VictorJuiz/thesis huggingface dataset:
Anisotropic electron hydrodynamics
Keywords: Physics.

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
Antigen-driven B cell responses in RA and Sars-Cov-2 vaccination
Keywords: Immunology.

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
Antitrust Law and Catastrophic Risk: Tension, Perspectives, and Reform
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
Text
Thesis

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.
Applications of machine learning to some statistical inference problems
Keywords: Statistics.

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
Application-specific software defined memory
Keywords: Electrical Engineering.

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
Applying Sensitivity Analysis of Basin Modeling Parameters Based On Fluid Accumulations
Keywords: Geological Sciences
Sedimentary basins > Mathematical models
Uncertainty > Mathematical models
Petroleum exploration
Text
Thesis

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.
Arbitrary polarization control with reconfigurable metasurface systems
Keywords: Electrical Engineering.

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
An architecture for integrated decision-making, motion planning, and control of automated vehicles
Keywords: Mechanical Engineering.

Automated vehicles have immense potential to improve the safety of our roadways. In order to handle the complex task of driving, they need the ability to make decisions regarding other road users, plan a trajectory, and control the vehicle, responding online to an evolving environment. For model-based control, it is important to use models that capture the full range of the vehicle's dynamics. We develop a tire model that is computationally tractable and useful in scenarios ranging from a stop-and-go maneuver to driving at the limits of road-tire friction. A model-based steering controller successfully demonstrates the efficacy of this tire model even when the vehicle is sliding on low-friction surfaces. In addition to being able to control the vehicle, an AV architecture must also be able to make discrete decisions regarding obstacles in the environment. Ultimately, these decisions are carried out by a controller commanding steering and longitudinal inputs, which motivates building a system that makes decisions based on the capabilities of the underlying controller. Our novel architecture partitions the drivable space into discrete options, solves a nonlinear optimization in each option in parallel, and then picks the solution that best satisfies high-level objectives such as safety and efficiency. Finally, frameworks for automated vehicles need to be designed with human values in mind. Safety is a top priority and is codified in legal texts as duty of due care. By leveraging the architecture described above to realize these human values, the vehicle drives safely and comfortably in an overtaking maneuver with oncoming traffic
Artificial Consciousness: Why is matters and how to approach it
Keywords: Artificial intelligence
Consciousness
Text
Thesis

Despite the rapid development in artificial intelligence, machines are nowhere close to the cognitive capabilities of humans. What could we be missing? This paper explores the idea that consciousness is the key to intelligence and the missing ingredient to artificial general intelligence. Any intelligence as advanced as humans or more advanced will have to be conscious, even though their consciousness may look different from ours. That consciousness is necessary for intelligence, including artificial intelligence should not be taken to mean that there is a hard cap for how advanced artificial intelligence can be. While consciousness as a concept appears to be extremely elusive, particularly the subjective, phenomenal aspect of consciousness, I claim that consciousness, if it exists, simply is the physical process that enables non-reflexive behavior. I support an eliminativist approach to understanding consciousness in the hopes of demystifying the idea of building artificial consciousness.
Assessing Compound Flood Risk for the San Francisco Bay Area, California
Keywords: Flooding, Compound Hazards, Hydraulic Modeling, Climate Change, Sea-level Rise, Precipitation
Text
Thesis

As climate change causes sea levels to rise, increases precipitation variability, and leads to larger, more frequent storms, communities are faced with ever increasing risks from flooding. Communities require reliable assessment of the compound risk they face now and how that risk changes in the future to decide how to mitigate their flood risk. Many of the San Francisco Bay Area’s planning around climate hazard mitigation efforts focus on the threat faced by sea level rise. However, coastal, riverine, and pluvial (surface runoff) flooding can happen concurrently leading to a compound hazard that is rarely taken into account. The goal of this study is to integrate the effects of coastal, riverine, and pluvial hazards by using preexisting hazard models to develop a map of the compound flood hazard for San Mateo County California. Our research expands upon San Mateo County’s previous work combining coastal and pluvial flooding through Cal Adapt using 2-D Hydrologic Engineering Center- River Analysis System (HEC-RAS) models that project flood hazard data into the future for 2030 and 2070 using changes in predicted precipitation data and sea level rise. We found that compared to flood maps from FEMA and the USGS the added effects of fresh water to the coastal flooding and sea-level rise increased the inundation depth and extent along the coast by up to 7 feet by 2070. Further inland, the 2030 storm scenarios were deeper, but in some areas were less extensive while the 2070 storm scenarios had more extensive and deeper flood inundation in some areas by up to 2 feet. This highlights the importance of compound hazard in assessing flood risk as some risks would otherwise not be accounted for.
Assessing Red Lines in the US-China-Taiwan Trilateral Relationship
Keywords: Center for International Security and Cooperation
red lines
Deterrence (Strategy)
grey zone
China
Taiwan
International relations
Text
Thesis

The idea of “red lines” has become a favorite catch-all term to discuss coercion, grey area tactics, and escalation. Particularly in the case of the US-China relationship over Taiwan, policymakers and scholars use red lines as a shorthand to conceptualize crisis thresholds, a point where ambiguity ends, and the stakes are highest. But there is limited consensus on the definition of red lines, and even less consensus on where red lines are between the US and China. This thesis creates a theoretical framework for understanding red lines and applies to it to the US-China-Taiwan case to explore how the US and China treat red lines in practice, and why some red lines fail where others succeed. Drawing on a set of case studies of Taiwan-centered red lines, I analyze how their integrity has evolved, contextualizing violations and enforcement through a typology. I assess red lines based on four main components: a situational threshold, demand, threat, and justification, and suggest that the strength of a red line is highly dependent on having all four components. Particularly in an era of grey area conflict between the US and China, understanding how to draw red lines most effectively, and which red lines are de jure versus de facto, is essential for preventing miscommunication and unwanted escalation.
Assisting walking in individuals with chronic stroke using exoskeletons
Keywords: Mechanical Engineering.

Stroke often results in hemiparesis and gait asymmetries, such as spatial, temporal, or kinematic asymmetries between the paretic and nonparetic legs. Asymmetric gaits have been correlated with higher metabolic cost, slower walking speeds, and lower mobility. These gaits can also cause joint pain due to repetitive high loads on the nonparetic limb. For these reasons, physical therapists try to decrease gait asymmetries, and their interventions have been shown to be effective. However, sessions are expensive, limiting access. More automated rehabilitation techniques have been developed, but they have not been more effective than conventional physical therapy. A better understanding of the mechanisms driving gait asymmetry could allow for the development of more targeted, effective, and accessible gait interventions. In my doctoral research, I first studied the correlation between step length asymmetry and metabolic cost in individuals with chronic stroke and in unimpaired participants. Participants were tasked with altering their step length asymmetry using biofeedback. All participants were able to significantly alter their step length asymmetry. Unimpaired participants self-selected a symmetric step length asymmetry that correlated to the lowest energy cost. However, for individuals with chronic stroke, metabolic cost minimization did not explain self-selected step length asymmetry. I then built a unilateral knee-ankle exoskeleton emulator that can actuate knee flexion, knee extension, and ankle plantarflexion. I designed a knee position controller to track desirable knee kinematics and demonstrated the mechatronic capabilities of the emulator system on one unimpaired participant and one participant with chronic stroke. The knee position controller was able to prevent negative impacts at the knee when plantarflexion torques were applied, and the position controller could track different desired knee trajectories with low tracking error. The results from these studies could better inform the design of future rehabilitation tools and assistive devices. Our results suggest that metabolic energy consumption probably will not be a barrier to therapists who seek to improve step length asymmetry. Additionally, we found that active ankle plantarflexion assistance can cause increased knee extension which might lead to long-term tissue damage with constant use. Assistive devices simultaneously assisting the ankle and knee could prevent these poor knee responses. This might allow for a more comfortable application of larger magnitude ankle torques which could potentially improve metabolic reductions. These projects have led to a new experimental tool that can be used to discover beneficial participant-specific assistance strategies for individuals with chronic stroke
Astrophysical signatures of axion-like particles
Keywords: Physics.

Axion-like particles generically couple to electromagnetism through the E.B operator, allowing for electromagnetic production of axions and axion-to-photon conversion in the presence of background fields. Neutron stars are excellent candidates to look for axion production and conversion as they possess some of the largest magnetic fields in the Universe, some in excess of 10^15 Gauss. In this thesis I will discuss two axion scenarios leading to detectable electromagnetic signatures. I will first discuss a new production mechanism for axions near the surfaces of actively pair-producing neutron stars (pulsars). Pulsar magnetospheres admit non-stationary vacuum gaps that are characterized by non-vanishing E.B. The vacuum gaps play an important role in plasma production and electromagnetic wave emission. I show that these gaps generate axions whose energy is set by the gap oscillation frequency. The density of axions produced in a gap can be several orders of magnitude greater than the ambient dark matter density. In the strong pulsar magnetic field, a fraction of these axions may convert to photons, giving rise to broadband radio signals. Another scenario considers the possibility that axion dark matter forms dense sub-structures (stars) on very small scales. When axion stars collide with neutron stars they convert very efficiently to electromagnetic waves, giving rise to bright flashes. I will discuss the detectability of such flashes using existing and planned radio telescopes
ASWIM IN A SEA OF POPPIES: OPIUM CHALLENGES THE ENGLISH EMPIRE, 1827-1910
Keywords: Malwa
Opium trade
Opium
Malwa opium
Opium war
Sassoon family
Sassoon, David, 1792-1864
Sassoon, Elias Victor, 1881-1961
Jardine, Matheson & Co.
Jamsetjee Jejeebhoy, 1783-1859
Jardine, William
Matheson, James, 1796-1878
India > Mumbai
Bombay
Qing Empire
China
Shanghai
Hong Kong
East India Company
British East India Company
Scottish history
monopoly
Cotton
Cotton textile industry
Baghdadi Jew
John Crawfurd
anti-opium
Text
Thesis

In this thesis, I argue that the very phenomena which are thought of as products of British hegemony were instead the outcome of the limits of British imperial power: firstly, the vast scale of the nineteenth century opium trade between India and the Qing Empire; secondly, the First Opium War; and finally, the historiography of British power itself.