These observations agree with current soil organic matter models that explicitly consider microbial physiology.
This feature helps analysts to build models that explicitly represent the physics of problems.
The focus is the estimation problem in the context of mathematical models that explicitly include unknown parameters.
The proposed Bayesian decision-theoretic approach resorts to probabilistic tendency models that explicitly characterize their levels of confidence.
This added forecasting volatility makes long-term transport models that explicitly consider travel demand uncertainty even more critical.
In January 2015, Sylvia Mathews Burwell, the secretary of the U.S. Department of Health and Human Services, announced plans to shift 30% of Medicare fee-for-service payments—$362 billion in 2014 to alternative models that explicitly reward value.
The increased availability of detailed trajectory data sets from naturalistic, observational, and simulation-based studies, is a key source for potential improvements in the development of detailed safety models that explicitly account for vehicle conflict interactions and various driving maneuvers.
Although it is well known that the physical and chemical properties of fly ashes play an important role in microstructural development, models that explicitly simulate the effects of these properties on the performance of pastes and mortars are not available.
We therefore advocate models that explicitly consider the mechanisms by which environmental variables affect individuals and populations16,18, and especially dynamic energy budget models, as tools to predict vital rates and other population dynamics determinants (for example, density dependence32) for yet-to-be-observed conditions.
Russ and colleagues highlight three health research partnership models that explicitly involve community members, researchers, and legislators, focusing in depth on the researcher policymaker relationship.
Innovations here include the introduction of tree models that explicitly address and incorporate the retrospective design, and the use of nonparametric Bayesian models involving Dirichlet process priors on the distributions of predictor variables.
