National Changhua University of Education

Based on the approach-avoidance framework, this study examines the effect of leaders’ aggressive humor on employees’ avoidance tendencies and further investigates how these avoidance tendencies influence employees’ work engagement. Additionally, leader-member exchange (LMX) is incorporated as a moderator in the relationship between avoidance tendencies and work engagement. We collect data through a questionnaire survey administered to full-time employees across various industries and job roles to enhance the generalizability of the findings. This study hypothesizes that aggressive humor increases employees’ avoidance tendencies (H1), avoidance tendencies reduce work engagement (H2), and LMX moderates the relationship between avoidance tendencies and work engagement (H3). The findings are expected to clarify the mechanism through which aggressive humor affects employees and offer practical implications for leader selection, leadership training, and strategies for enhancing work engagement.

Vocational education systems face increasing pressure to deliver high-quality skills training while ensuring resource efficiency, safety, and scalability. In machining programs, traditional hands-on training relies heavily on physical equipment, consumables, and close supervision, posing challenges for sustainable management. This study employs a quasi-experimental design with pretest–posttest measures and a comparison group to examine the effects of VR-based pre-training with 50 first-year vocational students. The findings indicate that VR-based preparation supports learners’ cognitive and experiential readiness and contributes to perceived preparedness for subsequent hands-on activities. No statistically significant differences in posttest performance were observed between groups. VR-based preparatory training supports risk mitigation in learning contexts by enabling cognitive rehearsal and structured procedural familiarization before physical practice. At the system level, VR-based pre-training transforms early-stage trial-and-error learning into a guided virtual environment that incorporates predefined operational sequences, procedural cues, and embedded safety prompts. This approach helps reduce safety risks for inexperienced learners and supports the more strategic use of instructional resources. Rather than establishing generalized or causal effects, the findings provide exploratory, empirically grounded insights derived from a single institutional context, offering a structured reference framework to inform the design, scaling, and validation of future multi-site or longitudinal research in vocational education management. Furthermore, the study explicitly aligns with Sustainable Development Goals 4 (Quality Education) and 8 (Decent Work and Economic Growth). This alignment underscores the study’s relevance to sustainability-focused vocational training initiatives.

[This corrects the article DOI: 10.3389/fpsyt.2022.836896.].

The integration of high-quality GaSb layers on GaAs substrates presents a promising route for developing antimonide-based optoelectronic devices on cost-effective platforms. In this work, we investigate the influence of antimony (Sb) flux during the low-temperature antimonidation process, which is proposed to promote Al–Sb reactions and the formation of an AlSb-like interlayer, on the crystallographic orientation as well as the electrical and optical properties of GaSb films subsequently grown on GaAs (001) substrates. Three samples with varying Sb supply conditions were analyzed using high-resolution x-ray diffraction, scanning transmission electron microscopy, and photoluminescence (PL) spectroscopy. Our results suggest that sufficient Sb flux during this initial stage favors the formation of a highly crystalline interlayer with dominant (002) characteristics, which, in turn, enables the subsequent epitaxial growth of GaSb with a (001) orientation. In contrast, reduced or absent Sb flux results in unfavorable (111) or mixed orientations, degraded crystalline quality, and diminished PL intensity. Electrical characterization further confirms that improved crystal orientation correlates with lower sheet resistance and higher carrier mobility. These findings highlight the critical role of Sb availability during antimonidation in determining the performance of GaSb-based heterostructures on GaAs substrates.

Emotional exhaustion among ICU professionals poses a significant threat to both health care quality and staff well-being. While patient safety culture (PSC) is recognized as a potential buffer, its longitudinal impact on emotional exhaustion remains underexplored, particularly within high-intensity clinical environments like ICUs. This study investigates how ICU professionals' perceptions of PSC influence the progression of emotional exhaustion over a 5-year period, highlighting shifts in organizational and psychological predictors. A 5-year longitudinal survey (2020-2024) was conducted in a regional teaching hospital in Taiwan. A total of 1213 valid responses were collected from ICU physicians and nurses using the Chinese version of the Safety Attitudes Questionnaire (CSAQ), which includes 6 PSC dimensions and an emotional exhaustion scale. Stepwise multiple regression was used annually to identify significant predictors of emotional exhaustion. Findings revealed a temporal shift in the predictors of emotional exhaustion. In 2020, organizational support factors-job satisfaction (β=-0.523, p<0.001) and perceptions of management (β=-0.443, p<0.001)-were significant negative predictors, while safety climate showed a counterintuitive positive association (β=0.264, p=0.004). From 2021 to 2024, stress recognition emerged as the most consistent protective factor (β range=-0.366 to -0.537, p<0.001). Interestingly, teamwork climate, often considered beneficial, was positively associated with emotional exhaustion in later years, suggesting added interpersonal burdens in collaborative ICU settings. Emotional exhaustion in ICU professionals is shaped by dynamic interactions between organizational structures and individual-level coping resources. Early burnout prevention should focus on institutional support, while long-term strategies should promote stress awareness and carefully manage team-based expectations. These findings provide health care leaders with actionable insights to design adaptive, stage-specific interventions to sustain psychological resilience in high-stress clinical environments.

This paper proposes a novel approach for distribution network reconfiguration (DNR) using swarm intelligence (SI) algorithms enhanced with shrinking encircling behavior to address non-convex optimization challenges in large-scale distribution networks. The methodology is applied to Taipower's distribution network, utilizing data from the Distribution Mapping Management System (DMMS) and Distribution Dispatch Control Center (DDCC) to create an OpenDSS-based simulation model. The proposed SI algorithms determine the optimal statuses of 4-way and 2-way feeder switches to minimize energy losses while adhering to constraints on bus voltage and feeder currents. Comparative evaluations of multiple SI algorithms identify those with shrinking encircling behavior as the most effective for the high-dimensional DNR problem. Additionally, a graph-theory-based rule is introduced to ensure radial network topology during reconfiguration. Numerical results demonstrate that the proposed approach reduces energy losses by 22.9%, achieves uniform feeder current distribution, and improves operational efficiency. These findings underscore the potential of this method to enhance modern distribution network management.

This paper presents a novel adaptive moving window forgetting factor method specifically designed for the decoupled recursive least squares approach applied to the second-order equivalent circuit model of batteries, The proposed technique adjusts weights using historical and current modeling errors, reducing complexity and improving parameter accuracy. To further improve its efficiency, the jellyfish search algorithm was employed to fine-tune the hyperparameters. Three distinct load profiles—the federal urban driving schedule, the dynamic stress test, and the supplemental federal test procedure driving schedule for United States —were selected to validate the effectiveness of the proposed algorithms. Experimental results show that the proposed method reduces the mean absolute error of terminal voltage by up to 74.3%, with an average improvement of 34.6% over the fixed forgetting factor method. Furthermore, it outperforms the sliding window difference forgetting factor method by up to 52.6%, with an average gain of 27.8%. Lastly, the method demonstrates up to 42.6% improvement and an average enhancement of 26.0% 20 over the original adaptive moving window forgetting factor method. In comparison to the aforementioned three methods, the proposed approach shows the capability to reduce mean absolute error of state of charge by up to 40.5%, 23.0%, and 7.6%, respectively