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Defect identification for unintentionally induced defects and radiation‐implemented defects always attracts great attention in semiconductor materials. Recent advances in carbon‐implemented single‐photon emitters in silicon urgently require the accurate identification of defect structures to reveal transition mechanisms. Using hybrid functional with finite size correction, we investigate the charge and optical transitions of carbon‐related defects, including CSiCSi, VSiCSi, CSi, SiiCSiCSi, and Ci. Except for Ci, other defects present the negative‐U feature in the charge transition process. CSiCSi and VSiCSi tend to perform p‐type conductivity with the electron capture transition close to the valence band, of which transition level ε (0/−1) is 0.30 eV for CSiCSi and ε (+1/−2) is 0.34 eV for VSiCSi. CSi and SiiCSiCSi present a bipolar doping character, and CSi tends to capture holes with transition ε (0/+2) = 0.10 eV. The optical transitions that typically emit or absorb light in the telecom optical wavelength bands are identified in these defects in terms of band edge recombination. The zero‐phonon lines of optical transitions of ε (+2/+1) for VSiCSi and Ci are consistent with a previous experiment involving single‐photon emitters. The findings are helpful to understand the performance degradation of silicon devices and provide a reference for identifying the structure of carbon‐related defects in silicon. [ABSTRACT FROM AUTHOR]

Structural variations (SVs) are a feature of plant genomes that has been largely unexplored despite their significant impact on plant phenotypic traits and local adaptation to abiotic and biotic stress. In this study, we employed woolly grape (Vitis retordii), a species native to the tropical and subtropical regions of East Asia with both coastal and inland habitats, as a valuable model for examining the impact of SVs on local adaptation. We assembled a haplotype‐resolved chromosomal reference genome for woolly grape, and conducted population genetic analyses based on whole‐genome sequencing (WGS) data from coastal and inland populations. The demographic analyses revealed recent bottlenecks in all populations and asymmetric gene flow from the inland to the coastal population. In total, 1,035 genes associated with plant adaptive regulation for salt stress, radiation, and environmental adaptation were detected underlying local selection by SVs and SNPs in the coastal population, of which 37.29% and 65.26% were detected by SVs and SNPs, respectively. Candidate genes such as FSD2, RGA1, and AAP8 associated with salt tolerance were found to be highly differentiated and selected during the process of local adaptation to coastal habitats in SV regions. Our study highlights the importance of SVs in local adaptation; candidate genes related to salt stress and climatic adaptation to tropical and subtropical environments are important genomic resources for future breeding programs of grapevine and its rootstocks. [ABSTRACT FROM AUTHOR]

The assessment and diagnosis of controller performance for model‐based closed‐loop control systems has received considerable attention in recent years. A recognized factor dilapidating the controller performance is mismatching the true dynamical model of the plant and the mathematic model employed in the controller. In order to reduce the heavy effort to re‐identify the entire model, a large amount of recent works have been focusing on locating the mismatch. To further improve the mathematic model as well as controller performance, in this article, we provide a novel prediction‐based plant‐model mismatch quantification approach, which belongs to the class of moment match methodology. In particular, two cases of output prediction are considered: one‐step ahead prediction and multistep ahead prediction. Compared with existing efforts along the same line of mismatch quantification, when using the one‐step ahead prediction, our method shows an advantage of light computational complexity. On the other hand, when utilizing multistep predictions, it shows better convergence and robustness than the former, especially in the case of structural mismatches, and the long‐term prediction capability of the model is employed. With both predictions and consideration of the existence of unknown noise models in practice, we show that the plant‐model mismatch and unknown parameters of noise models can be quantified as the solution of a minimization issue that penalizes the discrepancy between the sample of plant outputs and the predictions calculated by considering the plant‐model mismatch and noise model parameters. Several examples are provided to demonstrate the effectiveness of the proposed methods, respectively. [ABSTRACT FROM AUTHOR]

With the electrochemical performance of batteries approaching the bottleneck gradually, it is increasingly urgent to solve the safety issue. Herein, all‐in‐one strategy is ingeniously developed to design smart, safe, and simple (3S) practical pouch‐type LiNi0.8Co0.1Mn0.1O2||Graphite@SiO (NCM811||Gr@SiO) cell, taking full advantage of liquid and solid‐state electrolytes. Even under the harsh thermal abuse and high voltage condition (100 °C, 3–4.5 V), the pouch‐type 3S NCM811||Gr@SiO cell can present superior capacity retention of 84.6% after 250 cycles (based pouch cell: 47.8% after 250 cycles). More surprisingly, the designed 3S NCM811||Gr@SiO cell can efficiently improve self‐generated heat T1 by 45 °C, increase TR triggering temperature T2 by 40 °C, and decrease the TR highest T3 by 118 °C. These superior electrochemical and safety performances of practical 3S pouch‐type cells are attributed to the robust and stable anion‐induced electrode‐electrolyte interphases and local solid‐state electrolyte protection layer. All the fundamental findings break the conventional battery design guidelines and open up a new direction to develop practical high‐performance batteries. [ABSTRACT FROM AUTHOR]

This article studies the problem of prescribed‐time constrained tracking control for a class of 2×2$$ 2\times 2 $$ hyperbolic partial differential equation (PDE) systems with actuator dynamics, which are described by a set of nonlinear ordinary differential equations (ODEs). Since the control input only appears in the ODE subsystem rather than directly on the boundary of PDE subsystem, the control task becomes quite challenging. The most important is that for the control of such ODE controlled PDE systems we mainly make the following two contributions: (1) the controlled output of the PDE system tracks the reference signal within the prescribed time; (2) the controlled output and all the actuator states are constrained. It is the first time that such a prescribed‐time constrained tracking control problem is addressed for the PDE‐ODE coupled system considered in this article. Through rigorous theoretical proof, it is demonstrated that all the system states and control signals are bounded and sufficiently continuous by configuring appropriate design parameters. Finally, the performance is investigated via numerical simulation. [ABSTRACT FROM AUTHOR]

Family structure and characteristics are important factors that affect both economic development and CEOs' decision‐making. Corporate risk‐taking reflects the overall risk choices and preferences of decision‐makers in relation to various decisions. Using data for Chinese non‐state‐owned enterprises between the years 2000 and 2019, we examine the association between CEO offspring gender and corporate risk‐taking. We find that CEOs who have daughters are associated with a lower level of corporate risk‐taking than CEOs who have sons only. Raising daughters significantly stimulates cautious attitudes and behaviors in CEOs and reduces firm overinvestment, thereby lowering the level of corporate risk‐taking. Moreover, raising daughters has a more significant inhibitory effect on corporate risk‐taking for female CEOs and CEOs who were born in regions with a strong patriarchal culture. Our findings also show that CEOs with daughters can help companies effectively avoid financial crises. Focusing on both parenting behavior and corporate financial behavior, we suggest that the parent–child relationship extends far beyond the scope of the family, providing a broader perspective for understanding corporate decision‐making and financial behavior. [ABSTRACT FROM AUTHOR]

This work develops a network of adaptive boundary observers and studies the agreement between state and parameter estimates for a single target parabolic partial differential equation (PDE) system in the presence of structured and unstructured uncertainties. It is assumed that the unknown parameters take the form of either a structured uncertainty with unknown constant parameters or an unstructured uncertainty that can be neutralized by a radial basis function neural networks with unknown weights. The proposed adaptive observers consisting of m$$ m $$ agents in the network follow the structure of adaptive identifiers for the considered target PDE systems with the insertion of a penalty term in both the state and parameter estimates. Different from earlier efforts, the proposed adaptive laws include a penalty term of the mismatch between the parameter and state estimates generated by the other adjacent agents, which helps to accelerate the estimation of uncertainties. Additionally, the effects of these modifications on the agreement amongst the state and parameter estimates are investigated. Theoretical proofs are provided to show that the proposed approach guarantees the exponential convergence of estimation errors in the case of structured uncertainties and the ultimate boundedness of estimation errors in the case of unstructured uncertainties. Finally, numerical simulations are carried out to verify the effectiveness of the design methods. [ABSTRACT FROM AUTHOR]