Digital Commons Network^™

Preserving Privacy In Senior Care At Home Monitoring Systems, Sam Russel, Ryan Benton, Amy Campbell, Scott Sittig

Shelby Hall Graduate Research Forum Posters

Many seniors prefer to live at home which necessitates research into the application of technologies to provide a safer environment with less caregiver resources. However, the application of home health care (HHC) monitoring for seniors is still in an evolutionary stage. Present HHC systems are produced by private companies with general regulatory guidelines lacking specific care of the elderly. As such, each company that produces such a system claims to have better safety, privacy, and security that their competitors. A pressing issues is devising and applying a general framework for the application of technologies that delivers safety while preserving privacy. …

False Narratives, Real Consequences, Russell W. Cantrell, Matt Campbell

Shelby Hall Graduate Research Forum Posters

Social media is an increasingly significant tool in modern cyber warfare, capable of rapidly shaping public opinion. The swift dissemination of information complicates efforts to distinguish fact from fiction [1]. During public health crises, healthcare professionals use these platforms to share updates, yet their credible content must contend with false or deliberately misleading narratives [2]. This environment creates an opportunity for cyberattacks through social media influence campaigns [3]. While disinformation's role in political interference has been widely studied, its potential to destabilize healthcare remains largely unexplored. Prior research primarily focuses on how vaccine misinformation affects the general public [4]. This …

Detecting Sensor Data Manipulation, Ricky Green, Michael Black

Shelby Hall Graduate Research Forum Posters

The integration of Information Technology (IT) and Operational Technology (OT) have made OT devices vulnerable to threats that have been successfully exploited with devastating results. Many modern techniques for hardening and securing enterprise IT systems are either incompatible with OT components in an Industrial Control System (ICS), reduce the efficiency of processes, or are prohibitively expensive to implement. Research in the area of ICS security focuses on a top-down approach, such as intrusion prevention by securing the perimeter of the network and hardening computer systems. This approach is useful in business IT systems, but full compatibility with OT components in …

Topical Text Segmentation For Stream Of Consciousness Writing, Yuwei Lu, Ryan Benton

Shelby Hall Graduate Research Forum Posters

Stream of consciousness writing has a long history, including novelists James Joyce and Virginia Woolf. However, there has been little work done in automated and semi-automated analysis of such writing, which is the focus of this work. We plan to divide real streams of consciousness writing into distinct topical units and then capture different momentary meaningful topics from these units. By doing this, researchers and readers could gain a more nuanced understanding of the narrative structure and thematic elements. In addition, it would also support applications in fields like psychology and linguistics, where understanding thought processes and narrative structures is …

Modelled Flooding Impacts On Lower Fish River Watershed, Sebastian Loschner

Shelby Hall Graduate Research Forum Posters

This study investigates the impacts of compound flooding in the Lower Fish River watershed, Baldwin County, Alabama, with a focus on the potential effects of sea level rise due to climate change. Coastal flooding, particularly in smaller watersheds, is a growing concern as it results from the interaction of multiple factors, including rainfall, tidal changes, and extreme weather events. Compound flooding, which involves multiple flood drivers, is expected to worsen with climate change, as increased precipitation and rising sea levels create heightened flood risks. However, existing research on compound flooding predominantly focuses on large-scale watersheds, leaving a knowledge gap in …

Using Machine Learning Models To Improve The Cyber Physical Security Of Drones, Sean Lee, Aviv Segev

Shelby Hall Graduate Research Forum Posters

This research proposes a new manner of implementing machine learning models such that, when applied on a drone, it will be able to accurately identify and maintain the authenticity of the entity sending the control data to the drone. To begin with, the drone will, for a pre-determined amount of signals received per unit time, determine the average signal strength (RSSI) of them and use that average to determine the approximate distance between the drone and the source of those signals. This single data point will be fed into a custom implementation of the SCluStream algorithm (a real-time clustering machine …

A Mathematical Model Of The Electrical Power Management Systems Using The Core Values In Cooperative Game, Mohammed Musa, Jabbar Abbas

Journal of Applied Sciences and Nanotechnology

In the context of game theory, cooperative game has been applied in several fields and can be successfully used to evaluate the players (people or companies) involved. In cooperative game theory, the core is a concept that represents the set of feasible allocations (or distributions of total payoff) among players that cannot be improved upon by any coalition of players. This paper aims to apply a mathematical model to modeling cooperation among power stations and fuel supply producers using a core value-based optimization algorithm. We use the cooperative game to show the potential cost in cooperation through an optimization algorithm …

Proceedings Of The National Cancer Institute Workshop On Combining Immunotherapy With Radiotherapy: Challenges And Opportunities For Clinical Translation, Zachary S Morris, Sandra Demaria, Arta M Monjazeb, Silvia C Formenti, Ralph R Weichselbaum, James Welsh, Heiko Enderling, Jonathan D Schoenfeld, Joshua D Brody, Heather M Mcgee, Michele Mondini, Michael S Kent, Kristina H Young, Lorenzo Galluzzi, Sana D Karam, Willemijn S M E Theelen, Joe Y Chang, Mai Anh Huynh, Adi Daib, Sean Pitroda, Caroline Chung, Raphael Serre, Clemens Grassberger, Jie Deng, Quaovi H Sodji, Anthony T Nguyen, Ravi B Patel, Simone Krebs, Anusha Kalbasi, Caroline Kerr, Claire Vanpouille-Box, Logan Vick, Todd A Aguilera, Irene M Ong, Fernanda Herrera, Hari Menon, Deedee Smart, Jalal Ahmed, Robyn D Gartrell, Christina L Roland, Fatemeh Fekrmandi, Binita Chakraborty, Eric H Bent, Tracy J Berg, Alan Hutson, Samir Khleif, Andrew G Sikora, Lawrence Fong

Faculty, Staff and Student Publications

Radiotherapy both promotes and antagonises tumour immune recognition. Some clinical studies show improved patient outcomes when immunotherapies are integrated with radiotherapy. Safe, greater than additive, clinical response to the combination is limited to a subset of patients, however, and how radiotherapy can best be combined with immunotherapies remains unclear. The National Cancer Institute-Immuno-Oncology Translational Network-Society for Immunotherapy of Cancer-American Association of Immunology Workshop on Combining Immunotherapy with Radiotherapy was convened to identify and prioritise opportunities and challenges for radiotherapy and immunotherapy combinations. Sessions examined the immune effects of radiation, barriers to anti-tumour immune response, previous clinical trial data, immunological and …

Wayne E. Sabbe Arkansas Soil Fertility Studies 2024, Nathan A. Slaton

Arkansas Agricultural Experiment Station Research Series

Rapid technological changes in crop management and production require that the research efforts be presented in an expeditious manner. The contributions of soil fertility and fertilizers are major production factors in all Arkansas crops. The studies described within will allow producers to compare their practices with the university’s research efforts. Additionally, soil-test data and fertilizer sales are presented to allow comparisons among years, crops, and other areas within Arkansas.

Difference-Makers For Collecting Sexual Orientation And Gender Identity Data In Oncology Settings, Mandi L Pratt-Chapman, Edward J Miech, Megan A Mullins, Shine Chang, Gwendolyn P Quinn, Shail Maingi, Matthew B Schabath, Charles Kamen

Faculty, Staff and Student Publications

Purpose: The purpose of this analysis was to identify key difference-making conditions that distinguish oncology institutions that collect sexual orientation and gender identity (SOGI) data across a sample of American Society of Clinical Oncology (ASCO) members.

Methods: From October to November 2020, an anonymous 54-item web-based survey was distributed to ASCO members. Coincidence analysis was used to identify difference-making conditions for the collection of SOGI data.

Results: ASCO members' responses to just three items consistently distinguished practices that reported collecting both SO and GI data (n = 25) from those who did not (n = 20): (1)."Do you ask your …

Qsp Modeling Shows Pathological Synergism Between Insulin Resistance And Amyloid-Beta Exposure In Upregulating Vcam1 Expression At The Bbb Endothelium, Zengtao Wang, Vaishnavi Veerareddy, Xiaojiao Tang, Kevin J Thompson, Sunil Krishnan, Krishna R Kalari, Karunya K Kandimalla

Faculty, Staff and Student Publications

Type 2 diabetes mellitus (T2DM), characterized by insulin resistance, is closely associated with Alzheimer's disease (AD). Cerebrovascular dysfunction is manifested in both T2DM and AD, and is often considered as a pathological link between the two diseases. Insulin signaling regulates critical functions of the blood-brain barrier (BBB), and endothelial insulin resistance could lead to BBB dysfunction, aggravating AD pathology. However, insulin signaling is intrinsically dynamic and involves interactions among numerous molecular mediators. Hence, a mechanistic systems biology model is needed to understand how insulin regulates BBB physiology and the consequences of its impairment in T2DM and AD. In this study, …

Treating Ground Water For Agricultural And Individual Consumption, Gabby Miller, Bronson Scott, Michael Clawson

Biomedical Engineering

This project, conducted in collaboration with Cal Poly seniors and Da Vinci High School students, aims to develop a solar-powered groundwater purification system. This system is designed to provide clean water for agricultural use and individual consumption, addressing the growing concerns of groundwater contamination and accessibility needs. The final prototype integrates a gravity filtration system combined with chemical purification, utilizing aluminum sulfate and chlorine to remove particulates, bacteria, and organic compounds.

The research phase involved an extensive review of groundwater contamination issues, existing filtration technologies, and market analysis. Key design constraints included cost-effectiveness, ease of maintenance, and minimal energy consumption, …

Tiny Temp Neonatal Intensive Care Unit Infant Temperature Monitor, Alexandria Lukacsffi, Sydney Dedrick

Biomedical Engineering

This document outlines the key steps taken in the specification, design, and functionality of the Tiny Temp Neonatal Intensive Care Unit Infant Temperature Monitor. The BICEP team identified temperature monitors for infants in incubators in the NICU as an area of need after surveying hospitals in the San Luis Obispo area. Current thermometers are oversimplified in design, consisting of only the temperature probe and a piece of adhesive holding the probe directly onto the infant's skin. As a result, the adhesive is weak to prevent harm to the infant and, therefore, falls off the infant easily and frequently, posing a …

Experimental Approaches To Investigate Biophysical Interactions Between Homeodomain Transcription Factors And Dna, Fadwa Mekkaoui, Robert A. Drewell, Jacqueline M. Dresch, Donald E. Spratt

Chemistry

Homeodomain transcription factors (TFs) bind to specific DNA sequences to regulate the expression of target genes. Structural work has provided insight into molecular identities and aided in unraveling structural features of these TFs. However, the detailed affinity and specificity by which these TFs bind to DNA sequences is still largely unknown. Qualitative methods, such as DNA footprinting, Electrophoretic Mobility Shift Assays (EMSAs), Systematic Evolution of Ligands by Exponential Enrichment (SELEX), Bacterial One Hybrid (B1H) systems, Surface Plasmon Resonance (SPR), and Protein Binding Microarrays (PBMs) have been widely used to investigate the biochemical characteristics of TF-DNA binding events. In addition to …

My Gai Study Partner For Odes, Milena C. Cuellar

Open Educational Resources

My GAI Study Partner for ODEs is a scaffolded sequence of learning activities designed to support students in an Ordinary Differential Equations (ODEs) course by integrating the use of Generative AI tools—specifically Copilot, a platform accessible to all CUNY students and faculty. The activities are rooted in experiential learning, flipped classroom strategies, and self-directed learning principles. The sequence begins with two preparatory activities that introduce students to the ethical use and foundational concepts of Generative AI, fostering digital literacy and critical reflection. These are followed by a series of main activities—initially structured (Activity 3) and later more flexible …

Short-Run Subsidies And Long-Run Willingness To Pay: Learning And Anchoring In An Agricultural Experiment In Ethiopia, Solomon Balew, Erwin Bulte, Menale Kassie

All Peer-Reviewed Publications

We study how temporary provision of an agricultural innovation at zero cost affects long-run demand for that innovation. Our experimental design enables us to distinguish between an “anchoring effect” of subsidies and a “learning effect.” We document large and persistent anchoring and learning effects. For the innovation that we consider, an integrated pest management (IPM) package for Ethiopian smallholder farmers, the learning effect dominates the anchoring effect, so temporary subsidized provision promotes long-run technology diffusion.

A System Dynamics Model For Predicting African Armyworm Occurrence And Population Dynamics, Bonoukpoè Mawuko Sokame, Brian Kipkorir, Komi Mensah Agboka, Saliou Niassy, Yeneneh Belayneh, Maged Elkahky, Henri E.Z. Tonnang

All Peer-Reviewed Publications

This study develops a comprehensive system dynamics model to predict and manage African armyworm (Spodoptera exempta) outbreaks, a major threat to cereal crops across Africa. We applied system dynamics approache with its archetypes (causal loop diagram (CLD), reinforcing (R) and balancing (B)) to analyse the population dynamics of the pest. The VENSIM modelling platform (Ventana Systems Inc., DSS 8.2) was used to implement the models and carry out the simulations. The research integrates extensive data from 1980 to 2023, encompassing the African armyworm's life cycle stages, climatic variables, and intervention strategies, to simulate potential outbreak scenarios and evaluate the impacts …

2025 Belknap And Carroll Counties 4-H Presents Event Packet, Mikayla Cerney

UNH Cooperative Extension

No abstract provided.

Test 2025 Belknap And Carroll Counties 4h Presents Event Packet, Mikayla Cerney

UNH Cooperative Extension

No abstract provided.

The Cure-Comm Framework: A Guide For Infusing Cures With Science Communication, Rebekka Darner, Ebenezer Korkor

Faculty Publications – Biological Sciences

Researchers have employed diverse instructional strategies to impart science communication (SciComm) skills, a cherished 21st-century skill into undergraduate students. We reviewed the pedagogical strategies used in developing SciComm skills in undergraduates. This review revealed that analyzing data and scientific literature, increasing exposure to multiple writing contexts, providing multiple opportunities to present findings orally, and providing feedback are used to teach SciComm skills. Many instructors who implement course-based undergraduate research experiences (CURE) report improved SciComm skills as one of the benefits of CUREs. To decipher points of intersection among CUREs and SciComm pedagogical strategies, we also reviewed the literature on pedagogical …

Assessment Of Skin Fibrosis In A Murine Model Of Systemic Sclerosis With Multifunctional Optical Coherence Tomography, Harshdeep Singh Chawla, Yanping Chen, Minghua Wu, Pavel Nikitin, Jessica Gutierrez, Chandra Mohan, Manmohan Singh, Salavat R Aglyamov, Shervin Assassi, Kirill V Larin

Faculty, Staff and Student Publications

Significance: Systemic sclerosis (SSc) is a chronic idiopathic disease that causes immune dysregulation, vasculopathy, and organ fibrosis that affects more than 3 million people in the US alone. The modified Rodnan skin score (mRSS) is the current gold standard for diagnosing and staging skin fibrosis in SSc. However, mRSS is subjective, requires extensive training, and has high observer variability.

Aim: We aim to provide a quantitative method for the assessment of fibrosis.

Approach: We utilized optical coherence tomography (OCT), its extensions, optical coherence elastography (OCE), and OCT angiography (OCTA) to evaluate SSc-like fibrosis and therapy response in a mouse model. …

2025 March, Morehead State University. Office Of Communications & Marketing.

Morehead State Press Release Archive, 1961 to the Present

Press releases for March of 2025.

Quantifying The Role Of Active Listening And Reassurance In Virtual Health Coach Interactions, Ghulam Hussain, Brian Keegan, Robert Ross

Conference papers

Conversational Agents have the potential to support healthcare through coaching exercise routines, but are still lacking in demonstrating authentic social behaviours to support engagement. To this end, we present a series of experiments that we conducted in order to investigate how automated health care coaches can be more effective when their interaction style is tailored to demonstrate qualities associated with a good bedside manner, namely active listening and reassurance. To test this, we first developed a dataset of 135 dialogue excerpts from three distinct sources, i.e., original, handcrafted and LLMs, the latter two of which were tuned to demonstrate specific …

Tienen Alas, Pero No Las Pueden Usar: Stories Of Immigrants In Search Of Work Credentials, Jonathan Vega-Martinez, Maria M. Pache De Athayde, Fabián Torres-Ardila, Phillip Granberry

Gastón Institute Publications

This report presents the results of a qualitative research study, funded by the Latino Equity Fund of the Boston Foundation, aimed at understanding the challenges that highly skilled immigrants1 face when reentering their careers in Massachusetts.

Varium: Variational Autoencoder For Multi-Interest Representation With Inter-User Memory, Nhu Thuat Tran, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Frameworks for discovering multiple user interest factors based on Variational AutoEncoder (VAE) has demonstrated competitive recommendation performance. However, as VAE only considers one user as input at a time, sharing across like-minded users may not be adequately facilitated. Moreover, interest sharing between users is not always available and thus, poses a challenge for VAE to explicitly model this information. To resolve this, we introduce an inter-user memory-based mechanism to unsupervisedly discover latent interest sharing between users under VAE framework. Concretely, we design a memory including an array of prototypes, each hypothetically representing a group of users sharing a particular interest. …

Marginal Benefit Driven Rl Teacher For Unsupervised Environment Design, Dexun Li, Wenjun Li, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Training generally capable agents in complex environments is a challenging task that involves identifying the “right” environments at the training stage. Recent research has highlighted the potential of the Unsupervised Environment Design framework, which generates environment instances/levels adaptively at the frontier of the agent’s capabilities using regret measures. While regret approaches have shown promise in generating feasible environments, they can produce difficult environments that are challenging for an RL agent to learn from. This is because regret represents the best-case (upper bound) learning potential and not the actual learning potential of an environment. To address this, we propose an alternative …

Evaluating Software Development Agents: Patch Patterns, Code Quality, And Issue Complexity In Real-World Github Scenarios, Zhi Chen, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

In recent years, AI-based software engineering has progressed from pre-trained models to advanced agentic workflows, with Software Development Agents representing the next major leap. These agents, capable of reasoning, planning, and interacting with external environments, offer promising solutions to complex software engineering tasks. However, while much research has evaluated code generated by large language models (LLMs), comprehensive studies on agent-generated patches, particularly in real-world settings, are lacking. This study addresses that gap by evaluating 4,892 patches from 10 top-ranked agents on 500 real-world GitHub issues from SWE-Bench Verified, focusing on their impact on code quality. Our analysis shows no single …

Backdoor Token Unlearning: Exposing And Defending Backdoors In Pretrained Language Models, Peihai Jiang, Xixiang Lyu, Yige Li, Jing Ma

Research Collection School Of Computing and Information Systems

Supervised fine-tuning has become the predominant method for adapting large pretrained models to downstream tasks. However, recent studies have revealed that these models are vulnerable to backdoor attacks, where even a small number of malicious samples can successfully embed backdoor triggers into the model. While most existing defense methods focus on post-training backdoor defense, efficiently defending against backdoor attacks during training phase remains largely unexplored. To address this gap, we propose a novel defense method called Backdoor Token Unlearning (BTU), which proactively detects and neutralizes trigger tokens during the training stage. Our work is based on two key findings: 1) …

Sticky Information Technology Investment: Theory And Empirical Evidence, Peng Liang, Hasan Cavusoglu, Nan Hu

Research Collection School Of Computing and Information Systems

This article provides a new way of thinking about managerial discretion in information technology (IT) investment decisions. We delve into the existence, antecedents, and consequences of sticky IT investment behavior, an understudied managerial deliberate resource commitment decision in response to changes in sales. Guided by downsizing theory, we initially theorize and find that IT investments exhibit stickiness: IT investments move downward less for sales decreases than they move upward for equivalent increases. Then drawing upon agency theory, adjustment costs theory, and managerial expectations theory—which influence managers’ motivation for downsizing—we predict and demonstrate that managers’ empire-building incentives, their avoidance of adjustment …

Gender Biases Within Artificial Intelligence And Chatgpt: Evidence, Sources Of Biases, And Solutions, Qi Hui Jerlyn Ho, Andree Hartanto, Andrew Koh, Nadyanna M. Majeed

Research Collection School of Social Sciences

The growing adoption of Artificial Intelligence (AI) in various sectors has introduced significant benefits, but also raised concerns over biases, particularly in relation to gender. Despite AI's potential to enhance sectors like healthcare, education, and business, it often mirrors reality and its societal prejudices and can manifest itself through unequal treatment in hiring decisions, academic recommendations, or healthcare diagnostics, systematically disadvantaging women. This paper explores how AI systems and chatbots, notably ChatGPT, can perpetuate gender biases due to inherent flaws in training data, algorithms, and user feedback loops. This problem stems from several sources, including biased training datasets, algorithmic design …