VictorJuiz/thesis huggingface dataset:
Go west, young Han : internal migration as a strategy of counterinsurgency

Why was China able to insulate Xinjiang from Muslim insurgency for a generation during the Maoist period (1949-76) but not later (1981-2015)? The pattern challenges conventional understandings of "sons of the soil" conflicts because Muslim insurgency in Xinjiang decreased when Han in-migration to the region escalated, conversely increasing as Han in-migration declined. By considering counterinsurgency as a delegation problem, I show that state-supported internal migration through a multifunctional agency can be a strategy to reduce -- rather than cause indigenous insurgency. I analyze how the bingtuan in Maoist China served as a multifunctional agency for counterinsurgency -- an organization of Han migrants with the dual function of an armed force and farmers who supported their own livelihood through wasteland reclamation. The bingtuan's dual function provided a low-cost solution for precision-based counterinsurgency by removing the need for effective coordination between multiple agencies that each specialize in military force or intelligence collection. The threat of Soviet subversion via Xinjiang's Muslim population made the use a multifunctional agent optimal for targeting active insurgents precisely, without creating new grievances through indiscriminate repression. The Maoist state's command over key economic resources provided the requisite state capacity to induce compliance from its multifunctional agents. After Mao, declines in both foreign threat and a centrally controlled economy have led the state to use multiple counterinsurgent agencies that were unable to coordinate effectively, resulting in the re-emergence of Muslim insurgency. I test my theory through both within-Xinjiang analyses and cross-regional comparisons between Xinjiang and other peripheral provinces of China, Heilongjiang and Tibet. Evidence is based on my ethnographic fieldwork, interviews with professionals and officials, and an original collection of 550 hitherto untapped historical gazetteers

Keywords: Political Science.
Advisor: Laitin David D.
Oi Jean C. (Jean Chun)
Acharya Avidit
Blaydes Lisa
Going Green with the Green and Gray: How Interpretive Rangers' Perspectives Shape Climate Change Education in Yosemite National Park

Climate change is a clear and present danger to national parks and other protected areas across the United States where rising annual average temperatures and falling precipitation levels are resulting in a myriad of potentially devastating effects. These same parks are also tremendous sources of hope because they provide opportune settings for impactful climate change education through the interpretive programs they offer. To contribute to the development of such programs, this thesis aims to uncover how the experiences, identities, and perceptions of interpretive park rangers influence their approach to climate change interpretation. Through semi-structured interviews with six current and former Yosemite National Park (CA) interpretive rangers, I explored the rangers’ personal backgrounds, relationship to nature and Yosemite, climate change beliefs, and thoughts on climate change interpretation. I found that the rangers experience powerful internal conflicts related to when, whether, and how they include climate change in their interpretive programming. Those conflicts arise as their personal beliefs about climate change, relationship to Yosemite, and sense of professional responsibility to the park and visitors create tension with their (mis)conceptions (according to visitor studies) that climate change interpretation may spoil visitors’ experiences or instigate unwanted confrontation. This tension compromises rangers’ confidence in delivering climate change interpretation faithful to their own identities and deeply held beliefs. Equipped with a better understanding of park visitors’ beliefs and interests and with ongoing professional development, interpretive park rangers may be better supported institutionally and personally to leverage their identities, beliefs, and perspectives to maximize their efficacy as climate change educators.

Keywords: Graduate School of Education
interpretive park rangers
National Park Service
Yosemite National Park
climate change education
climate change interpretation
interviews
Thesis
The H3.3 G34W mutation disrupts the balance between H3K27 and H3K36 methylation to corrupt cellular identity in giant cell tumor of bone and an oncogenic role for ASH1L in lung adenocarcinoma and possibly multiple human cancers

The precise temporal and spatial coordination of histone lysine methylation dynamics across the epigenome regulates virtually all DNA-templated processes. A large number of histone lysine methyltransferase (KMT) enzymes catalyze the various lysine methylation events decorating the core histone proteins. Mutations, genetic translocations and altered gene expression involving these KMTs are frequently observed in cancer, developmental disorders and other pathologies. Therapeutic compounds targeting specific KMTs are currently being tested in the clinic, although overall drug discovery in the field is relatively under-developed. In chapter 1, we review the biochemical and biological activities of histone KMTs and their connections to human diseases, focusing on cancer. We also discuss the scientific and clinical challenges and opportunities in studying KMTs. In chapter 2, we characterize the role of the oncogenic H3.3 G34W mutation in Giant Cell tumor of the bone. To do so, we have created a novel cellular model of the disease using primary human mesenchymal stem cells. Using this model, along with biochemical assays, we determine the causal mechanistic consequences of the H3.3 G34W mutation and identify a novel potential mechanism for crosstalk between epigenetic modifications. In chapter 3, we discuss the role of the ASH1L in human cancers. We find that chromosomal amplification or gain of ASH1L is a highly recurrent event in many tumor types, including Lung Adenocarcinoma (LUAD). We interrogate the specific mechanisms involved in tumorigenesis of Lung Adenocarcinoma (LUAD) using biochemical methods as well as human LUAD cell lines to determine the mechanisms by which ASH1L contributes to tumorigenesis. We also utilize murine models of LUAD to determine the in vivo contributions of ASH1L to the process of tumorigenesis, and find that ASH1L plays a critical role in genetic models of LUAD. In chapter 4, we present a broader view of the field of cancer epigenetics in the context of H3K27 and H3K36 methylation. We highlight several outstanding questions of importance in the field, and nascent opportunities to answer them. We also discuss clinical opportunities on the horizon and the relationship they might have with these outstanding questions

Keywords: Biology.
Advisor: Gozani Or Pinchas
Dixon Scott James
Winslow Monte
Wysocka Joanna
Hardware acceleration For graph neural networks

Traditional deep neural networks (DNNs) rely on regularly structured inputs such as vectors, images, or sequences. This reliance on regularity makes them difficult to use in domains where data is naturally irregular, such as connections on social media. Graph neural networks (GNNs) extend DNNs to operate on arbitrarily structured graph-valued data. However, GNNs do not accelerate efficiently on CPUs, GPUs, and DNN accelerators such as a TPU, due to their irregular and input-dependent pattern of computation. As a result, GNNs have much higher inference latency than other types of DNNs in practice. This limits their use to applications where inference can be precomputed off-line. This dissertation presents hardware and software techniques to reduce the inference latency of GNNs. To this end, we make the following three contributions. First, we introduce a decomposition of GNN inference into a series of three computational phases: aggregate, combine, and update. This decomposition permits a simple representation for a broad class of GNNs we call GReTA. Second, we introduce a GNN accelerator architecture called GRIP. GRIP alleviates the bottlenecks in each phase by using separate memory subsystems specialized for the different access patterns in each phase of inference. Finally, we introduce optimizations to reduce the working memory and bandwidth requirements for GNN inference including caching partitions of feature data, inter-phase pipelining, and merging computation. We also introduce a novel optimization called vertex-tiling that substantially improves latency by increasing the reuse of weight values during inference. Taken together, these techniques significantly reduce the latency of GNN inference over existing state-of-the-art implementations. Evaluated on a broad range of models and datasets, our accelerator reduces latency by 7-70x compared to a CPU and GPU baseline

Keywords: Electrical Engineering.
Advisor: Levis Philip
Horowitz Mark (Mark Alan)
Ré Christopher
Harnessing the tumor microenvironment to enhance ovarian cancer immunotherapy

The five-year survival rate for ovarian cancer remains low despite improvements in therapy and many patients with advanced disease relapse following treatment. For a small subset of patients that have failed other treatment options, immune checkpoint blockade can provide beneficial responses, yet the majority of patients will experience progressive disease13. The goal of the work presented here is to explore options to target the tumor microenvironment in combination with existing immunotherapies to improve their efficacy. PMN-MDSCs are known to contribute to poor cancer outcomes and resistance to immunotherapy, yet we lack clinical therapies to target them. In the first part of this thesis, we identified the IL-5Rα/IL-33/ST2 signaling axis as a potential method to target PMN-MDSCs. In the second part, we demonstrated that FLASH irradiation can provide a safe and effective means to increase anti-tumor T cell activity in combination with αPD-1 checkpoint blockade. Future translational work in both of these areas will hopefully lead to the development of new treatment paradigms for ovarian cancer

Advisor: Rankin Erinn
Engleman Edgar G.
Graves Edward (Edward Elliot)
Sunwoo John B.
Hierarchical approximate factorization methods for the solution of sparse linear systems with application in geoscience

Hierarchical approximate factorization methods are a recent class of approaches to solving sparse linear systems such as those arising from discretized partial differential equations (PDEs). These methods sparsify the fill-in matrix blocks that arise in block Gaussian elimination (assuming that these blocks are low-rank) to obtain an approximate factorization of the given matrix. In the first part of the dissertation, we describe an approach to improving the accuracy of hierarchical approximate factorization methods on the eigenvectors corresponding to the smallest eigenvalues, which is critical for achieving fast convergence of the Krylov subspace methods. We exploit the fact that for a large class of problems, including many elliptic equations, the eigenvectors corresponding to the smallest eigenvalues are smooth functions of the PDE grid. In the second part, we describe an approach to obtaining an additional order of accuracy in the sparsification of the low-rank matrix blocks. To achieve fast convergence, such sparsification must introduce only a small amount of error. In our new approach, the 2-norm of the incurred error in the sparsification of a matrix block is squared, compared to previous approaches, with a small amount of additional computation. The third part is concerned with developing efficient hierarchical factorization methods for symmetric quasi-definite systems such as those arising from coupled poromechanics, as well as saddle-point systems that arise from fractured mechanics. While for symmetric positive definite matrices the existing hierarchical factorization methods are quite efficient, highly indefinite matrices pose a bigger challenge. We develop novel methods that exploit the global (quasi-definite or saddle-point) structure of the matrix for speed, accuracy, and stability

Advisor: Darve Eric
Saunders Michael A.
Tchelepi Hamdi
Hierarchical decision-making in coordinated multi-robot networks

Autonomous robots are deployed to solve a variety of tasks in a wide range of challenging and uncertain environments. Many of the tasks, such as urban package delivery and planetary terrain exploration, involve connected networks of robots coordinating with each other. This thesis presents a comprehensive decision-making framework for controlling such large coordinated multi-robot networks. We decouple the many complex intersecting challenges of our overall question and address them at different levels in a hierarchy. To solve the range of problems covered in this thesis, we draw upon theoretical results from combinatorial optimization, heuristic search, and sequential decision-making under uncertainty. We extend theory to application through state-of-the-art practical techniques for multi-agent methods. On a wide variety of simulations with real-world data, our algorithms compute high-quality decisions for large numbers of agents and tasks

Advisor: Bohg Jeannette
Kochenderfer Mykel J.
Pavone Marco
Sadigh Dorsa
High precision photoemission study of overdoped Bi2212 superconductors

High-temperature superconductivity in the cuprates is a complex and enduring problem. The complexity is evidenced by the phase diagram, where superconductivity is intertwined with a plethora of unconventional states in the pseudogap regime. In this thesis, we try to disentangle superconductivity from such states to better understand its nature. Using angle-resolved photoemission spectroscopy, we first study the cuprate phase diagram near the pseudogap critical doping in Bi2Sr2CaCu2O8+δ (Bi2212). With increasing doping, we find a temperature-independent boundary across which the pseudogap ends and quasiparticle-like excitations recover. The result challenges presumptions associating the pseudogap with a quantum critical point and suggests a relatively simple region in the phase diagram where superconductivity emerges from a Fermi-liquid-like normal state. In the second part, we focus on this pseudogap-free region to study the superconducting phase transition. We discover that the transition temperature coincides with the most rapid drop of zero-energy spectral intensity instead of the opening of the superconducting gap. We also observe a strong momentum anisotropy in the spectral signatures associated with the transition. These observations are consistent with the scenario that the superconducting transition in overdoped Bi2212 is driven by phase fluctuations

Keywords: Applied Physics.
Advisor: Shen Zhi-Xun
Kivelson Steven
Lee Young-Choon
High-valent copper-dioxygen assemblies : synthesis, characterization, and potential relevance to biological systems

Biological enzymes utilize various copper-based active sites to activate dioxygen creating a variety of copper-dioxygen assemblies. These assemblies carry out highly selective and difficult oxidative transformations vital to biological life. Insight into how Nature has optimized these active sites can be gleaned by studying synthetic structural mimics and has potential to be of great benefit to the industrial design of catalysts. While the resting structures of many of these active sites are known, the nature of the active oxidants are often less well-defined. In this thesis, efforts towards the cryogenic synthesis and spectroscopic characterization of copper(III)-containing oxidants, formed directly via dioxygen activation of biomimetic copper precursors, will be discussed. This work demonstrates both the kinetic and thermodynamic accessibility of the copper(III) oxidation state under biological ligation, which challenges existing assumptions in the literature through the identification of reactive intermediates

Keywords: Chemistry.
Advisor: Stack T. (T. Daniel P.)
Cui Yi
Solomon Edward I.
Holistic battery management system design for lithium-ion battery systems via physics-based modeling, estimation, and control

Lithium-ion battery systems used in electric vehicles and stationary grid storage applications are composed of numerous batteries that are interconnected to create a battery pack that can satisfy the high energy and power requirements of the desired application. However, the current research in the battery modeling and control community has focused mainly on lithium-ion batteries at the single cell-level in an isolated environment where the cell-to-cell interconnections and pack heterogeneities are not accounted for. Merely applying the existing knowledge of a single cell to such a large-scale battery pack assumes "modularity", wherein modularity is defined as the ability to extrapolate the behavior of a battery pack from a single cell. Recent experimental studies presented in the literature show evidence that the assumption of modularity, in terms of electrical, thermal, and aging behavior, does not hold true. The literature further highlights that a pack reaches its end-of-life sooner than a single cell, the thermal and aging gradient behavior of the pack is non-uniform and aggravated in comparison to a single cell, and the performance of a pack is adversely affected due to cell-to-cell heterogeneities induced by manufacturing variances. As a result, the design of Battery Management Systems for a pack must take these non-uniformities or peculiarities into account while developing algorithms for modeling, estimation, and control. To that end, this dissertation adopts a bottom-up approach by developing modeling and estimation tools at the cell-level, and then extending it to the module/pack-level for efficient control. An experimentally validated electrochemical model at the single cell-level forms the basis to develop a model-based observer to estimate "non-measurable" internal battery health variables. The cell-level electrochemical model is extended to a high-fidelity module-level model by incorporating the thermal, electrical, and aging interactions between cells to analytically and quantitatively understand the effect of heterogeneities and gradients on the behavior of battery modules. Subsequently, the model is utilized to develop an optimization-based control strategy to minimize the non-uniformities, thereby improving the safety and lifespan of battery modules. The outcome of this research will open up opportunities to advance knowledge of cell- and module-level dynamics, accurate real-time prognostic algorithms, and health-conscious module-level control. This research is primarily targeted towards the transportation sector (electric vehicles), but it can be extended to stationary grid storage applications, and more importantly used to determine the feasibility of using end-of-life lithium-ion cells in "second-use" applications

Keywords: Energy Resources Engineering.
Advisor: Onori Simona
Durlofsky Louis
Kovscek Anthony R. (Anthony Robert)
Holomorphic curve invariants of open contact manifolds

Contact homology is a well-established tool for studying contact manifolds. It was originally defined for closed manifolds, and variants have been produced for a certain class of open manifolds, but these depend on certain extra structure at infinity, and hence do not provide an invariant for the manifold itself. In this thesis, we introduce a variant of contact homology which is defined for certain ("convex") open manifolds. This provides the first tool for distinguishing tight contact structures on euclidean space and, as an application, we prove the existence of exotic tight contact structures on (4m+1)-dimensional euclidean space for every m> 0. In addition, we give a preliminary version of a general framework for defining algebraic invariants based on holomorphic curves

Keywords: Mathematics.
Advisor: Eliashberg Y.
Ionel Eleny
Manolescu Ciprian
Homeworking in Italy during the COVID-19 Pandemic: An Analysis of Preliminary European Labour Force Survey Results

This paper explores how the Italian homeworking landscape transformed during the 2020 pandemic in relation to the broader European context. After providing an overview of the history of homeworking in pre-pandemic Italy and Europe, I analyze 2020 homeworking data from national statistics institutes of individual countries collected as part of the European Union Labour Force Survey. I frame my study of homeworking within the three-element scheme proposed by Lutz Gschwind and Oscar Vargas in Telework in the 21st Century. While fluctuations in 2020 homeworking trends in Italy can be attributed to the unstable nature of the pandemic, I argue that the country’s volatile and short-term adoption of flexible working arrangements stems from barriers posed by employment regulation, working culture, and information and communication technology (ICT) infrastructure. My analysis takes into consideration the historical territorial divides on the Italian peninsula, as well as the “teleworkability” of–or the feasibility of implementing homeworking arrangements in–different economic sectors.

Keywords:  Department of Communication
italy
homeworking
smart working
internet
pandemic
covid-19
Thesis
Advisor: Jay Hamilton
Homo musicus : he musical instrument as a model of life and mind in early modern Europe

My dissertation examines the ways in which early modern physicians and natural philosophers employed musical metaphors and models in order to conceptualize human vital function and cognition. Almost every early modern investigation of the body, whether medical, physiological, or psychological, had to confront in some way the central tension between the faculties of the soul and the activities of the body. In music, musical instruments, and musical ideas, philosophers from across western Europe found conceptual tools with which they attempted to bridge this gap, by connecting the physical and even mechanical processes of the body with the more abstract phenomena of thought, cognition, health, and pleasure. Musical instruments were material and mechanical, and thus could describe the basic physical attributes of human bodies. But they were also affective, emotional, rational - in both their symbolism and their operation. By the middle of the 18th century, what I have dubbed homo musicus, or the musical human being, had become one of the most wide-spread metaphors of the human body, and indeed human experience. My dissertation thus tells an alternative history of mechanism, one which did not reject, but rather embraced, the soul and its faculties. Homo musicus was both an elaboration and a complication of cartesian dualism: it was a mechanism with soul

Keywords: History.
Advisor: Riskin Jessica
Baker Keith Michael
Findlen Paula
Hadlock Heather
How CS 184, Bridging Policy & Tech Through Design, Came to Be: Luck, Persistence + Strong marketing

Constanza Hasselmann’s capstone project detailed the inception, implementation, and success of the “CS 184- Bridging Policy & Technology through Design” course at Stanford University. Originally starting out as an independent study course inspired by her interest in public technology and design, Constanza notes how this quickly pivoted from an independent study structure to a student lab titled Public Interest Technology (PIT) @ Stanford. Through adamant community and academic support, the PIT Lab fully launched CS 184 in Spring 2020. Partnering up with various organizations, project mentors, and faculty, CS 184 served as a project-based course meant to engage with the emerging topic of public interest technology and serve as a space where students from different academic backgrounds worked with external partner organizations at the nexus of digital technology and public policy. The goal of the class and the Lab is to ultimately reach new student audiences, engage with additional faculty and offer a project incubator. CS 184 remains an active Stanford course that aims to create an environment for a vibrant and interdisciplinary community of students, faculty, and external partners.

Keywords: Design and technology
Public policy
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Report
Thesis