Digital Commons Network^™

The Effects Of Bicultural Identity On Risk-Taking And Moral Decision-Making In South Asian American College Students, Meera Puthukkudy

Honors Undergraduate Theses

The intent of this thesis was to explore how biculturalism in South Asian American college students impacts their behaviors, specifically moral decision-making and risk-taking behaviors. Bicultural individuals must navigate the complexities of their identity by integrating norms, values, and expectations from both their heritage culture and their dominant Western culture, which inherently creates a unique cognitive and psychological framework for evaluating choices. Participants in this study completed a survey online and were asked to complete three measures. First, the extent to which participants feel cultural harmony or conflict between their respective cultural identities was measured using the Bicultural Identity Integration …

To Print A Remake: An Analysis Of Hollywood Remakes And Their Cultural Value, Connor F. Seaton

Honors Undergraduate Theses

In recent years, audiences and movie critics have expressed concern that Hollywood’s growing reliance on remakes, sequels, franchises, and similar adaptations has led to a broader worry that originality is fading from modern cinema and that the industry is instead focused on using adaptations to maximize profits. Although adaptation is often seen as a commercially driven framework for reproducing existing intellectual property in a new media format, this thesis argues that it should be recognized as an autonomous cultural category with its own artistic, historical, and social significance and merit. By analyzing adaptation scholarship and reviewing its complex historical development, …

The Role Of The Amygdala In Huntington Disease-Associated Aggression, Luis Torres

Honors Undergraduate Theses

Huntington disease (HD) is a fatal neurodegenerative disorder caused by a trinucleotide CAG expansion in the huntingtin gene (HTT). HD is characterized by motor, cognitive, and psychiatric symptoms that significantly impact patient and caregiver quality of life. Psychiatric symptoms, including depression, anxiety, and irritability, are common manifestations of HD and can emerge years before the onset is clinically diagnosed. Aggression is a common and challenging psychiatric symptom in HD, often misunderstood and associated with caregiver stress, early institutionalization, and reduced quality of life. Despite its clinical impact, aggression in HD lacks effective, targeted treatment options. Similar to HD …

How Religious Priming Affects Morality In Sports, Daniel Prias

Honors Undergraduate Theses

This research focuses on filling the hole in existing literature regarding religious priming and how it affects morality in sports. This study examined whether different types of moral priming influenced moral reasoning in undergraduate soccer athletes. Participants were randomly assigned to one of four conditions: an external religious prime, an internal religious prime, a secular prime, or a no-prime control group. Moral reasoning was assessed using the Moral Reasoning in Sports Scenarios Questionnaire (MRSSQ), strength of religious faith was measured using the Santa Clara Strength of Religious Faith Questionnaire (SCSRFQ), and personality traits were assessed using the Mini International Personality …

Symbolic Racism And Punitive Policy Preferences In The First Quarter Of The Twenty-First Century, Anthony T. Fulinello

Honors Undergraduate Theses

Despite the decay in the acceptability of explicit racism brought about by the passage of the Civil Rights Act of 1964, implicit racism may continue to inform individual decision making even into the first quarter of the twenty-first century. Utilizing data from 25 years of the General Social Survey, this study examines how indicators of symbolic racism, a form of implicit racism, impact punitive policy preferences among the general United States population using separate logistic regression models isolating each indicator, plus a full model, for each outcome. Punitive policy preferences were operationalized as support for increased spending on crime prevention …

Breaking The Resistance: A Narrative Review Of The Evolution From Traditional Drugs To Precision Therapies In Epilepsy, Tirath Patel, Fathimathul Henna, Ashfaq Ahmed, Ayesha Ahmad, Noor Ul Huda, Syed Aaraiz Ul Hassan, Aiman Muhammad, Amna Javed, Maryem Filal, Nikhilesh Anand

School of Medicine Publications

Background: Epilepsy is a chronic neurological disorder characterized by recurrent seizures, affecting approximately 50 million individuals globally. While conventional antiseizure medications (ASMs) control seizures in 70-80% of patients, about 30% experience drug resistance or intolerable side effects, necessitating alternative approaches.

Objective: To critically compare the efficacy, safety, and accessibility of conventional and emerging therapies for epilepsy, particularly in the context of treatment-resistant cases and global disparities in care.

Methods: This narrative review synthesized evidence from 120 peer-reviewed articles published between 2015 and 2025. Literature was retrieved from PubMed, Embase, Cochrane Library, and Scopus using predefined search terms related to epilepsy …

Reduced Threat-Related Neural Efficiency: A Possible Biomarker For Pediatric Anxiety Disorders, Julia O. Linke, Reut Naim, Simona P. Haller, Parmis Khosravi, Beck Scheinberg, Meghan E. Byrne, Anita Harrewijn, Ellen Leibenluft, Melissa A. Brotman, Anderson M. Winkler, Daniel Samuel Pine

School of Medicine Publications

Objective: Pediatric anxiety disorders are common and predict adult psychopathology, yet current treatments, such as cognitive-behavioral therapy (CBT), produce lasting remission in less than 50% of affected youths. To support the search for improved, mechanistically grounded interventions, this study evaluated neural efficiency, defined as similarity in functional connectivity between a threat task and rest, as a potential biomarker. The study evaluated neural efficiency in relation to anxiety diagnosis and treatment response.

Methods: The authors compared 103 youths with an anxiety disorder diagnosis (mean age, 12.5 years [SD=2.91], 62% female) to 103 youths with no psychiatric diagnosis (mean age, 13.4 years …

Oregon’S History Of Using The Law To “Stack The Deck” In Favor Of White Males, Janet Steverson

Lewis & Clark Law Review

The United States has a sordid, racist history that permeates society still today. The State of Oregon has its own racist history, systematically excluding persons of Black African ancestry in its early years. This Essay explains this history and how seemingly historical practices continue to provide advantages to some, while detrimentally impacting others. This history is put in context by providing explanations of particular terms and this Essay further explains why examining these historical laws are critical in moving forward.

Taking Off The “Blindfold”: Exploring Montana’S Public Trust Doctrine And The Right To A Clean And Healthful Environment After Held V. Montana, Lizzy Gazeley

Lewis & Clark Law Review

As global average temperatures continue to rise, the threat of climate change looms closer. To evade climate catastrophe, greenhouse gas emissions will need to be substantially reduced. Despite climate change’s imminent risks, in the United States, both the federal government and states remain resistant to transitioning away from fossil fuel energy sources. To combat this government inaction, some litigants have turned to an ancient doctrine. The public trust doctrine provides that sovereigns must protect natural resources from substantial impairment to ensure the public’s right to use those resources.

In Held v. Montana, youth plaintiffs alleged that the State of Montana …

Immigration Federalism And The Promise Of State Constitutions, Joanne Gottesman

Lewis & Clark Law Review

This Article explores state constitutions’ promises and pitfalls for immigrant rights advocacy. This is a particularly urgent endeavor, given the anti-immigrant measures of President Trump’s second term and a U.S. Supreme Court that is willing to reverse longstanding precedent. Even cases like Plyler v. Doe, with its guarantee of free public education to undocumented children, could be vulnerable. While U.S. Supreme Court opinions protecting immigrant rights are the gold standard because they apply nationwide, state courts and state constitutions provide critical alternative avenues for relief that should not be overlooked.

This Article considers some state constitutional provisions that may help …

From Chainsaws To Courtrooms: Corporate Climate Litigation And Deforestation In Brazil, Maria Antonia Tigre, Mariana Barbosa Cirne

Lewis & Clark Law Review

Corporate climate litigation has emerged as one of the most dynamic and high-profile tools for addressing the private sector’s role in the climate crisis. While much of the scholarship and public debate has centered on cases in the United States and Europe, litigation targeting corporations in the Global South—particularly Brazil—has grown rapidly, both in volume and significance. Brazil now ranks among the world’s top jurisdictions for corporate climate damage claims. These suits have pioneered methods for quantifying climate damages, often from illegal deforestation, and have tested the reach of the civil liability regime in novel ways. This Article offers the …

Regulated Victimization: The Rise Of Human Trafficking Within The Oregon Massage Industry, Hannah Beaulieu

Lewis & Clark Law Review

Illicit massage businesses are massage spas that appear to operate as legitimate businesses but facilitate commercial sex acts behind closed doors. Recent law enforcement investigations in Oregon have revealed that some illicit massage businesses have facilitated the human trafficking of multiple victims. The illicit massage industry has steadily grown across the country but has especially boomed in recent years in Oregon. This Note investigates how the illicit massage industry has evolved to be so prevalent in our communities and what factors have contributed to the growth. It goes on to recommend ways to protect victims, to prevent further harm, and …

Quo Warranto In The Aftermath Of Loper Bright, Dennis Hall

Lewis & Clark Law Review

In 2024, the Supreme Court did away with Chevron deference in Loper Bright Enterprises v. Raimondo. One previously undiscussed consequence of this decision is how it opens the door to a broader use of quo warranto corporate charter revocation. Quo warranto is a legal remedy held by the states that has fallen into relative obscurity, but it has the power to regulate large corporations that have strayed from the bounds of acceptable activity. This Comment examines the history of corporations and corporate oversight regulation in the United States, as well as the history of quo warranto as a remedy. Additionally, …

Multi-Period Coordinated Planning Of Xfcs In Coupled Tn-Pdn Networks: Integrating Demand Charge Reduction And Pre-Existing Infrastructure, Waqas Ur Rehman, Siyuan Wang, Liheng Lv, Jonathan W. Kimball, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate charging infrastructure support. This paper aims to address the latter bottleneck and proposes a strategic multi-period coordinated planning model to optimally site and size battery energy storage system (BESS) assisted extreme fast charging stations in a highway transportation network and solar systems in a power distribution network. The proposed approach accounts for pre-existing charging stations, the increasing EV penetration levels, decreasing technology costs, and technological advancements in the future and …

Temperature Compensation In Loop And Patch Fss Strain Sensors: Analysis And Experimental Validation, Swathi Muthyala Ramesh, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are arrays of conductive elements or apertures that exhibit frequency-dependent reflection and transmission properties. Their electromagnetic response is influenced by geometry and environmental conditions, making them attractive for wireless strain-sensing applications. However, temperature variations can produce frequency shifts similar to those caused by strain, reducing measurement accuracy. This work investigates the effects of intrinsic temperature compensation on two common FSS unit cell geometries—loop and patch—through comprehensive simulation analysis. The results show that loop-based cells offer superior thermal stability, while patch-based cells provide greater strain sensitivity, illustrating the trade-off between thermal robustness and mechanical responsiveness. A patch-type …

Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Metal-coated optical fibers are widely employed in sensing applications owing to their superior mechanical strength and corrosion resistance. However, their calibration at elevated temperatures is hindered by hysteresis, manifested as discrepancies between heating and cooling cycles, primarily caused by residual strain from mismatched thermal expansion coefficients (TECs) between the metal coating and silica cladding. This research introduces an optimal heat treatment procedure aimed at minimizing the impact of the mismatch in TECs between the cladding and the coating materials that causes the residual strain in gold (Au) and copper (Cu) coated fibers for achieving reliable distributed high temperature sensing up …

Large Language Models For Neurology: A Mini Review, Donald C. Wunsch, Daniel B. Hier

Electrical and Computer Engineering Faculty Research & Creative Works

Large language models have the potential to transform neurology by augmenting diagnostic reasoning, streamlining documentation, and improving workflow efficiency. This Mini Review surveys emerging applications of large language models in Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy, with emphasis on ambient documentation, multimodal data integration, and clinical decision support. Key barriers to adoption include bias, privacy, reliability, and regulatory alignment. Looking ahead, neurology-focused language models may develop greater fluency in biomedical ontologies and FHIR standards, improving data interoperability and supporting more seamless collaboration between clinicians and AI systems. Two future developments have the potential to be particularly impactful: (1) …

Evaluation Of Multiple Generative Large Language Models On Neurology Board-Style Questions, Mohammad Almomani, Vijaya Valaparla, James Weatherhead, Xiang Fang, Alok Dabi, Chih Ying Li, Peter Mccaffrey, Dan Hier, Jorge Mario Rodríguez-Fernández

Electrical and Computer Engineering Faculty Research & Creative Works

Objective: To compare the performance of eight large language models (LLMs) with neurology residents on board-style multiple-choice questions across seven subspecialties and two cognitive levels. Methods: In a cross-sectional benchmarking study, we evaluated Bard, Claude, Gemini v1, Gemini 2.5, ChatGPT-3.5, ChatGPT-4, ChatGPT-4o, and ChatGPT-5 using 107 text-only items spanning movement disorders, vascular neurology, neuroanatomy, neuroimmunology, epilepsy, neuromuscular disease, and neuro-infectious disease. Items were labeled as lower- or higher-order per Bloom's taxonomy by two neurologists. Models answered each item in a fresh session and reported confidence and Bloom classification. Residents completed the same set under exam-like conditions. Outcomes included overall and …

Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

An output feedback (OF)-based control scheme utilizing both a scalable multilayer neural network (MNN) observer and actor–critic MNN via integral reinforcement learning (IRL)/adaptive dynamics programming (ADP) approach for a class of nonlinear systems with output constraints is introduced. The proposed observer, critic, and actor MNN weight updates are derived using a singular value decomposition (SVD) of MNN activation function gradient along with output error, Bellman and control input errors, respectively. Next, the approach incorporates continual learning (CL), utilizing a penalty function in the weight update laws for both actor–critic MNNs to consolidate knowledge from previous tasks and enhance learning in …

Multi-Parameter Optimization And Adaptive Temperature Compensation For Fbg Strain Sensors In Wide-Temperature-Range Aerospace Applications, Ruling Zhou, Jiacheng Yu, Yutang Dai, Jianguan Tang, Minghong Yang, Farhan Mumtaz

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate strain measurement in cryogenic fuel pipelines is crucial for ensuring the structural integrity and reliability of rocket engine systems operating under extreme thermal conditions. Fiber Bragg grating (FBG) sensors show significant potential for such applications; however, their inherent temperature-strain cross-sensitivity limits performance over wide temperature ranges. This research presents an enhanced compensation strategy combining multi-parameter optimization with temperature-zone-specific adaptation to improve the accuracy and stability of FBG-based strain sensing in harsh aerospace environments. Four special steel substrate materials including S03, S06, S07, and 1Cr18Ni9Ti, were evaluated using strain transfer theory and thermo-mechanical coupling simulations. Genetic algorithms optimized key design …

Safe Optimal Control Framework For Cooperative Manipulation Of Objects In Human–Robot Teams, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article introduces a distributed deep neural network (NN)-based adaptive control framework for cooperative object manipulation in human–robot teams with unknown agent dynamics by using three distinct multilayer NN observers (MNNOs). The first observer, termed the reference point estimator, enables each robotic agent to estimate the object's reference center using consensus-based learning, even without direct access to global reference trajectories. The second observer, referred to as the human force-to-trajectory estimator, uses human-applied forces to infer the intended position, velocity, and acceleration of the object, enabling real-time estimation of human intent. Together, these two observers allow distributed estimation of human-intended motion. …

High-Resolution, Fast-Response Optical Fiber Temperature Sensor With A Large Measurement Range Based On Fiber-Tip Alumina Fabry-Pérot Interferometer, Ruimin Jie, Chen Zhu, Robert Abbott, Michael Davis, Xiong Zhang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We present an alumina-tip optical fiber Fabry-Pérot interferometric temperature sensor exhibiting high-temperature performance, rapid response, and high resolution. Fabricated by fusion splicing an alumina micro disk directly to a single-mode fiber, the sensor achieves robust, stable operation without complex fabrication processes or adhesives. Experimental evaluation confirms a measurement range extending to 1000°C, with sensitivity of 28.66 pm/°C, a resolution of 0.042°C, and a rapid response time of approximately 13 ms. Compared to state-of-the-art optical fiber FPI sensors, our alumina-tip sensor offers superior overall performance, effectively addressing critical demands for high-resolution, fast-response temperature measurement in extreme environments including aerospace, structural monitoring, …

Waveguide-Assisted Single-Mode Fiber Bragg Gratings In A Highly Multimode Coreless Fiber Via Femtosecond Laser Inscription For Extreme Temperature Quasi-Distributed Thermal Sensing, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This research reports a potential quasi-distributed thermal mapping optical sensing system for extreme temperatures, leveraging femtosecond (fs) laser inscribed single-mode fiber Bragg gratings (FBGs) and a waveguide within coreless, highly multimode optical fiber, resulting in a single-mode structure. Unlike doped single-mode fibers, coreless fibers composed of silica rods prevent issues associated with dopant migration and ensure data accuracy. The strategic placement of point-by-point FBGs in a cascaded formation on the fs-laser inscribed waveguide facilitates localized multipoint sensing. The long-term stability of the proposed waveguide-assisted FBG system was assessed over 24 hours at elevated temperatures (1000°C), showing no hysteresis during heating …

Embeddable Optical Fiber Sensor For Simultaneous Strain And Temperature Monitoring, Amardeep Kaur, Sudharshan Anandan, Steve Eugene Watkins, Yinan Zhang, Kumbla Chandrashekhara, Hai Xiao

Electrical and Computer Engineering Faculty Research & Creative Works

We present an embeddable hybrid optical fiber sensor based on a cascaded extrinsic Fabry–Pérot interferometer (EFPI) and intrinsic Fabry–Pérot interferometer (IFPI) for simultaneous strain and temperature monitoring in high-performance composite materials. The sensor is fabricated using femtosecond laser micromachining and is embedded within bismaleimide composite laminates manufactured via an out-of-autoclave process. Experimental results demonstrate linear and decoupled responses to strain and temperature, with the EFPI showing minimal temperature sensitivity (1.7 pm/°C) and the IFPI exhibiting high temperature sensitivity (16.1 pm/°C). Strain sensitivities for both components were consistent at 0.6pm/με in embedded conditions. The sensor maintained structural integrity and stable spectral …

Distributed Temperature Sensing In The Spray-Cooled Shell Of A 150-Ton Dc Electric Arc Furnace Using Brillouin Optical Fiber Technology, Farhan Mumtaz, Yeshwanth Reddy Mekala, Koustav Dey, Rony Kumer Saha, Ogbole Collins Inalegwu, Manoj Kumar Pullagura, Bohong Zhang, Muhammad Roman, Nicholas Dionise, Zane Voss, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the deployment and validation of a Brillouin - distributed temperature sensing (DTS) system for real-time thermal monitoring of the spray-cooled upper shell of a 150-ton direct current Electric Arc Furnace (DC EAF) at Big River Steel Plant, Osceola, AR, USA. A four-channel Brillouin DTS system from OZ Optics was employed, with one active channel instrumented using an in-house-fabricated Brillouin scattering-depressed single-mode optical fiber (SMF28e+). The 60 m optical fiber sensor was fabricated, with 20 m allocated for thermal measurement and 40 m used as lead-in fiber to isolate the interrogator from the furnace environment. The fiber was …

Self-Calibrating Uav Navigation: Reinforcement Learning Approaches For Horizontal Trajectory Estimation, Shirin Nasr-Esfahani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate unmanned aerial vehicle (UAV) trajectory estimation is essential for autonomous navigation, particularly in GPS-denied environments. Visualodometry and simultaneous localization and mapping (SLAM) approaches require precise camera intrinsic parameters, which are typically obtained through predefined or offline calibration. Instead, in this work, we propose a reinforcement learning (RL)-based self-calibration framework that estimates camera intrinsic parameters directly from monocular video sequences, without requiring prior knowledge of the camera, environment, or calibration targets. This intrinsic parameter estimation is then leveraged to achieve robust UAV trajectory estimation using only video data. We formulate the problem as a sequential decision-making task, where an RL …

Performance Analysis And Optimization Of Fructose Memristor-Based Neuromorphic Systems, Harshvardhan Uppaluru, Shakil Mahmud Jiban, Shah Zayed Riam, Feng Zhao, Jinhui Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Natural organic memristors have demonstrated promising synaptic behavior, positioning them as strong candidates for synaptic devices in neuromorphic systems. This paper presents the fabrication and evaluation of a neuromorphic system based on natural organic 16-level and 32-level fructose memristors. First, the manufacturing process of fructose memristors is described in detail. Second, the nonlinear property associated with fructose memristors is investigated, and an optimization method is applied to address the nonlinear effects. The performance of the fructose memristor-based neuromorphic system on MNIST with a multi-layer perceptron and on CIFAR-10 with VGG-8 is evaluated and reported under various conditions -with/without nonlinearity optimization …

Integrating Optical And Radiofrequency Interferometry For Enhanced Phase Sensing, Ruimin Jie, Zhaopeng Zhang, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Interferometry is a crucial investigative technique used across diverse fields to achieve high-precision measurements. It works by analyzing the phase difference between two interfering waves, which results from variations in optical path lengths within an interferometer. We introduce a novel method for directly measuring changes in the phase difference within an optical interferometer, importantly, with the added advantage of a controllable enhancement factor. This approach is achieved through a two-step process: first, the optical phase difference is encoded into a sub-GHz radiofrequency (RF) signal using microwave-photonic manipulation; then, RF interferometry-assisted phase amplification is implemented at the destructive interference point. In …

Online Lifelong Optimal Adaptive Control Of Partially Uncertain Strict Feedback Discrete-Time Systems With Application To Quadrotor Uavs, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal adaptive tracking control of partially uncertain strict feedback discrete-time (DT) systems with application to quadrotor uncrewed aerial vehicles (UAVs). First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of the tracking error dynamics. The optimal adaptive tracking control problem is solved using an augmented system approach, where a horizon of future bounded reference trajectory points is used in the augmented state, when compared to using a single point. It is assumed that the internal dynamics of the strict feedback system are unknown, but the …

New Metrics For Disambiguating Feature Overlap And Catastrophic Forgetting In Incremental Learning Contexts, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Catastrophic forgetting remains a central challenge in lifelong learning, where newly acquired knowledge interferes with previously learned tasks, degrading performance over time. Mitigation strategies such as rehearsal and regularization have been proposed, but both introduce limitations, either by retaining old data or by constraining model updates in ways that may impair learning. Complicating matters, recent findings show that feature-space overlap between tasks can produce similar performance drops even in models that memorize data, making it difficult to distinguish true forgetting from representational interference. Current accuracy-based metrics fail to disentangle these effects, undermining diagnostic clarity. In this work, we introduce the …