VictorJuiz/thesis huggingface dataset:
Capture and acceleration of sub-100 keV electrons with alternating phase focusing silicon dielectric laser accelerator structures

We demonstrate a silicon-based electron accelerator that uses laser optical near fields to both accelerate and confine electrons over extended distances. Two dielectric laser accelerators (DLA) designs were tested, each consisting of two arrays of silicon pillars pumped symmetrically by pulse front tilted (PFT) laser beams, designed for average acceleration gradients 35MeV/m and 50MeV/m respectively. The DLA are designed to act as Alternating Phase Focusing (APF) lattices, where electrons, depending on the electron-laser interaction phase, will experience alternating longitudinal/transverse focusing/defocusing. By incorporating fractional period drift sections that alter the synchronous phase between ± 60 degrees off-crest, electrons captured in the designed acceleration bucket experience half the peak gradient as average gradient while also experiencing strong confinement forces that enable long interaction lengths. We demonstrate APF accelerators with interaction lengths up to 708μm and energy gains up to 23.7 ± 1.07 keV FWHM, a 25% increase from starting energy, demonstrating the ability to achieve substantial energy gains with sub-relativistic DLA. Also shown is the work on designing/producing a Silicon 1D grating used in the first demonstration of the quantum nature of DLA, and the post-processing of foundry chips for use as a DLA platform.

Keywords: Engineering.
Electrical Engineering.
Advisor: Solgaard Olav
Harris J. S. (James Stewart)
Howe Roger Thomas
Capturing brain dynamics with topological data analysis

As brain imaging technologies measure increasingly higher spatial resolutions and faster time scales, complementary advances in analyzing whole-brain activation time-series data are necessary. Topological models offer a powerful framework for this analysis by describing the dynamical organization of the brain as a graph and can effectively capture the underlying shape of the space explored by the brain, for example, during ongoing cognition. A recently established approach using the Mapper algorithm from topological data analysis (TDA) now enables the construction of these graphs from whole-brain functional imaging data. The work described in this thesis advances that approach in three ways. First, we provide new open-source tools for visualizing and extracting insights from shape graph representations of neuroscientific data learned by Mapper. Second, we introduce a new Mapper algorithm inspired by the high dimensionality of brain imaging data designed to reduce both information loss and computational cost. Third, we extend the Mapper-based approach to naturalistic fMRI data analysis, quantifying more ecologically valid transitions in the unstructured data and leveraging annotations provided by the paradigm (e.g., tasks, stimuli-derived features). By simultaneously addressing usability, scalability, and ecological validity, this dissertation takes us three steps closer to translational applications of our Mapper-based approach, and ultimately, to realizing the promise of precision neuroimaging. Along the way, we introduce a new fMRI dataset collected using a naturalistic self-viewing paradigm and describe a novel link between brain dynamics and behavior

Keywords: Humanities and Sciences.
Advisor: Saggar Manish 
Carlsson G. (Gunnar)
Hosseini Hadi
Causal inference with non-standard experimental designs

The past decades have seen a comprehensive body of research dedicated to causal inference in conventional experimental designs. However, as technological innovations continue to foster a rapid influx of data across numerous fields, the datasets derived often exhibit new structures that stem from unconventional designs. The thesis at hand is centered around the development of methods for conducting causal inference, particularly when the design deviates from the standard, thereby making conventional methods inapplicable. Chapter 2 delves into the regression discontinuity design in cases where the running variable is a noisy measurement of a latent variable. We propose a novel design-based approach for estimation and inference. This approach proves effective when applied to a broad array of widely-used estimands. Chapter 3 explores adaptive experimentation in the context of delayed feedback. In subchapter 3.1, we extend Thompson sampling to the proportional hazard model and develop a method capable of overcoming challenges associated with vaccine trials. Subsequently, in subchapter 3.2, we study the behavior of Thompson sampling when delays are unrestricted, providing theoretical regret bounds and conducting extensive experiments. Chapter 4 investigates policy learning in scenarios involving multiple treatments or multiple outcomes. In subchapter 4.1, we propose methods for evaluating policies when cost constraints accompany multiple treatments. In subchapter 4.2, we introduce a personalized experimentation system that can learn interpretable policies from experimental data and is scalable for big datasets

Keywords: Humanities and Sciences.
Statistics.
Advisor: Wager Stefan
Hastie Trevor
Siegmund David
Centering justice in conservation solutions for people and nature

Conservation science is more necessary than ever to address anthropogenic threats that endanger the ecosystems, biodiversity, and nature on which human well-being depends. However, despite longstanding acknowledgement of the intimate interconnections between people and nature, more work needs to be done to integrate people, especially the most marginalized, into conservation. In this dissertation, I draw on scholarship from ecology, ecosystem services, geography, environmental justice, human rights, and conservation social science to conceptualize conservation solutions that both benefit people and nature and center justice in human-dominated environments. In the first chapter, I model how policy-relevant riparian reforestation in Costa Rica can provide water quality benefits to people, and investigate whether those benefits flow to vulnerable populations. In the second chapter, I review how injustices have blocked access to nature in cities, and propose a new framework for centering justice in creating solutions to restore access. In the third chapter, I illustrate through a socio-ecological study that human/bird interactions in community gardens are an important type of nature access, and explore how they are distributed across an income gradient in the city of San Francisco. Taken together, these chapters present visions of a holistic version of conservation that centers both people and justice

Keywords: Humanities and Sciences.
Biology.
Advisor: Daily Gretchen C.
Ardoin Nicole M. (Nicole Michele)
Dirzo Rodolfo
Fukami Tadashi
Centralizers in reductive group schemes

Let A be a discrete valuation ring, and let G be a reductive $A$-group scheme. If H is a closed subscheme of G, we are interested in properties of the centralizer of H in G in various cases. Our investigations involve the development of relative versions of the Jordan decomposition and Springer isomorphisms and a study of schemes of homomorphisms between reductive group schemes. Several applications of these results to theorems over fields are described

Keywords: Humanities and Sciences.
Mathematics.
Advisor: Conrad Brian
Zhu X. (Xinwen)
Van Hoften Pol
CEOs' cultural origin and financial decision-making

This multidisciplinary thesis explores CEOs' financial reporting and investment decisions by synthesizing insights from accounting, finance, sociology, criminology, and anthropology research. The thesis includes two independent chapters. The first chapter investigates the association between CEOs' social-class origin and propensity to commit financial reporting fraud. The chapter is motivated by criminological and sociological theories suggesting a higher social-class origin can both stimulate and restrain criminality. I find that whereas CEOs accused by the SEC of committing fraud are more likely to come from poor and working-class backgrounds, CEOs without fraud allegations are more likely to come from middle- and upper-class backgrounds. The pattern continues to hold in a subsample of founder CEOs, suggesting selection in the labor market is unlikely to explain the association between CEOs' social-class origin and financial reporting fraud. In addition, I do not find evidence that bias in the SEC's enforcement decisions drives the association. Echoing criminological theory, I find CEOs' educational background mediates the association between social-class origin and financial reporting fraud. This finding suggests that endowed resources such as social connections and academic credentials reduce CEOs' incentives to defraud by providing them with a safety net and increasing their reputational costs. The second chapter investigates the association between target firms' receptiveness to being acquired in mergers and acquisition transactions (M&A) and their CEOs' adherence to cultural norms enshrining the protection of personal honor. Our hypothesis that target CEOs' adherence to honor may explain the receptiveness to M&A is motivated by anthropological evidence suggesting men who grew up in societies that developed a culture of honor feel obliged to retaliate whenever their status and property are threatened. Consistent with this narrative, we find targets with CEOs who grew up in states with a culture of honor are more likely to repeatedly engage in withdrawn deals without being acquired—suggesting a lower receptiveness to M&A. The pattern continues to hold in a subsample of founder CEOs. Focusing on CEO transitions, we find targets are less likely to be acquired when they have a CEO from an honor state than a CEO from a nonhonor state. Together, these findings suggest selection in the labor market and omitted firm characteristics are unlikely to drive the association between target CEOs' adherence to honor and receptiveness to M&A. Lastly, in support of the honor narrative, we find that among CEOs from honor states, those who grew up in rural areas—where cultural norms enshrining honor were more likely to persist—are the least receptive to M&A

Keywords: Business.
Advisor: Kasznik Ron
Goldberg Amir
McNichols Maureen
Change-point detection in mean and variance or both

The focus of this thesis is on developing statistical methods to identify change-points in datasets where there may be changes in both mean and variance. We propose novel statistical methods for detecting such change-points and discuss both type-I error approximations and power evaluations. Our first set of tests is based on score statistics for the single change-point problems and introduces a hyper-parameter to allow flexibility between change in the mean parameter and change in the variance parameter. We also introduce both box-type and ellipse-type statistics based on different shapes of the rejection region. Analyzing the score-based statistics is challenging due to the heavier than normal tails in the $\chi^2$ distribution in the variance component of the statistics. We develop theoretical methods that deal with this difficulty when approximating type-I error. Additionally, we provide marginal power calculations for assessing the effectiveness of these tests. The required modifications for both type-I error approximations and marginal power calculations for the interval change problems are discussed as well. Next, we propose tests based on the full generalized likelihood statistics and the box-type and ellipse-type statistics with the same hyper-parameter as in the score case. The theoretical results for this set of tests are simpler than the score tests because now both mean and variance components of our statistics are approximately Gaussian distributed. We provide type-I error approximations and marginal power calculations for the full generalized likelihood statistics in both single change-point and the interval change problems. Finally, we compare the power of all these statistics with the power of the classical change-point statistics which only allow change in the mean and assume variance is constant. We also examine some real-world datasets to demonstrate the effectiveness and pitfalls of these statistics

Keywords: Humanities and Sciences.
Statistics.
Advisor: Siegmund David
Lai T. L.
Linderman Scott
Changing Strategies of Mexican Drug Trafficking Organizations (DTOs) in the Context of Synthetic Opioids

This thesis examines the relationship between the United States demand for illicit substances and the evolution of Mexican drug trafficking organizations (DTOs), specifically within the context of a shift from heroin to synthetic opioids. A history of these interdependent actors provides a contextual understanding of Mexico’s current criminal landscape, where DTOs employ adaptive strategies to account for shifts in supply and demand. I also examine the distinctions between the supply chains for heroin and those for synthetic opioids, interpreting the possible implications for DTO strategies. Then, I conduct a regression analysis using a carefully curated set of violent event data from the Armed Conflict Location & Event Data Project (ACLED) to test whether the shift from heroin production to synthetic opioid production by DTOs led to a parallel shift in their presence and violence. My findings challenge the initial hypothesis that a decreasing rate of violence in heroin-producing regions is associated with an increasing rate of violence in Mexico’s Pacific ports - the primary node in the synthetic opioid supply chain. Further examination of the data provides valuable detail on the actions and strategies of Mexican DTOs from 2018 to the present day. I conclude by discussing the potential of event data to aid political violence research and explore possible policy solutions for both the U.S. opioid epidemic and drug violence in Mexico.  

Keywords: Center for International Security and Cooperation
Cartels
Opioids
Mexico
Heroin
Political violence
Text
Thesis
Advisor: MacCoun Robert
Changing the Agenda: Assessing the Evolution of the Peacebuilding Commission

The Peacebuilding Commission was created in 2005 to close an institutional gap in the UN. It was designed as a member-state body that would work to prevent catastrophic failure and also address what should be done once a crisis had been averted or violent conflict had come to an end. While the literature provides some assessment of the PBC’s impact in individual cases or areas, it has failed to evaluate the impact of the 2015 reform effort, which caused to significant and fundamental shift in the PBC’s operation. This thesis evaluates how this shift in operations changed both the form and substance of PBC engagement, examining both broad trends in the PBC’s agenda and work and its impact in specific contexts, using the cases of Liberia and Burkina Faso. It finds a pattern of broader-but-shallower engagement, with a consistently expanding agenda that covers a broader range of cases in addition to more thematic work, but less investment and ultimately less impact in individual cases. The post-2015 format of the PBC was less able to provide the sustained, high-investment, and long-term engagement that could support a strategic or advisory role or encourage political buy-in. However, the lighter form of engagement did allow the PBC to cover a greater range of cases and topics, and in “easier” cases a higher-investment form of engagement was likely not as necessary. Still, these findings have implications for continuing efforts to reform and improve the PBC, particularly given the number of difficult and complex cases currently on the agenda.

Keywords: United Nations
United Nations Peacebuilding Commission
Center on Democracy, Development, and the Rule of Law
Text
Thesis
Advisor: Stedman Stephen
Characterizing cell-autonomous and non-autonomous contributions of RUNX1 loss in hematopoiesis and leukemogenesis using genetically engineered primary human cells

Disease-initiating mutations in the transcription factor RUNX1 occur as germline and somatic events that cause leukemias with particularly poor prognosis. However, the role of RUNX1 in leukemogenesis is not fully understood and effective therapies for RUNX1-mutant leukemias remain elusive. Here, we use primary patient samples and a RUNX1 knockout model in primary human hematopoietic cells to investigate how RUNX1 loss alters human hematopoietic develop and contributes to leukemic progression and to identify targetable vulnerabilities. RUNX1 loss expanded monocytic differentiation at the expense of erythro-megakaryocytic cells due to dysregulation of key transcription factors regulating erythro-megakaryocytic (GATA1, SRF) and myeloid (NFB) differentiation. Surprisingly, RUNX1 loss decreased proliferative capacity and stem cell function. However, RUNX1-deficient cells selectively upregulated the interleukin-3 (IL-3) receptor. Exposure to IL-3, but not other JAK/STAT cytokines, rescued RUNX1 KO proliferative and competitive defects. Further, we demonstrated that RUNX1 loss repressed JAK/STAT signaling and rendered RUNX1-deficient cells sensitive to JAK inhibitors. Our study identifies a dependency of RUNX1-mutant leukemias on IL-3/JAK/STAT signaling, which may enable these aggressive blood cancers to be targeted with existing agents

Keywords: Medicine.
Advisor: Majeti Ravindra
Chan Charles (Charles M.)
Nakauchi Hiromitsu
Wu Joy
Characterizing hydrologic and economic risk due to flooding driven by atmospheric rivers

Atmospheric rivers (ARs), sometimes called "rivers in the sky," are long, narrow bands in the atmosphere that carry high levels of moisture from the tropics to the mid-latitudes. They deliver up to half of California's annual water supply, but they also can cause extreme precipitation and floods. The overall goal of this dissertation is to identify which ARs are most likely to cause damaging flooding. First, I connect AR hazard, which is based only on the intensity of the atmospheric event, to AR risk, which includes the exposure and vulnerability of infrastructure and communities. Using tools from earthquake engineering, probabilistic risk analysis, and interpretable machine learning, I characterize AR-driven flood risk from both a process-based (top-down) and a data-driven (bottom-up) perspective. These two complementary approaches are used to identify influential drivers of extreme consequences. I then quantify the contribution of temporal compounding to the hydrologic and economic impacts of ARs. Temporal compounding is the risk amplification that occurs when two or more AR storms occur in close succession. The series of ARs that affected California in the early months of 2023 are an example of the significant consequences that temporal compounding can cause when the hydrologic environment does not have time to recover between events. I create a new metric, AR sequences, to identify when temporal compounding is contributing to risk. I show that sequences are associated with higher levels of hydrologic impacts, such as extreme runoff and soil moisture, than ARs are on their own. They also increase both the probability and the magnitude of economic impacts from damaging flooding. Finally, sequences are expected to increase in frequency, intensity, and duration in a future climate, with the largest frequency increases occurring at the longest durations. Altogether, this dissertation both identifies a growing threat to California's water resources and introduces a suite of AR flood risk assessment tools to manage that threat.

Keywords: Engineering.
Advisor: Baker Jack
Fletcher Sarah
SerafinKatherine
Charging ahead or leaving behind? Climate change, air pollution and environmental justice consequences of vehicle electrification in India

India, with a population projected to reach 1.64 billion by 2050 and responsible for approximately 7% of all greenhouse gas (GHG) emissions, faces significant challenges in achieving environmental sustainability in its transportation system. Vehicle electrification has been proposed as a potential solution, but the net effects on GHG and criteria air pollutant emissions are influenced by the electricity generation mix, carbon capture and air pollution control technologies used. In this dissertation, we perform a state-specific life-cycle assessment to evaluate GHG and sulfur dioxide (SO2) emissions for representative passenger vehicles and technologies. Results show that battery electric vehicles (BEVs) have higher GHG and SO2 emissions in most states under present conditions, indicating that widespread vehicle electrification is not feasible until the grid decreases CO2 and SO2 emissions. We also model the change in PM2.5 exposure, premature mortality and monetized damages from multiple vehicle electrification and grid scenarios, finding that vehicle electrification under present day conditions increases premature deaths from air pollution. Higher PM2.5 exposure levels are seen in scheduled castes/tribes, poor, and rural populations compared to urban and high-income groups, particularly in high coal production states. Switching to zero-emitting electricity generation sources such as renewables, nuclear or installing technologies such as post combustion carbon capture and storage (CCS) and flue gas desulfurization units would reduce premature mortality from road transportation due to air pollution. We also find that enabling CCS in coal power plants in India could reduce power sector GHG emissions by 743 million metric tons per annum along with air pollution related health co-benefits

Keywords: Sustainability.
Energy Resources Engineering.
Advisor: Azevedo Inês M. L.
Brandt Adam (Adam R.)
Rajagopal Ram
Weyant John P. (John Peter)
Chemical ecology of alkaloids in poison frogs

Alkaloids are used as chemical defenses by taxa spanning the tree of life, including plants, insects, birds, fish, and amphibians. Poison frogs of the family Dendrobatidae sequester alkaloids from their diet of small arthropods and use these alkaloids, in tandem with their aposematic coloration, to deter predation. Poison frog toxicity has been studied for decades, with much of the work focusing on characterizing the diversity of toxins found across species. This foundational work has enabled the pursuit of additional questions looking at how these alkaloids shape the interactions of frogs with other organisms in their environments. In this dissertation work, I use a combination of natural sampling in the field, controlled laboratory experiments, and detailed in vitro and molecular analyses to explore the role of alkaloids in poison frog ecology and evolution. First, I explore the relative impact of genetics and the environment in shaping poison frog alkaloid profiles and find that poison frogs seem to be locally adapted to environmentally available alkaloids, such that frogs are better able to sequester, and in some cases modify, alkaloids to which they have been historically exposed. Then, I examine the impact of alkaloids on the skin microbiome of poison frogs and find that alkaloids play a significant role in shaping the microbiome, making microbial communities more diverse and less even. These patterns seem to be explained, at least in part, by the ability of some strains to metabolize alkaloids for use as a carbon source. Together, these findings expand upon our understanding of how alkaloids shape poison frog ecological interactions across scales ranging from the microscopic to the evolutionary.

Keywords: Humanities and Sciences.
Biology.
Advisor: O'Connell Lauren A.
Cremer Jonas
Fukami Tadashi
Relman David A.