Physical Sciences and Mathematics Commons^™

Formation And Quench Of Homonuclear And Heteronuclear Quantum Droplets In One Dimension, Simeon I. Mistakidis, T. Mithun, P. G. Kevrekidis, H. R. Sadeghpour, P. Schmelcher

Physics Faculty Research & Creative Works

We Study The Impact Of Beyond Lee-Huang-Yang (LHY) Physics, Especially Due To Intercomponent Correlations, In The Ground State And The Quench Dynamics Of One-Dimensional Quantum Droplets With An Ab Initio Nonperturbative Approach. It Is Found That The Droplet Gaussian-Shaped Configuration Arising For Intercomponent Attractive Couplings Becomes Narrower For Stronger Intracomponent Repulsion And Transits Towards A Flat-Top Structure Either For Larger Particle Numbers Or Weaker Intercomponent Attraction. Additionally, A Harmonic Trap Prevents The Flat-Top Formation. At The Balance Point Where Mean-Field Interactions Cancel Out, We Show That A Correlation Hole Is Present In The Few-Particle Limit Of LHY Fluids As Well …

Video Error Concealment Using Convolutional Neural Network, Shashi Khanal

MSU Graduate Theses

Missing information in the video frames is estimated as close as possible to the actual data during video error concealment process. Blocks or slices of information in the video frames can be missing in the decoder due to various reasons like corrupt media drives, network congestion, etc. which reduces the quality of experience for the viewers. One approach to deal with missing information in the video decoder is to use error concealment techniques to fill the missing information. Until now many of these error concealment techniques were based on conventional methods such as block copy, motion vector prediction, and interpolation. …

Prenatal Exposure To Per- And Polyfluoroalkyl Substances And Child Neurodevelopment, Jiwon Oh

Earth & Environmental Sciences Dissertations

Pregnant women are exposed to per- and polyfluoroalkyl substances (PFAS) primarily via ingestion of contaminated food, water, and house dust. PFAS in pregnant women can be transferred to their child through the placenta during pregnancy. Many long-chain PFAS have been frequently detected in blood of pregnant women, amniotic fluid, and umbilical cord blood for the last few decades. Prenatal exposure to PFAS has shown potential to adversely affect offspring’s neurodevelopment in laboratory animals. However, epidemiological evidence on associations between prenatal PFAS exposure and child neurodevelopment remains inconsistent. My dissertation research consists of four sub-studies whose objectives are (1) to examine …

Extracting Clinical Event Sequence By Using Association Rule Mining To Predict Clinical Events From Health Records, Aashara Shrestha

Computer Science and Engineering Dissertations

Data mining is the process of extracting useful information from large amounts of data. Data mining has been around for a long time, and there are many multiple methods of performing data mining. However, the abundance of data that has become available in the last decade has made it possible to mine through this data to uncover important patterns and sequences. The relationship between variables and the way in which they can lead to a specific outcome is an interesting area of research. Today's healthcare industry faces a number of challenges. Providers must reduce costs, improve transparency, and improve the …

Aqueous-Based Associated Solvents For Protein And Peptide Fractionation And Protein Purification, Sajad Tasharofi

Chemistry & Biochemistry Dissertations

The focus of this dissertation is studying capabilities of a novel two-phase system in enhancing protein identification in the whole-cell proteomics studies. In this document, two types of biphasic systems have been used for two different purposes. The first type of biphasic system is formed by the addition of 1,1,1,3,3,3-Hexafluoro-2-propanol (HFIP) to the aqueous solutions of water-miscible organic solvents. A combination of HFIP, organic solvent, and water forms a two-phase system in spite of the fact that every solvent pair in the three-component system is miscible and forms homogeneous solutions in water. This biphasic system is called Fluoroalcohol-Organic Associated Solvent …

Multinuclear Copper(I) And Silver(I) Pyrazolates: Synthesis, Luminescence, And Catalysis, Monika R. Patterson

Chemistry & Biochemistry Dissertations

Copper and silver pyrazolate complexes have numerous fascinating properties such as luminescence, catalytic ability, and complexation with small molecules. Using both more widely studied non-fluorinated pyrazolates and less common highly fluorinated pyrazolates as supporting ligands, we successfully synthesized and investigated several new coinage metal complexes. Synthetic details, structures, and properties i.e., luminescence and catalytic ability, have been studied. Chapter 2 of this research describes the synthesis of a new pyrazole with highly fluorinated aryl groups and corresponding trinuclear copper(I), silver(I), and gold(I) complexes. All three metal complexes exhibit bright blue luminescence under exposure to UV light. Additionally, the copper(I) complex …

Temperature-Pressure Phase Diagrams Of Metal Nitrogen Compounds Through Density Functional Theory Computations And Thermodynamic Calculations, Hanof Alkhaldi

Chemistry & Biochemistry Dissertations

The need for novel materials for new generations of applications is growing tremendously. One of many pathways to attain new materials is the route of high pressure synthesis. A particular active area in this high–pressure research is to attain nitrogen-rich compounds. Many of these compounds discovered over the last decades have a potential use as hard material or as high–energy storage material. While it is not possible to predict a potential application for a compound before its experimental realization, it is worthy to explore beforehand what opportunities may exist. This kind of targeted development requires understanding of the synthesis process, …

Fluoroalcohol Induced Supramolecular Biphasic Systems Of Zwitterionic Surfactants, Mixed Amphiphiles, And Polar Organic Solvents In Proteomics And Environmental Analysis, Durga Khanal

Chemistry & Biochemistry Dissertations

In this research, we have investigated several HFIP-induced biphasic systems of zwitterionic surfactants like CHAPS and DMMAPS and their mixed amphiphilic systems for the extraction, enrichment, and fractionation of mixture of standard proteins and complex sample mixture of yeast proteins. The biphasic systems of zwitterionic surfactants (CHAPS and DMMAPS) and their mixed amphiphiles with quaternary ammonium salts (QUATS= TBAB, TEAB) provide concomitant extraction of hydrophobic membrane proteins, enrichment of lower abundance proteins to one phase, and fractionation of complex sample mixture into two phases. The results obtained from these biphasic systems were compared with control systems of aqueous solutions of …

Study Of Barrier Heights And Magnetic Property Using Locally Scaled And Perdew-Zunger Self-Interaction Methods, Prakash Mishra

Open Access Theses & Dissertations

Kohn-Sham density functional theory is a widely used method to estimate the ground state total energies and densities of interacting correlated electronic structures of atoms, molecules, clusters, solids, and liquids. In theory, exact solutions for these properties can be obtained by solving self-consistent one-electron Schrodinger equations based on density functionals for the energy.The practical application of KS DFT require approximation to the exchange-correlation energy functional. Many density functional approximations (DFAs) have been developed with various degree of sophistication and complexity by the satisfaction of exact constraints. Depending on the complexity, these functionals include electron density, density gradients, density Laplacian, kinetic …

Electroluminescent Signals And Cosmogenicbackgrounds In High Pressure Xenon Gas Timeprojection Detectors, Leslie Rogers

Physics Dissertations

The NEXT collaboration is developing a sequence of high pressure xenon gas time projection chambers with the aim of creating a ton-scale, very low background neutrinoless double beta decay search. Finding evidence of neutrinoless double beta decay would give insight into the origins of the matter-antimatter asymmetry in the universe, the smallness of neutrino mass, and the symmetry structure of the Standard Model. My research involves addressing critical challenges on the path to realization of high pressure xenon gas detectors for ton-scale, very low background neutrinoless double beta decay searches. While most aspects of this technology are easily scalable, some …

Orbital Evolution Studies And Radio Searches Of Extra-Solar Moons, Marialis Rosario-Franco

Physics Dissertations

Exoplanetary research has undergone a great deal of development and growth. Achievements in theoretical studies and detection techniques have led to the discovery of 4,000+ exoplanets in ~3, 000 planetary systems to date. Despite this great success, and though candidates have been proposed, the confirmation of the first exomoon is yet to be accomplished. Understanding the constraints under which extrasolar moons form around exoplanets can provide insight into the overall formation of the system, the host planet’s habitability, and could even aid the process of drawing out the best observational candidates for exomoon searches. This work entails the use of …

Gpu-Based Monte Carlo Applications In Radiation Medicine, Youfang Lai

Physics Dissertations

Radiation can be used to image tumor site or kill tumor cells noninvasively, playing an important role in tumor diagnosis and treatment. Because of the increasing burden that cancer brings to the society, there always exists the demand of improving imaging resolution and contrast and improving radiation conformity for therapy. This depends on not only the advances of techniques, but, probably more importantly, the accurate and efficient modelling of radiation transport, enabling research on proof-of-concept for new tech and more complicated physics and chemical process in a quantitative way. Monte Carlo (MC) simulation method has been extensively used in medical …

The Arecibo Observatory As An Instrument For Investigating Orbital Debris, James Isaiah Murray

Physics Dissertations

In this dissertation, the Arecibo Observatory, both past and future, as an instrument for investigating orbital debris is investigated. For over three decades, models of the orbital debris environment in low Earth orbit (LEO) have been developed to assess the risk posed by orbital debris to spacecraft. While terrestrial radar measures debris 3 mm and larger and in-situ measurements provide data for debris smaller than 1 mm, no good data sources exist for debris between 1 mm and 3 mm in size. This results in large variations between competing orbital debris models. It also happens to be the size regime …

Nonlinear Mode Coupling Coefficients In Extrasolar Hot Jupiter Systems With Non-Solar Type Host Stars, Niyousha Davachi

Physics Theses

Short period planets tidally excite internal gravity modes within their host star. These excited modes, known collectively as the dynamical tide, dissipate orbital energy and cause the planet’s orbit to decay. In hot Jupiter systems, resonantly excited gmodes are driven to such large amplitudes in the stellar core that they nonlinearly excite a sea of secondary modes. These secondary modes can greatly enhance the efficiency of tidal dissipation compared to linear theory predictions and thus significantly increase the rate of orbital decay. In this thesis we calculate the three-mode coupling coefficients between the excited g-modes of hot Jupiter host stars. …

Energy Dissipation During Geomagnetic Storms, Fatemeh Bagheri

Physics Dissertations

Some fraction of the solar wind energy is transferred to the Earth magnetosphere and ionosphere. Sometimes this transfer of energy is exceptionally large, producing a magnetic storm. Storms occur when the Interplanetary Magnetic Field (IMF) turns southward and remains southward for an extended period of time. During the main phase of many magnetic storms, the solar wind Mach number is low, and IMF magnitude is large. Under these conditions, the ionospheric potential saturates, and it becomes relatively insensitive to further increases in the IMF magnitude. On the other hand, the dayside merging rate and the potential become sensitive to the …

An Analysis Of Significant Cyber Incidents And The Impact On The Past, Present, And Future, Seth E. Smith

Cybersecurity Undergraduate Research Showcase

This report discusses data collected on significant cybersecurity incidents from the early 2000s to present. The first part of the report addresses previously discussed information, data, and literature (e.g. case studies), pertinent to cybersecurity incidents. The findings from this study are framed by scholarly sources and information from the Federal Bureau of Investigation, a number of notable universities, and literature online, of which all support information discussed within this report. The second part of the report discusses data compiled upon analyzing significant cyber incidents and events from the Center for Strategic and International Affairs (CSIS). Finally, the last portion of …

Utilizing High Throughput Computing Techniques For The Predictions Of Spectroscopic Properties Of Astrophysically Relevant Molecules, Brian Ferrari

Electronic Theses and Dissertations, 2020-2023

Here, we utilize Quantum Chemistry (QC) approaches to predict the structures, vibrational frequencies, infrared intensities and Raman activities of unusual molecular species using the General Atomic and Molecular Structure System (GAMESS(US)) package. A Python-based software, AutoGAMESS, was developed to automate the workflow and take advantage of High Throughput Computing (HTC) techniques enabling the automated generation of spectroscopic data from hundreds of calculations. This approach was utilized to determine these properties for a series of carbon oxides (C2On; n = 3 to 4), anticipated to be produced during the radiation of pure carbon dioxide ices, under conditions relevant to the interstellar …

Spectral Dependence Of Deep Subwavelength Metallic Apertures In The Mid-Wave Infrared, Heath Gemar

Electronic Theses and Dissertations, 2020-2023

For two decades, extraordinary optical transmission (EOT) has amplified exploration into subwavelength systems. Researchers have previously suggested exploiting the spectrally selective electromagnetic field confinement of subwavelength cavities for multispectral detectors. Utilizing the finite-difference frequency domain (FDFD) method, we examine electromagnetic field confinement in both 2-dimensional and 3-dimensional scenarios from 2.5 to 6 microns (i.e., mid-wave infrared or MWIR). We explore the trade space of deep subwavelength cavities and its impact on resonant enhancement of the electromagnetic field. The studies provide fundamental understanding of the coupling mechanisms allowing for prediction of resonant spectral behavior based on cavity geometry and material properties. …

Machine Learning Techniques For Topic Detection And Authorship Attribution In Textual Data, Fereshteh Jafariakinabad

Electronic Theses and Dissertations, 2020-2023

The unprecedented expansion of user-generated content in recent years demands more attempts of information filtering in order to extract high-quality information from the huge amount of available data. In this dissertation, we begin with a focus on topic detection from microblog streams, which is the first step toward monitoring and summarizing social data. Then we shift our focus to the authorship attribution task, which is a sub-area of computational stylometry. It is worth mentioning that determining the style of a document is orthogonal to determining its topic, since the document features which capture the style are mainly independent of its …

Nonlinear Light-Matter Interactions In Novel Crystals For Broadband Mid-Infrared Generation, Taiki Kawamori

Electronic Theses and Dissertations, 2020-2023

Mid-infrared (MIR) laser sources have demonstrated diverse applications in science and technology. For spectroscopy applications, numerous molecules have unique absorption features in this range, and one needs a spectrally broad coherent laser source for parallel detection of mixtures of species. Frequency down-conversion in nonlinear optical materials via second-order nonlinear susceptibility is one of the promising techniques to generate the spectral coverage of more than an octave in the MIR, assisted by emerging novel crystals. The nonlinear light-matter interactions in such special crystals as ZnSe ceramics have not been analyzed. Additionally, through the use of high-intensity few-cycle optical pulses, high-order nonlinear …

The Social And Behavioral Influences Of Interactions With Virtual Dogs As Embodied Agents In Augmented And Virtual Reality, Nahal Norouzi

Electronic Theses and Dissertations, 2020-2023

Intelligent virtual agents (IVAs) have been researched for years and recently many of these IVAs have become commercialized and widely used by many individuals as intelligent personal assistants. The majority of these IVAs are anthropomorphic, and many are developed to resemble real humans entirely. However, real humans do not interact only with other humans in the real world, and many benefit from interactions with non-human entities. A prime example is human interactions with animals, such as dogs. Humans and dogs share a historical bond that goes back thousands of years. In the past 30 years, there has been a great …

High Spectral Brightness, Broad Area Quantum Cascade Lasers, Enrique Sanchez Cristobal

Electronic Theses and Dissertations, 2020-2023

Quantum cascade lasers are unipolar semiconductor lasers that offer a unique combination of compact size, high efficiency, high optical power, and flexibility to achieve a targeted emission wavelength with the same laser core material composition, employing so-called bandgap engineering. Since their invention in 1994, watt-level CW power with 5 to 20 % wallplug efficiency was demonstrated for QCLs throughout the entire 4 to 12 µm range, which makes QCLs very attractive for a number of practical applications. Our earlier work on broad-area QCLs emitting in the 4.6 µm to 5.7 µm spectral range demonstrated that CW power scaling with lateral …

2021 December - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

Comparative Analysis Of Kmer Counting And Estimation Tools, Ankitha Vejandla

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The rapid development of next-generation sequencing (NGS) technologies for determining the sequence of DNA has revolutionized genome research in recent years. De novo assemblers are the most commonly used tools to perform genome assembly. Most of the assemblers use de Bruijn graphs that break the sequenced reads into smaller sequences (sub-strings), called kmers, where k denotes the length of the sub-strings. The kmer counting and analysis of kmer frequency distribution are important in genome assembly. The main goal of this research is to provide a detailed analysis of the performance of different kmer counting and estimation tools that are currently …

Agent Based Modeling Of The Spread Of Social Unrest Based On Infectious Disease Spread Model, Anup Adhikari

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Social unrest activities are the tools for people to show dissatisfaction, and often people are motivated by similar unrest activities in another region. This causes a spread of unrest activities across space and time. In this thesis, we model the spread of social unrest across time and space. The underlying novel methodology is to model the regions as agents that transition from one state to another based on changes in their environment. The methodology involves (1) creating a region vector for each agent based on socio-demographic, cultural, economic, infrastructural, geographic, and environmental (SCEIGE) factors, (2) formulating neighborhood distance function to …

Quantum State Estimation And Tracking For Superconducting Processors Using Machine Learning, Shiva Lotfallahzadeh Barzili

Computational and Data Sciences (PhD) Dissertations

Quantum technology has been rapidly growing; in particular, the experiments that have been performed with superconducting qubits and circuit QED have allowed us to explore the light-matter interaction at its most fundamental level. The study of coherent dynamics between two-level systems and resonator modes can provide insight into fundamental aspects of quantum physics, such as how the state of a system evolves while being continuously observed. To study such an evolving quantum system, experimenters need to verify the accuracy of state preparation and control since quantum systems are very fragile and sensitive to environmental disturbance. In this thesis, I look …

An Information-Theoretic Analysis Of Adherence To Physical Exercise Routines, Lily Foster

Computational and Data Sciences (MS) Theses

One of the most common recommendations in healthcare is to simply form healthy habits, but little research has been done to understand the formation and continuation of a healthy habit that isn’t heavily influenced by an individual’s interpretation. Arizona State University’s WalkIT study aimed to analyze how goal setting and financial reinforcement can influence moderate-to-vigorous physical activity (MVPA) in adults, while using data from accelerometers to alleviate individual bias. In this trial, 512 insufficiently active adults were recruited to wear an accelerometer for 1 year and were then randomly assigned to one of the four study groups. Each group had …

Numerical Studies Of Regularized Navier-Stokes Equations And An Application Of A Run-To-Run Control Model For Membrane Filtration At A Large Urban Water Treatment Facility, Jeffrey Belding

UNLV Theses, Dissertations, Professional Papers, and Capstones

This dissertation consists of two parts. The first part consists of research on accurate and efficient turbulent fluid flow modeling via a family of regularizations of the Navier-Stokes equation which are known as Time Relaxation models. In the second part, we look into the modeling application for the filtration/backwash process at the River Mountains Water Treatment Facility in Henderson, NV.

In the first two chapters, we introduce the Time Relaxation models and their associated differential filter equations. In addition, we develop the regularization method which employs the Nth van Cittert deconvolution operator, which gives rise to the family of models. …

From Language Comprehension Towards General Ai, Binay Dahal

UNLV Theses, Dissertations, Professional Papers, and Capstones

Language comprehension or more formally, natural language understanding is one of the major undertakings in Artificial Intelligence. In this work, we explore a few of the problems in language understanding using fixed deep learning models. Specifically, first, we look into question generation. Asking questions relates to the cognitive ability of language comprehension and context understanding. For that reason, making progress in question generation is significant. We introduce a novel task called “question generation with masked target answer” and propose various models and present the baseline result for the task. Next, we extend on the question generation task and develop a …

Calculating The Learning Rate Of A Neural Network Using A Genetic Algorithm, Eric Miller

UNLV Theses, Dissertations, Professional Papers, and Capstones

In the field of Computer Science, neural networks and genetic algorithms have become very popular tools in solving complex problems. Because of this growing popularity, there has been several attempts to combine the two concepts. Some of these attempts focused on using genetic algorithms to determine the best architecture, starting weights, or feature selection, to name of few of the applications. While a lot of the research that is available focuses on solving more than one element of the neural network design or is looking to use genetic algorithms to replace a part of the traditional neural network, such as …