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Retrieving the fine‐mode fraction (FMF) of aerosol optical depth from satellite data is crucial for understanding the impact of natural versus anthropogenic aerosols on climate and air quality. However, few high‐quality global FMF products from MODIS exist. To address this gap, this study derives a new formulation of FMF as a function of the Ångström exponent (AE) based on over 20 years of AERONET measurements. Our results reveal a consistent FMF‐AE relationship across continental regions, supporting the feasibility of globally estimating FMF through a simple empirical function based on AE. Validation with independent NOAA GML data sets shows predicted FMF errors mostly within 0.1. Finally, applying this parameterization to MODIS Aqua and Terra data significantly improved satellite‐derived FMF agreement with AERONET compared to previous derivations. This parameterization provides a simple, valuable tool for accurately deriving FMF over land from MODIS and understanding its impact on climate and air quality. Plain Language Summary Aerosols are liquid and solid particles suspended in the atmosphere, with sizes ranging from a few nanometers to tens of micrometers. These particles, produced by natural sources or human activities, play a significant role in air quality and climate. Estimating aerosol size distributions is important for understanding their climate and environmental impacts. However this remains challenging on regional and global scales due to the difficulties in retrieving this information from satellite observations. To address this, we created a parameterization that predicts the fraction of fine particles based on the measured spectral variation of light extinction by aerosols, known as the Ångström exponent (AE). By analyzing 20 years of ground‐based sunphotometer data, we found a reliable pattern between AE and fine particle fraction. We then tested this method with in situ nephelometer data, and confirmed its accuracy. Finally, we applied our formula to satellite data, achieving better agreement with ground‐based observations compared to previous parameterization efforts. Our formula can help scientists understand air pollution and its climate effects more accurately using satellite and ground‐based data independently of location. Key Points A parameterization linking the fine‐mode fraction of aerosol optical depth to the Angstrom exponent was developed using AERONET data Validation of this parameterization with independent in situ nephelometer measurements demonstrates strong predictive capability Applying this parameterization to MODIS satellite data improves the predictive accuracy for fine‐ and coarse‐mode aerosol optical depth

China is transitioning from an immigrant-exporting country to an immigrant-importing country. To attract and retain global, it is necessary to analyze the factors influencing the settlement intentions of high skilled migrants to formulate policy support and tailor the management of transnational communities to their characteristics. This study used the Changchun sample from the Survey on Foreign Residents in China (SFRC 2017–2019) to examine the influence of social networks and social engagement on settlement intentions. It also considered differences in the classification of social networks and engagement strength, as well as classification by country of origin. This study identified that social networks and social engagement in the destination country play an essential role in the willingness of high skilled migrants to stay in Changchun. Additionally, international enclaves negatively affected their willingness to stay. Furthermore, the relative strength of migrants’ social networks and social engagement in the destination country exerted varying effects on the intensity of their settlement intentions. That is, using high skilled migrants with strong Chinese social networks and social engagement as the reference group, relying solely on a strong social network in China while lacking social engagement significantly reduced their willingness to settle. A weak social networks and low social engagement also significantly decreased their willingness to settle. Moreover, settlement intentions of the high skilled migrants differed significantly by country of origin. If we selected the same reference term, the willingness of expatriates from developed countries to stay decreased significantly. In the sections concerning comparison and robustness checks, national data were employed (SFRC 2019). Highly skilled expatriates in Guangzhou, Hangzhou, and Yiwu demonstrated the synergistic interaction between ethnic communities and work units ( danwei) , whereas those in Changchun exhibited a certain uniqueness, embedding themselves in Chinese society through their own human capital and danwei affiliations.

Constrained by traditional fuel-saving technologies that have almost reached the limit of fuel-saving potential, the difficulty in changing urban congestion, and the low market penetration rate of new energy vehicles, in the short term, eco-driving seems to be an effective way to achieve energy-saving and emissions reduction in the transportation industry. This paper reviews the energy-saving theory and technology of eco-driving, eco-driving capability evaluation, and the practical application of eco-driving, and points out some limitations of previous studies. Specifically, the research on eco-driving theory mostly focuses on a single vehicle in a single scene, and there is a lack of eco-driving research for fleets or regions. In addition, the parameters used to evaluate eco-driving capabilities mainly focus on speed, acceleration, and fuel consumption, but external factors that are not related to the driver will affect these parameters, making the evaluation results unreasonable. Fortunately, vehicle big data and the Internet of Vehicles (V2I) provides an information basis for solving regional eco-driving, and it also provides a data basis for the study of data-driven methods for the fair evaluation of eco-driving. In general, the development of new technologies provides new ideas for solving some problems in the field of eco-driving.

Resilience is the individual's ability to bounce back from trauma. It has been studied for some time in the U.S., but few studies in China have addressed this important construct. In mainland China, relatively little is known about the resilience of patients in clinical settings, especially among patients with breast cancer. In this study, we aimed to evaluate the level of resilience and identify predictors of resilience among mainland Chinese women newly diagnosed with breast cancer. A cross-sectional descriptive study was conducted with 213 mainland Chinese women newly diagnosed with breast cancer between November 2014 and June 2015. Participants were assessed with the Connor-Davidson Resilience Scale (CD-RISC), Social Support Rating Scale (SSRS), Medical Coping Modes Questionnaire (MCMQ, including 3 subscales: confrontation, avoidance, and acceptance-resignation), Herth Hope Index (HHI), and demographic and disease-related information. Descriptive statistics, bivariate analyses and multiple stepwise regression were conducted to explore predictors for resilience. The average score for CD-RISC was 60.97, ranging from 37 to 69. Resilience was positively associated with educational level, family income, time span after diagnosis, social support, confrontation, avoidance, and hope. However, resilience was negatively associated with age, body mass index (BMI), and acceptance-resignation. Multiple stepwise regression analysis indicated that hope (β = 0.343, P<0.001), educational level of junior college or above (β = 0.272, P<0.001), educational level of high school (β = 0.235, P<0.001), avoidance (β = 0.220, P<0.001), confrontation (β = 0.187, P = 0.001), and age (β = -0.108, P = 0.037) significantly affected resilience and explained 50.1% of the total variance in resilience. Women with newly diagnosed breast cancer from mainland China demonstrated particularly low resilience level, which was predicted by hope educational level, avoidance, confrontation, and age.

The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes a method to optimize the layout of sensors rationally. Firstly, this paper constructs a dual-objective model based on the accuracy and robustness indexes. Then, an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm is developed for this model, which introduces initialization strategy, the adaptive inertia weight strategy, the guided particle selection strategy and the external candidate solution (ECS) set maintenance strategy to multi-objective particle swarm optimization (MOPSO). Afterwards, the performance of IAMOPSO is verified by comparing with MOPSO applied on the existing inverse beam model. Finally, the IAMOPSO is employed to the deformation reconstruction of complex plate-beam model. The numerical and experimental results demonstrate that the IAMOPSO is an excellent tool for sensor layout in iFEM.

Chemical pollution threatens human health and ecosystem sustainability. Persistent organic pollutants (POPs) like per- and polyfluoroalkyl substances (PFAS) are expensive to clean up once emitted. Innovative and synergistic strategies are urgently needed, yet process integration and cost-effectiveness remain challenging. An in-situ PFAS remediation system is developed to employ a plant-derived biomimetic nano-framework to achieve highly efficient adsorption and subsequent fungal biotransformation synergistically. The multiple component framework is presented as Renewable Artificial Plant for In-situ Microbial Environmental Remediation (RAPIMER). RAPIMER exhibits high adsorption capacity for the PFAS compounds and diverse adsorption capability toward co-contaminants. Subsequently, RAPIMER provides the substrates and contaminants for in situ bioremediation via fungus Irpex lacteus and promotes PFAS detoxification. RAPIMER arises from cheap lignocellulosic sources, enabling a broader impact on sustainability and a means for low-cost pollutant remediation. Persistent organic pollutant (POP) remediation is important for protecting the environment and human health but can be expensive. Here, the authors report on the creation of a plant-based remediation material which can absorb high levels of POPs and then provide the nutrients needed for fungal degradation and detoxification.

Background Peer-assisted learning (PAL) has been widely implemented for many years worldwide. To further enhance the understanding of available data, a scoping review of systematic reviews was conducted to synthesize existing evidence on the effectiveness of PAL in health professional education, aiming to provide more comprehensive outcomes. Methods Nine databases were systematically searched. The review process was guided by the five-stage scoping review framework proposed by Arksey and O’Malley. The JBI Critical Appraisal Checklist for Systematic Reviews and Research Syntheses was used to assess the methodological quality. The results were narratively synthesized and reported following the Context, Input, Process, and Product (CIPP) evaluation model. Results 24 systematic reviews (including nine meta-analyses) were included. The majority of these reviews were synthesized using narrative analysis. The application of PAL in health professional education was developed. In the context of evaluation, support for the theory, problem-based drivers, and the need to develop teaching and assessment skills for students were the main reasons for the development of PAL. Inputs for PAL predominantly centered on tutor recruitment and tutor training. Common activities within the PAL process encompassed peer teaching, peer tutoring, peer feedback, peer simulation, peer discussion, peer-led debriefing, peer supervision, and curriculum design. Outcomes of PAL were categorized across peer tutees, peer tutors, health professional educators, and challenges of PAL. Conclusions Despite certain challenges, the reciprocal benefits of PAL for peer tutees and tutors are evident. It is recommended that relevant institutions should consider incorporating PAL into the curriculum for health professional students. Future research should aim to develop a more rigorous framework to determine the short- and long-term effects, cost-effectiveness, and generalizability of PAL in health professional education.

This study made an intercomparison of two model climates, simulated by a unified weather-climate model system (GRIST), under the Atmospheric Model Intercomparison Project (AMIP) experimental protocol. These two model AMIP simulations with PhysW and PhysC (AMIPW and AMIPC hereafter) are configured with different physics suites, but both generated by a unified dynamical core framework. PhysW and PhysC are originally designed for weather forecasting and climate simulation, respectively. Both AMIPW and AMIPC reach statistical equilibrium in the climate integration. They overall produce comparable model climates, while distinctive bias features also exist. Compared with the AMIP experiments of 54 climate models from CMIP6, both AMIPW and AMIPC demonstrate competitive performances in the mean state simulations. They capture the observed spatial distribution of large-scale circulation and precipitation, as well as replicate the seasonal migration and primary frequency-intensity structures of precipitation. However, due to different parameterization schemes such as convection and microphysics being utilized, the most notable differences between the models lie in processes related to moist physics. For instance, AMIPW tends to overestimate (underestimate) global shortwave (longwave) cloud radiative forcing, while AMIPC provides a more balanced estimation, with a significantly stronger longwave cloud radiative forcing over the tropics. In addition, AMIPC well reproduces cloud fraction and liquid content but underestimates cloud ice water content, whereas AMIPW significantly overestimates all these variables. Overall, the similarity between two model climates is higher than their discrepancy. The results demonstrate that the extent to which the selection of two distinct physics suites can influence the simulated model climate, within a unified model system.

Background Education has been recognised as necessary in forming and internalising professional values. The system and instructors' content in existing educational institutions focus on developing students' knowledge, skills and practices. Still, the development of values has yet to achieve significant effects, leading to a crisis in students' professional identity. Aims To construct a professional values growth theory for undergraduate nursing students and develop a corresponding education framework. Methods Through the review, some databases(PubMed、CINAHL、Web of Science、Wiley and Google Scholars)were searched using a systematic search strategy to collect relevant literature on professional values education. Based on the nursing professional values growth theory (Li and Li, Nursing Ethics In press, 2022), a theory of professional values growth of nursing undergraduates was developed using the method of theory derivation. Two rounds of expert meetings were conducted to review and revise an education framework of professional values of nursing undergraduates derived from that theory. Findings A total of 10 studies were included. The contents of two themes were analysed: theories and models and the current status of the professional values development of nursing students. The resulting professional values growth theory for undergraduate nursing students consists of five parts: key aspects, decisive opportunities, drivers, embodiment (humanistic sentiments, moral emotions), and outcomes. A total of five experts in the relevant fields were invited to this study. After two rounds of expert meetings, an education framework for undergraduate nursing students was finally developed, which consists of four parts: education objectives, education process and content, environment and conditions, and evaluation. Conclusion The education framework developed in this study has practical implications for the development of professional values of undergraduate nursing students, providing educational strategies and methods for the growth and internalisation of professional values of undergraduate nursing students.

Background Academic resilience can help students overcome academic setbacks or pressure and become a qualified nurse. However, few studies have explored the academic resilience of graduate nursing students and its related factors. Aim To assess the level of academic resilience among graduate nursing students and its associated factors. Design A cross-sectional design. Methods From July 2024 to September 2024, 345 graduate nursing students from 4 nursing colleges were investigated. We developed the Academic Resilience Scale for Graduate Nursing Students (ARSGNS) and evaluated its reliability and validity. The article detailing its development was published in BMC nursing. The general information questionnaire, Academic Resilience Scale, Research Competency Scale and Supportive Communication Scale were used to investigate. Descriptive statistical analysis, correlation analysis and hierarchical multiple regression analysis were performed to determine the associated factors. Findings The average score of academic resilience of nursing graduates was (90.24 ± 11.93). Having role models, student leadership experience, research competency, and communication competency were associated with academic resilience and together explained 39.7% of the variance. Conclusion The academic resilience of most graduate nursing students was at a medium level, and there is still a lot of room for improvement. Whether there is a role model, student leader experience, research competency and communication ability were significantly associated factors of academic resilience. Impact This study identified the level of academic resilience of graduate nursing students and its associated factors, suggesting that nursing educators should pay attention to the academic resilience of students during their graduate study period, integrate role model education into the daily teaching process, let every student have the opportunity to become a team leader as much as possible, and pay attention to improving the research competency and communication skills of graduate nursing students. So as to help students more effectively overcome academic pressure. Reporting method STROBE guidelines. Patient or public contribution No patient or public contribution. Clinical trial number Not applicable.