VictorJuiz/thesis huggingface dataset:
Combining light restriction and optogenetics to dissect the neural circuitry underlying behavior [electronic resource]

Aberrant states in the nervous system, both acute and chronic are the cause of mental health diseases that affect more than a quarter of Americans over the age of 18. The mechanisms underlying mental health diseases such as Parkinsons, schizophrenia, anxiety, and depression are poorly understood, and thus current treatment approaches are often ineffective or carry with them significant side effects. In order to improve our understanding of these diseases and others, new tools must be developed that take into account the complex dynamics and diversity of circuit elements that make up the neural substrates from which these behaviors arise from. Our lab has pioneered the use of light activated microbial opsins in mammalian neurons in order that we can manipulate neural circuits with cell- type specificity, millisecond temporal precision, and millimeter spatial resolution -- termed 'Optogenetics" . These genetically encoded elements include two broad classes, excitatory channels such as Channelrhodopsin - 2 (ChR2) and inhibitory pumps such as Halorhodopsin (NpHR). The use of these tools allow for bidirectional control ove r cell types and connections that make up the neural circuits that underlie behavior within normal and diseased mental health states using simple gene and light targeting approaches. But, the nervous system's structural complexity -- both in the geometrical arrangement of neurons and connections between neurons - requires more than these basic approaches to dissect its function. T o address this extra layer of complexity, the spatial control of light excitation itself could be a versatile method in combination with optogenetic approaches to dissect neural circuitry. The studies herein look to build upon current optogenetic technology by utilizing light restriction in order to control and dissect neural circuits with high precision. There are two approaches used to accomplish this: (1) in vivo and ex vivo one photon light restriction that utilize simple light restrictive optical elements to more precisely stimulate and inhibit both genetically targeted cells or connections between close brain areas and (2) in vivo and ex vivo two photon techniques that allow for fast excitation, inhibition, and bi- stable modulation at the level of a single - cell, multiple single - cells, or in some cases, sub-cellularly . The tools developed here can be used in a variety of systems and allows for the dissection of neural circuitry using optogenetics to a new level of precision that was otherwise unapproachable via any technique available to researchers. As these tools are further developed, a bridge between the individual cellular contributions to neural circuit function and behavioral neuroscience will hopefully emerge.

Keywords: Neurosciences.
Advisor: Deisseroth Karl primary advisor. Thesis advisor
Clandinin Thomas R. (Thomas Robert)
Hestrin Shaul
Malenka Robert C. advisor. Thesis advisor
Commercial video games as preparation for future learning [electronic resource]

In the field of digital game-based learning there has been much focus on the development of educational games—games designed specifically to teach. Attention has also been paid to commercial, off-the-shelf (COTS) games, but that work has focused mostly on the motivation, engagement, and community participation engendered by such games. Relatively little work has been done to examine the potential of incorporating COTS games into formal curricula, and to the best of my knowledge no one has studied what school-relevant learning benefits might accrue from simply playing COTS games in one's leisure time. This dearth of research is unsurprising: there is no reason to expect that games designed entirely to entertain would produce learning benefits on school content that are measurable by traditional assessments. A novel assessment framework called Preparation for Future Learning (PFL), however, is designed specifically to measure immature forms of knowledge that traditional assessments miss, by incorporating learning resources into the assessment process to determine what test takers' immature knowledge has prepared them to learn. In this study, I used the PFL framework to investigate whether being randomly assigned to receive and play one of two COTS games (Call of Duty 2, n = 34, or Civilization IV, n = 35) at home over the course of five weeks would prepare community-college students to learn from a lecture about World War II compared to a control condition that received no game (n = 33). Learning was measured by performance on pre- and post-lecture multiple-choice tests comprising items from the National Assessment of Educational Progress (NAEP), the California Standards Test (CST), and a purpose-built test from a World-War-II study guide produced by the company SparkNotes. Results indicated no condition differences in performance on the pre-lecture test but a significant positive effect of gameplay on the post-lecture test, suggesting that gameplay experiences had prepared participants in those conditions to learn more from the lecture. Additionally, responses to open-ended questions about two scenarios that had not been covered in the lecture suggested that the two games had influenced participants' attention to the lecture differently: CoD2 players were more attentive to local tactical elements, and Civ4 players to global strategic elements. Demonstrating school-relevant benefits of COTS gameplay strengthens the broader argument for digital game-based learning, suggests that educators could leverage recreational gameplay with appropriately designed formal instruction, and shows COTS game designers that incorporating even modestly school-relevant experiences in their games could help their players without compromising the appeal of their games.

Keywords: Education.
Advisor: Haertel Edward primary advisor. Thesis advisor
Schwartz Daniel L. primary advisor. Thesis advisor
Barron Brigid advisor. Thesis advisor
Commonplace-book stylistics [electronic resource] : romantic and victorian technologies of reading and writing

"Commonplace-Book Stylistics" offers a theory of composition based on nineteenth-century commonplace books, which were personal collections of quotations and information. Between 1795 and 1900 the tradition evolved from handwritten quotations in blank books to cut-and-pasted newspaper clippings in scrapbooks. Simultaneously, the types of quotation readers recorded changed dramatically. While Romantic writers liberally revised the words (and often the meaning) of texts they transcribed into their commonplace books, Victorians endorsed a growing celebrity culture as they preserved cartoons and photographs of their favorite writers alongside quotations. My project demonstrates how authors' engagements with new systems for arranging gathered information in commonplace books facilitated larger stylistic trends. For example, Coleridge repackaged other authors' verse in Biographia Literaria, Hazlitt translated poetry into prose for his essays, and Tennyson circulated commonplaces in In Memoriam. Joining history-of-the-book methodology and literary formalism, my project reads manuscript commonplace books for their structural qualities and analyzes how new ways for organizing extracts influenced literary style, particularly patterns of quotation. Ultimately, "Commonplace-Book Stylistics" re-contextualizes our understanding of central nineteenth-century texts by returning them to their material beginnings. Furthermore, it advocates for a reformulation of literature that attends to the specificity of material networks of reception and composition that nurtured both canonical and non-canonical texts alike.

Advisor: Gigante Denise
Moretti Franco
Woloch Alex
Compactifying picard stacks over degenerations of surfaces [electronic resource]

Moduli spaces of smooth varieties can be partially compactified by the addition of a boundary parametrizing reducible varieties. We address the question of partially compactifying the universal Picard stack (the moduli space of line bundles) over a moduli space of smooth varieties by extending it over such a partial compactification. We present a stability condition for line bundles on reducible varieties and use it to specify what boundary points should be added to the universal Picard stack to obtain a proper moduli space. Over surfaces with exactly two irreducible components, we give specific results on enumerating stable line bundles, which support the conjecture that these are the right boundary points to add. This generalizes work of Caporaso and others in the 1990s on compactifying the universal Picard variety over the moduli space of curves.

Keywords: Mathematics
Advisor: Vakil Ravi primary advisor. Thesis advisor
Ionel Eleny advisor. Thesis advisor
Li Jun (Mathematician)
Comparative modeling and protein-like features of hydrophobic-polar models on a two-dimensional lattice [electronic resource]

Lattice models of proteins have been extensively used to study protein thermodynamics, folding dynamics and evolution. Our study considers two different hydrophobic-polar (HP) models on the two-dimensional square lattice: the purely HP model and a model where a compactness-favoring term is added. We exhaustively enumerate all the possible structures in our models and perform the study of their corresponding folds, HP arrangements in space and shapes. The two models considered differ greatly in their numbers of structures, folds, arrangements, and shapes. Despite their differences both lattice models have distinctive protein-like features: (1) Shapes are compact in both models, especially when a compactness-favoring energy term is added. (2) The residue composition is independent of the chain length and is very close to 50% hydrophobic in both models, as we observe in real proteins. (3) Comparative modeling works well in both models, particularly in the more compact one. The fact that our models show protein-like features suggests that lattice models incorporate the fundamental physical principles of proteins. Our work supports the use of lattice models to study questions about proteins that require exactness and extensive calculations, such as protein design and evolution, which are often too complex and computationally demanding to be addressed with more detailed models.

Keywords: Physics
Advisor: Doniach S. primary advisor. Thesis advisor
Levitt Michael
Pande Vijay advisor. Thesis advisor
Competition and strategic interaction in new markets [electronic resource]

My dissertation focuses on how firms compete effectively in new markets, and explores several strategic issues faced by firms in these contexts. These include how firms strategically interact with their rivals, how they quickly and efficiently craft successful strategies and develop viable business models, and how they successfully position themselves as the cognitive referent in the new market they are creating. While prior research has examined many of these issues in the context of established markets, my research investigates new markets and traces the activities of entrepreneurial rivals. Through an in-depth, longitudinal field study of five firms in the online investing market, I develop new theory to explain how firms successfully achieve these objectives. The first theoretical framework offers an explanation for how firms win the race to develop a viable business model. As the new market emerged, high performing firms enacted three strategies in sequence, which helped them get to a business model quickly and efficiency. First, executives attended to substitutes and copied from rivals. Next, they actively tested assumptions and made major resource commitments to the most lucrative business model opportunity. Finally, they maintained loose links in the organizational activity system to accommodate emergent sources of value. The resultant middle range theory has implications for research on competition in new markets and the strategic processes of developing business models. The second theoretical framework offers an explanation for how some firms become the cognitive referent in a new market while others fail to do so. Although prior research has shown how firms and other actors use rhetoric and symbolic activities to create new markets, I analyze how entrepreneurial firms use the same cultural strategies to position themselves in a new market they are creating. Successful firms conceptualize market creation as problem solving and follow a sequence that begins with narrowly directed rhetorical attacks aimed at current solutions, progresses to shifting stories to coincide with emergent logics, and culminates with eschewing labels that audiences attach to them as these firms introduce novel products to the market. By contrast, unsuccessful firms undermine their own positions through improper use of symbolic market creation activities. The resultant theory is relevant to the literatures on cultural strategy and the performance of entrepreneurial firms.

Keywords: Management Science and Engineering
Advisor: Eisenhardt Kathleen M. primary advisor. Thesis advisor
Katila Riitta primary advisor. Thesis advisor
Byers Thomas (Thomas H.) advisor. Thesis advisor
Eesley Charles advisor. Thesis advisor
Powell Walter W. advisor. Thesis advisor
Computational algorithms and statistical models for ChIP sequencing analysis [electronic resource]

Chromatin immunoprecipitation coupled with ultra-high-throughput DNA sequencing (ChIP-seq) has been widely utilized to study genome-wide localization of protein-DNA interactions since 2007. This powerful technique provides comprehensive and high-resolution protein-DNA binding data for the identification of cis-regulatory elements, which is important for understanding and deciphering the underlying transcriptional gene regulatory mechanism. In this dissertation, I developed a computational and statistical framework for the analysis of ChIP-seq data. A typical pipeline for analyzing ChIP-seq data is presented and discussed, including data exploration and visualization, background estimation, peak detection, genomic annotation, and motif analysis. In particular, I developed and implemented a series of peak detection algorithms and methods for transcription factor (TF)-binding ChIP-seq data, for both single-replicate ChIP-seq datasets and multiple-replicate ChIP-seq datasets. For single-replicate peak calling, I developed an iterative conditional Binomial model for the two-sample problem (when both the treated ChIP sample and the negative control sample are available). This iterative method is computationally efficient and provides accurate estimation of joint background distribution between ChIP and negative control samples. Compared to other two-sample peak callers, our method produces higher sensitivity in peak calling and sharper motif resolution in detected peak regions. For the multiple-replicate problem, I put forward a hierarchical Negative Binomial model to assess binding signal variations among multiple ChIP-seq biological replicates. A closed-form empirical Bayes estimator of expected peak signal is developed by pooling information from all candidate peak regions. This empirical estimator significantly shrinks the variance of estimation error and increases the sensitivity in detecting binding loci of interest especially when the number of replicates is small. Our method outperforms existing heuristic approaches for multiple-replicate peak calling, including the pooling approach and the intersection approach. The computational algorithms and statistical models developed for ChIP-seq data analyses are applied and evaluated in a study of the Sonic Hedgehog (Shh) signaling pathway in the ventral neural tube of mouse embryos. By an integrative analysis of transcription profiling data, ChIP-seq data, function annotation and motif discovery, we identified hundreds of novel cis-regulatory elements mediated by Gli1, predicted potential co-binding partners of Gli1, and gained insights of Gli functions in mouse embryonic ventral neural tube development.

Advisor: Batzoglou Serafim primary advisor. Thesis advisor
Wong Wing Hung primary advisor. Thesis advisor
Dill David L. advisor. Thesis advisor
Computational efficiency in internet economics and resource allocation [electronic resource]

The Internet has created an environment for operations research to play a role in solving practical problems with large networks and a tremendous amount of data. In this thesis, I am interested in developing mathematical principles and computational methodologies underlying the huge multiple-agent environment created by social economic systems over the Internet. The three major topics covered are: 1. Social network advertising, modeling, and pricing: I propose an analytic model and solution for advertisement on a social network based on the concept of forwarding power. Forwarding power is a concept I derive to quantify the amount of information each node is able to gather from the network, or the power to forward information from its predecessors. In other words, the forwarding power is an individual's ability to forward others' opinions. Based on this new concept for a social network, I formulate an optimization model that maximize social welfare, a goal often favored by system designers. This has the advantage of being a convex program that can be solved in polynomial time. Furthermore, it derives a polynomial-time, implementable, and truthful mechanism for advertisement pricing. 2. Envy-free resource allocation: I study the computational efficiency of the envy-free cake-cutting problem. A solution to this problem would be a resource allocation among several partners such that no one entity would envy the anothers' allocated part. I am interested in understanding the query complexity to achieve this task, under both the oracle function model as well as the polynomial function model. I characterize the complete query complexity by developing an (asymptotically) matching query bound for the oracle function model. I also prove PPAD-completeness for the query complexity under the polynomial time function model. In deriving these results, I developed a comprehensive characterization of query complexity for discrete fixed points and the Tucker problem. 3. Finding pure Nash equilibria in supermodular games: A supermodular game abstracts relations in the players' strategic alternatives, among the participation agents. Tarski's fixed point on lattices forms the mathematical foundation for the supermodular game. For both supermodular games and Taski's fixed points, I find the first efficient algorithm to find one solution and prove hardness results to determine uniqueness (matching bounds for query complexity in the oracle function model and Co-NP-hardness in the polynomial function model). The modeling techniques, fundamental mathematical insights, and algorithmic tools developed in this thesis are expected to be useful for many related applications in Internet economics and resource allocation.

Keywords: Management Science and Engineering
Advisor: Ye Yinyu primary advisor. Thesis advisor
Goel Ashish advisor. Thesis advisor
Saberi Amin advisor. Thesis advisor
Computational Research on Adiposity, Nutrition, and Energy expenditure (CRANE) [electronic resource]

The rapid rise in obesity in the US over the last several decades parallels a decrease in infectious disease incidence and a rise in antimicrobial usage. The role of the microbiome—which is influenced by both disease and by biocidal chemicals—on body weight is of increasing interest. We desired to quantify effects of changes in disease patterns and microbiome shifts on body weight of the population; however, no population-level model of body weight existed. Drawing from a collection of literature describing models of individual body weight, a model was built to quantify weight changes across the population using publicly available data from the National Health and Nutrition Examination Survey (NHANES). The model used an energy balance perspective, quantifying energy intake and expenditure. First, dietary data was obtained to describe energy intake. Dietary data comes primarily from self-report and is notoriously inaccurate as individuals tend to under-estimate their food consumption. A dataset was obtained from a study where participants had completed dietary recall surveys and had had energy expenditure measured. Using this as a "training dataset", Chapter 3 describes two predictive models developed which adjust dietary intake to a more biologically plausible range. The models were validated, with a simulation of NHANES data, for their ability to produce estimates within bounds established a priori. They produced substantially more realistic estimates than those derived from the raw data. With better estimates of energy intake, a simulation model of body weight in a population was built (Chapter 4). A population was drawn from NHANES which represented a realistic cross-section of the U.S. population based on age, sex, and survey sampling weights. Energy intake and expenditure were tracked for each individual in the model, and an excess or deficiency of energy was converted to a gain or loss of body weight. The effect of ageing on the weight distribution of the population was calculated. The excess energy necessary to produce the shift in the body weight distribution of the US population over a 20-year period was estimated. The effect of an infectious agent's alteration of energy intake and expenditure and associated body weight was also calculated. Finally, the relationship between NHANES data on triclosan and body mass index (BMI) was studied (Chapter 5). Triclosan is a biocide that likely affects the gut microbiome. The effect of triclosan on BMI in a linear regression was studied with triclosan expressed in two ways: (1). as a binary variable (present vs. absent) and (2). in quartiles (in order to assess whether increased quantity of triclosan led to a trend in BMI). Triclosan presence was found to be associated with an increase in BMI. By quartile, BMI was higher in lower levels of triclosan compared to higher levels, suggesting the possibility of multiple mechanisms of action.

Keywords: Electrical Engineering
Advisor: Harris J. S. (James Stewart)
Brandeau Margaret L. advisor. Thesis advisor
Parsonnet Julie
Computer modeling of human lower limb muscles to study how muscle fiber lengths and velocities affect muscle force generation during walking and running [electronic resource]

Walking and running rely on the complex coordination of the neurological, muscular, and skeletal systems. The role of muscles in this system is to produce force, a task that is dramatically affected by the dynamics of muscle fibers. In walking and running, we do not know how fiber dynamics affect force generation because experimental tools are ill suited to these measurements. Computer models can be powerful tools for estimating muscle dynamics that cannot be measured experimentally. During my doctoral research I created a model based on state-of-the-art muscle architecture data that estimates fiber lengths and velocities during movement. I used this model to create simulations of muscle fiber dynamics for five subjects walking and running at multiple speeds. Analysis of my simulations revealed how walking or running speed affects force generation, explained how running enables some muscles to produce more force than they do in walking, and yielded normative muscle fiber lengths and velocities of eleven muscles during walking and running. The results support the hypothesis that the walk-to-run transition in human gait is related to the force generation ability of the plantarflexors, offer insights into dynamic properties of muscles that have not yet been measured during walking and running, and permit comparisons among muscles with diverse architecture. The model and simulations created as part of this work can be applied to many other research areas in biomechanics and have been made freely available at simtk.org.

Keywords: Mechanical Engineering
Advisor: Delp Scott primary advisor. Thesis advisor
Khatib Oussama advisor. Thesis advisor
McGill Kevin Charles advisor. Thesis advisor