Sentence examples for predictions of evolution from inspiring English sources

*minutes, †minutes, ‡doublings/hour, §10-9 ml/min £Under phase II conditions; under phase I conditions the optimal lysis interval is 2.7 min and fitness is 37.3 db/hr The failure of the mean lysis interval to adapt closer to the optimum over ~120 generations means that even qualitative predictions of evolution failed for ΦX174C.

However, the reduced contribution of political orientation to the prediction of evolution acceptance when religiosity and trust in science are added to the model suggests that there is likely substantial overlap between the two other predictors and political orientation.

Evolutionary Systems Biology (EvoSysBio) is defined here as working toward integrated interactive overviews of dynamic multi-dimensional fitness landscapes that are testable in the real world and enable the prediction of evolution.

At the Evolution 2010 meeting in Oregon in June 2010, a symposium on 'Moving towards a science of evolutionary prediction' suggested that the next challenge will be to improve the accuracy of evolutionary prediction (http://www.evolutionsociety.org/SSE2010), although the prediction of evolution is still difficult.

This constitutive response is able to provide accurate predictions of the evolution of shear bands seen in uniaxial compression tests.

This has provided much needed data for Multi-Body Dynandcs (MBD) simulations, and will allow better predictions of profile evolution of wheel and rail over a wider range of conditions.

The predictions of microstructural evolution and the flow behaviour at various hot working conditions agree well with the experimental results for an oxygen free high conductivity (OFHC) copper.

The model is capable of capturing the combined effects of these size scales by accounting for the interaction energies of the constrained dislocation structure, and provides quantitative predictions of the evolution of film stress during thermal excursions.

Moreover, they could become essential elements of network models, with the advantage of more accurate descriptions of real networks and predictions of their evolution.

This kind of interaction may in turn decouple the relationship between parasite transmission and its negative effect on host fitness, altering theoretical predictions of parasite evolution.

Taking these factors into account can produce very different predictions of the evolution of virulence than those resulting from simple laboratory experiments 41.