Next is a novel implementation of the τ-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate.
However, a droplet of large size (>30 μm) would be formed in this situation, which may in turn result in large time consumption for film drying.
Hence, bimodal distribution shown in Fig. 3 a becomes unimodal in large time limit with a form of Lifshitz-Slyozov-Wagner distribution.
Special software is required for solving Eqs. 1 and 2 simultaneously in large time series problems.
The present study showed that sampling data in large time blocks may lead to inaccuracy and imprecision in estimates of variance components.
However, without rigorous, robust, and detailed preclinical evaluations, novel neuroprotective drugs may prove to be ineffective when tested in large, time-consuming, and expensive human clinical trials.
To achieve this goal in large time-scale pollution estimation, aggregation of exposure data at small time scales is needed because daily exposure information is not always available from the existing air monitoring networks.
Coevolution of interacting proteins, in large time frames, has been intensively studied and is typically based on the evolutionary distances across different species (Moyle et al. 1994; Pazos and Valencia 2001; Goh and Cohen 2002).
Therefore, without rigorous, robust, and detailed preclinical evaluation, it is unlikely that novel neuroprotective drugs will prove effective when tested in large, time-consuming, and expensive human clinical trials, thereby warranting further well-designed and well-reported experimental animal studies.
However, these techniques require a sparse distribution of simultaneously activated fluorophores in the field of view, resulting in larger time needed for the construction of the full image.
