Physical Sciences and Mathematics Commons^™

Investigation Of Interactions Between 1,3 Dialkyl Imidazolium Ionic Liquids And Lignocellulosic Polymers, Aparna Annamraju

Doctoral Dissertations

Lignocellulosic biomass is a potential energy source for fuels, chemicals and materials production in a sustainable manner. A network of covalent and non-covalent bonds between the three main polymers of biomass, i.e., cellulose, hemicellulose and lignin, results in a compact structure that is resistant to chemical and biological attacks and therefore challenging for the efficient utilization of lignocellulosic biomass. Ionic liquids (ILs) have been reported to disrupt the bonds between these polymers and dissolve biomass at temperatures below 100 ˚C. Research through the years has shown that biomass pretreatment with IL brings out the selective dissolution of biomass polymers and …

Numerical Studies Of Superconductivity And Charge-Density-Waves: Progress On The 2d Holstein Model And A Superconductor-Metal Bilayer, Philip M. Dee

Doctoral Dissertations

The problem of superconductivity has been central in many areas of condensed matter physics for over 100 years. Despite this long history, there is still no theory capable of describing both conventional and unconventional superconductors. Recent experimental observations such as the dilute superconductivity in SrTiO₃ and near room-temperature superconductivity in hydride compounds under extreme pressure have renewed interest in electron-phonon systems. Adding to this is evidence that electron-phonon coupling may play a supporting role in unconventional systems like the cuprates and monolayer FeSe on SrTiO₃.

One way to make sense of these observations is to construct simple …

Measuring Electron Diffusion And Constraining The Neutral Current Π0 Background For Single-Photon Events In Microboone, Andrew Mogan

Doctoral Dissertations

Liquid Argon Time Projection Chambers (LArTPCs) are a rising technology in the field of experimental neutrino physics. LArTPCs use ionization electrons and scintillation light to reconstruct neutrino interactions with exceptional calorimetric and position resolution capabilities. Here, I present two analyses conducted in the MicroBooNE LArTPC at Fermilab: a measurement of the longitudinal electron diffusion coefficient, DL, in the MicroBooNE detector and a constraint of the systematic uncertainty on MicroBooNE's single-photon analysis due to the dominant neutral current (NC) π0 background. Longitudinal electron diffusion modifies the spatial and timing resolution of the detector, and measuring it will help correct for these …

Human Fatigue Predictions In Complex Aviation Crew Operational Impact Conditions, Suresh Rangan

Doctoral Dissertations

In this last decade, several regulatory frameworks across the world in all modes of transportation had brought fatigue and its risk management in operations to the forefront. Of all transportation modes air travel has been the safest means of transportation. Still as part of continuous improvement efforts, regulators are insisting the operators to adopt strong fatigue science and its foundational principles to reinforce safety risk assessment and management. Fatigue risk management is a data driven system that finds a realistic balance between safety and productivity in an organization. This work discusses the effects of mathematical modeling of fatigue and its …

Synthetic Heterosynaptic Plasticity Enhances The Versatility Of Memristive Systems Emulating Bio-Synapse Structure And Function, William T. Mcclintic

Doctoral Dissertations

Memristive systems occur in nature and are hallmarked via pinched hysteresis, the difference in the forward and reverse pathways for a given phenomenon. For example, neurons of the human brain are composed of synapses which apply the properties of memristance for neuronal communication, learning, and memory consolidation. Modern technology has much to gain from the characteristics of memristive systems, including lower power operation, on-chip memory, and bio-inspired computing. What is more, a relationship between memristive systems and synaptic plasticity exists and can be investigated focusing on homosynaptic and heterosynaptic plasticity. Where homosynaptic plasticity applies to interactions between neurons at a …

Study Of 134in Beta-Delayed Neutron Emission And Development Of A New Generation Neutron Detector, Joseph Heideman

Doctoral Dissertations

Beta-delayed neutron emission in very neutron-rich nuclei plays an essential role in nuclear structure and the understanding of the astrophysical r-process. A complete description of this process requires knowledge of both steps, beta decay and neutron emission. A leading theory poses the intermediate daughter nucleus to behave as a compound nucleus. The conditions for beta-delayed neutron emission of 134In are not well described by the assumptions in the neutron pandemonium hypothesis, therein providing a unique case to this process due to the proximity to 132Sn. Single-particle states in 133Sn obvserved after neutron emission have dissimilar shell occupancy compared to neutron-hole …

Machine Learning With Topological Data Analysis, Ephraim Robert Love

Doctoral Dissertations

Topological Data Analysis (TDA) is a relatively new focus in the fields of statistics and machine learning. Methods of exploiting the geometry of data, such as clustering, have proven theoretically and empirically invaluable. TDA provides a general framework within which to study topological invariants (shapes) of data, which are more robust to noise and can recover information on higher dimensional features than immediately apparent in the data. A common tool for conducting TDA is persistence homology, which measures the significance of these invariants. Persistence homology has prominent realizations in methods of data visualization, statistics and machine learning. Extending ML with …

Towards Neutron Transformation Searches, Joshua L. Barrow

Doctoral Dissertations

To probe the origins of the baryon asymmetry, baryon number violation, the last unconfirmed Sakharov condition, must be definitively observed experimentally. Similarly, the nature of dark matter is currently unknown, and calls out for new candidates to be investigated. Each of these issues can be considered through the study of neutron transformations.

Some rare baryon number violating processes, such as neutron-antineutron transformations, are expected to probe baryogenesis. Here, I show progress on this discovery target through construction of more accurate Monte Carlo models, the design of future detectors, creation of more complete atmospheric neutrino background simulations, and use of automated …

Optimal Communication Structures For Concurrent Computing, Andrii Berdnikov

Doctoral Dissertations

This research focuses on communicative solvers that run concurrently and exchange information to improve performance. This “team of solvers” enables individual algorithms to communicate information regarding their progress and intermediate solutions, and allows them to synchronize memory structures with more “successful” counterparts. The result is that fewer nodes spend computational resources on “struggling” processes. The research is focused on optimization of communication structures that maximize algorithmic efficiency using the theoretical framework of Markov chains. Existing research addressing communication between the cooperative solvers on parallel systems lacks generality: Most studies consider a limited number of communication topologies and strategies, while the …

Multi-Scale Computational Modeling Of Metal/Ceramic Interfaces, Abu Shama Mohammad Miraz

Doctoral Dissertations

Multi-scale atomistic calculations were carried out to understand the interfacial features that dictate the mechanical integrity of the metal/ceramic nanolaminates. As such, first principles density functional theory (DFT) calculations were performed to understand the electronic and atomistic factors governing adhesion and resistance to shear for simple metal/ceramic interfaces, whereas molecular dynamics (MD) simulations were performed to observe the impact of interfacial structures, such as misfit dislocation network geometries and orientation relationships, on interfacial mechanical properties.

For the DFT investigation, we choose metals with different crystal structures, namely - Cu (fcc), Cr (bcc) and Ti (hcp) along with a variety of …

Exploration Of N-Heterocyclic Carbenes For The Functionalization Of Gold Surfaces And Their Metal Complexes, Shelby L. Strausser

Doctoral Dissertations

Gold surface chemistry has progressed considerably towards many applications in medicine. Due to the non-toxic nature of gold in the human body, gold surfaces have been investigated for biometric sensors and targeted drug therapy agents. While gold is relatively unreactive in its elemental form, gold surfaces (such as films or nanoparticles) require a ligand for stability and improved functionality. The typical ligand is thiols for self-assembled monolayers on gold surfaces. While thiol self-assembly on surfaces is well understood, thiols are known to degrade or leach under a wide variety of conditions, including both thermal and chemical, which is toxic in …

Architectural-Element Analysis And Depositional Models For Pre-Vegetation Braidplain And Braid-Delta Environments, With Modern Analogues, Jason Gerhard Muhlbauer

Doctoral Dissertations

Pre-vegetation landscapes that blanketed the continents before the emergence vascular plants in the late-Silurian are proposed habitats for the earliest terrestrial biota and are analogous to martian setting thought to have potentially hosted life. Analysis of the middle member of the Wood Canyon Formation, a Cambrian age sandstone, reveal new details about terrestrial pre-vegetation environments. In fluvial middle-member stratigraphy, units are defined by stacking patterns of three facies associations (FA1-3). In FA1, stacked cosets, interpreted as braidplain barforms and channel fills, preserve vertical- and downstream-accretion elements under unimodal paleoflow. Floodplains, represented by FA2, include red-orange intervals of fine- to medium-grained …

Local Dynamics And Atomic-Level Structures In Metallic Liquids And Glasses, Zengquan Wang

Doctoral Dissertations

Structure and dynamics at the atomic level in metallic glasses and liquids are poorly understood when compared to the crystalline solids. For instance, even though viscosity is the basic property of liquids, its atomistic origin is not well elucidated. Also, the physics of the fragility of liquids and the crossover phenomenon is far from full understanding. Earlier, through molecular dynamics (MD) simulations a direct connection was found between the timescale describing the macroscopic viscous behavior, the Maxwell relaxation time (t_M = h/G_∞, h is the shear viscosity and G_∞ is the high-frequency shear modulus) and …

Spatio-Temporal Modeling Of Crime In Chicago, Illinois, Shelby Scott

Doctoral Dissertations

Gun crime is a major public health concern in the United States. In Chicago, Illinois, gun crime incurs a significant cost of life along with monetary costs and community unrest. Due to past legislation, there is limited research applying quantitative methods to gun crime in Chicago. The overall purpose of this work is to create a cellular automata model to observe and project the epidemic spread of gun crime in Chicago. To create that model, t-test analyses of temporal patterns, a Bayesian point process model, a negative binomial Bayesian subset selection, and a k-selection algorithm are used. The cellular automata …

An Analysis Of Modern Password Manager Security And Usage On Desktop And Mobile Devices, Timothy Oesch

Doctoral Dissertations

Security experts recommend password managers to help users generate, store, and enter strong, unique passwords. Prior research confirms that managers do help users move towards these objectives, but it also identified usability and security issues that had the potential to leak user data or prevent users from making full use of their manager. In this dissertation, I set out to measure to what extent modern managers have addressed these security issues on both desktop and mobile environments. Additionally, I have interviewed individuals to understand their password management behavior.

I begin my analysis by conducting the first security evaluation of the …

Mathematical Models In Medicine: The Immune Response Of Celiac Disease And The Environmental Transmission Of Clostridioides Difficile In Healthcare Settings, Cara Jill Sulyok

Doctoral Dissertations

Mathematical modeling is a useful technique to describe dynamics happening within events and allows one to address questions and test hypotheses that may be not be feasible to study in reality. This work uses mathematical models to describe two such phenomena, one relating to immunology and the other to the spread of infectious diseases.

Celiac disease is a hereditary autoimmune disease that affects approximately 1 in 133 Americans. It is caused by a reaction to the protein gluten found in wheat, rye, and barley. After ingesting gluten, a patient with celiac disease may experience a range of unpleasant symptoms while …

Data Driven Models Of Hemlock Woolly Adelgid Impacts And Biological Control, Hannah M. Thompson

Doctoral Dissertations

We present two models of the Adelges tsugae, the hemlock woolly adelgid, an invasive insect pest of Tsuga canadensis, eastern hemlock, in the eastern United States. An A. tsugae infestation often results in the death of T. canadensis within years, and has caused significant changes to hemlock forests. We construct two models composed of systems of ordinary differential equations with time dependent parameters to represent seasonality. The first model captures the coupled cycles in T. canadensis health and A. tsugae density. We use field data from Virginia to develop the model and to perform parameter estimation. The mechanisms …

Non-Academic Support Math Faculty Members Provide In Developmental Accelerated And Corequisite Support Courses In California Community Colleges, David Vakil '92

Doctoral Dissertations

To guide practitioners of rapidly evolving developmental math reform in community colleges, this study surveyed California community college math faculty who taught accelerated developmental courses or corequisite support courses. The survey was conducted during the early implementation phase of both course types, during spring and fall 2018 terms. This study measured faculty’s self-reported provision of forms of non-academic support, frequency of implementation, and reasons faculty believed the support would help students succeed. The literature review guided grouping non-academic support into five forms: nurturing, helping students’ motivation, providing a growth mindset theory of intelligence, helping provide social integration, and helping to …

Robustness Against Attacks And Uncertainties In Smart Cyber-Physical Systems, Prithwiraj Roy

Doctoral Dissertations

Cyber-Physical Systems (CPS) are sensing, processing, and communicating platforms, embedded with physical devices that provide real-time monitoring and control. Security challenges in CPS necessitate solutions that are robust against attacks and uncertainties and provide a seamless operation, especially when used in real-time applications to monitor and secure critical infrastructures. CPS mainly consists of a physical component for sensing or monitoring and a cyber component for processing and communicating. The quality of interactions between physical and cyber systems has direct impacts on the system’s performance and reliability.

CPS plays a major role in smart services and applications within a smart living …

Development Of Intelligent Stimuli-Responsive Biomaterials And Nanodevices, Shuo Yang

Doctoral Dissertations

"Structural DNA nanotechnology utilizes DNA molecules as building blocks to fabricate ordered artificial nanostructures at the molecular level. Among all DNA-based techniques, DNA origami has been considered as one of the most powerful tools for constructing artificial nanostructures with excellent programmability and addressability. Currently, most DNA origami nanostructures are static and do not have the ability to response to environmental stimulation. The development of environmental-responsive DNA origami nanostructures is a critical step towards the realization of intelligent dynamic DNA origami-based nanodevices. This research focuses on the design and fabrication process of both static and dynamic DNA origami nanostructures and their …

Neogene Dinoflagellate Cysts From The Tropical Americas, Damian Cardenas

Doctoral Dissertations

"Marine palynomorphs, mainly dinoflagellate cysts and acritarchs, constitute excellent proxies for biostratigraphic and paleoceanographic studies in neritic sequences. Neogene marine palynological studies have mostly focused on the Northern Hemisphere, resulting in the scarcity of dinoflagellate cysts and acritarchs from tropical latitudes. Forty samples encompassing the late Chattian-late Burgidalian time interval (~24.1- 17.3 Ma) in the Southern Caribbean were analyzed for their marine palynological contents. A biostratigraphic scheme for the region is proposed and includes the upper Chattian-lower Aquitanian Minisphaeridium latirictum Interval Zone (~23.9-22.0 Ma), the upper Aquitanian Achomosphaera alcicornu Interval Zone (~22.0-20.3 Ma), and the Burdigalian Cribroperidinium tenuitabulatum Interval Zone …

Proper Orthogonal Decomposition: New Approximation Theory And A New Computational Approach, Sarah Katherine Locke

Doctoral Dissertations

“Proper orthogonal decomposition (POD) projection errors and error bounds for POD reduced order models of partial differential equations have been studied by many. In this research we obtain new results regarding POD data approximation theory and present a new difference quotient (DQ) approach for computing the POD modes of the data.

First, we improve on earlier results concerning POD projection errors by extending to a more general framework that allows for non-orthogonal POD projections and seminorms. We obtain new exact error formulas and convergence results for POD data approximation errors, and also prove new pointwise convergence results and error bounds …

Exposure Assessment Of Emerging Contaminants: Rapid Screening And Modeling Of Plant Uptake, Majid Bagheri

Doctoral Dissertations

"With the advent of new chemicals and their increasing uses in every aspect of our life, considerable number of emerging contaminants are introduced to environment yearly. Emerging contaminants in forms of pharmaceuticals, detergents, biosolids, and reclaimed wastewater can cross plant roots and translocate to various parts of the plants. Long-term human exposure to emerging contaminants through food consumption is assumed to be a pathway of interest. Thus, uptake and translocation of emerging contaminants in plants are important for the assessment of health risks associated with human exposure to emerging contaminants. To have a better understanding over fate of emerging contaminants …

Spatiotemporal Variations Of Upper Crustal Anisotropy Along The San Jacinto Fault Zone In Southern California And The Fairview Region In Central Oklahoma, Enyuan Jiang

Doctoral Dissertations

"To discern spatial and explore the possible existence of temporal variations of upper crustal anisotropy along an ~15 km section of the San Jacinto Fault Zone (SJFZ) in California, and in the Fairview, Oklahoma, region, we conduct systematic shear wave splitting (SWS) investigations using local S-wave data recorded by seismic stations. Strong spatial variations in crustal anisotropy are revealed by 1694 and 405 pairs of splitting parameters (including the fast polarization orientation and the splitting time), respectively. For both areas, for raypaths traveling through the fault zones, the fast orientations are parallel to the faults and may be attributed to …

Mantle Flow Systems Associated With Slab Subduction And Absolute Plate Motion In Alaska Constrained By Shear Wave Splitting Analyses, Yuchen Yang

Doctoral Dissertations

"Alaska has long been recognized as a geologically complex region with a sharp contrast in tectonic activity between southern and northern Alaska. While the former is characterized by the subduction of the geometrically varying Pacific-Yakutat plate beneath the North American plate, the latter has a mostly stable cratonic setting. To investigate the mantle flow fields beneath Alaska and understand the influence of the subduction process on regional mantle dynamics, a total of 2790 pairs of well-defined teleseismic shear wave splitting (SWS) measurements recorded from 379 stations are obtained and analyzed. In addition, 247 pairs of SWS results from local earthquake …

Reduced Calibration Uncertainties For The Global Network Of Gravitational-Wave Observatories And The Impact On Sky Localization Of Burst-Like Sources, Dripta Bhattacharjee

Doctoral Dissertations

The Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) is a science facility in the United States devoted to the observation of gravitational waves (GWs). It comprises two kilometer-scale laser interferometers. It is a part of a global ground-based GW detector network that also includes Virgo in Italy and KAGRA in Japan. Calibration of the LIGO detectors is achieved using displacement fiducials generated by radiation pressure based systems called Photon Calibrators (Pcals). The first part of this research described here details the developments implemented during the third LIGO-Virgo-KAGRA (LVK) observation run, O3, in the propagation of laser power calibration via transfer standards …

Security Against Data Falsification Attacks In Smart City Applications, Venkata Praveen Kumar Madhavarapu

Doctoral Dissertations

Smart city applications like smart grid, smart transportation, healthcare deal with very important data collected from IoT devices. False reporting of data consumption from device failures or by organized adversaries may have drastic consequences on the quality of operations. To deal with this, we propose a coarse grained and a fine grained anomaly based security event detection technique that uses indicators such as deviation and directional change in the time series of the proposed anomaly detection metrics to detect different attacks. We also built a trust scoring metric to filter out the malicious devices. Another challenging problem is injection of …

Data And Resource Management In Wireless Networks Via Data Compression, Gps-Free Dissemination, And Learning, Xiaofei Cao

Doctoral Dissertations

“This research proposes several innovative approaches to collect data efficiently from large scale WSNs. First, a Z-compression algorithm has been proposed which exploits the temporal locality of the multi-dimensional sensing data and adapts the Z-order encoding algorithm to map multi-dimensional data to a one-dimensional data stream. The extended version of Z-compression adapts itself to working in low power WSNs running under low power listening (LPL) mode, and comprehensively analyzes its performance compressing both real-world and synthetic datasets. Second, it proposed an efficient geospatial based data collection scheme for IoTs that reduces redundant rebroadcast of up to 95% by only collecting …

Reveal Wind Loading Of Tornadoes And Hurricanes On Civil Structures Towards Hazard-Resistant Design, Ryan Honerkamp

Doctoral Dissertations

"Extreme winds impacting civil structures lead to death and destruction in all regions of the world. Specifically, tornadoes and hurricanes impact communities with severe devastation. On average, 1200 tornadoes occur in the United States every year. Tornadoes occur predominantly in the Central and Southeastern United States, accounting for an annual $1 billion in economic losses, 1500 injuries, and 90 deaths. The Joplin, MO Tornado in 2011 killed 161 people, injured more than 1000, destroyed more than 8000 structures, and caused $2.8 billion of property loss. Hurricanes occur predominantly on the United States East coast regions and along the coast of …

Multimodal Neuroscience Data Modeling And Inference, Sima Azizi

Doctoral Dissertations

“Mathematical models can be combined with deep learning and machine learning methods to provide new insights in neuroscience. The field of neuroscience is characterized by rich datasets that include fluid biomarkers, EEG signals, and advanced neuroimages. Recent advances in natural language processing have led to the opportunity to gain additional insights from rapidly growing text databases as well as electronic health records. In this research, we focus on applying computational intelligence methods to the analysis of three different complex data sources: blood levels of disease biomarkers, EEG signals from schizophrenic patients, and disease phenotypes encoded in electronic health records. First, …