A combined approach for the simulation of reactive, neutral, partially or fully ionized plasma flows is presented. This is realized in a code framework named “PICLas” for the approximate solution of the Boltzmann equation by particle based methods. PICLas combines the particle-in-cell method for the collisionless Vlasov–Maxwell system and the direct simulation Monte Carlo method for neutral reactive flows. Basic physical and mathematical modeling of both methods is addressed, and some application examples are presented in order to demonstrate the capabilities and the broad applicability of the solution strategy.

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Pressure reactivity indices are used in clinical research as a surrogate marker of the ability of the cerebrovasculature to maintain cerebral autoregulation. The use of pressure reactivity indices in patients with neurological injury represents a potential to move away from population-based physiological targets used in guidelines to individualized physiological targets. The aim of this review is to describe the underlying principles and development of pressure reactivity indices, alongside a critique of how they have been used in clinical research, including their limitations. The primary source literature was identified from a database search of PUBMed and OVID online using the search terms "pressure reactivity index" and "pressure reactivity indices". The evidence base regarding pressure reactivity indices currently remains Level III. Pressure reactivity indices rely on the correlation (-1 to +1) between the arterial blood pressure and intracranial pressure, with negative values indicating intact cerebral autoregulation and positive values indicating dysfunctional cerebral autoregulation. Meaningful data is taken from summary measures and trends. The traumatic brain injury population feature most prominently in the literature. There is limited description of the potential confounding factors that may affect pressure reactivity indices, including physiological parameters and therapeutic interventions. Plotting a pressure reactivity index against a cerebral perfusion pressure can indicate an optimal cerebral perfusion pressure to individualise patient care. There is potential to over interpret optimal cerebral perfusion pressure targets when the values of pressure reactivity indices are close to zero. There is an association between pressure reactivity indices and neurological outcomes, however the use of pressure reactivity indices as a prognostication tool is to be challenged. Average values of cerebral perfusion pressure that are not close to averaged values of optimal cerebral perfusion pressure are also associated with poor outcome. Further research is required to ascertain whether targeting an optimal cerebral perfusion pressure may alter outcome.

A high-order hybridizable discontinuous Galerkin spectral element method (HDGSEM) for Particle-In-Cell (PIC) schemes is presented for the simulation of electrostatic applications on three-dimensional unstructured curved meshes.The electrostatic Poisson equation is solved and optionally a Boltzmann relation for the electron species can be used which leads to non-linear source terms.The hybridizable formulation reduces the total number of unknowns of the field solver, allowing the simulation of large problems. The implementation of the HDGSEM solver in a PIC code is described and validated using several test cases with successive increasing complexity. It is shown that the high-order convergence properties are retained on curvilinear meshes, likewise when material jumps are introduced. The simulation of an ion optic illustrates the applicability of the presented method for complex geometries and large problem sizes.