SUMMARYSoybean is an important oil- and protein-producing crop and over the last few decades soybean genetic transformation has made rapid strides. The probability of occurrence of transgene flow should be assessed, although the discrimination of conventional and transgenic soybean seeds and their hybrid descendants is difficult in fields. The feasibility of non-destructive discrimination of conventional and glyphosate-resistant soybean seeds and their hybrid descendants was examined by a multispectral imaging system combined with chemometric methods. Principal component analysis (PCA), partial least squares discriminant analysis (PLSDA), least squares-support vector machines (LS-SVM) and back propagation neural network (BPNN) methods were applied to classify soybean seeds. The current results demonstrated that clear differences among conventional and glyphosate-resistant soybean seeds and their hybrid descendants could be easily visualized and an excellent classification (98% with BPNN model) could be achieved. It was concluded that multispectral imaging together with chemometric methods would be a promising technique to identify transgenic soybean seeds with high efficiency.
The infrared (IR) thermography diagnostic has recently been upgraded to achieve real-time temperature measurement and feedback capability in the experimental advanced superconducting tokamak (EAST). A new control and data acquisition program for IR camera is developed with online temperature calibration and compensation. Reflective memory (RFM) is configured in the data acquisition system for real-time data transmission to the plasma control system (PCS). Based on the upgraded IR thermography diagnostic, detachment plasma has been achieved for the first time in EAST with active temperature feedback. The divertor impurity seeding system is used to inject a sequence of short neon impurity pulses with 50% D 2 to increase the edge radiation of the plasma particles. The temperature of the divertor target plates decreases to the preset target value and the divertor detachment has been realized with no serious reduction of plasma stored energy and confinement observed in the temperature feedback control phase. As a new feedback control method, the IR temperature feedback control shows great application prospects for the temperature and heat flux control of the first wall components in future long pulse operation of EAST.
Silicone rubber (SR) filled with different concentrations of carbon nanotubes (CNTs), carbon black (CB) and (CNTs/CB) hybrid fillers was fabricated by melt blending. The effects of filler type on the electrical properties and piezoresistive properties (in the region of the percolation) of the conductive SR composites were studied. Percolation threshold of CNTs, CB and (CNTs/CB) based composites was found to be 0.20, 0.255 and 0.22 volume fraction respectively. The piezoresistive sensitivity G R of these conductive SR composites, dependent on different filler types, was 0.8549, 0.7267 and 0.9361 respectively. Compared to CB/SR and CNTs/SR, CNTs/CB/ SR revealed an unexpectedly high G R , which indicated that the synergistic effects have formed in CNTs/CB network. In addition, microscopic analysis (SEM) can also explain the existence of synergies. A model describing the electrical percolation of mixed carbon fillers CNTs and CB is proposed. The experimental value (0.22) of hybrid filler systems is smaller than the theoretical value (0.23), which can prove the existence of synergies once again.
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