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The effect of Sr2+ doping on the microstructural, electrical and mechanical properties of 0.93(Bi0.5Na0.5)TiO3–0.07BaTiO3 ceramics was investigated. The X-ray diffraction and Raman results show the phase transition from tetragonal phase to rhombohedral phase induced by Sr2+ ions. The Sr2+ doping promotes grain growth, but refines grains with Sr2+ content continuously increasing. Three dielectric anomalies at Td, Tp and Tm are obvious, and Td is seriously affected by Sr2+ content. The Td peak is confirmed by the T1 peak at dynamic mechanical analysis. The coercive field (Ec) and remnant polarization (Pr) are modified by grain size effect and phase structure induced by Sr2+ doping. The piezoelectric coefficient can be effectively improved by Sr2+ doping.

MicroRNAs (miRNAs) are short noncoding RNAs that can regulate target gene expression at the posttranscriptional level. It has been reported that bta-miR-145 shows differential expression between the different lactation stages of bovine mammary glands, but the function of bta-miR-145 in normal mammary glands remains unknown. The overexpression of bta-miR-145 significantly decreased the proliferation of mammary epithelial cells (p .05), whereas the IRS1 protein level was changed significantly after bta-miR-145 mimic or inhibitor transfection for 72 h (p

Parameter adjustment that maximizes the energy efficiency of cognitive radio networks is studied in this paper where it can be investigated as a complex discrete optimization problem. Then a quantum-inspired bacterial foraging algorithm (QBFA) is proposed. Quantum computing has perfect characteristics so as to avoid local convergence and speed up the optimization of QBFA. A proof of convergence is also given for this algorithm. The superiority of QBFA is verified by simulations on three test functions. A novel parameter adjustment method based on QBFA is proposed for resource allocation of green cognitive radio. The proposed method can provide a globally optimal solution for parameter adjustment in green cognitive radio networks. Simulation results show the proposed method can reduce energy consumption effectively while satisfying different quality of service (QoS) requirements.

In order to effectively solve combinatorial optimization problems, a membrane-inspired quantum bee colony optimization (MQBCO) is proposed for scientific computing and engineering applications. The proposed MQBCO algorithm applies the membrane computing theory to quantum bee colony optimization (QBCO), which is an effective discrete optimization algorithm. The global convergence performance of MQBCO is proved by Markov theory, and the validity of MQBCO is verified by testing the classical benchmark functions. Then the proposed MQBCO algorithm is used to solve decision engine problems of cognitive radio system. By hybridizing the QBCO and membrane computing theory, the quantum state and observation state of the quantum bees can be well evolved within the membrane structure. Simulation results for cognitive radio system show that the proposed decision engine method is superior to the traditional intelligent decision engine algorithms in terms of convergence, precision and stability. Simulation experiments under different communication scenarios illustrate that the balance between three objective functions and the adapted parameter configuration is consistent with the weights of three normalized objective functions.

A micro-emulsion method was used to prepare TiO2-coated carbon nanotubes (ME-TCNTs). The physico-chemical properties of these composites were characterized by modern analytical tools. Crystalline TiO2 within the composites was composed solely of anatase. Carbon nanotubes (CNTs) within the composites were virtually uniformly covered with TiO2. CNT addition increased the surface area and the amount of hydroxyl groups on the composite surface, which suppressed the recombination of photo-generated electron/hole pairs (excitons). The composite photoactivity was greater than that of pure TiO2 and the commercial photocatalyst P25 for methylene blue degradation, predominantly due to the effect of CNT addition. An optimal TiO2 loading of 12% was found to result in the highest photoactivity in comparison with other two loadings (6% and 15%). Too little TiO2 or excessive CNT addition shielded the TiO2 and reduced the UV intensity, due to photon scattering by the bare CNTs. However, a high TiO2 content was found to be ineffective in suppressing exciton recombination because of the large distance between the TiO2 and CNTs. The photoactivity of ME-TCNTs was greater than that of TiO2 coated carbon nanotubes (TiO2-CNTs) prepared by the sol–gel method. The uniform nanometer-scale TiO2 layer on the CNT surface provided a high concentration of surface hydroxyl groups, a low exciton recombination rate and a high surface area.