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This study aims to enhance the performance of supercapacitors, focusing particularly on optimizing electrode materials. While pure NiMn layered double hydroxides (LDHs) exhibit excellent electrochemical properties, they have limitations in achieving high specific capacitance. Therefore, this paper successfully synthesized composite materials of NiMn LDHs with varying loadings of graphene oxide (GO) using a hydrothermal method. Systematic physicochemical characterization of the synthesized materials, such as powder X‐ray diffraction (XRD), X‐ray photoelectron spectroscopy (XPS), field‐emission scanning electron microscopy (FE‐SEM), and Raman spectroscopy, revealed the influence of GO doping on the microstructure and electrochemical performance of NiMn LDHs. Electrochemical tests demonstrated that the NiMn LDHs/GO electrode material exhibited optimal electrochemical performance with a specific capacitance of 2096 F g−1 at 1 A g−1 current density and 1471 F g−1 at 10 A g−1, when GO doping level was 0.45 wt %. Furthermore, after 1000 cycles of stability testing, the material retained 53.3 % capacitance at 5 A g−1, indicating good cyclic stability. This study not only provides new directions for research on supercapacitor electrode materials but also offers new strategies for developing low‐cost and efficient electrode materials. [ABSTRACT FROM AUTHOR]

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A new flavonoid (bunge A) (1), a new sesquiterpene (bunge B) (8), a new furan derivative (bunge C) (12) and a new alkenoic acid (bunge D) (14), together with ten known ones [four flavonoids (2, 3, 4, 5), two phenylpropanoids (6, 7), three sesquiterpenes (9, 10, 11) and one lactone (13)] were isolated from the fruits of Prunus humilis Bunge [Cerasus humilis (Bunge) Sokolov]. Their structures were elucidated based on extensive spectroscopic analysis (including HR-ESI-MS and NMR) and comparison with previously published data. All compounds were evaluated for cytotoxic activity against three human tumour cell lines. Compound 3 and 4 showed weak antiproliferative activities against hepatocarcinoma cell HepG-2 at the concentration of 100 μM, which the inhibition rates were 55.34 ± 0.29 and 45.52 ± 0.37, respectively. And other compounds had almost no cytotoxic activity against the three tumour cell lines in vitro. [ABSTRACT FROM AUTHOR]

Vocal communication plays an important role in survival, reproduction, and animal social association. Birds and mammals produce complex vocal sequence to convey context-dependent information. Vocalizations are conspicuous features of the behavior of most anuran species (frogs and toads), and males usually alter their calling strategies according to ecological context to improve the attractiveness/competitiveness. However, very few studies have focused on the variation of vocal sequence in anurans. In the present study, we used both conventional method and network analysis to investigate the context-dependent vocal repertoire, vocal sequence, and call network structure in serrate-legged small treefrogs Kurixalus odontotarsus. We found that male K. odontotarsus modified their vocal sequence by switching to different call types and increasing repertoire size in the presence of a competitive rival. Specifically, compared with before and after the playback of advertisement calls, males emitted fewer advertisement calls, but more aggressive calls, encounter calls, and compound calls during the playback period. Network analysis revealed that the mean degree, mean closeness, and mean betweenness of the call networks significantly decreased during the playback period, which resulted in lower connectivity. In addition, the increased proportion of one-way motifs and average path length also indicated that the connectivity of the call network decreased in competitive context. However, the vocal sequence of K. odontotarsus did not display a clear small-world network structure, regardless of context. Our study presents a paradigm to apply network analysis to vocal sequence in anurans and has important implications for understanding the evolution and function of sequence patterns. [ABSTRACT FROM AUTHOR]

With an aim to address the disadvantages of the artificial bee colony algorithm of slow convergence speed and ease of falling into the local optimum in the later period of the evolution process as well as to improve the traditional artificial bee colony algorithm, the concept of the "global optimum" in particle swarm optimization is introduced. Therefore, an improved artificial bee colony algorithm, called particle bee colony (PBC), is proposed herein. First, the concept of degree toward optimum is proposed for measuring the degree to which the leader approaches or is removed from the "global optimum" in a limited iteration process. The individuals' values of degree toward optimum denote their "development potentials." The individuals that have a low degree toward optimum require a great mutation extent to find a good solution. Second, a new colony of bees, initiated by the particle bee, is uniquely developed. In mutation period, the leader will be changed into the scout or the particle bee according to the value of the degree toward optimum. The appearance of particle bees can increase the population diversity and expand the search area to a large extent. Next, analysis reveals that the sequence of population of the PBC is a finite homogeneous Markov chain and the population evolution process is monotonous. On the basis of the above observations, it can be proved that the population sequence of the proposed algorithm converges to the global optimum solution set with probability 1. Last, the algorithm proposed in this study is applied to numerical simulations of several classical test functions. Furthermore, the proposed algorithm is compared with the traditional artificial bee colony algorithm and other improved bee colony algorithms. The simulation results show that PBC increases the population dispersion and broadens the search area, thereby allowing the proposed algorithm to achieve fast convergence rate and high optimization accuracy.