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Our experiments are intended to: 1) verify the rationality of our proposed deadlock solving method; and 2) discuss how the model parameters affect the results.

Here, A is a matrix called the averaging kernel matrix (AKM), its diagonal elements indicating the extent to which the true model parameters affect the retrieved solution.

We focus on spatially invariant architectures to gain more insights into how model parameters affect emergence of this complex scale-invariant behavior, and to seek structures robust to communication constraints.

To investigate how the individual model parameters affect the three measures, the sensitivity coefficients were calculated for all three characterisations (Supplementary Figs. S1, S2 and S3) [ 35, 36].

This method requires careful analysis to determine the dominant processes on each time scale, and the resulting expressions show clearly how the model parameters affect the predicted auxin concentrations and speeds.

Bifurcation analysis indicates the dynamical mechanisms behind the transitions within the cell-cycle, while the mathematical simplification analysis provides proof of the existence of a limit cycle, yields explicit analytical expressions describing how model parameters affect cell size, and also provides conditions necessary for oscillations.

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So, model parameters affected by speed change should be calculated for each speed level.

Model parameters affecting the trend of relative permeability curves are discussed.

The selection of model parameters affects the performance of the system, but how to choose the optimum model parameters is not obvious, which needs a further study.

The results of the second comparative study show that, for all techniques, estimating more model parameters affects the estimation accuracy as well as the convergence of the estimated states and parameters.

The diagrams have been annotated to provide insight into how changing model parameters affects model outputs.

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