Open image in new window Fig. 2 Simulation example for the model depicted in Fig. 1 using identity and sum combination functions for all states.
We consider that one of the major contributions of this work is that it shows that the simple model depicted in Eq. 1 for silver oxidation does not allow to understand the complex phenomena that intervene in silver paints degradation in medieval illuminations.
This provides support for the model depicted in Figure 5a.
Hence, in the final SEM analyses, Fos counts obtained from combined layers V and VI of the LEC were added to the models in place of counts from the whole LEC (that is, for the novel object condition this analysis was based on the model depicted in Fig. 7E, and for the familiar object condition the analysis was based on the model depicted in Fig. 7B).
For the "true" model depicted in Figure 1(a), if we consider a single point in time that lies in a time segment where the state values change quickly, the distribution of the measurement at this certain point in time is quite broad.
Hence, for example, in the model depicted by Figure 1, Pa (X3) = [ X1, X2].
In Figures 12 and 13, the impulse responses of the first branch of the nonlinear model are depicted for different input levels, for the case of pedals 1 and 2 respectively.
The forward air mass trajectory calculated by the NOAA's HYSPLIT model is depicted for the radioCs activity concentration peaks, suggesting that the plume from the FDNPP site passed over the Tsukuba region.
This clearly points to the stability of NSCLC xenograft models, as depicted for breast, colon, and pancreatic tumor xenografts 29– 31.
Our model depicts two functions for MRB1: mediating multi-round kRNA editing by coordinating the exchange of multiple gRNAs required by RECC to edit lengthy regions of mRNAs, and then linking kRNA editing with other RNA processing events.
