Dissertation Defense Announcements

Candidate Name: Wei Rang
Title: Optimizing Performance of In-memory Computing with Hybrid Memory System
 November 11, 2021  10:00 AM
Location: Zoom link: https://uncc.zoom.us/j/97502079709
Abstract:

The development of in-memory computing has fueled the emergence of in-memory computing systems. Data explosion is also posing an unprecedented demand for memory capacity to handle the ever-growing data size. Thus, in-memory computing systems are increasingly looking inward at hybrid memory caches of under-processed data as resources to be mined. Our preliminary study finds that some existing data management strategies often trade application performance for low memory utilization, and hence can induce frequent I/O operations between memory system and storage system.

To achieve this goal, we propose to design a hybrid memory system that includes fast and relatively slow memory hardware. In order to realize a runtime system that automatically optimizes data management on hybrid memory, we will (1) propose a new shared in-memory cache layer among parallel executors that are co-hosted on the same computing node, which aims to improve the overall hit rate of data blocks; (2) develop a middleware layer built on top of existing deep learning frameworks that streamlines the support and implementation of online learning applications; (3) design a unified in-memory computing architecture with efficient data management strategy to optimize memory allocation and recycle for ML applications.



Candidate Name: Serang Park
Title: Terahertz optical properties of metamaterials and optical components fabricated using polymer-based additive manufacturing
 November 04, 2021  11:00 AM
Location: Grigg 131
Abstract:

Advancement in terahertz technologies have drawn interests in optical components suitable for the terahertz spectral range. Stereolithography, with its superior resolution, could be an efficient way of fabricating such terahertz elements with sub-wavelength scale architectures. However, stereolithographically fabricated terahertz optical elements or metamaterials have not yet been studied extensively. In this thesis, we sought to explore the terahertz optical properties of stereolithographically fabricated optics and novel metamaterials. Terahertz optical properties of materials commonly available for stereolithography have been accurately determined. Utilizing the determined properties, one-dimensional terahertz photonic crystals and defect modes within such crystals have been demonstrated for the first time through a single-step stereolithography from a single dielectric material. Mechanical tunability of the photonic bandgap and defect modes of the photonic crystals was experimentally realized. In addition, stereolithographically fabricated anisotropic metamaterial composed of slanted columnar structures have been investigated as a single layer, as well as constituent layers of one-dimensional photonic crystal structures for the first time. Off-axis parabolic reflectors have been demonstrated by metalizing a stereolithographically fabricated polymer base and by employing one-dimensional photonic crystal structure into design. In conclusion, stereolithography has been introduced as a new paradigm for fabrication of custom terahertz elements and novel metamaterials with tailored optical properties.



Candidate Name: Remi Ketchum
Title: MECHANISMS OF ACCLIMATION AND ADAPTATION IN THE SEA URCHIN ECHINOMETRA SP. EZ
 November 04, 2021  1:00 PM
Location: https://uncc.zoom.us/j/92697507458?pwd=NjFwd0lNUkRydGVrQzhYaW5wdUpsUT09
Abstract:

Climate change has resulted in warming of coastal aquatic habitats around the world at almost every latitude, threatening ecosystems with a significant loss in biodiversity and occurring at a rate that may exceed species’ ability to adapt. Understanding how reef species survive in habitats that currently experience extreme temperatures will help identify the biological processes that will govern future responses to climate change. The Persian/Arabian Gulf experiences the warmest coral reef temperatures on the planet (summer maxima ~35-36°C but can exceed 37°C) and connects to the neighboring Gulf of Oman, which experiences more benign environmental conditions (summer maxima of ~30-32°C). Here, we leverage this unique environmental gradient as a natural laboratory to better understand how the keystone sea urchin Echinometra sp. EZ copes with thermal extremes. Species survival in extreme habitats is dependent on their ability to acclimate over the course of an organisms’ lifetime and adapt over the course of many generations. Two complementary mechanisms for coping with environmental change are shifts in the host-associated microbial community, which can happen on a timescale of hours to days, and classic Darwinian evolution in which selection results in different patterns of alleles between populations over many generations. Here, we identify temperature as a robust predictor of community-level microbial variation and highlight specific bacterial taxa that may be crucial for maintenance of host homeostasis during thermal extremes. Next, we show that while there is a high degree of genetic admixture between all sites and bidirectional gene flow between the two seas, there is also significant population differentiation. We describe nine candidate loci that are under putative selection, including one collagen gene. Finally, we sequence, assemble, and annotate a chromosome-level genome that will add substantial value to future functional genomic datasets. Together, the research composing my dissertation has identified the importance of novel microbiome and genomic variation in the adaptation of a dominant ecosystem engineer to the warmest marine environment on Earth. These integrative results provide a foothold for understanding shared and unique mechanisms for the adaptation of marine species to historic and ongoing climate change.



Candidate Name: Taryn Greene
Title: THE NATURE AND DIMENSIONALITY OF REPETITIVE THOUGHT
 November 04, 2021  12:00 PM
Location: Virtual (Zoom)
Abstract:

Background: Current popular conceptualizations of the psychological process Repetitive Thought (RT) appear of limited accuracy due to ample construct proliferation (e.g. equating RT with rumination or worry), tautological definitions, and the construct being studied primarily in mentally disordered populations. This paper sought to unite current disparate lines of research surrounding RT, in order to illuminate and clarify the nature of RT.

Methods: Two studies were completed: First, a systematic literature review was conducted in order to develop a more comprehensive and conceptually coherent model of RT. Second, the structural validity of the model produced by the first study was empirically tested using factor analytic and multiple regression techniques.

Results: Partially Exploratory Factor Analyses revealed a strong general Repetitive Thinking factor, as well as a three-factor model that was empirically most appropriate (Intrusive Repetitive Thought, Deliberate Processing, and Self-Conscious Repetitive Thought). Additional validation analyses confirmed these findings.

Conclusions: This study contributes to our understanding of the nature of Repetitive Thought. Importantly, the three RT factors can be conceptualized as independent dimensions that are all part of a larger RT trait. The empirical and applied implications of the conceptualization of RT, as well as development of a preliminary measure of RT, are discussed.



Candidate Name: Peyman Razi
Title: Numerical Simulations and Low-Order Models of the Two-Way Interaction between Ocean Current Turbines and the Background Flow
 November 15, 2021  11:00 AM
Location: https://uncc.zoom.us/j/95188333283
Abstract:

Ocean Current Turbines (OCTs), which function similarly to wind and tidal turbines, represent a promising technology for harnessing the energy from oceanic currents such as the Gulf Stream. In planning the deployment of arrays of OCT devices, it is critical to consider the two-way interactions between the turbines and the ocean environment: temporally and spatially nonuniform flow fields are expected in the dynamic flow environments of western boundary currents, and include the presence of upstream shear and turbulence. These nonuniform flow conditions will affect power extraction, and the efficiency of the turbines when operating in isolation or as part of an array. Furthermore, models that are used in a predictive capability to compute the levelized cost of energy obtainable from such devices, or to optimize the layout of an array of turbines must be modified to account for the effects of such spatially and temporally inhomogeneous conditions. Similarly, the operation of OCT arrays can in turn influence the background flow in two significant ways, namely by contributing to the production of turbulence and through the generation of internal gravity waves that are radiated away from the point of origin. In this thesis, we have studied using detailed numerical simulations, the above two-way interaction between arrays of OCTs and the ocean environment. Insights developed from the simulations have guided the development of low-order wake interaction models capable of describing the effects of inhomogeneous flow conditions on array performance.
A new, wake interaction modeling framework capable of capturing the detailed effects of turbulence and upstream shear on various performance parameters associated with OCTs arranged in any arbitrary configuration has been developed. The model accounts for the effects of turbulence and shear on the structure of the turbine wakes, specifically the extents of near- and far-wake regions. The analytical description for turbine wake is combined with an existing wake interaction model, the Unrestricted Wind Farm Layout Optimization model to predict the global power output from an array of OCTs. The resulting modelling framework accurately captures the effect of inlet turbulence and shear on the OCT farm power and efficiency, and can be applied to any array configuration. Results from the model were validated against both Large Eddy Simulations and Reynolds Averaged Navier-Stokes simulations, in which the OCTs were modeled using a Blade Element Momentum model. The dispersion of OCT wake turbulence through the background stratification of the ocean was investigated using Large Eddy Simulations for different levels of the density stratification. The effects of varying the strength of the stratification as well as the turbulent forcing were studied. Finally, the wake turbulence associated with OCT operation can drive the formation and radiation of internal gravity waves in the density-stratified background flow of ocean currents. Through detailed numerical simulations, the effect of the propagation of the internal waves on the background turbulent diffusivity was studied, and found to alter the transport properties of the ambient flow. The properties of the internal wave field, and its impact on background turbulent mixing was found to depend both on the Richardson number and the ambient, upstream turbulence.



Candidate Name: Shreya Goyal
Title: VPS501, A NOVEL SNX-BAR PROTEIN INVOLVED IN AUTOPHAGY
 October 18, 2021  12:00 PM
Location: Zoom
Abstract:

Careful control of intracellular signaling pathways plays an important role in a cell’s ability to maintain stable internal conditions in the face of an ever-changing extracellular environment. This is particularly true as it relates to the process of cellular self-eating or autophagy. Macroautophagy (herein referred to as autophagy) is a catabolic process by which unneeded or damaged cellular components are sequestered as cargo into unique double-membrane vesicles called autophagosomes which fuse to the vacuole (yeast lysosome) to be metabolized. The autophagy-related (Atg) proteins that mediate and regulate the process are evolutionarily conserved across all autophagy pathways, including starvation-induced bulk autophagy and cargo-selective autophagy pathways. The central theme of this thesis is to understand how autophagy is affected by lipids and regulatory proteins in yeast. In this thesis, we have summarized the field’s understanding of lipid homeostasis and trafficking during autophagy and autophagosome formation. Furthermore, we have extended this knowledge by discovering a clear interplay between autophagy and the SNX-BAR protein subfamily. In recent years, the SNX-BARs have been reported to have emerging roles in autophagy, however, such mechanisms of action have been primarily indirect. In this thesis, we have characterized a novel SNX-BAR protein, we have termed Vps501 and have found it directly affects autophagy which brings to light a new role of SNX-BAR proteins in autophagy regulation.



Candidate Name: Bo Qiu
Title: Travel Time Forecasting on a Freeway Corridor: a Dynamic Information Fusion Model based on the Machine Learning Approach
 November 10, 2021  1:00 PM
Location: EPIC 1229
Abstract:

The metropolitan areas suffer more traffic, the change in travel time is very complex as it can be influenced by various factors, many of which are also unpredictable. Random forest was applied in the travel time prediction application to overcome the overfitting problem. Furthermore, the attention mechanism is implemented by developing the neural network to capture the inner relationship within the traffic data. The proposed long short memory neural network with attention mechanism method achieves its superior capability for TTP longer than 15 minutes (30 min to 60 min), overcoming the performance issue through long temporal dependency and memory blocks. To validate the accuracy and reliability of proposed models, the proposed approaches are tested using a freeway corridor in Charlotte, North Carolina, using the probe vehicle-based traffic data. Detailed information about the input variables and data preprocessing was presented. The results indicate that all proposed TTP models predicting in 15 minutes show better prediction performance over the other time horizons. A comparison with other prediction methods validates that the proposed hybrid LSTM and RF method can achieve a better prediction performance in accuracy and efficiency, proving its deployment is one of the successful solutions to critical, real-world transportation challenges.



Candidate Name: Karla Natalia Villatoro Godoy
Title: Three Essays on Corporate Financial Policies
 October 29, 2021  2:00 PM
Location: Virtual


Candidate Name: William Ray Leach
Title: Ambiguous Loss and Parental Traumatic Brain Injury
 November 04, 2021  12:00 PM
Location: Virtual- Email for Zoom Link
Abstract:

ABSTRACT

WILLIAM RAY LEACH. Ambiguous Loss and Parental Traumatic Brain Injury
(Under the direction of DR. DREW POLLY)

Parental traumatic brain injury (PTBI) and the effect it has on adolescents living in the home has been mostly avoided in the current literature. Even more rare in the literature is the idea of ambiguous loss, coined by Boss (1991). An ambiguous loss refers to a loss of someone who has not died, but who is also not the same person as before the injury, physically or mentally. Consequently, the loss is unclear and requires constant recalibration by the uninjured family members to accept their ever-changing injured family member. Together, no researcher has ever studied ambiguous loss as it relates to PTBI.
This study focused on three research questions:
Research Question 1: As it pertains to PTBI, what is the influence of ambiguous loss when experienced during adolescence?
Research Question 2: When PTBI is experienced in adolescence, how does the perception of ambiguous loss result in tangible consequences later in life?
Research Question 3: In what ways do adolescents experiencing ambiguous loss from PTBI describe their family, self, and situation? 
Using a qualitative approach, this phenomenological dissertation found that ambiguous loss affects adolescents in different ways and at different times after the injury has occurred. Ambiguous loss can also result in tangible consequences later in their life. The time since the injury can affect the severity of feelings of ambiguous loss, however, this study also found that PTBI adolescents can exhibit traits of resilience through their experience.




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