The prevalence of MCI affected by sex, age,education, which was lower in eastern than that in western China.

This work selected a PV power station located in the low latitude and high altitude plateau area of Sichuan, China, as the research object. The environment, climate, operation and maintenance status of the PV power station were investigated and the dust on PV panels was collected to measure its properties to analyse the source and composition of the dust. The results showed that the main component of the dust was SiO2 and the dust particles were relatively uniform in size and regular in shape but not uniform spherical particles. Meanwhile, EDEM-FLUENT simulation soft wares were employed to simulate the accumulation process of dust on the surface of PV panels at different wind speeds under the installation inclination of 25 degrees and 35 degrees, respectively. Furthermore, systematically analysing the force between the dust and PV panels, exploring the action modes of various forces and sorting out the dominant force were carried out for the establishment of a mechanical model for dust accumulation or dust removal. The force of dust in this PV power station mainly included gravity 10−9~10−8N, van der Waals force 10−9N, electrostatic force 10−9~10−11N and fluid force. Meanwhile, the larger particles almost accumulated in the front row of PV modules while the smaller particles can float farther with the wind. Finally, combined with the mechanical model of dust on the PV panel’s surface, dust’s adhesion process and accumulation mechanism were explained.

The wavelet transform domain LMS algorithm are integrated with variable step-size LMS algorithm, from which a new adaptive filtering algorithm is presented based on discrete wavelet transforms (NDWT-LMS). The algorithm can reduce the self-correlation of input signals effectively and can overcome the conflict between high convergence rate and low steady-state error in LMS algorithm which leading by fixed step-size, The computer simulation results indicate that the new algorithm has higher convergence rate and lower steady-state error to compared with LMS algorithm, it can be applied effectively in the adaptive systems.Keywords-adaptive filtering; wavelet transform; LMS algorithm; the wavelet transforms domain adaptive algorithm; variable stepsize adaptive algorithm