Iron(II)-catalyzed trifluoromethylation of vinylcyclopropanes

An efficient iron(II)-catalyzed trifluoromethylation of vinylcyclopropanes was developed.A series of CF3-containing dihydronaphthalene derivatives were prepared with a moderate to high yield.This method offers several advantages in terms of its mild condition,readily available and cheap catalyst,as well as short reaction time.Furthermore,the reaction mechanism was investigated preliminarily

Impacts of the Qinghai–Tibet Railway on Accessibility and Economic Linkage of the Third Pole

Constructing the Qinghai–Tibet Railway (QTR) was a landmark project and was beneficial to the sustainable development of the Third Pole. To understand the sustainable development of remote regions by the provision of railway, we studied the QTR’s impact on accessibilities and economic linkages for four cities in the Third Pole, Xining, Golmud, Nagqu, and Lhasa, and between these four cities and 29 capital cities in mid-eastern China. First, employing average shortest travel time (ASTT) and weighted average travel time (WATT) as indicators, we calculated the railway-based accessibilities for June 2006 and January 2013. Then, using a gravity model, railway-based economic linkages were determined. The results demonstrate that: (i) ASTT for Xining–Golmud decreased by 4.14 h from June 2006 to January 2013. Both ASTT and WATT indicated that the accessibilities of the four cities and between these four cities and 29 capital cities in mid-eastern China improved significantly, and the spatial disparity in accessibility for the four cities decreased, which increased the balance and sustainability of the transportation system; (ii) the average contribution rate of the QTR to improving economic linkages for six routes among the four cities was 25.29%, with the Xining–Nagqu and Nagqu–Lhasa linkages improving most significantly; (iii) the QTR strengthened economic linkages between the four cities and mid-eastern cities. Because of the QTR, the economic linkages between the four cities and 29 capital cities increased 27.58% on average. The spatial disparity in interurban economic linkages also decreased. Transporting products from Tibet should be promoted to strengthen the sustainability of economic growth

Mechanical and Microcrack Evolution Characteristics of Roof Rock of Coal Seam with Different Angle of Defects Based on Particle Flow Code

The creation of the natural ceiling rock of the coal seam is rife with fractures, holes, and other flaws. The angle of the defects has a significant influence on the mechanical characteristics and crack evolution of coal seam roof rock. Multi-scale numerical simulation software PFC2D gets adapted to realize the crack propagation and coalescence process in the roof rock of a coal seam with different angles of defects under uniaxial compression. The effect of flaw angles on the micro and macro mechanical characteristics of rock is also discovered. The results show that: (1) the defect angle has influence on the stress-strain, elastic modulus, peak strength, peak strain, acoustic emission (AE) and strain energy of roof rock of coal seam. When the defect angles are different, the starting position of the roof rock in a coal seam fracture is different. The quantity of microcracks firstly reduces with an increase in defect angles before gradually increasing. At the same fault angle, the cracks are mostly tensile ones and only a few shear ones. (2) When the defect angle is less than 90°, tensile and shear fractures are mostly localized at the defect’s two tips and propagate along the loading direction. When the defect angle is 90°, the tensile and shear cracks are not concentrated at the tip of the defect. (3) As the defect angles increase, the elastic strain energy rises initially and then falls, and the dissipated energy and total input energy both increase continuously. The elastic strain energy is greatest at the highest strength. The study provides a certain reference for the use of various analysis methods in practical engineering to evaluate the safety and stability of rock samples with pre-existing defects

A Study on Hydrochemical Characteristics and Evolution Processes of Groundwater in the Coastal Area of the Dagujia River Basin, China

Groundwater resource is vital for industrial, drinking and irrigation purposes in the Dagujia river basin, China. The objective of this work was to comprehensively assess the hydrochemical characteristics and evolution processes of the Quaternary aquifer (QA) and the bedrock aquifer (BA) of the basin using statistical methods and hydrochemical plots. In total, 56 groundwater samples were collected from the QA (34 samples) and BA (22 samples). In addition, statistical methods combined with the geographic information system were used to identify the hydrochemical parameters of groundwater, as well as its spatial distribution in the Dagujia river basin. The Piper diagram showed that Ca-Na-HCO3 was the dominant groundwater facies type, while nine QA samples collected near the coastal line showed the Na-Cl facies type. On the other hand, the Gibbs diagram showed that most samples fell in the rock dominance zone. The principal component analysis results showed that the water–rock interaction and anthropogenic activities are the controlling factors, which is consistent with the results obtained using other methods. The results of this study indicated that rock weathering controls the hydrochemical characteristics of groundwater, while anthropogenic contamination and sea water intrusion are becoming increasingly serious issues for both QA and BA in the Dagujia river basin. Therefore, both Quaternary and bedrock aquifers require more attention

Analysis of Seasonal Driving Factors and Inversion Model Optimization of Soil Moisture in the Qinghai Tibet Plateau Based on Machine Learning

The accuracy of soil moisture retrieval based on traditional microwave remote sensing models in the Qinghai Tibet Plateau (QTP) is unstable due to its unique plateau climate. However, considering the impact of multiple multi-scale factors effectively improves the accuracy and stability of soil moisture inversion. This article uses Sentinel-1 and seasonal climate data to analyze factors and influencing mechanisms of soil moisture in the QTP. First, an artificial neural network (ANN) was used to conduct a significance analysis to screen significant influencing factors to reduce the redundancy of the experimental design and insert information. Second, the normalization effect of each factor on the soil moisture inversion was determined, and the factors with significant normalization influences were input to fit the model. Third, different fitting methods combined the semi-empirical models for soil moisture inversion. The decision tree Chi-square Automatic Interaction Detector (CHAID) analyzed the model accuracy, and the Pearson correlation coefficient between the sample and measured data was tested to further validate the accuracy of the results to obtain an optimized model that effectively inverts soil moisture. Finally, the influencing mechanisms of various factors in the optimization model were analyzed. The results show that: (1) The terrain factors, such as elevation, slope gradient, aspect, and angle, along with climate factors, such as temperature and precipitation, all have the greatest normalized impact on soil moisture in the QTP. (2) For spring (March), summer (June), and autumn (September), the greatest normalized factor of soil moisture is the terrain factor. In winter (December), precipitation was the greatest factor due to heavy snow cover and permafrost. (3) Analyzing the impact mechanism from various factors on the soil moisture showed a restricted relationship between the inversion results and the accuracy of the power fitting model, meaning it is unsuitable for general soil moisture inversion. However, among the selected models, the accuracy of the linear fit was generally higher than 79.2%, the Pearson index was greater than 0.4, and the restricted relationship between the inversion results and accuracy was weak, making it suitable for the general inversion of soil moisture in the QTP

Transport characteristics of heavy metals in the soil-atmosphere-wheat system in farming areas and development of multiple linear regression predictive model

Abstract Heavy metal accumulation in agricultural products has become a major concern. Previous studies have focused on the transport of heavy metals from the soil and their accumulation in crops. However, recent studies revealed that wheat leaves, ears, and awns can also transport and accumulate heavy metals. Wheat grains can be influenced by two sources of heavy metals: soil contamination and atmospheric deposition. To comprehend the transport characteristics of heavy metals in soil, atmospheric deposition, and wheat, 37 samples each for wheat rhizosphere soil, wheat roots, stems, leaves, and grains were collected. Fifteen samples of atmospheric dry deposition and atmospheric wet deposition were collected from Linshu County (northern area), China. Based on the test data, the characteristics of heavy metals and their distribution in the study area were analyzed. Migration patterns of heavy metals in crops from different sources were investigated using Pearson correlation and redundancy analysis. Finally, a predictive model for heavy metals in wheat grains was developed using multiple linear regression analysis. Significant disparities in the distribution of heavy metals existed among wheat roots, stems, leaves, and grains. The coefficient of variation of heavy metals in atmospheric deposition was relatively high, indicating discernible spatial patterns influenced by human activities. Notably, a positive correlation was observed between the concentration of heavy metals in wheat grains and atmospheric deposition of Hg, Cd, and Pb. Conversely, Zn and Ni levels in wheat grains were significantly negatively associated with soil Zn, Ni, pH, and OM content. The contribution of heavy metal elements from different sources varied in their impact on the grain's heavy metal content. Specifically, atmospheric deposition was the primary source of Hg and Pb in wheat grains, while Cd, Ni, Cu, and Zn were predominantly derived from soil. Using a multiple linear regression model, we could accurately predict Hg, Pb, Cd, Ni, Zn, and As concentrations in crop grains. This model can facilitate quantitative evaluation of ecological risk of heavy metals accumulation in crops in the study area

Long non-coding RNA SPRY4-IT1: a new player in different diseases: DOI: 10.14800/rd.916

Long non-coding RNAs (lncRNAs) refer to a class of RNA molecules with poor protein coding potential and are usually larger than 200 nucleotides. SPRY4-IT1, a member of lncRNA, is derived from an intronic region within the SPRY4 gene. And accumulating evidence demonstrates that aberrant expression of SPRY4-IT1 is involved in the development of various diseases such as melanoma, esophageal squamous cell carcinoma (ESCC), renal cancer, gastric cancer, breast cancer, bladder cancer, Non-small-cell lung cancer (NSCLC), and preeclampsia. SPRY4-IT1 is significantly related to not only progression and prognosis of diseases but also cell proliferation, migration, invasion. SPRY4-IT1 contributes to various diseases via different molecular mechanism such as regulating the expression of proteins related to cell growth and migration, involving in epithelial–mesenchymal transition (EMT), affecting lipid metabolism, and regulating downstream gene expression. Moreover, SPRY4-IT1 can also be regulated by some epigenetic factors including Zeste homolog 2 (EZH2). Therefore, SPRY4-IT1 may be a novel prognostic biomarker and a potential therapeutic candidate for different diseases including various solid cancers and preeclampsia