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Reconciling Geodetic Strain and Seismicity Rate with Frequency-Magnitude Relation of the Largest Earthquakes
Get PDFThe aim of this thesis is to study how moment buildup rate on faults can be reconciled with moment release rate. We concentrate first on the Himalaya region and go on to look at faults worldwide. We first justify the extrapolation of GPS data in the Himalayan region over the approximate timescale of an earthquake cycle. To do this we show that GPS strain rates correlate with seismicity rates, and that the principal directions of strain found from GPS data are similar to those from earthquake moment tensors, showing that GPS data has been consistent at the timescale of earthquake strain-rate build-up, roughly 100-1000 years.
We next use geodetic data to show that the Main Himalayan Thrust (MHT) is locked from the surface to roughly 100 km north along its entire length, with no creeping patches. We also find the long-term slip rate on the fault, and these values agree with values from geomorphic studies, showing that here the tectonic regime has been stable with time, and most of the deformation is elastic. However, we also find a correspondence between the pattern of uplift rate predicted from the model and the topography, suggesting that a small amount of permanent deformation (10%) may occur, and again suggesting that the pattern of coupling has been stable with time.
We find the moment build-up rate on the MHT to be 15.1±1.0x1019 Nm/yr and compare this rate with the rate of moment release estimated from large earthquakes that have occurred on this fault in the past 1000 years. We use the conservation of moment principal to model the most likely maximum magnitude earthquake that needs to occur to balance the moment budget, and find that we need an earthquake of magnitude 9 or more with a recurrence time of roughly 800 years.
We extend this analysis to faults with no GPS data, and no long record of large earthquakes, by developing a method to find the expected maximum magnitude earthquake on faults assuming conservation of moment, and that the earthquakes follow the Gutenberg-Richter law. Our results compare well with historical catalogs where they are available.</p
Mechanisms Underlying Economic Choice
Get PDFThe current dissertation proposes three manners in which findings about the neuroscience of decision-making can inform traditional questions in economics that historically has been investigated using choice data alone, and without delineating the mechanism of choice.
The first chapter investigates the origins of a critical component of both economic and perceptual decision-making under uncertainty: the belief formation process. Most research has studied belief formation in economic and perceptual decision-making in isolation. One reason for this separate treatment may be the assumption that there are distinct psychological mechanisms that underlie belief formation in economic and perceptual decisions. An alternative theory is that there exists a common mechanism that governs belief formation in both domains. Here,we test this alternative theory by combining a novel computational modeling technique with two well-known experimental paradigms. I estimate a drift-diffusion model (DDM) and provide an analytical method to decode prior beliefs from DDM parameters. Subjects in our experiment exhibit strong extrapolative beliefs in both paradigms. In line with the common mechanism hypothesis, we find that a single computational model explains belief formation in both tasks, and that individual differences in belief formation are correlated across tasks. These results suggest that extrapolative beliefs in economic decision-making may stem from low-level automatic processes that also play a role in perceptual decision-making, and therefore might be difficult to suppress.
The second chapter investigates the role of the sex steroid hormone testosterone as a biological mediator that translates environmental changes into shifts in cognition, that influence decision-making. Correlational studies have linked testosterone with aggression and disorders associated with poor impulse control, but corresponding mechanisms are poorly understood and there is no evidence of causality. Building on a dual-process framework, I identify a mechanism for testosterone’s behavioral effects in humans: reducing cognitive reflection. In the largest testosterone administration study to date, 243 men received either testosterone or placebo and took the Cognitive Reflection Test (CRT) that estimated their capacity to override incorrect intuitive judgments with deliberate correct responses. Testosterone administration reduced CRT scores. The effect was robust to controlling for age, mood, math skills, treatment expectancy, and 14 other hormones. The effects were enhanced in subjects with high cortisol and estradiol levels. These findings suggest a unified mechanism underlying testosterone’s varied behavioral effects in humans and provide novel, clear, and testable predictions.
In the third chapter, I study dynamic unstructured bargaining with deadlines and one-sided private information about the amount available to share (the “pie size"). Using mechanism design theory, I show that given the players’ incentives, the equilibrium incidence of bargaining failures (“strikes”) should increase with the pie size, and I derive a condition under which strikes are efficient. In our setting, no equilibrium satisfies both equality and efficiency in all pie sizes. I derive two equilibria that resolve the trade-off between equality and efficiency by either favoring equality or favoring efficiency. Using a novel experimental paradigm, I confirm that strike incidence is decreasing in the pie size. Subjects reach equal splits in small pie games (in which strikes are efficient), while most payoffs are close to either the efficient or the equal equilibrium prediction when the pie is large. I employ a machine learning approach to show that bargaining process features recorded early in the game improve out of sample prediction of disagreements at the deadline. The process feature predictions are as accurate as predictions from pie sizes only, and adding process and pie data together improve predictions even more. As process data can be much richer than the series of cursor locations that we have used (for example, by including skin conductance, pupil dilation or facial expressions), better inference of outcome variables is likely feasible. Thus, if a policy maker or a mediator can access an independent measure of private information, an arbitration mechanism may allow boosting efficiency by taking this measurement into account.</p
Essays on Social Networks and Political Economy
Get PDFThis dissertation consists of two original studies in social networks and one original study in political economy. In the first two chapters, I study (i) how social networks form, and (ii) how economic agents optimize their behaviors for a given network structure. In the last chapter, I examine how election rules affect individual voting decisions and ultimate election outcomes.
In Chapter 1, "Social Network Formation and Strategic Interaction in Large Networks," I present a dynamic network formation model that aims to explain why some empirical degree distributions exhibit the increasing hazard rate property (IHRP). In my model, a sequentially arriving node forms a link with one existing node through a bilateral agreement. A newborn node prefers a highly linked node; however, the more links an existing node has, the more the marginal return from an additional link diminishes. I prove that the IHRP emerges if and only if the latter effect prevails over the former. I present two implications of the IHRP for strategic interactions in networks. First, when there is uncertainty about neighboring agents' connectivity, the IHRP guarantees that a unique Bayesian equilibrium exists in a network game with strategic complementarities. Second, the IHRP characterizes a monotone revenue-maximizing mechanism with allocative externalities.
In Chapter 2, "Monopoly Pricing and Diffusion of a (Social) Network Good," I present a model of dynamic pricing and diffusion of a network good sold by a monopolist. In the model, the network good is a subscription social network good. This means that in each period, each consumer has to pay a subscription price to use the good, and the utility derived from subscribing to the good increases as more of her neighboring consumers subscribe. Consumers myopically optimize their subscription decisions, and the monopolist chooses a sequence of subscription prices that maximizes his discounted sum of per-period profits. Three main results emerge. First, I characterize a unique steady state of the monopoly market. Second, I find that optimal sequences of subscription prices oscillate around the subscription price at the steady state as time passes. Third, I analyze how changes in the monopolist's discount factor and the density of the social network affect the subscription price, subscription rate, and deadweight loss at the steady state.
In Chapter 3, "A Model of Pre-Electoral Coalition Formation," I study how two different election rules, simple plurality (e.g., as in South Korea) and two-round runoff (e.g., as in France), affect political candidates’ incentives to form pre-electoral coalitions (PECs). In my model, three candidates compete for a single office, and two candidates can form a PEC. Since the candidates are both policy- and office-motivated, one candidate can incentivize the other candidate to withdraw his candidacy by choosing a joint policy platform. I find that PECs are more likely to form in plurality elections than in two-round runoff elections. I further examine how other electoral environments, such as ideological distance and pre-election polls, influence incentives to form PECs.</p
Rota-Baxter Algebras, Renormalization on Kausz Compactifications and Replicating of Binary Operads
Get PDFThis thesis is divided into two parts:
In the first part, we consider Rota-Baxter algebras of meromorphic forms with poles along a (singular) hypersurface in a smooth projective variety and the associated Birkhoff factorization for algebra homomorphisms from a commutative Hopf algebra. In the case of a normal crossings divisor, the Rota-Baxter structure simplifies considerably and the factorization becomes a simple pole subtraction. We apply this formalism to the unrenormalized momentum space Feynman amplitudes, viewed as (divergent) integrals in the complement of the determinant hypersurface. We lift the integral to the Kausz compactification of the general linear group, whose boundary divisor is normal crossings. We show that the Kausz compactification is a Tate motive and the boundary divisor is a mixed Tate configuration. The regularization of the integrals that we obtain differs from the usual renormalization of physical Feynman amplitudes, and in particular it gives mixed Tate periods in cases that have non-mixed Tate contributions in the usual form. This part is based on joint work with Matilde Marcolli (see (80)).
In the second part, we consider the notions of the replicators, including the duplicator and triplicator, of a binary operad. We show that taking replicators is in Koszul dual to taking successors in (9) for binary quadratic operads and is equivalent to taking the white product with certain operads such as Perm. We also relate the replicators to the actions of average operators. After the completion of this work (in 2012; see (85)), we realized that the closely related notions di-Var-algebra and tri-Var-algebra have been introduced independently in (48) (in 2011; see also (63; 64)) by Kolesnikov and his coauthors. In fact their notions also apply to not necessarily binary operads (64). In this regard, the second part of this thesis provides an alternative and more detailed treatment of these notations for binary operads. This part is based on joint work with Chengming Bai, Li Guo, and Jun Pei (see (85)).</p
Development of Zn-IV-Nitride Semiconductor Materials and Devices
Get PDF This thesis details explorations of the materials and device fabrication of Zn-IV-Nitride thin-films. Motivation in studying this materials series originates from its analgous properties to the III-Nitride semiconductor materials and its potential applications in photonic devices such as solar cells, light emitting diodes, and optical sensors. Building off of initial fabrication work from Coronel, Lahourcade et al., ZnSnxGe1-xN2 thin-films have shown to be a non-phase-segregating, tunable alloy series and a possible earth-abundant alternative to InxGa1-xN alloys. This thesis discusses further developments in fabrication of ZnSnxGe1-xN2 alloys by three-target co-sputtering and molecular beam epitaxy, and the resulting structural and optoelectronic characterization. Devices from these developed alloys are also highlighted.
Initial fabrication was based on the reactive radio-frequency (RF) sputtering technique and was limited to two-target sources and produced nanocrystalline films. Progression to three-target reactive RF co-sputtering for ZnSnxGe1-xN2 (x < 1) alloys is presented, where three-target co-sputtered alloys follow the structural and optoelectronic trends of the initial alloy series. However, three-target co-sputtering further enabled synthesis of alloys having < 10% atomic composition (x < 0.4) of tin, exhibiting non-degenerate doping. The electronic structure of sputtered thin-film surfaces for the alloy series were also characterized by photoelectron spectroscopy to measure their work functions and relative band alignment for device implementation.
Low electronic mobilities, degenerate carrier concentrations, and limited photoresponse may stem from the defective and nanocrystalline nature of the sputtered films. To improve crystalline quality, films were grown by molecular beam epitaxy (MBE). MBE ZnSnxGe1-xN2 films on sapphire and GaN were epitaxially grown, overall displaying single-crystalline quality films, higher electronic mobilities, and lower carrier concentrations. Througout experimentation, devices from both sputter deposited and MBE ZnSnxGe1-xN2 alloys films were constructed. Attempts at solid-state and electrochemical devices are described. Devices exhibited some photoresponse, providing a positive outlook for employment of ZnSnxGe1-xN2 alloys in solar cells or photon sensors.</p
Three Essays on Information Economics
Get PDFThe main theme of my thesis is how uncertainty affects behaviors. I explore how agents seek to resolve uncertainty in different environments. In Chapter 1, agents learn from the messages of informed experts in a signaling game. In Chapter 2, an agent learns about a fixed and uncertain physical environment through dynamic experimentation. In the last chapter, agents learn about others' preferences through the outcome of a central matching mechanism.
Motivated by the question of how opposing political candidates who are policy experts can communicate to voters in a way that helps them win the election, I study a delegation problem with two informed, self-interested agents. Agents make proposals before the decision maker decides to whom to delegate a task. The innovation is that there are multiple issues that the principal and agents care about, and the agents can be vague about any issue in their proposals. Intuition says that agents should be specific about the issues that they are trusted on and vague about other issues. I find the opposite: an agent is disadvantaged by revealing information about certain issues to the decision maker, those on which he is trusted by the principal on. The reason is that doing so enables his opponent to take advantage of this revealed information and undercut him. Essentially, when the principal is on an agent's side for some issue, that agent does not want to be specific, because it creates a visible target for his opponent to react to. He wants to be vague, because that allows the principal's ignorance about the optimal action create an insurmountable obstacle for his opponent. As a result, it is to an agent's advantage to be vague about the issue that he is trusted on.
The second chapter investigates the implication of biased updating in dynamic experimentation such as a firm's R&D process. People exhibit near miss effect during gambling. For example, if the first two wheels of a slot machine indicate a potential final outcome of jackpot but the last wheel indicates a loss, people are motivated to gamble more. An outcome that is close to a success but is still a failure is called a "near miss." In this chapter, I explain the near miss effect in a firm's repeated R&D process. There are two factors that sequentially affect the profitability of R&D, both of which are uncertain. First is whether the R&D team is skilled enough to make a technical breakthrough. If a breakthrough occurs, then a second factor comes into play, which is whether the market demand is high enough to make the product profitable. Moreover, good news for the first stage is a prerequisite for learning about the second stage. In each one of the infinite periods, the decision maker of the firm decides whether to involve in risky R&D and observe whether the outcome is a failure (no breakthrough), a success (with breakthrough and high market demand), or a near miss (with breakthrough but low market demand). I assume that the decision maker of the firm learns about the skill of the team properly, but when she updates about the market demand, she updates incorrectly and overweighs her prior. In particular, her posterior about the market demand is a convex combination of her prior and the Bayesian posterior. This bias affects the relative updating of the two factors, which gives rise to the near miss effect: after a near miss is observed, the decision maker values doing R&D more than before although she has received no payoff.
I show that if the decision maker is sufficiently biased and overweighs her prior enough, then she exhibits the near miss effect. I also compare the near miss effect for decision makers with different degrees of biases. As it turns out, the more biased a decision maker is, the more sever she exhibits the near miss effect. However, given the decision maker's belief about the two factors, the more biased she is, the less she values R&D. Consequently, the value of R&D is highest for a Bayesian.
In the last chapter, I study how well a centralized matching mechanism works when agents do not know others' preferences. I consider a standard two-sided marriage matching problem, except that agents only know their own preferences. Roth(1989) proved by an example the non-existence of a mechanism with at least one stable equilibria. In his proof, an agent is allowed to report a preference that is realized with ex ante zero probability, which violates the setup of a Bayesian game. Instead, by restricting agents to report only preferences with positive realization probabilities, I show that Roth's result still holds. More interestingly, as long as agents are allowed to form blocking pairs after a matching outcome is announced, the final outcome is always stable with respect to the true preferences. This means that even when the mechanism fails to produce a stable outcome, it can still release enough information for agents to initialize a blocking pair, which induces a stable outcome. </p
Electromyographic Signal Processing With Application To Spinal Cord Injury
Get PDFAn Electromyogram or Electromyographic (EMG) signal is the recording of the electrical activity produced by muscles. It measures the electric currents generated in muscles during their contraction. The EMG signal provides insight into the neural activation and dynamics of the muscles, and is therefore important for many different applications, such as in clinical investigations that attempt to diagnose neuromuscular deficiencies. In particular, the work in this thesis is motivated by rehabilitation for patients with spinal cord injury. The EMG signal is very important for researchers and practitioners to monitor and evaluate the effect of the rehabilitation training and the condition of muscles, as the EMG signal provides information that helps infer the neural activity in the spinal cord. Before the work in this thesis, EMG analysis required significant amounts of manual labeling of interesting signal features. The motivation of this thesis is to fully automate the EMG analysis tasks and yield accurate, consistent results.
The EMG signal contains multiple muscle responses. The difficulty in processing the EMG signal arises from the fact that the transient muscle response is a transient signal with unknown arrival time, unknown duration, and unknown shape. In addition, the EMG signal recorded from patients with spinal cord injury during rehabilitation is very different from the EMG signal of normal healthy people undergoing the same motions. For example, some of the muscle responses are very weak and thus hard to detect. Because of this, general EMG processing tools and methods are either not applicable or insufficient.
The primary contribution of this thesis is the development of a wavelet-based, double-threshold algorithm for the detection of transient peaks in the EMG signal. The application of wavelet transform in the detection of transient signals has been studied extensively and employed successfully. However, most of the theories assume certain knowledge about the shapes of the transient signals, which makes it hard to be generalized to the transient signals with arbitrary shapes. The proposed detection scheme focuses on the more fundamental feature of most transient signals (in particular the EMG signal): peaks, instead of the shapes. The continuous wavelet transform with Mexican Hat wavelet is employed. This thesis theoretically derived a framework for selecting a set of scales based on the frequency domain information. Ridges are identified in the time-scale space to combine the wavelet coefficients from different scales. By imposing two thresholds, one on the wavelet coefficient and one on the ridge length, the proposed detection scheme can achieve both high recall and high precision. A systematic approach for selecting the optimal parameters via simulation is proposed and demonstrated. Comparing with other state-of-the-art detection methods, the proposed method in this thesis yields a better detection performance, especially in the low Signal-to-Noise-Ratio (SNR) environment.
Based on the transient peak detection result, the EMG signal is further segmented and classified into various groups of monosynaptic Motor Evoked Potentials (MEPs) and polysynaptic MEPs using techniques stemming from Principal Component Analysis (PCA), hierarchical clustering, and Gaussian mixture model (GMM). A theoretical framework is proposed to segment the EMG signal based on the detected peaks. The scale information of the detected peak is used to derive a measure for its effective support. Several different techniques have been adapted together to solve the clustering problem. An initial hierarchical clustering is first performed to obtain most of the monosynaptic MEPs. PCA is used to reduce the number of features and the effect of the noise. The reduced feature set is then fed to a GMM to further divide the MEPs into different groups of similar shapes. The method of breaking down a segment of multiple consecutive MEPs into individual MEPs is derived.
A software with graphic user interface has been implemented in Matlab. The software implements the proposed peak detection algorithm, and enables the physiologists to visualize the detection results and modify them if necessary. The solutions proposed in this thesis are not only helpful to the rehabilitation after spinal cord injury, but applicable to other general processing tasks on transient signals, especially on biological signals.</p
Formation and Diagenesis of Sedimentary Rocks in Gale Crater, Mars
Get PDFThe history of surface processes on Mars is recorded in the sedimentary rock record. Sedimentary rock layers exposed in Gale Crater on the modern crater floor (Aeolus Palus) and on Mount Sharp (Aeolus Mons), which hosts one of the more complete records of transitions between major mineralogical eras on Mars, have been investigated by the Mars Science Laboratory Curiosity rover since landing in August 2012. This dissertation focuses on the formation and diagenesis of the sedimentary rocks in Gale crater in order to assess the compositional diversity of the volcanic sources around Gale crater, the effects of transport processes on the sediment grains, and the volumes and geochemistry of water that transported and cemented the sediments. The first study uses orbital mapping of a distinctive cemented boxwork layer on Mount Sharp to constrain a minimum volume of groundwater available to form this layer, 1 km above the modern floor of Gale, with implications for the formation of Mount Sharp. The other three studies use Curiosity rover imagery and geochemical data to investigate sedimentary rocks in Aeolus Palus and at the base of Mount Sharp. The second study identifies and describes diagenetic synaeresis cracks in the Sheepbed mudstone, at the lowest elevation in Aeolus Palus, with implications for the duration of water saturation of these lake sediments. The third and fourth studies identify and explain geochemical trends in the fluvio-deltaic Bradbury group, the Murray mudstone formation, and the eolian Stimson sandstone, focusing on geochemical diversity in the source regions for each of these units and how different depositional processes are reflected in the geochemical data. The sedimentary system in Gale crater has changed our understanding of Mars by expanding the known variety of igneous rocks, increasing estimates of the longevity of surface water lakes, and showing that there were once habitable environments on our neighboring planet
The Innate Immune System in Dendritic Cell-Targeted Lentiviral Vector Immunization and Cell-to-Cell Transmission of HIV-1
Get PDFDendritic cells (DCs) are the sentinels of the immune system, and thus specialized in transporting foreign antigen to T cells and initiating activation of innate and adaptive immune responses. In this work, we first explore how DCs sense viral pathogens and stimulate antigen-specific T cell responses. In particular, we find the DC-targeting HIV-1 derived lentiviral vector (LV) is a potent T cell vaccine in vivo. However, the exact mechanism behind such efficient immunization is not clear. Interestingly, we find that DC activation is triggered by cellular DNA packaged in LVs and at least partially dependent on the STING protein. Innate immune activation is independent of MyD88, TRIF and IPS-1, ruling out an involvement of Toll-like receptors or RIG-I-like receptor signaling. Further, we find that antigenic protein delivered in viral particles via pseudotransduction is sufficient to stimulate an antigen-specific immune response. Delivery of the viral genome encoding the antigen increases the magnitude of this response in vivo, but is irrelevant in vitro. Thus, pseudotransduction, genomic transduction, and STING-mediated activation thus collaborate to make the DC-targeted LV a uniquely powerful immunogen. In addition, we explore how DCs mediate HIV-1 infection of T cells via cell-to-cell infection. In particular, we assess how DC-to-T cell transmission of HIV-1 allows for a concentrated amount of virus to be directed to an uninfected T cell. We report that DCs amplify the efficiency of T cell infection, resulting in anti-retroviral drug insensitivity compared to T cell infection in the absence of DCs. The DC-mediated amplification and drug-insensitivity of T cell infection are both entirely dependent on physical cellular interactions. Further, we find that the input of a virus is important to the drug insensitivity of DC-to-T cell infection, but not DC-free T cell infection. Thus, we have studied two separate roles of DCs: initiating immune responses to LVs and mediating transmission of infectious HIV-1. The study of these roles is important to discovering novel immune adjuvants and identifying targeted therapeutics to inhibit viral dissemination
Photochemical Strategies to Decage Organic Compounds
Get PDFThis dissertation primarily describes new photochemical decaging systems that are activated by visible light. Such systems are expected to be useful as chemical biology tools or as drug delivery systems in a therapeutic context. A primary motivation for the development of these systems is for the treatment of traumatic brain injury, where a decaging strategy would require activation by low energy near-infrared light. Since most photochemical reactions are initiated using ultraviolet light, a primary challenge in developing these systems is overcoming the low energy efficiency of typical photochemical processes. Initial model systems are designed to address this challenge through use of the photoacidic effect. While many hydroxyaromatic compounds are known to become much more acidic in their excited state, the effect has never been utilized to accelerate an acid-catalyzed chemical reaction. Investigations are carried out in Chapter 2 to probe for the possibility of this unprecedented photochemistry. Ultimately, the results suggest that the acid-catalyzed decaging processes are too slow to be useful in a photochemical context. This finding led to the development of decaging strategies that utilize a phototriggered approach. In Chapter 2, a system is described where decaging occurs through rapid lactonization of a photogenerated hydroquinone. Formation of the hydroquinone results from an intramolecular photoreduction of the benzoquinone due to activation by violet light. Detailed mechanistic studies carried out on this system ultimately establish the importance of the triplet state in the overall reaction. While most benzoquinones form the triplet with unit efficiency, the system studied here forms the triplet in less than 10% yield. However, when the triplet is formed, it proceeds cleanly to products with high efficiency. Although the benzoquinone system has been useful for mechanistic studies, its application as a therapeutic decaging strategy has been challenging. Efforts to extend the wavelength toward the near-infrared have led to loss in photochemical reactivity. Ultimately, this challenge was overcome through the use of methylene blue. Methylene blue is a common organic dye that is activated by red light and undergoes photoreduction to a colorless form, similar to the benzoquinone systems. In Chapter 4, derivatives of methylene blue that are capable of undergoing photoreductive cyclization are designed and synthesized. Ultimately, these systems are found to be capable of rapidly decaging alcohols using red light