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Ocean mesoscale flows significantly influence nutrient distribution and biological productivity, yet the scarcity of eddy‐permitting observational data sets and climate modeling hinders understanding their role in carbon sequestration. Using an eddy‐resolving global simulation, this study investigates the significance of ocean mesoscales in air‐sea carbon dioxide (CO2) exchange. Results show over 30% of CO2 flux variance in energetic regions attributed to flows with horizontal scales smaller than 2°. Mesoscale flows can drive a cumulative CO2 flux that is either a net carbon sink or source depending on region, with magnitudes on the order of 105 tonnes of carbon per year. Variations in this mesoscale‐related CO2 flux are correlated with local relative vorticity and the background gradient of ocean partial pressure of CO2. This analysis underscores the importance of considering ocean mesoscales in monitoring carbon flux, highlighting the need to explore the influence of increasing eddy activity on carbon uptake in a changing climate. Plain Language Summary This study investigates the influence of ocean flows with horizontal scales of tens to hundreds of kilometers (called mesoscale flows) on the exchange of carbon dioxide between the ocean and the atmosphere using a state‐of‐the‐art high resolution global simulation. It is shown that in certain parts of the ocean, more than 30% of the variability in carbon dioxide exchange at the ocean surface is linked to these relatively small‐scale ocean motions. It is further revealed that mesoscale flows can lead to a significant gain or loss of carbon from the ocean at the regional level, and that depends on how the flow is oriented with respect to the background distribution of carbon in the ocean. Gaining a better understanding of how the mesoscale flow features influence air‐sea carbon dioxide exchange is crucial for understanding the ocean's role in the carbon cycle and its ability to absorb and store carbon in a changing climate. Key Points Over 30% of air‐sea CO2 flux variability is attributed to ocean spatial scales smaller than 2° in eddy‐rich regions The cumulative mesoscale‐induced CO2 flux is on the order of 105 tonnes of carbon per year Mesoscale‐related CO2 flux is governed by both relative vorticity and the background gradient of partial pressure of CO2

HighlightsThe reaction mechanisms of hydrogen evolution reaction (HER) on various crystal surfaces of zinc anode have been systematically investigated by first-principle calculations.Both the thermodynamic and kinetic aspects of HER have been studied to reveal the relative HER activity of several crystal surface of zinc anode.The generalized coordination number of surface Zn atoms are proposed as a key descriptor of HER activity of Zn anode.Hydrogen evolution reaction (HER) has become a key factor affecting the cycling stability of aqueous Zn-ion batteries, while the corresponding fundamental issues involving HER are still unclear. Herein, the reaction mechanisms of HER on various crystalline surfaces have been investigated by first-principle calculations based on density functional theory. It is found that the Volmer step is the rate-limiting step of HER on the Zn (002) and (100) surfaces, while, the reaction rates of HER on the Zn (101), (102) and (103) surfaces are determined by the Tafel step. Moreover, the correlation between HER activity and the generalized coordination number (CN¯) of Zn at the surfaces has been revealed. The relatively weaker HER activity on Zn (002) surface can be attributed to the higher CN¯ of surface Zn atom. The atomically uneven Zn (002) surface shows significantly higher HER activity than the flat Zn (002) surface as the CN¯ of the surface Zn atom is lowered. The CN¯ of surface Zn atom is proposed as a key descriptor of HER activity. Tuning the CN¯ of surface Zn atom would be a vital strategy to inhibit HER on the Zn anode surface based on the presented theoretical studies. Furthermore, this work provides a theoretical basis for the in-depth understanding of HER on the Zn surface.

During 2024-2025, global emergencies triggered intense online discourse, presenting a unique opportunity to examine how cultural factors shape emotional expression and knowledge dissemination. Understanding these dynamic mechanisms is crucial for enhancing the effectiveness of digital health communication and optimizing crisis response strategies. We analyzed how cultural and linguistic contexts influence emotional expression and thematic framing in social media comments during major emergencies in 2024-2025. We uncovered cross-cultural differences in collective emotions and narrative focuses, explaining how affective stance and discourse framing jointly shape the public construction of crisis meaning. We used a cross-sectional, convergent mixed methods design. Data were collected retrospectively from X (formerly Twitter; X Corp) and Weibo (Sina Weibo) between January 1 and December 31, 2024. Using purposive sampling, we selected 5-6 representative emergency events per month based on online visibility (capped at 600 comments/event). The dataset included 19,813 comments from X and 6536 comments from Weibo. Emotions were identified using a Cross-lingual Language Model-Robustly optimized Bidirectional Encoder Representations from Transformers approach, and thematic patterns were extracted with Bidirectional Encoder Representations from Transformers Topic. Integrated Gradients was used to interpret model outputs, while clustering and network analysis were applied to visualize cross-cultural patterns. Hofstede's cultural dimensions theory helped interpret cultural influences on discourse. This mixed computational approach enabled a detailed comparison of emotional structures and thematic discourse across linguistic communities. Significant cross-platform differences were observed in emotional distribution (χ² =8025.60; P<.001). Compared to X users, Weibo users, representing a collectivist culture, expressed concentrated negative emotions (20.37%; odds ratio [OR] 15.76, 95% CI 13.90-17.85), surprise (19.70%; OR 2.53, 95% CI 2.32-2.73), and fear (16.68%; OR 1.72, 95% CI 1.58-1.86), reflecting group-oriented anxiety and emotional contagion. In contrast, X (formerly Twitter) users in individualist contexts displayed dispersed sarcasm (43.49%; OR 55.19, 95% CI 43.95-69.21) and worry (15.30%; OR 55.27, 95% CI 34.74-87.88), indicating personalized and critical emotional styles. Topic modeling revealed dense clusters around \"safety,\" \"pray,\" and \"resettlement\" on Weibo, whereas X (formerly Twitter) comments emphasized decentralized themes of critique and responsibility. Semantic network analysis revealed a cohesive fear-prayer-rescue chain on Weibo and fragmented, debate-oriented interactions on X (formerly Twitter). Emergency discourse is not neutral but is systematically structured by cultural values that shape emotions and themes. Integrating multilingual computational and qualitative methods, we offer a replicable framework using large-scale data, moving crisis and infodemiological research beyond single-platform or survey-based approaches. Our findings advance theory-informed understanding of how cultural meaning systems translate into observable digital discourse under conditions of risk and uncertainty. They also offer practical implications for governments, public health agencies, international organizations, and digital platforms by informing culturally adaptive, platform-specific risk communication, community moderation, and crisis engagement strategies that can strengthen public trust, improve compliance with protective behaviors, and mitigate infodemic-related harms.

The impacts of interannual oscillations of the Gulf Stream (GS) on oceanic mesoscale variability are investigated using satellite observations of sea surface height (SSH) and sea surface temperature (SST) from 1993 to 2018. We show that variations in GS position, strength, and meandering status are the dominant spatiotemporal modes in regional SSH variability as they explain over 50% of the total variance. In particular, meridional shift of the GS associated with the large‐scale wind variation over the North Atlantic contributes to approximately 30% of SSH variability. We further find that this path displacement mode can drive approximately 15% of regional mesoscale variability in eddy kinetic energy and divergent eddy heat flux. This observational‐based evidence of ocean mesoscale response to GS shift infers a potentially important forcing mechanism that could drive eddy‐scale ocean variability and has far‐reaching implications for regional ocean and ecosystem dynamics in response to climate variation. Plain Language Summary The Gulf Stream (GS) is one of the most energetic current in the global ocean which plays an important role in transporting warm water from low to high latitudes to maintain earth's climate system. The region near the GS is occupied by vigorous mesoscale eddy activity which is essential for regional heat and nutrient transport. The impact of GS variation on mesoscale field is largely unknown in this important area. In this study, we systematically investigated the year‐to‐year changes of different GS properties and found that the ocean surface variability in the study region is largely driven by GS changes. We further revealed that variation in mesoscale fields is highly related to the shift of the GS path in response to large‐scale atmospheric oscillation. This observed adaptation of mesoscale activities to large‐scale forcing may have important implications for a new mechanism to explain oceanic mesoscale variability, which may shed some light on potential predictability of mesoscale activities from large‐scale observations in the GS region. Key Points The observed Gulf Stream (GS) properties drive over 50% of ocean surface variability during 1993–2018 The GS shift associated with North Atlantic Oscillation dominates regional interannual variability Meridional displacement of the GS explains approximately 15% of oceanic mesoscale variation

As a subclass of Mobile Ad hoc Networks (MANETs), Vehicle Ad hoc Networks (VANETs) possess multi-hop relay communication and dynamic topology reconstruction capabilities and are widely applied in various social activities. When they are used as clusters to perform various disaster search and rescue operations or communication relay, reliable, secure, and timely communication connectivity becomes particularly important. This paper focuses on the research of connectivity reliability in VANETs, emphasizing the impact of node movement characteristics and various failure modes on the connectivity reliability of VANETs: As a cluster, the nodes in VANETs have interactive relationships and no longer follow a random movement model, exhibiting regular movements of the network as a whole; the failure modes of nodes in VANETs include vehicular hardware/software failure, energy consumption failure, intentional attack, and isolation failure. Additionally, to optimize node communication energy consumption, the paper proposes a routing path identification algorithm. Finally, the paper presents a simulation algorithm for solving the connectivity reliability of VANETs. Through MATLAB simulation experiments, the effectiveness and correctness of the proposed algorithm are verified, and it is found that the attraction distance between nodes has a certain impact on the isolation failure mode and connectivity reliability.

As the core carrier of cognitive construction, the design optimization of campus learning space is crucial to the improvement of education quality, but the existing research focuses on the analysis of behavioral preferences and lacks an in-depth analysis of the psychological dynamics of users. Through multimodal questionnaires and spatiotemporal tracking, we developed an ‘expectation–perception–behavior’ framework to quantify discrepancies between users’ visual expectations and actual experiences. The results showed that blue and wood tones significantly enhanced learning efficiency; however, there was a significant difference between facility usability and sound insulation. Based on this, dynamic environment adjustment, virtual reality preview, and modular flexible space strategies are proposed to optimize spatial performance through biophilic design and intelligent regulation. This study provides interdisciplinary methodological innovation for architecture, education, and environmental psychology and promotes the transformation of campus space, injecting new momentum into the transformation of global stock space, the construction of a sustainable education ecology, and contributing to the overall improvement of social cognitive performance.

Effective communication in English is a critical behavioral competency for seafarers in a multilingual maritime environment, directly impacting operational safety. However, a gap exists between current Maritime English (ME) training in China and the actual communication demands of global seafaring. This study aims to identify the specific ME skills including linguistic, behavioral, and sociolinguistic dimensions that are most important for on-board performance and safety management from the perspective of pre-service maritime students at Shanghai Maritime University. A mixed-methods approach was used, combining structured questionnaires (n = 313) with in-depth follow-up interviews (n = 10). The results identified 24 highly needed ME skills, particularly focused on areas governing safety-critical behaviors, such as wireless communication, security protocols, and emergency procedures. In addition, based on learner profiling, the study depicts two different learner characteristics: exam-focused and work-focused students, each with different views on the importance of skills. Work-focused students place greater emphasis on the practicality of their skills. The interview data confirms and enriches these quantitative research results. The research findings emphasize that ME courses must be more closely aligned with real-world communicative scenarios and behaviors, prioritize scenario based teaching and practical operations, and tailor differentiated teaching based on learner psychology and behavioral preference. This study offers references for maritime education institutions with similar learner profiles to optimize ME curricula, prioritize secure communication skills, and strengthen industry-education collaboration, thereby enhancing pre-service maritime students’ safety behavior and professional competitiveness in China.

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The Nitrogen Balance Index is a key indicator of crop nitrogen status, but conventional monitoring methods are invasive, costly, and unsuitable for large-scale application. This study targets early-season winter wheat in the Guanzhong Plain and proposes a framework that integrates Sentinel-2 imagery with Sen2Res super-resolution reconstruction, multi-feature optimization, and interpretable machine learning. Super-resolved imagery demonstrated improved spatial detail and enhanced correlations between reflectance, texture, and vegetation indices and the Nitrogen Balance Index compared to native imagery. A two-stage feature-selection strategy, combining correlation analysis and recursive feature elimination, identified a compact set of key variables. Among the tested algorithms, the random forest model achieved the highest accuracy, with R2 = 0.77 and RMSE = 1.57, representing an improvement of about 20% over linear models. Shapley Additive Explanations revealed that red-edge and near-infrared features accounted for up to 75% of predictive contributions, highlighting their physiological relevance to nitrogen metabolism. Overall, this study contributes to the remote sensing of crop nitrogen status through three aspects: (1) integration of super-resolution with feature fusion to overcome coarse spatial resolution, (2) adoption of a two-stage feature optimization strategy to reduce redundancy, and (3) incorporation of interpretable modeling to improve transparency. The proposed framework supports regional-scale NBI monitoring and provides a scientific basis for precision fertilization.

This study analyzes the behavioral characteristics of interactions between an experienced Chinese teacher and students in an elementary Chinese classroom through a case analysis, aiming to provide insights for novice teachers. Using the Flanders Interaction Analysis System (FIAS), this research evaluated interaction patterns in a 45 min Chinese demonstration class involving eight students from European, American, and Southeast Asian countries. The results showed the following: (1) The teacher’s speech accounted for 44.72% of class time, and they mainly used direct language to guide students. (2) Students’ speech accounted for 41.27%, showing their active participation but limited autonomy in self-initiated talk and independent engagement. Improvements are needed in students’ ability to initiate more speech and engage independently without teacher prompts. (3) Classroom structure reflects “student-centered, teacher-led” principles through open questioning and peer interaction. This study proposes some practical recommendations, advocating for increasing opportunities for student-initiated discourse, implementing structured questioning techniques, and strengthening collaborative group work. These findings provide empirical insights into balancing teacher–student interaction dynamics in cross-cultural language classrooms.