Single-Valued Neutrosophic Set Correlation Coefficient and Its Application in Fault Diagnosis

With the increasing automation of mechanical equipment, fault diagnosis becomes more and more important. However, the factors that cause mechanical failures are becoming more and more complex, and the uncertainty and coupling between the factors are getting higher and higher. In order to solve the given problem, this paper proposes a single-valued neutrosophic set ISVNS algorithm for processing of uncertain and inaccurate information in fault diagnosis, which generates neutrosophic set by triangular fuzzy number and introduces the formula of the improved weighted correlation coefficient. Since both the single-valued neutrosophic set data and the ideal neutrosophic set data are considered, the proposed method solves the fault diagnosis problem more effectively. Finally, experiments show that the algorithm can significantly improve the accuracy degree of fault diagnosis, and can better satisfy the diagnostic requirements in practice.

Gene Set Correlation Analysis and Visualization Using Gene Expression Data

Background: Gene set enrichment analyses (GSEA) provide a useful and powerful approach to identify differentially expressed gene sets with prior biological knowledge. Several GSEA algorithms have been proposed to perform enrichment analyses on groups of genes. However, many of these algorithms have focused on identification of differentially expressed gene sets in a given phenotype. Objective: In this paper, we propose a gene set analytic framework, Gene Set Correlation Analysis (GSCoA), that simultaneously measures within and between gene sets variation to identify sets of genes enriched for differential expression and highly co-related pathways. Methods: We apply co-inertia analysis to the comparisons of cross-gene sets in gene expression data to measure the costructure of expression profiles in pairs of gene sets. Co-inertia analysis (CIA) is one multivariate method to identify trends or co-relationships in multiple datasets, which contain the same samples. The objective of CIA is to seek ordinations (dimension reduction diagrams) of two gene sets such that the square covariance between the projections of the gene sets on successive axes is maximized. Simulation studies illustrate that CIA offers superior performance in identifying corelationships between gene sets in all simulation settings when compared to correlation-based gene set methods. Result and Conclusion: We also combine between-gene set CIA and GSEA to discover the relationships between gene sets significantly associated with phenotypes. In addition, we provide a graphical technique for visualizing and simultaneously exploring the associations of between and within gene sets and their interaction and network. We then demonstrate integration of within and between gene sets variation using CIA and GSEA, applied to the p53 gene expression data using the c2 curated gene sets. Ultimately, the GSCoA approach provides an attractive tool for identification and visualization of novel associations between pairs of gene sets by integrating co-relationships between gene sets into gene set analysis.

Relations Between the Behavioral Approach System (BAS) and Self-Reported Life History Traits

The behavioral approach system (BAS) has been shown to be important in everyday life. However, its putative evolutionary origins have not been extensively studied. The purpose of this study was to explore relationships between BAS processes and life history strategies, or lifestyles, within life history theory. The BAS scales were assessed by the Reinforcement Sensitivity Theory of Personality Questionnaire (RST-PQ) and Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ-20), while lifestyles were measured by the Mini-K. Data from 457 participants (173 males) were analyzed by structural equation modelling, followed by set correlation to examine personality and Mini-K relationships. The structural model showed that RST-PQ Reward Interest, Goal-Drive Persistence and Reward Reactivity correlated with a slow lifestyle, while RST-PQ Impulsivity and (SPSRQ) Sensitivity to Reward (SR) did not correlate with the Mini-K. However, set correlation analysis revealed that SR correlated negatively with the Mini-K subscale Experience in romantic relationship and highlighted the importance of Insight, planning, and control in explaining the role of the BAS within slow lifestyle strategy. The findings are discussed in terms of possible evolutionary origins of the BAS.

Research on Interface Symbols of Sand Groups and Characters of Interior Gyrations of Heidimiao Layer in Yingtai Area

This article is intended to identify interface symbols of sand groups by combining logging data with seismic data, and set correlation symbols of 8 sand groups in strata Nen 3 (H1) and Nen 4 (H2) of Nenjiang group. Characteristics of interior gyrations of those sand groups are analyzed according to core and logging data. Besides, sand group features of a single well are expected to be studied in this article. Upon the data and analysis, foundation information is provided for the research on sand distribution characteristics of Heidimiao oil layer and controlling factors of oil and water distribution.