Particulate nitrate (NO3−) in coastal air affects the nitrogen cycle and cloud condensation nuclei, yet its chemical formation processes, especially with respect to air mass transport and local emissions, are poorly understood. To clarify NO3− sources and formation mechanisms, nitrogen and oxygen isotopic compositions (δ15N and Δ17O) for NO3− and Δ17O of ozone (O3) were measured at a mountain site located in Tai Mo Shan (640 m a.s.l.) and δ15N and Δ17O of NO3− were measured at an urban site located in Tsim Sha Tsui (60 m a.s.l.) in Hong Kong, a coastal megacity of southern China. Average δ15N-NO3−, Δ17O-NO3−, and Δ17O-O3 at the mountain site were −1.1 ± 2.1‰, 22.4 ± 1.1‰, and 24.1 ± 1.4‰, respectively, while urban δ15N-NO3− and Δ17O-NO3− were 0.8 ± 1.3‰ and 21.1 ± 0.9‰. Bayesian modeling identified the NO2 + OH reaction as the dominant nitrate formation pathway at both sites, highlighting the role of photochemical processes in coastal environments. N2O5 hydrolysis was more prevalent at the humid mountain site, and HC/DMS/XNO3 pathway influenced urban areas through hydrocarbon emissions and marine air masses. Natural gas and coal combustion emerged as the predominant contributors to nitrate aerosols at Tai Mo Shan, where the absence of local emissions underscored regional transport of these aerosols, while NOx emissions from ships and vehicles dominated urban NO3− sources. Transitioning to clean fuels and electric vehicles is vital for reducing urban NOx emissions and associated health risks from nitrate particles.
The manipulation of articulated objects for part-level motion is crucial due to their prevalence in real-world applications. Although current manipulation methods have improved interaction quality, they share a common issue: neglecting the completeness of motion trajectories. For example, when we use a front-loading drum washing machine, the expected action is to manipulate the door from fully closed to fully open. However, these methods might only result in it being half-open. To tackle this limitation, we introduce a novel framework for optimizing motion trajectories based on multimodal fusion. Specifically, we explicitly model trajectory completeness and propose a motion trajectory construction paradigm (MTCP). This paradigm is applied to a large-scale dataset containing a wide range of articulated objects, generating high-quality motion trajectories for multimodal fusion. Furthermore, to handle trajectory homogeneity, we propose a trajectory enhancement policy (TEP) that enriches the trajectory set by capturing the multimodal distribution of feasible trajectories. Subsequently, to enhance the learning efficiency and task adaptability of Multimodal Large Language Models (MLLMs), we propose a learning strategy for 3D perception inspired by 2D perception (3PI2P), complemented by a progressive reasoning approach. This strategy integrates a dual-branch input design using RGB images and depth maps, combined with six forms of visual question answering tasks, to achieve collaborative reasoning and deep fusion of 2D semantics and 3D geometric information. The robustness and generalizability of the framework are demonstrated through evaluations in both simulation and real-world environments.
China’s atmospheric environment modeling has advanced rapidly in response to intensifying air pollution challenges, emerging scientific needs, and growing international engagement. This review synthesizes advances across the historical evolution of model systems, key innovations in mechanisms and technologies, and emerging strategic directions. We trace the development from early offline models to fully coupled meteorology–chemistry systems, culminating in high-resolution, multi-pollutant platforms increasingly integrated with artificial intelligence. These models have improved the representation of key processes such as heterogeneous chemistry, secondary aerosol formation, and ozone photochemistry, and have enhanced forecasting capacity through ensemble approaches, data assimilation, and decision-support applications. However, significant challenges remain, including the incomplete simulation of multiphase and feedback processes under compound extremes, limited computational scalability for high-resolution and ensemble use, and fragmented integration of multi-source observations. To address these challenges, this review highlights four priorities: (1) incorporate machine learning into mechanistic modeling; (2) advance open-source and internationally aligned platforms; (3) develop flexible numerical schemes for multi-scale coupling; (4) embed atmospheric chemistry into Earth system models. China’s experience illustrates not only a national transformation from model adaptation to innovation but also provides transferable insights for the global modeling community.
Educators are a vital yet vulnerable workforce, often facing mental health issues. Although intervention programs exist, the extant literature primarily focuses on student services. This paper presents a systematic review and meta-analysis to evaluate technology-mediated psychological interventions for educators. A thorough search across seven electronic databases identified 27 studies for the systematic review and 17 for the meta-analysis. The review summarizes various types and content of these interventions, along with the mental health outcomes they address. Technology-mediated interventions primarily used web-based platforms, smartphone-delivered applications, and online videoconferencing. Most of these interventions were delivered asynchronously. Moreover, they were classified into four categories: behavioral, cognitive-behavioral, mindfulness, and knowledge-based, targeting different mental health concerns. Meta-analyses revealed that these interventions significantly reduced anxiety symptoms/worrying (Hedges' g = -0.52, p < 0.05, k = 11), depressive symptoms (g = -0.52, p < 0.05, k = 9), and stress (g = -0.79, p < 0.001, k = 14) when compared to control groups. However, reductions in burnout (g = -0.54, p = 0.08, k = 9) and improvements in well-being (g = 0.48, p = 0.09, k = 9) were statistically nonsignificant. The results suggest that technology-mediated mental health interventions can be effective in addressing mental health issues (e.g., anxiety, depression) among educators. Thus, they can be integrated into teacher education and professional development programs. It is recommended that future research focus on evidence-based digital mental health solutions to enhance teacher well-being and improve educational quality.
Given the growing recognition of corporate social responsibility (CSR) as a strategic initiative, especially tied to major national events like the Olympics, this study explores how corporations' sponsorship of national teams affects consumer-company identification (CCI) and subsequent positive and negative relational outcomes. Employing the social identity theory, the study examined how national identification can further translate into CCI via identity salience and reduce corporate hypocrisy via in-group bias, moderated by communal engagement on social media. To test the hypothesized relationships, an online survey (N = 755) was conducted via Dynata. Results revealed that communal engagement significantly moderated the positive relationship between national identification and CCI, strengthening this link among highly engaged individuals. Moreover, elevated CCI further reduced corporate hypocrisy perceptions among those with low and moderate engagement, whereas its effect was minimal for highly engaged individuals. Those who strongly identified with companies sponsoring Team USA perceived a strong CCI, which further resulted in increase in positive word-of-mouth intentions. Lastly, the findings uncovered the double-edged role of highly engaged publics, as their heightened scrutiny weakened the mitigating effect of national identification on corporate hypocrisy. This highlighted their potential as both powerful advocates and critical evaluators of corporate actions. The findings offer practical insights into segmenting their audiences based on cause involvement on social media and adjusting CSR strategies accordingly.
