Asymptotic Equivalency of Two Different Approaches of L-statistics

There are several ways to establish the asymptotic normality of $L$-statistics, depending upon the selection of the weights generating function and the cumulative distribution function of the underlying model. Here, in this paper it is shown that the two of the asymptotic approaches are equivalent/equal for a particular choice of the weights generating function.