Physical Sciences and Mathematics Commons^™

Maximum Empirical Likelihood Estimation In U-Statistics Based General Estimating Equations, Lingnan Li

Open Access Dissertations

In the first part of this thesis, we study maximum empirical likelihood estimates (MELE's) in U-statistics based general estimating equations (UGEE's). Our technical maneuver is the jackknife empirical likelihood (JEL) approach. We give the local uniform asymptotic normality condition for the log-JEL for UGEE's. We derive the estimating equations for finding MELE's and provide their asymptotic normality. We obtain easy MELE's which have less computational burden than the usual MELE's and can be easily implemented using existing software. We investigate the use of side information of the data to improve efficiency. We exhibit that the MELE's are fully efficient, and …

Controlling For Confounding Network Properties In Hypothesis Testing And Anomaly Detection, Timothy La Fond

Open Access Dissertations

An important task in network analysis is the detection of anomalous events in a network time series. These events could merely be times of interest in the network timeline or they could be examples of malicious activity or network malfunction. Hypothesis testing using network statistics to summarize the behavior of the network provides a robust framework for the anomaly detection decision process. Unfortunately, choosing network statistics that are dependent on confounding factors like the total number of nodes or edges can lead to incorrect conclusions (e.g., false positives and false negatives). In this dissertation we describe the challenges that face …

Nanophotonics For Dark Materials, Filters, And Optical Magnetism, Mengren Man

Open Access Dissertations

Research on nanophotonic structures for three application areas is described, a near perfect optical absorber based on a graphene/dielectric stack, an ultraviolet bandpass filter formed with an aluminum/dielectric stack, and structures exhibiting homogenizable magnetic properties at infrared frequencies. The graphene stack can be treated as a effective, homogenized medium that can be designed to reflect little light and absorb an astoundingly high amount per unit thickness, making it an ideal dark material and providing a new avenue for photonic devices based on two-dimensional materials. Another material stack arrangement with thin layers of metal and insulator forms a multi-cavity filter that …

Measurement Of The Upsilon(Ns) Cross Section At Cdf, Michael D. Meier

Open Access Dissertations

Since the bound bb¯ system was first discovered, researchers have been trying to explain the production mechanism for quarkonium to learn more about this system. Several different theories try to describe quarkonium production, and while these theories agree with experimental measurements of production rates, theoretical predictions for quarkonium polarization vary. Careful measurement of the ϒ( nS) angular distribution along with the ϒ(nS) cross section can provide insight into the quarkonium production mechanism. This analysis measures the ϒ(nS) cross section and ϒ(1 S) polarization parameters.

Advances In Raman Hyperspectral Compressive Detection Instrumentation For Fast Label Free Classification, Quantitation And Imaging, Bharat R. Makani

Open Access Dissertations

Multiple prototypes of hyperspectral compressive detection (CD) Raman spectrometers have previously been constructed in the Ben-Amotz lab and have proven to be useful for fast, label-free chemical identification, quantitation and imaging. The CD spectrometer consists of a volume holographic grating (VHG) that linearly disperses the Raman photons into its component wavelengths and all wavelengths are focused onto a digital micromirror devise (DMD). The DMD is an optical modulator that consists of an array of programmable 10μm mirrors that can reflect photons in either +12° or -12° to the incoming light. The DMD is tilted such that the +12° photons go …

Investigation Of Cellular Microenvironments And Heterogeneity With Biodynamic Imaging, Daniel Alexander Merrill

Open Access Dissertations

Imaging of biological tissue in a relevant environment is critical to accurately assessing the effectiveness of chemotherapeutic agents in combatting cancer. Though many three-dimensional (3D) culture models exist, conventional in vitro assays continue to use two-dimensional (2D) cultures because of the difficulty in imaging through deep tissue. 3D tomographic imaging techniques exist and are being used in the development of 3D efficacy assays. However, most of these assays look at therapy endpoint (dead or living cancer cell count) and do not capture the dynamics of tissue response.

Biodynamic imaging (BDI) is a 3D tomographic imaging and assay technique that uses …

Rees Algebras And Iterated Jacobian Duals, Vivek Mukundan

Open Access Dissertations

Consider the rational map Ψ : [Special characters omitted.] where the fi's are homogeneous forms of the same degree in the homogeneous coordinate ring R = k[ x1,…,xd] of [Special characters omitted.]. Assume that I = (f 1,…,fm) is a height 2 perfect ideal in the polynomial ring R. In this context, the coordinate ring of the graph of Ψ is the Rees algebra of I and the co-ordinate ring of the image of Ψ is the special fiber ring. We study two settings. The first setting is when I is almost …

Exploring Spin-Transfer-Torque Devices And Memristors For Logic And Memory Applications, Zoha Pajouhi

Open Access Dissertations

As scaling CMOS devices is approaching its physical limits, researchers have begun exploring newer devices and architectures to replace CMOS.

Due to their non-volatility and high density, Spin Transfer Torque (STT) devices are among the most prominent candidates for logic and memory applications. In this research, we first considered a new logic style called All Spin Logic (ASL). Despite its advantages, ASL consumes a large amount of static power; thus, several optimizations can be performed to address this issue. We developed a systematic methodology to perform the optimizations to ensure stable operation of ASL.

Second, we investigated reliable design of …

Martingales, Singular Integrals, And Fourier Multipliers, Michael A. Perlmutter

Open Access Dissertations

Many probabilistic constructions have been created to study the Lp-boundedness, 1 < p < ∞, of singular integrals and Fourier multipliers. We will use a combination of analytic and probabilistic methods to study analytic properties of these constructions and obtain results which cannot be obtained using probability alone.

In particular, we will show that a large class of operators, including many that are obtained as the projection of martingale transforms with respect to the background radiation process of Gundy and Varapolous or with respect to space-time Brownian motion, satisfy the assumptions of Calderón-Zygmund theory and therefore boundedly map L1 to weak- L1.

We will also use a method of rotations to study the L p boundedness, 1 < p < ∞, of Fourier multipliers which are obtained as the projections of martingale transforms with respect to symmetric α-stable processes, 0 < α < 2. Our proof does not use the fact that 0 < α < 2 and therefore allows us to obtain a larger class of multipliers, indexed by a parameter, 0 < r < ∞, which are bounded on L p. As in the case of the multipliers which arise as the projection of martingale …

Parametric Approaches To Fractional Programs: Analytical And Empirical Study, Chong Hyun Park

Open Access Dissertations

Fractional programming is used to model problems where the objective function is a ratio of functions. A parametric modeling approach provides effective technique for obtaining optimal solutions of these fractional programming problems. Although many heuristic algorithms have been proposed and assessed relative to each other, there are limited theoretical studies on the number of steps to obtain the solution. In this dissertation, I focus on the linear fractional combinatorial optimization problem, a special case of fractional programming where all functions in the objective function and constraints are linear and all variables are binary that model certain combinatorial structures. Two parametric …

Multivariate Statistical Methods That Enable Fast Raman Spectroscopy, Owen G. Rehrauer

Open Access Dissertations

Raman spectroscopy is a useful tool in investigating inter- and intra-molecular interactions as well as classifying and quantifying chemical species in a sample. Many materials of societal interest, such as proteins and pharmaceuticals, have distinctive Raman spectra with sharp features. However, the adoption of Raman spectra has been hindered by the low rate of Raman scattering, interference from fluorescence, and high spectrometer costs. This work demonstrates multivariate stastical methods that enable fast Raman measurements, despite the low rate of Raman scattering. These methods include a novel type of spectrometer, that uses computer-controlled optical filters to efficiently capture Raman photons and …

Kinetics And Mechanisms Of Amine Bis-Phenolate Polymerization Catalysts Featuring Titanium, Zirconium, Or Hafnium Centers, Paul Daniel Pletcher

Open Access Dissertations

The story of Group IV metallocene polymerization catalysts has been a tremendous success in the ability to tune chemical reactivity through structural design. As new, nonmetallocene catalyst systems are being investigated, there has been a lack of quantitative relationships for predicting optimal catalyst design for both desired reactivity and polymeric properties. By utilizing a rational catalyst design strategy that focuses on obtaining a quantitative kinetic analysis of all relevant chemical steps from a family of related catalysts, we have attempted to correlate the fundamental reactivity within the olefin polymerization mechanism to distinctive chemical structures. Such studies have revealed both predictive, …

Coupling Qualitative And Quantitative Analyses Of Pharmaceutical Materials Enabled By Second Harmonic Generation Microscopy, Paul D. Schmitt

Open Access Dissertations

The detection and characterization of crystallinity is critical throughout the drug development process. From the initial establishment of an active pharmaceutical ingredient’s (API) crystal structure to stability testing and quality control, the phase of an API affects the solubility, bioavailability, stability, and efficacy of a drug product. Second harmonic generation (SHG) microscopy has recently been developed as a selective and rapid method for imaging crystallinity in drug formulations. While SHG microscopy can enable the high signal-to-noise (SNR) detection of crystallinity, the intrinsic chemical information content within SHG images is relatively low. In cases of trace crystallinity and/ or small crystal …

Evolutionary Potential Of A Dispersal-Restricted Species In Response To Climate Change, Lorena Torres Martinez

Open Access Dissertations

Habitat replacement and fragmentation associated with projected climate change pose a critical threat to global biodiversity. Edaphically limited plant species with restricted dispersal abilities will be especially handicapped to track their optimal climate spatially. Instead, the persistence of these species will depend on their capacity to adapt in situ to novel climate regimes. Here I evaluated the evolutionary potential of Lasthenia fremontii, an annual plant species restricted to ephemeral wetlands called vernal pools in California to adapt to the projected patterns of climate change. Across L. fremontii distribution there is a latitudinal gradient in precipitation which, combined with reduced …

Data Driven Low-Bandwidth Intelligent Control Of A Jet Engine Combustor, Nathan L. Toner

Open Access Dissertations

This thesis introduces a low-bandwidth control architecture for navigating the input space of an un-modeled combustor system between desired operating conditions while avoiding regions of instability and blow-out. An experimental procedure is discussed for identifying regions of instability and gathering sufficient data to build a data-driven model of the system's operating modes. Regions of instability and blow-out are identified experimentally and a data-driven operating point classifier is designed. This classifier acts as a map of the operating space of the combustor, indicating regions in which the flame is in a "good" or "bad" operating mode. A data-driven predictor is also …

Implementing And Testing A Panel-Based Method For Modeling Acoustic Scattering From Cfd Input, S. Hales Swift

Open Access Dissertations

Exposure of sailors to high levels of noise in the aircraft carrier deck environment is a problem that has serious human and economic consequences. A variety of approaches to quieting exhausting jets from high-performance aircraft are undergoing development. However, testing of noise abatement solutions at full-scale may be prohibitively costly when many possible nozzle treatments are under consideration. A relatively efficient and accurate means of predicting the noise levels resulting from engine-quieting technologies at personnel locations is needed. This is complicated by the need to model both the direct and the scattered sound field in order to determine the resultant …

Packet Filter Performance Monitor (Anti-Ddos Algorithm For Hybrid Topologies), Ibrahim M. Waziri

Open Access Dissertations

DDoS attacks are increasingly becoming a major problem. According to Arbor Networks, the largest DDoS attack reported by a respondent in 2015 was 500 Gbps. Hacker News stated that the largest DDoS attack as of March 2016 was over 600 Gbps, and the attack targeted the entire BBC website.

With this increasing frequency and threat, and the average DDoS attack duration at about 16 hours, we know for certain that DDoS attacks will not be going away anytime soon. Commercial companies are not effectively providing mitigation techniques against these attacks, considering that major corporations face the same challenges. Current security …

Single-Conformation Spectroscopy Of Hydrogen Bonding Networks: Solvation, Synthetic Foldamers, And Neurodegenerative Diseases, Patrick S. Walsh

Open Access Dissertations

The hydrogen bond is one of the most important interactions in natural processes ranging from protein folding to chemical reactions. Two complementary methodologies are applied to understanding this important interaction: top-down and bottom-up. Top-down methods use large molecules, such as proteins, revealing secondary structure information. Bottom-up experiments are performed on small molecules, utilizing high-resolution spectroscopy to reveal underlying quantum mechanical effects. The complexity gap is formed between these two experimental regimes; between large and small molecules; between bulk and individual solvent molecules; between classical mechanics calculations and quantum chemical calculations. This dissertation will focus on the application of gas phase, …

Learning From Data: Plant Breeding Applications Of Machine Learning, Alencar Xavier

Open Access Dissertations

Increasingly, new sources of data are being incorporated into plant breeding pipelines. Enormous amounts of data from field phenomics and genotyping technologies places data mining and analysis into a completely different level that is challenging from practical and theoretical standpoints. Intelligent decision-making relies on our capability of extracting from data useful information that may help us to achieve our goals more efficiently. Many plant breeders, agronomists and geneticists perform analyses without knowing relevant underlying assumptions, strengths or pitfalls of the employed methods. The study endeavors to assess statistical learning properties and plant breeding applications of supervised and unsupervised machine learning …

Ultracold Quantum Scattering In The Presence Of Synthetic Spin-Orbit Coupling, Su-Ju Wang

Open Access Dissertations

Two-body scattering constitutes one of the most fundamental processes in various physical systems ranging from ultracold dilute quantum gases to energetic quark- gluon plasmas. In this dissertation, we study the low-energy atomic collision physics in the presence of synthetic gauge fields, which are generated by atom-light interaction. One category of synthetic gauge fields is the artificial spin-orbit coupling. We discuss three different aspects in scattering theory: ultracold collision, scattering resonance, and bound state formation from a few-body perspective when the atomic spin states are coupled with their center-of-mass motion. The understanding of the spin-orbit effects on the modification of the …

Improving The Eco-System Of Passwords, Weining Yang

Open Access Dissertations

Password-based authentication is perhaps the most widely used method for user authentication. Passwords are both easy to understand and use, and easy to implement. With these advantages, password-based authentication is likely to stay as an important part of security in the foreseeable future. One major weakness of password-based authentication is that many users tend to choose weak passwords that are easy to guess. In this dissertation, we address the challenge and improve the eco-system of passwords in multiple aspects. Firstly, we provide methodologies that help password research. To be more specific, we propose Probability Threshold Graphs, which is superior to …

Quantum Coherence And Entanglement In Open Quantum Systems, Yiteng Zhang

Open Access Dissertations

We humans always want to believe that we can overpower nature. However, the reality is that nature outperforms humans in many aspects. Animals' abilities to navigate/orient and photosynthesis are two excellent examples in these aspects. However, the mechanisms underlying them are still unknown. For decades, scientists and researchers have made a lot of efforts to reveal these mysteries in nature.

Recently, quantum coherence and entanglement are believed to play a crucial role in such biological systems–avian compass and photosynthesis. Thus, nature might know more tricks to utilize quantum mechanics than humans. Studies on the mechanisms underlying avian compass and photosynthesis …

Extreme-Strike And Small-Time Asymptotics For Gaussian Stochastic Volatility Models, Xin Zhang

Open Access Dissertations

Asymptotic behavior of implied volatility is of our interest in this dissertation. For extreme strike, we consider a stochastic volatility asset price model in which the volatility is the absolute value of a continuous Gaussian process with arbitrary prescribed mean and covariance. By exhibiting a Karhunen-Loève expansion for the integrated variance, and using sharp estimates of the density of a general second-chaos variable, we derive asymptotics for the asset price density for large or small values of the variable, and study the wing behavior of the implied volatility in these models. Our main result provides explicit expressions for the first …

The Design And Statistical Analysis Of Single-Cell Rna-Sequencing Experiments, Faye H. Zheng

Open Access Dissertations

Next-generation DNA- and RNA-sequencing (RNA-seq) technologies have expanded rapidly in both throughput and accuracy within the last decade. The momentum continues as emerging techniques become increasingly capable of profiling molecular content at the level of individual cells. One goal of this research is to put forward best practices in the design of single-cell RNA-sequencing (scRNA-seq) experiments, specifically as it relates to choices regarding the trade-off between sequencing depth and sample size. In addition to general guidelines, an interactive tool is presented to aid researchers in making experiment-specific decisions that are informed by real data and practical constraints. Further, a new …

Mathematical Models Of Ebola Virus Disease And Vaccine Preventable Diseases, Yinqiang Zheng

Open Access Dissertations

This thesis focuses on applying mathematical models to studies on the transmission dynamics and control interventions of infectious diseases such as Ebola virus disease and vaccine preventable diseases.

Many models in studies of Ebola transmission are based on the model by Legrand et al. (2007). However, there are potential issues with the Legrand model. First, the model was originally formulated in a complex form, leading to confusion and hindering its uses in practice. To overcome the difficulty, the Legrand model is reformulated in a much simpler but equivalent form in this thesis. The reformulated model also provides an intuitive understanding …

Learning Program Specifications From Sample Runs, He Zhu

Open Access Dissertations

With science fiction of yore being reality recently with self-driving cars, wearable computers and autonomous robots, software reliability is growing increasingly important. A critical pre-requisite to ensure the software that controls such systems is correct is the availability of precise specifications that describe a program's intended behaviors. Generating these specifications manually is a challenging, often unsuccessful, exercise; unfortunately, existing static analysis techniques often produce poor quality specifications that are ineffective in aiding program verification tasks.

In this dissertation, we present a recent line of work on automated synthesis of specifications that overcome many of the deficiencies that plague existing specification …

Topographic Constraints On Magma Accumulations Below The Actively Uuplifting Uturuncu And Lazufre Volcanic Centers In The Central Andes, Jonathan P. Perkins, Noah J. Finnegan, Scott T. Henderson, Tammy M. Rittenour

Geosciences Faculty Publications

Geodetic surveys of Volcán Uturuncu and the Lazufre volcanic complex in the Central Andes of South America reveal sustained surface uplift from magmatic intrusion at depth. However, the decadal timescales of geodetic surveys are short relative to the timescales of magma chamber growth. Thus, from geodesy alone, it is difficult to infer the deformation and hence magma accumulation history of these volcanoes. Here we combine data from InSAR, long-wavelength topography, GPS and high-resolution topographic surveys of lake shorelines and rivers, and lava flow morphology to constrain the spatial and temporal evolution of magmatism at Uturuncu and Lazufre. Near Uturuncu, dated …

Protein Residue-Residue Contact Prediction Using Stacked Denoising Autoencoders, Joseph Bailey Luttrell Iv

Honors Theses

Protein residue-residue contact prediction is one of many areas of bioinformatics research that aims to assist researchers in the discovery of structural features of proteins. Predicting the existence of such structural features can provide a starting point for studying the tertiary structures of proteins. This has the potential to be useful in applications such as drug design where tertiary structure predictions may play an important role in approximating the interactions between drugs and their targets without expending the monetary resources necessary for preliminary experimentation. Here, four different methods involving deep learning, support vector machines (SVMs), and direct coupling analysis were …

Synthesis, Characterization And Biological Evaluation Of Pyrrolo[2,1-C][1,4]Benzodiazepines For Cytotoxicity And Serine Β-Lactamases Inhibition, Joel K. Annor-Gyamfi

Electronic Theses and Dissertations

Pyrrolo[2,1-c][1,4]benzodiazepine (PBD) derivatives possess cancerostatic and anti-infective properties thus making them candidates of possible antibacterial agents. ²-lactam antibiotics are vital weapons for the treatment of bacterial infections, but their existence and effectiveness has been faced with resistance from ²-lactamases. Therefore, the need for new effective antimicrobial drugs is very crucial. In this work, we synthesized in high yields, PBD analogs 1−3, 5 and 7−9 in three to four synthetic steps from commercially available L-proline and isatoic anhydride. MTT Assay was employed to test the in vitro cytotoxicity of PBD analogs 1, 2, 5 …

Multilevel Models For Longitudinal Data, Aastha Khatiwada

Electronic Theses and Dissertations

Longitudinal data arise when individuals are measured several times during an ob- servation period and thus the data for each individual are not independent. There are several ways of analyzing longitudinal data when different treatments are com- pared. Multilevel models are used to analyze data that are clustered in some way. In this work, multilevel models are used to analyze longitudinal data from a case study. Results from other more commonly used methods are compared to multilevel models. Also, comparison in output between two software, SAS and R, is done. Finally a method consisting of fitting individual models for each …