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Evaluation of Kidenga: A Community-Based Mobile Application for Arboviral Disease Surveillance
No full textBackground: Arboviral diseases including Zika, dengue, and chikungunya represent growing public health threats in the United States (U.S.), with dengue cases reaching record levels globally and local transmission documented some U.S. border states. Traditional surveillance systems face critical limitations including underreporting, and delays in laboratory confirmation. Mobile health applications offer opportunities for participatory surveillance (PS) by enabling real-time community reporting of symptoms and mosquito activity while delivering educational resources. In 2016, the University of Arizona launched Kidenga, a bidirectional mobile surveillance tool designed to address emerging arboviral threats during the Zika epidemic. Despite promotional efforts in high-risk states, the platform has never undergone comprehensive evaluation of intentions to use the tool, participation sustainability, syndromic data quality, or perceived community value. This dissertation addresses this gap through three aims examining factors associated with intention to use Kidenga, participation patterns and healthcare-seeking behavior, and community perceptions in Puerto Rico (PR) with comparative assessment of artificial intelligence tools for qualitative analysis.Methods: Three methodological approaches were employed. For Aim 1, cross-sectional survey data were collected in U.S.-Mexico region, and PR between July and September 2018. An integrated Unified Theory of Acceptance and Use of Technology (UTAUT) and Health Belief Model (HBM) framework guided variable selection. Primary outcomes were behavioral intentions to report illness symptoms and mosquito locations via mobile application. Multivariable ordinal logistic regression models assessed associations between predictor variables and outcomes. For Aim 2, longitudinal analysis was conducted on weekly reports submitted between September 2016 and July 2017. Participation was categorized as high (≥2 reports) or low (1 report). Syndromic definitions followed World Health Organization (WHO) guidelines for Zika-like illness, dengue-like illness, and chikungunya-like illness. Geographic distribution, and temporal patterns of reports were assessed. User retention was measured through monthly churn rates, and healthcare-seeking behavior was evaluated using logistic regression with cluster-robust standard errors. For Aim 3, focus group discussions (FGD) were conducted with community members in Ponce, PR to evaluate Kidenga features. Human-led inductive thematic analysis was conducted. Three generative AI tools received identical prompts through Application Programming Interface (API) in two approaches to conduct thematic analysis, and codebooks were systematically compared for thematic convergence and comprehensiveness. Results: Aim 1 findings demonstrated that 84.6% of participants indicated intention to report illness symptoms and 77.6% indicated intention to report mosquito locations, with strong correlation between outcomes. Performance expectancy significantly predicted both outcomes, with participants motivated by personal or family benefits showing 2.80 times higher odds of symptom reporting (95% CI: 1.43 - 5.53, p=0.003) and community-motivated participants showing 2.52 times higher odds (95% CI: 1.26 - 5.04, p=0.009) compared to science-motivated participants. Social influence emerged as the strongest predictor, with community leaders demonstrating 4.67 times higher odds for symptom reporting (95% CI: 2.72 - 8.02, p<0.001) and 4.28 times higher odds for mosquito habitat reporting (95% CI: 2.79 - 6.58, p<0.001). Perceived susceptibility to mosquito-borne diseases showed participants believing they were likely to contract disease had 2.93 times higher odds for mosquito location reporting (95% CI: 1.99 - 4.29, p<0.001). Environmental cues to action and self-efficacy measured through mosquito prevention behavior score demonstrated dose-response relationships with both outcomes. Aim 2 findings revealed that among 536 core users, 63.1% demonstrated high participation. The system captured 122 Zika-like illness cases (8.9% of reports), 31 dengue-like illness cases (2.3%), and 26 chikungunya-like illness cases (1.9%). Geographic concentration occurred in Pima County, Arizona (103 users) and Miami-Dade County, Florida (61 users). Temporal analysis revealed an 8-10 week lag between peak Google search interest (July-August 2016) and maximum participation (October 2016), with correlation declining from 0.36 to near-zero by February 2017. Monthly churn rates ranged from 50-97.5%. Users reporting mosquito activity had 1.82 times higher odds of high participation (95% CI: 1.22 - 2.71, p=0.003), and symptomatic users had 1.99 times higher odds (95% CI: 1.26 - 3.13, p=0.003). Among 121 arboviral syndrome cases, only 26.4% sought healthcare, with testing rates varying from 9.4% for Zika to 83.3% for chikungunya. Zika-like illness significantly predicted healthcare seeking (aOR=2.76, 95% CI: 1.2-6.3, p=0.016). Recent travel was the strongest predictor of arboviral syndromes with 4-9-fold increased odds. Aim 3 findings showed human-led analysis identified 14 themes. All three AI tools successfully identified core themes related to design, usability, notifications, and privacy. Notably LLMs detected Cultural & Language themes that were not explicitly coded by human researchers, while under-detecting Technical Issues theme. Conclusions: The integrated UTAUT-HBM framework successfully explained adoption intentions. Analysis of actual usage during the Zika outbreak revealed that while Kidenga demonstrated feasibility for capturing arboviral syndromic data, substantial challenges emerged. Community evaluation in Puerto Rico revealed that members valued Kidenga for disease prevention while identifying needs for enhancement. Generative AI tools demonstrated capability for rapid preliminary coding in qualitative analysis but lacked the depth and contextual sensitivity of human analysis. Implementation: Implementing PS platforms should prioritize preemptive deployment before epidemic peaks to align with periods of maximum public concern, establish partnerships with local health departments and community organizations to provide ongoing promotion and relevance, and develop retention strategies through incentives or activation only during time periods of increased risk. GPS-based real-time location tracking with user consent should be used to enable nuanced spatial-temporal analyses identifying disease importation patterns and local transmission areas. Messaging strategies should emphasize personal and community protection benefits while engaging community leaders as champions and early adopters.Release after 01/12/203
Silage Corn Yield, Water Productivity, and Quality Under Different Irrigation Scenarios in Arizona
No full textCorn (Zea mays L.) is one of the most cultivated crops in the United States, covering about 86.5 million acres, representing about 17% of the total land area (514.93 million acres) devoted to corn worldwide (Our World in Data, 2023). In 2024, corn was cultivated on 70,000 acres in Arizona, with 50,000 acres devoted to silage corn, producing approximately 1,350,000 tons (Food and Agriculture Organization of the United Nations, 2025). Silage corn in Arizona requires a substantial amount of water, especially during the reproductive growth stages (Payero et al., 2006). Depending on weather, irrigation methods, and crop management practices, silage corn may require 16 to 30 acre-inches of water per season (Andales and Schneekloth, 2017) and is typically harvested at the dent, R5 reproductive stage, when whole-plant moisture reaches about 60-70%. Harvesting at this stage maintains silage quality and digestibility while minimizing yield losses (Lauer, 2016; Roth and Heinrichs, 2001). In consideration of water scarcity and the necessity for water conservation, the implementation of deficit irrigation strategies in arid and semi-arid regions, aligned with crop growth stages and their respective sensitivity to water stress, can enhance on-farm management practices by reducing irrigation water consumption, diminishing evaporation losses, minimizing energy consumption, and increasing economic returns from investments in irrigation water supplies (Elsadek et al., 2023, 2025; Elshikha et al., 2024). Furthermore, improving soil quality through accurate estimation of the salt leaching fraction and soil amendments may enhance soil structure and increase water retention capacity, thereby contributing to higher crop yields (Elshikha et al., 2025). on irrigation water management, silage corn yield, water productivity, and quality under different irrigation methods, rates (80% and 100% of calculated crop evapotranspiration, ETc), and soil conditions: A soil amendment (a), Liquid Natural Clay (LNC), provided by the Desert Control Company (https://www.desertcontrol.com, accessed on 20 November 2025), that was evaluated for its effects on soil moisture retention and yield and compared to an unamended control. The findings will guide growers to make informed decisions to enhance silage corn yield, water productivity, and quality in Arizona, USA.This work was supported by the University of Arizona Cooperative Extension Water Irrigation Efficiency Program, which is funded by the Arizona State Legislature
Linking Forest Structure, Fire Severity, and Snowpack Variability: A Multi-Scale Remote Sensing Study Across Mountain Landscapes
No full textForests are essential components of the global biosphere, serving as major carbon reservoirs and providing critical ecosystem services. In the western United States, intensifying wildfires—driven by regional climate change, altered fuel conditions, and land use shifts—are reshaping forest structure and accelerating vegetation succession. Forest structure (the three-dimensional arrangement of biotic and abiotic components) and forest function (the physiological processes that regulate energy and matter fluxes) jointly underpin ecosystem resilience. These structural and functional attributes are closely linked to snowpack dynamics, which play a vital role in regulating hydrological processes and sustaining water resources. This connection is particularly critical in Arizona, where mountain snowpack represents a critical source of surface water for ecosystems and downstream human use. Despite this importance, the interactions among forest structure, ecosystem function, snowpack variability, and post-disturbance recovery remain insufficiently understood.This dissertation investigates how variability in forest environments interplays with forest structural and functional characteristics and snowpack dynamics across Arizona’s diverse mountain landscapes. By integrating multispectral, thermal, and LiDAR remote sensing, this research investigates burn severity, vegetation recovery, and snowpack dynamics. A central focus is placed on understanding how structural and functional diversity, together with surrounding environmental conditions and canopy heterogeneity, influence both burn severity and snow processes, including accumulation, retention, and melt, and how these interactions can be quantified to generate actionable insights. The first chapter provides an overview of the dissertation and introduces the foundational background of key factors of the Santa Catalina Mountains, one of the primary study areas. This chapter also characterizes the topographic and climatic features of Arizona that influence regional fire and snow dynamics related to recent climate change. Furthermore, it delineates the contributions of the principal authors involved in the associated studies to clarify their respective roles in this body of work. Lastly, the chapter discusses the broader implications of these research findings and their potential impact on related scientific fields. The following three appendices include two published articles (Appendices A and B) and one manuscript prepared for journal submission (Appendix C). The first two studies examine how pre- and post-fire vegetation structural and functional variables are associated with burn severity, using multiple remote sensing platforms. The first study identified vegetation-related indices (NDVI, canopy cover, and tree density) as significant predictors of burn severity across all land cover types. These variables, which reflect drought-sensitive functional traits and available fuel loads, were strongly correlated with burn severity, indicating that areas with denser and greener vegetation experienced more intense burns. The second study explored the relationships between burn severity, quantified by the differenced Normalized Burn Ratio (dNBR), and vegetation structure and function derived primarily from LiDAR and satellite data. While LiDAR provided high-resolution structural detail, its limited spatial coverage restricted the generalizability of results across all ecosystems. Moreover, variations in dominant vegetation types influenced the accuracy and ecological interpretation of LiDAR-derived metrics. Despite these limitations, both studies revealed consistent patterns in how forest structure and function respond to fire, offering broader insights into post-fire vegetation dynamics in mountainous landscapes. The third study investigates how forest structure, topography, and radiative energy shape snow accumulation and melt across three forested mountain sites in semiarid Arizona. Using distributed Snowtography observations, LiDAR-derived snow depth, radiation measurements, and high-resolution SnowPALM simulations, we evaluated spatial patterns in peak SWE, snow cover duration, and liquid water input. SnowPALM accurately reproduced observed snow and radiation dynamics, capturing strong canopy- and aspect-driven gradients. Sky View Factor emerged as a key control on incoming longwave radiation, supporting core model assumptions. Semi-partial correlation analyses showed that, after accounting for accumulation, net radiation is the dominant driver of peak SWE, SCD, and melt. Overall, snowpack evolution in these semiarid forests reflects the combined effects of terrain-regulated accumulation and radiatively driven ablation, with sensitivity to energy inputs increasing under warmer, drier conditions. By linking forest structure, function, and snow processes within a remote-sensing framework, this work advances understanding of how disturbance and climate interact to shape ecosystem trajectories, hydrological resilience, and regional energy balance in the various types of mountain regions in Arizona, United States.Release after 07/22/202
New Federal Reporting Requirement for Small Businesses: Beneficial Ownership Information
No full textOwning a small business comes with many challenges and among those challenges is the requirement to file forms and reports to various governmental entities. Effective January 1, 2024, there is yet another reporting requirement that has recently become a requirement for many small businesses. The Beneficial Ownership Information (BOI) reporting was implemented by the Financial Crimes Enforcement Network (abbreviated FinCEN), an arm of the U.S. Department of the Treasury, to capture information about small businesses who oftentimes “fly under the radar” when it comes to reporting their business ownership, activities, and revenues. In 2021 the U.S. Congress pass the Corporate Transparency Act. This law creates a new reporting requirement as part of the United States government’s attempt to make it harder for bad actors to hide income or benefit from ill-gotten gains through nontransparent ownership structures. This Act is aimed at catching money launderers and those who fund terrorism, however all small business owners must be aware that they might be required to file a BOI Report (BOIR)
Digitally Branded: The Developmental Catastrophe of Juvenile Sex Offender Registries
No full textJuvenile sex offender registration was never a natural fit for the youth justice system, but in the digital age, it has become deeply harmful. What began as a paper-based precaution has evolved into a sprawling digital regime that permanently brands adolescents at the most formative stage of life. This article examines how technological change has turned registration into a publicly searchable network of stigma—amplified by data aggregators, search engines, neighborhood apps, and real estate platforms—that makes youthful misbehavior both permanent and inescapable.
Drawing on insights from developmental neuroscience and criminology, the article explains why adolescent sexual misconduct is often impulsive, peer-driven, and rarely predictive of future offending. Yet federal mandates like the Sex Offender Registration and Notification Act (SORNA) continue to impose offense-based registration on youth as young as fourteen, ignoring evidence about adolescent development and undermining the juvenile justice system’s rehabilitative aims.
The modern registry’s reach imposes novel harms that traditional legal frameworks have not fully addressed. Public access fuels ongoing exclusion, identity foreclosure, and algorithmic discrimination, locking youth into stigmatized identities and exacerbating racial and socioeconomic disparities. These harms ripple outward to destabilize families and communities.
Empirical research confirms that juvenile sexual recidivism is rare and that registration fails to improve public safety. Instead, it misallocates resources and inflicts long-term damage. This article urges a rethinking of juvenile registration policies, calling for reforms grounded in developmental science, technological awareness, and evidence-based alternatives such as confidential monitoring, risk-based assessments, and therapeutic intervention.6 month embargo; published 16 February 2026This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
The Eric Seedorff Rock Sample Collection
No full textThis inventory represents a diverse rock collection from porphyry and epithermal deposits across North and South America that were collected by Eric Seedorff between the 1970s-2010s. Samples have been organized and catalogued by student workers with the inventory available as a table at the end of this document, as well as a spreadsheet. Samples are available for inspection following correspondence and discussion with the AZGS mineral resources team.Documents in the AZGS Documents Repository collection are made available by the Arizona Geological Survey (AZGS) and the University Libraries at the University of Arizona. For more information about items in this collection, please contact [email protected]
Activating Shared Print as a Strategy for Legacy Print Access
No full textArticle publication forthcoming in Collaborative Librarianship issue 16.1. https://digitalcommons.du.edu/collaborativelibrarianship/While most libraries participate in collaborative shared print efforts but tend only to rely on them as a failsafe, this article underscores the timeliness and importance of more libraries “activating” shared print as a core strategy for access to legacy print content. The University of Arizona’s experiences with SCELC and HathiTrust for monographs and the WEST-Internet Archive pilot for serials are discussed as examples of how libraries might choose to pursue this approach.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
34 - Sugar King Park, Saipan
No full textDanielle P. Williams reading poems from Chamorrita SongThese recordings are made available by the University of Arizona Press and University of Arizona Libraries. If you have questions about this title, please contact the UA Press at http://www.uapress.arizona.edu/
21 - creation myth
No full textDanielle P. Williams reading poems from Chamorrita SongThese recordings are made available by the University of Arizona Press and University of Arizona Libraries. If you have questions about this title, please contact the UA Press at http://www.uapress.arizona.edu/
12 - Chamorrita Song
No full textDanielle P. Williams reading poems from Chamorrita SongThese recordings are made available by the University of Arizona Press and University of Arizona Libraries. If you have questions about this title, please contact the UA Press at http://www.uapress.arizona.edu/