No abstract

No abstract

Intelligent drug delivery system based on “stimulus-response” mode emerging a promising perspective in next generation lipid-based nanoparticle. Here, we classify signal sources into physical and physiological stimulation according to their origin. The physical signals include temperature, ultrasound, and electromagnetic wave, while physiological signals involve pH, redox condition, and associated proteins. We first summarize external physical response from three main points about efficiency, particle state, and on-demand release. Afterwards, we describe how to design drug delivery using the physiological environment in vivo and present different current application methods. Lastly, we draw a vision of possible future development.

The silicon micromechanical gyroscope, which will be introduced in this paper, represents a novel MEMS gyroscope concept. It is used for the damping of a single-channel control system of rotating aircraft. It differs from common MEMS gyroscopes in that does not have a drive structure, itself, and only has a sense structure. It is installed on a rotating aircraft, and utilizes the aircraft spin to make its sensing element obtain angular momentum. When the aircraft is subjected to an angular rotation, a periodic Coriolis force is induced in the direction orthogonal to both the angular momentum and the angular velocity input axis. This novel MEMS gyroscope can thus sense angular velocity inputs. The output sensing signal is exactly an amplitude-modulation signal. Its envelope is proportional to the input angular velocity, and the carrier frequency corresponds to the spin frequency of the rotating aircraft, so the MEMS gyroscope can not only sense the transverse angular rotation of an aircraft, but also automatically change the carrier frequency over the change of spin frequency, making it very suitable for the damping of a single-channel control system of a rotating aircraft. In this paper, the motion equation of the MEMS gyroscope has been derived. Then, an analysis has been carried to solve the motion equation and dynamic parameters. Finally, an experimental validation has been done based on a precision three axis rate table. The correlation coefficients between the tested data and the theoretical values are 0.9969, 0.9872 and 0.9842, respectively. These results demonstrate that both the design and sensing mechanism are correct.