Digital Commons Network^™

Budget Recommendations Fy2025-26, Tennessee. Commission On Children And Youth.

Annual Report

No abstract provided.

Shall I: Do The Motivations For Breakup Sex Differ Across Different Scenarios?, T. Joel Wade, Zoe Macuto

Faculty Journal Articles

This research investigated endorsement of the 4 motivators (relationship maintenance, ambivalence, hedonism, miscellaneous) for engaging in breakup sex across three relationship breakup scenarios, i.e., a breakup occurred due to: general reasons, infidelity, and being in a long distance relationship using an online questionnaire with a primarily White, primarily heterosexual sample (n = 304, Mage = 20.67). Results indicated that women are more likely than men to engage in breakup sex for relationship maintenance reasons when the breakup is due to general reasons, and for a long distance breakup scenario, non-heterosexuals engage in breakup sex for relationship maintenance reasons, and overall …

Deepgridmclp: A Deep Reinforcement Learning Approach To Solve The Maximal Covering Location Problem With Facilities In Continuous Regions, Yang Zhong

CGU Theses & Dissertations

The Maximal Covering Location Problem (MCLP) is a classic Combinatorial Optimization Problem (COP) in spatial optimization and operations research, predominatnly used for strategic public facility placement. The model’s objective is to determine the optimal locations for a fixed number of facilities in order to serve the largest possible demands within a desired service distance. In its original form, the MCLP model is formulated with discrete facility candidate points. However, in many practical situations, the facilities can be positioned anywhere in a continuous region. For example, in environmental planning or wireless network design, the prospective facility placements may be established in …

Optimization Of A Vertical-Axis Wind Turbine Airfoils Using Machine Learning, Numerical And Experimental Methodologies, Leovigildo Torres Angel

CGU Theses & Dissertations

This study aimed to enhance the aerodynamic performance of a Vertical-Axis Wind Turbine (VAWT) airfoil through a multidisciplinary approach that combines Machine Learning (ML), Computational Fluid Dynamics (CFD), and experimental validation. The focus was on enhancing the lift-to-drag coefficients ratio (퐶 푙 /퐶 퐷 ), particularly at higher Angles of Attack (AoA ≥ 20°), a critical operational regime for VAWTs. A baseline airfoil of 12-inch chord length and 10-inch wingspan was analyzed using ANSYS Fluent across a range of AoA (0°–90°) at a constant freestream velocity of 10 m/s (Re ≈ 2.0 × 10 5 ). This served as a …

Women’S Leader Development: Examining The Impact Of Leadership Grants, Bias Interrupters, Stereotype Threat, And Purpose On Leader Identity, Emily L. Chan

CGU Theses & Dissertations

Leader identity is a proximal outcome of individual leader development processes, particularly important for women leaders who may face systematic denials of their leadership. Understanding the mechanisms that bolster and hinder leader identity is crucial for emerging women leaders. In two simulation experiments, I proposed and tested strategies for mitigating the negative impact of leadership denials and stereotype threat on an individual’s leader identity. In the first experiment, I hypothesized that perceptions of granted leadership claims through written bias interrupter statements (i.e., “women are encouraged to apply”) buffered the negative relationship between leadership denials (ads without the statement “women are …

He Lāhui Ano MaikaʻI Keia: Japanese Immigration And The Intersections Of Ethnicity And Sovereignty In Kalakaua's HawaiʻI, Neal Melela'i Cooper

CGU Theses & Dissertations

The late 19th century was a tumultuous period in Hawaiian history. Characterized by the interrelated questions of royal succession, political sovereignty, and labor immigration, the period of King Kalakaua's reign was the culmination of a building social crisis that had begun the moment American settler-colonials arrived on the shores of the archipelago. Throughout this time, King Kalakaua leveraged his acute political mind to build a coalition of nationalist Hawaiians in order to restore native traditions and seek out allies abroad in the hopes of resisting America's military and economic might. Using the labor supply as a wedge, Kalakaua was able …

Declarative Design For Spatial Analysis Models, Yassine Elouri

CGU Theses & Dissertations

Geographic Information Systems (GIS) have become indispensable tools in addressing complex spatial challenges across diverse domains, including urban planning, environmental conservation, and climate change. However, the technical expertise required to use GIS effectively, particularly proficiency in general-purpose programming languages (GPLs), remains a significant barrier to broader adoption. Domain-Specific Languages (DSLs) have proven to lower this barrier by offering tailored abstractions that simplify problem-solving in specific domains. Despite their potential, the GIS domain lacks a formal DSL framework that bridges the gap between the design of spatial analysis models and their practical implementation. This research addresses this gap by proposing Gaia, …

Market Implied Risk-Free Rates: An Analysis Of The Put-Call Parity Implied Rate, Silviu Velovici

CGU Theses & Dissertations

This study investigates the interest rate implied by put-call parity as an alternative, market-based proxy for the risk-free rate. Studying the implied risk-free rate from option prices is important because it provides insights into how market participants collectively perceive short-term financing conditions, independent of official Treasury-Bill yields. Since Treasury securities and the LIBOR are conventionally used as proxies for the risk-free rate, any persistent discrepancy between the put-call parity implied rate and the Treasury-Bill rate, or the put-call parity implied spread, can be interpreted as a signal of market frictions, investor behavior anomalies, sentiment-driven pricing dynamics, or information asymmetries.

By …

Gene Expression Changes In Human Cerebral Arteries Following Hemoglobin Exposure: Implications For Vascular Responses In Sah, Chathathayil M Shafeeque, Arif O Harmanci, Sithara Thomas, Ari C Dienel, Devin W Mcbride, Kumar T Peeyush, Spiros L Blackburn

Faculty, Staff and Student Publications

Subarachnoid hemorrhage (SAH), characterized by the presence of hemoglobin (Hb) in the subarachnoid space, significantly impacts cerebral vessels, leading to various pathological outcomes. The toxicity of cell-free Hb released from erythrocytes and its metabolites after SAH causes vasoconstriction and neuronal damage, and correlates with delayed ischemic neurological deficits (DIND). While animal models have provided substantial and invaluable data in the research of aneurysmal SAH, the specific effects of subarachnoid blood on cerebral arteries remain greatly understudied. Here, we describe the changes in the genetic profile of human cerebral arteries exposed to free Hb for 48 h. We performed an ex …

Hslic Annual Report Fy2024-25, University Of New Mexico Health Sciences Library And Informatics Center

HSLIC Annual Reports

Annual report for FY 2024-2025.

Cognitive Biases As Interrupters In Evidence Based Practice Decision-Making: Dataset, Jonathan Eldredge, Deirdre Hill

Publications

No abstract provided.

Religion-Justified Childhood Maltreatment, Maladjustment, And Child Abuse Potential, Hannah Doctor

Theses and Dissertations

Childhood abuse is a widely studied construct that has been shown to be related to higher levels of maladjustment and physical discipline and abuse perpetration in adulthood. Religion has been studied in relation to traumatic experiences and shown to be a factor that may help mitigate subsequent maladjustment. The idea religion may have been used to justify abusive acts has not been as widely studied but may complicate the picture of religion being a protective or resiliency factor. The present study sought to explore the relationships between religion, childhood abuse, maladjustment, and parenting behaviors. It was hypothesized that religion being …

The Effects Of Chronic Sleep Deprivation On Visuomotor Performance Using Electroencephalographic Measurement, Jaxon Duane Erie

Theses and Dissertations

The present study investigated the impact of acute and chronic sleep deprivation on visuomotor performance using both electroencephalographic (EEG) and behavioral measures (Senaptec Sensory Station) in a sample of 43 college students aged 18 to 27. Participants were assigned to low or high sleep conditions based on Chronic Sleep Reduction Questionnaire (CSRQ) scores, while acute sleep deprivation was assessed via the Karolinska Sleepiness Scale (KSS). Heart rate variability (HRV) was recorded to support condition placement, but comparisons revealed no significant differences between groups. No significant differences were found in visuomotor control or eye-quickness assessments. However, visual clarity was significantly better …

Rethinking Pilot Retention In The United States: An Analysis Of Key Factors, Michael James Hickey

Theses and Dissertations

This thesis examined pilot retention challenges in U.S. regional and low-cost carriers (LCCs), focusing on nonfinancial incentives such as quality of life, career stability, and work-life balance, which may have a greater influence on retention than traditional financial incentives. This quantitative, survey-based approach assesses how pilots rank the factors that influence their retention. Using a sample of U.S.-based pilots, the study examines six key areas adapted from a European pilot retention framework. Statistical analyses, including the Friedman test, the Mann-Whitney U test, and the Kruskal-Wallis test, identified correlations between demographic variables and retention priorities. The inherent financial constraints of regional …

Using Machine Learning To Investigate Weather Impacts On Crop Yield For Probabilistic, Climate-Informed Predictive Crop Breeding, Levi Newell

Theses and Dissertations

As the world’s population continues to grow, the importance of food security willonly continue to increase, with some estimates requiring a global increase in food production between 59 and 98% by 2050. The agriculture industry is also a crucial economic driver, with the industry supporting 20% of the state of North Dakota’s workforce, and with a total valuation of $41.3 billion. The economic importance of this industry and the challenges of future growth prompt a need for data driven decision making into the future, particularly with predictive crop breeding. This is the method by which crops are developed that are …

The Effect Of Salaciousness, Consistency, And Timing Of Disclosure On Alibi Believability In The Eyes Of A Jury, Jasper Allen Schmidtwood

Theses and Dissertations

Past research indicates a prevalent distrust of alibi evidence, coined by Olson and Wells (2004) as the alibi skepticism hypothesis. This inherent distrust prompts inquiries into the factors that enhance or undermine the credibility of alibi evidence in a trial. Utilizing attribution theory (Allison et al., 2012; Weiner, 2010), this study investigates the elements contributing to the believability of alibi statements, specifically the impact of alibi consistency, timing of disclosure, and the salaciousness of the alibi statement on jurors' perceptions of the defendant's character. Participants were randomly assigned to one of twelve conditions and read a mock trial summary that …

Walk This Way: Effects Of Eyewitness Identification Factors And The Featural Justification Effect On Mock-Juror Decision-Making, Lauren Nicole Stornelli

Theses and Dissertations

Surveillance cameras serve many purposes, including security, monitoring, and investigating crimes. The presence of surveillance cameras allows for a new form of witness: a non-eyewitness, where crimes are captured by surveillance cameras without a physical witness present (Pezdek & Lerer, 2023a). As such, police officers are acting as eyewitnesses by identifying the perpetrator from the surveillance evidence and testifying about their identification at trial (Rumschik et al., 2020). Previous studies have examined participants’ ability to accurately match previously viewed faces with faces on surveillance evidence, with results suggesting accuracy rates around chance (e.g., Bruce et al., 2001; White et al., …

Superhypergraph Neural Networks And Plithogenic Graph Neural Networks: Theoretical Foundations, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Hypergraphs extend traditional graphs by allowing edges to connect multiple nodes, while superhypergraphs further generalize this concept to represent even more complex relationships. Neural networks, inspired by biological systems, are widely used for tasks such as pattern recognition, data classification, and prediction. Graph Neural Networks (GNNs), a well-established framework, have recently been extended to Hypergraph Neural Networks (HGNNs), with their properties and applications being actively studied. The Plithogenic Graph framework enhances graph representations by integrating multi-valued attributes, as well as membership and contradiction functions, enabling the detailed modeling of complex relationships. In the context of handling uncertainty, concepts such as …

Reconsideration Of Neutrosophic Social Science And Neutrosophic Phenomenology With Non-Classical Logic, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Body-Mind-Soul-Spirit Fluidity is a concept rooted in psychology and phenomenology, offering significant insights into human decision-making and well-being. Similarly, in social analysis and social sciences, frameworks such as PDCA, DMAIC, SWOT, and OODA have been established to enable structured evaluation and effective p roblem-solving. Furthermore, in phenomenology and social sciences, various logical systems have been developed to address specific objectives and practical applications. This paper extends these concepts using the Neutrosophic theory, revisiting their mathematical definitions and exploring their properties. The Neutrosophic Set, an extension of the Fuzzy Set, is a highly flexible framework that has been widely studied in …

Cvitlnn: A Hybrid Approach Based On Vision Transformer And Liquid Neural Network For Covid-19 Detection, Muhammad Waqaq, Florentin Smarandache, Muhammad Yasir, Farrukh Arslan, Anum Ali

Branch Mathematics and Statistics Faculty and Staff Publications

The COVID-19 pandemic has underscored the need for accurate and rapid diagnostic tools to assist clinical decision-making. Conventional deep learning models for COVID-19 detection in Chest X-Ray (CXR) images face challenges in poor generalization across imaging conditions and high computational demands. To address these issues, this study proposes CviTLNN, a novel hybrid model combining Vision Transformers (ViTs) and Liquid Neural Networks (LNNs) to improve feature extraction and classification. Specifically, CviTLNN employs a ViT with 24 transformer encoder blocks for efficient extraction of spatial features. The self-attention mechanism of ViTs effectively captures global and local dependencies in CXR images. Furthermore, …

Facilitated Group Care For Maternal And Child Health Model Fidelity: A Scoping Review, Ashley Gresh, Phoebe Parker, Anne Batchelder, Jalana Lazar, Christina X. Marea, Camilla Bjelland, Rohan D. Jeremiah, Giovanna Cristina Machado-Kayzuka, Hayden Geibel, Dhruvi R. Patel, Esnath Kapito, Kathleen F. Norr, Crystal L. Patil

Department of Pediatrics Faculty Publications

Group care is a transformative model of prenatal, postnatal, and well-child care. The Centering-based group care model has three core components: health care, interactive learning, and community building. It has been implemented in 33 countries with associated improved maternal and child health outcomes. Maintaining fidelity to the model is essential for its effectiveness. However, to date no standardised measure of fidelity to the group care model exists. This review aimed to explore how fidelity is measured in group care and identify common themes to understand what is essential to maintain fidelity. We used the scoping review framework by Arksey & …

Physics-Informed Deep Learning With Kalman Filter Mixture For Traffic State Prediction, Niharika Deshpande, Hyoshin (John) Park

Engineering Management & Systems Engineering Faculty Publications

Accurate traffic forecasting is crucial for understanding and managing congestion for efficient transportation planning. However, conventional approaches often neglect epistemic uncertainty, which arises from incomplete knowledge across different spatiotemporal scales. This study addresses this challenge by introducing a novel methodology to establish dynamic spatiotemporal correlations that captures the unobserved heterogeneity in travel time through distinct peaks in probability density functions, guided by physics-based principles. We propose an innovative approach to modifying both prediction and correction steps of the Kalman Filter (KF) algorithm by leveraging established spatiotemporal correlations. Central to our approach is the development of a novel deep learning model …

Patterns Of Exclusive, Dual And Poly Tobacco Products Use Among Cancer Survivors In The United States, Ateeqa Ijaz, Miranda E. Gehris, Paul T. Harrell, Aditya Chakraborty, Rime Jebai, Wei Li, Olatokunbo Osibogun, Seyedeh Yasaman Alemohammad, Ziyad Ben Taleb, Ebbie Kalan

Department of Pediatrics Faculty Publications

Purpose

Identifying tobacco products use (TPU) patterns among cancer survivors (CSs) is critical to optimize survivorship care. This study examines exclusive cigarette/e-cigarette, dual (two tobacco-products) and poly (≥ 3 tobacco-products) use among CSs (vs. no cancer history) and its sub-types: smoking-related-cancers (SRCs) vs. non-smoking-related cancers (NSRCs) while also exploring socio-demographic factors.

Methods

The study analyzed 86,551 adults from the 2021–2023 National Health Interview Survey, including 10,846 (9.7%) CSs. Participants were categorized and analyzed based on their CSs status and TPU patterns. Weighted logistic regression models assessed the relationship between TPU and CSs status while adjusting for socio-demographic characteristics.

Results

CSs …

Comprehensive Benchmarking Of Several Machine Learning And Bayesian Models For Early-Stage Diabetes Risk Prediction: A Large-Scale Comparative Study, Md. Iqbal Hossain, Najila Alam Porno

Mathematics & Statistics Faculty Publications

Diabetes remains a critical global health challenge, with early detection is crucial for effective management. This study presents a comprehensive benchmarking analysis of 14 diverse machine learning and Bayesian models for early-stage diabetes risk prediction using clinical data [2] from Sylhet, Bangladesh. This research evaluated traditional methods (Logistic Regression, Decision Trees), ensemble techniques (Random Forest, XGBoost, LightGBM), Bayesian approaches (BART, Bayesian Logistic Regression), and advanced neural architectures (Deep Belief Networks) using both 70-30 train-test splits and 10-fold cross-validation. The results demonstrate that ensemble methods consistently outperformed other approaches, with Random Forest(RF) achieving the highest cross-validated AUC (0.9951) and accuracy (0.9699). …

A Comparative Analysis Of Preprocessing Filters For Deep Learning-Based Equipment Power Efficiency Classification And Prediction Models, Sang-Ha Sung, Chang-Sung Seo, Michael Pokojovy, Sangjin Kim

Mathematics & Statistics Faculty Publications

The quality of input data is critical to the performance of time-series classification models, particularly in the domain for industrial sensor data where noise and anomalies are frequent. This study investigates how various filtering-based preprocessing techniques impact the accuracy and robustness of a Transformer model that predicts power efficiency states (Normal, Caution, Warning) from minute-level IIoT sensor data. We evaluated five techniques: a baseline, Simple Moving Average, Median filter, Hampel filter, and Kalman filter. For each technique, we conducted systematic experiments across time windows (360 and 720 min) that reflect real-world industrial inspection cycles, along with five prediction offsets (up …

A Decision-Space Model Explains Context-Specific Decision Making, Dirk W. Beck, Cory N. Heaton, Luis D. Davila, Lara I. Rakocevic, Sabrina M. Drammis, Danil Tyulmankov, Atanu Giri, Shreeya Umashankar Beck, Qingyang Zhang, Michael Pokojovy, Kenichiro Negishi, Alexis A. Salcido, Neftali F. Reyes, Andrea Y. Macias, Serina A. Batson, Paulina Vara, Raquel J. Ibáñez Alcalá, Safa B. Hossain, Graham L. Waller, Laura E. O'Dell, Travis M. Moschak, Ki A. Goosens, Alexander Friedman

Mathematics & Statistics Faculty Publications

Optimal decision-making requires consideration of internal and external contexts. Biased decision-making is a transdiagnostic symptom of neuropsychiatric disorders. We created a computational model demonstrating how the striosome compartment of the striatum constructs a context-dependent mathematical space for decision-making computations, and how the matrix compartment uses this space to define action value. The model explains multiple experimental results and unifies other theories like reward prediction error, roles of the direct versus indirect pathways, and roles of the striosome versus matrix, under one framework. We also found, through new analyses, that striosome and matrix neurons increase their synchrony during difficult tasks, caused …

Norfolk Core Redevelopments And Population Disruption Dispersal, Sumner Darling

Institute for the Humanities Master's Papers, Projects, and Capstones

This project is an analysis of the racial impacts of the redevelopment of the downtown area of Norfolk, Virginia in the period of 1939-1959. The overall goal is to understand the ethnic and racial impacts of redevelopment and how populations were treated differently during the two styles of redevelopment that were employed in the city. The existing research on this topic tends to focus on the segregation of the education system in the city over the community population segregation. This makes it difficult to find sources that show the impacts of other factors like redevelopment of minority communities. Through research …

Impacts Of Tick Parasitism On The Rodent Gut Microbiome, Robert J. Brinkerhoff, Joshua Pandian, Meghan Leber, Isabella D. Hauser, Holly D. Gaff

Biological Sciences Faculty Publications

Host microbiota may impact disease vector behavior and pathogen transmission, but little is known about associations between ectoparasites and microbial communities in wildlife reservoir species. We used Illumina metagenomic sequencing to explore the impacts of tick parasitism on the rodent fecal microbiome in both a field and laboratory setting. We found that tick parasitism on wild hosts was associated with variation in the fecal microbiota of both the white-footed deermouse, Peromyscus leucopus, and the southern cotton rat, Sigmodon hispidus. In a lab experiment, we detected significant changes to the fecal microbiome after experimental exposure to immature ticks in …

Mobula, Bioinspiration, Filter Feeding, Form And Function, J. B. Teeple, S. R. Kahane-Rapport, K. E. Cohen, L. Hamann, J. A. Strother, E. W.M. Paig-Tran

Biological Sciences Faculty Publications

Mobulas (manta and devil rays) are large-scale ram filter feeders that separate planktonic food particles from large volumes of water with minimal clogging. This contrasts with most human-made filters that can suffer from problematic clogging requiring additional mechanisms for clearing blocked surfaces and maintaining performance. Prior studies have shown that mobulas employ a unique mechanism referred to as ricochet separation to filter feed, whereby captive vortices in filter pores cause particles to bounce off the filter surfaces and away from the filter pores. This mechanism enables the filtration of particles smaller than the pore size and reduced clogging. However, few …

Multi-Locas Gwas Mapping And Candidate Gene Analysis Of Anticancer Peptide Lunasin In Soybean (Glycine Max L. Merr), Rikki Locklear, Jennifer Kusumah, Layla Rashad, Felicia Lugaro, Sonia Viera, Nathan Kipyego, Faith Kipkosgei, Daisy Jerop, Shirley Jacquet, Mythy Addelmajid Kassem, Jiazheng Yuan, Elvira De Mejia, Rouf Mian

Biological Sciences Faculty Publications

Soybean (Glycine max) peptide lunasin exhibits significant cancer-preventive, antioxidant, and hypocholesterolemic effects. This study aimed to identify quantitative trait nucleotides (QTNs) associated with lunasin content and to annotate the candidate genes in the soybean genome. The mapping panel of 144 accessions was gathered from the USDA Soybean Germplasm Collection, encompassing diverse geographical origins and genetic backgrounds, and was genotyped using SoySNP50K iSelect Beadchips. The lunasin content in soybean seeds was measured using the enzyme-linked immunosorbent assay (ELISA) method, with lipid-adjusted soybean flour prepared from seeds obtained from the Germplasm Resource Information Network (GRIN) of USDA-ARS in 2003 and …