Digital Commons Network^™

Environmental Dna For Endangered Freshwater Mussel Monitoring: A Review On Global Synthesis Of Edna Methods, Challenges, And Innovative Strategies, Mizanur Rahman, Md. Saydur Rahman, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

Freshwater mussels (family Unionidae) are among the most endangered aquatic species worldwide, making effective monitoring vital for their conservation. Traditional surveys are laborious, time-consuming, and often miss rare or low-density populations. Environmental DNA (eDNA) is a highly sensitive, non-invasive approach for freshwater mussel detection and monitoring; however, uncertainties in ecological interpretation continue to limit its broader application in freshwater biodiversity monitoring. We conducted a systematic review of 49 peer-reviewed studies, identified through an extensive literature search, to assess temporal research trends, methodological advancements, ecological contexts, and regulatory readiness of freshwater mussel eDNA monitoring. Findings show that freshwater mussel eDNA research …

Boundary Integral Method For A Modified Mullins–Sekerka System, Ly Le

Mathematics & Statistics ETDs

This thesis develops a boundary integral method for a modified Mullins–Sekerka system arising as the sharp-interface limit of a nonreciprocal Cahn–Hilliard model. Nonreciprocal coupling changes the classical Cahn–Hilliard structure by introducing an additional conserved field, leading to coupled elliptic and parabolic dynamics at the interface. Using matched asymptotic expansions, we formally derive the modified Mullins–Sekerka model and then apply the boundary integral method to rewrite it on the moving interface. The elliptic component is represented using the periodic Green’s function for the Laplace equation, while the parabolic component is represented using the periodic heat kernel. This method reduces the bulk …

Mining Legacy And Wildfires: Interfacial Reactions Affecting Metal Mobility, Eresay Alcantar-Velasquez

Earth and Planetary Sciences ETDs

We identified water labile interfacial reactions between laboratory burned pinewood ash and mine waste solids that influence metal mobilization. The Upper Gallinas Creek Watershed in New Mexico is affected by wildfires and mining legacy. Pinewood and mine waste sediments were sampled from the area, and the pinewood was burned at 350°C to simulate medium burn intensity ignition. Rapid desorption and gradual dissolution of Mn and Fe was detected by ICP-MS as pH decreased over time. After reacting 18 MΩ ultra-pure water with a mixture of pinewood ash and mine waste sediments Fe (143%) and Mn (89.2%) concentrations increased over time. …

Gradients Of Abandonment, William Tatman

Geography ETDs

As urban-rural disparities drive depopulation in rural areas worldwide, local strategies emerge as pathways for resilience. Research on Ojika, a Japanese island that has lost 75% of its population since the 1960s, reveals an Abandonment Gradient: a nuanced pattern of disuse adapted to modern polycrises. Extending the concept of "lying fallow" to homes and infrastructure, this thesis focuses on abandonment practices that reflect complex realities of labor, capital, and climate uncertainty. Rather than viewing depopulating communities as passive victims of out-migration, this paper argues they are critical sites for generating crisis response. Communally crafted attitudes toward unused space and more-than-human …

Elucidation Of Spin-Hamiltonian Parameters Via Spectroscopy, Magnetization, And Computation, Joshua C. Mengell

Chemistry and Chemical Biology ETDs

Molecular Quantum Information Science (QIS) is fundamentally concerned with using spin-systems as quantum bits (qubits) or as sensors. Prerequisite to using molecular systems for QIS applications, it must be understood how one can design molecules with bespoke magnetic characteristics. Herein we study various paramagnetic molecular compounds, describing their complex magnetic characteristics using a spin-Hamiltonian formalism. We utilize various (sometimes novel) methods for determining these spin-Hamiltonian parameters. Many of these molecules possess magnetic characteristics, which make them attractive as qubits or for sensing applications. These characteristics include higher total spin-states (qudits—S_T>1/2), forbidden interstate electronic transitions, systems of spatially distant …

Exploring The Nature And Role Of Local Cation Ordering In Disordered Rock Salt Cathodes For Li- And Na-Ion Batteries, You Wang

Chemistry and Chemical Biology ETDs

Cation-disordered rock-salt (DRX) cathodes provide a highly tunable platform for next-generation Li- and Na-ion batteries, but their electrochemical behavior is strongly influenced by local structural features hidden in average crystal structures. This dissertation systematically investigates local cation ordering in Li- and Na-based DRX cathodes to understand its effects on Li+/Na+ transport, redox activity, structural evolution, and electrochemical performance. In Li-based systems, Raman spectroscopy and electrochemical analysis reveal that local layered cation ordering in Mn- and Fe-based DRX cathodes is closely correlated with electrochemical behavior. Over-stoichiometric Li-based DRX oxyfluorides further demonstrate that excess Li can regulate local cation ordering, improve Li+ …

Mapping And Modeling Threat-Evoked Brain States After Early Life Adversity, Taylor W. Uselman

Biomedical Sciences ETDs

Early life adversity (ELA) increases lifelong neuropsychiatric vulnerability. Yet how ELA reorganizes brain-wide activity and circuit coordination across later experience remains unclear. This dissertation tests the hypothesis that ELA alters adult brain-wide activity and responses to threat through disrupted coordination among neural systems that regulate emotional experience, including prefrontal-limbic and monoaminergic systems. Longitudinal manganese-enhanced MRI of adult mice exposed to standard or fragmented early care, combined with computational processing and statistical modeling, quantified brain states before, during, and long after innate predator threat. These studies established that acute threat evokes large-scale, distributed brain activity that evolves over time. ELA potentiates …

Multiscale Network Modeling Of Native And Modified Photosynthetic Light-Harvesting Complexes, Zane E. Armijo

Chemical and Biological Engineering ETDs

Photosynthetic light-harvesting complexes harvest solar energy and direct electronic excitations toward reaction centers with exceptional efficiency. This dissertation models the Fenna--Matthews--Olson complex of green sulfur bacteria, coupled to the PscA1 reaction center, as a chromophoric network. Forster resonance energy transfer theory, validated against numerically exact hierarchical equations of motion, was implemented in kinetic Monte Carlo simulations to resolve fine-grained excitation-transport pathways. The predicted charge-transfer efficiency of 77\% agrees with experiment, with the FMO2 monomer and its gateway pigment governing interfacial transfer. Systematic single, multi, and symmetry-preserving site removals, interpreted through Mobius inversion, identify critical pigments and show that cooperative effects …

Wildfire Impacts On Fluvial Hydrology From Watershed To National Scales, Paige G. Tunby

Civil Engineering ETDs

Wildfires alter the water quantity and quality in downstream river networks. Fires promote biodiversity, maintain habitat, and provide many ecosystem services in a fire-adapted landscape. However, changes in the natural fire regimes can alter ecosystem function and threaten the water security of impacted downstream communities. The magnitude, timing, and persistence of these impacts are difficult to predict due to the lack of high-resolution datasets with adequate coverage to evaluate spatiotemporal trends after a fire. This dissertation moves us beyond the status quo to evaluate post-fire fluvial responses across scales, from the event-scale impacts after the Hermit’s Peak-Calf Canyon wildfire in …

Algorithmic Sculpting Of Complex Fused Silica Surfaces For Nondestructive, Mode-Matched Cavity Quantum Electrodynamics: Adaptive Co2 Milling And Simulation-Guided Ultrafast Inscription, From Fiber Fabry-Perot Cavities To Monolithic Architectures, Meagan E. Parker

Optical Science and Engineering ETDs

Quantum sensors achieve exceptional measurement sensitivity through coherent, well-isolated quantum systems, but practical deployment is hindered by destructive readouts that require repeated state preparation and create long system dead times. Optical cavities enable continuous, nondestructive measurements with minimal back-action, yet integrating high-finesse cavities into scalable quantum devices remains limited by existing fabrication methods. To overcome these constraints, an adaptive CO₂ laser-milling platform was developed. Guided by glass thermodynamics and melt dynamics, this closed-loop system uses in-situ phase-shifting interferometry to sculpt complex fused-silica surfaces with sub-nanometer root-mean-square roughness. The platform was validated by fabricating extended-length fiber Fabry–Pérot cavities and monolithic micro-cavity …

Ionophore-Based Plga Nanosensor For Selective Ion Detection And Imaging, Zhiyu Tang

Electronic Theses and Dissertations

Accurate detection of electrolyte ions is essential for biological research, disease diagnosis, and the investigation of cellular function. In this study, we developed ionophore-based PLGA nanosensors for the optical detection of biologically important ions. The nanosensors were prepared by encapsulating ionophores, chromoionophore III, and ion exchangers within PLGA nanoparticles. The resulting nanosensors showed uniform morphology, good colloidal stability, and concentration-dependent optical responses toward Na⁺, K⁺, and Ca²⁺ over the range of 10⁻⁶ to 10⁻¹ M. Reversible fluorescence responses under repeated ion concentration changes confirmed the stability and robustness of the sensors. The nanosensors also demonstrated reliable analytical performance for K⁺ …

A Hybrid Deep Learning Model Combining Cnn And Extreme Learning Machine For Cyberattack Classification, Israa S. Kamil

Journal of Intelligent Informatics, Networking, and Cybersecurity

As ransomware attacks and zero-day exploits grow sophisticated, the need for intelligent, accurate systems to detect such threats becomes clearer. In this paper, a hybrid learning model based on Convolutional Neural Networks (CNNs) and Extreme Learning Machine (ELM) is presented to improve multiclass classification performance for cybersecurity applications. The framework combines CNNs' hierarchical feature learning with ELMs' fast classification. An attention mechanism that assigns weights to each feature based on importance is included in the final model. The hybrid model performed well on the metrics: precision = 0.97, recall = 0.98, and F1- score = 0.97, and, as expected from …

Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap

Journal of Cybersecurity Education, Research and Practice

 Abstract -This conceptual essay addresses the need for systemic and systematic transdisciplinary analytical techniques within cybersecurity and technical security. This conceptual essay is contingent upon recognition that cybersecurity is not simply technical in nature, it does not need an adversary, and more importantly it is based upon systems engineering and systems thinking.  The essay contributes a socio-technical attribution chain and field-specific ontology/taxonomy which distinguish user-triggered events from root causes, latent conditions, technical debt, validation failures, governance failures, and attribution bias before assigning responsibility to end users. It systematically defines an ontology inclusive of developer technical debt, organizational debt arising from …

The Characterization Of Bridging Waters And Ions In Protein-Rna Complexes, Leslie Duong

Master's Theses

Here we explore the role of bridging waters and ions in protein-RNA complexes. From an initial set of 33 high-resolution X-ray crystal structures, 17 were identified such that protein-RNA complex and component protein and RNA chains were found within 1 pH unit as indicated by crystallization conditions and their diffraction temperatures meeting one of two ranges: above or below freezing. To define an even more realistic set, 12 unbound-unbound and unbound-pseudo-unbound complexes from the 17-set were studied, showing the large fraction of complexes indicating more protein and RNA water hydrogen bonding in their actual interfacial regions as opposed to those …

Hydrus Modeling Of A Sahelian Agroforestry System: An Investigation Of Local Water Balance, Nicole A. Butler

Master's Theses

Effects of drought can devastate agricultural productivity in the West African Sahel. Climate complexities, such as lower-than-average rainfall and high winds, can lead to crop failure and low yields, thereby creating food security issues. Agriculture in the Sahel is primarily rainfed, and the rain is becoming increasingly unpredictable due to the changing climate. The method of intercropping groundnut (Arachis hypogea) and pearl millet (Pennisetum glaucum) with the shrub species Piliostigma reticulatum can combat the effects of climate change and restore degraded soil. Intercropping can increase water availability and crop yield when compared to crops grown in the absence of shrubs. …

Hybrid Microbial-Enzymatic Electrosynthesis For De Novo Decanoic Acid Production From Co2, Yongze Wang, Wenjin Dong, Meijing Wei, Su Song, Zhiqing Huang, Yaojie Liu, Shelley D. Minteer, Hui Chen

Chemistry Faculty Research & Creative Works

The steady increase in atmospheric CO₂ levels is a key driver of anthropogenic climate change, prompting widespread global concern. In this context, the sustainable conversion of CO₂ into value-added chemicals represents an attractive route toward carbon-neutral manufacturing and green chemistry. Here, we developed a proof-of-concept hybrid microbial-enzymatic electrosynthesis system that combines microbial electrosynthesis (MES) and enzymatic electrosynthesis (EES) to convert CO₂ into decanoic acid under ambient conditions, using electrical energy. In the MES module, CO₂ was converted to acetate via the Wood–Ljungdahl pathway of Clostridium ljungdahlii, using H2 produced by electrochemical water splitting as the electron …

A Machine Learning Approach For Water Quality Assessment In The Lower Rio Grande Valley Watershed, Saika Nowshin Nowrin, Chu-Lin Cheng, Jungseok Ho, Jinwoo An, Fatemeh Nazari

Civil Engineering Faculty Publications

Water quality analysis plays an essential role in maintaining the health and sustainability of river ecosystems, especially in semi-arid regions like the Arroyo Colorado Watershed in South Texas. Since the river is a vital source of water supply for local communities, agriculture, and wildlife, it faces significant challenges and pollution from land use changes, climate variation, and agricultural runoff. Continuous monitoring and assessment of water quality parameters and their temporal variability are essential to ensure the drinking water supply and aquatic ecosystem health. However, comprehensive laboratory-based water quality investigations are often constrained by higher costs, logistical complexity, and limited manpower. …

Can Machines Testify? Llms And The Boundaries Of Testimonial Epistemology, Michael J. Cummins

Philosophy Summer Fellows

As Large Language Models and AI chatbots become increasingly prevalent, pressing questions are raised about whether beliefs formed through LLM interactions carry the same epistemic weight as beliefs formed through human testimony. How we answer this question depends on whether LLMs can function as testifiers, a role which is typically assumed to require a human or human-like agent. This assumption has gone largely unexamined, yet its consequences are significant: if LLM outputs cannot constitute testimony, then the justificatory tools of testimonial epistemology are unavailable to any beliefs formed through LLM interaction. This paper challenges that assumption. It first argues that …

Editorial: Participatory And Just Governance: Empowering Local And Indigenous Communities, Melissa Haeffner, Maiko Sakamoto, Jenia Mukherjee, Hong Quan Nguyen, Soyo Takahashi

Environmental Science and Management Faculty Publications and Presentations

The papers in this Research Topic (RT) extend insights on the roles of social relations, institutional arrangements, Indigenous ways of knowing, local knowledge, and decisionmaking participation in shaping water governance and practice. Despite efforts to predict flows and possible hazards, we continue to observe “unintended consequences” when humans interact with waterscapes. What we often learn, we argue, is that what appears “unintended” often reflects a deliberate architecture of exclusion; one that becomes legible only when social power relations are placed at the center of analysis alongside hydrological variables. Doing so may illuminate where injustice complicates intentions and what difference participatory …

Using A Cell Flux Model To Investigate Phytoplankton Growth And Macromolecular Allocation Under Iron Limitation, Margaret Bernish, Meng Gao, Jongsun Kim, Benoit Pasquier

School of Earth, Environmental, & Marine Sciences Faculty Publications

Global biogeochemical models are powerful tools used to interpret observations and empirical data, create hypotheses, and make predictions. Many of these models, however, represent marine microbes as static stoichiometric reactions that convert nutrients into biomass. To better constrain the biological processes that control nutrient cycling in the global ocean, we extend the Cell Flux Model of Phytoplankton to explore the impact of dissolved iron concentration on the allocation of macromolecules and elemental ratios within phytoplankton cells. This model is supported by data obtained from a range of incubation experiments conducted with phytoplankton of varying species and size categories. Model output …

A Dual- Task Hierarchical Graph Attention Network For Protein-Protein Interaction Sites Prediction, Oras A. Hussein, Eman S. Al-Shamery

Journal of Intelligent Informatics, Networking, and Cybersecurity

In computational structural biology, it is still very hard to accurately find protein-protein interaction (PPI) sites and estimate how strong the interaction would be. In this research, we provide an innovative two-stage deep learning framework that combines residue-level graph representation learning with protein-level regression to achieve a thorough modeling of protein interactions. Protein structures first encoded as residue graphs, with nodes that stand for amino acids and edges that show how close they are to each other in space. To find binding residues, a deep residual Graph Attention Network v2 (GATv2) uses multi-head attention, residual connections, and Jumping Knowledge aggregation …

Oregon State Rank Assessment For Thompson Mistmaiden (Romanzoffia Thompsonii), Nora Dunkirk, Gabriel Campbell, Sue Vrilakas

Institute for Natural Resources Publications

Oregon state conservation status assessment for Thompson mistmaiden (Romanzoffia thompsonii) using NatureServe methodology, 2026.

A Professional Development Course On Data-Driven Dynamical Systems At A Primarily Undergraduate Institution - Part B: Professional Development Framework And Institutional Implementation, Alessandro M. Selvitella, Jeffrey R. Anderson

CODEE Journal

This paper presents the professional-development and institutional-implementation component of a three-paper program on introducing data-driven dynamical systems into undergraduate ordinary differential equations instruction at a primarily undergraduate institution. The companion paper \cite{SelvitellaAnderson2026} develops the mathematical and computational content, including regression, regularization, Dynamic Mode Decomposition, Sparse Identification of Nonlinear Dynamics, and a Van der Pol oscillator activity. The present paper asks a complementary implementation question: what departmental structures, graduate teaching assistant roles, professional-development activities, and course-support pathways are needed for such materials to become teachable within local undergraduate settings?

We describe a three-phase professional-development model for graduate teaching assistants in the …

Cytotoxicity Of Bioactive Peptides From Cowpea (Vigna Unguiculata L. Walp) Against Breast Cancer Cells (Mcf-7), Dian R. Ningsih, Zusfahair Zusfahair, Ely Setiawan, Purwati Purwati, Kasta Gurning, Fitri A. Puspita Sari, Elya Widiawati

Karbala International Journal of Modern Science

Cancer is characterized by dysregulated metabolic signaling pathways, leading to uncontrolled cellular proliferation. Current cancer treatments, which involve surgery, radiotherapy, and chemotherapy, still cause adverse systemic toxicities. Accordingly, one possible effort that can be undertaken is to explore safe anticancer substances from protein sources such as peptides. Bioactive peptides can be isolated by hydrolyzing cowpea (Vigna unguiculata L. Walp) protein with trypsin. The objectives of this study were to isolate and fractionate bioactive peptides from cowpea, to determine the anticancer activity of peptide fractions, to identify active peptide fractions as anticancer agents using Liquid Chromatography High Resolution Mass Spectrometry …

Exogenous Ribosome Incorporation Induces Lineage Transdifferentiation In Intestinal And Liver Cancer Cells, Haoxuan Gu, Nadia Wahyuningsih, Keisuke Yamashita, Shota Inoue, Fuchao Tan, Mani Sharaki, Muhaimin Rifa’I, Kunimasa Ohta

Karbala International Journal of Modern Science

It has previously been shown that exogenous bacterial ribosomes added to somatic cells and various cancer cell lines generate ribosome-induced cell clusters (RICs) capable of transdifferentiating into multiple cellular lineages. However, the scope of ribosome-induced transdifferentiation in cancer cells remains poorly understood. This study aimed to analyze the effects of exogenous ribosome incorporation on human cancer cell lines, specifically the intestinal epithelial cell line Caco-2 and the hepatocellular carcinoma cell line HepG2. Caco-2 and HepG2 cells were cultured with purified bacterial ribosomes in human ES/iPS cell medium after trypsinization, resulting in the formation of ribosome-induced Caco-2 (RICs-Ca) and HepG2 (RICs-He) …

Selenoprotein P And Selenium As Potential Diagnostic Biomarkers For Breast Cancer Patients, Farah A. Rashid, Rawaa A. Ali, Hanaa A. Ali

Karbala International Journal of Modern Science

Breast cancer incidence increases in last decade. Oxidative stress increases during cancer development causes consuming of antioxidants. Selenium and its transporting protein, selenoprotein P have an important role in redox homeostasis. This study aims to investigate whether or not selenium and selenoprotein P could be diagnostic biomarkers for breast cancer patients. This study was included 30 individuals in control group who is age- and BMI-matched with 60 breast cancer patients. Selenium was measured by colorimetric assay kit and selenoprotein P was determined by Sandwich ELISA kits. The results indicate significant decrease (p < 0.0001) of serum selenium and selenoprotein P in breast cancer patients compared to control. A positive significant correlation (r = 0.6214, p < 0.0001) was found between selenium and selenoprotein P in breast cancer patients. Selenium has an excellent diagnostic accuracy with area under curve 0.9831, sensitivity 95% and specificity 100% at cut-off less than 3.54 mmol/L. Furthermore, selenoprotein P has also an excellent area under curve 0.9958 with sensitivity 96.77% and specificity 100% at cut-off less than 4.15 ng/ml. These exploratory findings appear that selenium and selenoprotein P could be potential diagnostic biomarkers for breast cancer patients. Further investigations in large-multicenter populations are needed to confirm results.

Tapping Into The Ocean’S Hidden Energy: Feasibility Of A 5 Mw Otec Installation In North Bali, Widodo Setiyo Pranowo, Yani Permanawati, Gisela Malya Asoka Anindita, Agung Kurniawan, Albertus Sulaiman, Johar Setiyadi, Safri Burhanuddin, Ivonne Milichristi Radjawane, Hansan Park, Endro Sigit Kurniawan

Karbala International Journal of Modern Science

Indonesia is an archipelagic country surrounded by water and faces energy challenges due to the low use of renewable energy. Among the potential renewable options, marine energy is a particularly suitable resource given the country’s geographical nature. Based on this discussion, seawater temperature can be used as an alternative ocean thermal en-ergy known as ocean thermal energy conversion (OTEC) by using the difference in sea surface and deep-sea water temperatures. Therefore, this study aimed to examine OTEC installations in North Bali waters using closed-cycle OTEC calculations for a 5 MW system. Following this objective, we examined the water conditions by …

Oregon State Rank Assessment For California Pinefoot (Pityopus Californicus), Lindsey K. Wise

Institute for Natural Resources Publications

Oregon state conservation status assessment for California Pinefoot (Pityopus californicus) using NatureServe methodology, 2026.

Coordinating Meaning With Ai System Cards: A Thematic Analysis, Jennifer Rene French Cyrek

Doctoral Dissertations and Projects

As the meaning of AI risk remains unsettled across sociotechnical and public discourse, AI system cards are an emergent, yet understudied, genre of technical documentation through which AI technology developers publicly frame new AI system capabilities including risks. This thematic content analysis study examines how AI technology developers coordinate meaning regarding risk and responsible development in stewardship of AI. Guided by a constitutive view of communication and systems theory, second-order cybernetics, and the cybernetic tradition, this study analyzes a purposive corpus of AI system cards collected from 2023-2025 using thematic content analysis and the hierarchy of meaning heuristic from coordinated …

New Paradigm Of Forestry And Grassland Research Driven By Artificial Intelligence, Zhang Huaiqing, Jiaojun Zhu, Yang Liu, Tingdong Yang, Tian Gao, Jing Zhang, Xueyan Zhu, Yan Chen, Xian Jiang, Zeyu Cui, Jingwei Tan, Kexin Lei

Bulletin of Chinese Academy of Sciences (Chinese Version)

Addressing the current limitations in forestry and grassland research, particularly in cross-scale system cognition, complex process mechanism representation, and multi-scenario simulation, this study proposes an artificial intelligence-driven paradigm reconstruction framework, to shift the research model from experience-oriented approaches toward data- and intelligence-driven integration. On this basis, the study systematically establishes a multidimensional mapping between artificial intelligence and forestry and grassland research across research objects, processes, and objectives, and clarifies their intrinsic coupling mechanisms and technical pathways. Furthermore, it develops a foundational capability system to support the new paradigm from four key dimensions: data, computing power, models, and applications. By examining …