VictorJuiz/thesis huggingface dataset:
On adjectival comparatives [electronic resource]
Keywords: Linguistics.

The syntax and semantics of adjectival comparatives like (1a) are complicated matters that have concerned both syntacticians and semanticists for at least 100 years. (1) a. Orcutt is taller than Smith (is) (1) b. The maximal degree of height Orcutt possesses is greater than the maximal degree of height Smith possesses It is generally agreed that (1a) is a suitable paraphrase of the meaning of (1b), which suggests, both implicitly and explicitly, that any formal syntactico-semantic analysis of adjectival comparatives should make reference to (at least) the notions of degrees, scales, and measures. The path I will pursue in this dissertation takes each of the aforementioned concepts seriously but moves away from standardly assumed degree-based analyses like Seuren (1973), von Stechow (1984), Heim (1985), Kennedy (1997) and Heim (2006) (to name just a few) to a more Cresswellilan-one (Cresswell 1976). This might seem odd, if only because recent work like Kennedy (1997) can also be understood in a Cresswellilan-light. However, there are many aspects of Cresswell's (1976) proposal--philosophical and formal--and in the work presented here, degrees themselves will not be understood as proper objects in my semantic ontology. If degrees exist at all, they will be understood as real numbers necessary only when considering a small sub-class of comparative constructions. I will argue that, in making such a move, one gets a better and more general treatment of the syntax and semantics of adjectival comparatives in the form of, what I take to be at least, a transparent albeit Spartan semantic representation language that makes no use of various misbehaved covert operators at the level of logical form that are traditionally present in the various semantic analysis of adjectival comparatives considered here. I will show that, even under the assumption of such minimal representations, my analysis gets the semantic facts involving adjectival comparatives right.
On symplectic homology of the complement of a positive normal crossing divisor in a projective variety [electronic resource]
Keywords: Mathematics.

This dissertation studies how symplectic homology of the complement of the smooth zero set $D$ of a section of a positive line bundle $\cL$ over a projective variety $(X, J)$ changes as $D$ degenerates to a normal crossing divisor $D_{\mbox{sing}}$ with two smooth connected components. By analyzing the pluri-subharmonic functions obtained from a metric on $\cL$, we show that the change in the Weinstein structure of the complement is characterized by handle removals along the unstable submanifolds of critical points in a small neighborhood of the set of singular points of $D_{\mbox{sing}}.$ Parallel to work by Bourgeois-Eckholm-Eliashberg (\cite{BEE}), we construct a chain complex from the removed unstable submanifolds such that its homology completes the Viterbo transfer map in a long exact sequence. The effect of divisor degeneration on symplectic homology of the complement is then essentially reflected by the $A_\infty$ structure of a collection of Lagrangian spheres on $D$, which are the boundary at infinity of the removed unstable submanifolds.
On the shape of a high-dimensional random lattice [electronic resource]
Keywords: Mathematics.

The statistics concerning lattices in high dimensions (call "the geometry of numbers" in the literature) used to be studied intensively in the mid-20th century, especially by C.A. Rogers and Wolfgang Schmidt. By perhaps an accident of history, it has become forgotten by mathematicians for almost 50 years. Yet there is still plenty of wonderful mathematics left there to develop, and furthermore, recently people in various sectors — computer science, cryptography, number theory, and even dynamics — are starting to realize the need and benefits of understanding high-dimensional lattices and related topics. This thesis is largely in three parts. In Chapter 1, we give an exposition on the Rogers integration formula and its variants, the main technical device in the study of high-dimensional lattices. In Chapter 2, inspired by the ideas of Schmidt, we prove that the lengths of the first O(n^(1/2)) shortest vectors of an n-dimensional random lattice exhibit a Poisson distribution as n → ∞, improving a recent result of Sodergren. In Chapters 3 and 4, we prove a few previously unknown facts on the statistics of the LLL bases that help answer a few questions that have been raised regarding the peculiar behavior of the LLL algorithm, and then present an experimental result that supports our theoretical conclusions and suggests where future research could be headed to.
On-chip generation of non-classical states of light via quantum dots coupled to photonic crystal nanocavities [electronic resource]
Keywords: Electrical Engineering.

Cavity quantum electrodynamics has enabled unprecedented control over the fundamental interaction of light and matter. New types of on-chip optical technologies that exploit the quantum mechanical nature of light have the potential to open up an entirely new direction for semiconductor devices, combining the fine control of cavity quantum electrodynamics with the convenience of the semiconductor platform. However, the practical implementation of quantum technologies on a chip will require an on-demand source of non-classical states of light, such as pulses with a well-defined number of photons. In this dissertation, I present the development of a semiconductor non-classical light source based on coupling artificial atoms (quantum dots) to small mode-volume optical resonators (photonic crystal nanocavities). The strong coupling we achieve between a quantum dot and a photonic crystal nanocavity produces a hybridization of the quantum dot excitation with the optical field confined inside the cavity. I demonstrate how the rich energy structure exhibited by this system enables us to control the statistics of photons in a transmitted laser beam, moving between sub-Poissonian and super-Poissonian on demand. I also discuss how these non-classical states of light can be characterized by examining the higher-order photon correlations measured via a generalized Hanbury Brown and Twiss type interferometer. Furthermore, I show that by detuning the quantum dot resonance away from the cavity resonance, we can improve both the purity and the efficiency of single-photon generation in this system. This approach allows us to combine the high fidelity of single quantum emitters with the high repetition rate and accessibility of optical cavities. Finally, I explore methods for scaling up this system by fabricating multiple photonic crystal nanocavities in such a way that they couple to each other. I present the experimental realization of a photonic molecule (two coupled photonic crystal nanocavities) that is strongly coupled to a quantum dot contained inside one of the component cavities. I also examine the fabrication of coupled optical cavity arrays in this photonic crystal platform. Our experimental findings demonstrate that the coupling between the cavities is significantly larger than the fabrication-induced disorder in the cavity frequencies. Satisfying this condition is necessary for using such cavity arrays to generate strongly correlated photons, which could potentially be used for the quantum simulation of many-body systems.
Online allocation rules for display advertising [electronic resource]
Keywords: Management Science and Engineering.

Efficient allocation of impressions to advertisers in display advertising has a significant impact on advertisers' utility and the browsing experience of users. The problem becomes particularly challenging in the presence of advertisers with limited budgets as this creates a complex interaction among advertisers in the optimal impression assignment. In this thesis, we study online impression allocation in display advertising with budgeted advertisers. That is, upon arrival of each impression, cost and revenue vectors are revealed and the impression should be assigned to an advertiser almost immediately. Without any assumption on the distribution/arrival of impressions, we propose a framework to capture the risk to the ad network for each possible allocation; impressions are allocated to advertisers such that the risk of ad network is minimized. In practice, this translates to starting with an initial estimate of dual prices and updating them according to the belief of the ad network toward the future demand and remaining budgets. We apply our algorithms to a real data set, and we empirically show that Kullback-Leibler divergence risk measure has the best performance in terms of revenue and balanced budget delivery. Moreover, we address many practical challenges such as delay, unknown arrival rate, and frequency capping.
Operando X-ray photoelectron spectroscopy investigation of ceria/gas electrochemical interfaces [electronic resource]
Keywords: Applied Physics.

At solid-gas electrochemical interfaces, gas molecules interact dynamically with surface ions and electrons. A fundamental understanding of the technologically important interfaces can lead to better fuel cells and electrolyzers. In the bulk of typical oxygen-ion-conducting solids, oxygen vacancies and mobile electrons migrate under the influence of concentration and electrostatic potential gradients. Similarly, at gas-solid interfaces, these charge carriers migrate across an electrochemical double layer. The two-way traffic of ions and electrons contrasts sharply with conventional metal-based electrocatalysis, in which only electrons are transferred. This type of ion insertion reaction is ubiquitous in energy conversion and storage devices, such as lithium ion batteries, water-splitting membranes and solid oxide fuel cells. CeO2-[delta] (ceria) is a model oxygen-ion-conducting electrode, which is commonly employed to catalyze H2 oxidation and H2O dissociation reactions, as well as CO oxidation and CO2 dissociation reactions. In my thesis studies, I developed synchrotron-based ambient pressure X-ray photoelectron spectroscopy to characterize the electrochemical double layer under reaction conditions. Concentrations and binding energy of oxygen ions, localized electrons, and surface reaction intermediates were quantified using core level and valence band X-ray photoelectron spectroscopy as a function of electrochemical overpotentials. These measurements reveal that localized electrons and oxygen vacancies segregate persistently from the bulk to the surface, resulting in concentrations up to four orders of magnitude greater on the surface than in the bulk. Under water splitting conditions, H2O molecules incorporate rapidly into surface oxygen vacancies. Spectroscopy and electrochemistry results suggest that the electron transfer between Ce 4f states and OH adsorbates is rate determining. Under CO oxidation and CO2 dissociation conditions, on the other hand, carbonate is the stable adsorbate. The larger footprint of carbonate relative to hydroxyl adsorbate gives rise to adsorbate-adsorbate interactions, resulting in a coverage-dependent reaction pathway. Lastly, measurement of surface dipole potential energy in both cases reveals intrinsic dipole moments of adsorbates as the origin of electrostatic potential gradient near the surface. Combined, these in-situ investigations unravel the electrochemical reaction pathway, particularly the role of point defects at ceria/gas interfaces, and establish a rational path towards enhancing the efficacy of oxide electrocatalysts.
Optical absorption control in two-dimensional materials with nanophotonic structures [electronic resource]
Keywords: Electrical Engineering.

We investigate the control of optical absorption in two-dimensional materials such as graphene and monolayer molybdenum disulfide (MoS2) by the use of nanophotonic structures. Why do we care? For two reasons: speed and energy efficiency. Modern societies run on computers, and these computers use a huge amount of energy. The less electricity or light that needs to move to carry information from one place to another, the faster and more energy-efficient the transfer of that information can be. Electronic circuits can only operate at the highest speeds when they're very small (much smaller than optical wavelengths), and because the chip designers have already hit the wall on Moore's Law they can't get any smaller with silicon. So next-generation electronics designers are looking for new materials -- and in particular, there has been huge interest in atomically-thin materials such as graphene and MoS2. The excellent electronic, mechanical, and thermal properties of graphene (a layer of carbon one atom thick) make it a particularly attractive material for high speed opto-electronics. However, it's single-pass optical absorption is low. To use graphene for a high-efficiency photodetector or modulator, we need to increase the absorption to 100%. This thesis presents two schemes for achieving total absorption in graphene. On the other hand, when we consider solar photovoltaic energy generation speed isn't a factor, but energy efficiency most certainly is: we want to absorb as much of the light as we can, preferably using as small of a device as we can. (In retrospect, it's obvious why 70's-80's solar never took off: the panels were simply too big and ugly!) For this task, we turn to MoS2, which has a direct bandgap (important for making a solar cell), and has its band edge at the red end of the spectrum, allowing it to absorb throughout the visible. This thesis discusses the nanophotonic design rules to make an optimized broadband absorption in atomically thin layers such as MoS2.
Optical coherence tomography endoscope design and complementary image reconstruction techniques for bladder cancer management [electronic resource]
Keywords: Electrical Engineering.

Bladder cancer is the most costly cancer to treat as the high rate of recurrence necessitates lifelong surveillance. White light cystoscopy (WLC) — the standard tool used for diagnosis and surveillance — has three limitations, which reduce the effectiveness and efficiency of managing patients with recurrent bladder cancer. First, WLC cannot accurately detect all tumors, causing some to go untreated. Second, WLC cannot gauge the penetration depth of tumors, an important factor for determining the course of treatment. This means that any detected lesions must be biopsied in a more costly and risky follow-up procedure. Third, it is difficult to review cystoscopy images, making it easy to overlook signs of cancer due to workflow challenges or insufficient annotations. To overcome these limitations, I developed novel techniques to improve cystoscopy examinations. Specifically, I developed a miniaturized, rapid-scanning optical coherence tomography (OCT) endoscope that can augment WLC during clinical examinations. OCT is a promising complementary imaging technique whose ability to visualize the subsur- face appearance of the bladder wall reveals early stage tumors better than WLC alone and makes it possible to stage cancers. Additionally, to improve the review of the cystoscopy data, I developed techniques that can enable a more comprehensive review among and be- tween WLC and OCT imaging data. These techniques include (1) a volumetric mosaicing algorithm to extend the field of view of OCT, (2) 3D reconstruction technique to generate models with the shape and appearance of the bladder, and (3) a registration approach that registers OCT data to the 3D bladder model. Taken together, the new OCT endoscope and image reconstruction algorithms I describe can have a substantial impact on the future of cystoscopy.
Optimization and analytics for air traffic management [electronic resource]
Keywords: Management Science and Engineering.

The air traffic management system is important to the United States' economy and way of life. Furthermore, it is complex and largely controlled by human decision makers. We studied and learned from these expert decision makers to facilitate the transition to an increasingly autonomous air traffic management system that leverages the strengths of both computer systems and humans to provide greater value to stakeholders. In particular, we constructed decision models and corresponding solution algorithms that enable decision-support tool development. Our approach to building the decision models and algorithms leveraged expert input and feedback, operational decision data analytics, fast-time simulations, and human-in-the-loop simulations. We utilized and extended techniques from optimization, dynamic programming, and machine learning both for developing solution algorithms and for making inferences about decisions based on operational data. In this dissertation we discuss our research on three types of decisions in the air traffic management system. The first is faced by supervisors of air traffic controllers: how to configure available airspace, controllers, and other resources to ensure safe and efficient operations in a region of airspace over a period of time. The second type of decision is faced by airlines: how to assign a set of flights to a set of slots in an Airspace Flow Program. The third type of decision is faced by air traffic flow managers: when to implement a Ground Delay Program.
Optogenetic control of neurons beyond the brain [electronic resource]
Keywords: Bioengineering.

Optogenetic tools have immense value in targeting genetically specified excitable cells with high temporal precision throughout the body, and have been used extensively to investigate circuits of the brain. Optogenetics has great potential to analyze the neural circuitry of the peripheral nervous system (PNS) and spinal cord in freely moving animals, but has been limited by the technical difficulties of delivering opsins and light to these heterogeneous systems. In this thesis, I present novel optogenetic tools for use throughout the nervous system in freely moving animals. Included are viral strategies to target opsins to cutaneous C-fiber nociceptors and peripheral motor neurons as well as methods to deliver light via optical fiber to peripheral nerves, and wirelessly to cutaneous nerve terminals, spinal cord, and motor cortex of the brain. Using these optogenetic tools, we investigated pain and motor control in awake and freely moving mice and rats and provided proof-of-concept for potential therapies for neuropathic pain and paralysis. This technology opens the door for therapeutic development and more advanced investigations of the nervous system.
Organic transistors based on Van der Waals heterostructures [electronic resource]
Keywords: Electrical Engineering.

Organic semiconductor devices have been actively investigated due to their potential use in low-cost, large-area, transparent, and flexible electronics. The highly efficient charge transport in polycrystalline organic films is crucial for achieving high performance devices and extending the scope of their applications. The charge transport in polycrystalline organic films is mainly limited by scattering at grain boundaries and trap sites at semiconductor-metal and semiconductor-dielectric interfaces. We demonstrate the use of van der Waals heterostructure of an organic semiconductor and 2D materials to minimize interface traps for efficient charge transport in this dissertation. In addition to high efficient charge transport, both n- and p-channel transistors are required to implement complementary metal-oxide-semiconductor (CMOS) circuits that are considered as desirable due to their scalability, high noise immunity, and low static power dissipation. In this dissertation, we show that both n- and p-channel transistors can be obtained with a single organic semiconductor by using doping method.
Oscillatory data analysis and fast algorithms for integral operators [electronic resource]
Keywords: Mathematics.

This dissertation consists of two independent parts: oscillatory data analysis (Part I) and fast algorithms for integral operators in computational harmonic analysis (Part II). The first part concentrates on developing theory and efficient tools in applied and computational harmonic analysis for oscillatory data analysis. In modern data science, oscillatory data analysis aims at identifying and extracting principle wave-like components, which might be nonlinear and non-stationary, underlying a complex physical phenomenon. Estimating instantaneous properties of one-dimensional components or local properties of multi-dimensional components has been an important topic in various science and engineering problems in resent three decades. This thesis introduces several novel synchrosqueezed transforms (SSTs) with rigorous mathematical, statistical analysis, and efficient implementation to tackle challenging problems in oscillatory data analysis. Several real applications show that these transforms provide an elegant tool for oscillatory data analysis. In many applications, the SST-based algorithms are significantly faster than the existing state-of-art algorithms and obtain better results. The second part of this thesis proposes several fast algorithms for the numerical implementation of several integral operators in harmonic analysis including Fourier integral operators (including pseudo differential operators, the generalized Radon transform, the nonuniform Fourier transform, etc.) and special function transforms (including the Fourier-Bessel transform, the spherical harmonic transform, etc.). These are useful mathematical tools in a wide range of science and engineering problems, e.g., imaging science, weather and climate modeling, electromagnetics, quantum chemistry, and phenomena modeled by wave equations. Via hierarchical domain decomposition, randomized low-rank approximations, interpolative low-rank approximations, the fast Fourier transform, and the butterfly algorithm, I propose several novel fast algorithms for applying or recovering these operators.
Overgeneral autobiographical memory in major depressive disorder is associated with abnormal neural activity during retrieval [electronic resource]
Keywords: Psychology.

Major Depressive Disorder (MDD) is a psychiatric mood disorder that is associated with abnormal cognitive processes, including overgeneral memory (OGM) for autobiographical events. When asked to produce memories from their own lives, depressed individuals produce fewer specific memories than do their nondepressed peers. The neural basis of OGM in MDD, however, is not yet clear. Specifically, we do not know if depressed individuals exhibit normal memory-related neural activation during encoding; we also do not know if individuals with MDD show neural signatures that have been found to be related to retrieval of content, i.e. cortical reinstatement. To address these questions, depressed and nondepressed adults completed a standard measure of autobiographical memory specificity and, inside a Magnetic Resonance Imaging (MRI) scanner, a paired-associates learning task. At the behavioral level, depressed individuals showed evidence of decreased specificity of autobiographical memory relative to healthy controls, but did not exhibit impairment in associative learning. At the neural level, depressed and nondepressed participants did not differ during encoding. During retrieval, a predicted difference between depressed and nondepressed participants in neural activity in the hippocampus was also not obtained. Importantly, however, compared to their nondepressed peers, depressed individuals showed less activity in the right prefrontal cortex during the successful retrieval of images. In addition, and also counter to hypotheses, there was robust evidence of cortical reinstatement of image category information in both depressed and nondepressed individuals. Together, these findings suggest that OGM in MDD is not related to an inability to reactivate visual information or to an inability to form or encode associative memories. Instead, it seems that if OGM in MDD is related to some systematic aberrant neural function, this abnormality is a subtle difference between depressed and nondepressed individuals in retrieval processes that is mediated by the prefrontal cortex.