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How Joint Management of the Fena Valley Reservoir Furthers the Cooperative Endeavour Towards Self-Determination of the People of Guam [Article]
No full textArticleThe Fena Valley Reservoir and Wastewater Treatment Plant is one of the remaining utility systems in Guam wholly owned and managed by the Navy. The Navy maintains these systems to support its military installations, while selling treated water to the local government. The transfer to the local government stands to demonstrate an ongoing cooperative relationship to bring Guam closer to self-determination. However, principal obstacles include: (1) lack of guidance from Congress for utility systems transfers in overseas territories; (2) Guam’s struggles to meet current and growing demand and resolve environmental challenges; and (3) balancing the United States’ interests in promoting self-determination and military priorities. There should be a transfer of ownership and management of Fena for three reasons: (1) the transfer is consistent with the Department of Defense’s congressional authorization for utility privatization; (2) the “One Guam Initiative” between Guam and the Navy allows for improvement and integration of utility systems to meet the growing civilian population and military buildup;
and (3) the transfer is a unique opportunity for the United States to demonstrate its commitment to promoting the wellbeing of those that have not yet attained a full measure of self-government.This material published in Arizona Journal of Environmental Law & Policy is made available by the James E. Rogers College of Law, the Daniel F. Cracchiolo Law Library, and the University of Arizona Libraries. If you have questions, please contact the AJELP Editorial Board at https://ajelp.com/contact-us
Safeguarding American Ingenuity: A Comparative Analysis of International Trade Regimes in Mitigating Chinese Intellectual Property Theft [Note]
No full textNoteThe ever-present tension between the United States and China has heightened in recent years due to a rise in the theft of American intellectual property from Chinese semiconductors. Pharmaceutical intellectual property is at the crux of this issue, as a hit to this valuable market comes with severe penalties for the United States. Neither legislation from the World Trade Organization nor the more recent Phase One Trade Deal can present a viable solution for this issue, resulting in the need for a structural rebirth in international trade legislation. Previous discussions on this issue have touched on the need to rebalance the TRIPS Agreement and reassess the United States’ trade relationship with China. These arguments do not clarify the need to reformat the WTO as a whole and recognize the institution for what it is—a system that was not created to support the levels of innovation and technology that exist today; a system that certainly did not account for China’s contrasting market structure. This paper examines a new dynamic goal that would require 1) the WTO to hold China fiscally and criminally responsible for its unfair market practices; 2) the United Nations to create a new, encompassing multilateral trade agreement in the future; and 3) the United States to develop a concrete plan to decouple from China.This material published in Arizona Journal of International and Comparative Law is made available by the James E. Rogers College of Law, the Daniel F. Cracchiolo Law Library, and the University of Arizona Libraries. If you have questions, please contact the AJICL Editorial Board at http://arizonajournal.org/contact-us/
Design, Analysis, and Evaluation of Highly Secure Smart City Infrastructures and Services
No full textCritical infrastructure systems, such as energy networks, water treatment facilities, and 5G telecommunications, form the backbone of national security and public welfare. However, many of these systems rely on outdated technologies, rendering them increasingly vulnerable to evolving cyber threats. As these infrastructures become increasingly digitized under Industry 4.0, integrating cloud computing, Artificial Intelligence (AI), and the Industrial Internet of Things (IIoT), they simultaneously introduce a broader attack surface susceptible to threats such as sensor spoofing, Denial-of-Service (DoS), and man-in-the-middle attacks. Realistic, scalable, and interoperable testbeds are essential to evaluate cybersecurity risks and mitigation strategies in such interconnected environments. Existing isolated testbeds are limited in their ability to replicate cross-domain dependencies and security vulnerabilities inherent in modern smart cities. To address this gap, this dissertation introduced the Federated Cybersecurity Testbeds as a Service (FCTaaS) framework, an innovative approach that federates geographically and logically distributed testbeds to enable more robust and integrated cybersecurity experimentation. FCTaaS offers remote access to specialized hardware and software resources, streamlining testbed discovery, orchestration, and resource management. This enables researchers and educators to conduct complex cybersecurity experiments without the overhead of local setup or infrastructure ownership. The research specifically focuses on developing two cyber-physical testbeds: the Water Treatment Facility Testbed (WTFT) and the 5G Telecommunication Testbed (5GTT). These testbeds closely mirror real-world operations, offering a rich experimental environment for vulnerability analysis and defense validation. A core contribution of this work is the design of a cyber-resilient architecture that leverages Edge AI and Anomaly Behavior Analysis to enable real-time threat detection and mitigation. An autoencoder-based machine learning model was designed and implemented for anomaly detection in the water treatment facility. Deployed on edge hardware, the system achieved 98.3\% detection accuracy with an average inference latency of 19.6 ms. Additionally, resilience evaluation revealed that the proposed mitigation strategy improved system resilience by an average of 25.7 points, demonstrating the importance of lightweight, low-latency AI-based solutions in protecting mission-critical infrastructure. Building on this, a comprehensive 5G testbed was developed for both research and education. It integrates open-source 5G software with physical radio hardware to emulate real-world 5G environments. Through experiments simulating DoS attacks and database exploits, the study revealed vulnerabilities in core network functions, notably the AMF and MySQL database services, which can compromise both network availability and data integrity. A second autoencoder-based anomaly detection model was developed and evaluated to counter these threats. The model achieved 98.9\% detection accuracy across multiple network attack scenarios, validating its effectiveness in securing 5G systems. Beyond the design of testbeds and detection systems, the FCTaaS framework addresses three fundamental aspects of cyber-physical system resilience: interoperability, scalability, and interdependency. The interoperability use case demonstrated seamless integration between the 5G network and water treatment monitoring systems, enabling real-time data collection and supervisory control. The scalability study revealed system limitations when handling more than 300 concurrent remote nodes, identifying critical thresholds for infrastructure performance. Lastly, the interdependency analysis highlighted the cascading effects of cyberattacks, showing that a targeted DoS attack on the 5G UPF could entirely disrupt water treatment communication systems, emphasizing the systemic risk posed by interconnected infrastructure. In conclusion, this dissertation offers a unified, scalable, and practical solution for advancing cybersecurity research through federated testbeds. The FCTaaS framework significantly contributes to the field by enabling realistic experimentation across interconnected systems, facilitating the development of AI-driven security mechanisms, and promoting hands-on education. Its impact lies in bridging the gap between isolated testbed environments and the complex, integrated ecosystems found in modern smart cities and paving the way for resilient, secure, and adaptive cyber-physical infrastructure.Release after 05/21/202
Differential Metabolite Expressions in Firefighters Induced by Fireground Exposure: A Comparative Metabolomics Analysis
No full textFirefighters are regularly exposed to known or probable carcinogens, including polycyclic aromatic hydrocarbons (PAHs), benzene, formaldehyde, phthalates, and other harmful substances. This exposure occurs mainly through inhalation of smoke released during fire events and dermal exposure. Consequently, firefighters face a higher risk of selected cancers, such as bladder cancer. The International Agency for Research on Cancer (IARC) classified firefighters' occupational exposure as carcinogenic to humans, but there is still a lack of mechanistic evidence on what and how fireground exposure elevates cancer risks and the relationship between fireground exposure and metabolite expression in humans remains poorly understood. Research is also limited regarding the differences between wildland-urban interface (WUI) firefighting and structure fires concerning the biological response in firefighters. Additionally, there is a need to understand how women firefighters respond differently to fireground exposure compared to men firefighters. To address these gaps, we bring together three projects involving male and women firefighters, exposed to various types of fires. Powered by the high-resolution metabolomics pipeline and the high-resolution liquid-chromatography mass-spectrometry (LC-MS) platform, these projects aim to evaluate the impact of fireground exposure on firefighters' metabolisms, together with other important factors for firefighters: Project 1 assesses changes in the urinary metabolome by Hispanic ethnicity among male firefighters respond to structure fires. Prior to project 1, we developed an analytical pipeline for urine-based metabolomics, which was applied to investigate the effect of fireground exposure (prior analysis) and ethnicity (project 1) on metabolome as disparity in cancer risk has been observed among Hispanic and non-Hispanic firefighters. Two publications have been produced from project 1, titled “Evaluating changes in firefighter urinary metabolomes after structural fires: an untargeted, high-resolution approach” and “Differential metabolic profiles by Hispanic ethnicity among male Tucson firefighters”. Project 2 assesses changes in the urinary metabolome by fireground exposure in male firefighters responding to WUI fires. WUI fires differ from structure fires in that they introduce a much more complex exposure matrix due to the involvement of both wildland biomass and built materials. We also tried to compare the metabolic responses across different fire types, looking for unique and shared biological responses that might understand prevalent conditions among these firefighters. One manuscript has been produced based on project 2 which is being peer reviewed as of the time of dissertation process. Project 3 assesses changes in the urinary metabolome by training fire exposures in women firefighters. Project 3 investigates metabolic responses to training fire exposures among women firefighters, differing from previous projects in both exposure matrix and population. Although training fires are resembling structure fires regarding burning materials, they are intrinsically different in fire intensity and participants activities. We also compared metabolic responses by fire exposure across two populations (genders).Release after 10/19/202
Quantitative Susceptibility Mapping: From Theory to Application for Static and Dynamic Imaging
No full textQuantitative Susceptibility Mapping (QSM) is a magnetic resonance imaging (MRI) post-processing technique that uses the image phase to map the spatial distribution of magnetic susceptibility in tissues, which arises from biological sources such as iron, myelin, and calcium. QSM is a broad research field due to the complexity of computing magnetic susceptibility. As such, QSM research has focused on refining the processing algorithms, leading to the development of numerous approaches with different advantages. These approaches may incorporate assumptions about the susceptibility distribution, such as spatial smoothness, but most do not consider information from other image contrasts, which may better delineate the edges between different tissue types. Additionally, QSM has been widely applied to measure iron deposition in the brain and stroke induced microbleeds and hemorrhages, among other applications. Although typically used to obtain static information about the brain, recent applications have expanded QSM to dynamically measure susceptibility changes due to the hemodynamic response of blood to neuronal activation, demonstrating the potential for QSM to measure acute susceptibility dynamics. To holistically address QSM for the brain, a multifaceted research approach was employed, which included the following: 1) implementation of a susceptibility mapping algorithm that incorporates prior knowledge of the brain’s magnetic susceptibility distribution based on multi-contrast MRI to inform the mapping process, 2) investigation of the impact of different QSM algorithms in a large-scale, multi-site study, and 3) extension of QSM from static to dynamic applications by developing a novel processing framework to analyze susceptibility changes within the brain during various physiological processes, such as normal breathing versus breath-holding and the cardiac cycle. Through this work, we demonstrate the broad applicability of QSM, from theoretical development to algorithm implementation, as well as practical applications – contributing to a deeper understanding of its capabilities and potential for future research
Drivers of Microbial Community Composition in Crops: A Focus on Lettuce
No full textUnderstanding interactions between crops and their associated microbiomes is important for improving plant resilience, productivity, and sustainability, particularly in the face of climate change in resource-limited agricultural systems. In this dissertation, I investigated the diversity, composition, and functional potential of microbial communities associated with lettuce (Lactuca sativa L.), with a specific focus on foliar and root-associated fungi and bacteria across diverse genotypes, among species of Lactuca, across various cultivation environments, and from the perspectives of amplicon sequencing (metabarcoding), metagenomics, and genome characterization. In the first study, I used metabarcoding to characterize the endophytic microbiomes of 12 lettuce genotypes grown under desert agriculture conditions. I found that microbial community composition differed among lettuce genotypes and was associated with root morphology and leaf nutrient profiles, particularly zinc. These findings suggest a potential link between host traits and microbial community structure, with implications for breeding programs aiming to enhance crop nutrition and resilience via microbiome selection. In the second study, I compared foliar fungal communities across 98 accessions of wild and cultivated Lactuca species grown under controlled greenhouse conditions. I accessed published genomes of the plants themselves, mining those datasets for fungal genomic signatures. This metagenomic-based approach revealed that wild relatives consistently hosted more diverse and compositionally distinct fungal communities relative to L. sativa. These differences were independent of geographic origin and were associated with reduced pest and disease susceptibility. My results thus support the broad hypothesis that domestication may have led to the loss of beneficial microbial associations, or the tools for establishing them, and underscore the potential of microbiome-informed breeding and rewilding strategies to enhance crop health.The third study focused on the isolation and genomic characterization of five fungal endophytes from a wild relative of cultivated lettuce: Lactuca serriola, which grows as a roadside- and field weed in southern Arizona. These isolates, which represented common fungi from L. serriola in dryland conditions, were selected based on successful culturing and representation of distinct morphotypes. I assembled and annotated draft genomes of endophytic strains of Alternaria postmessia, Alternaria alternata (two strains), Fusarium falciforme, and Aspergillus terreus. These data represent foundational genomic resources for future research into the functional roles and evolutionary relationships of endophytes in wild relatives of crops, which may be transferred to crop plants as biostimulants, bioprotectants, or biocontrol agents. In the fourth study, I sequenced and analyzed genomes of nine fungal isolates from field-grown lettuce to assess the biosynthetic potential of their secondary metabolite pathways and carbohydrate-active enzymes. These isolates were selected based on successful culturing, taxonomic diversity, and representation of both epiphytic and endophytic lifestyles. While initial hypotheses predicted reduced biosynthetic gene cluster (BGC) richness in lettuce-associated fungi due to selective pressures associated with lettuce breeding and cultivation, comparative analyses revealed variation across isolates and showed that species identity, rather than host type or lifestyle, was the primary predictor of BGC count. Several Alternaria isolates harbored conserved polyketide clusters, including those associated with alternariol and T4HN biosynthesis, which showed 100% similarity to experimentally validated entries in the MiBIG database. Although BiG-SCAPE identified gene cluster families (GCFs) across the dataset, these reference-matching clusters were not always grouped, reflecting methodological differences in how the tools assess similarity. These findings challenge assumptions about host-driven genome streamlining in crop-associated fungi and instead highlight the importance of species-level context in shaping biosynthetic and functional diversity. Together, these four studies provide an integrated view of how plant genotype, domestication status, and environmental conditions shape the structure and functional potential of the lettuce microbiome. This work advances understanding of plant-microbe interactions in arid agroecosystems and contributes to emerging frameworks for microbiome-assisted breeding, sustainable crop management, and functional trait discovery in plant-associated microbes
PV Performance Modeling with Noisy and Incomplete Datasets
No full textAs photovoltaic (PV) power generation gains increasing traction globally as an energy source, there is a growing need to be able to accurately predict power output of PV systems. Accurate predictions enable the module characterization, forecasting, and performance analysis that drives decisions to invest in solar energy or not. These predictions rely on mathematical models of PV systems which relate PV system performance to irradiance and PV cell temperature via model parameters such as the power output under reference conditions, temperature derating coefficient, and the degradation rate of the PV module. In this dissertation, it is shown that the most accurate predictions can be made with the use of laboratory PV module characterization and on-site weather and irradiance measurements, while two new methods are proposed to improve the applicability of the PVWatts irradiance-to-power model to existing PV power production datasets. The first proposed method is the use of a goodness-of-fit metric with a simple function fitted to daily PV power production data to detect and remove cloudy days without the use of irradiance-based clear-sky detection. Filtering based on the clear-sky detection method and time of day is demonstrated to improve the applicability of the PVWatts model to existing PV power production datasets even in the absence of on-site weather and irradiance data. The second proposed method combines models to remove variables and uses a statistical fitting approach to enable the analysis of PV array performance from datasets that otherwise lack sufficient information to inform model parameters. The viability of this approach is demonstrated for both on-site and remote weather and irradiance datasets. Both of these techniques will be discussed along with their impact on data interpretation and prediction fidelity
Baptizing the Bees: Vergilian Allegory in Confessions 9.10
No full textThis thesis examines how Augustine forms intertextual links between Vergil’s Georgics 4 and his Confessions 9.10. Both texts employ themes of katabasis, sacrifice, rebirth, perfect society, and didactic heroism, which enables Augustine to intertextually lift Vergil’s text out of its original context and into a new Christianizing and Neoplatonic context. To understand how Augustine forms this intertext, I begin the thesis by developing a theory of intertextuality which compares the process of intertextuality to allegorical interpretation. I next consider the role Augustine gives to Vergil’s Georgics 4 in Confessions 10, where Augustine prominently makes allusion to the Vergilian text. Although textual allusion to Vergil is not a prominent feature in Confessions 9.10, I argue that the scene in Confessions 9.10 is structurally and thematically similar to Augustine’s treatment in Confessions 10. The thesis concludes by considering how Confessions 9.10 plays on the themes found in Georgics 4, and how Augustine is able to assert his own perspective onto Vergil’s text by placing it into a Christian context
Quantum Communications with Near-Term Quantum Networks
No full textQuantum networks promise to enable provably secure communications, enhanced sensing, enhanced imaging and distributed quantum information processing. However, low generation rates and the quality of distributed entanglement will constrain near-term quantum networks. This dissertation explores near-term quantum networks for shared entanglement generation. We begin by reviewing the theoretical limits of quantum communications and the principles underlying quantum links and repeaters, including various photon-based and memory qubit encodings. We then analyze quantum link architectures for entanglement generation for a diverse class of photonic encodings. We subsequently analyze linear-chain quantum repeater networks; we discuss improvements to the rate-vs.-loss scaling with time-multiplexed entanglement swaps and the practical limitations associated with finite memory coherence times and buffer capacities. We propose satellite-assisted quantum links as an alternative to quantum repeaters, presenting and analyzing several candidate link architectures
An Intervention to Support Well-Being and Reduce Burnout in Psychiatric Nurse Practitioners
No full textPurpose: The purpose of this quality improvement project was to address burnout and promote well-being among Psychiatric Mental Health Nurse Practitioners (PMHNPs) in the Psychiatric Nurse Practitioner Collective in Tucson, Arizona and assess burnout risk levels. An asynchronous educational intervention was developed to provide evidence on burnout and well-being and introduce Cyclic Sighing, a breathwork technique selected to support nervous system regulation and enhance mitochondrial function. Background: Burnout syndrome results from prolonged exposure to chronic, unmanageable stress and is characterized by emotional exhaustion, depersonalization, and reduced personal accomplishment. Among healthcare providers, including PMHNPs, burnout is linked to significant psychological and physiological harm—disrupting autonomic nervous system balance, reducing mitochondrial efficiency, and impairing emotion regulation, memory, and executive function. The consequences of provider burnout extend beyond the individual, contributing to higher turnover, reduced quality of care, and increased systemic strain on healthcare delivery. In Arizona, where unmet mental health needs are among the highest in the country, PMHNPs face disproportionate stress as they shoulder increasing demand with limited support. Interventions that are brief, accessible, and grounded in neurobiological evidence are urgently needed to support provider well-being and stabilize care systems. Methods: Nineteen PMHNPs participated in the project by viewing an educational presentation and completing a post-intervention survey. The survey included items assessing knowledge, confidence, and intent to use Cyclic Sighing, as well as an adapted version of the abbreviated Maslach Burnout Inventory (aMBI) developed for this project to estimate burnout risk. Results: Post-survey responses indicated high levels of understanding of burnout and well-being (mean = 4.53), confidence in applying the breathwork technique (4.26), and intent to incorporate it (4.32). Burnout risk scores indicated moderate emotional exhaustion (mean EE = 3.32), low depersonalization (1.97), and high personal accomplishment (3.88). Overall, 10.5% of participants were classified as high risk for burnout, 52.6% as moderate, and 36.8% as low. Conclusions: This project highlights the potential impact of brief, neuroscience-informed education combined with supportive practices. Interventions that address burnout and well-being through strategies that support multiple health aspects may serve as powerful tools to support PMHNP well-being and reduce burnout risk