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One of the major obstacles hindering the application of zinc metal batteries is the contradictory demands from the Zn metal anode and cathodes. At the anode side, water induces serious corrosion and dendrite growth, remarkably suppressing the reversibility of Zn plating/stripping. At the cathode side, water is essential because many cathode materials require both H+ and Zn2+ insertion/extraction to achieve a high capacity and long lifespan. Herein, an asymmetric design of inorganic solid-state electrolyte combined with hydrogel electrolyte is presented to simultaneously meet the as-mentioned contrary requirements. The inorganic solid-state electrolyte is toward the Zn anode to realize a dendrite-free and corrosion-free highly reversible Zn plating/stripping, and the hydrogel electrolyte enables consequent H+ and Zn2+ insertion/extraction at the cathode side for high performance. Therefore, there is no hydrogen and dendrite growth detected in cells with a super high-areal-capacity up to 10 mAh·cm−2 (Zn//Zn), ~5.5 mAh·cm−2 (Zn//MnO2) and ~7.2 mAh·cm−2 (Zn//V2O5). These Zn//MnO2 and Zn//V2O5 batteries show remarkable cycling stability over 1000 cycles with 92.4% and over 400 cycles with 90.5% initial capacity retained, respectively. While Zinc anodes are thermodynamically unstable in aqueous solutions, the protons (H+) from the water favor the cathodes of Zinc batteries. Here, the authors address this contradiction by designing an asymmetric electrolyte composed of an inorganic solid-state electrolyte and a hydrogel electrolyte. [ABSTRACT FROM AUTHOR]

A permutation is happy, if it can be transformed into the identity permutation using as many short swaps as one third times the number of inversions in the permutation. The complexity of the decision version of sorting a permutation by short swaps, is still open. We present an O(n) time algorithm to decide whether it is true for a permutation to be happy, where n is the number of elements in the permutation. If a permutation is happy, we give an O (n 2) time algorithm to find a sequence of as many short swaps as one third times the number of its inversions, to transform it into the identity permutation. A permutation is lucky, if it can be transformed into the identity permutation using as many short swaps as one fourth times the length sum of the permutation's element vectors. We present an O(n) time algorithm to decide whether it is true for a permutation to be lucky, where n is the number of elements in the permutation. If a permutation is lucky, we give an O (n 2) time algorithm to find a sequence of as many short swaps as one fourth times the length sum of its element vectors to transform it into the identity permutation. This improves upon the O (n 2) time algorithm proposed by Heath and Vergara to decide whether a permutation is lucky. We show that there are at least 2 ⌈ n 2 ⌉ - 2 happy permutations as well as 2 n - 4 lucky permutations of n elements. [ABSTRACT FROM AUTHOR]

Ultrathin oxides have been reported to possess excellent properties in electronic, magnetic, optical, and catalytic fields. However, the current and primary approaches toward the preparation of ultrathin oxides are only applicable to amorphous or polycrystalline oxide nanosheets or films. Here, we successfully synthesize high-quality ultrathin antimony oxide single crystals via a substrate-buffer-controlled chemical vapor deposition strategy. The as-obtained ultrathin antimony oxide single crystals exhibit high dielectric constant (~100) and large breakdown voltage (~5.7 GV m−1). Such a strategy can also be utilized to fabricate other ultrathin oxides, opening up an avenue in broadening the applicaitons of ultrathin oxides in many emerging fields. The ultrathin oxide nanosheets obtained through previous approaches usually exhibit amorphism or polycrystallinity, which limit their properties towards electronic devices. Here, the authors synthesize ultrathin antimony oxide single crystals with high dielectric constant (~100) and large breakdown voltage (~5.7 GV m−1). [ABSTRACT FROM AUTHOR]

Aiming at the problems of parameter optimization and insufficient utilization of split reads in the detection for copy number variation (CNV), a new definition of relative read depth (RRD) and a randomized sampling strategy (RGN) are proposed in this paper. Compared to the raw read depth, the RRD parameter has weak correlation with GC content, mappability and the width of analysis windows tiled along the genome. The RGN strategy is based on the weighted sampling strategy which can speed up the read count data analysis. Subsequently, we propose an improved detection algorithm for CNV based on hidden Markov model (CNV-HMM). The HMM detects the abnormal signal of read count data and outputs the detection results of candidate CNVs. At the end of the algorithm, we filter out the results of candidate CNVs using the split reads to improve the performance of CNV-HMM algorithm. Finally, the experiment results show that our CNV-HMM algorithm has higher sensitivity and accuracy for CNVs detection than most of current detection algorithms and applicative both for diploid animal and plant. [ABSTRACT FROM AUTHOR]

Genome rearrangement problems have been extensively studied for more than two decades, intended to understand the species evolutionary relationships in terms of the long range genetic mutations at the genome level. While most earlier studies focus on the simplified genomes ignoring gene duplicates, thousands of whole genome sequencing projects reveal that a genome typically carries multiple gene duplicates distributed in various ways along the genome. Given a source genome and a target genome such that one is a re-ordering of the genes in the other, we measure the evolutionary distance by the minimum number of reversals applied on the source genome to recover all the gene adjacencies in the target genome. We define this optimization problem as sorting by reversals to recover all adjacencies, or SBR2RA in short. We show that SBR2RA is APX-hard and uncover some similarities and differences to the classic counterpart, the sorting by reversals problem. From the approximability perspective, we present a 2 α -approximation algorithm, where α ∈ [ 1 , 2 ] is the best approximation ratio for a related optimization problem which is suspected to be NP-hard. [ABSTRACT FROM AUTHOR]

The metal-free synthesis of graphene on single-crystal silicon substrates, the most common commercial semiconductor, is of paramount significance for many technological applications. In this work, we report the growth of graphene directly on an upside-down placed, single-crystal silicon substrate using metal-free, ambient-pressure chemical vapor deposition. By controlling the growth temperature, in-plane propagation, edge-propagation, and core-propagation, the process of graphene growth on silicon can be identified. This process produces atomically flat monolayer or bilayer graphene domains, concave bilayer graphene domains, and bulging few-layer graphene domains. This work would be a significant step toward the synthesis of large-area and layer-controlled, high-quality graphene on single-crystal silicon substrates. [ABSTRACT FROM AUTHOR]

The scaffold filling problem aims to set up the whole genomes by filling those missing genes into the scaffolds to optimize a similarity measure of genomes. A typical and frequently used measure for the similarity of two genomes is the number of common adjacencies. One-sided scaffold filling is given by a scaffold and a whole genome, and asks to fill the missing genes into that scaffold to result in such a genome that the number of common adjacencies between it and the given genome is maximized. Two-sided scaffold filling is given by two scaffolds, and asks to fill the missing genes into those two scaffolds respectively to result in such two genomes that the number of common adjacencies between them is maximized. One-sided scaffold filling can be approximated to $$\frac{5}{4}$$ by now. However, the algorithmic progress for two-sided scaffold filling seems rare. What we know for two-sided scaffold filling is a 2-approximation algorithm by now. In this paper, we propose a new algorithm for two-sided scaffold filling which can achieve a performance ratio of $$\frac{3}{2}$$ in $$O(N^3)$$ time, where $$N$$ is the number of genes in an output genome. An example can be given to show that the performance ratio $$\frac{3}{2}$$ for this algorithm is actually tight. [ABSTRACT FROM AUTHOR]

Minimum Common String Partition (MCSP) has drawn much attention due to its application in genome rearrangement. In this paper, we investigate three variants of MCSP: MCSP, which requires that there are at most c elements in the alphabet; d-MCSP, which requires the occurrence of each element to be bounded by d; and x-balanced MCSP, which requires the length of blocks being in range ( n/ k− x, n/ k+ x), where n is the length of the input strings, k is the number of blocks in the optimal common partition and x is a constant integer. We show that MCSP is NP-hard when c≥2. As for d-MCSP, we present an FPT algorithm which runs in O(( d!)) time. As it is still unknown whether an FPT algorithm only parameterized on k exists for the general case of MCSP, we also devise an FPT algorithm for the special case x-balanced MCSP parameterized on both k and x. [ABSTRACT FROM AUTHOR]

Block-move is one of the popular operations for genome rearrangement. A short block-move is an operation on a permutation that moves an element at most two positions away from its original position. Heath and Vergara investigated the problem of finding a minimum-length sorting sequence of short block-moves for a given permutation and devised a 4/3-approximation algorithm. In this paper, we present a new 14/11-approximation algorithm for this problem. Firstly, we devise an exact polynomial time algorithm for sorting a special kind of sub-permutations called umbrella; then we split the permutation into a series of related umbrellas and sort them greedily. We obtain a new lower bound of the short block-move distance by exploiting the properties of five kinds of sub-permutations. After some complicated analysis, we prove that the approximation ratio of the new algorithm is at most 14/11. [ABSTRACT FROM AUTHOR]

Cerebellar granule cell neurons undergo apoptotic cell death when subjected to serum-free conditions at physiological concentrations of potassium (5 mM). Protein kinase C (PKC) is known to play a role in preventing neuronal apoptosis under trophic factor deprivation, but its role in protecting cerebellar neurons from cell death under conditions of low potassium is unknown. This study sought to determine the involvement of PKC in neuronal survival and to determine if PKC regulated the phosphatidylinositol 3-kinase (PI 3-K)/Akt pathway in low physiologic concentrations of potassium. Incubation with a pan-PKC inhibitor, Ro-31-8220 (2 μM), or a specific PKCα inhibitor, Gö6976, protected cerebellar granule cell neurons from low potassium-mediated cell death. In contrast, phorbol ester (TPA, 100 nM), a PKC activator, increased cell death. Incubation with, Ro-31-8220 rescued neurons from cell death induced by the PI 3-K inhibitor, LY294002, suggesting that Ro-31-8220 may affect Akt phosphorylation. Western blot analysis showed that serum-free, low potassium conditions decreased Akt phosphorylation, which was exacerbated by treatment with LY294002. In contrast, PKC inhibitors, Gö6976 or Ro-31-8220, increased Akt phosphorylation approximately two and fourfold, respectively, in low potassium conditions. Because Akt activation appears to be critical in promoting neuronal survival under these culture conditions, increased Akt phosphorylation brought about by inhibiting PKC promotes neuronal survival. [ABSTRACT FROM AUTHOR]

The paper briefly reviews NP-hard optimization problems and their inapproximability. The hardness of solving CLIQUE problem is specifically discussed. A dynamic-programming algorithm and its improved version for CLIQUE are reviewed and some additional analysis is presented. The analysis implies that the improved algorithm, HEWN (hierarchical edge-weighted network), only provides a heuristic or useful method, but cannot be called a polynomial algorithm. [ABSTRACT FROM AUTHOR]

The Plasmodium falciparum protein, apical membrane antigen 1 forms a complex with another parasite protein, rhoptry neck protein 2, to initiate junction formation with the erythrocyte and is essential for merozoite invasion during the blood stage of infection. Consequently, apical membrane antigen 1 has been a target of vaccine development but vaccination with apical membrane antigen 1 alone in controlled human malaria infections failed to protect and showed limited efficacy in field trials. Here we show that vaccination with AMA1–RON2L complex in Freund's adjuvant protects Aotus monkeys against a virulent Plasmodium falciparum infection. Vaccination with AMA1 alone gave only partial protection, delaying infection in one of eight animals. However, the AMA1–RON2L complex vaccine completely protected four of eight monkeys and substantially delayed infection (>25 days) in three of the other four animals. Interestingly, antibodies from monkeys vaccinated with the AMA1–RON2L complex had significantly higher neutralizing activity than antibodies from monkeys vaccinated with AMA1 alone. Importantly, we show that antibodies from animals vaccinated with the complex have significantly higher neutralization activity against non-vaccine type parasites. We suggest that vaccination with the AMA1–RON2L complex induces functional antibodies that better recognize AMA1 as it appears complexed with RON2 during merozoite invasion. These data justify progression of this next generation AMA1 vaccine towards human trials. Malaria: Inhibiting parasite invasion of red blood cells A vaccine targeting a protein complex that allows malaria-causing parasite to enter red blood cells has been produced. Malaria caused by the parasite Plasmodium falciparum is an oft-deadly infectious disease without an effective vaccine. A team of researchers at the National Institutes of Health led by Prakash Srinivasan, currently at the Johns Hopkins Malaria Research Institute, United States, demonstrated the efficacy of a vaccine candidate that works by priming a host's immune system to a parasitic protein complex required to form a junction with red blood cells, allowing entry and proliferation of the pathogen. The group's vaccine conferred more effective protection in monkeys than prior candidates that targeted only one component of the parasitic protein complex. This research warrants a closer look into how this candidate, and others targeting the protein complex, can be used to prevent malaria in humans. [ABSTRACT FROM AUTHOR]