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Purpose. To quantify macular vascular density using optical coherence tomography angiography (OCTA) and to investigate its relationship with retinal thickness in myopic eyes of young adults. Methods. In this cross-sectional study, 268 myopic eyes without pathological changes were recruited and divided into three groups: mild myopia (n=81), moderate myopia (n=117), and high myopia (n=70). Macular vascular density was quantified by OCTA and compared among three groups. Average retinal thickness, central subfield thickness, and macular ganglion cell complex (mGCC) thickness were also evaluated and compared. Correlations among these variables were analyzed. Results. There was no statistical difference in superficial (62.3 ± 5.7% versus 62.7 ± 5.9% versus 63.8 ± 5.5%) and deep macular vascular densities (58.3 ± 9.6% versus 59.2 ± 9.3% versus 60.9 ± 7.9%) among mild-myopia, moderate-myopia, and high-myopia groups (both P>0.05). Superficial and deep macular vascular densities both had correlations with mean arterial pressure. Furthermore, superficial macular vascular density was significantly correlated with mGCC thickness. Conclusions. Varying degrees of myopia did not affect macular vascular density in young healthy adults. In addition, superficial macular vascular density, as an independent factor, was positively correlated with mGCC thickness. [ABSTRACT FROM AUTHOR]

Baijiu is a unique and traditional distilled liquor in China. Flavor plays a crucial rule in baijiu. Up to now, the research on the flavor of baijiu has progressed from the identification of volatile compounds to the research on key aroma compounds, but the release mechanism of these characteristic compounds is still unclear. Meanwhile, volatile compounds account for only a tiny fraction, whereas ethanol and water account for more than 98% of the content in baijiu. By summarizing the ethanol–water hydrogen bond structure in different alcoholic beverages, it was found that flavor compounds can affect the association strength of the ethanol–water hydrogen bond, and ethanol–water can also affect the interface distribution of flavor compounds. Therefore, the research on ethanol–water microstructure in baijiu is helpful to realize the simple visualization of adulteration detection, aging determination and flavor release mechanism analysis of baijiu, and further uncover the mystery of baijiu. [ABSTRACT FROM AUTHOR]

Developing production technology pathways of sustainable aviation fuel (SAF) that align with China's national conditions and aviation transportation needs is crucial for promoting the SAF industry and achieving China's carbon peak and carbon neutrality goals. This article first projects the future SAF demand in China for the coming decades. Using SAF demand data as an input, this article employs the TOPSIS analysis method to comprehensively evaluate the suitability of four SAF production technology pathways at different stages of development in China, which are Hydroprocessed Esters and Fatty Acids (HEFA), Alcohol-to-Jet (AtJ), Natural Gas + Fischer–Tropsch Synthesis (G + FT), and Power-to-Liquid (PtL). The research results reveal the following trends: HEFA-based processes are the most suitable technology pathways for China in the near term; the G + FT route, based on energy crops, appears the most likely to support civil aviation needs in the medium to long term. In the long run, the PtL route holds significant potential, especially with the decreasing costs of green electricity, advancements in carbon capture, utilization, and storage (CCUS) technology, and improvements in SAF synthesis methods. In the final section of this article, we provide recommendations to drive the development of the SAF industry in China. [ABSTRACT FROM AUTHOR]

The pollution of heavy metals is extremely serious in China, including zinc (Zn), copper (Cu), lead (Pb), and cadmium (Cd). Heavy-metal-transporting ATPase (HMA) belongs to a subfamily of the P-ATPase family, which absorbs and transports Zn, Cu, Pb, and Cd in plants. Here, we describe a ZmHMA-encoding HMA family protein that positively regulates Cd and Zn tolerance. The real-time fluorescence quantification (RT-PCR) results revealed that ZmHMA3 had a high expression in B73, and the expression of ZmHMA3 was sensitive to Cd in yeast cells, which was related to Cd accumulation in yeast. Additionally, the Arabidopsis thaliana homologous mutants of AtHMA2 showed Cd sensitivity compared with WT. The overexpressing ZmHMA3 plants showed higher tolerance under Cd and Zn stresses than the wild type. The overexpression of ZmHMA3 led to higher Cd and Zn accumulation in tissues based on the subcellular distribution analysis. We propose that ZmHMA3 improves maize tolerance to Cd and Zn stresses by absorbing and transporting Cd and Zn ions. This study elucidates the gene function of the ZmHMA3 response to Cd and Zn stress and provides a reference for improving the characteristics of heavy metals enrichment in existing maize varieties and the plant remediation technology of heavy-metal-contaminated soil. [ABSTRACT FROM AUTHOR]

• A new operational model with ant-miner algorithm was proposed to predict the risk of forest fires in cloud-rich areas. • The performance of proposed model was compared with that of the national risk prediction model of China. • The proposed model was compared to other risk prediction models with two classical machine learning algorithms. • The ant-miner algorithm-based model was more effective and reliable. Annually, millions of hectares of forest lands around the world are destroyed by fires. To minimize the fire-caused losses, more studies on the risk prediction of forest fires need to be carried out. For predicting the risk of forest fires in cloud-rich areas (e.g., the southwest of China), the synergetic use of operational forecasting systems and remote sensing-based models is expected to have a consistent performance. Therefore, we proposed in this study a new model based on ant-miner algorithm which has a good capability of solving multivariable and non-linear problems in the synergetic modeling of multi-source data. Based on historical fire data during 2000–2018 in Chongqing city, its performance was tested, and then was compared with that of other three models (i.e., meteorological data-, Artificial Neural Network-, and Support Vector Machine-based models). Results showed that, without interference from human factors, the risk predictions of proposed model were more objective. And, its mined-rules were easier to understand and also portable across multiple GIS platforms. Moreover, the proposed model has a better performance at predicting risk levels (i.e., overall accuracy was 79.02% and Kappa coefficient was 0.678) and the spatial distribution of its predictions were more detailed. This research indicated that the ant-miner algorithm-based model was more effective and reliable, and it could be used for constructing the operational system of risk predictions for forest fires in cloud-rich areas. [ABSTRACT FROM AUTHOR]