Digital Commons Network^™

Early Detection Of Infectious Diseases: A Review Of Recent Advances In Pathogen Identification, Molecular Tools, And Metabolomics-Driven Biomarker Discovery, Patrica Ivy Agorsor, Michael O. Eze

Chemistry Faculty Research & Creative Works

The recent COVID-19 pandemic has heightened public interest in noninvasive methods for early diagnosis of infectious diseases. In addition, various government agencies have implemented "infectious disease preparedness" to mitigate future outbreaks. This review highlights conventional and advanced methods for infectious disease diagnosis with an emphasis on emerging mass spectrometry methods. Conventional methods for pathogen identification, such as culture-based techniques and molecular methods, have limitations with respect to sensitivity, specificity, and turnaround time. Recent advances in high-resolution mass spectrometry have revolutionized the field of infectious disease biomarker discovery. These techniques enable the comprehensive profiling of metabolites in various biological samples, identification …

Ecologic Factors Contributing To West Nile Virus Hyperendemicity In Central South Carolina: An Integrated Vector–Human–Environmental Study, Elba S. Fridriksson, Ahayla Muraleedharan, Kyndall C. Dye-Braumuller, Madeleine M. Meyer, Kia Zellars, Hiuxuan Li, Melissa S. Nolan Ph.D., Mph

Faculty Publications

West Nile virus (WNV) is an endemic arboviral infection in the United States that has undergone phyloge-netic evolution since its introduction 25 years ago. An integrated vector–human–pathogen study was conducted in the summer of 2023 to unearth contemporary Culex quinquefasciatus habitat patterns and human transmission spillover foci in South Carolina, a state with historically little WNV data. A serosurvey revealed WNV seroprevalence 10 times the national average (22% versus 2%, respectively), with unusual epidemiologic risk factors. Female Culex quinquefas-ciatus WNV positivity was low (2.7%), with viral phylogenetics 100% homologous to the WN02 clade. Mosquito vectors clustered in affluent urban neighborhoods …

On Robust Estimation Of Multivariate Location And Scale With Applications, Soumya Chakraborty

Doctoral Theses

The principal objective of this thesis is, in a nutshell, to provide robust estimators of multivariate location and scale which have reasonable to high model efficiency but avoid high computational complexity so as to be practically useful in real problems. We utilize the minimum density power divergence (DPD) and the related philosophy to invoke robustness. There are some computational issues while minimizing the DPD in different multivariate set-ups. We will work on this problem rigorously and come up with three types of estimation procedures which are explicitly or implicitly related to the minimum DPD methodology, keeping the computational issue in …

Undergraduate Engagement In Neutron Scattering As A Pathway To U.S. Competitiveness And A Diverse Scientific Workforce, Hillary L. Smith

Physics & Astronomy Faculty Works

Engaging undergraduate students in neutron scattering experiments through beamtime trips, student internships, or class visits is a powerful driver of scientific progress in the United States. These experiences provide hands-on exposure to advanced instrumentation, mentorship from diverse scientists, and insight into large-scale research infrastructure. By contributing meaningfully to proposal development, sample preparation, data collection, and data analysis, students develop confidence, scientific identity, and a sense of belonging, particularly those from underrepresented backgrounds. Early engagement cultivates a skilled and motivated scientific workforce, strengthens the capabilities and mission of national laboratories, and ensures continued U.S. leadership in discovery and innovation.

Developing Deep Neural Network Based Brain Computational Models From Psychophysics Data Of Some Simple Perceptual Phenomena: Visual As Well As Auditory, Chandran Keerthi S

Doctoral Theses

The thesis, consisting of nine chapters, explores the methodology of building testable brain computational models using Deep Neural Networks (DNN), which are trained by psychophysics data. Psychophysics is the quantitative study of perception of physical stimuli. In psychophysics experiments, one or more parameters associated with the stimuli are changed, and the human subject’s responses to the stimuli are recorded. This thesis encompasses both experimental psychophysics works, as well as computational models of the phenomena involved. The contributory chapters of the thesis start in Chapter 2 with the perspective building of the novel methodology followed throughout this research involving psychophysics on …

Boronate Esters For The Binding And Detection Of Low Molecular Weight Volatile Amines, Xiaoning Li, James Boyt, Steven Sloope, Luke T. Lackovic, Mark D. Smith, James J. Lavingne

Faculty Publications

Conjugated thiophene-based diboronate esters, 1–4, were synthesized to investigate how substituents on catechol alter the Lewis acidity and accessibility to boron, and influence binding interactions with low molecular weight Lewis basic amines. Crystallographic analysis indicated that both boron centres bind analyte and that Lewis base coordination induces deplanarization of the conjugated system. Spectroscopic studies demonstrate that amine binding disrupts conjugation, producing distinct and reproducible optical responses that depend on analyte basicity and structure, with association constants in organic solvent ranging from 10³ to 10⁶ M⁻¹. Quantitative binding analyses indicate strong negative cooperativity between the two boron …

Biologically-Inspired Multiscale Neuromorphic Architecture, Christian O'Reilly, Ramtin Zand

Publications

This white paper proposes a biologically-inspired multiscale neuromorphic architecture that bridges key gaps between artificial neural networks (ANNs), spiking neural networks (SNNs), and biological neural networks (BNNs). While SNNs offer promising energy efficiency, their broader adoption remains limited by suboptimal performance and the need for novel learning paradigms. To address these challenges, the proposed framework integrates structural and functional principles observed in the brain, including hierarchical organization, sparse and modular connectivity, predictive coding, and diverse neuronal dynamics.

The architecture operates across micro-, meso-, and macro-scales, incorporating neuron-level diversity (e.g., excitatory/inhibitory and principal/support cells), canonical microcircuits (CMCs), and large-scale hierarchical organization. …

Lc-Ms/Ms Method Development For The Analysis Of Cannabinoids In Wastewater, Abigail M. Castellanos, Ava La Lande

The Kean Review: Journal in Student Research

The goal of this research was to establish a reliable method to detect the presence of cannabinoids in wastewater and increase the sensitivity of detection. Since the legalization of cannabis in many states, toxicology research has expanded on methods of detection in hopes of identifying usage patterns. At the Joint Meeting of Essex and Union Counties, it was established that cannabinoids are not thoroughly accounted for in the process of filtering wastewater in addition to our limited understanding of consumption trends. This stands true for many wastewater facilities, especially as the intake of cannabis remains prevalent for various populations across …

Fisheries Management Paper No. 311: West Coast Deep Sea Crustacean Resource Harvest Strategy, Department Of Primary Industries And Regional Development, Western Australia

Fisheries Management Papers

Harvest strategies for Western Australia’s (WA) aquatic resources are formal documents developed by the Department of Primary Industries and Regional Development (DPIRD, the Department) to support decision-making processes that ensure the outcomes are consistent with the principles of Ecologically Sustainable Development (ESD; Fletcher 2002a) and Ecosystem Based Fisheries Management (EBFM; Fletcher et al. 2012). Harvest strategies are a key component of all contemporary fishery management systems and a requirement for certification under the Marine Stewardship Council (MSC). The objectives of ESD are reflected in the objectives of the Fish Resources Management Act 1994 (FRMA).

This West Coast Deep Sea Crustacean …

Impact Of Iron-Bearing Fillers On The Mechanical Strength And Chemical Stability Of Magnesium Potassium Phosphate Matrices Incorporating Rhenium, Sergey Sayenko, Volodymyr Shkuropatenko, Hans Conrad Zur Loye, Petr Vecernik, Monika Kiselova, Vlastislav Kašpar, Vlastimil Miller, Petr Bezdicka, Jan Šubrt, Petra Ecorchard, Natalija Murafa, Iva Milisavljevic, Scott T. Misture

Faculty Publications

We report on the study of the immobilization process of non-radioactive rhenium (Re), a chemical analogue of technetium-99 (⁹⁹Tc), in compounds based on magnesium potassium phosphate (MKP), as well as the possibility of enhancing their properties with iron-bearing additives/fillers. Powdered Re2O7 was used as the initial Re-containing source. Because of the solubility and high leachability of Tc (VII), which is also volatile at high temperatures, its immobilization for long-term storage and disposal poses a serious challenge to researchers. Taking this into account, low-temperature stabilization technology based on MKP, a cementitious material, is currently considered promising. We prepared experimental …

Responsible Ai In Teaching And Learning, Asa B. Stone, Mark C. Stone, Derek M. Heeren, Santosh Pitla

PRAIRIE: Pioneering Responsible AI for Research, Innovation, and Education

The rapid adoption of generative artificial intelligence (AI) in higher education presents both transformative opportunities and significant pedagogical risks. While AI tools are becoming embedded in academic and professional environments, their integration into teaching and learning raises critical questions about cognitive engagement, academic integrity, equity, and skill development. This white paper proposes a principled framework for the responsible integration of AI in higher education, grounded in the dual commitment to AI literacy and the cultivation of durable skills.

The framework articulates six core principles: purposefulness; transparency; integrity and attribution; critical AI literacy; equity and access; and privacy and data protection. …

Variation In Food Web Reliance On Green And Brown Energy Pathways Across Ecosystem Gradients, James W. Sturges, W. Ryan James, Ryan J. Rezek, Rolando O. Santos, Mack White, Gina A. Badlowski, Shakira Trabelsi, Jordan Massie, Justin S. Lesser, Joel C. Trexler, James Nelson, Jennifer S. Rehage

Marine Science

Aquatic food webs typically include highly coupled fast, ‘green’ energy pathways driven by algae or phytoplankton and slower, ‘brown’ energy channels driven by detritus and terrestrial plants. Quantifying how much energy biological communities obtain from each of these pathways is essential, particularly across multiple interconnected food webs over large areas, because energy dynamics are known to influence ecosystem structure and function. Despite their importance, few studies track variance in energy channel contributions to food webs across interconnected habitats during distinct hydrologic seasons. In this study, we used tri-isotope Bayesian mixing models to quantify seasonal contributions of energy pathways to consumers …

Supporting Data – Urban Stream, Cardinal Court, Isu, Normal, November 9, 2023 To May 1, 2025, Eric Wade Peterson, Ava Miller

Faculty Publications - Geography, Geology, and the Environment

Between November 9, 2023 to May 1, 2025, water samples were collected upstream and downstream along a segment of a stream adjacent to Cardinal Court on the Illinois State University campus. At each location, samples were collected at the surface. In-situ measurements of Dissolved Oxygen, Specific Conductance, and Temperature were recorded with a YSI 85. Anion samples were analyzed using a Ion Chromatograph for fluoride (F^-), chloride (Cl^-), nitrate as nitrogen (NO3-N), phosphate (PO₄^3-), and sulfate (SO₄^2-). The available dataset provides the recorded field parameters and the analyzed ion concentrations.

Monosaccharide Binding To Synthetic Carbohydrate Receptor Microarrays, Milan A. Shlain

Dissertations, Theses, and Capstone Projects

Chapter 1: A glycan detection platform comprised of synthetic carbohydrate receptors (SCRs) immobilized onto polymer brushes was prepared. SCR043, an alkene-containing SCR, was incorporated into grafted-from polymer brushes using hypersurface photolithography, resulting in microarrays of SCR043-functionalized polymer brushes, where brush height (h) and SCR grafting density (Γ) is controlled precisely at each feature in the array. The influence of h and Γ on the binding to five fluorescently labelled monosaccharides – α-glucose (α-Gluc-FL), α-galactose (α-Gal-FL), α-mannose (α-Man-FL), β-glucose (β-Gluc-FL), and β-galactose (β-Gal-FL) – in aqueous buffer …

Mechanistic Studies Of Aerobic Photochemistry: Gold Nanoclusters, Nanoparticles, And Solution-Phase Systems, Serah Essang

Dissertations, Theses, and Capstone Projects

This thesis comprises five chapters as enumerated below.

Chapter 1 describes our findings on the reactions of Au glutathione nanocluster (Au₂₀SG₁₆) with singlet oxygen (¹O₂) in D₂O. We noticed it underwent a self-photooxidation reaction. Leading us to mechanistic studies using photophysical, photochemical, theoretical, and indirect trapping methods. We found rapid total quenching of singlet oxygen (¹O₂) by ground-state Au₂₀(SG)₁₆, with evidence for dioxygen insertion into the nanocluster. Supported by analyses with IR, ESI-MS, and density functional theory, we propose the formation of …

Development Of Novel Anti-Cancer Colchicine Analogs: Synthesis And Configurational Studies, Orugbani S. Eli

Dissertations, Theses, and Capstone Projects

Colchicine, a naturally occurring alkaloid, has long been known as a potent therapeutic agent. Despite its efficacy treating gout and other inflammatory disorders, its severe toxicity, limited selectivity, and poor pharmacological profile have restricted its broader clinical application. Reported advantages of colchicine-site ligands as vascular-disrupting agents, including reduced susceptibility to multidrug resistance, have revived interest in the colchicine site on tubulin as a validated therapeutic target for cancer. This dissertation focuses on the development of new colchicine analogs, detailing the synthetic method to functionalized AC-ring derivatives, as well as the evaluation of their configurational stability and biological activity.

In Chapter …

Demographic And Other Correlates Of Non-Prescription Drug Use Among College Students During The Covid-19 Pandemic, Subi Gandhi, Sidketa Fofana, Md Rafiul Islam, Tamer Oraby

School of Mathematical & Statistical Sciences Faculty Publications

Background and objectives: Substance use among college students in the U.S. remains a pressing concern and may have intensified during the COVID-19 pandemic due to increased stress, uncertainty, and academic disruptions. This study investigates the relationship between non-prescription drug use and various demographic, mental health, and behavioral factors among college students during the pandemic's early stages.

Methods: Data were collected through online and in-person surveys in the summer semester of 2021. Behavioral health was assessed using validated instruments: the Patient Health Questionnaire-9 (PHQ-9) for depression and the Drug Abuse Screening Test-20 (DAST-20) for substance use. Demographic and behavioral variables were …

Cyber Science Education Meets Healthcare Technology, Angela Spencer

Journal of Cybersecurity Education, Research and Practice

The research investigates how cyber science education combines with healthcare technology during the digital age to resolve a fundamental research gap in these two advancing areas. A combined approach utilizing extensive surveys and detailed interviews evaluates the functionality of learning platforms as well as cybersecurity measures and potential uses of emerging virtual reality (VR) and augmented reality (AR) tools to improve both educational and clinical environments. The research document describes its methodologies thoroughly while. The research documents multiple quantitative and qualitative results before performing its analysis, which leads to strategy development for digit. The researchers worked to find ways that …

Cellscout: Visual Analytics For Mining Biomarkers In Cell State Discovery, Rui Sheng, Zelin Zang, Jiachen Wang, Yan Luo, Zixin Chen, Yan Zhou, Shaolun Ruan, Huamin Qu

Research Collection School Of Computing and Information Systems

Cell state discovery is crucial for understanding biological systems and enhancing medical outcomes. A key aspect of this process is identifying distinct biomarkers that define specific cell states. However, difficulties arise from the co-discovery process of cell states and biomarkers: biologists often use dimensionality reduction to visualize cells in a two-dimensional space. Then they usually interpret visually clustered cells as distinct states, from which they seek to identify unique biomarkers. However, this assumption is often this assumption often fails to hold due to internal inconsistencies in a cluster, making the process trial-and-error and highly uncertain. Therefore, biologists urgently need effective …

The Tool/Weapon Duality Of Mathematics, Alexandre Borovik

Journal of Humanistic Mathematics

This paper outlines the principal moral and ethical issues of mathematics and existential choices a mathematician may face in his professional life. My text is a manifesto; it is a list of declarations rather than a systematic development of the theme. Indeed each section could be expanded into a paper on its own. I hope to write fairly soon a more detailed exposition.

A Note On Modeling Prejudice, Alan Lockard, Edwin Harcourt

Journal of Humanistic Mathematics

We model prejudice in the context of an iterated prisoner’s dilemma tournament. Prejudice here is defined as the inability to distinguish amongst members of an identifiable group. We run a computer simulation where agents of one of two groups with defined strategies are randomly matched against each other. The agents either cooperate with or defect against the agent they are matched with. Our focus is on agents who play an unprejudiced version of the Tit-for-Tat strategy (cooperate with any player in the first encounter, and then apply the same strategy [defect or cooperate] that the opposing player played against them …

Exploring The Dynamics Of Romantic Relationships Through The Lens Of Prem Rog, Umang Jain, Dheeraj Sharma, Pranay Goswami, Kuldeep Malik

Journal of Humanistic Mathematics

Romantic relationships are dynamic events that begin, grow, and frequently remain for a long time in a stagnant or fluctuating state until possibly dissipating. Although they are unquestionably the most significant dynamic events in our lives, dynamic systems theory has only recently included them in its formal framework. Without a mathematical model, it would be impossible to analyze and comprehend the dynamics because, in general, love stories are too brief to allow things to stabilize and are affected by the ups and downs of the surrounding community. In this paper, we set up models made up of four ordinary differential …

Microplastics In St. John, United States Virgin Islands Sediments: Methodological Approaches And Variability Of Microplastics Concentrations And Accumulation Rates, Henry B. Arbaugh, Sarah C. Gray, Dimitri Deheyn

Theses

Sediment samples were collected from a near shore and reef site in Coral Bay, St. John, United States Virgin Islands (USVI) from 2007-2016, using tube sediment traps. These samples provide an opportunity to study microplastics (MPs) in an area where no previous MP studies have been performed. Most sedimentary MP studies utilize benthic samples which can only measure MP concentrations (#MP/g or #MP/mL sediment), while sediment traps can provide MP accumulation rates (#MP/cm²/day) as a function of time. However, the methods used for extracting MPs from benthic samples have not been tested using sediment trap samples whose characteristics, …

Evaluation Of Large Language Models As Decision Support Tools For Head And Neck Cancer Management: A Blinded Multidisciplinary Simulation Study, Sholem Hack, Ron J. Karni, Antonino Maniaci, Christopher E. Fundakowski, Luca Castellani, Fabiola Incandela, Remo Accorona, Miguel Mayo-Yanez, Martina Violati, Lorenzo Giannini, Niccolo' Mevio, Alberto Maria Saibene

Department of Otolaryngology - Head and Neck Surgery Faculty Papers

BACKGROUND: The management of head and neck cancer relies on multidisciplinary expertise; however, access to tumor boards remains variable. Large language models (LLMs) may support guideline-based decision-making, although performance in complex oncologic scenarios is not well defined.

METHODS: Fourteen synthetic cases based on real tumor board encounters were evaluated. Five blinded comparator arms produced recommendations: a human expert, Non-RAG-GPT-4, Non-RAG-GPT-5, RAG-GPT-4, and RAG-GPT-5. Eight head and neck oncologic surgeons scored each recommendation for appropriateness, clarity, specificity, and feasibility using 5-point Likert scales. Paired permutation testing and inter-rater reliability were assessed.

RESULTS: LLM outputs showed close alignment with expert recommendations. RAG-based …

Multifunctional Green Wall Systems For Greywater Treatment And Hygrothermal Regulation In Egypt, Laila Ossama Mohamed Elhusseiny Abdelsalam

Theses and Dissertations

Increasing environmental concerns regarding climate change and the intensifying challenge of water scarcity in Egypt necessitate the development of innovative, sustainable, and resource-efficient strategies for wastewater reuse. In the built environment, greywater constitutes a significant, relatively low-contaminant wastewater stream that, if treated to comply with Egyptian Codes and relevant international standards, can be safely reused for non-potable applications such as irrigation, landscaping, and building services. This research investigates the efficacy of an integrated green wall panel system, installed on building façades, for decentralized greywater treatment under Egypt’s climatic and environmental conditions, while simultaneously enhancing hygrothermal performance to reduce building energy …

A Virtual-Reality-Based Dental Simulator For Endodontics With Automated Formative Feedback, Yousef Salah Abo El Ela

Theses and Dissertations

Advancements in virtual reality (VR) and haptic technology are transforming the landscape of medical and dental education, offering new avenues for safe, immersive, and repeatable training experiences. Within dentistry, endodontics presents unique challenges for preclinical education due to anatomical complexity, limited access to extracted teeth, ethical concerns, and the shortcomings of conventional plastic models. Despite endodontics specific plastic teeth being available, they fall short of replicating the hardness of real extracted teeth, are relatively costly compared to generic plastic teeth, and are ultimately a disposable item which makes them inadequate as a sustainable long-term solution. Extracted teeth do a much …

Potent, Selective Pyrrolopyrimidine Pde11a4 Inhibitors With Improved Pharmaceutical Properties, Shams Ul Mahmood, Rama Krishna Boddu, Jeremy Eberhard, Charles S. Hoffman, John Gordon, Dennis Colussi, Wayne Childers, Elvis Amurrio, Marie Danaher, Michy P. Kelly, David P. Rotella

Department of Chemistry and Biochemistry Faculty Scholarship and Creative Works

Previous work demonstrated target engagement with an orally bioavailable, potent, selective PDE11A4 inhibitor in the mouse hypothalamus. This compound was limited by low aqueous solubility, stimulating the need for alternative leads with improved pharmaceutical properties to carry out efficacy studies. This paper outlines optimization of a pyrrolopyrimidine hit leading to a potent, selective PDE11A4 inhibitor with improved pharmaceutical properties and promising activity in cell-based models of enzyme activity.

Patient-Specific Lumped-Parameter Model For Quantifying Vessel-Specific Remodeling And Predicting Right Ventricular Function In Pulmonary Hypertension, Christopher G. Lechuga, Amirreza Kachabi, Mitchel J. Colebank, Claudia E. Korcarz, Farhan Raza

Faculty Publications

Purpose: Pulmonary hypertension (PH) is a heterogeneous disease with patient-specific variability and vessel-specific remodeling, which eventually lead to right ventricular (RV) failure. The gold standard for RV assessment—pressure–volume (PV) loop acquisition—is invasive and limited to specialized settings. This study aims to develop a patient-specific lumped-parameter model that quantifies vessel-specific remodeling and simulates RV PV loops across PH phenotypes using routine clinical data.

Methods: A lumped-parameter model was calibrated using right heart catheterization and echocardiography data. Model agreement was assessed by R2 values for pressure and flow goodness-of-fit, and model-derived hemodynamic metrics were comparedwith clinical values. A dimensionality reduction approach was …

Characterization Of Ru(Ii) Polypyridyl Photosensitizers Bound To Tio2 Supports Through A New Covalent Metal-Ester Bonding Motif, D. M. S. C. Dissanayake, Christopher T. Lebarron, Laura C. Maybach, Joseph J. Kuchta Iii, Seyyedamirhossein Hosseini, Aaron K. Vannucci

Faculty Publications

The development of photoelectrochemical (PEC) devices involves the attachment of molecular photosensitizers onto solid supports. Particularly significant to this work are PECs that rely on ruthenium-based photosensitizers on high band gap metal oxide (MOx) supports. In this study, we have explored a new ester binding motif (MOx-ester) to covalently attach a ruthenium polypyridyl photosensitizer to TiO₂. This new MOx-ester photoanode is compared to the traditional photoanodes that utilize acid/base binding groups to attach the molecular Ru sensitizers to TiO₂. The new MOx-ester binding motif is characterized by cyclic voltammetry UV-Vis, solid state ¹³C NMR, and …

From Latent Manifolds To Targeted Molecular Probes: An Interpretable, Kinome-Scale Generative Machine Learning Framework For Family-Based Kinase Ligand Design, Gennady M. Verkhivker, Ryan Kassab, Keerthi Krishnan

Mathematics, Physics, and Computer Science Faculty Articles and Research

Scaffold-aware artificial intelligence (AI) models enable systematic exploration of chemical space conditioned on protein-interacting ligands, yet the representational principles governing their behavior remain poorly understood. The computational representation of structurally complex kinase small molecules remains a formidable challenge due to the high conservation of ATP active site architecture across the kinome and the topological complexity of structural scaffolds in current generative AI frameworks. In this study, we present a diagnostic, modular and chemistry-first generative framework for design of targeted SRC kinase ligands by integrating ChemVAE-based latent space modeling, a chemically interpretable structural similarity metric (Kinase Likelihood Score), Bayesian optimization, and …