A New Computed Torque Control System with an Uncertain RBF Neural Network Controller for a 7-DOF Robot

A novel percutaneous puncture robot system is proposed in the paper. Increasing the surgical equipment precision to reduce the patient\u27s pain and the doctor\u27s operation difficulty to treat smaller tumors can increase the success rate of surgery. To attain this goal, an optimized Computed Torque Law (CTL) using a radial basis function (RBF) neural network controller (RCTL) is proposed to improve the direction and position accuracy. BRF neural network with an uncertain term (URBF) which is able to compensate the system error caused by the imprecision of the model is added in the RCTL system. At first, a 7-DOF robotic system is established. It consists of robotic arm and actuator control channels. Now, the RBF compensator is added to the CTL to adjust the robot arm to reduce the position and direction errors. The angle and velocity errors of the robot arm are compensated using the RBF controller. According to the Lyapunov theory, the accuracy of torque control system depends on path tracking errors, inertia of robot, dynamic parameters and disturbance of each joint. Compared to general CTL approaches, the precision of a 7-DOF robot could be improved by adjusting the RBF parameters

Aestivation induces widespread transcriptional changes in the African lungfish

Aestivation is a special ability possessed by some animals to cope with hot and dry environments utilizing dormancy. At a macroscopic level, dormant animals stop moving and eating. At the microscopic level, the expression of a large number of genes in these animals is strictly controlled. However, little is known about what changes occur during aestivation, especially in fish. In this study, we used transcriptome analysis to examine what changes occur in the gills and lungs of the African lungfish (Protopterus annectens) during the maintenance phase of aestivation and speculated on their causes. We found that aestivating transcriptomes were highly similar between gills and lungs. We also found that some genes showed differential expression or alternative splicing, which may be associated with different organs. In addition, differential expression analysis revealed that the lungs maintained significantly higher bioactivity during aestivation, which suggests that the main respiratory organ in aestivating lungfish can transform. Our study provides a reference point for studying the relationship between aestivation and hibernation and further increases understanding of aestivation

Comprehensive Transcriptome Analysis Reveals Accelerated Genic Evolution in a Tibet Fish, Gymnodiptychus pachycheilus

Elucidating the genetic mechanisms of organismal adaptation to the Tibetan Plateau at a genomic scale can provide insights into the process of adaptive evolution. Many highland species have been investigated and various candidate genes that may be responsible for highland adaptation have been identified. However, we know little about the genomic basis of adaptation to Tibet in fishes. Here, we performed transcriptome sequencing of a schizothoracine fish (Gymnodiptychus pachycheilus) and used it to identify potential genetic mechanisms of highland adaptation. We obtained totally 66,105 assembled unigenes, of which 7,232 were assigned as putative one-to-one orthologs in zebrafish. Comparative gene annotations from several species indicated that at least 350 genes lost and 41 gained since the divergence between G. pachycheilus and zebrafish. An analysis of 6,324 orthologs among zebrafish, fugu, medaka, and spotted gar identified consistent evidence for genome-wide accelerated evolution in G. pachycheilus and only the terminal branch of G. pachycheilus had an elevated Ka/Ks ratio than the ancestral branch. Many functional categories related to hypoxia and energy metabolism exhibited rapid evolution in G. pachycheilus relative to zebrafish. Genes showing signature of rapid evolution and positive selection in the G. pachycheilus lineage were also enriched in functions associated with energy metabolism and hypoxia. The first genomic resources for fish in the Tibetan Plateau and evolutionary analyses provided some novel insights into highland adaptation in fishes and served as a foundation for future studies aiming to identify candidate genes underlying the genetic bases of adaptation to Tibet in fishes

Enthusiastically Foster Individual Transport Operations; Actively Exercise Management

>i>Hubei Daily>/i> editor's note: Discussions in this paper centering on the question âWhy Aren't Individual Transport Operations Allowed Unimpeded Development?â have received much notice from leaders and departments at every level; they have also been given strong support by readers. It has brought a major question in the reform of transportation into the limelight through the case studies presented and through the views expressed. This is conducive to the implementation of Circular no. 1 issued by the party's Central Committee earlier this year, which asked that the fight against "leftist" influences be continued, and that new problems in the course of developing state, collective, and individual enterprises simultaneously be correctly handled. The discussions have aroused further support for peasant-operated transportation, toward the end that the rural economy and transport industry both become more viable. This article is a summary of these discussions.

Surviving under pressure

Genomic analysis has shed light on how hadal snailfish have adapted to living at depths of several thousand metres

A Comprehensive Evaluation of Graph Kernels for Unattributed Graphs

Graph kernels are of vital importance in the field of graph comparison and classification. However, how to compare and evaluate graph kernels and how to choose an optimal kernel for a practical classification problem remain open problems. In this paper, a comprehensive evaluation framework of graph kernels is proposed for unattributed graph classification. According to the kernel design methods, the whole graph kernel family can be categorized in five different dimensions, and then several representative graph kernels are chosen from these categories to perform the evaluation. With plenty of real-world and synthetic datasets, kernels are compared by many criteria such as classification accuracy, F1 score, runtime cost, scalability and applicability. Finally, quantitative conclusions are discussed based on the analyses of the extensive experimental results. The main contribution of this paper is that a comprehensive evaluation framework of graph kernels is proposed, which is significant for graph-classification applications and the future kernel research