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Osteoprotegerin (OPG) and osteopontin (OPN) are bone metabolism biomarkers which are involved in the regulation of vascular calcification processes and prediction of future adverse cardiac events.
As most reactions take place in solution, the study of solvent effects on relevant molecular properties – either by experimental or theoretical methods – is crucial for the design of new processes and prediction of technological properties.
With the increase in frequency of such blooms, various monitoring approaches, treatment processes, and prediction models have been developed in due course.
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With this, the model training process and prediction process can be evaluated independently of each other.
Response surface methodology (RSM) was employed for kinetic modeling of process and prediction the yield.
A two dimensional finite element code has been developed for the simulation of the mechanical process and prediction of the defects.
The properties required for precise simulation of the process and prediction of damage accumulation (equivalent stress as function of equivalent strain and temperature and low bound ductility function) are obtained in the temperature interval 20 400 °C and described in details.
The modified ARM, based on Miller and Bowman's mechanism (MB-ARM), and adjusted to predict an extinction limit reasonably, was the most suitable mechanism for the unsteady simulation, taking into consideration computational cost, stiffness during the ignition process, and prediction performance for an unsteady flame with sinusoidal transient disturbances.
Simple empirical description of biochemical reaction networks is insufficient for discovery of the general principles underlying biological process and prediction of dynamic response of biological networks to drug interventions or environmental perturbation [3].
We propose that the division of disease genes by mode of inheritance will enhance both understanding of the disease process and prediction of candidate disease genes in the future.
Based on these findings, they proposed that the division of human diseasome by mode of inheritance (dominant or recessive) could enhance both understanding of the disease process and prediction of candidate disease genes.
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