Global warming is limiting availability of water resources in arid and semi-arid regions,and so understanding water use efficiency(WUE)is increasingly important for agricultural production in those *** China is the la...
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Global warming is limiting availability of water resources in arid and semi-arid regions,and so understanding water use efficiency(WUE)is increasingly important for agricultural production in those *** China is the largest cotton producing area,the problem of balancing WUE and efficient cotton production is a major *** this study,we used a natural population of 517 Upland cotton accessions to conduct a water-controlled trial in south and north of Xinjiang over two years.A total of 18 traits including agronomic traits,fiber yield indices and fiber quality indices,were investigated for broad-sense heritability and coefficient of *** water limitation was found to promote the establishment of favorable agronomic traits in cotton,associated with an increased cotton yield of 8.46%in Xinjiang,at the expense of a certain degree of fiber quality,such as decreased fiber length and an over-higher micronaire *** detected 33 QTL related to response to water limitation using a drought resistance coefficient(DRC),and 6 QTL were found using a comprehensive indicator of CIDT(comprehensive index of drought tolerance)at the genetic level by integrating resequencing *** novel QTL-hotspots including six differentially expressed genes(DEGs)were further identified related to the drought response of *** findings not only suggested a new approach to irrigation of cotton fields in Xinjiang,but also provided abundant genetic evidence for genetic breeders to study drought improvement of crops.
Research on the origin and source of hydrate-bound gas and its relationship to deep conventional oil and gas accumulation in a basin is critical to understanding the accumulation mechanism of gas hydrates and to resou...
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Research on the origin and source of hydrate-bound gas and its relationship to deep conventional oil and gas accumulation in a basin is critical to understanding the accumulation mechanism of gas hydrates and to resource evaluation of gas hydrate accumulation. In this study, the hydrate-bound gas obtained via pressure coring and the production gas recovered during a production test on a gas hydrate reservoir in the Shenhu area offshore of Southern China were tested and discussed. The geochemical analysis results indicate that methane is the predominant gas, and heavier hydrocarbons (C2+) are also present but in low concentrations. The molecular compositions of the hydrate gas recovered from two production test sites are similar to those of the hydrate-bound gas acquired via pressure coring. In addition to the isotopic composition of the methane, the carbon and hydrogen isotopes of the C2+ hydrocarbons were obtained for the first time. The delta C-13 isotopes of the methane range from -66.6 parts per thousand to -46.2 parts per thousand, indicating that the hydrate-bound gases have a mixed origin, containing both biogenic and thermogenic gases. The plot of delta C-13(1) versus delta C-13(2) suggests that the biogenic and thermogenic hydrocarbons were derived from marine organic matter and terrestrial organic matter, respectively. The isotopic characterization of the hydrate-bound gas reveals that the thermogenic hydrate gas contains both humic-type gas and sapropel-type gas, but the sapropel-type gas is predominant. The source rocks of the thermogenic hydrate gas are interpreted to be both the gas-prone coal measure strata of the Enping Formation and the oil-prone medium-deep lacustrine strata of the Wenchang Formation, the latter of which contributed more to the hydrocarbon supply of the gas hydrates. In addition, the maturity of the source rocks of the thermogenic hydrate gas may be lower than that of the deeply buried conventional hydrocarbons discovered in the Ba
Research about constructing multi-dimensional carbon nanomaterials is of great significance in electrocatalytic and sensing fields in order to integrate structural merits of each individual unit. Also, nano-materials ...
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Research about constructing multi-dimensional carbon nanomaterials is of great significance in electrocatalytic and sensing fields in order to integrate structural merits of each individual unit. Also, nano-materials with enzyme-like activities are prospective candidates for artificial enzyme design and electrochemical application. Herein, we fabricate Co, N co-doped hierarchical hybrid (Co@NCNTs/NC) nanozyme, which integrates of both N-doped carbon nanotubes (NCNTs) and N-doped carbon sheets (NC). The three-dimensional (3D) porous carbon composite is prepared by thermal treatment of metal-organic framework (MOF) which was synthesized by growing of ZIF-67 on ZIF-L at room temperature. The obtained nanomaterial not only possesses an improved oxidase-like activity that can catalyze 3,3',5,5'-tetramethylbenzidine (TMB) in the absence of hydrogen peroxide (H2O2), but also constructs a signal amplification platform towards dopamine (DA) due to the synergistic catalysis of Co species and N-doped porous carbon architecture. The electrocatalytic performance for DA detection shows a broad linear range from 30 nM to 710 mu M and a detection limit of 9 nM. The Co@NCNTs/NC/GCE is employed to practically detect DA in human serum and artificial cerebrospinal fluid (aCSF) samples with satisfactory results. The present work exhibits a great promising in colorimetric and electrochemical sensing fields and presents a new sight for the fabrication of MOF-derived nanozyme. (C) 2021 Elsevier Ltd. All rights reserved.
BACKGROUND: The risk factors of hypertensive disorders in pregnancy (HDP) could be summarized into three categories: clinical epidemiological factors, hemodynamic factors and biochemical factors. OBJECTIVE: To establi...
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BACKGROUND: The risk factors of hypertensive disorders in pregnancy (HDP) could be summarized into three categories: clinical epidemiological factors, hemodynamic factors and biochemical factors. OBJECTIVE: To establish models for early prediction and intervention of HDP. METHODS: This study used the three types of risk factors and support vector machine (SVM) to establish prediction models of HDP at different gestational weeks. RESULTS: The average accuracy of the model was gradually increased when the pregnancy progressed, especially in the late pregnancy 28-34 weeks and >= 35 weeks, it reached more than 92%. CONCLUSION: Multi-risk factors combined with dynamic gestational weeks' prediction of HDP based on machine learning was superior to static and single-class conventional prediction methods. Multiple continuous tests could be performed from early pregnancy to late pregnancy.
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