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Plant height is a key agronomic trait that is closely to the plant morphology and lodging resistance in wheat. However, at present, the few dwarf genes widely used in wheat breeding have narrowed wheat genetic diversity. In this study, we selected a semi-dwarf wheat mutant dwarf33 that exhibits decreased plant height with little serious negative impact on other agronomic traits. Genetic analysis and mutant gene mapping indicated that dwarf33 contains a new recessive semi-dwarf gene Rht-SN33d, which was mapped into ~1.3 Mb interval on the 3DL chromosome. The gibberellin metabolism-related gene TraesCS3D02G542800, which encodes gibberellin 2-beta-dioxygenase, is considered a potential candidate gene of Rht-SN33d. Rht-SN33d reduced plant height by approximately 22.4% in mutant dwarf33. Further study revealed that shorter stem cell length may be the main factor causing plant height decrease. In addition, the coleoptile length of dwarf33 was just 9.3% shorter than that of wild-type Shaannong33. These results will help to expand our understanding of new mechanisms of wheat height regulation, and obtain new germplasm for wheat improvement. [ABSTRACT FROM AUTHOR]

Evaluating shadow prices is critical in devising environmental regulatory policies for pollutants. Compared to traditional frontier estimation methods, this paper uses a recently developed data-driven approach named convex quantile regression, taking both the noise and inefficiency into account and estimating the shadow prices locally. This paper is the first work applying convex quantile regression to jointly evaluate shadow prices of CO2, SO2, and NOx produced by U.S. coal power plants from 2010 to 2017. During this period, five major regulatory provisions were implemented for U.S. coal power plants. We find that the shadow prices of CO2, SO2, and NOx increased from 2010 to 2017. The increase in the shadow price of CO2 is mainly due to the increase in electricity prices, while the increase in shadow prices of SO2 and NOx is mainly due to the successful emission reductions. Moreover, the results show that the CSARP and CSARP Update have significantly increased the shadow prices of SO2 and NOx. However, the relatively lower market allowance prices compared to the shadow prices indicate that society could benefit more if the government could increase the market prices of the pollutants to be more close to the shadow prices. [ABSTRACT FROM AUTHOR]

This paper combines the semiparametric modified ordinary least-squares approach by Simar et al. (2017) with the nonparametric shape constraint regression approach by Du et al. (2013) to evaluate the performance in the semiconductor industry. Using panel data on 470 companies in the global semiconductor industry over 1999–2018, we compare technical eficiencies between the integrated device manufacturer business model and the fabless-foundry business model. The performance differences between the vertically integrated device manufacturers and the vertically specialized fabless and foundry firms are disentangled by the intensity of labour and capital in a very flexible form. The estimation results indicate that the capital-intensive integrated device manufacturers taking advantage of the economies of scale are operating more efficiently than the niche fabless companies in the global semiconductor industry. [ABSTRACT FROM AUTHOR]

Objectives High-frequent opioid use tends to increase an individual's risk of opioid use disorder, overdose and death. Thus, it is important to predict an individuals' opioid use frequency to improve opioid prescription utilization outcomes. Methods Individuals receiving at least one opioid prescription from 2016 to 2018 in the national representative data, Medical Expenditure Panel Survey, were included. This study applied five machine learning (ML) techniques, including support vector machine, random forest, neural network, gradient boosting and XGBoost (extreme gradient boosting), to predict opioid use frequency. This study compared the performance of these ML models with penalized logistic regression. The study outcome was whether an individual lied in the upper 10% of the opioid prescription distribution. Predictors were selected based on Gelberg–Andersen's Behavioral Model of Health Services Utilization. The prediction performance was assessed using the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC) in the test data. Patient characteristics as predictors for high-frequency use of opioids were ranked by the relative importance in prediction in the test data. Key findings Random forest and gradient boosting achieved the top values of both AUROC and AUPRC, outperforming logistic regression and three other ML methods. In the best performing model, the random forest, the following characteristics had high predictive power in the frequency of opioid use: age, number of chronic conditions, public insurance and self-perceived health status. Conclusions The results of this study demonstrate that ML techniques can be a promising and powerful technique in predicting the frequency of opioid use and health outcomes. [ABSTRACT FROM AUTHOR]

The purposes of this study were to provide palynological information about apricots and to reveal the relationships among six ecological groups of apricots by describing the morphological characteristics of their pollen. The pollen grains of 175 accessions belonging to three species (Prunus armeniaca L., Prunus sibirica L., and Prunus mume Sieb. et Zucc.) of Prunus were examined using light microscopy and scanning electron microscopy. The pollen grains were isopolar monads, radially symmetric, medium to large in size, prolate or subprolate, and 3-colporate. Most pollen grains exhibited striate exine ornamentation, and a few exhibited striato-reticulate or cerebroid exine ornamentation. Cluster analysis divided the six ecological groups into two groups: one including the Central Asian, North China, and Dzhungar-Ili ecological group accessions and another including the Northeast Asian, European, and East China ecological group accessions. Principal component analysis revealed that equatorial diameter, colpus length, colpus width, and ridge width were the most important metrical pollen traits, and can be used as powerful diagnostic characters in apricot identification. We speculated that the cultivated apricots in Xinjiang were domesticated from wild apricots from the Ili Valley. This study describes the morphological characteristics of apricot pollen grains and provides some morphological information for future studies on the phylogenetic relationships of apricots. [ABSTRACT FROM AUTHOR]

Induced mutation is an important approach for creating novel plant germplasms. The introduction of dwarf or semi-dwarf genes into wheat has led to great advancements in yield improvement. In this study, four elite dwarf wheat mutants, named dm1 – dm4 , induced from γ-ray irradiation or ethyl methanesulfonate (EMS) mutagenesis, were used to identify transcriptome variations and dwarfing mechanisms. The results showed that the hotspot regions of mutations distributed on the chromosomes were consistent among the four mutant lines and these regions were mainly located around the 50, 360 and 400 Mb positions of chromosome 1A and the distal regions of chromosomes 2A and 2BL. Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggested that 'protein processing in endoplasmic reticulum' was the most common significantly enriched pathway based on the differentially expressed genes (DEGs) between wildtype (WT) and the mutants. Notably, 18 out of 20 genes involved in this process encode heat shock proteins (HSPs). The results implied that HSPs might participate in wheat dwarfism response and function in the dwarfism process through protein folding and/or degradation. Moreover, seven genes in dm4 involved in modulating auxin levels were down-regulated and dm4 was more sensitive to auxin treatment compared with WT, indicating the important roles of auxin in regulation of dwarf phenotype in dm4. This study not only identified transcriptome sequence variation induced by physical and chemical mutagenesis but also revealed potential dwarfing mechanisms in the wheat mutant lines. [ABSTRACT FROM AUTHOR]