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•A new method amended existing widely used risk assessment methods was developed.•Critical sources and critical source area for road dust were introduced and identified.•Fuel ...combustion contributed the largest to heavy metal but less to ecological risks.•Pesticide and fertilizers contributed half of risks, posing no less than moderate risks.•Traffic exhaust was critical in all seasons, with higher impact within smaller ring roads.
To explore the spatial variation of source-specific ecological risks and identify critical sources of heavy metals in road dust, 36 road dust samples collected in Beijing in March 2017 were analyzed for heavy metals. A new method that takes into consideration the heavy-metal toxic response and is flexible to changes in the number of calculated heavy metals, called the Nemerow integrated risk index (NIRI), was developed for ecological risk assessment. The NIRI indicated that heavy metals posed considerable to high risks at the majority of sites, and 22 % of the sites suffered extreme risk in spring (NIRI > 320). Four main sources were identified based on positive matrix factorization (PMF): traffic exhaust, fuel combustion, construction, and use of pesticides and fertilizers. Owing to the lower toxic response factors of representative heavy metals of fuel combustion than those of other sources, although fuel combustion had the highest contribution (34.21 %) to heavy metals in spring, it only contributed 5.57 % to ecological risks. Critical sources and critical source areas were determined by considering the contributions to both heavy metals and ecological risks. The use of pesticide and fertilizer and traffic-related exhaust were identified as critical sources of heavy metals in spring. Source-specific ecological risks and critical sources of heavy metals changed with the changing seasons, which suggests that different strategies should be adopted in different seasons.
Nowadays, machine learning (ML) methods have gained much attention and have been applied in some important related applications in earth science field, including observation data mining, geoscience ...image recognition, remote sensing image classification and so on. These ML-based applications play important roles in our daily life. However, in meteorological and oceanographic forecast, numerical is still the most popular method. Although researchers have proposed some ML-based prediction methods to overcome the shortcomings of numerical weather forecast methods, the explainability for the forecast result of artificial intelligence (AI) technology is still not as good as numerical weather forecast methods. Therefore, in this paper, we propose a random forest based adjusting method, which introduces AI technology to correct wind prediction results of numerical model. The proposed adjusting method greatly improves the accuracy of forecast results. Furthermore, the physical meanings of parameters in the numerical model are retained in adjusting results. From experimental evaluations, it is obvious that the root mean square error (RMSE) of each feature is reduced greatly. In detail, the average RMSE of 10m wind decreased by more than 45%, and the average RMSE of sea level pressure decreased by more than 50%. It is worth noting that the improvement here is the average of all forecasts for whole region within 7 days.
•A RF based adjusting method is designed to correct the output of WRF model.•A DNN model is applied as the feature selector to replace the original data.•The RMSE of wind gets an average decrease of 40% compared with WRF model.•The DNN selected features can improve the adjusting accuracy by 5%.
Water and nitrogen (N) deficiencies are the major limitations to crop production, particularly when they occur simultaneously. By supporting metabolism, even when tissue water capacity is lower, ...nitrogen and priming may reduce drought pressure on plants. Therefore, the current study investigates the impact of nitrogen and priming on wheat to minimize post-anthesis drought stress. Plant morphology, physiology, and biochemical changes were observed before, during, and after stress at the post-anthesis stage. The plants were exposed to three water levels, i.e., well watering (WW), water deficit (WD), and priming at jointing and water deficit (PJWD) at the post-anthesis stage, and two different nitrogen levels, i.e., N180 (N1) and N300 (N2). Nitrogen was applied in three splits, namely, sowing, jointing, and booting stages. The results showed that the photosynthesis of plants with N1 was significantly reduced under drought stress. Moreover, drought stress affected chlorophyll (Chl) fluorescence and water-related parameters (osmotic potential, leaf water potential, and relative water content), grain filling duration (GFD), and grain yield. In contrast, PJWD couple with high nitrogen treatment (N300 kg ha
–1
) induced the antioxidant activity of peroxidase (37.5%), superoxide dismutase (29.64%), and catalase (65.66%) in flag leaves, whereas the levels of hydrogen peroxide (H
2
O
2
) and superoxide anion radical (O
2
–
) declined by 58.56 and 66.64%, respectively. However, during the drought period, the primed plants under high nitrogen treatment (N300 kg ha
–1
) maintained higher Chl content, leaf water potential, and lowered lipid peroxidation (61%) (related to higher activities of ascorbate peroxidase and superoxide dismutase). Plants under high nitrogen treatment (N300 kg ha
–1
) showed deferred senescence, improved GFD, and grain yield. Consequently, the research showed that high nitrogen dose (N300 kg ha
–1
) played a synergistic role in enhancing the drought tolerance effects of priming under post-anthesis drought stress in wheat.
In the context of automated testing in the automotive industry, the accurate and effective detection of target icons on vehicle-machine interfaces is crucial for ensuring the efficiency and precision ...of automated testing processes. This paper addressed the challenge of effectively detecting vehicle-machine interface icons by proposing a three-stage verification detection algorithm based on machine vision. This paper employed an enhanced template matching technique to achieve precise positioning and initial verification of car and machine icons. Subsequently, a two-stage verification process was implemented, which focuses on detecting local changes using pixel blocks. The three-stage verification was accomplished through a three-channel separation detection of characteristic pixel points based on RGB values. Additionally, this paper utilized the collaborative capabilities of LabVIEW and OpenCV to overcome integration challenges. This joint programming approach bridged the gap between LabVIEW and OpenCV. Experimental results unequivocally underscored the paramount significance of the three-stage verification detection algorithm, rooted in the realm of machine vision. The algorithm's novel three-stage approach, intricately designed to combat background interference, not only elevated the precision of icon detection but also introduced an ingenious mechanism for classifying detection results. In this regard, it successfully overcome the limitations that have historically hindered traditional machine vision algorithms, ultimately demonstrating its paramount importance in the field of computer vision.
Simian retrovirus subtype 8 (SRV-8) infections have been reported in cynomolgus monkeys (
) in China and America, but its pathogenicity and immunogenicity are rarely reported. In this work, the ...SRV-8-infected monkeys were identified from the monkeys with anemia, weight loss, and diarrhea. To clarify the impact of SRV-8 infection on cynomolgus monkeys, infected monkeys were divided into five groups according to disease progression. Hematoxylin (HE) staining and viral loads analysis showed that SRV-8 mainly persisted in the intestine and spleen, causing tissue damage. Additionally, the dynamic variations of blood routine indexes, innate and adaptive immunity, and the transcriptomic changes in peripheral blood cells were analyzed during SRV-8 infection. Compared to uninfected animals, red blood cells, hemoglobin, and white blood cells were reduced in SRV-8-infected monkeys. The percentage of immune cell populations was changed after SRV-8 infection. Furthermore, the number of hematopoietic stem cells decreased significantly during the early stages of SRV-8 infection, and returned to normal levels after antibody-mediated viral clearance. Finally, global transcriptomic analysis in PBMCs from SRV-8-infected monkeys revealed distinct gene expression profiles across different disease stages. In summary, SRV-8 infection can cause severe pathogenicity and immune disturbance in cynomolgus monkeys, and it might be responsible for fatal virus-associated immunosuppressive syndrome.
Shoot branching is inhibited by a low red/far-red ratio (R/FR). Prior studies have shown that the R/FR suppressed
branching by promotes bud abscisic acid (ABA) accumulation directly. Given that wheat ...tiller buds are wrapped in leaf sheaths and may not respond rapidly to a R/FR, systemic cytokinin (CTK) may be more critical. Here, systemic hormonal signals including indole-3-acetic acid (IAA), gibberellins (GA) and CTK and bud ABA signals in wheat were tested under a low R/FR. The results showed that a low R/FR reduced the percentage of tiller occurrence of tiller IV and the tiller number per plant. The low R/FR did not rapidly induced ABA accumulation in the tiller IV because of the protection of the leaf sheath and had little effect on IAA content and signaling in the tiller nodes. The significant change in the CTK levels was observed earlier than those of other hormone (ABA, IAA and GA) and exogenous cytokinin restored the CTK levels and tiller number per plant under low R/FR conditions. Further analysis revealed that the decrease in cytokinin levels was mainly associated with upregulation of cytokinin degradation genes (
,
) in tiller nodes. In addition, exposure to a decreased R/FR upregulated the expression of GA biosynthesis genes (
,
), resulting in elevated GA levels, which might further promote CTK degradation in tiller nodes and inhibit tillering. Therefore, our results provide evidence that the enhancement of cytokinin degradation is a novel mechanism underlying the wheat tillering response to a low R/FR.
During the iron ore sintering process, its SiO2 content considerably affects the sinter quality. In this study, the effect of SiO2 content on iron ore sintering indexes was studied, with mineral ...composition and microstructure analyses. It was shown that the strength and reducibility of sintering products improved when SiO2 content increased. The sinter yield and tumbler index increased from 69.57% and 58.67% to 74.02% and 62.32%, respectively, with SiO2 content increasing from 3.92% to 5.12%. Moreover, the reduction disintegration index (RDI+3.15) increased from 66.50% to 68.28%. There was a quadratic function relationship between SiO2 content (x) and RDI+3.15 (y): y = −0.4841x2 + 5.8932x + 50.8189. Maintaining the SiO2 content in the range of 4.52% to 5.12% would promote the formation of compound calcium ferrite (SFCA) and silicate as the main binding phase which determined the quality of sintering products.
It has been widely reported that the sintering productivity and sintering bed permeability would be reduced when adopting ultra-deep bed sintering. To solve the aforementioned problems, the ...double-layer sintering process with stand-support (DLSP-S) is proposed in this research to achieve the sintering of a 1000 mm ultra-deep bed. The results showed that compared with the double-layer sintering process, the DLSP-S improved the yield and productivity of sintering from 64.53% and 1.76 t·m−2·h−1 to 66.74% and 2.12 t·m−2·h−1, respectively. The research findings showed that the quasi-fines of 5–10 mm were reduced by 2.1% when the stand height increased from 0 mm to 350 mm, which further illustrated the effect of the DLSP-S. During the DLSP-S, the air permeability of the sinter bed was evidently improved and the content of O2 in the lower layer was enhanced. The present study provides an effective approach to improve the bed permeability and sintering productivity in high-bed sintering.
Genomic imprinting can lead to allele-specific expression (ASE), where one allele is preferentially expressed more than the other. Perturbations in genomic imprinting or ASE genes have been widely ...observed across various neurological disorders, notably autism spectrum disorder (ASD). In this study, we crossed rhesus cynomolgus monkeys to produce hybrid monkeys and established a framework to evaluate their allele-specific gene expression patterns using the parental genomes as a reference. Our proof-of-concept analysis of the hybrid monkeys identified 353 genes with allele-biased expression in the brain, enabling us to determine the chromosomal locations of ASE clusters. Importantly, we confirmed a significant enrichment of ASE genes associated with neuropsychiatric disorders, including ASD, highlighting the potential of hybrid monkey models in advancing our understanding of genomic imprinting.
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•Cynomolgus-rhesus hybrid macaques is a powerful platform to investigate imprinting.•Location information of ASE genes can be obtained using hybrid strategy.•Identification of ASE genes benefits understanding the association between imprinting and neuropsychiatric disorders.
Coke breeze is added as fuel in sintering process. The size distribution of coke breeze is one of the important factors, which plays an important role in achieving proper sintering process. ...Therefore, the effects of size distribution of coke breeze on sintering performance are investigated. Experimental results show that, in practical production, we should adjust the size distribution of coke breeze according to the different production strategy (aimed for best strength or highest productivity, or others). For example, aimed for sinter with maximum tumble strength, the size distribution of coke breeze should be 57.20% of −1 mm, 25.63% of 1–3 mm, 11.17% of 3–5 mm, and 6.00% of +5 mm. Then the tumble strength of sinter increases about 1.48%, production yield increases about 1.7%. Similarly, aimed for sinter with maximum productivity, the size distribution of coke breeze should be 47.22% of −1 mm, 23.10% of 1–3 mm, 28.68% of 3–5 mm, and 1.00% of +5 mm. For this case, the productivity increases 0.1 t m−2 h−1, the sintering speed increases 0.7 mm min−1, and the production yield increases 0.4%. There are two reasons for that sinter B (optimized by maximum tumble strength) has better sintering performances, they are as follows: (i) the effect of coke breeze size on the sintering temperature profile and (ii) pores distribution. The research results of present work could give a scientific guide to reasonably utilize fuel resources in practical sintering process.
In case of practical sinter production, the time of high temperature zone (+1200 °C) is relatively lower, thermocouple 1 and thermocouple 2 are 170 and 330 s, respectively. While in case of maximum tumble strength, they are 190 and 370 s, respectively. Therefore, the effect of coke breeze size on the sintering temperature profile is the essential for sintering performances.
