Publications by authors named "Ehsan Mahdavi"

The stabilization of nanoparticles is a main concern to produce an efficient nanofluid. Here, we carry out Molecular Dynamics (MD) modeling to evaluate the stabilization of 2D graphene, oxygen- and hydrogen-functionalized graphene, and TiCO MXene nano-sheets in carbon dioxide (CO) liquid under supercritical conditions. The rheological properties (i.

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MicroRNAs (miRNAs) are a class of short RNA molecules that regulate gene expression by binding directly to messenger RNAs. Conventional approaches to miRNA target prediction estimate the accessibility of target sites and the strength of the binding miRNA by finding optimums of some energy models, which involves O(n3) computations. Alternatively, we narrow down potential binding sites of miRNAs to suboptimal hits of a pairwise alignment algorithm called Fitting Alignment in O(n2).

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