VictorJuiz/thesis huggingface dataset:
Analysis of Pathologic Complete Response Rates Between Different Neoadjuvant Radiation Treatment Regimens for Rectal Cancer

The standard of care for rectal cancer is long or short course radiation followed by surgery with or without adjuvant chemotherapy. Recently, total neoadjuvant therapy (TNT), an approach consisting of giving all chemotherapy and radiotherapy prior to definitive surgery, has been demonstrated to be a promising alternative. This study aims to assess the pathologic complete response (pCR) rates among different neoadjuvant treatment regimens and determine if neoadjuvant chemotherapy improves pCR rates. Electronic medical databases were queried to identify rectal cancer patients treated with neoadjuvant therapy at one institution from 2006-2019. Patients were grouped accordingly: long-course chemoradiation (CRT), long-course chemoradiation with chemotherapy (CRT TNT), short-course radiation (SCRT), and short-course radiation with chemotherapy (SCRT TNT). Patients without follow-up data or surgical pathology reports were excluded. pCR was defined as no evidence of disease at surgery. pCR rates were compared using descriptive statistics and Chi-square analysis. 249 patients were analyzed. There were 200 (80.3%) patients who received CRT, 26 (10.4%) who received CRT TNT, 13 (5.2%) patients who received SCRT, and 10 (4%) patients who received SCRT TNT. Initial stage was different between groups, with metastatic patients more likely to receive SCRT TNT (p<0.001). The median time to surgery were significantly different between groups (p<0.001). 11 (42.3%) and 6 (60%) patients received FOLFOX, and 13 (50%) and 4 (40%) of the patients received XELOX for CRT TNT and SCRT TNT, respectively. The remaining patients (7.7%) in the CRT TNT group received Capecitabine. For CRT, 53 (26.5%) patients achieved pCR, 3 (11.5%) in CRT TNT, 1 (7.7%) in SCRT, and 2 (20%) in SCRT TNT. None of these differences were statistically different (p=0.19). On univariate analysis, age (p=0.13), clinical T stage (p=0.13), clinical N stage (p=0.95), time to surgery (p=0.82), and presence of chemotherapy in the neoadjuvant regimen (p=0.22) were not significant predictors for pCR. Surprisingly, in this analysis, total neoadjuvant treatment for rectal cancer did not improve pCR rates over CRT or SCRT alone. Because of the relatively small numbers of patients in the TNT and SCRT groups, interpretation of these data should be considered preliminary. These data indicate that given the high pCR rates achievable with standard of care CRT, additional gains in pCR rates may require a more intensive TNT approach. Future studies are needed to further investigate this hypothesis prospectively.

Keywords:  Department of Biology
Biology
rectal cancer
total neoadjuvant therapy
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Thesis
Advisor: Le Quynh
Morrison Ashby
Analyzing Candidates' Ideological Messaging Throughout the Electoral Cycle

Conventional wisdom suggests that primary elections attract a loyal base of partisans, and consequently, political candidates must take more extreme positions to secure the nomination before moderating for the general electorate. Yet, the academic literature contains little empirical evidence on candidate positioning over the electoral process. I address this gap by using congressional candidates' tweets to quantify ideological rhetoric during the 2020 election using three different approaches. First, I adopt a data-driven approach to select the most partisan bigrams and specify a multinomial model of speech; second, I use a theoretically-derived dictionary to measure the frequency of moral values associated with political convictions; finally, I specify a natural language model using a deep learning architecture. I provide one of the first empirical analyses on the evolution of candidates' ideological messaging over the entire election cycle. I find statistically significant evidence of moderation among Republican but not Democratic candidates, with mixed support for greater movement in competitive general elections. I conclude that Republicans likely face stronger incentives than Democrats to employ extreme rhetoric in primaries and thus to moderate in general elections.

Keywords: Machine Learning
Social Media
Stanford University Department of Economics
Political Communication
Ideology
Elections
Text Analysis
Political Economy
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Thesis
Advisor: Gentzkow Matthew
Analyzing the Relationship Between Exchange Rate Pass-Through and Inflation Persistence

I measure the relationship between exchange rate pass-through and inflation persistence across 22 small and medium sized economies with mostly flexible exchange rates. Using data from the International Monetary Fund, national statistics offices, and the Bank for International Settlements, my estimates for exchange rate pass-throughs and inflation persistence present two main results. First, I find that a positive, non-linear relationship exists between exchange rate pass-through and inflation persistence across the sample countries. Second, I find some evidence that countries that have had varying levels of monetary policy success display a similar non-linear relationship between exchange rate pass-through and inflation persistence across time. These two results suggest that the dynamics of inflation depend in part on the sensitivity to inflationary shocks and thus the efficacy of monetary policy.

Keywords: Exchange rate pass-through
Inflation persistence
Monetary policy
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Thesis
Advisor: Bocola Luigi
Taylor John B.
Angafakafonua as Tongan identity : Tongan Mormonism, the Tongan crip gang, and sacred education spaces

In this dissertation, I survey Tongan historical narratives, ethnographies, social media, and personal interviews to understand the role of religion in producing a Tongan American identity. In analyzing details from this survey, I identify the religious thread of angafakafonua (way of the land) as the process by which Tongans navigated their new American landscape in the 1950s and beyond. The thread of angafakafonua connects 19th c. Wesleyan Methodist Christianity, Tongan Mormonism, and Tongan Crip Gang members in Utah. My dissertation argues that religion is essential to understanding Tongan collective identity in America. Tongan Americans construct their ethnic and racial identities through the lens of religion—that is, Tongans navigate their racial identity in America through a religious epistemology. Indeed, for Tongan Americans, religion and race are co-constitutional: their religious and racial identities are created over and against each other

Keywords: Religious Studies.
Advisor: Gin Lum Kathryn
Chang Gordon H.
Diaz Vicente M. (Vicente Miguel)
Animal entanglements : interspecies performance in South Asia

Animal Entanglements investigates how performance articulates the ways in which humans and nonhuman animals encounter, transform, and entangle each other. Situated within the context of the resurgence of a nationalist political discourse in India that asserts the importance of certain animals to the Indian social and religious fabric, the dissertation explores how nonhuman animals shape the discourses of religion, caste, class, gender, and sexuality. It queries how animals entangle us in their mythological and material charge, and move us to reconsider normative forms of sociality, subjecthood, and belonging. Drawing upon a capacious understanding of performance that includes political protest, traditional sport, independent film, performance art, and folklore, each chapter considers affective and embodied entanglements that are premised on touching, venerating, consuming, protecting, and imagining animals. My case studies contend that interspecies performance is not limited to practices of intimacy, adoration, and kinship, but also addresses encounters with nonhuman animals that are precarious and contested. Animal Entanglements connects performance to broader questions of religious assertions and state violence; casteist and gendered marginalization; and nationalistic and migrant belonging. In doing so, this dissertation provides critical insights into the ways in which interspecies modes of performance are crucial to the processes of being and becoming in South Asia and its diasporas

Keywords: Theater and Performance Studies.
Advisor: Menon Jisha
Brody Jennifer DeVere
Inoue Miyako
Robinson Aileen
Animal migration and behavioral flexibility in an era of rapid global change

Migration is a widespread, critical, and increasingly-threatened behavior expressed by diverse animal taxa. Beyond being one of the most awe-inspiring biological phenomena on Earth, migration also plays a key role in ecosystem functioning worldwide. Despite the prevalence of this behavior and its ecological and evolutionary significance, migration is a complex behavior, leaving significant knowledge gaps in understanding how animals navigate environmental variability and human-induced rapid environmental change in deciding when and where to migrate. This gap stems in part from the difficulty of observing and integrating individual-level and population-level behavior of migratory species in the wild, especially in oceanic ecosystems. The complexity and scale of animal migration also challenges applied ecologists and natural resource managers to develop more dynamic management strategies for the protection of migratory species alongside human resource use. In this dissertation, I aim to advance both theoretical and applied ecological understanding of animal migration by exploring the role of social cues and environmental variability in migration, linking individual and population-level behavior for observation of migration in remote ecosystems (specifically in the migratory Eastern North Pacific blue whale population), and considering the tools and strategies required for dynamic and equitable management of migratory populations and the ecosystems they inhabit

Keywords: Biology.
Advisor: Crowder Larry B.
Goldbogen Jeremy
McKenna Megan F.
Micheli Fiorenza
Ryan John (Oceanographer)
Anisotropic electron hydrodynamics

This dissertation explores the physical consequences of point anisotropy in hydrodynamic systems, focusing in particular on hydrodynamic electrons in ultra-pure, quasi-two-dimensional metals at low temperature. Since the presence of an ionic lattice breaks continuous rotational invariance in this context, textbook Galilean-invariant hydrodynamics is generically inappropriate for electron fluids and must instead be generalized to account for the reduced symmetry. First, an introduction to electron hydrodynamics and the relevant group theory is given. Next, a kinetic theory model for electronic scattering in two-dimensional Fermi liquids with polygonal Fermi surfaces is developed, and the consequences of point anisotropy for this model's hydrodynamic limit are discussed. A systematic treatment of the viscosity tensor for two-dimensional fluids of arbitrary point group is then given, followed by a proposal for a symmetry-exploiting viscometry technique that can isolate and measure the multiple, distinct viscosity components that generically appear in anisotropic fluids. Finally, the implications of inversion-symmetry breaking in an anisotropic electron fluid are studied by specializing to the case of a triangular point group. The breaking of inversion symmetry is found to allow for an analogue of the piezoelectric effect in solids, and a highly-symmetrical device geometry for detecting this ``hydrodynamic piezoelectric effect" is proposed

Keywords: Physics.
Advisor: Kivelson Steven
Lucas Andrew (Postdoctoral fellow in theoretical condensed matter physics)
Goldhaber-Gordon David
Hartnoll Sean
Antigen-driven B cell responses in RA and Sars-Cov-2 vaccination

B cells play a central role in protective immunity by secreting antibodies directed against antigens from pathogens, and by activating T cells via antigen presentation of the cognate antigen. Conversely, in autoimmunity, B cells play a pathogenic role by secreting autoantibodies against self-antigens and triggering autoreactive T cells. However, the exact mechanisms mediating the development of antigen specific B cell responses in autoimmunity and vaccination warrant further investigation. Here, we characterize the B cell responses in patients with seropositive rheumatoid arthritis (RA) and in individuals who received the BNT162b2 mRNA vaccine against SARS-CoV-2. By sequencing the plasmablasts repertoire of RA patients, we demonstrate that extensively somatically hypermutated RA blood plasmablasts encode anti-citrullinated protein antibodies (ACPA) that target both citrullinated human autoantigens and in situ citrullinated epitopes from oral bacteria. In RA patients with periodontitis, oral bacteremias result in systemic translocation of these citrullinated oral bacteria into blood activating ISG15+ inflammatory monocytes, a myeloid population associated with clinical arthritis flares and present in RA synovium. Our findings indicate that repeated oral bacterial mucosal breaks mediate autoimmunity by driving activation and epitope spreading of the ACPA response to target both citrullinated bacterial and human antigen(s) via molecular mimicry. Additionally, we characterize the B cell response to the novel BNT162b2 mRNA vaccine against SARS-CoV-2 spike (S). The first vaccine dose elicits IgA+ plasmablasts against S protein subunit S2 (S2) on day 7, consistent with a secondary memory response derived from prior infections with betacoronaviruses that cause the common cold. On day 21, we observed an influx of minimally mutated IgG+ switched memory B cells against the S protein subunit S1 (S1) that contains the receptor binding domain (RBD), representing a primary response of recently matured naive B cells. The second vaccine dose boosted the anti-S1 and anti-RBD B cell response and produced high titers of antibodies that potently neutralize Wuhan-Hu-1 SARS-CoV-2 pseudovirus and partially neutralize novel variants. Taken together, our results demonstrate how B cell responses continuously evolve to contribute to health and autoimmunity

Keywords: Immunology.
Advisor: Robinson William (William Hewitt)
Davis Mark M.
Engleman Edgar G.
Kim Peter
Antitrust Law and Catastrophic Risk: Tension, Perspectives, and Reform

Coordination among international companies has the potential to meaningfully assist in reducing the likelihood and severity of global catastrophic risks. Risk-reducing initiatives might include companies mutually agreeing to reduce their carbon footprint, ensure that advanced AI systems are safe and robust before deployment, or preventing malicious actors from using advances in biotechnology to create novel bioweapons. However, current antitrust law jurisprudence is hostile to these efforts. Current antitrust law categorically rejects the notion that competition can ever be harmful, for example by pressuring companies to cut corners and increase risks, instead focusing on protecting a dangerously narrow conception of consumer welfare. In this paper, I dissect this tension, trace the evolution of relevant law, apply that law in the context of existing proposals to reduce global catastrophic risks, and propose reform through a narrowly tailored statutory exemption for certain forms of corporate coordination.

Keywords: Public Policy Program
Antitrust, artificial intelligence, climate change, biosecurity, pandemic prevention, longtermism, catastrophic risk, competition policy, international cooperation
Stanford University
Humanities and Sciences
Public Policy Program
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Thesis
Advisor: Freeman Engstrom David
Anyonic quantum computation via F-matrices and duality in quantum group theory

Quantum computers promise to solve problems far beyond our current capabilities. Topological quantum computers promise a scalable approach to quantum computation using intrinsically error-protected bits encoded in two-dimensional materials supporting anyons. This thesis studies the mathematical foundations of Topological Quantum Computing. This means we answer questions about ribbon fusion categories (RFCs) and establish results in the representation theory of quantum groups under the guise of understanding the computational power of theorized topological quantum computers. The main objective to understand the braid group representations arising from anyon systems, since they describe the sets of logic gates available anyonic computers for information processing. In the first part we explain the process of anyonic quantum computing and simulate it by constructing braid group representations arising from RFCs. We express each braid generator explicitly using polynomials in the category's F- and R-matrices. The main novelty is that we designed and implemented an F-matrix solver for SageMath that can explicitly compute unitary braid group representations arising from fusion rings associated to simple complex Lie algebras. In the second part we focus on metaplectic anyons, modeled by the spinor object in the fusion rings associated to orthogonal Drinfeld-Jimbo quantum groups. We obtain the associated braid representations using a detailed description of the centralizer algebras over tensor products of the spinor module These algebras elude the usual methods because the braiding operators have too many eigenvalues. We carve a new path. In the quantum group world, the spinor object can be viewed as a certain exterior algebra, so understanding the desired centralizers is tantamount to proving a quantized skew Howe duality theorem. We develop a unified approach to skew Howe duality via Clifford algebras. First we construct commuting actions of quantum general linear groups that factor through a quantized Clifford algebra and then we extend to orthogonal types through a seesaw. The actions de-quantize appropriately, so our approach unifies various quantum and classical results in the literature

Advisor: Bump Daniel
Conrad Brian
Rowell Eric 
Ying Lexing
Applications of machine learning to some statistical inference problems

With impressive statistical learning techniques, new solutions can be provided to challenging problems in statistics. Statistical questions regarding heterogeneous treatment effects and conditional densities are two such examples. Heterogeneous treatment effects describe the influence of a drug or policy with an emphasis on individual variability. I explored the possibilities of applying machine learning tools to the estimation, inference, and accuracy assessment of heterogeneous treatment effects. Conditional densities characterize how a response depends on a set of covariates and extends conditional means to incorporate information like scale and shape. I developed a series of statistical methods for the conditional density estimation borrowing strengths from decision trees and gradient boosting. Despite the maturity of existing machine learning algorithms, careful modifications are required to adapt standard approaches to non-classification and non-prediction queries with desirable statistical properties

Keywords: Statistics.
Advisor: Hastie Trevor
Tibshirani Robert
Wager Stefan
Application-specific software defined memory

In the past three decades, the clock frequency of CPU processors has increased more than 10x. With the multi-core architecture, CPU processors continue to deliver more and more compute power each year. In contrast, the memory speed is limited by physical constraints and increasingly complicated system topology. Non-uniform memory access, or NUMA, in which one or more types of memory devices are distributed in the system, has become a new normal in today's data center. Non-uniform memory access effects often limit the performance of modern NUMA systems. Remote memory accesses have lower bandwidth and can be hundreds of nanoseconds to microseconds slower than local DRAM accesses. While many memory-intensive applications demonstrate diversified access patterns in both time and space, existing memory systems are hardwired and cannot optimize to application-specific memory access patterns. In this thesis, I will propose Software Defined Memory architecture (SDM), a novel memory system that allows the software to define application-specific policies for data placement and coherence for the critical subset of the data in a NUMA system. I will demonstrate the hardware design of SDM, and discuss the policy designs for application-specific data placement, data coherence, and software-defined memory access. The SDM design significantly improves the performance of HPC applications in a NUMA system, by 2.13x on average for investigated HPC applications, and generates 2.6x performance per dollar for critical database applications

Keywords: Electrical Engineering.
Advisor: Kozyrakis Christoforos
Dally William J.
Horowitz Mark (Mark Alan)
Applying Sensitivity Analysis of Basin Modeling Parameters Based On Fluid Accumulations

Petroleum exploration validates conceptual geologic models. The validation is partly successful. Historically, the industry has been constructing numerical models to forecast its exploratory success. While basin and petroleum system numerical modeling depend on many uncertain parameters, becomes important quantifying the uncertainties included in basin modeling forecasts.
The focus of this dissertation is the distance-based global sensitivity analysis of basin modeling input parameters. The aim is to search the most influent parameters in order to operationally constrain the uncertainty of the forecast.
The methodology is demonstrated with four constructions representing the geology of Campos Basin, a typical oil-bearing passive margin basin. First, with a simple layer-cake model containing just the essential layers for a petroleum system. Second, an Earth model with a characteristically complex structural framework, including a salt layer and three faults. Then, maps of saturation are used to investigate vertical migration within the Earth model. Finally, a perturbation of the structural framework is considered to represent structural uncertainty.

Keywords: Geological Sciences
Sedimentary basins > Mathematical models
Uncertainty > Mathematical models
Petroleum exploration
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Thesis
Advisor: Caers Jef
Hosford Scheirer Allegra
Arbitrary polarization control with reconfigurable metasurface systems

The fundamental motivation of this work is the lack of versatile polarization components. In particular, while there exist methods for creating fixed achromatic waveplates and for tuning the birefringence of single wavelength waveplates, there is no universal waveplate that both works over a broad wavelength range and can be reconfigured to a desired retardance. We will show how metasurfaces—ultra-thin nanophotonics devices—can be combined to create systems capable of achromatic reconfigurable birefringence using a novel dual-metasurface platform. These systems rely on symmetry breaking though micro-scale displacements to modify the polarization state of incident light. We analyze these systems both theoretically and characterize them experimentally. In addition, we generalize this method beyond the naturally occurring basis of linear polarization to entirely arbitrary polarization bases. These arbitrary elliptical waveplates provide versatility for on-demand polarization control. We further show how these reconfigurable systems can be cascaded to form systems that are capable of generating arbitrary polarization states from a given input polarization. This polarization state generation is shown to be achromatic and has the potential for ultra-fast tuning speeds

Keywords: Electrical Engineering.
Advisor: Fan Jonathan Albert
Heinz Tony F.
Miller D. A. B.