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This paper presents a two-time-scale human-centric microgrid optimization framework, developed based on singular perturbation theory. First, a comprehensive model is constructed, integrating the electrical characteristics of microgrid components with the evolutionary dynamics of consumer behavior. Subsequently, the system is decomposed into distinct fast and slow time scales using singular perturbation theory, enabling the effective separation of rapid electrical responses from the slower motivational dynamics of consumer behavior. Tailored optimal control strategies are then formulated for each time scale to ensure the rapid stabilization of fast system dynamics in response to transient disturbances and the gradual optimization of slow system dynamics under steady-state conditions. Finally, the proposed approach is validated through preliminary numerical simulations, which demonstrate its potential effectiveness in maintaining microgrid stability under transient conditions, facilitating behavioral adaptation, and improving operational efficiency of the microgrid. [ABSTRACT FROM AUTHOR]

Aims/Background The prevalence of postpartum fatigue among primipara is high in China, which seriously affects women's subsequent physical and mental recovery. In order to deeply understand this phenomenon, domestic scholars began to conduct research on postpartum fatigue from the aspects of assessment tools and intervention measures. This study aims to investigate postpartum fatigue in primiparous women and its association with family functioning and social support, providing valuable insights for improving the condition in this population. Methods Primiparous women from February 2023 to March 2024 were selected as participants. Baseline demographic information was collected, and postpartum fatigue levels were assessed using Postpartum Fatigue Scale (PFS) at 7 days postpartum. Social support was evaluated with Postpartum Social Support Scale, and maternal role adaptation was assessed using Maternal Role Adaptation Questionnaire (MRAQ). Pearson correlation analysis was conducted to examine the relationship between postpartum fatigue levels, role adaptation, and social support. Results A total of 210 survey questionnaires were distributed; following which, 201 valid questionnaires were received. The total PFS score was 13.93 ± 4.53 points. Among the participants, 50 cases (24.87%) experienced no fatigue, 58 cases (28.86%) with mild fatigue, 78 cases (38.81%) with moderate fatigue, and 15 cases (7.46%) with severe fatigue. There were statistically significant differences in all dimensions and total scores of the Postpartum Social Support Level Scale for primiparas with different levels of postpartum fatigue (p < 0.001), with those facing severe fatigue reporting significantly lower level of social support. There were statistically significant differences in the comparison of each dimension and total score of the role adaptation scale for primiparas with different levels of postpartum fatigue (p < 0.001). The degree of role adaptation in patients with severe fatigue was significantly lower. The PFS score of primiparas was negatively correlated with the level of social support and role adaptation (r = –0.693, r = –0.735, p < 0.001). Conclusion The majority of primiparous women experience varying degrees of postpartum fatigue at 7 days postpartum. Poor newborn health, artificial feeding, and nighttime feeding frequency ≥4 times per night can exacerbate postpartum fatigue. Good social support and role adaptation are beneficial in alleviating postpartum fatigue. Strengthening social support and role adaptation can help reduce postpartum fatigue levels in primiparous women. [ABSTRACT FROM AUTHOR]

The application of self-assembled membrane technology in metal surface corrosion protection is more and more extensive. Using simple and effective membrane technology to prepare green and environment-friendly membrane products has become a research hotspot in the field of anti-corrosion membrane. In this paper,the research progress of metal surface self-assembled film preparation technology is summarized.Taking the metal surface self-assembled monolayer membrane and its composite membrane as the research object, the classification, characteristics, applications and anti-corrosion mechanism, etc.of self-assembled membrane technology on the surface of aluminum/aluminum alloy, copper, copper alloy, stainless steel and other active metals are expounded respectively.It is pointed out that the research on the interface bonding between membrane and substrate, mechanism of film formation, mechanism of corrosion protection and so on is not perfect yet, which is still a scientific problem to be solved urgently.

Featured Application: In the realm of Intelligent Transportation Systems, accurate prediction of traffic flow is paramount for optimizing traffic management and enhancing road safety. Our research addresses the critical challenge of capturing and modeling the complex spatial–temporal correlations inherent in traffic data. While recent advancements have seen the deployment of Spatial–Temporal Graph Neural Networks (STGNNs) and transformer models to tackle this issue, our study identifies and overcomes significant limitations in existing methodologies. In the realm of Intelligent Transportation Systems (ITSs), traffic flow prediction is crucial for multiple applications. The primary challenge in traffic flow prediction lies in the handling and modeling of the intricate spatial–temporal correlations inherent in transport data. In recent years, many studies have focused on developing various Spatial–Temporal Graph Neural Networks (STGNNs), and researchers have also begun to explore the application of transformers to capture spatial–temporal correlations in traffic data. However, GNN-based methods mainly focus on modeling spatial correlations statically, which significantly limits their capacity to discover dynamic and long-range spatial patterns. Transformer-based methods have not sufficiently extracted the comprehensive representation of traffic data features. To explore dynamic spatial dependencies and comprehensively characterize traffic data, the Spatial–Temporal Fusion Embedding Transformer (STFEformer) is proposed for traffic flow prediction. Specifically, we propose a fusion embedding layer to capture and fuse both native information and spatial–temporal features, aiming to achieve a comprehensive representation of traffic data characteristics. Then, we introduce a spatial self-attention module designed to enhance detection of dynamic and long-range spatial correlations by focusing on interactions between similar nodes. Extensive experiments conducted on three real-world datasets demonstrate that STFEformer significantly outperforms various baseline models, notably achieving up to a 5.6% reduction in Mean Absolute Error (MAE) on the PeMS08 dataset compared to the next-best model. Furthermore, the results of ablation experiments and visualizations are employed to clarify and highlight our model's performance. STFEformer represents a meaningful advancement in traffic flow prediction, potentially influencing future research and applications in ITSs by providing a more robust framework for managing and analyzing traffic data. [ABSTRACT FROM AUTHOR]

In view of the input dead‐zone, unknown control direction and difficulty in satisfying the prescribed performance that suffered in practical systems, an improved prescribed performance‐based adaptive control scheme is stressed for uncertain nonlinear systems in this paper. Firstly, by adopting a characteristic function, the input dead‐zone is linearized to a model with bounded perturbation. To settle the "computation complexity" issue, an adaptive controller is built via command filter design method, where the fuzzy logic systems are introduced to approximate the unknown nonlinearities. Meanwhile, the Nussbaum function is brought in controller design to counter the hardship of unknown control direction. Besides, the tracking error can be restricted in the prescribed boundary in finite time with the improved performance function. The presented control approach can not only ensure the finite‐time convergence property of tracking error and the boundedness of all signals in the closed‐loop system, but also easily implement in engineering. Finally, the simulation examples confirm the validity of the designed control scheme. [ABSTRACT FROM AUTHOR]