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In the field of ultra-high field MR imaging, the challenges associated with higher frequencies and shorter wavelengths necessitate rigorous attention to multichannel array design. While the need for such arrays remains, and efforts to increase channel counts continue, a persistent impediment—inter-element coupling—constantly hinders development. This coupling degrades current and field distribution, introduces noise correlation between channels, and alters the frequency of array elements, affecting image quality and overall performance. The goal of optimizing ultra-high field MRI goes beyond resolving inter-element coupling and includes significant safety considerations related to the design changes required to achieve high-impedance coils. Although these coils provide excellent isolation, the higher impedance needs special design changes. However, such changes pose a significant safety risk in the form of strong electric fields across low-capacitance lumped components. This process may raise Specific Absorption Rate (SAR) values in the imaging subject, increasing power deposition and, as a result, the risk of tissue heating-related injury. To balance the requirement of inter-element decoupling with the critical need for safety, we suggest a new solution. Our method uses high-dielectric materials to efficiently reduce electric fields and SAR values in the imaging sample. This intervention tries to maintain B1 efficiency and inter-element decoupling within the existing array design, which includes high-impedance coils. Our method aims to promote the full potential of ultra-high field MRI by alleviating this critical safety concern with minimal changes to the existing array setup. [ABSTRACT FROM AUTHOR]

PySPH is an open-source, Python-based, framework for particle methods in general and Smoothed Particle Hydrodynamics (SPH) in particular. PySPH allows a user to define a complete SPH simulation using pure Python. High-performance code is generated from this high-level Python code and executed on either multiple cores, or on GPUs, seamlessly. It also supports distributed execution using MPI. PySPH supports a wide variety of SPH schemes and formulations. These include, incompressible and compressible fluid flow, elastic dynamics, rigid body dynamics, shallow water equations, and other problems. PySPH supports a variety of boundary conditions including mirror, periodic, solid wall, and inlet/outlet boundary conditions. The package is written to facilitate reuse and reproducibility. This article discusses the overall design of PySPH and demonstrates many of its features. Several example results are shown to demonstrate the range of features that PySPH provides. [ABSTRACT FROM AUTHOR]