level of competition on the rates of license violations within the Washington State Recreational Marijuana Market. I exploit a 2016 policy change in which some counties received a bump in the amount of firms allowed to operate in the county, while others did not. Using a difference-in- differences approach around this competition shock, this paper finds that counties that received more licenses were correlated with significant, higher levels of license violations than those that did not.

Keywords:  Department of Economics
Department of Economics
Stanford University
Competition
Marijuana
Washington
Cheating
Difference-in-Differences
License
County
Regulation
Thesis
Advisor: Clerici-Arias Marcelo
Larsen Brad
The gilded renewal : capital, politics, and the re-fashioning of Marseille

By labeling Marseille's urban renewal gilded, this dissertation argues that the city's rehabilitation is inherently spectacular. Marseille's EuroMediterranean renovation participates in a profound mystification of the social relations of capital accumulation and state governance, visible in the limits of the discursive understandings of the changing city center. As the French State works to take Marseille from murder capital to fashion capital, the material and discursive spectacle of the transformation of urban space and cultural life obscures not only the city's entrenched poverty, ethnic divisions, and housing insecurity, but, even more disconcerting, the increasing imbrication of state and capital and the abandonment of the city's political sphere. In this quest for demystification, I uncover how the process of refashioning Marseille devolves into the production and circulation of spectacles of renewal by tracing the networks and social relations of a diverse cast of actors, including city and state officials, real estate developers, urban planners, business owners, and fashion designers. Finally, I question the possibility of the resuscitation of the political sphere by examining how several citizen-led associations and the networks they constitute articulate alternative ways of living together in the struggle over the meaning, image, and experience of urban space and the future of Marseille.

Keywords: Anthropology.
Advisor: Ebron Paulla A.
Ferguson James
Hansen Thomas Blom
Yanagisako Sylvia Junko
Going viral : printing disease in early modern Germany

This dissertation traces the cultural history of virality to the turn of the sixteenth century and uncovers the pervasive notion that ideas can be transmitted analogously to diseases. I argue that a discourse of virality, which is commonplace in the digital age, arises in this period in response to the development of new forms of print media. By looking at the works of vernacular poets and Humanist scholars as well as medical professionals, both canonical and non-canonical, and by discussing three contagious diseases with different pathological and social profiles - plague, syphilis, and the English sweating sickness - this dissertation expands our picture of early print to include sources that have generally been excluded from print's history. This dissertation also contributes to the recent scholarly tendency to view print as a technological development whose introduction also included setbacks, continuities, and criticism, rather than as a phenomenon that revolutionized early modern Europe. Writers on these three diseases raise concerns that print spreads harmful or false information, stokes fears, and cannot be controlled. As such, these writers participate in a discourse of virality, suggesting that printed information on disease may be more dangerous than the disease itself.

Keywords: German Studies.
Advisor: Starkey Kathryn 
Daub Adrian 
Findlen Paula 
Puff Helmut 
Stokes Laura