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Articles 301 - 330 of 3961

Full-Text Articles in Physical Sciences and Mathematics

Exploring The Multiplex Detection Capabilities Of Raman Spectroscopy On Mock Street Samples Containing Illicitly Manufactured Fentanyls, Mia Laverne Williams Burnett Jan 2020

Exploring The Multiplex Detection Capabilities Of Raman Spectroscopy On Mock Street Samples Containing Illicitly Manufactured Fentanyls, Mia Laverne Williams Burnett

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Illicitly manufactured fentanyls (IMFs) have become a global and local epidemic and have recently caused an increase in the number of accidental exposures and overdoses in first responders and the community. The aim of the research is to explore a method to discriminate between IMFs and cutting agents in mock street samples using Raman Spectroscopy. Predominant Raman bands corresponding to the structural moieties of each individual illicit, licit drugs, and cutting agents were tracked, then used to discriminate between varying components in a mock street sample. In conclusion, discrimination between the components in the mixture was obtained using Raman Spectroscopy. …

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Finding Pythagoras In The Pythagoreans, Brandon Barnes Jan 2020

Finding Pythagoras In The Pythagoreans, Brandon Barnes

Classics Ancient Science Fair

This presentation for the Ancient Science Fair deals with the Pythagorean Theorem. Since Pythagoras himself did not write down his work, early scholars had to work to find the knowledge and unify it among differing sources.

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Completion Reasoning Emulation For The Description Logic El+, Aaron Eberhart, Monireh Ebrahimi, Lu Zhou, Cogan Shimizu, Pascal Hitzler Jan 2020

Completion Reasoning Emulation For The Description Logic El+, Aaron Eberhart, Monireh Ebrahimi, Lu Zhou, Cogan Shimizu, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We present a new approach to integrating deep learning with knowledge-based systems that we believe shows promise. Our approach seeks to emulate reasoning structure, which can be inspected part-way through, rather than simply learning reasoner answers, which is typical in many of the black-box systems currently in use. We demonstrate that this idea is feasible by training a long short-term memory (LSTM) artificial neural network to learn εℒ+ reasoning patterns with two different data sets. We also show that this trained system is resistant to noise by corrupting a percentage of the test data and comparing the reasoner’s and LSTM’s …

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The Development Of Pet Imaging Agents For Neurodegenerative Disorders, Christine Morgan Kinstedt Jan 2020

The Development Of Pet Imaging Agents For Neurodegenerative Disorders, Christine Morgan Kinstedt

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With the intent to synthesize a potent and viable PET imaging agent for Alzheimer’s disease and/or Parkinson’s disease utilizing tau protein aggregates or alpha-synuclein aggregates as the ailments’ respective targets, researchers in this investigation synthesized derivatives of the chalcone scaffold in order to determine a lead molecule for further drug development. This molecular structure, which due to its ability to cross the blood brain barrier (BBB), has demonstrated efficiency in a number of neurodegenerative diseases and constitutes a convenient starting point for the development of potential imaging agents for Alzheimer’s and Parkinson’s diseases. Since simple chalcones have been demonstrated to …

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Scalable, Pluggable, And Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems, Michael Partin Jan 2020

Scalable, Pluggable, And Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems, Michael Partin

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Features and attributes that describe an event (disasters, social movements, etc.) are heterogeneous in nature. For virtually all events that impact humans, technology enables us to capture a large amount and variety of data from many sources, including humans (i.e., social media) and sensors/internet of things (IoTs). The corresponding modalities of data include text, imagery, voice and video, along with structured data such as gazetteers (i.e., location-based data) and government and statistical data. However, even though there is often an abundance of information produced, this information is fragmented across the various modalities and sources. The DisasterRecord system aims to provide …

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Towards Interpretable And Reliable Deep Neural Networks For Visual Intelligence, Ning Xie Jan 2020

Towards Interpretable And Reliable Deep Neural Networks For Visual Intelligence, Ning Xie

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Deep Neural Networks (DNNs) are powerful tools blossomed in a variety of successful real-life applications. While the performance of DNNs is outstanding, their opaque nature raises a growing concern in the community, causing suspicions on the reliability and trustworthiness of decisions made by DNNs. In order to release such concerns and towards building reliable deep learning systems, research efforts are actively made in diverse aspects such as model interpretation, model fairness and bias, adversarial attacks and defenses, and so on. In this dissertation, we focus on the research topic of DNN interpretations for visual intelligence, aiming to unfold the black-box …

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Improving Pain Management In Patients With Sickle Cell Disease Using Machine Learning Techniques, Fan Yang Jan 2020

Improving Pain Management In Patients With Sickle Cell Disease Using Machine Learning Techniques, Fan Yang

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Sickle cell disease (SCD) is an inherited red blood cell disorder that can cause a multitude of complications throughout a patient's life. Pain is the most common complication and a significant cause of morbidity. Since pain is a highly subjective experience, both medical providers and patients express difficulty in determining ideal treatment and management strategies for pain. Therefore, the development of objective pain assessment and pain forecasting methods is critical to pain management in SCD. On the other hand, the rapidly increasing use of mobile health (mHealth) technology and wearable devices gives the ability to build a remote health intervention …

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Enabling Static Program Analysis Using A Graph Database, Jialun Liu Jan 2020

Enabling Static Program Analysis Using A Graph Database, Jialun Liu

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This thesis presents the design, the implementation, and the evaluation of a database-oriented static program analysis engine for the PHP programming language. This engine analyzes PHP programs by representing their semantics using a graph-based data structure, which will be subsequently stored into a graph database. Such scheme will fundamentally facilitate various program analysis tasks such as static taint analysis, visualization, and data mining. Specifically, these complex program analysis tasks can now be translated into built-in declarative graph database operations with rich features. Our engine fundamentally differs from other existing static program analysis systems that mainly leverage intermediate representation (IRs) to …

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Investigating Heterogeneous Nucleation Of Barite Using Hydrothermal Atomic Force Microscopy And Optical Microscopy, Ankita B. Gurav Jan 2020

Investigating Heterogeneous Nucleation Of Barite Using Hydrothermal Atomic Force Microscopy And Optical Microscopy, Ankita B. Gurav

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In order to develop a better understanding heterogeneous nucleation of barite, barite precipitation was studied under varying experimental parameters. Hydrothermal atomic force microscopy (HAFM) and optical microscopy were used to investigate the effect of change in temperature, supersaturation and varying ratios of ions on heterogeneous nucleation of barite. In the experiments conducted at higher temperatures, the particles thus nucleated were found to display characteristic hexagonal and rhomboidal shapes. In comparing results of particle densities among different ion ratios, there is evidence suggesting that barium to sulfate ratio plays a role of promoter. Wherein, the ratios with higher [Ba2+] concentration were …

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Evolution Of Electron Properties After Nanosecond Repetitively Pulsed Discharges In Air Measured By Thomson Scattering, Chase S. Murray Jan 2020

Evolution Of Electron Properties After Nanosecond Repetitively Pulsed Discharges In Air Measured By Thomson Scattering, Chase S. Murray

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This work was an investigation of nanosecond repetitively pulsed discharges in air by measuring the evolution of electron density and electron temperature between pulses using Thomson scattering of laser light. Bursts of repetitive pulses within several microseconds after the initial pulse were found to exhibit a coupling effect and create an even higher electron density than the initial pulse. The wide range of temperatures and densities of the electrons existing between pulses allow an opportunity to explore both the collective and non-collective regimes of Thomson scattering. By measuring electron density and temperature at a variety of times, an accurate description …

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Topological Analysis Of Averaged Sentence Embeddings, Wesley J. Holmes Jan 2020

Topological Analysis Of Averaged Sentence Embeddings, Wesley J. Holmes

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Sentence embeddings are frequently generated by using complex, pretrained models that were trained on a very general corpus of data. This thesis explores a potential alternative method for generating high-quality sentence embeddings for highly specialized corpora in an efficient manner. A framework for visualizing and analyzing sentence embeddings is developed to help assess the quality of sentence embeddings for a highly specialized corpus of documents related to the 2019 coronavirus epidemic. A Topological Data Analysis (TDA) technique is explored as an alternative method for grouping embeddings for document clustering and topic modeling tasks and is compared to a simple clustering …

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Design Of A Novel Wearable Ultrasound Vest For Autonomous Monitoring Of The Heart Using Machine Learning, Garrett G. Goodman Jan 2020

Design Of A Novel Wearable Ultrasound Vest For Autonomous Monitoring Of The Heart Using Machine Learning, Garrett G. Goodman

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As the population of older individuals increases worldwide, the number of people with cardiovascular issues and diseases is also increasing. The rate at which individuals in the United States of America and worldwide that succumb to Cardiovascular Disease (CVD) is rising as well. Approximately 2,303 Americans die to some form of CVD per day according to the American Heart Association. Furthermore, the Center for Disease Control and Prevention states that 647,000 Americans die yearly due to some form of CVD, which equates to one person every 37 seconds. Finally, the World Health Organization reports that the number one cause of …

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Community Structure Has Greater Effect On Water Column Ammonium Cycling Than Nutrients And Temperature In Shallow Lake Mesocosms, Shannon Marie Collins Jan 2020

Community Structure Has Greater Effect On Water Column Ammonium Cycling Than Nutrients And Temperature In Shallow Lake Mesocosms, Shannon Marie Collins

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Harmful algal blooms (HABs) impact lakes worldwide and are caused by excess nitrogen (N) and phosphorus (P) loading from watersheds. Climate warming and nutrient loading effects on N cycling were examined in shallow lake mesocosms in Denmark. N loading to some mesocosms ceased in June 2018 and resumed in June 2019. Ammonium (NH4+) uptake, regeneration, and nitrification and nitrate uptake rates were evaluated. High nutrient, ambient temperature mesocosms exhibited the highest NH4+ cycling rates. Before resumption of N loading in high nutrient mesocosms, NH4+ regeneration supported 46 % of potential microbial NH4+ demand, versus 24 % with N loading. Nutrient …

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Quantum Chemical Pka Estimation Of Carbon Acids, Saturated Alcohols, And Ketones Via Quantitative Structure-Activity Relationships, Corey Adam Baldasare Jan 2020

Quantum Chemical Pka Estimation Of Carbon Acids, Saturated Alcohols, And Ketones Via Quantitative Structure-Activity Relationships, Corey Adam Baldasare

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Acid dissociation constants, often expressed as pKa values, afford vital information with regards to molecular behavior in various environments and are of significance in fields of organic, inorganic, and medicinal chemistry. Several quantitative structure-activity relationships (QSARs) were developed that correlate experimental pKas for a given class of compounds with a descriptor(s) calculated using density functional theory at the B3LYP/6-31+G** level utilizing the CPCM solvent model. A set of carbon acids provided a good final QSAR model of experimental aqueous pKas versus ΔEH2O (R2 = 0.9647) upon removal of three aldehydes as outliers. A study of saturated alcohols offered a final …

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Geoaware - A Simulation-Based Framework For Synthetic Trajectory Generation From Mobility Patterns, Jameson D. Morgan Jan 2020

Geoaware - A Simulation-Based Framework For Synthetic Trajectory Generation From Mobility Patterns, Jameson D. Morgan

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Recent advances in location acquisition services have resulted in vast amounts of trajectory data; providing valuable insight into human mobility. The field of trajectory data mining has exploded as a result, with literature detailing algorithms for (pre)processing, map matching, pattern mining, and the like. Unfortunately, obtaining trajectory data for the design and evaluation of such algorithms is problematic due to privacy, ethical, dataset size, researcher access, and sampling frequency concerns. Synthetic trajectories provide a solution to such a problem as they are cheap to produce and are derived from a fully controllable generation procedure. Citing deficiencies in modern synthetic trajectory …

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Extracting Information From Subroutines Using Static Analysis Semantics, Luke A. Burnett Jan 2020

Extracting Information From Subroutines Using Static Analysis Semantics, Luke A. Burnett

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Understanding how a system component can interact with other services can take an immeasurable amount of time. Reverse engineering embedded and large systems can rely on understanding how components interact with one another. This process is time consuming and can sometimes be generalized through certain behavior.We will be explaining two such complicated systems and highlighting similarities between them. We will show that through static analysis you can capture compiler behavior and apply it to the understanding of a function, reducing the total time required to understand a component of whichever system you are learning.

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Predicting Subjective Sleep Quality Using Objective Measurements In Older Adults, Reza Sadeghi Jan 2020

Predicting Subjective Sleep Quality Using Objective Measurements In Older Adults, Reza Sadeghi

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Humans spend almost a third of their lives asleep. Sleep has a pivotal effect on job performance, memory, fatigue recovery, and both mental and physical health. Sleep quality (SQ) is a subjective experience and reported via patients’ self-reports. Predicting subjective SQ based on objective measurements can enhance diagnosis and treatment of SQ defects, especially in older adults who are subject to poor SQ. In this dissertation, we assessed enhancement of subjective SQ prediction using an easy-to-use E4 wearable device, machine learning techniques and identifying disease-specific risk factors of abnormal SQ in older adults. First, we designed a clinical decision support …

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Identifying Knowledge Gaps Using A Graph-Based Knowledge Representation, Daniel P. Schmidt Jan 2020

Identifying Knowledge Gaps Using A Graph-Based Knowledge Representation, Daniel P. Schmidt

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Knowledge integration and knowledge bases are becoming more and more prevalent in the systems we use every day. When developing these knowledge bases, it is important to ensure the correctness of the information upon entry, as well as allow queries of all sorts; for this, understanding where the gaps in knowledge can arise is critical. This thesis proposes a descriptive taxonomy of knowledge gaps, along with a framework for automated detection and resolution of some of those gaps. Additionally, the effectiveness of this framework is evaluated in terms of successful responses to queries on a knowledge base constructed from a …

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Intersections Of Deleted Digits Cantor Sets With Gaussian Integer Bases, Vincent T. Shaw Jan 2020

Intersections Of Deleted Digits Cantor Sets With Gaussian Integer Bases, Vincent T. Shaw

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In this paper, the intersections of deleted digits Cantor sets and their fractal dimensions were analyzed. Previously, it had been shown that for any dimension between 0 and the dimension of the given deleted digits Cantor set of the real number line, a translate of the set could be constructed such that the intersection of the set with the translate would have this dimension. Here, we consider deleted digits Cantor sets of the complex plane with Gaussian integer bases and show that the result still holds.

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Introducing Functionality To Poly(Arylene Ether)S Via Modification Of Diphenyl Sulfone – Type Monomers, Zahida Humayun Jan 2020

Introducing Functionality To Poly(Arylene Ether)S Via Modification Of Diphenyl Sulfone – Type Monomers, Zahida Humayun

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The synthesis of poly(arylene ether)s, with a pendent aryl iodide, was achieved via nucleophilic aromatic substitution (NAS) polycondensation of DI-DFDPS monomer. The platform diiodo-difluorodiphenyl sulfone monomer, DFDPS-DI (3), was prepared in one-step, via EAS chemistry. Structural characterization was provided by NMR spectroscopy, GC/MS, and elemental analysis. As “pre” approach didn’t work here, so “post” approach was used to synthesize N-heterocycle functionalized copolymers. The DI-copolymers were subjected to copper-catalyzed C-N coupling reaction with carbazole, phenoxazine, and indole and the syntheses of chromophore based copolymer were successfully carried out. A series of PAEs containing carbazole, phenoxazine, and indole substituents were synthesized and …

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Stream Clustering And Visualization Of Geotagged Text Data For Crisis Management, Nathaniel C. Crossman Jan 2020

Stream Clustering And Visualization Of Geotagged Text Data For Crisis Management, Nathaniel C. Crossman

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In the last decade, the advent of social media and microblogging services have inevitably changed our world. These services produce vast amounts of streaming data, and one of the most important ways of analyzing and discovering interesting trends in the streaming data is through clustering. In clustering streaming data, it is desirable to perform a single pass over incoming data, such that we do not need to process old data again, and the clustering model should evolve over time not to lose any important feature statistics of the data. In this research, we have developed a new clustering system that …

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Quantifying Contributions To The Variance Of Permeability And Porosity Within The Western Belt Sandstones Of The Cypress Formation, Illinois Basin, Nathaniel Frederick Dulaney Jan 2020

Quantifying Contributions To The Variance Of Permeability And Porosity Within The Western Belt Sandstones Of The Cypress Formation, Illinois Basin, Nathaniel Frederick Dulaney

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One of the strategies for reducing the emission of the greenhouse gas carbon dioxide (CO2) and mitigating its accumulation into the Earth’s atmosphere is geologic sequestration (GSCO2). This process might be paired with enhanced oil recovery (EOR) within depleted oil reservoirs to provide an economic incentive for GSCO2. Heterogeneity within reservoirs (e.g. spatial differences in entry pressure, permeability, and porosity) can exert significant influence on the dynamics of fluid flow during EOR and GSCO2, and thus on the ultimate success of GSCO2-EOR. The Western Belt sandstones of the Cypress Formation in the Illinois Basin are candidate reservoirs for GSCO2-EOR. Heterogeneity …

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Optimization Study Of A Combined Wind-Solar Farm For A Specified Demand, Venkat Siddhartha Rama Jan 2020

Optimization Study Of A Combined Wind-Solar Farm For A Specified Demand, Venkat Siddhartha Rama

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At the present time, using wind and solar energy for producing electricity in the United States is becoming cost competitive. According to Lazard’s 2019 [36] levelized cost of energy (LCOE) analysis of a number of energy sources used for producing electricity in the United States, wind and solar are cheaper than natural gas and coal. While capital, maintenance, operation, and fuel costs are included in LCOE numbers, energy source intermittency is not. Intermittency is an important issue with wind and solar energy sources, but not with natural gas or coal energy sources. Combining wind and solar energy sources into one …

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Targeting Oncogenic K-Ras And Monoamine Oxidase B Utilizing Chalcones Bearing The 3,4,5-Trimethoxyphenyl Motif, Cody Fourman Jan 2020

Targeting Oncogenic K-Ras And Monoamine Oxidase B Utilizing Chalcones Bearing The 3,4,5-Trimethoxyphenyl Motif, Cody Fourman

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Oncogenic K-Ras is a driver protein found in specific cancers and was once thought to be “undruggable.” However, recent advances have suggested that mislocalizing K-Ras from the plasma membrane could be a viable strategy to target these cancers. The objective of this project was to identify a lead compound and determine a structure-activity relationship from chalcones bearing the 3,4,5-trimethoxy motif towards oncogenic K-Ras and MAO-B. This was accomplished by keeping the trimethoxy group consistent on one ring while varying the electron-donating or -withdrawing groups on the opposite ring. Previous work showed chalcones of this specific archetype exhibiting indiscriminate MAO inhibition, …

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An Adversarial Framework For Deep 3d Target Template Generation, Walter E. Waldow Jan 2020

An Adversarial Framework For Deep 3d Target Template Generation, Walter E. Waldow

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This paper presents a framework for the generation of 3D models. This is an important problem for many reasons. For example, 3D models are important for systems that are involved in target recognition. These systems use 3D models to train up accuracy on identifying real world object. Traditional means of gathering 3D models have limitations that the generation of 3D models can help overcome. The framework uses a novel generative adversarial network (GAN) that learns latent representations of two dimensional views of a model to bootstrap the network’s ability to learn to generate three dimensional objects. The novel architecture is …

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The Fate Of Anthropogenic Nitrogen Along Hydrologic Continuums: Patterns Of Transformation And Recycling In A Eutrophic Lake And Coastal Marine Sediments, Daniel K. Hoffman Jan 2020

The Fate Of Anthropogenic Nitrogen Along Hydrologic Continuums: Patterns Of Transformation And Recycling In A Eutrophic Lake And Coastal Marine Sediments, Daniel K. Hoffman

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Eutrophication of aquatic systems can have cascading effects along hydrological continua from watersheds to coasts that result in impaired ecosystem health. In freshwater systems, blooms of toxic, non-nitrogen (N) fixing cyanobacteria (cyanoHABs), such as Microcystis, proliferate due to external loading of chemically reduced forms of N (e.g., ammonium (NH4+) and urea), which promote growth and toxin production. In coastal marine systems, nutrient loading can promote harmful algae blooms and threaten vulnerable, native vegetation, such as seagrasses, which provide valuable ecosystem services but are under threat globally from anthropogenic stressors. This dissertation focuses on NH4+ cycling in the water column of …

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Degradation Of Trichloroethene By Radicals Produced By Oxygenation Of Various Reduced Iron Minerals, Jonathon Michael Deeter Jan 2020

Degradation Of Trichloroethene By Radicals Produced By Oxygenation Of Various Reduced Iron Minerals, Jonathon Michael Deeter

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Fe(II)-containing minerals (often as oxides and sulfides) are commonly present in the shallow subsurface and aquifers. Recent studies have shown that Fe(II) can generate reactive oxygen species upon oxygenation. This bench-scale investigation examined the generation of radical species from [Fe(II)]-containing mineral phases when exposed to oxygen. The Fe(II)-minerals in this study were chemically-reduced hydrous ferric oxide (HFO) and goethite, magnetite, and mackinawite (FeS). This research demonstrated that trichloroethene (TCE) can rapidly degrade by radicals produced from Fe(II)-containing oxides if gaseous oxygen is introduced in reactors. In contrast, there was little or no TCE degradation from oxygenation of freshly-prepared ferrous sulfide …

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Marine Vertebrate Communities From The Cisuralian Epoch (Permian Period) Of Central North America, Ryan C. Shell Jan 2020

Marine Vertebrate Communities From The Cisuralian Epoch (Permian Period) Of Central North America, Ryan C. Shell

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Marine vertebrates from the Cisuralian Epoch early Permian Period) are rare in the global fossil record. In particular, species-rich faunas from individual localities are poorly represented, with single occurrence localities that do not fully capture faunal tends in marine vertebrate ecology across this interval. This dissertation helps to close this gap by reporting marine vertebrate fossils from five localities across central North America, containing four to 15 unequivocal vertebrate taxa, as well as a new single occurrence locality near the Carboniferous-Permian boundary. This survey includes representatives from the first three of the four Cisuralian faunal stages, and is the result …

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Anthrax Event Detection: Analysis Of Public Opinion Using Twitter During Anthrax Scares, The Mueller Investigation, And North Korean Threats, Michele E. Miller Jan 2020

Anthrax Event Detection: Analysis Of Public Opinion Using Twitter During Anthrax Scares, The Mueller Investigation, And North Korean Threats, Michele E. Miller

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When people allow fear to drive their decision making, they often make decisions that do more harm than good. Examples of this include stocking up on ciprofloxacin, flooding doctors’ offices and buying black market antibiotics after the anthrax attacks of 2001. Therefore, it is important to be able to address what people are saying when another anthrax attack occurs. Supervised and unsupervised machine learning methodologies can be utilized to detect an event, classify the tweets by event, and to determine the main topics of discussion. Over the period of data collection, twenty events were detected. Three of these events concerned …

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Quantitative Susceptibility Mapping (Qsm) Reconstruction From Mri Phase Data, Sara Gharabaghi Jan 2020

Quantitative Susceptibility Mapping (Qsm) Reconstruction From Mri Phase Data, Sara Gharabaghi

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Quantitative susceptibility mapping (QSM) is a powerful technique that reveals changes in the underlying tissue susceptibility distribution. It can be used to measure the concentrations of iron and calcium in the brain both of which are linked with numerous neurodegenerative diseases. However, reconstructing the QSM image from the MRI phase data is an ill-posed inverse problem. Different methods have been proposed to overcome this difficulty. Still, the reconstructed QSM images suffer from streaking artifacts and underestimate the measured susceptibility of deep gray matter, veins, and other high susceptibility regions. This thesis proposes a structurally constrained Susceptibility Weighted Imaging and Mapping …

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