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This paper analysis the common fault types of primary Electrical Power Steering system, meanwhile classify every fault. It provides the basis for further troubleshooting and maintenance. At the same time this paper propose a practical working principle of fault-tolerant, in order to make the EPS system more security and durability.

Abstract Background Accurate breed identification is essential for the conservation and sustainable use of indigenous farm animal genetic resources. In this study, we evaluated the phylogenetic relationships and genomic breed compositions of 13 sheep breeds using SNP and InDel data from whole genome sequencing. The breeds included 11 Chinese indigenous and 2 foreign commercial breeds. We compared different strategies for breed identification with respect to different marker types, i.e. SNPs, InDels, and a combination of SNPs and InDels (named SIs), different breed-informative marker detection methods, and different machine learning classification methods. Results Using WGS-based SNPs and InDels, we revealed the phylogenetic relationships between 11 Chinese indigenous and two foreign sheep breeds and quantified their purities through estimated genomic breed compositions. We found that the optimal strategy for identifying these breeds was the combination of DFI_union for breed-informative marker detection, which integrated the methods of Delta, Pairwise Wright's FST, and Informativeness for Assignment (namely DFI) by merging the breed-informative markers derived from the three methods, and KSR for breed assignment, which integrated the methods of K-Nearest Neighbor, Support Vector Machine, and Random Forest (namely KSR) by intersecting their results. Using SI markers improved the identification accuracy compared to using SNPs or InDels alone. We achieved accuracies over 97.5% when using at least the 1000 most breed-informative (MBI) SI markers and even 100% when using 5000 SI markers. Conclusions Our results provide not only an important foundation for conservation of these Chinese local sheep breeds, but also general approaches for breed identification of indigenous farm animal breeds.

The study is based on 162 Agricultural Cooperatives in Zhejiang Province. On the basis of literature, this paper analyzes the service situation of agricultural production cooperatives, including production, processing and financing. The influencing factors are discussed theoretically and tested empirically. The study concluded that most cooperatives provide pre-and post-production supply services to participating members, as well as financing services. In addition, in order to strengthen human resources, the leaders of each cooperative are encouraged and the service awareness of the agricultural industrial chain of the cooperative is enhanced; the membership is expanded to facilitate agricultural production and the provision of financing services by the cooperative. At the same time, the increase in post-natal strength provides a positive impact on cooperatives and optimizes the overall market environment for cooperatives. Of course, the agricultural industrial chain services provided by cooperatives are also affected by the variety of products.

In order to fulfill rapid and trace detection of heavy metals, in the study, gold-nanoparticlesgraphene modified glass carbon electrodes were used to detect lead(Pb(II)) ions. The lead ion (Pb(II)) standard sample in acetic acid-sodium acetate buffer solution was detected by the modified electrode, and the detection conditions were optimized. Under the optimized conditions, in the buffer solution with pH=4.5, the lead ions peak current showed excellent linear relationship with the lead ion concentration in the range of 0.2~50μg/L (R2=0.995), and the minimum detection limit was 0.34μg/L. At the same time, the actual water samples were determined by nano-gold-graphene/glass carbon electrodes for lead ions, and the recovery ranges was 92.94%~101.47%, which showed that the gold-nanoparticles-graphene/glass carbon electrodes possessed significant detection performance for the actual water samples.

This paper aims at the pilot study of the object following for automated guided vehicle (AGV).The proposed approach utilizes the laser range finder (LRF) to detect the distances of all obstacles surrounded in a specified angle range. The AGV can autonomously follow the assigned object according to the rational reflection intensity and range of the object sensed from LRF. The cruise speed control for a moving object depending on the distance between AGV and this object is considered since it is one of the crucial parameters for object following. This paper also discusses the influences of the sensor delay which is an indispensable issue in both control law and control logic. This pilot study employs a down scaled AGV to verify the feasibilities of the steering, accelerating, braking, and object following algorithms developed for AGVs.