Chinese character recognition has attracted much research interest due to its wide applications. Although it has been studied for many years, some issues in this field have not been completely resolved yet, \textit{e.g.} the zero-shot problem. Previous character-based and radical-based methods have not fundamentally addressed the zero-shot problem since some characters or radicals in test sets may not appear in training sets under a data-hungry condition. Inspired by the fact that humans can generalize to know how to write characters unseen before if they have learned stroke orders of some characters, we propose a stroke-based method by decomposing each character into a sequence of strokes, which are the most basic units of Chinese characters. However, we observe that there is a one-to-many relationship between stroke sequences and Chinese characters. To tackle this challenge, we employ a matching-based strategy to transform the predicted stroke sequence to a specific character. We evaluate the proposed method on handwritten characters, printed artistic characters, and scene characters. The experimental results validate that the proposed method outperforms existing methods on both character zero-shot and radical zero-shot tasks. Moreover, the proposed method can be easily generalized to other languages whose characters can be decomposed into strokes.
Excess Manganese (Mn) is toxic to plants and reduces crop production. Although physiological and molecular pathways may drive plant responses to Mn toxicity, few studies have evaluated Mn tolerance capacity in roots and leaves. As a result, the processes behind Mn tolerance in various plant tissue or organ are unclear. The reactivity of peanut (Arachis hypogaea) to Mn toxicity stress was examined in this study. Mn oxidation spots developed on peanut leaves, and the root growth was inhibited under Mn toxicity stress. The physiological results revealed that under Mn toxicity stress, the activities of antioxidases and the content of proline in roots and leaves were greatly elevated, whereas the content of soluble protein decreased. In addition, manganese and iron ion content in roots and leaves increased significantly, but magnesium ion content decreased drastically. The differentially expressed genes (DEGs) in peanut roots and leaves in response to Mn toxicity were subsequently identified using genome-wide transcriptome analysis. Transcriptomic profiling results showed that 731 and 4589 DEGs were discovered individually in roots and leaves, respectively. Furthermore, only 310 DEGs were frequently adjusted and controlled in peanut roots and leaves, indicating peanut roots and leaves exhibited various toxicity responses to Mn. The results of qRT-PCR suggested that the gene expression of many DEGs in roots and leaves was inconsistent, indicating a more complex regulation of DEGs. Therefore, different regulatory mechanisms are present in peanut roots and leaves in response to Mn toxicity stress. The findings of this study can serve as a starting point for further research into the molecular mechanism of important functional genes in peanut roots and leaves that regulate peanut tolerance to Mn poisoning.
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