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Editorial: Ai's Impact On Higher Education: Transforming Research, Teaching, And Learning, Alyse Jordan, Ashley L. Dockens, Natalia Anastasia Pierson, Xinyue Ren

STEMPS Faculty Publications

[Introduction] This Research Topic provides a comprehensive examination of how artificial intelligence (AI) is transforming higher education. The collected studies reveal several interconnected themes that illuminate both the opportunities and challenges of AI integration in academic settings. This editorial summarizes these themes and articulates their significance for the future of higher education.

Application Of Genetic Algorithm In Container Vessel Stowage Planning With Carbon Tax Considerations, Ming-Feng Yang, Wei-Hao Su, Ko-Meng Hu, Yu-Hsuan Li

Journal of Marine Science and Technology–Taiwan

This study developed a method for optimizing stowage planning for container vessels, a crucial aspect of international trade logistics. Over 80% of global trade depends on containerized transportation; thus, effective stowage planning is essential for minimizing transportation costs and enhancing operational efficiency. In the proposed hybrid optimization approach, integer programming is combined with a genetic algorithm to generate optimal stowage plans. The key factors considered in this method include load capacity limits, stacking constraints, and carbon tax regulations. The proposed method involves maximizing space utilization while minimizing logistics costs, with particular emphasis on reducing port dwell times. The findings of …

Exploring The Red Sea Crisis’S Supply Chain Disruption Impacts On The Shipping Industry, Po-Hsing Tseng, Nick Pilcher

Journal of Marine Science and Technology–Taiwan

Since October 7, 2023, the Houthi militia in Yemen has continuously attacked Israel and its nearby ships in the Red Sea. This crisis has impacted on global ship operations, freight rates, and shipping networks, since this conflict seriously affects the international trade between Europe and Asia and brings many unpredictable butterfly effects (e.g. supply chain disruption, and high transportation costs in shipping and air cargo). This papero explores its impact on the supply chain and suggests potential solutions;, and to consider perceptions on who should be responsible for the crisis, and who will actually shoulder the responsibility for the crisis. …

Operational Risk Evaluation Of Oil Tankers Via Multivariate Gaidai Reliability Framework Incorporating Memory Effects, Oleg Gaidai, Shicheng He, Jinlu Sheng, Yan Zhu, Alaa Elsayed, Mahmoud El-Wazery

Journal of Marine Science and Technology–Taiwan

The retreat of Arctic Sea ice may exert a major impact on economy，potentially transforming the nature of commerce between Asia, Europe, and the Americas. Projections indicate a 40% reduction in transit distance and a 30% decrease in voyage time between Europe and northwest Asia compared to traditional routes such as the Suez Canal. However, even during summer navigation, fragmented floating ice persists, generating stochastic ice loads on vessel bows and hulls through complex ship-to-ice interaction. For structural design, statistical extrapolation methods are required to accurately assess excessive areal bow/hull stresses. This study proposes a novel multi-modal structural damage risk assessment …

New Insights Into Decapod Chemical Communication: A Focus On The Hydrothermal Vent Crab Xenograpsus Testudinatus, Jishnu Panamoly Ayyappan, Mark June S. Consigna, Li-Chun Tseng, Jiang-Shiou Hwang

Journal of Marine Science and Technology–Taiwan

Chemical communication in decapod crustaceans has been extensively studied for over 150 years, with most of the research focusing on sex pheromones. These crustaceans inhabit chemically complex environments and rely on diverse chemical signals for essential behaviors such as mate recognition, predator avoidance, and social interaction. This review synthesizes key findings from studies on shrimp, crayfish, lobsters, and crabs, the most well-documented taxa in crustacean chemical ecology. Various appendages, including the first and second antennae, mouthparts, and walking legs, are involved in chemosensory detection. Special emphasis is placed on chemical communication in extreme environments such as hydrothermal vents (HVs), with …

Geo-Chemical Fractionations Of Phosphorus In Sediments Of Thuy Trieu Lagoon And Cam Ranh Bay, Vietnam, Phu H. Le, Ngoc H. Pham, Dung T. Le, Tuan Linh T. Vo, Binh V. Tran, The V. Ho

Journal of Marine Science and Technology–Taiwan

The geochemical fractions of phosphorus (P) and its bioavailability in sediments of Thuy Trieu Lagoon and Cam Ranh Bay were investigated. Twenty-four surface sediment samples were collected in the dry season (Jun 2024) and the rainy season (Oct 2024). A sequential extraction procedure was applied to identify the phosphorus (P) fractions in sediments, including Exchangeable P (Ex-P), iron-bound P (Fe-P), aluminum-bound P (Al-P), calcium-bound P (Ca-P), and residual P (Res-P). Total P (TP) ranged from 214.9 to 2365.2 µg.g^-1, and the Ca-P fraction was the dominant chemical form in sediments. Based on the results of Pearson correlation and …

Beyond Basic Needs : Exploring The Antecedents And Outcomes Of Seafarers’ Well-Being, Chian Liou, Cheng Kuo Sung, Kimberly Hsiu-Chin Lee, Jiunn Liang Guo

Journal of Marine Science and Technology–Taiwan

Given the importance of seafarers’ mental health and the limited literature on this topic, this study aims to explore the causes and consequences of seafarers’ well-being. A questionnaire survey was conducted, and the data were analyzed using structural equation modeling and hierarchical regression analysis. Consistent with the predictions of the happy and productive worker thesis, this study found that the more satisfied the seafarers are with the shipping company’s seafarer policy, the higher their well-being tends to be, leading to a more positive work attitude. Interestingly, the study found that a company effect is significantly present in this correlation; that …

Deep Learning-Based Model For Automated Prediction Of Coastal Changes: A Robust Approach To Environmental Forecasting, Tsair-Fwu Lee, Chu-Ho Chang, Chin-Shiuh Shieh, Chih-Hsien Wu, Jen-Chung Shao, Chien-Liang Chiu

Journal of Marine Science and Technology–Taiwan

The coastline stands as a critical domain encompassing industry and the environment. The escalating global warming, leading to elevated sea levels and intensified wave-current interactions, has given rise to substantial coastal erosion. This predicament, in conjunction with excessive human development and Taiwan's coastal areas' extreme climatic impact, accentuates the perceptibility of coastal beach alterations. As a result, coastal erosion has emerged as a pressing issue necessitating resolution. Traditional methodologies for assessing coastline changes have conventionally relied on manual measurements. However, owing to the fluctuating distance of coastlines, influenced by tidal patterns, extended measurement processes over several months are susceptible to …

Model Performance For Predicting Trends And Analyzing The Impacts Of Sea Surface Temperature Changes In The Gulf Of Thailand, Tanatpong Udomchaipitak, Nathaphon Boonnam

Journal of Marine Science and Technology–Taiwan

This study focuses on assessing and improving the predictive performance of sea surface temperature (SST) in the Gulf of Thailand under unique environmental challenges. Data from the Hybrid Coordinate Ocean Model (HYCOM) were utilized, covering the period from July 1994 to June 2024 at depths ranging from 0 to 30 meters. After cleaning the data using the Interquartile Range (IQR) method, the processed dataset was tested using four models: Recurrent Neural Network (RNN) architectures, including Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), as well as Convolutional Neural Networks (CNNs). Model performance was enhanced by tuning the parameters over …

Explorations Of Dna-Single-Walled Carbon Nanotube Interactions To Develop Multiplexed Molecularly Specific Biosensors For Inflammation, Amelia K. Ryan

Dissertations and Theses

Inflammatory cytokines such as interleukin-6 (IL-6) and interleukin-12 (IL-12) are central regulators of immune signaling and key biomarkers of disease, yet existing assays for their detection remain slow, invasive, and lack multiplexing ability. This dissertation advances the development of single-walled carbon nanotube (SWCNT) optical nanosensors capable of real-time, multiplexed, and molecularly specific cytokine detection through innovative use of single-stranded DNA (ssDNA) interfaces.

First, an IL-6-specific DNA aptamer was employed as both a dispersing agent and recognition probe for SWCNT fluorescence sensing. Sequence modifications, including anchor domains, truncations, and thermally induced refolding, were systematically tested to optimize sensitivity and selectivity. The …

Requirements And C&Dh Design, Space Dynamics Laboratory

Space Dynamics Laboratory Publications

• What is it?
• Processor Selection
• CDH Hardware
• OS Selection
• Memory - Radiation
• Memory - Radiation Mitigation
• Memory - Partitions
• Memory - File System
• System Startup
• Startup Stages
• Software Start-up
• Serial Protocol
• I2C / One Wire Communication Tips
• Fault Handling: Watchdog Timer
• CDH Watchdog (Simple)
• CDH Watchdog (Use Case)
• Watchdog Timer Tips
• Synchronizing and Managing Time

Atmospheric Waves Experiment (Awe) Mission Overview, Pedro Sevilla

Space Dynamics Laboratory Publications

The AWE instrument images atmospheric gravity waves from the ISS, quantifying energy and momentum fluxes into the ionosphere-thermosphere system to better understand how tropospheric weather influences space weather

Fairness-Aware And Culturally Adaptive Machine Learning For Predicting Adolescent Substance Use, Stephanie Nworgu

Senior Honors Theses and Projects

Early initiation of substance use during adolescence poses significant risks to long-term health, educational attainment, and social outcomes, making early identification a critical public health priority. Machine learning models have increasingly been used to predict substance use risk; however, many such models do not explicitly examine whether predictive performance differs across demographic groups. This senior project examines the fairness of logistic regression models used to predict first-time alcohol use among adolescents. Using nationally representative survey data from the Youth Risk Behavior Surveillance System (YRBSS), pooled across the 2017, 2019, 2021, and 2023 survey cycles, this study develops logistic regression–based predictive …

Sickle-Cell Genotyping Cost Analysis In Amua And R, Nicholas P. Haley

Senior Honors Theses and Projects

Sickle cell disease (SCD) is a prevalent genetic disorder in the United States, with a significant economic burden due to the high costs of care, especially from chronic red blood cell (RBC) transfusions. These transfusions carry risks such as alloimmunization, which can lead to complications like delayed hemolytic transfusion reactions (DHTRs), further increasing healthcare costs in addition to increasing suGering. This study aims to aid in the evaluation of cost-eGective strategies for SCD management using Markov models, currently within TreeAge Pro software, which is proprietary. A decision model was adapted from the Kacker et al. (2013) study, which analyzed the …

The Role Of Leptin In The Regulation Of The Soluble Amyloid Precursor Protein Alpha (Sappa) Levels In Non-Small Cell Lunch Cancer (Nsclc) Cell Media, Benjamin Haddad

Senior Honors Theses and Projects

We previously found that the levels of soluble amyloid precursor protein α (sAPPα) are partly regulated by acetylcholinesterase (AChE) in human non-small cell lung cancer cell lines A549 (p53 wild-type) and H1299 (p53-null). In this study, we hypothesize that sAPPα is partly regulated by leptin, a hormone classically recognized for its anorexigenic role in appetite regulation— yet recently shown to play a role in cancer cell signaling. It was observed that cells treated with leptin exhibited greater concentrations of sAPPα and lower concentrations of Aβ40/42 in the media compared to those of cells left untreated. An opposite effect was observed …

A Wall Of Smoke: Understanding The Drivers Of The June 2023 Canadian Wildfire Smoke Event For New York City, Gregory S. Randazzo

Dissertations and Theses

The 2023 Canadian wildfire season was notable for its extent and the dense smoke it produced. Motivated by the resulting air quality impacts in the New York City region, we explore how the total particulate matter output from the Quebec fires influenced PM2.5 concentrations downstream in New York City. Using injection height data from the Regional Advanced Baseline Imager + VIIRS Emissions dataset, we relate the tropospheric injection heights of the fires with the broader synoptic context and surface PM2.5 concentrations. Using data from the NYS Mesonet Profiler Network, radiosondes, and ERA5 reanalysis, we document the connection between an anomalous …

It’S Time To Stop Calling People "Stakeholders", Bethann Garramon Merkle, Evelyn Valdez-Ward, Priya Shukla, Skylar R. Bayer

Human–Wildlife Interactions

Although the term “stakeholder” has been widely used in science communication, recent expansion in the discourse around the negative connotations of the term necessitate that scientists and practitioners cease using the term. We discuss why this shift is necessary, how it affects our own praxis, and suggest resources for working through more respectful and just language. Looking to the science communication literature can help recalibrate terminology in positive ways.

Cost-Effective Strategies For Feral Swine Control: Exploring Trapping Equipment Cooperatives, Phil Kenkel, Riza Radmehr, Rodney Holcomb, Mckenzie Boyce

Human–Wildlife Interactions

Feral swine (Sus scrofa) in the United States have become a growing concern, with a population of ≥6 million and causing annual damages of ≥$1.5 billion USD. Because of their high reproductive capacity, effective control methods are crucial to reducing or slowing their population growth. While remotely monitored and triggered traps have proven to be an effective control strategy, the cost of sophisticated trapping equipment, which can cost ≥$7,000 USD, is often cost prohibitive for many landowners. Despite the pressing need to address the challenge of making effective feral swine control methods more affordable, there are few studies …

Precision Haptics For Rehabilitation: Quantifying Directional Bias And Force Threshold Effects On Motor Learning, Conor J. Nolan

UNF Graduate Theses and Dissertations

Hand rehabilitation represents a critical challenge in modern physical therapy, with significant implications for patients' quality of life and functional independence. Despite technological advancements across healthcare, traditional hand assessment methods often rely on subjective measures or lack task-specific biomechanical assessment capabilities. This thesis investigates the effects of haptic force feedback, handedness, and rotation direction on circle-tracing task completion using a within-subjects factorial design with 20 university participants examining varying resistance levels (0.0N, 0.5N, 1.2N) across different movement configurations using a 3D Systems Touch X haptic device with 0.023mm precision. Results demonstrate that moderate haptic force (0.5N) significantly enhanced spatial accuracy …

Label Correlated Contrastive Learning For Medical Report Generation, Xinyao Liu, Junchang Xin, Bing Tian Dai, Qi Shen, Zhihong Huang, Zhiqiong Wang

Research Collection School Of Computing and Information Systems

Background and Objective: Automatic generation of medical reports reduces both the burden on radiologists and the possibility of errors due to the inexperience of radiologists. The model that utilizes attention mechanism and contrastive learning can generate medical reports by capturing both general and specific semantics. However, existing contrastive learning methods ignore the specificity of medical data, that is, a patient may suffer from multiple diseases at the same time. This means that the lack of fine-grained relationships for contrastive learning will lead to the problem of insufficient specificity. Methods: To address the above problem, a label correlated contrastive learning method …

Bayesian Networks For Safety-Critical Systems, Joseph Mietkiewicz

Theses

This thesis addresses a operational challenge in modern industrial operations: the increasing complexity of systems and the consequent cognitive burden on operators. As industrial technologies advance, the human-computer interface has become the primary conduit for information flow, playing a pivotal role in operational decision-making. However, the proliferation of data often leads to information overload, potentially compromising rather than enhancing operator performance. This research explores an approach to this pressing issue through the application of Bayesian networks as decision support systems in safety- critical scenarios. Our study employs a multi-faceted approach, combining theoretical modeling with empirical testing. Through collaboration with industry …

Gamified Mhealth System For Evaluating Upper Limb Motor Performance In Children: Cross-Sectional Feasibility Study, Md Raihan Mia, Sheikh Iqbal Ahamed, Samuel Nemanich

Computer Science Faculty Research and Publications

Background: Approximately 17% of children in the United States have been diagnosed with a developmental or neurological disorder that affects upper limb (UL) movements needed for completing activities of daily living. Gold-standard laboratory assessments of the UL are objective and precise but may not be portable, while clinical assessments can be time-intensive. We developed MoEvGame, a mobile health (mHealth) gamification software system for the iPad, as a potential advanced technology to assess UL motor functions.

Objective: This feasibility study examines whether MoEvGame can assess children’s whole-limb movement, fine motor skills, manual dexterity, and bimanual coordination. The specific aims were to …

Investigating The Temperature Effects On Aedes Aegypti And Dengue Virus In Central Argentina: Perspectives From Mathematical Modeling, Morgan H. Jackson

Theses and Dissertations

Dengue virus (DENV) causes over 390 million infections and around 40,000 deaths worldwide each year. DENV is primarily transmitted by the mosquito Aedes aegypti, and both the life cycle of these mosquitoes and DENV transmission are significantly impacted by temperature. In the temperate region of Central Argentina, where dengue outbreaks first began in 2009, outbreaks only occur following new introductions of DENV from other regions. Due to the relationships between temperature and DENV and temperature and Ae. aegypti, the risk of an outbreak changes throughout the year. Here, we develop and analyze mathematical models for both mosquito population dynamics and …

Substrate Preference And Foraging Behavior Of Two Declining Warblers In Appalachian Shrublands, Samantha Fishman

Theses and Dissertations

Abstract Shrubland and early successional habitats (ESH) support a diversity of wildlife, including many declining songbirds. However, nonnative shrubs increasingly dominate these habitats, potentially altering habitat quality by influencing prey availability. Habitat quality can be assessed by observing foraging behaviors of songbirds and identifying preferred and avoided substrates as well as testing the predictions of optimal foraging theory; specifically that birds will maximize their energy gain relative to the costs. We examined foraging behaviors of Golden-winged Warblers (Vermivora chrysoptera; GWWA) and Chestnut-sided Warblers (Setophaga pensylvanica; CSWA) in ESH on private lands in Virginia with varying amounts …

Optimal Data Splitting Methods, Sujay Mudalgi

Theses and Dissertations

In predictive modeling, effective data splitting is crucial for creating statistically representative training and validation sets. The state-of-the-art data splitting methods are based on minimizing the energy distance between the split subsets. However, there are a number of limitations in the existing methods, which this dissertation aims to address. First, the existing methods were computationally inefficient. Thus, Chapter 2 proposes a method to scale up these approaches for big data. Here, we introduce scalable Twinning (s-Twinning), which significantly improves the execution speed of data splitting without sacrificing accuracy. Second, the existing methods did not consider the predictive relationship in the …

Machine Learning Models Leveraging Patient-Similarity And Clinical Temporality For Disease Prognoses, Ahmad F. Al Musawi

Theses and Dissertations

Electronic Health Records (EHRs) constitute a comprehensive and high-dimensional repository of clinical data, encompassing a wide array of patient-level information such as diagnoses, procedures, medications, laboratory results, and unstructured clinical narratives. These data hold immense potential for advancing predictive modeling in healthcare, including tasks such as disease progression modeling, hospital readmission prediction, and length of stay (LoS) estimation. However, the intrinsic complexity of EHR data—manifested in its heterogeneity, sparsity, and temporal dynamics—poses significant analytical challenges that limit the generalizability and interpretability of conventional machine learning models. Recent methodological advancements in deep learning and graph-based learning, particularly Graph Neural Networks (GNNs), …

Establishing A Conventional Linac-Based Electron Flash Beam, Justin Defrancisco

Theses and Dissertations

Problems: A rediscovered radiotherapy technique, FLASH, involves increasing the dose rate to >40 Gy/s. For a given dose, FLASH is shown to decrease the normal tissue complication probability without affecting the tumor control probability. More preclinical studies are necessary to confirm and enable these desirable properties on humans. Current preclinical investigations have diverse constraints, requiring FLASH apparatuses with flexible parameters and accurate control. However, there are limited FLASH platforms available, the existing ones are costly. Our institution is not in possession of any such infrastructure. Even if available, dosimetry and beam control in FLASH are extremely lacking. There is …

Insights Into Factors Influencing Radical Coupling Chemistry Of Monolignols During Lignification And Induced Changes In Plant Secondary Metabolism, Rachel Poornima Sutherland

Theses and Dissertations--Chemistry

Lignin is a complex aromatic biopolymer and an important constituent in plant cell walls. The process of lignin biosynthesis, known as lignification, is poorly understood and challenging to study but has important implications in a variety of fields including sustainable energy, bioengineering, and materials science and is therefore of interest to pursue. In the final stage of lignification, H-, G-, and S-monolignols are oxidized by laccase and peroxidase enzymes to generate radical species that couple to form dimers and further oligomeric species to ultimately produce the lignin polymer. Biomimetic lignin model systems utilize in vitro oxidative coupling reactions as an …

Characterization Of A Large-Scale Electrohydrodynamic Vortex Confinement Flow For Particle Agglomeration, Sanjay Dangi

Graduate Research Theses & Dissertations

With industrialization and the increasing use of microplastics and nanoparticle-based products, the concentration of fine particulate matter (PM2.5) in the biosphere has increased due to the disposal of manufacturing waste and expired parts. If inhaled, PM2.5 can have detrimental health effects, as these particles can travel deep into the lungs and even penetrate blood vessels. Conventional fabric filters used for indoor air quality control have drawbacks, including the need for periodic filter replacement and a high-pressure drop across the filter over time, which leads to increased power consumption. In power plants, electrostatic precipitators (ESPs) are primarily used to collect fly …

Climate Migration And Urban Survival: Evidence From Chittagong’S Slums, Mohammad Nur Nobi

Graduate Research Theses & Dissertations

This study examines the impact of climate change on rural-to-urban migration in Chittagong, Bangladesh. Based on a primary survey of 400 respondents across 35 slums in the country's second-largest city, the analysis employs two estimation methods: a multinomial logit model to assess the influence of climate-related factors on migration decisions, and a logit model to evaluate the impact of migration on the living conditions of migrants. The results show that individuals involved in ‘agriculture and daily labor’ are most likely to migrate. Compared to the base category (‘Other Reasons’) for migration, the odds ratios for ‘floods’, ‘droughts’, and ‘better job …