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In the case of bottleneck sectors, more policy intervention is needed to promote productivity growth by subsidizing R&D investment.
Although both kinds of events (coalescence during or before the bottleneck) do not occur in the same periods of time, the variability across markers may cause overlaps in the predicted time of the bottleneck and lead to bimodal population size distributions as shown for example in Fig. 6 in a case of bottleneck.
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dThe detailed process of computing these solutions is demonstrated in the following three cases of bottleneck users.
d The detailed process of computing these solutions is demonstrated in the following three cases of bottleneck users.
By analyzing the probabilities for three cases of bottleneck users, we prove that the worst-case computational complexity of PASA is O ( K 3 ).
Let P 1,P 2,P 3 denote the probability for case of one bottleneck user, case of two bottleneck users, and case of three bottleneck users, respectively.
In the case of one bottleneck user, w.l.o.g, we assume the i-th user is the bottleneck user.
In the case of two bottleneck users, w.l.o.g, we assume the i-th and j-th users are the bottleneck users.
In case of three bottleneck users, w.l.o.g, we assume the i-th user, j-th user, and k-th user are the bottleneck users.
Otherwise, we turn to check the case of two bottleneck users.
The model properties have been then examined especially for the case of single bottleneck homogeneous network which is closely investigated.
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