University of the District of Columbia

ABSTRACT This reflective analysis examines faculty development challenges and opportunities at the University of the District of Columbia (UDC), a public HBCU and the only urban land‐grant institution in the United States. As UDC advances a unified “One UDC” vision, the institution is repositioning itself as a flagship university while integrating instruction across multiple locations, including its embedded community college (UDC‐CC), where nearly half of the student population is enrolled. This institutional structure necessitates a coordinated approach to faculty development that supports equity, instructional consistency, and student success across campuses. Drawing on practice‐informed initiatives, the paper describes how AI‐infused faculty development, including live, performative demonstrations using VerseBot, a custom instructional AI persona built on ChatGPT, addresses faculty concerns related to teaching effectiveness, student engagement, academic integrity, and resource disparities. Embedding AI literacy and ethical guidance within first‐year coursework, alongside structured professional development such as Association of College and University Educators (ACUE) certification, positions AI as a supportive instructional resource rather than a substitute for pedagogy. By situating AI integration within a layered faculty development model that combines policy alignment, culturally responsive practice, and hands‐on experimentation, this paper offers transferable insights for urban‐serving universities and community colleges seeking to leverage emerging technologies while upholding commitments to access, equity, and academic rigor.

Humans believed Earth was 78% nitrogen (N2) and 21% oxygen (O2) until the 2020s. Based on data collected by balloons and satellites since the 1980s, evidence suggests that Earth's atmosphere is composed of complex molecules such as nitrogen dioxide (NO2) with polar bent molecular structures, similar to water (H2O). Although nitrogen-oxygen mixing ratios have been recorded for over 50 years, they have often been overlooked in studies of redox reactions, biological systems, and nitrogen-fixing bacteria. Microorganisms, including bacteria in oceans and soils, release nitrous oxides, NO2, NO, and N2O, which are abundant in these environments. Nitric oxide (NO) is also among the most prevalent molecules in biological systems; experiments indicate that NO2 and NO diffuse rapidly across cell membranes. Measurements at altitudes of 10-12 km show a ratio of 1 NO to 2-6 times NO2, with air density estimates indicating 300-400% more NO2 compared to NO at the surface. Near the surface, the ratio is approximately 2:1 NO, similar to the historically accepted 78% nitrogen measurements. This data suggests that the air density of NO2 is less than 2.05257 g/L or kg/m3, which is about 68% heavier than the standard air density of 1.19 g/L. Ongoing research enhances data models related to atmospheric composition, aerodynamics, climate change, biological processes, materials science, surface redox reactions, and planetary studies.

Abstract The COVID-19 pandemic significantly altered dietary habits, including processed meat consumption, which holds critical health implications. This cross-sectional study utilized the Dietary Screening Tool (DST) to analyze age- and gender-related differences in processed meat consumption among 10,050 U.S. adults aged 40–100 years. Three age groups (40–60, 61–80, and 81–100 years) were compared using binary logistic regression to assess the odds of decreased processed meat consumption by age and gender. Results revealed significant disparities: women were 23.6% less likely than men to report reduced processed meat consumption. Participants aged 40–60 years were 47% more likely to reduce processed meat consumption compared to those aged 61–80 years and over twice as likely compared to those aged 81–100 years. The difference between the 61–80 and 81–100 age groups was not statistically significant. These findings suggest that younger adults, particularly those aged 40–60 years, were more likely to decrease processed meat consumption, possibly due to heightened health awareness during the pandemic. In contrast, women exhibited a lower likelihood of reduced processed meat consumption, underscoring potential gender-specific challenges in dietary habits. This study highlights the need for tailored dietary interventions addressing processed meat consumption. Public health strategies should focus on promoting healthier dietary patterns through targeted messaging for diverse demographic groups, particularly during public health crises.

Background: Tirzepatide is a dual glucose-dependent insulinotropic polypeptide and glucagon like peptide-1 receptor agonist that has been shown to have cardiometabolic benefits. However, the real-world eligibility, uptake, and population level impact remains unclear. Research Question/Aims: To describe patients in the U.S. who meet an indication for tirzepatide, to understand its real-world uptake, and to estimate the population level impact on cardiometabolic risk factors if uptake were to increase. Methods: A retrospective study using electronic medical record data from 5 US health systems in PCORnet® identified a cohort of adults between 3/31/2023-3/31/2024 who were obese (BMI of ≥30 kg/m2) or overweight (27 kg/m2 - < 30 kg/m2) with at least one weight-related co-morbidity). Effect estimates of cardiometabolic risk factor changes from the SURMOUNT-1 trial and SURPASS-2 trial were applied to estimate population-level impacts of tirzepatide on weight and other cardiometabolic risk factors. Results: A total of 2,092,393 individuals had obesity or were overweight with at least one weight related comorbidity. About 25% were overweight; and 39%, 20%, and 16% had class 1, 2 and 3 obesity, respectively. The mean age (SD) was 54 (17.1) years, 57.2% were female, 19.7% were Black or African American, 9.1% were of Hispanic ethnicity, and 83.6% had commercial or government insurance. Approximately 20% had diabetes, and 21% had 4 or more obesity-related comorbidities. Overall, 1.3% (n=26,577) were prescribed any dose of tirzepatide, including 3.9% of those with diabetes and 0.6% of those without diabetes. Among those with diabetes, 7.0% of those with commercial and 2.4% of those with government insurance were prescribed tirzepatide; among those without diabetes, the respective proportions were 0.9% and 0.4%. A substantial reduction in weight was estimated with tirzepatide. The figure shows estimated changes in population-level distribution of weight if tirzepatide (at varying doses) was used by all eligible patients, stratified by diabetes status. Changes in other cardiometabolic risk factors were also estimated to be improved. Conclusions: Across 5 large US health systems, only 1.3% of eligible patients were prescribed tirzepatide. Greater uptake is projected to be associated with population-level improvements in weight and other cardiometabolic risk factors. There is a critical need to overcome access and other barriers to the use of effective obesity medications.

The increase in worldwide flight traffic and the growing number of aerial vehicles necessitate the incorporation of innovative technologies into aviation regulatory practices. The Automatic Dependent Surveillance-Broadcast (ADS-B) system complies with the International Civil Aviation Organization’s recent flight safety regulations and is now widely adopted by most airlines. Nevertheless, ADS-B features some serious vulnerabilities due its open nature which may results in several attacks such as spoofing endangering flight operations. In addition, ADS-B governance requirements vary significantly per regions while AI-based methods lack formal oversight and alignment with AI governance. In this paper, we bridge this gap by providing a mapping of ADS-B vulnerabilities, attacks and AI-based solutions with the National Institute of Standards and Technology (NIST) Risk Management Framework (RMF), and the NIST AI RMF. We also highlight the ADS-B mandates in case studies focusing on USA, Europe, Canada, China and Australia. Our findings highlights the gap in applying cybersecurity and AI risk management frameworks in aviation. This paper would serve as a reference for key stakeholders in aviation aiming to conduct further research in this field and establish a foundational layered governance framework that addresses all the highlighted gaps in this work.

Since the 19th century, railway systems have evolved into complex Cyber Physical Systems (CPS) benefiting from the advances made in mechanics, control networks, signaling systems and more notably communication technologies. This sophistication was accompanied, however, with a rising pace of cyber threats in recent years that jeopardizes the safety of operations. Most proposed machine learning approaches that dealt with this problem struggle in presence of evolving attacks targeting trains, and cannot generalize across different tasks. In this paper, we bridge that gap by proposing SecMTL-Rail, a novel framework that goes beyond Single Task Learning (STL) by leveraging a novel multi-task learning (MTL) to detect and classify several types of railway cyber threats including Denial of Service (DoS), Distributed Denial of Service (DDoS) and Web attacks. We evaluated our SecMTL-Rail framework on the CICIDS2017 dataset due to shared similarities with railway attacks in networks environment. Our results highlight the superiority of our design over classic STL approaches across the performance metrics that we used.

The design and production of goods have been completely transformed by additive manufacturing (AM), which makes it possible to create components with intricate and complex geometries that were previously impossible or impractical to produce. However, current technologies continue to produce coarse-surfaced metal components that typically exhibit fatigue properties, resulting in component failure and unfavorable friction coefficients on the printed part. Therefore, to improve the surface quality of the fabricated parts, post-processing of AM-created components is required. With emphasis on electroless nickel plating, ChemPolishing (CP), and ElectroPolishing (EP), this study investigates post-processing methods for stainless steel that is additively manufactured (AM). The rough surfaces created by additive manufacturing (AM) restrict direct use. While ElectroPolishing (EP) achieves high material removal rates but may not be consistent, ChemPolishing (CP) offers uniform smoothening. Nickel plating enhances additive manufacturing (AM) products’ resistance to wear and scratches and corrosion protection. To optimize nickel deposition, medium (6%–9%) and high (10%–13%) phosphorus nickel was tested using the L9 Taguchi design of experiments (DOE). Mechanical properties, including scratch resistance and adhesion, were evaluated using the TABER 5900 reciprocating (Taber Industries, North Tonawanda, NY, USA) abraser apparatus, a 5 N scratch test, and ASTM B-733 thermal shock method. Surface analysis was performed with the KEYENCE VHX-7000 microscope (Keyence Corporation, Itasca, IL, USA), and chemical composition before and after nickel deposition was assessed via the ThermoFisher Phenom XL scanning electron microscope (SEM, Thermo Fisher Scientific, Waltham, MA, USA) Optimal processing conditions, determined using Qualitek-4 software, Version 20.1.0 revealed improvements in both surface finish and mechanical robustness. This comprehensive analysis underscores the potential of nickel-coated additive manufacturing (AM) parts for enhanced performance, offering a pathway to more durable and efficient additive manufacturing (AM) applications.

The progression into undergraduate engineering programs presents significant challenges for first-year students, influencing their sense of belonging, motivation, and persistence.This workin-progress paper investigates the impact of a specific collaborative, student-led educational support within a first-year Introduction to Engineering course at a diverse community college.Students engaged in a 4-week project involving urban air quality prediction using Machine Learning through Python, culminating in the creation of peer-generated educational videos documenting their work.This research examines how these student-led activities and peer produced materials influence students' engagement, confidence, and persistence, as well as their sense of belonging and emerging engineering identity.A mixed-methods approach, including pre-and post-surveys utilizing adapted validated scales (Walton & Cohen, Good et al., Godwin et al.) and qualitative reflections, is implemented.Preliminary findings are anticipated to show positive shifts in student insight.

Throughout history, communities have struggled to build homes in places actively hostile to their presence, a challenge long faced by African descendants in the American diaspora. In cities across the U.S., including Washington, D.C., efforts have often been made to erase Black cultural identity. D.C., once a hub of Black culture, saw its urban fabric devastated during the 1968 riots following Dr. Martin Luther King Jr.’s assassination. Since then, redevelopment has been slow and, more recently, marked by gentrification, which has further displaced Black communities. Amid this context, Black architects such as Michael Marshall, FAIA, and Sean Pichon, AIA, have emerged as visionary leaders. Their work exemplifies Value-Inclusive Design and aligns with Roberto Verganti’s Design-Driven Innovation by embedding cultural relevance and community needs into development projects. These architects propose an intentional approach that centers Black identity and brings culturally meaningful businesses into urban redevelopment, shifting the paradigm of design practice in D.C. This collective case study (methodology) argues that their work represents a distinct architectural style, Black Modernism, characterized by cultural preservation, community engagement, and spatial justice. This research examines two central questions: Where does Black Modernism begin, and where does it end? How does it fit within and expand beyond the broader American Modernist architectural movement? It explores the consequences of the destruction of Black communities, the lived experiences of Black architects, and how those experiences are reflected in their designs. Additionally, the research suggests that the work of Black architects aligns with heutagogical pedagogy, which views community stakeholders not just as beneficiaries, but as educators and knowledge-holders in architectural preservation. Findings reveal that Black Modernism, therefore, is not only a design style but a method of reclaiming identity, telling untold histories, and building more inclusive cities.