VictorJuiz/thesis huggingface dataset:
In vivo high-resolution magnetic resonance imaging [electronic resource]

Magnetic resonance imaging is a powerful, non-invasive modality that provides excellent soft-tissue contrast, but it suffers from a relatively low signal-to-noise ratio and is inherently prone to artifacts. Although technological progress over the last few decades has dramatically enhanced the resolution and quality of magnetic resonance images, specific clinical challenges highlight the need for further improvements. First, patients with peripheral arterial disease are at high risk for developing skin ulcers, which are often detected at a late stage, when amputation is the only treatment option. High-resolution imaging might detect changes in skin early enough to enable alternative treatments. Second, higher-resolution larynx imaging is highly desirable for the exact assessment of cartilage invasion, which is a critical step in cancer staging and in the selection of the appropriate treatment. High-resolution skin and larynx magnetic resonance imaging poses specific engineering challenges. The resolution of magnetic resonance images is first hampered by insufficient signal-to-noise ratio. Dedicated surface coils and/or higher field strengths overcome this limitation. Receive-only and transmit/receive 1-inch-diameter coils are shown to be suitable for skin imaging at 1.5 T, 3 T, and 7 T, and a dedicated three-channel array for larynx imaging provides a dramatic increase in resolution over the conventionally used 8-channel neurovascular array. The next engineering challenge involves eliminating artifacts from high-resolution images. Chemical shift artifacts are a concern in skin imaging, especially at higher field strengths, because the hypodermis is a fat layer. A multi-echo sequence is introduced that separates fat and water and provides good signal-to-noise ratio for all skin layers. Motion artifacts affect both skin and larynx images. In skin, where motion is usually rigid-body, navigator-based motion correction proves effective, and navigators can be integrated into the multi-echo sequence that separates fat and water. In larynx, where motion is complex, a new real-time algorithm combining a reacquisition strategy with navigator-based motion correction accounts for the different types of motion. One additional concern with skin imaging at higher field strengths is the increase in the spin-lattice relaxation time T1, which compromises the signal-to-noise ratio. Robust T1 mapping requires the use of a 4-parameter model. A novel nonlinear Least-Squares algorithm reduces the complex minimization problem to a straightforward 1D search, making the fitting procedure much faster. T1 mapping performed in skin at 1.5 T, 3 T, and 7 T shows that the increase in T1 slightly attenuates the benefits of higher field strengths but does not offset them.

Keywords: Electrical Engineering
Advisor: Nishimura Dwight George primary advisor. Thesis advisor
Pauly John (John M.) primary advisor. Thesis advisor
Damrose Edward J. advisor. Thesis advisor
Conolly Steven advisor. Thesis advisor
Incorporating the dynamic nature of molecules improves performance of structure-based function prediction methods [electronic resource]

Structural Genomics consortia aim to determine the structure of proteins with novel folds. In order to interpret their biological significance, it is critical to annotate the functions of these structures. Most structures are solved by X-ray crystallography experiments and represent static snapshots of the molecules. Structure-based function prediction methods do not perform well when the snapshots fail to display the relevant functional conformations. We show that coupling structure-based function prediction methods to molecular dynamics simulations considerably improves their performance in locating calcium binding sites. Our approach can be easily extended to other functions of interest. In particular, we generated short- to medium- scale molecular simulation trajectories (1ns -- 10ns) using GROMACS, a software suite developed for creating molecular dynamics simulations. Gromos 43a5, Gromos 53a6, AMBER '96, AMBER '99SB, AMBER '03, and OPLS-AA force fields were used to generate trajectories for 11 pairs of PDB structures, HOLO and APO form for the presence of calcium ions in the structures (22 structrures in total). Extracting structures at various time points over the course of the simulations we created structural ensembles which inform about the dynamic nature of each of the simulation systems. Using FEATURE, a machine learning algorithm that evaluates the presence of enriched physico-chemical properties around a site of interest, we analyzed the structural ensembles for the presence of calcium binding sites. We devised a clustering algorithm which allowed for definitive determination of the similarity of the local environments around the points identified by FEATURE as potential calcium binding site centers in different structural ensembles for each of the 22 PDB structures. Our results indicate that short scale simulations with 2 or 3 different force fields generate sufficient structural diversity to allow for improved identification of calcium binding sites. Furthermore, inclusion of calcium ions in the simulation systems does not significantly improve the performance of FEATURE. This result highlights the need for improved force fields, such that the dynamic nature of calcium binding sites can be accurately reproduced.

Keywords: Genetics
Advisor: Altman Russ primary advisor. Thesis advisor
Cherry Joe H.
Levitt Michael
Sherlock Gavin advisor. Thesis advisor
Increased light harvesting in dye-sensitized solar cells using Förster resonant energy transfer [electronic resource]

Dye-sensitized solar cells (DSCs) are an emerging photovoltaic technology with the potential for large scale manufacturing and low cost processing. However, the power conversion efficiency of DSCs must increase from 11% to 14% to be commercially competitive with conventional solar cell technologies. DSCs do not completely absorb all of the photons from the visible and near infrared portion of the solar spectrum and consequently have lower short circuit photocurrent densities compared to inorganic photovoltaic devices. A variety of sensitizing dyes have been explored, but it is extremely challenging to develop a single sensitizing dye that can absorb strongly in the visible and near-infrared spectrum. The focus of this doctoral thesis is on developing fundamentally new DSC architectures which incorporate energy transfer processes in order to improve light harvesting. Chapter One will introduce the conventional dye-sensitized solar cell architecture and general operating principles for photocurrent generation. Chapter Two will focus on the general theory behind Forster Resonant Energy Transfer (FRET) and modeling of the average excitation transfer efficiency (ETE), which is the fraction of excited dyes that undergo energy transfer to the sensitizing dye, inside of the DSC. Chapter Three describes a new design where energy relay dyes unattached to the titania absorb high energy photons and transfer their energy to the sensitizing dye via Förster resonant energy transfer. This architecture allows for stronger and broader spectral absorption for the same film thickness. In liquid DSCs, we demonstrate a 26% increase in power conversion efficiency when using an energy relay dye with an organic, near-infrared sensitizing dye and show that the average excitation transfer can be greater than 95%. Chapter Four demonstrates that energy relay dyes can be mixed inside of a solid, organic hole conductor (e.g. spiro-OMeTAD) for solid-state DSCs. Chapter Five describes the concept of using energy relay dyes, cosensitized on the TiO2 surface, that directly absorb near-infrared light and undergo energy transfer to a neighboring a Ruthenium based metal ligand complex (i.e. C106). Near-infrared energy relay dyes have the potential to increase light harvesting in the 700-800 nm portion of the spectrum and can be implemented in state-of-the-art DSC systems. The final chapter will briefly describe the opportunities for future study and potential commercialization of DSCs.

Keywords: Materials Science and Engineering
Advisor: McGehee Michael
Cui Yi
Peumans Peter
Individual investors and corporate earnings [electronic resource]

This dissertation comprises two papers on the trading of individual investors around earnings announcements: 1. This study examines the effect of earnings announcements on individual investors' trading decisions and their trading profits. Consistent with earnings news informing the trading decisions of individual investors, I find that earnings announcements are associated with significant increases in individual investor market participation, and that these increases persist even after controlling for the information in prices. Moreover, and in contrast to the conventional wisdom that disclosure benefits unsophisticated investors at the expense of more sophisticated investors, I find that individuals' trades around earnings announcements earn economically and statistically significant losses, and that these losses are significantly greater than the losses of non-announcement trades. Consistent with these losses resulting from inefficient information processing, I find the higher the information content of the earnings announcement the greater the loss, and that increased losses around earnings announcements are concentrated among those individual investors who are not classified as affluent or active traders. Given the limited information processing ability of individual investors, the results suggest a more nuanced view of the welfare effects of disclosure. 2. This study examines the effect of contrarian retail trades on the pricing of earnings information. Consistent with price pressure from contrarian retail trades delaying the adjustment of prices to earnings information, I find that the negative price drift accompanying bad news is largest when retail investors buy on bad news, and that the positive price drift accompanying good news is largest when retail investors sell on good news. These findings are consistent with the correlated trading of retail investors around earnings announcements causing a delayed price adjustment which manifests as drift.

Advisor: Larcker David F.
Beaver William
Lee Charles M. C. advisor. Thesis advisor
Individual investors and corporate earnings [electronic resource]

This dissertation comprises two papers on the trading of individual investors around earnings announcements: 1. This study examines the effect of earnings announcements on individual investors' trading decisions and their trading profits. Consistent with earnings news informing the trading decisions of individual investors, I find that earnings announcements are associated with significant increases in individual investor market participation, and that these increases persist even after controlling for the information in prices. Moreover, and in contrast to the conventional wisdom that disclosure benefits unsophisticated investors at the expense of more sophisticated investors, I find that individuals' trades around earnings announcements earn economically and statistically significant losses, and that these losses are significantly greater than the losses of non-announcement trades. Consistent with these losses resulting from inefficient information processing, I find the higher the information content of the earnings announcement the greater the loss, and that increased losses around earnings announcements are concentrated among those individual investors who are not classified as affluent or active traders. Given the limited information processing ability of individual investors, the results suggest a more nuanced view of the welfare effects of disclosure. 2. This study examines the effect of contrarian retail trades on the pricing of earnings information. Consistent with price pressure from contrarian retail trades delaying the adjustment of prices to earnings information, I find that the negative price drift accompanying bad news is largest when retail investors buy on bad news, and that the positive price drift accompanying good news is largest when retail investors sell on good news. These findings are consistent with the correlated trading of retail investors around earnings announcements causing a delayed price adjustment which manifests as drift.

Keywords: Business.
Advisor: Larcker David F. primary advisor. Thesis advisor
Beaver William advisor. Thesis advisor
Lee Charles M. C. advisor. Thesis advisor
Information advantage in a global economy [electronic resource] : geography, social networks and hedge fund returns

Recent research finds that information advantage--access to accurate, timely and relevant information--is a key resource in the knowledge economy. Despite this, academics have reached no consensus on the sources of information advantage, proposing various mechanisms ranging from the local (e.g. agglomeration, local social networks) to the global (e.g. fields, pipelines, world cities). Academics have only begun to examine when each of these mechanisms are relevant, which is just as important as how they function. This dissertation addresses this gap, investigating how different mechanisms generate different types of information advantage, and when each is relevant. Although this theory should apply across many different knowledge industries, the dissertation focuses on a manageable empirical scope: the hedge fund industry. This empirical focus matches the theoretical framework, as there are few propositions so universally agreed upon and so little studied as "information flows drive global financial markets". Hedge funds are interesting for both theoretical and substantive reasons. Not only are they extremely sensitive to information advantage, but they also drive a large proportion of securities trading volume worldwide, and relate to systemic financial risks. This dissertation analyzes data from the BarclaysHedge database and the Directory of Corporate Affiliations using hierarchical linear models. The results suggest that specific geographic areas, field-level networks and a "global social capital network" provide different types of information advantage, which are relevant to different types of hedge funds. Overall, this dissertation identifies the hedge funds having information-based competitive advantages, and explains where these advantages come from. These finding not only have theoretical implications, but substantive ones as well.

Keywords: Sociology.
Advisor: Granovetter Mark S. primary advisor. Thesis advisor
Shin Gi-Wook primary advisor. Thesis advisor
Powell Walter W. advisor. Thesis advisor
Information elicitation, incentives, and markets [electronic resource]

Information plays a prominent role in economic decisions. Over the past decade, with the enhancement of communication technology and the development of large marketplaces, information economics has become a key component in the study of modern economic environments. In my thesis, I ask how an uninformed principal can purchase information from supposedly better informed agents. My doctoral research strives (i) to extend the theoretical foundations of information elicitation, and (ii) to provide efficient means of elicitation that can be implemented with existing computational resources. I first consider the problem of incentivizing a single agent to provide accurate probabilistic information, that is, information about the uncertainty of a future outcome. This outcome can represent, for example, future sales or stock market prices, and the principal may wish to learn the average sales or the volatility of a stock. I show that the principal may not obtain all information directly, and characterize the information that can be obtained, along with the appropriate incentive devices. For example, she can get the average sales but not the stock volatility. However, the principal can always obtain any information indirectly, by asking for extra information. This leads to a notion of elicitation complexity: how much is needed to infer the information of interest. I then consider the problem of elicitation from multiple agents, using betting markets or prediction markets, which are contingent claims markets specifically designed for the purpose of aggregating traders information. For both cases, I describe the information that such markets can reveal, and explain how to design the assets and the market mechanisms so as to obtain the information of interest. Finally, I consider the case of eliciting arbitrary opinions. As those can be purely subjective, it is generally not possible to design appropriate incentive schemes for a single agent, but I show that with multiple agents one may design surveys or opinion polls that enforce truthful reporting.

Advisor: Shoham Yoav primary advisor. Thesis advisor
Goel Ashish advisor. Thesis advisor
Saberi Amin advisor. Thesis advisor
The informational content of perceptual experience [electronic resource]

This dissertation develops a naturalistic theory of perceptual content based on the insight that our perceptual experience measures the world. This theory is motivated in detail by examples from color perception. The basic idea is that possible color experiences define a measurement scale, and the causal relationship between this scale and the world determines the contents of the measurements it performs. This content is informational content in the sense that it captures the complete information carried by the percept about the world. The biggest problem for a naturalistic theory of perceptual content is accounting for perceptual error. This dissertation provides an alternative to the current most popular strategy for analyzing representational error naturalistically, teleosemantics. I describe how information theory provides the apparatus for analyzing representational efficacy. This suggests that the intentional content of a percept may then be identified with the unique state of the world it represents most effectively. Once we have an analysis of intentional content, we can identify perceptual errors as situations in which a percept's content and the state of the world which caused it diverge.

Keywords: Philosophy
Advisor: Suppes Patrick
Taylor Kenneth Allen
Diaconis Persi advisor. Thesis advisor
Perry John
Ryckman Thomas advisor. Thesis advisor
Informed electrical resistivity imaging for monitoring infiltration dynamics in the near surface [electronic resource]

Determining the spatial distribution of subsurface properties is critical to developing efficient groundwater management strategies. Though hydrologic methods can accurately measure these properties, they often have sparse spatial coverage and cannot capture the spatial variation. Integrating geophysical and standard methods can provide more comprehensive measures of spatial and temporal variation in hydrologic properties. Electrical resistivity imaging (ERI) provides continuous maps of the subsurface electrical conductivity, which is related to water content in the vadose zone, making it particularly useful for groundwater applications. However, differences in measurement scales and the challenge of obtaining accurate images of electrical conductivity can limit the ability to integrate ERI with existing hydrologic data. To address these issues I present a framework for informed imaging, the incorporation of all available information into the acquisition, inversion and interpretation of electrical resistivity data. This framework includes methods for informed experimental design, time-lapse inversion, and integration of different data types into a consistent hydrogeologic model. I present an application of informed imaging to monitoring flow beneath an artificial recharge pond, which is part of an aquifer storage and recovery project for managing coastal groundwater resources. As a first step in informed imaging, I create a hydrostratigraphic model, which incorporates hydrologic, geologic, and geophysical data into a systematic framework. I use this model with the proposed experimental design method to select acquisition arrays for ERI experiments. Monitoring data acquired at the pond are inverted using an implementation of the extended Kalman filter, which incorporates all previously acquired information into the inversion of data at each time-step. This is the first application of this method to surface-ERI data collected in the field. Furthermore, I present an analysis of the impact of measurement support on the estimated correlation structure of properties in anisotropic systems, which must be accounted for when integrating processed geophysical data into hydrologic models. The successful application of these methodologies to monitoring flow at an artificial recharge pond leads me to conclude that using an informed imaging approach can enhance the use of geophysical methods to developing groundwater management strategies.

Keywords: Geophysics
Advisor: Knight Rosemary (Rosemary Jane)
Beroza Gregory C. (Gregory Christian) advisor. Thesis advisor
Harris Jerry M. advisor. Thesis advisor
Kitanidis P. K. (Peter K.) advisor. Thesis advisor
Pidlisecky Adam advisor. Thesis advisor
Infrared phenomenology of ultraviolet physics beyond the standard model [electronic resource]

Supersymmetry and string theory are among the most compelling candidates for describing physics beyond the Standard Model. As much of the physics entailed by string theory and supersymmetry is expected to lie at very high energies, it is therefore instrumental to look for new ways in which the dynamics of inaccessible energies may be made apparent at more accessible ones. This thesis explores ways in which ultraviolet physics motivated by the shortcomings of the Standard Model may give rise to new signatures and phenomena in the infrared. We begin by considering a variety of potentially-observable new degrees of freedom arising from the compactification of higher-dimensional supersymmetric theories. We then turn to the implications of supersymmetry and confining dynamics for Standard Model flavor and supersymmetry breaking. In each case the models under consideration leave an imprint -- sometimes directly, often obliquely -- on observables at lower energies, from which we may extract signals accessible at the LHC and other experiments.

Keywords: Physics
Advisor: Dimopoulos Savas
Kachru Shamit
Silverstein Eva