In near-infrared (NIR) analysis of plant extracts, excessive background often exists in near-infrared spectra. The detection of active constituents is difficult because of excessive background, and correction of this ...In near-infrared (NIR) analysis of plant extracts, excessive background often exists in near-infrared spectra. The detection of active constituents is difficult because of excessive background, and correction of this problem remains difficult. In this work, the orthogonal signal correction (OSC) method was used to correct excessive background. The method was also compared with several classical background correction methods, such as offset correction, multiplicative scatter correction (MSC), standard normal variate (SNV) transformation, de-trending (DT), first derivative, second derivative and wavelet methods. A simulated dataset and a real NIR spectral dataset were used to test the efficiency of different background correction methods. The results showed that OSC is the only effective method for correcting excessive background.展开更多
By utilizing a natural mercury lamp, the transverse Zeeman background correction method, which is used for trace mercury measurement in air, is studied. In this paper, a natural mercury lamp is used as a light source,...By utilizing a natural mercury lamp, the transverse Zeeman background correction method, which is used for trace mercury measurement in air, is studied. In this paper, a natural mercury lamp is used as a light source, and is placed in a 1.78-T magnetic field. The lamp emits two linearly polarized light beams σ± and π of 253.65-nm resonance line, which are used as bias light and absorbing light, respectively. A polarization modulation system is used to allow σ± and π light beams to pass through alternately with a certain frequency. A multipath optical cell with 12-m optical path is used to increase optical distance. Based on the system described above, the influence caused by UV absorbing gases, such as NO2, SO2, acetone, benzene, and O3, is analyzed. The results show that it may reduce the detection limit when the concentrations of these gases exceed 83.4 ppm, 20.3 ppm, 142.3 ppm, 0.85 ppm, and 0.55 ppm, respectively. The detection limit of the system is calculated and can achieve up to 1.44 ng/m3 in 10 minutes. Measurements on mercury sample gas and air are carded out, and the measured data are compared with the data of RA-915 mercury analyzer （Russia）. The result shows that the correlation coefficient reaches up to 0.967. The experimental results indicate that the transverse Zeeman background correction method can be used to quantify trace mercury in air with high-precision.展开更多
Differential electrochemical mass spectrometry(DEMS)is one of the most powerful techniques for both the mechanistic and kinetic study of complicated electrocatalytic reactions.It can provide information on the nature ...Differential electrochemical mass spectrometry(DEMS)is one of the most powerful techniques for both the mechanistic and kinetic study of complicated electrocatalytic reactions.It can provide information on the nature and yields of the products generated,their production rate,and the structure-activity relationship between the electrocatalysts and the target reactions.The precise calibration of the mass signal is a prerequisite for the accurate evaluation of reaction kinetics.In this work,we use the oxidation reactions of CO and HCOOH to demonstrate how certain conditions,such as the flow rate and solution composition,affect the collection efficiency and ionization probability of the species to be detected.These parameters can affect the determination of the mass calibration constant and the accuracy of the subsequent quantitative DEMS analysis.We show the relationship between the mass calibration constant and the flow rate,and provide strategies for eliminating this and the related problems.展开更多
The identification of anomalies within stream sediment geochemical data is one of the fastest developing areas in mineral exploration.The various means used to achieve this objective make use of either continuous or d...The identification of anomalies within stream sediment geochemical data is one of the fastest developing areas in mineral exploration.The various means used to achieve this objective make use of either continuous or discrete field models of stream sediment geochemical data.To map anomalies in a discrete field model of such data,two corrections are required:background correction and downstream dilution correction.Topography and geomorphology are important factors in variations of element content in stream sediments.However,few studies have considered,through the use of digital terrain analysis,the influence of geomorphic features in downstream dilution correction of stream sediment geochemical data.This study proposes and demonstrates an improvement to the traditional downstream dilution correction equation,based on the use of digital terrain analysis to map single-element anomalies in stream sediment geochemical landscapes.Moreover,this study compares the results of analyses using discrete and continuous field models of stream sediment geochemical data from the Xincang area,Xizang.The efficiency of the proposed methodology was validated against known mineral occurrences.The results indicate that catchment-based analysis outperforms interpolation-based analysis of stream sediment geochemical data for anomaly mapping.Meanwhile,the proposed modified downstream dilution correction equation proved more effective than the original equation.However,further testing of this modified downstream dilution correction is needed in other areas,in order to investigate its efficiency further.展开更多
Various methods and specialized software programs are available for processing two- dimensional gel electrophoresis （2-DGE） images. However, due to the anomalies present in these images, a reliable, automated, and h...Various methods and specialized software programs are available for processing two- dimensional gel electrophoresis （2-DGE） images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and hor- izontal streaking, fuzzy spots, and background noise, which greatly complicate computational anal- ysis. In this paper, we review the preprocessing techniques applied to 2-DGE images for noise reduction, intensity normalization, and background correction. We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images： Gaussian, Rayleigh, and exponen- tial, with signal-to-noise ratios （SNRs） ranging 8-20 decibels （dB）. We compared the performanceof wavelet, contourlet, total variation （TV）, and wavelet-total variation （WTTV） techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sen- sitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10- 20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best per- formance with any level of Gaussian noise and low levels （20-14 dB） of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image.展开更多
基金Project supported by the Zhejiang Province Key Technologies R & DProgram (No. 021103549)the National Key Technologies R & DProgram (No. 2001BA701A45), China
文摘In near-infrared (NIR) analysis of plant extracts, excessive background often exists in near-infrared spectra. The detection of active constituents is difficult because of excessive background, and correction of this problem remains difficult. In this work, the orthogonal signal correction (OSC) method was used to correct excessive background. The method was also compared with several classical background correction methods, such as offset correction, multiplicative scatter correction (MSC), standard normal variate (SNV) transformation, de-trending (DT), first derivative, second derivative and wavelet methods. A simulated dataset and a real NIR spectral dataset were used to test the efficiency of different background correction methods. The results showed that OSC is the only effective method for correcting excessive background.
基金Project supported by the National Natural Science Foundation of China(Grant No.41275037)the Science-Technology Foundation for Young Scientist of Anhui Province,China(Grant No.1308085JGD03)the Anhui Provincial Natural Science Foundation,China(Grant No.1308085QF124)
文摘By utilizing a natural mercury lamp, the transverse Zeeman background correction method, which is used for trace mercury measurement in air, is studied. In this paper, a natural mercury lamp is used as a light source, and is placed in a 1.78-T magnetic field. The lamp emits two linearly polarized light beams σ± and π of 253.65-nm resonance line, which are used as bias light and absorbing light, respectively. A polarization modulation system is used to allow σ± and π light beams to pass through alternately with a certain frequency. A multipath optical cell with 12-m optical path is used to increase optical distance. Based on the system described above, the influence caused by UV absorbing gases, such as NO2, SO2, acetone, benzene, and O3, is analyzed. The results show that it may reduce the detection limit when the concentrations of these gases exceed 83.4 ppm, 20.3 ppm, 142.3 ppm, 0.85 ppm, and 0.55 ppm, respectively. The detection limit of the system is calculated and can achieve up to 1.44 ng/m3 in 10 minutes. Measurements on mercury sample gas and air are carded out, and the measured data are compared with the data of RA-915 mercury analyzer （Russia）. The result shows that the correlation coefficient reaches up to 0.967. The experimental results indicate that the transverse Zeeman background correction method can be used to quantify trace mercury in air with high-precision.
基金supported by the National Natural Science Foundation of China(no.21872132,21832004,91545124)the 973 Program from the Ministry of Science and Technology of China(no.2015CB932301)。
文摘Differential electrochemical mass spectrometry(DEMS)is one of the most powerful techniques for both the mechanistic and kinetic study of complicated electrocatalytic reactions.It can provide information on the nature and yields of the products generated,their production rate,and the structure-activity relationship between the electrocatalysts and the target reactions.The precise calibration of the mass signal is a prerequisite for the accurate evaluation of reaction kinetics.In this work,we use the oxidation reactions of CO and HCOOH to demonstrate how certain conditions,such as the flow rate and solution composition,affect the collection efficiency and ionization probability of the species to be detected.These parameters can affect the determination of the mass calibration constant and the accuracy of the subsequent quantitative DEMS analysis.We show the relationship between the mass calibration constant and the flow rate,and provide strategies for eliminating this and the related problems.
基金financially supported by the National Natural Science Foundation of China(NNSFC,Project No.42002298)the Chinese Geological Survey(Project Nos.DD20201181,DD20211403)+1 种基金the National Key Research and Development Program of China(NKRDPC,Project No.2017YFC0601501)funded by The Project of"Big Data Analysis and Major Project Evaluation of Strategic Mineral Resources"from the Chinese Geological Survey。
文摘The identification of anomalies within stream sediment geochemical data is one of the fastest developing areas in mineral exploration.The various means used to achieve this objective make use of either continuous or discrete field models of stream sediment geochemical data.To map anomalies in a discrete field model of such data,two corrections are required:background correction and downstream dilution correction.Topography and geomorphology are important factors in variations of element content in stream sediments.However,few studies have considered,through the use of digital terrain analysis,the influence of geomorphic features in downstream dilution correction of stream sediment geochemical data.This study proposes and demonstrates an improvement to the traditional downstream dilution correction equation,based on the use of digital terrain analysis to map single-element anomalies in stream sediment geochemical landscapes.Moreover,this study compares the results of analyses using discrete and continuous field models of stream sediment geochemical data from the Xincang area,Xizang.The efficiency of the proposed methodology was validated against known mineral occurrences.The results indicate that catchment-based analysis outperforms interpolation-based analysis of stream sediment geochemical data for anomaly mapping.Meanwhile,the proposed modified downstream dilution correction equation proved more effective than the original equation.However,further testing of this modified downstream dilution correction is needed in other areas,in order to investigate its efficiency further.
基金supported by the Instituto Tecnológico Metropolitano (ITM) of Medellín, Colombia (Grant No. P14227) awarded to SR
文摘Various methods and specialized software programs are available for processing two- dimensional gel electrophoresis （2-DGE） images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and hor- izontal streaking, fuzzy spots, and background noise, which greatly complicate computational anal- ysis. In this paper, we review the preprocessing techniques applied to 2-DGE images for noise reduction, intensity normalization, and background correction. We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images： Gaussian, Rayleigh, and exponen- tial, with signal-to-noise ratios （SNRs） ranging 8-20 decibels （dB）. We compared the performanceof wavelet, contourlet, total variation （TV）, and wavelet-total variation （WTTV） techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sen- sitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10- 20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best per- formance with any level of Gaussian noise and low levels （20-14 dB） of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image.
