The artificial potential field approach provides a simple and effective motion planner for robot navigation. However, the traditional artificial potential field approach in practice can have a local minimum problem, i.e., the attractive force from the target position is in the balance with the repulsive force from the obstacle, such that the robot cannot escape from this situation and reach the target. Moreover, the moving object detection and avoidance is still a challenging problem with the current artificial potential field method. In this paper, we present an improved version of the artificial potential field method, which uses a dynamic window approach to solve the local minimum problem and define a danger index in the speed field for moving object avoidance. The new danger index considers not only the relative distance between the robot and the obstacle, but also the relative velocity according to the motion of the moving objects. In this way, the robot can find an optimized path to avoid local minimum and moving obstacles, which is proved by our experimental results.

Ewing sarcoma (ES) is a common primary malignancy in children and adolescents. Progression of treatment methods hasn't contributed a lot to the imrovement of prognosis. To identify potential prognostic biomarkers, a meta-analysis pipeline of multi-gene expression datasets for ES from the Gene Expression Omnibus (GEO) was performed. Three datasets were screened and differential expression genes (DEGs) in ES samples compared with normal tissues were identified through limma package and subjected to network analysis. As a result, 1,470 DEGs were obtained which were mainly involved in biological processes associated with immune response and transcription regulation. Network analysis obtained 22 core genes with high network degree and fold change. Kaplan-Meier analysis based on ES datasets from The Cancer Genome Atlas identified five genes, including glycogen phosphorylase, muscle-associated, myocyte-specific enhancer factor 2C, tripartite motif containing 63, budding uninhibited by benzimidazoses1 and Ras GTPase-activating protein 1, whose altered expression profiles are significantly associated with survival. Changes of their expression values were further confirmed through RT-qPCR in ES cell and normal cell lines. Those genes may be considered as potential prognostic biomarkers of ES and should be helpful for its early diagnosis and treatment.

To improve the collaboration efficiency of the networked manufacturing coalition for automobile die enterprise, the networked manufacturing system framework is put forward. Then the information model, resource model and organization structure model are studied one of the other. The information model contains three layers lengthways and the product lifecycle is divided into 5 stages on landscape; for the resource model, the resource is classified and described, the relationship between resource entities is analyzed. The participants of each member enterprise are grouped according to the task relevance in organization structure model, and collaborative discussion center is constructed for the participants to communicate. On the basis, the workflow model is then discussed, the activity in business process is described with UML, then the UML activity diagram is transformed to Petri net graph, thus the workflow model can be diagnosed and analyzed.

In this paper, a concept of extended Master Model is presented, mould features are classified and the master model of information hierarchy of mould is built. According to feature mapping theory, mapping categories of mould features are defined, mapping from mould features in various stage to cost feature field is implemented, which lays foundation for building cost information model of mould and implementation of cost oriented mould design.