Reconstructing a nonlinear dynamical system from empirical time series is a fundamental task in data-driven analysis. One of the main challenges is the existence of hidden variables; we only have records for some variables, and those for hidden variables are unavailable. In this work, the techniques for Carleman linearization, phase-space embedding, and dynamic mode decomposition are integrated to rebuild an optimal dynamical system from time series for one specific variable.
View Article and Find Full Text PDFHepatitis C virus (HCV) genotype 1 is the most prevalent HCV infection in China. Sofosbuvir-based direct antiviral agent (DAA) regimens are the current mainstays of treatment. Sofosbuvir/velpatasvir (SOF/VEL) and sofosbuvir/ledipasvir (SOF/LDV) regimens became reimbursable in China in 2020.
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