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BackgroundThe major depressive disorder has high prevalence among adolescents， and non-suicidal self-injury （NSSI） behaviors frequently occur among patients， therefore， major depressive disorder in adolescents has become the researching focus.ObjectiveTo explore the effect of mentalization-based family therapy （MBFT） on depressive symptoms and NSSI behavior in adolescents with major depressive disorder， and to provide references for the rehabilitation of major depressive disorder in adolescents.MethodsA total of 90 adolescent patients with major depression disorder who met the diagnostic criteria of International Classification of Diseases， 10th edition （ICD-10） for depressive disorders and attended Wuhan Mental Health Center from January to December 2022 were selected， and were assigned into study group （n=44） and control group （n=46） using random number table method. All participants received routine intervention， based on this， study group added a 60-minute MBFT intervention once a week for 8 weeks. Before the intervention and at the end of 1st， 2nd，4th and 8th week，the two groups were assessed using Hamilton Depression Scale-24 item （HAMD-24）， General Self-Efficacy Scale （GSES）， Pittsburgh Sleep Quality Index （PSQI） and Ottawa Self-injury Inventory （OSI）.ResultsThe repeated measures analysis of variance reported a statistical main effect of time， main effect of group， and interaction effect between time and group at the baseline and the end of 1st， 2nd， 4th and 8th week of treatment in HAMD-24 score （F=69.621， 15.428， 29.623， P˂0.05）， OSI score （F=176.642， 37.682， 21.873， P˂0.05）， GSES score （F=215.236， 57.421， 27.857， P˂0.05） and PSQI score （F=268.541， 61.863， 33.867， P˂0.05）. Individual effect analysis discovered a statistical difference between study group and control group at the end of 2nd， 4th and 8th week of treatment in HAMD-24 score （t=5.567， 8.645， 6.233， P˂0.01）， OSI score （t=3.675， 11.817， 9.632， P˂0.01）， GSES score （t=23.462， 31.709， 12.750， P˂0.01） and PSQI score （t=9.664， 22.457， 9.333， P˂0.01）.ConclusionMBFT may improve depressive symptoms， NSSI behavior， sleep quality and self-efficacy in adolescents with major depressive disorder. ［Funded by 2022 Natural Science Foundation Project of Hubei Province （number， 2022CFB483）］

Due to the huge composition space, composition screening is of great importance to the optimization of high‐entropy diborides (HEBs) with exceptional oxidation resistance. However, related studies are lacking. Here, a novel rapid, effective strategy to fully screen the compositions on the oxidation resistance of HEBs is proposed. Specifically, the synthesis of the equiatomic 1‐ to 9‐cation multicomponent diborides of the IVB, VB, and VIB groups in seconds via an ultrafast ultrahigh‐temperature synthesis technique is realized. Subsequently, combined with the thermogravimetric analysis and first‐principles calculations, the roles of incorporated elements are systematically explored. The results show that Zr, Cr, Ta, Nb, and W elements are the key to the improved oxidation resistance of HEBs, while Ti, Mo, and V elements are destructive. In particular, the positive roles of metal elements are mainly attributed to the partial dissolution of the generated metal oxides into the generated B2O3 glass, which can improve the viscosity of B2O3 and thus enhance its high‐temperature stability and reduce the oxygen diffusion rate, as confirmed by the first‐principles calculations. This study paves a way to rapidly screen the elements in HEBs, which can be a guide for further anti‐oxidation designs. [ABSTRACT FROM AUTHOR]

In order to extract characteristics of partial discharge signals, the paper proposed an adaptive threshold algorithm for processing partial discharge data by using ensemble empirical mode decomposition method for analysis of XLPE cable partial discharge signals. Firstly, partial discharge signals containing noise are decomposed into a number of independent mode function components by ensemble empirical mode decomposition method, and then adaptive threshold processing and reconstruction of the resulting mode function component were carried out to suppress noise. The algorithm overcomes mode mixing problem of empirical mode decomposition method, and simulation and measuring data verify its correctness and feasibility.