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Hashing has shown its efficiency and effectiveness in facilitating large-scale multimedia applications. Supervised knowledge (e.g., semantic labels or pair-wise relationship) associated to data is capable of significantly improving the quality of hash codes and hash functions. However, confronted with the rapid growth of newlyemerging concepts and multimedia data on the Web, existing supervised hashing approaches may easily suffer from the scarcity and validity of supervised information due to the expensive cost of manual labelling. In this paper, we propose a novel hashing scheme, termed zero-shot hashing (ZSH), which compresses images of "unseen" categories to binary codes with hash functions learned from limited training data of "seen" categories. Specifically, we project independent data labels (i.e., 0/1-form label vectors) into semantic embedding space, where semantic relationships among all the labels can be precisely characterized and thus seen supervised knowledge can be transferred to unseen classes. Moreover, in order to cope with the semantic shift problem, we rotate the embedded space to more suitably align the embedded semantics with the low-level visual feature space, thereby alleviating the influence of semantic gap. In the meantime, to exert positive effects on learning high-quality hash functions, we further propose to preserve local structural property and discrete nature in binary codes. Besides, we develop an efficient alternating algorithm to solve the ZSH model. Extensive experiments conducted on various real-life datasets show the superior zero-shot image retrieval performance of ZSH as compared to several state-of-the-art hashing methods.

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Although sodium-ion batteries (SIBs) are considered as alternatives to lithium-ion batteries (LIBs), the electrochemical performances, in particular the energy density, are much lower than LIBs. A metal-organic compound, cuprous 7,7,8,8-tetracyanoquinodimethane (CuTCNQ), is presented as a new kind of cathode material for SIBs. It consists of both cationic (Cu ↔Cu ) and anionic (TCNQ ↔TCNQ ↔ TCNQ ) reversible redox reactions, delivering a discharge capacity as high as 255 mAh g at a current density of 20 mA g . The synergistic effect of both redox-active metal cations and organic anions brings an electrochemical transfer of multiple electrons. The transformation of cupric ions to cuprous ions occurs at near 3.80 V vs. Na /Na, while the full reduction of TCNQ to TCNQ happens at 3.00-3.30 V. The remarkably high voltage is attributed to the strong inductive effect of the four cyano groups.