为了表达语言的因果作用，所需要的研究是对于语言的直接操纵，查看认识效果。
To demonstrate the causal role of language, what's needed are studies that directly manipulate language and look for effects in cognition.
贝叶斯网络用因果关系图的形式表达变量间相互关系，实现复杂系统的故障模式和效应分析。
Variable correlation is expressed with consequence graph in Bayesian Networks (BN), analysis of failure mode and effect of complex system is realized.
第二，就表达怒气之英语习语而言，因果转喻是严具生产力之概念模式。
Second, causality metonymy is by far the most productive model that English idioms of anger reflect.
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