VictorJuiz/thesis huggingface dataset:
Increased light harvesting in dye-sensitized solar cells using Förster resonant energy transfer [electronic resource]
Keywords: Materials Science and Engineering

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.
Individual investors and corporate earnings [electronic resource]
Keywords: Business.

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.
Information advantage in a global economy [electronic resource] : geography, social networks and hedge fund returns
Keywords: Sociology.

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.
The informational content of perceptual experience [electronic resource]
Keywords: Philosophy

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.
Informed electrical resistivity imaging for monitoring infiltration dynamics in the near surface [electronic resource]
Keywords: Geophysics

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.
Infrared phenomenology of ultraviolet physics beyond the standard model [electronic resource]
Keywords: Physics

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.
In-situ calibration and direct de-embedding of RF integrated circuits and microwave structures using self-compensating techniques [electronic resource]
Keywords: Electrical Engineering

Characterization of on-wafer or system-on-chip RF devices and structures usually requires the use of an external calibration substrate followed by measurements and application of de-embedding techniques. While different de-embedding techniques have been published, none of them provides calibration and de-embedding in a single step. In this work an In-situ and self-compensating method that provides calibration and direct de-embedding is presented. This method relies on the integration of calibration and verification structures along with the device under test (DUT). Characterization or accurate modeling of a single standard allows reference-plane setting at the input/output ports of the DUT and direct measurement and de-embedding of the intrinsic DUT while embedded verification standards ensure validity of the calibration coefficients. Furthermore, the embedded verification structures can be used to implement an iterative method for determining the reactive element of the required single standard with nearly no constraints and the compactness of a self-contained test bench where the effects of any probing interface can be directly calibrated out in a single-step operation and without requiring separate measurement and/or modeling of each structure between the DUT and the probing point. Simulation and lab measurements ranging from the low MHz region up to V-band (67GHz) demonstrate that the new method is valid for direct extraction of DUT data without the need for separate calibration and de-embedding steps or external calibration substrates and with the advantage of being able to control the position of the reference plane by fulfilling very simple layout requirements. In addition, it also presents a direct method for detecting and possibly correcting the unavoidable probe displacement that affects most of the manual and automatic probe stations used for circuit and device characterization. This probe displacement detection technique treats mechanical shifts as deviations of a first set of complex solutions that would initially result in a fully balanced system. The only requirement for the implementation of this technique is the inclusion of a set of wideband coupled lines that allow direct sensing of the incident and reflected waves and a reference signal for phase and relative amplitude measurements. Moreover, this technique does not require any calibration process other than being able to store the initial state of the test system, an initial set of solutions and the actual solutions to the current state of the test system.
An integrated impedance biosensor array [electronic resource]
Keywords: Electrical Engineering

Affinity biosensors are important tools for detecting DNA, proteins, cells, and other biomedical analytes. Although optical readout is prevalent, impedance readout is promising for many applications due to lower cost, reduced system size, and label-free operation. Impedance biosensors detect the binding of a target biomolecule to an immobilized probe by quantifying changes in the the electrode-electrolyte interface impedance. Impedance biosensors traditionally use bulky and expensive instruments to monitor the impedance of a single electrode. We describe miniaturized and inexpensive readout circuitry for an array of such sensors. By using a sensor array, multiple analytes can be simultaneously detected and limitations inherent to individual sensors can be mitigated. Reducing the size and cost of the measurement system enables new applications. We present a measurement system for a 6x6 array of impedance biosensors built from off-the-shelf components. Experimental results with DNA probe-target pairs confirm others' reports that changes in the interface impedance can signify binding. Other experiments with proteins demonstrate that changes in the nonlinearity of the I-V relationship can also indicate probe-target binding. We show that the impedance and the nonlinearity can be quantified simultaneously by superimposing a large-amplitude tone on the impedance-measurement tone and analyzing the resulting intermodulation tones. We conclude by describing an integrated array of measurement circuits implemented in 0.18 um CMOS. Each of the 36 measurement pixels contains an impedance-measuring circuit plus tone cancellation circuitry, which enables simultaneous nonlinearity measurement. To prevent the large-amplitude excitation from saturating the amplifier output, a per-pixel digital feedback loop injects an appropriate cancelling current at the amplifier input. Impedance changes of 0.2% can be detected using the integrated measurement circuit. Each pixel occupies 0.14 mm2 and consumes 1.9 mW.
Integrative modeling for genome-wide regulation of gene expression [electronic resource]
Keywords: Biology.

High-throughput genomics has been increasingly generating the massive amount of genome-wide data. With proper modeling methodologies, we can expect to archive a more comprehensive understanding of the regulatory mechanisms of biological systems. This work presents integrative approaches for the modeling and analysis of gene regulatory systems. In mammals, gene expression regulation is combinatorial in nature, with diverse roles of regulators on target genes. Microarrays (such as Exon Arrays) and RNA-Seq can be used to quantify the whole spectrum of RNA transcripts. ChIP-Seq is being used for the identification of transcription factor (TF) binding sites and histone modification marks. RNA interference (RNAi), coupled with gene expression profiles, allow perturbations of gene regulatory systems. Our approaches extract useful information from those genome-wide measurements for effectively modeling the logic of gene expression regulation. We present a predictive model for the prediction of gene expression from ChIP-Seq signals, based on quantitative modeling of regulator-gene association strength, principal component analysis, and regression-based model selection. We demonstrate the combinatorial regulation of TFs, and their power for explaining genome-wide gene expression variation. We also illustrate the roles of covalent histone modification marks on predicting gene expression and their regulation by TFs. We present a dynamical model of gene expression profiling, and derive the perturbed behaviors of the ordinary differential equation (ODE) system. Based on that, we present a regularized multivariate regression method for inferring the gene regulatory network of a stable cell type. We model the sparsity and stability of the network by a regularization approach. We applied the approaches to both a simulation data set and the RNAi perturbation data in mouse embryonic stem cells.
Interest rate modeling and a time series model for functional data [electronic resource]
Keywords: Statistics

In finance, an interest rate derivative is a financial instrument where the underlying asset is an interest rate at which payments are made based on a notional amount. A common approach to price interest rate derivatives is through the use of interest rate models. However, a drawback with this approach is that calibration of interest rate models does not involve the interest rate being modeled. Hence, calibrated models may not be good representations of interest rates and may not produce reliable derivative prices. To deal with the issue, we propose a time series modeling approach to analyze interest rates, specifically, the zero-coupon yield curves. In this approach, yield curves are modeled as functional data and we introduce models that are based on the well-known autoregressive model in time series analysis. The objective of this approach is to understand the dependency of the yield curves on historical data and to predict future yield curves before they are observed. The proposed models are illustrated and compared with the time series of US Treasury zero-coupon yield curves. We explore how individual models perform during different times in an economic cycle. We also propose a way to predict future caplet prices by combining yield curve prediction using functional time series models and historical implied volatilities of caplets. The time series approach that we propose are shown to work well against existing models such as the Hull-White model.
Interplay of attractive interactions and trap anisotropy in Bose-Einstein condensates [electronic resource]
Keywords: Applied Physics

We evaporatively cool attractively interacting bosonic 7Li in a quasi-one dimensional (quasi-1D) trap to well below the non-interacting particle condensation temperature for our trap but do not observe conventional Bose-Einstein condensation (BEC). Rather than the macroscopic occupation of a single quantum state, for our coldest clouds we observe densities far above the minimum required for quantum degeneracy and widths many times greater than the non-interacting and Gross-Pitaevskii (GP) predictions. We quantify the discrepancies, which together indicate the formation of clouds with multiply macroscopically occupied trap states. We hypothesize that the specific combination of a quasi-1D anisotropic trap and attractively interacting atoms might provide for many-body states that reside in manifolds of nearly degenerate states, which could inhibit conventional BEC. This idea is probed theoretically using the two-body interaction Hamiltonian to extend the single-mode many-body mean-field GP formalism to allow for atom scattering between two single-particle trap modes. We find that many odd-relative parity energy-adjacent single-particle state pairs exhibit sizable degenerate many-body eigenenergy fractions for atom numbers below the critical atom number at which attraction-induced collapse occurs. The sensitivity to state pair relative parity and our variational width analyses indicate, however, that one and two single-particle state models are ultimately insufficient for these systems. Mechanism-independent, such bright short coherence length matter-wave sources, analogous to superluminescent diodes, could prove useful in actualizing portable atom-based sensors.