Future smart mobile electronics and wearable robotics that can perform delicate activities controlled by artificial intelligence can require rapid motion actuators working at low voltages with acceptable safety and improved energy efficiency. Accordingly, ionic soft actuators can have great potential over other counterparts because they exhibit gentle movements at low voltages, less than 2 V. However, these actuators currently show deficient performances at sub‐1 V voltages in the high‐frequency range because of the lack of electrode materials with the vital antagonistic properties of high capacitance and good conductivity. Herein, a mutually exclusive nanohybrid electrode (pMoS2‐nSNrGO) is reported consisting of oxide‐doped p‐type molybdenum‐disulfide and sulfur‐nitrogen‐codoped n‐type reduced‐graphene‐oxide. The pMoS2‐nSNrGO electrode derives high capacitance from MoS2 and good charge transfer between the two components from p‐n nano‐junctions, resulting in excellent actuation performances (670% improvement compared with rGO electrode at 0.5 V and 1 Hz, together with fast responses up to 15 Hz). With such excellent performances, these actuators can be successfully applied to realize an artificial soft robotic finger system for delicately touching the fragile surfaces of smartphones and tablets. The mutually exclusive pMoS2‐nSNrGO electrode can open a new way to develop high‐performance soft actuators for soft robotic applications in the future.

Background The RNF213 ( ring finger protein 213 gene) variant R4810K is a susceptibility allele not only for Moyamoya disease (MMD) but also for intracranial atherosclerosis (ICAS) in East Asian populations. We hypothesized that this variant would affect the distribution of ICAS and recurrence of cerebrovascular events. Methods and Results We conducted a prospective study of patients with ICAS and MMD using high‐resolution magnetic resonance imaging and RNF213 R4810K genotyping. Patients were included in the ICAS group when relevant plaques existed on high‐resolution magnetic resonance imagingand in the MMD group when they carried the variant and high‐resolution magnetic resonance imaging showed no plaques but characteristic features of MMD. We compared clinical and neuroimaging features of patients with ICAS‐ RNF213 + with patients with ICAS‐ RNF213 − and of patients with MMD. Of 477 patients, 238 patients were in the ICAS group and 239 were in the MMD group. Among patients with ICAS, 79 patients (33.2%) were in the ICAS‐ RNF213 + group and 159 (66.8%) in the ICAS‐ RNF213 − group. Tandem lesions were significantly more common in the ICAS‐ RNF213+ group than in the ICAS‐ RNF213 − group (40.3% versus 72.2%, P <0.001), and their distributions were similar between the ICAS‐ RNF213+ and MMD groups. The presence of the R4810K variant (hazard ratio [HR], 3.203; 95% CI, 1.149–9.459; P =0.026) and tandem lesions (≥3) (HR, 8.315; 95% CI, 1.930–39.607; P =0.005) were independently associated with recurrent cerebrovascular events. Conclusions Patients with ICAS carrying the RNF213 R4810K variant showed clinical and imaging features distinct from patients with ICAS without the variant, suggesting that the R4810K variant plays a role in intracranial atherosclerosis in East Asian patients.

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Wind noise in road vehicles is being made much quieter to satisfy customers' demands for comfortable driving environments. The interaction between outside flows and exterior surfaces at the front and sides of a vehicle forms a strong swirling fluid structure called A-pillar vortex which is one of the most crucial wind noise sources. The geometrical characteristics of the A-pillar can determine the size or strength of the vortex structure. It is tremendously time-intensive and costly to change the shape of the A-pillar if it cannot be modified in the early development stage. For early determination of its shape, a reliable numerical methodology to predict vehicle interior noise due to the A-pillar vortex should be applied. This can be very challenging because the numerical method should simulate the complicated fluid behaviors as noise sources and the structural motions acting as transmission and propagation paths with acceptable precision. In this study, various numerical solvers are validated as the predictive tool of the interior transmitted noise in a simplified vehicle model. The solvers examined in the open benchmark study use various computational fluid and vibro-acoustic methods. It is shown that most of the software has prediction ability enough to industrial purposes.