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Residual Gas Analysis of the FS8 Pressure Suit Glove
No full textImmediate accessThis item is made available by the University of Arizona Center for Human Space Exploration (CHaSE) with support from the University of Arizona Libraries. If you have questions, please visit https://www.b2science.org/center-human-space-exploration-chase
A Discrete Choice Experiment To Assess Preferences for a Future Preventative HIV Vaccine Among Key Populations in Uganda
No full textHuman immunodeficiency virus (HIV) affects over 39 million people worldwide, with Uganda being among the top ten countries most affected. Key populations are at heightened risk and require effective prevention measures. Discrete choice experiments (DCEs), derived from economics, identify factors influencing behavioral decisions. This study combined a systematic literature review, key informant interviews (KIIs), and a cross-sectional DCE survey to explore preferences for HIV prevention strategies in Uganda.We reviewed 71 stated preference studies from 2,970 screened (34,558 participants) published between 2018 and 2022. Most were DCEs (82%), conducted in Africa, with location (55%) and cost (39%) as the most common attributes. In the 20 KIIs conducted in March 2024, participants highlighted barriers such as duration, accessibility, and stigma. In June 2024, we surveyed 406 participants (85 young women, 159 female sex workers, 132 participants self-identifying as belonging to the LGBTQ+ community) using purposive and community-based sampling. Preferences were influenced most by severe side effects (β: -0.69, 95% CI: -0.78, -0.60), effectiveness (30% increase, β: 0.39, 95% CI: 0.34, 0.44), and cost (50,000 UGX/~14 USD increase, β: -0.22, 95% CI: -0.27, -0.17). Side effects had the greatest influence, followed by effectiveness and cost. Participants stressed the importance of accessible information and tailored messaging to address diverse preferences. Affordable or free prevention options with minimal side effects were essential attributes to increase uptake of HIV prevention strategies. Policymakers should prioritize reducing financial barriers and transparently communicate safety and efficacy to enhance uptake and improve public health outcomes.Release after 01/21/202
Robust PHY-layer Signaling and Enhanced Security for Wi-Fi Systems
No full textWi-Fi is a key component of the wireless ecosystem. It is the predominant technology for indoor wireless access and increasingly for outdoor use, with ubiquitous deployment for networks at enterprise, healthcare, public safety, residential buildings, smart factories, offices, restaurants, and many more. Its prevalence relies on continuous advancements in its efficiency, capacity, coverage, and security. To improve these aspects, Wi-Fi protocols have rapidly evolved over the past two decades, incorporating more advanced features, specified by a series of IEEE 802.11 standards. Seamless support of these features while maintaining compatibility and interoperability with earlier Wi-Fi generations necessitates robust Physical (PHY)-layer signaling. Such signaling plays a crucial role in frame processing and channel access by conveying essential parameters, e.g., frame length, transmission rate, connection bandwidth, beamforming capabilities, etc. Moreover, PHY-layer signaling has the potential to facilitate PHY-layer authentication and encryption. Despite its clear benefits, existing Wi-Fi PHY-layer signaling introduces high overhead due to the extended Signaling (SIG) fields of the frame header. Moreover, legacy devices cannot decode newly added SIG fields that are tailored for advanced features, thus limiting their functionality. Furthermore, existing Wi-Fi PHY-layer signaling lacks adequate protection for confidentiality, authenticity, and integrity. These vulnerabilities along with other inherent problems in the PHY-layer implementations of Wi-Fi standards have exposed Wi-Fi systems to various attacks. This dissertation focuses on developing novel robust PHY-layer signaling for Wi-Fi, and exploring security threats that target PHY-layer signaling and their countermeasures. We first propose a novel and robust PHY-layer signaling mechanism for recent generations of Wi-Fi that are built on Orthogonal Frequency Division Multiplexing (OFDM) and Multiple-Input-Multiple-Output (MIMO). More specifically, we develop a scheme called Extensible Preamble Modulation (eP-Mod), which enables Wi-Fi devices to embed user-defined signaling bits within the Short Training Fields (STFs) of the preamble. To strike a balance between capacity and reliability, we explore multiple eP-Mod variants that adapt to channel conditions and leverage MIMO diversity and multiplexing gains. We then extend eP-Mod to different MIMO schemes, channel widths, and OFDM-based IEEE 802.11 standards while maintaining low design complexity. Most importantly, our redesigned STFs satisfy the stringent IEEE standards' requirements on the preamble functions, including frame detection and synchronization. Therefore, STF with eP-Mod offers a robust PHY-layer signaling approach without compromising the primary functions of the standardized preamble. Furthermore, our scheme is backward-compatible with legacy (eP-Mod-unaware) devices. Through numerical analysis, extensive simulations, and hardware experiments, we demonstrate the practicality and reliability of eP-Mod. Next, we study adversarial attacks on existing PHY-layer signaling mechanism. We uncover vulnerabilities in standardized Wi-Fi preambles, including predictability, weak integrity, and lack of authenticity and confidentiality guarantees. We craft three Preamble Injection and Spoofing (PrInS) attacks that exploit these vulnerabilities along with the PHY-layer receive state machine and the capture effect. In PrInS attacks, an adversary can inject forged preambles without payloads, aiming to disrupt legitimate receptions or force deferral of legitimate transmissions. As a countermeasure, we propose to customize and randomize STFs of the preamble using eP-Mod so that a Wi-Fi device can authenticate a received preamble. Accordingly, we enhance the receive state machine to incorporate the preamble authentication and following mitigation steps.
We then introduce a novel SIG tampering (SIGTAM) attack against the crucial SIGs of the preamble. In SIGTAM, an adversary transmits a carefully crafted adversarial signal on select subcarriers of the targeted SIGs while remaining resilient to integrity validation, channel impairments, and synchronization errors. We also introduce a selective jamming attack on the SIGs, called SIGJAM, to demonstrate the superiority of SIGTAM in terms of power efficiency and efficacy. To defend against the SIGTAM attack, we propose a scheme that detects the attack, identifies affected subcarriers, and recovers legitimate SIGs.
In our experiments and simulations, PrInS and SIGTAM attacks are shown to lead to high frame discard and error rates, low channel utilization, poor throughput, and high latency. Besides, these attacks are stealthy and energy-efficient, as the adversarial signal only lasts for a few microseconds and may span narrow and dynamic bands. This poses challenges to their detection. Nevertheless, these attacks can be detected by our proposed approaches with nearly 100\% probability in most scenarios. Moreover, SIGs can be successfully recovered from the SIGTAM attack except for attacks with marginal normalized energy. Our defense mechanisms are shown to have no impact on the performance of the Wi-Fi system. Finally, we utilize machine learning (ML) techniques to detect and classify smart jamming on Wi-Fi systems. While our initial focus is on preamble jamming, pilot jamming, and interleaving jamming, our approach can be generalized to selective attacks like SIGTAM and SIGJAM. To deal with the time-frequency selectivity of smart jamming, we apply the continuous wavelet transform (CWT) to partially overlapped segments of the received in-phase and quadrature (I/Q) samples for feature extraction. The scalogram of the CWT is used as input to a deep convolutional neural network (DCNN) classifier that determines the type of smart jamming attack. Our solution achieves high accuracy in detecting and classifying these jamming attacks even at a high signal-to-jamming power ratio (SJR), with robustness against variants of preamble jamming and pilot jamming. Notably, the proposed scalogram-based classifier outperforms the spectrogram-based classifier, especially in the high SJR regime
Plato and the Greek Origins of Nomocracy
No full textI argue that in the ideal constitutions of Plato’s Republic and Plato’s Laws, there is a consistent concern with using law to limit the authority of the rulers. While scholars traditionally have viewed the political theory of the Laws as utterly distinct from that of the Republic, I argue that in both we can see Plato using two distinctive legal tools to answer the Juvenal Conundrum, i.e. the question of “who will guard the guardians?” These legal tools are the entrenchment of laws and the rule of law. Entrenched laws are laws that cannot be changed by any procedure, person, or group of people. In the Republic, Plato uses entrenchment of the laws concerning the education of the guardians to ensure that the rulers of his ideal city will be virtuous, and will accordingly rule with the interests of the whole city in mind, while in the Laws, Plato uses entrenchment of the laws to temper democratic self-rule without thereby increasing monarchical rule of other citizens. The rule of law, on recent accounts, requires that rule be exercised, legitimated, and exhausted by law alone, and requires legal recourse and remedy for all citizens of a polity. I argue that the constitutional designs of the Republic and the Laws both turn out to satisfy the rule of law in this way. In the Republic, the guardians rule by law, and have their office and powers delineated by the laws of the city. In addition, the citizens of Kallipolis seem to participate in holding the rulers to account and have some legal recourse in the form of the rulers’ dependence on wages provided by the citizens of the city. The constitution of the Laws embodies the rule of law, I argue, even more than that of Kallipolis. Entrenchment and the rule of law, I argue, are what we can call nomocratic elements of constitution, because they give political authority to laws over and above individuals and groups of individuals. Although Plato was not the first Greek thinker to discuss these nomocratic ideas, Plato is the first philosopher to integrate nomocratic elements in a constitutional theory, and does so consistently throughout his philosophical corpus
It's Not The Students' Fault: A Qualitative Study on the Ways in Which Academic Capitalism Impacts College Student Food Insecurity
No full textThis research explores the vital role of campus pantries in decreasing food insecurity among college students, revealing significant systemic challenges rooted in academic capitalism. This dissertation is based on qualitative methods to interview thirteen employees at six higher education institutions to understand how systemic practices further perpetuate or mitigate food insecurity. Findings from this study highlight that the reliance on external funding creates instability and highlights a disparity between performative institutional support and the genuine commitment needed for sustainable operations. Findings suggest that staff members expressed a desire for consistent funding, emphasizing the inadequacy of current practices that often disguise underlying issues. Employing the concept of organizational theater, the study illustrates how curated displays of support can obscure the urgent need for systemic change. Additionally, the research utilizes the framework of structural violence to uncover how institutional policies marginalize vulnerable populations, perpetuating food insecurity. By addressing the root causes, stakeholders can develop interventions that go beyond mere symptom management. Recommendations for improving practice include enhancing communication between pantry staff and university leadership, establishing formalized funding strategies, and fostering direct engagement to better align resources with needs. Ultimately, the findings advocate for a multifaceted approach that balances external funding with genuine institutional commitment. By prioritizing authentic support for campus pantries, universities can create a more equitable environment that empowers all students to thrive, reinforcing their mission to promote education and providing opportunities for every student to graduate
Mapping Therapeutic Pathways from Neuropsychiatric Disorders to Alzheimer's Disease
No full textAlzheimer’s disease (AD) is a progressive, irreversible neurodegenerative disorder and the leading cause of dementia worldwide, accounting for 60-80% of all cases. Clinically, it is characterized by chronic cognitive decline – including memory loss, visual-spatial deficits, and personality changes – that ultimately impairs the individual’s autonomy. Globally, 150-152 million people are projected to be living with AD by 2050-2060, with U.S. prevalence expected to nearly double from 7 million to 13.8 million in the same period. Despite decades of research, no cure exists, highlighting the urgent need for innovative strategies to prevent or slow AD progression.CNS-active drugs, or medications developed to treat neuropsychiatric disorders (NPDs) such as depression, insomnia, epilepsy, schizophrenia, and ADHD, represent a promising but underexplored strategy for AD prevention. These conditions share pathological features with AD, including oxidative stress, neuroinflammation, synaptic dysfunction, and protein aggregation. Several epidemiologic studies have suggested that treatments for NPDs may reduce dementia risk, but mechanistic validation and translational studies are lacking. Leveraging approved drugs with known safety profiles could provide a cost-effective and accelerated pathway to AD therapeutics, especially if complementary or synergistic combinations can be identified. Based on these observations, this dissertation tested the central hypothesis that pharmacological treatments for NPDs can reduce the risk or severity of AD by modulating shared pathological processes. A reverse translational pipeline was employed by first identifying protective associations in a large human population, then validating candidate therapies in an established AD mouse model, and finally mapping biological overlaps between AD, neuropsychiatric disorders, and CNS-active drugs using human datasets. This bidirectional approach, bridging epidemiology, preclinical experimentation, and systems biology, was designed to maximize translational relevance and highlight mechanisms not apparent through a single research strategy. Analyses of a medical claims database comprising more than 300,000 patients revealed that exposure to CNS-active drugs correlated with a 50% reduced risk of developing AD, particularly among older adults receiving long-term therapy. Antidepressants, sedatives, anticonvulsants, and stimulants were associated with the strongest protective effects, whereas atypical antipsychotics were associated with increased risk. Combination therapy was linked to greater risk reduction than monotherapy, with the pairing of a Z-drug and an SNRI showing the greatest benefit. In 5xFAD mice, treatment with zolpidem and atomoxetine – selected based on epidemiologic signals – significantly reduced subiculum amyloid-β plaque density and improved sleep architecture in females compared to vehicle-controls. Given the pronounced influence of sex on AD pathology, follow-up molecular analyses were conducted in females to investigate mechanisms underlying this plaque reduction. These analyses revealed reduced Tnfα gene expression without alterations in microglial parameters. Although treatment did not directly preserve synaptic markers or neuronal density, correlations between reduced plaques, lower Tnfα, and preserved Bdnf expression emphasized the importance of inflammatory regulation and synaptic resilience in limiting AD pathology during early disease stages. Finally, network-based analyses of human datasets in STRING indicated that zolpidem, atomoxetine, duloxetine, and gabapentin interacted with AD-relevant pathways, such as protein trafficking, mitochondrial function, and synaptic signaling at levels comparable to or exceeding the standard AD therapy donepezil. Together, these findings indicated that CNS-active drugs may modulate key aspects of AD biology and could be studied for repurposing efforts to prevent or delay disease onset. By integrating human epidemiology, animal modeling, and pathway mapping, this work highlights the value of reverse translational strategies for drug discovery. Encouraging the adoption of such bidirectional pipelines offers a realistic, impactful path toward precision prevention and improved therapies, moving the field closer to altering the trajectory of AD and related dementias
Push Roll Power
No full textImmediate accessThis item is made available by the University of Arizona Center for Human Space Exploration (CHaSE) with support from the University of Arizona Libraries. If you have questions, please visit https://www.b2science.org/center-human-space-exploration-chase
Prediction, Interpretation and Counterfactual Generation for Acute Care Applications
No full textOrgan failure in critically ill patients is a dynamic process which evolves over time as physiological stateschange and multiple organ systems interact. Anticipating these changes and understanding what drives them is essential for improving patient outcomes, yet current tools often lack the ability to provide both accurate forecasts and clinically meaningful insights. There is a growing need to move beyond prediction to explore “what if” scenarios that can guide clinicians to treatment decisions and offer actionable strategies at the bedside. This work presents an integrated framework for advancing AI-related translational sciences that addresses these gaps through three components. First, we developed predictive models using longitudinal clinical data to forecast the onset and progression of organ dysfunction and offer early warnings of deterioration. Second, we applied interpretable methods to identify the clinical variables and temporal patterns that are most influential to model outputs, ensuring transparency and alignment with biomedical domain knowledge. Third, we generate counterfactual patient trajectories to explore how changes in treatments or physiological states may have influenced outcomes. Applied on real-world intensive care datasets, the framework demonstrate strong predictive performance, interpretable explanations that clinicians find meaningful, and counterfactual scenarios that are both plausible and actionable. Together, these contributions connect model development to prospective clinical evaluation, creating a unified approach that integrates prediction, interpretation, and counterfactual reasoning to enable more informed and timely decision making in critical care.Dissertation not available (per author’s request
Reducing Primary Care Provider Burnout with the Utilization of DAX AI Ambient Scribe
No full textBackground: Healthcare provider burnout is a long-term stress reaction that remains a significant challenge in the primary care practice. Burnout was found to contribute to higher intent for job turnover, decreased job satisfaction, increased career regret, decreased job satisfaction, increased low professionalism, reduced productivity, and decreased patient satisfaction (Hodkinson et al., 2022). When assessing contributing factors, the most common answer is the electronic medical record (EMR). The use of ambient AI scribes, such as DAX, embedded into the Epic charting system can decrease the time spent charting, both in the office and at home, while increasing the number of characters used, with a decrease in provider contribution (Owens et al., 2023).
Purpose: This quality improvement project aimed to reduce primary care provider burnout with the utilization of DAX AI ambient scribes. Methods: The quality improvement project was conducted at Tucson Family Medicine, an office of the Arizona Community Physicians group, and a primary care clinic. Eligible providers were NPs, PAs, and any physicians currently practicing; in total, eight were eligible. An initial email was sent out with information regarding primary care burnout and the benefits of utilizing DAX. The providers were then asked to complete a Mini Z 2.0 survey, and if interested, sign up for DAX. A month after implementation, the survey was resent to the eligible providers to complete the Mini Z 2.0 survey again. Results: The initial survey had two respondents, one of whom was a DAX user and the other was not. The Mini Z 2.0 totals found that non-DAX users scored 35.00, while DAX users scored 39.00; both scores were below the threshold of greater than or equal to 40, indicating that anything above 40 indicates a joyful workplace. The mean score = 37.00, again below the 40.00 threshold. Subscale 1 mean=20.50, greater than or equal to 20.00, indicating a supportive work environment. Subscale 2 mean=15.00, greater than or equal to 20.00, indicating a reasonable office pace and EMR stress. The follow-up survey found that both users stated they use DAX AI, with a mean of 35.50, which is below the 40.00 threshold. Subscale 1 mean=19 and Subscale 2 mean=14.5, both falling below 20.00.
Conclusions: Although the study did not yield statistically significant results due to the smaller sample size, previous data and results suggest a positive impact on provider burnout with the use of ambient AI scribes, such as DAX. With a larger sample size, multiple PDSA cycles, and collated pre- and post-data, the impact of DAX on primary care provider burnout can be further studied
Re-envisioning Post-camp: Navigational Experience of First-generation Latinx Migrant Farmworker Students
No full textThis case study examines the postsecondary educational journeys of First-Generation Latinx Migrant Farmworker (FGLxMF) students following their participation in the College Assistance Migrant Program (CAMP) along the U.S.–México border. While CAMP offers first-year academic support and retention services (Araujo, 2011; Bejarano & Valverde, 2012; Duron, 1995; Garcia & Nieto, 2021), limited research explores how students navigate and graduate from college after that initial year—particularly in rural borderland contexts. While grounded in the context of rural U.S. Southwest, Yosso’s (2005) Community Cultural Wealth and Moll et al.’s (1992) Funds of Knowledge theoretical frameworks informed the study. Findings revealed that all participants leveraged different forms of capital and household knowledge. Specifically, participants’ experiences revealed how temporal-emotional and healing capital operate across fragmented timelines through emotional labor, dimensions that the existing literature has not fully theorized. Further research must expand on these findings since most student success models define persistence through uninterrupted enrollment, successful institutional integration, and completion (Tinto, 1975); however, this study’s findings indicate that participants’ persistence is non-linear, emotional, and relational