Quality Prediction and Control of Reducing Pipe Based on EOS-ELM-RPLS Mathematics Modeling Method

The inspection of inhomogeneous transverse and longitudinal wall thicknesses, which determines the quality of reducing pipe during the production of seamless steel reducing pipe, is lags and difficult to establish its mechanism model. Aiming at the problems, we proposed the quality prediction model of reducing pipe based on EOS-ELM-RPLS algorithm, which taking into account the production characteristics of its time-varying, nonlinearity, rapid intermission, and data echelon distribution. Key contents such as analysis of data time interval, solving of mean value, establishment of regression model, and model online prediction were introduced and the established prediction model was used in the quality prediction and iteration control of reducing pipe. It is shown through experiment and simulation that the prediction and iteration control method based on EOS-ELM-RPLS model can effectively improve the quality of steel reducing pipe, and, moreover, its maintenance cost was low and it has good characteristics of real time, reliability, and high accuracy

Comparing the diagnostic accuracy of five common tumour biomarkers and CA19-9 for pancreatic cancer: a protocol for a network meta-analysis of diagnostic test accuracy

Introduction: Surgical resection is the only curative treatment for patients with resectable pancreatic cancer. Unfortunately, 80%–85% of patients present with locally advanced or metastatic unresectable pancreatic cancer at the time of diagnosis. Detection of pancreatic cancer at early stages remains a great challenge due to lack of accurate detection tests. Recommendations in existing clinical practice guidelines on early diagnosis of pancreatic cancer are inconsistent and based on limited evidence. Most of them endorse measuring serum CA19-9 as a complementary test, but also state that it is not recommended for diagnosing early pancreatic cancer. There are currently no other tumour-specific markers recommended for diagnosing early pancreatic cancer. This study aims to evaluate and compare the accuracy of five common tumour biomarkers (CA242,carcino-embryonic antigen (CEA)), CA125, microRNAs and K-ras gene mutation) and CA19-9 and their combinations for diagnosing pancreatic cancer using network meta-analysis method, and to rank these tests using a superiority index. Methods and analysis: PubMed, EMBASE and the Cochrane Central Register of Controlled Trials will be searched from inception to April 2017. The search will include the above-mentioned tumour biomarkers for diagnosing pancreatic cancer, including CA19-9. The risk of bias for each study will be independently assessed as low, moderate or high using criteria adapted from the Quality Assessment of Diagnostic Accuracy Studies 2. Network meta-analysis will be performed using STATA V.12.0 and R software V.3.4.1. The competing diagnostic tests will be ranked by a superiority index. Ethics and dissemination: Ethical approval and patient consent are not required since this study is a network meta-analysis based on published studies. The results of this network meta-analysis will be submitted to a peer-reviewed journal for publication

A new species of Unachionaspis MacGillivray, 1921 (Hemiptera: Coccomorpha Diaspididae) from China

Tian, Feng, Xing, Jichun (2022): A new species of Unachionaspis MacGillivray, 1921 (Hemiptera: Coccomorpha Diaspididae) from China. Zootaxa 5124 (5): 520-532, DOI: https://doi.org/10.11646/zootaxa.5124.5.

Two new species of Aulacaspis Cockerell, 1893 (Hemiptera: Coccomorpha: Diaspididae) from China

Tian, Feng, Xing, Jichun (2022): Two new species of Aulacaspis Cockerell, 1893 (Hemiptera: Coccomorpha: Diaspididae) from China. Zootaxa 5087 (1): 154-178, DOI: https://doi.org/10.11646/zootaxa.5087.1.

Quality prediction and control of reducing pipe based on EOS-ELM-RPLS mathematics modeling method,”

The inspection of inhomogeneous transverse and longitudinal wall thicknesses, which determines the quality of reducing pipe during the production of seamless steel reducing pipe, is lags and difficult to establish its mechanism model. Aiming at the problems, we proposed the quality prediction model of reducing pipe based on EOS-ELM-RPLS algorithm, which taking into account the production characteristics of its time-varying, nonlinearity, rapid intermission, and data echelon distribution. Key contents such as analysis of data time interval, solving of mean value, establishment of regression model, and model online prediction were introduced and the established prediction model was used in the quality prediction and iteration control of reducing pipe. It is shown through experiment and simulation that the prediction and iteration control method based on EOS-ELM-RPLS model can effectively improve the quality of steel reducing pipe, and, moreover, its maintenance cost was low and it has good characteristics of real time, reliability, and high accuracy

Analysis of Diversity and Linkage Disequilibrium Mapping of Agronomic Traits on B-Genome of Wheat

© Ivyspring International Publisher. This is an open-access article distributed under the terms of the Creative Commons Licens

Quantitative trait loci controlling amino acid contents in wheat (Triticum aestivum L.)

Abstract Quantitative trait locus/loci (QTL) for amino acid content (AAC), 17 individual amino acid and total amino acid (TAA) contents of wheat were studied using a doubled haploid (DH) population containing 168 progeny lines derived from a cross between 'Huapei 3' and 'Yumai 57', Chinese bread wheat cultivars. The inclusive composite interval mapping (ICIM) was applied on wheat meals from 2008 and 2009 in Shandong province, China using QTL IciMapping 2.2. The results indicated that total 32 QTL were detected in wheat meals from 2008, contributing to 4.86-30.95% of total phenotypic variation. Total 53 QTL, accounting for 4.39-23.87% of total phenotypic variance, were detected in wheat meals from 2009. Most QTL were co-localized, forming 13 QTL clusters in two cropping seasons, whereas 4 QTL clusters were coincident in two years. Especially, the loci near marker Xbarc86 on chromosome 3A detected in both years influenced 13 amino acids, and also controlled protein and wet gluten contents, which could be used for marker for protein and amino acids contents

Discovery of Consistent QTLs of Wheat Spike-Related Traits under Nitrogen Treatment at Different Development Stages

Spike-related traits such as spike length (Sl), fertile spikelet number (Fsn), sterile spikelet number (Ssn), grain number per spike (Gns), and thousand-kernel weight (Tkw) are important factors influencing wheat yield. However, reliably stable markers that can be used for molecular breeding in different environments have not yet been identified. In this study, a double haploid (DH) population was used for quantitative trait locus (QTL) mapping of five spike-related traits under four different nitrogen (N) supply dates in two locations and years. Seventy additive QTLs with phenotypic variation ranging from 4.12 to 34.74% and 10 major epistatic QTLs were identified. Eight important chromosomal regions on five chromosomes (1B, 2B, 2D, 5D, and 6A) were found. Sixteen stable QTLs were detected for which N application had little effect. Among those stable QTLs, QSl.sdau-2D-1, and QSl.sdau-2D-2, with phenotypic variation explained (PVE) of 10.4 and 24.2%, respectively, were flanked by markers Xwmc112 and Xcfd53 in the same order. The QTLs QSsn.sdau-2B-1, QFsn.sdau-2B-1, and QGns.sdau-2B, with PVE ranging from 4.37 to 28.43%, collocated in the Xwmc179-Xbarc373 marker interval. The consistent kernel wheat QTL (QTkw.sdau-6A) on the long arm of chromosome 6A, flanked by SSR markers Xbarc1055 and Xwmc553, showed PVE of 5.87–15.18%. Among these stable QTLs, the two flanking markers Xwmc112 and Xcfd53 have been validated using different varieties and populations for selecting Sl. Therefore, these results will be of great value for marker-assisted selection (MAS) in breeding programs and will accelerate the understanding of the genetic relationships among spike-related traits at the molecular level

Transcriptome Dynamic Analysis Reveals New Candidate Genes Associated with Resistance to Fusarium Head Blight in Two Chinese Contrasting Wheat Genotypes

In recent years, Fusarium head blight (FHB) has developed into a global disease that seriously affects the yield and quality of wheat. Effective measures to solve this problem include exploring disease-resistant genes and breeding disease-resistant varieties. In this study, we conducted a comparative transcriptome analysis to identify the important genes that are differentially expressed in FHB medium-resistant (Nankang 1) and FHB medium-susceptible (Shannong 102) wheat varieties for various periods after Fusarium graminearum infection using RNA-seq technology. In total, 96,628 differentially expressed genes (DEGs) were identified, 42,767 from Shannong 102 and 53,861 from Nankang 1 (FDR 1). Of these, 5754 and 6841 genes were found to be shared among the three time points in Shannong 102 and Nankang 1, respectively. After inoculation for 48 h, the number of upregulated genes in Nankang 1 was significantly lower than that of Shannong 102, but at 96 h, the number of DEGs in Nankang 1 was higher than that in Shannong 102. This indicated that Shannong 102 and Nankang 1 had different defensive responses to F. graminearum in the early stages of infection. By comparing the DEGs, there were 2282 genes shared at the three time points between the two strains. GO and KEGG analyses of these DEGs showed that the following pathways were associated with disease resistance genes: response to stimulus pathway in GO, glutathione metabolism, phenylpropanoid biosynthesis, plant hormone signal transduction, and plant–pathogen interaction in KEGG. Among them, 16 upregulated genes were identified in the plant–pathogen interaction pathway. There were five upregulated genes, TraesCS5A02G439700, TraesCS5B02G442900, TraesCS5B02G443300, TraesCS5B02G443400, and TraesCS5D02G446900, with significantly higher expression levels in Nankang 1 than in Shannong 102, and these genes may have an important role in regulating the resistance of Nankang 1 to F. graminearum infection. The PR proteins they encode are PR protein 1-9, PR protein 1-6, PR protein 1-7, PR protein 1-7, and PR protein 1-like. In addition, the number of DEGs in Nankang 1 was higher than that in Shannong 102 on almost all chromosomes, except chromosomes 1A and 3D, but especially on chromosomes 6B, 4B, 3B, and 5A. These results indicate that gene expression and the genetic background must be considered for FHB resistance in wheat breeding