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.

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.

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.

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.

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.

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.

Multiple grain-size fraction analysis of heavy minerals and the provenance identification of sediments from the abandoned Huanghe River,eastern China

The quantitative analysis of sediment sources in a sink is an important scientific topic and challenge in provenance research.The characteristics of heavy minerals,combined with the geochemical constituents of detrital grains,provide a reliable provenance-tracing approach.We developed a mineral identification method to analyze the multiple grain-size fraction of sediments,from which the elemental geochemistry of hornblende was used to compare the characteristics of sediments from the Huaihe River and Huanghe(Yellow)River in eastern China.Elements that were statistically identified as being able to discriminate sediment provenance were employed to perform a quantitative analysis of the sources of sediments of the abandoned Huanghe River.Results reveal that the Huaihe River is characterized by a high amphibole content of>60%and that the Huanghe and abandoned Huanghe rivers have greater abundances of limonite and carbonate minerals compared with those of the Huaihe River.The contents of trace elements and rare earth elements in hornblende show that the sediments of the abandoned Huanghe River are similar to those of the Huanghe River but different from those of the Huaihe River.Furthermore,chemical mass balance was used to calculate the relative contributions of different provenances of sediment from the abandoned Huanghe River,and nine trace elements of hornblende were identified as discriminators of provenance.Approximately 2%of the hornblende in the abandoned Huanghe River is derived from the Huaihe River and 98%from the Huanghe River.Considering the proportion of hornblende in the total sediment,it is inferred that the contribution of Huaihe River sediment to the abandoned Huanghe River is approximately 0.5%.This study shows that mineral analysis using multiple grain-size fractions(within the wide range of 1Φto 6Φ)with assessment in elemental geochemistry of hornblende can characterize the provenance of fluvial material in coastal zones.

Mangrove wetlands distribution status identification, changing trend analyzation and carbon storage assessment of China

This research investigates the ecological importance,changes,and status of mangrove wetlands along China’s coastline.Visual interpretation,geological surveys,and ISO clustering unsupervised classification methods are employed to interpret mangrove distribution from remote sensing images from 2021,utilizing ArcGIS software platform.Furthermore,the carbon storage capacity of mangrove wetlands is quantified using the carbon storage module of InVEST model.Results show that the mangrove wetlands in China covered an area of 278.85 km2 in 2021,predominantly distributed in Hainan,Guangxi,Guangdong,Fujian,Zhejiang,Taiwan,Hong Kong,and Macao.The total carbon storage is assessed at 2.11×10^(6) t,with specific regional data provided.Trends since the 1950s reveal periods of increase,decrease,sharp decrease,and slight-steady increases in mangrove areas in China.An important finding is the predominant replacement of natural coastlines adjacent to mangrove wetlands by artificial ones,highlighting the need for creating suitable spaces for mangrove restoration.This study is poised to guide future mangroverelated investigations and conservation strategies.

Characterization and quantification of multi-field coupling in lithium-ion batteries under mechanical constraints

The safety and durability of lithium-ion batteries under mechanical constraints depend significantly on electrochemical,thermal,and mechanical fields in applications.Characterizing and quantifying the multi-field coupling behaviors requires interdisciplinary efforts.Here,we design experiments under mechanical constraints and introduce an in-situ analytical framework to clarify the complex interaction mechanisms and coupling degrees among multi-physics fields.The proposed analytical framework integrates the parameterization of equivalent models,in-situ mechanical analysis,and quantitative assessment of coupling behavior.The results indicate that the significant impact of pressure on impedance at low temperatures results from the diffusion-controlled step,enhancing kinetics when external pressure,like 180 to 240 k Pa at 10℃,is applied.The diversity in control steps for the electrochemical reaction accounts for the varying impact of pressure on battery performance across different temperatures.The thermal expansion rate suggests that the swelling force varies by less than 1.60%per unit of elevated temperature during the lithiation process.By introducing a composite metric,we quantify the coupling correlation and intensity between characteristic parameters and physical fields,uncovering the highest coupling degree in electrochemical-thermal fields.These results underscore the potential of analytical approaches in revealing the mechanisms of interaction among multi-fields,with the goal of enhancing battery performance and advancing battery management.

Penetration Study of Key Technologies for Cybersecurity Risk Assessment

In recent years,with the frequent occurrence of cyber security incidents,people have paid more attention to it.Information security risk assessment is a very important research topic.This paper gives a brief overview of the theory of cybersecurity risk assessment,focuses on the description of the current mainstream cybersecurity risk assessment methods,classifies and compares the existing methods according to the nature of the methods,and analyses the advantages,disadvantages,and application scope of each method.Finally,the main factors affecting the evaluation results are summarized and refined,and future research hotspots in this field are proposed.Through the empirical analysis of the three factors,the influence of the correlation of the three factors,the uncertainty of the evaluation indexes,and the timeliness of the evaluation on the evaluation results are concluded,which provides a reference for future research on evaluation methods.

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.

Nondestructive Quantitative Analysis of Cofrel Medicines by Double ANN-NIR Spectroscopy

In this paper, a double artificial neural network （DANN） algorithm was used to parse near infrared （NIR） reflectance spectrum of Cofrel medicines. The contents of benproperine phosphate, which is the effective ingredient in Cofrel medicines, were accurately nondestructive quantitatively predicted. Compared the results with those of HPLC, the relative errors （RE %） were less than 0.18%. The analytical results could be applied to qualitative control of Cofrel medicines.

A New Method for Clay Mineral Analysis and Its Application in Geology

X-ray diffraction (XRD) peaks in a low-angle diffraction section of clayminerals, especially those of authigenic origin, have broadening and tailing features in shape.Using the five basic parameters, peak position, peak height, width, shape coefficient and asymmetry,to describe an XRD peak is more accurate, comprehensive and integrated than using only 3 of them,position, height and width. Following the concept of the five basic parameters of an XRD peak, theprogram Decoform proposed in this study provides more information in mineralogical analyses byfitting actual XRD profiles. In combination with the HW-IR plot, Decoform can he systematically andaccurately used in the comprehensive analyses of crystallinity, domain size, lattice strain andquantitative phase. It is also of value for the geological investigations of diagenesis,metamorphism, basin maturity, structural stress field and so on.

Quantitative analysis of the dynamic change and spatial differences of the ecological security: a case study of Loess Plateau in northern Shaanxi Province

Using the theory and method of the ecological footprint, and combining the changes of regional land use, resource environment, population, society and economy, this paper calculated the ecological footprint, ecological carrying capacity and ecological surplus/loss in 1986-2002 on the Loess Plateau in northern Shaanxi Province. What is more, this paper has put forward the concept of ecological pressure index, set up ecological pressure index models, and ecological security grading systems, and the prediction models of different ecological footprints, ecological carrying capacity, ecological surplus and ecological safety change, and also has assessed the ecological footprint demands of 10,000 yuan GDE The results of this study are as follows： （1） the ecological carrying capacity in northern Shaanxi shows a decreasing trend, the difference of reducing range is the fastest; （2） the ecological footprint appears an increasing trend; （3） ecological pressure index rose to 0.91 from 0.44 during 1986-2002 on the Loess Plateau of northern Shaanxi with an increase of 47%; and （4） the ecological security in the study area is in a critical state, and the ecological oressure index has been increasing rapidlv.

A feature selection method combined with ridge regression and recursive feature elimination in quantitative analysis of laser induced breakdown spectroscopy

In the spectral analysis of laser-induced breakdown spectroscopy,abundant characteristic spectral lines and severe interference information exist simultaneously in the original spectral data.Here,a feature selection method called recursive feature elimination based on ridge regression(Ridge-RFE)for the original spectral data is recommended to make full use of the valid information of spectra.In the Ridge-RFE method,the absolute value of the ridge regression coefficient was used as a criterion to screen spectral characteristic,the feature with the absolute value of minimum weight in the input subset features was removed by recursive feature elimination(RFE),and the selected features were used as inputs of the partial least squares regression(PLS)model.The Ridge-RFE method based PLS model was used to measure the Fe,Si,Mg,Cu,Zn and Mn for 51 aluminum alloy samples,and the results showed that the root mean square error of prediction decreased greatly compared to the PLS model with full spectrum as input.The overall results demonstrate that the Ridge-RFE method is more efficient to extract the redundant features,make PLS model for better quantitative analysis results and improve model generalization ability.

Mathematic Models for Analysis of Quality Components in Sugarcane Juice with Fourier Transform Near Infrared Spectroscopy

With the technique of Fourier transform near infrared (FT-NIR) spectroscopy, the calibration models for quantitative analysis of sucrose and polarization in sugarcane juice were developed by using transmission mode and calibrating with partial least square (PLS) algorithm. The determination coefficients (R2) of the predicted models for sucrose and polarization in juice were 0. 9980 and 0. 9979 respectively; the root mean square errors of cross validation (RMSECV) were 0. 143 and 0. 155% for sucrose and polarization in juice respectively. The predictive errors measured by FT-NIR were close to those by routine laboratory methods. The results demonstrated that the FT-NIR methods had high accuracy and they were able to replace the routine laboratory analysis. It was also demonstrated that as a rapid and accurate measurement, the FT-NIR technique had potential applications in quality control of mill sugarcane, establishment of payment system based on sugarcane quality, and selection of clones in sugarcane breeding.

MULTI-PEAK MATCH INTENSITY RATIO METHOD OF QUANTI-TATIVE X-RAY DIFFRACTION PHASE ANALYSIS

A new method for quantitative phase analysis is proposed by using X-ray diffraction multi-peak match intensity ratio. This method can obtain the multi-peak match intensity ratio among each phase in the mixture sample by using all diffraction peak data in the mixture sample X-ray diffraction spectrum and combining the relative intensity distribution data of each phase standard peak in JCPDS card to carry on the least square method regression analysis. It is benefit to improve the precision of quantitative phase analysis that the given single line ratio which is usually adopted is taken the place of the multi-peak match intensity ratio and is used in X-ray diffraction quantitative phase analysis of the mixture sample. By analyzing four-group mixture sample, adopting multi-peak match intensity ratio and X-ray diffraction quantitative phase analysis principle of combining the adiabatic and matrix flushing method, it is tested that the experimental results are identical with theory.

AN EXTERNAL STANDARD METHOD OF QUANTITATIVE PHASE ANALYSIS OF THE SAMPLE CONTAINING AN AMORPHOUS PHASE BY X—RAY DIFFRACTION

A new method of the quantitative phase analysis of the sample containing an amorphous phase or a standardless phase by X-ray diffraction is proposed in the paper. The addtion of a reference phase or some analytical phase to the analyzed sample is not required in this method and the experimental results are satisfactory.

iTRAQ quantitative analysis of plasma proteome changes of cow from pregnancy to lactation

Dairy cows undergo tremendous changes in physiological, metabolism and the immune function from pregnancy to lac- tation that are associated with cows being susceptible to metabolic and infectious diseases. The objective of this study is to investigate the changes of plasma proteome on 21 d before expected calving and 1 d after calving from dairy cows using an integrated proteomic approach consisting of minor abundance protein enrichment by ProteoMiner beads, protein labeling by isobaric tags for relative and absolute quantification, and protein identification by liquid chromatography coupled with tandem mass spectrometry. Nineteen proteins were changed around the time of calving. These proteins were asso- ciated with response to stress, including acute-phase response and defense response, based on the proteins annotation. In particular, three up-regulated proteins after calving including factor V, a2-antiplasmin and prothrombin were assigned into the complement and coagulation pathway. These results may provide new information in elucidating host response to lactation and parturition stress, and inflammatory-like conditions at the protein level. Differential proteins may serve as potential markers to regulate the lactation and parturition stress in periparturient dairy cows.