448 research outputs found
Modeling of cavity nucleation, early‐stage growth, and sintering in polycrystal under creep–fatigue interaction
No full textA mechanistic-based cavitation model that considers nucleation, early-stage growth, and sintering under creep–fatigue interaction is proposed to predict the number density of cavities ρ. Both the nucleation and early-stage growth rates, controlled by grain boundary (GB) sliding under tension, are formulized as a function of local normal stress σn. Cavity sintering that occurs during the compression is governed by the unconstrained GB diffusion depending on the σn. Modeling results provide important insights into experimental load-waveform design. First, test with initial compression promotes higher ρ compared to the initial tension, if the unbalanced hold time in favor of tension is satisfied. Second, the ρ value does not have a monotonic dependence on either the compressive hold time or stress, because of their competing effect on nucleation and sintering. Third, the optimum value of stress variation rate exists in terms of obtaining the highest ρ value due to sintering effect
sj-doc-1-jbm-10.1177_03936155231161366 - Supplemental material for Overexpression of complement C5a indicates poor survival and therapeutic response in metastatic renal cell carcinoma
No full textSupplemental material, sj-doc-1-jbm-10.1177_03936155231161366 for Overexpression of complement C5a indicates poor survival and therapeutic response in metastatic renal cell carcinoma by Changjun Yang, Faying Yang, Xiang Chen, Yunpeng Li, Xiaoyi Hu, Jianming Guo and Jiaxi Yao in The International Journal of Biological Markers</p
EXPRESSION OF HEMOPEXIN IN ACUTE REJECTION OF RAT LIVER ALLOGRAFT IDENTIFIED BY SERUM PROTEOMIC ANALYSIS
No full textAcute rejection (AR) and acceptance of allograft after liver transplantation (LTx) remain critical issues that need addressing to improve prognosis. We therefore performed rat orthotopic LTx and proteomic analyses to screen for immune response-related biomarkers in sera. Markers identified were validated at the mRNA and/or protein levels, and the molecules of interest were functionally explored. Compared with syngeneic controls, signs of AR as well as spontaneous acceptance were observed in hematoxylin and eosin-stained sections of liver allografts. In accordance with the severity of AR, 30 protein spots displaying significant changes in abundance were identified using two-dimensional differential gel electrophoresis. Ultimately, 14 serum proteins were sequenced and five spots of interest were identified as hemopexin (HPX). Expression of HPX was significantly and inversely associated with the severity of AR at both the mRNA and protein levels. In vitro, Mt-1, Ho-1, Fth, Ifn-, and Il-17 transcripts were significantly upregulated in lysates of lymphocytes stimulated with HPX, whereas Il-10 markedly was remarkably downregulated. Interferon-, IL-10, and IL-17 proteins in the supernatant of HPX-stimulated lymphocytes were significantly altered in keeping with the mRNA level. Our data facilitated the generation of a proteomic profile to enhance the understanding of rat liver AR. In view of finding that the HPX serum level is negatively associated with the severity of AR of rat liver allograft, we propose that in vitro treatment with HPX regulates cytokine expression in rat lymphocytes
High performance computing for advanced modeling and simulation of building virtual reactor
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Process Materials Scientific Data for Intelligent Service Using a Dataspace Model
No full textNowadays, materials scientific data come from lab experiments, simulations, individual archives, enterprise and internet in all scales and formats. The data flood has outpaced our capability to process, manage, analyze, and provide intelligent services. Extracting valuable information from the huge data ocean is necessary for improving the quality of domain services. The most acute information management challenges today stem from organizations relying on amounts of diverse, interrelated data sources, but having no way to manage the dataspaces in an integrated, user-demand driven and services convenient way. Thus, we proposed the model of Virtual DataSpace (VDS) in materials science field to organize multi-source and heterogeneous data resources and offer services on the data in place without losing context information. First, the concept and theoretical analysis are described for the model. Then the methods for construction of the model is proposed based on users’ interests. Furthermore, the dynamic evolution algorithm of VDS is analyzed using the user feedback mechanism. Finally, we showed its efficiency for intelligent, real-time, on-demand services in the field of materials engineering
An Integrated Solution for Improving Semantic Content Searching in Distributed Environment
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