Humans are born with the ability and the need for affection, but communicating affection as a social behavior is historically bound. Based on the digitized books of Google Ngram Viewer from 1960 through 2008, the present research investigated affectionate communication (AC) in China and the United States, and its changing landscape along with social changes from collectivist to individualistic environments. In particular, we analyzed the frequency in terms of verbal affection (e.g., love you, like you), non-verbal affection (e.g., hug, kiss), and individualism (indicated by the use of first-person singular pronouns such as I, me, and myself) in Chinese and American books. The results revealed an increasing trend for AC in recent decades, although the frequency of affection words was lower in Chinese than in American books. Further, individualism was positively related to the frequency of affection words in both Chinese and American books. These results demonstrate the effect of cultural changes on AC, in that affection exchange becomes popular in adaptation to individualistic urban environments. These findings exemplify a cross-cultural difference in the expression of love and the cultural universality of social change in Eastern and Western societies.

Hybrid wheel–track systems have found extensive applications due to the advantages a combination of wheels and tracks. However, the coupling influence between the wheeled and tracked mechanisms poses a challenge to stable and efficient controller design and implementation. This paper focuses on the lateral dynamic control of a vehicle in scenarios where both tracks and wheels are in contact with the ground. A dynamic model of a vehicle is first established based on the tire brush model and linearized general track model. Based on the dynamic model, a novel adaptive model predictive control (AMPC) method is designed considering the coupling and nonlinearity of the wheels and tracks to simultaneously regulate both mechanisms. Compared with traditional model predictive control approaches, the AMPC controller takes the side-slip angle and slip ratio as constraints to prevent the vehicle from reaching unstable states. Simulations are conducted to validate the effectiveness of the controller, and the results indicate that the controller has the capacity to optimize the objective’s yaw-rate response while maintaining lateral vehicle stability and preventing slip by imposing constraints.

To address the question of which posture trailing-arm vehicles (TAVs) should be adopted while driving, this study introduces an innovative active posture controller (APC) to improve both path-following and handling stability performance. Leveraging a nonlinear tire model that considers corner load variation and wheel camber, alongside the kinematics and double-track model of TAVs, the impact of vehicle body posture on handling performance has been investigated. To fully utilize the four-wheel independent drive and posture adjustable characteristics of the TAV mechanisms, an integrated nonlinear model predictive control (NMPC) combining APC and tire forces distribution is devised. Through simulations conducted using Simulink-Multibody (2023a), the effectiveness of the proposed controller is demonstrated, particularly when compared to the scheme that does not account for the unique posture adjustment mechanisms of TAVs.