VictorJuiz/thesis huggingface dataset:
Thinking Otherwise

My dissertation, Thinking Otherwise, is a triptychal essay that pursues the consequences of a common feature of two very different artists, Agnes Martin and Alice Notley, who each renounce the products of reason—concepts, ideas, knowledge—for the sake of thinking. Both choose the theory of evolution to exemplify their refusal to believe in ideas. Evolution is forsworn because of its fitness as an emblem of reason—a paragon of reason’s fruits that stands as explanation and cause of the way things are the way they are. Upon release from the class or hold of mental objects whose function the theory of evolution exemplifies, each artist performs a visionary perceptive mode without which her art would be impossible, and which she avers is transmissible to the audience./nChapter one reads against the ubiquitous trend in Martin scholarship that divides the visual from the verbal, dissociating Martin’s “visions”—the way her paintings occurred to her entire, “the size of a postage stamp”—from her “voices,” auditory hallucinations symptomatic of Martin’s schizophrenia. Critics insist on this division between Martin’s visions and her voices to preserve the integrity of the paintings, leaving them uncompromised by Martin’s mental illness. I argue that consigning the voices to Martin’s pathology undermines her thinking about thinking, an activity that isn’t the same as the wordless activity her visions provide. To take seriously the mental activity Martin wants her work to initiate, I turn to two psychoanalysts working at the time Martin was diagnosed: Marion Milner—for her work on the boundary between creativity and madness in both her clinical studies and her auto-criticism—and W.R. Bion, for his understanding of hallucinosis and his theory of thinking as an apparatus that develops in response to thoughts./nChapter two maps the trajectory by which Alice Notley’s “poetics of disobedience” authorizes not only her remaking of poetic genres, but also the launching of scientistic claims which culminate in her insistence that poetry determines speciation and is a tool with which we can measure the laws and nature of the universe. I show how Notley’s work exceeds the limits of feminist epistemology, and I consider her work in connection with the decolonial work of Édouard Glissant and Sylvia Wynter. The imbrication of Notley’s formal imagination and a counterpoetics (Glissant’s term) leads to a counterhumanism (Wynter’s term), which rivals secular humanism—deposing Darwin’s the Descent of Man with Notley’s The Descent of Alette./nThe final chapter reads Martin’s paintings and Notley’s poems to discover a synthetic argument for measure’s capacity to recondition both the materials and process of thinking. Inhabiting the nexus of creative and academic writing, this chapter is a lyric essay that is both a narrative of my own responses to the objects of study and an exploratory confession of my methodology and my own filiative poetics.

Advisor: Hejinian, Lyn
Statistical Methods and Analyses in Computational Genomics: Explorations of Eukaryotic Transcription

The introduction of next-generation, or high-throughput, sequencing techniques has fundamentally altered our perception of the genome and transcriptome by permitting the simultaneous study of tens of thousands of distinct transcripts. In recent years, the popularity of next-generation sequencing has risen due to reductions in costs and the steady accumulation of novel genetic and genomic discoveries which would have proven difficult to uncover with older approaches. The continued proliferation of these techniques both in number and frequency of use has resulted in unique data types and experimental structures which require analysis and frequently methodological development./nIn this dissertation, I explore eukaryotic transcription from multiple perspectives by applying both classical and novel statistical methods to data generated by different next-generation sequencing protocols. I begin by constructing spatial nascent transcription profiles based on various RNA Polymerase II footprinting procedures to demonstrate the profound deleterious effect of RNA transcript decay factor deletion on mRNA production in yeast, bolsterering and expanding upon prior evidence of the inextricable link between RNA synthesis and decay. My focus then shifts to the development and application of a tensor-based method to RNA-seq data of both the bulk and single-cell varieties. This method is intended for use with data produced in experiments with increasingly-common specially-structured designs in which samples share tissues and/or individuals, and I show that it more robustly and powerfully characterizes the transcriptome via simulation and application to human bulk gene expression measurements. I conclude by employing this method jointly with traditional approaches to investigate the tissue-specific effects on gene expression as measured in murine single-cell RNA-seq and discuss the merits of tensor methods in such a setting.

Advisor: Song, Yun S
The Role of Commercial Buildings in China’s Renewable Electricity Future: Forecasting Load and Demand Response Potential

As renewable energy continues to play a larger role in China's electricity grid, obstacles for increasing grid flexibility and reliability need to be addressed. Improved grid flexibility could be achieved by institutional changes, adding flexible supply, improving the reliability and efficiency of the transmission sector, or enhancing demand side flexibility. This dissertation focuses on the potential of demand response (DR) to provide flexibility in times of extreme need in a future with large penetration of renewables. It develops two different DR models that can be used to estimate DR impact for commercial buildings at the building level and at the national level, respectively./nUsing a national level model, this dissertation characterizes the impact of DR events across the commercial sector to provide flexibility across four netload cases in 2030: hours of high and low netload, and hours of high down and up ramping. I describe the methodology to actuate DR by managing the buildings' HVAC system and explain the expected impact statistics. I find that for a 2030 basecase netload scenario with installed renewable capacity of about 1,200 GW, DR from the commercial sector can decrease peak netload between 7 and 12 GW, saving the system between 7 and 12 billion dollars in deferred capacity expansion. Extending demand response to the highest 1% of netload hours in the year, an average of 3 to 4 GW decrease in needed capacity during those hours is possible. This decrease is equivalent to a 276 to 377 GWh reduction in demand, and additional operation savings of between 21 to 28 million dollars. Calculating the cost and benefits of increasing netload at the lowest hours requires further analysis on the potential generation portfolio in 2030 that is likely to benefit from an increased operational baseload. In addition, DR can provide flexibility to alleviate extreme ramping down and up throughout the year. Actuating DR on the highest 1% ramping hours of the year can provide, on average, between 6 to 11 GW per hour and -14 to -27 GW per hour for the extreme down and up ramping hours of the year.

Advisor: Callaway, Duncan S
Cancer-associated mRNAs regulated by the Helix-Loop-Helix motif of human EIF3A

Improper regulation of translation initiation, a vital check-point of protein synthesis in the cell, has been linked to a number of cancers. Overexpression of protein subunits of eukaryotic translation initiation factor 3 (eIF3) has been associated with increased translation of mRNAs involved in cell proliferation. In addition to playing a major role in general translation initiation by serving as a scaffold for the assembly of translation initiation complexes, eIF3 regulates translation of specific cellular mRNAs and viral RNAs. Mutations in the N-terminal Helix-Loop-Helix (HLH) RNA-binding motif of the EIF3A subunit in eIF3 interfere with Hepatitis C Virus Internal Ribosome Entry Site (IRES) mediated translation initiation in vitro. Here we show that the EIF3A HLH motif controls translation of a small set of cellular transcripts enriched in oncogenic mRNAs, including MYC. We also demonstrate that the HLH motif of EIF3A acts specifically on the 5’-UTR of MYC mRNA and modulates the function of EIF4A1 on select transcripts during translation initiation. In Ramos lymphoma cell lines, which are dependent on MYC overexpression, mutations in the HLH motif greatly reduce MYC expression, impede proliferation and sensitize cells to anti-cancer compounds. These results reveal the potential of the EIF3A HLH motif in eIF3 as a promising chemotherapeutic target.

Advisor: Cate, Jamie H.D.
Mechanisms and applications of DNA-targeting CRISPR interference proteins

The ongoing battle between bacteria and phage has influenced the evolution of complex defense pathways. In bacteria and archaea, clustered regularly interspaced short palindromic repeats (CRISPR) and their CRISPR-associated (Cas) proteins form the basis for RNA-guided adaptive immunity and antiviral defense. The most streamlined CRISPR systems contain the class 2 interference cas genes, which encode a single polypeptide capable of executing all the functions of target search and destruction. This work describes the mechanisms of target recognition and cutting by the class 2 DNA-targeting nucleases, Cas9 and Cas12a (formerly Cpf1), with an emphasis on their biotechnological applications./nThe ability to program Cas9 or Cas12a to target and cut any DNA sequence by simply changing its guide RNA sequence has revolutionized genome editing. Although Cas9 and Cas12a are both RNA-guided DNA endonucleases, these proteins have little sequence or structural similarity, and several functional differences highlight the evolutionary diversification of CRISPR interference proteins. In particular, Cas9 contains two nuclease domains called HNH and RuvC that cut each strand of the dsDNA substrate to generate a blunt end. The finding that Cas9 undergoes multiple conformational states in the steps leading up to DNA cleavage underscored the importance of conformational control. Using biochemical and single-molecule approaches, we describe a conformational checkpoint that governs activation of Cas9 and uncover a region within the protein responsible for sensing target mismatches that can be further engineered to enhance cleavage fidelity./nUnlike Cas9, Cas12a cuts dsDNA with a single RuvC nuclease domain, leaving a staggered end. We find that the RuvC is active only on single-stranded DNA (ssDNA), highlighting the requirement for dsDNA unwinding to facilitate cutting of both strands of the dsDNA substrate. Furthermore, we reveal that once Cas12a binds to a complementary ss- or dsDNA sequence, the RuvC nuclease non-specifically degrades any ssDNA molecule in trans. In the presence of a reporter molecule, this trans-cleavage activity by Cas12a is repurposed as a versatile DNA detection tool and has attomolar sensitivity when coupled with isothermal amplification. Together, the mechanistic framework of Cas9 and Cas12a provides a foundation for engineering fidelity and developing novel DNA detection technologies.

Advisor: Doudna, Jennifer A
On Renormalized Volume

Renormalized volume $\VR$ is a quantity that gives a notion of volume for hyperbolic manifolds having infinite volume under the classical definition. Its study for convex co-compact hyperbolic 3-manifolds can be found in \cite{KrasnovSchlenker}, while the geometrically finite case including rank 1-cusps was developed in \cite{MoroianuGuillarmouRochon}. In this dissertation we will answer what value is the infimum of the renormalized volume for a given geometrically finite hyperbolic manifold with incompressible boundary, and how a sequence converging to the infimum behaves. Partial results to this question were given in the acylindrical case by the author in \cite{Vargas16} and in the convex co-compact case by \cite{Vargas17} and \cite{BBB17} independently (\cite{BBB17} studied the gradient flow of the renormalized volume). In addition to finding the infimum value, we give the notion of additive geometric convergence in order to describe any sequence converging to the infimum. The study of local minima on the acylindrical case was done in parallel by \cite{Moroianu} and \cite{Vargas15}, which \cite{Vargas16} proves to be the infimum.

Advisor: Agol, Ian
Data Hallucination, Falsification and Validation using Generative Models and Formal Methods

The increasing pervasiveness and fast-paced development of deep learning (DL) systems with human-like perception, agency and creativity has brought concern related to information reliability: the generative models that have surprised and confused humans with their high quality media hallucinations can be used to fool other computer systems and humans to believe that the generated media is real. In addition to developing strategies to increase the quality of the data produced with generative models, specially generative adversarial networks (GANs), our research community has been exploring mechanisms to better understand and control the data they generate./nIn the context of data falsification, formal methods (FM) and formal specifications (FS) can be used to prevent adversarial attacks by verifying that some potentially adversarial data follows the specifications of the real data. Formal methods and formal specifications can also be used to guide the output of a generator such that, as much as possible, the generated data fulfills the specifications of the real data. Although formal methods have been largely and sucessfuly used in the field of software and hardware engineering, their interaction with Artificial Neural Networks (ANNs) poses many challenges that are yet to be solved./nIn this thesis, we address challenges related to hallucination, falsification and/nvalidation of data using generative models and formal methods. We start by focusing on artistic applications related to music by developing an automata-based system for machine improvisation with formal specifications. We briefly describe the Control Improvisation framework and describe its application to machine improvisation with formal specifications. We propose data abstractions derived from symbolic music data and describe strategies for mining specifications from them. We then use the mined specification to summarize a musical style and guide the improvisation of a generative model./nNext, we focus on security applications in speech synthesis and investigate the efficiency of generative models such as WaveNet, SampleRNN and our own GAN model in performing spoofing attacks to fool a text-independent speaker recognition system. Inspired by universal background models (UBMs) in speech, we propose a modification to the Wasserstein GAN objective function such that data from multiple speakers can be used to generate data from a single speakers, increasing the efficiency of our spoofing attacks./nLast, in the hope of preventing adversarial attacks produced with data synthesized by generative models, specially GANs, we look at the properties of synthesized samples hoping to find traces of the data generation process that can be used to identify the data as adversarial. We empirically show that the data produced with these generative models do not follow the specifications of the real data and that they have universal properties, byproducts from the models and the algorithms used to train them, that can be used to identify the source of the data.

Advisor: Campion, Edmund
Seshia, Sanjit A.
Rapid ASIC Design for Digital Signal Processors

Application-specific integrated circuit (ASIC) signal processors are necessary to achieve the high performance and low power requirements of modern applications, but long development times are one hurdle contributing to their declining adoption. A significant percentage of their development time goes into the design and verification of the architecture, with the remainder consumed by back-end ASIC flow work and chip testing. Agile hardware principles, borrowed from a similar successful software approach and previously applied to general-purpose processors, offer a promising solution to continuing the development of signal processing systems on a chip (SoCs)./nThis work presents a digital signal processing SoC design framework that, when coupled with agile design principles, supports rapid prototyping and designing of ASICs for signal processing applications. First, applications and existing ASIC solutions are explored and analyzed in Chapter 2 to glean useful properties and trends. From this, Chapter 3 proposes a model for a generic signal processing SoC is developed. Next, a new Chisel generator design framework is presented in Chapter 4. Chisel is a hardware construction language written as a DSL in Scala, allowing for high-level and functional programming use when designing hardware. This framework couples a general-purpose processor with a signal processing accelerator, and much of the library code for connectivity, memory mapping, and programming is made available. This framework, when coupled with an agile design process, supports rapid development of ASICs. The accelerator performs streaming signal processing to offload high-throughput computational kernels from the CPU. As processing elements for the desired application are produced, processing moves from the CPU to the accelerator. Low-rate processing tasks are computed on the CPU, meaning tape-out occurs on time and produces a working chip able to perform the entire application./nThe methodology and proposed agile design process were validated on two separate chips in Chapters 5 and 6, spanning two applications and two process nodes. The ASIC spectrometer (Splash2), for which the RTL was designed in eight weeks by one person, demonstrates the power of Chisel to rapidly construct processing element generators. These generators were then improved and the parameters adjusted as physical design and timeline constraints imposed new restrictions. The radar receive processor design fleshed out the generator framework details. A significantly larger design, this chip required about 300 engineering-weeks of work over 9 months, equivalent to a team of 8 engineers working full time. About 30% of that time was spent designing the framework and reusable processing elements. This represents a 56% reduction in development time compared to the estimated 14.4 months from standard practices (excluding time for framework design, fabrication, and testing). Both efforts produced working chips competitive against state-of-the-art custom ASICs in terms of performance, power, and capabilities.

Advisor: Nikolic, Borivoje
Tight-Binding Hamiltonians for Modeling Light Harvesting Systems

This thesis is concerned with tractable methods for modeling the optical and electronic properties of photosynthetic light harvesting complexes. We begin by investigating the validity of the commonly used Frenkel Exciton Hamiltonian, and find that it is inaccurate at the intermolecular distances commonly encountered in photosynthetic systems. We introduce semi-empirical tight-binding Hamiltonians and dynamics models that are better able to simulate the electronic properties of these chromophores at the proper distances and orientations. These models are validated by comparisons of the predictions to experimental results.

Advisor: Whaley, Katharine B
Extending the Strange Metal Phenomenology of High-Tc Superconductors With High Magnetic Fields

Probably the most significant challenge facing condensed matter physics today is to understand metallic behavior that falls outside the independent electron approximation. The number of metallic systems for which this approximation fails is small but these systems are of exceptional interest because they often display exciting phenomena like high-Tc superconductivity. Additionally, these systems exhibit a common pattern of anomalies, giving us hope that there is a universal physical picture by which we can understand them. Two of these anomalies are in the charge transport sector: a T-linear resistivity and a strongly T-dependent Hall effect. This dissertation seeks to extend this pattern by studying the charge transport properties of the iron-pnicited superconductor BaFe2(As1-xPx)2 at very high magnetic fields. The data obtained in these experiments reveal significant magnetic analogues of both the aforementioned anomalous temperature dependencies, and confirm that the dynamics in this system conform to two of the predictions of quantum critical theory: scale invariance and the existence of a uniform fan-like region around the quantum anti-ferromagnetic quantum phase transition. These findings support the hypothesis that quantum criticality is at the root of these particular anomalies, while simultaneously challenging the naive version of the theory and creating new opportunities for investigating the microscopic nature of the strongly correlated state.

Advisor: Analytis, James G
Patient-Specific Vascular Model Construction and Modification for Blood Flow Simulation and Analysis

Cardiovascular disease has remained the leading cause of death worldwide for the past 15 years, and organizations such as the American Heart Association (AHA) and the National Institute for Health (NIH) spend hundreds of millions of U.S. dollars annually to investigate heart disease and stroke. Local characteristics of blood flow in the heart and the rest of the cardiovascular system provide important information in both understanding progression of and diagnosis of cardiovascular diseases. Unfortunately, current medical imaging techniques cannot provide data with high enough temporal and spatial resolution to extract meaning- ful and accurate research conclusions. Thus, many researchers investigate cardiovascular diseases using a patient-specific blood flow simulation framework. In this framework, a pa- tient’s geometry is constructed on a computer from medical image data, and a numerical simulation, such as finite element analysis (FEA), is used to provide very high detail infor- mation. Typically, the most time consuming step and also one of the most crucial steps in this pipeline is constructing the geometry of interest from the image data. In addition, many of the tools to create an image-based model are commercial, not readily available, or dispersed amongst a variety of software packages. This dissertation discusses two main avenues of research: (1) the development of unique, customized, and open-source tools for vascular model construction and meshing for FEA and (2) the investigation into and the creation of novel model construction methods for an alternative of FEA called isogeometric analysis (IGA). All of the tools developed were implemented using open-source tools such as the Visualization Toolkit (VTK) and have been implemented into the software framework SimVascular. In addition, many of the methods developed were tested for applicability and robustness on the open-source vascular model repository, which is a large database of over 100 vascular models provided by the Open Source Medical Software Corporation (OSMSC).

Advisor: Shadden, Shawn C.