Digital Commons Network^™

Phytochemical Analysis, Antioxidant, And Antibacterial Properties Of Partition Fractions Of Adansonia Digitata And Annona Muricata Extracts Using Chloroform, Ethyl Acetate, Ethanol, And Aqueous Solvent Systems, Fagbohun Oyenike Bushirat, Hassan Abdusalam Adewuyi, Sakariyau Adio Waheed, Maryam Nana Musa, Timothy God-Giveth Olusegun, Ayomide Babatunde Ishola, Agumage Idoko, Adeola Victor Kolawole, Adesanmi Adefunmilayo Oluwatuyi, Sarah Ngozi Agwasim

Chemistry & Biochemistry Faculty Publications

Adansonia digitata and Annona muricata are traditionally used medicinal plants with reported pharmacological properties. In this study, we aimed to elucidate the phytochemical composition, antioxidant activity, and antibacterial properties of partition fractions of Adansonia digitata and Annona muricata extracts obtained using chloroform, ethyl acetate, ethanol, and aqueous solvent systems. The plant extracts were successively partitioned using chloroform, ethyl acetate, ethanol, and aqueous solvent systems. Phytochemical analysis was performed using standard methods. Antioxidant activity was evaluated using FRAP and DPPH assays. Antibacterial activity was assessed using agar well diffusion and MIC determination. Phytochemical analysis revealed the presence of alkaloids (10.2-15.6%), flavonoids …

The Importance Of Solution Studies For The Structural Characterization Of The Enterovirus 5' Cloverleaf, Morgan G. Daniels, Meagan E. Werner, Xiaobing Zuo, Steven M. Pascal

Chemistry & Biochemistry Faculty Publications

Enteroviruses initiate genomic replication via a highly conserved mechanism that is controlled by an RNA platform, also known as the 5' cloverleaf (5'CL). Here, we present a biophysical analysis of the 5'CL conformation of three enterovirus serotypes under various ionic conditions, utilizing CD spectroscopy, size-exclusion chromatography, and small-angle X-ray scattering. In general, a tendency toward a smaller monomeric hydrodynamic radius in the presence of salts was observed, but the exact structural signature of each 5'CL varied depending upon the serotype. Rhinovirus B14 (RVB14) exhibited at least two monomeric conformations and a low propensity for dimerization, while poliovirus 1 (PV1) showed …

Training Set Augmentation And Harmonization Enables Radiomic Models To Detect Early Onset Of Lung Cancer, Claire Huchthausen, Menglin Shi, Gabriel L.A. Sousa, James Larner, Einsley Janowski, Jonathan Colen, Krishni Wijesooriya

Data Science Faculty Publications

Radiomics-based machine learning models have the potential to detect lung cancer at inception from CT scans and transform patient outcomes. Low malignancy rates in early-development pulmonary nodules (PNs) and variable image acquisition hinder development of clinically applicable radiomics-based early detection models. To address these challenges, we augmented training using later-development PNs and harmonized for acquisition effects. We first trained machine learning models to predict PN malignancy using radiomic features from scans of early-development benign and malignant PNs (n = 187) harmonized using ComBat. Observing near-chance performance, we augmented training with later-development benign and malignant PNs (n = 225). We evaluated …

Advancing Pedagogical And Instructional Design Through Artificial Intelligence (Ai) In Education And Training Contexts, Mohan Yang, Jewoong Moon, Tian Luo, Jinhee Kim

STEMPS Faculty Publications

[Introduction] "The only way to discover the limits of the possible is to go beyond them into the impossible." - Arthur C. Clarke

It is our pleasure and honor as guest editors for this special issue of the Journal of Applied Instructional Design (JAID) to present "Advancing Pedagogical and Instructional Design through Artificial Intelligence (AI) in Education and Training Contexts." This issue arrives at a truly timely moment, as the rapid and continuous development of generative artificial intelligence (GenAI) is fundamentally reshaping the traditional paradigms of teaching, learning, and training.

Morphing Shape Metastructures Using The Hybrid Position Feedback Control And Bistable Structural Elements, Mehmet Simsek, Thomas E. Alberts, Onur Bilgen

Mechanical & Aerospace Engineering Faculty Publications

This research introduces a new multi-degree-of-freedom metastructure concept utilizing a hybrid position feedback controller. An arbitrary number of bistable segments, or structural elements, are connected serially or in parallel to form a distributed bistable structure, or a so-called metastructure. The hybrid controller, an unstable-then-stable second-order single-degree-of-freedom system, leverages the resonant mode of a bistable system to destabilize it and dynamically induce snap-through between equilibria. The metastructure inherits multiple bistable positions, maintaining equilibrium shapes without consuming power and enabling many equilibrium configurations. Two geometric configurations are proposed and analyzed using a modified hybrid feedback control approach, which rejects forces from neighboring …

Designing Tpack-Driven Mobile Learning With Digital Citizenship For Biology Education: Insights From Ngt And Ism Approaches, Cik Jamaliah Abd Manaf, Shakinaz Desa, Muhamad Ikhwan Mat Saad, Helen Crompton

STEMPS Faculty Publications

The rapid digitization of education and the complexity of scientific content demand the integration of digital citizenship in TPACK-based mobile learning for Biology. This study aimed to identify and prioritize relevant digital citizenship practices using a Design and Development Research approach. In Phase One, the Nominal Group Technique with 10 experts evaluated eight proposed practices. Phase Two employed Interpretive Structural Modeling with nine experts to structure hierarchical relationships. Seven practices were retained, with Ethical Use of Digital Resources as the top-level driver. The resulting framework supports ethical and discipline-specific mobile learning models, promoting responsible digital engagement in Biology education.

A Bibliometric Analysis Of Ai-Driven Healthcare Literature Containing Kos Keywords: Trends, Themes, And Gaps, Julaine Clunis, Eric Asare

STEMPS Faculty Publications

As artificial intelligence (AI) becomes increasingly embedded in healthcare applications, concerns have emerged around the trustworthiness, interpretability, and context-awareness of these systems. Knowledge Organization Systems (KOS) hold considerable potential to address these challenges by supporting semantic standardization, explainability, and domain alignment. This study presents a bibliometric analysis of scholarly publications referencing both AI and healthcare concepts to examine how KOS are positioned within this evolving discourse. The findings indicate that while early literature frequently and explicitly referenced KOS—such as ontologies, controlled vocabularies, and classification systems—their visibility has declined relative to newer paradigms such as machine learning and large language models. …

Impacts Of Physical Inactivity Models On Endothelial Function: A Systematic Review, Joel E. Harden, J. David Branch, Leryn J. Reynolds

Exercise Science Faculty Publications

Background

Endothelial dysfunction is associated with cardiovascular disease and cardiac events. Numerous studies demonstrate that a reduction in physical activity/exercise levels are associated with poor endothelial function. Yet, these studies use a plethora of models to mimic reduced activity levels which may have widely different results on endothelial function. It is pertinent to collectively review these articles to provide a comprehensive understanding of the impact of reduced activity on vascular health, as endothelial function is one of many factors that influences vascular tone.

Objective

The purpose of this systematic review is to examine and synthesize the current literature regarding the …

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.

Suntan (And Other Solar Trigonometric Functions): Solutions For Fermi Questions: February 2025, John Adam

Mathematics & Statistics Faculty Publications

The article discusses the intensity of sunlight on the side of the author's face as they walk to and from their office, focusing on the solar zenith angle θ. It presents a formula for solar irradiance and explores how the intensity changes based on the angle and elevation. The solutions to the questions posed in the article provide insights into the maximum irradiance levels at different angles and elevations.

M Star Opacities: The B³Π–X³Δ Band System Of Tio, Peter F. Bernath, Manish Bhusal, Mirek R. Schmidt

Chemistry & Biochemistry Faculty Publications

The spectra of titanium monoxide (TiO) are used to classify M stars. TiO experimental cross sections based on a high-resolution emission spectrum recorded with a Fourier transform spectrometer at the National Solar Observatory are used for the analysis of the TiO B³Π–X³Δ transition (𝛾' system). The 3–2 and 4–3 vibrational bands are analyzed for the first time, and the analysis of the 2–1 band is revised. The transition dipole moment function from an ab initio calculation is used to calculate the band strengths. These band strengths are used to produce a B³Π–X³Δ line list for the vibrational levels v' ⩽ …

Leading Beyond The School Walls: Understanding Principal Community Activism, Jason D. Salisbury, Meagan S. Richard

Educational Leadership & Workforce Development Faculty Publications

The purpose of this study is to investigate the ways school leaders perceive and engage in community-focused, activist leadership in response to community needs. We rely on a critical qualitative research design that draws on critical urban theory. Sources of data include a pilot focus group, semi-structured in-depth interviews with activist leaders, and publicly available documents. Findings demonstrate the ways that leaders engaged in activism by developing understandings of the communities they served as a first step to activism, rooting their schools as a physical resource for communities, and responding to community needs via activist practices. Through their work, leaders …

Supporting Social Justice In Physical Education Teacher Education Programs: A Qualitative Analysis Of Adapted Pe Teachers' Perspectives, Ann-Catherine Sullivan, Christianna Blanchard-Alworth, Cynthia K. Piletic, Linda Hilgenbrinck

Educational Leadership & Workforce Development Faculty Publications

Despite attention to sociocultural issues in Physical Education Teacher Education (PETE), the role of Adapted Physical Education (APE) teachers as social justice advocates remains underexplored. A primary responsibility of APE teachers is to provide specially designed instruction to students with disabilities (SWD), so they have access to the general physical education curriculum to make progress toward grade-level standards. This study presents a qualitative analysis of the perspectives of National Adapted Physical Education Teachers of the Year (APE TOYs) on advocating for social justice within PETE programs. A phenomenological approach with mixed-methods design was used. Findings emphasise the importance of fairness, …

Overcoming Resistance To Ai In Higher Education: A Case Study, C. Tomovic, M. Tomovic

Educational Leadership & Workforce Development Faculty Publications

While the deployment of AI in business and industry is widely acknowledged for its potential to improve efficiencies, decision-making, and automation, its implementation often encounters several challenges. These include integrating AI with existing systems, ensuring data quality and availability, bridging the employee skills gap, overcoming resistance to change, addressing ethical concerns, managing costs, complying with regulations, and handling ongoing maintenance and updates. In the context of higher education, however, the challenges take a different shape. Faculty members may express concerns about how AI could disrupt traditional teaching methods, necessitate changes in course delivery, and raise issues related to job security …

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 …

Multimodal Wearable Intelligence For Dementia Care In Healthcare 4.0: A Survey, Po Yang, Gaoshan Bi, Jun Qi, Xulong Wang, Yun Yang, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

As a new revolution of Ubiquitous Computing and Internet of Things, multimodal wearable intelligence technique is rapidly becoming a new research topic in both academic and industrial fields. Owning to the rapid spread of wearable and mobile devices, this technique is evolving healthcare from traditional hub-based systems to more personalised healthcare systems. This trend is well-aligned with recent "Healthcare 4.0" which is a continuous process of transforming the entire healthcare value chain to be preventive, precise, predictive and personalised, with significant benefits to elder care. But empowering the utility of multimodal wearable intelligence technique for elderly care like people with …

Last-Minute Coordination: Adapting To Demand To Support Last-Mile Operations, Kedong Chen, Hung-Chung Su, Kevin Linderman, William Li

Information Technology & Decision Sciences Faculty Publications

In the highly competitive e-commerce industry, customer-facing warehouses are crucial as the “order penetration points” for e-commerce last-mile operations. This research examines how warehouses use last-minute coordination, an unstructured mechanism, to ensure sufficient inventory at the order penetration points. Previous research has focused on structured mechanisms like contracts and inventory management systems to enhance warehouse performance. However, these mechanisms can be ineffective when faced with unforeseen local contingencies. To adjust inventory and adapt to changes in supply and/or demand, warehouses need to engage in unstructured, last-minute coordination with other warehouses. Using coordination and loose coupling theories, we find that coordinating …

A Two-Phase Learning Approach Integrated With Multi-Source Features For Cloud Service Qos Prediction, Fuzan Chen, Jing Yang, Haiyang Feng, Harris Wu, Minqiang Li

Information Technology & Decision Sciences Faculty Publications

Quality of Service (QoS) is a key factor for users when choosing cloud services. However, QoS values are often unavailable due to insufficient user evaluations or provider data. To address this, we propose a new QoS prediction method, Multi-source Feature Two-phase Learning (MFTL). MFTL incorporates multiple sources of features influencing QoS and uses a two-phase learning framework to make effective use of these features. In the first phase, coarse-grained learning is performed using a neighborhood-integrated matrix factorization model, along with a strategy for selecting high-quality neighbors for target users. In the second phase, reinforcement learning through a deep neural network …

A Spoofing Speech Detection Method Combining Multi-Scale Features And Cross-Layer Identification, Hongyan Yuan, Linjuan Zhang, Baoning Niu, Xianrong Zheng

Information Technology & Decision Sciences Faculty Publications

Pre-trained self-supervised speech models can extract general acoustic features, providing feature inputs for various speech downstream tasks. Spoofing speech detection, which is a pressing issue in the age of generative AI, requires both global information and local features of speech. The multi-layer transformer structure in pre-trained speech models can effectively capture temporal information and global context in speech, but there is still room for improvement in handling local features. To address this issue, a speech spoofing detection method that integrates multi-scale features and cross-layer information is proposed. The method introduces a multi-scale feature adapter (MSFA), which enhances the model’s ability …

Optimal Control Of Queueing Systems With Error-Prone Servers, Junqi Hu, Sigrún Andradóttir, Hayriye Ayhan

Information Technology & Decision Sciences Faculty Publications

Consider a Markovian tandem line with finite intermediate buffers and an equal number of stations and servers. Servers are flexible but noncollaborative, so that a job can be processed by at most one server at any time. When a job is being processed, it can be damaged and wasted depending on the proficiency of the server. We identify the dynamic server assignment policy that maximizes the long-run average throughput of the system with two stations and two servers. We find that the optimal policy is either a single or a double threshold policy on the number of jobs in the …

Investing In The Age Of Generative Ai: A Gpt-Based Sentiment Analysis Approach, Xianrong Zheng

Information Technology & Decision Sciences Faculty Publications

Generative AI, which ushers a new age of AI, comes with huge economic potential. To capitalize the AI boom, investors are interested in trading AI stocks. AI chatbots, which can identify and classify the sentiment from financial news, can be leveraged for investment. So, this paper proposes a GPT-based sentiment analysis approach for trading AI stocks. Also, natural experiments are conducted to evaluate its effectiveness. Initial results show that the approach achieves a good rate of return.

A Comparison Of Service Needs For Face-To-Face To Online Programs, Ali Ardalan, Roya K. Ardalan, G. Steven Rhiel

Information Technology & Decision Sciences Faculty Publications

Higher education institutions strive to gain a competitive advantage over similar programs offered by other institutions. A criterion for comparing programs is the quality of service. The definition of quality from the customer's view is "fitness for use," which incorporates the value generated by the product. Each learner may evaluate programs differently from other learners. It is impossible to develop a unique standard for program quality that is defined by a specific set of factors and specific level for each of these factors. This study presents an extensive set of factors that may affect learners' satisfaction. Higher education administrators should …

Optimal Control And Structurally-Informed Gradient Optimization Of A Custom 4-Dof Rigid-Body, Brock Marcinczyk, Logan E. Beaver

Mechanical & Aerospace Engineering Faculty Publications

This work develops a control-centric framework for a custom 4-DOF rigid-body manipulator by coupling a reduced-order Pontryagin’s Maximum Principle (PMP) controller with a physics-informed Gradient Descent stage. The reduced PMP model provides a closed-form optimal control law for the joint accelerations, while the Gradient Descent module determines the corresponding time horizons by minimizing a cost functional built directly from the full Rigid-Body Dynamics. Structural-mechanics reaction analysis is used only to initialize feasible joint velocities—most critically the azimuthal component—ensuring that the optimizer begins in a physically admissible region. The resulting kinematic trajectories and dynamically consistent time horizons are then supplied to …

Applying Transfer Learning For Street-Scale Nuisance Flood Forecasting In Coastal-Urban Cities, Binata Roy, Jonathan L. Goodall, Diana Mcspadden, Chetan Kumar, Steven Goldenberg, Yidi Wang, Malachi Schram

VMASC Publications

An important challenge with Machine Learning (ML) is its transferability; i.e., whether a ML model trained on one set of data can be applied to a second set of data without requiring full re-training of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether a ML model trained for one …

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 …

5g-Practical Byzantine Fault Tolerance: An Improved Pbft Consensus Algorithm For The 5g Network, Xin Liu, Xing Fan, Baoning Niu, Xianrong Zheng

Information Technology & Decision Sciences Faculty Publications

The consensus algorithm is the core technology of blockchain systems to maintain data consistency, and its performance directly affects the efficiency and security of the whole system. Practical Byzantine Fault Tolerance (PBFT) plays a crucial role in blockchain consensus algorithms by providing a robust mechanism to achieve fault-tolerant and deterministic consensus in distributed networks. With the development of 5G network technology, its features of high bandwidth, low latency, and high reliability provide a new approach for consensus algorithm optimization. To take advantage of the features of the 5G network, this paper proposes 5G-PBFT, which is an improved practical Byzantine fault-tolerant …

Atmospheric Chemistry Experiment (Ace) Winds, Matthew Wyatt, Peter F. Bernath, Chris Boone, Léo Lavy, Ryan Johnson

Chemistry & Biochemistry Faculty Publications

The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) uses limb geometry to measure transmittance spectra of Earth's atmosphere by solar occultation. Line-of-sight wind speeds can be derived via Doppler shifts of molecular lines in infrared spectra. The wind look direction angles relative to geodetic North are derived from geometry. We validate the new ACE version 5.3 (v.5.3) line-of-sight winds with MIGHTI and meteor radar vector wind observations and find a ±15 m/s sunrise/sunset shift above 80 km. We also compare line-of-sight winds from ACE-FTS v.5.2 and v.5.3 with vector winds from the MERRA-2, HWM14, and WACCM-X models. A ±15 m/s …

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, …