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关于论文的语态问题

 

关于语态,较为传统的一种主张认为应以被动语态为主,因为被动语态可省略施动者,使强调的事物作为主语而突出了它们的“主体”地位,似乎更有利于阐明事实。

但也有一些作者认为,有时用主动语态在结构上似乎更简练,更能直接有力地表达,以突出动词所表达的内容。

据笔者长期观察,随着时间的推移,特别是在当今这个“以人为本”或“以人为中心”的时代,越来越多的作者似乎倾向于用主动语态,以体现人的主观能动性和创造性。

笔者认为,一切应顺其自然---既不要全盘否定被动语态,也不要千篇一律地使用主动语态,也就是说,尽可能地将主动语态与被动语态巧妙、有机地结合起来,以清晰、简洁的语言结构来阐述作者的思想或论文的内涵。

下面是笔者在近期阅读英文期刊文献过程中看到的部分例句,在此与读者分享:

We usethe Compound Topographic Index (CTI) to represent moisture content of the area.

★At this time the measured displacement showed a sharp up slope movement followed by a steady but increasing down slope movement

We also use the p-values (defined as the probability of finding a test statistic value as great as the observed test statistic value, assuming that the null hypothesis is true) in order to assess the significance of each regression coefficient….We reject the null hypothesis if the p-value is less than the significance value (α)we choose; here,we use α=0.001, corresponding to a 99% confidence level. Therefore if p<α,we reject the null hypothesis, and thereby assume that the regression coefficient is not equal to zero, and equals the computed value.

★In order to apply this approach to a global data set,we use multiple landslide inventories to calibrate the model. Using the model formula previously determined (using the Wenchuan earthquake data),we use the four datasets discussed in Section 1.3.1 in our global database to determine the coefficients for the global model.

★The resulting database is used to build a predicative model of the probability of landslide occurrence.

★Substantial effort has been invested to understand where seismically induced landslides may occur in the future, as they are a costly and frequently fatal threat in mountainous regions。

★Performance of the regression modelis assessed using statistical goodness-of-fit metrics and a qualitative review to determine which combination of the proxies provides both the optimum predication of landslide-affected areas and minimizes the false alarms in non-landslide zones.

★This paper reviews these factors, covering the characteristics, types and magnitudes, environmental impacts, and remediation of mine tailings dam failures.

★This conceptual model allowed the deformation of elements within the slope to be kept to a minimum.

★Those numerical studies mentioned above successfully validated the usage of supplemental means for the full scale tests and also contributed to develop and optimize new type of rockfall barrier system effectively.

★ The slope, however,was observed to remain largely saturated for most of the year with a phreatic surface near or at the surface.

We begin modeling by assessing qualitative relationships within the data, moving forward by using logistic regression as a statistical method for establishing a functional form between the predictor variables and the outcomes (Figure 3).We iterate over combinations of predictor variables and outcomes within the model, focusing first on one training event (Wenchuan, China), with the ultimate goal of expanding the analysis to global landslide datasets.

★Median, minimum, and maximum slope values calculated from Shuttle Radar Topography Mission (SRTM) elevation data by Verdian et al. (2007) are used in tests of the model.

★If we define 20% probability of a landslide to be the threshold, any probability equal to or greater than 20% will then be defined as a landslide prediction.

★The RS unit is suitable for testing both fully-softened shear strength and residual shear strength parametersthat can be used for slope stability assessments of various scenarios.

★Approximately 5% of all earthquake-related fatalities are caused by seismically induced landslides, in some cases causing a majority of non-shaking deaths.

★Unsaturated residual shear strength can also be used as a macroscopic indicator of the nature of micro-structural changes experienced by the soils when subjected to drying.

★These data were originally calculated for the purpose of mechanical landslide modeling, and are used here as a statistical constraint on landslide susceptibility.