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Articles 1 - 30 of 57430
Full-Text Articles in Physical Sciences and Mathematics
Growth, Lipid Production And Biodiesel Potential Of Chromulina Freiburgensis Dofl., An Acidophilic Chrysophyte Isolated From Berkeley Pit Lake, June E. Mohler Mitman
Growth, Lipid Production And Biodiesel Potential Of Chromulina Freiburgensis Dofl., An Acidophilic Chrysophyte Isolated From Berkeley Pit Lake, June E. Mohler Mitman
Graduate Theses & Non-Theses
Microalgae remain a promising, but underdeveloped source of lipids for sustainable biodiesel. Some of the obstacles to cost-effective commercial-scale production have been culture contamination and expensive harvest methods. A chrysophyte isolated from Berkeley Pit Lake and identified as Chromulina freiburgensis, was found to grow rapidly in a pH 2.5 liquid medium and to amass numerous intracellular lipid bodies. This research addresses the scarcity of published knowledge on the topic of chrysophyte species as potential lipid sources for biodiesel. It investigates how growth phase, culture conditions, and harvest timing influence the quantity and composition of lipids produced by this alga. …
Rice Biomass Response To Various Phosphorus Fertilizers In A Phosphorus-Deficient Soil Under Simulated Furrow-Irrigation, Jonathan B. Brye
Rice Biomass Response To Various Phosphorus Fertilizers In A Phosphorus-Deficient Soil Under Simulated Furrow-Irrigation, Jonathan B. Brye
Crop, Soil and Environmental Sciences Undergraduate Honors Theses
Wastewater-recovered phosphorus (P), in the form of the mineral struvite (MgNH4PO4⋅6H2O), may provide a sustainable alternative to rapidly decreasing rock phosphate reserves. Struvite can be generated via chemical and/or electrochemical precipitation methods, potentially reducing the amount of P runoff to aquatic ecosystems. The objective of this greenhouse tub study was to evaluate the effects of chemically- and electrochemically precipitated struvite (CPST and ECST, respectively) on above- and belowground plant response in a hybrid rice cultivar (Gemini 214, RiceTec) grown using furrow-irrigation compared to other common fertilizer-P sources [i.e., triple super phosphate (TSP) and diammonium phosphate (DAP)] in a P-deficient silt …
Design And Synthesis Of N-Succinyl-L,L-2.6-Diaminopimelic Acid Desuccinylase Inhibitors As Potential Novel Antibiotics, Thomas Dipuma
Design And Synthesis Of N-Succinyl-L,L-2.6-Diaminopimelic Acid Desuccinylase Inhibitors As Potential Novel Antibiotics, Thomas Dipuma
Master's Theses
N-Succinyl-L,L-2,6-Diaminopimelic Acid Desuccinylase (DapE) is a bacterial enzyme located in the lysine biosynthetic pathway of all Gram-negative and most Gram-positive species of bacteria including the notorious ESKAPE pathogens, or pathogenic strains of bacteria that have developed significant levels of resistance to currently available antibiotics. As a means to combat this challenge of growing antimicrobial resistance, we have identified the bacterial enzyme DapE as a conserved, novel enzymate target within these resistant bacterial strains,as DapE is responsible for the production of m-DAP and lysine which are ultimately employed in bacterial cell wall synthesis. The overall aim of this research is to …
Meet Me In The Middle: A Scoping Review On Understanding Adolescent Needs In Climate Communication, Gwendolyn Monica Hoff Anderson
Meet Me In The Middle: A Scoping Review On Understanding Adolescent Needs In Climate Communication, Gwendolyn Monica Hoff Anderson
Master's Projects and Capstones
The greatest effects of climate change are likely to be felt by youth. Young people are disproportionately affected by climate change due to their critical developmental stage and lack of power, and they experience both higher severity and prevalence of mental health issues related to climate change. Strong emotions have long been recognized as potential catalysts for action, or they may lead to paralyzing feelings of being overwhelmed. Climate communication is a critical tool to spark climate concern and encourage action. Activism, in turn, may help youth manage their anxiety about climate change. This scoping review examines emerging evidence on …
The Loneliest Galaxies In The Universe: A Gama And Galaxy Zoo Study On Void Galaxy Morphology., Lori E. Porter
The Loneliest Galaxies In The Universe: A Gama And Galaxy Zoo Study On Void Galaxy Morphology., Lori E. Porter
College of Arts & Sciences Senior Honors Theses
The large-scale structure (LSS) of the Universe is comprised of galaxy filaments, tendrils, and voids. The majority of the Universe’s volume is taken up by these voids, which exist as underdense, but not empty, regions. The galaxies found inside voids are void galaxies and expected to be some of the most isolated objects in the Universe. However, their standard morphology remains poorly studied. This study, using the Galaxy and Mass Assembly (GAMA) data and Galaxy Zoo survey, aims to remedy this. For completeness purposes, we use void galaxies identified by Alpaslan et al. (2014) with stellar masses (M*) of 10 …
Soil Health And Remediation For Urban Gardens In Utah, Melissa Chilinski
Soil Health And Remediation For Urban Gardens In Utah, Melissa Chilinski
All Graduate Plan B and other Reports
Urban environments are at an increased risk of soil contamination and poor soil health due to anthropogenic causes. As healthy farmland is developed, new urban farmers and gardeners are often left growing food on unwanted land with unknown histories of previous use. Varied research and methods for obtaining healthy soils can cause new growers to make decisions that negatively impact soil health and fertility, or on the other hand, conflicting information can cause individuals to become unnecessarily fearful of common soil contaminants and their effect on human health. Common soil contaminants, like trace metals (often referred to as heavy metals) …
The Novel Chlorination Of Zirconium Metal And Its Application To A Recycling Protocol For Zircaloy Cladding From Spent Nuclear Fuel Rods, Breanna K. Vestal
The Novel Chlorination Of Zirconium Metal And Its Application To A Recycling Protocol For Zircaloy Cladding From Spent Nuclear Fuel Rods, Breanna K. Vestal
Doctoral Dissertations
A novel protocol has been developed for the chemical removal of zirconium alloy (Zircaloy) cladding from spent nuclear fuel rods and subsequent isolation and purification of nuclear-grade zirconium chloride derived therefrom. This protocol is based on the chemistry developed from two new scientific findings.
First, two new oxidative chlorination reactions have been discovered for zirconium metal. In both solvents, zirconium can be quantitatively chlorinated at temperatures less than 150°C, with the operative equations seen below. In sulfur monochloride, the reaction is completed in 2 – 4 hours via surface etching, exhibiting 0th order kinetic behavior. The elemental sulfur byproduct …
Subterraneans: A Regional Earth Dwelling For Comfort And Beauty, Isaak Benchoff
Subterraneans: A Regional Earth Dwelling For Comfort And Beauty, Isaak Benchoff
Architecture Undergraduate Honors Theses
Subterraneans is a study of an affordable, self-sufficient, sustainable, and dignified housing prototype for the region of Northwest Arkansas. It is a design process investigation based on the ideas of turning a local, sustainable material into affordable homes that can be built within a community of people sharing land and resources. The homes would utilize as many natural materials as possible to minimize the impact on the Earth and the cost to the owners.
Research looked at many different vernacular building precedents as well as the work done by contemporary design firms in the area of economical, low-impact, and passively …
Deephtlv: A Deep Learning Framework For Detecting Human T-Lymphotrophic Virus 1 Integration Sites, Johnathan Jia, Johnathan Jia
Deephtlv: A Deep Learning Framework For Detecting Human T-Lymphotrophic Virus 1 Integration Sites, Johnathan Jia, Johnathan Jia
The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access)
In the 1980s, researchers found the first human oncogenic retrovirus called human T-lymphotrophic virus type 1 (HTLV-1). Since then, HTLV-1 has been identified as the causative agent behind several diseases such as adult T-cell leukemia/lymphoma (ATL) and a HTLV-1 associated myelopathy or tropical spastic paraparesis (HAM/TSP). As part of its normal replication cycle, the genome is converted into DNA and integrated into the genome. With several hundreds to thousands of unique viral integration sites (VISs) distributed with indeterminate preference throughout the genome, detection of HTLV-1 VISs is a challenging task. Experimental studies typically use molecular biology …
Using Object Detection To Navigate A Game Playfield, Peter Kearnan Hyde-Smith
Using Object Detection To Navigate A Game Playfield, Peter Kearnan Hyde-Smith
Master's Theses (2009 -)
Perhaps the crown jewel of AI is the self-navigating agent. To take many sources of data as input and use it to traverse complex and varied areas while mitigating risk and damage to the vehicle that is being controlled, visual object detection is a key part of the overall suite of this technology. While much efforts are being put towards real-world applications, for example self-driving cars, healthcare related issues and automated manufacturing, we apply object detection in a different way; the automation of movement across a video game play field. We take the TensorFlow Object Detection API and use it …
Named Entity Recognition From Biomedical Text, Maged Guirguis
Named Entity Recognition From Biomedical Text, Maged Guirguis
Theses and Dissertations
As vast amounts of unstructured data are becoming available digitally, computer-based methods to extract relevant and meaningful information are needed. Named entity recognition (NER) is the task of identifying text spans that mention named entities, and to classify them into predefined categories. Despite the existence of numerous and well-versed NER methods, the bio-medical domain remains under-studied. The objective of this research is to identify an efficient technique for NER tasks from biomedical data. This is achieved by investigating using deep learning technologies namely pre-trained BERT [1] model and its variances SciBERT [2] and BioBERT [3]. Preprocessing the data before passing …
Unlocking Potential: The School-To-Prison Pipeline For Students With Disabilities, Navena F. Chaitoo
Unlocking Potential: The School-To-Prison Pipeline For Students With Disabilities, Navena F. Chaitoo
Dissertations, Theses, and Capstone Projects
This research uses quasi-experimental, matched sampling to examine the school-to-prison pipeline for students with disabilities using data from the National Longitudinal Study of Adolescent to Adult Health. This study presents novel insights into an at-risk group that has faced disproportionate rates of school discipline and incarceration. The study finds school suspension to be associated with future involvement in the criminal legal system and lower educational attainment. Disability was not found to mediate the relationship between suspension and future involvement in the criminal legal system or the relationship between suspension and academic outcomes. However, disability was found to be a statistically …
A Stronger Strong Schottky Lemma For Euclidean Buildings, Michael E. Ferguson
A Stronger Strong Schottky Lemma For Euclidean Buildings, Michael E. Ferguson
Dissertations, Theses, and Capstone Projects
We provide a criterion for two hyperbolic isometries of a Euclidean building to generate a free group of rank two. In particular, we extend the application of a Strong Schottky Lemma to buildings given by Alperin, Farb and Noskov. We then use this extension to obtain an infinite family of matrices that generate a free group of rank two. In doing so, we also introduce an algorithm that terminates in finite time if the lemma is applicable for pairs of certain kinds of matrices acting on the Euclidean building for the special linear group over certain discretely valued fields.
Social Impacts Of Robotics On The Labor And Employment Market, Kelvin Espinal
Social Impacts Of Robotics On The Labor And Employment Market, Kelvin Espinal
Dissertations, Theses, and Capstone Projects
Robotics have been introduced into the workplace to perform tasks that human beings have traditionally fulfilled. Complementing or substituting human labor with robotics eliminates human involvement in functions attributable to hazardous environments, heavy lifting, toxic substances, and repetitive low-level tasks. On the other hand, they are meant to be more efficient and cost-effective, saving money, time, and labor. However, since the introduction of robotics in the workforce, societal opposition has been towards this branch of technology in fear of losing employment, wages, and purpose.
Previous studies have reported an overarching societal fear that adopting robotics in the workplace and industry …
Optimized Peptide Nanomaterials As Delivery Vehicles For Hydrophobic Metal-Based Anticancer Agents, Yaron Marciano
Optimized Peptide Nanomaterials As Delivery Vehicles For Hydrophobic Metal-Based Anticancer Agents, Yaron Marciano
Dissertations, Theses, and Capstone Projects
Enzyme-responsive materials have been well explored, particularly as therapeutic and diagnostic agents. In this thesis we demonstrate that anionic self-assembling peptides can be utilized as delivery vehicles for metal-based hydrophobic payloads. The tunability of the system is highlighted as well as the increase in cytotoxicity and selectivity in vitro. The rapid degradation of peptides in cell media may lead to the formation of new peptide-drug bioconjugates with increased activity and selectivity. The physiological stability of these peptide delivery vehicles has been optimized by capping the N-terminus with an acetyl group. This simple backbone modification was shown to not prevent self-assembly, …
Carbon Dioxide Capture Potential Of Chitosan-Nanocrystalline Cellulose Aerogel Composite Materials: Synthesis, Functionalization, And Characterization, Victor Oghenekohwo
Carbon Dioxide Capture Potential Of Chitosan-Nanocrystalline Cellulose Aerogel Composite Materials: Synthesis, Functionalization, And Characterization, Victor Oghenekohwo
Theses and Dissertations
The carbon dioxide capture technology has been established as an invaluable player in the current global efforts to allay the warming of the planet and climate change. In this connection, the study centers on the valorization of waste organic materials for the application described herein. The sorbents, sourced from a combination of by-products of food processing and agricultural residue waste products, viz. seafood waste and sugarcane bagasse, showed prospects for selective carbon dioxide capture, adsorbing up to 5.78 mg/g of the gas at 273 K and 2.82 mg/g at 298 K, as observed on the Micromeritic ASAP 2020 surface area …
Azimuthal Anisotropy Of Different Quark-Flavored Particles In High Energy "Simulated" Proton-Proton Collisions, Mahmoud Rateb
Azimuthal Anisotropy Of Different Quark-Flavored Particles In High Energy "Simulated" Proton-Proton Collisions, Mahmoud Rateb
Theses and Dissertations
Anisotropic flow in high energy heavy-ion collisions is taken as a key evidence for the formation of QGP for brief seconds right after the collisions. Hydrodynamic models including QGP formation are accurate at predicting the azimuthal anisotropy of the produced particles at low transverse momenta. At high momenta however, hydrodynamic models predict no azimuthal anisotropy for particles of different masses and quark-flavors; the logic being that because of their high momenta, the particles pass through the media without having any time to have any reactivity. This is contrary to results from experiments where measurements of particles of different quark flavors …
Polyethersulfone Thin-Film Nanocomposite Membrane Embedded With Amine-Functionalized Graphene Oxide For Desalination Applications, Ahmed Bahaeldin
Polyethersulfone Thin-Film Nanocomposite Membrane Embedded With Amine-Functionalized Graphene Oxide For Desalination Applications, Ahmed Bahaeldin
Theses and Dissertations
Thin-film nanocomposite (TFN) desalination membranes were prepared based on a polyethersulfone (PES) support, where the polyamide (PA) layer was embedded with amine-functionalized graphene oxide (GO). The effect of adding various concentrations of functionalized and un-functionalized GO on the desalination performance, hydrophilicity, and morphology of the membranes was additionally assessed throughout this work. Scanning electron microscopy (SEM) measurements were used to assess the morphology of the membranes in combination with Brunauer-Emmett-Teller (BET) analysis. Contact angle measurements were used to gauge the hydrophilicity of the synthesized membranes. The membrane with the best desalination performance contained 1x10-3 wt/vol% of functionalized GO in …
Spike-Time Neural Codes And Their Implication For Memory, Alexandra Busch
Spike-Time Neural Codes And Their Implication For Memory, Alexandra Busch
Electronic Thesis and Dissertation Repository
The possibility of temporal coding in neural data through patterns of precise spike times has long been of interest in neuroscience. Recent and rapid advancements in experimental neuroscience make it not only possible, but also routine, to record the spikes of hundreds to thousands of cells simultaneously. These increasingly common large-scale data sets provide new opportunities to discover temporally precise and behaviourally relevant patterns of spiking activity across large populations of cells. At the same time, the exponential growth in size and complexity of new data sets presents its own methodological challenges. Specifically, it remains unclear how best to (1) …
National Development And The Sustainability Of Mining In The Atacama Desert, Chile, Dakota Soleil Osgood
National Development And The Sustainability Of Mining In The Atacama Desert, Chile, Dakota Soleil Osgood
Capstone Collection
As climate change continues to intensify on a global scale, efforts have been made to implement renewable energies and progressive technologies. These tools are critical in the shift towards a more sustainable practice, and yet analysis of localized impacts from the development of these mechanisms is inadequate. Chile has been and continues to be a leading country in mineral extraction, with an economic history founded in the mining industry. The establishment of mining in Chile as a progressive tool has aided the social and economic development of the nation. Consequences of mining extraction, however, include intensive environmental degradation, human rights …
Community Detection Via Persistent Homology Surfaces, Abigail Jenkins
Community Detection Via Persistent Homology Surfaces, Abigail Jenkins
Theses and Dissertations
Network science continues to be an area of growing interest. In this thesis we introduce new methods of analyzing the structure of networks through the use of persistent homology. We propose the notion of a network's persistent surface, which allows us to visualize a vertex's relation to the whole network from a purely homological point of view. We further introduce a method of persistent surface community detection that finds vertices that play the same structural role in the network. We describe how these concepts provide the basis for an equivalence class among the vertices of a network, and provide many …
Visual Analytics And Modeling Of Materials Property Data, Diwas Bhattarai
Visual Analytics And Modeling Of Materials Property Data, Diwas Bhattarai
LSU Doctoral Dissertations
Due to significant advancements in experimental and computational techniques, materials data are abundant. To facilitate data-driven research, it calls for a system for managing and sharing data and supporting a set of tools for effective data analysis and modeling. Generally, a given material property M can be considered as a multivariate data problem. The dimensions of M are the values of the property itself, the conditions (pressure P, temperature T, and multi-component composition X) that control the concerned property, and relevant metadata I (source, date).
Here we present a comprehensive database considering both experimental and computational sources …
Machine Learning Models Interpretability For Malware Detection Using Model Agnostic Language For Exploration And Explanation, Ikuromor Mabel Ogiriki
Machine Learning Models Interpretability For Malware Detection Using Model Agnostic Language For Exploration And Explanation, Ikuromor Mabel Ogiriki
Theses and Dissertations
The adoption of the internet as a global platform has birthed a significant rise in cyber-attacks of various forms ranging from Trojans, worms, spyware, ransomware, botnet malware, rootkit, etc. In order to tackle the issue of all these forms of malware, there is a need to understand and detect them. There are various methods of detecting malware which include signature, behavioral, and machine learning. Machine learning methods have proven to be the most efficient of all for malware detection. In this thesis, a system that utilizes both the signature and dynamic behavior-based detection techniques, with the added layer of the …
Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators, Olugbenga Joshua Gbidi
Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators, Olugbenga Joshua Gbidi
Theses and Dissertations
Bound states in the continuum (BICs) are waves that remain in the continuous spectrum of radiating waves that carry energy, however, still localized within the spectrum. BICs, also embedded eigenmodes, exhibit high quality factors that have been observed in optical and acoustic waveguides, photonic structures, and other material systems. Presently, there are limited means to select these BICs in terms of the quality factor and their excitation. In this work, we show that a different type of BIC, Quasi-BICs (Q-BICs), in open resonators can have their quality attuned by introducing embedded scatters. Using microwave cavities and dielectric scatters as an …
On Partially Observed Tensor Regression, Dinara Miftyakhetdinova
On Partially Observed Tensor Regression, Dinara Miftyakhetdinova
Major Papers
Tensor data is widely used in modern data science. The interest lies in identifying and characterizing the relationship between tensor datasets and external covariates. These datasets, though, are often incomplete. An efficient nonconvex alternating updating algorithm proposed by J. Zhou et al. in the paper "Partially Observed Dynamic Tensor Response Regression" provides a novel approach. The algorithm handles the problem of unobserved entries by solving an optimization problem of a loss function under the low-rankness, sparsity, and fusion constraints. This analysis aims to understand in detail the proposed algorithms and their theoretical proofs with, potentially, dropping some of the assumptions …
Measurement Of Near-Threshold Proton Branching Ratios In 31s Important For Novae, Sudarsan Balakrishnan
Measurement Of Near-Threshold Proton Branching Ratios In 31s Important For Novae, Sudarsan Balakrishnan
LSU Doctoral Dissertations
Classical novae are stellar explosions that contribute to the nucleosynthesis of isotopes on the proton-rich side of the valley of stability up to 40Ca. In ONe novae, the incompletely understood reaction rate of 30P(p,γ)31S is known to strongly influence the production rate of several stable isotopes such as 30Si, 31P, and 32,33,34S. A precise measurement of this reaction rate has several potential implications towards matching astrophysical observables to the physical composition of the nova site -- the observed elemental abundance ratios of O/S and S/Al have been suggested as useful `thermometers' to gauge …
Uniformity Test Based On The Empirical Bernstein Distribution, Ran Sun
Uniformity Test Based On The Empirical Bernstein Distribution, Ran Sun
Major Papers
In this paper, we firstly review the origin of Bernstein polynomial and the various application of it. Then we review the importance of goodness-of-fit test, especially the uniformity test, and we examine lots of different test statistics proposed by far. After that we suggest two new statistics for testing the uniformity. These two statistics are based on Komogorov-Smirnov test type and Cramér-Von Mises test type, respectively. Also we embed Bernstein polynomial into those test type and take advantage of great approximation performance of this polynomial. Finally, we run a Monte-Carlo simulation to compare the performance of our statistics to those …
Optimal Speed Of A Machine In An Assembly Line Using The Continuous Time Markov Chain Rate Matrix, Chandi Darshani Rupasinghe
Optimal Speed Of A Machine In An Assembly Line Using The Continuous Time Markov Chain Rate Matrix, Chandi Darshani Rupasinghe
Major Papers
The optimal speed of a machine in an assembly line is determined using a Markov decision process type model. We develop the rate matrix that represents the inter-event time of a machine, either repair time or time to breakdown, as a function of speed. We consider the rate of time to breakdown with a variety of functions of speed. We find limiting probabilities and express profit in terms of these probabilities. We then find the optimal speed to maximize profit. Further, we assume an underlying function of speed and simulate data using R. From the simulated data, we estimate the …
Spectral Sequences And Khovanov Homology, Zachary J. Winkeler
Spectral Sequences And Khovanov Homology, Zachary J. Winkeler
Dartmouth College Ph.D Dissertations
In this thesis, we will focus on two main topics; the common thread between both will be the existence of spectral sequences relating Khovanov homology to other knot invariants. Our first topic is an invariant MKh(L) for links in thickened disks with multiple punctures. This invariant is different from but inspired by both the Asaeda-Pryzytycki-Sikora (APS) homology and its specialization to links in the solid torus. Our theory will be constructed from a Z^n-filtration on the Khovanov complex, and as a result we will get various spectral sequences relating MKh(L) to Kh(L), AKh(L), and APS(L). Our …
Leveraging A Machine Learning Based Predictive Framework To Study Brain-Phenotype Relationships, Sage Hahn
Leveraging A Machine Learning Based Predictive Framework To Study Brain-Phenotype Relationships, Sage Hahn
Graduate College Dissertations and Theses
An immense collective effort has been put towards the development of methods forquantifying brain activity and structure. In parallel, a similar effort has focused on collecting experimental data, resulting in ever-growing data banks of complex human in vivo neuroimaging data. Machine learning, a broad set of powerful and effective tools for identifying multivariate relationships in high-dimensional problem spaces, has proven to be a promising approach toward better understanding the relationships between the brain and different phenotypes of interest. However, applied machine learning within a predictive framework for the study of neuroimaging data introduces several domain-specific problems and considerations, leaving the …