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Consequently, under suitable assumptions, the complexity of regression queries is at most exponential in its contextual width.
It's unclear to which growth phase the fitness effects relate to: is it most exponential growth, or stationary phase as well.
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These results indicated that, as expected, most exponential-phase cells were synthesizing DNA, although fewer were in strains defective in double-strand break repair and HJ processing.
However, this model exhibits some of the same accelerating patterns as in the generalized growth model, ascertained by the growth rate of the most recent exponential epoch being 2.4% (2.3 5.2%), larger than that of the first exponential epoch, 1.6% (1.3 2.1%).
MLFD has at most an exponential tail.
In this case, the relation can be modeled by some non-linear function, the most frequently exponential function ((y=be^{cx})) or logarithmic function ((y={b}_{{0}} +b_1 ell n x)) [1].
Concerning the complexity theory of RPDL, Streett [1982] had already established that RPDL had the finite model property; precisely that every RPDL satisfiable formula A is satisfiable in a model of size at most triply exponential in the length of A. An automata-theoretic argument permitted to conclude that the problem (RPDL-SAT) can be solved in deterministic triple exponential time (3-EXPTIME).
Further, we show that, if a finite uniform EL interpolant exists, then there exists one that is at most triple exponential in the size of the original TBox, and that, in the worst case, no smaller interpolants exist, thereby establishing tight worst-case bounds on their size.
In the most advanced exponential coding format, where multiple levels of fluorescence intensity can be distinguished for each color, the maximum number of probes that can be coded by n colors, each having x levels of fluorescence intensity, is expressed by: Pn1 + Σ [xi Pni] (where i = 2 to n).
We can see from Figure 8 that the relaxation of this estimated cost function is mainly determined by the most rapid exponential terms, and is virtually complete by 3 4 million time steps, with a limited volume dependence.
Despite that the neighborhood size in Kumar's approach is larger than in Rzhetsky and Nei's algorithm, it requires examining a number of topologies that is, at most, an exponential function of the number of leaves n: (n - 1)!/2, and generates solution in a shorter computing time.
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