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 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).

Quantitative Analysis of Seeing with Height and Time at Muztagh-Ata Site Based on ERA5 Database

Seeing is an important index to evaluate the quality of an astronomical site.To estimate seeing at the Muztagh-Ata site with height and time quantitatively,the European Centre for Medium-Range Weather Forecasts reanalysis database(ERA5)is used.Seeing calculated from ERA5 is compared consistently with the Differential Image Motion Monitor seeing at the height of 12 m.Results show that seeing decays exponentially with height at the Muztagh-Ata site.Seeing decays the fastest in fall in 2021 and most slowly with height in summer.The seeing condition is better in fall than in summer.The median value of seeing at 12 m is 0.89 arcsec,the maximum value is1.21 arcsec in August and the minimum is 0.66 arcsec in October.The median value of seeing at 12 m is 0.72arcsec in the nighttime and 1.08 arcsec in the daytime.Seeing is a combination of annual and about biannual variations with the same phase as temperature and wind speed indicating that seeing variation with time is influenced by temperature and wind speed.The Richardson number Ri is used to analyze the atmospheric stability and the variations of seeing are consistent with Ri between layers.These quantitative results can provide an important reference for a telescopic observation strategy.

A novel box-counting method for quantitative fractal analysis of threedimensional pore characteristics in sandstone

Fractal theory offers a powerful tool for the precise description and quantification of the complex pore structures in reservoir rocks,crucial for understanding the storage and migration characteristics of media within these rocks.Faced with the challenge of calculating the three-dimensional fractal dimensions of rock porosity,this study proposes an innovative computational process that directly calculates the three-dimensional fractal dimensions from a geometric perspective.By employing a composite denoising approach that integrates Fourier transform(FT)and wavelet transform(WT),coupled with multimodal pore extraction techniques such as threshold segmentation,top-hat transformation,and membrane enhancement,we successfully crafted accurate digital rock models.The improved box-counting method was then applied to analyze the voxel data of these digital rocks,accurately calculating the fractal dimensions of the rock pore distribution.Further numerical simulations of permeability experiments were conducted to explore the physical correlations between the rock pore fractal dimensions,porosity,and absolute permeability.The results reveal that rocks with higher fractal dimensions exhibit more complex pore connectivity pathways and a wider,more uneven pore distribution,suggesting that the ideal rock samples should possess lower fractal dimensions and higher effective porosity rates to achieve optimal fluid transmission properties.The methodology and conclusions of this study provide new tools and insights for the quantitative analysis of complex pores in rocks and contribute to the exploration of the fractal transport properties of media within rocks.

Research on the Work-for-Relief Policy within the Scope of Comprehensive Rural Revitalization:Quantitative Analysis of Policy Texts Based on 71 Policy Documents

Work-for-relief plays a unique role in China’s journey toward modernization.From the perspectives of policy tools and interest analysis,this paper uses quantitative analysis of policy texts and integrates grounded theory to build a policy expression analysis model to discuss the current work-for-relief policy system.The study found that China’s use of the work-for-relief policy is unbalanced,and it is necessary to enhance the involvement of non-governmental sectors,as well as to fully consider the policy’s target groups and the social issues that need addressing.

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.

Evaluation of Reference Genes for Quantitative Real-Time PCR Analysis in Manila Clam Ruditapes philippinarum Under Hypoxic Stress

Quantitative real-time PCR(qRT-PCR)has been widely used for gene expression analysis,and selection of reference genes is a key point to obtain accurate results.To find out optimal reference genes for qRT-PCR in Manila clam Ruditapes philippinarum in response to hypoxia,different tissues were used and compared to evaluate the stability of candidate reference genes under low oxygen stress(DO 0.5mgL^(−1) and DO 2.0mgL^(−1))and normal condition(DO 7.5mgL^(−1)).Seven candidate reference genes were selected to evaluate the stability of their expression levels.The reference genes were evaluated by Delta Ct,BestKeeper,NormFinder and geNorm,and then screened by RefFinder calculation.Under hypoxic stress of 0.5mgL^(−1),the most suitable reference gene for gill and hepatopancreas was RPL31,and the optimal reference genes for axe foot and adductor muscle were TUB and HIS,respectively.For hypoxic stress of 2.0mgL^(−1),the most stable reference gene for gill and hepatopancreas was RPL31,and the optimal reference genes for axe foot and adductor muscle were RPS23 and EF1A,respectively.At the normal condition,HIS and EF1A were identified as the optimal internal reference genes in gill and hepatopancreas respectively,and GFRP2 was the best internal reference gene for axe foot and adductor muscle.The present findings will provide important basis for the selection of reference genes for qRT-PCR analysis of gene expression level in bivalves under hypoxic stress,which might be helpful for the analysis of other molluscs too.

Importance of Three-Dimensional Piezoelectric Coupling Modeling in Quantitative Analysis of Piezoelectric Actuators

This paper demonstrates the importance of three-dimensional(3-D)piezoelectric coupling in the electromechanical behavior of piezoelectric devices using three-dimensional finite element analyses based on weak and strong coupling models for a thin cantilevered piezoelectric bimorph actuator.It is found that there is a significant difference between the strong and weak coupling solutions given by coupling direct and inverse piezoelectric effects(i.e.,piezoelectric coupling effect).In addition,there is significant longitudinal bending caused by the constraint of the inverse piezoelectric effect in the width direction at the fixed end(i.e.,3-D effect).Hence,modeling of these effects or 3-D piezoelectric coupling modeling is an electromechanical basis for the piezoelectric devices,which contributes to the accurate prediction of their behavior.

Social-ecological perspective on the suicidal behaviour factors of early adolescents in China:a network analysis

Background In early adolescence,youth are highly prone to suicidal behaviours.Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.Aims To explore the risk and protective factors of suicidal behaviours(ie,suicidal ideation,plans and attempts)in early adolescence in China using a social-ecological perspective.Methods Using data from the cross-sectional project‘Healthy and Risky Behaviours Among Middle School Students in Anhui Province,China',stratified random cluster sampling was used to select 5724 middle school students who had completed self-report questionnaires in November 2020.Network analysis was employed to examine the correlates of suicidal ideation,plans and attempts at four levels,namely individual(sex,academic performance,serious physical llness/disability,history of self-harm,depression,impulsivity,sleep problems,resilience),family(family economic status,relationship with mother,relationship with father,family violence,childhood abuse,parental mental illness),school(relationship with teachers,relationship with classmates,school-bullying victimisation and perpetration)and social(social support,satisfaction with society).Results In total,37.9%,19.0%and 5.5%of the students reported suicidal ideation,plans and attempts in the past 6 months,respectively.The estimated network revealed that suicidal ideation,plans and attempts were collectively associated with a history of self-harm,sleep problems,childhood abuse,school bullying and victimisation.Centrality analysis indicated that the most influential nodes in the network were history of self-harm and childhood abuse.Notably,the network also showed unique correlates of suicidal ideation(sex,weight=0.60;impulsivity,weight=0.24;family violence,weight=0.17;relationship with teachers,weight=-0.03;school-bullying perpetration,weight=0.22),suicidal plans(social support,weight=-0.15)and suicidal attempts(relationship with mother,weight=-0.10;parental mental llness,weight=0.61).Conclusions This study identified the correlates of suicidal ideation,plans and attempts,and provided practical implications for suicide prevention for young adolescents in China.Firstly,this study highlighted the importance of joint interventions across multiple departments.Secondly,the common risk factors of suicidal ideation,plans and attempts were elucidated.Thirdly,this study proposed target interventions to address the unique influencing factors of suicidal ideation,plans and attempts.

Quantitative Parameters Analysis for Prenatally Echocardiographic Diagnosis of Atrioventricular Septal Defects

Background:Atrioventricular septal defects(AVSDs)are screened and diagnosed usually rely on the imaging characteristics of fetal echocardiography(FE).However,diagnosis on images is heavily depended on sonographers’experience and the quantitative data are rarely studied.Objective:This study aimed to realize the prenatal diagnosis of AVSDs by analyzing the quantitative data on FE.Methods:One hundred and thirteen cardiac quantitative data was analyzed in 370 normal and 49 AVSDs fetuses retrospectively.The top six with the highest diagnostic accuracy rate were acquired according to the area under the curve(AUC),and the diagnostic value of six variables was analyzed.Results:Six parameters obtained on the four-chamber view(4CHV),including the atrial to ventricular length ratio in end-diastole(AVLR-ED),AVLR-ED combined with the atrial to ventricular length ratio in end-systole(AVLR-ES),quantile score(Q score)of AVLR-ED,Q score of AVLR-ES,Q score of ventricle length in end-diastole(VL-ED),and AVLR-ES,were the top six with the highest diagnostic value,and the AUC was 0.99(95%CI 0.99–1.00),0.99(95%CI 0.99–1.00),0.99(95%CI 0.98–1.00),0.95(95%CI 0.91–0.99),0.93(95%CI 0.87–0.99),and 0.91(95%CI 0.83–1.00),respectively.And within the 20%false positive rate,the diagnostic sensitivity was greater than 100%,100%,100%,90%,90%,and 88%,respectively.Conclusions:Six variables could be used for prenatal diagnosis of AVSDs.Among them,AVLR-ED and Q score of AVLR-ED,obtained on the 4CHV,were more convenient to acquire and had higher diagnostic accuracy.

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.

Lagrangian coherent structure analysis on transport of Acetes chinensis along coast of Lianyungang,China

Spatial heterogeneity or“patchiness”of plankton distributions in the ocean has always been an attractive and challenging scientific issue to oceanographers.We focused on the accumulation and dynamic mechanism of the Acetes chinensis in the Lianyungang nearshore licensed fishing area.The Lagrangian frame approaches including the Lagrangian coherent structures theory,Lagrangian residual current,and Lagrangian particle-tracking model were applied to find the transport pathways and aggregation characteristics of Acetes chinensis.There exist some material transport pathways for Acetes chinensis passing through the licensed fishing area,and Acetes chinensis is easy to accumulate in the licensed fishing area.The main mechanism forming this distribution pattern is the local circulation induced by the nonlinear interaction of topography and tidal flow.Both the Lagrangian coherent structure analysis and the particle trajectory tracking indicate that Acetes chinensis in the licensed fishing area come from the nearshore estuary.This work contributed to the adjustment of licensed fishing area and the efficient utilization of fishery resources.

Role of intelligent/interactive qualitative and quantitative analysisthree-dimensional estimated model in donor-recipient size mismatch following deceased donor liver transplantation

BACKGROUND Donor-recipient size mismatch(DRSM)is considered a crucial factor for poor outcomes in liver transplantation(LT)because of complications,such as massive intraoperative blood loss(IBL)and early allograft dysfunction(EAD).Liver volumetry is performed routinely in living donor LT,but rarely in deceased donor LT(DDLT),which amplifies the adverse effects of DRSM in DDLT.Due to the various shortcomings of traditional manual liver volumetry and formula methods,a feasible model based on intelligent/interactive qualitative and quantitative analysis-three-dimensional(IQQA-3D)for estimating the degree of DRSM is needed.AIM To identify benefits of IQQA-3D liver volumetry in DDLT and establish an estimation model to guide perioperative management.METHODS We retrospectively determined the accuracy of IQQA-3D liver volumetry for standard total liver volume(TLV)(sTLV)and established an estimation TLV(eTLV)index(eTLVi)model.Receiver operating characteristic(ROC)curves were drawn to detect the optimal cut-off values for predicting massive IBL and EAD in DDLT using donor sTLV to recipient sTLV(called sTLVi).The factors influencing the occurrence of massive IBL and EAD were explored through logistic regression analysis.Finally,the eTLVi model was compared with the sTLVi model through the ROC curve for verification.RESULTS A total of 133 patients were included in the analysis.The Changzheng formula was accurate for calculating donor sTLV(P=0.083)but not for recipient sTLV(P=0.036).Recipient eTLV calculated using IQQA-3D highly matched with recipient sTLV(P=0.221).Alcoholic liver disease,gastrointestinal bleeding,and sTLVi>1.24 were independent risk factors for massive IBL,and drug-induced liver failure was an independent protective factor for massive IBL.Male donor-female recipient combination,model for end-stage liver disease score,sTLVi≤0.85,and sTLVi≥1.32 were independent risk factors for EAD,and viral hepatitis was an independent protective factor for EAD.The overall survival of patients in the 0.85<sTLVi<1.32 group was better compared to the sTLVi≤0.85 group and sTLVi≥1.32 group(P<0.001).There was no statistically significant difference in the area under the curve of the sTLVi model and IQQA-3D eTLVi model in the detection of massive IBL and EAD(all P>0.05).CONCLUSION IQQA-3D eTLVi model has high accuracy in predicting massive IBL and EAD in DDLT.We should follow the guidance of the IQQA-3D eTLVi model in perioperative management.

Semi-analytical solution for drained expansion analysis of a hollow cylinder of critical state soils

The expansion of a thick-walled hollow cylinder in soil is of non-self-similar nature that the stress/deformation paths are not the same for different soil material points.As a result,this problem cannot be solved by the common self-similar-based similarity techniques.This paper proposes a novel,exact solution for rigorous drained expansion analysis of a hollow cylinder of critical state soils.Considering stress-dependent elastic moduli of soils,new analytical stress and displacement solutions for the nonself-similar problem are developed taking the small strain assumption in the elastic zone.In the plastic zone,the cavity expansion response is formulated into a set of first-order partial differential equations(PDEs)with the combination use of Eulerian and Lagrangian descriptions,and a novel solution algorithm is developed to efficiently solve this complex boundary value problem.The solution is presented in a general form and thus can be useful for a wide range of soils.With the new solution,the non-self-similar nature induced by the finite outer boundary is clearly demonstrated and highlighted,which is found to be greatly different to the behaviour of cavity expansion in infinite soil mass.The present solution may serve as a benchmark for verifying the performance of advanced numerical techniques with critical state soil models and be used to capture the finite boundary effect for pressuremeter tests in small-sized calibration chambers.

Developing Reliable Digital Healthcare Service Using Semi-Quantitative Functional Resonance Analysis

Since entering the era of Industry 4.0,the concept of Healthcare 4.0 has also been put forward and explored by researchers.How to use Information Technology(IT)to better serve people’s healthcare is one of the most featured emerging directions in the academic circle.An important field of Healthcare 4.0 research is the reliability engineering of healthcare service.Because healthcare systems often affect the health and even life of their users,developers must be very cautious in the design,development,and operation of these healthcare systems and services.The problems to be solved include the reliability of business process,system functions,and personal healthcare data.The Functional Resonance Analysis Method(FRAM)has been applied in reliability engineering for safety-critical systems in available studies,using both qualitative and quantitative approaches.However,the method has not been applied in the field of digital healthcare services development.Therefore,to narrow the gap,we present in this paper a semi-quantitative functional resonance analysis method to develop reliable healthcare services for diabetics.Moreover,this paper has tried to improve the reliability design of the service-oriented architecture(SOA)of traditional insulin pump therapy by system thinking.