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This study focuses on developing a comprehensive model of a rigid overhead system, which includes essential components such as the suspension structure, positioning clamp, and expansion joint. The modelling approach utilizes finite element theory and beam elements to accurately represent the displacement, stiffness, and mass characteristics of the system. The models also incorporate the suspension structure and positioning line clamp, which play crucial roles in suspending and positioning the busbar. Various suspension structures and positioning line clamps are evaluated based on their dynamic characteristics. The expansion joint, responsible for connecting different anchor sections of the rigid overhead system, undergoes a detailed analysis. Different assembly scenarios, including ideal and deflected assembly conditions, are considered. To simulate the dynamic behaviour of the expansion joint, additional beams are introduced into the system model. The primary finding of the analysis is that the maximum stresses observed in the constructed expansion joint model, under different temperature conditions and normal/deflected assembly conditions, remain within the permissible stress limits of the material. This indicates a high level of safety. However, certain areas exhibit stress concentration, particularly at the sliding block B and sliding rod A positions. This stress concentration is primarily attributed to the unique assembly form of the expansion joint. To improve stress distribution and enhance service reliability, the analysis suggests optimizing the installation deflection angle and geometric design of the expansion joint. Furthermore, the concentrated mass at the expansion joint significantly impacts the current collection quality of the pantograph-overhead system. Mitigating this negative impact can be achieved by reducing the mass of the expansion joint. [ABSTRACT FROM AUTHOR]

The rigid catenary system is widely used in tunnels to power electric trains via contact with a pantograph. Due to gravity, the contact wire normally has a sag that may affect the dynamic interaction performance with a pantograph. To reduce the contact wire sag, the most efficient measure is to improve the moment of inertia of the conductor rail, which is used to clamp the contact wire. Six new types of conductor rail with large moments of inertia are developed based on a conventional conductor rail. Then both the static and dynamic analyses are conducted to investigate the performance of the new types of conductor rail with a big moment of inertia. The conductor rail's 3D solid finite element model is built using a finite element approach. The vertical deflection and the stress distribution are comparatively analyzed among different types of conductor rail. The analysis results indicate that the vertical deflection and maximum stress are significantly reduced when using the conductor rail with a large moment of inertia. The best performance is observed when the conductor rail of case 1 is used. The maximum sag is reduced by 28.37%, and the maximum stress is decreased by 27.76% compared with the conventional conductor. Finally, a pantograph model is included to evaluate the dynamic performance of the conductor rail with large moments of inertia. The results indicate that contact force fluctuation is significantly reduced after the conductor rails with large moments of inertia are presented. The conductor rail of case 1 shows the best performance, which can reduce the contact force standard deviation by 32% and 27% at speeds of 160 km/h and 200 km/h. [ABSTRACT FROM AUTHOR]

A variety of Chinese textual operational text data has been recorded during the operation and maintenance of the high-speed railway catenary system. Such defect text records can facilitate defect detection and defect severity analysis if mined efficiently and accurately. Therefore, in this context, this paper focuses on a specific problem in defect text mining, which is to efficiently extract defect-relevant information from catenary defect text records and automatically identify catenary defect severity. The specific task is transformed into a machine learning problem for defect text classification. First, we summarize the characteristics of catenary defect texts and construct a text dataset. Second, we use BERT to learn defect texts and generate word embedding vectors with contextual features, fed into the classification model. Third, we developed a deep text categorization network (DTCN) to distinguish the catenary defect level, considering the contextualized semantic features. Finally, the effectiveness of our proposed method (BERT-DTCN) is validated using a catenary defect textual dataset collected from 2016 to 2018 in the China Railway Administration in Chengdu, Lanzhou, and Hengshui. Moreover, BERT-DTCN outperforms several competitive methods in terms of accuracy, precision, recall, and F 1 -score value. [ABSTRACT FROM AUTHOR]

Ear shank length (ESL) has significant effects on grain yield and kernel dehydration rate in maize. Herein, linkage mapping and genome-wide association study were combined to reveal the genetic architecture of maize ESL. Sixteen quantitative trait loci (QTL) were identified in the segregation population, among which five were repeatedly detected across multiple environments. Meanwhile, 23 single nucleotide polymorphisms were associated with the ESL in the association panel, of which four were located in the QTL identified by linkage mapping and were designated as the population-common loci. A total of 42 genes residing in the linkage disequilibrium regions of these common variants and 12 of them were responsive to ear shank elongation. Of the 12 genes, five encode leucine-rich repeat receptor-like protein kinases, proline-rich proteins, and cyclin11, respectively, which were previously shown to regulate cell division, expansion, and elongation. Gene-based association analyses revealed that the variant located in Cyclin11 promoter affected the ESL among different lines. Cyclin11 showed the highest expression in the ear shank 15 days after silking among diverse tissues of maize, suggesting its role in modulating ESL. Our study contributes to the understanding of the genetic mechanism underlying maize ESL and genetic modification of maize dehydration rate and kernel yield. [ABSTRACT FROM AUTHOR]

Salinization seriously threatens the normal growth of maize, especially at the seedling stage. Recent studies have demonstrated that circular RNAs (circRNAs) play vital roles in the regulation of plant stress resistance. Here, we performed a genome-wide association study (GWAS) on the survival rate of 300 maize accessions under a salt stress treatment. A total of 5 trait-associated SNPs and 86 candidate genes were obtained by the GWAS. We performed RNA sequencing for 28 transcriptome libraries derived from 2 maize lines with contrasting salt tolerance under normal and salt treatment conditions. A total of 1217 highly expressed circRNAs were identified, of which 371 were responsive to a salt treatment. Using PCR and Sanger sequencing, we verified the reliability of these differentially expressed circRNAs. An integration of the GWAS and RNA-Seq analyses uncovered two differentially expressed hub genes (Zm00001eb013650 and Zm00001eb198930), which were regulated by four circRNAs. Based on these results, we constructed a regulation model of circRNA/miRNA/mRNA that mediated salt stress tolerance in maize. By conducting hub gene-based association analyses, we detected a favorable haplotype in Zm00001eb198930, which was responsible for high salt tolerance. These results help to clarify the regulatory relationship between circRNAs and their target genes as well as to develop salt-tolerant lines for maize breeding. [ABSTRACT FROM AUTHOR]

Gray leaf spot (GLS), caused by the fungal pathogen Cercospora zeina (C. zeina), is one of the most destructive soil-borne diseases in maize (Zea mays L.), and severely reduces maize production in Southwest China. However, the mechanism of resistance to GLS is not clear and few resistant alleles have been identified. Two maize inbred lines, which were shown to be resistant (R6) and susceptible (S8) to GLS, were injected by C. zeina spore suspensions. Transcriptome analysis was carried out with leaf tissue at 0, 6, 24, 144, and 240 h after inoculation. Compared with 0 h of inoculation, a total of 667 and 419 stable common differentially expressed genes (DEGs) were found in the resistant and susceptible lines across the four timepoints, respectively. The DEGs were usually enriched in 'response to stimulus' and 'response to stress' in GO term analysis, and 'plant–pathogen interaction', 'MAPK signaling pathways', and 'plant hormone signal transduction' pathways, which were related to maize's response to GLS, were enriched in KEGG analysis. Weighted-Genes Co-expression Network Analysis (WGCNA) identified two modules, while twenty hub genes identified from these indicated that plant hormone signaling, calcium signaling pathways, and transcription factors played a central role in GLS sensing and response. Combing DEGs and QTL mapping, five genes were identified as the consensus genes for the resistance of GLS. Two genes, were both putative Leucine-rich repeat protein kinase family proteins, specifically expressed in R6. In summary, our results can provide resources for gene mining and exploring the mechanism of resistance to GLS in maize. [ABSTRACT FROM AUTHOR]

A deficiency in the macronutrient phosphate (Pi) brings about various changes in plants at the morphological, physiological and molecular levels. However, the molecular mechanism for regulating Pi homeostasis in response to low-Pi remains poorly understood, particularly in maize ( Zea mays L.), which is a staple crop and requires massive amounts of Pi. Therefore, in this study, we performed expression profiling of the shoots and roots of maize seedlings with Pi-tolerant genotype at both the transcriptomic and proteomic levels using RNA sequencing and isobaric tags for relative and absolute quantitation (iTRAQ). We identified 1944 differentially expressed transcripts and 340 differentially expressed proteins under low-Pi conditions. Most of the differentially expressed genes were clustered as regulators, such as transcription factors involved in the Pi signaling pathway at the transcript level. However, the more functional and metabolism-related genes showed expression changes at the protein level. Moreover, under low-Pi conditions, Pi transporters and phosphatases were specifically induced in the roots at both the transcript and protein levels, and increased amounts of mRNA and protein of two purple acid phosphatases (PAPs) and one UDP-sulfoquinovose synthase (SQD) were specifically detected in the roots. The new insights provided by this study will help to improve the P-utilization efficiency of maize.