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The purpose of this paper is to show that research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of policy formulation and implementation.

In view of the four dimensions which are internal demand, external pressure, policy innovation environment and service characteristic, a system of factors affecting policy diffusion is established. On this basis, a Multilayer Fuzzy Cognitive Map (MFCM) model for policy diffusion of GPPS is constructed. Nonlinear Hebbian Learning algorithm and genetic algorithm are applied to optimize the two components of the MFCM model, which are relationship between nodes at the same layer and influence weights between nodes at different layers, respectively. Taking Nanjing municipal government purchasing elderly-care services in China as the empirical object, simulation of policy diffusion based on the MFCM model is carried out, aiming to obtain the key factors influencing policy diffusion and the dynamic diffusion mechanism of GPPS policy.

Research results show that, compared with monolayer Fuzzy Cognitive Map, the MFCM model converges faster. In addition, simulation results of policy diffusion indicate that economic development level of jurisdiction, superior pressure, administrative level and operability of services are key influencing factors which are under four dimensions correspondingly. And the dynamic influencing mechanism of key factors has also been learned.

This paper constructs the MFCM model, which is a new approach based on several monolayer FCMs, to study the policy diffusion mechanism.

This study aims to introduce a novel bidirectional soft actuator as an enhancement to conventional pneumatic network actuators. This improvement involves integrating air chambers positioned at specific angles to improve stability, adaptability and grasping efficiency in various environments.

The design approach incorporates air chambers positioned at a 45° angle relative to the horizontal direction at the actuator's terminus, along with additional chambers at a 90° angle. Mathematical models are developed for longitudinal and transverse bending, as well as for obliquely connected cavities, based on the assumption of piecewise constant curvature. Analyses are conducted on output forces, bending characteristics and end contact areas for both transverse and longitudinal ends.

The proposed soft actuator surpasses traditional pneumatic network actuators in gripping area due to the inclusion of a diagonal air cavity and a transverse pneumatic network structure at the terminus. As a result, it provides torsion and gripping force in both directions. Testing on a dedicated platform with two variants of grippers demonstrates superior gripping force capability and performance in complex environments.

Through the design of multiangle chambers, the soft actuator exhibits diverse driving angles and morphological variations, offering innovative design perspectives for industrial grasping.

The design of multiangle chambers facilitates personalized configurations of soft actuators by researchers, enabling tailored angles for specific interaction environments to achieve desired functionalities. This approach offers novel insights into soft actuator design, addressing more prevalent industrial grasping challenges.

This study introduces a novel soft actuator design that significantly enhances gripping capabilities in comparison to conventional pneumatic network actuators. The incorporation of specific air chamber configurations and mathematical modeling provides valuable insights for the development of adaptable and efficient robotic grippers for industrial and household applications.