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¿Conoces Tus Limones? Introducing New Breast Cancer Educational Materials in Rural Arizona
No full textBackground: Breast cancer disproportionately affects rural Hispanic women. While multiple professional societies recommend regular screening mammograms for early detection, many women lack consistent access to this test. The Know Your Lemons (KYL) visual educational tools, developed in 2003, were designed to address barriers to breast health education, including taboos, low literacy, language differences, and cultural sensitivities. Purpose: This quality improvement project evaluated the effectiveness and appropriateness of the KYL materials in a rural, Spanish-speaking community in southern Arizona, with a focus on knowledge gain and confidence in recognizing the signs of breast cancer. Methods: The investigator introduced the KYL materials to a local breast cancer support group. Guided by Lewin’s Change Model, participants completed a pretest, attended an educational presentation (delivered in Spanish with written materials available in English and Spanish), and then completed a posttest. Time was provided for questions and discussion. Results: Eight women participated in the session. Post-test analysis showed universal knowledge improvement. All participants reported that the KYL materials were clear, attractive, culturally appropriate, and easy to understand. Conclusions: The KYL intervention increased participants’ confidence in breast self-awareness and their knowledge of breast cancer warning signs. Within this rural, Spanish-speaking community, the materials were consistently rated as culturally relevant and engaging. These findings suggest that KYL is a practical, scalable tool with potential for broader implementation across local healthcare systems to support earlier recognition of breast cancer in underserved populations
Use of a Talent Matrix in Developing Nursing Leadership: A Program Evaluation
No full textBackground: Inpatient Nurse Managers play a pivotal role in achieving outcomes aligned with the Quadruple Aim, enhancing patient experience, improving population health, reducing costs, and supporting provider well-being. At UW Health’s University Hospital, leadership identified a need for a more dynamic and consistent method to assess the performance and potential of Inpatient Nurse Managers beyond the traditional annual review. Purpose: This Doctor of Nursing Practice (DNP) project aimed to evaluate the implementation of a 9-box talent matrix as a leadership assessment tool. The goal was to determine its effectiveness in identifying leadership growth opportunities and its relationship to key performance indicators: hospital-acquired conditions (HACs), patient satisfaction, RN engagement, and RN turnover. Methods: A retrospective, descriptive design was employed using the CDC Program Evaluation Framework. Four talent review cycles were conducted between July 2023 and August 2025. Nurse managers were assessed and placed on the 9-box matrix, and their placement was correlated with unit-level outcome data across the four metrics. Results: Findings revealed a directional relationship between higher talent matrix placement and improved HAC scores and RN engagement. However, patient satisfaction and RN turnover showed greater variability, suggesting that additional contextual factors such as unit culture, staffing dynamics, and leadership transitions may influence these outcomes.
Conclusions: The 9-box talent matrix proved to be a valuable tool for fostering continuous leadership development, enabling targeted coaching, and enhancing accountability. While limitations such as anonymized data and calibration consistency were noted, the matrix offers a replicable framework for healthcare organizations seeking to strengthen nursing leadership and improve clinical and team outcomes
Implementation of a Suicide Prevention Toolbox To Enhance Confidence in Treating High-Risk Patients
No full textBackground: Suicide remains a critical concern to public health that is experienced at disproportionately higher rates within rural communities. These populations face heightened barriers, including limited access to care, stigma, and social isolation. Since primary or integrated healthcare settings often represent the first or only point of contact for those at risk for suicide, provider preparedness is crucial to preventing suicide.Purpose: The purpose of this project was to enhance provider knowledge and confidence in identifying and managing suicidal or high-risk patients within MHC Healthcare, an integrated rural healthcare center in Tucson, AZ. It aimed to increase awareness of evidence-based and relevant local suicide prevention resources and to improve interdisciplinary competence through education. Methods: The Suicide Prevention Toolbox was electronically disseminated to 111 MHC providers across disciplines via email. This implementation was guided by the Knowledge to Action Framework and followed the Plan-Do-Study-Act model. This educational toolbox included evidence-based strategies, screening tools, and local resources for providers. A post-presentation survey was used to evaluate the perceived knowledge, confidence, and intent or likelihood of applying the presented material. Results: Five providers completed the evaluation survey. Despite limited responses, results demonstrated positive trends. Most participants reported increased knowledge, confidence, and a likelihood to integrate suicide prevention strategies into their practice. Qualitative comments highlighted the value of interdisciplinary communication and identified barriers such as maintaining patient safety and contact.
Conclusions: Findings from this project support brief, targeted educational interventions to strengthen provider competence in suicide prevention within rural integrated healthcare. Although the scope of this project was small, it underscores the importance of integrating suicide prevention into ongoing professional training and improvement initiatives. Continued refinement of this intervention for broader implementation could enhance provider confidence and competency, as well as interprofessional collaboration, ultimately improving patient outcomes and safety
Promoting Resilience and Reducing Stress: A Program Evaluation of Mind-Body Skills Groups in Graduate Nursing Education
No full textBackground: Stress and burnout are pervasive challenges among healthcare professionals and are associated with decreased quality of patient care. In response to these concerns, mind-body skills have gained increasing attention as effective interventions for addressing these concerns. Supported by a growing body of evidence, these practices have been shown to reduce stress, enhance resilience, and promote personal health and well-being. Additionally, mind-body skills may strengthen clinicians’ capacity to support healing within the populations they serve. Purpose: This program evaluation examined the impact of an eight-week Mind-Body Skills Group (MBSG) on perceived stress and resilience among Psychiatric-Mental Health Nurse Practitioner (PMHNP) students using validated measures of stress (Perceived Stress Scale - PSS) and resilience (Connor-Davidson Resilience Scale - CD-RISC). Methods: PMHNP students were recruited from a cohort of 32. Of these, 23 expressed interest in participating, and 11 completed the eight-week MBSG series. Sessions were conducted virtually via a HIPAA-compliant Zoom platform using the standardized Center for Mind-Body Medicine (CMBM) format. Each two-hour session followed a structured curriculum incorporating meditation, centering practices, and mind-body skill development. Participants were recruited through the D2L learning management platform, with voluntary participation requiring attendance and completion of pre- and post-intervention measures. Quantitative analyses included a descriptive review of all available responses (n = 11) and paired comparisons for participants who completed both pre- and post-intervention surveys (n = 8). Results: Quantitative analysis demonstrated statistically significant improvements in resilience and moderate reductions in perceived stress following the intervention. Mean CD-RISC scores 13 increased from 59.38 (SD = 13.27) to 70.38 (SD = 10.40), t(7) = 2.86, p = .02, with a large effect size (d = 1.01). Mean PSS scores decreased modestly from 18.14 (SD = 6.48) to 17.00 (SD = 7.59), t(6) = 0.34, p = .75, d = −0.13. Qualitative data supported these findings, revealing enhanced emotional regulation, mindfulness, and self-efficacy. Participants described improved stress management, stronger peer connection, and sustained use of learned techniques beyond the intervention period. Conclusions: The MBSG intervention was associated with measurable increases in resilience and self-regulation, as well as modest reductions in perceived stress, among graduate nursing students. The findings align with neurophysiological evidence demonstrating that mindfulness practices modulate cortical and autonomic activity, providing a plausible biological mechanism for the observed outcomes. Implementation of structured mind-body programs within nursing curricula may promote adaptive coping, emotional resilience, and long-term professional wellbeing
Microstructure Analytics of Powder Metallurgy Ni-Base Superalloy RR1073 Through Thermomechanical Processing
No full textThe use of electron backscatter diffraction coupled with X-ray energy dispersive spectroscopy has been combined to create a quantitative data collection approach called Microstructure Analytics. This approach has allowed for the assessment of the changes occurring in the microstructure of an advanced polycrystalline, powder metallurgy Ni-base superalloy, RR1073, through numerous thermomechanical processes. This has led to a deeper understanding of the changes that occur in this alloy at a quantitative level not seen prior. A much deeper fundamental understanding of the microstructural features that evolve from the various thermomechanical processes were rationalized and explained using fundamental materials science and physical metallurgy concepts and mechanisms. These physically based metrics obtained from this approach have provided insightful understanding to the changes that could be implemented in the thermomechanical processing of this alloy to create desired unimodal grain size distributions and mechanical properties. Systematic tracking of the quantitative microstructure metrics to steps in the powder metallurgy process as far back as the hot isostatic pressed process all the way to solutioned heat treatment have been characterized. This insightful methodology has provided new knowledge to the superalloy community regarding microstructure evolution in polycrystalline powder metallurgy alloys that have been needed to begin to realize improvements in the microstructure that will potentially lead to increased service temperatures of aero engines and a means to track microstructures in a systematic quantitative manner
Cybersecurity Architecture for Telemetry Networks: Development of a Comprehensive Cybersecurity Framework for Industrial Control Systems (ICS) and SCADA Networks
No full textTelemetry systems in critical infrastructure face unprecedented cybersecurity challenges as industrial networks become increasingly interconnected. This paper presents an advanced telemetry security assessment framework implementing a comprehensive Industrial Control System (ICS) cybersecurity simulation platform based on the Purdue Model architecture. The platform provides realistic threat analysis capabilities and defense strategy validation for telemetry-enabled industrial environments. Our implementation features real-time network communication across six Purdue levels, cross-level attack propagation simulation, and interactive threat storytelling capabilities. A unique feature of the system is its ability to detect attacks that originate as internal lateral movements as well as those that are from internetfacing services, thereby demonstrating real-time attack scenarios. Validation of the experiment in this work is executed using two-dozens of simulated devices across all Purdue levels, with the results revealing 94% efficiency for security controls. Web platforms adopted include PostgreSQL database integration, OpenPLC runtime integration among others. Study results indicate the usefulness of cybersecurity training and implementationInternational Foundation for TelemeteringProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit https://telemetry.org/contact/ if you have questions about items in this collection
LEVERAGING PILOT SEQUENCE ORTHOGONALITY FOR LOW COMPLEXITY SPACE-TIME CODING RECEIVERS
No full textThis paper explores CPM waveforms used for telemetry purposes, with a specific focus on SOQPSK TG standard and its integration with Space-Time Coding to address the two-antenna problem. Cur rent state-of-the-art receiver algorithms face challenges, including delays, error propagation, and poor performance at low SNR levels. To address these issues, this paper introduces a novel re ceiver design leveraging improved correlation properties of new pilot sequences. The proposed design performs CSI estimation at the pilot detection stage, thus eliminating iterative processes, mitigating long synchronization times, and enhancing receiver performance at lower SNR levels.International Foundation for TelemeteringProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit https://telemetry.org/contact/ if you have questions about items in this collection
ALIGNMENT OF ARTIFICIAL INTELLIGENCE (AI) ATTITUDES: EXAMINING HR AND ENTRY-LEVEL APPLICANT PERSPECTIVES ON AI USAGE IN JOB APPLICATIONS
No full textGenerative Artificial Intelligence (AI), specifically large language models capable of generating human language, has become increasingly accessible and integrated in a wide range of industries. The purpose of this thesis is to inquire and report on the alignment of Human Resources (HR) professionals’ attitudes and policies regarding AI with those of college students. This thesis specifically explores the context of the alignment of opinions about applicants using AI to support their application process in an ethical and practical sense. This attitudinal alignment is examined through interviews with college students and HR professionals within the retail industry. This thesis has the specific scope of looking at internship and entry-level applicants because of the convenience sampling methods used to identify participants from the author’s experience and connections within this industry. A short case study is also presented on an organization that has a robust AI policy already in place. This thesis is relevant because of the lack of data available at this frontier of increasing AI accessibility and the ambiguity of ethical AI guidelines across industry. The findings show an overall inflated belief of AI usage, an alignment in attitudes about lying about experiences as a clear unethical use of AI, ambiguity in defining other boundaries of unethical use, and how important transparency is in providing insight for future internship and entry-level job applicants who are considering using AI to assist in their applications. The addenda includes storytelling materials to guide students on how using AI may affect their application process, as well as inform HR recruiters about their applicant’s opinions and actions
Rehabilitation of the Rimac river
No full textSustainable Built Environments Senior Capstone ProjectAbstract
Although institutional actions in Lima, Peru aim to address river cleaning, wastewater control, and riverbank recovery, these efforts remain fragmented and uneven in their social and environmental outcomes, resulting in limited long term impact. This research analyzes the rehabilitation of the Rímac River as a public, environmental, and social space within the urban structure, starting from its current condition of deterioration, pollution, insecurity, and disconnection from the city. Previous studies reveal that most rehabilitation approaches prioritize technical and infrastructural solutions, while issues of social equity, citizen participation, and long-term governance are often treated as secondary components.
To address this gap, this research adopts a qualitative methodology based on an auto ethnographic approach supported by document analysis, a comparative study of the Remedios and Xochimilco rivers in Mexico, and an interview with a specialist in cultural ecology. This methodological framework allows for the identification of integrated and context sensitive strategies that combine ecological restoration, technological infrastructure, institutional coordination, and community participation, while also acknowledging the need to distribute environmental benefits and risks more equitably over time within the Rímac River basin.
The alignment of technical interventions, governance structures, and active citizen involvement achieved sustained improvements in environmental quality, reduced health risks, and ecosystem recovery in the reference cases. In contrast, the Rímac River continues to face high levels of pollution, informal occupation, insecurity, and weak public appropriation of its riverbanks, limiting its integration into everyday urban life. The research argues that effective rehabilitation requires moving beyond isolated technical actions toward an integrated and phased framework that incorporates environmental education, social activation, urban safety, and community-based governance. By understanding the Rímac as a socio ecological system, this study proposes a realistic and adaptable approach that strengthens intergenerational equity, supports long term sustainability, urban resilience, and inclusive regeneration along the river corridor.This item is part of the Sustainable Built Environments collection. For more information, contact http://sbe.arizona.edu
Utilization of Cross-Linked Polyethylene (XLPE) Waste in the Production of Sustainable Cementious Construction Materials
No full textThe increasing generation of cross-linked polyethylene (XLPE) waste, primarily from decommissioned power cables and industrial applications, poses a significant environmental challenge due to its non-recyclable thermoset nature. This study investigates a sustainable pathway for managing XLPE waste by incorporating it into three major construction materials including concrete, fluidized thermal backfill material (FTBM) and controlled low-strength material (CLSM). The study evaluates the feasibility of using XLPE waste as a partial replacement for fine and coarse aggregates, aiming to reduce environmental burdens while maintaining or enhancing material performance.To this end, a comprehensive experimental program was designed to examine the effects of different XLPE replacement levels (0, 5, 10, and 15% by volume) and varying water to cement (W/C) ratios (0.45, 0.50, and 0.55) on the fresh, hardened, and durability properties of concrete, including slump, density, ultrasonic pulse velocity, compressive, tensile, and flexural strengths, as well as permeability, water absorption, and freeze–thaw resistance. FTBM and CLSM mixtures were also developed and tested to assess flowability, unit weight, setting time, thermal resistivity, and suitability for field applications. The leaching potential of XLPE waste was also evaluated to ensure environmental safety. Results demonstrate that incorporating XLPE waste can effectively reduce material density and thermal conductivity, contributing to lightweight and thermally efficient mixtures suitable for backfilling and non-structural applications. Optimal XLPE replacement levels were identified that maintain acceptable strength and durability while promoting waste valorization. To complement the experimental program, advanced machine learning (ML) techniques were employed to develop predictive models for estimating the unconfined compressive strength (UCS) of XLPE-modified construction materials. A comprehensive database was constructed by integrating experimental data from this study with published datasets, encompassing a wide range of mix design parameters. Multiple supervised learning algorithms, including random forest (RF), support vector regression (SVR), gradient boosting (GB), and artificial neural networks (ANN), were trained and optimized using cross-validation techniques. The ML models achieved high predictive accuracy, with the tree-based and ANN-based models showing the strongest generalization performance. Sensitivity analyses and feature importance evaluations revealed that the W/C ratio, XLPE content, and cement dosage were the most influential predictors of UCS. The integration of experimental and data-driven approaches in this research provides a robust framework for both understanding and optimizing the performance of XLPE-incorporated materials. The developed ML models enable efficient prediction of UCS, reducing the need for extensive laboratory testing and supporting rapid mix design optimization. To sum up, this study demonstrates the technical feasibility and environmental benefits of reusing XLPE waste in construction materials while advancing intelligent modeling tools for sustainable material engineering.Release after 01/05/202