Digital Commons Network^™

Unexpected Outcomes During The Attempted Iodination Of Biphenol, Henry Nguyen

Honors Theses

The goal of this research was to create a new procedure to iodinate 4,4- biphenol using a ball miller. Iodination of 4,4-biphenol was first attempted in solution using electrophilic aromatic substitution. Several attempts were made to iodinate 4,4-biphenol, but the general insolubility of crude products inhibited progress. Interestingly, NMR analysis of the aqueous ammonia product suggested that 4,4-biphenol dimerized or polymerized with itself to make an ether. The exact mechanism by which the ether dimer was created is unknown, but the reaction may have occurred using a radical mechanism. Though the original goal of the project is left unmet, a …

Applying Markov Processes To Model Disability In Relapsing Multiple Sclerosis Patients, Anastasia Hartzes

All ETDs from UAB

Modeling disability in multiple sclerosis (MS) is challenging due to its complexity and non-linearity, with utilized methodology having many limitations. Lack of a suitable biomarker has led to relying on statistical models to understand disease progression. Markov methodology has been limitedly applied to the clinically-assessed Expanded Disability Status Score (EDSS), but not to patient-reported Patient Determined Disease Steps (PDDS); both measure disease progression and disability, and neither have been analyzed using the Test of Lumpability (TOL). It is common practice to aggregate these scores for computational or inferential convenience; in the case of Markov Chains (MC), combining states is referred …

Modeling And Optimization Of Advanced Hybrid Ground Source Heat Pump Systems, Gaoyang Hou

All ETDs from UAB

Heating, Ventilation and Air Conditioning (HVAC) systems contribute significantly to building energy efficiency. Most conventional HVAC systems, such as electrical resistance heater or air to air heat pumps, require high energy consumption while generating a large amount of carbon emission. Therefore, the HVAC system of a building has become the core part of the building design process to improve energy efficiency. Ground source heat pumps (GSHP) offering a relatively high coefficient of performance (COP) and low carbon emission have become a widely-accepted choice. By adding assistive components or alternative heat exchangers, the overall performance can be boosted to a new …

A Low-Cost Planar Inkjet-Printed Carbon Nanotube Field Effect Transistor For Sensor And Circuit Applications, Md Toriqul Islam

All ETDs from UAB

The semiconductor-based transistor is an essential building block of electronic components, computing applications, and sensors. However, the fabrication of this primary electronic element is complex and costly, especially when considering flexible electronics for bio-sensing applications. This thesis work proposes a new circuit manufacturing technique to print planar inkjet-printed carbon nanotube field effect transistor (CNTFET), sensor and circuits on paper and polyethylene terephthalate (PET) film substrate to reduce the complexity of the system and to lower the cost of conventional fabrication schemes. Single walled carbon nanotubes (SWCNTs) are being used as semiconductor ink for an inkjet-printer to facilitate and fabricate two …

Rapid Melting Of Aluminum Alloys By Induction Melting, Carlos Alfonso Larrazabal Colina

All ETDs from UAB

RAPID MELTING OF ALUMINUM ALLOYS BY INDUCTION MELTING CARLOS ALFONSO LARRAZABAL COLINA MATERIAL SCIENCE AND ENGINEERING ABSTRACT Die-casting and high-pressure die-casting are manufacturing processes meant to produce high volumes of parts. However, the die-casting industry suffers when the market is low or when short quantities of a part are needed, because this process may not be as flexible in small quantities. In such situations, one piece of the operation that is inflexible is running excess melting and holding furnace capacity. Rapid induction melting systems are proposed here as an alternative to big furnaces to provide amounts of molten metal in …

Kinetics Of Thermal Decomposition And Polymerization During Continuous Cooling, Tatsiana Liavitskaya

All ETDs from UAB

The processes that naturally occur on heating such as thermal decompositions and polymerizations can be made to proceed on cooling. Studying the resulting cooling kinetics is the major objective of this work. The kinetics of the reactions are explored by using differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) in combination with isoconversional kinetic analysis. The kinetic parameters obtained on cooling are compared to the ones evaluated on heating and physical insights into the differences and similarities in the kinetics of the processes on heating and cooling are proposed. The study is driven by the hypothesis that the kinetics on …

A Deep Learning Approach For Identifying Key Biomarkers In Medical Imaging Applications, David Odaibo

All ETDs from UAB

Although Deep Leaning has achieved great success in many domains in recent years, research into its applicability and effectiveness in medical applications has been limited for various reasons. Some of these barriers are related to the historic impression that neural networks are black boxes, especially when applied to medical diagnosis and offer no in terpretation into prediction. In this dissertation, I demonstrated that deep learning can be an effective utility in medical diagnosis and biomarker detection. In particular, I have developed deep learning models that can identify biomarkers in brain hemorrhage, brain tumor, pneumonia, diabetic retinopathy and Parkinsons disease, with …

A Study Of Approximation Error In Eulerian Hydrocodes, Parth Yogeshbhai Patel

All ETDs from UAB

In this study, we examine a number of approximations in the formulation of hydrocodes. These approximations were borne out of an original requirement for the code to run as fast as possible i.e. with accuracy being secondary to speed. Many of these approximations originated from the 1970’s when computers were slow and memory was at a premium. Although speed and memory are not as much of an issue today, these approximations are still used to formulate the hydrocodes. In this study, the effect of these approximations is examined systematically. The lumped mass approximation is a simplification to the consistent mass …

The Real-Time Extractiion Of Neural Spikes For Brain-Machine Interface Application Using Deep Learning Algorithm, Patel Sahaj Anilbhai

All ETDs from UAB

The detection of neural spikes in real-time and accurately has become the center of interest for the researchers in the field of brain-machine/computer interface (BMI/BCI). The primary challenge in the Brain-Machine interface is to translate raw neuronal response signals into the control of electrical actuators. Only accurate and rapid classification of neural response can help efficiently and conveniently to disable peoples, particularly those suffering from spinal cord injury, stocks, etc., Recording from neurons and analyzing them with many different methods are not new. However, the primary challenge here is the real-time recording and classifying the spikes with higher accuracy. In …

Examining Teachers' Perceptions And Practices Of Family Engagement With Families Of Emergent Bilinguals In Pre-Kindergarten And Kindergarten Classrooms: A Mixed Methods And Multiple Case Study, Julie I. Paul

All ETDs from UAB

This study addressed pre-K and kindergarten teachers’ perceptions and practices of family engagement with families of students who are Dual Language Learners/Emergent Bilinguals. The study employed an explanatory sequential mixed methods design (Quan --> QUAL) (Creswell & Plano-Clark, 2018). To address the purpose of the study, the overarching mixed methods question was: How do pre-K and kindergarten teachers engage families of all their students and families of students who are emergent bilinguals? Mixing of the strands occurred after the quantitative data was collected. Quantitative results helped develop the semi-structured interview protocol for the qualitative phase of the study. Qualitative results …

Bayesian Hierarchical Negative Binomial And Zero-Inflated Negative Binomial Models For High-Dimensional Analyses With Applications To Human Microbiome Count Data, Amanda H. Pendegraft

All ETDs from UAB

The human microbiome was first described as an “ecological community of commensal, symbiotic, and pathogenic microorganisms that literally share our bodyspace”. These microorganisms, also known as microbes and bacteria, are known for participation in human health. For example, microbes extract energy from foods that are otherwise indigestible, synthesize vitamins and amino acids necessary for important bodily functions, and protect hosts against disease-carrying pathogens. Therefore, the pursuit of human microbiome research is important for understanding the influence of microorganisms throughout human systems. Human microbiome research is founded on advances in next-generation sequencing technology. Namely, the identification of microbes that constitute the …

Investigating The Relationship Between Nurse Burnout And Self-Reported Medication Administration Errors In Alabama Hospitals, Aoyjai Prapanjaroensin

All ETDs from UAB

Background: Approximately 30% to 60% of nurses report high levels of burnout worldwide. Nurse burnout may impact vigilance and job performance. Nursing job performance may decrease due to lowered alertness if nurses have high levels of burnout, and this issue may be related to the act of committing a medication error. Of the very few studies exploring the relationship between nurse burnout and medication errors, the findings are conflicting. The purpose of this study is to examine the relationship between nurse work environment characteristics, burnout levels and self-reported medication administration errors as well as patient safety grades among nursing staff …

Quantifications Of Theranostic Polymer-Based Particles For Image-Guided Drug Delivery, Sithira Ratnayaka

All ETDs from UAB

Modern medicine employs many drugs in its disease treatment methods. This is because they provide the best permanent solutions to complicated ailments. However the usefulness of these drugs is mitigated by several factors, namely that of specific release. Common drug delivery mechanisms lack the specificity needed to ensure that release is limited to the diseased area, which can lead to unnecessary side effects. By utilizing medical imaging, both drug delivery devices and physiology can be observed by physicians, which can greatly increase the specificity of drug delivery. Specifically, utilizing a very inert medical imaging modality, such as ultrasound, guarantees minimum …

Personal Universes: A Solution To The Multi-Agent Value Alignment Problem, Roman V. Yampolskiy

Faculty and Staff Scholarship

AI Safety researchers attempting to align values of highly capable intelligent systems with those of humanity face a number of challenges including personal value extraction, multi-agent value merger and finally in-silico encoding. State-of-the-art research in value alignment shows difficulties in every stage in this process, but merger of incompatible preferences is a particularly difficult challenge to overcome. In this paper we assume that the value extraction problem will be solved and propose a possible way to implement an AI solution which optimally aligns with individual preferences of each user. We conclude by analyzing benefits and limitations of the proposed approach.

An Explainable Autoencoder For Collaborative Filtering Recommendation, Pegah Sagheb Haghighi, Olurotimi Seton, Olfa Nasraoui

Faculty and Staff Scholarship

Autoencoders are a common building block of Deep Learning architectures, where they are mainly used for representation learning. They have also been successfully used in Collaborative Filtering (CF) recommender systems to predict missing ratings. Unfortunately, like all black box machine learning models, they are unable to explain their outputs. Hence, while predictions from an Autoencoderbased recommender system might be accurate, it might not be clear to the user why a recommendation was generated. In this work, we design an explainable recommendation system using an Autoencoder model whose predictions can be explained using the neighborhood based explanation style. Our preliminary work …

High Efficiency, Fast Dynamic Response Sc Dc-Dc Converter For Battery Management System, Ruikuan Lu

All ETDs from UAB

Batteries have always been considered as one of the important, reliable, light-weight, and ubiquitous energy sources in our daily lives. As battery technology has progressed, different types of battery controlling, monitoring, and supervising technologies are also being rapidly developed. Most of the modern portable electronic devices are battery-powered (lithium-ion batteries, solar cells, fuel cells, etc.). The charging and discharging of the batteries are normally based on DC-DC converter. Form converter structure, the switches and capacitors based converter without inductive components is widely applied. In addition, the switched-capacitor (SC) converters are typically integrated with a monolithic integrated circuit, the low-cost and …

Light Transmission And Wear Of Translucent Zirconia After Conventional And Fast Sintering Cycle, Anvita Maharishi

All ETDs from UAB

ABSTRACT Introduction: Zirconia is classified by the mole percentage of yttria contained in the zirconia. The most strong and opaque material contains 3 mol % yttria, intermediate strength and opacity contain 4 mol %, and whereas 5 mol % is the weakest but most translucent zirconia. Refined zirconia powder is pressed into a mold to form a disc which is then milled to form a restoration. Post milling of sintered zirconia restorations is necessary to obtain final mechanical and physical properties of the restoration. Traditionally conventional sintering cycles required 6-8 hours to sinter. Whereas, fast sintering cycles have been have …

Reported Clinical And Financial Performance Of Hospitals With Physician Ceos Compared To Those With Nonphysician Ceos, Leon Moores

All ETDs from UAB

Leaders impact organizational behavior and performance, and CEOs may have greater impact via numerous proposed mechanisms. Because of this, organizations expend considerable resources recruiting and selecting CEOs and may benefit from information suggesting a positive impact on organizational performance based upon measurable CEO characteristics. Little work has been done comparing the performance of hospitals with physician CEOs versus non-physician CEOs, in spite of the ease of identification of this characteristic and extant leadership theories suggesting a relationship between technical expertise and success in leading highly technical organizations. We compared multiple measures of reported clinical and financial performance and our linear …

The Impact Of College Athletic Success On Donations And Applicant Quality, Benjamin Baumer, Andrew Zimbalist

Mathematics Sciences: Faculty Publications

For the 65 colleges and universities that participate in the Power Five athletic conferences (Pac 12, Big 10, SEC, ACC, and Big 12), the football and men’s basketball teams are highly visible. While these programs generate tens of millions of dollars in revenue annually, very few of them turn an operating “profit.” Their existence is thus justified by the claim that athletic success leads to ancillary benefits for the academic institution, in terms of both quantity (e.g., more applications, donations, and state funding) and quality (e.g., stronger applicants, lower acceptance rates, higher yields). Previous studies provide only weak support for …

Renewables-Integrated Internal Combustion Engine-Based Multi-Generation Options For Uab Buildings, Qing Mu

All ETDs from UAB

Distributed energy, also district or decentralized energy is generated or stored by a variety of small, grid-connected devices referred to as distributed energy resources, or distributed energy resource systems. The Distributed Generation (DG) systems can increase energy system reliability, reduce peak power requirements, and improve energy infrastructure resilience. In this study, a DG system using renewable energy sources and energy storage has been introduced for the whole University of Alabama at Birmingham (UAB) campus. The energy sources for this DG system are photovoltaic arrays, a natural-gas-powered Internal Combustion Engine (ICE), and wind turbines. The energy storage component used in this …

Convergence In A Disk Stacking Model On The Cylinder, Christophe Golé, Stéphane Douady

Mathematics Sciences: Faculty Publications

We study an iterative process modeling growth of phyllotactic patterns, wherein disks are added one by one on the surface of a cylinder, on top of an existing set of disks, as low as possible and without overlap. Numerical simulations show that the steady states of the system are spatially periodic, lattices-like structures called rhombic tilings. We present a rigorous analysis of the dynamics of all configurations starting with closed chains of 3 tangent, non-overlapping disks encircling the cylinder. We show that all these configurations indeed converge to rhombic tilings. Surprisingly, we show that convergence can occur in either …

The Role Of The Built Environment In Transforming Underserved Neighborhoods Into Smart And Connected Communities, Mary Claire Nabors

All ETDs from UAB

The goal of this report is to create a model for transforming underserved neighborhoods into smart, connected, healthy, and sustainable communities by focusing on the built environment. To do this, there must be a thorough neighborhood analysis of the existing conditions with recommendations for what needs to be done, both short term and long term. The built environment impacts many aspects of a neighborhood and the quality of life for residents. Sidewalks, streets, lighting, landscaping, and accessibility are all components of the built environment and research has continuously shown how the deterioration of the built environment affects the health and …

Inverse Problems, Regularization And Its Applications, Abinash Nayak

All ETDs from UAB

Inverse problems arise in a wide spectrum of applications in fields ranging from engineering to scientific computation. Connected with the rise of interest in inverse problems is the development and analysis of regularization methods, such as truncated singular value decomposition (TSVD), Tikhonov regularization or iterative regularization methods (like Landerweb iterations), which are a necessity in most inverse problems due to their ill-posedness. TSVD can be used when dealing with (small) finite dimensional linear problems, but is computationally very expensive, and sometimes even unfeasible, for large scale linear problems or nonlinear problems. In such scenarios, Tikhonov regularization is an attractive alternative, …

Academic Preparation For Business, Industry, And Government Positions, Alejandra Alvarado, Candice R. Price

Mathematics Sciences: Faculty Publications

According to the 2015 Annual Survey of the Mathematical Sciences, 1901 PhDs were awarded in the USA. The report shows that 52% of those recipients are working in academia. This is a decrease from the 2014 survey which stated that 56% of new doctoral recipients went on to academia. Thus, what support do we, as academics, provide to this growing population of business/industry, or government job seekers? The goal of this paper is to provide insight into programs tackling this question along with relevant information and advice for new PhDs interested in jobs outside of academia as well as those …

Modeling Stock Prices With Differential Equations, Jessica Barnett

All ETDs from UAB

Forecasting the stock market has long been subject to speculation, especially after the global financial crisis in 2008. In this thesis, we formulate a predictive model of the trend of a chosen stock that is derived from verifiable economic tendencies (absent appropriate economic laws) that interact through a system of nonlinear delay differential equations. The system is populated inversely from current economic data and solved numerically using MATLAB. As a result, we are able to use the forecasted trend to estimate a stock’s drift in order to also incorporate the randomness of the stock market. Lastly, we compare the predictions …

The Weight Of Social Relationships: Social Network Analysis In An Adult Weight Loss Program, Alena Borgatti

All ETDs from UAB

Adult behavioral obesity interventions often show improved attendance and weight loss when delivered in a group, as opposed to individual, therapy format. However, research on the exact mechanisms through which group therapy confers additional weight loss is lacking. Pediatric obesity interventions have recently begun to utilize social network analysis (SNA) to identify structural ties that may improve adherence and weight loss; however, this research is limited and has yet to be replicated in an adult weight loss program. The current study is the first to evaluate social networks in an adult behavioral weight loss intervention. Four weight loss groups were …

Legal Conditions Limiting The Possibility Of Acquiring Financing By Local Government Entities. Current State And Proposed Changes, Sebastian Skuza

Monografie/Monographs

The study primarily focuses on an attempt to answer the question formulated below: Is the currently functioning system of legal limitations applied in relation to the possibility of acquiring sources of refundable financing by local government entities justified?

The presented study is primarily an analysis of the currently applicable legal solutions from the perspective of borrowing needs of local government entities in the area of financial law as of 1 May 2018. The aim of this study is to present the barriers to the possibility of entering into financial commitments by local government entities within the national regulatory environment, their …

Comparison Of Longitudinal Voxel-Based Morphometry (Vbm) And Tensor-Based Morphometry (Tbm) For Detecting Structural Use-Dependent Neuroplastic Changes After Constraint-Induced Movement Therapy, Brent Maddox Womble

All ETDs from UAB

Constraint-Induced Movement therapy (CI therapy) is an efficacious physical rehabilitation intervention for lateralized upper-extremity motor deficits resulting from neurological injury or disease, which has been shown to result in use-dependent structural and functional neuroplasticity. While use-dependent neuroplasticity has been shown to result in structural changes in brain tissue density, thickness, and volume, the exact cellular mechanisms underpinning this neuroplasticity in humans have yet to be determined. The present study involved a novel use of synthetic data, with the overall aim of elucidating the nature of structural use-dependent neuroplasticity produced by CI therapy. Longitudinal voxel-based morphometry (VBM) and tensor-based morphometry (TBM) …

The Effect Of Right Ventricular Insertion Cooling On Wavebreak Initiation Following Defibrillation Shocks, Han Yu

All ETDs from UAB

Although strong defibrillation shocks can save patients from life-threating tachyarrhythmias, the function of the heart may be compromised. We found in an earlier study that the right ventricular insertion (RVI) is responsible for most of the initial propagation failure (wavebreak) that drives the transition from ventricular tachycardia (VT) to ventricular fibrillation (VF). To determine whether suppression of wavebreak at the RVI region can decrease VF re-occurrence after defibrillation, thereby decreasing the defibrillation shock strength threshold (DFT), a cooling method was developed to impede waves from propagating between the right ventricle (RV) and the left ventricle (LV) through the RVI. The …

A Deep Learning Framework For Medical Image Segmentation, Zheng Zhang

All ETDs from UAB

Deep Learning (DL) has rapidly become a methodology of choice for analyzing medical images and increasingly attracts researcher’s attention in the medical research community. The brain is one of the most important organs in the human body. Within the context of human brain disease, research and care, accurately detecting, evaluating and segmenting human brain abnormalities play an important role in brain disease diagnosis, prognosis, and treatment planning. A significant challenge in developing good brain abnormalities segmentation methods is the high variation of brain abnormalities such as differences in shape, size, location, appearance, and regularity. Deep Learning approach ad-dresses this challenge …