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Conductive porous carbons are promising sulfur host materials for improving mass and areal capacities in lithium-sulfur (Li–S) batteries, but they face a few congenital deficiencies, such as low tap density and weak entrapment ability toward lithium polysulfides (LiPS), resulting in poor volumetric performance. Herein, we report a self-supporting cathode based on electrochemical active graphene-like RuO2 (GRO) without the incorporation of any carbon hosts and additives to synchronously acquire high mass, areal and volumetric capacities. It has been certified that dynamic evolutions of both conductive GRO host and sulfur guest during cell operation expedite chemisorption/conversion of LiPS and regulate nucleation/growth of solid Li2S, which enables GRO-S with medium sulfur loading to achieve an almost theoretical capacity at 0.2 C. Remarkably, the electrode with higher sulfur loading of 8.4 mg cm−2 delivers mass, areal and volumetric capacities of 1225 mAh g−1, 10.3 mAh cm−2 and 1981 mAh cm−3 at 0.2 C, respectively. The volumetric capacity records the highest value in reported Li–S batteries. The cathode material reported in this work opens new avenues for the development of high-energy-density and long-life Li–S batteries.

In statistics mean absolute deviation plays an important role in measuring spread of a data. In this paper, we focus on using the jackknife, the adjusted and the extended jackknife empirical likelihood methods to construct confidence intervals for the mean absolute deviation of a random variable. The empirical log-likelihood ratio statistic is derived whose asymptotic distribution is a standard chi-square distribution. The results of simulation study show the comparison of the average length and coverage probability by using jackknife empirical likelihood methods and normal approximation method. The proposed adjusted and extended jackknife empirical likelihood methods perform better than other methods, in particular for skewed distributions. We use real data sets to illustrate the proposed jackknife empirical likelihood methods.

Complete mitochondrial genome plays an important role in the accurate revelation of phylogenetic relationships among metazoans. Here we present the complete mitochondrial genome sequence from a sea cucumber Apostichopus japonicus (Echinodermata: Holothuroidea), which is the first representative from the subclass Aspidochirotacea. The mitochondrial genome of A. japonicus is 16,096 bp in length. The heavy strand consists of 31.8% A, 20.2% C, 17.9% G, and 30.1% T bases (AT skew = 0.027: GC skew = 0.062). It contains thirteen protein-coding genes (PCGs), twenty-two transfer RNA genes, and two ribosomal RNA genes. There are a total of 3793 codons in all thirteen mitochondrial PCGs, excluding incomplete termination codons. The most frequently used amino acid is Leu (15.77%), followed by Set (9.73%), Met (8.62%), Phe (7.94%), and Ala (7.28%). Intergenetic regions in the mitochondrial genome of A. japonicus are 839 bp in total, with three relatively large regions of Unassigned Sequences (UAS) greater than 100 bp. The gene order of A. japonicus is identical to that observed in the five studied sea urchins, which confirms that the gene order shared by the two classes (Holothuroidea and Echinoidea) is a ground pattern of echinoderm mitochondrial genomes. Bayesian tree based on the cob gene supports the following relationship: (outgroup, (Crinoids, (Asteroids, Ophiuroids, (Echinoids, Holothuroids)))). (C) 2009 Elsevier B.V. All rights reserved.

Interest in meshfree (or meshless) methods has grown rapidly in recent years in solving boundary value problems (BVPs) arising in mechanics, especially in dealing with difficult problems involving large deformation, moving discontinuities, etc. In this paper, we provide a theoretical analysis of the reproducing kernel particle method (RKPM), which belongs to the family of meshfree methods. One goal of the paper is to set up a framework for error estimates of RKPM. We introduce the concept of a regular family of particle distributions and derive optimal order error estimates for RKP interpolants on a regular family of particle distributions. The interpolation error estimates can be used to yield error estimates for RKP solutions of BVPs.