VictorJuiz/thesis huggingface dataset:
Dreaming in public : art, politics, and power in late medieval Rome
Keywords: Art and Art History.

In the thirteenth century, the city of Rome was adorned with frescoes, mosaics, and sculptures of dreaming figures: images that frequently depicted a sleeping figure amidst an oneiric scene. This dissertation argues that these dream depictions were a powerful visual tool in the period, one that used the intimate qualities of dreaming to address its audience in profoundly personal terms. These dream images in medieval Rome assimilated scientific conceptions into the visual arts, drew on popular cultures of dream interpretation and divination, illustrated both contemporary and historical political aspirations as well as theology and eschatology. Ultimately this powerful medium, I argue, became a carefully crafted political tool, one that the papacy wielded to great effect in the thirteenth century to illustrate the extent of its role in the life of the faithful, a doctrine clearly espoused by the church beginning with the Fourth Lateran Council of 1215. The first chapter explores the roots of this visual phenomenon, examining the political context and history of how an image of Emperor Constantine dreaming became a central visual device in a small and heavily fortified papal chapel at the Basilica of Santi Quattro Coronati. The second chapter focusses on dream images in the public square: arguing that a scene of a dream depicted on the façade of the church of Santa Maria in Aracoeli served as an overt political statement precisely by appealing to popular practices of dream interpretation. The third chapter considers the city's most prominent dream image, the façade of the Basilica of Santa Maria Maggiore, within the intellectual and scientific culture of the period, arguing that the peculiar image functioned as a kind of diagram of cutting-edge dream science. The final chapter examines thirteenth-century conceptions of dream interpretation, reassessing now-lost frescoes of the Basilica of San Paolo fuori le mura as like a dream to be interpreted by its viewers. A further conclusion reflects on the ethics and politics of this kind of Art History, considering dream interpretation as fundamental part of art historical analysis and methodology. By considering these dreams images as the fundamentally visual nexus of scientific discovery, mass culture, popular religious practices, and political histories in the city I argue that these prominent images of the oneiric were a powerful and political visual medium in medieval Rome that has been largely overlooked in histories of the city
Drugs and the Black Panther Party: A Study in Contradiction. An Ideological and Intimate History, 1966-1972
Keywords:  Department of History
Stanford Department of History
drugs
Black Panther Party
contradiction
dialectical materialism
Huey Newton
violence
Thesis

This thesis uncovers the ideology of the Black Panther Party surrounding drugs alongside Party members' personal experiences with drug addiction as a further exploration of the founding concept of the Black Panther Party, contradiction, in its many manifestations and expressions.
Duration and intensity of end-Permian Marine Anoxia
Keywords: Anoxia
Uranium > Isotopes
Uranium > Concentrations
end-Permian
Monte Carlo method
Text
Thesis

Ocean anoxia was an important kill mechanism in the end-Permian mass extinction and uranium isotope data are among the most powerful tools for quantifying the global extent and duration of ocean deoxygenation. Although coherent stratigraphic variation in uranium isotope ratios (δ238U) and uranium concentrations ([U]) indicative of prolonged deoxygenation is well established, the precise extent of anoxia and associated uncertainty have yet to be quantified. Uncertainty arises from both noise in the data and imprecise knowledge of key parameters within the uranium cycle. In this study, we use the Monte Carlo method to explore a range of scenarios and their implications for the uranium cycle across the Permian-Triassic boundary and through the first 1.7 million years of the Triassic. We then compare model predictions against measured data using principal component analysis to identify model runs and associated parameter values most compatible with trends in the observed data. The best-fitting models indicate a pronounced increase in the extent of seafloor anoxia across the Permian/Triassic transition, reaching ~17.8% of the seafloor (95% CI: [10.9%, 47.1%]), lasting anywhere from 20 kyr to 1.2 Myr. There is an inverse relationship between the extent and duration of anoxia in the set of best-fitting models. This initial pulse of pronounced anoxia is followed by a prolonged aftermath, which continues through the remainder of the study interval, of less extensive, yet still expanded, anoxia covering 7.8% of the seafloor (95% CI: 1.6%, 48.9%]). Both expanded and protracted anoxia are required to fit existing data, with no indication of re-oxygenation during the study interval.
Dynamic introspection
Keywords: Philosophy.

In this dissertation, I study an under-appreciated type of introspection that helps explain how we can come to know the world around us. Much of today's epistemology, can be traced back to the work of Rene Descartes, and to the skeptical challenge he posed: what can we know beyond doubt? A longstanding response to Descartes' challenge is to locate the underlying assumptions that drove him, and others, to their skeptical conclusion; Descartes reached his skeptical position while assuming that subjects have clear and direct access to their own minds, that they have full introspection. During the last 70 years, philosophers have challenged these assumptions, developing tools in epistemology and philosophical logic to study the kind of ignorance subjects have about their own knowledge. Nevertheless, there is a type of introspection, which I call dynamic introspection, that has not caught the attention of epistemologists. This introspection is about, on the one hand, what we know about the way new experience will affect our future knowledge and on the other hand, what we know about the ways we got our current knowledge. Many epistemological debates either ignore such questions or implicitly assume that we are always certain about these matters. Do I need to have the prior certainty that my sources of information are trustworthy in order to gain knowledge from them? The answer to such questions depends on the dynamic introspective abilities we assume we have. Understanding the nature of dynamic introspection can vindicate our reliance on ordinary knowledge in the face of skeptical doubt. A subject might know that there is a tree in front of her (as a result of her perceptual experience) without having the ability to explain the exact source of her knowledge. I argue that this lack of dynamic introspection is natural, and does not lead to skeptical problems. In this dissertation, I introduce a new logical framework for analyzing and modeling dynamic introspection. After introducing the logical framework in Chapter 2, I use it to analyze important debates from the contemporary epistemological literature in which, I argue, dynamic introspection principles implicitly play a key role, and much can be learned by making them explicit. One debate concerns the skeptical challenge to the possibility of our perceptual knowledge about the external world: how can we answer the skeptic who doubts the possibility of perceptual knowledge? The second debate concerns the limits to which we can know and access our own internal mental world: what can we know about our own knowledge? By making the underlying dynamic introspection principles explicit in such debates, I hope to make a meaningful contribution to our understanding of our own knowledge
Dynamics in nanostructured liquids and surfaces probed with nonlinear infrared and optical spectroscopies
Keywords: Chemistry.

Many condensed phase systems with complex nanostructure are regularly being developed to address important technological problems. Although the systems may appear static on a macroscopic level, at the molecular level their structure is constantly evolving on ultrafast time scales. However, because these materials are new and more complex than the existing ones, much is still unknown about the local structures and dynamics that give rise to their function. Nonlinear infrared and optical spectroscopies are a powerful class of methods that measure the ultrafast dynamical fluctuations occurring in molecular systems. These methods use short femtosecond pulses of light to perturb and subsequently probe the optical properties of a material system through interactions with molecular properties such as vibrations or molecular polarizabilities. Polarization-selective pump-probe (PSPP) and two-dimensional infrared (2D IR) spectroscopies respectively measure the orientational dynamics and vibrational frequency dynamics of a vibrational probe molecule, which can serve as a reporter of the surrounding structure. Optical Kerr Effect (OKE) spectroscopy measures the collective polarizability dynamics of a molecular ensemble, providing information on collective orientational dynamics. Using these methods, the dynamics in three classes of molecular systems, an ionic liquid, mesoporous silica, and a dipolar liquid, were revealed
Effective mapping class group dynamics
Keywords: Mathematics.

We prove a quantitative estimate with a power saving error term for the number of filling closed geodesics of a given topological type and length at most L on an arbitrary closed, orientable, negatively curved surface. More generally, we prove estimates of the same kind for the number of free homotopy classes of filling closed curves of a given topological type on a closed, orientable surface whose geometric intersection number with respect to a given filling geodesic current is at most L. The proofs rely on recent progress made on the study of the effective dynamics of the mapping class group on Teichmüller space and the space of closed curves of a closed, orientable surface, and introduce a novel method for addressing counting problems of mapping class group orbits that naturally yields power saving error terms. This method is also applied to study counting problems of mapping class group orbits of Teichmüller space with respect to Thurston's asymmetric metric
Effects of optical and environmental parameters on angle-resolved photoemission from materials
Keywords: Applied Physics.

Studies in condensed matter physics have led to the discovery of a profusion of materials with interesting quantum properties, such as superconductors and topological insulators. The wide variety of material systems demands a wide variety of experimental techniques. I focus on two techniques: angle-resolved photoemission spectroscopy (ARPES), which measures electronic band structure in the energy and momentum domains; and time-resolved ARPES, which probes out-of-equilibrium phenomena by extending ARPES to the time domain. There are many parameters which can affect measurements of quantum materials. I show how varying nonlinear crystal thickness in an ultrafast laser setup allows for fine-tunable time and energy resolution in time-resolved photoemission. Achieving a high degree of control over resolutions is critical for enabling new experiments. I also investigate how Bi2Se3 surfaces change to bismuth upon exposure to air, potentially affecting results of surface-sensitive measurements in atmosphere. High control and understanding of temporal, spectroscopic, and sample composition properties, as well as the optical and environmental parameters which control them, are essential to performing successful experiments on quantum materials
The effects of relatedness and population structure on patterns of genomic sharing
Keywords: Genetics.

In this dissertation, I use several approaches to study patterns of genomic sharing. Chapters 2 and 3 take a theoretical approach, modeling the effect of consanguinity on patterns of genomic sharing. In Chapter 4, I describe a new method to detect IBD segments between closely related individuals. Lastly, in Chapter 5, I take a data-driven approach, analyzing levels of genomic segment sharing as well as genotype sharing to understand the genetic relationship between ancient and modern Indigenous individuals in North America
Efficient predictive coding in neural networks in the presence of disorder and delays
Keywords: Physics.

Biological neural networks face a formidable task: performing reliable computations in the face of intrinsic stochasticity in individual neurons, imprecisely specified synaptic connectivity, and nonnegligible delays in synaptic transmission. A common approach to combatting such biological heterogeneity involves averaging over large redundant networks of N neurons resulting in coding errors that decrease classically as 1/sqrt(N). Recent work demonstrated a novel mechanism whereby recurrent spiking networks could efficiently encode dynamic stimuli, achieving a superclassical scaling in which coding errors decrease as 1/N. This specific mechanism involved two key ideas: predictive coding, and a tight balance, or cancellation between strong feedforward inputs and strong recurrent feedback. However, the theoretical principles governing the efficacy of balanced predictive coding and its robustness to noise, synaptic weight heterogeneity and communication delays remain poorly understood. To discover such principles, we introduce an analytically tractable rate-neuron model of balanced predictive coding, in which the degree of balance and the degree of weight disorder and noise can be dissociated unlike in previous balanced network models, and we develop a mean field theory of coding accuracy. Furthermore, we extend our analysis and elucidate the dependence of coding accuracy on delays and noise in a spiking neural model. Overall, our work provides and solves a general theoretical framework for dissecting the differential contributions neural noise, synaptic disorder, chaos, synaptic delays, and balance to the fidelity of predictive neural codes, reveals the fundamental role that balance plays in achieving superclassical scaling, and unifies previously disparate models in theoretical neuroscience
Efficient simulation for complex systems
Keywords: Management Science and Engineering.

This dissertation consists of two parts, with the central topic on efficient simulation. The first part focuses on the problem of optimal stratified sampling with finitely many and infinitely many strata. We present a more general framework for analysis and design of adaptive sampling algorithms achieving optimal convergence rate. We show that asymptotic optimal variance can be achieved. The second part focuses on hospital-level COVID demand forecast, where we provide a method to generate consistent forecast intervals. We show that no stationarity assumption of the underlying point process is required for the proposed method. Furthermore, the model is computationally lightweight to estimate, as compared to epidemiology and machine learning based models
Electric field driven microfluidics for acceleration of CRISPR enzyme kinetics and its application in molecular diagnostics
Keywords: Aeronautics and Astronautics.

Rapid and early-stage screening is crucial, especially during pandemics, for early identification of infected persons and control of disease spread. CRISPR biology offers new and effective methods for rapid and accurate pathogen detection. Despite their versatility and specificity, existing CRISPR diagnostic methods suffer from the requirements of up-front nucleic acid extraction, large reagent volumes, and several manual steps — factors which prolong the process and impede use in low-resource settings. Moreover, the sensitivity and assay time for CRISPR-based approaches are fundamentally limited by the enzyme kinetic rates. In this experimental and theoretical work, we combine microfluidics, on-chip electric field control, and CRISPR to directly address limitations of current CRISPR diagnostic methods. We find that electric field gradients can be used to control and accelerate CRISPR reactions by co-focusing Cas--gRNA, reporters, and target nucleic acids within a microfluidic chip. We achieve an appropriate electric field gradient using a selective ionic focusing technique known as isotachophoresis (ITP) implemented on a microfluidic chip. In this thesis, we first develop and validate a model based on Michaelis-Menten enzyme kinetics theory and tailor it to regimes common in conventional CRISPR diagnostics. We map out an estimate of the limits of detection and achievable assay speeds of existing CRISPR-based diagnostics given current known and consistent (i.e., physically possible) kinetics rate data. We then develop a kinetics model which couples ITP physics with CRISPR reactions. We experimentally validate the model and identify key regimes for product formation and reaction acceleration in ITP. We then apply our ITP-CRISPR method to the rapid (30 min) detection of the RNA of SARS-CoV-2, the virus that causes COVID-19, starting from raw nasopharyngeal swab samples. Unlike previous CRISPR diagnostic assays, we also use ITP for automated purification of target RNA from raw samples. This electric field control enables a new modality for a suite of microfluidic CRISPR-based diagnostic assays
Electrically reconfigurable phase-change antennas and metasurfaces
Keywords: Electrical Engineering.

The success of semiconductor electronics is built on the creation of compact, low-power switching elements that offer routing, logic, and memory functions. The availability of nanoscale optical switches could have a similarly transformative impact on the development of dynamic and programmable metasurfaces, optical neural networks, and quantum information processing. Phase-change materials are uniquely suited to enable the creation of dynamically tunable optical elements and metasurfaces, as they offer high-speed electrical switching between amorphous and crystalline states with notably different optical properties. Their non-volatility also enables metasurface pixels to afford convenient programming of desired functions and a reduced power consumption. The high refractive index of phase change materials has already been harnessed to fashion them into compact optical antennas. Here, we take the next important step, by showing electrically switchable phase-change antennas and metasurfaces that offer strong, reversible, non-volatile, multi-phase switching and spectral tuning of light scattering in the visible and near-infrared spectral ranges. Their successful implementation relies on a careful joint thermal and optical optimization of each optical device that comprises a metal strip that simultaneously serves as a plasmonic resonator and a miniature heating stage. In the dissertation, three functional optical devices are demonstrated with electrical tunability. An optical antenna featuring 30% modulation of the scattered light intensity is first presented and helps us understand our approach of switching phase-change materials. Based on this knowledge, a metasurface is developed, which can afford electrical modulation of the reflectance by more than 4-fold. Lastly, optical antennas are carefully arranged together to build a metasurface that can direct light into different directions and shows promise in individual control of each antenna. The works presented in this dissertation open the opportunity to create a wide range of dynamic random access metasurfaces capable of programmable and active wavefront manipulation
The electrochemical phase transformation in LiXFePO4
Keywords: Materials Science and Engineering.

Phase separation induces heterogeneity and are common in many industries, such as energy storage, metallurgy, polymers and life sciences. Such heterogeneity, often in the form of spatially distributed phases of different compositions, directly impacts the performance and degradation of a material. For example, in electrochemical phase-separating materials such as lithium ion batteries, the phase separation boundaries has been shown to impact the transport and stress accumulation, thus controls the rate performance and lifetime. Understanding the spatiotemporal electrochemical transformation dynamics is therefore important; but the thermodynamically heterogeneous nature, as well as the non-linear dynamics underlying the non-equilibrium electrochemical reaction kinetics makes this goal challenging. More importantly, in a realistic device operation cycle, fluctuating current is unavoidable, but most of the transient behavior beyond steady current conditions are under-explored. In this dissertation, I demonstrate an approach that integrates advanced characterization, phase field theory and numerical computation to understand electrochemical phase transformation, extending beyond typical constant current conditions. Using LiXFePO4 as a model system, I will break the challenge into two parts based on phase-field theory. First, I will focus on understanding the stress/strain development during phase separation. This allows for a proper construction of the materials behavior at equilibrium. To be specific, the chemo-mechanical constitutive relation that governs the material deformation upon lithiation is extracted through a partial differential equation constrained optimization from correlative images composed of strain and composition. Additional chemo-mechanical insights such as generations of dislocations can be drawn, which may be key to understanding battery lifetime. Having established the equilibrium picture of the material, I will next discuss the transient transformation dynamics beyond constant current conditions. Mechanisms of electrode activation that minimizes resistance through current pulses, as well as the power law relaxation of the metastable solid solution will be discussed. These results provide fundamental insights on optimal battery operation strategies. These findings are generalizable to many other phase-separating systems and demonstrate the potential of merging advanced characterization, phase-field theory, and numerical computation for scientific discovery
Elucidating the role of Axin in beta-catenin destruction and stabilization
Keywords: Structural Biology.

Wnts are a family of secreted ligands that regulate embryonic development and stem cell renewal. One way they do so is by increasing cellular concentrations of the transcriptional coactivator beta-catenin by blocking its degradation. As the key scaffold of the beta-catenin destruction complex, Axin promotes beta-catenin degradation. However, it is also essential for the recruitment of the destruction complex to the Wnt-bound receptors to halt beta-catenin destruction in response to a Wnt signal. While most of the essential proteins and many of the key events in Wnt/beta-catenin signal transduction are known, the precise mechanistic logic of both how the beta-catenin destruction completely efficiently destroys beta-catenin in the absence of Wnt and how Wnt binding to its receptors halts this destruction remains unclear. To probe the function of Axin in the Wnt ON and OFF states, structural, biochemical, and enzymatic analyses of the interactions among Axin, GSK-3, beta-catenin, and Dishevelled were carried out. These results inform our understanding of this fundamental signaling pathway