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Association of glucose response shape in OGTT with markers of pancreatic health and inflammation across diverse ages
No full textContext. The shape of glucose response in oral glucose tolerance test (OGTT) is a biomarker for pancreatic b-cell health. A biphasic response is deemed metabolically healthier compared to monophasic, while persistent increase is harbinger of diabetes. Objective. To assess the relationship of inflammatory markers with the shape of glucose OGTT response in a wide age range and populations. Design. Reanalysis of data obtained in cross-sectional prospective clinical studies. Patient or Other Participants. Individuals of self-reported Black ancestry (adolescents, n = 276, age 16.3 ± 1.7 years, 47.5 % female; young adults, n = 486, age 37.7 ± 7.5 years, 49.6 % female) were seen at Thomas Jefferson University between 2006- 2011.
Data was obtained from Pennington Biomedical Research Center for healthy individuals enrolled in clinical studies with OGTT data (n = 95, age 55.2 ± 9.9 years, 52.3 % female, 27.3% Black). Main Outcome Measure(s). Classification of OGTT glucose response curve into biphasic, monophasic and persistent increase groups. Correlation of glycemic indices and inflammatory markers with the shape of the OGTT glucose response curve.
Results. Persistent increase glucose curve was associated with lower insulinogenic and Matsuda index, phase 1 and phase 2 insulin secretion, but higher HOMA-IR and glucose AUC compared to monophasic or biphasic groups. Circulating inflammatory markers (CRP, PAI1, TNF-a) were higher while adiponectin lower in the persistent increase group. Findings were more prominent in adults compared to adolescents. Conclusions. Shape of glucose response curve is a biomarker for glycemia measures and obesity related inflammation across ages
Megatons Into Megawatts: The Deal Eliminating 20,000 Atomic Bombs
No full textMegatons Into Megawatts was a deal between the US and Russia from 1993-2013 that removed 500 metric tons of highly enriched uranium (HEU) from Russian nuclear warheads which was diluted and sold to the US to fuel civil nuclear reactors, producing 10 percent of US electricity annually while eliminating the potential to make over 20,000 Hiroshima weapons. The multibillion dollar proceeds to Russia from the deal helped keep the collapsed Soviet nuclear complex from leaking “loose nukes” and weapons expertise that could have imperiled global security. The US also diluted over 150 metric tons of HEU in tandem, over 6000 bombs. Experts hailed the “HEU Deal” among the most significant reductions of the nuclear threat ever, eliminating a third of the world’s atomic bomb material. But the achievement, extending over two decades, multiple presidencies, and executed primarily by commercial means, remains little known. This history provides the first comprehensive study of the origins, the negotiations at the highest levels in the US and Russia to get the agreement into place, and the many challenges that imperiled its operation—in the US, Russia, and in commercial markets—which were overcome to fulfill the agreement. The author participated in many phases of the deal.
An Afterword addresses whether, and under what conditions, a future variant of the HEU Deal might be possible, despite Putin’s ongoing war on Ukraine, recalling that the collapse of the Soviet nuclear empire in 1991 spurred the swords to plowshares HEU Deal that would have seemed impossible a decade earlier, and that large stockpiles of nuclear weapon materials remain, are costly to store, and arguably of declining marginal utility.
Moreover, the acceleration of climate change, increasing costs of extreme weather damage, rising world energy demand, including for Artificial Intelligence (AI) which will rival nuclear weapons in military applications, provide additional reasons to understand how Megatons into Megawatts succeeded, overcame past rivalry, used civil nuclear energy and the market to rid of excess HEU stockpiles while producing carbon free baseload electricity, to better face the rapid onrush of current global threats and transformative opportunities
Beyond Binary: Understanding Gender-diverse Students’ Experiences in Science Education
No full textPast decades of research on gender in science education have yielded important insights into the experiences of cis women and girls and have also facilitated their increased participation in scientific fields. However, in recent years as understandings of gender have become increasingly constructivist and fluid, especially among young people, a gap has emerged between the way that many students understand gender, and the binary way that it is presented in most research. Highlighting the specific experiences of students of diverse gender identities in science classrooms is especially crucial given an increasingly polarized and hostile political climate around gender.
This study uses the theoretical frameworks of Fourth Wave Feminism and Queer Theory to focus on the experiences of gender-diverse young people along the construct of sense of belonging, engagement in science, and perceptions of science. These constructs are explored through an explanatory sequential mixed methodology, using a quantitative survey (n = 232) with demographic questions, questions about social media, and three survey instruments used to assess each of the research question constructs. The quantitative strand was analyzed and used to inform the qualitative strand (n = 5), conducted using critical-case sampling from the quantitative participants to collect detailed experiences using a semi-structured interview protocol.
These findings added context and depth to the overarching patterns found in the quantitative data. The triangulation of quantitative and qualitative data uncovered stark differences in sense of belonging between gender-diverse participants and their cis peers. Though the quantitative data around engagement showed few significant differences between groups, the qualitative interviews revealed the complex ways gender-diverse students navigated science curriculum and pedagogy, indicating a tension between interest in science and comfort in science learning communities. Furthermore, despite feeling less welcome, many gender-diverse participants expressed high regard for science’s importance and value for society.
The qualitative data analysis yielded five interconnected themes that were also aligned with quantitative findings: (1) representation and visibility gaps, (2) finding and building community, (3) evolution of scientific understanding, (4) navigating social spaces in science classrooms, and (5) intersectional identities. These results point toward needed reforms in science education, including explicit institutional support structures for gender-diverse students, curricular adaptations that reflect contemporary gender understandings, and pedagogical approaches that build community rather than isolation. This study expands science education equity research beyond binary gender constructs and provides concrete directions for supporting students whose experiences have remained underrepresented in previous literature
Exploring the Effects of AI-Generated Pedagogical Agents in Instructional Videos on Learning
No full textThis dissertation examined the effects of AI-generated versus human pedagogical agents on learning outcomes, cognitive load, and visual attention in multimedia learning. Using a 2 x 2 mixed factorial design, 58 adult participants viewed two instructional videos that varied by agent type (AI or human) and video order. Learning outcomes were measured through retention and transfer tasks, cognitive load was assessed using a subjective scale, and visual attention was recorded through eye-tracking data focused on the agents’ face, eyes, and hands.
Findings indicated no significant differences in retention or transfer between AI and human agents, suggesting that well-designed AI agents can be as instructionally effective as humans. However, video order significantly influenced retention, with declarative-first sequences leading to higher scores. While cognitive load scores did not differ significantly, descriptive trends suggested that procedural content presented first may increase perceived effort.
Eye-tracking results showed that human agents consistently drew more attention to facial and eye regions, while AI agents attracted greater attention to gesture-related areas. These results highlight the importance of content sequencing and the alignment of visual and auditory cues. The study provides practical and theoretical insights for designing effective AI-generated instructional agents that support engagement and learning in multimedia environments
Distinguishing Among Climate Change-Related Risks
Full text linkUnderstanding the diverse types of climate change-related risks is crucial for developing effective strategies to address the global climate crisis. A holistic yet disaggregated approach allows for a comprehensive view of the challenges while enabling targeted responses from various stakeholders. This document outlines three main categories of climate-related risks: planetary, economic, and financial, detailing their relevance to various stakeholders, timeframes, and potential response strategies.
This short brief aims to disentangle the complex nature of risk discussions for productive discourse and appropriate risk management approaches for different stakeholders. In practice, discussions related to assessing and responding to climate change risk have conflated categories of risk, confusing discussions and undermining the effectiveness of related strategies. We hope this brief can bring clarity and rigor to analyses of risk and support constructive discussion among policymakers, financial institutions, social sector actors, and the public. We plan to follow this short briefing with a longer report including more detailed analysis, integrating feedback to these initial ideas
Climate Predictability Tool version 18.6.1
No full textThe Climate Predictability Tool (CPT) is a software package for constructing a seasonal climate forecast model, performing model validation, and producing forecasts given updated data. Its design has been tailored for producing seasonal climate forecasts using model output statistic (MOS) corrections to climate predictions from general circulation model (GCM), or for producing forecasts using fields of sea-surface temperatures or similar predictors. Although the software is specifically tailored for these applications, it can be used in more general settings to perform canonical correlation analysis (CCA), principal components regression (PCR), or multiple linear regression (MLR) on any data, and for any application
The Politics of Love as National Identity: Hitbolelut as a Literary Trope in Gader Chaya (2014)
No full textPublished in May 2014, Gader Chaya, a romance novel by Persian-Jewish Israeli author Dorit Rabinyan, sparked national controversy when it was banned from Israel’s high school curriculum for allegedly promoting hitbolelut—inter-ethnic romance between Jews and gentiles, especially between Israeli Jews and Palestinian Arabs. The novel tells the tragic love story of Liat, a Persian-Jewish Israeli, and Hilmi, a Palestinian, set in post-9/11 New York against the backdrop of the Second Intifada and the building of the Israeli separation wall. The title, meaning both “hedge” and metaphorically a “living fence,” underscores the emotional and political boundaries between the lovers. Framed by Liat’s liberal Zionist perspective, the novel explores themes of national betrayal and diasporic freedom. Rooted in Rabinyan’s real-life relationship with Palestinian artist Hassan Hourani, the novel’s censorship and acclaim reflect Israel’s deep anxieties around assimilation. This thesis traces hitbolelut through five essays: its biblical and linguistic origins; its paradox within a Jewish-majority state; its role in post-Zionist identity; its literary function in Gader Chaya; and its social reception. The Epilogue revisits how hitbolelut both defines and divides Jewish Israeli society
An exploration of the role of visuals and users’ imagery and verbal preferences on goal attainment and coaching chatbot adoption
No full textArtificial intelligence chatbots could scale coaching, however user adoption is a challenge. We investigate the effect of images on chatbot adoption and coaching efficacy by comparing a text-only coachbot (TextBot, n=126) with a text+images bot (ImageBot, n=116). We measure goal attainment and technology adoption one week apart, as well as users’ preferences for imagery and verbal modes of communication. Perceived goal attainment increased at T2 for both bots. If “Correct word usage” was important, users found the TextBot to be less “fun”. Users with lower “Imagination” also found the TextBot easier to use, and were more likely to use it. We introduce the concept of “AI coach customization”.
Keywords: artificial intelligence chatbots, chatbots, coaching chatbots, AI coaching, technology adoption, UTAUT, visual verbal preference, goal attainment, visual coachin
Credibility and Performance in Gay Asylum Claims
No full textUnited States asylum courts rely on credibility determinations to assess whether an asylum seeker is eligible for asylum. By examining asylum claims made by gay men on the basis that they experienced persecution due to their sexuality in their country of origin, it becomes clear that credibility assessments are subjective and often rooted in prejudice.
Keywords: gay, homosexual, asylum, asylum claims, credibility, United States, America, performance, performativ
Risks and opportunities for mental health in the neighborhood: An exploration of residential segregation, social cohesion, and depressive symptoms among Latinxs
No full textBackground: In the neighborhood and health literature there has been extensive work on the benefits of neighborhood social cohesion on health in the United States (US) population and conversely the negative effects of residential racial segregation on health among African Americans.
Though Latinxs are one of the fastest growing populations in the US, there is limited research on what features of social integration may affect their perceptions of neighborhood social cohesion. Additionally, Latinxs are often treated as a monolith in spite of the heterogeneity of the ethnic group and the evidence of within-group differences in health outcomes. Finally, the impact of segregation on the mental health of this population is understudied, though past research has showed inconsistent findings.
Methods: In this three-paper dissertation I used the Multi-Ethnic Study of Atherosclerosis, a multi-site population-based study, and its ancillary Neighborhood Study collected in 2010 and 2016. The first paper examined the association between three indicators of acculturation and integration proxies (i.e. English language proficiency, perceived interpersonal discrimination, and density of social engagement destinations) and neighborhood social cohesion using multilevel linear regression models. The second paper examined the moderating effect of English language proficiency on the association between neighborhood social cohesion and depressive symptoms also using multilevel linear regression models. Finally, using inverse odds ratio weighting, a counterfactual approach, the third paper investigated the mediating role of neighborhood social cohesion and neighborhood problems in the association between residential Latinx-White racial segregation and depressive symptoms. Mediators were assessed at the individual and neighborhood level.
Results: In paper 1, results showed that interpersonal discrimination was significantly associated with lesser neighborhood social cohesion. In paper 2, I found that social cohesion was associated with lesser depressive symptoms, no matter the English language proficiency of the respondent. Lastly, in paper 3 the results showed that there was a direct and indirect association between segregation and depressive symptoms through neighborhood problems at the neighborhood level. There were gender differences in both paper 2 and 3.
Conclusion: These findings suggest that among US Latinxs, understanding neighborhood social cohesion and residential Latinx-White segregation represent opportunities for improving mental health, with implications for policy and social work practice