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The paper presents the results of the validation of the developed pool evaporation model using literature and our own experimental data.
We have used the expectation maximization (EM) learning algorithm in the BN to refine the conditional probabilities in parameterization of the risk assessment model using literature and experimental data.
The length was based on simulations by a simple heterogeneous one dimensional model using literature parameters and kinetic data, while the diameter was selected to assure a linear fluid velocity between 0.5 and 2 m/s.
Calvano et al constructed a general inflammation network model using literature and gene expression data from blood leukocytes exposed to endotoxin in vivo.
In the case of RHA1, although annotated, several degradation pathways of various xenobiotics were missing from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) (the primary biochemical database used [ 25]) and they were added to the model using literature data and other online databases [ 26, 27] to account for its catabolic ability.
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We further developed this model using literature-published data to help answer these additional questions.
Initially, we developed SAR rules and binary QSAR models using literature data for targeted design of new heteroaryl chalcone compounds with anti-TB activity.
Currently available models generally rely on cross-validation for quality assessment of model performance, although some models use literature-mining and small-scale forward genetics assays to characterize the quality of a few prioritized prediction results [51].
The FE models were validated using literature results.
The models were validated using literature data for the parameters – synthesis gas compositions, time factor, sweep flow rate and steam to CO ratio.
Alkylbenzene results were generally well reproduced by simulations using literature models.
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