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In recent years, exploring the physical mechanisms of brain functions has been a hot topic in the fields of nonlinear dynamics and complex networks, and many important achievements have been made, mainly based on the characteristic features of time series of human brain. To speed up the further study of this problem, herein we make a brief review on these important achievements, which includes the aspects of explaining: (i) the mechanism of brain rhythms by network synchronization, (ii) the mechanism of unihemispheric sleep by chimera states, (iii) the fundamental difference between the structural and functional brain networks by remote synchronization, (iv) the mechanism of stronger detection ability of human brain to weak signals by remote firing propagation, and (v) the mechanism of dementia patterns by eigen‐microstate analysis. As a brief review, we will mainly focus on the aspects of basic ideas, research histories, and key results but ignore the tedious mathematical derivations. Moreover, some outlooks will be discussed for future studies. [ABSTRACT FROM AUTHOR]

Against the backdrop of the gradually exposed credit bond default risk in China, how to accurately identify and efficiently warn of corporate bond default risk has become a key concern for both academia and practice. To effectively solve a series of key problems in the traditional credit risk warning model, such as insufficient warning performance, single optimization target of hyperparameters, and weak model interpretability, this study integrates machine learning algorithms such as LightGBM, NSGA- II, and SHAP to constructs a LightGBM-NSGA- II-SHAP for early warning of corporate bond default risk, and empirically analyzes and tests the warning performance of the proposed model. The research results show that the warning accuracy of the proposed model exceed 85%, and compared with traditional machine learning models, the warning performance of the proposed model in this study is more excellent. In addition, the impact of visualization of warning features on warning results is demonstrated through the SHAP algorithm, and it is found that coupon interest rate, profit margin on fixed assets, total issuance, and receivable turnover etc. are the key features for identifying corporate bond defaults. [ABSTRACT FROM AUTHOR]

Summary: A fast evolution within mitochondria genome(s) often generates discords between nuclear and mitochondria, which is manifested as cytoplasmic male sterility (CMS) and fertility restoration (Rf) system. The maize CMS‐C trait is regulated by the chimeric mitochondrial gene, atp6c, and can be recovered by the restorer gene ZmRf5. Through positional cloning in this study, we identified the nuclear restorer gene, ZmRf5, which encodes a P‐type pentatricopeptide repeat (PPR) family protein. The over‐expression of ZmRf5 brought back the fertility to CMS‐C plants, whereas its genomic editing by CRISPR/Cas9 induced abortive pollens in the restorer line. ZmRF5 is sorted to mitochondria, and recruited RS31A, a splicing factor, through MORF8 to form a cleaving/restoring complex, which promoted the cleaving of the CMS‐associated transcripts atp6c by shifting the major cleavage site from 480th nt to 344 th nt for fast degradation, and preserved just right amount of atp6c RNA for protein translation, providing adequate ATP6C to assembly complex V, thus restoring male fertility. Interestingly, ATP6C in the sterile line CMo17A, with similar cytology and physiology changes to YU87‐1A, was accumulated much less than it in NMo17B, exhibiting a contrary trend in the YU87‐1 nuclear genome previously reported, and was restored to normal level in the presence of ZmRF5. Collectively these findings unveil a new molecular mechanism underlying fertility restoration by which ZmRF5 cooperates with MORF8 and RS31A to restore CMS‐C fertility in maize, complemented and perfected the sterility mechanism, and enrich the perspectives on communications between nucleus and mitochondria. [ABSTRACT FROM AUTHOR]

As an emerging concept, employee green advocacy has received increasing attention in the research of marketing and business circles. However, few studies have examined the influence of green human resource management (GHRM) on employee green advocacy. Therefore, this study aims to explore the influence of GHRM on employee green advocacy and investigates the mediation role of green passion and the moderator role of supervisory support for the environment. Data collected from 334 employees from 15 companies in China at three time points. The results suggest that GHRM positively impacts green passion and employee green advocacy, green passion positively impacts employee green advocacy, green passion partially mediates the relationship between GHRM and employee green advocacy. Additionally, supervisory support for the environment moderates the positive relationship between GHRM and green passion and employee green advocacy. [ABSTRACT FROM AUTHOR]