VictorJuiz/thesis huggingface dataset:
Assessing the Evolution and Impacts of Brazilian Hydropower

For over a century, hydropower has represented the largest source of Brazilian electricity, supplying more than three-quarters of power today. This paper traces Brazil’s reliance on hydropower over the 20th century alongside a growing concern for the impacts of industrialization on the environment, which culminated in the implementation of the Environmental Impact Assessment (EIA) in 1988. The adoption of the EIA was a defining moment for Brazilian environmental regulation. It required detailed analysis of proposed projects and allowed officials to make informed decisions regarding environmental and social impacts. This paper conducts a review of the EIA system, including both its global and Brazilian implementation, its influence on hydropower projects, and the fundamental challenges it faces as a regulatory tool. The theoretical evaluation of the EIA is expanded on through the comparison of Brazil’s largest Amazonian hydropower projects, the Tucuruí Dam, constructed before the EIA, and the Belo Monte Dam, constructed after. This comparative analysis demonstrates that the EIA has significantly altered the planning of hydropower dams, while also highlighting flaws in the EIA process that undermine its ability to mitigate environmental and social impacts. Although it is possible to reduce certain impacts associated with hydropower, this study suggests that issues such as deforestation, flooding, mass-displacement, loss of ecosystems, greenhouse gas emissions, and impacts on indigenous peoples are virtually unavoidable when constructing mega-dams within the Amazon region. These results recommend a renewed focus on alternative energy sources and necessitate careful consideration of hydropower’s role in Brazilian sustainable development.

Keywords: Hydropower
Brazil
Environmental Impact Assessment
Sustainable development
Text
Thesis
Assessing the Impact of the COVID-19 Pandemic on Health and Social Wellbeing in Low-socioeconomic Status Seniors

The COVID-19 pandemic has presented challenges for all age groups, with older adults being disproportionately affected as some of the most vulnerable people in society. Low-socioeconomic status (SES) older adults experience further challenges surrounding mental health, social wellbeing, and food insecurity. Given the unprecedented nature of the pandemic, it is important to understand the extent of the impact COVID-19 has had on this population, with the ultimate goal of identifying gaps in care services for low-SES seniors and opportunities for improved programming. In this cross-sectional mixed methods study, 93 low-SES seniors living in two affordable housing communities in the East Bay Area were surveyed. Around 76% of participants were aged 70 or older, 72% were female, and 58% identified as non-Hispanic White. In the printed 6-page questionnaire, participants were asked to reflect on their experiences prior to the pandemic and compare them to their present state, one year into the pandemic. Following survey collection, a subset of five respondents was interviewed over the phone to identify key themes. Statistical analyses on the survey data showed that as compared to pre-COVID-19, participants indicated a significant decline in their diet and nutrition, physical health, sleep quality, mental health, and social networks. In terms of social wellbeing, there was a decline in feelings of connectedness to one’s community and time spent eating in the company of others, and an increase in feelings of loneliness and isolation. However, perceptions of general support and having people to turn to did not decline. Interview data generally confirmed survey findings, with participants, two of whom had lost partners during the pandemic, frequently citing feelings of anxiety and intense isolation from friends. Finally, participants indicated a need for better COVID-19 informational services and programming. These results reveal the need for increased safe social programming and outlets for low-SES seniors who often suffer from poorer mental and physical health at baseline. The findings help reveal the changing needs of seniors during this challenging time and urge the development of solutions to improve health and wellbeing in the low-SES senior population, especially during periods of crisis involving social restrictions.

Keywords: Older people
Older people > Care
COVID-19 Pandemic (2020-)
Health
low-income
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Thesis
Atom manipulation-enhanced quasiparticle interference : accessing band structure, pseudospin and landau levels

We have developed a method to investigate electron wavefunction using scanning tunneling microscope (STM). By imaging the defects in a condensed matter system, one can measure the properties of wavefunctions solely based on the density of state. For example, our method probes the electronic dispersion which is unavailable otherwise because the crystal momentum is encoded in the phase of a Bloch wave. We aim to study electronic structures with a spatial resolution that is beyond the reach of transport measurements which are limited by the size of electrical contacts, and optical methods which are limited by the size of optical beams. With atom manipulation, we further extend the method to study the inner degree of freedom of a wavefunction such as pseudospin. Electrons scatter differently upon defects with different symmetry. By designing the symmetry of defects using atom manipulation, we measure pseudospin and pseudospin selection rule based on the interference patterns of electron scattering around different defects. In this thesis, I first derive the relation between wavefunctions and scattering patterns from the first principle. This theory is then validated in experiments with quantum corrals that host well-understood particle-in-a-box wavefunctions. All experiments are conducted on nanostructures and lattices created by patterning the two-dimensional electronic surface state of the Cu(111) surface with carbon monoxide (CO) molecules. I then apply the method to several quantum materials, including graphene and quasicrystals, to study their electronic structures. Finally, I present studies that relate to quantum scattering of two-dimensional electrons, including a Fermionic Casimir force and an inverse scattering problem

Keywords: Applied Physics.
Advisor: Kasevich Mark A.
Manoharan Harindran C. (Harindran Chelvasekaran)
Devereaux Thomas Peter
Auditing bias and representation in sociotechnical systems

Algorithms are ubiquitous and critical sources of information, increasingly acting as gatekeepers and intermediaries on virtually any topic, including our friends and family, news and politics, entertainment, and even health and well-being. However, studying such content poses considerable challenges, as it is both dynamic and ephemeral: these algorithms are constantly changing, and frequently changing silently, with no record of the content to which users have been exposed over time. To address these challenges, in this dissertation I argue for the need for an interdisciplinary approach that combines strategies, methods, and insights from computational and behavioral sciences. In particular, one strategy that has proven effective is the algorithm audit: a method of repeatedly querying an algorithm and observing its output to draw conclusions about the algorithm's opaque inner workings and possible external impact. Algorithm audits can, without access to underlying algorithms, identify patterns in algorithmic content with important social implications in domains including politics, discrimination and bias, and news media. In my dissertation, I present an overview of the algorithm audit methodology, including the history of audit studies in the social sciences from which this method is derived; a summary of key algorithm audits over the last two decades in a variety of domains; and a set of best practices for conducting algorithm audits today. I concretize these contributions by detailing two case studies, scraping algorithm audits I have conducted. Subsequently I describe a new class of algorithm audits I term intervention auditing, and a system developed for researchers to conduct such audits. Finally, I conclude by discussing the social, ethical, and political dimensions of auditing algorithms, and proposing normative standards for the use of this method, in particular advocating for algorithm auditors to consider this method as a possible vehicle for activism—a method with the potential to bring about social change for the greater good

Advisor: Hancock Jeff 
Landay James A.
Bernstein Michael S.
Karahalios Karrie
Augmenting transition systems for scalable symbolic model checking

Symbolic model checking is an important tool for finding bugs (or proving the absence of bugs) in modern hardware and software systems. Because of this, improving the ease of use, scalability, and performance of model checking tools and algorithms continues to be an influential research direction. In service of this goal, we present two tools followed by two novel techniques that expand the state of the art in symbolic model checking. The first tool, Smt-Switch, provides simple, uniform, and high-performance access to satisfiability modulo theories (SMT) solving for applications in areas such as automated reasoning, planning, and formal verification. We then present Pono, an open-source SMT-based model checker built on Smt-Switch. Pono is designed to be both a research platform for developing and improving model checking algorithms, as well as a performance-competitive tool to be used for academic and industry verification applications. Next, we use this infrastructure to prototype two model checking approaches that reduce the difficulty of a problem by modifying the given transition system model. First, we develop a framework for model checking infinite-state systems by automatically augmenting them with auxiliary variables, enabling quantifier-free induction proofs for systems that would otherwise require quantified invariants. We combine this mechanism with a counterexample-guided abstraction refinement scheme for the theory of arrays. Our approach can, in many cases, reduce inductive reasoning with quantifiers and arrays to quantifier-free and array-free reasoning. Second, we adapt partial order reduction (POR) for bounded model checking of synchronous hardware and introduce a novel technique that makes partial order reduction practical in this new domain. We demonstrate substantial performance improvements over unaltered bounded model checking with this technique, despite the conventional wisdom that POR is only applicable for asynchronous systems

Keywords: Electrical Engineering.
Advisor: Barrett Clark
Horowitz Mark (Mark Alan)
Matthews John Robert
Trippel Caroline
Autonomous exploration of complex environments using active SLAM

This dissertation develops a novel algorithm to perform autonomous surveys of unexplored 2D and 3D environments by extending the coverage path planning (CPP) literature to perform surveys using probabilistic coverage estimation. Robotic survey missions are designed to gather data from an environment and produce maps after the robot has been retrieved. The maps can take the form of 2D mosaics for planar terrain and 3D reconstructions for complex 3D environments. Survey missions of this form have applications in search-and-rescue, structural inspection, and scientific study. The goal of the survey mission is to achieve complete coverage, which is to have the robot observe every part of the environment before it is retrieved. Complete coverage becomes an issue when the robot does not have accurate localization, which can happen in environments that experience GPS-denial, e.g. underwater. In such environments, simultaneous localization and mapping (SLAM) is commonly used for localization. SLAM is an approach that corrects odometry with additional information in the form of terrain features. However, SLAM performance can degrade when there are insufficient features available, i.e. the terrain is feature-poor. There has been an evolution of algorithms that addresses the problem of surveying GPS-denied feature-poor terrain. State-of-the-art survey methods plan paths based on a coverage map, an estimate of which parts of the target area have been seen by the robot. This approach is called CPP. This thesis extends the CPP literature by developing an algorithm called SLAM directed by uncertainty-based node connections (SLAM-DUNC). For 2D surveys, SLAM-DUNC incorporates localization uncertainty into the coverage map to calculate a probability of coverage and plans paths based on this quantity. This extension enables probabilistic coverage estimation with cameras. For 3D surveys, paths are planned using a similar quantity called the probability of occupancy. SLAM-DUNC was demonstrated in simulation and on flight hardware, both in 2D and 3D environments. In 2D, SLAM-DUNC produced less false positive coverage compared to a non-probabilistic coverage method. For surveys in 3D environments, SLAM-DUNC produced an occupancy estimate that maintained accuracy and conservativeness in feature-poor terrain. An additional contribution is the improvement of a known localization algorithm called GraphSLAM to be more robust to false feature correspondences. These improvements are demonstrated using field data

Keywords: Aeronautics and Astronautics.
Advisor: Rock Stephen M.
Kochenderfer Mykel J.
Schwager Mac
Averaging Americans : literature, statistics, and inequality

Averaging Americans: Literature, Statistics, and Inequality was sparked by a computational discovery I made in a corpus of more than 18,000 works of US fiction: statistical words such as average, normal, and typical distinguish postbellum fiction from its antecedents quantitatively and qualitatively. Averaging Americans explores how authors of the long nineteenth century used statistical thinking to rewrite American identity in ways that were both reactionary and radically egalitarian. This increasing dependence on statistical concepts at the same time that US fiction becomes polemically invested in realist representation is less a coincidence than an understudied fact of US literary history. I reveal how claims to representativeness take on aesthetic and political urgency amid struggles over citizenship, the biopolitics of population management, and the inequalities that define Reconstruction, the Gilded Age, and the Progressive Era. Critiquing claims to representativeness reveals how that concept is both central to yet undertheorized by literary studies. The average American may well be the long nineteenth century's most important fictional character

Advisor: Jones Gavin Roger
Algee-Hewitt Mark
McGurl Mark
Moya Paula M. L.
B cell dysregulation in immune mediated diseases

Alterations in B cell homeostasis drive pathogenesis of various immune mediated diseases. Breaks in peripheral tolerance allow autoreactive B cells to differentiate in to pathogenic auto-antibody secreting cells. B cells themselves may directly drive pathogenesis through antigen-presentation capabilities and secretion of pro-fibrotic factors. Lastly, the inability of B cells to mount effective responses against pathogens may trigger subsequent inflammatory or autoimmune reactions. In this work, we dissect various ways in which B cells contribute to pathogenesis of inflammatory disease by evaluating their role in three different immune mediated diseases. In chapter 2 we identify a potential regulatory role for B cells in the context of Systemic Lupus Erythematosus (SLE), an autoimmune disease characterized by the pathogenic secretion of anti-nuclear antibodies. We found that CD52 is a B cell regulatory glycoprotein elevated on the surface of B cells in patients and acts to suppress B cell hyperactivity both through its surface expression and through the secretion of a soluble form that can bind receptor Siglec-10. In chapter 3 we describe a population of B cells that is significantly expanded in IgG4-RD, a fibroinflammatory condition characterized by infiltration of IgG4+ plasma cells into tumefactive lesions and the development of storiform fibrosis. The expanded population of B cells was CD21— and CXCR5+, expressing high levels of pathogenic B cell marker CD11c. Moreover, the frequency of this expanded population correlated with clinical parameters such as IgG4 titers. We observed a tremendous elevation of CXCL13, the ligand for CXCR5, strongly implicating the CXCR5-CXCL13 axis in recruiting B cells to affected tissue, making it a viable therapeutic target. Lastly, in chapter 4 we performed high-dimensional sequencing on B cells from sarcoidosis patients, a disease characterized by spontaneous granuloma formation. Although B cells have not been directly implicated in the inflammation, we observed a less diverse and less mutated B cell receptor repertoire; together, our findings point to the initiation of sarcoidosis after ineffective antibody mediated clearance of pathogen from affected organs. In total, this work sheds novel insights on the role of B cells— from the initial stages of activation and germinal center recruitment, to the development of a diverse antibody repertoire— in the context of poorly understood immune mediated conditions and contributes important knowledge for the advancement of better treatments for affected patients

Advisor: Robinson William (William Hewitt)
Maltzman Jonathan
Mellins Elizabeth
Bayesian WIMP Parameter Inference for LXe TPCs

Astrophysical evidence has long indicated the presence of a large percentage of invisible mass in the universe. The presence of this invisible and essentially collision-less mass, known as dark matter, has only been detected so far by its gravitational influence on astrophysical objects. Physicists have hypothesized that the Weakly Interacting Massive Particle (WIMP), a particle with mass in the GeV/c^2 range that interacts with baryonic matter at a weak scale, is a prime candidate for dark matter. If the WIMP hypothesis is correct, experiments on Earth can aim to discover them by looking for rare scatters off of atomic nuclei, which the LUX-ZEPLIN (LZ) experiment aims to do. LZ will use a liquid xenon Time Projection Chamber (LXe TPC) to detect elastic scatters off of xenon atoms caused by impinging WIMPs.
This thesis will introduce a generalized Bayesian statistical framework that is able to infer a WIMP's mass and spin-independent scattering cross section from simulated datasets. The framework will be developed around the LZ detector template, but will efficiently generalize to other similar LXe TPCs. We utilize this framework to generate and reconstruct several simulated experiments to highlight the statistical limitations on parameter inference posed when utilizing LXe TPCs. We also compare the change in reconstruction efficiencies caused by detectors of different masses and different background rates. Our reconstructions indicate that at low event rates, reduced backgrounds do not provide a significant gain in parameter resolution due to limitations posed by the WIMP scattering spectrum. On the contrary, increased detector sizes provide significant gains in statistical resolution. This indicates that for parameter inference purposes, future experiments should prioritize larger tonne-year detectors over reduced backgrounds.

Keywords:  Department of Physics
LUX-ZEPLIN
LZ
Dark Matter
WIMP
Parameter Inference
Bayesian
Text
Thesis
Advisor: Akerib Daniel
Shutt Tom
Better optimization algorithms, moving beyond the classics

This thesis studies several problems in optimization, from complexity-theoretic investigations to algorithm design questions. More specifically, (1) we give an iteration complexity-optimal algorithm for minimizing highly smooth convex function with Lipschitz continuous higher-order derivatives; (2) we investigate the complexity of optimizing convex, non-smooth functions with a highly parallel oracle, giving an algorithm with improved depth compared to the state-of-the-art and obtaining tighter lower bound characterizing when the parallel information helps compared to its fully sequential counterpart; (3) we propose an efficient sketching-based distributed algorithm with lightweight communication that can return high-accuracy solution for problem having composite structure. Through a better understanding of the fundamental barrier to problem efficiency on one hand, and the design of practical algorithms addressing requirement of modern computation model on the other, the thesis offers glimpse of the vast opportunities that the role of optimization remains to play for data science in either direction

Keywords: Electrical Engineering.
Advisor: Candès Emmanuel J. (Emmanuel Jean)
Pilanci Mert
Wootters Mary
Better Together? The Effect of U.S. Defense Industry Consolidation on Procurement Outcomes

Many policymakers believe that the consolidation of the U.S. defense industry is suboptimal, pointing to cost overruns, program delays, and technological problems with products. Meanwhile, economists believe that there may actually be efficiencies to be gained through consolidation in the defense industry and that therefore, its effects are not always negative. Utilizing a novel approach that combines economic and social science analyses, this thesis asks whether the consolidation of the U.S. defense industry has, in fact, increased costs and schedule delays of major defense acquisition programs and decreased private sector innovation and investment in innovation. Analysis of original datasets of Selected Acquisition Report summary table data from 2000-2020, schedule delay data compiled from GAO Annual Weapon’s Assessment reports since 2003, and company research and development spending of the prime contractors from 2000-2020 suggests that defense industry consolidation leads to negative effects on the cost and schedule of major defense acquisition programs as well as varied effects on private sector innovation/investment in innovation. Case studies of the F-35 and Ground Based Strategic Deterrent illustrate the dangers of the current states of the procurement process and the defense industry and also raise questions about the efficacy of current economic methodologies for analyzing cost growth of major defense acquisition programs. Policymakers should consider further examination of defense industry competition and M&A activity as well as the benefits of knowledge-based acquisition practices as the Department of Defense moves towards key decision points regarding legacy systems and the future of U.S. defense capabilities.

Keywords:  Center for International Security and Cooperation
Defense
Procurement
Defense Industry Consolidation
Prime Contractors
Major Defense Acquisition Programs
Selected Acquisition Reports
Political Science
Thesis
Advisor: Zegart Amy
Larsen Brad