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    Future of Earthquake Early Warning: Quantifying Uncertainty and Making Fast Automated Decisions for Applications

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    Earthquake early warning (EEW) systems have been rapidly developing over the past decade. Japan Meteorological Agency (JMA) has an EEW system that was operating during the 2011 M9 Tohoku earthquake in Japan, and this increased the awareness of EEW systems around the world. While longer-time earthquake prediction still faces many challenges to be practical, the availability of shorter-time EEW opens up a new door for earthquake loss mitigation. After an earthquake fault begins rupturing, an EEW system utilizes the first few seconds of recorded seismic waveform data to quickly predict the hypocenter location, magnitude, origin time and the expected shaking intensity level around the region. This early warning information is broadcast to different sites before the strong shaking arrives. The warning lead time of such a system is short, typically a few seconds to a minute or so, and the information is uncertain. These factors limit human intervention to activate mitigation actions and this must be addressed for engineering applications of EEW. This study applies a Bayesian probabilistic approach along with machine learning techniques and decision theories from economics to improve different aspects of EEW operation, including extending it to engineering applications. Existing EEW systems are often based on a deterministic approach. Often, they assume that only a single event occurs within a short period of time, which led to many false alarms after the Tohoku earthquake in Japan. This study develops a probability-based EEW algorithm based on an existing deterministic model to extend the EEW system to the case of concurrent events, which are often observed during the aftershock sequence after a large earthquake. To overcome the challenge of uncertain information and short lead time of EEW, this study also develops an earthquake probability-based automated decision-making (ePAD) framework to make robust decision for EEW mitigation applications. A cost-benefit model that can capture the uncertainties in EEW information and the decision process is used. This approach is called the Performance-Based Earthquake Early Warning, which is based on the PEER Performance-Based Earthquake Engineering method. Use of surrogate models is suggested to improve computational efficiency. Also, new models are proposed to add the influence of lead time into the cost-benefit analysis. For example, a value of information model is used to quantify the potential value of delaying the activation of a mitigation action for a possible reduction of the uncertainty of EEW information in the next update. Two practical examples, evacuation alert and elevator control, are studied to illustrate the ePAD framework. Potential advanced EEW applications, such as the case of multiple-action decisions and the synergy of EEW and structural health monitoring systems, are also discussed.</p

    Phospholipids and a Protein-Conducting Channel Regulate Cotranslational Protein Targeting

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    Signal recognition particle (SRP) and signal recognition particle receptor (SR) are evolutionarily conserved GTPases that deliver secretory and membrane proteins to the protein-conducting channel Sec61 complex in the lipid bilayer of the endoplasmic reticulum in eukaryotes or the SecYEG complex in the inner membrane of bacteria. Unlike the canonical Ras-type GTPases, SRP and SR are activated via nucleotide-dependent heterodimerization. Upon formation of the SR•SRP targeting complex, SRP and SR undergo a series of discrete conformational changes that culminate in their reciprocal activation and hydrolysis of GTP. How the SR•SRP GTPase cycle is regulated and coupled to the delivery of the cargo protein to the protein-conducting channel at the target membrane is not well-understood. Here we examine the role of the lipid bilayer and SecYEG in regulation of the SRP-mediated protein targeting pathway and show that they serve as important biological cues that spatially control the targeting reaction. In the first chapter, we show that anionic phospholipids of the inner membrane activate the bacterial SR, FtsY, and favor the late conformational states of the targeting complex conducive to efficient unloading of the cargo. The results of our studies suggest that the lipid bilayer acts as a spatial cue that weakens the interaction of the cargo protein with SRP and primes the complex for unloading its cargo onto SecYEG. In the second chapter, we focus on the effect of SecYEG on the conformational states and activity of the targeting complex. While phospholipids prime the complex for unloading its cargo, they are insufficient to trigger hydrolysis of GTP and the release of the cargo from the complex. SecYEG modulates the conformation of the targeting complex and triggers the GTP hydrolysis from the complex, thus driving the targeting reaction to completion. The results of this study suggest that SecYEG is not a passive recipient of the cargo protein; rather, it actively releases the cargo from the targeting complex. Together, anionic phospholipids and SecYEG serve distinct yet complementary roles. They spatially control the targeting reaction in a sequential manner, ensuring efficient delivery and unloading of the cargo protein. In the third chapter, we reconstitute the transfer reaction in vitro and visualize it in real time. We show that the ribosome-nascent chain complex is transferred to SecYEG via a stepwise mechanism with gradual dissolution and formation of the contacts with SRP and SecYEG, respectively, explaining how the cargo is kept tethered to the membrane during the transfer and how its loss to the cytosol is avoided. In the fourth chapter, we examine interaction of SecYEG with secretory and membrane proteins and attempt to address the role of a novel insertase YidC in this interaction. We show that detergent-solubilized SecYEG is capable of discriminating between the nascent chains of various lengths and engages a signal sequence in a well-defined conformation in the absence of accessory factors. Further, YidC alters the conformation of the signal peptide bound to SecYEG. The results described in this chapter show that YidC affects the SecYEG-nascent chain interaction at early stages of translocation/insertion and suggest a YidC-facilitated mechanism for lateral exit of transmembrane domains from SecYEG into the lipid bilayer. </p

    Interpretation of Lunar Topography: Impact Cratering and Surface Roughness

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    This work seeks to understand past and present surface conditions on the Moon using two different but complementary approaches: topographic analysis using high-resolution elevation data from recent spacecraft missions and forward modeling of the dominant agent of lunar surface modification, impact cratering. The first investigation focuses on global surface roughness of the Moon, using a variety of statistical parameters to explore slopes at different scales and their relation to competing geological processes. We find that highlands topography behaves as a nearly self-similar fractal system on scales of order 100 meters, and there is a distinct change in this behavior above and below approximately 1 km. Chapter 2 focuses this analysis on two localized regions: the lunar south pole, including Shackleton crater, and the large mare-filled basins on the nearside of the Moon. In particular, we find that differential slope, a statistical measure of roughness related to the curvature of a topographic profile, is extremely useful in distinguishing between geologic units. Chapter 3 introduces a numerical model that simulates a cratered terrain by emplacing features of characteristic shape geometrically, allowing for tracking of both the topography and surviving rim fragments over time. The power spectral density of cratered terrains is estimated numerically from model results and benchmarked against a 1-dimensional analytic model. The power spectral slope is observed to vary predictably with the size-frequency distribution of craters, as well as the crater shape. The final chapter employs the rim-tracking feature of the cratered terrain model to analyze the evolving size-frequency distribution of craters under different criteria for identifying "visible" craters from surviving rim fragments. A geometric bias exists that systematically over counts large or small craters, depending on the rim fraction required to count a given feature as either visible or erased

    The C. elegans ALA Neuron: Its Transcriptions and Roles in Inducing Sleep

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    A long-standing yet to be accomplished task in understanding behavior is to dissect the function of each gene involved in the development and function of a neuron. The C. elegans ALA neuron was chosen in this study for its known function in sleep, an ancient but less understood animal behavior. Single-cell transcriptome profiling identified 8,133 protein-coding genes in the ALA neuron, of which 57 are neuropeptide-coding genes. The most enriched genes are also neuropeptides. In combination with gain-of-function and loss-of-function assays, here I showed that the ALA-enriched FMRFamide neuropeptides, FLP-7, FLP-13, and FLP-24, are sufficient and necessary for inducing C. elegans sleep. These neuropeptides act as neuromodulators through GPCRs, NPR-7, and NPR-22. Further investigation in zebrafish indicates that FMRFamide neuropeptides are sleep-promoting molecules in animals. To correlate the behavioral outputs with genomic context, I constructed a gene regulatory network of the relevant genes controlling C. elegans sleep behavior through EGFR signaling in the ALA neuron. First, I identified an ALA cell-specific motif to conduct a genome-wide search for possible ALA-expressed genes. I then filtered out non ALA-expressed genes by comparing the motif-search genes with ALA transcriptomes from single-cell profiling. In corroborating with ChIP-seq data from modENCODE, I sorted out direct interaction of ALA-expressed transcription factors and differentiation genes in the EGFR sleep regulation pathway. This approach provides a network reference for the molecular regulation of C. elegans sleep behavior, and serves as an entry point for the understanding of functional genomics in animal behaviors

    Vibrational Pooling and Constrained Equilibration on Surfaces

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    In this thesis, we provide a statistical theory for the vibrational pooling and fluorescence time dependence observed in infrared laser excitation of CO on an NaCl surface. The pooling is seen in experiment and in computer simulations. In the theory, we assume a rapid equilibration of the quanta in the substrate and minimize the free energy subject to the constraint at any time t of a fixed number of vibrational quanta N(t). At low incident intensity, the distribution is limited to one- quantum exchanges with the solid and so the Debye frequency of the solid plays a key role in limiting the range of this one-quantum domain. The resulting inverted vibrational equilibrium population depends only on fundamental parameters of the oscillator (ωe and ωeχe) and the surface (ωD and T). Possible applications and relation to the Treanor gas phase treatment are discussed. Unlike the solid phase system, the gas phase system has no Debye-constraining maximum. We discuss the possible distributions for arbitrary N-conserving diatom-surface pairs, and include application to H:Si(111) as an example. Computations are presented to describe and analyze the high levels of infrared laser-induced vibrational excitation of a monolayer of absorbed 13CO on a NaCl(100) surface. The calculations confirm that, for situations where the Debye frequency limited n domain restriction approximately holds, the vibrational state population deviates from a Boltzmann population linearly in n. Nonetheless, the full kinetic calculation is necessary to capture the result in detail. We discuss the one-to-one relationship between N and γ and the examine the state space of the new distribution function for varied γ. We derive the Free Energy, F = NγkT − kTln(&#8721;Pn), and effective chemical potential, μn ≈ γkT, for the vibrational pool. We also find the anti correlation of neighbor vibrations leads to an emergent correlation that appears to extend further than nearest neighbor.</p

    Tools for the Study of Dynamical Spacetimes

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    This thesis covers a range of topics in numerical and analytical relativity, centered around introducing tools and methodologies for the study of dynamical spacetimes. The scope of the studies is limited to classical (as opposed to quantum) vacuum spacetimes described by Einstein's general theory of relativity. The numerical works presented here are carried out within the Spectral Einstein Code (SpEC) infrastructure, while analytical calculations extensively utilize Wolfram's Mathematica program. We begin by examining highly dynamical spacetimes such as binary black hole mergers, which can be investigated using numerical simulations. However, there are difficulties in interpreting the output of such simulations. One difficulty stems from the lack of a canonical coordinate system (henceforth referred to as gauge freedom) and tetrad, against which quantities such as Newman-Penrose Psi_4 (usually interpreted as the gravitational wave part of curvature) should be measured. We tackle this problem in Chapter 2 by introducing a set of geometrically motivated coordinates that are independent of the simulation gauge choice, as well as a quasi-Kinnersley tetrad, also invariant under gauge changes in addition to being optimally suited to the task of gravitational wave extraction. Another difficulty arises from the need to condense the overwhelming amount of data generated by the numerical simulations. In order to extract physical information in a succinct and transparent manner, one may define a version of gravitational field lines and field strength using spatial projections of the Weyl curvature tensor. Introduction, investigation and utilization of these quantities will constitute the main content in Chapters 3 through 6. For the last two chapters, we turn to the analytical study of a simpler dynamical spacetime, namely a perturbed Kerr black hole. We will introduce in Chapter 7 a new analytical approximation to the quasi-normal mode (QNM) frequencies, and relate various properties of these modes to wave packets traveling on unstable photon orbits around the black hole. In Chapter 8, we study a bifurcation in the QNM spectrum as the spin of the black hole a approaches extremality.</p

    Detecting Actions of Fruit Flies

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    In this thesis we describe a system that tracks fruit flies in video and automatically detects and classifies their actions. We introduce Caltech Fly-vs-Fly Interactions, a new dataset that contains hours of video showing pairs of fruit flies engaging in social interactions, and is published with complete expert annotations and articulated pose trajectory features. We compare experimentally the value of a frame-level feature representation with the more elaborate notion of bout features that capture the structure within actions. Similarly, we compare a simple sliding window classifier architecture with a more sophisticated structured output architecture, and find that window based detectors outperform the much slower structured counterparts, and approach human performance. In addition we test the top performing detector on the CRIM13 mouse dataset, finding that it matches the performance of the best published method. </p

    Observational and Theoretical Advances in Cosmological Foreground Emission

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    Observational and theoretical work towards the separation of foreground emission from the cosmic microwave background is described. The bulk of this work is in the design, construction, and commissioning of the C-Band All-Sky Survey (C-BASS), an experiment to produce a template of the Milky Way Galaxy's polarized synchrotron emission. Theoretical work is the derivation of an analytical approximation to the emission spectrum of spinning dust grains. The performance of the C-BASS experiment is demonstrated through a preliminary, deep survey of the North Celestial Pole region. A comparison to multiwavelength data is performed, and the thermal and systematic noise properties of the experiment are explored. The systematic noise has been minimized through careful data processing algorithms, implemented both in the experiment's Field Programmable Gate Array (FPGA) based digital backend and in the data analysis pipeline. Detailed descriptions of these algorithms are presented. The analytical function of spinning dust emission is derived through the application of careful approximations, with each step tested against numerical calculations. This work is intended for use in the parameterized separation of cosmological foreground components and as a framework for interpreting and comparing the variety of anomalous microwave emission observations.</p

    Experimental and Theoretical Studies of Notch Signaling-Mediated Spatial Pattern

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    Notch signaling acts in many diverse developmental spatial patterning processes. To better understand why this particular pathway is employed where it is and how downstream feedbacks interact with the signaling system to drive patterning, we have pursued three aims: (i) to quantitatively measure the Notch system's signal input/output (I/O) relationship in cell culture, (ii) to use the quantitative I/O relationship to computationally predict patterning outcomes of downstream feedbacks, and (iii) to reconstitute a Notch-mediated lateral induction feedback (in which Notch signaling upregulates the expression of Delta) in cell culture. The quantitative Notch I/O relationship revealed that in addition to the trans-activation between Notch and Delta on neighboring cells there is also a strong, mutual cis-inactivation between Notch and Delta on the same cell. This feature tends to amplify small differences between cells. Incorporating our improved understanding of the signaling system into simulations of different types of downstream feedbacks and boundary conditions lent us several insights into their function. The Notch system converts a shallow gradient of Delta expression into a sharp band of Notch signaling without any sort of feedback at all, in a system motivated by the Drosophila wing vein. It also improves the robustness of lateral inhibition patterning, where signal downregulates ligand expression, by removing the requirement for explicit cooperativity in the feedback and permitting an exceptionally simple mechanism for the pattern. When coupled to a downstream lateral induction feedback, the Notch system supports the propagation of a signaling front across a tissue to convert a large area from one state to another with only a local source of initial stimulation. It is also capable of converting a slowly-varying gradient in parameters into a sharp delineation between high- and low-ligand populations of cells, a pattern reminiscent of smooth muscle specification around artery walls. Finally, by implementing a version of the lateral induction feedback architecture modified with the addition of an autoregulatory positive feedback loop, we were able to generate cells that produce enough cis ligand when stimulated by trans ligand to themselves transmit signal to neighboring cells, which is the hallmark of lateral induction

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