Sentence examples for models we concluded from inspiring English sources

After producing our models, we concluded that the two models were sufficient for our purposes.

To explain this tilt motion based on pre-existing fault models, we concluded that a slip along the conjugate fault coseismically occurred during the earthquake.

In keeping with studies using computationally intensive individual-based models, we concluded that, for the purposes of limiting spread, prevention was better than cure [2], [3].

By silencing NAV3 expression and studying mutant forms in animal models, we concluded that NAV3 inhibits metastasis.

Because there was no interaction between state and the animal contact variables in the models, we concluded that the effect estimate was consistent across the 2 states.

Since the treatment indicator was non-significant in all these models, we concluded that the selection bias had been successfully removed, and our subsequent models would be balanced (Dehejia and Wahba 2002).

After comparing these three models, we conclude that the seismic moment and moment rate functionare well constrained.

The results show that the proposed MONF model outperforms the above benchmark models; we conclude that the MONF model is a new alternative tool that should be used in flood susceptibility mapping.

Given the poor results of the mineralization regression models, we conclude that probability density functions, rather than regression models, are likely to be more useful for describing pesticide or estrogen mineralization parameters at the regional scale.

From these fitting models, we conclude that the velocity toward the root of the end effector is inversely proportional to the distance from the center of the end effector's circular motion, in addition, we can calculate and predict the velocity in the Y-direction if the end-effector frequency and amplitude are known.

Among the studied models, we conclude that the one derived from the X-ray structure of the PFV integrase exhibited the best performance to rank the potencies of the compounds in the training set, with the predictive power being further improved by explicitly modeling five water molecules within the catalytic side of IN.