Dissertation Defense Announcements

Candidate Name: Weina Ke
Title: Functional Nucleic Acid Nanoparticles and Their Delivery using Exosomes
 December 02, 2020  4:00 PM
Location: Zoom meeting
Abstract:

Nucleic acid biopolymers are essential to all living organisms. The chemical makeup of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) consist of sequences of only four monomers. However, they transmit and express genetic information for various biological functions based on stored blueprints. Along with communicating the flow of genetic information (DNA → RNA→ protein), nucleic acids have also become a preferred material for fabrication of objects and scaffolds at the nanoscale. Nucleic acid-based assemblies that interact with each other and communicate with the cellular machinery represent a new class of reconfigurable nanostructures that enable precise control over their formulation and physicochemical properties and activation of multiple biological functionalities. Therefore, the use of nucleic acids offers a unique platform for development of nanoparticles which consist of nanoscale-size oligonucleotides designed to fold into predicted three-dimentional structures. They can serve as scaffolds capable of carrying numerous functional moieties such as: RNA interference activators for gene silencing, aptamers for specific targeting of selected molecules, immunostimulatory sequences for modulating immune responses, and fluorescent entities for bioimaging. Programmable, controllable, biocompatible, rationally designed, and self-assembled nucleic acid nanoparticles have become attractive candidates for diverse therapeutic options. Despite profound advances in the field of therapeutic nucleic acids, their negative charges decrease membrane permeation capacity, thus hindering their translation from experimental research to clinical application. This dissertation focuses on the development of nucleic acid nanoparticles as therapeutics with defined immunostimulatory properties accompanied by rationally designed systems able to regulate the duration of therapeutic activity. Furthermore, a safe, efficient and stable intracellular delivery system for multi-functional nucleic acid nanoparticle platforms is investigated.



Candidate Name: Qiang Liu
Title: Intelligent Network Management for Heterogeneous Services in Mobile Edge Computing
 December 01, 2020  1:00 PM
Location: Virtual Webex Meeting: https://uncc.webex.com/uncc/j.php?MTID=mb3d0d71414f36eef036e7594a89ac7df, Password: uncc@2020
Abstract:

The proliferation of connected devices creates various use cases and heterogeneous services, e.g., augmented/virtual reality (AR/VR), vehicle-to-everything (V2X), and mobile artificial intelligence. These services and use cases have diverse networking and performance requirements such as throughput and delay, which challenge the "one-fit-all" service architecture in current networks. In this research, an intelligent network management framework in mobile edge computing is explored. The primary challenges lie in the unique characteristics of heterogeneous services and complicated correlations between network management on multiple technical domains and high-dimension performance requirements in the complex mobile networks. This research addresses these challenges with two different management approaches. From the perspective of service providers, multiple mobile systems are designed to allow service adaptation under complex network dynamics, e.g., channel variation and traffic workload, which dynamically and adaptively adjust resource allocations and system configurations by exploiting the unique characteristics of individual services. From the perspective of infrastructure providers, multiple network systems are proposed to enable orchestration intelligence without accurate performance modelings of services, which automatically learn to orchestrate multiple domain network resources for supporting various services by exploiting advanced machine learning techniques.



Candidate Name: Todd Noste
Title: Freeform Optical Surface Form Metrology with Serial Data Acquisition
 December 01, 2020  10:00 AM
Location: Webex
Abstract:

Freeform optics, or optics with no axis of rotational invariance, provide optical designers more degrees of freedom, flexibility, and opportunity for innovation increasing optical performance and system integration while decreasing the form factor. Advancements in optical fabrication have enabled freeform surface manufacture with greater precision. Metrology instruments and techniques are needed to verify the performance of freeform optical surfaces and systems to keep up with design and manufacture. Freeform optics often have high slopes, no axis of symmetry, and a large departure from spherical, making traditional metrology techniques inadequate. This research was conducted to enable form measurements of freeform mirrors in the 250 mm class for a next generation three mirror anastigmatic (TMA) telescope complete with a statement of the measurement uncertainty to fill the gap in metrology of freeform optics. A flexible metrology instrument that could measure relatively large optics with customizable probe paths and sampling strategies was needed while maintaining the required precision.



Candidate Name: Prashanth Jaganmohan
Title: Data Processing, Modeling, and Error Analysis in Discrete Part Geometric Inspection
 December 07, 2020  10:00 AM
Location: Webex
Abstract:

In today’s world of modern metrology, it becomes increasingly common to find new technologies which employ non-traditional measuring mechanisms in attempts to provide new advantages to lever over competing measuring instruments. In addition to such new technologies emerging, parts being measured also tend to grow in complexity, presenting new and unique challenges in their measurement. As a result of such advancements in technology and increasing part complexities, it becomes necessary to develop and optimize data processing, data modeling methods and error analysis methods tailored to a given measurement technique or a given part. This dissertation explores these aspects of discrete part metrology and presents solutions for each case considered. A data processing method is developed to allow measurement of any complex part using a precision rotary table and a set of triangulation-based laser line sensors. Machine learning approaches are also explored for a similar measurement problem. The system described is tailored to measure desired discrete parts (gears in this case) and can be considered a custom coordinate measuring system (CMS). An essential step to pushing such custom machines or new measurement technologies into widespread use, is the development of standardized test procedures that enable users to compare different technologies by their performance against traceable standards. Development of such standards often involve designing performance evaluation test procedures that are sensitive to as many known error sources are possible. Therefore, such an approach is adopted for two measuring technologies, namely X-Ray Computed Tomography (XCT) and Stereo-vision Photogrammetry. In each case, several known error sources are characterized, and recommendations are made on ways to capture them. Further, from an automation perspective, it becomes essential to use a data modeling system that can support descriptions of complex parts and their measurement results, as well as accommodate new measurement technologies and tools. To this end, a promising candidate, the Quality Information Framework (QIF) has been identified.



Candidate Name: Abhispa Sahu
Title: Environmentally sustainable synthesis of novel nano assisted ion exchange systems for facile and high-capacity water purification
 November 25, 2020  2:00 PM
Location: Burson, UNC Charlotte
Abstract:

Demand for clean and safe drinking water is a global challenge because of water scarcity, growth of human population, urbanization, and anthropogenic pollution. Purification of water involves removal of small molecules and ions from ground water addressed as “emerging contaminants” which are extremely mobile and toxic in nature, do not degrade or hydrolyze easily, and highly soluble in water resulting in bioaccumulation. Most of the current water treatment systems have complex deficiencies that affect their overall performance. We have synthesized carbon nanostructures assisted ion exchange resins in aqueous medium that help remove these emerging contaminants in a fast, easy, and high capacity manner while supporting less contact time and low transmembrane resistance primarily achieved using thin film assemblies. We have developed a novel sonochemistry assisted atom transfer radical polymerization (SONO-ATRP) process for synthesis of polyelectrolyte anion exchange resins in water without use of any external initiator or reducing agents while using only a few ppm of catalyst. We successfully performed high-density functionalization of polyelectrolyte anion exchange resin strands onto single walled carbon nanotubes sidewalls using the SONO-ATRP process while at low reaction temperatures thereby providing a less energy intensive alternative for green chemistry. We have developed green processes to defluorinate fluorographite in water and simultaneously perform covalent grafting of anionic short brushes of poly(vinyl benzyl trimethylammonium chloride) to its surface under mild reaction conditions without need of any external reactive reagents. Field Emission Scanning Electron microscopy of thin film of functionalized carbon nanotubes demonstrated pin-hole free mesoporous architecture illustrating scaffold robustness while thin films of functionalized fluorographite exhibited stacked arrangement of plate-like structures. Exfoliation and functionalization of fluorographite was revealed through Transmission Electron Microscopy. Both the resins demonstrated high water flux (>1500 L m^(-2) h^(-1) bar^(-1)) due to their intrinsic architecture and high percent removal (>90%) of contaminants due to the tortuous path length during molecular transport through the membrane. These properties enable adsorption of impurities at environmentally relevant concentrations. These materials exhibited facile regeneration and reusage of the thin films, thus supporting sustainability. In conclusion, these processes abide by the principles of green chemistry and their processability opens new avenues for smart point-of-use water purification systems.



Candidate Name: Wesley O. Davis
Title: Enhancing Distribution Planning Methods To Facilitate High Growth Distributed Energy Resources
 December 01, 2020  10:30 AM
Location: Online Zoom Meeting, Join Zoom Meeting, https://uncc.zoom.us/j/99371803400?pwd=QXhBM1AySUNBY1paZWY3RFhvUlRuQT09
Abstract:

Climate change is one of the most pivotal issues for the world in which we live today.

The power grid transformation to become, smarter sustainable and carbon-free,

has been a primary emphasis in recent times. This includes the integration of Distributed

Energy Sources (DERs). In this work, innovative and novel techniques are

presented to facilitate and expedite the engineering, planning, and deployment of

high penetration levels of renewable and distributed energy resources to aggressively

attack climate change and move the industry to a new paradigm. Towards this end,

both traditional and non-traditional techniques and methodologies are leveraged to

enhance distribution planning methods such that more electric distribution feeders

can be analyzed more dynamically. Tried and true iterative mathematical techniques

and convergence algorithms are used to adhere to the Laws of Physics for the flow of

electricity.

Findings in the area of Control Theory and System Identification are used to develop

dynamic and predictive models of the electric distribution system that analyze

the impact of interconnecting high levels of renewable generation. These predictive

models are represented by parametric models or transfer functions developed from the

Laplace Transform technique, leveraging proven powerful tools of time-domain and

frequency domain analysis to evaluate system stability. Critical to this work is both

the validation of realized models wherein these models can accurately predict system

response at varying load levels, renewable energy penetration levels, all-around necessary

sensitivities. Such a dynamic model development process can be used and

applied to any electric distribution feeder to better optimize penetration levels and

provide the planning engineer with smart models to optimize system planning.



Candidate Name: Brisa Urquieta de Hernandez
Title: The influence of urban restructuring on the social determinants of health in a Hispanic immigrant population in Charlotte, North Carolina.
 November 18, 2020  9:00 AM
Location: Zoom Meeting https://commonspirit.zoom.us/j/92564786302?pwd=anIyR25iVkdySjhMaTRibHpKbFpldz09
Abstract:

The environment where a person lives impacts their health more than clinical care provided. (RWJF, 2013) This research posits that the determinants of health (DOH) are best understood as a combination of social, structural, spatial and temporal aspects, not just “social”. Literature to date acknowledges these dimensions, although researchers have yet to fully explore. Utilizing a mixed-method approach, this research explores various DOH and their interactions spatially, structurally and temporally at the neighborhood level and how changes to those determinants are impacted by restructuring forces adversely affecting a Hispanic immigrant population. Specifically, this research aims to answer the following questions (1) How are the DOH impacted by the social, spatial, structural and temporal elements individually and in concert; (2) How has urban restructuring been a factor in the DOH for the Hispanic immigrant population in Southwest (SW) Charlotte; and (3) How does the acknowledgement of the structural, spatial and temporal aspects of DOH inform action to address the social and health needs of Hispanic immigrants living in Charlotte, NC. The South Boulevard corridor in the SW area of the city is the ideal case study location as it is simultaneously experiencing several forms of urban restructuring and an on-going influx of Hispanic immigrants. Ultimately, urban restructuring is an overlooked DOH in its own right - especially as it impacts vulnerable communities such as Hispanic immigrants as well as the importance of viewing the DOH in a nuanced manner acknowledging the influence and interactions of the various aspects.



Candidate Name: Alexander Blum
Title: Investigation of chemical wear in single point diamond turning of Copper-Nickel alloys
 December 07, 2020  1:30 PM
Location: CPM Conference Room, Duke Centennial Hall


Candidate Name: Kimberly Papay Rogers
Title: Perfect people, perfect environment: Applying person-environment interaction theory to examine the impact of Instagram use on health-related psychological outcomes among perfectionists
 November 12, 2020  10:00 AM
Location: Zoom, please email kpapay@uncc.edu for link
Abstract:

Perfectionism was once thought to be a detrimental personality trait that impacts health and psychological outcomes in negative ways. However, modern conceptualizations demonstrate that this trait is multidimensional and that impacts on outcomes are complex. Additionally, person-environment interaction (PEX) theories stipulate that personality traits are only triggered and expressed in environments that are relevant for that trait, that individuals are drawn to environments that “fit” with their underlying personality traits, and that personality traits can interact with environmental conditions in unique ways. Thus, the present study was designed to apply this perspective and examine the impact of perfectionism on psychological outcomes in the context of one particularly perfection-focused environment: the social networking site of Instagram. Secondary analysis of an existing data set was undertaken to address three research questions: (1) Are perfectionists drawn to the social media environment of Instagram? (2) Does perfectionism impact specific aspects of Instagram use? and (3) Is Instagram a more detrimental environment for perfectionists than non-perfectionists? An overall pattern of findings across 70 regression analyses provided preliminary answers to these questions. Results demonstrate that individuals high in one dimension of perfectionism, evaluative concerns perfectionism (ECP), are more likely to use Instagram and that these individuals tend to engage in active and problematic Instagram behaviors. Additionally, results demonstrate that these specific Instagram behaviors exacerbate the detrimental impact of ECP on psychological outcomes. Results of this study shed new light on both perfectionism and Instagram use, as well as highlight the importance of contextualizing both person-level and environment-level determinants of health-related psychological outcomes in general. Empirical and applied implications are discussed.



Candidate Name: Arash Karimzadeh
Title: Prediction of Defect Hotspots for Highway Maintenance Management: A Multi-asset Machine Learning Approach
 November 11, 2020  12:30 PM
Location: online
Abstract:

Given multiple budget and revenue constraints that the transportation sector encounters, predictive analytics enables maintenance agencies to make effective decisions, prioritize maintenance tasks, and provide efficient life-cycle planning. To this end, risk-based predictive models have provided promising results in representing the susceptibility of assets to future defects. Hence, the main objective of this study is to provide an integrated framework for predicting the occurrence probability of multiple defects on different highway asset types. Several gaps in previous models were identified, including limitations in predictive frameworks given the inadequate scope of available inspection data, expert-based selection of contributing factors, and ignoring the interrelationships between neighboring assets. Therefore, this study proposes a risk-based method that combines a risk score generator and a Machine Learning (ML) algorithm to predict the hotspots of multiple defects in a given roadway. To find the best fit, the model is chosen from a pool of ML algorithms selected from different categories. To measure the efficiency of the proposed model, its performance is investigated on a selected case study. The proposed framework produced significant accurate results within the extent of available data in the case study for calculating risk scores of erosion, obstruction, and cracking on paved ditches given historical weather, traffic, maintenance, and inspection data of five selected neighboring assets (flexible pavements, unpaved ditches, slopes, small pipes and box culverts, and under drain pipes and edge drains). Additionally, the contribution of the considered factors was investigated to further study the importance of individual contributors. The framework offers decision-makers a holistic view of degradation risks of multiple assets, which could enable them to prepare an integrated asset management program. Additionally, a similar framework can be applied to other linear infrastructure systems such as sanitary sewers, water networks, and railroads.