Identification of Two Vulnerability Features: A New Framework for Electrical Networks Based on the Load Redistribution Mechanism of Complex Networks

This paper proposes a new framework to analyze two vulnerability features, impactability and susceptibility, in electrical networks under deliberate attacks based on complex network theory: these two features are overlooked but vital in vulnerability analyses. To analyze these features, metrics are proposed based on correlation graphs constructed via critical paths, which replace the original physical network. Moreover, we analyze the relationship between the proposed metrics according to degree from the perspective of load redistribution mechanisms by adjusting parameters associated with the metrics, which can change the load redistribution rules. Finally, IEEE 118- and 300-bus systems and a realistic large-scale French grid are used to validate the effectiveness of the proposed metrics

A fault prediction method for catenary of high-speed rails based on meteorological conditions

Fault frequency of catenary is related to meteorological conditions. In this work, based on the historical data, catenary fault frequency and weather-related fault rate are introduced to analyse the correlation between catenary faults and meteorological conditions, and further the effect of meteorological conditions on catenary operation. Moreover, machine learning is used for catenary fault prediction. As with the single decision tree, only a small number of training samples can be classified correctly by each weak classifier, the AdaBoost algorithm is adopted to adjust the weights of misclassified samples and weak classifiers, and train multiple weak classifiers. Finally, the weak classifiers are combined to construct a strong classifier, with which the final prediction result is obtained. In order to validate the prediction method, an example is provided based on the historical data from a railway bureau of China. The result shows that the mapping relation between meteorological conditions and catenary faults can be established accurately by AdaBoost algorithm. The AdaBoost algorithm can accurately predict a catenary fault if the meteorological conditions are provided. Document type: Articl

Electrical Network Operational Vulnerability Evaluation Based on Small-World and Scale-Free Properties

Assessment of electrical network vulnerability based on complex network theory (CNT) has attracted increasing attention. However, CNT focuses on analyzing the structural vulnerability and has significant limitations regarding operational vulnerability. To address the lack of a comprehensive CNT-based framework to assess operational vulnerability, a temporal-spatial correlation graph (TSCG) that considers the topological, physical, and operational characteristics of electrical networks is proposed. To better assess vulnerability, two metrics, i.e., impact ability and susceptibility of branches, based on symmetric entropy from the load redistribution mechanism of electrical networks and their corresponding TSCGs are proposed. Applications to IEEE 39-bus system, IEEE 118-bus system, and French grid demonstrate that the proposed TSCGs have distinctive features that can intuitively and simply reveal the features of impact ability and susceptibility in CNT

Genome-Wide Association Studies Identified Three Independent Polymorphisms Associated with α-Tocopherol Content in Maize Kernels

Tocopherols are a class of four natural compounds that can provide nutrition and function as antioxidant in both plants and animals. Maize kernels have low α-tocopherol content, the compound with the highest vitamin E activity, thus, raising the risk of vitamin E deficiency in human populations relying on maize as their primary vitamin E source. In this study, two insertion/deletions (InDels) within a gene encoding γ-tocopherol methyltransferase, Zea mays VTE4 (ZmVTE4), and a single nucleotide polymorphism (SNP) located ∼85 kb upstream of ZmVTE4 were identified to be significantly associated with α-tocopherol levels in maize kernels by conducting an association study with a panel of ∼500 diverse inbred lines. Linkage analysis in three populations that segregated at either one of these three polymorphisms but not at the other two suggested that the three polymorphisms could affect α-tocopherol content independently. Furthermore, we found that haplotypes of the two InDels could explain ∼33% of α-tocopherol variation in the association panel, suggesting ZmVTE4 is a major gene involved in natural phenotypic variation of α-tocopherol. One of the two InDels is located within the promoter region and associates with ZmVTE4 transcript level. This information can not only help in understanding the underlying mechanism of natural tocopherol variations in maize kernels, but also provide valuable markers for marker-assisted breeding of α-tocopherol content in maize kernels, which will then facilitate the improvement of maize as a better source of daily vitamin E nutrition

Tectonic Features of the Wufeng–Longmaxi Formation in the Mugan Area, Southwestern Sichuan Basin, China, and Implications for Shale Gas Preservation

AbstractShale gas resources in mainland China and its commercial exploitation has been widely focused on the Wufeng–Longmaxi Formation organic-matter-rich shale in the Sichuan Basin. However, whether southwestern margin of the Sichuan Basin can produce high-quality shale gas has not been well resolved, which might be related to the poor understanding of the relationship between Cenozoic tectonic deformation and shale gas preservation. To answer the aforementioned scientific question, we conducted a detailed work in the Mugan area to show geologic structures and gas contents in the area through seismic profiles and geochemistry analysis. Specifically, the stable Mugan syncline shows a high gas content (>2.6 m3/t measured at three boreholes D1, D2, and D3), whereas its periphery presents a poor gas content (about 0.6 m3/t measured at two boreholes X1 and Y1). Moreover, oblique fracture density and dissolved pores are much higher at boreholes X1 and Y1 than that at the other three boreholes. We propose an opposite-verging thrust fault model to explain the different gas contents and tectonic features in the Mugan area, which might indicate that regions in the southwestern Sichuan Basin with similar tectonic and stratigraphic characteristics as those in the Mugan syncline are likely to produce high-yield shale gas. This finding provides new insights into the exploration theory of shale gas in the Tibetan Plateau

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P \u3c 2.25 × 10−6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P \u3c 1 × 10−3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize