2) In the subsection headed "Up-regulating cytokinin degradation captures predicted effects of decreasing model values of T", the expression "similar to the model output".
Thus, by generating a decreased inhibition zone with more branches in the branching zone or an increased inhibition zone with fewer branches in the branching zone respectively, the effects of depleting or elevating SHI-mediated auxin biosynthesis captures predicted effects of changing the target auxin concentrations H apex and H in the model.
To determine this requires prospective larger scale and longer term studies that can be used to model how the biomarker and the process it captures predicts the clinical endpoint [26,66,67].
Suggestions: 1) In the subsection headed "Auxin biosynthesis mutants capture predicted effects of changing model values H apex and H": This section is written cryptically.
Suggestions: 1) In the subsection headed "Auxin biosynthesis mutants capture predicted effects of changing model values Hapex and H": This section is written cryptically.
We will review the expansion of the CATH resource to capture predicted domain structures in the genome sequence data and to provide information on the likely functions of proteins mediated by their constituent domains.
We review the expansion of the CATH and SCOP resources to capture predicted domain structures in the genome sequence data and to provide information on the likely functions of proteins mediated by their constituent domains.
Variable abbreviations: maxtemp daily maximum temperature, rh relative humidity, mfv/ffv male/female feeding rate (visits/h/chick) Coef' indicates the estimated coefficient and ' SE standard error of that estimate in the model Second, we looked at whether parental behavior the day before capture predicted brood survival.
To illustrate the confidence intervals graphically, we also captured predicted values of the probability of sharing a pathogen at 5-My intervals, for each of the 1000 models, and then calculated the 0.025, 0.5, and 0.975 quantiles to use for 95% confidence intervals of the curves.
Comparison of the proposed model predictions with the results from two empirical models currently being implemented in design works, a neural network-based model from literature and also the field data shows that the EPR model is capable of capturing, predicting and generalizing predictions to unseen data cases, for lateral load bearing capacity of piles with very high accuracy.
For the loading process of larger particles in the parallel model the pressure drop from the LB CA model agree well with the predictions of the empirical model, and the interceptive capture efficiency predicted by the empirical model is also in good agreement with the LB CA results.
