Digital Commons Network^™

Enhanced Carbon Burial In Seagrass Meadows Under Ocean Acidification Revealed By Carbon Dioxide Vents, Theodor Kindeberg, Teixidó, Steeve Comeau, Jean Pierre Gattuso, Beat Gasser, Alice Mirasole, Samir Alliouane, Ioannis Kalaitzakis, Denisa Berbece, Christopher Cornwall, Pere Masque

Research outputs 2022 to 2026

Seagrass meadows are natural carbon sinks, yet the effect of ocean acidification on their carbon burial capacity remains poorly understood. Here we investigated natural carbon dioxide vents in Ischia, Italy to assess how seawater pH influences carbon burial in an area dominated by the seagrass Posidonia oceanica. Organic carbon burial rates (mean ± standard error) between 1954 – 2021 were low under ambient conditions (1.5 ± 0.5 g m-2 yr-1) but increased sharply under acidified conditions (7 ± 1 g m-2 yr-1), reaching sevenfold higher values under extreme acidification (10 ± 3 g m-2 yr-1). Stable isotopes suggest that these …

The Downstream Effect Of Gender Bias On Academic Performance And Career Aspirations Amongst Female Students In Stem Via Gender-Professional Identity Integration (G-Pii), Chi-Ying Cheng, Shuna Shiann Khoo, Shih-Fen Cheng, Yeow Leong Lee, Vandana Ramachandra Rao

Research Collection School of Social Sciences

Background Gender imbalance in STEM, characterized by a significant underrepresentation of women, remains a significant challenge. Although gender bias is a well-known contributor to women’s attrition from STEM, the psychological mechanisms linking gender bias to departure are less well understood. Our research investigates early antecedents of attrition and the psychological processes that precede leaving the STEM pathway in tertiary education. Drawing upon identity integration research, we propose that perceived gender bias exerts undermines female STEM students’ academic performance and career aspirations by reducing their Gender-Professional Identity Integration (G-PII), a construct that captures individual differences in the perceived compatibility between a …

Psychometric Evaluation And Cognitive Correlates Of The Tactile Mental Cutting Test: Investigating Reliability, Validity, Gender Differences In Spatial Ability, Executive Function And Social Emotional Competence Among Native American Elementary Students, Sujata Basnet

All Graduate Theses and Dissertations, Fall 2023 to Present

Spatial ability-the ability to understand, visualize, and mentally manipulate shapes and objects-is important for learning in science, technology, engineering, and mathematics (STEM). However, many traditional spatial ability tests rely heavily on drawings and other visual representations and have often been developed and evaluated with populations that do not adequately represent culturally diverse students. As a result, there is a need for assessment approaches that are developmentally appropriate, engaging, and potentially more inclusive for young learners. The Tactile Mental Cutting Test (TMCT) provides one such approach by allowing students to explore three-dimensional objects through touch and physical manipulation while solving spatial …

Evaluating The Transformation Of Land Cover, Land Surface Temperature, And Urban Heat Island In Sylhet Division Through Geospatial Analysis, Md Fazle Rabbi Joy, Md Abdur Rahim, Md Mahfuzar Rahman, Sumiaya Amin Preota, Mohammed Mahathee Hossain

School of Earth, Environmental, & Marine Sciences Faculty Publications

Rapid and unplanned urbanization has significantly transformed land use/land cover (LULC), contributing to increased land surface temperature (LST) and the emergence of urban heat islands (UHIs), especially in ecologically fragile regions. This study focuses on the Sylhet Division of Bangladesh, assessing LULC changes, LST dynamics, and UHI expansion from 1994 to 2024 using Landsat satellite imagery, normalized difference vegetation index (NDVI), normalized difference water index (NDWI) indices, and field-based LST validation. Unsupervised classification reveals a 191.75% increase in settlement areas and a 25.65% loss in forest cover. Correspondingly, the highest LST zones (> 30 °C) were absent in 1994 but …

The Role Of Corporate Sustainability Goals In Shaping Organizational Intentions And Adoption Of Green Technologies In Small- And Medium-Sized Enterprises, Syed Zamberi Ahmad, Abdul Rahim Abu Bakar, Imane Belyamani, Manar Fawzi Bani Mfarrej

All Works

This study investigates green technology adoption (GTA) among small and medium-sized enterprises (SMEs) in the United Arab Emirates (UAE), focusing on the influence of corporate sustainability goals (CSG) and sustainability motivation (SM). Utilizing institutional theory, the theory of planned behavior (TPB), and resource-based view (RBV), the research highlights how SMEs integrate environmental, social, governance (ESG) and economic considerations into their CSG to enhance GTA. Addressing a gap in prior research that has largely emphasized external drivers of adoption while underexploring internal organizational mechanisms, the study conceptualizes CSG as strategic intent and models SM as a second-order construct . Based on …

A Journey To The Midwest For Migrant Farmwork: Women's Testimonies Examining Their Lived Experiences Using Autoethnography And Plática Research Methodologies, Yesenia G. Alcalá

Theses & Dissertations

A JOURNEY TO THE MIDWEST FOR MIGRANT FARMWORK: WOMEN’S TESTIMONIES EXAMINING THEIR LIVED EXPERIENCES USING AUTOETHNOGRAPHY AND PLÁTICA

RESEARCH METHODOLOGIES

Yesenia Garza Alcalá, Master of Business Administration

University of the Incarnate Word 2026

The purpose of my research was to share the stories of five women who experienced a yearly migratory routine from Del Rio, Texas, to work in farms and factories in the Midwest, and how that annual journey shaped and educated us. The women are four of my older sisters and me, all of whom traveled and worked in the Princeville, Illinois, migrant camp, where we experienced the …

From Post-Hoc To Pre-Assessment Evaluation: Llms As Collaborative Partners For Simulating Student Performance, Siaw Ling Lo, Ping Fan Ke, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Ensuring the quality of multiple-choice questions (MCQs) remains a complex challenge in higher education, as traditional post-hoc psychometric analyses often identify flaws only after students have been negatively impacted. While Large Language Models (LLMs) offer potential for simulating student performance to validate items before delivery, they are frequently hindered by a “high-accuracy bias” that prevents larger models from realistically mimicking student errors. This paper proposes the Triadic Pedagogical Fit (TPF) framework, which triangulates Model Scale, Task Complexity via Revised Bloom’s Taxonomy, and Instructional Persona to optimize pre-assessment evaluation. Through two studies, we demonstrate that while Mid-scale (12B) models effectively mirror …

Long Range Battery-Free Wireless Power Transfer Testbed For Underground Mines Iot And Lpwan Devices, Anabi Hilary Kelechi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

Underground mines are susceptible to occasional roof falls and cave-ins, temporarily destroying the existing wireless communications and telemetry infrastructure. During this temporary outage, intermittent provision of electrical energy wirelessly to the already deployed low-power wireless area networks (LPWAN) and Internet of Things (IoT) devices assumes a fundamental requirement. In this article, we propose and design a long-range far-field radio frequency (RF) wireless power transfer (WPT) testbed to power LPWAN and IoT devices at 35 m in an underground mines facility. Class AB external power amplifier (PA) was introduced to achieve a long-distance RF WPT, in the 880 MHz band. Thus, …

A Critical Review Of Pharmaceutical Pollutants In Soil And Air: Ecotoxicological Impacts On Animal, Plant And Microbial Communities - Health Hazards And Waste Management, Md Faisal Amin, Md. Saydur Rahman

School of Integrative Biological & Chemical Sciences Faculty Publications

Pharmaceutical contamination in soil and air has become a critical environmental concern due to its widespread sources, complex behavior, and long-lasting ecological impacts. This review comprehensively explores the presence, fate, and effects of pharmaceutical compounds in soil, highlighting their entry routes, environmental persistence, and biological consequences. Pharmaceuticals infiltrate terrestrial and aquatic environments through various pathways, including agricultural application, pharmaceutical manufacturing waste, sewage sludge, hospital and household discharges, irrigation with contaminated water, and atmospheric deposition. A wide range of drug classes, such as antibiotics, analgesics, non-steroidal anti-inflammatory drugs, antidepressants, anticancer drugs, and hormones, have been identified in both soil and air …

Eccentric Exercise: Muscle Damage To The New Normal, Kazunori Nosaka

Research outputs 2022 to 2026

No abstract provided.

Recent Canadian Immigration Reforms And Their Consequences For Migrant Children And Families’ Health: The “Globalization Of Indifference”?, Rachel Kronick, Marianne Côté-Olijnyk, Efrat Arbel

All Faculty Publications

Despite its reputation as a welcoming nation to refugees, Canada has enforced increasing restrictions on asylum, even in the face of evidence from the United States and around the world of the profound harm such restrictions cause. In this paper, we outline recent Canadian legal and policy reforms and their potential impacts on refugee health equity. Following Farmer's approach of ethnographic case narratives that aim to portray how current policy and legislation are embodied and felt in migrants' lives, we document avoidable harms to migrant children and families. Our data come from qualitative research with inadmissible asylum seekers and narrative …

Correctional Officer Suicide: A Theory-Driven Investigation Of Acquired Capability And Suicide Behavior, Abigail R. Andersen

All-Inclusive List of Electronic Theses and Dissertations

A growing body of research suggests that correctional officers (COs) die by suicide at a significantly higher rate compared to the general population and some other public safety personnel. Despite what is known about this phenomenon, an understanding of the risk factors driving the high rate of suicide among this population remains unclear. Specifically, little attention has been paid to specific risk factors for suicide among this population and there is an overall absence of theory-driven research investigating CO suicide. The present study sought to address the gap in this area of research by investigating potential risk factors for suicide …

Harnessing Digital Twin (Dt) Technology For Food Security And Climate Resilience In Sub-Saharan Africa (Ssa), Henri E.Z. Tonnang, Francis Chianu, Siyabusa Mkuhlani, Francis Muthoni, John Michael Humphries Choptiany, Franck B.N. Tonle, Bonoukpoe M. Sokame, Mercy Lung’Aho

All Peer-Reviewed Publications

Sub-Saharan Africa (SSA) faces chronic food insecurity despite possessing approximately 60% of the world’s uncultivated arable land. Field trials generate evidence but are costly and insufficiently scaled to address accelerating climate and demographic pressures. Digital twin (DT) technology, defined as the continuous, bidirectional virtual replication of physical systems using real-time data, supports monitoring, modelling, and optimisation of agrifood systems. To our knowledge, however, no published synthesis has examined DT agriculture research through the lens of SSA food systems or smallholder farming realities. A PRISMA-compliant systematic review was conducted across bibliographic databases using a pre-defined Boolean search and adapted PICOS eligibility …

Beyond Legacy Indices: A Critical Review Of The Modified Nemerow, Mean Enrichment Quotient, And Aggregated Multivariate Environmental Risk (Amer) Indices For Heavy Metal Pollution In Sediments, Md Shahnul Islam, Anjuman Ara

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Background: Heavy metal pollution in sediments poses persistent ecological risks due to metal toxicity, bioaccumulation, and potential for remobilization. Legacy indices have been widely used for decades but suffer from fundamental flaws, including arbitrary background dependence, lack of grain-size normalization, and poor ecological relevance.

Objective: This review critically evaluates three emerging sediment pollution indices, the Modified Nemerow, Mean Enrichment Quotient (MEQ), and Aggregated Multivariate Environmental Risk (AMER) index, to assess their methodological advances and potential to replace legacy approaches.

Methods: A structured literature search was conducted in Web of Science, Scopus, and Google Scholar (2010–2026). Using an adapted Birch framework, …

Characterization Of Regulation Of Ace2 And Morphogenesis (Ram) Pathway Components In Aspergillus Fumigatus, Devi Naga Jyothi Bale

Theses and Dissertations (ETD)

Aspergillus fumigatus CotA is a conserved protein kinase and predicted orthologue of Cbk1, a terminal kinase of the Regulation of Ace2 and Morphogenesis (RAM) network. In our previous study, disruption of CotA resulted in carbon source dependent invasive growth with the mutant exhibiting preferential growth on glucose but severely impaired growth on alternate carbon sources. This pathway in other fungi has been implicated in the regulation of morphogenesis, stress responses, and virulence, but this study is the first one to characterize it in the pathogenic filamentous fungus.  In yeast, the RAM network includes the CotA ortholog, Cbk1, and associated proteins, …

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

A Data-Driven Koopman Framework For Station-Keeping On Near Rectilinear Halo Orbit, Anusha Sharma Malladi

Theses and Dissertations

Cislunar missions have gained significant attention in recent decades, motivating the need for efficient modeling and reliable control. In this work a Koopman operator based framework is developed for approximating the error dynamics around a reference Near Rectilinear Halo Orbit (NRHO) in the Earth-Moon Circular Restricted Three-Body Problem (CR3BP). A decoder free neural network is used to learn a lifted linear representation of the nonlinear CR3BP dynamics and a residual based approach is used to identify the corresponding control input matrix. The model is then implemented in a receding-horizon target point controller and compared with uncontrolled propagation and a State …

Comparative Performance Of Physiological Vital-Sign Forecasting Under Random And Patient-Wise Splitting Using Deep Learning, Lavanya Vasavi Chittem Reddy

Theses and Dissertations

Physiological vital-sign forecasting estimates future measurements based on recent temporal patterns and can support analysis of continuously recorded monitoring data. This study comparatively evaluated deep feedforward, recurrent, bidirectional recurrent, long short-term memory, and bidirectional long short-term memory architectures for one-step-ahead forecasting of peripheral oxygen saturation, heart rate, and pulse rate. Each model received consecutive observations of peripheral oxygen saturation, heart rate, pulse rate, respiratory rate, and age, while separate single-output models predicted the next value of the selected target.

Random and patient-wise data splitting were compared using identical input definitions, preprocessing procedures, model architectures, and training hyperparameters. The strongest architecture …

Developing Imitation Learning Policies By Exploring Diffusion Framework For Quadcopters, Likith Swamireddy

Theses and Dissertations

Imitation learning offers a promising approach in developing near-optimal onboard policies for nonlinear systems, by learning from computationally expensive trajectory planners during offline training. Existing State-of-the-art methods commonly learn deterministic mappings from observations to actions by training fast neural networks to mimic the expert demonstrations, which can limit their ability to capture the action distribution, when the policy is trained on multiple possible expert commands to reach the same target, and this may lead to unsafe scenarios in the obstacle environments. To address these challenges, this study explores Diffusion Models (DMs) as a feedback controller for quadcopters that learns the …

In-Process Large Language Model Requesting Through Knowledge Graphs For Interfacing With Manufacturing Digital Twins, Reiki Tanaya Karuka, Vinh Nguyen

Michigan Tech Publications

Digital twins (DTs) have potential to improve manufacturing processes by providing in-process monitoring and reducing trial-and-error while improving process prediction and performance. However, identifying anomalies or defects in a DT environment remains a very time intensive process that requires multidisciplinary expertise and significant manual effort in analyzing the system. Large language models (LLMs) offer potential capabilities to interpret system-level information and support user-driven querying, but their effectiveness is limited by hallucinations when reasoning over large and dynamic manufacturing datasets inherent to process monitoring DTs. Knowledge graphs (KGs) have emerged as efficient tools in the industrial domain to efficiently represent data …

The Future Of Nature-Based Recreation In Warming Tropical Cities, Perrine Hamel, Emma E. Ramsay, Shawnda A. Morrison, Su Li Heng, Winston T. L. Chow, Beatrice H. Ho, Pearl Min Sze Tan, Moshe Mandelmilch, Lancy Sim, Jason Kai Wei Lee

Research Collection College of Integrative Studies

Nature-based recreation promotes health in tropical cities but is increasingly threatened by rising heat. This review presents recent evidence on the issue of humid heat stress and outdoor recreation in tropical cities and outlines key adaptation strategies – addressing hazard, exposure, and vulnerability – to enable ‘heat-smart’ nature-based activities. Despite existing solutions, critical research gaps remain, especially in integrating social, physiological, and technological insights to better address humid heat stress in tropical urban environments.

A Systematic Review Of Audio Deepfake Detection Techniques For Digital Investigation, Mahra Alnaqbi, Richard Adeyemi Ikuesan

All Works

Deepfake technology has been driven by advanced machine learning and revolutionized multimedia creation by synthesizing hyper-realistic content. It includes images, videos, and audio. While its creative applications in entertainment and accessibility are significant, the technology also poses critical risks, especially in fraud, disinformation, and identity theft. Audio deepfakes are a subset of this phenomenon that replicate human voices with enhanced precision, mimicking tone, accent, and subtle vocal nuances. This has raised concerns in security-sensitive domains like voice authentication and forensic investigations. This systematic literature review (SLR) adopts PRISMA guidelines to explore the state-of-the-art in audio deepfake detection. It examines existing …

Image And Metadata-Driven Personality Inference For Career Recommendation: A Social Media-Based Ai Framework For Adolescents, Heba Ismail, Maryam Alhefeiti, Ashraf Khalil

All Works

This study presents a novel AI-based framework that leverages Instagram image and metadata analysis to infer Big Five personality traits and deliver personalized career recommendations for high school students in the UAE. Addressing the limitations of traditional recommender systems that rely on self-reported questionnaires or text, the proposed approach uses multimodal visual features—including profile metrics, HSV color patterns, semantic image labels, and texture analysis—to enable a non-intrusive, scalable personalization method. A pilot study involving data from 30 student accounts served as a proof of concept. Correlation analysis identified profile and HSV features as the most predictive, and four machine learning …

Fig-Gan: Fundus Image Generation Via Deep Learning Based Generative Adversarial Network For Amd Disease Diagnosis, Kailasa Thrishul, Ahed Abugabah, Amina Salhi, Manel Ayadi, Mohamed M. Sithik, D. Jayaprakash, A. Ahilan

All Works

Globally, age-related macular degeneration (AMD) remains a main cause of irreversible vision loss. Recently, deep learning models have primarily focused on classifying fundus images for early detection of AMD progression. However, existing models rarely address the generation of future progression-aware fundus images, particularly when complete real longitudinal follow-up scans are unavailable. This limitation makes it difficult to track retinal changes over time and highlights the need for generative models capable of producing realistic drusen-level structural variations. To address these issues, a novel deep learning-based FIG-GAN model is to generate synthetic future fundus images from baseline inputs. Multi-Attention U-Net (MAU-Net) is …

A Performance-Optimized V2v Task Offloading Framework For Real-Time Vehicular Communication, Tariq Qayyum, Asadullah Tariq, Ikbal Taleb, Mohamed Adel Serhani, Zouheir Trabelsi

All Works

As vehicular applications become increasingly complex, their computational demands often exceed the capabilities of individual vehicles. Vehicular Edge Computing (VEC) alleviates this limitation by enabling task delegation to nearby edge resources; however, high mobility, dynamic topology, and fluctuating vehicle density make real-time offloading decisions challenging. To address these issues, we propose a performance-optimized Vehicle-to-Vehicle (V2V) task offloading framework for dense and dynamic Vehicular Ad-hoc Networks (VANETs). The framework follows a two-stage design: (i) context-aware edge-node selection based on live topology capture via periodic beaconing, and (ii) cumulative score-based dynamic priority queuing at the selected edge node. The priority score jointly …

Smart Medical System Integrating Clinical Workflows For Robust Skin Cancer Detection Across Heterogeneous Pathologies, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

All Works

Skin cancer is among the most prevalent and life-threatening dermatological diseases worldwide, with melanoma responsible for a substantial proportion of skin cancer–related deaths due to delayed and unreliable diagnosis. Conventional clinical screening based on visual inspection and expert interpretation is inherently subjective and often affected by inter-observer variability, lesion heterogeneity, and imaging artifacts, highlighting the need for accurate and generalizable automated diagnostic systems. This study proposes a novel hybrid deep learning architecture for skin cancer classification that integrates an attention-guided autoencoder with a transformer-inspired global context modeling module, forming a unified and robust representation learning framework. The encoder–decoder structure is …

Temporally Rigorous And Traceable Predictive Maintenance Via Joint Labeler-Model Optimization, Maytha Al-Ali, Ahmad Alharbi

All Works

Predictive maintenance (PdM) is a critical enabler of intelligent asset management in Industry 4.0, yet many existing frameworks remain difficult to operationalize due to methodological fragmentation. Common limitations include sacrificing temporal realism and class granularity for computational expediency, decoupling labeling strategy design from model hyperparameter optimization, and insufficient support for reproducibility and deployment traceability; particularly in rare-failure regimes. To address these challenges, we propose a unified, end-to-end, and fully traceable PdM framework that jointly optimizes labeling and model parameters while enforcing strict temporal fidelity. The proposed pipeline co-optimizes the failure lookahead window () and LightGBM hyperparameters within a single Bayesian …

Computational Studies Of Triplet State Formation In Zinc Dipyrrin Complexes, Reuben Kwabla Adigbli

Electronic Theses and Dissertations

Zinc dipyrromethene complexes are promising earth-abundant photosensitizers due to their strong visible-light absorption and tunable excited states. To rationally design them for photocatalysis and photodynamic therapy, a molecular-level understanding of triplet-state formation is needed, but details of intersystem crossing remain unclear. To study the effect of π-extension, we synthesized an indole-substituted zinc dipyrrin complex: the dipyrromethane ligand was prepared from indole and mesitaldehyde, oxidized to the dipyrromethene, then coordinated with zinc. DFT and TD-DFT calculations determined ground and excited-state geometries and energies in different solvents, modeled absorption spectra, and visualized charge distributions. The results show how solvent polarity shifts energies …

An Assessment Of Accessibility And Affordability Of Inpatient Psychiatric Care In Tennessee, Kailee Havrda

Electronic Theses and Dissertations

Introduction: Access to mental health has seen changes over the past decade, but little research and attention have been given to access to inpatient psychiatric facilities. Inpatient psychiatric care is crucial for patients experiencing mental health emergencies who need immediate access to care. Gaps in spatial accessibility, affordability, and the access and assessment process were identified due to a lack of available information in the field.

Methods: Secondary data from the Tennessee Department of Health were used to assess financial accessibility through payer source charges and patient encounters, as well as through mapping of inpatient psychiatric facilities and conducting drive …

Kindergarten Teachers’ Perceptions Of Instructional Approaches For Teaching Sequencing Concepts: Worksheet, Hands-On, And Beebot-Integrated Lessons, Savannah P. Partin

Electronic Theses and Dissertations

The purpose of this qualitative multiple-case study was to explore kindergarten teachers’ perceptions of three instructional approaches for teaching sequencing concepts: worksheet-based instruction, hands-on manipulative instruction, and BeeBot-integrated instruction. Sequencing is a foundational early literacy skill that supports reading comprehension, story retelling, and understanding the order of events. Although sequencing is commonly taught through traditional instructional methods, limited research has examined how kindergarten teachers perceive the use of educational robotics as a tool for literacy instruction. The study was guided by constructivist theory, sociocultural theory, and developmental systems theory. Participants included six kindergarten teachers from a public elementary school in …