VictorJuiz/thesis huggingface dataset:
CRISPR adaptation to RNA [electronic resource]

Cells use a variety of mechanisms to mitigate the threat of genetic invasions and to prevent the propagation of parasitic information. A family of prokaryotic adaptive immune systems associated with Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) arrays has been shown to protect cell populations from "selfish DNA" such as plasmids and viruses. CRISPR-mediated immunity begins with an "adaptation" phase in which the host acquires short sequence segments (spacers) from the genome of the infectious agent. The spacers are stored within CRISPR arrays in the host genome and serve as heritable molecular memories of the invader. This information is used by CRISPR-associated (Cas) nucleases in the subsequent "interference" phase to identify and disrupt future infections by the same invader. Most CRISPR-Cas systems can be phylogenetically classified into three major types. Type I and Type II systems acquire spacers from (and subsequently interfere with) DNA sequences, while Type III systems additionally target RNA sequences for degradation. In the absence of any known mechanisms for CRISPR adaptation to RNA, this was believed to be an auxiliary mode of attack against DNA parasites. We discovered that some Type III systems can acquire spacers directly from RNA, suggesting that these CRISPR-Cas systems could learn to fend off RNA parasites as well. This system represents, to our knowledge, the first identified cellular process in which sequence information is actively acquired from RNA and deposited (as DNA) into the genome at the behest of the host cell. Moreover, direct acquisition of RNA spacers into CRISPR arrays represents a novel and uniquely sequence-agnostic mode among the handful of known mechanisms for reverse flow of genetic information from RNA into DNA genomes, including reverse transcription machineries associated with retroviruses, telomeres, retrotransposons, mobile group II introns, and phage diversity generating elements.

Keywords: Chemical and Systems Biology.
Advisor: Fire Andrew Zachary primary advisor. Thesis advisor
Jarosz Daniel advisor. Thesis advisor
Kirkegaard Karla advisor. Thesis advisor
Meyer Tobias advisor. Thesis advisor
Critical approaches to the materiality of source code [electronic resource] : between text and machine

This dissertation is concerned with uncovering and describing the ways that source code written in computer programming languages works as expressive language rather than simply as a tool to give instructions to machines. By considering the relationship between word and action in a diverse range of digital contexts, I show how artifacts generally considered in the domain of computer science can be taken up within the humanities. Chapter 0 discusses the relationship between digital computing and earlier analog computing, highlighting how source code abstracts away from the digital in ways isomorphic to how digitality itself requires abstracting away from its analog substrate. This chapter also contains an extensive review of extant media-theoretical work on source code. Chapter 1 considers the development of the English-like business programming language COBOL, with an eye toward understanding the language's syntax as a canny rhetorical move to gain the trust of executives skeptical of computerizing business processes. Chapter 2 considers more recent attempts to change the relationship between the English language and computing. Chapter 3 consists of a close read of computer scientist Ken Thompson's "Reflections on Trusting Trust, " wherein Thompson describes a methodology of exploiting compilers to make undetectable and potentially hostile changes to software. Chapter 4 considers science fiction writer Ted Chiang's "Seventy-Two Letters, " a novella that satirizes the ideology of code as action through placing it in a radically defamiliarized context, and thereby points out the dangers of understanding code as the source of action. Through analyzing these artifacts, I develop an argument for understanding the relationship between text and machines established via source code as being a political concern, rather than merely a technical one, and show how humanists can use critical theory to contribute to computing, through showing how the material textuality of source code marks works in digital media.

Advisor: Lunsford Andrea A.
Mullaney Thomas S. (Thomas Shawn) primary advisor. Thesis advisor
Turner Fred advisor. Thesis advisor
Cryptographic multilinear maps and their applications [electronic resource]

Cryptographic multilinear maps are a powerful tool that allows one to perform certain arithmetic operations on encoded values without being able to decode them. The study of multilinear maps was initiated by Boneh and Silverberg in 2003, but it was not until 2013, with the breakthrough works of Garg, Gentry, and Halevi and of Coron, Lepoint, and Tibouchi, that we knew of any candidate constructions. In this thesis, we show that multilinear maps can be used to give new constructions of a number of important cryptographic primitives. We begin with program obfuscation, an extremely powerful primitive that allows one to "scramble" the code of an arbitrary program, so that an adversary cannot learn anything about how it works except by running it. Unlike previous approaches, our construction operates directly on straight-line programs, rather than converting them to matrix branching programs. Because of this, our construction requires only poly(d, s) multilinear map operations for a circuit of depth d and size s---as opposed to previous constructions, for which the number of operations is exponential in d. We also use multilinear maps to construct order-revealing encryption (ORE) with best-possible security. ORE enables one to learn which of any pair of ciphertexts is greater, while leaking no other information. Prior to this work, the best known construction relied on general-purpose two-input functional encryption, which is not currently implementable due to the size of the parameters required. In this work, on the other hand, to compare two 16-bit encrypted values we only need a degree-9 multilinear map. We conclude with a discussion of the cryptanalysis of multilinear maps. In 2014, Cheon, Han, Lee, Ryu, and Stehle presented an attack on the multilinear map of Coron, Lepoint, and Tibouchi (CLT). They show that given many low-level encodings of zero, the CLT multilinear map can be completely broken, recovering the secret factorization of the CLT modulus. The attack is a generalization of the "zeroizing" attack of Garg, Gentry, and Halevi. In this thesis, we strengthen the attack of Cheon et al., by showing that CLT can be broken under some circumstances even without low-level encodings of zero. These new attacks, along with the other contributions of this thesis, further underscore the central importance of developing new kinds of multilinear maps.

Advisor: Boneh Dan
Valiant Gregory advisor. Thesis advisor
Williams Ryan (Richard Ryan)
Cyber risk analysis for a smart grid [electronic resource] : how smart is smart enough?

As electric sector stakeholders make the decision to upgrade traditional power grid architectures by incorporating smart grid technologies and new intelligent components, the benefits of added connectivity must be weighed against the risk of increased exposure to cyberattacks. Therefore, decision makers must ask: how smart is smart enough? This dissertation presents a probabilistic risk analysis (PRA) framework to this problem, involving systems analysis, stochastic modeling, economic analysis, and decision analysis to quantify the overall benefit and risk facing the network and ultimately help decision makers formally assess tradeoffs and set priorities given limited resources. Central to this approach is a new Bayes-adaptive network security model based on a reformulation of the classic "multi-armed bandits" problem, where instead of projects with uncertain probabilities of success, a network defender faces network nodes that can be attacked at uncertain Poisson-distributed rates. This new technique, which by similarity we call "multi-node bandits, " takes a dynamic approach to cybersecurity investment, exploring how network defenders can optimally allocate cyber defense teams among nodes in their network. In effect, this strategy involves taking teams that traditionally respond to cyber breaches after they occur, and instead employing them in a proactive manner for defensive and information gathering purposes. We apply this model to a case study of an electric utility considering the degree to which to integrate demand response technology into their smart grid network, jointly identifying both the optimal level of connectivity and the optimal strategy for the sequential allocation of cybersecurity resources. Additional analytical and empirical results demonstrate the extension of the model to handling a range of practical network security applications, including sensitivity analysis to organization-specific security factors, settings with dynamic or dependent rates of attack, or handling defense teams as imperfect detectors of cyberattacks.

Keywords: Management Science and Engineering.
Advisor: Paté-Cornell M. Elisabeth (Marie Elisabeth) primary advisor. Thesis advisor
Bambos Nicholas advisor. Thesis advisor
Nesbitt Dale advisor. Thesis advisor
Dam them All: On the Failure of Dams and Dam Building Frameworks

My thesis research concerns the relationship between resource scarcity and conflict, with a particular focus on South Africa and Lesotho's international water agreement, the Lesotho Highlands Water Project. The LHWP, as with many large dam projects, has been fraught with problems and the politics surrounding it have been contentious. My research details and analyzes the various factors that have hampered the LHWP, with particular emphasis on the role of private interests, financial incentives, poor infrastructure planning and water management. My findings ultimately argue that it is the framework through which we consider and approve dam projects that is flawed, and leads to pervasive flaws in their commissioning and construction. The known impacts of global climate change, including global warming and the increasing unpredictability of temperature and precipitation, both contribute to and compound these factors. As a result, the political repercussions of large dam projects like the LHWP will become increasingly salient and demand political responses.

Keywords: thesis
dams
dam
water
resource conflict
climate change
global warming
lesotho
south africa
International Relations
IR
History
Cavallo
Thesis
Advisor: Samoff Joel
Data sampling and constrained reconstruction for high-dimensional MRI [electronic resource]

Magnetic resonance imaging (MRI) is a powerful and flexible modality for medical imaging. Data samples in MRI are acquired in the spatial frequency domain (k-space) through a time-consuming and inherently sequential process, and consequently, the scan time is proportional to the number of acquired samples. Many clinical MRI applications require data acquisition with additional dimensions, such as channels in a phased-array receive coil in parallel MRI, time in dynamic contrast-enhanced (DCE) MRI, or multiple slices excited in imaging near metallic implants, which introduce additional acquisition requirements. Modern higher-dimensional MRI applications have potential to overcome scan time limitations with constrained image reconstruction methods that exploit dependencies between auxiliary dimensions. Two major issues are that the required inversions can be ill-conditioned depending on k-space sampling patterns and may require explicit knowledge of inter-dimensional dependencies that is hard to obtain in practice. Thus, many applications compromise robustness to motion, temporal resolution, or spatial resolution. This thesis introduces new computational methods for k-space sampling and constrained reconstruction that push the current limits of high-dimensional MRI. To address the sampling problem, a general relationship between k-space sampling and problem conditioning is described using differential domain analysis, a tool that has roots in computer graphics. The theory is then used for on-the-fly design of adaptive k-space sampling patterns. Informed by new insights into k-space sampling, new methods for constrained reconstruction in DCE-MRI and MRI near metallic implants are introduced and evaluated in clinical imaging. A new k-space sampling trajectory is introduced in a clinical DCE-MRI protocol. This approach enables both conventional unconstrained reconstruction at lower temporal resolution or compressed sensing reconstruction at a retrospectively adjustable higher temporal resolution, providing robustness to breath hold loss or rapid contrast enhancement. Initial assessment of the technique, used in imaging over 3000 patients at Stanford, demonstrates its benefit. A similar approach is proposed to enable rapid imaging of patients with metallic implants by exploiting dependencies between excited slices. The reconstruction of on-resonance and off-resonance signals is formulated as robust principal component analysis, which exploits new sources of redundancy not describable in existing compressed sensing methods. Clinical evaluation in a small pilot study shows the feasibility of imaging near metal three-fold faster than the standard technique.

Keywords: Electrical Engineering.
Advisor: Hargreaves Brian Andrew primary advisor. Thesis advisor
Pauly John (John M.) advisor. Thesis advisor
Vasanawala Shreyas
Data-driven methodologies for efficient materials calculations [electronic resource]

As the world of electronic simulations progresses from a world where we can perform tens to thousands to millions of calculations, the way we perform science must evolve in order to most efficiently use the increasingly vast amounts of data. This thesis aims to contribute to laying the groundwork for the necessary paradigm shift. One clear aspect that must tackled in such a shift is the implementation of additional automation, automating tasks ranging from the set-up and performance of calculations to the analysis of the ensuing results. This thesis consists of three projects tackling this problem, merging databases of electronic structure calculation with machine learning and model fitting techniques. These projects are i) A procedure to algorithmically determine optimal convergence parameters, for use in varied large-scale studies, ii) Frameworks for utilizing benchmark and reference data to create post-calculation schemes which are cheap, robust, and universal, and iii) Development and benchmarking of improvements to the Drag method for transition state determination, as well as first attempts at using data to accelerate more expensive NEB calculations.

Keywords: Chemistry.
Advisor: Nørskov Jens K.
Markland Thomas E.
Martinez Todd J. (Todd Joseph)
Data-driven operations and incentives in healthcare [electronic resource]

The United States has the highest per-capita healthcare spending in the world, surpassing annual national expenditures of $2.5 trillion a year. Yet, there are serious concerns about the quality of care, including medical errors, as well as the underuse and overuse of healthcare resources. This thesis focuses on improving patient outcomes through (1) optimizing hospital operations using machine learning and statistical decision-making tools based on increasingly available data, and (2) the design of healthcare policy that better aligns provider incentives with the goal of high-quality and cost-effective care. Chapter 1 proposes new algorithms for personalized medical decision-making that can efficiently leverage high-dimensional patient data. Chapter 2 empirically assesses pitfalls of current pay-for-performance healthcare policies. Chapter 3 studies the game-theoretic design of pay-for-performance policies that optimize hospitals' financial incentives in the presence of institutional constraints.

Keywords: Electrical Engineering.
Advisor: Bayati Mohsen primary advisor. Thesis advisor
Johari Ramesh
Zenios Stefanos A. advisor. Thesis advisor
Data-sparse algorithms for structured matrices [electronic resource]

In the first part of the dissertation, we present a method for updating certain hierarchical factorizations for solving linear integral equations with elliptic kernels. In particular, given a factorization corresponding to some initial geometry or material parameters, we can locally perturb the geometry or coefficients and update the initial factorization to reflect this change with asymptotic complexity that is polylogarithmic in the total number of unknowns and linear in the number of perturbed unknowns. In the second part, we consider the application of hierarchical factorizations to the problem of spatial Gaussian process maximum likelihood estimation, i.e., parameter fitting for kriging. We present a framework for scattered (quasi-)two-dimensional observations using skeletonization factorizations to quickly evaluate the Gaussian process log-likelihood and its gradient, which we use in the context of black-box numerical optimization for parameter fitting of low-dimensional Gaussian processes. Finally, we introduce the strong recursive skeletonization factorization (RS-S), a new approximate matrix factorization based on recursive skeletonization for solving discretizations of linear integral equations associated with elliptic partial differential equations in two and three dimensions (and other matrices with similar hierarchical rank structure). RS-S uses a simple modification of skeletonization, strong skeletonization, which compresses only far-field interactions. We further combine the strong skeletonization procedure with alternating near-field compression to obtain the hybrid recursive skeletonization factorization (RS-WS), a modification of RS-S that exhibits reduced storage cost in many settings.

Advisor: Ying Lexing primary advisor. Thesis advisor
Darve Eric advisor. Thesis advisor
Papanicolaou George advisor. Thesis advisor
De novo mutations in autism implicate the synaptic elimination network

Autism has been shown to have a major genetic risk component; the architecture of documented autism in families has been over and again shown to be passed down for generations. While inherited risk plays an important role in the autistic nature of children, de novo (germline) mutations have also been implicated in autism risk. Here we find that autism de novo variants verified and published in the literature are Bonferroni-significantly enriched in a gene set implicated in synaptic elimination. Additionally, several of the genes in this synaptic elimination set that were enriched in protein-protein interactions (CACNA1C, SHANK2, SYNGAP1, NLGN3, NRXN1, and PTEN) have been previously confirmed as genes that confer risk for the disorder. We then validated that the synaptic elimination gene set is implicated in autism by doing a case-control analysis using the iHART dataset, which currently contains 2308 whole genomes. The results demonstrate that autism-associated de novos are linked to proper synaptic pruning and density, hinting at the etiology of autism and suggesting pathophysiology for downstream correction and treatment.

Keywords: O'Connell, Chloe
Wall, Dennis P.
Autism
synaptic elimination
Bioengineering
School of Engineering
Honors
Pediatrics
Biomedical Data Science
statistics
Thesis
Death on a pedestal [electronic resource] : political martyrdom in late Qing China

This dissertation examines political martyrdom as a symptom of spiritual crisis in China's transformation toward a modern secular society at the turn of the twentieth century. The late Qing period witnessed an unprecedented impulse for self-destruction in assassination activities and civil rights movements, which generated symbolic expressions, intellectual discourses, and popular imaginations. Focusing on these accounts of how martyrdom was interpreted and performed, I argue that the excessive gesture of self-destruction, while serving various political causes, has a unique agenda of reviving the tradition of spiritual cultivation missing from emergent models of secular politics. Tracing late Qing political actors' anxiety regarding the teleological imaginaries of popular sovereignty, I investigate how they drew inspirations from transnational religio-philosophical sources to justify voluntary death, enlarging the scope of life beyond biological existence. The spiritual visions underlying political martyrdom point to alternative ways of constructing subjectivity, self-other relations, and community in Chinese political culture—a subject inherent but overlooked in the global wave of fin-de-siècle disenchantment with the secular order. Ultimately, this dissertation locates the register of Chinese spirituality beyond both established religious traditions and political ideological commitments. It also intervenes in the ongoing study of secularism by offering a new light to define what is secular in modern Chinese society.

Keywords: East Asian Languages and Cultures.
Advisor: Wang Ban
Reichert Jim (James Robert) advisor. Thesis advisor
Zhou Yiqun
Zur Dafna advisor. Thesis advisor
Decision Making under uncertainty in groundwater management

Managing water resources is one of the most pressing environmental chal-
lenge of the coming decades. With a changing climate, growing popula-
tion and change of land use, the stress on water resources has dramati-
cally increased (De Marsily & Abarca-del Rio, 2016). Whereas policies are
emerging on the use of surface water, groundwater is still lacking sustain-
able exploitation strategies. Designing optimal policies for groundwater
extraction is challenging. This is especially due to the uncertainties on the
climate, subsurface and human behavior. This study is focusing on the
importance of data in a decision-making framework to solve groundwater
management problems. Two approaches of groundwater management are
considered. In a first time, the formalism of Markov Decision Processes is
adopted. The problem of a single decision-maker trying to optimize the
groundwater extraction under an uncertain recharge is modeled and solved
using a reinforcement learning algorithm to produce optimal groundwater
usage policies. A Q-Learning algorithm successfully calculate the optimal
policy in that case. In a second time, the focus is directed on human be-
havior and in particular multiple groundwater user interactions. A Game
Theoretical framework is adopted and a two-players is successfully created.
The study is focusing on the sensitivity analysis of the Nash Equilibrium,
in particular on the different hydrogeological parameters that influence it.
A Value of Information problem is tackled, showing the importance of ac-
curate geological data in such a framework.

Keywords:  Department of Geological Sciences
groundwater
uncertainty
Thesis
Advisor: Caers Jef
Demystifying disproportionality [electronic resource] : loose coupling in the special education identification process for English learners

The disproportionate representation of culturally and linguistically diverse students in special education has been identified as a problem by educational researchers and policymakers for decades. Though it is well-established that English learners (ELs) are disproportionately represented in special education, what is less clear is why such disproportionality exists. This study fills a gap in the literature by taking a close look at how ELs are identified as eligible or not for special education. Using participant observation research methods, I followed 16 ELs across two schools through the process of being identified as eligible (or not) for special education. The findings from the study indicate that the process of identifying ELs for special education eligibility took place in fragmented environments. This study suggests that if the civil rights of ELs is to be maintained, significant changes must be made to how practitioners relate to, understand, and are trained to implement policy.

Keywords: Education.
Advisor: Goldenberg Claude
Lit Ira W. primary advisor. Thesis advisor
Hakuta Kenji advisor. Thesis advisor
Jiménez Tomás R. (Tomás Roberto)