RESUMEN
This study investigates the dynamic characteristics of natural rubber (NR)/polybutadiene rubber (PBR)-based hybrid magnetorheological elastomer (MRE) sandwich composite beams through numerical simulations and finite element analysis, employing Reddy's third-order shear deformation theory. Four distinct hybrid MRE sandwich configurations were examined. The validity of finite element simulations was confirmed by comparing them with results from magnetorheological (MR)-fluid-based composites. Further, parametric analysis explored the influence of magnetic field intensity, boundary conditions, ply orientation, and core thickness on beam vibration responses. The results reveal a notable 10.4% enhancement in natural frequencies in SC4-based beams under a 600 mT magnetic field with clamped-free boundary conditions, attributed to the increased PBR content in MR elastomer cores. However, higher magnetic field intensities result in slight frequency decrements due to filler particle agglomeration. Additionally, augmenting magnetic field intensity and magnetorheological content under clamped-free conditions improves the loss factor by from 66% to 136%, presenting promising prospects for advanced applications. This research contributes to a comprehensive understanding of dynamic behavior and performance enhancement in hybrid MRE sandwich composites, with significant implications for engineering applications. Furthermore, this investigation provides valuable insights into the intricate interplay between magnetic field effects, composite architecture, and vibration response.
RESUMEN
Information exchange between brain regions is key to understanding information processing for social decision-making, but most analyses ignore its dynamic nature. New insights on this dynamic might help us to uncover the neural correlates of social cognition in the healthy population and also to understand the malfunctioning neural computations underlying dysfunctional social behavior in patients with mental disorders. In this work, we used a multi-round bargaining game to detect switches between distinct bargaining strategies in a cohort of 76 healthy participants. These switches were uncovered by dynamic behavioral modeling using the hidden Markov model. Proposing a novel model of dynamic effective connectivity to estimate the information flow between key brain regions, we found a stronger interaction between the right temporoparietal junction (rTPJ) and the right dorsolateral prefrontal cortex (rDLPFC) for the strategic deception compared with the social heuristic strategies. The level of deception was associated with the information flow from the Brodmann area 10 to the rTPJ, and this association was modulated by the rTPJ-to-rDLPFC information flow. These findings suggest that dynamic bargaining strategy is supported by dynamic reconfiguration of the rDLPFC-and-rTPJ interaction during competitive social interactions.