VictorJuiz/thesis huggingface dataset:
Star Wars, Poison Gas, and Cybersecurity: Lessons from the Past for a Better Future
Keywords:  Center for International Security and Cooperation
Center for International Security and Cooperation
Cybersecurity
International agreements
Reykjavik Summit
Chemical Weapons Convention
Thesis

Though numerous countries have been victims of hostile operations in cyberspace ranging from espionage of trade secrets to a shutdown of the nation’s electrical grid, little progress has been made in the international system towards a formal international agreement to regulate activities in the domain. Much of the existing literature on arms control in cyber-space is pessimistic and emphasizes why cooperation will fail without communicating how cooperation might succeed. This thesis seeks to fill that gap by examining the question: under what conditions will international agreements in cyberspace be more likely? Assessing two historical case studies in the Reykjavik Summit and the Chemical Weapons Convention for their implications regarding such agreements, this thesis explores the conditions which make an agreement in cyberspace more likely through a lens of five variables - technology, geopolit-ical dynamics, state interests, domestic environments, and information. The most important condition of an international agreement in cyberspace is the willingness of parties to make reciprocal concessions during negotiations. This thesis further finds that the existence of the following conditions increase the likelihood of an agreement: the major players in cyberspace are committed to the objective of an agreement, the use of cyber tools rather than the tools themselves are being regulated, and private sector concerns are included in negotiations. These findings suggest areas of focus for current world leaders seeking to regulate the cyber-space domain. Further, this thesis concludes that cyberspace does not exist in a vacuum and that negotiators on cyberspace have much to learn from historical cases.
Stasis : the nature, frequency, and intensity of political violence in ancient Greece
Keywords: Classics.

This dissertation examines the nature, frequency, and intensity of violent political conflict (stasis) in the c. 1,100 city-states (poleis) inhabited by the ancient Greeks between 500 and 301 BCE. Against existing scholarship, which conflates stasis with modern analogs like civil war, revolution, and internal war, I highlight the many ways in which stasis was a historically distinctive concept. I show that most poleis experienced stasis at an average rate of more than once per decade and that most staseis produced fewer than a dozen casualties. I also introduce new methods and new tools to overcome three of the most significant obstacles that face attempts to study Greek history on a panhellenic scale: the scarcity, ambiguity, and deep biases of the evidentiary record.
Statistical and computational techniques for GPU-accelerated PET image reconstruction
Keywords: Electrical Engineering.

Positron emission tomography (PET) is an imaging modality that can detect a contrast agent that preferentially accumulates on or inside diseased cells with concentrations as low as pico-mol/L. Since diseases typically begin on molecular and cellular levels, PET's sensitivity to fine molecular changes makes it essential for detection, staging, and treatment of oncological, cardiovascular, and neurological diseases. Moreover, PET is indispensable for basic research of biological processes, and pharmaceutical development. This dissertation presents mathematical and algorithmic techniques for increasing the safety, ac- curacy, and affordability of PET imaging. Particularly, it presents the first ever maximum likelihood expectation maximization (MLEM) algorithm for photon attenuation correction from PET emission data alone. This is the only existing technique that guarantees monotonic increase of PET image likelihood with estimation iterations. Moreover, the dissertation presents advances in stochastic modeling, inverse problems with incomplete data, numerical optimization, parallel computing, and graphics processing unit (GPU)-based formulation of the method, that reduce image estimation du- ration from 5 days to under an hour, by accelerating the algorithm by over 200-fold compared with single CPU-based formulation, and reducing its memory usage by 5-fold. Furthermore, the disser- tation shows how these advances could benefit other algorithms that model the imaging system in PET, SPECT, and CT. Particularly, it shows how they can accelerate single scatter simulation (SSS) by over 100-fold compared with single CPU-based formulation, and increase PET's geometrical sys- tem matrix compression used in the image reconstruction process by over 800-fold compared with today's state of the art methodology. Finally, using the advances described above, the dissertation presents the first ever MLEM algorithm for joint correction of photon attenuation and tissue-scatter from PET emission data alone.
Statistical inference of properties of distributions
Keywords: Electrical Engineering.

Modern data science applications---ranging from graphical model learning to image registration to inference of gene regulatory networks---frequently involve pipelines of exploratory analysis requiring accurate inference of a property of the distribution governing the data rather than the distribution itself. Notable examples of properties include mutual information, Kullback--Leibler divergence, total variation distance, the entropy rate, among others. This thesis makes contributions to the performance, structure, and deployment of minimax rate-optimal estimators for a large variety of properties in high-dimensional and nonparametric settings. We present general methods for constructing information theoretically near-optimal estimators, and identify the corresponding limits in terms of the parameter dimension, the mixing rate (for processes with memory), and smoothness of the underlying density (in the nonparametric setting). We employ our schemes on the Google 1 Billion Word Dataset to estimate the fundamental limit of perplexity in language modeling, and to improve graphical model learning. The estimators are efficiently computable and exhibit a ``sample size enlargement'' phenomenon, i.e., they attain with $ samples what prior methods would have needed \log n$ samples to achieve. We provide a brief survey on our utilization and development of relevant tools from approximation theory, probability theory, and functional analysis.
Stipa pulchra in serpentine grasslands host a diverse community of foliar fungal pathogens with little potential impact on the outcomes of plant invasions
Keywords:  Department of Biology
Biology
Ecology and Evolution
Ecology
Disease Ecology
California grasslands
Stipa pulchra
Stanford University Department of Biology
Thesis

The invasion of California grasslands is striking and extensive: since the 19th century, invasive annual grasses from the Mediterranean have come to dominate 9.2 million hectares of grassland previously dominated by native perennial grasses. As in many species invasions, the mechanisms driving the spread of invasive species in these grasslands remain poorly understood. Disease, which may prevent and/or facilitate invasions through its influence on the outcomes of interspecies competition, represents a relatively unexplored but potentially powerful driver in this invasive event. California grassland plant communities found in serpentine soils with high heavy metal content and low essential plant nutrient availability are exceptional in that they remain largely uninvaded and continue to include diverse native grasses and forbs. In these remnant communities, I assessed the potential for foliar disease to play a role in maintaining and/or reducing native plant persistence in California grasslands. To do this, I: 1) measured foliar disease burden in serpentine and nonserpentine populations of the native bunchgrass Stipa pulchra, 2) compared the fungal foliar pathogen communities hosted by the surveyed plants, and 3) analyzed the chemical makeup of serpentine and nonserpentine plant tissue in order to understand potential impacts of soil chemistry on plant health and pathogen community composition. I found that serpentine and nonserpentine Stipa experience low disease pressure from distinct communities of foliar pathogens, and that serpentine plants, like the soil they grow in, have elevated Ni and Mg content and decreased C, N, Ca, and P content compared to nonserpentine plants. The results imply that pathogens are unlikely to affect the persistence of this native plant, but that plants may structure their pathogen communities via either plant community composition or via tissue chemistry. Plant invasions and/or soil type are shown to have potentially far-reaching effects on pathogen diversity and community composition, with implications for efforts to conserve native plant communities and to beneficially shift public perceptions of parasites.
Stochastic models for flow and transport in heterogeneous porous media
Keywords: Energy Resources Engineering.

Modeling flow and transport in porous media is an important part of the decision-making process in managing crucial resources such as underground aquifers and hydrocarbon reservoirs, subsurface disposal of contaminants, and the design of battery systems. The multiscale nature of porous media, the heterogeneity of their properties and the uncertainty of our knowledge of these properties pose significant modeling challenges that have been the focus of extensive research. In this work, four important contributions are made to the modeling of flow and transport in porous systems. First, a non-local formulation is rigorously derived to find the average flow solution in multiscale porous media. Second, the stochastic representation of the flow problem is used for quantifying the flow uncertainty in cases with heterogeneous conductivity fields. An algorithm is proposed for using the Feynman-Kac formulation for one-dimensional elliptic problems with piecewise constant conductivity and various schemes were explored to improve the efficiency of particle tracking algorithms for both stochastic and deterministic flow problems. The third contribution of this work is the introduction of the stencil method, a discrete temporal Markov model for modeling transport in networks representing porous material. The stencil method simplifies the temporal models used to simulate mean transport in porous media. Finally, a fast discrete temporal Markov velocity process is introduced to simulate ensemble transport in highly heterogeneous continuum scale conductivity fields. This is the first stochastic model to simulate dispersion in high-variance conductivity fields for both Gaussian and exponential correlation structures.
Strain engineering germanium-tin in group IV photonics
Keywords: Materials Science and Engineering.

The scaling of technology nodes to smaller length scales has enabled unprecedented growth for silicon integrated circuits (IC). The reduction of critical feature dimensions has allowed larger densities of integrated components and improved performance on the device level. At the same time, however, scaling has presented increasing challenges for the performance of global electrical interconnects, which comprise the longest wire lengths on a chip. One solution to overcoming the limitations of electrical interconnect technology is the integration of optical interconnects. While optical communications has already been employed on much larger length scales, the application of optical interconnects for chip-to-chip and on-chip communications has yet to be realized. In the IC industry, the silicon (Si) complementary metal-oxide-semiconductor (CMOS) platform has unified and enabled large-scale integration, but Si performs poorly as an active optical material due to its indirect band gap. As a result, an integrated Si laser has remained elusive in Si photonics, although the ability to leverage this platform for photonic integration has the potential to achieve low cost and high-throughput manufacturing, while maintaining compatibility with CMOS electronics. Developing a tunable direct band gap group IV semiconductor can instead be achieved using the binary germanium-tin system. The incorporation of Sn into the Ge crystal reduces the energy difference between the direct and indirect conduction band minima. A major challenge of the germanium-tin system is lattice mismatch with respect to Si or Ge-buffered Si substrates. Significant compressive strain arises from the coherent epitaxial growth of germanium-tin on these substrates, which inhibits the onset of the fundamental direct gap. This dissertation explores methods of strain engineering pseudomorphic germanium-tin epitaxy to relieve lattice mismatch strain that inhibits the onset of the fundamental direct band gap.
Strategies to Address Forced Labor in Industries with Globally-Integrated Supply Chains: Lessons Learned from Case Studies in Palm Oil, Prawn Farming, and Cattle Ranching
Keywords: Global supply chains
Forced labor > Law and legislation
Text
Thesis

Nahla Gedeon Achi’s capstone project focused on evaluating the successes and shortcomings of efforts to address forced labor in three industries with globally-integrated supply chains: palm oil, cattle ranching in Brazil, and prawn farming in Thailand. More specifically, Nahla looked to provide a comprehensive overview and analysis of a subset of existing strategies to address human trafficking within these varied industries. As a former research assistant for the Stanford Center for Ocean Solutions (COS), Nahla also tied her capstone project to existing initiatives put forth by COS and the Center for Human Rights and International Justice addressing slavery in tuna supply chains. Nahla hopes that her capstone project not only brings to light grave human rights issues within these industries, but also demonstrates how concerted efforts from governments, corporations, consumers, and communities everywhere will we be able to fully eliminate forced labor from all supply chains.
Stretchable serpentine microwave devices for next-generation wearable systems
Keywords: Electrical Engineering.

Over recent years, the use of patterned serpentine geometries in stretchable wearable electronics has attracted significant attention, especially for health monitoring in fitness and biomedical applications. While stretchable serpentine systems have been demonstrated for direct-current (DC) and low-frequency applications, there is a need to further study the influence of the serpentine geometry on high-frequency characteristics, to avoid potential parasitic effects or impedance issues. Furthermore, the impact of the serpentine stretching mechanics on wireless performance remains relatively unexplored. This work describes a general strategy for producing stretchable microwave components in which rigid, planar metallic structures are deconstructed into stretchable mesh geometries based on subwavelength-scale unit cells. The impact of this conversion strategy on microwave performance is examined for serpentine meshed transmission lines and antennas. Observations of surface current propagation and antenna radiation efficiency indicate an inherent trade-off between mechanical stretchability and microwave performance. Using the insight gained from investigating the performance impacts on transmission lines and antennas, the serpentine conversion strategy is then applied to produce a stretchable electromagnetic device for biomedical wireless power transfer in the electromagnetic midfield. A stretchable microwave phased surface is designed and fabricated to transmit a focused electromagnetic field into the human body to wirelessly power a miniature biomedical implant. Its performance with stretching is characterized in an experimental setup, and results indicate that with proper design, the serpentine phased surface can achieve comparable performance to its solid counterpart. To ensure optimal design decisions for future stretchable microwave systems, a general methodology is developed to model the microwave performance of various serpentine geometries. Serpentine designs are implemented in a microstrip transmission line system, and the effective transmission line parameters are extracted by fitting results to an equivalent transmission line model. This methodology is utilized to benchmark the serpentine microwave performance relative to alternative materials approaches. It is also useful for assessing the performance impacts of changes to the serpentine design. From these demonstrations, it is clear that the proposed methodology is highly useful for evaluating and improving the performance of future wearable systems.
Stringy nonlocality and black hole physics
Keywords: Physics.

We analyze nonlocal effects in string theory near black hole horizons. Due to extended string effects, early infalling matter can be detected by late observers long after they fall into the black hole. The nonlocal effects are derived via an analysis of the six-point string scattering matrix in flat space, as well as by probing the scattering with a background dilaton. We also derive simple new string solutions in three dimensions.
Structural and functional characterizations of mitochondrial calcium uniporter
Keywords: Molecular and Cellular Physiology.

In this thesis, I mainly worked on the structural and functional characterization of a mitochondrial calcium channel named MCU. Mitochondrial calcium plays critical roles in a wide range of fundamental cellular processes, including controlling the rate of ATP production, regulating the initiation of cell death and shaping cytosolic calcium signaling. Since fifty years ago when it was first demonstrated that fully energized mitochondria can rapidly load up calcium ions (Ca2+), the machinery behind this process has been extensively explored. This uptake is mediated by a highly selective calcium channel called the mitochondrial calcium uniporter (MCU), which resides on the inner mitochondrial membrane. The molecular identity of the uniporter was only uncovered relatively recently. MCU bears no discernable sequence similarity to other known channels and represents a new class in ion channels with its unique selectivity and conductance properties. In this thesis, I used both X-ray crystallography and single-particle cryo-electron microscopy to determine the structures of MCU from two species containing all domains, and I established rapid and efficient functional characterization platforms in cells and in liposomes. Unexpectedly, the stoichiometry, overall architecture, and local structural details of the new structures differed markedly from the NMR cMCU structure. The physiological relevance of those structures was corroborated by the observation of a consistent architecture across species and chemical environments, and by the systematical functional assays. Structural and functional characterizations provided insights into Ca2+ coordination, selectivity, and permeation, establishing a framework for understanding the mechanism of MCU function.
Structural phase stability and van der Waals computation for two-dimensional materials
Keywords: Materials Science and Engineering.

Two-dimensional (2D) materials are a family of materials that are atomically thin, with ultra-high surface-to-volume ratio. Multiple 2D materials can be held together by van der Waals interaction to build layered heterostructures. Since the first experimental isolation of a 2D material graphene in 2004, 2D materials have attracted much attention as promising candidate materials for future nanoscale devices. In the first part of the dissertation, I focus on a unique property of a small subset of 2D transition metal dichalcogenide (TMD) monolayers: the potential to exist in multiple competing crystal structures. Phase change materials have wide spread applications from electronics, optics to energy technology. Here, I study the structural phase stability control of a TMD monolayer, MoTe2 monolayer, with surface adsorption of atoms and molecules. Our density functional theory (DFT) calculations reveal the potential for surface adsorption to induce a structural phase change between the competing semiconducting and metallic crystal structures of the monolayer. Further, I find that the MoxW1-xTe2 monolayer alloy composition can be tuned to achieve some degree of molecular selectivity in phase changes, providing a basis for nanoscale molecular sensing applications. I next focus on van der Waals computation for 2D materials. As an alternative to expensive standard electronic-structure approaches, I explore the potential for an electromagnetic approach to describe van der Waals interactions to provide faster computation for layered materials, including some non-pairwise effects which may be important for layered materials. Surprisingly, we find that this electromagnetic approach, based on a modified Lifshitz model, combined with DFT calculations of optical properties can provide total van der Waals interaction energies within 8-20% of the advanced electronic structure calculations for a variety of layered heterostrctures. This method potentially provides a powerful tool for studying van der Waals interactions in layered heterostructure devices. Finally, I applied our defined Lifshitz model to study surface wettability of 2D materials and their layered forms. The literature contains a wide variation of reported water contact angles for graphene, postulated to be associated with contaminations. However, a theoretical understanding of this variation has yet to be quantitatively fully explored. Here, I utilized the Lifshitz model to find that certain forms of contamination can indeed induce the large variation in reported water contact angles for layered materials. I also make predictions on layer dependence and substrate dependence of wettability.