The IEEE Standard 1624 provides a foundation for the assessment of organizational reliability capability (ORC). However, to better match the individual characteristics of different industries, this standard needs to be suitably clipped and adjusted, so as to develop customized models for the reliability capability evaluations of different organizations. To evaluate the ORC of China's aviation enterprises effectively, we propose a reliability engineering capability maturity model ( RE-CMM) for China's aviation industry, with adequate consideration of the features closely associated with China's aviation enterprises and China's military standards. The proposed RE-CMM model is established on the theoretical basis of Capability Maturity Model Integration (CMMI), combined with the IEEE standard and China's military standards for Reliability, Maintainability, and Supportability (RMS). Structural equation modeling (SEM) is used to verify the validity of the RE-CMM model. We use a fuzzy method for the evaluation of reliability engineering capability. Detailed steps of reliability engineering capability assessment are also provided for the application of the model. Finally, a case study on a Chinese aviation enterprise is given to illustrate the model and method.Index Terms-Fuzzy integral, multiple index evaluation, reliability capability, triangular fuzzy number. ABBREVIATIONS AND ACRONYMS R&DResearch and Development ORC Organization Reliability Capability REC Reliability Engineering Capability CMM Capability Maturity Model CMMI Capability Maturity Model Integration RE-CMM Reliability Engineering Capability Maturity Model
A risk scenario is a combination of risk events that may result in system failure. Risk scenario analysis is an important part of system risk assessment and avoidance. In engineering activity-based systems, important risk scenarios are related to important events. Critical activities, meanwhile, mean risk events that may result in system failure. This article proposes these definitions of risk event and risk scenario based on the characteristics of risk in engineering activity-based systems. Under the proposed definitions, a risk scenario framework generated based on importance measure analysis is given, in which critical activities analysis, risk event identification, and risk scenario generation are the three main parts. Important risk events are identified according to activities’ uncertain importance measure and important risk scenarios are generated on the basis of a system’s critical activities analysis. In the risk scenario generation process based on importance analysis, the importance degrees of network activities are ranked to identify the subject of risk events, so that risk scenarios can be combined and generated by risk events and the importance of scenarios is analyzed. Critical activities are analyzed by Taguchi tolerance design, mathematical analysis, and Monte Carlo simulation methods. Then the degrees of uncertain importance measure of activities are solved by the three methods and these results are compared. The comparison results in the example show that the proposed method of uncertain importance measure is very effective for distinguishing the importance level of activities in systems. The calculation and simulation results also verify that the risk events composed of critical activities can generate risk scenarios.
BackgroundHypertrophic cardiomyopathy (HCM) is a prevalent cardiovascular disease characterized as asymmetric hypertrophy of ventricular muscles. Cardiac morphological abnormality may result in slight or severe cardiopulmonary symptoms, arrhythmia, heart failure, and even sudden death. Previous studies have shown that HCM was an inherited disease where sixty percent carry mutations in genes encoding sarcomere proteins. However, considering heterogeneous phenotype or prognosis, the underlying mechanisms remain unclear.MethodsThe gene expression profiles of GSE36961 and GSE160997 were analyzed by ‘limma’ and ‘weighted gene co-expression network analysis (WGCNA)’ package in R to identify differentially expressed genes (DEGs) and key modules, respectively. Then, enrichment analysis was performed based on Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Protein-protein interaction network was constructed based on the overlapped genes of DEGs and key modules, and we identified the top 4 hub genes using ‘cytohubba’ according to inner connectivity.ResultsWe identified the red and brown modules as the key modules. Enrichment analysis showed that cellular divalent inorganic cation homeostasis, collagen−containing extracellular matrix, and actin binding were significantly enriched. VSIG4, CD163, FCER1G, and LAPTM5 were identified as hub genes.ConclusionsThis study suggested that VSIG4, CD163, FCER1G, and LAPTM5 might be hub genes associated with the progression of HCM. Further studies are required to elucidate the underlying mechanisms and provide potential therapeutic targets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.