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The proposed rule does not ensure a strict decrease of d KS ( f | S ~ |, f target ) at each step, but it reduces step by step the difference between f | S ~ | and Ftarget, which contributes, in the long term, to a decrease of d KS ( f | S ~ |, f target ).
Again, there is a visible increase in the deviation away from the baseline state as more clusters are added rather than a strict decrease.
Each call to line 4 takes O(m) time, where m= j− i, and causes a strict decrease in Vec of 2 m units.
The strict decrease in transcript levels for all conditions and the significant increase in fitness at high temperature for all hosts suggests to us that transcription provides the underlying basis for the adaptive advantage of these synonymous substitutions.
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is strict decreasing on and, (4).
(3) is continuous and strict decreasing on with.
which implies that, and hence is strict decreasing on.
It follows that and thus is strict decreasing on.
By the strict decreasing of μ ̄ ( a ( t ) ) with respect to a(t) (see [11]), where μ ̄ ( a ( t ) ) is the k th eigenvalue of (1.2) corresponding to the weight function a(t), we have μ ̄ ( a ( t ) ) < μ ̄ ( λ k ) = 1.
We shall show C k ν crosses the hyperplane {1} × E in ℝ × E. By the strict decreasing of μ k (c(t)) with respect to c(t) (see [11]), where μ k (c(t)) is the k th eigenvalue of (1.2) corresponding to the weight function c(t), we have μ k (c(t)) > μ k (λ k ) = 1.
By the strict decreasing of μ k (f) with respect to weight function f (see [11]), where μ k (f) denotes the k th eigenvalue of (1.2) corresponding to weight function f, we can show that our condition c(t) ≤ λ k < ⋯ < λk+j≤ a(t) is equivalent to the condition f0 < μ k < · · · < μk+j< f∞.
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