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Rechargeable aqueous Zn-ion batteries are attractive cheap, safe and green energy storage technologies but are bottlenecked by limitation in high-capacity cathode and compatible electrolyte to achieve satisfactory cyclability. Here we report the application of nonstoichiometric ZnMnO/carbon composite as a new Zn-insertion cathode material in aqueous Zn(CFSO) electrolyte. In 3 M Zn(CFSO) solution that enables ∼100% Zn plating/stripping efficiency with long-term stability and suppresses Mn dissolution, the spinel/carbon hybrid exhibits a reversible capacity of 150 mAh g and a capacity retention of 94% over 500 cycles at a high rate of 500 mA g. The remarkable electrode performance results from the facile charge transfer and Zn insertion in the structurally robust spinel featuring small particle size and abundant cation vacancies, as evidenced by combined electrochemical measurements, XRD, Raman, synchrotron X-ray absorption spectroscopy, FTIR, and NMR analysis. The results would enlighten and promote the use of cation-defective spinel compounds and trifluoromethanesulfonic electrolyte to develop high-performance rechargeable zinc batteries.

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Semantic part localization can facilitate fine-grained categorization by explicitly isolating subtle appearance differences associated with specific object parts. Methods for pose-normalized representations have been proposed, but generally presume bounding box annotations at test time due to the difficulty of object detection. We propose a model for fine-grained categorization that overcomes these limitations by leveraging deep convolutional features computed on bottom-up region proposals. Our method learns whole-object and part detectors, enforces learned geometric constraints between them, and predicts a fine-grained category from a pose-normalized representation. Experiments on the Caltech-UCSD bird dataset confirm that our method outperforms state-of-the-art fine-grained categorization methods in an end-to-end evaluation without requiring a bounding box at test time.

SummaryMissense mutations in PTEN-induced kinase 1 (PINK1) cause autosomalrecessive inherited Parkinson's disease (PD). We have exploited our recent discovery that recombinant insect PINK1 is catalytically active to test whether PINK1 directly phosphorylates 15 proteins encoded by PD-associated genes as well as proteins reported to bind PINK1. We have discovered that insect PINK1 efficiently phosphorylates only one of these proteins, namely the E3 ligase Parkin. We have mapped the phosphorylation site to a highly conserved residue within the