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Performance of the Flexible Means in EST Translation

English for science and technology(EST) is an important way to describe scientific work, and flexible means(FM) is the generally accepted method to translate EST. In this paper, we evaluate the application of flexible means in EST translation(ESTT) via the explicit questionnaire. Directly employing the principal component analysis(PCA), we obtain the relative importance of seven different kinds of FM. Based on analytic hierarchy process(AHP), we take three kinds of EST including biological EST(BEST), agricultural EST(AEST) and medical EST(MEST) as our objects to investigate the application of FM, with the seven FM being criterion layer and the three EST being scheme layer. We find that, the application of FM in BEST is the most common among the three EST.