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Clubroot is a major disease and severe threat to Chinese cabbage, and it is caused by the pathogen Plasmodiophora brassicae Woron. This pathogen is an obligate biotrophic protist and can persist in soil in the form of resting spores for more than 18 years, which can easily be transmitted through a number of agents, resulting in significant economic losses to global Chinese cabbage production. Rhizosphere microbiomes play fundamental roles in the occurrence and development of plant diseases. The changes in the rhizosphere microorganisms could reveal the severity of plant diseases and provide the basis for their control. Here, we studied the rhizosphere microbiota after clubroot disease infections with different severities by employing metagenomic sequencing, with the aim of exploring the relationships between plant health, rhizosphere microbial communities, and soil environments; then, we identified potential biomarker microbes of clubroot disease. The results showed that clubroot disease severity significantly affected the microbial community composition and structure of the rhizosphere soil, and microbial functions were also dramatically influenced by it. Four different microbes that had great potential in the biocontrol of clubroot disease were identified from the obtained results; they were the genera Pseudomonas, Gemmatimonas, Sphingomonas, and Nocardioides. Soil pH, organic matter contents, total nitrogen, and cation exchange capacity were the major environmental factors modulating plant microbiome assembly. In addition, microbial environmental information processing was extremely strengthened when the plant was subjected to pathogen invasion, but weakened when the disease became serious. In particular, oxidative phosphorylation and glycerol-1-phosphatase might have critical functions in enhancing Chinese cabbage's resistance to clubroot disease. This work revealed the interactions and potential mechanisms among Chinese cabbage, soil environmental factors, clubroot disease, and microbial community structure and functions, which may provide a novel foundation for further studies using microbiological or metabolic methods to develop disease-resistant cultivation technologies. [ABSTRACT FROM AUTHOR]

This article proposed a new quality control method (CS‐MSF) to identify potential outliers in the surface temperature observations. The CS‐MSF method employed cosine similarity and moving surface fitting to obtain the estimated value of the target station. For the regions with complex terrain and low weather station density, another quality control method (CE‐GBDT) was employed to compensate for the shortcomings of CS‐MSF. Compared to the spatial regression test method (SRT) and inverse distance weighting method (IDW), the results indicated that CS‐MSF outperformed SRT and IDW in all the cases. And CE‐GBDT was superior to the other methods for the regions with complex terrain and low weather station density. The comparison results led to the recommendation that the two proposed methods are effective quality control methods in identifying the seeded errors for the surface temperature observations. [ABSTRACT FROM AUTHOR]

Complexly distributed aerosol particles have significant impacts on climate and environmental changes. As one of the vital atmospheric power sources, the wind field deeply affects the distribution and transport of aerosol particles. For a more comprehensive investigation of the aerosols flux and transport mechanism, two retrieval methods of aerosol optical properties (backscatter coefficient and extinction coefficient at 1550 nm) from coherent Doppler lidar (CDL) observation are proposed in this paper. The first method utilizes the calculated aerosol backscatter coefficient (532 nm) from Mie-scattering lidar datasets and the iterative Fernald method to retrieve aerosol optical property profiles during joint measurements with CDL and Mie-scattering lidar. After verifying the correctness of the first method compared with AERONET datasets, we proposed the second retrieval method. Using the forward integral Fernald method with near-ground reference aerosol extinction coefficient calculated by atmospheric visibility, aerosol optical properties at 1550 nm could be obtained. Thirty-six-day joint measurements with two lidars were specially designed and conducted to verify the correctness of these retrieval methods. The validation results of these two methods indicate great performances, where the mean relative errors are 0.0272 and 0.1656, and the correlation coefficients are 0.9306 and 0.9197, respectively. In conclusion, the feasibility of these two retrieval methods extends the capability of CDL to detect aerosol optical properties and also provides a possibility to observe the aerosol distribution and transport process comprehensively, which is a great promotion of aerosol transport studies development. [ABSTRACT FROM AUTHOR]

A method is presented for inferring both the refractive index and the size distribution of aerosol from observations of a dual-scattering-angle optical particle counter (OPC). An existing prototype of an OPC with 60[degrees] and 90[degrees] dual-scattering angles was used for the experiments. Based on the high sensitivity of the OPC response to the refractive index of particulates, two families of size distribution curves may be calculated. The solution of the refractive index corresponds to the superposition of the two size distributions. This method was applied to the simulation and to the field measurements conducted in Beijing and Hefei, and the results of both are presented. OCIS codes: 290.3030, 290.5850, 120.0120.

Aeolus wind products became available to the public on 12 May 2020. In this study, Aeolus wind observations, L-band radiosonde (RS) data, and the European Centre for Medium-Range Weather Forecasts fifth-generation atmospheric reanalysis (ERA5) data were used to analyze the seasonality of Aeolus wind product performance over China. Based on the Rayleigh-clear and Mie-cloudy data, the data quality of the Aeolus effective detection data was verified, and the results showed that the Aeolus data were in good agreement with the L-band RS and ERA5 data. The Aeolus data relative errors in the four regions (Chifeng, Baoshan, Shapingba, and Qingyuan) in China were calculated based on different months (July to December 2019 and May to October 2020). The relative error in the Rayleigh-clear data in summer was significantly higher than that in winter, with the mean relative error parameter in July 174 % higher than that in December. The mean random error increased by 0.97 m s -1 in July compared with December, which also supported this conclusion. In addition, the distribution of the wind direction and high-altitude clouds in different months (July and December) was analyzed. The results showed that the distribution of the angle between the horizontal wind direction of the atmosphere and the horizontal line of sight had a greater proportion in the high error interval (70–110 ∘) in summer, and this proportion was 8.14 % higher in July than in December. The cloud top height in summer was approximately 3–5 km higher than that in winter, which might decrease the signal-to-noise ratio of Aeolus. Therefore, the wind product performance of Aeolus was affected by seasonal factors, which might be caused by seasonal changes in wind direction and cloud distribution. [ABSTRACT FROM AUTHOR]

The free moisture in crop kernels after being naturally dried is referred to as kernel moisture content (KMC). Maize KMC reflects grain quality and influences transportation and storage of seeds. We used an IBM Syn10 DH maize population consisting of 249 lines and an association panel comprising 310 maize inbred lines to identify the genetic loci affecting maize KMC in three environments. Using the IBM population detected 13 QTL on seven chromosomes, which were clustered into nine common QTL. Genome‐wide association analysis (GWAS) identified 16 significant SNPs across the 3 environments, which were linked to 158 genes across the three environments. Combined QTL mapping and GWAS found two SNPs that were located in two of the mapped QTL, respectively. Twenty‐three genes were linked with the loci co‐localized in both populations. Of these 181 genes, five have previously been reported to be associated with KMC or to regulate seed development. These associations were verified by candidate gene association analysis. Two superior alleles and one favorable haplotype for Zm00001d007774 and Zm00001d047868 were found to influence KMC. These findings provide insights into molecular mechanisms underlying maize KMC and contribute to the use of marker‐assisted selection for breeding low‐KMC maize. [ABSTRACT FROM AUTHOR]

The observation of the nocturnal boundary layer height (NBLH) plays an important role in air pollution and monitoring. Through 39 d of heavy pollution observation experiments in Beijing (China), as well as an exhaustive evaluation of the gradient, wavelet covariance transform, and cubic root gradient methods, a novel algorithm based on the cluster analysis of the gradient method (CA-GM) of lidar signals is developed to capture the multilayer structure and achieve night-time stability. The CA-GM highlights its performance compared with radiosonde data, and the best correlation (0.85), weakest root-mean-square error (203 m), and an improved 25 % correlation coefficient are achieved via the GM. Compared with the 39 d experiments using other algorithms, reasonable parameter selection can help in distinguishing between layers with different properties, such as the cloud layer, elevated aerosol layers, and random noise. Consequently, the CA-GM can automatically address the uncertainty with multiple structures and obtain a stable NBLH with a high temporal resolution, which is expected to contribute to air pollution monitoring and climatology, as well as model verification. [ABSTRACT FROM AUTHOR]

Background: Transoral endoscopic thyroid surgery via the vestibular approach (TOETVA) has been gradually accepted worldwide due to its scar-free effect on the neck. Even central cervical lymphadenectomy has been performed in some cases of papillary thyroid carcinoma (PTC). However, there are few reports involving lateral neck dissection with TOETVA. In this study, we attempted to perform selective lateral neck dissection (SLND) for PTC via a transoral vestibular approach.Methods: This prospective study was conducted from January 2016 to December 2018 in twenty PTC patients with unilateral T1 tumors without capsular invasion and patients with abnormal level III and IV lymph nodes who underwent SLND via a transoral vestibular approach.Results: Endoscopic surgery was successfully accomplished in all 20 PTC patients. The mean age was 29.2 ± 5.5 (20-41) years. The mean operation time was 146.0 ± 18.7 (114-193) min. The average postoperative hospital stay was 6.8 ± 1.3 (5-10) days. The mean number of removed nodes was 7.4 ± 2.5 (4-12) in the central neck and 10.9 ± 2.8 (6-16) in the lateral neck, and the positive yield amounts were 2.0 ± 1.2 (0-4) and 2.7 ± 1.9 (0-6), respectively. No major complications occurred except for 1 case of transient unilateral recurrent laryngeal nerve palsy and two cases of effusion in the operative area. No evidence of persistent or recurrent disease was observed in these patients during a mean follow-up of 24.3 ± 9.1 (6-36) months. The cosmetic results and protection of personal privacy of this procedure were excellent.Conclusion: Endoscopic SLND via the transoral vestibular approach is feasible, safe, and effective for selected PTCs. A multicenter large comparative study is necessary. [ABSTRACT FROM AUTHOR]

Ear tip‐barrenness (ETB) phenotype threatens crop yield, because it reduces the kernel number per ear. The genetic basis of ETB in maize remains largely unknown. Herein, a genome‐wide association study (GWAS) and quantitative trait loci (QTL) mapping were jointly applied to identify the significant genetic loci interrelated with ETB. Six significant SNPs were detected at a stringent P‐value threshold (1.95 × 10−6). Additionally, four environment‐stable SNPs were co‐detected across a single environment and best linear unbiased prediction (BLUP) model at a less stringent P‐value threshold (1 × 10−4). The above 10 SNPs were closely linked to 6 candidate genes, which mainly involved seed development, photosynthesis and ethylene response. Moreover, the ratio of superior allele at each significant SNP ranged from 0 to 83.33% in 30 investigated maize elite lines. QTL mapping identified 14 QTL with phenotypic variation explained (PVE) ranging from 3.64 to 7.09%, of which one QTL (qETB2‐1) was repeatedly identified in two environments. Combined analysis of GWAS and QTL mapping showed that one SNP (PZE‐102175229, chromosome 2: 217 66 Mb) was located in the QTL (qETB2‐2, chromosome 2: 215 90–217 82 Mb). Eighteen gene models situated in the linkage disequilibrium (LD) region of the co‐localized SNP were further used to evaluate their correlation with ETB by candidate gene association analysis. Two superior haplotypes and two superior alleles were detected among 74 lines for Zm00001d007195, Zm00001d007197 and Zm00001d007201. These results provide more information for clarifying the molecular mechanism of ETB and for speeding up the genetic improvement of maize varieties. [ABSTRACT FROM AUTHOR]

Summary: Kernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10−6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10−3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1,CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize. [ABSTRACT FROM AUTHOR]

The features of upper-air visibility at altitudes of 0.1, 0.3, and 0.5 km and the two-dimensional haze characteristics in the northwest of downtown Beijing were studied by using a multi-platform analysis during haze episodes between 17 December 2016 and 6 January 2017. Through the multi-platform data analysis in hourly and daily variation, the upper-air visibility increased along with the decrease of PM2:5 mass concentration. And the upper-air visibility on non-haze days was about 3-5 times higher than that on haze days with the ground-based Raman-Mie lidar data between 13 December 2016 and 11 January 2017. The vertical transport of pollutants can be inferred from the delayed variation of upper-air visibility between high altitude and low altitude. In addition, the two-dimensional haze characteristics could be studied by analyzing the correlation between vertical haze parameters (atmospheric boundary layer, haze thickness, and aerosol optical thickness) and horizontal haze parameter (upper-air visibility). The characteristics of multi-parameters have been analyzed and concluded for different haze levels. [ABSTRACT FROM AUTHOR]

A method for the rapid characterization of motor oil by laser-induced fluorescence and phosphorescence is reported using a fluorescence spectrometer and an intensified charge coupled device camera. The fluorescence and phosphorescence spectra were able to classify motor oil brands using 355-nm laser excitation with multivariate analysis methods. The recognition rate was up to 100%. This approach offers high sensitivity and accuracy for rapid quality characterization of motor oil. [ABSTRACT FROM PUBLISHER]

A new laser-induced fluorescence method is presented to classify brands of motor oil. A 266-nanometer radiation was employed to collect sixty sets of fluorescence spectra for each brand. Cluster analysis and support vector machine were employed to distinguish motor oils with principal component analysis, which was applied to extract spectral characteristics. The recognition accuracy was up to 100 percent. The results demonstrate that laser-induced fluorescence offers rapid response, high recognition, and high sensitivity for the classification of motor oils. [ABSTRACT FROM PUBLISHER]

A time-resolved fluorescence (TRF) technique is presented for classifying motor oils. The system is constructed with a third harmonic Nd:YAG laser, a spectrometer, and an intensified charge coupled device (ICCD) camera. Steady-state and time-resolved fluorescence (TRF) measurements are reported for several motor oils. It is found that steady-state fluorescence is insufficient to distinguish the motor oil samples. Then contour diagrams of TRF intensities (CDTRFIs) are acquired to serve as unique fingerprints to identify motor oils by using the distinct TRF of motor oils. CDTRFIs are preferable to steady-state fluorescence spectra for classifying different motor oils, making CDTRFIs a particularly choice for the development of fluorescence-based methods for the discrimination and characterization of motor oils. The two-dimensional fluorescence contour diagrams contain more information, not only the changing shapes of the LIF spectra but also the relative intensity. The results indicate that motor oils can be differentiated based on the new proposed method, which provides reliable methods for analyzing and classifying motor oils. [ABSTRACT FROM AUTHOR]