The main purpose in applying this method is to detect preliminarily the hydrocarbon-bearing zones without need to know porosity.
For this purpose, in this study, several methods (N2 adsorption desorption, SEM, EDS and FT-IR) were employed to characterize the immobilized lipase in order to investigate probable mechanism for the enhancements of enzyme activity and enantioselectivity after immobilization.
In an experiment where very large selective advantages are expected, more regular sampling would be beneficial for the purposes of this method (in Supplementary Tables, we have applied a heuristic cut off such that f i >0.5→0.5 in order to prevent these events biasing the reported fitness ratio statistics).
However, our purpose in this study is to propose a method, which analyze rather small amounts of low-quality data from the slip on the plate interface beneath the ocean bottom.
Given the clear necessity of having an available method for that purpose, in this paper a set of equations for computing the temperature distribution of circular CFT columns filled with normal strength concrete is provided.
In this way, most of the better iterative efficiency could be expected, which is just our purpose in improving the method.
Parameters extracted from the GLCM can be used to define similarity properties for corrosion detection purpose in image segmentation methods based on region approach.
A discussion of instances where the "regulated" believes that studies have not been adequate, or others habe been ignored, or misinterpreted for regulatory purposes in included.A method of settling controversial questions to eliminate the litigation route is proposed.
While this is suitable for experimental purposes in animals, this delivery method is not directly applicable in a therapeutic context.
The EMD method served two purposes in this study: (1) to decompose different weather time series into IMFs; each oscillated at certain time scales, and (2) to de-trend (i.e., to remove residual component from raw data) the time series of weather data to produce a zero-mean distribution, thus reducing spurious regression and multi-collinearity in subsequent multiple linear regression analyses.
