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@@ -38,14 +38,14 @@ Computational modeling of cardiovascular blood flow has emerged as a valuable to
 While simulations of blood flow can be performed using various high and low-fidelity techniques, lumped-parameter or zero-dimensional modeling is a low-order technique that is widely used in various applications that require quick estimation of bulk flow quantities, such as flow and pressure at specific anatomical locations.
 
 We introduce `svZeroDSolver`, an efficient and modular package for performing lumped-parameter (zero-dimensional) simulations of cardiovascular blood flow.
+As part of the `Simvascular` open-source project, `svZeroDSolver` allows users to go from medical imaging to fast zero-dimensional evaluations of patient-specific hemodynamics.
 `svZeroDSolver` is written in C++ using an object-oriented framework.
-It designed so that a user can simply specify a `.json` dictionary of lumped-parameter "blocks" -- such as blood vessels, valves, heart chambers, junctions between blood vessels, and boundary conditions (along with their associated parameters) -- which the code uses to automatically assemble and solve the governing equations corresponding to the user-specified vascular model.
+It designed so that simply specifying a `.json` dictionary of lumped-parameter "blocks" -- such as blood vessels, valves, heart chambers, junctions between blood vessels, and boundary conditions (along with their associated parameters) -- allows the code to automatically assemble and solve the governing equations corresponding to the user-specified vascular model.
 In addition, the package includes Python and C++ APIs to facilitate its use with other software packages.
 For example, it can be integrated into Python-based optimization and uncertainty quantification applications.
 It can also be interfaced with high-performance C++/Fortran software for high-fidelity cardiovascular flow simulations, where `svZeroDSolver` can conveniently provide lumped-parameter boundary conditions.
 `svZeroDSolver` also includes an application, called `svZeroDCalibrator`, to automatically calibrate parameters of a given zero-dimensional model to recapitulate independent measurements of hemodynamics at specific anatomical locations from high-fidelity simulations -- thus improving the accuracy of zero-dimensional simulations.
 
-
 # Statement of need
 
 The ability to non-invasively quantify patient-specific hemodynamics via computational simulations has been shown to improve patient outcomes and reduce invasive clinical procedures in large randomized clinical trials [@TAYLOR2023].