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Recently, a unified stochastic particle (USP) method [14] has been developed for the simulation of multiscale nonequilibrium gas flows. Compared with the conventional stochastic particle methods, such as the direct simulation Monte Carlo (DSMC) method, USP can be applied with much larger time steps and cell sizes as it couples the effects of particle movements and collisions. To extend the applicability of USP to complex nonequilibrium gas flows, we develop a USP solver referred to as SPARTACUS within the framework of SPARTA, which is a widely used software based on the DSMC method for the simulation of rarefied gas flows. Inheriting from SPARTA, SPARTACUS is parallelized with the message passing interface (MPI), and it is open-source under the GNU General Public License (GPL) and released in an online repository with essential documentation, tutorial examples, and benchmark cases. To evaluate the performance of SPARTACUS, the test cases cover from one to three dimensional flows with a wide range of the Knudsen number and Mach number, including Couette flow, lid-driven cavity flow, hypersonic flow past a cylinder, and supersonic flow around a blunt body. The results obtained by SPARTACUS in the rarefied and continuum regimes are in good agreement with DSMC and computational fluid dynamics (CFD) results, respectively. Moreover, SPARTACUS has significant computational efficiency advantage over traditional DSMC solvers, especially for three-dimensional nonequilibrium gas flows. In addition, SPARTACUS shows comparable parallel efficiency with SPARTA, so it is promising to be applied with high performance computing for the simulation of complex multiscale gas flows encountered in engineering problems. Program Title: SPARTACUS CPC Library link to program files: https://doi.org/10.17632/pyb343w7zv.1 Developer's repository link: https://github.com/KKFeng/spartacus Licensing provisions: GNU General Public License version 2 Programming language: C++ External routines/libraries: SPARTA (http://sparta.sandia.gov/) Nature of problem: Multiscale simulation of nonequilibrium gas flows using unified stochastic particle method. Solution method: Unified Stochastic Particle (USP) method. • An open-source unified stochastic particle solver, SPARTACUS, was developed for the simulation of multiscale gas flows. • The results obtained by SPARTACUS in both rarefied and continuum regimes agree well with DSMC or CFD results. • SPARTACUS has significant computational efficiency advantage over traditional DSMC solvers. [ABSTRACT FROM AUTHOR]

• Design a hybrid hardware-driven visual stimulator that can save system computing resources. • Propose a lightweight BCI master control framework for SSVEP-BCI wheelchair signal processing. • Implement a small size, low power, and user-friendly electric wheelchair prototype for system evaluation. Electric wheelchairs, as mobile auxiliary equipment, improve the quality of life and self-independence of the disabled. The brain-computer interface (BCI) is used to establish a direct connection between the brain and the wheelchair, which adopts the electroencephalogram (EEG) signal to control the wheelchair. Compared with other types of BCI, the steady-state visual evoked potentials (SSVEP)-BCI is more suitable to control the electric wheelchair due to the advantages of higher information transmission rate (ITR), higher signal-to-noise ratio (SNR), and less training. However, the existing SSVEP-BCI electric wheelchairs need to be equipped with at least one personal computer to drive the visual stimulator and process EEG signals in real-time. As a result, the electric wheelchair system is complicated, bulky, and limited in movement flexibility, so it is difficult to popularize in real-life scenarios. Therefore, to improve the portability and applicability of the SSVEP-BCI electric wheelchair, a lightweight SSVEP-BCI system is needed, which should be as light and energy-saving as possible while meeting functional requirements. This paper presents an embedded lightweight SSVEP-BCI electric wheelchair with a hybrid stimulator. A hybrid hardware-driven visual stimulator is designed, which combines the advantages of liquid crystal display (LCD) and light-emitting diode (LED) to achieve lower energy consumption than the traditional LCD stimulator. In addition, a lightweight BCI framework is designed to realize BCI program functions on the embedded platform for achieving similar performance as those on a personal computer. Experiments on real systems show that our embedded lightweight SSVEP-BCI electric wheelchair can be successfully operated by all eight subjects with a 93.9% average success rate of command operation. In addition, compared with the traditional LCD stimulator, the hybrid hardware-driven visual stimulator can save up to 27% of energy. [ABSTRACT FROM AUTHOR]