Recently building information models have substantially improved the explicit semantic content of design information.
These models have substantially improved research access – especially for those based in developing countries – but the benefits are yet to translate into more efficient research workflows.
EJF models had substantially better prediction R compared with the individual JF models using either the original or reduced maps for the three traits.
When applying previously specified risk prediction models to our population, both models were able to adequately predict outcomes among smokers, however, both models had substantially less predictive ability among never smokers.
Mathematical models have substantially improved our ability to predict the response of a complex biological system to perturbation, but their use is typically limited by difficulties in specifying model topology and parameter values.
Studies performed in vertebrate models have substantially advanced our understanding of the pathogenesis of NEC and IBD, and are arguably the most commonly used experimental systems in the field of intestinal inflammation.
Studies performed in human and animal models have substantially contributed to our knowledge of molecular mechanism of muscle degeneration but still these findings are inadequate for developing effective therapy.
As a result, the mean of the VIF of the final model has substantially dropped and was well below the threshold limit.
In the case of microglia, selective silencing of the mutant gene in the innate immune cells of the CNS and in macrophages in a SOD1-model has substantially slowed disease progression [4], [5].
Whether or not the individual images are of interest depends on the nature of the study and we not that the random-effects model has substantially more unknown parameters.
