Exact(1)
The models were then converted into quasi-deterministic and fully stochastic forms for simulation using the method of arbitrary partial propensities (MAPP [ 52]), an 'exact' variant of the Gillespie direct method [ 53].
Similar(59)
In VisualSim, the simulation flow can be explained as follows: the simulator translates the graphical depiction of the system into a form suitable for simulation execution and executes simulation of the system model, using user specified model parameters for simulation iteration.
Trait phenotypes were simulated based on a heritability (h) of 0.3 and all other variation in phenotype was due to a random environmental effect drawn from a normal distribution with variance σ e 2. Three reference data sets of 1 750 animals were formed for the simulation study.
While these two forms of simulation (explicit QTL simulation vs. single-locus fixed- s simulation) cannot be exactly calibrated to match one another, the qualitative result that the explicit QTL simulation is capturing more complex and realistic dynamics motivated our use of QTL-based simulations for assessing power and experimental design choices going forward.
Although educational theory provides a sound rationale for using this form of simulation, there is little published evidence for its effectiveness.
Since the authors solved the crystal structures of NP7 at low (5.8) and high pH (7.8) and in NO-bound form, for MD simulations these structures could be used to model the molecular systems rather than using NP4 structures.
We also show how the framework of weakly enforced boundary conditions can be used to develop variational forms for multi-domain simulations of heterogeneous media.
We exploit the open-source packages developed under the FEniCS project and solve the coupled and nonlinear weak form for the simulations demonstrated in the next sections.
Although we confine ourselves in this paper to illustrations in the context of genetic designs, we stress that this form of simulation can be used for power calculations in a wide range of other designs such as random effects models, growth curve and simplex models, and structural models.
This driving force forms the basis for simulations of nucleation and growth in films in which simulation parameters, such as film thickness and temperature, are systematically varied.
This paper presents some advances of finite element explicit formulation for simulation of metal forming processes.
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