Telocytes had been identified as a peculiar stromal cell type implicated in tissue homeostasis and the development and pathophysiology of diseases. Telocyte existed in most organs and tissues in humans and animals. However, few studies have examined telocytes in ApoE gene deficient mice. In our studies, we verified the existence, the morphology and immunohistochemical characteristics of telocytes in critical organs of the ApoE−/− mice. Male adult ApoE−/− mice were selected as an experimental model. Immunohistochemical bio‐markers, such as CD34, CD117, CD28, Vimentin and PDGFR‐α were utilized to determine the distribution and morphology of telocytes in the heart, liver and kidney. Telocyte expressed positively for CD34 and CD117, and partial telocyte and telopode expressed positively for PDGFR‐α in heart and liver, but negatively in kidney. Double immunofluorescence assays for CD28/Vimentin, CD34/CD117 and CD34/PDGFR‐α were used to demonstrate the biochemistry speciality of telocytes, respectively. The evidence of telocytes in the ApoE‐/‐ mice is the first step of our sturdy, which aims to demonstrate changes in telocytes in atherosclerosis in this animal model.

The existence of the failure transitivity of machine tool components makes the fault transfer probability of components demonstrate dynamic time-variability, which affects the importance of components and further affects the machine maintenance cycle. Therefore, studying fault transfer probability and the importance of machine tool components is necessary. In this article, the fault transfer probability of component is defined according to component fault propagation directed graph and component independent fault and related fault model based on time correlation. Assuming that the fault propagation follows the Markov process, the improved LeaderRank algorithm is applied to evaluate the importance of components by introducing background node and calculating failure impact degree of component on the basis of out-degree. Finally, the specific application is verified by taking the fault information of a certain type of machine as an example.

No abstract

No abstract

In order to solve the problem of weighting factor in the maintenance comprehensive weighted allocation model based on failure rate and design characteristics. Firstly, the fuzzy comprehensive evaluation method is introduced. Secondly, the fuzzy judgment matrix is established by using the three-scale method and the weight is obtained. Then the binary fuzzy contrast is used to establish the relationship matrix of the influencing factors and the evaluation matrix is obtained. The weighting factor is calculated by the fuzzy transformation. When the failure rates vary widely, the allocation results will weak the design characteristics by relying on the failure rate. So the weighting factor should be modified to improve the rationality of the distribution result. Finally, take a machining center as an example to verify the maintenance distribution application.