Wireless charging is an important issue in wireless sensor networks, since it can provide an emerging and effective solution in the absence of other power supplies. The state-of-the-art methods employ a mobile car and a predefined moving path to charge the sensor nodes in the network. Previous studies only consider a factor of the network (i.e., residual energy of sensor node) as a constraint to design the wireless charging strategy. However, other factors, such as the travelled distance of the mobile car, can also affect the effectiveness of wireless charging strategy. In this work, we study wireless charging strategy based on the analysis of a combination of two factors, including the residual energy of sensor nodes and the travelled distance of the charging car. Firstly, we theoretically analyze the limited size of the sensor network to match the capability of a charging car. Then, the networked factors are selected as the weights of traveling salesman problem (TSP) to design the moving path of the charging car. Thirdly, the charging time of each sensor node is computed based on the linear programming problem for the charging car. Finally, a charging period for the network is studied. The experimental results show that the proposed approach can significantly maximize the lifetime of the wireless sensor network.

This paper presents a platform technology with experimental results that show the scientists and biologists a way to rapidly investigate and analyze the biological effects of localized extremely low frequency (ELF) electromagnetic field (EMF) on living cells. The proximity effect of the localized ELF-EMF on living cells is revealed using the bio-compatible microplatform on which an on-glass inductive coil array, the source of the localized ELF-EMF in micro scale, is designed, fabricated and operated with a field strength of 1.2 ± 0.1 mT at 60 Hz for cell culturing study. After a 72 h ELF-EMF exposure, HeLa (human cervical cancer) and PC-12 (rat pheochromocytoma) cells exhibit about 18.4% and 12.9% cell proliferation rate reduction, respectively. Furthermore, according to the presented dynamic model, the reduction of the proliferation can be attributed to the interference of signal transduction processes due to the tangential currents induced around the cells.

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