Engineering Commons^™

Molecular Theoretical Model For Lipid Bilayers: Adsorption Of Lipidated Proteins On Lipid Bilayers As A Function Of Bilayer Composition And Curvature, Shauna Celeste Kennard

Theses and Dissertations

Protein localization on biological membranes is motivated by either highly selective recognition of specific target membrane components or nonspecific attraction to general physical properties of the membrane, such as charge, lipid heterogeneity, and curvature. Here we discuss the interaction between lipidated proteins and lipid bilayer membranes from a comprehensive examination of how features of the membrane and its lipid constituents, including lipid composition, headgroup size, degree of tail saturation, tail length (bilayer thickness), and membrane geometry, affect the adsorption ability of the proteins. Of key importance is the strong interconnection among these compositional and morphological elements of the membrane in …

An Ontology For Cardiothoracic Surgical Education And Clinical Data Analytics, Maryam Panahiazar, Yorick Chern, Ramon Riojas, Omar S.Latif, Usha Lokala, Dexter Hadley, Amit Sheth, Ramin E.Beygui

Faculty Publications

The development of an ontology facilitates the organization of the variety of concepts used to describe different terms in different resources. The proposed ontology will facilitate the study of cardiothoracic surgical education and data analytics in electronic medical records (EMR) with the standard vocabulary.

Learning Depth From Images, Zhenyao Wu

Theses and Dissertations

Estimating depth from images has become a very popular task in computer vision which aims to restore the 3D scene from 2D images and identify important geometric knowledge of the scene. Its performance has been significantly improved by convolutional neural networks in recent years, which surpass the traditional methods by a large margin. However, the natural scenes are usually complicated, and hard to build the correspondence between pixels across frames, such as the region containing moving objects, illumination changes, occlusions, and reflections. This research explores rich and comprehensive spatial correspondence across images and designs three new network architectures for depth …

Distributed Interdigital Capacitor (Idc) Sensing For Cable Insulation Aging And Degradation Detection, Md Nazmul Al Imran

Theses and Dissertations

Nuclear power plants (NPPs) contain myriad power, control, instrumentation, and other types of cables. The polymer insulation and jacket materials of such cables degrade over time due to operation and environmental conditions e.g., heat, humidity, and radiation. Since the life span of NPPs may extend beyond 40-50 years regular monitoring of cable insulation and jacket polymers is critical to ensure safe and reliable operation. The agingrelated degradation of cables causes changes in the relative permittivity or dielectric constant of the insulation and jacket materials. Capacitor sensors, if properly designed and developed can measure this change and thus can provide an …

Long Non-Coding Rna Pvt1 – An Exploratory Study In Ovarian And Endometrial Cancer, Kevin Tabury

Theses and Dissertations

Gynecological cancers, ovarian and endometrial cancer, are still leading causes of cancer-related death in women worldwide. Early detection methods as well as treatment resistance remain a challenge. Long non-coding RNAs (lncRNAs) are emerging as therapeutic targets with diagnostic and prognostic potential with lncRNA PVT1 being one of them.

Here I test and demonstrate the role of PVT1 in ovarian cancer growth and metastasis. PVT1 is amplified and overexpressed in ovarian cancer and has predictive value for survival and response to targeted therapeutics. We find that expression of PVT1 is regulated by tumor cells in response to cellular stress, particularly loss …

Role Of Epigenome In Regulation Of Inflammation By Ahr Ligands 2,3,7,8-Tetrachlorodibenzo-P-Dioxin And 6-Formylindolo[3,2-B] Carbazole, Alkeiver Cannon

Theses and Dissertations

Autoimmune Hepatitis (AIH) is a chronic inflammatory disease of the liver mediated by immune cells and characterized by a variety of parameters including circulating autoantigens, elevated immunoglobulin G (IgG) and aminotransferases, and interface hepatitis. Unfortunately, despite treatment with broadly immunosuppressive drugs, the disease progresses to cirrhosis and end-stage liver disease in several cases. In order to develop a more specific treatment, the mechanisms governing the liver injury resulting from inflammation and autoimmunity need to be elucidated.

For decades, activation of Aryl Hydrocarbon Receptor (AhR) was excluded from consideration as a therapeutic approach due to the potential toxic effects of AhR …

Sex Differences And Potential Non-Invasive Treatments For Calcific Aortic Valve Disease, Henry Pascal Helms

Theses and Dissertations

Calcific Aortic Valve Disease (CAVD) is a progressive heart disease that ranges from aortic valve sclerosis to aortic valve stenosis. It is characterized by intense calcification and compromised valve function. CAVD affects 25% of people older than 65 and 50% of people older than 85. These rates are expected to increase in the United States due to higher levels of obesity and diabetes, as well as an aging population. CAVD is the leading cause of valve replacement surgery. Annual healthcare costs for these valve replacements are currently estimated to be approximately 2 billion dollars. There are currently no medications approved …

Non-Intrusive Microwave Surface Wave Technique For Cable Damage And Aging Detection, Ahmed Shah Arman

Theses and Dissertations

Power plants, power distribution and transmission networks, automobiles, aircrafts, trains, industrial manufacturing plants etc. use a variety of cables and wires. The insulation and jacket polymer materials of cables can degrade over time due to operational stressors and environmental conditions. Materials may age, corrode, get chaffed and go missing which if remain undetected and unaddressed can result in major failures. Insulation degradation or damage detection from a distance normally involves the application of direct contact reflectometry techniques. This requires the cable to be disengaged and a diagnostic signal to be directly applied to a cable with a return path. While …

Hybrid Theory-Machine Learning Methods For The Prediction Of Afp Layup Quality, Christopher M. Sacco

Theses and Dissertations

The advanced manufacturing capabilities provided through the automated fiber placement (AFP) system has allowed for faster layup time and more consistent production across a number of different geometries. This contributes to the modern production of large composite structures and the widespread adaptation of composites in industry in general and aerospace in particular. However, the automation introduced in this process increases the difficulty of quality assurance efforts. Industry available tools for predicting layup quality are either limited in scope, or have extremely high computational overhead. With the advent of automated inspection systems, direct capture of semantic inspection data, and therefore complete …

Image Restoration Under Adverse Illumination For Various Applications, Lan Fu

Theses and Dissertations

Many images are captured in sub-optimal environment, resulting in various kinds of degradations, such as noise, blur, and shadow. Adverse illumination is one of the most important factors resulting in image degradation with color and illumination distortion or even unidentified image content. Degradation caused by the adverse illumination makes the images suffer from worse visual quality, which might also lead to negative effects on high-level perception tasks, e.g., object detection.

Image restoration under adverse illumination is an effective way to remove such kind of degradations to obtain visual pleasing images. Existing state-of-the-art deep neural networks (DNNs) based image restoration …

Cross Domain Semantic Segmentation, Xinyi Wu

Theses and Dissertations

As a long-standing computer vision task, semantic segmentation is still extensively researched till now because of its importance to visual understanding and analysis. The goal of semantic segmentation is to classify each pixel of images based on the pre-defined classes. In the era of deep learning, convolutional neural networks largely improve the accuracy and efficiency of semantic segmentation. However, this success is achieved with two limitations: 1) a large-scale labeled dataset is required for training while the labeling process for this task is quite labor-intensive and tedious; 2) the trained deep networks can get promising results when testing on the …

Cnn-Based Semantic Segmentation With Shape Prior Knowledge, Yuhang Lu

Theses and Dissertations

Semantic segmentation that aims at grouping discrete pixels into connected regions is a fundamental step in many high-level computer vision tasks. In recent years, Convolutional Neural Networks (CNNs) have made breakthrough progresses in public semantic segmentation benchmarks. The ability of learning from large-scale labeled datasets empowers them to generalize to unseen images better than traditional nonlearning-based methods. Nevertheless, the heavy dependency on labeled data also limits their applications in tasks where high-quality ground truth segmentation masks are scarce or difficult to acquire. In this dissertation, we study the problem of alleviating the data dependency for CNN-based segmentation with a focus …

Oxidized Graphitic Nano-Amendment Of Cement Composites: Exploring Truly Low Concentrations And Novel Particle Morphologies, Shohana Iffat

Theses and Dissertations

Oxidized graphitic nanoparticles such as multiwalled carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs), can produce enhancements in physicomechanical properties of cement composites that are relevant to structural and durability performance, provided that said nanoparticles are well dispersed in the composite. Lower-bound MWCNT concentrations are reported in the literature in the range 0.01-0.05% in weight of cement (wt%). Such concentrations may not be costeffective for practical applications and may also be excessive since they would result in a nanoparticle surface area at or above 105 m2 for 1 m3 of cement paste, or 104.5 m2 for 1 m 3 of concrete, …

Knowledge-Infused Learning, Manas Gaur

Theses and Dissertations

In DARPA’s view of the three waves of AI, the first wave of AI, symbolic AI, focused on explicit knowledge. The second and current wave of AI is termed statistical AI. Deep learning techniques have been able to exploit large amounts of data and massive computational power to improve human levels of performance in narrowly defined tasks. Separately, knowledge graphs have emerged as a powerful tool to capture and exploit a variety of explicit knowledge to make algorithms better apprehend the content and enable the next generation of data processing, such as semantic search. After initial hesitancy about the scalability …

Development Of Micro-Sized Algan Deep Ultraviolet Light Emitting Diodes And Monolithic Photonic Integrated Circuits, Richard Speight Floyd Iii

Theses and Dissertations

III-Nitride materials-based visible emission LEDs have emerged as a disruptive technology in the fields of lighting,ⁱ) communications,^ii,iii,iv) and displays.^v,vi) Shorter wavelength LEDs in the DUV spectral region (210nm – 360nm) with ultra-wide bandgap (UWBG) Al_xGa_1-xN active layers are now poised to displace toxic Mercury-based light sources.^vii) Over the past decade AlGaN LEDs operating in the deep ultra-violet (DUV) spectral region (200 nm < λ_emission < 300 nm) have been deployed in novel applications including autonomous drone-based sterilization and sanitization systems, ^viii) point-of-use water purification systems, ^ix) photo-therapeutics,x) gas sensors,xi) and non-line-of-sight (NLOS) communications.^xii) Similarly, DUV light detectors using ultra-wide bandgap (UWBG) Al …

Identifying And Discovering Curve Pattern Designs From Fragments Of Pottery, Jun Zhou

Theses and Dissertations

The surface of many cultural heritage objects, such as pottery sherds found in the Southeastern Woodlands, were embellished with curve patterns. The original full designs of these patterns reflect rich historical and cultural information. However, in practice, most objects are fragmentary, making the complete underlying designs unknowable at the scale of the sherd fragment. The challenge to reconstruct and study complete designs is stymied because 1) most pottery sherds contain only a small portion of the underlying full design, 2) curve patterns detected on a sherd are usually incomplete and noisy, and 3) in the case of a stamping application, …

Nondestructive Material Characterization Using A Fully Noncontact Ultrasonic Lamb Wave System For Thin Metals, Nuclear Cladding, And Composite Materials, Elsa Z. Compton

Theses and Dissertations

Effective non-destructive evaluation (NDE) inspection system and methods are highly desired in a broad range of engineering applications including thin metal structure thickness evaluation. Ultrasonic guided waves in thin-walled structures, namely Lamb waves, have gained popularity as a NDE method. By using the ultrasonic waves in conjunction with high spatial resolution multidimensional wavefield measurements, thickness evaluations for thin metals can be achieved. This thesis explores the configuration and application of a fully noncontact ultrasonic Lamb wave NDE system for thickness characterization and evaluation of very thin metal plates. We have tested the actuation and sensing of Lamb waves for thickness …

The Effect Of Pulsed Field Dc Electrophoresis And Field Amplified Sample Stacking On The Microchip Electrophoretic Separation Of Organic Dyes, Travis Geoffrey Stewart

Theses and Dissertations

The utility of field amplified sample stacking and pulsed field electrophoresis toward improving electrophoretic outcomes was studied with regards to the electrophoretic separation of three organic dyes rhodamine B, 2’,7’-dichlorofluorescein, and fluorescein salt in microchip electrophoresis conditions. In this study, there were four experimental groups: nonstacking nonpulsed, nonstacking pulsed, sample stacking nonpulsed, and sample stacking pulsed.

Electrophoretic outcomes were evaluated by examining the electrophoretic separations under an epifluoresence detection method, plotting the signal intensities vs. time, and comparing separation resolutions and signal-to-noise ratios between experimental groups. From this it was shown that sample stacking nonpulsed conditions yielded the best outcome …

Networked Digital Predictive Control For Modular Dc-Dc Converters, Castulo Aaron De La O Pérez

Theses and Dissertations

The concept of power electronics building blocks (PEBB) has driven advancements in highly modularized converter systems with many identical subsystems. PEBBs are distributed subsets of converter systems and thus require communication with a control system for their coordination. For this type of system, the communication latency with hard deterministic deadlines is the driving attribute of communication system requirements. However, inherent communication requirements for PEBB-based converter systems also provide opportunities for coordination of energy flow.

Leveraging developments in Gigabit serial communication channels, a control and communication platform architecture for distributed control schemes based on the 2D-Torus communication network topology was developed …

Automated Contingency Management For Water Recycling System, Shijie Tang

Theses and Dissertations

NASA’s exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and beyond. Communication latency and extreme limitations of power and life-supporting resources make it imperative to operate the DSH systems in a highly autonomous fashion. One such system is the Environmental Control and Life Support System (ECLSS) which needs to be monitored and optimized to support its designated missions.

Integrated System Health Management (ISHM) technologies have been developed in the past decades to provide a real-time assessment of system health and use this information to improve …

Table Of Contents

Journal of the South Carolina Academy of Science

No abstract provided.

Nuclear Fuel Cycle: Safe Management Of Spent Nuclear Fuel, Robert L. Sindelar

Journal of the South Carolina Academy of Science

The aim for storage of spent nuclear fuel (SNF) either in wet or in dry storage systems is to ensure general safety objectives are met throughout a desired storage period. Staff at the Savannah River National Laboratory (SRNL), in collaborations with partners at other national laboratories, industry research organizations, and the University of South Carolina (UofSC), have performed materials aging testing and analyses, and have established nuclear materials aging management programs to support extended periods of safe storage of research reactor (RR) SNF and of commercial power reactor (PR) SNF pending ultimate disposal. Several example challenges include susceptibility of aluminum …

Allure: A Multi-Modal Guided Environment For Helping Children Learn To Solve A Rubik's Cube With Automatic Solving And Interactive Explanations, Kausik Lakkaraju, Thahimum Hassan, Vedant Khandelwal, Prathamjeet Singh, Cassidy Bradley, Ronak Shah, Forest Agostinelli, Biplav Srivastava, Dezhi Wu

Faculty Publications

Modern artificial intelligence (AI) methods have been used to solve problems that many humans struggle to solve. This opens up new opportunities for knowledge discovery and education. We demonstrate ALLURE, a collaborative educational AI system for learning to solve the Rubik's cube that is designed to help students improve their problem solving skills. ALLURE can both find its own strategies for solving the Rubik's cube and explain those strategies to humans. In the future, ALLURE will also be able to collaborate with humans by building on user-provided strategies for solving the Rubik's cube and as well as generalize to other …

The NTh-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems (Nth-Casam-N): Mathematical Framework, Dan Gabriel Cacuci

Faculty Publications

This work presents the n^th-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (n^th-CASAM-N), which enables the most efficient computation of exactly determined expressions of arbitrarily high-order sensitivities of generic nonlinear system responses with respect to model parameters, uncertain boundaries, and internal interfaces in the model’s phase space. The mathematical framework underlying the n^th-CASAM-N is proven to be correct by using mathematical induction. The n^th-CASAM-N is formulated in linearly increasing higher-dimensional Hilbert spaces—as opposed to exponentially increasing parameter-dimensional spaces—thus overcoming the curse of dimensionality in sensitivity analysis of nonlinear systems.

Illustrative Application Of The Nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems To The Nordheim–Fuchs Reactor Dynamics/Safety Model, Dan Gabriel Cacuci

Faculty Publications

The application of the recently developed “nth-order comprehensive sensitivity analysis methodology for nonlinear systems” (abbreviated as “nth-CASAM-N”) has been previously illustrated on paradigm nonlinear space-dependent problems. To complement these illustrative applications, this work illustrates the application of the nth-CASAM-N to a paradigm nonlinear time-dependent model chosen from the field of reactor dynamics/safety, namely the well-known Nordheim–Fuchs model. This phenomenological model describes a short-time self-limiting power transient in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted, either intentionally or by accident. This model is sufficiently complex to demonstrate all the …

Comparative Analysis Of Reactive Power Compensation Devices In A Real Electric Substation, Hannan Tariq, Stanislav Czapp, Sarmad Tariq, Khalid Mehmood Cheema, Aqarib Hussain, Ahmad H. Milyani, Sultan Alghamdi, Z. M. Salem Elbarbary

Faculty Publications

A constant worldwide growing load stress over a power system compelled the practice of a reactive power injection to ensure an efficient power network. For this purpose, multiple technologies exist in the knowledge market out of which this paper emphasizes the usage of the flexible alternating current transmission system (FACTS) and presents a comparative study of the static var compensator (SVC) with the static synchronous compensator (STATCOM), inducted in a real electric substation. The aim is to improve the power factor (PF) and power quality and to encounter reliably extreme conditions. A 220 kV electric substation was opted for the …

Can Language Models Capture Graph Semantics? From Graphs To Language Model And Vice-Versa, Tarun Garg, Kaushik Roy, Amit Sheth

Publications

Knowledge Graphs are a great resource to capture semantic knowledge in terms of entities and relationships between the entities. However, current deep learning models takes as input distributed representations or vectors. Thus, the graph is compressed in a vectorized representation. We conduct a study to examine if the deep learning model can compress a graph and then output the same graph with most of the semantics intact. Our experiments show that Transformer models are not able to express the full semantics of the input knowledge graph. We find that this is due to the disparity between the directed, relationship and …

Commemorative Issue In Honor Of Professor Gerhard Ertl On The Occasion Of His 85th Birthday, Stanislaw Waclawek, Andrzej Kudelski, Jochen A. Lauterbach, Dionysios D. Dionysiou

Faculty Publications

This Special Issue (SI) is dedicated to Professor Gerhard Ertl on his eighty-fifth birthday. Professor Ertl is a Professor Emeritus at the Fritz-Haber-Institut der Max-Planck-Gesellschaft (Berlin, Germany). He won the Nobel Prize in Chemistry in 2007 for his work on the fundamental understanding of heterogeneously catalyzed reactions. According to the Royal Swedish Academy of Sciences, Professor Ertl’s research laid the groundwork for the current understanding of the chemistry of surfaces that has helped, for example, in understanding how ammonia is synthesized and how fuel cells generate energy. This SI includes articles focused on materials with potential applications as cathodes for …

Knowledge-Driven Drug-Use Namedentity Recognition With Distant Supervision, Goonmeet Bajaj, Ugur Kursuncu, Manas Gaur, Usha Lokala, Ayaz Hyder, Srinivasan Parthasarathy, Amit Sheth

Publications

As Named Entity Recognition (NER) has been essential in identifying critical elements of unstructured content, generic NER tools remain limited in recognizing entities specific to a domain, such as drug use and public health. For such high-impact areas, accurately capturing relevant entities at a more granular level is critical, as this information influences real-world processes. On the other hand, training NER models for a specific domain without handcrafted features requires an extensive amount of labeled data, which is expensive in human effort and time. In this study, we employ distant supervision utilizing a domain-specific ontology to reduce the need for …

Therapeutic Payload Delivery To The Myocardium: Evolving Strategies And Obstacles, Tarek Shazly, Arianna Smith, Mark J. Uline, Francis G. Spinale

Faculty Publications

No abstract provided.