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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]

• The feruloyl esterase activity in different layers of Jiupei at different fermentation times were determined and tracked. • The microorganisms with feruloyl esterase activity were screened and identified in Jiupei of sesame-flavor baijiu. • The conditions of enzyme production were optimized by liquid fermentation. Baijiu is a national beverage in China. Some functional compounds have been identified in baijiu, one of which is ferulic acid. One route for in situ ferulic acid synthesis is catalysed by feruloyl esterase from microorganisms using baijiu raw materials as substrates. However, few studies have focused on microorganisms obtained from baijiu that have feruloyl esterase activity. In this work, microorganisms with feruloyl esterase activity were screened in the fermented raw materials of baijiu. Four different microorganisms with feruloyl esterase activity were identified, and one strain, designated J1, showed high feruloyl esterase activity. The strain J1 belonged to the genus Acetobacter and showed the closest relationship with Acetobacter fabarum and Acetobacter lovaniensis. The feruloyl esterase production capacity of J1 was confirmed, and the fermentation conditions were optimised. The optimal enzyme production conditions for the highest feruloyl esterase activity required an initial fermentation pH of 7.0 at 30 °C, an inoculation volume of 10 %, and culturing for 24 h. [ABSTRACT FROM AUTHOR]

The Yangtze River Economic Belt (YREB) is an important strategic area in China. However, frequent extreme precipitation events have caused great economic losses and human casualties in this region. In this article, we explore the spatial and temporal links between extreme precipitation events and Sunspot Number (SSN), El Niño Southern Oscillation (ENSO), Arctic Oscillation (AO) and Pacific Decadal Oscillation (PDO) in this important economic belt. According to the research findings, all of the extreme precipitation indices (EPIs) except for consecutive dry days (CDD) and consecutive wet days (CWD) showed an upward trend in the YREB over the 59 years. The spatial distributions of very wet days (R95p), extremely wet days (R99p), max 1-day precipitation amount (Rx1day) and max 5-day precipitation amount (Rx5day) had similar distribution patterns, showing decreasing trends from east to west. The EPIs generally had a 2–4-year band, suggesting stronger and more elusive changes. The wavelet coherence (WTC) spectra suggested that SSN, ENSO, AO, and PDO have different effects on extreme precipitation events during different time periods. Before 1985, the SSN, ENSO, AO, PDO and extreme precipitation events shared similar oscillation periods, but after 1985, their oscillation periods were no longer consistent with each other. In addition, solar activity and the AO mainly had negative correlations with extreme precipitation events, while the ENSO and PDO had predominantly positive correlations with the EPIs. This paper provides a reference for national economic strategic planning and natural resource management in the YREB. [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]

With the explosive economic development of China over the past few decades, air pollution has become a serious environmental problem and has attracted increasing global concern. Using satellite-based PM 2.5 data from 2000 to 2015, we found that the temporal-spatial variation of PM 2.5 in East China is characterized by high concentrations in the northern part and low concentrations in the southern part of East China, and by being seasonally high in autumn and winter but low in spring and summer. We also found that the regional average PM 2.5 concentration shows an approximative peak pattern over the last 16 years, with the highest, 60.13 μg m − 3 , and the lowest, 46.18 μg m − 3 , occurring in 2007 and 2000, respectively. Despite obviously diminishing heavy polluted regions with a PM 2.5 of > 80 μg m − 3 after 2011, those cells dominated by natural background have still not recovered back to the clean level of 2000. These characteristics are valuable information to analyze the relative contributions of anthropogenic emissions and atmospheric conditions to the temporal-spatial variation characteristics of PM 2.5 . [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]