Digital Commons Network^™

Motion Artifacts (Ma) At-Rest In Measured Arterial Pulse Signals: Time-Varying Amplitude In Each Harmonic And Non-Flat Harmonic-Ma Coupled Baseline, Md Mahfuzur Rahman, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Motion artifacts (MA) cause great variability in a measured arterial pulse signal, and treatment of MA solely as a baseline drift (BD) fails to eliminate its effect on the measured signal. This paper presents a study on the effect of MA at rest (< 0.7 Hz) on measured arterial pulse signals using a microfluidic-based tactile sensor. By taking full account of the dynamic behavior of the transmission path from the true pulse signal in an artery to a measured pulse signal at the sensor, the tissue-contact-sensor (TCS) stack, an analytical model of MA in a measured pulse signal is developed. In this model, the TCS stack is treated as a 1DOF system for its dynamic behavior; MA is quantified as the displacement (i.e., BD) and time-varying system parameters (TVSP) of the TCS stack. The mathematical expression of MA in a measured pulse signal reveals that while BD remains as low-frequency additive noise, TVSP causes time-varying harmonics in a measured pulse signal. Further time-frequency analysis (TFA) of measured pulse signals validates the existence of TVSP and, for the first time, reveals its effect on a measured pulse signal: time-varying amplitude in each harmonic and non-flat harmonic-MA-coupled baseline.

Wasting Disease Of A Marine Foundation Species Links Community Interactions To Disease Dynamics, Lillian R. Aoki, Olivia J. Graham, Reyn M. Yoshioka, Rebecca Maher, Lindsay Alma, Eileen E. Hofmann, Colleen A. Burge, Drew Harvell, Maya L. Groner

CCPO Publications

Infectious disease plays a key role in shaping marine communities, including in seagrass meadows, which form biodiverse coastal habitats. Eelgrass (Zostera marina) is the most widespread seagrass species and is susceptible to seagrass wasting disease, caused by the protist Labyrinthula zosterae. As a foundation species, eelgrass strongly influences ecosystem structure, function and services; recent work has begun to explore the links between critical community interactions and seagrass wasting disease. Here, we highlight recent advances about how the eelgrass community regulates and responds to seagrass wasting disease, from the microbiome to herbivores and filter feeders. We further show …

Preparing The Built Environment In Grenada For Future Sea Level Rise And Extreme Precipitation Events, Rocco D. Boyd, Meagan P. Duncan, Alivia D. Markham, Adelle K. Novak, Blaizen B. Bloom, Ashawne Edwards, Jai S. Lewis, Hans-Peter Plag

CCPO Publications

[Introduction] Communities across the globe are being affected by climate change in numerous ways. However, those most often affected, especially by sea level rise, are those small island nations that are pressed for space already; this includes the island of Grenada. Grenada is located in the southern portion of the Caribbean and is bordered by the Caribbean Sea (West) and the Atlantic Ocean (East). The planning and development authority (PDA) has been identified as the main stakeholder involved in this case study, but recommendations will be made to all parties involved to best accomplish our mission.

Key stakeholders were initially …

Towards Dynamic Learner State: Orchestrating Ai Agents And Workplace Performance Via The Model Context Protocol, Mohan Yang, Nolan Lovett, Belle Li, Zhen Hou

Educational Leadership & Workforce Development Faculty Publications

Current learning and development approaches often struggle to capture dynamic individual capabilities, particularly the skills they acquire informally every day on the job. This dynamic creates a significant gap between what traditional models think people know and their actual performance, leading to an incomplete and often outdated understanding of how ready the workforce truly is, which can hinder organizational adaptability in rapidly evolving environments. This paper proposes a novel dynamic learner-state ecosystem—an AI-driven solution designed to bridge this gap. Our approach leverages specialized AI agents, orchestrated via the Model Context Protocol (MCP), to continuously track and evolve an individual’s multi-dimensional …

Automating International Human Rights Adjudication, Veronika Fikfak, Laurence R. Helfer

Faculty Scholarship

International human rights courts and treaty bodies are increasingly turning to automated decision-making (“ADM”) technologies to expedite and enhance their review of individual complaints. These tribunals have yet to consider many of the legal, normative, and practical issues raised by the use of different types of automation technologies for these purposes. This article offers a comprehensive and balanced assessment of the benefits and challenges of introducing ADM into international human rights adjudication. We argue in favor of using ADM to digitize documents and for internal case management purposes and to make straightforward recommendations regarding registration, inadmissibility, and the calculation of …

The Reliability Response To Patent Law’S Ai Challenges, Arti K. Rai

Faculty Scholarship

Pervasive AI use adds newfound importance to longstanding debates over patent timing and reliability. Patent claims on speculative ideas generated by AI, or even the infusion of speculative AI-generated ideas into the public domain, may defeat patent incentives for more careful research. Although challenges that AI use poses for patent validity requirements like human inventorship and nonobviousness have received more attention, reliability is equally important.

Indeed, as this Article argues, the issues are linked. If requirements for inventorship and nonobviousness were adjusted to emphasize reliability, a human role could be preserved, and AI use would not necessarily threaten patents. Currently, …

The Future Of Ai Regulation In Drug Development: A Comparative Analysis, Gabriela Lenarczyk, Timo Minssen, Nicholson Price, Arti Rai

Faculty Scholarship

As artificial intelligence (AI) transforms drug development, regulatory frameworks are evolving to oversee its implementation, particularly at the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA). This paper makes three contributions to understanding emerging regulatory approaches. First, we offer a comparative analysis of how these agencies have responded to AI-driven advances, incorporating new US executive orders and the European Union (EU)’s AI Act. Second, we propose a novel analytical framework to understand regulatory divergence: the FDA’s flexible, dialog-driven model contrasts with the EMA’s structured, risk-tiered approach, reflecting broader institutional and political-economic differences. While the former encourages …

Fortifying Nuclear Security: Cultivating Vigilance Culture Among Personnel For Enhanced Prevention And Response, Sabariah Kader Ibrahim, Sonia Naz

International Journal of Nuclear Security

A vigorous nuclear security culture is crucial in preventing the theft and sabotage of nuclear material. It requires vigilance from all employees because relying solely on closed-circuit television systems and security personnel is insufficient to deter potential threats. Employee attentiveness plays a vital role in recognizing and preventing suspicious activities. However, achieving a strong security culture is challenging because of the lack of incidents in some facilities, leading to employee complacency.

This paper highlights the pivotal role of personnel in the success of nuclear security measures, emphasizing the need for a proactive and vigilant mindset among staff. Through the analysis …

Development Of An Ecg-Based Deep Learning Model For Pediatric Congenital Heart Disease (Chd) Diagnosis, Annbar Mekouar

Selected Full-Text Master Theses 2021-

Congenital heart disease (CHD) stands as the leading congenital anomaly which affects pediatric populations throughout the world. The effectiveness of treatment depends on both early diagnosis and accurate identification but echocardiography requires manual interpretation which proves time-consuming and inconsistent especially when examining pediatric patients with their distinct cardiac systems. The research aims to create a deep learning-based diagnostic framework which uses ECG data to identify coronary artery disease subtypes in pediatric patients. The model uses high-quality datasets from Dr. Ignacio Lugones to extract R-R intervals and QRS durations through convolutional neural networks (CNNs). The system addresses pediatric-specific challenges while enhancing …

A Machine Learning Based Framework For Predicting Drug Cardiotoxicity Using A Combination Of Ecg Biomarkers And Drug Dosage Data, Jamie Wong

Selected Full-Text Master Theses 2021-

Drug-induced cardiotoxicity presents a significant challenge in clinical practice and drug clinical development, particularly with medications that modulate calcium, potassium, and sodium channels that influence cardiac electrophysiology. Clinical practice often relies on QTc prolongation alone as a predictor, which lacks specificity and may lead to excluding other safe therapeutic options. To address this limitation, this study integrates electrocardiogram (ECG) biomarkers with normalized drug dosage data to improve the accuracy of cardiotoxicity risk prediction using machine learning techniques. ECG features, including QT, QRS, RR, and PR intervals, were analyzed alongside normalized dosage data to account for dose-dependent cardiac effects. A physiologically …

Strategic Identification Of Prognostic Biomarkers For Knee Osteoarthritis Via Optimized Regression Techniques, Varun Sri Sai Vemuri

Selected Full-Text Master Theses 2021-

Knee Osteoarthritis (KOA) is a progressive musculoskeletal disease involving cartilage matrix degradation, subchondral bone remodeling, and systemic inflammation, significantly impairing joint function and mobility. Existing KOA prediction models are not designed to account for nonlinear multimodal biomarker interactions or to integrate biochemical and imaging data, thus limiting their clinical utility. The current method for early detection and prediction of KOA disease progression is primarily based on machine learning-based approaches using radiographic imaging data, static feature selection, and deterministic outputs. These machine learning approaches often fail to capture the pathophysiology of KOA disease progression, which involves a complex cascade of processes, …

Multi-Modal Graph Learning For Vision Language Model In General And Medical Domains, Xinyue Hu

Computer Science and Engineering Dissertations - Archive

Multi-modal learning has gained significant attention in deep learning for its ability to integrate and process information from multiple modalities, such as text, images, and videos. By leveraging complementary information from different modalities, it enables a more comprehensive understanding of complex data in various tasks. Simultaneously, graph learning, a prominent paradigm that models structured data as graphs, captures both local and global dependencies, providing a natural framework to represent intricate interactions and contextual relationships. When combined with multi-modal learning, these graph-based approaches have the potential to enhance feature representation and reasoning by effectively fusing heterogeneous data, leading to more robust …

Adverse Childhood Experiences, Depression And Subjective Cognitive Decline By Gender: A Moderated Mediation Analysis, Monique J. Brown, Darlingtina K. Esiaka, Jaya Viswanathan

Behavioral Science Faculty Publications

Studies assessing depression as a mediating factor between adverse childhood experiences (ACEs) and subjective cognitive decline (SCD) are lacking. Therefore, the aims of this study were to: (1) determine the mediating role of depression in the association between ACEs and SCD; and (2) assess the moderating role of gender. Data were obtained from the 2023 Behavioral Risk Factor Surveillance Study (BRFSS) survey (N = 38,600). Crude and adjusted path analyses were used to determine the mediating role of depression between ACEs and SCD. Adjusted analyses controlled for sociodemographic confounders. ACEs were positively associated with depression (B = 0.129, p …

Exploring The Impact Of Generative Ai Chatgpt On Critical Thinking In Higher Education: Passive Ai-Directed Use Or Human-Ai Supported Collaboration?, Nesma Ragab Nasr, Chih-Hsiung Tu, Jennifer Werner, Tonia Bauer, Cherng-Jyh Yen, Laura Sujo-Montes

STEMPS Faculty Publications

Generative AI is weaving into the fabric of many human aspects through its transformative power to mimic human-generated content. It is not a mere technology; it functions as a generative virtual assistant, raising concerns about its impact on cognition and critical thinking. This mixed-methods study investigates how GenAI ChatGPT affects critical thinking across cognitive presence (CP) phases. Forty students from a four-year university in the southwestern United States completed a survey; six provided their ChatGPT scripts, and two engaged in semi-structured interviews. Students’ self-reported survey responses suggested that GenAI ChatGPT improved triggering events (M = 3.60), exploration (M = 3.70), …

The Effects Of Return To Prairie In Barber County, Kansas: A Case Study Using Ndvi And Dendrochronology, Elijah O. Joy

Master's Theses or Doctor of Nursing Practice

This study aims to evaluate the impact of prairie restoration efforts in Barber County, Kansas, with a focus on removal of Eastern Red Cedar. Restoration effectiveness was assessed using remote sensing of satellite scenes via NDVI, density analysis, and dendrochronological methods. The tree density analysis revealed a 66% reduction across the study area and a 99% reduction in the fully restored zones. NDVI analysis from 2010 to 2024 showed higher summer vegetation health and seasonal fluctuations influenced by climate variability and fire events. Dendrochronological data from tree cores reveals growth patterns and establishes a baseline for future dendrochronological chronologies. The …

Leveraging Data Science For Resilience: Improving Trauma-Informed Care Practice For Adverse Childhood Experience With Ai & Data Science Application, Mohmmad Arif Shaik

Master's Theses

Adverse Childhood Experiences (ACEs) have long-lasting effects on physical health, mental well-being, education, and socioeconomic outcomes. Resilient Georgia (RG), a statewide initiative, seeks to address ACEs through trauma-informed care and data-driven strategies. However, challenges in data collection, analysis, and tracking set back the effectiveness of these efforts. This study explores the role of data science and interactive visualization tools in improving outcomes for individuals and communities affected by ACEs. A key focus of this research is the development of a data science management application designed to enhance data collection and improve real-time decision-making. The application features interactive dashboards that allow …

Faithful Narratives From Complex Conceptual Models: Should Modelers Or Large Language Models Simplify Causal Maps, Tyler J. Gandee, Philippe J. Giabbanelli

VMASC Publications

(1) Background: Comprehensive conceptual models can result in complex artifacts, consisting of many concepts that interact through multiple mechanisms. This complexity can be acceptable and even expected when generating rich models, for instance to support ensuing analyses that find central concepts or decompose models into parts that can be managed by different actors. However, complexity can become a barrier when the conceptual model is used directly by individuals. A ‘transparent’ model can support learning among stakeholders (e.g., in group model building) and it can motivate the adoption of specific interventions (i.e., using a model as evidence base). Although advances in …

Evaluating The Chemical Reactivity Of Wildfire-Derived Dissolved Organic Molecules: Glutathione Binding Through Kendrick Mass Defect Analysis, Hannah M. Hamontree, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

The emerging risks to organisms of pyrogenic-derived dissolved organic matter (PyDOM) from forest fires are of concern due to its toxic and mutagenic potential (e.g., pro-oxidative responses in fauna through the depletion of glutathione, a nitrogen- and sulfur-containing tripeptide found in cells). This study simulates this phenomenon in a laboratory setting by identifying bonding between reduced l-glutathione and organic molecules in leachates from environmentally weathered biomass samples (charred and uncharred) using Kendrick Mass Defect (KMD) analysis from formula lists obtained from negative-mode electrospray ionization-Fourier transform-ion cyclotron resonance-mass spectrometry ((-)ESI-FT-ICR-MS). These formula lists reveal a 10-fold increase in nitrogen- and sulfur-containing …

The Importance Of Atomic Charges For Predicting Site-Selective Ir-, Ru-, And Rh-Catalyzed C-H Borylations, Shannon M. Stephens, Kyle M. Lambert

Chemistry & Biochemistry Faculty Publications

A supervised machine learning model has been developed that allows for the prediction of site selectivity in late-stage C-H borylations. Model development was accomplished using literature data for the site-selective (≥95%) C-H borylation of 189 unique arene, heteroarene, and aliphatic substrates that feature a total of 971 possible sp² or sp³ C-H borylation sites. The reported experimental data was supplemented with additional chemoinformatic descriptors, computed atomic charges at the C-H borylation sites, and data from parameterization of catalytically active tris-boryl complexes resulting from the combination of seven different Ir-, Ru-, and Rh-based precatalysts with eight different ligands. Of the over …

Challenges Associated With Pfas Detection Method In Africa, Abdullahi Tunde Aborode, Ridwan Olamilekan Adesola, Ibrahim Idris, Waheed Sakariyau Adio, Segun Olapade, Gladys Oluwafisayo, Israel Ayobami Onifade, Sodiq Fakorede, Taiwo Bakare-Abidola, Jelil Olaoye, Adedeji Daniel Ogunyemi, Oluwaseun Adeolu Ogundijo, Olamilekan Gabriel Banwo, Adetolase Azizat Bakre, Peter Oladoye, Grace Adegoye, Noimat Abeni Jinadu

Chemistry & Biochemistry Faculty Publications

Per- and polyfluoroalkyl substances (PFAS) are a group of man-made chemicals that are widely present in many industries. Monitoring and analyzing PFAS in Africa is challenging due to the limited availability of mass spectrometry (MS), which is an essential technique for detecting PFAS. This review assesses the scope and impact of the shortage of mass spectrometry instruments in Africa, emphasizing the resulting limitations in monitoring environmental and public health threats. The review analyzes the existing PFAS monitoring, the accessibility of MS instruments, and the technical capabilities within the continent. This study suggests that fewer African countries have sufficient MS instruments, …

Nucleotide-Derived Bacterial Alarmones Attenuate The Induction Of Type-I Interferon Responses In A Murine Macrophage Reporter Cell Line, Ryan P. Kilduff, Erin B. Purcell, Lisa M. Shollenberger

Chemistry & Biochemistry Faculty Publications

The stringent response is a well-studied phenomenon in many bacterial systems and regulates resource-consuming activities such as transcription, translation, and replication. The stringent response is a well-conserved signaling framework, as are the nucleotide-derived signaling mediators, collectively referred to as (p)ppGpp or as alarmones. There is a wealth of research evaluating nucleotide-derived alarmone signaling in bacterial models, however, their potential to modulate innate immune signaling has not yet been evaluated. Several common pathogen-synthesized molecules, such as lipopolysaccharide (LPS) and cyclic-di-AMP (c-di-AMP), act as pathogen-associated molecular patterns (PAMPs), which are common patterns that alert the innate immune system of bacterial infection. The …

Cellular Responses Of Astrangia Poculata (Ellis And Solander, 1786) And Its Symbiont To Experimental Heat Stress, Tyler E. Harman, Daniel Barshis, Briana Hauff Salas, Kevin B. Strychar

Biological Sciences Faculty Publications

Climate change has had devastating effects on tropical coral reefs; however, much less is known regarding how heat stress affects temperate coral. This research focuses on Astrangia poculata (Ellis and Solander, 1786) collected from Narragansett Bay, RI, during the summer and winter seasons and understanding the effect of experimental thermal extremes (i.e., 26 °C) on seasonally different populations. Photosynthetic efficiency (Fv/Fm), symbiont density (via an inverse relationship with pixel intensity), and oxidative stress via reactive oxygen species (ROS) concentrations were measured on symbiotic and aposymbiotic A. poculata. Higher Fv/Fm rates were observed in summer- vs. winter-collected corals (p ≤ …

Leveraging Gpt-4o For Automated Extraction Of Neural Projections From Scientific Literature, Rashmie Abeysinghe, Gorbachev Jowah, Licong Cui, Samden D Lhatoo, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Sudden Unexpected Death in Epilepsy (SUDEP) is a major cause of death for epilepsy patients having uncontrolled seizures. Understanding the complex neural circuits within the central nervous system is crucial for understanding the mechanisms underlying cardiorespiratory regulation, particularly in the context of SUDEP. This study explores the potential of GPT-4o, a cutting-edge language model, to automate the extraction of neural projections from scientific literature. We developed prompts to extract neuroscientific structures, extract projections, and perform synonym harmonization. Applying the approach to four neuroscientific articles, the method extracted 205 projections. A random sample of 100 projections identified was handed over to …

Modified N-Heterocyclic Carbene Catalysts For Polyurethane Synthesis, Charise D. Young

Pomona Senior Theses

Polyurethanes are widely used polymers synthesized from diisocyanate and diol molecules. They are ubiquitous polymeric materials with important industrial applications. Their increasing market value prompts the need for selective and efficient production which can be achieved through N-Heterocyclic carbene (NHC) catalysis. N-heterocyclic carbenes are heterocyclic molecules containing a carbene atom and at least one nitrogen adjacent to the carbene center. The nitrogen substituents on the adjacent nitrogen play an important role in influencing their steric and electronic properties and resultant reactivity.^1,2 There is a lack of a comprehensive understanding of the steric and electronic properties of NHCs and how …

Optimizing And Scaling Up Tcfh–Nmi Pyrrole Acylation For Organic Syntheses, Grant H. Miller

Pomona Senior Theses

Traditional ketone synthesis often depends on toxic reagents and hazardous solvents, which limits its scalability and environmental compatibility. The TCFH–NMI method has shown strong potential for amide, ester, and thioester formation, but its use in ketone synthesis has only been recently described, and only on small scales. This thesis addresses that gap by optimizing a scalable synthesis of 2-(monomethyl succinyl)-3,5-dimethylpyrrole using monomethyl succinate and 2,4-dimethylpyrrole as model substrates. Key reaction parameters were systematically refined to improve yield, reproducibility, and sustainability. The final protocol avoids chromatography, operates at room temperature, and consistently delivers high yields. These features position it as a …

Huchum: The Legacy Of Fire Suppression, Indigenous Land Management, And Media Representation, Carolyn Coyne

Pomona Senior Theses

In my thesis, I examine how various forms of news media from the 1900s to present day in Ohlone territory have framed a particular hegemonic ideology around fire that matches early colonial journal entries – an ideology that is fueled by fear, sensationalism, and exclusion and directly commits violence against the Ohlone people. I investigate this time period because this is when modern news corporations, like The New York Times, rose into prominence. Specifically, I question how media representations of fire inform regulations over controlled burns; what are the similarities in discourse between media framing and policy? What tactics are …

Swimming In Sh*T: Quantifying Lagoon Flushing Impacts On Fecal Indicator Bacteria In Surf Zones Of Three Beaches On The East End Of Long Island, Ny, Brody C. Eggert

Pomona Senior Theses

This thesis investigates how lagoon flushing influences fecal indicator bacteria (FIB) concentrations—specifically enterococcus bacteria—in the surf zones of East Hampton and Southampton, New York. Focusing on the coastal lagoons of Georgica Pond, Sagg Pond, and Mecox Bay, the study analyzes how episodic inlet openings and environmental conditions affect enterococcus levels at adjacent recreational beaches. Using over 700 observations from the Surfrider Foundation’s Blue Water Task Force (BWTF) database, I construct a series of statistical models ranging from ordinary least squares to mixed effects frameworks; this thesis shows my process in developing this model. My analysis reveals that open inlets between …

Rwanda's Natural Remedies: A Fresh Look At The Fight Against Malaria, Leandre Nsabimana Ndisanze

Pomona Senior Theses

Malaria remains one of the most devastating parasitic diseases globally, disproportionately affecting sub-Saharan Africa, where Rwanda continues to face high transmission rates and rising resistance to conventional interventions. Despite decades of control efforts, the emergence of drug-resistant Plasmodium falciparum and insecticide-resistant Anopheles mosquitoes threatens to reverse recent gains. This research responds to the urgent need for sustainable and culturally relevant alternatives by exploring the therapeutic potential of Rwandan traditional medicinal plants. These indigenous remedies, long used by local healers, offer an underexplored reservoir of bioactive compounds that may provide the basis for novel antimalarial drugs.

The central hypothesis of this …

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

Faculty, Staff and Student Publications

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

Some Types Of Hyperneutrosophic Set (6): Multineutrosophic Set And Refined Neutrosophic Set, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This paper builds on the foundational advancements introduced in [22, 29–32]. The Neutrosophic Set pro-vides a flexible mathematical framework for managing uncertainty by utilizing three membership functions: truth, indeterminacy, and falsity. Recent extensions, such as the HyperNeutrosophic Set and the SuperHy-perNeutrosophic Set, have been developed to address increasingly complex and multidimensional challenges. Comprehensive formal definitions of these concepts are provided in [26]. In this paper, we further extend various specialized classes of Neutrosophic Sets. Specifically, we explore extensions of the MultiNeutrosophic Set and the Refined Neutrosophic Set using HyperNeutrosophic Sets and 𝑛-SuperHyperNeutrosophic Sets, providing detailed analysis and examples.