Digital Commons Network^™

Metadata Analysis On The Relationship Between Sleep, Depression, And Cognition In Older Adults, Sara Miller, Kristie Stephens, Grayson Harris, Vincent Flegeance

Science University Research Symposium (SURS)

Metadata Analysis on the relationship between sleep, depression, and cognition in older adults

Abstract

Previous research has revealed that both sleep and depression play significant roles in influencing memory. Adequate sleep facilitates memory consolidation during rest, ultimately enhancing cognitive performance. In contrast, elevated levels of depression are associated not only with physical symptoms, but also with declines in cognitive functioning. The present study aims to determine whether the cognitive benefits of sufficient sleep duration outweigh the detrimental effects of depression on memory. We hypothesize that sleep duration will have a stronger influence on memory consolidation in older adults than depression. …

Evaluating The Effects Of Water Quality And Anthropogenic Disturbance On Salamander Species Diversity, Abundance And Health In Warner Parks, Tatum P. Fortney, Chase Kinsey

Science University Research Symposium (SURS)

Salamanders utilize cutaneous respiration, making them vulnerable to pollution, shifts in water chemistry, and habitat degradation. Increased anthropogenic habitat use may be a detriment to local salamander populations and pollution increases with land use. Understanding how water quality influences salamander abundance, diversity and physiological condition is crucial for amphibian conservation and for assessing freshwater ecosystem health, as they serve as a key bioindicator species. The objective of this study was to examine how variation in water quality parameters influences salamander species abundance, diversity and locomotor performance across stream sites within Warner Parks in Nashville, Tennessee. Field sampling was conducted weekly …

Pd-1 Blockade Induced Bone Loss Occurs In A T-Cell Dependent Manner And May Be Mediated By Ifnγ-Driven Osteoclast Activation, Elena Amonette, Paige M. Hill

Science University Research Symposium (SURS)

PD-1 Blockade Induced Bone Loss Occurs in a T-Cell Dependent Manner and May Be Mediated by IFNγ-Driven Osteoclast Activation

^†Elena Amonette¹, ^†Paige Hill¹, Gwenyth J. Joseph², Rachelle W. Johnson^2,3

¹Belmont University, Nashville, TN; ²Vanderbilt University, Nashville, TN; ³Vanderbilt University Medical Center, Nashville, TN

^†These authors contributed equally to this work

Immune checkpoint inhibitors (ICIs) are becoming increasingly prevalent in the treatment of various cancers due to their ability to reduce tumor mediated T cell death and lengthen the anti-tumor response. One such therapy that is increasingly utilized …

Synthesis And Characterization Of Eco-Engineered Hollow Fe2o3/Carbon Nanocomposite Spheres: Evaluating Structural, Optical, Antibacterial, And Lead Adsorption Properties, Islam Gomaa, Nikita Yushin, Mekki Bayachou, Vojislav Stani´, Inga Zinicovscaia

Chemistry Faculty Publications

This work presents a facile mechano-thermal route for the synthesis of carbon-decorated, hollow, mesoporous alpha-Fe2O3 microspheres. Comprehensive characterization (XRD, XPS, FT-IR, SEM/EDX, TGA, zeta-potential) confirmed the formation of phase-pure hematite with nanoscale crystallites (similar to 19 nm), substantial residual surface carbon (similar to 40 wt%) consistent with Fe-O-C linkages, and a positive surface charge (+15.9 mV). The hierarchical hollow/mesoporous architecture enables fast ion transport and provides extensive interior binding sites, resulting in rapid Pb(II) uptake that reaches 92% removal in approximate to 15 min at pH 5.0. The adsorption follows a Langmuir isotherm (q(max) approximate to 70.6 mg/g) and pseudo-second-order …

Detecting Generative-Ai-Enabled Polymorphic Malware: A Semantic-Behavior Approach, Allyson M. Morris

Cybersecurity Undergraduate Research Showcase

AI drastically reduces the effort required to produce malware that mutates both its code and behavior, thereby creating polymorphic and nondeterministic variants in which traditional signatures and many heuristic defenses fail. In this paper, I survey recent developments in AI-assisted malware generation, explain why conventional defenses are insufficient, and propose a layered detection architecture emphasizing semantic behavior, streaming anomaly detection, and defensive generative augmentation. I also outline why this approach generalizes to previously unseen AI-mutated samples, provide an evaluation plan with meaningful metrics, and describe a feasible MVP roadmap for practical deployment. Recent disclosures and threat intelligence further highlight the …

A Comprehensive Evaluation Of Next-Generation Firewall Effectiveness Against Encrypted And Evasive Threats In Enterprise Networks, John Costanzo, Favour Anene

Cybersecurity Undergraduate Research Showcase

Encrypted traffic is becoming a pillar of security and privacy in enterprise networks. According to Google Transparency Report, over 95 percent of internet traffic is encrypted with the use of Hypertext Transfer Protocol secure (HTTPS), Transport Layer Security (TLS) 1.3 and Quick UDP Internet Connections (QUIC). Although encryption safeguards confidentiality and integrity, it has also introduced new blind spots to the conventional security solutions. Encrypted channels are used to hide command-and-control (C2) traffic, issue malware and extract sensitive data without their notice.

To make the issue even harder, the opponents have sophisticated avoidance methods including traffic fragmentation, tunneling, and polymorphic …

Investigating The Security Vulnerabilities Of Ip Cameras: Classifications And Trends From Public Cve Data, Sam Oliver

Cybersecurity Undergraduate Research Showcase

Internet of Things (IoT) devices are increasingly targeted by cyber attacks due to weak authentication, insecure communication protocols, outdated firmware, and many other vulnerabilities. Internet Protocol (IP) cameras, a subset of these IoT devices, are particularly vulnerable and often transmit sensitive information. This paper analyzes vulnerability data from the National Vulnerability Database (NVD) to classify security vulnerabilities affecting IP cameras. Using this dataset, the paper examines the types and frequencies of these vulnerabilities, including authentication bypass, web interface exploits, and default and weak credentials. We additionally examine trends over time and across categories. This research aims to identify the primary …

Experiences And Challenges Of Grades 6-12 Principals And Assistant Principals Supporting Implementation Of Standards-Based Learning, Judith Ann Zeka

Walden Dissertations and Doctoral Studies

The problem addressed in this study was that grades 6-12 principals and assistant principals are unprepared to support teachers’ planning and implementation of standards-based learning in classrooms at mid-size rural school districts in a single midwestern state. Grounded in Senge’s five disciplines of a learning organization, the purpose of this study was to examine grades 6-12 principals’ and assistant principals’ experiences and challenges, the resources needed, and the perceived influence of their leadership in the implementation of standards-based learning in content-area classrooms at the study sites. For this basic qualitative study, semistructured interviews were conducted with 11 principals and two …

Correcting Class Imbalance Through Synthetic Training Data And 3d Modeling For Carabid Pitfall Trap Sampling, Blair Mirka

Geography ETDs

Crowdsourced biodiversity data provide an accessible foundation for large-scale ecological monitoring, but class imbalance limits automated species identification, particularly for rare taxa. This research explores the use of synthetic training data generated from 3D models of carabid beetle museum specimens to improve detection and classification performance for underrepresented species in crowdsourced datasets. High-resolution 3D models were created to simulate variation in lighting, orientation, and background. These synthetic images were incorporated into convolutional neural network training datasets at varying synthetic-to-real ratios to assess their impact on classification accuracy. Models were evaluated using controlled pitfall-trap imagery to examine the influence of scene …

Locations Of Outfalls In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly M. Kibler, Melinda J. Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_Outfalls_IRL_LWL.shp was created under grants from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon (IRL) and Lake Worth Lagoon (LWL).

The dataset presented here includes the location of outfalls identified throughout the study region and general characteristics of the shoreline where they were identified.

Seagrass Persistence In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly Kibler, Melinda Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_seagrasspersistence_IRL_LWL.shp was created with support from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon (IRL) and Lake Worth Lagoon (LWL). The dataset presented herein represents persistence of seagrass throughout waters of the IRL and LWL.

Re: Butte Priority Soils Operable Unit (Bpsou) 2025 Monthly Progress Report. Consent Decree For The Butte Priority Soils Operable Unit. Civil Action No. Cv 89-039-Bu-Seh, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Soccer In-Game Event Classification Using Spatio-Temporal Data, Million Haileyesus

Theses and Dissertations

Classifying soccer ball events, such as pass, shot, ball loss, and ball out, are crucial for advancing game analytics and tactical insights. This thesis investigates the application of machine learning to classify these ball events using player and ball spatio-temporal data, as well as additional features. We implement and compare traditional machine learning algorithms (AdaBoost, Logistic Regression, and Random Forest) with several deep learning approaches, including Feed-Forward Neural Network (FFNN), sequence-to-sequence (seq2seq) recurrent models (Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU)), and Transformer. Our experiments, evaluated on a dataset comprising of three professional soccer matches using accuracy, precision, …

11.10.2025 Ored Connect, Liz Williamson

ORED Newsletter

• Sherilyn Hulugalla winds Biosafety and Biosecurity Month Challenge

All Bets Are On: Addiction, Prediction, Regulation, And The Future Of Financial Gambling, Sharon Rabinovitz, Nizan G. Packin

Fordham Intellectual Property, Media and Entertainment Law Journal

This Article challenges traditional financial regulation by exploring how prediction markets—initially developed as sophisticated tools for collective forecasting—increasingly resemble gambling venues. These platforms, once designed to harness crowd wisdom, have transformed into high-stakes ecosystems where engage- ment-driven features blur the boundary between forecasting and betting. This evolution presents a dual challenge: on one hand, certain platforms, including regulated ones, offer innovative avenues for price discovery and risk hedging; on the other, their gamblified design exposes users to significant behavioral and financial risks.

Through comprehensive empirical analysis of gamblification and self-determination manipulation across five prediction market interfaces, this Article demonstrates how …

Board Of Directors Meeting Minutes (November 10, 2025), Dmacc

Board of Directors Meeting Minutes

This file contains the minutes from the Des Moines Area Community College Board meeting held on November 10, 2025.

Mapping Empirical Evidence On Artificial Intelligence Tools For Mathematics Teachers: A Scoping Review, Ghan Shyam Joshi, Steven M. Heinold

Purdue AI in P-12 Education Conference

Artificial Intelligence (AI) is reshaping education, yet its integration into K–12 mathematics remains limited. This scoping review synthesizes 7 empirical studies (2022–2025). The primary purpose of this review is to explore the benefits, challenges, and gaps in AI integration in mathematics. This review is guided by Arksey and O'Malley's scoping review framework. The reviewed literature data is analyzed through reflexive thematic analysis. This review identified four key themes: prompting literacy, accuracy norms, efficiency, and personalization. Results showed that AI can strengthen reasoning and engagement in mathematics teaching and learning. The effectiveness relies on teacher agency, ongoing professional development, and systemic …

Teachers’ Knowledge And Beliefs In The Implementation Of Ai In Algebra Instruction, Comfort Temitope Aje, Modiu Olaguro

Purdue AI in P-12 Education Conference

This review examines how secondary mathematics teachers’ knowledge and beliefs about Artificial Intelligence (AI) shape their use of AI-based learning tools in algebra instruction. Drawing on Wilkins’ (2008) adaptation of Ernest’s (1989) model, the study synthesizes existing literature to explain how teachers’ understanding of AI interacts with their beliefs to influence the depth and quality of classroom implementation. The review highlights the reciprocal relationship between knowledge, beliefs, and practice, emphasizing the need for sustained professional development to support purposeful and equitable integration of AI in mathematics teaching.

Overholser Selected As Latterell Visiting Alumnus, Communications And Marketing

Campus News Archive

No abstract provided.

An Integrated Ca–Markov Modeling Framework For Forecasting Land Use And Land Cover Dynamics In Arkansas, Usa, Rasool Vahid, Mohamed H. Aly

Environmental Dynamics Faculty Publications and Presentations

Land use and land cover (LULC) changes significantly shape urban environments and directly impact ecological and socioeconomic systems. This study aims to explore these interconnections by employing the Cellular Automata–Markov (CA–Markov) model to assess and predict LULC dynamics in Arkansas. Historical LULC datasets from 2001 to 2021, obtained from the National Land Cover Database, were simplified from 11 into 5 classes to facilitate analysis and effectively map transitions. The model was validated by predicting LULC for 2016 and 2021 and comparing the predictions with the real maps, achieving an overall accuracy of approximately 91.9%, using model validation metrics, including precision, …

On Influence Tail Bounds In Online Social Networks, Michael Simpson, Laks V. S. Lakshmanan, Venkatesh Srinivasan

Mathematics and Computer Science

The influence estimation and maximization problems study the expected reach of a seed set in social networks under a stochastic propagation model. Motivated by the practical utility of characterizing the distribution of reach values, we systematically analyze the tail behaviour of the reach of a seed set. We study tail bound query problems that, for a given seed set, compute either the maximum reach for a given probability threshold or the highest probability of achieving a target reach. We prove #P-hardness and propose algorithms that balance efficiency and accuracy. We also examine tail bound optimization problems that find a seed …

Framework And Methodology For Risk-Based Bridge And Tunnel Asset Management: Risk-Based Asset Ranking And Corridor Prioritization, David Y. Yang, Arash Khosravifar, Diane Moug, Avinash Unnikrishnan

Civil and Environmental Engineering Faculty Publications and Presentations

This report presents the results of Phase II of the project, "Framework and Methodology for Risk-based Bridge and Tunnel Asset Management". The research was carried out at Portland State University in collaboration with engineers and officials at the Oregon Department of Transportation (ODOT) and Federal Highway Administration (FHWA). Using the framework and methodology developed in Phase I of the project, the primary goal of Phase II is to showcase the practical application in risk-based asset management. In particular, the report includes the following two case studies: Case Study I — Weighted hazard scenarios for seismic risk assessment of Oregon Highway …

Software-Defined Networking Powered By Ai-Driven Anomaly Detection, Dina Moloja, Vusumuzi Malele Prof

Journal of Cybersecurity Education, Research and Practice

Software Defined Networking (SDN) revolutionizes network control by separating the control plane from the data plane. Although the latter improves SDN agility and scalability, it creates a security hole, particularly in a central control plane, leading to SDN environments becoming high-profile targets for advanced cybersecurity threats. Due to static and signature-based point-in-time behavior, traditional security methods are unable to keep up with modern attacks that are an anomaly to SDNs. Artificial Intelligence (AI) with its different applications and techniques, has the capability of detecting SDN cyber threats’ anomalies. This paper presents the results of a literature scoping exercise that used …

Nanofiber-Enabled Rapid And Non-Destructive Sensors For Meat Quality And Shelf-Life Monitoring: A Review, Karna Ramachandraiah, Elizabeth M. Martin, Alya Limayem

Food Science Faculty Publications and Presentations

The meat industry faces significant economic losses and environmental impacts due to spoilage and waste, much of which results from inadequate, delayed, or inefficient quality assessment. Traditional methods used for assessing meat quality are often time-consuming, labor-intensive, and lack the ability to provide real-time information, making them insufficient for modern supply chains that demand safety, freshness, and minimal waste. Recent advances in nanotechnology position nanofibers (NFs) as promising materials for addressing these challenges through smart sensing and active packaging. NFs, characterized by their high surface-to-volume ratio, tunable porosity, and small diameter, enable superior encapsulation and immobilization of sensing agents. These …

Efficient Multimodal Streaming Recommendation Via Expandable Side Mixture-Of-Experts, Yunke Qu, Liang Qu, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin

Research outputs 2022 to 2026

Streaming recommender systems (SRSs) are widely deployed in real-world applications, where user interests shift and new items arrive over time. As a result, effectively capturing users' latest preferences is challenging, as interactions reflecting recent interests are limited and new items often lack sufficient feedback. A common solution is to enrich item representations using multimodal encoders (e.g., BERT or ViT) to extract visual and textual features. However, these encoders are pretrained on general-purpose tasks: they are not tailored to user preference modeling, and they overlook the fact that user tastes toward modality-specific features such as visual styles and textual tones can …

Air Emissions From Combustion And Incineration Processes: Insights Into Air Quality And Us Epa Regulations, Madjid Delkash

All Faculty Scholarship (Archived)

The escalating global generation of waste necessitates robust and environmentally sound management strategies. Among these, combustion and incineration processes play a crucial role in waste volume reduction and energy recovery. Nevertheless, these thermal treatment methods are significant sources of atmospheric pollutants, impacting air quality and public health. This review systematically examines air emissions from four major incineration types regulated under the U.S. Environmental Protection Agency’s (EPA) Clean Air Act (CAA) Sects. 111 (New Source Performance Standards [NSPS]) and 129 (National Emission Standards for Hazardous Air Pollutants [NESHAP]). These categories include Large Municipal Waste Combustors (LMWC), Hospital/Medical/Infectious Waste Incinerators (HMIWI), Commercial …

Contrasting Effects Of Impervious Cover On Riparian Plant And Soil Bacterial Communities In A Rapidly Urbanising Himalayan City, Karma Jamtsho, Mark A. Lund, David Blake, Eddie Van Etten

Research outputs 2022 to 2026

Rapid urbanisation—particularly the expansion of impervious surfaces—is reshaping riparian landscapes worldwide. These areas are frequently targeted for development due to their favourable topography, abundant water resources, and aesthetic appeal. However, the impact of increasing impervious cover on soil bacterial communities in biodiverse urban riparian zones remains poorly understood, especially in developing countries, raising concerns about potential declines in essential ecosystem functions. In this study, we investigated the effects of impervious cover, quantified as the Percentage of Total Impervious Area (PTIA), on the taxonomic and functional diversity of riparian soil bacteria in Thimphu City, Bhutan. Using plot-based taxonomic profiling and metagenomic …

Proactllm: Proactive Conversational Information Seeking With Large Language Models, Shubham Chatterjee, Xi Wang, Shuo Zhang, Sajad Ebrahimi, Zhaochun Ren, Debasis Ganguly, Gareth Jones, Emine Arrousse, Hamed Zamani

Computer Science Faculty Research & Creative Works

Large Language Models (LLMs) have transformed information access by enabling human-like text understanding and generation. This workshop explores the next step for conversational AI: building proactive information-seeking assistants that go beyond reactive question answering. We aim to investigate how LLMs can anticipate user needs, model complex context, support mixed-initiative interactions, integrate retrieval and external tools, personalize responses, adapt through feedback, and ensure fairness, transparency, and cognitive grounding. Bringing together experts from NLP, IR, HCI, and cognitive science, the workshop will serve as a timely forum for advancing intelligent, proactive dialogue systems. It will also foster interdisciplinary collaboration.

The Correlation Of Students’ Grit To Their Achievement At Stkip Muhammadiyah Of Southwest Aceh, Ainain Tajriani, Sukri Adani

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

The grit theory emphasizes that persistence and passion for pursuing long-term goals are more important for success than innate talent alone. The purpose of this research was to assess students' grit levels and examine how they relate to academic performance. The study employed a quantitative correlational design to systematically measure numerical data, which helps identify patterns and relationships among various influencing factors. Participants included 136 students (75 English students and 61 Mathematics students). The research process involved: 1) collecting data via a questionnaire, 2) cleaning the data to remove outliers, 3) analyzing the data with SPSS, and 4) interpreting the …

E-Pocket Book Of Angiosperms Diversity Of Ghimbo Pomuan Sacred Forest To Improve Students’ Species Literacy And Plant Awareness, Hikmah Hidayah, Siti Zubaidah, Frida Kunti Setiowati

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

Students' low species literacy and limited awareness of plant diversity highlight the need for contextualised learning media based on local plant resources. This study aims to develop, assess the feasibility, and evaluate the effectiveness of an e-pocket book on Angiospermae diversity in Ghimbo Pomuan Sacred Forest, Kampar, Riau, Indonesia, as an innovative learning tool for higher education. This e-pocket book was developed using the Lee & Owens multimedia development model, which includes the stages of analysis, design, development, implementation, and evaluation. The feasibility test results showed that this e-pocket book was rated as very valid with an average score of …