Expression of DHS1 in cotton is induced upon infection by Verticillium dahliae , and overexpression of GhDHS1 endows transgenic Arabidopsis plants excellent Verticillium resistance. Verticillium wilt is caused by a soil-borne fungus Verticillium dahliae. Resistance in most cotton cultivars is either scarce or unavailable, making Verticillium wilt a major obstacle in cotton production. Here, we identified a 3-deoxy-7-phosphoheptulonate synthase (DHS, EC 4.1.2.15) gene from Gossypium hirsutum, named GhDHS1. Its 1620 bp open reading frame encodes a putative 59.4 kDa protein. Phylogenetic analysis indicated that GhDHS1 is clustered in a clade with potato and tomato DHSs that can be induced by wounding and elicitors, respectively. Expression analysis demonstrated that GhDHS1 is constitutively expressed in cotton roots and stems, but transcripts are rare or non-existent in the leaves. Subcellular localization showed that GhDHS1 occurs in the plastids. When plants of three cultivars were inoculated with V. dahliae, DHS1 expression was more significantly up-regulated in the roots of resistant G. barbadense cv. Pima90-53 and G. hirsutum cv. Jimian20 than in the susceptible G. hirsutum cv. Han208. This suggested that DHS1 is involved in the cotton resistance to Verticillium wilt. Furthermore, GhDHS1 overexpressing transgenic lines of Arabidopsis were developed via Agrobacterium tumefaciens-mediated transformation. Compared with the untransformed WT (wild type), these transgenic plants showed excellent Verticillium wilt resistance with a significantly lower disease index. The overexpressing transgenic lines also had significantly longer primary roots and greatly increased xylem areas under V. dahliae infection. Overall, our results indicate that GhDHS1 performs a role in the cotton resistance to V. dahliae and would be potential to breeding cottons of Verticillium wilt resistance.

The funct i on of the servo p latform i s to control the borehole's deviat i on and or i entation by us i ng an automatic control method to dr i ve the platform sus p end i ng at a special angle. However, i t i s not an easy job to control th i s cylindr i cal and rotat i ng platform at a part i cular angle under the complex downhole env i ronment. The key to solve th i s p roblem is to establish a su i table nonl i near model. Based on the structure analysis of the p latform, a general law of dynam i cs equation is obtained by analyzing friction, dr i ll i ng fluid shock, eccentric action, etc. A hydraulic driving torque test has been done, wh i ch i nd i cates that the dynam i cs analys i s i s reasonable. The model l i es the foundat i on for the research of p latform's control method and the improvement of mechan i cal des i gn.

Based on the generate mechanism of rolling bearing fault signal and its modulation model in the process of spreading, an improved method that combining Hilbert transformation and Stochastic Resonance (SR) is proposed for rolling bearing fault features extraction. Subsequently, the method is used to extract fault signal features from three kinds of typical faults, the surface damage of the inner ring, outer ring stripping injury and roller electrical erosion. First, low frequency envelope components are acquired from rolling bearing vibration signals through Hilbert transformation. Then, depending on the advantage of SR that SR is immune to noise and sensitive to periodic signal, cyclical faults signal of the low frequency envelope is highlighted by using the variable step size solution that can overcome adiabatic condition limitation of SR system. The experimental results show that the algorithm can extract the fault feature and identify the fault type effectively.

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