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Traction power systems (TPSs) play a vital role in the operation of electrified railways. The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target. On the basis of sorting out the power supply structures of conventional AC and DC modes, this paper first reviews the characteristics of the existing TPSs, such as weak power supply flexibility and low-energy efficiency. Furthermore, the power supply structures of various TPSs for future electrified railways are described in detail, which satisfy longer distance, low-carbon, high-efficiency, high-reliability and high-quality power supply requirements. Meanwhile, the application prospects of different traction modes are discussed from both technical and economic aspects. Eventually, this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system, speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode, employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy. [ABSTRACT FROM AUTHOR]

The discovery and characterization of the opaque endosperm gene provide ideas and resources for the production and application of maize. We found an o213 mutant whose phenotype was opaque and shrunken endosperm with semi-dwarf plant height. The protein, lipid, and starch contents in the o213 endosperm were significantly decreased, while the free amino acid content in the o213 endosperm significantly increased. The aspartic acid, asparagine, and lysine contents were raised in the o213 endosperm by 6.5-, 8.5-, and 1.7-fold, respectively. Genetic analysis showed that this o213 mutant is a recessive single-gene mutation. The position mapping indicated that o213 is located in a 468-kb region that contains 11 protein-encoding genes on the long arm of chromosome 5. The coding sequence analysis of candidate genes between the WT and o213 showed that ZmYSL2 had only a single-base substitution (A–G) in the fifth exon, which caused methionine substitution to valine. Sequence analysis and the allelic test showed that o213 is a new mutant allele of ZmYSL2. The qRT-PCR results indicated that o213 is highly expressed in the stalks and anthers. Subcellular localization studies showed that o213 is a membrane transporter. In the variation analysis of o213, the amplification of 65 inbred lines in GWAS showed that this 3-bp deletion of the first exon of o213 was found only in temperate inbred lines, implying that the gene was artificially affected in the selection process. Our results suggest that o213 is an important endosperm development gene and may serve as a genetic resource. [ABSTRACT FROM AUTHOR]

Phosphorus deficiency is one of the major factors limiting plant growth and grain yield. Improving plant tolerance to Pi deficiency through genetic mechanism is an important source to increase grain yield. In this study, bioinformatics analysis, expression, and natural variation in ZmNAC134 gene with low Pi tolerant traits were analyzed under low Pi conditions. A total of 177 diverse heterotic groups of maize inbreds were used to identify the nucleotide diversity and alleles of ZmNAC134, which plays a vital role in the regulation of root architecture in response to Pi deficiency evolutionary results showed that ZmNAC134 has 3 homologous genes and these genes have one exon and conserved domain. The phenotypic traits showed significant difference for each of the 22 traits under deficient and sufficient Pi conditions. A total of 27 SNPs were identified in the coding region of ZmNAC134 and no InDels among 177 inbred lines. Among 27 SNPs, a total of 8 sites were highly significantly associated with multiple traits of low Pi tolerant trait index at − log10 P = 3.43. Although, 7 sites under Pi normal and 9 sites under Pi deficient conditions, of which four synonymous sites (position S24, S82, S164, and S1037) were associated with diverse number of traits in low Pi and normal Pi conditions and LD was not tight among these sites. Furthermore, the expression pattern was compared between Pi tolerant 178 and Pi sensitive 9782 inbred lines. ZmNAC134 was highly up-regulated in the roots and leaves of Pi tolerant 178 inbred line at 3 days, 7 days, and 9 days in roots and 7 days and 12 days in leaves while down-regulated in roots and leaves of Pi sensitive 9782 inbred line. In addition, protein encoded by ZmNAC134 was located in both nucleus and cytoplasm. Our findings provide the new insight of ZmNAC134 gene involved in low Pi stress and responsible against low Pi condition and the significant association of polymorphic loci with traits could be helpful to find out the molecular marker for genetic resources for further molecular maize breeding program. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is the most important macronutrient for plant growth and development. Hence, understanding genetic architectures and functional genes involved in the response to N deficiency can greatly facilitate the development of low-N-tolerant cultivars. In this study, we collected 212 quantitative trait loci (QTL) of agronomically important traits under low-N stress conditions in maize. We then identified 21 consensus QTL (cQTL) strongly induced for low-N tolerance after excluding overlapping cQTL containing QTL simultaneously identified in meta-analyses of studies performed under other environmental conditions. Among the 21 cQTL, 30 candidate maize genes were identified from maize large-scale differential expression data derived from analyses of low-N stress, and the 12 most important maize orthologs were identified using homologous BLAST analyses of genes with known functions in N use efficiency in model plants. Furthermore, maize orthologs associated with low-N tolerance and metabolism were also predicted using large-scale expression data from other model plants. The present genetic loci and candidate genes indicate the molecular mechanisms of low-N tolerance in maize and may provide information for QTL fine mapping and molecular marker-assisted selection. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is required for numerous developmental processes, such as flowering and reproduction, in maize (Zea mays L.). It is also an essential nutrient in fertilizers to sustain high yields in farmlands with insufficient available phosphate, particularly in acid soils in China. Flowering time is a key factor influencing the adaptation of maize to the local environment and is associated with high yields. However, few studies have focused on the genetic characteristics of flowering time under low phosphate conditions. In this study, a recombinant inbred line (RIL) population derived from a cross between X178 and 9782 was evaluated for three flowering time traits under two phosphates (Pi) levels at four locations. We found that low phosphate significantly delayed the flowering stage of maize and proposed the hypothesis of "Phosphorus Accumulation Effect". Mixed-model-based composite interval mapping was used to dissect the genetic basis of the flowering time traits. A total of 41 quantitative trait loci (QTL) was identified for the three flowering time traits through four procedures. Among these 41 QTL, 38 focused on four hot regions, including bin 2.02, bin 2.03, bin 5.04, and bin 6.01. These regions and linked markers should be the targets for fine mapping, map-based cloning, and marker-assisted selection of flowering time and phosphate utilization efficiency. [ABSTRACT FROM AUTHOR]

A correction to the article "Mining for Low-Nitrogen Tolerance Genes by Integrating Meta-Analysis and Large-Scale Gene Expression Data From Maize" by Bowen Luo et al. that was published in a 2015 issue is presented.