In Tunisia,water scarcity is only adding pressure on water demand in agriculture.In the context of sustainable development goals,Tunisia has been reusing treated wastewater(TWW)as a renewable and inexpensive source fo...In Tunisia,water scarcity is only adding pressure on water demand in agriculture.In the context of sustainable development goals,Tunisia has been reusing treated wastewater(TWW)as a renewable and inexpensive source for soil fertigation and groundwater(GW)recharge.However,major risks can be expected when the irrigation water is of poor quality.This study aims for evaluating the potential risk of TWW and GW irrigation on soil parameters.Accordingly,we evaluated the suitability of water quality through the analysis of major and minor cations and anions,metallic trace elements(MTEs),and the sodium hazard by using the sodium adsorption ratio(SAR)and the soluble sodium percentage(SSP).The risk of soil sodicity was further assessed by SAR and the exchangeable sodium percentage(ESP).The degree of soil pollution caused by MTEs accumulation was evaluated using geoaccumulation index(Igeo)and pollution load index(PLI).Soil maps were generated using inverse spline interpolation in ArcGIS software.The results show that both water samples(i.e.,TWW and GW)are suitable for soil irrigation in terms of salinity(electrical conductivity<7000μS/cm)and sodicity(SAR<10.00;SSP<60.00%).However,the contents of PO_(4)^(3-),Cu^(2+),and Cd^(2+)exceed the maximum threshold values set by the national and other standards.Concerning the soil samples,the average levels of SAR and ESP are within the standards(SAR<13.00;ESP<15.00%).On the other hand,PLI results reveal moderate pollution in the plot irrigated with TWW and no to moderate pollution in the plot irrigated with GW.Igeo results indicate that Cu^(2+)is the metallic trace element(MTE)with the highest risk of soil pollution in both plots(Igeo>5.00),followed by Ni^(2+)and Pb^(2+).Nevertheless,Cd^(2+)presents the lowest risk of soil pollution(Igeo<0.00).Statistical data indicates that Ca^(2+),Na+,Ni^(2+),and Pb^(2+)are highly distributed in both plots(coefficient of variation>50.0%).This study shows that the use of imagery tools,such as ArcGIS,can provide important information for evaluating t展开更多
Reagents are optimized for the simultaneous determination of trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in zinc sulfate solution, which contains an extremely large excess of Zn^(2+). First, the reagents and their d...Reagents are optimized for the simultaneous determination of trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in zinc sulfate solution, which contains an extremely large excess of Zn^(2+). First, the reagents and their doses for the experiment are selected according to the characteristics of the zinc sulfate solution. Then, the reagent doses are optimized by analyzing the influence of reagent dose on the polarographic parameters(i.e. half-wave potential E_(1/2) and limiting diffusion current I_p). Finally, the optimization results are verified by simultaneously determining trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in the presence of an extremely large excess of Zn^(2+). The determination results indicate that the optimized reagents exhibit wide linearity, low detection limits, high accuracy and good precision for the simultaneous determination of trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in the presence of an extremely large excess of Zn^(2+).展开更多
Dimensionality reduction is very important in pattern recognition, machine learning, and image recognition. In this paper, we propose a novel linear dimensionality reduction technique using trace ratio criterion, name...Dimensionality reduction is very important in pattern recognition, machine learning, and image recognition. In this paper, we propose a novel linear dimensionality reduction technique using trace ratio criterion, namely Discriminant Neighbourhood Structure Embedding Using Trace Ratio Criterion (TR-DNSE). TR-DNSE preserves the local intrinsic geometric structure, characterizing properties of similarity and diversity within each class, and enforces the separability between different classes by maximizing the sum of the weighted distances between nearby points from different classes. Experiments on four image databases show the effectiveness of the proposed approach.展开更多
文摘In Tunisia,water scarcity is only adding pressure on water demand in agriculture.In the context of sustainable development goals,Tunisia has been reusing treated wastewater(TWW)as a renewable and inexpensive source for soil fertigation and groundwater(GW)recharge.However,major risks can be expected when the irrigation water is of poor quality.This study aims for evaluating the potential risk of TWW and GW irrigation on soil parameters.Accordingly,we evaluated the suitability of water quality through the analysis of major and minor cations and anions,metallic trace elements(MTEs),and the sodium hazard by using the sodium adsorption ratio(SAR)and the soluble sodium percentage(SSP).The risk of soil sodicity was further assessed by SAR and the exchangeable sodium percentage(ESP).The degree of soil pollution caused by MTEs accumulation was evaluated using geoaccumulation index(Igeo)and pollution load index(PLI).Soil maps were generated using inverse spline interpolation in ArcGIS software.The results show that both water samples(i.e.,TWW and GW)are suitable for soil irrigation in terms of salinity(electrical conductivity<7000μS/cm)and sodicity(SAR<10.00;SSP<60.00%).However,the contents of PO_(4)^(3-),Cu^(2+),and Cd^(2+)exceed the maximum threshold values set by the national and other standards.Concerning the soil samples,the average levels of SAR and ESP are within the standards(SAR<13.00;ESP<15.00%).On the other hand,PLI results reveal moderate pollution in the plot irrigated with TWW and no to moderate pollution in the plot irrigated with GW.Igeo results indicate that Cu^(2+)is the metallic trace element(MTE)with the highest risk of soil pollution in both plots(Igeo>5.00),followed by Ni^(2+)and Pb^(2+).Nevertheless,Cd^(2+)presents the lowest risk of soil pollution(Igeo<0.00).Statistical data indicates that Ca^(2+),Na+,Ni^(2+),and Pb^(2+)are highly distributed in both plots(coefficient of variation>50.0%).This study shows that the use of imagery tools,such as ArcGIS,can provide important information for evaluating t
基金Projects(61533021,61321003,61273185)supported by the National Natural Science Foundation of ChinaProject(2015CX007)supported by the Innovation-driven Plan in Central South University,ChinaProject(13JJ8003)supported by the Joint Fund of Hunan Provincial Natural Science Foundation of China
文摘Reagents are optimized for the simultaneous determination of trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in zinc sulfate solution, which contains an extremely large excess of Zn^(2+). First, the reagents and their doses for the experiment are selected according to the characteristics of the zinc sulfate solution. Then, the reagent doses are optimized by analyzing the influence of reagent dose on the polarographic parameters(i.e. half-wave potential E_(1/2) and limiting diffusion current I_p). Finally, the optimization results are verified by simultaneously determining trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in the presence of an extremely large excess of Zn^(2+). The determination results indicate that the optimized reagents exhibit wide linearity, low detection limits, high accuracy and good precision for the simultaneous determination of trace amounts of Cu^(2+), Cd^(2+) and Co^(2+) in the presence of an extremely large excess of Zn^(2+).
文摘Dimensionality reduction is very important in pattern recognition, machine learning, and image recognition. In this paper, we propose a novel linear dimensionality reduction technique using trace ratio criterion, namely Discriminant Neighbourhood Structure Embedding Using Trace Ratio Criterion (TR-DNSE). TR-DNSE preserves the local intrinsic geometric structure, characterizing properties of similarity and diversity within each class, and enforces the separability between different classes by maximizing the sum of the weighted distances between nearby points from different classes. Experiments on four image databases show the effectiveness of the proposed approach.
