Sugar level is an important determinant of fruit taste and consumer preferences. However, upstream regulators that control sugar accumulation during fruit maturation are poorly understood. In the present work, we found that glucose is the main sugar in mature pitaya (Hylocereus) fruit, followed by fructose and sucrose. Expression levels of two sucrose-hydrolyzing enzyme genes HpINV2 and HpSuSy1 obviously increased during fruit maturation, which were correlated well with the elevated accumulation of glucose and fructose. A WRKY transcription factor HpWRKY3 was further identified as the putative binding protein of the HpINV2 and HpSuSy1 promoters by yeast one-hybrid and gel mobility shift assays. HpWRKY3 was localized exclusively in the nucleus and possessed trans-activation ability. HpWRKY3 exhibited the similar expression pattern with HpINV2 and HpSuSy1. Finally, transient expression assays in tobacco leaves showed that HpWRKY3 activated the expressions of HpINV2 and HpSuSy1. Taken together, we propose that HpWRKY3 is associated with pitaya fruit sugar accumulation by activating the transcriptions of sucrose metabolic genes. Our findings thus shed light on the transcriptional mechanism that regulates the sugar accumulation during pitaya fruit quality formation.

Active contour model is an important research field in computer vision and many researchers studied the variational method in recent years. The traditional snake model is unable to converge to the concave area and it has a lower convergence. By improving the external energy, researchers introduced a gradient vector flow active contour model (GVFsnake). Several standard images are used to segmenting experiments, and the results show that GVF has obvious advantages compared with traditional snake model in the iteration number of force field. Experiments show that the method is faster and better to converge in the concave area. The edge information can be kept well and diffused more quickly.

This paper proposes a new approach to determining the complex system design for a product mix comprising complex hierarchies of subassembly and components. Pareto Ant Colony Optimisation as an especially effective meta-heuristic for solving the problem of complex system design was introduced in this paper. A Pareto Optimal Set of complex system in which only the non dominated solutions allow ants to deposit pheromones over the time and cost pheromone matrices after certain generation runs. Simulation results show that the model for complex system and the hybrid algorithms are effective to the design of complex system.

Aimed at the problem of low accuracy rate for face recognition and speaker recognition in noisy environment, a multi-biometric model fusing face features and speech features is presented by combining Normalization and SVM theory based on the research of feature level fusion. Face features and speech features are first extracted by pulse coupled neural network and VQ-SVM respectively. Then the distance between tested people and template people is calculated after getting the fused feature on the feature level fusion. In order to reduce the computational cost and improve the recognition performance, matching distance is normalized and finally recognized by SVM. Experiment on the ORL database show that even when the signal to noise ratio is declined, recognition rate of the fused system is clearly higher than the single system under noisy environment and the purpose of identity recognition is achieved.