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Summary: Soybean is a short‐day plant that typically flowers earlier when exposed to short‐day conditions. However, the identification of genes associated with earlier flowering time but without a yield penalty is rare. In this study, we conducted genome‐wide association studies (GWAS) using two re‐sequencing datasets that included 113 wild soybeans (G. soja) and 1192 cultivated soybeans (G. max), respectively, and simultaneously identified a candidate flowering gene, qFT13‐3, which encodes a protein homologous to the pseudo‐response regulator (PRR) transcription factor. We identified four major haplotypes of qFT13‐3 in the natural population, with haplotype H4 (qFT13‐3H4) being lost during domestication, while qFT13‐3H1 underwent natural and artificial selection, increasing in proportion from 4.5% in G. soja to 43.8% in landrace and to 81.9% in improve cultivars. Notably, most cultivars harbouring qFT13‐3H1 were located in high‐latitude regions. Knockout of qFT13‐3 accelerated flowering and maturity time under long‐day conditions, indicating that qFT13‐3 functions as a flowering inhibitor. Our results also showed that qFT13‐3 directly downregulates the expression of GmELF3b‐2 which is a component of the circadian clock evening complex. Field trials revealed that the qft13‐3 mutants shorten the maturity period by 11 days without a concomitant penalty on yield. Collectively, qFT13‐3 can be utilized for the breeding of high‐yield cultivars with a short maturity time suitable for high latitudes. [ABSTRACT FROM AUTHOR]

In this paper, the event‐triggered distributed consensus tracking control problem for a class of multi‐agent systems (MASs) is studied, where denial‐of‐service (DoS) attacks and Bouc‐Wen hysteresis inputs are considered in the communication channel and the actuator, respectively. First, when communication networks are subject to malicious DoS attacks, the connection weights of the communication topology graphs are affected. To address this problem, this paper establishes topological models of the communication network using a switching topology method, and gives connection recovery strategies for the communication network. Second, in order to save communication resources, a distributed control protocol based on an event‐triggered mechanism and locally deployed estimator is designed for DoS signals occurring in the communication network of states and control inputs. In addition, the effect of unknown Bouc–Wen hysteresis input is eliminated using the Nussbaum‐type function. Then, based on Lyapunov stability theory, the boundedness of all signals in the closed‐loop system is verified, and the objective of consensus control is achieved. Finally, the effectiveness of the proposed control scheme is demonstrated by numerical and practical simulation examples. [ABSTRACT FROM AUTHOR]

The habenula (Hb) is involved in many natural human behaviors, and the relevance of its alterations in size and neural activity to several psychiatric disorders and addictive behaviors has been presumed and investigated in recent years using magnetic resonance imaging (MRI). Although the Hb is small, an increasing number of studies have overcome the difficulties in MRI. Conventional structural‐based imaging also has great defects in observing the Hb contrast with adjacent structures. In addition, more and more attention should be paid to the Hb's functional, structural, and quantitative imaging studies. Several advanced MRI methods have recently been employed in clinical studies to explore the Hb and its involvement in psychiatric diseases. This review summarizes the anatomy and function of the human Hb; moreover, it focuses on exploring the human Hb with noninvasive MRI approaches, highlighting strategies to overcome the poor contrast with adjacent structures and the need for multiparametric MRI to develop imaging markers for diagnosis and treatment follow‐up. Level of Evidence: 3 Technical Efficacy Stage: 2 [ABSTRACT FROM AUTHOR]

The secondary cooling water flow and the cast slab surface temperature can directly affect the quality of the slab. To address the above problems, the group has developed a wavelet weight-twin support vector machine (WTWTSVR) based model for predicting the secondary cooling water flow and the cast slab surface temperature. Compared with traditional machine learning algorithms, the model has the advantages of strong generalization ability, fast computation speed, and good fitting effect, effectively overcoming the disadvantages of multiple locally optimal solutions, equal weights, and easy overfitting that may exist in traditional neural network forecasting algorithms. To reduce the influence of noise interference on the actual data, a wavelet transform-based weighted algorithm (WTW) is introduced on the basis of a twin support vector machine algorithm, and the data is processed by noise reduction using wavelet analysis, while the reconstructed signal is given weights to avoid the overfitting phenomenon. The production practice shows that the prediction accuracy of the model is 92.6% and 93.5% for 200 furnace times (200 groups of samples); the prediction accuracy is 96.2% and 96.3% for secondary cooling water flow rate and casting slab surface temperature within the error range of ±5% and ±10%, respectively. The double hit rate within different error ranges within 10 °C reached 90.4%, which can fully meet the actual production requirements of a steel mill, and also provide guidance for the forecast of the flow rate of the secondary cooling water and the cast slab surface temperature. [ABSTRACT FROM AUTHOR]