Accurate method based on data filtering for quantitative multi-element analysis of soils using CF-LIBS

To obtain more stable spectral data for accurate quantitative analysis of multi-element,especially for the large-area in-situ elements detection of soils, we propose a method for a multielement quantitative analysis of soils using calibration-free laser-induced breakdown spectroscopy(CF-LIBS) based on data filtering. In this study, we analyze a standard soil sample doped with two heavy metal elements, Cu and Cd, with a specific focus on the line of Cu I324.75 nm for filtering the experimental data of multiple sample sets. Pre-and post-data filtering,the relative standard deviation for Cu decreased from 30% to 10%, The limits of detection(LOD)values for Cu and Cd decreased by 5% and 4%, respectively. Through CF-LIBS, a quantitative analysis was conducted to determine the relative content of elements in soils. Using Cu as a reference, the concentration of Cd was accurately calculated. The results show that post-data filtering, the average relative error of the Cd decreases from 11% to 5%, indicating the effectiveness of data filtering in improving the accuracy of quantitative analysis. Moreover, the content of Si, Fe and other elements can be accurately calculated using this method. To further correct the calculation, the results for Cd was used to provide a more precise calculation. This approach is of great importance for the large-area in-situ heavy metals and trace elements detection in soil, as well as for rapid and accurate quantitative analysis.

Simplified quantitative analysis method and its application in the insitu synthesized copper-based azide chips

Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.

Research on batch multielement rapid quantitative analysis based on the standard curve-assisted calibration-free laserinduced breakdown spectroscopy method

This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve(SC)and calibration-free laser-induced breakdown spectroscopy(CF-LIBS)technology to achieve synchronous,rapid,and accurate measurement of elements in a large number of samples,namely,SC-assisted CF-LIBS.Al alloy standard samples,divided into calibration and test samples,were applied to validate the proposed method.SC was built based on the characteristic line of Pb and Cr in the calibration sample,and the contents of Pb and Cr in the test sample were calculated with relative errors of 6%and 4%,respectively.SC built using Cr with multiple characteristic lines yielded better calculation results.The relative contents of ten elements in the test sample were calculated using CF-LIBS.Subsequently,the SC-assisted CF-LIBS was executed,with the majority of the calculation relative errors falling within the range of 2%-5%.Finally,the Al and Na contents of the Al alloy were predicted.The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples.Furthermore,this quantitative analysis method was successfully applied to soil and Astragalus samples,realizing an accurate calculation of the contents of multiple elements.Thus,it is important to advance the LIBS quantitative analysis and its related applications.

Quantitative analysis and prediction of the sound field convergence zone in mesoscale eddy environment based on data mining methods

The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and convergence zone(CZ)characteristics.Based on the Gaussian vortex model,we construct various sound propagation scenarios under different eddy conditions,and carry out sound propagation experiments to obtain simulation samples.With a large number of samples,we first adopt the unified regression to set up analytic relationships between eddy conditions and CZ parameters.The sensitivity of eddy indicators to the CZ is quantitatively analyzed.Then,we adopt the machine learning(ML)algorithms to establish prediction models of CZ parameters by exploring the nonlinear relationships between multiple ME indicators and CZ parameters.Through the research,we can express the influence of ME on the CZ quantitatively,and achieve the rapid prediction of CZ parameters in ocean eddies.The prediction accuracy(R)of the CZ distance(mean R:0.9815)is obviously better than that of the CZ width(mean R:0.8728).Among the three ML algorithms,Gradient Boosting Decision Tree has the best prediction ability(root mean square error(RMSE):0.136),followed by Random Forest(RMSE:0.441)and Extreme Learning Machine(RMSE:0.518).

Qualitative analysis of aromatic compounds via 1D TOCSY techniques

The aromatic compounds,including o-xylene,m-xylene,p-xylene,and ethylbenzene,primarily originate from the catalytic reforming of crude oil,and have a wide variety of applications.However,because of similar physical and chemical properties,these compounds are difficult to be identified by gas chromatography(GC)without standard samples.With the development of modern nuclear magnetic resonance(NMR)techniques,NMR has emerged as a powerful and efficient tool for the rapid analysis of complex and crude mixtures without purification.In this study,the parameters of one-dimensional(1D)total correlation spectroscopy(TOCSY)NMR techniques,including 1D selective gradient TOCSY and 1D chemicalshift-selective filtration(CSSF)with TOCSY,were optimized to obtain comprehensive molecular structure information.The results indicate that the overlapped signals in NMR spectra of nonpolar aromatic compounds(including o-xylene,m-xylene,p-xylene and ethylbenzene),polar aromatic compounds(benzyl alcohol,benzaldehyde,benzoic acid),and aromatic compounds with additional conjugated bonds(styrene)can be resolved in 1D TOCSY.More importantly,full molecular structures can be clearly distinguished by setting appropriate mixing time in 1D TOCSY.This approach simplifies the NMR spectra,provides structural information of entire molecules,and can be applied for the analysis of other structural isomers.

Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

Consequences of Insufficient Selectivity in Quantitative and Qualitative Chemical Analysis

A problem in chemical analysis in connection with measurements of a substance normally occurring in a sample, or identification of a substance which should not exist in a sample, is insufficient selectivity. In this article, we analyze this problem and propose remedies. We use a real doping case to illustrate how chemical noise causes a serious selectivity problem, probably causing a false positive outcome.

Qualitative and Quantitative Analysis of Alkaloids in Cortex Phellodendri by HPLC-ESI-MS/MS and HPLC-DAD

A combined method of high performance liquid chromatograph-elecrtrospray-ionization mass spectrometer（HPLC-ESI-MS/MS） coupled with a photodiode array detector（HPLC-DAD） and principal component analysis（PCA） was applied to the qualitative and quantitative analyses of alkaloids in Cortex Phellodendri（CP） samples, and to the differentiation of two species of CP, Cortex Phellodendri Chinensis（CPC） and Cortex Phellodendri Amurensis（CPA）. Twenty-two peaks appeared in the HPLC-MS base peak chromatogram of CP detected by the HPLC-ESI-MS/MS analysis, and the alkaloids were identified according to the MSn data, the known MS fragmentation rules and the literature data. Five alkaloids including berberine, palmatine, jatrorrhizine, phellodendrine and magnoflorine were simultaneously determinated by the HPLC-DAD. Berberine was the primary component in all CP samples, and the contents of berberine and palmatine were exploited to be two critical parameters for effective discrimination between the two species of CP. The average content of berberine in CPC（58.75 mg/g） was higher than that in CPA（9.16 mg/g）, while the content of palmatine was less, only 0.25 mg/g in CPC and 4.19 mg/g in CPA. With the use of PCA, samples datasets were separated successfully into two different clusters corresponding to the two species, and berberine, pahnatine, phellodendrine and magnoflorine contribute most to the above mentioned calssifying . The proposed method oroved to be a useful tool in the aualitv control of Chinese herbal medicines.

Qualitative and semi-quantitative analysis of health-care pharmaceutical products using laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS) is a sensitive optical technique that is capable of rapid multi-elemental analysis. The development of this technique for elemental analysis of pharmaceutical products may eventually revolutionize the field of human health. Under normal circumstances, the elemental analysis of pharmaceutical products based on chemical methods is time-consuming and complicated. In this investigation, the principal aim is to develop an LIBS-based methodology for elemental analysis of pharmaceutical products. This LIBS technique was utilized for qualitative as well as quantitative analysis of the elements present in Ca-based tablets. All the elements present in the tablets were detected and their percentage compositions were verified in a single shot, using the proposed instrument. These elements(e.g., Ca, Mg, Fe, Zn, and others) were identified by the wavelengths of their spectral lines, which were verified using the NIST database. The approximate amount of each element was determined based on their observed peaks and the result was in exact agreement with the content specification. The determination of the composition of prescription drug for patients is highly important in numerous circumstances. For example, the exploitation of LIBS may facilitate elemental decomposition of medicines to determine the accuracy of the stated composition information. Moreover, the approach can provide element-specific, meaningful, and accurate information related to pharmaceutical products.

Spectra-assisted laser focusing in quantitative analysis of laser-induced breakdown spectroscopy for copper alloys

Laser-induced breakdown spectroscopy(LIBS)is a capable technique for elementary analysis,while LIBS quantitation is still under development.In quantitation,precise laser focusing plays an important role because it ensures the distance between the laser and samples.In the present work,we employed spectral intensity as a direct way to assist laser focusing in LIBS quantitation for copper alloys.It is found that both the air emission and the copper line could be used to determine the position of the sample surface by referencing the intensity maximum.Nevertheless,the fine quantitation was only realized at the position where the air emission(e.g.O(I)777.4 nm)reached intensity maximum,and also in this way,a repeatable quantitation was successfully achieved even after 120 days.The results suggested that the LIBS quantitation was highly dependent on the focusing position of the laser,and spectra-assisted focusing could be a simple way to find the identical condition for different samples’detection.In the future,this method might be applicable in field measurements for LIBS analysis of solids.

Quantitative morphometric analysis of a deep-water channel in the Taranaki Basin, New Zealand

The morphological changes of deep-water channels have an important influence on the distributions of channel sand reservoirs,so it is important to explore the morphological change process of deep-water channel for the exploration and development of deep-water oil and gas.Based on a typical sinuous Quaternary channel(Channel I)in the Taranaki Basin,New Zealand,a variety of seismic interpretation techniques were applied to quantitatively characterize the morphological characteristics of the Channel I,and the relationships between the quantitative parameters and the morphological changes of the Channel I,as well as the controlling factors affecting those morphological changes,were discussed.The results are as follows:(1)in the quantitative analysis,six parameters were selected:the channel depth,width,sinuosity,and aspect ratio(width/depth),the channel swing amplitude(λ)and the channel bend frequency(ω);(2)according to the quantitative morphological parameters of the channel(mainly including three parameters such as channel sinuosity,ωandλ),the Channel I was divided into three types:the low-sinuous channel(LSC),the high-sinuous channel(HSC),the moderate-sinuous channel(MSC).U-shaped channel cross-sections developed in the LSC,V-shaped channel cross-sections developed in the HSC,including inclined-V and symmetric-V cross-sections,and dish-shaped channel cross-sections developed in the MSC;(3)the morphological characteristics of the LSC and MSC were related to their widths and depths,while the morphology of the HSC was greatly affected by the channel width,a change in depth did not affect the HSC morphology;(4)the morphological changes of the Channel I were controlled mainly by the slope gradient,the restricted capacity of the channel and the differential in fluid properties.

DecodeSTORM:A user-friendly ImageJ plug-in for quantitative data analysis in single-molecule localization microscopy

Quantitative data analysis in single-molecule localization microscopy(SMLM)is crucial for studying cellular functions at the biomolecular level.In the past decade,several quantitative methods were developed for analyzing SMLM data;however,imaging artifacts in SMLM experiments reduce the accuracy of these methods,and these methods were seldom designed as user-friendly tools.Researchers are now trying to overcome these di±culties by developing easyto-use SMLM data analysis software for certain image analysis tasks.But,this kind of software did not pay su±cient attention to the impact of imaging artifacts on the analysis accuracy,and usually contained only one type of analysis task.Therefore,users are still facing di±culties when they want to have the combined use of different types of analysis methods according to the characteristics of their data and their own needs.In this paper,we report an ImageJ plug-in called DecodeSTORM,which not only has a simple GUI for human–computer interaction,but also combines artifact correction with several quantitative analysis methods.DecodeSTORM includes format conversion,channel registration,artifact correction(drift correction and localization¯ltering),quantitative analysis(segmentation and clustering,spatial distribution statistics and colocalization)and visualization.Importantly,these data analysis methods can be combined freely,thus improving the accuracy of quantitative analysis and allowing users to have an optimal combination of methods.We believe DecodeSTORM is a user-friendly and powerful ImageJ plug-in,which provides an easy and accurate data analysis tool for adventurous biologists who are looking for new imaging tools for studying important questions in cell biology.

Energy-dispersive X-ray Spectroscopy for the Quantitative Analysis of Pyrite Thin Specimens

To explore ways to improve the accuracy of quantitative analysis of samples in the micrometer to nanometer range of magnitudes,we adopted analytical transmission electron microscopy(AEM/EDS)for qualitative and quantitative analysis of pyrite materials.Additionally,the k factor of pyrite is calculated experimentally.To develop an appropriate non-standard quantitative analysis model for pyrite materials,the experimentally calculated k factor is compared with that estimated from the non-standard quantitative analytical model of the instrument software.The experimental findings demonstrate that the EDS attached to a TEM can be employed for precise quantitative analysis of micro-and nanoscale regions of pyrite materials.Furthermore,it serves as a reference for improving the results of the EDS quantitative analysis of other sulfides.

Qualitative and Quantitative Analysis of Linoleic Acid in Polygonati Rhizoma

Objective To explore the major compound in Polygonati Rhizoma(Huang Jing,黄精)for quality control.Methods The major compound was isolated and analyzed by liquid chromatography-mass spectrometry(LC-MS),and subsequently further identified by nuclear magnetic resonance(NMR).Thin layer chromatography(TLC)was optimized based on the previous methods reported in the Chinese Pharmacopeia(2015 edition).Results The major compound was isolated from the natural material and identified as linoleic acid.A high performance liquid chromatography(HPLC)method with robust linearity(R2=0.9997),specificity,precision,stability,repeatability and recovery was developed for linoleic acid determination.TLC chromatogram was improved significantly after optimization for qualitative analysis.Conclusions The optimized TLC method is practical and can be adopted for quality control of Polygonati Rhizoma(Huang Jing,黄精).The levels of linoleic acid vary between species of Polygonati Rhizoma(Huang Jing,黄精),with Polygonatum cyrtonema Hua(Jiang Xing Huang Jing,姜型黄精)showing the highest contents.This study provides valuable information for quality control of Polygonati Rhizoma(Huang Jing,黄精).

Qualitative and Quantitative Analysis of Five Bioactive Flavonoids in <i>Salix bordensis</i>Turcz. by HPLC-DAD and HPLC-ESI-MS

The qualitative characterization and quantitative analysis of five bioactive flavonoids in Salix bordensis Turcz. were achieved via reversed-phase high-performance liquid chromatography coupled with diode array detection and tandem mass spectrometry, by using an Agilent ZORBAX SB-C18 HPLC column with a gradient elution of 0.3% (v/v) formic acid in water and methanol as the mobile phase. The compounds in the mixture were clearly identified by comparing their HPLC-DAD ultraviolet spectra, retention times, and MS data with those of corresponding reference compounds. All calibration curves showed good linearity (r2 > 0.9998) within the test ranges. The LOD, LOQ, specificity, precision, and accuracy for the method were validated. The results demonstrated that this analytical approach is ideal for the determination of bioactive compounds, such as flavonoids, and that it constructed a basis for the comprehensive evaluation of the quality of Salix bordensis Turcz.

Quantitative Analysis of Land Use Landscape Pattern in Shihezi Desert Oasis

Based on the land use status map of Shihezi City,the land use landscape map of Shihezi City was made with the support of GIS then many landscape indices were selected to quantitatively analyze the landscape pattern characteristics of Shihezi Oasis from three aspects of landscape diversity index,landscape space configuration index and plaque characteristics index. The results showed that the main plaque types of the landscape in Shihezi reclamation area are arable land and water areas,which totally account for 58% of the total area; farmland,gardens,woodland,urban sites,industrial and mining land use were embedded in this oasis landscape in the form of mosaics,and their fractal index was high due to the strong impact of human activities; arable land and mining land distribution was scattered,but marshes and other uncultivated land were relatively concentrated. The dominance degree of the landscape was low because there was no advantageous type in this landscape and all patches distributed equably which was easily to be disturbed so that the whole landscape was unstable. Comprehensively speaking,the landscape in Shihezi region was rather complicate,and its diversity index,fragmentation degree and heterogeneity were high.

Analysis on the Configuration Path of Improving the Quality and Efficiency of County-Level Libraries in China

County-level libraries have an inescapable responsibility for cultivating local cultural identity and realizing rural revitalization.Therefore,we analyzed factors that afect the service fficiency of gass-1oots libraries in Henan Province through a field investigation and qualitative comparative analysis(QCA),and proposed a higlh-efficiency configuration.In addition,we put forward the strategy of improving the quality and efficiency of our country's county-level libraries in the electonic information age.

Quantitative analysis of γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method

Objective:To develop and validate an image analysis method for quantitative analysis ofγ-oryzanol in cold pressed rice bran oil.Methods:TLC-densitometric and TLC-image analysis methods were developed,validated,and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil.The results obtained by these two different quantification methods were compared by paired t-test.Results:Both assays provided good linearity,accuracy,reproducibility and selectivity for determination of γ-oryzanol.Conclusions:The TLC-densitomelric and TLC-image analysis methods providett a similar reproducibility,accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil.A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods.As both methods were found to be equal,they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil.

Quantitative traits correlative analysis and growth comparison among different populations of bay scallop,Argopecten irradians

The shell traits and weight traits are measured in cultured populations of bay scallop, Argopecten irradians. The results of regression analysis show that the regression relationships for all the traits are significant (P<0.01). The correlative coefficients between body weight, as well as tissue weight with shell length, shell height and shell width are significant (P<0.05). But the correlative coefficients between the anterior and posterior auricle length with body weight as well as tissue weight are not significant (P>0.05). The multiple regression equation is obtained to estimate live body weight and tissue weight. The above traits except anterior and posterior auricle length are used for the growth and production comparison among three cultured populations, Duncan's new multiple range procedure analysis shows that all the traits in the Lingshuiqiao (LSQ) population are much more significant than those of the other two populations (P<0.01), and there is no significant difference between the Qipanmo (QPM) and Dalijia (DLJ) populations in all traits (P>0.05). The results indicate that the LSQ population has a higher growth rate and is expected to be more productive than the other two populations.

Signed Directed Graph and Qualitative Trend Analysis Based Fault Diagnosis in Chemical Industry

In the past 30 years,signed directed graph(SDG) ,one of the qualitative simulation technologies,has been widely applied for chemical fault diagnosis.However,SDG based fault diagnosis,as any other qualitative method,has poor diagnostic resolution.In this paper,a new method that combines SDG with qualitative trend analysis(QTA) is presented to improve the resolution.In the method,a bidirectional inference algorithm based on assumption and verification is used to find all the possible fault causes and their corresponding consistent paths in the SDG model.Then an improved QTA algorithm is used to extract and analyze the trends of nodes on the consis-tent paths found in the previous step.New consistency rules based on qualitative trends are used to find the real causes from the candidate causes.The resolution can be improved.This method combines the completeness feature of SDG with the good diagnostic resolution feature of QTA.The implementation of SDG-QTA based fault diagno-sis is done using the integrated SDG modeling,inference and post-processing software platform.Its application is illustrated on an atmospheric distillation tower unit of a simulation platform.The result shows its good applicability and efficiency.