Soft active materials can generate flexible locomotion and change configurations through large deformations when subjected to an external environmental stimulus. They can be engineered to design 'soft machines' such as soft robots, compliant actuators, flexible electronics, or bionic medical devices. By embedding ferromagnetic particles into soft elastomer matrix, the ferromagnetic soft matter can generate flexible movement and shift morphology in response to the external magnetic field. By taking advantage of this physical property, soft active structures undergoing desired motions can be generated by tailoring the layouts of the ferromagnetic soft elastomers. Structural topology optimization has emerged as an attractive tool to achieve innovative structures by optimizing the material layout within a design domain, and it can be utilized to architect ferromagnetic soft active structures. In this paper, the level-set-based topology optimization method is employed to design ferromagnetic soft robots (FerroSoRo). The objective function comprises a sub-objective function for the kinematics requirement and a sub-objective function for minimum compliance. Shape sensitivity analysis is derived using the material time derivative and adjoint variable method. Three examples, including a gripper, an actuator, and a flytrap structure, are studied to demonstrate the effectiveness of the proposed framework.

Two major problems of ultrasound imaging are low-contrast and speckle noise. Traditionally, before speckle reduction, an enhancement algorithm is employed to improve the quality of the image. However, the noise is enhanced as well. To overcome this drawback, we introduce a novel fuzzy anisotropic diffusion approach for speckle reduction and contrast enhancement. Maximum fuzzy entropy principle is used to map the image from space domain to fuzzy domain. Then, fractional-order partial differential equation is used to remove noise and to preserve edges. Finally, the subpixel operator is utilized as a tuning parameter to achieve the optimal result. We test the proposed method on synthetic and real breast ultrasound (BUS) images. The experimental results demonstrate that the proposed method can preserve the edges and enhance the structural details of the BUS images well while removing speckle noise.