A Reappraisal of the Safety and Cost-Effectiveness of Statin Therapy in Primary Prevention

Statins are among the most investigated drugs of all time. There is now a wealth of evidence supporting their use in the primary and secondary prevention arenas. The reduction in event recurrence has since been demonstrated across all levels of risk and in elderly patients. As a result, it is now accepted practice for statins to be prescribed universally in secondary prevention unless contraindicated. The extension of this policy into the primary prevention setting is more problematic, with moral and financial issues arising from the long-term treatment of many young apparently healthy individuals. For these reasons it is necessary to prove not only the financial sustainability of such a strategy but also the long-term safety of statins and the degree of benefit that might be expected.

Model reduction for nonlinear aerodynamics and aeroelasticity using a Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of Computational Fluid Dynamics (CFD) solvers, for fast nonlinear aerodynamic and aeroelastic modeling. A nonlinear function is identified on selected interpolation points by
a discrete empirical interpolation method (DEIM). The flow field is then reconstructed using a least square approximation of the flow modes extracted
by proper orthogonal decomposition (POD). The aeroelastic reduce order
model (ROM) is completed by introducing a nonlinear mapping function
between displacements and the DEIM points. The proposed model is investigated to predict the aerodynamic forces due to forced motions using
a N ACA 0012 airfoil undergoing a prescribed pitching oscillation. To investigate aeroelastic problems at transonic conditions, a pitch/plunge airfoil
and a cropped delta wing aeroelastic models are built using linear structural models. The presence of shock-waves triggers the appearance of limit
cycle oscillations (LCO), which the model is able to predict. For all cases
tested, the new ROM shows the ability to replicate the nonlinear aerodynamic forces, structural displacements and reconstruct the complete flow
field with sufficient accuracy at a fraction of the cost of full order CFD
model.

CoO nanoparticles embedded in three-dimensional nitrogen/sulfur co-doped carbon nanofiber networks as a bifunctional catalyst for oxygen reduction/evolution reactions

High-performance and low-cost bifunctional electrocatalysts play crucial roles in oxygen reduction and evolution reactions. Herein, a novel three-dimensional (3D) bifunctional electrocatalyst was prepared by embedding CoO nanoparticles into nitrogen and sulfur co-doped carbon nanofiber networks (denoted as CoO@N/S-CNF) through a facile approach. The carbon nanofiber networks were derived from a nanostructured biological material which provided abundant functional groups to nucleate and anchor nanoparticles while retaining its interconnected 3D porous structure. The composite possesses a high specific surface area and graphitization degree, which favors both mass transport and charge transfer for electrochemical reaction. The CoO@N/S-CNF not only exhibits highly efficient catalytic activity towards oxygen reduction reaction (ORR) in alkaline media with an onset potential of about 0.84 V, but also shows better stability and stronger resistance to methanol than Pt/C. Furthermore, it only needs an overpotential of 1.55 V to achieve a current density of 10 mA cm^-2, suggesting that it is an efficient electrocatalyst for oxygen evolution reaction (OER). The ΔE value (oxygen electrode activity parameter) of CoO@N/S-CNF is calculated to be 0.828 V, which demonstrates that the composite could be a promising bifunctional electrocatalyst for both ORR and OER.

Model reduction for nonlinear aeroelasticity using the Discrete Empirical Interpolation Method

A novel surrogate model is proposed in lieu of computational fluid dynamic (CFD) code for fast nonlinear aerodynamic modeling. First, a nonlinear function is identified on selected interpolation points defined by discrete empirical interpolation method (DEIM). The flow field is then reconstructed by a least square approximation of flow modes extracted by proper orthogonal decomposition (POD). The proposed model is applied in the prediction of limit cycle oscillation for a plunge/pitch airfoil and a delta wing with linear structural model, results are validate against a time accurate CFD-FEM code. The results show the model is able to replicate the aerodynamic forces and flow fields with sufficient accuracy while requiring a fraction of CFD cost.