Digital Commons Network^™

Effects Of Unilateral Lower Limb Suspension On Quadriceps’ Structure And Contractile Function, Eve N. Elmore

Theses and Dissertations--Kinesiology and Health Promotion

BACKGROUND: Muscle unloading such as bed rest or space flight decreases strength and cross-sectional area concomitant with a slow-to-fast fiber type shift, of anti-gravitational muscles such as the quadriceps. Diffusion tensor imaging (DTI) quantifies tissue anisotropic properties such as Fractional Anisotropy, Mean Diffusivity, Axial Diffusivity, and Radial Diffusivity, as well as muscle volume, fascicle length, and physiological cross-sectional area, and has recently been adapted to assess skeletal muscle structure. In skeletal muscle, anisotropic properties correlate with muscle fiber type and contractile function and may be responsive to unloading-induced atrophy.

PURPOSE: To assess the changes in quadriceps’ size, anisotropy, and contractile …

Influence Of Deception Of Task Duration On The Sex-Specific Physiological, Neuromuscular, And Affective Responses To Rpe-Clamp Cycle Ergometry, Pasquale Succi

Theses and Dissertations--Kinesiology and Health Promotion

Several theories exist to explain the interaction of sensory afferent feedback and efferent feedforward signals on the generation of a rating of perceived exertion (RPE) which influence endurance exercise pacing and performance. Within these theories, exists the premise that the expected duration of exercise plays a role within the generation of an individual’s RPE and their endurance performance. Previous work has demonstrated equivocal findings of this influence, while other research has suggested potential differences between males and females. However, an RPE-clamp model, where the external workload is modulated to maintain a constant perceptual intensity, has not previously been used to …

An Investigation Of Body Image And Eating Behaviors In Former Ncaa Heptathletes, Claire Bailey

Theses and Dissertations--Kinesiology and Health Promotion

Research consistently supports associations between body image dissatisfaction and disordered eating pathologies in collegiate athletes (e.g., Reel & Voelker, 2012; Sundgot-Borgen, 1994). More specifically, female NCAA athletes report feeling torn between peak performance body composition and body fat levels fitting ideal feminine standards (Beckner & Record, 2016; Carson et al., 2020). Examining track and field, most event groups hold a lean-promoting perspective. However, heptathletes warrant further investigation due to the multifaceted and contradictory nature of events. Specifically, heptathletes encounter complex pressures training for a wide range of physical demands, which can create confusion in expected body types (Heazlewood et al., …

Understanding Intention And Behavior Of Practicing Yoga Through The Lens Of Theory Of Planned Behavior Specifically In Rural Communities; A Qualitative Study, Shelley Meyer

Theses and Dissertations--Kinesiology and Health Promotion

While there are known health benefits for participating in yoga, little has been studied on the intention and behavior for why individuals practice yoga especially through a theoretical lens and intense qualitative thematic analysis. Targeting the rural community considers other extenuating circumstances experienced by rural residents that can impact yoga participation in rural areas. Interviews were used to gain insight into a holistic viewpoint with the rich data bringing clarity to an individual’s thought process (of intention) to incorporate yoga (behavior) in their daily life. Utilizing the Theory of Planned Behavior as the theoretical framework for developing interview questions allowed …

The Effect Of Visual Signaling On Psychomotor Learning: An Explanatory Mixed Methods Study In Physical Therapy Education, Julie Pfeiffer

Theses and Dissertations--Education Sciences

The signaling principle states that people learn better when cues are used to highlight important information in a multimedia presentation. Prior research has shown that visual signaling improves learning by directing the learner’s attention to the relevant information of the instruction, improving the learner’s ability to select essential words and pictures. While the visual signaling principle has been applied to learning in the cognitive domain, the effect of visual signaling on learning within the psychomotor domain is limited. The purpose of this study is to investigate the effect of the signaling principle on learning psychomotor skills from multimedia instruction, specifically …

Student Loan Debt: Exploring The Economic Influences On Federal Student Loan Default For Students That Attended Public, Two-Year Institutions, Brian Perry

Theses and Dissertations--Educational Policy Studies and Evaluation

Over the past 30 years, a shift occurred in higher education that saw more of the burden for paying for postsecondary education placed on students. Combined with rising tuition and fees, this has led students to take on increasing amounts of student debt. Despite the historic rise in student loans, surprisingly little attention has focused on those students who default on their student loans. Additionally, the academic literature on student loans has predominately focused on traditional students at four-year institutions, despite the fact that nearly half of all undergraduates attend public two-year institutions. Finally, those studies that include economic factors …

Data In Higher Education: Exploring The Collection, Interpretation, And Utilization Of Information For Institutional Decision-Making Around Diversity, Equity, And Inclusion, Terri Berkley

Theses and Dissertations--Educational Policy Studies and Evaluation

This study investigates how higher education institutions in the Appalachian region collect, assess, and utilize data to inform diversity, equity, and inclusion (DEI) initiatives and broader institutional transformations. It focuses on understanding how data influences policy reforms, operational practices, and cultural shifts within these institutions. Through a mixed-methods approach—comprising surveys, semi-structured interviews, and focus groups—the study examines the perspectives of key stakeholders, including DEI administrators, non-DEI administrators, and executive-level leaders.

The research identifies how institutional roles and positionality shape stakeholders' engagement with data and their ability to implement DEI-informed strategies. Key findings highlight discrepancies in data access, interpretation, and application, …

Increasing Expectations For Entry: Analyzing Changes In Labor Market Entry-Level Education Requirements Over Time With Potential Implications For Credential Or Degree Inflation And Returns-To-Education, William Nicholas Grinstead

Theses and Dissertations--Educational Policy Studies and Evaluation

The dissertation asks the following question: Have occupations increased academic degree requirements over time?

The literature review provides background on the origin and criticisms of the concept of a “knowledge economy.” It addresses economic “signaling theory” and sociologic “credentialism.”

The methodology relies on a trend analysis using the Bureau of Labor Statistics (BLS) Occupational Outlook Handbook and the occupations’ Standard Occupational Classification (SOC) system and its predecessor the Dictionary of Occupational Titles (DOT). In order to address whether occupations have increased academic degree requirements over time, this dissertation will compare entry-level education requirements for BLS SOC occupations that today are …

Black Girl Wisdom: A Black Feminist Analysis Of Success Strategies Of Professional African American Women At Predominately White Higher Education Institutions, Teasia Jordan

Theses and Dissertations--Educational Policy Studies and Evaluation

This phenomenological study examines the success strategies employed by professional African American women (AAW) at predominately white higher education institutions (PWIs). Grounded in Black Feminist Thought (BFT), the “Outsider Within” framework (Collins, 1986), and the concept of “failed citizenship” (Banks, 2017), it explores how AAW navigate and redefine success within environments shaped by exclusionary white patriarchal norms. Through interviews with ten co-laborers, two themes emerged: liberation from unsupportive environments and negotiation strategies to define success.

Findings reveal that AAW’s success strategies center on identity, self-awareness, and rejecting institutional oppression. Co-laborers articulated their liberation by naming the environment as oppressed, fostering …

Effect Of On-Duty Resistance Training On Neuromuscular Function In Structural Firefighters, Jamal L. Thruston

Theses and Dissertations--Kinesiology and Health Promotion

Participation in on-duty exercise is critical to enhance firefighter safety and readiness. However, these sessions are often interrupted with emergency responses and require firefighters to work in a fatigued state that may increase injury risk. Therefore, the purpose of this study was to assess the impact of on-duty resistance training on neuromuscular function. A sample of 18 firefighters (Age: 38.8±8.0yr; Body fat: 24.9±7.0%) completed 3 testing sessions, separated by at least 72 hr to compare the effects of circuit (CT) versus heavy resistance training (HRT) fatigue on neuromuscular function. During Session 1, anthropometrics and familiarization trials of balance and neuromuscular …

Examining High School Mathematics Teachers' Research-Based Instructional Practices And Their Relationship To Students' Learning Outcomes: A Convergent Parallel Mixed-Method Study, Isiaka Busari

Theses and Dissertations--Science, Technology, Engineering, and Mathematics (STEM) Education

This convergent parallel mixed-methods study examines the relationship between high school mathematics teachers' research-based instructional practices and students' learning outcomes in Algebra 1 classrooms at a high school in a central region of a Southern U.S. State. The research addresses improving mathematics proficiency in the United States, where national performance remains below average. Guided by psychological and social constructivism, the study involved three Algebra 1 teachers and 171 students. Data were collected through classroom observations using the Mathematics Classroom Observation Protocol for Practices (MCOP²), teacher interviews, and student pre-and post-tests. Quantitative data from tests and MCOP² were …

Marine Protection And Environmental Forcing Influence Fish-Derived Nutrient Cycling In Kelp Forests, June Shrestha, Joseph R. Peters, Jennifer E. Caselle, Scott L. Hamilton

Faculty Research, Scholarly, and Creative Activity

Animal consumers excrete dissolved inorganic nitrogen, an essential nutrient for regulating primary production and macroalgal growth in the ocean. Often overlooked in attempts to explain kelp forest productivity, relatively little is known about the role of consumers in nutrient cycling in temperate systems, such as the magnitude of nutrients excreted and the factors that influence spatial and temporal variability in consumer-derived nutrients. To investigate the supply of ammonium (NH4+) excreted by the dominant members of the nearshore rocky reef fish community, we combined empirically-measured relationships between excretion rate and body mass with data on fish density and size structure from …

Mitigating Risk: Predicting H5n1 Avian Influenza Spread With An Empirical Model Of Bird Movement, Fiona Mcduie, Cory T. Overton, Austen A. Lorenz, Elliott L. Matchett, Andrea L. Mott, Desmond A. Mackell, Joshua T. Ackerman, Susan E.W. De La Cruz, Vijay P. Patil, Diann J. Prosser, John Y. Takekawa, Dennis L. Orthmeyer, Maurice E. Pitesky, Samuel L. Díaz-Muñoz, Brock M. Riggs, Joseph Gendreau, Eric T. Reed, Mark J. Petrie, Chris K. Williams

Faculty Research, Scholarly, and Creative Activity

Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting 600 bird and mammal species globally and over 83 million birds across North America (December 2023), poses a serious global threat to animals and public health. We combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was …

Next Steps For Assessing Ocean Iron Fertilization For Marine Carbon Dioxide Removal, Ken O. Buesseler, Daniele Bianchi, Fei Chai, Jay T. Cullen, Margaret Estapa, Nicholas Hawco, Seth John, Dennis J. Mcgillicuddy, Paul J. Morris, Sara Nawaz, Nishioka, Anh Pham, Kilaparti Ramakrishna, David A. Siegel, Sarah R. Smith, Deborah Steinberg, Kendra A. Turk-Kubo, Benjamin S. Twining, Romany M. Webb

Faculty Research, Scholarly, and Creative Activity

There are many potential approaches to marine carbon dioxide removal (mCDR), of which ocean iron fertilization (OIF) has the longest history of study. However, OIF studies to date were not primarily designed to quantify the durability of carbon (C) storage, nor how wise OIF might be as an mCDR approach. To quantify C sequestration, we introduce a metric called the “centennial tonne,” defined as 1,000 kg of C isolated from atmospheric contact for on average at least 100 years. We present the activities needed to assess OIF from a scientific and technological perspective, and additionally, how it might be responsibly …

Optimal Tool Path For Extrusion-Based Additive Manufacturing To Improve Geometrical Accuracy And Productivity, Robert Ehlers, Amir Armani

Faculty Research, Scholarly, and Creative Activity

The objective of this study was to improve the geometrical accuracy and productivity of extrusion-based additive manufacturing processes. Four algorithms were developed to adaptively change the track width in each layer (i.e., adaptive rastering); optimize the rastering orientation for each layer; adaptively change the layer thickness (i.e., adaptive slicing); and optimize the overall orientation of part. These algorithms were implemented in a commercial 3D printer and several case-studies were conducted to examine their efficacy (individually and combined). The results were compared with standard tool path planning software and indicated a significant improvement in both geometrical accuracy and productivity.

Navigating Enterprise Constraints: Building A Hybrid Multi-Modal Mobile Intelligent App, Ketan Malempati, Akshat Gupta, Kaikai Liu

Faculty Research, Scholarly, and Creative Activity

The promise of artificial intelligence (AI) has prompted various industries to explore how it can enhance their businesses and improve customer experiences. However, the practical deployment of AI services faces challenges due to internal infrastructure limitations, data policies, and network restrictions. In this paper, we present our current project - a solution designed to empower mental health centers with AI tools while adhering to stringent data and network constraints. Our approach involves deploying AI services and data within internal enterprise networks, while the customer-facing mobile app resides in the public cloud. We introduce a custom AI agent system that monitors …

Resume Content Generation Using Llama 2 With Adapters, Navaneeth Sai Nidadavolu, William B. Andreopoulos

Faculty Research, Scholarly, and Creative Activity

This paper presents a novel approach to enhancing the Llama language model for generating customized resumes tailored to domain-specific job descriptions. Unlike traditional methods that rely heavily on extensive fine-tuning, we implement scalable adapter modules to minimize parameter adjustments. This approach preserves the model's inherent ability to generate coherent and contextually appropriate language across diverse tasks, ensuring that its general linguistic capabilities remain intact. Additionally, we employ a prompting strategy to dynamically create a diverse and comprehensive dataset, ensuring high relevance to various job roles. Using a dataset of 10,000 job descriptions and resumes, our approach resulted in a 20% …

Rescaling: Change Agency And The Emerging Geography Of Economic Relationships, Markus Grillitsch, Björn Asheim, Nichola Lowe, Sophie Kelmenson, Lea Fünfschilling, Karl Johan Lundquist, Yahia Mahmoud, Mikhail Martynovich, Pauline Mattsson, Magnus Nilsson, Johan Miörner, Torben Schubert

Faculty Research, Scholarly, and Creative Activity

In this paper, we propose a theoretical and conceptual framework for articulating and studying changes in the global economic landscape and illustrate this framework in the current context. The framework pivots around the notion of rescaling, which is interpreted from a human agency perspective. We disentangle three theoretically distinct dimensions of rescaling and show how they play together using concrete examples. The theoretical and conceptual framework links the intended and unintended consequences of globalisation to current rescaling efforts, and allows us to investigate when, why, and how changes to the geography of economic relationships occur.

Selective Laser Melting And Mechanical Characterization Of Superalloys Made From Recycled Parts, Hugo Tupac-Yupanqui, Amir Armani

Faculty Research, Scholarly, and Creative Activity

Geometrically complex functional parts from recycled Inconel 718 were additively manufactured and characterized. Scrap parts were melted, recycled, and used in a new gas atomization process to produce the feedstock for a selective laser melting printer. Optimal print parameters were determined using finite element simulations. Standard test methods were employed to experimentally examine the properties of parts, including their density, anisotropic tensile behavior, chemical composition, and fracture surface. The results indicated that scrap Inconel 718 parts can be used to additively manufacture high-quality functional parts. As a case-study, an automotive turbocharger was resigned and additively manufactured based on the findings …

Student Understanding Of Divergence And Curl In Upper-Division Electromagnetism, J. Toby Stuckey, Gina M. Quan

Faculty Research, Scholarly, and Creative Activity

The purpose of this paper is to understand and characterize student thinking about the physics concepts of divergence and curl in the context of upper-division electromagnetism for physics majors. We interviewed five students at a west coast university who had taken at least one semester of upper-division electricity and magnetism. The interview prompted students to describe divergence and curl in multiple representations (visually, mathematically, qualitatively). Our analysis identified that students can notice but struggle to resolve discrepancies between the mathematical calculations and the graphical representations of vector fields. We illustrate examples of when students appear to have a disconnect between …

Study Of Using Variational Quantum Linear Solver For Solving Poisson Equation, Nithin Reddy Govindugari, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

Quantum computing is promising in speeding up the system of linear equations (SLE) solving process. However, its performance is limited by noise. The variational quantum linear solver (VQLS) algorithm is expected to be more resilient to noise than gate-based quantum computing algorithms. This is because error correction is not available yet and VQLS is based on cost function minimization. In this paper, the gate insulator Poisson equation is solved using VQLS. The results are compared to technology computer-aided design (TCAD) results and gate-based quantum algorithm results. We show that, even without error-free qubits, the IBM-Q quantum computer hardware can solve …

Tcad Structure Input File Generation Using Large Language Model, Le Minh Long Nguyen, Albert Lu, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

In this paper, we study the possibility of using Large Language Models (LLMs) to create Technology Computer-Aided-Design (TCAD) structure generation input files. LLMs are machine learning models trained on vast amounts of text data from the Web and are designed to understand, generate, and interact with humans through natural languages such as English. However, unlike programming languages with abundant training examples on the Web, TCAD examples are scarce. In this work, by using TCAD Sentaurus Structure Editor (SSE) as an example, 7000 nanowire data are generated to fine-tune open-source models (Llama 2 and 3) to obtain chatbots that can generate …

Differential Expression Analysis Of Treatment Resistant And Treatment Susceptible Neisseria Gonorrhoeae Paired With Gene Set Enrichment Analysis, Kinzie Bailey

Theses

Neisseria gonorrhoeae, the bacterium which causes gonorrhea, is a public health threat as recognized by the CDC due to the risk of untreatable gonorrhea due to the high prevalence of resistance to antibiotics in the gonococcal population [1]. Current screening methods for resistance to antibiotics for clinical infections may take up to 2 days to produce results, which could result in delays in treatment, unnecessary follow-up appointments, inappropriate antibiotic prescriptions, and overall poor treatment outcomes [2]. In this study, we utilize RNA sequencing (RNA-seq) to characterize the expression patterns of resistant and susceptible strains of N. gonorrhoeae. Here, we look …

Machine Learning, Fuzzy Logic And Zero Trust-Based Quishing Prevention Solution For Android Smartphones, Felix William

Theses

QR code phishing, or "quishing," exploits the widespread adoption of QR codes to embed malicious URLs that lead users to phishing sites or initiate malware downloads. Unlike traditional phishing methods, QR phishing is uniquely deceptive, leveraging the inherent trust and convenience associated with QR codes while bypassing standard detection mechanisms. This thesis presents the SEQR scanner, a novel solution tailored to detect and prevent QR phishing attacks, specifically focusing on Android platforms. By integrating multiple detection mechanisms—machine learning prediction, fuzzy logic algorithm, and third-party blacklisting APIs—the solution effectively identifies malicious QR codes with precision. A zero-trust-based mechanism is implemented alongside …

Machine Learning Framework For Detecting Ldap Injection Attacks, Rahul Nair

Theses

LDAP injection attacks have posed a growing danger to web application security, utilizing directory service vulnerabilities to obtain unauthorized access or tamper with sensitive information in recent times. In this thesis, a comprehensive method is developed for detecting and preventing LDAP injection attacks by utilizing a role-based access control approach to generate a unique dataset. Various categories and variations of LDAP queries that mimic real attack situations, as well as legitimate benign queries representing typical LDAP operations, are included in the dataset to further classify them based on user roles. Four different machine learning algorithms, including XGBoost, Logistic Regression, Support …

Florescence, Evan D. Jaccodine

Theses

Florescence is a photographic project that provokes conversation between mediums, methods, and attitudes in art and design. Starting as grainy, screened Risograph prints mounted into custom wood frames, the uniformity of mechanical reproduction is distorted by handmade craft elements. The images examine the materiality of making as part of the message they produce; they are both eclectic handmade objects and mass-produced products. These pictures intend to communicate an idea like an advertisement, except the message, meaning, or intention isn’t clear. I am interested in the moment when the viewer comes close enough to the image to see the prints' poor …

Tracked Gulls Help Identify Potential Zones Of Interaction Between Whales And Shipping Traffic, Megan A. Cimino, Heather Welch, Jarrod A. Santora, David Kroodsma, Elliott L. Hazen, Steven J. Bograd, Pete Warzybok, Jaime Jahncke, Scott A. Shaffer

Faculty Research, Scholarly, and Creative Activity

Seabird-vessel interactions are often studied through the lens of fisheries bycatch, but seabirds encounter many watercraft types. Western Gulls Larus occidentalis breeding on the Farallon Islands (California, USA) have a foraging domain that encompasses both shipping lanes and productive fishing grounds, resulting in ample opportunities for vessel encounters. Previous research showed that these Western Gulls can serve as ecosystem indicators because their foraging behavior is linked to ocean prey conditions, and because their foraging grounds overlap with that of Humpback Whales Megaptera novaeangliae, which can make prey accessible. Because ship strikes and entanglement in fishing gear are concerns for whales …

Use Or Not: A Qualitative Study On The User Adoption And Abandonment Of Voice Shopping With Smart Speakers, Jiahe Lan, Yu Chen, Zheng Yan

Faculty Research, Scholarly, and Creative Activity

The recent advances in smart speakers impel the emergence and prevalence of voice shopping - placing orders on voice assistants. Previous work has studied user acceptance of voice shopping and the factors influencing users' experience of voice shopping. However, despite the growing interest in the use of voice shopping, little is known about the limited usage or abandonment of voice shopping. In this paper, we address this research gap through a qualitative study of 43 users of Tmall Genie, a smart speaker popular in China. We found that participants are willing to make low-involvement purchases via voice shopping. However, after …

Erratum To: Reconfigurations In Brain Networks Upon Awakening From Slow Wave Sleep: Interventions And Implications In Neural Communication (Network Neuroscience), Cassie J. Hilditch, Kanika Bansal, Ravi Chachad, Lily R. Wong, Nicholas G. Bathurst, Nathan H. Feick, Amanda Santamaria, Nita L. Shattuck, Javier O. Garcia, Erin E. Flynn-Evans

Faculty Research, Scholarly, and Creative Activity

After publication of our paper Reconfigurations in brain networks upon awakening from slow wave sleep: Interventions and implications in neural communication, we noticed an error in our condition labels that required some revision of figures and text and some new interpretations throughout the manuscript. The error was a consequence of the double-blind nature of the original experimentation which contained two interventions: (1) a blue-enriched light intervention, as originally mentioned; and (2) an olfactory odorant condition. In review of previous analyses and presentations of the data, there was a time when non-descriptive labels (e.g., “A”, “B”) were accidentally swapped, indicating the …

A Comparative Multivariate Analysis Of Var And Deep Learning-Based Models For Forecasting Volatile Time Series Data, Saroj Gopali, Sima Siami-Namini, Faranak Abri, Akbar Siami Namin

Faculty Research, Scholarly, and Creative Activity

The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), Simple Exponential Smoothing (SES), deep learning models, and, most notably, univariate Long Short-Term Memory (LSTM) built based on univariate variable where the next lag of time series is leveraged for forecasting the next cycle of data. This paper takes this line of research to the next level by focusing on forecasting time series data based on “multivariate” modeling and analysis. To have a better insight of the performance of various deep learning-based models when multivariate …