Wildfire smoke is increasingly degrading U.S. air quality via the emission and transport of pollutants. Smoke's direct role as a pollutant is well-documented; however, smoke also affects pollutant concentration indirectly by changing the shortwave actinic flux necessary for photochemical reactions. We compute smoke-driven changes in surface-level and boundary-layer downwelling actinic flux (F down arrow) at 550 and 380 nm (NO2 photolysis peak) along a 2018 Western wildfire Experiment for Cloud chemistry, Aerosol absorption, and Nitrogen (WE-CAN) research flight through the California Central Valley. The onboard HIAPER Airborne Radiation Package (HARP)-Actinic Flux instrument measured F down arrow. To assess changes in F down arrow relative to smoke-free conditions and at altitudes not sampled by the aircraft, we calculate F down arrow under assumed background and observed smoke conditions using the U.S. National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) Tropospheric Ultraviolet and Visible (TUV) radiation model. Under smoke-impacted conditions, modeled F down arrow minorly underestimates HARP observations; the average modeled-to-measured ratio is 0.93 at 550 nm and 0.89 at 380 nm. Relative to modeled background conditions, observed (modeled) smoke-impacted F down arrow at 380 nm decreased by 24% (38%), 15% (24%), and 8% (18%) at 0-0.5 km, 0.5-1 km, and 1-1.5 km, respectively. At the ground, smoke decreased modeled F down arrow at 380 nm by 43%-likely an upper bound, as the modeled values slightly underestimate observations. As climate change drives more severe wildfire seasons, understanding smoke's impact on actinic flux is essential for constraining future air quality, and recent extreme seasons like 2018 offer opportunities for such analyses.
Although many perceive positive stereotypes as complimentary, research has revealed a variety of ways these stereotypes are harmful to oppressed groups, including their role in sustaining inequality and their operation as microaggressions. Despite these findings, a recent study demonstrated that liberal White Americans endorsed positive stereotypes of Black and Native Americans, which was partly due to their internal motivation to respond without prejudice. However, no prior work has explored liberal dominant group members' reasoning for their beliefs about positive stereotypes. To explore the apparent contradiction between internal motivation to respond without prejudice and endorsement of positive stereotypes, we conducted a study in which 698 self-identified liberal White Americans, the vast majority of whom were internally motivated to respond without prejudice, wrote reasons for their attitudes toward positive stereotypes of Black and Native Americans. Through qualitative thematic analysis, we identified a range of patterns in participants' written reasoning. Most participants endorsed positive stereotypes, and believed them helpful to the target groups, because they perceived them as complimentary. A smaller number were critical of positive stereotypes, most often because they believed stereotypes ignore differences among target group members. Few participants expressed concerns about how these stereotypes negatively impact interpersonal interaction and legitimate systemic oppression. Our findings suggest that there may be a paradox among some potential allies: they may reinforce oppression through beliefs they perceive to be helpful. We discuss theoretical implications of these findings, as well as practical implications for social change.
This article presents a collaborative speculative writing exercise in which international educators and researchers imagined the future of Generative Artificial Intelligence (GenAI) in education through three fictional scenarios. The exercise employed a relay structure: one participant began each story, and a different participant completed it. After the stories were finished, all participants read the scenarios they had not written and responded to a set of reflective questions. We treat the resulting scenarios and reflections as a qualitative, multi-voiced dataset and read them through a light analytical framework centred on postdigital temporality, relay discontinuity and recurring thematic tensions. The scenarios explore a GenAI-free Reset Day in a corporate training centre, a family navigating educational choices with the help of a GenAI assistant, and an underground school resisting a fully automated world. Situated within the postdigital condition, the article engages education fiction as a mode of collective inquiry that enacts the entanglement of human and technological agency it seeks to explore. The relay handoff introduced productive friction, and the reflections surfaced recurring questions about dependency, listening, measurement and the difficulty of translating situated, story-based imaginaries into policy recommendations. The contribution is both methodological, in theorising relay-based education fiction writing, and analytical, in showing how familiar postdigital concerns are reassembled through collaborative fictional handoffs.
In recent decades, millions of Chinese women workers have migrated from their remote villages to the industrial factories in the modern cities, but little is known about their career development. The present study aimed to examine the diverse work experiences of young Chinese migrant women workers from the perspective of the Trajectory Equifinality Approach and the Chaos Theory of Careers. The semi-structured interviews were conducted individually with thirty-two Chinese women workers. We used thematic and ideal type analysis to analyze the interview data, and identified four distinct typologies based on the personal projects women workers were pursuing: Mothers, Family-Centered, Active Learners, and Money-Only. The findings deepen our understanding of the nuanced career experiences and dynamic interplay of the developmental tasks during emerging adulthood. By acknowledging the multiple career trajectories and integration between career and other life domains, the Trajectory Equifinality Approach and the Chaos Theory of Careers could inform policy makers to tailor the interventions that address the specific challenges faced by Chinese migrant women workers within broader socio-cultural contexts.
Objective:This study investigates the relationship between lower-body strength, power, and lunge velocity in elite female fencers of different weapons (foil, épée, and saber) to analyze the differences in fitness requirements between weapons and to provide a scientific basis for specialized fitness training. Methods:A cross-sectional study design was used to include 45 female fencers (12 in foil, 16 in saber, and 17 in épée) who performed the isometric mid-thigh pull test (IMTP), countermovement jump, squat jump, drop jump, static lunge velocity and advance lunge velocity tests. A one-way Analysis of Variance (ANOVA) was used to compare the differences among weapons groups, and Pearson's correlation was used to analyze the relationship between lower-body strength, power, and lunge velocity. Results:Épée fencers had significantly higher advance lunge velocity than foil (P = 0.0003) and saber (P = 0.0001). The IMTP-50 ms rate of force development (RFD) of saber fencers was significantly better than that of épée fencers (P = 0.0213). Correlation analysis showed that the advance lunge velocity of foil fencers was strongly and positively correlated with IMTP relative maximal force (r = 0.63, P = 0.030). In contrast, the static lunge velocity of saber fencers was strongly correlated with squat jump height (r = 0.67, P = 0.004) and IMTP 250-300 ms RFD (r = 0.53, P = 0.035). Conclusion:Significant differences in lunge performance were found between fencers of different weapons. The results indicate that épée fencers exhibit significantly superior advance lunge velocity compared to foil and saber fencers. Furthermore, foil fencers require greater lower-body strength, and saber fencers rely more on the ability to develop force rapidly. The study supports the development of differentiated physical training programs for each weapon to optimize competitive performance.
