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In this paper, the ubiquitous muti-beam beamwidth of the Rotman lens is tentative studied using widening technique. Phase weighted beam synthesis is adopted, and matched cables are connected between ports of the lens array and antennas. The measured widening pattern and un-widening pattern are compared, which demonstrates that the beam of the Rotman lens can be widened through phase weighting. Then, the measured database is analyzed. Results show that, the phase deviation of phase value inputted into the ports of the lens array must be considered when widening the beam.

The purpose of this paper is to study the effects of clothing pressure on blood circulation during gymnastics sports. First, the values of pressure and blood circulation in static and dynamic states were measured on 8 young females with body size similar to the standard body. Then the change rate of Blood Velocity and Blood Flow were found under dynamic states significantly increased. At the same time, using SPSS software suggested that the change rate of Blood Velocity and Blood Flow are affected by pressure. The pressure of the gymnastics tights, Blood Velocity and Blood Flow are positively correlated. The pressure of text sites, Blood Velocity and Blood Flow are positively related. At last it helps to use blood circulation indexes as an important criterion to evaluate clothing comfort.

Due to the fact that each sensor node of wireless sensor networks (WSNs) is usually powered by batteries which cannot be recharged in most cases, there exist a contradiction between the limited energy supply and the demand of a long network lifetime. The emerging compressed sensing (CS) theory provides a promising scheme to alleviate this contradiction. The existing methods based on both CS and sparse random projections may save energy to some extent, they still result in some unnecessary energy consumption. In order to further save the energy, this paper proposes an alternate data gathering method based on sparse random projections. In the proposed method, we adopt an alternate strategy, that is, the sensor nodes are randomly divided into two groups, one group monitors the data and the other keeps silence in a period, and they switch the duty in the next period. In addition, the ill-posed problem of signal recovery may be solved because monitoring data may be viewed as compressible signal in general. So the proposed method can save the energy and guarantee the balanced load. Experimental results show that the proposed method consumes less energy to obtain almost same reconstruction quality of the signal, compared with the existing methods based on random projections.