VictorJuiz/thesis huggingface dataset:
Scalable inference for crossed random effects models
Keywords: Statistics.

Crossed random effects models are widely used in statistics for modeling data with crossed structure with applications ranging from political science to recommendation systems. However, the computational costs of estimation and inference of the crossed random effects models limit its application on large-scale data sets. With N observations, the cost of computing maximum likelihood estimates scales as O(N^{3/2}) at best. A similar situation arises for Bayesian inference, where the Gibbs sampler takes O(N^{1/2}) iterations to converge, leading once again to a total cost of O(N^{3/2}). In this talk, we propose a variant of backfitting algorithm in the context of likelihood based inference to compute a generalized least squares estimate each iteration of which costs O(N) and provably converges in O(1) iterations. We illustrate our method on a data set from Stitch Fix. We shall also briefly discuss provably-scalable variants of standard approaches besides likelihood based inference
Scattering studies of magnetic and charge correlations in two-dimensional quantum magnets
Keywords: Materials Science and Engineering.

The study of quantum magnets in two-dimensional systems is a forefront field in both materials science and condensed matter physics research. Such materials not only provide rich platforms for potential applications of novel materials but also further our understanding of basic physics. Neutron and x-ray scattering are powerful tools to explore the magnetic and charge correlations in these materials. This thesis describes the experimental investigation of two model systems in bulk crystalline form, one with a two-dimensional kagome lattice and one with a two-dimensional square lattice, both consisting of Cu2+ ions with spin-1/2. Strong quantum fluctuations give competing ground states or phases in both systems. Recently, barlowite Cu4(OH)6FBr has attracted much attention as the parent compound of a new kagome quantum spin liquid candidate. Our new synthesis method produced large single crystals of a new variant of barlowite, which has a higher symmetry space group compared to the previously reported one. Our elastic magnetic neutron scattering measurements reveal that the magnetic ground state of the new high-symmetry barlowite at low temperatures has a special pinwheel q = 0 magnetic order. In the intermediate temperatures, our numerical calculations and inelastic neutron scattering indicate that the kagome spins are in a potential pinwheel valence bond crystal state. Both of the two ground states are in close proximity to the long-sought quantum spin liquid state. The second part of my thesis is focused on the spin and charge correlations in high-Tc cuprate superconductors. Cuprate materials display intriguing physical phenomena due to the coexistence of various phases, which may interact with the superconductivity. The La-based family is a canonical example where both the spin and charge correlations could form "stripes". Magnetic neutron scattering reveals a rather surprising feature of the spin stripes in the model material La1.88Sr0.12CuO4: regardless of whether they are static or fluctuating, these stripes are always tilted from the high-symmetry direction of underlying lattices. Comparison with numerical simulations reveals the important role of the next-nearest neighbor electron hopping. Resonant soft x-ray scattering measurements offer important information about the charge order in another cuprate material stage-6 O-doped La2CuO4+y. By tuning both temperature and the dopant disorder level, we clearly observe two types of charge orders with distinct correlation lengths and behaviors at low temperatures. A coherent picture based on microscopic phase separation is proposed to explain the relationship between charge and spin orders with superconductivity in these materials
Scope 3 Emissions from Purchased Goods: Using Food Purchasing as a Case Study for Best Practices
Keywords: Scope 3 Emissions
Food Categorization
Purchased goods
Food purchasing emissions
Categorization Script
Text
Thesis

This work answers questions relevant to the determination of Scope 3 emissions from purchased goods: 1) how does the use of weight-based versus spend-based emissions factors (EF) affect the magnitude of emissions calculated, 2) how does using different sources for emissions factors within a same type of EF affect overall estimated emissions, and 3) what is needed to standardize and ease calculation of Scope 3 emissions across institutions, countries, and backgrounds such that the process can be automated and ensure replicable results. To answer these questions, a collaboration with seven universities across the United States was formed to share best practices and food purchasing data. This collaboration enabled the development of a python-based categorization tool to ease and standardize calculation of Scope 3 emissions from purchased foods and helped validate and expand the applicability of the results and methodologies. To understand the impact of different emissions factors on calculated emissions outcomes, the Stanford 2019 food purchasing data was used as a case study and both weight-based (kg CO2-eq/kg item purchased) and spend-based (kg CO2-eq/$ item purchased) EFs were applied to this data set. It was found that for the 2019 Stanford food purchasing case study, the largest estimated emissions were about 2.5times larger than the smallest estimated emissions, and although the range of estimated emissions for the weight-based factors is larger than the range for the spend-based factors, the average is remarkably similar at 10,543 and 11,282 metric tons of CO2-eq respectively.
A search for non-resonant HH -> bbbb at sqrt(s) = 13 TeV with the ATLAS detector -or- 2b, and then another 2b ... now that's the thesis question
Keywords: Physics.

The Standard Model (SM) characterizes the fundamental building blocks of nature, with its experimental characterization culminating with the discovery of the Higgs boson a decade ago. While subsequent Higgs measurements have thus far confirmed the SM predictions, a critical test for our understanding of electroweak symmetry breaking is to study the shape of the Higgs potential by measuring the Higgs self-coupling — which can be probed by searching for events with two Higgs bosons (HH). This thesis presents a search for HH production with each Higgs subsequently decaying into two b-quarks. The extremely small predicted HH signal, coupled with a complex background that cannot be effectively simulated, makes this analysis an ideal test bed for machine learning applications. This thesis also presents the developments in novel algorithms for b-quark jet identification and background estimation that build on recent advancements in machine learning (including deep sets, neural reweighting methods, and normalizing flows) that have been crucial to the HH analysis. The HH -> 4b analysis sets an observed (expected) upper limit on the HH SM cross-section of 5.4 (8.1), a 30% improvement on the previous analysis strategy. We additionally constrain the Higgs self-coupling in the kappa framework with observed (expected) limits of [-3.9, 11.1] ( [-4.6, 10.8] )
Searching for Compassion in Compassionate Release: Protecting the Health of People Experiencing Incarceration
Keywords: Medicine
Incarceration
Public health
Social justice
Health disparities
Text
Thesis

Compassionate release - the release of incarcerated people with medical conditions from
prisons and jails - is a widely underutilized mechanism. Releasing people with medical
conditions from carceral settings can protect individuals’ health - especially during crises such as
the COVID-19 pandemic - and can help promote the health of all people experiencing
incarceration by reducing overcrowding. More literature is needed to understand the barriers and
facilitators to compassionate release to encourage its utilization. The first section of this thesis is
a scoping review that maps existing literature on compassionate release to Bronfenbrenner’s
Ecological Systems Theory to understand key recommendations for improving compassionate
release and where there are gaps in the literature. Findings from this review demonstrate key
recommendations such as establishing greater transparency in the application process, ensuring
accessibility of applications based on literacy levels, and establishing medical-legal partnerships.
Identified gaps for future research include understanding racial disparities in compassionate
release as well as understanding perspectives of caregivers of previously incarcerated
individuals. The second section of this thesis presents a survey study on perceptions towards
compassionate release from jail staff in California during the COVID-19 pandemic. Results
highlight that not all jails in California use compassionate release widely and compassionate
release remains inaccessible for people such as those with respiratory illnesses and people
convicted of violent crimes. Engaging carceral staff using evidence-based recommendations is
crucial in expanding compassionate release. Implementing these recommendations and
researching identified gaps can inform policy and practice to promote the health of people
experiencing incarceration.
Segregation and inequality across neighborhoods, classrooms, and police jurisdictions
Keywords: Sociology.

Our lives are profoundly shaped by our interactions with public institutions and by the characteristics of those particular institutional units with which we interact. Institutions group populations and spaces into manageable units that operate under distinct conditions. This differentiation is often accompanied by unequal provisions of public goods across units, promoting social inequality, and frequently contributes to disparities as these unequal provisions map onto the segregation of social groups across units. Improving our public institutions requires a detailed picture of how geographic and institutional boundaries divide populations and configure the unequal distribution of public goods. To that end, this dissertation considers spatial segregation, institutional segregation, and institutional inequality with respect to three institutions: housing, schooling, and policing. Chapter 1 provides a formal framework for understanding and overcoming bias in measures of residential income segregation. Chapter 2 uses an innovative approach to studying segregation at small scales to uncover and explain the high nationwide prevalence of racial classroom segregation in Brazil. Chapter 3 uses novel data to estimate benchmarked police homicide rates, finding substantial inequality in police deadliness among US police departments that face similar risks to officer and public safety
Selectional preferences and semantic similarity in adjectives
Keywords: Linguistics.

In this thesis, I study the variables that affect the selection between semantically similar adjectives in English, such as ``big''/``large'', ``high''/``tall'', and ``fast''/``quick''. Currently, there is no general model for predicting the selection between adjectives that compete on a given meaning. The proposals that do exist focus on specific pairs of adjectives rather than the selection between them across the board. I attempt to bridge this gap by integrating models of lexical competition with theories of adjective semantics. I propose a novel distinction between an indicative property of an adjective and its focal dimensions. The former is the core meaning of the adjective, and it is an abstract property with undetermined variables. The latter are possible value assignments for these undetermined variables, which can saturate the indicative property in different ways depending on which ones are selected. I show how these two meaning components interact to yield the selectional preferences expressed by adjectives. Motivated by this theoretical analysis, as well as well-known approaches to pragmatics, I raise the hypothesis that semantically similar adjectives should express a distributional pattern in which the rarer one conveys a more specialized meaning than the more frequent one. I operationalize this hypothesis using the Rational Speech Acts framework, and demonstrate through a series of quantitative studies how it predicts the empirical distribution of adjectives
A self-resistance guided approach to the discovery of novel antibiotics
Keywords: Chemistry.

Due to the rise in antibiotic resistance among common pathogens, there is a clear and growing need for novel antibiotics that might bypass existing resistance or breath new life into old drugs. Traditional methods of antibiotic drug discovery have increasingly failed due to rediscovery of old antibiotics. In this dissertation, we first review many of the current strategies towards antibiotic drug discovery and explore emerging tools in this area. We then leverage one of these tools, self-resistance guided genome mining, in combination with an in-house list of polyketide synthase containing biosynthetic gene clusters. Using this approach, we are able to identify and characterize a novel antibiotic from a source that has not traditionally been considered a major source of useful natural products. In doing so, we not only provide a new molecule to aid in the fight against growing drug resistance, but provide validation for the utility of self-resistance guided genome mining as a tool in this effort
Semiconductor technology and circuit techniques for high-performance MHz-range power converters
Keywords: Electrical Engineering.

Conventional power converters contain semiconductor devices switching in the tens to hundreds of kilohertz (kHz) range. Extending the switching frequency to the multi-MHz range brings opportunities to reduce the size and weight of power converters as the energy storage requirements decrease. Additionally, MHz-frequency power converters and amplifiers enable new applications such as plasma generators for semiconductor processing equipment, medical sanitation, and CO2 reforming. Despite these promises and opportunities, building efficient power converters at much higher frequencies still poses a significant challenge. In MHz-frequencies, wide bandgap (WBG) semiconductor devices, such as gallium nitride (GaN) and silicon carbide (SiC), have the potential to improve the performance of these systems as they have orders of magnitude lower specific on-resistance compared to silicon (Si) devices. One of the main issues is the soft-switching Coss losses in WBG devices, which have not been previously well-studied and modeled in the literature, and these losses significantly degrade the efficiency of power converters. We present the measurement results and techniques to characterize the Coss losses in wide bandgap devices, as well as discuss the physical root causes of these losses in SiC power devices. In addition to the Coss losses, effectively utilizing SiC MOSFETs poses a challenge, as designing fast transitioning and low loss gate drivers at MHz frequencies is difficult. As a solution, we develop resonant gate drivers that can drive SiC MOSFETs up to 30 MHz while conserving over five times as much gating power compared to available commercial counterparts. Lastly, we utilize these WBG devices in broadband power amplifier demonstrations suitable for radiofrequency (RF) plasma generation applications at 13.56 MHz. To achieve high performance across broadband, we employ various RF circuit techniques including reactance compensation, phase-switched impedance modulation, and power combining. As a result, these amplifiers showcase some of the highest efficiencies published in the literature, including over 90% across a 4 MHz bandwidth for a 300 W system and over 95% efficiency across 4 MHz for a 1 kW system
Sensory-Friendly Design in the United States
Keywords: ADA Amendments Act of 2008 (United States)
Barrier-free design
Design
Autism
Sensory-friendly
Accessibility
Public spaces
Architecture
Americans with Disabilities Act of 1990 (United States)
Sensory stimulation
Sensory discrimination
Text
Thesis

In the United States, the accessibility of public space design is largely guided by the requirements of the Americans with Disabilities Act, passed in 1990. These criteria largely detail physical accessibility guidelines intended to ensure accessibility of public spaces by individuals with varying physical ability levels. While these requirements undoubtedly have a positive impact on the experiences of people with physical differences, current ADA standards provide little - though not zero - guidance on making spaces accessible for individuals with autism spectrum disorder or other neurological differences which increase sensitivity to sensory stimuli, despite this being a protected disability category as defined by the most recent Standards for Accessible Design published in 2010. As the number of children diagnosed with autism spectrum disorder in the United States increases each year, engineers and architects have the opportunity to further improve accessibility of public spaces to children and adults with autism by incorporating thoughtful sensory design strategies into public design schemes.
This thesis utilizes research on existing accessibility standards with an examination of the intention of public space design to include and exclude certain members of society from the public eye. In addition, this work draws upon the author’s personal experiences as a sibling of someone with autism, as well as supplementary interviews of experts with many hours of experience interacting with individuals with autism spectrum disorder in order to determine which design strategies might be most effective in ensuring sensory accessibility for individuals with sensitivities to sensory stimuli. These conclusions result in several recommendations for design requirements which may be added to existing accessibility design standards. These key recommendations for public spaces include the implementation of shading and thoughtful lighting strategy, the use of auditory barriers and noise-dampening surfaces, and increase of access to privacy within public spaces. When applied on a broad scale, public spaces may become generally more accessible to individuals of all sensory sensitivities and to the broader community as a whole.
¿Sequía o saqueo? Scarcity, Power, and Inequality in Chilean Water Markets
Keywords: Water justice
Drought
Chile
Water markets
Text
Thesis

“No es sequía, es saqueo” (it’s not drought, it’s plunder) is a common phrase in activist circles to argue that it is not just drought that threatens Chile’s water resources, but rather a market-based model for water management that results in an extremely unequal distribution of water. This phrase exists in stark contrast to the worldwide acclaim Chile—the only country in the world with fully-privatised water rights—has received for its model’s potential to combat worsening water scarcity. Despite these opposing viewpoints and their implications for water markets as a drought-response mechanism in other parts of the world, empirical understanding of how scarcity and inequality impact Chile’s water markets remains limited, especially on a broader geographic and temporal scale. This study draws upon a dataset of nationwide water rights transactions, combining them with Standardised Precipitation Index data to identify water scarcity’s impact on market outcomes. I then employ Social Network Analysis methods to quantify market power and inequalities across time and space. I find that a small group of agents dominates the market through their involvement in the vast majority of transactions and volume transacted, their ownership of the lion’s share of water volume, and their strong tendency to trade with one another. Markets only respond to scarcity in the areas with the most unequal distribution of water volume, and scarcity decreases the tendency of highly-powerful agents to trade amongst themselves, suggesting that drought merely serves the interests of the powerful through predatory market behaviour.
Serial X-ray crystallography : pushing the boundaries of structure and dynamics
Keywords: Applied Physics.

Over its long history, macromolecular X-ray crystallography has proven to be the most popular method for structural biology. Recent advent of serial X-ray crystallography at X-ray free-electron laser facilities and synchrotrons have revolutionized the field allowing scientists to study proteins that were previously inaccessible. Radiation damage-free structures from microcrystals at room temperature are routinely studied these days. The next frontier of serial X-ray crystallography will be in studying the function of the proteins by reconstructing a detailed movie of the protein in motion. Conformational variations/changes of proteins are studied using diffuse scattering and pump-probe type of experiments. My research is focused on developing advanced data analysis methods in the field of macromolecular X-ray crystallography to extract more information from massive datasets and push the boundaries of the status quo. Here is a summary of projects I would like to highlight. The first project advances the analysis of pump-probe and mixing-jet experiments by applying machine learning to correct for uncertainty/inaccuracy of measured pumping or mixing times in serial femtosecond X-ray crystallography (SFX) experiments. In pump-probe or mixing-jet experiments, we either excite the crystals using an optical light or mix the crystals with a catalyst to trigger motion, followed by an X-ray probe after a certain delay. Although these methods have been broadly used to study protein dynamics, few people have considered the effects of jitter in these inaccurate timestamps, which can be critical in the study of ultrafast protein dynamics. In our work, we have applied the diffusion map method to embed high-dimensional diffraction images into low-dimensional latent space to correct for the time jitter. The second project is a reproducibility study of diffuse scattering in crystalline isocyanide hydratase in three forms, its wild type and two mutants. Different from ultrabright Bragg peaks that arise from the coherent diffraction of periodic crystal lattices, diffuse scattering is much weaker and is induced by imperfections inside the crystal lattice, such as protein motion and/or other forms of disorders. I have developed advanced methods to extract much weaker diffuse scattering signals from diffraction images, and then studied possible protein motions that cause these diffuse signals, by comparing liquid-like motions model to the experimental data. This work demonstrates a potential utility for selecting a preferred atomic displacement parameter model from diffuse scattering data
Si vis pacem, para bellum : essays on military preparations and deterrence
Keywords: Political Science.

This dissertation focuses on how military preparations made 'in peace' shape the dynamics of deterrence and the ability to prevent a crisis from occurring. Resolve has received most of the attention in past studies of deterrence, yet military capability and how it is developed has major implications for deterrence as well as peacetime force posture and security assistance through military alliances. I assemble empirical evidence and provide formal theoretical logic that highlight the role of military preparations in deterrence. In doing so, this dissertation contributes to an area of deterrence studies that has been understudied by past scholars and is of immediate relevence to policy-makers confronting problems of interstate tensions and conflict