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Numerical modeling tools were used for the definition and analysis of the electrode geometry and the material mechanical properties.
Instrumental analyses accompanied by analytical modeling tools were employed to assess physico-chemical changes induced by variations in chemical composition of cementitious composites, i.e. mortar binders.
In the present study, modeling tools were used to describe the copolymerization of styrene with ethylene glycol dimethacrylate (EGDMA) beyond the gel point.
The modeling tools were also applied to the more widely used continuous arterial spin labeling (CASL) method and predicted that specially shaped gradients could allow similar reductions in SAR.
In the current study our objective was to determine if subsets of genes can predict the time to the next acute relapse in patients with MS. Data-mining and predictive modeling tools were utilized to analyze a gene-expression dataset of 94 non-treated patients; 62 patients with definite MS and 32 patients with clinically isolated syndrome (CIS).
Until recently most fractured-reservoir modeling tools were limited to simple discrete statistical models.
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To make this forecast reliable, good models and therefore good modeling tools are required.
In addition to being able to share models with any and every user of the platform, features to export models in formats that can work with other modeling tools are also available.
The need for advanced modeling tools is increasing.
Molecular modeling tools are used to explore their mechanism of action.
Presently, modeling tools are limited by computational capability, uncertainty in experimental data, and physical accuracy.
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