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Empowering Neurodivergent Students through Extended Reality/Virtual Reality, Game-Based Learning to Increase Cybersecurity Literacy and Career Readiness
No full textRecent cyberattacks have caused the U.S. government to prioritize cybersecurity. A 2025 White House press release documents that the U.S. economy annually endures billions of dollars in losses to cyber-enabled fraud and cybercrime. Cyberattacks are increasing, so the need
for cybersecurity workers is high. Cyberseek and the National Institute of Standards Technology (NIST) in the United States report more than 400,000 job vacancies in the cybersecurity field. The 2025 Gartner CIO Talent Planning Survey surveyed 487 IT leaders, revealing that
81% of IT leaders anticipate a surge in the demand for cybersecurity skills over the next three years. The shortage of cybersecurity workers and the increasing skills gap present significant employment opportunities for individuals with neurological differences, such as Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD), among others. Between 2011 and 2021, the National Science Foundation (NSF) reported that 34.9 million Americans worked in STEM fields. Among these 34.9 million individuals, only one million
have disabilities (both physical and mental conditions). Currently, there is limited quantitative data available to determine the specific STEM careers pursued by individuals with disabilities. Despite this, qualitative research and interviews suggest a strong correlation between
computer-related fields, such as cybersecurity, and success among the neurodivergent population. Individuals with neurological differences, often referred to as “neurodivergent,” a term coined by Kassiane Asasumasu in 2000, or “neurodiverse,” a term coined by Judy Singer in the late 1990s, possess specific skills to fill cybersecurity roles.
The most in-demand cybersecurity skills in the current market are identifying hidden relationships and patterns, mitigating cognitive biases, problem-solving, and more. Sophos, a well-known security solutions vendor, reports that 54% of companies say their IT department cannot handle sophisticated methods, such as ransomware, phishing, and Distributed Denial of Service (DDoS) attacks by cybercriminals. In its latest Cybersecurity Workforce Study, the International Information System Security Certification Consortium (ISC2), the world’s largest
IT security organization, states that 70% of cybersecurity professionals report that their organizations are understaffed. There is a lack of technological pedagogical tools for this talent pool, such as XR/VR and GBL. The objective of this study is to design and develop Immersive
Cybersecurity Experiences (ICE), a Virtual Reality and Game-based learning framework, to improve the cybersecurity literacy of the neurodivergent audience for cybersecurity career readiness. By involving the neurodivergent population in the design process of this framework, we can gain insights on how to keep them engaged and motivated and design to accommodate their learning preferences
A Randomized Controlled Trial to Determine the Effects of Curcumin and Epigallocatechin Gallate Supplementation on Serum Brain Derived Neurotrophic Factor and Mood Disturbance in Adults
Get PDFMood disorders such as depression, anxiety, stress, and sleep disturbances are becoming increasingly prevalent. Brain-Derived Neurotrophic Factor (BDNF), a neurotrophin involved in neuroplasticity and neuronal health, has emerged as a promising biomarker associated with psychiatric and mood related conditions. The research on and use of alternative treatments for such conditions are increasing with nutritional compounds like epigallocatechin-3-gallate (EGCG) and curcumin demonstrating potential neuroprotective and mood-modulating effects. This study aimed to evaluate the impact of supplementation with these two compounds on mood disorder symptomology and serum BDNF in a young adult population with moderate depression symptoms. This was a randomized double-blinded placebo-controlled trial (RCT) where eligible participants were randomized to consume EGCG (350mg/day) and curcumin (1,330mg/day) or placebo capsules for 8-weeks. Mood outcomes were measured using the Depression, Anxiety and Stress Scale (DASS-21) and Generalized Anxiety Disorder (GAD-7), sleep was assessed using the Global Sleep Assessment Questionnaire (GSAQ), and physical activity was measured with the International Physical Activity Questionnaire (IPAQ), all assessed at baseline, Week 4 and Week 8 with dietary intake and serum BDNF measured at baseline and Week 8. Individuals that were ineligible for the RCT due to low DASS-21 scores (controls) were recruited and matched to case participants by age, sex, and race for a case-control study.
Results indicated significant improvements in mood (DASS-21 Composite, DASS-21 Depression, DASS-21 Stress, DASS-21 Anxiety, GAD-7, p < .001 for all), sleep (p < .001) and physical activity scores (p < .01) across all RCT participants with no significant difference between supplement and placebo groups. Mean serum BDNF levels did increase on average over the intervention in both groups but not to a statistically significant amount with no group by time interactions found. Correlation analysis revealed significant positive correlations between sugar intake (g/kg body weight) and mood symptoms in the intervention group at Week 8, further highlighting dietary impacts on mental health. Healthy Eating Index (HEI) scores for fruit and vegetable intake were included to control for dietary polyphenol intake. Higher baseline fruit and vegetable intake was associated with lower depression, anxiety, and stress scores at select timepoints. However, changes in fruit and vegetable intake during the intervention were not significantly related to changes in mood symptomology, which suggests that dietary improvements did not account for any mood changes that were observed over the 8-week period.
In the case-control study, the cases group had significantly higher mood disturbance scores compared to the matched controls (DASS-21 Composite and all subscales, as well as GAD-7, p < .001 for all). Physical activity levels of the cases group were significantly lower than the controls (p < .037). There were significant differences found in serum BDNF between the groups, with cases showing significantly lower levels versus controls (p <.001). Healthy Eating Index (HEI) scores in the case-control analysis showed that baseline fruit and vegetable intake did not significantly predict mood symptom severity with no differences in diet quality observed between cases and controls. This indicates comparable baseline dietary pattern with minimal confounding from polyphenol intake in mood outcome comparisons.
This study found that although the supplement group demonstrated significant reductions in mood disturbance and sleep disturbance scores, concurrent improvements in the placebo group indicate that the supplement had no effect. Several factors may have contributed to these null results and can be addressed in future studies. Additional research is warranted to delineate the specific roles of EGCG and curcumin, particularly in relation to BDNF modulation
Products for Transformative Meaning: A Methodology for Sandbox Products As Emergent, Unorthodox Creative Tools Enabled by the Reframing of Design Praxis Through the Nexus Object Hermeneutic
No full textThis thesis argues that the field of Industrial Design is philosophically ill-equipped to accommodate and adapt to the growing imminence of the Transformation Economy. At the cusp of a progression from mere commodities, services, or experiences, user preferences have begun to shift towards the desire for more meaningful engagement with products which openly address notions of holistic fulfillment, human flourishing, or eudaemonia. Closing this perceived “meaning gap” for users in the current product economy necessitates a genuine re-evaluation of contemporary design theory and praxis. This thesis argues that the dominant paradigm of the contemporary designer is negatively influenced by a progressive series of interrelated historical ruptures regarding ontology, metaphysics, theology, technology, materiality, and secularism.
This emergent desire for transformational value amongst certain user groups cannot be categorically met due to an embedded pluralism within the current design paradigm formed out of the Modern Movement, as well as modernism in a broad sense; these movements have openly opposed historical continuity regarding the a priori categories of philosophy which must first be coherent in order to form clarity regarding “transformation” or “eudaemonia”.
This presents a profound dilemma for designers insofar that the demand for this holistic fulfillment and transformational experience remains perpetually unbalanced by a lack of relevant methodologies for such products. The previous leniency upon tangible principles of functionalism and utilitarianism in industrial design is insufficient for this transformational category of user experience which corresponds to intangible aspects of object encounters.
In response to this dilemma, this thesis proposes the Nexus Object Hermeneutic as a new cognitive tool for designers: a mental model for re-categorizing objects based on their ontological efficacy rather than strict utility. This framework emphasizes how objects may influence user states of being and correspond to perceptual meaning and identity. This conceptual bedrock provides potential for engaging burgeoning categories of products which pertain to user transformation and ontological change rather than mere function.
Out of this distinction emerges the Sandbox Product (SBP): a burgeoning category of unorthodox creative tools which facilitate creative empowerment, encourage layered engagement, cater to flexible use cases, foster re-enchantment of the external world, and provide playful experiences and novel aesthetics.
This thesis recognizes the user desire for creative fulfillment as a fundamental corollary within the emerging umbrella of transformational design propositions. This means that creativity corresponds directly with notions of eudaemonia and holistic human flourishing. Enabled by the provided philosophical distinctions within the Nexus Object Hermeneutic, a subsequent methodology will be provided for these Sandbox Products as a step forward into the world of transformational design
Effectiveness, Safety, and Cost-Effectiveness of Immune Checkpoint Inhibitors for Metastatic Non-Small Cell Lung Cancer: Leveraging Real-World Evidence
No full textObjective: The purpose of this doctoral dissertation project was to 1) compare the effectiveness of first-line individual immune checkpoint inhibitor (ICI) agents and ICI in combination with chemotherapy (ICI-Chemotherapy) versus ICI monotherapy (ICI-Monotherapy) for patients with metastatic non-small cell lung cancer (mNSCLC), 2) develop regression and machine learning (ML) models for the prediction of immune-related adverse events (irAEs), and 3) evaluate the cost-effectiveness of first-line cemiplimab plus chemotherapy (CCT) compared to pembrolizumab plus chemotherapy (PCT).
Methods: For Aims 1 and 2, we used the 2014–2020 Surveillance, Epidemiology, and End Results (SEER)-Medicare-linked database. In aim 1, we designed a new-user cohort to compare the effectiveness of first-line atezolizumab, nivolumab, and pembrolizumab among older adults with mNSCLC. Overall survival (OS) was compared using unadjusted, multivariable-adjusted, and propensity score matching (PSM) Cox proportional hazards models. Additionally, we emulated two hypothetical target trials to compare OS between first-line ICI-Monotherapy and ICI-Chemotherapy, and 4 versus 6 cycles of chemotherapy within the first-line ICI-Chemotherapy regimens. The clone-censor-weight approach and discrete-time hazards model were applied to estimate the per-protocol treatment effects. OS was evaluated through survival curves, 72-week OS probabilities,72-week restricted mean survival time (RMST), and hazard ratios (HR). In aim 2, given the suboptimal performance of models in predicting overall irAEs, we systematically evaluated predictive performance across irAE subtypes, ultimately focusing on endocrine-related irAEs. Patients with mNSCLC treated with first-line ICIs were randomly divided into training (80%) and testing (20%) sets. We developed the Least Absolute Shrinkage and Selection Operator (LASSO) and ML approaches, including random forest, support vector machines, and XGBoost, to predict 3-month endocrine-related irAEs. Model performance was evaluated using accuracy, F1 score, and the area under the receiver operating characteristic curve (AUROC) in the test set. In aim 3, a three-state partitioned survival model with a 10-year time horizon was constructed. Clinical data were sourced from the EMPOWER-Lung 3, KEYNOTE-407, and KEYNOTE-189 trials. Costs and quality of life inputs were obtained from the 2024 U.S. Centers for Medicare & Medicaid Services drug price lists and published literature. We calculated the total cost, quality-adjusted life-years (QALYs) gained, and the incremental cost-effectiveness ratio (ICER).
Results: Pembrolizumab was associated with a significant survival benefit compared to atezolizumab (multivariable-adjusted HR=0.67; 95% confidence interval (CI)=0.53-0.84; PSM HR=0.69; 95% CI=0.54-0.87) and nivolumab (multivariable-adjusted HR=0.83; 95% CI=0.69-0.99). In the per-protocol analysis of emulated target trials, ICI-Chemotherapy provided a marked OS advantage over ICI-Monotherapy, including a 5.5% higher 72-week OS rate (95% CI=4.2%-6.7%), a 6.27-week additional RMST gain (95% CI=4.88-7.61), and HR=0.76 (95% CI=0.71-0.81). Patients receiving 6 versus 4 cycles of chemotherapy had a 5.1% (95% CI=–0.9%–11.0%) higher 72-week OS rate, a 2.19-week additional RMST gain (95% CI=0.54–4.92), and an HR of 0.83 (95% CI=0.65–0.95). The LASSO model outperformed other ML models to predict 3-month endocrine-related irAEs, achieving an accuracy of 0.791 (95% CI=0.789–0.793), an F1 score of 0.507 (95% CI=0.502–0.512), and an AUROC of 0.724 (95% CI=0.719–0.728). The most important predictors identified included pre-existing endocrine disorders, type 2 diabetes, use of atezolizumab, concurrent chemotherapy, and patient demographics. In the cost-effectiveness analysis, the total cost of PCT was 175,247 with 1.657 QALYs, indicating that CCT was a dominant first-line treatment strategy over PCT (ICER=−$675,304 per QALY) for patients with mNSCLC.
Conclusion: Pembrolizumab was associated with a significant OS benefit compared with atezolizumab and nivolumab among older adults with mNSCLC. Adding chemotherapy to first-line ICI therapy offered additional survival benefits over ICI-Monotherapy, and extending chemotherapy from 4 to 6 cycles was associated with additional improvements in survival outcomes. The LASSO model demonstrated the best performance in predicting endocrine-related irAEs using SEER-Medicare data. Compared with PCT, CCT was a dominant first-line treatment option for mNSCLC from a cost-effectiveness perspective
Latent Profiles of Cannabis Use Patterns and Associations with Binge Eating and Eating Pathology Outcomes
No full textAs rates of recreational cannabis use continue to increase among United States adults, there is growing interest in understanding potential health co-mordibities and vulnerabilities. Although past work supports cannabis use and eating pathology comorbidity, and cannabis use can enhance appetite and reward responses to food, little is known about how specific patterns of cannabis use may relate to binge eating and other forms of eating disorder pathology. The purpose of this study is to identify distinct subgroups of recreational cannabis users based on several use characteristics, including subjective changes to appetite and hedonic properties of food using latent profile analysis, and to examine differences across profiles in binge eating and other eating disorder symptoms. Participants (N = 435, male = 189) were adults recruited through Prolific who endorsed past-month cannabis use and completed a battery of self-report measures assessing cannabis use characteristics, eating changes while using cannabis, eating pathology, and emotion regulation. Results supported four unique profiles of cannabis users based on six indicators: “Infrequent Users, Moderate Eating Changes, Low Risk,” “Intense Users, Low Eating Changes, Mild Risk,” “High-Risk Coping Users, Strong Eating Changes,” and “Frequent Users, Slight Eating Changes, Mild Risk.” While all profiles reported more binge eating symptoms while under the influence of cannabis, the “High Risk Coping Users, Strong Eating Changes” profile reported more frequent/severe binge eating symptoms, greater endorsement of other eating pathology symptoms, and more difficulties with emotion regulation compared to other profiles. Findings highlight the utility of person-centered approaches for capturing co-morbidity risk, and may help guide screening and intervention tools for determining eating disorder risk among those using cannabis
Essays on Platform Agency in Crowdsourcing
No full textDigital platforms are socio-technical systems that enable interaction and exchange between distributed users through algorithmic and interface design. Within this broader category, crowdsourced systems mobilize labor, capital, or knowledge from large, decentralized user bases. Far from being neutral intermediaries, these platforms exercise active agency through their design choices, governance policies, and algorithmic decisions—fundamentally shaping participation patterns and resource flows. This dissertation examines platform agency in such crowdsourced systems across three essays. Essay 1 examines how crowdfunded prosocial lending platforms influence financial resource allocation by shaping lender attention via platform engagement. Essay 2 analyzes how driver–customer familiarity in crowdsourced delivery acts as a relational resource, improving delivery performance and suggesting pathways for more relationship-sensitive dispatch algorithms. Essay 3 takes a novel methodological outlook, integrating netnographic insights with NLP-based analysis, to understand crowdsourced delivery driver challenges and develop a configurational specification for a microworld simulation prototype. Together, these essays advance a unified argument: platforms are not neutral marketplaces but active orchestrators of crowd-based resources, with far-reaching implications for efficiency, equity, and resilience in supply chain systems and operations
Petrogenesis and Isotope Geochemistry of Nepheline Syenites from the Arkansas Alkaline Province, SE USA
No full textSilica-undersaturated nepheline syenites are rare, and a great example of outcrops within the Arkansas Alkaline Province (AAP) in central Arkansas, near Little Rock. It has been thought that the AAP formed as part of the Bermuda hotspot. Previous studies have performed geochronological analyses determining an age between 88 – 106 Ma, but the magmatic processes involved and the origin of these rocks remain unclear.
This study reports new Nd-Sr-Pb-Hf isotopic compositions plus major and trace element data for nepheline syenites from Arkansas. These nepheline syenites are characterized by depleted Nd and Hf isotopic compositions, radiogenic Pb isotopes (206Pb/204Pb=19.5), and high Na2O (>6%) and K2O (>6%) contents. The high 206Pb/204Pb ratios that were measured for these samples argue against subduction processes and significant upper or lower contributions. Sr and Pb isotope values, as well as depleted Nd-Hf isotopic compositions, indicate that there was a mixing of both enriched mantle (EM2) and high 238U/204Pb (HIMU) mantle components. The trace element data proved to be very useful in determining the tectonic setting of these samples, by first clearly indicating that these samples match the characteristics of a within-plate setting. Positive Nb and Ta anomalies argue against subduction processes or significant involvements of upper crustal materials, while the positive Nb-kick characterize ocean island basalts that form due to mantle plumes. Based on the data, and the ages determined by previous studies this study believes that these nepheline syenites were most likely a part of the Bermuda hot spot in Arkansas
Food Safety Implications of Preharvest Water Use in Hydroponic and Soil-Based Production of Fresh Produce
Get PDFFresh produce is frequently associated with foodborne outbreaks and recalls, as these products are highly susceptible to microbial contamination from the environment and poor handling practices. At the preharvest level, numerous contamination routes may compromise the safety of fresh produce, including agricultural water. Agricultural water is a well-documented route of preharvest contamination, and outbreaks involving pathogens such as Escherichia coli and Salmonella have been linked to contaminated irrigation water. To prevent food safety issues associated with fresh produce, the Food and Drug Administration(FDA) established the Produce Safety Rule (PSR) in 2016. Following the implementation of the PSR, significant research efforts have been made nationwide to characterize risks associated with agricultural water. However, most studies have focused on large fresh produce-growing regions (e.g., the Southwest and Northeast U.S.), leaving critical knowledge gaps in understudied regions, such as the Southeastern U.S., particularly in Alabama.
In Alabama, more than 2,000 small farms operate with limited regulatory oversight due to exemptions under the PSR, which could represent food safety risks to consumers, especially given the state’s historical challenges with surface and groundwater quality. In contrast, Georgia (particularly the southwestern region) has a larger commercial produce industry and has received greater research attention. To address regional disparities in data and oversight, this dissertation presents findings from two longitudinal studies evaluating the prevalence and diversity of two foodborne pathogens (Salmonella and pathogenic E. coli) in PSR-covered farms in Georgia and exempt farms in Alabama. Machine learning models (e.g., random forest) were developed to predict pathogen prevalence. Overall, findings from the two studies indicate that pathogen presence is not strictly associated with farm size or PSR compliance status. The frequent detection of enteric pathogens in both Georgia and Alabama highlights the influence of local agricultural practices on water quality.
In addition, to address knowledge gaps regarding food safety needs among produce growers in Alabama, a two-phase exploratory study was conducted. Phase 1 involved a needs assessment survey, and phase 2 focused on developing an extension program centered on technical support for agricultural water quality and risk mitigation. Findings from phase 1 suggest that specialty crop growers in Alabama are interested in learning about food safety plan writing, cleaning and sanitizing, and postharvest handling. Based on the results from phase 2, produce growers benefited from the extension program, as prior to this, only 40% had tested their water sources. Moreover, it was identified that fecal indicator bacteria were prevalent in surface and groundwater sources.
In parallel, this dissertation examines the behavior of Salmonella in hydroponic production systems, prompted by recent outbreaks and recalls associated with hydroponically grown produce. While most existing research has focused on lettuce, this study evaluates the survival of Salmonella in herbs (basil, cilantro, and arugula) grown under Nutrient Film Technique (NFT) systems. Results show that Salmonella can survive in nutrient solutions for up to 35 days, and sporadic contamination in the system can lead to the presence of the pathogen in edible tissue. The insights this hydroponic study contributes to the growing body of knowledge regarding Salmonella in Controlled Environment Agriculture.
Collectively, this research advances our understanding of the implications of preharvest agricultural water quality in diverse farming contexts. Here, we provided practical information to improve the microbial safety of fresh produce grown in the Southeastern U.S. Lastly, this information will guide Alabama food safety educators in establishing produce safety programming, prioritizing the current needs
Rollover-Aware Data-Driven Lateral Control for Tractor-Trailer Evasive Maneuvers
No full textIn this dissertation, a new rollover-aware evasive maneuver algorithm is developed.
Specifically, a stochastic nonlinear model predictive controller is created, which can successfully
perform an emergency maneuver in the desired distance while also satisfying the rollover
prevention constraints. Many active safety systems for tractor-trailer rollover prevention are
reactive systems in the sense that they wait for the vehicle to exceed certain thresholds before
applying a corrective measure to ensure safety. This work aims to develop an evasive
maneuvering algorithm that explicitly accounts for safety thresholds satisfying both obstacle
avoidance and rollover avoidance objectives. Experimental data from an emergency braking
maneuver is used to set expected performance standards for an evasive maneuver algorithm.
A parameter-free controller is developed that can operate even in the presence of system
delays. Both modeling and estimator uncertainty are considered so that intelligent methods
of robust constraint enforcement can be implemented.
Typically, parametric models are used for the development of a tractor-trailer lateral
controller; however, due to the large number of parameters that can change when trailers are
exchanged and the associated difficulty of estimating the new parameters, a parameter-free
model is developed. The parameter-free model, called the ultra-local model, utilizes only
measurements of the controlled state to form an accurate local model of the dynamic system.
This ultra-local model is developed in such a way that even if time delays exist in the system
or in the measurements themselves, stable estimation of the ultra-local model can still occur,
which is a novel development. The single tunable parameter in the ultra-local model is then
parameterized as a function of the vehicle velocity to allow for updating during an evasive
maneuver when estimating the parameter may not be possible.
The ultra-local model is tested within the context of a nonlinear model predictive controller.
While this implementation successfully performed obstacle avoidance, it was unable
to enforce the acceleration constraints, which enforce rollover prevention, with any regularity.
To fix this, the sources of uncertainty in the system were analyzed, and the Pontryagin
difference, along with chance-constraints, were utilized to generate a robust constraint set.
These robust constraints were then implemented in a Stochastic Nonlinear Model Predictive
Control (SNMPC) formulation.
Results from the SNMPC simulations demonstrate that both obstacle avoidance and
rollover prevention are feasible within the context of an evasive maneuver scenario. When
loaded to 29483kg and driven at 22.3m/s the tractor-trailer was able to avoid an obstacle
50m away, which is the distance it takes a vehicle with these parameters to stop with the aid
of ABS. Furthermore, even with the influence of sensor noise, the rollover prevention acceleration
constraint was satisfied more than 99% of the time, which is the specified threshold
set by the chance-constraint. This proves the feasibility of the developed methods for use as
a new form of rollover-aware evasive maneuver algorithm
“You Can’t Beat a Cover Crop:” Assessing the Sustainability Outcomes of a Cover Crop Incentive Program in Alabama
No full textConservation agriculture approaches and technologies (e.g., cover crops, variable-rate irrigation) can increase resource use efficiencies and help make intensified agricultural systems more sustainable. Entities across sectors are investing significant funding toward increasing adoption of these methods, and the “Future of Farming” (FF) project is an example of one such initiative. The FF project involves farmers, researchers, and other agricultural professionals in research on conservation agriculture, and it includes a cover crop incentive program (FF-CCIP) which was used as a case study for this project. Literature used to inform this study covered sustainability, technology adoption, cover crops, incentive programs, sustainable intensification, and the agricultural treadmill. Data came from interviews with farmers (n=23) enrolled in the FF- CCIP. Analyses identified trends in farmers’ motivations for enrolling; perceptions of incentive programs, cover crops, and production meetings; learning within their social networks; and values and objectives regarding stewardship. These trends were then compared with institutional objectives to understand areas of improvement for future incentive programs. Trends were also compared with research on sustainable intensification (SI), an agricultural approach typically used in international and Global South contexts. Findings suggest that expanded outreach efforts could lead to more effective incentive programs. Findings also suggest that more research on conservation agriculture technologies is needed to assess the potential negative financial outcomes on farmers who adopt these tools and practices. Further, findings demonstrate alignment between conventional agriculture in the US and SI production: economic outcomes tend to be prioritized over environmental and social outcomes in both systems, and the continuous need for technology generated by ever-increasing demands for market efficiencies contributes to this unbalanced prioritization of outcomes