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Limited studies address high school gifted students' social and emotional needs (Knudsen, 2018; Kregel, 2015). Additionally, there is a lack of research regarding high school gifted students' and AIG directors' perspectives on the social and emotional strategies implemented locally within their school districts (Clinkenbeard, 2012; Kitsantas et al., 2017). Therefore, the purpose of this dissertation was (a) to discover the services school districts proposed to implement to meet the social and emotional needs of high school gifted students and (b) to explore high school gifted students’ and AIG directors’ perspectives about these services. Using purposeful sampling, this qualitative research included five participants from two school districts. The data collection methods implemented during this study were compiling school documents (i.e., 2022–2025 Local AIG Plans ) and conducting five separate interviews. I used document analysis to analyze data from the Local AIG Plans and thematic analysis to analyze data from the interviews. Results from the document analysis yielded three themes: program-level and curricula strategies, resources and support, and collaboration and counseling strategies. Results from the thematic analysis of interviews yielded three themes on how schools implement social and emotional services from the participants' perspective: social and emotional services, interaction, and gathering and sharing information. Further, the thematic analysis of participants' in-depth perspectives about these services yielded three themes: satisfaction and awareness, counseling, and limitations and improvements.
Random anti-reflective nanostructured surfaces (rARSS) enhance optical transmission through suppression of Fresnel reflection at layered-media boundaries. Windows with rARSS treatment are characterized (transmittance, reflectance, and scatter) using spectrophotometry and scatterometry to assess transmissive scatter performance over various spectral bands. Using measured spectral data, partial-integrated scatter values were obtained, allowing the comparison of random anti-reflective surface performance to optically flat surfaces.
Using a transfer function approach, an approximation of far-field light scatter can be modeled based on surface statistics. rARSS feature topology was determined using optical profilometry to obtain statistical surface roughness parameters, to assess the structured-surface feature scales. Random rough surfaces are well-modeled by Gaussian statistics, making them ideal candidates for a surface transfer function approach of surface scatter analysis.
The Generalized Harvey-Shack surface scatter theory was used to calculate surface feature diffractive effects. Scatter distributions predicted using a Gaussian two-parameter model of a random surface and structured surface metrology data were compared to measured scatter data for assessment of the transfer function model validity within the bandlimit of interest. Results show that prediction of wide angle rARSS optical scatter is viable using the transfer function approach, but the theory fails to predict transmission enhancement due to the inclusion of roughness.
The significance of this study was to give an active voice to the experiences of women superintendents. By giving voice to the lived experiences of women superintendents, the study sought to further understand the phenomenon of women dominating the teaching profession and other entry-level positions in education yet having a noticeably limited presence in the superintendency. More specifically, studying the barriers and supports women superintendents encounter could lead to significant opportunities to narrow the gender gap of women in the superintendency. Bringing awareness to the barriers and supports women superintendents experience could also foster more equitable workplaces. This qualitative, exploratory study aimed to identify barriers and supports faced by women school district superintendents as they ascended into the role and while they serve in the role. In this basic qualitative study, the researcher’s data sources involved semi-structured, one-on-one interviews with women superintendents. Results of the study indicate that participants felt that advancement factors were multifaceted and systematic, and employment pathways impacted options. In addition, personal obstacles acted as a barrier to reaching the superintendency. Also, gender discrimination was present while ascending to the superintendency and while serving in the role. Results also concluded that women superintendents credited their ongoing success to mentors and professional development. Implications included the need for awareness of leadership development opportunities for women in education, elimination of the glass ceiling, and additional research from women who aspire to be superintendents.
A staggering number of Internet-of-Things (IoT) devices harbor intrinsic security vulnerabilities in firmware. Memory errors especially predominate as a potent category among these vulnerabilities. Memory errors not only permit remote attackers to achieve Turing-complete access to compromised IoT devices but also provide a means to orchestrate massive Distributed Denial-of-Service (DDoS) attacks, capable of destabilizing even the most resilient Internet infrastructures. Standard protection techniques against memory errors, such as ASLR, can be easily bypassed, undermining their effectiveness. While certain advanced defense measures, such as software diversity and control-flow integrity, have been adapted for IoT devices, their constraints and associated overheads often render them impractical for deployment in real-world IoT devices.
This dissertation presents a holistic approach to securing memory error vulnerabilities in IoT firmware as four research thrusts: (1) we investigate remote attack strategies that exploit memory error vulnerabilities in ARM and x86 IoT firmware in the presence of standard software defenses such as DEP and ASLR; we also demonstrate man-in-the-middle attack strategies on actual IoT devices using tools such as Wi-Fi Pineapple; (2) we build and validate a testbed capable of hosting real-world IoT binaries in a simulated network, for deploying authentic DDoS scenarios; (3) we develop an IoT software diversity defense technique to resist memory error exploits; our technique generates multiple, semantically equivalent, syntactically distinct variations of IoT firmware that thwart mass duplication of identical firmware, thereby making it more challenging for attackers to deduce implementation details (crucial for memory error exploits) of any of these firmware binaries; and (4) we create cybersecurity educational modules for undergraduate and graduate students for teaching memory error exploit and defense techniques; we deploy our modules in multiple sections of an undergraduate introductory cybersecurity course at UNC Charlotte and analyze data collected through surveys on learning outcomes, engagement and experience.
In the continuous pursuit of advanced therapeutics, the field of bioinformatics has innovated tools that allow unprecedented control over the proteome, profoundly shaping our understanding and manipulation of biological domains. Computational approaches to protein design grapple with the intricacies of protein behavior, encompassing everything from interaction dynamics to stability challenges. Methods in structural bioinformatics for peptide design typically hinge on the datasets of structures that have statistics applied to ascertain the effectiveness of protein design and modulation. When dealing with proteins that are poorly resolved, disordered, or niche, this task usually falls to experts in structural biology and often requires significant laboratory resources.
This thesis discusses an automated pipeline, devised to integrate remote sequence homology, structural modeling, and binding simulations of peptides to disordered proteins. Significant design and testing underpin this pipeline, aiming to generate binding peptides to any sequence, sidestepping the absolute requirement for an expert or a tedious process to produce leads. The utility of this pipeline is assessed across a diverse set of protein systems to refine its methodology. With the recent rise of machine learning-driven predictive or generative models, we explore their potential when integrated with our pipeline in attempt to address challenges in the computation of peptide binder design.
Faithful repair of DNA lesions is central to maintaining genomic integrity. Illegitimate repair of chromosomal DNA damage, especially double-strand breaks (DSBs), can lead to mutations and genome rearrangements. Homologous recombination (HR) is a highly conserved molecular process that plays an important role in the repair of DSBs and the maintenance of genome stability. However, it is not fully understood which cell populations at which developmental stages in vivo have the potential to use this “error-free” repair mechanism. Further, although HR is considered to be “error-free”, illegitimate inter-chromosomal HR has been linked to the formation of chromosomal translocations that are a hallmark of leukemias, lymphomas, and sarcomas. For my studies, I engineered a transgenic mouse “Rainbow Mouse” model to induce specific chromosomal DSBs in vivo and score for inter-chromosomal HR repair in multiple tissues and cell types. I used the Rainbow Mouse to address critical biological questions- What is the relative frequency of inter-chromosomal HR repair among different tissue subpopulations? Which cell types are more likely to utilize this mechanism? Can DSBs induced in utero be repaired by inter-chromosomal HR repair? I hypothesized a significant difference in inter-chromosomal HR observed in different cell types based on their cellular differentiation state.
Overall, my research demonstrates a function reporter model to evaluate inter-chromosomal HR in vivo. My research identified specific cell types, such as pancreatic duct cells and hematopoietic stem cell enriched LIN-/CD34+ populations that undergo DSB-induced inter-chromosomal HR leading to mutation. The findings from my research highlight developmental and cell type-specific differences in the potential for inter-chromosomal HR to be used in the repair of DSBs. The Rainbow mouse model utilized in this study has the potential for long-term application in assessing the mutagenic effects of various environmental and dietary compounds, as well as understanding the role of specific proteins involved in repairing DNA damage induced by these compounds.
This dissertation addresses the problem of non-myopic online exploration and visual sensor coverage of large-scale unknown environments using an autonomous robot. We introduce a novel perception roadmap, referred to as the Active Perception Network (APN), that represents a connected configuration space over a concurrently built spatial map. The APN is modeled by a hierarchical topological hypergraph that equips a robot with an understanding of how to traverse throughout a concurrently built spatial map, and facilitates predictive reasoning on the expected visible information of the environment from untraversed regions of the map.
As new information is added to the map during exploration, the APN is iteratively updated by an adaptive algorithm entitled Differential Regulation (DFR), which applies difference-aware strategies to constrain the complexity of each update to the size of changed map information, independent of its total size. DFR employs a view sampling-based strategy to expand and refine traversability knowledge as map knowledge increases, using a novel frontier-based approach to evaluate information gain and guide the sampling and pruning of views within the APN. The APN serves as a knowledge model which can be applied for graph-based exploration planning. An evolutionary planner, designated as APN-P, leverages the hierarchical representation of the APN to perform non-myopic exploration planning that dynamically adapts to the changing map and APN states.
This dissertation further presents a software development framework, Active Perception for Exploration, Mapping, and Planning (APEXMAP), that addresses the unique software design and implementation challenges inherent to online exploration and active perception tasks, which are non-trivial. APEXMAP provides a generalized modular framework for these challenges, which is made open source for the benefit of the research community.
In the U.S., there has been a steady increase in the number of adult children (i.e., filial caregivers) providing care to their aging parents. Filial caregiving impacts not only the caregiver and recipient, but also caregivers’ spouses. This necessitates an understanding of how filial caregivers and their spouses cope with the stressors of caregiving. Communal coping, which involves both couple members viewing a stressor as a shared problem and responsibility that is managed together (Lyons et al.,1998), provides a promising framework for understanding how couples cope with chronic stressors. However, in the context of filial caregiving, wherein the responsibility of providing care is an extra-dyadic stressor, and the non-caregiving spouse may feel less obligated to be involved in providing care, it is unclear whether communal coping would be beneficial for caregivers’ and spouses’ personal and relational well-being, and whether there are motivations driving communal coping. My dissertation was designed to examine the antecedents and consequences of communal coping in this unique context. Forty-two filial caregivers and their spouses (N = 83 individuals) completed an online survey assessing relational motives (i.e., compassionate goals and communal strength), communal coping, and personal and relational well-being. Results indicated that communal coping was beneficial for caregivers’ relational well-being and that compassionate goals may be an important predictor of communal coping for spouses. These findings broaden our understanding of the consequences of communal coping for caregivers’ and spouses’ personal and relational well-being and offer insight into how relational motives contribute to communal coping in the context of filial caregiving. Further research examining the relationship between relational motives, communal coping, and subsequent effects on well-being in the filial caregiving context is suggested.
Nearly 65% of adults report experiencing at least one adverse childhood experience (ACEs). Women are more likely to report experiencing 4 or more ACEs. While the association between ACEs and adverse physical and mental health outcomes in adulthood is well supported, few studies have examined the impact of ACEs on reproductive, prenatal, and perinatal health. Women with a history of ACEs have increased odds of unintended pregnancy, pregnancy complications, and delivering infants who are low birth weight and preterm birth. The purpose of this dissertation was to assess the associations between ACEs and contraceptive use, early initiation of prenatal care (PNC), and delivering a small for gestational age (SGA) infant.
Three separate population-based studies were conducted to investigate these associations using Add Health Public-Use Data, which is a subset of publicly available data from the full National Longitudinal Study of Adolescent Health dataset. The first study assessed the association between ACEs and contraceptive use. The second study evaluated the association between ACEs and early initiation of PNC. The third study examined the ACEs-SGA association as well as examined race/ethnicity as an effect modifier of this association. Logistic regression and multivariate logistic regression were used to calculate the unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs), respectively. Stratified analysis by race/ethnicity was conducted on the ACEs-SGA association. Given the complex sampling design of Add Health Public-Use Data, all analyses were performed using SAS survey procedures (version 9.4, SAS Institute Inc. Cary, NC).
Across all studies, ACEs were associated with adverse health outcomes. In the first study, women with a family history of suicidal behavior had statistically significant decreased odds of contraceptive use (AOR=0.69, 95% CI: 0.51-0.96). Findings from the second study demonstrated that women who experienced parental alcoholism had 82% statistically significant decreased odds of early initiation of PNC (AOR=0.18, 95% CI: 0.06-0.55). In the third study on ACEs and birth outcomes, women who experienced parental alcoholism had statistically significant increased odds of delivering an SGA infant (AOR=4.11, 95% CI: 1.09-15.52). When stratified by race/ethnicity, among Non-Hispanic White women, those who experienced parental alcoholism had 7-fold statistically significant increased odds of delivering an SGA infant (AOR=7.39, 95% CI: 1.44-37.88). Among Non-Hispanic Black/Hispanic/Other women, those who experienced parental alcoholism had 1.6-fold increased odds of delivering an SGA infant (AOR=1.55, 95% CI: 0.22-10.84).
This dissertation addresses existing gaps in the literature on the impact of ACEs on women’s reproductive, prenatal, and perinatal health. Study results highlight the importance of integrating mental health and reproductive health care services. By implementing trauma-informed care practices such as ACEs screening during reproductive health and PNC visits, healthcare providers may provide additional support for this high-risk population of women. In addition, healthcare providers should underscore the importance of PNC during preconception reproductive health counseling as these visits may serve as an opportunity to engage these women before a pregnancy. By doing so, early PNC may reduce and prevent SGA births.
With adolescent mental health problems on the rise, secondary school teachers are in a prime position to support students. This study sought to fill a scholarly research gap and inform future mental health literacy (MHL) training needs for teachers and to identify implications for their professional practice. Specifically, this study sought to address the limited research available on the newly deemed “at-risk” population of students in high achieving schools (HASs) enrolled in accelerated courses taught by Advanced Placement (AP) teachers. The purpose of this basic interpretive qualitative study was to investigate the perceptions of high school AP teachers in HASs regarding MHL by understanding how they perceive and develop their MHL knowledge base, the effectiveness of training they have received, and the relationship between their MHL knowledge and professional practice. Results of the study from semi-structured one-on-one interviews with five high school Advanced Placement (AP) teachers within a HAS indicated that the MHL knowledge base of these teachers was inadequate for supporting students with mental health problems. Further, results indicated that the MHL training that they have received was insufficient, leading them to rely on experience beyond in-school training to develop knowledge. Implications of the study suggest a need for targeted, comprehensive pre-service and school-level MHL training and curriculum for high school AP teachers to be developed, integrated across courses, and monitored by leadership.
