VictorJuiz/thesis huggingface dataset:
Quantitative approaches to energy justice: The theory and praxis of examining fair access to reliable electricity

Energy justice has emerged as a rapidly growing academic discipline at the intersection of social justice, energy policy, technologies, and the environment. It considers how both the benefits and burdens of our energy system are distributed across society, particularly as our system transitions to address climate change. This dissertation contributes to this emerging field by investigating issues of electricity access, distribution of energy burdens, and fairness of energy decision-making. By combining technical knowledge of electric power systems, methods from applied data science, and theory from energy justice, the following research examines the implications of inequitable access to reliable electricity around the world. Part I of this dissertation summarizes and reviews the landscape, theory, and methods of energy justice in order to motivate Part II which applies these methods and concepts to three timely energy justice issues./nIn brief:/nCh 1: Introduction and Motivation - Offers an overview of the landscape and evolution of the energy justice field through a systematic review and analysis./nCh 2: Theory - Investigates the philosophical roots of energy justice theory by incorporating broader debates and approaches from political philosophy and other social justice disciplines./nCh 3: Methods - Reviews methods for measuring distributive energy justice via equality and equity, noting their strengths, weaknesses, and opportunities to inform decision-making./nCh 4: Application 1: Solar and gender - Using mixed-methods, this chapter investigates how the distributional benefits of off-grid solar are mediated by gender and class in rural Tanzania thereby investigating inequities in access to the benefit of solar electrification./nCh 5: Application 2: Reliability of energy access - This chapter empirically studies the reliability of household electricity access in Tanzania, Kenya, and India using data from a diverse set of technologies. It thereby investigates inequities in how the burden of unreliability changes across different energy access solutions./nCh 6: Application 3: Rotating outages - This final application chapter quantifies the extent to which a uniquely shareable energy burden of rotating power outages was inequitably distributed across communities in California in August 2020 and investigates the procedures that led to such outcomes./nCh 7: Conclusion

Advisor: Kammen, Daniel M
Noise is the signal: uncovering the kinetic fingerprints of gene regulatory logic

Predicting how interactions between transcription factors and regulatory DNA sequence dictate rates of transcription and, ultimately, drive developmental outcomes remains an open challenge in quantitative biology. Indeed, despite decades of biochemical and genetic studies that have established a reasonably complete "parts list" of the molecular components driving eukaryotic transcription, the field nonetheless lacks a satisfactory understanding of how interactions between these molecular components unfold across space and time to give rise to gene regulatory logic. Recently, technical advancements have begun to provide glimpses into this molecular black box, dramatically improving our ability to trace how molecular pieces move, interact, and assemble. However, if we are to fully realize the immense potential of these exciting new technologies, then our ideas need to catch up with our experiments./nIn this thesis, we argue that quantitative models have a central role to play in synthesizing the ever-increasing array of cutting-edge experimental measurements into a coherent theory for the molecular basis of transcriptional control. To this end, we seek to develop conceptual, theoretical and computational frameworks for dissecting how molecular reactions at individual gene loci give rise to the formation of dynamic patterns of gene expression and facilitate cellular decision-making. Chapters 2 and 3 describe previously published works that combine live imaging, statistical inference, and simple quantitative models to probe how transcription factor proteins regulate the dynamics of transcriptional bursting at target gene loci to give rise to stripes of gene expression early on in fruit fly development. Chapter 4 describes a series of analyses following-up on various results from these works. We also use this chapter to break new ground, however, examining how 2 spot experiments, which track the output of two identical gene loci in each cell, can be used to estimate rates of information transmission at individual gene loci from live imaging data./nIn Chapters 5 and 6, we connect phenomenological models of transcriptional bursting employed in the preceding sections to truly molecular models that seek to understand how key transcriptional behaviors emerge from molecular interactions at the gene locus. Chapter 5 examines a puzzling gap revealed by recent live imaging studies between the rapid timescale (seconds) of transcription factor binding and the slow timescale (minutes to hours) of transcriptional bursts, and proposes two simple theoretical frameworks for bridging this gap. Chapter 6 investigates how the presence of energy-dissipating processes within the eukaryotic transcriptional cycle can open the door to new kinds of gene regulatory logic that increase the rate at which gene loci transmit information. Finally, Chapter 7 describes ongoing work to develop a novel Bayesian framework, burstMCMC, that uses efficient inference techniques to examine how transcription factor proteins regulate transcriptional burst dynamics.

Advisor: Garcia, Hernan G
Centering Equity in Teacher Education: Critical Inquiry Groups in the Preservice Context

Although inequities are rooted across the educational ecosystem, access to high-quality learning represents a salient inroad for improving marginalized students’ educational experiences. However, preparing teachers to enact equity-centered pedagogy—that which renders high-quality learning accessible to all students—remains a multidimensional problem with a dearth of empirically supported solutions. Given special educators’ central role in supporting marginalized students’ learning, ensuring that special educator preparation supports the development of an equity-centered practice is of particular importance./nTherefore, this study examines Teacher Study Groups (TSGs) as a model for building preservice special educators’ practice and, in doing so, examines the underlying processes of preservice learning that result in instructional improvements. My conceptual framework articulated communities of practice theory with empirical research on teacher learning and the conception of critically inclusive pedagogy, which cross-pollinates access- (i.e., Universal Design for Learning) and asset-based (e.g., culturally sustaining pedagogy) paradigms./nTo understand the underlying processes that preservice teachers’ traverse as they build capacity in critically inclusive practices, I studied preservice teachers’ participation in a course-embedded TSG. Through a convergent mixed methods design, I examined 60 preservice teachers’ instructional quality prior to and following participation, along with their knowledge, attitudes, and knowledge calibration, as well as teaching artifacts and reflections shared during weekly sessions. In alignment with a convergent approach, I first analyzed quantitative and qualitative data separately, and I then integrated data through a joint display analysis to generate meta-inferences. Results indicated that participants significantly improved practice and foregrounded salient participatory experiences that hindered and facilitated participants’ professional growth. I conclude with a discussion of implications for equity-centered teacher preparation.

Advisor: Cunningham, Anne E
Functional nanocomposites through the design of filler/matrix interfaces

Nanocomposites use nanomaterials with characteristic lengths in nanometers resulting in a high surface-to-volume ratio. Furthermore, the large filler/matrix interface reduces the interparticle distances lower than the radius of gyrations of polymers, thus changing the polymer chain conformation. Therefore, the incorporated nanofillers can fundamentally alter the characteristics of polymers and realize remarkable performances compared to conventional composites. However, ironically, the large interfacial area makes it challenging for the interplay of enthalpic and entropic contributions of the filler and polymer matrix. Unfortunately, this causes phase separation and agglomeration of nanoparticles, compromising the properties of nanocomposites. Therefore, it is essential to tailor the thermodynamic driving forces at the filler/matrix interfaces to achieve desired morphology and, ultimately, enhanced physical properties. Here, I introduced functional organic-inorganic nanocomposites consisting of nanoscopically dispersed functional nanoparticles through the design of filler/matrix interfaces. Thanks to the uniform dispersion of nanoparticles, the presented nanocomposites displayed multifunctionalities, such as electrical conductivity with mechanical flexibility, degradability with scalability, and simultaneous enhancement of strength and ductility, which are generally mutually exclusive.

Advisor: Ritchie, Robert O
CRISPR/Cas9-mediated editing of pepper Bs5 homolog in tomato (Solanum lycopersicum) confers disease resistance to bacterial spot disease

Xanthomonas spp. are the causative pathogens of bacterial spot and have caused major yield losses in commercial varieties of tomato and pepper. Bacterial spot disease is a threat to worldwide production of Solanaceous crops, especially in warm and humid environments. The Bacterial Spot 5 (Bs5) gene, which is conserved among Solanaceae, is composed of three exons, and encodes a small proline-rich putative tail-anchored protein with an unknown function. Bs5 is flanked by its paralog, Bs5-like, in a head-to-head orientation. The Bs5 protein is a putative member of the cysteine-rich transmembrane module (CYSTM) protein family, a diverse family found to be expressed in response to biotic and abiotic stress in many eukaryotes. A naturally occurring recessive allele, bs5, was found in pepper to confer disease resistance against a hypervirulent strain of Xanthomonas euvesicatoria in pepper (Capsicum annuum). The bs5 resistance phenotype is characterized by restricted pathogen growth and an absence of necrotic lesions characteristic of bacterial spot susceptibility. Pepper varieties containing the bs5 allele have shown durable resistance, impeding the emergence of bs5-resistant strains in commercial fields. Deployment of the bs5 allele in tomato has the potential to confer disease resistance against bacterial spot. The causative mutation of bs5 is an in-frame six nucleotide deletion in the third exon. It was unknown whether the precise six nucleotide deletion is the sole mutation that confers the resistance phenotype against bacterial spot. We set out to investigate whether introducing nucleotide insertions or deletions to the coding region of tomato Bs5 would be sufficient to introduce resistance. Using CRISPR/Cas9-mediated gene editing, we established two distinct mutant lines with mutations in exon 2 of Bs5 and Bs5-L. We also established a mutant line with mutations in exon 3, the location of the bs5 allele mutation in pepper. Our objective was to establish bs5 resistance in tomatoes using CRISPR/Cas9 based genome editing. We were able to generate several mutant tomato lines with alleles distinct from bs5 in the pepper allele. These tomato lines exhibited resistance against several species of xanthomonads.

Advisor: Staskawicz, Brian
Doudna, Jennifer
Building a Multilingual Internet: The View from South Asia

In this dissertation, I argue that the digitization of the Bangla letter, khanda ta, tracks the transformation of the Western-oriented early consumer Internet into an open, global infrastructure that better met the needs of international, multilingual users longing for digital representation and equal affordances for communication. The story takes place primarily between 2000 and 2005, in South Asia and Silicon Valley, but ventures out in time and space to contextualize the events at hand. I follow the trajectories of standards-makers, software hobbyists, government officials, major software companies, and linguists in turn, showing what stakes and interests they held during this period, and how they shape the debate over khanda ta. The issue sits of khanda ta sits at the crux of several dichotomies that achieve a certain synthesis through its resolution: the gap between new open-channel internet governance institutions and traditional, closed-participation forms of governance; the opposition between the new entrants from the Global South and the mostly-Western actors who had designed the early Internet; and the tension between socially-meaningful language conventions and machine-readable technical standards./nKhanda ta’s eventual inclusion, or “encoding”, in the Unicode Standard represents the victory of the open-governance model of new industry consortia such as the Unicode Consortium, in which older authorities such as government ministries and international treaty organizations must fit themselves. It also represents a recognition of the values and expertise of the Global South, embodied by the South Asian experts in this debate, amongst those of the Western technical elite designing critical digital infrastructures. And it highlights the role of intermediaries who must accumulate both technical and linguistic expertise to build technical tools and standards for language. In the end, my goal is to show the multitudinous threads that came together to build a multilingual internet.

Advisor: Ray, Isha
Duguid, Paul
Investigating the Structure and Downstream Biology Effects of the Juxtamembrane Domain of the Epidermal Growth Factor Receptor

The Epidermal Growth Factor Receptor (EGFR), also known as ErbB1 or HER1 in humans, is a member of the ErbB family. EGFR is a receptor tyrosine kinase (RTK) responsible for communicating cellular signaling across the plasma membrane related to cell proliferation, metabolism, and migration. EGFR mutations and overexpression are known to be related to cancer. Thus, understanding EGFR biology and the molecular mechanism of EGFR activation can lead to important therapeutic strategies. The importance of the juxtamembrane (JM) domain of the EGFR has gathered attention as evidence showed that its intermolecular and intramolecular interactions are crucial for EGFR function.In this dissertation, I describe my graduate work in four chapters detailing the study of the EGFR JM function and its role in regulating the downstream biology of the EGFR. Chapter 1: This chapter builds on the literature review and previous efforts, introducing the role and importance of EGFR in cellular biology, and the role of the JM domain in EGFRactivation. In this chapter, JM structure and the manipulation to affect EGFR signaling were described. Chapter 2: This chapter describes peptides mimicking the JM domain dimer in activated EGFR used for high-resolution structural studies. The designs of these JM-mimicking peptides were detailed. Peptide synthesis, purification, and characterizations that reveal the secondary structure were discussed. Chapter 3: Looking beyond the JM domain, the structural study described in this chapter focused on peptides containing both the transmembrane domain (TM) and the JM domain segment to investigate the allosteric relationship within EGFR. Preparation and characterization of membrane mimics that stabilize TM-containing peptides were reported. Chapter 4: In the final chapter, I report a collaborative work I partake that reveals the effect of JM structure and conformation on EGFR biology in terms of cellular trafficking and receptor degradation. Another preliminary work using APEX2-based proximity labeling toward mass spectrometry proteomics was reported. Finally, this chapter summarized the outlook on future directions following the groundwork laid out in the scope of this dissertation.

Advisor: Schepartz, Alanna
The ABC's of Mathematics Perceptions

What does the word "math" evoke? It is in many ways a fraught term eliciting negative reactions and unpleasant memories. In this dissertation, I explore the variety of ways we humans perceive this concept, starting with the internal (perceptions of ability), then the personal journey (perceptions of belonging), and finally the external (perceptions of conception). I employ a mixture of experiments and computational modeling in order to develop a more holistic understanding of how people perceive math and reinforce human studies with data collected from naturalistic settings - specifically, the internet, to explore word usage and how discussions of math seem to dier from mentions of other concepts.

Advisor: Rafferty, Anna N
Griffiths, Thomas L
Usable and Efficient Systems for Machine Learning

Machine learning has become a key driver for technological advancement in the last decade on the back of major progress in programming interfaces and scalable systems. Libraries such as Scikit-learn and Keras have made it easier to implement machine learning algorithms and applications, while innovations in distributed systems have enabled model training at an unprecedented scale. However, machine learning tooling is far from perfect today; practitioners still face many challenges when developing applications powered by machine learning./nThis dissertation aims to improve the usability and resource efficiency of systems for developing and productionizing machine learning applications by investigating multiple directions identified through extensive empirical evidence gathering and analysis. First, we study the applied machine learning literature and execution traces of publicly available machine learning workflows to understand common practices and shed light on the highly iterative process of model development. Using our insights, we present a solution to accelerate the iterative model development process. Next, we analyze the provenance graph of thousands of production pipelines to uncover latent inefficiencies when running these pipelines. Using these insights, we propose a solution to significantly reduce wasted computation in such systems. Our solutions harness classic techniques from systems, databases, and programming languages to automate data management and optimize computation in machine learning application development. Finally, we synthesize findings from interviews with current users of automated machine learning tools to examine the role of automation in model development, as we look ahead to the future of machine learning developer tools.

Advisor: Parameswaran, Aditya G
Microlocal analysis for 0th order pseudodifferential operators

Zeroth order pseudodifferential operators with Morse--Smale dynamical assumption have been used as a model for the dynamics of internal waves. The operators provide a novel mathematical explanation to the formation of attractors for two dimensional internal waves in a bounded aquarium. In addition, the spectral properties are somewhat surprisingly related to phenomena in quantum scattering./nIn this thesis we introduce an analogue of the scattering matrix and describe its geometric structure. We also study the dynamics of resonances and answer a question posed by Colin de Verdi\`ere by proving the generic absence of embedded eigenvalues./nThe definition of the scattering matrix, although based on analogues with Euclidean scattering, is more involved as we need to deal with the principal symbols of Lagrangian distributions. After being conjugated by certain natural unitary operators, our scattering matrix turns out to be a Fourier integral operator and its canonical relation is related to the bicharacteristics of the operator./nResonances for 0th order pseudodifferential operators are defined as limits of eigenvalues for the operator with viscosity. We show that the convergences rate is linear for simple embedded eigenvalues of the operator. We also consider 0th order perturbations of 0th pseudodifferential operators. A series expansion of resonances for the perturbed operators near embedded eigenvalues for the original operator is proved. A special case of this expansion gives the Fermi golden rule. Using the formulae for the coefficients in the expansion, we prove the absence of embedded eigenvalues for generic perturbation./nAs a by-product of the study of 0th order pseudodifferential operators, we state and prove the sharp radial estimates in Besov spaces, which generalize the corresponding estimates in Sobolev spaces.

Advisor: Zworski, Maciej R.
Advancing Organizational Capabilities to Improve Patient Engagement in Health Care

Health care delivery organizations are increasingly being encouraged to implement strategies to engage patients in their health and health care yet have varying capabilities to support patient-centered care. Improving the quality of health care delivery requires a better understanding of the multi-level organizational capabilities that enable patient engagement. This dissertation develops a conceptual framework to delineate the health care system, physician practice, and team factors associated with patient engagement in chronic care./nThe first study links clinical data to surveys of patients with diabetes in fourteen community health center sites to examine if the availability of team member expertise is associated with patient experiences of chronic care, and whether the relationship is consistent for small versus large sites. The second study uses a nationally representative survey of physician practices and health systems to clarify how health systems may influence the adoption of patient engagement and chronic care management capabilities in constituent physician practices. The third study utilizes Mokken scale analysis and a survey of adult primary care practices to reveal potential pacing and foundation setting in the adoption of patient engagement strategies.

Advisor: Rodriguez, Hector P.
Targeted Learning for Capture Recapture Models and Treatment Effect Estimation

This dissertation develops modern statistical methods, targeted maximum likelihood estimation (TMLE) and ensemble machine learning, for two common problems in epidemiology and public health: 1) estimating the population size based on capture recapture designs, and 2) estimating the continuous and discrete treatment effect of multiple exposures. For the first problem, We proposed novel target parameters for each identification assumption and robust estimators based on TMLE, provided the efficient influence curves for each the parameter, proved the statistical properties of the estimators, and applied them to data collected from national-level infectious disease surveillance systems. We also used simulations with identification assumption violations to test the reliability of the estimation. For the second problem, we developed our target parameter and TMLE estimators and applied them to various types of empirical data collected by community-level follow-up surveys and state-level electronic health record data. We provided simulations and sensitivity analysis to show the performance of the TMLE estimators compared to existing ones. In chapter 1, we gave an introduction to TMLE, the road map of targeted learning, and a more detailed summary of the following chapters. In chapter 2, we developed a novel approach to estimate the population size based on capture recapture designs and evaluated the estimation reliability. In chapter 3, we utilized the targeted learning approach to assess the performance of a diabetes care program on glycemic control of type 2 diabetes patients, and identified patient subgroups with most successful treatment effects. In chapter 4, we proposed a robust variable importance measure based on TMLE and applied it in estimating the transmission effects of mother’s eating behavior on the next generation.

Advisor: van der Laan, Mark
Hubbard, Alan