Digital Commons Network^™

Microplastics As Physical Hubs Amplifying Antiobiotic Resistance Under Mixed-Contaminant Selection In Wastewater Systems, Liyuan Hou

Spring Runoff Conference

Microplastics (MPs) are tiny plastic particles within the range of (0.1 mm to 5 mm) in size

Integrating Hydrology And Human Water Footprints: A Case Study Of The Great Salt Lake Watershed, Rocky Lynne Seeley

Spring Runoff Conference

A new model, comprehensively integrating hydrologic, water footprint, and virtual water data

Balancing Water Needs In Walker Basin, Peter Stanton

Spring Runoff Conference

Walker Lake 

Supported 50% of Mineral County economy 

Traditional homeland of Walker River Paiute Tribe (Agai Dicutta) 

World-class fishery

Annual Loon Festival

Investigation Of Molecular Footprints In Ultra-High Diluted Homoeopathic Solutions Of Arnica Montana And Rhus Toxicodendron Through Combined Infrared And Impedance Spectroscopy, Sharbadeb Kundu, Usha Rani Dash, Chirasree Roychaudhuri, Aindrila Roy, Sanatan Chattopadhyay, Rathin Chakravarty, Debadatta Nayak, Subhash Kaushik, Amit Roy Chowdhury, Ananya Barui, Subhadip Chakraborty

Indian Journal of Research in Homoeopathy

Background: The study of ultra-high diluted (UHD) solutions is a compelling and controversial domain in modern science. Despite numerous investigations and hypotheses, there is a lack of rigorous, reproducible empirical evidence supporting the existence of molecular footprints beyond the Avogadro's limit. Objective: This study conducted a detailed investigation of the molecular and electrical properties, focusing on hydrogen bonding and impedance to understand the fundamental nature of UHD solutions. Materials and methods: Combined impedance and infrared spectroscopic investigations were performed to probe the structural behaviour of relevant water networks at the molecular level of UHD alcoholic extract of Arnica montana (AM) …

Multi-Modal Tensor Fusion For Alzheimer’S Disease Recognition, Mason Li, Tiffany Le, Jiajing Huang, Yuxin Wen

Engineering Faculty Articles and Research

Accurate and early diagnosis of Alzheimer’s disease (AD) is critical for effective intervention, disease monitoring, and patient care. Traditional diagnostic approaches rely on a single modality, such as clinical assessments, neuroimaging, or genetic markers, which may fail to capture the complex, multifaceted nature of AD. Multimodal learning has therefore been explored to integrate complementary information across data sources. However, conventional fusion strategies, including early feature concatenation and late decision-level fusion, often model modalities independently and fail to capture high-order cross-modal interactions. To address these limitations, we propose a multimodal tensor fusion network (MTFN) that integrates heterogeneous data sources, including visual …

What Does Next-Generation Mass Spectrometry Offer For Proteomics? A Comprehensive Platform Comparison, Filipa Blasco Tavares Pereira Lopes, Daniela Schlatzer, Tara Sudhadevi, Anantha Harijith, Marzieh Ayati, Mehmet Koyutürk, Mark R. Chance

Computer Science Faculty Publications

Next-generation mass spectrometry platforms (Orbitrap Astral, timsTOF Ultra) are reshaping proteomics by enhancing analytical depth and sensitivity. We compared these platforms against Orbitrap Exploris 480 using neonatal mouse lung tissues from a bronchopulmonary dysplasia model (n = 12), employing four acquisition strategies: Exploris 480 DDA/DIA, Astral HR-DIA, and timsTOF Ultra DIA-PASEF. All platforms identified ∼4000 proteins in common, with 98% proteome coverage of data-dependent acquisition (DDA) identifications using data-independent (DIA) methods and 92% concordance between next-generation systems. Orbitrap Astral and timsTOF Ultra quantified >225,000 peptides and 13,000 proteins, representing ∼800% and ∼300% greater depth than Exploris 480 DDA, respectively. …

Secure Machine Learning In Networking Systems, Wenwei Zhao

USF Tampa Graduate Theses and Dissertations

With the rapid integration of Machine Learning (ML) into networking systems, ensuring the security and trustworthiness of these intelligent frameworks has become a paramount concern. While ML offers unprecedented capabilities in spectrum management and collaborative learning, it also introduces novel vulnerabilities that can be exploited by sophisticated adversaries. This dissertation investigates and addresses critical security challenges across three key dimensions of ML-driven networking: adversarial spectrum sensing, the security of privacy-preserving unlearning processes, and efficient post-attack model recovery.

First, we address the threat of adversarial spectrum attacks in cognitive radio networks, where malicious nodes manipulate sensing reports to disrupt spectrum access. …

Pheasant Forever Loan Program, Will Benkelman

Spring Runoff Conference

Bear River Watershed Community Conservation Program

Our Mission: Pheasants Forever (PF) and Quail Forever’s (QF) mission is to conserve pheasants, quail, and other wildlife through habitat improvements, public access, education, and conservation advocacy.

Logan River Watershed Draft Environmental Impact Statement, Zan Murray

Spring Runoff Conference

Agenda:

Program Overview: PL-566 & NEPA

Project Need and Purpose

Project Alternatives

Preferred Alternative Costs and Benefits

NEPA Timeline/Current Schedule

Questions

Cache Water District Conservation Program, Autumn Matthews

Spring Runoff Conference

Conservation and Education Programs.

Conservation Goals:

Increase community awareness through outreach, workshops, and community programs that support water conservation.

Expand and improve programs that encourage water savings and more efficient water use across the community.

Help residents save money by promoting water efficiency and reducing unnecessary water use.

Beyond The Survey: Performance Assessments For Higher-Order Sustainability Literacy In Higher Education, Gregory Vincent Massara, Courtney B. Ryan, Mary Ellen Mallia

Educational Policy & Leadership Other Graduate Student Scholarship

Purpose This study explores how a performance-based assessment measures students’ higher-order sustainability competencies in ways that multiple-choice or scaled-survey tools, common ways to assess sustainability literacy, may not.

Design/Methodology/Approach This exploratory case study created a performance task for a first-year honors writing and critical inquiry course. Students (n=9) analyzed a scenario across environmental, social, and economic domains. A rubric measured students’ abilities to address all three domains and articulate a feasible and balanced solution supported by credible evidence.

Findings Students demonstrated proficiency in defining the three sustainability domains but tended to struggle to balance them. Choosing scenarios in familiar local …

2025 San Diego Regional Climate Collaborative Annual Report, San Diego Regional Climate Collaborative

San Diego Regional Climate Collaborative

The San Diego Regional Climate Collaborative is a network for public agencies that serves the San Diego region to share expertise, leverage resources and advance comprehensive solutions to facilitate climate change planning. By partnering with academia, nonprofits, and businesses, the SDRCC also works to leverage the profile of regional leadership. This is the 2025 San Diego Regional Climate Collaborative Annual Report.

Marine Vehicle Dynamics Using Koopman Operator Theory With Hybrid Observables, Mikhalib A L Green

LSU Master's Theses

Accurate modeling of marine vehicle dynamics remains challenging due to strong nonlinear hydrodynamic effects, environmental disturbances, and sensitivity to configuration changes, particularly for small-scale platforms. Classical physics-based models require extensive parameter identification and often exhibit degraded performance outside narrow operating regimes, while purely data-driven approaches may lack structure or impose high computational cost. This thesis presents a data-driven Koopman operator framework with hybrid observables for modeling the dynamics of unmanned marine vehicles. The proposed approach combines structured monomial observables with a learned neural network embedding to construct a lifted state representation in which the nonlinear vehicle dynamics are approximated by …

Large-Scale File Fragment Classification Via Multi-View Learning, Samuel Hildebrand

LSU Master's Theses

File reassembly is one of the most fundamental tasks in digital forensics, enabling recovery of data from potentially damaged storage media even when file system metadata is unavailable. This thesis reviews more than two decades of work in the realm of file carving, with a particular focus on fragmented file carving, which remains a focus of research, and file fragment classification, a principal component of fragmented file carving. This thesis serves a literature review of both file carving and fragmented file carving, surveys the massive amounts of data needed for the task of fragment classification and the datasets that serve …

Draft Final Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites Bres No. 30 – Atlantic 1 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Being There For Mom: The Strengths Of Daughtering, Allison M. Alford, Kaitlin E. Phillips, Luke V. Stipanovic, Cayd A. Rocha-Barnette, Michelle Miller-Day

Communication Faculty Articles and Research

Objective

Daughters undertake daughtering, or the everyday role portrayal of contributing to a meaningful family relationship with their mothers, but the labor of it is often invisible.

Background

Using a strengths-based approach, we investigated what daughters do well in their relationships with mothers.

Method

We analyzed the responses of 1,444 women to the open-ended question, “What do you do well as a daughter?” to learn more about how women describe their daughtering. Utilizing the artificial intelligence of a large language model for data analysis, we supplied definitions and descriptions of 12 virtues and strengths from existing literature and created a …

Best Integrated Writing Spring 2026 - Complete Edition, Wright State University School Of Humanities And Cultural Studies, Tracy Smith, Kristie Mckiernan

Best Integrated Writing

Best Integrated Writing includes excellent student writing from Integrated Writing courses taught at Wright State University.

Tornado Alley In A Changing Climate: The Eastward Shift, Kenny Reinhard

Best Integrated Writing

Reinhard argues that climate change is driving an eastward shift in Tornado Alley from the Great Plains toward the southeastern United States, increasing tornado frequency in more densely populated and less-prepared regions. It highlights how changing atmospheric conditions—such as increased moisture, instability, and wind shear—are contributing to this shift and emphasizes the need for improved preparedness and infrastructure in newly affected areas.

Enhancing Cyber Hygiene Among Communities Through Experiential Cyber-Security Awareness Programs, Dr Atul Bamrara, Partha Roy, Vishwanath Gargote, Khandu Thungon

Journal of Cybersecurity Education, Research and Practice

Human error remains the most frequently exploited vulnerability in the cyber-security ecosystem. Despite substantial investments in technical safeguards, cybercriminals increasingly rely on social engineering, misinformation, and emotionally manipulative tactics to compromise users. This study examines behavioral changes among participants who underwent structured cyber-security workshops addressing both conventional cyber hygiene practices and emerging digital threats. The training modules covered digital arrest scams, identity theft, sextortion, fake technical support fraud, fake social media profiles, online gaming related risks, and deep fake manipulation. The workshops were designed using interactive simulations, real world case studies, and hands on problem based exercises, with the explicit …

Dietary Inflammatory Index And Objective Disease Activity In Ibd: No Association Found, Rúbia Moresi Vianna De Oliveira, Ana Carolina Junqueira Vasques, Stefhani Andrioli Romero, Nitin Shivappa Mbbs, Mph, Ph.D., Michael David Wirth, James Hébert Scd, Glaucia Fernanda Soares Ruppert Reis, Cristiane Kibune Nagasako

Faculty Publications

Background

Inflammatory Bowel Disease (IBD) involves genetic and environmental factors, but the relationship between disease activity, adiposity, and diet remains unclear.

Objective

To investigate the association between endoscopic/radiological activity of IBD, body adiposity, and the Dietary Inflammatory Index with or without adjustment for energy density (E-DII or DII).

Method

An observational, cross-sectional study was carried out. Endoscopic activity was defined by an endoscopic Mayo score >2, Crohn’s Disease Endoscopic Index of Severity (CDEIS) > 5, and/or the presence of a deep ulcer in any intestinal segment. Body adiposity was estimated using the body mass index, waist circumference, and waist-hip ratio (WHR). …

Quantifying Global Internal Displacement Risk At The Hazard-Vulnerability-Conflict Nexus, Wenzhao Li, Surendra Maharjan, Rejoice Thomas, Hesham Morgan, Ali Elgendy, Susan Mikhail, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

This study introduces a novel, diagnostic hazard-specific displacement risk index that integrates high-resolution hazard data with social vulnerability metrics and historical displacement records, uncovering overlooked compound risks in conflict areas and links between environmental stress and instability. Our methodology combines historical displacement records with environmental, demographic, and socioeconomic indicators to identify high-risk regions and quantify interactions between hazards and conflict across six major hazard types. Results reveal floods as the primary displacement driver, particularly in South Asia (Bangladesh, India, Pakistan) and Sub-Saharan Africa (Nigeria, Ethiopia), where dense populations in flood-prone areas intersect with low socioeconomic resilience. Droughts disproportionately impact arid …

Housing Affordability Analysis Of Hillsborough County, Fl, Usa – Quantitative And Geographical Analysis Using Spatiotemporal Data, Bomin Koh

USF Tampa Graduate Theses and Dissertations

Housing affordability assessments rely on the 30 percent income method and generalized linear regression (GLR)-based hedonic price modeling. Both provide broad insights but fail to capture spatial heterogeneity in affordability challenges. This study upgrades housing affordability assessment approaches by incorporating the residual income method and Geographically Weighted Regression (GWR). The primary objective of this study is to determine whether methodological improvements, residual income method and GWR, yield significantly different results and provide a more accurate and spatially adaptive understanding of affordability dynamics in Hillsborough County, Florida.

The 30 percent income method is widely used and classifies households as cost-burdened if …

Circulating Levels Of Insulin-Like Growth Factor I (Igf-I) And Risk Of Multiple Myeloma: An Observational And Mendelian Randomisation Study, Yolanda Benavente, Sara Hermosa, Nikos Papadimitriou, Alyssa I. Clay-Gilmour Ph.D., Elizabeth E. Brown, Jonathan N. Hofmann, Nathaniel Rothman, Qin Lan, Sonja I. Berndt, Demetrius Albanes, Mark Purdue, Mitchell J. Machiela, Stephen J. Chanock, Parveen Bhatti, Wendy Cozen, Aaron Norman, Susan L. Slager, James R. Cerhan, Vincent Rajkumar, Et. Al.

Faculty Publications

No abstract provided.

How Do Water Utilities Meet Growing Demand And Maintain Resilience Through Water Reuse? A Systems Thinking Approach, Elizabeth F. Vicario

USF Tampa Graduate Theses and Dissertations

Water and wastewater utility management is becoming increasingly complex due to factors like urbanization, climate change, new regulations, and rising costs. Utility leaders must balance competing political and financial pressures while managing aging infrastructure, rising demand, climate resilience planning, and customer concerns about affordability. Reuse of treated wastewater has emerged as a promising solution to address scarcity, declining source water quality, and new regulations on wastewater discharge in the United States. However, water reuse is not one-size-fits-all, and bespoke solutions are needed to optimize economic, environmental, and social returns from this finite resource. Despite growing interest, little is known about …

Advancing Environmental Justice Through Chemical Education: Perspective From New Orleans’ Water And Air Quality Challenges, Ja’Lynn Keller, Sita Aggarwal, Rami A. Al-Horani, Morewell Gasseller, Navneet Goyal

Faculty and Staff Publications

New Orleans, Louisiana, faces profound environmental vulnerabilities arising from the convergence of industrial pollution, urban runoff, and climate change–driven weather events. This paper examines systemic challenges affecting water and air quality in the region, with particular focus on low-income and marginalized communities disproportionately burdened by environmental degradation. Drawing on educational and community-based monitoring initiatives at Xavier University of Louisiana and Southeastern Louisiana University, we highlight the integration of student learning with real-time data collection of contaminants such as fecal coliforms, heavy metals, hydrocarbons, and polycyclic aromatic hydrocarbons (PAHs). The aftermath of Hurricane Katrina revealed significant fecal contamination in sediment layers, …

Analysis Of Novel Cannabis Products Labeled As Containing Thc-Jd, Kaelas R. Munger, Carlton C. B. Bone, Killian M. Anreise, Robert M. Strongin

Chemistry Faculty Publications and Presentations

Objective:

THC-JD (tetrahydrocannabioctyl) is a semi-synthetic cannabinoid with an eight-carbon C3 side chain, present in only trace amounts in hemp, requiring synthesis for commercial use. It has been promoted as potentially 19 times more potent than delta-9-THC, consistent with enhanced CB1 receptor affinities for cannabinoids with 7-8 carbon C3 side chains. While one peer-reviewed report identified THC-JD (tetrahydrocannabioctyl) in Japanese online products, an anecdotal report from the U.S. suggests mislabeling. Method: To inform regulatory efforts and consumer awareness and to address these discrepancies, this study chemically analyzed five U.S. commercial cannabis vape products marketed as containing THC-JD. Results: Utilizing GC-MS …

Addressing The Problems Of Data Variations, Quality, And Scarcity In Training Deep Neural Networks, Jian Sun

Electronic Theses and Dissertations

The performance of deep neural networks (DNNs) is strongly influenced by the characteristics and quality of the underlying datasets. This Ph.D. dissertation addresses three pervasive data challenges-imbalance, quality degradation, and scarcity-that commonly hinder the effectiveness of DNNs in computer vision (CV) and natural language processing (NLP) applications.

Class imbalance remains one of the most frequent causes of degraded model generalization. While Focal Loss effectively mitigates inter-class imbalance by assigning higher weights to minority classes, it struggles with intra-class imbalance, particularly in video datasets where longer clips dominate feature representation. To address this, I implement and utilize …

Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies, Kara Combs, Lance E. Champagne, Bruce A. Cox, Christine M. Schubert Kabban, Trevor Bihl, Grace Lemming

Faculty Publications

Analogical reasoning is an increasingly popular, lightweight solution to enable large language model (LLM)-level reasoning without computational complexity. Still, it has yet to be adopted due to its reliance on strictly hand-formatted data. Therefore, we propose Analogy2KG (“Analogy to Knowledge Graph”), as an automatic pipeline that transforms text into a KG format via a fine-tuned version of information extraction (IE) algorithms for long-text analogies. The need to verify that the complex underlying analogical structure of the data is maintained was done via paired samples tests in the creation and validation of this pipeline. Graph density was used to evaluate the …

Health Effects Of Cadmium And Manganese Exposure On Luteinizing Hormone Levels: A Pilot Study Of Female Infertility, Shatha F. Alhous, Anees A. Al-Hamzawi, Murtadha Sh. Aswood

Al-Bahir

Female infertility occurs for many reasons, some unknown. Exposure to heavy metals is a risk factor that negatively impacts on female reproductive system. Therefore, this study aimed to evaluate the effect of cadmium Cd and manganese Mn on luteinizing hormone LH levels for females’ infertility. This study included a healthy group (n = 20), primary infertile females (n = 40), and secondary infertile females (n = 20) collected from Al-Zahraa hospital in Najaf center, Iraq. The Atomic Absorption Spectroscopy (AAS) was used to measure the cadmium and manganese concentrations and LH levels were measured by a Maglumi 800 from Snibe …

Clinical Prediction Of Posttreatment Migraine Recurrence Using Biofeedback Data: A Machine Learning Framework For Enhanced Patient Stratification And Treatment Monitoring, Shibbir Ahmed Arif, Ferdib-Al-Islam, Mehidy Hasan Sium

School of Computing Faculty Scholarship and Creative Works

Migraine is a complex neurological disorder with significant implications for individual well-being and public health. Predicting migraine occurrences after treatment is crucial for evaluating therapeutic efficacy and enabling personalized care, yet remains largely underexplored. This study proposes a robust machine learning framework to predict posttreatment migraine headache occurrences using real-world headache log data collected from 133 patients undergoing biofeedback therapy. The methodology includes rigorous data preprocessing, outlier removal via the interquartile range (IQR) method, and class imbalance correction through the synthetic minority oversampling technique (SMOTE). A total of 10 classical and a hybrid ensemble machine learning models were developed and …