Digital Commons Network^™

From Perfect Victim To Resilient Upstander: How Educators Can Help Middle-School Students With Asd Thrive Despite Peer Aggression, Julie R. Johnson

All Electronic Theses and Dissertations

Students with Autism Spectrum Disorder (ASD) are more likely to be bullied by peers (46-94%), bullied by siblings, and chronically bullied than typically developing students (30.5%). Some victims become bullies, particularly when impulsivity and hostility are high or perseverance or prudence are low. Students with ASD are more likely to become bully-victims, especially if they have certain comorbidities. This literature review explores how educators can mitigate this cycle. Schools need a multi-tiered system of supports to support victims with ASD so they do not become bullies: Tier One needs clear policies, anti-bullying programs, and neurodiversity-affirming classrooms. Tiers Two and Three …

Physical Activity And Cognitive Function Among Youth: Implications And Recommendations For Increasing Physical Activity Participation, Allison C. Ims

All Electronic Theses and Dissertations

Physical activity is extensively recognized as an essential part of a healthy lifestyle. For children, it is important for the development of their physical, cognitive, social, and emotional well-being. Nationally, there are physical activity recommendations for youth; however, most children and adolescents do not meet these recommendations. It’s recommended that youth participate in at least 60 minutes of moderate to vigorous physical activity daily. However, many youth are not achieving this recommendation due to physical, environmental, and social barriers. The purpose of this thesis was to look at the relationship between physical activity, executive functioning, and academic performance among youth. …

Towards A Sustainable Art World: The Essential Role Of Sustainability Leads In The Arts And Cultural Sector, Isobella Win Richings

MA in Art Business Dissertations

The purpose of this dissertation is to investigate the role of sustainability leads within art institutions and how their implementation benefits a company’s development towards being a sustainable business. Due to the increasing pressure that the art world faces considering the environmental crisis which we are experiencing in the 21st century, it is integral to understand what is being done and what can be further instigated to create a sustainable future of the art world.

Although this study uses research that already exists within the discourse of environmental sustainability and the cultural sector, the main sources used to come to …

A Quantitative Analysis Of Burrowing And Subterranean Locomotion In The Sand Lance Using A Transparent Sediment, Issei Fujita, Makoto Tomiyasu, Jun Yamamoto, Yasuzumi Fujimori

Journal of Marine Science and Technology–Taiwan

Sand lances (Ammodytes spp.) rely on rapid burrowing into sediment for predator avoidance. Although their sediment grain-size preferences are well documented, the biomechanics underlying burrowing success remain unclear because natural substrates are opaque. Using a transparent-sediment system, we directly visualized and quantified burrowing kinematics to: (1) test the effect of body size (total length, TL) on burrowing success; (2) examine entry mechanisms (e.g., swimming speed, entry angle); and (3) describe locomotion within sediment. Logistic regression on the full dataset (N = 28 fish) identified TL as the primary determinant of success, with larger individuals exhibiting significantly higher success …

Cruise Network Design Under Sequential Duopolistic Entry, Ta-Hui Yang, Ching-Hui Tang, Wan-Tien O

Journal of Marine Science and Technology–Taiwan

This study addresses the network design for international cruise services in a duopolistic market, where carriers enter and make decisions sequentially. The leader, who makes the first move, makes decisions as there is no competitor in the market. The follower, who makes decisions later, has to design their network considering the existing leader’s network. The leader’s model is a mixed integer linear problem while the follower’s model is a mixed integer nonlinear problem. Therefore, a heuristic is proposed to solve the problem. The commercially available general algebraic modeling system is used in conjunction with its different solvers to solve the …

Effect Of Heat Treatment On The Corrosion And Wear Behavior Of 17-4 Ph Stainless Steel For Marine Applications, Syuan Tai, I-Kon Lee, Ming-Yuan Lin, Kang-Yu Liao, Chin-Chun Chang, Hung-Bin Lee

Journal of Marine Science and Technology–Taiwan

This study explores the tribocorrosion behavior of conventionally cast 17-4 PH stainless steel under real seawater conditions, focusing on the effects of three heat treatments (Solution, H900, H1100). Electrochemical tests, tribocorrosion experiments, SEM, XPS, and quantitative analysis were used to establish a three-stage tribocorrosion mechanism. Results show that H900 exhibits superior corrosion and wear resistance, while H1100 suffers increased material loss and surface cracking at high potentials. Elemental analysis revealed NbC migration forming third-body particles, which, although briefly reducing friction, induced local stress concentration and crack initiation. The findings highlight the critical influence of microstructure, passive film stability, and third-body …

Enhancing Underwater Imagery And Organism Detection Using Reinforcement Learning, K. Arul Deepa, P. Ramya, Karpaga Vinodha, Dharmaraja C

Journal of Marine Science and Technology–Taiwan

Underwater environments pose significant challenges in assessing image quality and organism detection due to light scattering and absorption, which limits visibility and color fidelity. Existing solutions often fail to effectively address these challenges, resulting in suboptimal image quality and hindering organism identification. This paper examines the problem through a dual-focused approach: enhancing underwater images and detecting organisms using the Underwater Image Enhancement Benchmark (UIEB) dataset. The first step introduces a state-of-the-art method for image enhancement by applying reinforcement learning (RL) principles. By formulating the enhancement process as a Markov Decision Process (MDP)—where states are represented by image features and actions …

Design, Testing And Controls For Air Source Heat Pump System In Cold Climates Using Natural & Conventional Refrigerants, S M Abdur Rob

Dissertations and Theses

Fossil-fuel based heating systems used in the residential buildings in northeastern U.S region are not only inefficient but also largely responsible for the greenhouse gas emissions in U.S. Electrification of the buildings has been proved to be the most efficient way to reduce the greenhouse gas emissions where Heat Pumps can be the best alternative to replace the natural gas based heating system to accelerate the electrification process. Among different types of heat pumps, the Air Source Heat Pump (ASHP) system is widely used due to the easy installation and energy efficiency. Conventional heat pump technologies use various types of …

Executive Self-Management Of Reading And Writing For College Students With Adhd, Jiajie Li

Dissertations and Theses

Background. College students with ADHD often experience difficulties with self managed academic tasks, for which there are currently few specific interventions. The present study examined associations among ADHD symptom severity, executive functioning, academic achievement, and perceived helpfulness of reading- and writing-focused sessions within a cognitive-behavioral intervention for college students with ADHD. Method. N = 41 undergraduate students (Mean age = 21.32 years, SD = 2.74; 70.7% female) with ADHD were recruited into a 12-week group-based cognitive behavioral intervention for executive functioning difficulties. Two sessions were devoted to skills and strategies specific to academic tasks, Reading for Retention and Planning, Organizing, …

Examining The Spatial Variability Of Summer Heat In New York City Using Landsat Land Surface Temperature, Ryan Kabir

Dissertations and Theses

Extreme heat is the leading weather-related cause of death in the United States, and in New York City (NYC) approximately 370 heat-related deaths occur annually on average. The spatial distribution of surface heat exposure across NYC is highly uneven, low-income neighborhoods and communities of color consistently face higher temperatures, yet the intraurban spatial structure of land surface temperature (LST) during heatwave events has not been systematically characterized at high resolution. The New York City Panel on Climate Change Fourth Assessment (NPCC4) identifies this as an explicit research gap, noting that its own projections, based on global climate models downscaled to …

An Examination Of The Potential Impact Of Herpes Zoster Vaccination Of Younger Adults, Katherine N. Goyette

Public Health Theses

Varicella-zoster virus causes two distinct clinical syndromes, varicella, commonly known as chicken pox, and herpes zoster, commonly known as shingles. Natural varicella infection (as opposed to inoculation) is a necessary precursor to herpes zoster, which can cause serious pain and suffering. There is some evidence that rates of herpes zoster may have increased since the introduction of the varicella vaccine in the United States in younger adults, possibly due to less exogenous boosting by community varicella. However, the vaccine against herpes zoster is only approved for adults ages 50 and above. This paper thus examines the change in rates of …

Single-Cell Gene Perturbation Prediction Via Sclambda-Program, Jingyi Guo

Public Health Theses

Predicting single-cell transcriptomic responses to single and multi-gene perturbations is essential for mapping regulatory networks, resolving disease mechanisms and identifying therapeutic targets. Several state-of-the-art deep learning methods, especially scLAMBDA, have demonstrated strong performance in predicting perturbation outcomes. However, computational biology still faces a fundamental trade-off between predictive accuracy and biological interpretability. To reconcile these objectives, there is an urgent need to develop models that can generate accurate perturbation predictions and simultaneously uncover distinct functional pathways. Thus, we introduce scLAMBDA-Program, a novel deep generative variational autoencoder framework that builds upon the robust predictive foundation of the scLAMBDA architecture. scLAMBDA-Program incorporates a …

Water Resource Governance And Health Equity In Angola, Mads Harner

Public Health Theses

AbstractBackground: Angola is confronting a set of intertwined challenges including water insecurity, increasing climate variability, and deep structural inequality that together intensify the burden of waterborne and water-related diseases (Lombana Cordoba et al., 2021; World Health Organization, 2025). Roughly half of the population does not have reliable access to safe drinking water, and gaps in sanitation and hygiene infrastructure, especially in peri-urban and rural areas, facilitate the spread of illnesses such as cholera, diarrheal diseases, and malaria (UNICEF Angola, 2025; Moreira et al., 2012). These issues are further exacerbated by drought and broader climate variability, and underlying them are historical …

Pediatric Rheumatic Heart Disease Screening For Secondary Antibiotic Prophylaxis: An Explainable Shannon Energy Approach Using Heart Phonocardiogram In Northeast Brazil, Zhuohui Lin

Public Health Theses

Rheumatic Heart Disease (RHD), caused by Group A Streptococcus (GAS), remains a significant global health burden, particularly among children in low- and middle-income countries. Untreated GAS infection can lead to acute rheumatic fever and subsequent chronic valvular damage of RHD, such as mitral valve (MV) regurgitation. Hence, early detection is critical for the administration of Secondary Antibiotic Prophylaxis to prevent disease progression. Although deep learning models demonstrate high diagnostic accuracy, limited explainability restricts clinical adoption, especially in resource-limited settings. In this proof-of-concept study, we evaluated Shannon energy (SE) transformation as a proxy to differentiate holosystolic murmurs associated with RHD-related mitral …

From Genomic Surveillance To Vaccine Efficacy: Assessing The Impact Of Plasmodium Falciparum Rh5 Genetic Diversity On Blood-Stage Malaria Vaccine Performance, Xinyan Wei

Public Health Theses

Malaria remains a major public health burden in sub-Saharan Africa. The development and deployment of effective malaria vaccines is a priority for reducing disease burden and severe outcomes. The protective immunity generated by current malaria vaccines declines over time, requiring booster doses to sustain efficacy. Consequently, next-generation malaria vaccines are under development, including a blood-stage vaccine targeting reticulocyte-binding protein homolog 5 (RH5), the most advanced candidate in clinical development. This study investigates whether genetic diversity in PfRH5 may influence vaccine efficacy using amplicon sequencing and bioinformatic analyses across three complementary approaches. Firstly, this study characterizes PfRH5 genetic diversity across multiple …

Asymptomatic Tb Duration And Transmission Models, Zhichao Zhou

Public Health Theses

Tuberculosis (TB) transmission is sustained in part by asymptomatic disease states that limit the effectiveness of passive case finding interventions that rely on symptom-based diagnosis. Here we develop a transmission model that represents the duration of asymptomatic disease with a gamma-distributed waiting time. By chaining multiple asymptomatic sub-states, we find that the gamma-distributed model provides a better fit to the observed distribution of the duration of asymptomatic disease than a simple one-state model which imposes an assumption of an exponentially-distributed duration of asymptomatic disease. Comparing the fitted gamma-distributed model and the simple model, we quantify how assumptions about the distribution …

Nicotine, Bdnf, And Ꞵ-Adrenergic Ligand Receptors Regulate Soluble E-Cadherin Signaling In Non-Small Cell Long Cancer, Stuti Goel

Senior Honors Theses and Projects

E-cadherin is a protein that normally helps cells adhere to each other. Sometimes, part of this protein is cleaved off and released outside the cell as soluble E-cadherin (sE-cad). When this happens, there is less E-cadherin left on the cell surface. Enzymes called matrix metalloproteases, especially MMP9, are responsible for this cleavage. In this study, we investigated E-cadherin in two non-small cell lung cancer cell lines, A549 and H1299. We found that treating these cells with brain-derived neurotrophic factor (BDNF), nicotine, or epinephrine increased the amount of MMP9 released into the surrounding media. When the cells were treated with propranolol, …

Climate Change Impacts On Hydrology In The Upper James Watershed, Imiya Mudiyanselage Chathuranika, Dalya Ismael

Engineering Technology Faculty Publications

Hydrological modeling of the Upper James Watershed (UJW), Virginia, is critical for predicting water availability, flood management, agriculture, ecosystem protection, and hydropower production under increasing climate change. The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) is applied to evaluate climate change impacts on key hydrological components within the watershed. Future climate conditions were assessed for the near (NF: 2026-2050), mid (MF: 2051-2075), and far (FF: 2076-2100) periods using three Global Climate Models (GCMs) under Shared Socioeconomic Pathways SSP 2-4.5 and SSP 5-8.5. Climate data were bias-corrected using the Linear Scaling Method (LSM) and used to drive the HEC-HMS model. Results project …

Assessing Climate Change Impacts On Wildfire Risk In Central Appalachian Forests Of The Eastern United States, Imiya Mudiyanselage Chathuranika, Dalya Ismael

Engineering Technology Faculty Publications

Wildfire risk is increasing in the eastern U.S., yet spatial and climate-driven assessments remain limited. This study evaluates climate change impacts on wildfire risk in the Upper James Watershed (UJW) using baseline (2000–2019), near-future (2021–2040), and far-future (2061–2080) projections from a 12-model CMIP6 global climate model (GCM) ensemble under SSP2–4.5 and SSP5–8.5. A wildfire risk model was developed in ArcGIS Pro using nine key factors and validated with MODIS hotspot data, showing good agreement between modeled risk patterns and observed fire occurrences (NOF = 0.21, RMSE = 4.20, MAE = 3.37). Baseline risk was primarily driven by land cover, fire-lookout …

Improving Medical Diagnostics With Vision-Language Models: Convex Hull-Based Uncertainty Analysis, Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick, Michel Audette

Engineering Technology Faculty Publications

In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs’ consistency and uncertainty, particularly in critical applications such as healthcare, which demand a high level of trust and reliability. This paper proposes a novel approach to evaluate uncertainty in VLMs’ responses using a convex hull approach on a healthcare application for visual question answering (VQA). For any VLM, temperature refers to a sampling parameter used in probabilistic generation, which controls the randomness of the model’s output. The LLM-CXR model is selected as the medical …

Artificial Intelligence (Ai) In Educating Next Generation Of Engineering Technology Students, Adel El-Shahat, Murat Kuzlu, Vukica M. Jovanovic, Katherine Smith, Abdullah Al Mamun, Otilia Popescu

Engineering Technology Faculty Publications

Artificial Intelligence (AI) is transforming education, particularly for electrical engineering technology (EET) students, by presenting adaptive learning, immediate responses, and unconventional tools. Therefore, this paper proposes investigating modern learning to employ AI in educating future electrical engineering technology students. Firstly, the paper explores how to shape AI knowledge for EET students, supplying them with hands-on skills in AI tasks, clarifying coding, data analysis, and AI ethical usage. Then, as educators, what are the efficient AI tools to utilize in teaching, such as tailored tutoring, automated code assessment, AI-driven design/simulation, lecture dictation, and smart content creation? Key tools, for instance, Google …

A Methodological Framework For Modernizing Engineering Course Content With Large Language Models, Katherine Smith, Dalya Ismael, Otilia Popescu, Murat Kuzlu, Adel El-Shahat, Vukica M. Jovanovic

Engineering Technology Faculty Publications

The rapid evolution of technology presents challenges for engineering educators. While the core engineering methods often remain relevant over time, course materials rapidly become outdated in presentation and pedagogical approach. This paper presents a methodological framework for using large-language models (LLMs) to modernize engineering course content with a case study in an advanced technical analysis course.

The methodology follows a phased approach that is designed to be repeatable and verify the accuracy and completeness of course content. During the first phase, an LLM is used to map outdated text-heavy content to a modern format using a LaTeX template. The second …

Short-Window Market Reactions To Real Estate M&A: A Comparative Event Study Of Reits And Real Estate Services Firms, Aryan Kaila

CMC Senior Theses

Existing research on real estate mergers has largely focused on REIT acquirers in isolation, typically finding near-zero bidder reactions in short event windows. There is little work that directly compares REITs with publicly listed real estate services (RES) firms that operate in the same market cycles and conditions but follow different business models. Using a transaction-level dataset of 137 U.S. mergers from 1994 to 2024, this study applies event-study methodology and cross-sectional regression analysis to investigate whether equity markets respond differently to acquisitions undertaken by REITs and real estate services firms. The estimates show that REIT acquirers experience notably more …

Sustainable Community-Wide Model To Enhance Cancer Data Usage And Utility, Emily S Boja, Mousumi Ghosh, Ying Huang, Tung-Shing Mamie Lih, Rawan Shraim, Gregory Wheeler, Diana Thomas, Rakesh Khanna, Stephanie Sandor, Jinghui Zhang, Sapna Oberoi, Nicolas J Llosa, Aditya Suru, Fernanda Silva Michels, Eric Durbin, Anna Fernandez, Lucy Han, James Galbraith, Yin Lu, Brian Furner, James H Tanis, Michael Watkins, David Higgins, Gavriel Matt, Xin Zhou, Yang Li, Marcin Cieslik, Jamie Estill, Michael Sierk, Yanling Sun, Weiping Ma, Joseph Flores-Toro, Freddie Pruitt, Subhashini Jagu, Elmer A Fernández, Daniela Orschanski, Stephanie J Spielman, Jaclyn Taroni, Trinh Nguyen, Brian Capaldo, Erin Beck, Tanja Davidsen, Johanna Goderre Jones, Minghong Ward, Anne Sturcke, Jennifer M Torres Del Valle, Sean Hanlon, Danielle Daee, Brandon Wright, Nathaniel Boyd, Heather Basehore, Liang Liu, Ying Hu, Daoud Meerzaman, Huiqing Li, Ying Wu, Gregory H Reaman, Erin Rudzinski, Jack F Shern, Brigitte Widemann, Warren Kibbe, Jaime Guidry Auvil

Children’s Nutrition Research Center Staff Publications

Despite vast investments in data collection, generation, and sharing from childhood cancer studies, for example, Gabriella Miller Kids First Research Program, Childhood Cancer Data Initiative, and other efforts, secondary use of data remains a challenge especially for rare diseases. The National Cancer Institute (NCI) Office of Data Sharing (ODS) aimed to promote FAIR (Findable, Accessible, Interoperable, Reusable) data sharing practices to enhance data utility, accelerate discovery, and foster interdisciplinary collaboration. NCI ODS launched its inaugural Data Jamboree focusing on childhood cancer alongside its third Annual Symposium in September 2025. Over 120 participants with diverse backgrounds coalesced into 23 multidisciplinary teams …

Effects Of Flooding-Induced Migration On The Food Security Status Of Farming Households In Rivers State, Nigeria, Jacinta Nmutaka Umechukwu, Daniel Bruce Sarpong, Ama Ahene-Codjoe, Taeyoon Kim

All Rsif Scholars' Publications

The agricultural landscape in Rivers State, Nigeria, is increasingly threatened by the dual challenges of escalating flooding events and return migration. Historically, flooding in the region has shifted from isolated incidents to a persistent and widespread hazard, significantly disrupting agricultural livelihoods and rural stability. This study assessed the effects of flooding-induced migration on the food security status of farming households in Nigeria. Data were collected on the episodes that occurred between 2011–2022 to estimate the coping strategies of the farmers. The farm revenue specifically from 2022 production activities was also computed. This was used in estimating the effect of flooding-induced …

A Lightweight Quantum-Secure Authentication And Key Agreement Protocol For Vehicular Ad-Hoc Networks, Lasseni Coulibaly, Damien Hanyurwimfura, Evariste Twahirwa, Abubakar Diwani

All Rsif Scholars' Publications

Intelligent transportation systems, a critical pillar for smart cities, enable real-time vehicular communications to prevent human errors and improve traffic safety and efficiency. However, the open and highly dynamic nature of vehicular networks exposes them to various security threats, including message tampering, impersonation, and privacy violations. Several authentication and key agreement (AKA) protocols have been proposed to mitigate these risks, but often fail to maintain future-proof security against emerging quantum threats or introduce significant latency that affects real-time applications by relying on computationally expensive public-key cryptography, blockchain or centralized architectures. This paper proposes a new AKA protocol that combines hash-based …

Modeling Of Intraday Fluctuations In Future Climate Parameters And Their Impact On Perovskite Solar Modules, From A Sustainable Development Perspective, Wakiang Emile Latchiba, Sebastian Waita, Robert Kruege, Julius M. Mwabora

All Rsif Scholars' Publications

Modeling of intraday fluctuation in future climate parameters. This study uses ARIMA and LSTM models to evaluate and examine the prediction accuracy of four main meteorological parameters (solar irradiance, temperature, relative humidity, and wind speed) that have an impact on perovskite solar modules using Chad as an example. The findings show that the use of averaged climatic data considerably obscures the effects of intraday fluctuation, which significantly increases power output volatility and speeds up degradation. Increasing short-term temperature extremes may further jeopardize system reliability, according to projections under future climate scenarios. The results highlight the necessity of climate-resilient photovoltaic modeling …

Development And Validation Of An Algorithmic Randomization Model For A Cefr-Aligned English Proficiency Test For College Students, Jamjumrat Deeprom

PASAA

No abstract provided.

From Policy To Practice In Assessment : A Cefr-Aligned Professional Development Model For Classroom-Based Assessment In Iranian Efl Classrooms, Amir Ghajarieh, Zuraidah Mohd Don

PASAA

No abstract provided.

Heteronormativity And Gender Inequality In Three Esp Textbooks In Thailand : Multimodal Discourse Analysis, Akkasit Kathapant, Kriangkrai Vathanalaoha

PASAA

No abstract provided.