Sentence examples for between the solution for from inspiring English sources
Under the same conditions of Theorem 6, when (Delta t=O(N^{-1})), the (L^{2}_{omega}) norm error estimates between the solution for Problem 3 and the series of solutions of Problem 5 are as follows: biglVert u(t_{n} -u_{N}^{n} bigrVert_{n} -u_{a} = O bigl(Delta t^{2},N}^{n} bigrVertuad1leq nleq K, 2leq qleq N+1.
Under the same conditions of Theorem 6, if the solutions of Problem 3 (u(t_{n})in H^{q}_{omega}(Omega)) ((2le qle N+1)), when (Delta t=O(N^{-1})), the errors between the solution for Problem 3 and the series of solutions of Problem 5 have the following estimates: biglVert nablabigl u(t_{n} -u_{N}^{n} bigr) bigrVert_{n} -u_{a} = O bigl(Delta t,N}^{nq} bigr), quad1leq nleq K, 2leq qleq N+1.
We calculate the impact distribution for a given TFBS by setting the diffusion rate parameter to zero in the model equations and computing the difference in all nuclei and at all times between the solution for the case with all sites included and the solution for the case with the binding site of interest excluded.
"Results and discussion" section describes the experiments that allow us to highlight and discuss the differences between the solutions for the MDP and LP models.
Our experiments show that as campaign budgets grow, this difference between the solutions for the MDP and for the LP formulations decreases quickly.
But here it is important to note that the complex formation term introduces significant coupling between the solutions for A and B, so the binding partner now plays a role in determining the concentration of a, rather than simply being a passive product of complex breakdown.
In addition, we present results which indicate that the difference between the DDtN solution and the solution for each of the other three boundary conditions has the correct behavior when the artificial boundary is enlarged.
To avoid choosing a prior preferred value of porosity, 404 regularization equations were included in the calibration that penalized the solution for differences between nearest-neighbor pilot point values weighted inversely proportional to their separation distance.
Figure 10 shows the relation between the best solution for the PBI function with the weight vector (0.9, 0.1) for three specifications of (theta ) when the Pareto front is linear.
Theorem 4.2 Under the hypotheses of Theorem 4.1, we have the following error estimates between the accuracy solution for the traffic flow LWR model and the solutions of the POD-based reduced-order FDEA (17) and (18): | ρ ( x i, t n ) − ρ i ∗ n | = O ( C n λ M + 1, Δ x 2, Δ t 2 ), 1 ≤ i ≤ I, 1 ≤ n ≤ N. (25).
