Digital Commons Network^™

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio

VMASC Publications

Prior research on power-law distributions has primarily focused on modeling frequency patterns, with less attention given to rank distributions and how ranked positions reflect relative importance among elements. In discrete power-law distributions, frequency-based metrics often provide limited discrimination in the tail, where elements may exhibit similar counts but differ in relative dominance. These patterns are especially evident, for instance, in academic publishing, where keywords, affiliations, and citations commonly exhibit power-law behavior. To address this limitation, we introduce the Relative Importance Factor (RIF) Index, a statistical measure derived from the estimated discrete power-law rank distribution rather than an additional independent parameter. …

Cybersecurity Center For Offshore Wind Energy (Final Project Round), Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models …

Taylorkan-Vit: Parameter-Efficient Vision Transformers For Medical Image Classification, Kaniz Fatema, Dr. Emad Mohammed, Dr. Sukhjit Singh Sehra

Theses and Dissertations (Comprehensive)

Effective and interpretable classification of medical images remains a critical challenge in computer-aided diagnosis, particularly in data-scarce and resource-constrained clinical settings where traditional deep learning models prove impractical. This study addresses the fundamental barrier to Vision Transformer adoption in medical imaging—massive parameter counts and data requirements—through a systematic two-phase methodology. Phase 1 evaluates three spline-based Kolmogorov–Arnold Network (KAN) variants to identify the optimal nonlinear approximation function for parameter-efficient medical image classification: SBTAYLOR-KAN (B-splines with Taylor series), SBRBF-KAN (B-splines with Radial Basis Functions), and SBWAVELET-KAN (B-splines with Morlet wavelets). Comprehensive experiments across brain MRI, chest X-rays, and tuberculosis datasets—without any image …

Flexible Cu Nanostructured Laser-Induced Graphene Electrodes For Highly Sensitive And Non-Invasive Lactate Detection In Saliva, Anju Joshi, Gymama Slaughter

Center for Bioelectronics Publications

A scalable and facile fabrication strategy is presented for developing a flexible, nanostructured, non-enzymatic electrochemical sensor for lactate detection based on copper-modified laser-induced graphene (CuNPs/LIG). A one-step electrodeposition process was employed to uniformly decorate the porous LIG framework with copper nanostructures, offering a cost-effective and reproducible approach for constructing enzyme-free sensing platforms. Scanning electron microscopy and energy-dispersive X-ray spectroscopy confirmed dense Cu nanostructure loading and efficient interfacial integration across the conductive LIG surface. The resulting CuNPs/LIG electrode exhibited excellent electrocatalytic performance, achieving a sensitivity of 8.56 μA µM⁻¹ cm⁻² with a low detection limit of 42.65 …

A Scalable Paper-Based Electrochemical Sensor Employing Mwcnts For Isoniazid Detection, Sri Ramulu Torati, Gymama Slaughter

Center for Bioelectronics Publications

Isoniazid (INZ) is an antimicrobial agent that treats tuberculosis by inhibiting the InhA enzyme in Mycobacterium tuberculosis, making sensitive and reliable methods for routine monitoring essential to ensure safe and effective therapy. We report the development of a novel paper-based electrochemical sensor for the sensitive and selective detection of isoniazid. The sensor is constructed using a gold inkjet-printed electrode (GIPE) modified with gold nanoparticles (AuNPs), chitosan (CH), and multi-walled carbon nanotubes (MWCNTs), forming a GIPE/AuNPs/CH/MWCNTs sensor. Electrochemical deposition of AuNPs effectively addressed insulating gaps generated during the sintering of the gold ink, enhancing electrical conductivity and surface uniformity. The …

Recent Advances In Triboelectric Nanogenerators For Biomedical And Cardiovascular Monitoring, Amit Sarode, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Triboelectric nanogenerators (TENGs) have emerged as versatile self-powered platforms for wearable and implantable biomedical sensing, offering an alternative to battery-dependent electronic devices. By converting biomechanical energy from physiological motion into electrical signals, TENGs enable simultaneous energy harvesting and active sensing within flexible, lightweight, and biocompatible architectures. This review summarizes recent advances from 2020 to 2025 in triboelectric nanogenerator (TENG)-based cardiovascular monitoring. The discussion focuses on material systems, device configurations, sensing mechanisms, and applications including pulse detection and cuffless blood pressure estimation. Representative studies are compared to highlight emerging trends in wearable and self-powered sensing technologies. However, differences in experimental conditions, …

A Portable Potentiostat Integrated With A Pt/Zno/Lig Electrode For Non-Enzymatic Glucose Detection, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Continuous glucose monitoring is critical for effective diabetes management; however, conventional benchtop potentiostats are bulky, costly, and unsuitable for decentralized point-of-care (PoC) applications. To address these limitations, this work presents a miniaturized, low-cost electrochemical sensing platform integrating a non-enzymatic glucose sensor with a portable potentiostat. The sensing electrode is based on laser-induced graphene modified with zinc oxide and platinum nanostructures via electrodeposition to enable sensitive glucose detection under physiological conditions. A custom-designed portable potentiostat was developed to control electrode potentials and perform electrochemical measurements, and its performance was experimentally validated against a commercial Metrohm system. Glucose detection was evaluated using …

Modern Potentiostat Architectures For Electrochemical Sensing: Design, Integration, And Future Directions, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Potentiostats are essential to electrochemical sensing, enabling precise control of electrode potentials and measurement of current responses. As demand grows for portable, wearable, and point-of-care systems, potentiostat design has evolved from benchtop instruments to compact, low-power, and wirelessly connected platforms. This review provides a comprehensive, system-level perspective on modern potentiostat architectures, covering operational principles, analog front-end design, signal generation and acquisition, communication protocols, and software integration. Unlike prior reviews that treat these aspects independently, this work integrates electrochemical theory with electronic design and data communication frameworks. Key components, including operational amplifiers, transimpedance amplifiers, DAC/ADC subsystems, and microcontroller-based control, are examined …

Nanofibrous Materials And Nanoparticles For Combating Antimicrobial Resistance: Synthesis, Integration, And Translational Perspectives, Rewati Raman Ujjwal, Ashish Dilip Sutar, Rahul Shukla, Gymama Slaughter

Center for Bioelectronics Publications

Antimicrobial resistance (AMR) is a major global health challenge driven by mechanisms such as biofilm formation, efflux pumps, and genetic mutations. Nanoparticulate and fibrous materials have emerged as promising strategies to overcome these limitations through multimodal antimicrobial action and controlled drug delivery. This review highlights recent advances in electrospun nanofibrous systems, including natural and synthetic polymer-based scaffolds, stimuli-responsive nanofibers, and functionalized patches. Nanoparticle-loaded nanofiber systems demonstrate enhanced performance, including bacterial eradication, sustained drug release, and significant biofilm disruption. Multifunctional systems combining antimicrobial, antioxidant, and immunomodulatory properties further show synergism. Emerging innovations, such as piezoelectric and smart sensing systems, enable self-powered …

Electrochemical Hemoglobin Biosensors For Point-Of-Care Diagnostics, Ashwini Dantanarayana, Gymama Slaughter

Center for Bioelectronics Publications

Hemoglobin (Hb) and its glycated variant (HbA1c) are essential clinical biomarkers for diagnosing anemia, acute hemorrhage, and long-term glycemic control. The growing demand for decentralized point-of-care (POC) testing has accelerated the development of rapid, inexpensive, and portable electrochemical sensing platforms. These technologies exploit the intrinsic redox activity of the heme prosthetic group, yet achieving efficient direct electron transfer (DET) remains a fundamental challenge because the electroactive iron center is deeply embedded within the globin structure. This review critically examines recent advances in electrochemical Hb sensing, tracing the evolution of electrode architectures from conventional carbon substrates to nanostructured materials, including graphene, …

Remote Sensing-Based Rice Detection: Novel Indices From Optical And Sar Synergy, Kaifi Chomani

Mansoura Engineering Journal

Accurate rice mapping is challenging due to the lack of a simple, efficient approach and the complexity and limited ability of existing methods to distinguish rice fields from non-rice fields. This study proposes two novel indices: the Multispectral Rice Detection Index (MRDI), which utilises optical imagery, and the OptiRadar Rice Index (ORRI), which incorporates both optical and Synthetic Aperture Radar (SAR) data. Ground-truth data from the Cropland Cropping Systems (CROS) were used to assess the performance of both indices. The findings indicated that MRDI achieved an overall accuracy of 97.97% with perfect recall (100%) but lower precision (78.65%). However, the …

Analysis Of Policies And Incentives For The Successful Implementation Of Hydrogen-Fueled Medium-Duty And Heavy-Duty Vehicles In Humboldt County, California, Alka Verma

Cal Poly Humboldt theses and projects

The 21st century has seen a significant rise in global greenhouse gas (GHG) emissions, with the transportation sector contributing 23% of these emissions. Medium-duty and heavy-duty vehicles (MD/HD) are particularly impactful, accounting for over a quarter of transport-related emissions. In Humboldt County, California, transportation represents 53% of total emissions, with MD/HD vehicles being a major contributor. As light-duty vehicles shift to zero-emission alternatives, the MD/HD sector faces unique challenges. Hydrogen fuel cell vehicles offer a promising solution, providing longer range, higher energy density, and quicker refueling compared to battery electric vehicles (BEVs). These features make hydrogen an attractive option for …

Exploring The Interplay Of Operational Conditions, Microbial Communities, And Water Quality In Drinking Water Ozone-Biofiltration, Kara Yvonne Cunningham

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ensuring reliable access to safe drinking water is a growing global challenge as water utilities face variable source water quality driven by population growth, land‑use change, and climate change impacts. To address these challenges, utilities are implementing advanced treatment technologies designed to improve reliability under variable source water conditions. Ozone-biofiltration has emerged as a treatment approach that can reduce a wide range of natural and anthropogenic contaminants. However, despite its increased use, there is limited insight into the biological processes shaping filter function or how they respond to operational and environmental changes. Advances in molecular microbiology and high-throughput sequencing now …

Bridging Physics-Based Modeling And Machine Learning To Predict Material Behavior: Applications In Fatigue Crack Growth And Dielectric Property Characterization, Ansan Pokharel

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation integrates physics-based modeling with machine learning (ML) to predict how materials behave under complex thermal and mechanical conditions. A key innovation of this work is the use of finite element analysis (FEA) to supplement experimental data. This approach creates more diverse and representative synthetic datasets, helping to reduce the limitations and biases that arise when training ML models solely on experimental measurements. The research focuses on two applications: improving the prediction of fatigue properties in superalloys and estimating temperature-dependent, high-frequency dielectric properties relevant to microwave-based chemical processing.

In the first study, low-cycle fatigue experiments were performed on the …

Using Aqueous Geochemistry Of Acid Mine Drainage To Spatially Investigate Concentrations Of Rare Earth Elements Throughout West Virginia, Pennsylvania, And Maryland, Elyssa Lynn Allen

Graduate Theses, Dissertations, and Problem Reports (ETD)

Rare earth elements (REEs) are an important commodity utilized in many industries such as electronics, defense, manufacturing, medicine, and green energy production. A lack of economical domestic sources forces the United States to import a majority of its supply, and incentivizes novel methods of acquisition. Mining regions of the United States, such as Appalachia or the West, are afflicted with acid mine drainage (AMD) impacted surface waters. REEs occur in varying concentrations within coal seams, indicating that coal and its waste are potential avenues of recovery that might also incentivize the remediation of coal impacted areas. Understanding spatial and geochemical …

Hyperglycemia Detection From Sigle - Lead Ecg Using A Hybrid Cnn & Transformer Model, Adam Ayomikun Ogunjembola

Graduate Theses, Dissertations, and Problem Reports (ETD)

Abstract
Hyperglycemia Detection from Single-Lead ECG using a Hybrid CNN & Transformer Model
Adam Ogunjembola

Diabetes Mellitus is known as high blood glucose. This high blood glucose level happens when the body has a problem with producing or using insulin. Insulin is a very important hormone that the pancreas makes to control how much glucose gets into the bloodstream and cells. Diabetes Mellitus has an effect on the body if it is not treated, such as damaging the blood vessels and nerves which can lead to stroke, kidney failure, heart attack and permanent loss of vision. Since people with diabetes …

Development And Validation Of A Multi-Output Neural Network-Based Virtual Temperature Sensor For Electric Vehicle Thermal Management, Dalton Michael Wiggins

Graduate Theses, Dissertations, and Problem Reports (ETD)

Battery electric vehicles (BEVs) rely on accurate thermal management to ensure component performance, efficiency, safety, and long-term durability. Critical propulsion system components, including electric motors and high-voltage battery packs, are commonly monitored using physical temperature sensors. However, these sensors increase system cost, introduce additional hardware complexity, and may be impractical for directly measuring temperatures at critical internal locations. Virtual temperature sensors (VTSs) provide a software-based alternative by estimating component temperatures using readily available vehicle operating data.

This research presents the development and validation of a long short-term memory (LSTM) neural network-based virtual temperature sensor capable of simultaneously estimating the motor …

Analysis Of Battery Degradation Effects On Optimized Torque Splitting In Dual-Motor Electric Vehicles, Homer E. Butcher

Graduate Theses, Dissertations, and Problem Reports (ETD)

Battery electric vehicle performance depends on both powertrain efficiency and battery-health. In dual-motor all-wheel-drive battery electric vehicles, driver-requested torque can be distributed between front and rear electric drive units, creating an opportunity to reduce electrical energy demand through torque allocation. However, lithium-ion battery aging changes the electrical behavior of the energy storage system through capacity fade and internal resistance growth. Capacity fade reduces the usable energy and vehicle range, while resistance growth increases voltage drop, current-related losses, and battery electrical loading. This thesis evaluates how these degradation effects influence the energy consumption, simulated range, and battery electrical behavior of optimized …

Assessing Water Quality In Drinking Water Distribution Systems: Rural Infrastructure Challenges, Hydrodynamic Effects On Biofilms, And Biofilm Contribution To Disinfection By-Products Formation, Vinila Vasam

Graduate Theses, Dissertations, and Problem Reports (ETD)

Access to clean and safe drinking water remains one of the most persistent public health and environmental challenges in the United States. Maintaining water quality after leaving the treatment plant in drinking water distribution systems (DWDS) is a complicated and often overlooked challenge. Most research focuses on water treatment and source water quality, but not on the miles of pipe that follow. Aging infrastructure, complex flow patterns in the DWDS, and limited resources make water quality management especially difficult. This dissertation includes three core studies: 1) A system-level analysis of small and rural utilities in the geographically complex region of …

Detection And Management Of Attacks On Synchronized Networks, Michael T. Spearman

Honors Theses and Capstones

The Precision Time Protocol (IEEE 1588) provides sub-microsecond clock synchronization across packet-switched networks and has become foundational infrastructure in 5G fronthaul, industrial control systems, and financial exchanges. Despite its criticality, most deployed PTP networks operate without active security monitoring, and no standardized detection mechanism exists for the class of attacks that deliberately stay below conventional jitter thresholds. This thesis investigates whether hardware-level ptp4l offset logs alone are sufficient to reliably detect two such attacks, slowly wandering packet delay injection and rogue master spoofing, and whether detection can occur before severe synchronization failure.

A hardware-in-the-loop testbed was constructed using two hosts …

Combining Haptic Feedback With Electromyography To Study Knee Injury In Stationary Cycling, Christopher Kirby

Honors Theses

Patellofemoral Pain Syndrome (PFPS) is the most prevalent overuse injury in cycling, often linked to altered neuromuscular activation patterns of the quadriceps and hamstrings. While sensory feedback has successfully modified cyclists posture, there is a critical lack of evidence-based interventions targeting the underlying muscle activation imbalances associated with chronic knee pain. This study aimed to develop and validate a novel, real-time biofeedback system that utilizes electromyography (EMG) to trigger vibrotactile cues, aiming to shift muscle onset timing earlier in the pedal stroke to mitigate PFPS-related imbalances. A closed-loop system was engineered by integrating a Delsys EMG system with a SageMotion …

Sewer Pipe Condition Assessment Using An Ensemble Machine Learning Framework For Infrastructure Decision Support, Mahnaz Rouhi

Civil Engineering Dissertations

Aging wastewater infrastructure presents significant challenges for municipalities across the United States, with many sewer networks approaching or exceeding their design life. Conventional inspection methods, such as closed-circuit television (CCTV), are limited by subjectivity, cost, and inefficiency. To address these challenges, this study develops an ensemble machine learning framework for assessing the structural condition of sewer pipelines using inspection records enriched with geospatial attributes.

The primary objective of this research is to enhance predictive accuracy, interpretability, and decision-support for risk-based asset management. The scope of the study encompasses 4,802 CCTV inspection records from Dallas, TX, and Tampa, FL, integrating physical, …

A Transdisciplinary Approach To Advancing Water Security And Public Health: The “Nurse + Engineer” Model For Achieving Sustainability In Wash Systems Using Community-Based Participatory Research, Daniel B. Oerther, Sarah Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Human health is linked to the health of the environment, a concept referred to as planetary health. As environmental challenges become increasingly complex, single-disciplinary approaches are insufficient to achieve sustainable solutions. This article presents a transdisciplinary framework, termed the "Nurse + Engineer" model, as a novel methodology for addressing complex problems at the nexus of environmental engineering and public health. The model integrates the technical design and systems-level thinking of environmental engineering with the community-based, patient-centered care of nursing. This work details the key lessons learned from the retrospective application of this framework to a series of multi-year, community-based participatory …

Environmental Engineers Develop Solutions To Problems Of Planetary Health: The Legacy Of Professor P. Aarne Vesilind, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The principal ethical obligation of the engineering profession, to "hold paramount the health, safety, and welfare of the public," has been challenged for decades. Professor P. Aarne Vesilind identified two primary deficiencies: an anthropocentric bias that values nature only instrumentally and the use of non-mandatory, aspirational language for environmental protection, which resulted in the exclusion of enforceable environmental canons. This paper argues that two recent developments provide a comprehensive response to Vesilind's recommendations for engineering ethics. First, the United States Bureau of Labor Statistics has redefined environmental engineering as "developing solutions to problems of planetary health." Second, Oerther proposed a …

Sainik Vol 1 Issue 2, Sastra Deemed To Be University

SAINIK

No abstract provided.

Powering The Machine, Draining The Planet: Whether U.S. Environmental Law Is Equipped To Regulate The Energy And Water Demands Of Ai Data Centers, Michael Marcu

Journal of Earth and Life Science

Artificial intelligence (AI) data centers have become one of the United States' fastest-growing and least-regulated sources of environmental stress. In 2024 alone, U.S. data centers consumed 183 terawatt-hours (TWh) of electricity more than the entire nation of Pakistan and consumed an estimated 17 billion gallons of water (IEA, 2025; Berkeley Lab, 2024). By 2030, electricity demand from these facilities is projected to reach 426 TWh, a 133% increase in six years (Pew Research Center, 2025). This paper examines whether the existing U.S. environmental regulatory framework put by the National Environmental Policy Act (NEPA), the Clean Water Act (CWA), and the …

Fiber-Reinforced Composites For Vaginal Tissue Engineering Applications, Samyuktha S. Kolluru, Abir Hamdaoui, Annabella M. Mascot, Siobhan S. Sutcliffe, Jerry L. Lowder, Michelle L. Oyen, Samantha G. Zambuto

Mechanical Engineering Faculty Publications

The vagina is a fibromuscular tube-shaped organ that plays critical roles in menstruation, pregnancy, and female sexual health. Vaginal tissue constituents, including cells and extracellular matrix components, contribute to tissue structure, function, and prevention of injury and pathology. However, much microstructural function remains unknown, including how the fiber-cell and cell–cell interactions influence macromechanical properties. A deeper understanding of these interactions will provide critical information needed to reduce and prevent vaginal pathologies. Our objective for this work is to design a novel tissue-mimicking biomaterial for vaginal tissue engineering, and characterize its biological and mechanical performance in the vaginal microenvironment. We successfully …

Paraná Fiz, Cloey Dias

Student Research Design & Innovation Symposium

This project focused on the conceptualization and design of a beverage brand inspired by the Paraná River located in Argentina. The river, the second longest in South America, was used as both a cultural and visual reference, symbolizing movement, energy, and natural vitality. These characteristics guided the overall concept and aesthetic direction of " Paraná Fiz", a yerba mate-infused soda water brand. The product aimed to merge traditional Argentine influences with a modern beverage format through flavors inspired by popular Argentine fruits. The project involved extensive visual branding development, including the creation of a custom logo, four distinct flavor identities, …

Fairness Without Demographic Attributes In Medical Vision–Language Models, Ahsan Habib Akash

Graduate Theses, Dissertations, and Problem Reports (ETD)

Vision–language models (VLMs) and the embedding models that underlie them have become the default representation layer for multimodal artificial intelligence. Trained by contrastive alignment over enormous, loosely curated image–text corpora, they inherit the demographic skew of that data, and they encode it in the geometry of the shared embedding space itself. The consequence is a model that performs unevenly across demographic groups even when no protected attribute is ever supplied as an input. In consumer applications this is an equity problem; in medicine it is a safety problem, because an embedding that is systematically less discriminative for one subpopulation translates …

Dielectrophoretic Biomarkers For Cancer Detection And Cell Analysis: Integrating Microfluidics And Ai, Raphael Olumide Oladokun

Graduate Theses, Dissertations, and Problem Reports (ETD)

Pancreatic ductal adenocarcinoma (PDAC) carries a five-year survival rate of 13%, driven largely by late-stage diagnosis and the absence of sensitive noninvasive screening tools. Current diagnostic methods lack the sensitivity to detect disease-associated systemic changes at early and precancerous stages, representing a critical clinical gap. This dissertation addresses the central hypothesis that PDAC and its pathological subtypes induce measurable, disease-associated electrophysiological changes in circulating PBMCs that can serve as correlative liquid-biopsy biomarkers. To test this hypothesis, this work asks: can dielectrophoresis (DEP), impedance and zeta potential analysis with AI-assisted classification distinguish benign pancreatic conditions (non-malignant control), precancerous lesions (primarily IPMNs), …