Research on rational layout of strut arms of tainter gate in vertical frame

The overall stability of hydraulic tainter steel gate decrease seriously, and they are caused by improper structure layout of the two-way eccentric compression of struts. Chinese and American specification method, structural mechanics method and finite element method are respectively used to study rational structural layout of strut arms in vertical frame. First of all, a unified method for rational layout of struts of tainter gate in vertical frame is deduced by using structural mechanics method that simplifies curve girder as straight girder on the basis of zero rotation in vertical girder. Second, rational layouts of struts were researched by utilizing spatial finite element method according to zero rotation in vertical girder. The 756 groups rational layout results of the above three methods with different water heads, different number of struts and different unit stiffness ratios were researched. The differences of struts stress and material dosages of various rational layout methods were evaluated. From the point of view of the forces of tainter gate struts in vertical frame, as the results shown, the layouts of struts by Chinese and American specification method, straight beam method and finite element method are large eccentric compression, small eccentric compression and axial compression respectively. The layout of struts with specification method in lower head is quite different from straight beam method and finite element method, and the layouts of deep water head with straight beam method and finite element method are tend to be consistent. Unit stiffness ratio between vertical girder and strut has little effect on layout of tainter gate struts, but has a great influence on material dosages of tainter gate. Compared with specification method, layout of tainter gate with two struts and three struts by using straight beam method and finite element method can improve stability of struts and save materials of overall tainter gate structure, and the material saving rates of tainter gate with two struts and three struts with finite element method are respectively [32.63, 47.58] (%) and [21.61, 30.01] (%). Rational layout concise charts of tainter gate with two struts and three struts by specification method, straight beam method and finite element method are given, which can be used directly for projects designs. Compared with specification method, the layout of struts of straight beam method and finite element method is not only security and economy, but also method and mechanics concept are simple, which can provide the theoretical basis for specification revision of Chinese and American.Peer Reviewe

Investigating safety and liability of autonomous vehicles: Bayesian random parameter ordered probit model analysis

Purpose – This study aims to investigate the safety and liability of autonomous vehicles (AVs), and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs. Design/methodology/approach – The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations. The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs, respectively, as well as accommodating the heterogeneity issue simultaneously. Findings – The findings show that day, location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability. Originality/value – The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability

QTL mapping and genomic prediction of resistance to wheat head blight caused by Fusarium verticillioides

Fusarium head blight (FHB), is one of the destructive fugue diseases of wheat worldwide caused by the Fusarium verticillioides (F.v). In this study, a population consisting of 262 recombinant inbred lines (RILs) derived from Zhongmai 578 and Jimai 22 was used to map Quantitative Trait Locus (QTL) for FHB resistance, with the genotype data using the wheat 50 K single nucleotide polymorphism (SNP) array. The percentage of symptomatic spikelet (PSS) and the weighted average of PSS (PSSW) were collected for each RIL to represent their resistance to wheat head blight caused by F.v. In total, 22 QTL associated with FHB resistance were identified on chromosomes 1D, 2B, 3B, 4A, 5D, 7A, 7B, and 7D, respectively, from which 10 and 12 QTL were detected from PSS and PSSW respectively, explaining 3.82%–10.57% of the phenotypic variances using the inclusive composite interval mapping method. One novel QTL, Qfhb. haust-4A.1, was identified, explaining 10.56% of the phenotypic variation. One stable QTL, Qfhb. haust-1D.1 was detected on chromosome 1D across multiple environments explaining 4.39%–5.70% of the phenotypic variation. Forty-seven candidate genes related to disease resistance were found in the interval of Qfhb. haust-1D.1 and Qfhb. haust-4A.1. Genomic prediction accuracies were estimated from the five-fold cross-validation scheme ranging from 0.34 to 0.40 for PSS, and from 0.34 to 0.39 for PSSW in in-vivo inoculation treatment. This study provided new insight into the genetic analysis of resistance to wheat head blight caused by F.v, and genomic selection (GS) as a potential approach for improving the resistance of wheat head blight

Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance

Genomic selection (GS) is a powerful tool for improving genetic gain in maize breeding. However, its routine application in large-scale breeding pipelines is limited by the high cost of genotyping platforms. Although sequencing-based and array-based genotyping platforms have been used for GS, few studies have compared prediction performance among platforms. In this study, we evaluated the predictabilities of four agronomic traits in 305 maize hybrids derived from 149 parental lines subjected to genotyping by sequencing (GBS), a 40K SNP array, and target sequence capture (TSC) using eight GS models. The GBS marker dataset yielded the highest predictabilities for all traits, followed by TSC and SNP array datasets. We investigated the effect of marker density and statistical models on predictability among genotyping platforms and found that 1K SNPs were sufficient to achieve comparable predictabilities to 10K and all SNPs, and BayesB, GBLUP, and RKHS performed well, while XGBoost performed poorly in most cases. We also selected significant SNP subsets using genome-wide association study (GWAS) analyses in three panels to predict hybrid performance. GWAS facilitated selecting effective SNP subsets for GS and thus reduced genotyping cost, but depended heavily on the GWAS panel. We conclude that there is still room for optimization of the existing SNP array, and using genotyping by target sequencing (GBTS) techniques to integrate a few functional markers identified by GWAS into the 1K SNP array holds great promise of being an effective strategy for developing desirable GS breeding arrays

High prevalence of hyperglycaemia and the impact of high household income in transforming Rural China

<p>Abstract</p> <p>Background</p> <p>The prevalence of hyperglycaemia and its association with socioeconomic factors have been well studied in developed countries, however, little is known about them in transforming rural China.</p> <p>Methods</p> <p>A cross-sectional study was carried out in 4 rural communities of Deqing County located in East China in 2006-07, including 4,506 subjects aged 18 to 64 years. Fasting plasma glucose (FPG) was measured. Subjects were considered to have impaired fasting glucose (IFG) if FPG was in the range from 5.6 to 6.9 mmol/L and to have diabetes mellitus (DM) if FG was 7.0 mmol/L or above.</p> <p>Results</p> <p>The crude prevalences of IFG and DM were 5.4% and 2.2%, respectively. The average ratio of IFG/DM was 2.5, and tended to be higher for those under the age of 35 years than older subjects. After adjustment for covariates including age (continuous), sex, BMI (continuous), smoking, alcohol drinking, and regular leisure physical activity, subjects in the high household income group had a significantly higher risk of IFG compared with the medium household income group (OR: 1.74, 95% CI: 1.11-2.72) and no significant difference in IFG was observed between the low and medium household income groups. Education and farmer occupation were not significantly associated with IFG.</p> <p>Conclusions</p> <p>High household income was significantly associated with an increased risk of IFG. A high ratio of IFG/DM suggests a high risk of diabetes in foreseeable future in the Chinese transforming rural communities.</p

Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize

The two most important activities in maize breeding are the development of inbred lines with high values of general combining ability (GCA) and specific combining ability (SCA), and the identification of hybrids with high yield potentials. Genomic selection (GS) is a promising genomic tool to perform selection on the untested breeding material based on the genomic estimated breeding values estimated from the genomic prediction (GP). In this study, GP analyses were carried out to estimate the performance of hybrids, GCA, and SCA for grain yield (GY) in three maize line-by-tester trials, where all the material was phenotyped in 10 to 11 multiple-location trials and genotyped with a mid-density molecular marker platform. Results showed that the prediction abilities for the performance of hybrids ranged from 0.59 to 0.81 across all trials in the model including the additive effect of lines and testers. In the model including both additive and non-additive effects, the prediction abilities for the performance of hybrids were improved and ranged from 0.64 to 0.86 across all trials. The prediction abilities of the GCA for GY were low, ranging between − 0.14 and 0.13 across all trials in the model including only inbred lines; the prediction abilities of the GCA for GY were improved and ranged from 0.49 to 0.55 across all trials in the model including both inbred lines and testers, while the prediction abilities of the SCA for GY were negative across all trials. The prediction abilities for GY between testers varied from − 0.66 to 0.82; the performance of hybrids between testers is difficult to predict. GS offers the opportunity to predict the performance of new hybrids and the GCA of new inbred lines based on the molecular marker information, the total breeding cost could be reduced dramatically by phenotyping fewer multiple-location trials

Genome-Wide Association Mapping and Genomic Prediction Analyses Reveal the Genetic Architecture of Grain Yield and Flowering Time Under Drought and Heat Stress Conditions in Maize

Drought stress (DS) is a major constraint to maize yield production. Heat stress (HS) alone and in combination with DS are likely to become the increasing constraints. Association mapping and genomic prediction (GP) analyses were conducted in a collection of 300 tropical and subtropical maize inbred lines to reveal the genetic architecture of grain yield and flowering time under well-watered (WW), DS, HS, and combined DS and HS conditions. Out of the 381,165 genotyping-by-sequencing SNPs, 1549 SNPs were significantly associated with all the 12 trait-environment combinations, the average PVE (phenotypic variation explained) by these SNPs was 4.33%, and 541 of them had a PVE value greater than 5%. These significant associations were clustered into 446 genomic regions with a window size of 20 Mb per region, and 673 candidate genes containing the significantly associated SNPs were identified. In addition, 33 hotspots were identified for 12 trait-environment combinations and most were located on chromosomes 1 and 8. Compared with single SNP-based association mapping, the haplotype-based associated mapping detected fewer number of significant associations and candidate genes with higher PVE values. All the 688 candidate genes were enriched into 15 gene ontology terms, and 46 candidate genes showed significant differential expression under the WW and DS conditions. Association mapping results identified few overlapped significant markers and candidate genes for the same traits evaluated under different managements, indicating the genetic divergence between the individual stress tolerance and the combined drought and HS tolerance. The GP accuracies obtained from the marker-trait associated SNPs were relatively higher than those obtained from the genome-wide SNPs for most of the target traits. The genetic architecture information of the grain yield and flowering time revealed in this study, and the genomic regions identified for the different trait-environment combinations are useful in accelerating the efforts on rapid development of the stress-tolerant maize germplasm through marker-assisted selection and/or genomic selection

Integrative transcriptome and metabolome analysis reveals the mechanisms of light-induced pigmentation in purple waxy maize

IntroductionWaxy maize, mainly consumed at the immature stage, is a staple and vegetable food in Asia. The pigmentation in the kernel of purple waxy maize enhances its nutritional and market values. Light, a critical environmental factor, affects anthocyanin biosynthesis and results in pigmentation in different parts of plants, including in the kernel. SWL502 is a light-sensitive waxy maize inbred line with purple kernel color, but the regulatory mechanism of pigmentation in the kernel resulting in purple color is still unknown.MethodsIn this study, cyanidin, peonidin, and pelargonidin were identified as the main anthocyanin components in SWL502, evaluated by the ultra-performance liquid chromatography (UPLC) method. Investigation of pigment accumulation in the kernel of SWL502 was performed at 12, 17, and 22 days after pollination (DAP) under both dark and light treatment conditions via transcriptome and metabolome analyses.ResultsDark treatment affected genes and metabolites associated with metabolic pathways of amino acid, carbohydrate, lipid, and galactose, biosynthesis of phenylpropanoid and terpenoid backbone, and ABC transporters. The expression of anthocyanin biosynthesis genes, such as 4CL2, CHS, F3H, and UGT, was reduced under dark treatment. Dynamic changes were identified in genes and metabolites by time-series analysis. The genes and metabolites involved in photosynthesis and purine metabolism were altered in light treatment, and the expression of genes and metabolites associated with carotenoid biosynthesis, sphingolipid metabolism, MAPK signaling pathway, and plant hormone signal transduction pathway were induced by dark treatment. Light treatment increased the expression level of major transcription factors such as LRL1, myc7, bHLH125, PIF1, BH093, PIL5, MYBS1, and BH074 in purple waxy maize kernels, while dark treatment greatly promoted the expression level of transcription factors RVE6, MYB4, MY1R1, and MYB145.DiscussionThis study is the first report to investigate the effects of light on waxy maize kernel pigmentation and the underlying mechanism at both transcriptome and metabolome levels, and the results from this study are valuable for future research to better understand the effects of light on the regulation of plant growth