建立了一种基于近红外光谱(Near infrared spectroscopy,NIR)结合小波变换-随机森林(Wavelet transform-Random forest,WT-RF)的用于甲醇汽油中甲醇含量快速定量分析的方法。采用傅里叶变换红外光谱仪采集54个甲醇汽油样品的光谱,并进...建立了一种基于近红外光谱(Near infrared spectroscopy,NIR)结合小波变换-随机森林(Wavelet transform-Random forest,WT-RF)的用于甲醇汽油中甲醇含量快速定量分析的方法。采用傅里叶变换红外光谱仪采集54个甲醇汽油样品的光谱,并进行光谱解析;探究不同光谱预处理方法对样品NIR光谱的处理效果,重点探究基于不同小波基函数与小波分解层数的小波变换(Wavelet transform,WT)光谱预处理效果,并通过优化变量重要性阈值筛选随机森林RF校正模型的输入变量;基于优化后的参数及输入变量,构建了甲醇汽油NIR光谱的WT-RF模型。为了进一步验证此模型的预测性能,将其与小波变换-偏最小二乘校正模型(Wavelet transform-Partial least squares,WT-PLS)和小波变换-最小二乘支持向量机校正模型(Wavelet transform-Least square support vector machine,WT-LSSVM)进行对比。结果表明,WT-RF校正模型具有最佳的预测性能,其交叉验证决定系数(Coefficient of determination of cross-validation,Rcv2)和均方根误差(Root mean square error of cross-validation,RMSECV)分别是0. 9990和0. 0044%,预测集决定系数(Coefficient of determination of prediction set,Rp2)和均方根误差(Root mean square error of prediction set,RMSEP)分别为0.9885和0.0191%。研究结果表明,NIR光谱结合WT-RF算法是一种快速准确定量分析甲醇汽油中甲醇含量的方法。展开更多
Fluorescence interferometry is developed and applied to study ultrafast amplitude and phase dynamics for fleeinduction decay in powdered rare earth solids. The time-resolved phase dynamics of free-induction decay thro...Fluorescence interferometry is developed and applied to study ultrafast amplitude and phase dynamics for fleeinduction decay in powdered rare earth solids. The time-resolved phase dynamics of free-induction decay throughout the decaying process is accurately determined by using a novel dual-channel correlation technique and subpicosecond dephasing time is measured for Nd3+ solids at room temperature. The phase dynamics is well simulated with linear coherent polarization theory.展开更多
柴油车是城市氮氧化物和颗粒物污染的主要来源之一。以一种新型的发动机前端空气净化技术(warp air clean,WAC)为研究对象,研究其对7辆柴油货车在怠速和自由加速阶段的减排效果。结果表明:WAC对柴油货车一氧化碳(CO)、氮氧化物(NO_(x))...柴油车是城市氮氧化物和颗粒物污染的主要来源之一。以一种新型的发动机前端空气净化技术(warp air clean,WAC)为研究对象,研究其对7辆柴油货车在怠速和自由加速阶段的减排效果。结果表明:WAC对柴油货车一氧化碳(CO)、氮氧化物(NO_(x))、碳氢化合物(HC)和颗粒物数量(particulate number,PN)的平均减排率分别为12.2%、2.9%、3.9%和11.3%;不同排放标准下,WAC对国Ⅲ车辆的净化效果更佳。同一排放标准下,轻型柴油车的减排效果要优于重型柴油车;怠速(空挡)阶段,WAC对使用年限长、排放标准低的车辆净化效果更佳;自由加速阶段,WAC对CO、NO_(x)和HC的净化作用主要表现为降低车辆加速过程中气体污染物排放的峰值,最高分别可达70.6%、50.0%和38.6%。展开更多
The combination of hologram quantitative structure-activity relationship(HQSAR)and consensus modeling was employed to study the quantitative structure-property relationship(QSPR)model for calculating the aqueous hydro...The combination of hologram quantitative structure-activity relationship(HQSAR)and consensus modeling was employed to study the quantitative structure-property relationship(QSPR)model for calculating the aqueous hydroxyl radical oxidation reaction rate constants(kOH)of organic micropollutants(OMPs).Firstly,individual HQSAR model were established by using standard HQSAR method.The optimal individual HQSAR model was obtained while setting the parameter of fragment distinction and fragment size to“B”and“3~6”respectively.Secondly,consensus HQSAR model was established by building the regression model between the kOH and the hologram descriptors with consensus partial least-squares(cPLS)approach.The obtained individual and consensus HQSAR model were validated with a randomly selected external test set.The result of external test set validation demonstrates that both individual and consensus HQSAR model are available for predicting the kOH of OMPs.Compared with the optimal individual HQSAR model,the established consensus HQSAR model shows higher prediction accuracy and robustness.It is shown that the combination of HQSAR and consensus modeling is a practicable and promising method for studying and predicting the kOH of OMPs.展开更多
文摘建立了一种基于近红外光谱(Near infrared spectroscopy,NIR)结合小波变换-随机森林(Wavelet transform-Random forest,WT-RF)的用于甲醇汽油中甲醇含量快速定量分析的方法。采用傅里叶变换红外光谱仪采集54个甲醇汽油样品的光谱,并进行光谱解析;探究不同光谱预处理方法对样品NIR光谱的处理效果,重点探究基于不同小波基函数与小波分解层数的小波变换(Wavelet transform,WT)光谱预处理效果,并通过优化变量重要性阈值筛选随机森林RF校正模型的输入变量;基于优化后的参数及输入变量,构建了甲醇汽油NIR光谱的WT-RF模型。为了进一步验证此模型的预测性能,将其与小波变换-偏最小二乘校正模型(Wavelet transform-Partial least squares,WT-PLS)和小波变换-最小二乘支持向量机校正模型(Wavelet transform-Least square support vector machine,WT-LSSVM)进行对比。结果表明,WT-RF校正模型具有最佳的预测性能,其交叉验证决定系数(Coefficient of determination of cross-validation,Rcv2)和均方根误差(Root mean square error of cross-validation,RMSECV)分别是0. 9990和0. 0044%,预测集决定系数(Coefficient of determination of prediction set,Rp2)和均方根误差(Root mean square error of prediction set,RMSEP)分别为0.9885和0.0191%。研究结果表明,NIR光谱结合WT-RF算法是一种快速准确定量分析甲醇汽油中甲醇含量的方法。
基金Supported by the National Natural Science Foundation of China under Grant No.29673058Ministry of Education under GrantNo.97055803and Natural Science Foundation of Guangdong under Grant No.970146.
文摘Fluorescence interferometry is developed and applied to study ultrafast amplitude and phase dynamics for fleeinduction decay in powdered rare earth solids. The time-resolved phase dynamics of free-induction decay throughout the decaying process is accurately determined by using a novel dual-channel correlation technique and subpicosecond dephasing time is measured for Nd3+ solids at room temperature. The phase dynamics is well simulated with linear coherent polarization theory.
文摘柴油车是城市氮氧化物和颗粒物污染的主要来源之一。以一种新型的发动机前端空气净化技术(warp air clean,WAC)为研究对象,研究其对7辆柴油货车在怠速和自由加速阶段的减排效果。结果表明:WAC对柴油货车一氧化碳(CO)、氮氧化物(NO_(x))、碳氢化合物(HC)和颗粒物数量(particulate number,PN)的平均减排率分别为12.2%、2.9%、3.9%和11.3%;不同排放标准下,WAC对国Ⅲ车辆的净化效果更佳。同一排放标准下,轻型柴油车的减排效果要优于重型柴油车;怠速(空挡)阶段,WAC对使用年限长、排放标准低的车辆净化效果更佳;自由加速阶段,WAC对CO、NO_(x)和HC的净化作用主要表现为降低车辆加速过程中气体污染物排放的峰值,最高分别可达70.6%、50.0%和38.6%。
基金supported by the National Natural Science Foundation of China(No.21775118)Shaanxi Natural Science Basic Research Project(No.2018JM2018)+2 种基金Youth Innovation Team of Shaanxi Universities(No.2019.21)Young Outstanding Talent Support Program of Shaanxi UniversitiesXi’an Shiyou University Youth Research and Innovation Team Construction Plan(No.2019QNKYCXTD17),and Xi’an Shiyou University Graduate Innovation and Practice Ability Training Project(No.YCS19211016)。
文摘The combination of hologram quantitative structure-activity relationship(HQSAR)and consensus modeling was employed to study the quantitative structure-property relationship(QSPR)model for calculating the aqueous hydroxyl radical oxidation reaction rate constants(kOH)of organic micropollutants(OMPs).Firstly,individual HQSAR model were established by using standard HQSAR method.The optimal individual HQSAR model was obtained while setting the parameter of fragment distinction and fragment size to“B”and“3~6”respectively.Secondly,consensus HQSAR model was established by building the regression model between the kOH and the hologram descriptors with consensus partial least-squares(cPLS)approach.The obtained individual and consensus HQSAR model were validated with a randomly selected external test set.The result of external test set validation demonstrates that both individual and consensus HQSAR model are available for predicting the kOH of OMPs.Compared with the optimal individual HQSAR model,the established consensus HQSAR model shows higher prediction accuracy and robustness.It is shown that the combination of HQSAR and consensus modeling is a practicable and promising method for studying and predicting the kOH of OMPs.
