Black high school students experience discrimination in a variety of formats in and outside of school. Such discrimination can be distressing and may lead to racial battle fatigue (RBF), which is the physiological, psychological, or behavioral strain people of color experience after exhaustive cope with on-going racial discrimination. RBF has rarely been studied among Black adolescent populations, and operationalizations about how RBF manifests are limited. The present study aimed to define and categorize RBF manifestations among Black high school students. This study qualitatively examined the ways in which recent Black high school graduates (N =17; ages 18-21) experienced RBF during their time in secondary education settings, and it considered the discriminatory context in which RBF arose. Results also suggest that RBF manifested in four distinct behavioral, psychological, or emotional ways. Furthermore, RBF manifestations arose due to discrimination related to microaggressions, macroaggressions, and overt discrimination.
Trees can redirect large volumes of rainwater to the base of their stems. This stemflow not only redistributes water but also channels canopy-derived solutes to the forest floor. Building on research showing canopy geometry and bark properties govern stemflow volumes, we examined how those same traits modulate the biogeochemical side of this flux. Over a 12-month period in Jamari National Forest (Brazil), we quantified stemflow volume and solute chemistry for 19 trees grouped by diameter at breast height (D: < 10, 10-20 and > 20 cm), crown area (CA: < 30, 30-60 and > 60 m(2)) and bark texture (smooth, fissured and rough). Small-stemmed, smooth-barked trees produced the greatest stemflow yields, whereas large-stemmed, rough-barked trees generated lower volumes but higher mean ion concentrations. Macronutrient-rich species appear to flip the usual water-flux story on its head. For example, calcium and potassium (two key nutrients for plant growth) rose sharply from 1.1 kg-Ca2+ ha(-1) and 4.9 kg-K+ ha(-1) in small, smooth-barked trees to 6.3 and 7.7 kg ha(-1), respectively, in large rough-barked individuals. In contrast, trace anions such as chloride and bromide declined with size and roughness (Cl-: 1.3 to 0.4 kg ha(-1); Br-: 0.20 to 0.03 kg ha(-1)). These contrasting patterns show that although small, smooth trees may dominate stemflow water routing, older, structurally complex trees disproportionately deliver the nutrients that drive forest productivity. Consequently, conserving structural diversity-including mature, rough-barked specimens-is essential for maintaining biogeochemical cycling in Amazonian forests threatened by deforestation and climate change.
Diffusion models have emerged as a powerful class of generative models, demonstrating impressive results across visual domains such as image and video synthesis. This survey provides a comprehensive taxonomy of generative models, with a particular focus on diffusion models and their applications in enhancing visual fidelity for text-to-image and text-to-video generation. We discuss the theoretical foundations of diffusion models, including their formulation through stochastic differential equations, and analyze the forward noising and reverse denoising processes that enable stable training and high-quality generation. The survey further categorizes diffusion architectures, including pixel-space and latent-space models, and examines their design choices, training strategies, and trade-offs across different resolution regimes. In addition, we review noise characteristics in real-world imaging domains and discuss their implications for diffusion-based models. Denoising strategies are analyzed by distinguishing between in-model denoising mechanisms and external denoising techniques used in preprocessing and post-processing pipelines. The survey also summarizes commonly used datasets and evaluation metrics for generative modeling, providing a practical perspective on benchmarking and model comparison. Finally, we discuss current challenges, including computational efficiency, scalability, and robustness to diverse noise distributions, and outline potential directions for future research. This survey aims to provide a structured reference for understanding diffusion models and their applications in visual generation tasks.
PurposeMilitary veterans face significant challenges when transitioning from their military career to the civilian sector. To better understand the transitioning process and develop effective strategies for veteran career advancement, this paper aims to develop a mediation model of veteran career resilience by accentuating a relational understanding of agency and resilience.Design/methodology/approachA sample of 412 US veterans participated in an online survey. The study used mediation analyses to test its hypotheses.FindingsThe findings offer empirical support for the model in which veterans' experience of leadership with their direct military supervisor as well as support at home during their service are positively associated with their agency of career resilience, which has a significant predictive effect on their civilian career satisfaction.Research limitations/implicationsThe study makes significant theoretical contributions by advancing the construct of agency of veteran career resilience and developing a mediation model that accentuates a relational understanding of agency and resilience in military veterans' career development. One key limitation is its cross-sectional survey design.Practical implicationsThe findings have direct practical implications for leadership training in the military, the development of career agency in soldiers while serving and the building of social support networks.Originality/valueThe originality of the study lies in the proposed construct of agency of career resilience during military service and the mediation mechanism that facilitates the development of veteran career resilience. The findings also have practical implications for supporting veteran career development and transition prior to their exit from the military.
In the United States and across the globe, democratic institutions are facing sustained threats, raising urgent questions about how resistance movements can organize and sustain collective action over long periods of time. In prior editorials, we have focused on providing strategies for individual behavior scientists to engage in nonviolent resistance. In this editorial, we expand that perspective to consider how behavior science can participate in the design, organization, and sustainability of resistance movements. Drawing from behavior analysis, behavioral systems analysis, culturo-behavioral systems science, and contextual behavior science, we examine how shared values, participation structures, leadership practices, and reinforcement systems can support long-term resistance efforts when terminal reinforcers are delayed and uncertain. We provide examples of how to create opportunities for participation along a continuum of risk levels, how psychological flexibility may contribute to committed action among participants, and structures that distribute leadership and reduce attrition. Research on resistance movements consistently shows that mobilization alone is insufficient. Durable change requires organization, reliable production of aggregate products, and sustained contact with selecting environments. We conceptualize resistance movements as behavioral systems that can be intentionally designed to increase participation, coordination, and persistence over time. As behavior scientists, we can contribute not only as researchers and consultants, but as participants who help design environments and organizations that make sustained collective action possible. The success of resistance movements is not a function of mobilization alone. It emerges when movements are intentionally designed to play the long game, cultivating the structures and practices necessary for sustained, adaptive, and enduring action.
