Achieving Win–Win Solutions in Telecoupled Human–Land Systems

Telecoupling refers to socioeconomic and environmental interactions between distant places. Telecoupling is becoming even more significant in the increasingly globalized world and it plays a key role in the emergence of major global environmental problems. In particular, it contributes to land degradation and the achievement of the United Nations’ Sustainable Development Goals (SDGs). However, there is a lack of systematic examination of the impacts of telecoupling on land system change, and how to respond to the undesirable impacts. Based on CiteSpace Software, here we analyze the current research status of telecoupled human–land systems, including publications, major scientific research institutions, and research processes. We explore the impacts of telecoupling on land and how to respond to these impacts. Finally, we propose a framework that is composed of impact identification, system integration, and responses to achieve a win-win situation in telecoupled human–land systems. The framework can help to create a sustainable future for telecoupled human–land systems

Mitigation mechanism of zinc oxide nanoparticles on cadmium toxicity in tomato

Cadmium (Cd) pollution seriously reduces the yield and quality of vegetables. Reducing Cd accumulation in vegetables is of great significance for improving food safety and sustainable agricultural development. Here, using tomato as the material, we analyzed the effect of foliar spraying with zinc oxide nanoparticles (ZnO NPs) on Cd accumulation and tolerance in tomato seedlings. Foliar spraying with ZnO NPs improved Cd tolerance by increasing photosynthesis efficiency and antioxidative capacity, while it reduced Cd accumulation by 40.2% in roots and 34.5% in leaves but increased Zn content by 33.9% in roots and 78.6% in leaves. Foliar spraying with ZnO NPs also increased the contents of copper (Cu) and manganese (Mn) in the leaves of Cd-treated tomato seedlings. Subsequent metabonomic analysis showed that ZnO NPs exposure alleviated the fluctuation of metabolic profiling in response to Cd toxicity, and it had a more prominent effect in leaves than in roots. Correlation analysis revealed that several differentially accumulated metabolites were positively or negatively correlated with the growth parameters and physiol-biochemical indexes. We also found that flavonoids and alkaloid metabolites may play an important role in ZnO NP-alleviated Cd toxicity in tomato seedlings. Taken together, the results of this study indicated that foliar spraying with ZnO NPs effectively reduced Cd accumulation in tomato seedlings; moreover, it also reduced oxidative damage, improved the absorption of trace elements, and reduced the metabolic fluctuation caused by Cd toxicity, thus alleviating Cd-induced growth inhibition in tomato seedlings. This study will enable us to better understand how ZnO NPs regulate plant growth and development and provide new insights into the use of ZnO NPs for improving growth and reducing Cd accumulation in vegetables

Catalytic promiscuity of O-methyltransferases from Corydalis yanhusuo leading to the structural diversity of benzylisoquinoline alkaloids

O-methyltransferases play essential roles in producing structural diversity and improving the biological properties of benzylisoquinoline alkaloids (BIAs) in plants. In this study, Corydalis yanhusuo, a plant used in traditional Chinese medicine due to the analgesic effects of its BIA-active compounds, was employed to analyze the catalytic characteristics of O-methyltransferases in the formation of BIA diversity. Seven genes encoding O-methyltransferases were cloned, and functionally characterized using seven potential BIA substrates. Specifically, an O-methyltransferase (CyOMT2) with highly efficient catalytic activity of both 4′- and 6-O-methylations of 1-BIAs was found. CyOMT6 was found to perform two sequential methylations at both 9- and 2-positions of the essential intermediate of tetrahydroprotoberberines, (S)-scoulerine. Two O-methyltransferases (CyOMT5 and CyOMT7) with wide substrate promiscuity were found, with the 2-position of tetrahydroprotoberberines as the preferential catalytic site for CyOMT5 (named scoulerine 2-O-methyltransferase) and the 6-position of 1-BIAs as the preferential site for CyOMT7. In addition, results of integrated phylogenetic molecular docking analysis and site-directed mutation suggested that residues at sites 172, 306, 313, and 314 in CyOMT5 are important for enzyme promiscuity related to O-methylations at the 6- and 7-positions of isoquinoline. Cys at site 253 in CyOMT2 was proved to promote the methylation activity of the 6-position and to expand substrate scopes. This work provides insight into O-methyltransferases in producing BIA diversity in C. yanhusuo and genetic elements for producing BIAs by metabolic engineering and synthetic biology

Dynamic Sealing Behavior of Sand Self-Juxtaposition Windows on a Trap-Bounding Fault in a Natural Gas Storage Site

AbstractAn understanding of across-fault seals is essential for planning an injection/production strategy for a fault-bounded gas storage site. In addition, it is more likely to permit lateral leakage for a fault with sand self-juxtaposition windows. This paper is aimed at identifying the dynamic sealing behaviors of a sand self-juxtaposition fault on the geological and gas injection timescales. Banzhongbei gas storage site, China, was taken as a target area, and fault seals and hydrocarbon distributions within the original reservoirs were studied. The results showed that across-fault pressure differences of 0.085~0.146 MPa (equivalent to 41.6~71.5 m oil-column and 27.0~46.4 m gas-column heights) were supported by sand self-juxtaposition windows on the B816 fault, and the resultant absolute permeability (5.97×10−2~5.69×10−1 mD) of the fault was nearly 3~4 orders of magnitude lower than the average absolute permeability of reservoirs (1.16×102 mD). Gas composition contrasts, between the original and injection gas coupled with dynamic pressure monitoring data, indicated that lateral leakage occurred across sand self-juxtaposition windows under the condition of high across-fault pressure difference. However, the low-permeability fault showed strong negative influence on the efficiency of fluid flow in the model calculations and prolongs the timescales of pressure-difference decayed as much as 5 orders of magnitude relative to those of nonfault model calculations. These modeled dynamic sealing behaviors of sand self-juxtaposition windows may lead to a better understanding of the relative retardation of across-fault gas flow by weak sealing faults on the gas injection/production timescale

Preparation of Aligned Ultra-long and Diameter-controlled Silicon Oxide Nanotubes by Plasma Enhanced Chemical Vapor Deposition Using Electrospun PVP Nanofiber Template

Well-aligned and suspended polyvinyl pyrrolidone (PVP) nanofibers with 8 mm in length were obtained by electrospinning. Using the aligned suspended PVP nanofibers array as template, aligned ultra-long silicon oxide (SiOx) nanotubes with very high aspect ratios have been prepared by plasma-enhanced chemical vapor deposition (PECVD) process. The inner diameter (20–200 nm) and wall thickness (12–90 nm) of tubes were controlled, respectively, by baking the electrospun nanofibers and by coating time without sacrificing the orientation degree and the length of arrays. The micro-PL spectrum of SiOx nanotubes shows a strong blue–green emission with a peak at about 514 nm accompanied by two shoulders around 415 and 624 nm. The blue–green emission is caused by the defects in the nanotubes

A Risk Prediction Model of Hard Landing Based on Random Forest Algorithm

Landing safety is a hot issue in civil aviation safety management. In order to fully mine the influence factors of hard landing in flight data and effectively predict the risk of hard landing, the random forest algorithm was introduced. Firstly, this paper qualitatively analyzed the influence factors of hard landing, and chose the features of the model based on the flight data. Secondly, this paper gives a quantitative analysis method of the importance of features based on Gini index. Finally, for the dataset of hard landing was class-imbalanced, the model was training based on SMOTE method. Then, the random forests classifier was built and verified by real flight data. The results showed that the recall rate of the model was 85.50%. The model can not only effectively prevent the occurrence of hard landing, but also provide a method reference for airlines to apply data mining to improve the ability of flight events management

Effects of caffeine ingestion on physiological indexes of human neuromuscular fatigue: A systematic review and meta‐analysis

Abstract Background Caffeine is often used as a stimulant during fatigue, but the standard of characteristic physiological indicators of the effect of caffeine on neuromuscular fatigue has not been unified. The purpose of this systematic review and meta‐analysis is to summarize current experimental findings on the effects of caffeine on physiological indexes before and after neuromuscular fatigue, identify some characteristic neuromuscular physiological indexes to assess the potential effects of caffeine. Methods The Preferred Reporting Items for Systematic Reviews and Meta‐analyses are followed. We systematically searched PubMed, Google academic, and Web of Science for randomized controlled trials. We searched for studies on caffeine's (i) effects on neuromuscular fatigue and (ii) the influence of physiological indexes changes. Meta‐analysis was performed for standardized mean differences (SMD) between caffeine and placebo trials in individual studies. Results The meta‐analysis indicated that caffeine significantly improves voluntary activation (VA) (SMD = 1.46;95%CI:0.13, 2.79; p < .00001), PTw (SMD = 1.11, 95%CI: –1.61, 3.84; p < .00001), and M‐wave (SMD = 1.10, 95%CI: –0.21, 2.41; p < .00001), and a significant difference (p = .003) on measures of Peak Power (PP), and insignificant difference on measures of heart rate (HR) (I2 = 0.0, p = .84) and Maximal oxygen uptake (VO2) (I2 = 0.0, p = .76). Conclusion The analysis showed that caffeine intake had a relatively large effect on VA, potentiated twitch (PTw), M‐wave, which can be used as characteristic indexes of caffeine's impact on neuromuscular fatigue. This conclusion tends to indicate the effects of caffeine on neuromuscular fatigue during endurance running or jumping or muscle bending and stretching. The caffeine intake had a big effect on the electromyogram (EMG) and peak power (PP), and its effect role needs to be further verified, this conclusion tends to indicate the effect of caffeine on neuromuscular fatigue during jumping or elbow bending moment movements. HR, VO2, maximal voluntary contraction (MVC) cannot be used as the characteristic indexes of caffeine on neuromuscular fatigue. This conclusion tends to indicate the effect of caffeine on neuromuscular fatigue during endurance exercise. However, the results of meta‐analysis are based on limited evidence and research scale, as well as individual differences of participants and different physical tasks, so it is necessary to interpret the results of meta‐analysis cautiously. Therefore, future research needs to explore other physiological indicators and their indicative effects in order to determine effective and accurate characteristic indicators of caffeine on neuromuscular fatigue

High-resolution mapping of water photovoltaic development in China through satellite imagery

Renewable energy is crucial to address climate change and achieve carbon neutrality. Within the existing technologies, photovoltaics is one of the most promising renewable energies. However, large-scale development of photovoltaics always needs a large amount of space, competing for land with other usages. Installing photovoltaics on water surfaces such as lakes and reservoirs is one of the major solutions to solve the contradiction between photovoltaic development and land shortage. In recent years, many countries have been actively promoting the development of water photovoltaic (WPV) to reduce carbon emission and meet increased energy demand, of which China is far ahead. Mapping the spatial distribution of WPV with satellite image time series will help reveal the spatial distribution, assess the scale and future potential of national WPV development, and understand its environmental impact. However, studies and reliable spatial data on the extent and distribution of WPV are still lacking. To address this gap, we proposed a classification algorithm based on Random Forest to extract WPV features and determine the types of the WPV from the Sentinel time series. The results show that the area of WPV in China reached 165 km2 in 2019, with an average annual growth of 43.8 km2 from 2016 to 2019. Among them, Stationary Photovoltaic (SPV) accounts for 95% of the total WPV, while Floating Photovoltaic (FPV) only accounts for 5%. Based on our WPV mapping results, we estimated the installed capacity and power generation of WPV would be approximately 6911 MW and 7.8 TWh yr−1, accounting for 3.4% and 3.5% of the total cumulative installed PV capacity and total PV power generation, respectively. This study provides an efficient and robust approach for extracting WPV at a large scale. The WPV data can be a valuable supplement to official tabulate data because it contains much finer spatial information that can assist stakeholders with future WPV planning and environmental impact assessment