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High-Resolution Modeling of Extreme Heat Events With Socioeconomic Consideration: A Real-Case WRF-LES Approach
No full textThe overarching goals of this work is to explore best practices for micro-scale modeling of a real case, identify relevant phenomena by using high-resolution modeling, and to explore their implications for public health, and climate resilience strategies in Hampton Roads, VA, USA. This project employs the Weather Research and Forecasting (WRF) model to conduct a comprehensive study of Hampton Roads, utilizing a coupled mesoscale to microscale modeling capable of resolving boundary layer turbulence. This study has three primary objectives: (1) to establish the optimal mesoscale to Large-Eddy Simulation (LES) configurations for complex geographical regions such as the Hampton Roads (HR) domain and address challenges inherent to multi-scale modeling; (2) as a demonstration, to identify extreme heat episodes and urban heat islands within the study area; and (3) to explore the correlation between these heat islands and the socio-economic characteristics of HR neighborhoods. Model performance was evaluated using observational data, applying standard statistical metrics such as correlation coefficient, mean bias, and root mean square error to select the most realistic model configuration. Similar statistical methods were used to assess the relationship between heat exposure and socio-economic factors. We also introduce a new metric, cooling energy demand, to quantify the potential economic burden of extreme heat. The Results show that lower-income communities are disproportionately exposed to higher heat levels and face greater cooling energy demands compared to rural areas. In addition, through extensive testing, we identified the cell-perturbation method as an effective approach for producing physically realistic LES simulations validated against observations. Future work will extend this approach to neighborhood-scale air quality modeling to develop a more comprehensive understanding of environmental stressors and support targeted climate resilience strategies for vulnerable communities
Vape Counseling at Pediatric Practices: The Rethink Vape Toolkit
No full textIntroduction:
E-cigarettes (Vapes) represent the most common form of tobacco used by adolescents, with one out of every 29 (3.5%) middle school students and one in every 13 (7.8%) of high school students vaping daily. This project aimed to increase vape screening and prevention education in youth visits at pediatric practices, to increase provider comfort with the topic of vaping, and to evaluate this educational process.
Methods:
A provider training and resource modules (talking points, billing codes, and shareable parent/teen-tailored resources) were developed. Providers (N = 32) completed an anonymous pre/postsurvey regarding their knowledge, comfort levels, barriers, and practices related to teen vaping. Key-informant interviews (N = 20) were conducted to identify barriers and seek solutions to incorporate risk counseling into daily practice. Monthly meetings were held to achieve Continuous Quality Improvement (CQI) in pediatric practices. The frequency of providing vaping information in the Depart Summary was monitored.
Results:
Reported barriers to providing vape prevention counseling, including lack of knowledge, lack of resources, discomfort with topic, and patient resistance, were significantly reduced after participation. Time constraints continued to be the greatest barrier to preventive counseling. Physicians who indicated they often or always provide vape prevention information during a visit increased from 9 to 50 percent. Average resources provided increased from 1 to 94 per month.
Discussion:
Tailored provider-training and resources increased physician knowledge of and confidence with the topic of vaping as well as the frequency of screening and preventive guidance provided to teens and their families
Empathetic Differentiated Instruction in Deaf Education: Examining Influencing Factors and Experienced Educator Practices
No full textThis mixed-methods study investigated how experienced K–12 deaf educators implement empathetic, differentiated instruction (EDI) to support the academic and linguistic needs of deaf students who use American Sign Language (ASL) as their language of learning. Guided by Tracey and Baaki’s instructional design empathy model and grounded in constructivism, the study explored how teachers navigated the tension between standardized, English (sound-based) curriculum demands and the need to make instructional decisions aligned with signed language modalities and responsive to students’ real-time learning needs.
A custom electronic survey was distributed to a national sample of experienced educators, with 19 respondents completing Likert-scale items, multiple-choice questions, and an open-ended reflection prompt. Quantitative data were analyzed using descriptive statistics, while qualitative responses underwent thematic coding.
Findings revealed that educators consistently employed empathy-informed instructional strategies, including ASL-based pedagogy, curriculum adaptations, and dual language access strategies. However, systemic constraints such as rigid, standards-driven pacing guides, interpreter-reliant learning experiences, and sound-based instructional materials often hindered successful implementation. Despite these barriers, educators demonstrated innovation, cultural responsiveness, and a strong commitment to student-centered design. The findings underscore the need for ASL-aligned instructional frameworks, increased systemic support, and professional development focused on managing modality constraints, enhancing reflective practice, and promoting instructional equity. The findings underscore the need for ASL-aligned instructional frameworks, greater systemic support, and professional development focused on modality constraints, reflective practice, and curriculum flexibility
Exploring the Impact of Generative AI ChatGPT on Critical Thinking in Higher Education: Passive AI-Directed Use or Human-AI Supported Collaboration?
No full textGenerative AI is weaving into the fabric of many human aspects through its transformative power to mimic human-generated content. It is not a mere technology; it functions as a generative virtual assistant, raising concerns about its impact on cognition and critical thinking. This mixed-methods study investigates how GenAI ChatGPT affects critical thinking across cognitive presence (CP) phases. Forty students from a four-year university in the southwestern United States completed a survey; six provided their ChatGPT scripts, and two engaged in semi-structured interviews. Students’ self-reported survey responses suggested that GenAI ChatGPT improved triggering events (M = 3.60), exploration (M = 3.70), and integration (M = 3.60); however, responses remained neutral during the resolution stage. Two modes of interaction were revealed in the analysis of students’ ChatGPT scripts: passive, AI-directed use and collaborative, AI-supported interaction. A resolution gap was identified; nonetheless, the interview results revealed that when GenAI ChatGPT was utilized with guidance, all four stages of cognitive presence were completed, leading to enhanced critical thinking and a reconceptualization of ChatGPT as a more knowledgeable other. This research suggests that the effective use of GenAI in education depends on the quality of human–AI interaction. Future directions must orient toward an integration of GenAI in education that positions human and machine intelligence not as a substitution but as co-participation, opening new epistemic horizons while reconfiguring assessment practices to ensure that human oversight, critical inquiry, and reflective thinking remain at the center of learning
Contributors
No full textInformation about contributors to articles in volume 5 issue 3 of Reconstruction
Environmentally Friendly Chelation for Enhanced Algal Biomass Deashing
No full textHigh ash content in algal biomass limits its suitability for biofuel production by reducing combustion efficiency and increasing fouling. This study presents a green deashing strategy using nitrilotriacetic acid (NTA) and deionized (DI) water to purify Scenedesmus algae, which was selected for its high ash removal potential. The optimized sequential treatment (DI, NTA chelation, and DI+NTA treatment at 90–130 °C) achieved up to 83.07% ash removal, reducing ash content from 15.2% to 3.8%. Elevated temperatures enhanced the removal of calcium, magnesium, and potassium, while heavy metals like lead and copper were reduced below detection limits. CHN analysis confirmed minimal loss of organic content, preserving biochemical integrity. Unlike traditional acid leaching, this method is eco-friendly after three cycles. The approach offers a scalable, sustainable solution to improve algal biomass quality for thermochemical conversion and supports circular bioeconomy goals
Soft Law, Activism, and Climate Displacement: Rethinking International Protections for the Environmentally Displaced
No full textClimate change is displacing millions of people globally, yet those forced to migrate due to environmental factors remain unprotected under existing international refugee law. This paper argues that legal recognition for climate refugees can emerge not through immediate treaty reform but through the evolution of soft law and norm creation. Drawing on constructivist theory, it examines how activism, international organizations, and legal precedents contribute to shifting global norms. Through case studies such as Ioane Teitiota v. New Zealand and the Fridays for Future movement, the paper shows how strategic litigation and advocacy can build momentum for future legal protections. It concludes by proposing a hybrid framework that bridges refugee law, environmental governance, and human rights
The Invisible Default: Examining Representation in Digital Collections
No full textThis mixed-method study investigates the representation of race and ethnicity within the J. Willard Marriott Digital Library at the University of Utah. The digital collections analyzed in this study come from the Marriott Library’s Special Collections, which represent only a fraction of the library’s physical material (less than 1 percent), albeit those most public facing. Using a team-based approach with librarians from various disciplines and areas of expertise, this project yielded dynamic analysis and conversation combined with heavy contemplation. These investigations are informed by contemporary efforts in librarianship focused on inclusive cataloging, reparative metadata, and addressing archival silences. By employing a data-intensive approach, the authors sought methods of analyzing both the content and individuals represented in our collections. This article introduces a novel approach to metadata analysis—as well as a critique of the team’s initial experiments—that may guide future digital collection initiatives toward enhanced diversity and inclusion