| 1 | Chemical and Isotopic Characteristics of the Water and Suspended Particulate Materials in the Yangtze River and Their Geological and Environmental Implications显示文摘The chemical and isotopic characteristics of the water and suspended particulate materials(SPM) in the Yangtze River were investigated on the samples collected from 25 hydrological monitoring stations in the mainsteam and 13 hydrological monitoring stations in the major tributaries during 2003 to 2007. The water samples show a large variation in both δD( 30‰ to 112‰) and δ18O( 3.8‰ to 15.4‰) values. Both δD and δ18O values show a decrease from the river head to the Jinsha Jiang section and then increase downstream to the river mouth. It is found that the oxygen and hydrogen isotopic compositions of the Yangtze water are controlled by meteoric precipitation, evaporation, ice(and snow) melting and dam building. The Yangtze SPM concentrations show a large variation and are well corresponded to the spatial and temporal changes of flow speed, runoff and SPM supply, which are affected by the slope of the river bed, local precipitation rate, weathering intensity, erosion condition and anthropogenic activity. The Yangtze SPM consists of clay minerals, clastic silicate and carbonate minerals, heavy minerals, iron hydroxide and organic compounds. From the upper to lower reaches, the clay and clastic silicate components in SPM increase gradually, but the carbonate components decrease gradually, which may reflect changes of climate and weathering intensity in the drainage area. Compared to those of the upper crust rocks, the Yangtze SPM has lower contents of SiO2, CaO, K2 O and Na2 O and higher contents of TFe2 O3 and trace metals of Co, Ni, Cu, Zn, Pb and Cd. The ΣREE in the Yangtze SPM is also slightly higher than that of the upper crust. From the upper to lower reaches, the CaO and MgO contents in SPM decrease gradually, but the SiO2 content increases gradually, corresponding to the increase of clay minerals and decrease of the carbonates. The δ30SiSPM values( 1.1‰ to 0.3‰) of the Yangtze SPM are similar to those of the average shale, but lower than those of the granite rocks( 0.3‰ to 0.3‰), reflecting the effect of silicon isotope fractionation in silicate weathering process. The δ30SiSPM values of the Yangtze SPM show a decreasing trend from the upper to the middle and lower reaches, responding to the variation of the clay content. The major anions of the river water are HCO 3, SO 4 2, Cl, NO 3, SiO 4 4 and F and the major cations include Ca2+, Na+, Mg2+, K+ and Sr2+. The good correlation between HCO3-content and the content of Ca2+may suggest that carbonate dissolution is the dominate contributor to the total dissolved solid(TDS) of the Yangtze River. Very good correlations are also found among contents of Cl, SO4 2, Na+, Mg2+, K+and Sr2+, indicating the important contribution of evaporite dissolution to the TDS of the Yangtze River. High TDS contents are generally found in the head water, reflecting a strong effect of evaporation in the Qinghai-Tibet Plateau. A small increase of the TDS is generally observed in the river mouth, indicating the influence of tidal intrusion. The F and NO3 contents show a clear increase trend from the upstream to downstream, reflecting the contribution of pesticides and fertilizers in the Chuan Jiang section and the middle and lower reaches. The DSi shows a decrease trend from the upstream to downstream, reflecting the effect of rice and grass growth along the Chuan Jiang section and the middle and lower reaches. The dissolved Cu, Zn and Cd in the Yangtze water are all higher than those in world large rivers, reflecting the effect of intensive mining activity along the Yangtze drainage area. The Yangtze water generally shows similar REE distribution pattern to the global shale. The δ30SiDiss values of the dissolved silicon vary from 0.5‰ to 3.7‰, which is the highest among those of the rivers studied. The δ30SiDiss values of the water in the Yangtze mainsteam show an increase trend from the upper stream to downstream. Its DSi and δ30SiDiss are influenced by multiple processes, such as weathering process, phytolith growth in plants, evaporation, phytolith dissolution, growth of fresh water diatom, adsorption and desorption of aqueous monosilicic acid on iron oxide, precipitation of silcretes and formation of clays coatings in aquifers, and human activity. The δ34SSO4 values of the Yangtze water range from 1.7‰ to 9.0‰. The SO4 in the Yangtze water are mainly from the SO4 in meteoric water, the dissolved sulfate from evaporite, and oxidation of sulfide in rocks, coal and ore deposits. The sulfate reduction and precipitation process can also affect the sulfur isotope composition of the Yangtze water. The87Sr/86Sr ratios of the Yangtze water range from 0.70823 to 0.71590, with an average value of 0.71084. The87Sr/86Sr ratio and Sr concentration are primary controlled by mixing of various sources with different87Sr/86Sr ratios and Sr contents, including the limestone, evaporite and the silicate rocks. The atmospheric precipitation and anthropogenic inputs can also contribute some Sr to the river. The δ11B values of the dissolved B in the Yangtze water range from 2.0‰ to 18.3‰, which is affected by multifactors, such as silicate weathering, carbonate weathering, evaporite dissolution, atmospheric deposition, and anthropogenic inputs. | DING Tiping GAO Jianfei TIAN Shihong SHI Guoyu CHEN Feng WANG Chengyu LUO Xurong HAN Dan | 2014 | Acta Geologica Sinica(English Edition)2014，88，1： | 10 |
| 2 | Chemical and Isotopic Characters of the Water and Suspended Particulate Materials in the Yellow River and Their Geological and Environmental Implications显示文摘The chemical and isotopic characteristics of the water and suspended particulate materials(SPM)in the Yellow River were investigated on the samples collected from 29 hydrological monitoring stations in the mainstem and several major tributaries during 2004 to 2007.TheδD andδ^(18)O values of the Yellow River water vary in large ranges from-32‰to-91‰and from-3.1‰to-12.5‰,respectively.The characters of H and O isotope variations indicate that the major sources of the Yellow River water are meteoric water and snow melting water,and water cycle in the Yellow River basin is affected strongly by evaporation process and human activity.The average SPM content(9.635g/L)of the Yellow River is the highest among the world large rivers.Compared with the Yangtze River,the Yellow River SPM has much lower clay content and significantly higher contents of clastic silicates and carbonates.In comparison to the upper crust rocks,the Yellow River SPM contains less SiO_2,CaO,K_2O and Na_2O,but more TFe_2O_3,Co,Ni,Cu,Zn,Pb and Cd.The abnormal high Cd contents found in some sample may be related to local industrial activity.The REE contents and distribution pattern of the Yellow River SPM are very close to the average value of the global shale.The averageδ^(30)Si_(SPM)in the Yellow River(-0.11‰)is slightly higher than the average value(-0.22‰)of the Yangtze River SPM.The major factors controlling theδ^(30)Si_(SPM)of the Yellow River are the soil supply,the isotopic composition of the soil and the climate conditions.The TDS in the Yellow River are the highest among those of world large rivers.Fair correlations are observed among Cl^-,Na^+,K^+,and Mg^(2+)contents of the Yellow River water,indicating the effect of evaporation.The Ca^(2+)and Sr^(2+)concentrations show good correlation to the SO_4^(2-)concentration rather than HCO_3^-concentration,reflecting its origin from evaporates.The NO_3^-contents are affected by farmland fertilization.The Cu,Zn and Cd contents in dissolved load of the Yellow River water are all higher than those of average world large rivers,reflecting the effect of human activity.The dissolved load in the Yellow River water generally shows a REE distribution pattern parallel to those for the Yangtze River and the Xijiang River.Theδ^(30)Si values of the dissolved silicon vary in a range from 0.4‰to 2.9‰,averaging1.34‰.The major processes controlling the D_(Si)andδ^(30)Si_(Diss)of the Yellow River water are the weathering process of silicate rocks,growth of phytolith in plants,evaporation,dissolution of phytolith in soil,growth of fresh water diatom,adsorption and desorption of aqueous monosilicic acid on iron oxide and human activities.The averageδ^(30)Si_(Diss)value of the Yellow River is significantly lower than that of the Nile River,Yangtze River and Siberia rivers,but higher than those of other rivers,reflecting their differences in chemical weathering and biological activity.Theδ^(34)S_(SO4)values of the Yellow River water range from-3.8‰to 14.1‰,averaging 7.97‰.There is some correlation between SO_4^(2-)content andδ^(34)S_(SO4).The factors controlling theδ^(34)S_(SO4)of the Yellow River water are the SO_4 in the meteoric water,the SO_4 from gypsum or anhydrite in evaporite rocks,oxidation and dissolution of sulfides in the mineral deposits,magmatic rocks and sedimentary rocks,the sulfate reduction and precipitation process and the sulfate from fertilizer.The^(87)Sr/^(86)Sr ratios of all samplesrange from 0.71041 to 0.71237,averaging 0.71128.The variations in the^(87)Sr/^(86)Sr ratio and Sr concentration of river water are primarily caused by mixing of waters of various origins with different^(87)Sr/^(86)Sr ratios and Sr contents resulting from water-rock interaction with different rock types. | DING Tiping GAO Jianfei TIAN Shihong WANG Huaibai LI Ming WANG Chengyu LUO Xurong HANG Dan | 2016 | Acta Geologica Sinica(English Edition)2016，90，1： | 4 |
| 3 | Detection of antimicrobial resistance and virulence-related genes in Streptococcus uberis and Streptococcus parauberis isolated from clinical bovine mastitis cases in northwestern China显示文摘The objectives of this study were to investigate antimicrobial resistance of Streptococcus uberis and Streptococcus parauberis isolated from cows with bovine clinical mastitis in China and to examine the distribution of resistance-and virulence-related gene patterns.Antimicrobial susceptibility was determined by the E-test.Genes encoding antimicrobial resistance and invasiveness factors were examined by PCR.A total of 27 strains were obtained from 326 mastitis milk samples.Streptococcus parauberis isolates(n=11)showed high resistance to erythromycin(90.9%),followed by tetracycline(45.5%),chloramphenicol(36.4%)and clindamycin(27.3%).Streptococcus uberis isolates(n=16)were highly resistant to tetracycline(81.3%)and clindamycin(62.5%).Both species were susceptible to ampicillin.The most prevalent resistance gene in S.uberis was tetM(80.0%),followed by blaZ(62.5%)and ermB(62.5%).However,tetM,blaZ,and ermB genes were only found in 27.3,45.5,and 27.3%,respectively,of S.parauberis.In addition,all of the isolates carried at least one selected virulence-related gene.The most prevalent virulence-associated gene pattern in the current study was sua+pauA/skc+gapC+hasC detected in 22.2%of the strains.One S.uberis strain carried 7 virulence-associated genes and belonged to the sua+pauA/skc+gapC+cfu+hasA+hasB+hasC pattern.More than 59.3%of analysed strains carried 4 to 7 virulence-related genes.Our findings demonstrated that S.parauberis and S.uberis isolated from clinical bovine mastitis cases in China exhibited diverse molecular ecology,and that the strains were highly resistant to antibiotics commonly used in the dairy cow industry.The data obtained in the current study contribute to a better understanding of the pathogenesis of bacteria in mastitis caused by these pathogens,and the findings are relevant to the development of multivalent vaccines and targeted prevention procedures. | ZHANG Hang YANG Feng LI Xin-pu LUO Jin-yin WANG Ling ZHOU Yu-long YAN Yong WANG Xurong LI Hong-sheng | 2020 | Journal of Integrative Agriculture2020，19，11： | 3 |
| 5 | All-optical image classification through unknown random diffusers using a single-pixel diffractive network显示文摘Classification of an object behind a random and unknown scattering medium sets a challenging task for computational imaging and machine vision fields.Recent deep learning-based approaches demonstrated the classification of objects using diffuser-distorted patterns collected by an image sensor.These methods demand relatively large-scale computing using deep neural networks running on digital computers.Here,we present an all-optical processor to directly classify unknown objects through unknown,random phase diffusers using broadband illumination detected with a single pixel.A set of transmissive diffractive layers,optimized using deep learning,forms a physical network that all-optically maps the spatial information of an input object behind a random diffuser into the power spectrum of the output light detected through a single pixel at the output plane of the diffractive network.We numerically demonstrated the accuracy of this framework using broadband radiation to classify unknown handwritten digits through random new diffusers,never used during the training phase,and achieved a blind testing accuracy of 87.74±1.12%.We also experimentally validated our single-pixel broadband diffractive network by classifying handwritten digits'0'and'1'through a random diffuser using terahertz waves and a 3D-printed diffractive network.This single-pixel all-optical object classification system through random diffusers is based on passive diffractive layers that process broadband input light and can operate at any part of the electromagnetic spectrum by simply scaling the diffractive features proportional to the wavelength range of interest.These results have various potential applications in,e.g.,biomedical imaging,security,robotics,and autonomous driving. | Bijie Bai Yuhang Li Yi Luo Xurong Li Ege Cetintas Mona Jarrrahi Aydogan Ozcan | 2023 | Light(Science & Applications)2023，12，4： | 0 |
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