VictorJuiz/thesis huggingface dataset:
Scalable hierarchical high-order CFD solvers for future exascale architectures
Keywords: Engineering.
Aeronautics and Astronautics.

With the public launch of supercomputer Frontier at Oak Ridge National Laboratory in May 2022, we are officially entering the exascale era of computing, characterized by systems capable of executing one exaFLOPS (10^18 floating-point operations per second). With the anticipated advent of additional exascale supercomputers in the forthcoming years, the extraordinary leap in computational power promises to revolutionize various fields for scientific discovery. For the Computational Fluid Dynamics (CFD) community to harness the power of these future supercomputers for complex Navier-Stokes computations, we must rethink and redesign numerical algorithms for extreme parallelism, paying particular attention to data placement and movement. In addition, advances in turbulence simulation technology will play a critical role in the analysis and design of aerospace systems. The accurate prediction of turbulence is essential for determining aerodynamic characteristics of aircrafts. High-order numerical methods have recently emerged as a promising approach to address various challenges of scale-resolving simulations. Yet, efficient preconditioners and linear solvers, which are often the most computationally intensive parts of implicit high-order codes, are still largely elusive. In this work, we aim to design a high-order CFD solver capable of providing high-fidelity solutions for scale-resolving simulations while simultaneously showcasing efficient scalability on prospective exascale supercomputers. To this end, this dissertation presents the development and implementation of a hierarchical scalable high-order CFD solver framework. The proposed framework integrates a promising hierarchical preconditioner based on Sparsified Nested Dissection and a communication-avoiding iterative Krylov solver with guaranteed numerical stability. The performance of the framework is evaluated in an implicit Discontinuous Galerkin high-order solver. With scaling studies, we demonstrate the algorithmic scalability and robustness of the overall framework for solving real-world aerospace engineering problems
Scalable infrastructure for digital currencies
Keywords: Engineering.

Recent years have seen a significant increase in interest among policymakers and financial institutions in digital currencies and a new generation of financial infrastructure. This thesis investigates the design of computational infrastructure and economic mechanisms for these new systems. Specifically, this thesis develops infrastructure that, unlike prior state-of-the-art systems, performs with computational scalability that is nearly-linear on both best-case and worst-case workloads, and that does not significantly limit the range of operations that a user can express. Building this infrastructure requires instantiating and therefore demonstrating the practical feasibility of previously-unused types of economic mechanisms for exchanging digital currencies, with efficiency and fairness properties of independent interest. This thesis then studies the economic tradeoffs encoded in mechanisms for exchanging assets, the tradeoffs involved when combining different mechanisms together, and ways in which these mechanisms interact with the underlying computational infrastructure.
Scaling deep robotic learning to broad real-world data
Keywords: Engineering.

From general object grasping to in-hand manipulation, deep learning has enabled a number of exciting robotic manipulation capabilities in recent years. Despite this, the quintessential home robot that can enter a previously unseen home environment and complete a wide range of tasks like humans can is far from a reality. While there are many problems to solve in accomplishing this goal, one of the central bottlenecks lies in learning control policies from the robot's sensor inputs that can generalize to new tasks, objects, and environments. For example, a robot cooking in a home cannot afford to re-learn from scratch for each new dish, nor is it feasible to hard-code state features for every new kitchen a robot might encounter. One potential route to accomplishing this generalization is to train the robot on a wide distribution of data that contains many tasks, objects, and environments. Indeed, this recipe of large, diverse datasets combined with scalable offline learning algorithms (e.g. self-supervised or cheaply supervised learning) has been the key behind recent successes in natural language processing (NLP) and vision. However, directly extending this recipe to robotics is nontrivial, as we neither have sufficiently large and diverse datasets of robot interaction nor is it obvious what types of learning algorithms or sources of supervision can enable us to scalably learn skills from these datasets. The goal of this thesis lies in tackling these challenges, and replicating the recipe of large-scale data and learning in the context of robotic manipulation. The first part of this thesis will discuss how we can scalably collect large and diverse datasets of robots interacting in the physical world and how we can effectively pre-train self-supervised world models on such offline robot datasets. We'll then explore how we might use these pre-trained world models to solve tasks by combining them with planning, first for solving long-horizon manipulation tasks, and second for completing tasks specified by natural language. Finally, we'll discuss how we might go beyond robot data and unlock the broad sources of data that exist on the web, like videos of humans, to enable more effective learning in our robots, specifically through reward learning and visual pre-training. The thesis will conclude by discussing open challenges, particularly how we might unify the paradigms of simulation, real-world data collection, and videos of humans to realize the vision of a general-purpose household robot
Scaling human feedback
Keywords: Engineering.

Human-generated data has been pivotal for significant advancements in artificial intelligence (AI). As AI models scale and are applied to a wider range of tasks, the demand for more and increasingly specialized human data will grow. However, current methods of acquiring human feedback, such as learning from demonstrations or preferences, and designing objective functions or prompts, are becoming unsustainable due to their high cost and the extensive effort or domain knowledge they require from users. We addresses this challenge by developing algorithms that reduce the cost and effort of providing human feedback. We leverage Foundation models to aid users in offering feedback. Users initially define their objectives (through language or a small dataset), and Foundation models expand this into more detailed feedback. A key contribution is an algorithm, based on a large language model, that allows users to cheaply define their objectives and train a reinforcement learning agent without needing to develop a complex reward function or provide extensive data. For situations where initial objectives are poorly defined or biased, we introduce an algorithm that efficiently queries humans for more information, reducing the number of needed queries. Finally, we conclude by proposing an information-gathering algorithm that eliminates the requirement for human intervention altogether, streamlining the feedback process. By making it cheaper for users to give feedback, either during training or when queried for more information, we hope to make learning from human feedback more scalable.
Scaling single cell genomics analysis to millions of cells
Keywords: Engineering.

Improved experimental methods in single cell genomics have increased dataset sizes by two orders of magnitude in the last five years, such that software scalability is quickly becoming a key bottleneck in our ability to analyze and understand multi-million cell atlases. Most analysis methods load full datasets in memory, resulting in excessive memory usage that scales one-to-one with dataset size. Furthermore, existing compressed storage formats for single cell datasets are so slow to read that practical analysis must be performed on uncompressed data. This work describes BPCells, a software package for scalable analysis of massive single cell RNA-seq and ATAC-seq datasets. BPCells provides lossless, seekable bitpacking compression for scATAC-seq fragment alignments and sparse single cell counts matrices. These compression formats are so fast that a single thread can decompress a dataset faster than loading an uncompressed version from a hard drive. Additionally, BPCells implements disk-backed streaming computations that can reduce memory requirements by two orders of magnitude compared to popular tools like Scanpy and Seurat, while incurring little or no speed penalty. Notably, BPCells can reproduce the results of existing software packages to within numerical precision, making it a drop-in replacement for existing tools. This work covers the design and implementation of BPCells, along with applications of single cell analysis
Scavenged state : archives and the making of modern China
Keywords: Humanities and Sciences.
History.

Scavenged State reconstructs the socioeconomic and political history of modern Chinese archives. A key concept for this project is scavenging, a term that is not usually applied to state archive creation. Often considered a desperate survival tactic that occurs in the wake of ruin, I found that archival scavenging in China was surprisingly systematic, strategic, and creatively optimistic. Over a century of civil war, imperial invasion, and revolution, certain caches of documents were privileged and then reintroduced as foundational for a variety of states, including Japanese-aligned, warlord, republican, and communist. When pressured to conform to international standards (such as those favored by France, the Soviet Union, or the United Nations), record keepers advocated for "Chinese-style" systems, deliberately ambiguous phrasing that reached to imperial precedent for authority while embedding contemporary political concerns about state survival in reforms of archival material processes. These processes—which included everything from document accession and indexing guidelines to exhibition strategies, destruction protocols, and security audits—reveal fascinating shifts in strategic conservation. My research on the development and implementation of these seemingly mundane curatorial procedures shaped the source-base that scholars and policymakers rely on today. Documentary protocols turn out to have been highly political. Recognizing the role of scavenging in the creation of state archives calls for us to decenter the party-state and make room for local and individual agency in summoning forth visions for modern China
Science fiction's pedagogy : didactic models and experiential simulations
Keywords: Humanities and Sciences.

This dissertation proposes a conceptual framework for the following areas of inquiry: 1) understanding science fiction pedagogy at different scales, 2) examining the relationship between model and simulation as one of curriculum, and 3) evaluating the uses of science fictional texts in humanistic and STEM education contexts. It applies that framework in the service of literary criticism, producing readings of science fiction novels using curricular reading as a practice. It then turns to the question of whether slaves and robots are substitutable and the pedagogical implications of that substitution. Using digital humanities methods, the dissertation concludes by examining the substitutability premise in a single text, using text-comparison methods, and in corpora of science fiction and traditional realism, using word embeddings.
Screen stutter : lettrism and the disarticulation of the avant-garde
Keywords: Humanities and Sciences.
Art and Art History.

In everyday conversation, sonic excesses of voice, such as hums, lisps, slurs, sighs, and stutters, impede communication, burden interlocutors, and diminish one's sense of self-sovereignty. Yet for a group of artists working in Paris throughout the French Fourth Republic (1946--1958), non-semantic vocalizations were sounds of significant avant-garde aesthetic import. In "Screen Stutter: Lettrism and the Disarticulation of the Avant-Garde, " I draw out the form and function of the disarticulate voice in the production and reception of postwar art and cinema. I explore why artists and filmmakers Isidore Isou (1925--2007), Maurice Lemaître (1926--2018), and Gil J. Wolman (1929--1995), collectively working under the label "Lettrism, " utilized the errors, excesses, and aporias of speech as critical, albeit understudied, materials to cut, project, and perform
Seamus Heaney: The Poet as Ethnographer
Keywords: Poetry, Modern
Ethnography
Northern Ireland
Dinnseanchas
Crafts
Irish Troubles
Sectarian Violence
Archaeology
Anthropology
Heaney, Seamus
Crediting Poetry
Classicism
Culture
Myth
Halfie
Ritual
Complicity
Text
Thesis

Anthropologist James Clifford describes ethnography as “a state of being in culture while looking at culture, a form of personal and collective self-fashioning.” Many poems of Seamus Heaney (1939-2013), particularly his early ones, read like ethnographies of everyday rural life in mid-century Northern Ireland, providing firsthand knowledge of farming, crafts, the Ulster dialect, and the rituals and history of his homeland. Heaney’s work celebrates the Irish values of hard work, family loyalty, personal warmth, humor and perseverance in the face of adversity, but it also highlights the violence and complicity of his culture, particularly in relation to the sectarian strife of the Irish Troubles (1969-1998). As Heaney’s renown as a poet grew, his “halfie” identity as a native-born Irishman who was also a British intellectual with a global readership served to expand his perspective. His myth-based poems, especially those written toward the end of the Troubles, transformed his ethnographic approach into a more universal vision of humanity, while maintaining the connection to his Northern Irish rural background.
Security, Governance and Development Beyond the Pavement: A Quantitative Assessment of the Afghan Local Police
Keywords: Afghanistan, Local Security, Economic Development, Afghan Local Police, Local Governance
Text
Thesis

The Afghan Local Police (ALP) was the most robust local defense mobilization effort used in the War in Afghanistan. Funded by the United States and under the purview of the Afghan government, The ALP program aimed at fostering self-defense among local communities while reinforcing the authority of traditional governance institutions. Active from 2010-2020, the program amassed a force of 34,000 men, composed over 8% of the Afghan National Security force, cost the US government $1.2 billion, and even gained a reputation as the American “exit strategy”. Still, little quantitative work has been done to assess how the Afghan Local Police lived up to its ambitious goals of establishing sustainable political order in the countryside. Moreover, only anecdotal evidence provides insight into the ALP's impact on the lives of individual villagers. In this thesis, I build a theory integrating the Afghan Local Police with governance, security, and economic development outcomes. To explore this theory, I measure variables such as nightlight radiance, (a proxy for economic development) and survey data on support for the local government and belief in the local government’s ability to maintain security. I find that, despite originally aspiring to be a crucial part of the local governance and security strategy, the Afghan Local Police failed to correlate with any of these outcomes. I conclude by contextualizing these findings in the broader War in Afghanistan, highlighting how the international coalition's disregard for rural areas contributed to the Taliban's eventual takeover.
Seeing Like a Citizen: Fragmented Citizenship in Santiago de Chile
Keywords: Citizenship
Democracy
Inequality
State
Latin America
Chile
Text
Thesis
Book

This thesis investigates how socioeconomically vulnerable individuals in Santiago de Chile conceptualize and exercise their citizenship in the wake of the 2019 estallido social. Using qualitative analysis of 31 in-depth, semi-structured interviews, the study develops a grounded theory of “fragmented citizenship.” Fragmentation refers to the asymmetrical and often contradictory experiences of citizenship at the individual level in contexts where the state is highly visible but uneven in its provision of services, programs, and goods. Beyond the convergence of these structural conditions of the state—wide visibility and irregular presence—the study found that participants’ multidimensional ideals of citizenship exacerbate fragmentation by setting high expectations of state provision. Fragmentation, in turn, shapes citizens’ engagement with the state, with respondents more likely to exercise their citizenship in areas where they perceive the state to be functioning effectively. Conversely, participants described strategic disengagement from the state and their citizenship where they perceived it to be less fully and reliably realized, further contributing to fragmentation. Through a nuanced and timely ground-level analysis, this thesis builds upon prior research on how citizenship plays out in practice in Latin America to provide valuable insight into the crisis of democracy in Chile and beyond, examining the implications of high citizen expectations coupled with uneven state performance for democratic citizenship.
Seismic velocity model building with deep convolutional neural networks
Keywords: Sustainability.
Geophysics.

This thesis focuses on recovering wave velocity estimates from seismic data with limited recording offsets and band-limited frequency content using Deep Learning (DL), specifically using deep convolutional neural networks (CNN). A combined strategy combines a supervised learning framework to recover the low-wavenumber components of velocity models with the traditional Full Waveform Inversion (FWI) to recover high-wavenumbers. We demonstrate the methodology on synthetic industry benchmark problems and a field data application with an open-source Gulf of Mexico seismic dataset.
Selective organocatalytic ring-opening polymerization of cyclic esters and carbonates
Keywords: Humanities and Sciences.
Chemistry.

Chapter 1 introduces polyesters as sustainable alternatives to traditional petroleum-based plastics, including biorenewable sourcing, degradability, and methods of synthesis and manufacture. It specifically highlights the advantages of polyesters produced by ring-opening polymerization (ROP) and manufactured by additive manufacturing technologies. Chapter 2 describes a catalyst system comprising a hindered base and a primary alcohol initiator which can be utilized for controlled, ultrafast polymerization cyclic monomers when utilized in conjunction with a continuous flow reactor. It highlights the advantages of continuous flow reactors for improving reaction control. Chapter 3 describes a fast, selective organocatalyst for the ROP of cyclic esters and carbonates that functions by simultaneous activation through hydrogen bonding while the monomer is activated by the bound counter ion. Chapter 4 discusses recent developments in the synthesis of polyester resins by ROP, and the mechanical properties of parts generated from them using continuous liquid interface production (CLIP) additive manufacturing. Appendix 1, Appendix 2, and Appendix 3 serve as supplementary information about the materials, methods, and results from Chapter 2, Chapter 3, and Chapter 4, respectively
Selling snake oil and unicorns : performative standardization in the evaluation of early-stage entrepreneurial ideas
Keywords: Business.

This dissertation investigates the process through which venture capital and angel investors evaluate early-stage entrepreneurial ideas. It draws on three sources of data: an ethnographic study conducted across two years of an annual pitch competition in Silicon Valley, archival data from this competition, and interviews with early-stage investors. Chapter 1 inductively examines how structural and temporal constraints within the startup funding ecosystem set the stage for a heretofore unexamined evaluation process. This chapter introduces this process—performative standardization—as involving the collaborative construction of an idea's value by investors and entrepreneurs, followed by the assessment of this constructed value according to widely-shared investor standards. Building on these findings, Chapter 2 delves into how a startup idea's value is quantified and defined, and develops a process model specifying performative standardization. Paradoxically, this chapter finds that investors both acknowledge an idea's quantified value to be subjective and unknowable, yet place weight on it when making evaluative decisions. Chapter 3 leverages the pitch competition's archival data to analyze the consequences of performative standardization. The results reveal how entrepreneurs predominantly adapt their pitches—specifically, the future financial projections detailing an idea's value in the future—to align with investor expectations following the performative standardization process. Moreover, the results show that investors evaluate ideas more positively when pitches include aspects of performative standardization that meet widely-shared standards. Collectively, these chapters underscore the significance of performative standardization as a cultural process that serves not only to assess ideas at the point of evaluation, but also to coordinate and align stakeholders on a common trajectory toward actualizing an idea into a successful venture
Sensing the broadening world : the birth of incense culture in song dynasty China (960-1279)
Keywords: Humanities and Sciences.
East Asian Languages and Cultures.

This dissertation investigates how incense, a once highly exclusive commodity of foreign origins, became widely available since the eleventh century and revolutionized China's sensibility of scents. I examine representations of incense in poetry, tales, treatises, catalogues (pu 譜), and paintings by the scholar-officials, the shaping force of Song society and culture. My analysis uncovers how exquisite scents served as an important medium for Song literati to reconceptualize spirituality, officialdom, private life, knowledge, and cultural others. I demonstrate how the scholar-officials created the xiangpu 香譜 genre to systematically define incense for the first time in Chinese history. The fascination with incense also led to unprecedentedly in-depth explorations of the far south, the main source of domestic incense supply, which reshaped the cultural image of this traditionally stigmatized and underrepresented region. While my research fits with the current "material turn" in sinology, it extends to the growing field of sensory studies. I call attention to scents, one prominent yet neglected topic in China and the global past, establishing the significance of incense in relation to aesthetics, social class, ethnicity, and knowledge production. I argue that the process of knowing and integrating incense into Chinese culture and literature reflected an epistemological change among Song scholar-officials. The invention of incense culture is indicative of the period's growing interest in individual experience, material culture, local distinctiveness, economic incentives, and practical knowledge, all of which were decisive factors in steering China to early modernity