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| 1 | Environmental factors influencing snowfall and snowfall prediction in the Tianshan Mountains, Northwest China显示文摘Snowfall is one of the dominant water resources in the mountainous regions and is closely related to the development of the local ecosystem and economy. Snowfall predication plays a critical role in understanding hydrological processes and forecasting natural disasters in the Tianshan Mountains, where meteorological stations are limited. Based on climatic, geographical and topographic variables at 27 meteorological stations during the cold season(October to April) from 1980 to 2015 in the Tianshan Mountains located in Xinjiang of Northwest China, we explored the potential influence of these variables on snowfall and predicted snowfall using two methods: multiple linear regression(MLR) model(a conventional measuring method) and random forest(RF) model(a non-parametric and non-linear machine learning algorithm). We identified the primary influencing factors of snowfall by ranking the importance of eight selected predictor variables based on the relative contribution of each variable in the two models. Model simulations were compared using different performance indices and the results showed that the RF model performed better than the MLR model, with a much higher R^2 value(R^2=0.74; R^2, coefficient of determination) and a lower bias error(RSR=0.51; RSR, the ratio of root mean square error to standard deviation of observed dataset). This indicates that the non-linear trend is more applicable for explaining the relationship between the selected predictor variables and snowfall. Relative humidity, temperature and longitude were identified as three of the most important variables influencing snowfall and snowfall prediction in both models, while elevation, aspect and latitude were of secondary importance, followed by slope and wind speed. These results will be beneficial to understand hydrological modeling and improve management and prediction of water resources in the Tianshan Mountains. | ZHANG Xueting LI Xuemei LI Lanhai ZHANG Shan QIN Qirui | 2019 | Journal of Arid Land2019，11，1： | 8 |
| 2 | Performance and uncertainty analysis of a short-term climate reconstruction based on multi-source data in the Tianshan Mountains region,China显示文摘Short-term climate reconstruction,i.e.,the reproduction of short-term(several decades)historical climatic time series based on the relationship between observed data and available longer-term reference data in a certain area,can extend the length of climatic time series and offset the shortage of observations.This can be used to assess regional climate change over a much longer time scale.Based on monthly grid climate data from a Coupled Model Inter-comparison Project phase 5(CMIP5)dataset for the period of 1850–2000,the Climatic Research Unit(CRU)dataset for the period of 1901–2000 and the observed data from 53 meteorological stations located in the Tianshan Mountains region(TMR)of China during the period of 1961–2011,we calibrated and validated monthly average temperature(MAT)and monthly accumulated precipitation(MAP)in the TMR using the delta,physical scaling(SP)and artificial neural network(ANN)methods.Performance and uncertainty during the calibration(1971–1999)and verification(1961–1970)periods were assessed and compared using traditional performance indices and a revised set pair analysis(RSPA)method.The calibration and verification processes were subjected to various sources of uncertainty due to the influence of different reconstructed variables,different data sources,and/or different methods used.According to traditional performance indices,both the CRU and CMIP5 datasets resulted in satisfactory calibrated and verified MAT time series at 53 meteorological stations and MAP time series at 20 meteorological stations using the delta and SP methods for the period of 1961–1999.However,the results differed from those obtained by the RSPA method.This showed that the CRU dataset produced a low degree of uncertainty(positive connection degree)during the calibration and verification of MAT using the delta and SP methods compared to the CMIP5 dataset.Overall,the calibrated and verified MAP had a high degree of uncertainty(negative connection degree)regardless of the dataset or reconstruction method used.Therefore,the reconstructed time series of MAT for the period of 1850(or 1901)–1960 based on the CRU and CMIP5 datasets using the delta and SP methods could be used for further study.The results of this study will be useful for short-term(several decades)regional climate reconstruction and longer-term(100 a or more)assessments of regional climate change. | LI Xuemei Slobodan P SIMONOVIC LI Lanhai ZHANG Xueting QIN Qirui | 2020 | Journal of Arid Land2020，12，3： | 2 |
| 3 | Curcumin enhances the radiosensitivity in nasopharyngeal carcinoma cellsinvolving the reversal of differentially expressed long non-coding RNAs显示文摘 | Qirui Wang Haoning Fan Ying Liu Zhixin Yin Hongbing Cai Jie Liu Zhiyuan Wang Meng Shao Xuegang Sun Jianxin Diao Yuanliang Liu Li Tong Qin Fan | 2014 | International Journal of Oncology2014，，3： | 1 |
| 4 | g-C_(3)N_(4) Derived Materials for Photocatalytic Hydrogen Production: A Mini Review on Design Strategies显示文摘Hydrogen production through solar energy is one of the most important pathways to meet the growing demand of renewable energy,and photocatalyst participation in solar hydrolytic hydrogen production has received great attention in recent years in terms of low cost,high efficiency,and flexible design.Particularly,g-C_(3)N_(4)(Graphitic-like carbon nitride material),as a unique material,can catalyze the hydrogen production process by completing the separation and transmission of charge.The easily adjustable pore structure/surface area,dimension,band-gap modulation and defect have shown great potential for hydrogen production from water cracking.In this review,the most recent advance of g-C_(3)N_(4) including the doping of metal and non-metal elements,and the formation of semiconductor heterojunction is highlighted.The main modification strategies and approaches for the design of g-C_(3)N_(4) for hydrogen production,as well as the influence of various materials on hydrogen evolution regarding the photocatalysis mechanism and advantages brought by theoretical calculations are specially and briefly illu-strated.Potential design pathways and strategies of g-C_(3)N_(4) are discussed.In addition,current challenges of hydrogen production from g-C_(3)N_(4) water splitting are summarized and can be expected. | Kai Su Shaoqi Deng Linxiao Li Qirui Qin Jingyu Yang Yan Chen Shengli Zhang Junming Chen | 2022 | Journal of Renewable Materials2022，10，3： | 0 |
| 5 | Towards unraveling relationships in Xylariomycetidae(Sordariomycetes)显示文摘The classification of subclass Xylariomycetidae is revisited with additional collections and phylogeny based on novel rDNA sequence data.Phylogenetic inferences are provided and are based on analysis of 115 sequence data,including new data for 27 strains.An updated outline to the subclass is presented based on the phylogenies and comprises two orders,18 families and 222 genera.An account of each order,family and genus in the subclass is given.We accept the orders Amphisphaeriales and Xylariales based on morphological and phylogenetic evidence.Amphisphaeriales comprises Amphisphaeriaceae,Bartaliniaceae fam.nov.,Clypeosphaeriaceae,Discosiaceae fam.nov.,Pestalotiopsidaceae fam.nov.and Phlogicylindriaceae fam.nov.Xylariales comprises Apiosporaceae,Cainiaceae,Coniocessiaceae,Diatrypaceae,Graphostromataceae(doubtful),Hyponectriaceae,Iodosphaeriaceae,Lopadostomaceae fam.nov.,Melogrammataceae,Pseudomassariaceae fam.nov.,Vialaeaceae and Xylariaceae.The new genera and species introduced are Arthrinium hyphopodii,A.subglobosa,Cainia anthoxanthis,Ciferriascosea gen.nov.,C.fluctamurum,C.rectamurum,Discosia neofraxinea,D.pseudopleurochaeta,Hyalotiella rubi,Seimatosporium cornii,S.ficeae,S.vitis and Truncatella spartii. | Indunil C.Senanayake Sajeewa S.N.Maharachchikumbura Kevin D.Hyde Jayarama D.Bhat E.B.Gareth Jones Eric H.C.McKenzie Dong Qin Dai Dinushani A.Daranagama Monika C.Dayarathne Ishani D.Goonasekara Sirinapa Konta Wen Jing Li Qiu Ju Shang Marc Stadler Nalin N.Wijayawardene Yuan Pin Xiao Chada Norphanphoun Qirui Li Xing Zhong Liu Ali H.Bahkali Ji Chuan Kang Yong Wang Ting Chi Wen Lucile Wendt Jian Chu Xu Erio Camporesi | 2015 | Fungal Diversity2015，，4： | 0 |
| 6 | Recent Advance on Torrefaction Valorization and Application of Biochar from Agricultural Waste for Soil Remediation显示文摘With the increase of global proportion of soil pollution and the number of areas at risk,researchers have sought to develop various pathways to repair or relieve the pollutants in soil.Among them,biochar represents one multi-dimensional soil amendment which has got great deal of attention on its physicochemical properties towards the removal or mitigation of contaminants in soil.A variety of agricultural wastes like straw and manure prepared from different torrefaction process have been employed as feedstock for the production of biochar,which can be applied to the contaminated soil to facilitate the growing environment for crops,and to improve soil fertility and microbial environment.In addition,the utilization of biochar for soil remediation is also considered as a pro-cess of carbon sequestration.The purpose of this review is to summarize the latest research progress in torrefac-tion processes and mechanism of agricultural waste,the effects of different torrefaction methods on the formation and properties of biochar were explained,coupled with the effects of process parameters.Especially,the conver-sion and mechanisms of biochar prepared from agricultural wastes composed mainly with lignocellulosic material were discussed,and the characteristics of biochar prepared for improving soil physical and chemical character-istics,microbial community characteristics,nutrients,and the stability and relief of soil pollutants,especially heavy metals,are compared.Finally,this work discussed the application and future technical challenges of soil remediation based on agricultural waste derived biochar. | Kai Su Qirui Qin Jingyu Yang Linxiao Li and Shaoqi Deng | 2022 | Journal of Renewable Materials2022，10，2： | 0 |
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