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Gibberellin-dioxygenases genes plays important roles in the regulating plant development. However, Gibberellin-dioxygenases genes are rarely reported in maize, especially response to gibberellin (GA). In present study, 27 Gibberellin-dioxygenases genes were identified in the maize and they were classified into seven subfamilies (I-VII) based on phylogenetic analysis. This result was also further confirmed by their gene structure and conserved motif characteristics. And gibberellin-dioxygenases genes only occurred segmental duplication that occurs most frequently in plants. Furthermore, the gibberellin-dioxygenases genes showed different tissue expression pattern in different tissues and most of the gibberellin-dioxygenases genes showed tissue specific expression. Moreover, almost all the gibberellin-dioxygenases genes were significantly elevated in response to GA except for ZmGA2ox2 and ZmGA20ox10 of 15 gibberellin-dioxygenases genes normally expressed in leaves while 10 and 11 gibberellin-dioxygenases genes showed up and down regulated under GA treatment than that under normal condition in leaf sheath. In addition, we found that ZmGA2ox1, ZmGA2ox4, ZmGA20ox7, ZmGA3ox1 and ZmGA3ox3 might be potential genes for regulating balance of GAs which play essential roles in plant development. These findings will increase our understanding of Gibberellin-dioxygenases gene family in response to GA and will provide a solid base for further functional characterization of Gibberellin-dioxygenases genes in maize.

Aqueous zinc‐ion batteries (ZIBs) are regarded as among the most promising candidates for large‐scale grid energy storage, owing to their high safety, low costs, and environmental friendliness. Over the past decade, vanadium oxides, which are exemplified by V2O5, have been widely developed as a class of cathode materials for ZIBs, where the relatively high theoretical capacity and structural stability are among the main considerations. However, there are considerable challenges in the construction of vanadium‐based ZIBs with high capacity, long lifespan, and excellent rate performance. Simple widenings of the interlayer spacing in the layered vanadium oxides by pre‐intercalations appear to have reached their limitations in improving the energy density and other key performance parameters of ZIBs, although various metal ions (Na+, Ca2+, and Al3+) and even organic cations/groups have been explored. Herein, we discuss the advances made more recently, and also the challenges faced by the high‐performance vanadium oxides (V2O5‐based) cathodes, where there are several strategies to improve their electrochemical performance ranging from the new structural designs down to sub‐nano‐scopic/molecular/atomic levels, including cation pre‐intercalation, structural water optimization, and defect engineering, to macroscopic structural modifications. The key principles for an optimal structural design of the V2O5‐based cathode materials for high energy density and fast‐charging aqueous ZIBs are examined, aiming at paving the way for developing energy storage designed for those large scales, high safety, and low‐cost systems.

No abstract

Although side-channel attacks based on deep learning are widely used in AES encryption algorithms, there is little research on lightweight algorithms. Lightweight algorithms have fewer nonlinear operations, so it is more difficult to attack successfully. Taking SPECK, a typical lightweight encryption algorithm, as an example, directly selecting the initial key as the label can only crack the first 16-bit key. In this regard, we evaluate the leakage of SPECK’s operations (modular addition, XOR, shift), and finally select the result of XOR operation as the label, and successfully recover the last 48-bit key. Usually, the divide and conquer method often used in side-channel attacks not only needs to train multiple models, but also the different bytes of the key are regarded as unrelated individuals. Through the visualization method, we found that different key bytes overlap in the position of the complete electromagnetic leakage signal. That is, when SPECK generates a round key, there is a connection between different bytes of the key. In this regard, we propose a transfer learning method for different byte keys. This method can take advantage of the similarity of key bytes, improve the performance starting-point of the model, and reduce the convergence time of the model by 50%.