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Background: Although previous studies have found that parenting style significantly predicts emotional and behavioral problems (EBPs) among Chinese adolescents, the mechanism between different parenting styles and EBPs requires in-depth investigation. In our study, we aimed to investigate the mediating effect of resilience, a positive psychological characteristic, between parenting style and EBPs among Chinese adolescents. Methods: In this cross-sectional study, we used a multistage stratified cluster random sampling method to collect data in Shenyang, Liaoning Province from November to December 2019. Self-developed questionnaires were distributed to 1028 adolescents aged 10–18. Finally, the study consisted of 895 participants. The bootstrap method was used to investigate the role of resilience as a mediator in the relationship between different parenting styles and EBPs from a positive psychology perspective. Results: The mean score of EBPs was 12.71 (SD = 5.77). After controlling for variables such as gender, age, left-behind children, family type and family income, resilience partially played a mediating role in the associations of paternal rejection (a × b = 0.051 BCa95%CI:0.023,0.080), maternal rejection (a × b = 0.055 BCa95%CI: 0.024, 0.086), paternal emotional warmth (a × b = -0.139 BCa95%CI: -0.182, -0.099) and maternal emotional warmth (a × b = -0.140 BCa95%CI: -0.182, -0.102), with EBPs. The effect sizes were11.28%, 11.51%, 40.76%, and 38.78%, respectively. Conclusions: Resilience could partially mediate the relationship between parenting style and EBPs, highlighting that parents should adopt a positive parenting style and that resilience improvement could be effective in reducing EBPs among Chinese adolescents. [ABSTRACT FROM AUTHOR]

Metal silicides are considered promising candidates for the replacement of graphite due to their larger capacity than graphite used in Li-ion batteries. In this work, a type of lithium silicide composite material consisting of LixSi, graphite (G), and porous carbon (PC) together with carbon coating treatment, denoted as (LS-G-PC)@C, was prepared by high-energy ball milling and subsequent pitch pyrolysis. This type of material is used as a pre-lithiation additive to improve the initial Coulombic efficiency (ICE) of Si-based anodes. The microstructural characteristic of (LS-G-PC)@C composite material was analyzed by x-ray diffraction and scanning electron microscopy. The electrochemical properties were evaluated by cyclic voltammetry, electrochemical impedance spectroscopy, and capacity cycling tests. It has been found that the irregular particles of LS compounds are uniformly dispersed on the graphite sheet, which constitutes an effective conductive network together with PC. The addition of a 5 wt. % (LS-G-PC)@C pre-lithiation additive makes the ICE of a low ICE silicon-based composite material increase by 16%. At a current density of 100 mA g−1, the discharge capacity retention rate of the silicon-based composite increased from 86.1% to 91% after the 19th cycle, showing good cycle stability. Further work is to add higher levels of our pre-lithiation additive in order to improve the ICE significantly. [ABSTRACT FROM AUTHOR]

Changes in plant leaf color during development are directly related to the accumulation or degradation of certain phytochemicals such as anthocyanins. Since some anthocyanins can be beneficial to human health and provide insights into the biology of leaves, the underlying processes and timing by which plants produce these molecules has been the focus of numerous studies. The tree species Hopea hainanensis generally produces green leaves at all growth stages; however, a few explored individuals have been identified possessing red leaves on the top of the seedlings at a young stage. While the phenomenon of leaf color varying with age has been studied in several species, the underlying mechanisms are largely unknown in H. hainanensis. Using a metabolomics approach, the young red leaves in H. hainanensis were found to contain higher levels of anthocyanins and flavonoids than the young green-leaved individuals. Among anthocyanins, pelargonidin and cyanidin were the most likely candidates contributing to the red color of the young leaves. Transcriptome results indicated the genes related to the production of these anthocyanins were significantly upregulated, leading to greater accumulation of red pigments. Specifically, the expression of several MYB and bHLH genes in young red leaf lines was significantly higher than that in the young green leaf lines, especially HhMYB66 , HhMYB91 , HhMYB6 , and HhbHLH70. As such these four transcription factors are probably the main regulatory genes resulting in young red leaves in H. hainanensis. From these results, comparative analyses with other species can be made to better understand the evolution of pigment biosynthesis and how anthocyanins function in plant metabolism and evolution/adaptation. [ABSTRACT FROM AUTHOR]

In this work, NiCoO nanowires/reduced graphene oxide (NCO/RGO) composites were synthesized through a simple hydrothermal method followed by a thermal annealing process. When employed as anodes for sodium-ion batteries (SIBs), the NCO/RGO composites exhibit a high maximum capacity of 422.1 mAh g after 50 cycles at a current density of 100 mA g. Furthermore, even at a high current density of 2000 mA g, a capacity of 275.1 mAh g is still maintained, which surpasses those of most previously reported NCO. The attractive electrochemical performance of NCO/RGO composites is attributed to the synergistic effect between NCO and RGO, and enables them to be a very promising candidate for high performance SIBs. [ABSTRACT FROM AUTHOR]

The sparse representation-based classification (SRC) has been proven to be a robust face recognition method. However, its computational complexity is very high due to solving a complex -minimization problem. To improve the calculation efficiency, we propose a novel face recognition method, called sparse representation-based classification on k-nearest subspace (SRC-KNS). Our method first exploits the distance between the test image and the subspace of each individual class to determine the nearest subspaces and then performs SRC on the selected classes. Actually, SRC-KNS is able to reduce the scale of the sparse representation problem greatly and the computation to determine the nearest subspaces is quite simple. Therefore, SRC-KNS has a much lower computational complexity than the original SRC. In order to well recognize the occluded face images, we propose the modular SRC-KNS. For this modular method, face images are partitioned into a number of blocks first and then we propose an indicator to remove the contaminated blocks and choose the nearest subspaces. Finally, SRC is used to classify the occluded test sample in the new feature space. Compared to the approach used in the original SRC work, our modular SRC-KNS can greatly reduce the computational load. A number of face recognition experiments show that our methods have five times speed-up at least compared to the original SRC, while achieving comparable or even better recognition rates. [ABSTRACT FROM AUTHOR]