ID 原文 译文
813 实验结果显示，在 P200 时间段里，腹侧前额叶与后顶叶之间神经振荡存在相位同步现象，并且后顶叶电极神经震荡的相角滞后于前额叶电极，这表明 P200 对应的检索过程是由前额叶驱动后顶叶的一种自上而下的控制过程。 For P200, the experiment result shows that the neural oscillation has phase synchronization between prefrontal cortex and posterior partial cortex and the phase angle ofposterior partial cortex lags behind prefrontal cortex, indicating that the brain completed task rule retrieval and P200 reflectsa top-down process driven by prefrontal cortex.
814 在 P300 的时间段里，对 theta 波段频谱分布的研究结果显示了切换任务中大脑的激活强度显著大于重复任务中大脑的激活强度， For P300, the research results of theta band oscillation distribution show that the brain activation in the cue switch was significantly greater than in the cue repeat.
815 而且，两种任务中该频段的能量均主要分布在右侧后顶叶，它揭示了任务集配置和更新与 theta 波段神经振荡之间的密切关系。 Meanwhile, the power of theta band os-cillation was mainly distributed in the posterior partial cortex, which shows that theta band oscillation is related with the reconfiguration and update of task set.
816 本文以上发现为揭示大脑认知灵活性的神经振荡机制提供了一种新的途径，有助于我们深入了解任务切换的认知加工过程。 The above findings provide a new way to reveal the neural oscillation mechanism ofbrain cognitive flexibility, which helps us to understand the cognitive process of task switching.
817 语言资源加工和语言学研究，对大规模树库的结构化检索有很高需求。 Language resource processing and linguistics research require effective retrieval on syntax tree corpus.
818 本文针对句法树语料设计了索引、检索方法。 This paper presented an index and search method for syntax tree corpus, which is efficient, accurate, and flexible.
819 针对汉语的特点以及知识抽取任务的需求，我们设计了七种索引结构，旨在借助句法树的结构、属性信息，进行高效、准确的知识抽取。 Based on the features of Chinese language and the needs for knowledge extraction, we designed seven types of indexes, aiming that with the help of structure and attribute information, knowledge extraction will be performed more effectively and accurately.
820 本方法不仅支持字符串检索、属性检索，也支持基于句法树结构、属性信息的检索。 Apart from general retrieval functions, our method supports retrieval based on the structure and attribute information of syntaxtrees.
821 实验证明，本方法高效、准确。 Experiments show that our method is both accurate and efficient.
822 量子元胞自动机(Quantum-dot Cellular Automata，QCA)是一种具有新型计算范式的纳米器件，它是未来有望替代传统 CMOS 器件的有力竞争者之一。 Quantum-dot cellular automata (QCA)is a kind of nano-devices with special computing paradigm, which is one of powerful competitors to replace traditional CMOS devices in the future.