Objective:To study the causality relationship between diastolic blood pressure(DBP)and hypertensive renal disease with renal failure(HRDRF)and the mediating role of hear t failure(HF)in the causality relationship by n...Objective:To study the causality relationship between diastolic blood pressure(DBP)and hypertensive renal disease with renal failure(HRDRF)and the mediating role of hear t failure(HF)in the causality relationship by network Mendelian randomization(MR).Methods:Genome-wide analysis of DBP,HRDRF,and HF was downloaded from the public database(Genome-Wide Analysis Study[GWAS])and was used to analyze the results and to conduct mediated MR analysis.Results:Analysis showed that DBP was positively correlated with HRDRF(OR=1.0002,95%CI:1.0001–1.0003,P=1.8076e-05)and DBP was positively correlated with HF(OR=1.0295,95%CI:1.0221–1.0370,P=2.5292e-15).HF and HRDRF had a positive causal effect(OR=1.0001,95%CI:1.0000–1.0001,P=0.0152).Mediation analysis showed that the contribution ratio of HF to the combined effect of DBP and HRDRF was 24.69%.Conclusions:DBP can increase the risk of renal disease with renal failure,and HF may play an impor tant role in mediating this causal relationship.展开更多
Objective: To compare the clinical efficacy of conventional Western medicine combined with Qiliqiangxin capsule and western medicine alone in the treatment of chronic heart failure, and to prove that Qiliqiangxin caps...Objective: To compare the clinical efficacy of conventional Western medicine combined with Qiliqiangxin capsule and western medicine alone in the treatment of chronic heart failure, and to prove that Qiliqiangxin capsule combined treatment has more advantages, providing reference for clinical decision-making in the treatment of chronic heart failure. Methods: Randomized controlled trials (RCTs) of conventional Western medicine treatment and Western medicine combined with Qiliqiangxin capsule in the treatment of chronic heart failure were searched in databases such as PubMed, Embase, Webofscience, CNKI, WanFang, VIP, and CBM. The bias risk assessment was conducted using the RCT tool recommended by Cochrane, and then the meta-analysis was performed using RevMan5.4 and Stata17 software. Compare the efficacy evaluation of cardiac function, left ventricular ejection fraction (LVEF), left ventricular end diastolic diameter (LVEDD), cardiac stroke output (SV), 6-minute walking test (6MWT), and N-terminal proBNP in the conventional western medicine combined with Qiliqiangxin capsule group (hereinafter referred to as the treatment group) and the conventional western medicine group (hereinafter referred to as the control group). Results: A total of 20 RCTs meeting the criteria were included, including 2953 patients, including 1508 in the treatment group and 1445 in the control group. The results of meta-analysis showed that the treatment group had significantly better cardiac function evaluation, LVEF, LVEDD, SV, 6MWT, and NT-proBNP improvement than the control group. Its central functional efficacy evaluation (OR=2.09,95% CI: 1.71-2.55, P<0.001), LVEF (WMD=7.05,95% CI: 5.30-8.79, P<0.00001), LVEDD (WMD=6.73, 95% CI: 3.18-10.29, P=0.0002), SV (WMD=6.73, 95% CI: 3.18-10.29, P=0.0002), 6MWT (SMD=0.70,95% CI: 0.54-0.87, P<0.00001), NT-proBNP (SMD=-1.95,95% CI: -2.5 2 to 1.38 (P<0.0001), with statistically significant differences. Conclusion: Conventional western medicine combined with Qiliqiangxin capsule can significantly improve the clinical efficacy of heart failure, improve LVEF, LVEDD, SV, and NT-proBNP index, and improve exercise tolerance. It is worth using for reference in the treatment.展开更多
Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomne...Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomness of failure threshold.Firstly,a random-coefficient regression(RCR)model is used to model the degradation process of aeroengines.Then,the RUL distribution based on fixed failure threshold is derived.The prior parameters of the degradation model are calculated by a two-step maximum likelihood estimation(MLE)method and the random coefficient is updated in real time under the Bayesian framework.The failure threshold in this paper is defined by the actual degradation process of aeroengines.After that,a expectation maximization(EM)algorithm is proposed to estimate the underlying failure threshold of aeroengines.In addition,the conditional probability is used to satisfy the limitation of failure threshold.Then,based on above results,an analytical expression of RUL distribution of aero-engines based on the RCR model considering random failure threshold(RFT)is derived in a closed-form.Finally,a case study of turbofan engine is used to demonstrate the effectiveness and superiority of the RUL prediction method and the parameters estimation method of failure threshold proposed.展开更多
Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a n...Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a nonlinear random coefficient regression(RCR) model with fusing failure time data.Firstly, some interesting natures of parameters estimation based on the nonlinear RCR model are given. Based on these natures,the failure time data can be fused as the prior information reasonably. Specifically, the fixed parameters are calculated by the field degradation data of the evaluated equipment and the prior information of random coefficient is estimated with fusing the failure time data of congeneric equipment. Then, the prior information of the random coefficient is updated online under the Bayesian framework, the probability density function(PDF) of the RUL with considering the limitation of the failure threshold is performed. Finally, two case studies are used for experimental verification. Compared with the traditional Bayesian method, the proposed method can effectively reduce the influence of imperfect prior information and improve the accuracy of RUL prediction.展开更多
Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the fail...Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold(RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization(EM) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.展开更多
Outwash deposit is a unique type of geological materials, and its features such as heterogeneity, discontinuity and nonlinearity determine the complexity of mechanical characteristics and failure mechanism. In this wo...Outwash deposit is a unique type of geological materials, and its features such as heterogeneity, discontinuity and nonlinearity determine the complexity of mechanical characteristics and failure mechanism. In this work, random meso-structure of outwash deposits was constructed by the technique of computer random simulation based on characteristics of its meso-structure in the statistical sense and some simplifications, and a series of large direct shear tests on numerical samples of outwash deposits with stone contents of 15%, 30%, 45% and 60% were conducted using the discrete element method to further investigate its mechanical characteristics and failure mechanism under external load. The results show that the deformation characteristics and shear strength of outwash deposits are to some extent improved with the increase of stone content, and the shear stress–shear displacement curves of outwash deposits show great differences at the post-peak stage due to the random spatial distribution and content of stones. From the mesoscopic view, normal directions of contacts between "soil" and "stone" particles undergo apparent deflection as the shear displacement continues during the shearing process, accompanying redistribution of the magnitude of contact forces during the shearing process. For outwash deposits, the shear zone formed after shear failure is an irregular stripe due to the movements of stones near the shear zone, and it expands gradually with the increase of stone content. In addition, there is an approximately linear relation between the mean increment of internal friction angle and the stone content lying between 30% and 60%, and a concave nonlinear relation between the mean increment of cohesion and stone content, which are in good agreement with the existing research results.展开更多
The value range of the failure threshold will generate an uncertain influence on the prediction results for the remaining useful life(RUL) of equipment. Most of the existing studies on the RUL prediction assume that t...The value range of the failure threshold will generate an uncertain influence on the prediction results for the remaining useful life(RUL) of equipment. Most of the existing studies on the RUL prediction assume that the failure threshold is a fixed value,as they have difficulty in reflecting the random variation of the failure threshold. In connection with the inadequacies of the existing research, an in-depth analysis is carried out to study the effect of the random failure threshold(RFT) on the prediction results for the RUL. First, a nonlinear degradation model with unit-to-unit variability and measurement error is established based on the nonlinear Wiener process. Second, the expectation-maximization(EM) algorithm is used to solve the estimated values of the parameters of the prior degradation model, and the Bayesian method is used to iteratively update the posterior distribution of the random coefficients. Then, the effects of three types of RFT constraint conditions on the prediction results for the RUL are analyzed, and the probability density function(PDF) of the RUL is derived. Finally,the degradation data of aero-turbofan engines are used to verify the correctness and advantages of the method.展开更多
BACKGROUND Heart failure(HF),an end-stage manifestation of various cardiac diseases,poses an enormous economic and health burden on society.Vericiguat may be an effective drug in the treatment of HF.AIM To explore by ...BACKGROUND Heart failure(HF),an end-stage manifestation of various cardiac diseases,poses an enormous economic and health burden on society.Vericiguat may be an effective drug in the treatment of HF.AIM To explore by meta-analysis the efficacy and safety of Vericiguat in treating chronic heart failure.METHODS Databases,including PubMed,EMBASE,Web of Science,and Cochrane Library,were searched to collect all published randomized controlled trials(RCTs)on Vericiguat treatment of chronic heart failure from the earliest electronic records to those published in March 2023.Two investigators independently screened the literature according to inclusion and exclusion criteria,evaluated the quality of the studies,and extracted valid data before conducting a meta-analysis using RevMan5.4.RESULTS Four RCTs with 5919 patients were included,and the meta-analysis showed that treatment with 10 mg Vericiguat reduced the incidence of the primary endpoint(a composite of cardiovascular mortality and first heart-failure-related hospital-ization)in patients with chronic heart failure compared to placebo[relative risk(RR)=0.91,95%confidence interval(CI):0.85–0.98,P=0.01],and reduced the incidence of heart-failure-related hospitalization(RR=0.92,95%CI:0.84–1.00,P=0.05).However,for the incidence of cardiovascular and all-cause death,there were no significant differences between the Vericiguat and placebo groups.In addition,the two groups did not show significant differences in blood pressure,heart rate,and Kansas Cardiomyopathy Questionnaire physical limitation score.In terms of safety,10 mg Vericiguat did not increase the risk of adverse effects in patients with chronic heart failure.Vericiguat may increase the risk of symp-tomatic hypotension(RR=1.17,95%CI:0.98–1.39,P=0.08)and syncope(RR=1.18,95%CI:0.90–1.55,P=0.24),but not significantly.CONCLUSION Vericiguat(10 mg)was more effective than placebo in treating patients with chronic heart failure and had a better safety profile.展开更多
Objective:The purpose of this study was to assess the efficacy and safety of Chinese herbal medicine(CHM)in the treatment of chronic heart failure(CHF)patients according to syndrome differentiation.Methods:In this mul...Objective:The purpose of this study was to assess the efficacy and safety of Chinese herbal medicine(CHM)in the treatment of chronic heart failure(CHF)patients according to syndrome differentiation.Methods:In this multicenter,randomized,double-blind,placebo-controlled clinical trial,a total of 220 CHF patients were assigned to receive CHM or placebo granules without decoction according to syndrome differentiation in addition to their standard western treatment for 4 weeks.The change in the left ventricular ejection fraction(LVEF)was the primary outcome,and the changes in the TCM syndrome scores(TCM-SS)and New York Heart Association functional classification(NYHA-FC)were the secondary outcomes.展开更多
Heart failure is now widely spread throughout the world.Heart disease affects approximately 48%of the population.It is too expensive and also difficult to cure the disease.This research paper represents machine learni...Heart failure is now widely spread throughout the world.Heart disease affects approximately 48%of the population.It is too expensive and also difficult to cure the disease.This research paper represents machine learning models to predict heart failure.The fundamental concept is to compare the correctness of various Machine Learning(ML)algorithms and boost algorithms to improve models’accuracy for prediction.Some supervised algorithms like K-Nearest Neighbor(KNN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF),Logistic Regression(LR)are considered to achieve the best results.Some boosting algorithms like Extreme Gradient Boosting(XGBoost)and Cat-Boost are also used to improve the prediction using Artificial Neural Networks(ANN).This research also focuses on data visualization to identify patterns,trends,and outliers in a massive data set.Python and Scikit-learns are used for ML.Tensor Flow and Keras,along with Python,are used for ANN model train-ing.The DT and RF algorithms achieved the highest accuracy of 95%among the classifiers.Meanwhile,KNN obtained a second height accuracy of 93.33%.XGBoost had a gratified accuracy of 91.67%,SVM,CATBoost,and ANN had an accuracy of 90%,and LR had 88.33%accuracy.展开更多
Nodes in the wireless sensor networks （WSNs） are prone to failure due to energy depletion and poor environment, which could have a negative impact on the normal operation of the network. In order to solve this probl...Nodes in the wireless sensor networks （WSNs） are prone to failure due to energy depletion and poor environment, which could have a negative impact on the normal operation of the network. In order to solve this problem, in this paper, we build a fault-tolerant topology which can effectively tolerate energy depletion and random failure. Firstly, a comprehensive failure model about energy depletion and random failure is established. Then an improved evolution model is presented to generate a fault-tolerant topology, and the degree distribution of the topology can be adjusted. Finally, the relation between the degree distribution and the topological fault tolerance is analyzed, and the optimal value of evolution model parameter is obtained. Then the target fault-tolerant topology which can effectively tolerate energy depletion and random failure is obtained. The performances of the new fault tolerant topology are verified by simulation experiments. The results show that the new fault tolerant topology effectively prolongs the network lifetime and has strong fault tolerance.展开更多
Objective To investigate the immediate effects of electro-acupuncture(EA)on endometrial blood flow among recurrent implantation failure(RIF)patients.Methods Eighty RIF patients,enrolled from March 2022 to December 202...Objective To investigate the immediate effects of electro-acupuncture(EA)on endometrial blood flow among recurrent implantation failure(RIF)patients.Methods Eighty RIF patients,enrolled from March 2022 to December 2022,were randomly allocated into either the EA group(40 cases)or the waiting-list(WL)group(40 cases)by using a random number table.The EA group underwent acupuncture at points of Shenting(GV 24),Baihui(GV 4),Benshen(GB 13),bilateral Zigong(EX-CA 1),Huangshu(KI 16),Sanyinjiao(SP 6)and Xuehai(SP10),and electric acupuncture apparatus was connected to EX-CA 1,KI 16,SP 6,and SP 10 with disperse-dense waves at 4/20 Hz frequencies for 30 min after transvaginal ultrasound,while the WL group received no intervention.The primary outcome measured was the endometrial volume blood flow.The secondary outcomes included the bilateral uterine artery index,endometrial volume,endometrial blood flow type,vascular distribution index(VI^(MV))for endometrial and ovary,clinical pregnancy rate,and embryo implantation rate.Results In the EA group,there was a notable decrease in the bilateral pulsatility index and a significant improvement in the endometrial blood flow type post-EA(P<0.05).Both the endometrial blood flow type and VI^(MV) for the endometrium and right ovary were markedly higher in the EA group compared to the WL group post-treatment(P<0.05).Conversely,no significant disparities were observed in vascular index,flow index,vascular blood flow index,uterine arterial blood flow indices,endometrial volume,clinical pregnancy rate and embryo implantation rate between the two groups after treatment(P>0.05).Besides,no adverse events related to EA were observed.Conclusions EA can promptly ameliorate VI^(MV) for the endometrial and right ovary,and endometrial blood flow type.Future randomized controlled trials are warranted to investigate the long-term effects of EA on blood flow of RIF patients and its implications for pregnancy outcomes.(Trial registration No.ChiCTR2200057377).展开更多
A modified discontinuous deformation analysis (DDA) algorithm was proposed to simulate the failure behavior of jointed rock. In the proposed algorithm, by using the Monte-Carlo technique, random joint network was gene...A modified discontinuous deformation analysis (DDA) algorithm was proposed to simulate the failure behavior of jointed rock. In the proposed algorithm, by using the Monte-Carlo technique, random joint network was generated in the domain of interest. Based on the joint network, the triangular DDA block system was automatically generated by adopting the advanced front method. In the process of generating blocks, numerous artificial joints came into being, and once the stress states at some artificial joints satisfy the failure criterion given beforehand, artificial joints will turn into real joints. In this way, the whole fragmentation process of rock mass can be replicated. The algorithm logic was described in detail, and several numerical examples were carried out to obtain some insight into the failure behavior of rock mass containing random joints. From the numerical results, it can be found that the crack initiates from the crack tip, the growth direction of the crack depends upon the loading and constraint conditions, and the proposed method can reproduce some complicated phenomena in the whole process of rock failure.展开更多
BACKGROUND Microvascular tissue reconstruction is a well-established,commonly used technique for a wide variety of the tissue defects.However,flap failure is associated with an additional hospital stay,medical cost bu...BACKGROUND Microvascular tissue reconstruction is a well-established,commonly used technique for a wide variety of the tissue defects.However,flap failure is associated with an additional hospital stay,medical cost burden,and mental stress.Therefore,understanding of the risk factors associated with this event is of utmost importance.AIM To develop machine learning-based predictive models for flap failure to identify the potential factors and screen out high-risk patients.METHODS Using the data set of 946 consecutive patients,who underwent microvascular tissue reconstruction of free flap reconstruction for head and neck,breast,back,and extremity,we established three machine learning models including random forest classifier,support vector machine,and gradient boosting.Model performances were evaluated by the indicators such as area under the curve of receiver operating characteristic curve,accuracy,precision,recall,and F1 score.A multivariable regression analysis was performed for the most critical variables in the random forest model.RESULTS Post-surgery,the flap failure event occurred in 34 patients(3.6%).The machine learning models based on various preoperative and intraoperative variables were successfully developed.Among them,the random forest classifier reached the best performance in receiver operating characteristic curve,with an area under the curve score of 0.770 in the test set.The top 10 variables in the random forest were age,body mass index,ischemia time,smoking,diabetes,experience,prior chemotherapy,hypertension,insulin,and obesity.Interestingly,only age,body mass index, and ischemic time were statistically associated with the outcomes.CONCLUSIONMachine learning-based algorithms, especially the random forest classifier, were very important incategorizing patients at high risk of flap failure. The occurrence of flap failure was a multifactordrivenevent and was identified with numerous factors that warrant further investigation.Importantly, the successful application of machine learning models may help the clinician indecision-making, understanding the underlying pathologic mechanisms of the disease, andimproving the long-term outcome of patients.展开更多
The problem of production control for a hybrid manufacturing/remanufacturing system under uncertainty is analyzed. Two sources of uncertainty are considered: machines are subject to random breakdowns and repairs, and ...The problem of production control for a hybrid manufacturing/remanufacturing system under uncertainty is analyzed. Two sources of uncertainty are considered: machines are subject to random breakdowns and repairs, and demand level is modeled as a diffusion type stochastic process. Contrary to most of studies where the demand level is considered constant and fewer results where the demand is modeled as a Poisson process with few discrete levels and exponentially distributed switching time, the demand is modeled here as a diffusion type process. In particular Wiener and Ornstein-Uhlenbeck processes for cumulative demands are analyzed. We formulate the stochastic control problem and develop optimality conditions for it in the form of Hamilton-Jacobi-Bellman (HJB) partial differential equations (PDEs). We demonstrate that HJB equations are of the second order contrary to the case of constant demand rate (corresponding to the average demand in our case), where HJB equations are linear PDEs. We apply the Kushner-type finite difference scheme and the policy improvement procedure to solve HJB equations numerically and show that the optimal production policy is of hedging-point type for both demand models we have introduced, similarly to the known case of a constant demand. Obtained results allow to compute numerically the optimal production policy in hybrid manufacturing/ remanufacturing systems taking into account the demand variability, and also show that Kushner-type discrete scheme can be successfully applied for solving underlying second order HJB equations.展开更多
Anisotropic spatial variability of soil properties is frequently encountered in geotechnical engineering practice due to the complex depositional process.To quantitatively evaluate the response of slope failure relate...Anisotropic spatial variability of soil properties is frequently encountered in geotechnical engineering practice due to the complex depositional process.To quantitatively evaluate the response of slope failure related to anisotropic spatial variability of soil properties and reveal the underlying influence of anisotropic spatial variability of soil properties on the slope reliability,this study integrates the random finite difference method(RFDM)into a probabilistic assessment framework and adopts general spatial variability and a cohesive-frictional soil slope example for illustration.A parametric analysis is carried out to investigate the influence of general anisotropic spatial variability of soil properties on slope failure probability and failure characteristics.The results show that the directional angles of scales of fluctuation of general anisotropic spatial variability significantly affect the slope failure probability.The dominant failure mode is the intermediate type in most cases of general anisotropic spatial variability,which is distinguished from the shallow failure mode occurring in the homogenous state.Overestimation of cross-correlation between c and u(qc;u),scales of fluctuation(dmax and dmin)in general anisotropic spatially variable soils significantly influences the average slip mass volumes of deep and multi-slip failure mode.Compared with transverse anisotropic spatial variability,general anisotropic spatial variability significantly ampli-fies the effects of qc;u,dmax and dmin on slope reliability.展开更多
On the basis of Miner's linear cumulative damage theorem, random variables are introduced to evaluate objectively the fatigue damage of a semi-submerged platform structure and a method is presented to analyze the ...On the basis of Miner's linear cumulative damage theorem, random variables are introduced to evaluate objectively the fatigue damage of a semi-submerged platform structure and a method is presented to analyze the fatigue reliability of the structure in its design life. The reliability of the method is verified through numerical examples and some conclusions are drawn, which have certain guiding and reference value for design and inspection.展开更多
Functional failure mode of commercial deep sub-micron static random access memory（SRAM） induced by total dose irradiation is experimentally analyzed and verified by circuit simulation. We extensively characterize th...Functional failure mode of commercial deep sub-micron static random access memory（SRAM） induced by total dose irradiation is experimentally analyzed and verified by circuit simulation. We extensively characterize the functional failure mode of the device by testing its electrical parameters and function with test patterns covering different functional failure modes. Experimental results reveal that the functional failure mode of the device is a temporary function interruption caused by peripheral circuits being sensitive to the standby current rising. By including radiation-induced threshold shift and off-state leakage current in memory cell transistors, we simulate the influence of radiation on the functionality of the memory cell. Simulation results reveal that the memory cell is tolerant to irradiation due to its high stability, which agrees with our experimental result.展开更多
A probability based model of block failure capacity of pile foundation in clay soil under axial load is developed. The model was based on the first order second moment method. Instead of using point variability, the s...A probability based model of block failure capacity of pile foundation in clay soil under axial load is developed. The model was based on the first order second moment method. Instead of using point variability, the soil inherent variability is modelled as random field model. Based on this model, a reliability based factor of safety for designing pile group foundation, taking into account bock failure mechanism, is proposed. Furthermore, using simplified lognormal model, the relationship between the factor of safety used in design practice and target reliability may be derived explicitly.展开更多
In this paper, the inference for the Burr-X model under progressively first-failure censoring scheme is discussed. Based on this new censoring were the number of units removed at each failure time has a discrete binom...In this paper, the inference for the Burr-X model under progressively first-failure censoring scheme is discussed. Based on this new censoring were the number of units removed at each failure time has a discrete binomial distribution. The maximum likelihood, Bootstrap and Bayes estimates for the Burr-X distribution are obtained. The Bayes estimators are obtained using both the symmetric and asymmetric loss functions. Approximate confidence interval and highest posterior density interval (HPDI) are discussed. A numerical example is provided to illustrate the proposed estimation methods developed here. The maximum likelihood and the different Bayes estimates are compared via a Monte Carlo simulation study.展开更多
基金supported by the scientific research project of Shanxi Provincial Health Commission(No.2022073)。
文摘Objective:To study the causality relationship between diastolic blood pressure(DBP)and hypertensive renal disease with renal failure(HRDRF)and the mediating role of hear t failure(HF)in the causality relationship by network Mendelian randomization(MR).Methods:Genome-wide analysis of DBP,HRDRF,and HF was downloaded from the public database(Genome-Wide Analysis Study[GWAS])and was used to analyze the results and to conduct mediated MR analysis.Results:Analysis showed that DBP was positively correlated with HRDRF(OR=1.0002,95%CI:1.0001–1.0003,P=1.8076e-05)and DBP was positively correlated with HF(OR=1.0295,95%CI:1.0221–1.0370,P=2.5292e-15).HF and HRDRF had a positive causal effect(OR=1.0001,95%CI:1.0000–1.0001,P=0.0152).Mediation analysis showed that the contribution ratio of HF to the combined effect of DBP and HRDRF was 24.69%.Conclusions:DBP can increase the risk of renal disease with renal failure,and HF may play an impor tant role in mediating this causal relationship.
基金National Natural Science Foundation of China Regional Science Foundation Project(No.82160887)General Project of Guangxi Natural Science Foundation(No.2021GXNSFAA220111)Guangxi Natural Science Foundation Project Youth Science Foundation Project(No.2021GXNSFBA196018)。
文摘Objective: To compare the clinical efficacy of conventional Western medicine combined with Qiliqiangxin capsule and western medicine alone in the treatment of chronic heart failure, and to prove that Qiliqiangxin capsule combined treatment has more advantages, providing reference for clinical decision-making in the treatment of chronic heart failure. Methods: Randomized controlled trials (RCTs) of conventional Western medicine treatment and Western medicine combined with Qiliqiangxin capsule in the treatment of chronic heart failure were searched in databases such as PubMed, Embase, Webofscience, CNKI, WanFang, VIP, and CBM. The bias risk assessment was conducted using the RCT tool recommended by Cochrane, and then the meta-analysis was performed using RevMan5.4 and Stata17 software. Compare the efficacy evaluation of cardiac function, left ventricular ejection fraction (LVEF), left ventricular end diastolic diameter (LVEDD), cardiac stroke output (SV), 6-minute walking test (6MWT), and N-terminal proBNP in the conventional western medicine combined with Qiliqiangxin capsule group (hereinafter referred to as the treatment group) and the conventional western medicine group (hereinafter referred to as the control group). Results: A total of 20 RCTs meeting the criteria were included, including 2953 patients, including 1508 in the treatment group and 1445 in the control group. The results of meta-analysis showed that the treatment group had significantly better cardiac function evaluation, LVEF, LVEDD, SV, 6MWT, and NT-proBNP improvement than the control group. Its central functional efficacy evaluation (OR=2.09,95% CI: 1.71-2.55, P<0.001), LVEF (WMD=7.05,95% CI: 5.30-8.79, P<0.00001), LVEDD (WMD=6.73, 95% CI: 3.18-10.29, P=0.0002), SV (WMD=6.73, 95% CI: 3.18-10.29, P=0.0002), 6MWT (SMD=0.70,95% CI: 0.54-0.87, P<0.00001), NT-proBNP (SMD=-1.95,95% CI: -2.5 2 to 1.38 (P<0.0001), with statistically significant differences. Conclusion: Conventional western medicine combined with Qiliqiangxin capsule can significantly improve the clinical efficacy of heart failure, improve LVEF, LVEDD, SV, and NT-proBNP index, and improve exercise tolerance. It is worth using for reference in the treatment.
基金supported by the National Natural Science Foundation of China(61703410,61873175,62073336,61873273,61773386,61922-089)the Basic Research Plan of Shaanxi Natural Science Foundation of China(2022JM-376).
文摘Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomness of failure threshold.Firstly,a random-coefficient regression(RCR)model is used to model the degradation process of aeroengines.Then,the RUL distribution based on fixed failure threshold is derived.The prior parameters of the degradation model are calculated by a two-step maximum likelihood estimation(MLE)method and the random coefficient is updated in real time under the Bayesian framework.The failure threshold in this paper is defined by the actual degradation process of aeroengines.After that,a expectation maximization(EM)algorithm is proposed to estimate the underlying failure threshold of aeroengines.In addition,the conditional probability is used to satisfy the limitation of failure threshold.Then,based on above results,an analytical expression of RUL distribution of aero-engines based on the RCR model considering random failure threshold(RFT)is derived in a closed-form.Finally,a case study of turbofan engine is used to demonstrate the effectiveness and superiority of the RUL prediction method and the parameters estimation method of failure threshold proposed.
基金supported by National Natural Science Foundation of China (61703410,61873175,62073336,61873273,61773386,61922089)。
文摘Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a nonlinear random coefficient regression(RCR) model with fusing failure time data.Firstly, some interesting natures of parameters estimation based on the nonlinear RCR model are given. Based on these natures,the failure time data can be fused as the prior information reasonably. Specifically, the fixed parameters are calculated by the field degradation data of the evaluated equipment and the prior information of random coefficient is estimated with fusing the failure time data of congeneric equipment. Then, the prior information of the random coefficient is updated online under the Bayesian framework, the probability density function(PDF) of the RUL with considering the limitation of the failure threshold is performed. Finally, two case studies are used for experimental verification. Compared with the traditional Bayesian method, the proposed method can effectively reduce the influence of imperfect prior information and improve the accuracy of RUL prediction.
基金Projects(51475462,61174030,61473094,61374126)supported by the National Natural Science Foundation of China
文摘Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold(RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization(EM) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.
基金Project(2011CB013504) supported by the National Basic Research Program(973 Program)of ChinaProject(2013BAB06B01) supported by the National Science&Technology Pillar Program during the Twelfth Five-year Plan Period+2 种基金Projects(11772118,51479049,51709282) supported by the National Natural Science Foundation of ChinaProject(2017M620838) supported by the Postdoctoral Science Foundation of ChinaProject(487237) supported by the Natural Sciences and Engineering Research Council of Canada
文摘Outwash deposit is a unique type of geological materials, and its features such as heterogeneity, discontinuity and nonlinearity determine the complexity of mechanical characteristics and failure mechanism. In this work, random meso-structure of outwash deposits was constructed by the technique of computer random simulation based on characteristics of its meso-structure in the statistical sense and some simplifications, and a series of large direct shear tests on numerical samples of outwash deposits with stone contents of 15%, 30%, 45% and 60% were conducted using the discrete element method to further investigate its mechanical characteristics and failure mechanism under external load. The results show that the deformation characteristics and shear strength of outwash deposits are to some extent improved with the increase of stone content, and the shear stress–shear displacement curves of outwash deposits show great differences at the post-peak stage due to the random spatial distribution and content of stones. From the mesoscopic view, normal directions of contacts between "soil" and "stone" particles undergo apparent deflection as the shear displacement continues during the shearing process, accompanying redistribution of the magnitude of contact forces during the shearing process. For outwash deposits, the shear zone formed after shear failure is an irregular stripe due to the movements of stones near the shear zone, and it expands gradually with the increase of stone content. In addition, there is an approximately linear relation between the mean increment of internal friction angle and the stone content lying between 30% and 60%, and a concave nonlinear relation between the mean increment of cohesion and stone content, which are in good agreement with the existing research results.
基金supported by the China Postdoctoral Science Foundation(2017M623415)。
文摘The value range of the failure threshold will generate an uncertain influence on the prediction results for the remaining useful life(RUL) of equipment. Most of the existing studies on the RUL prediction assume that the failure threshold is a fixed value,as they have difficulty in reflecting the random variation of the failure threshold. In connection with the inadequacies of the existing research, an in-depth analysis is carried out to study the effect of the random failure threshold(RFT) on the prediction results for the RUL. First, a nonlinear degradation model with unit-to-unit variability and measurement error is established based on the nonlinear Wiener process. Second, the expectation-maximization(EM) algorithm is used to solve the estimated values of the parameters of the prior degradation model, and the Bayesian method is used to iteratively update the posterior distribution of the random coefficients. Then, the effects of three types of RFT constraint conditions on the prediction results for the RUL are analyzed, and the probability density function(PDF) of the RUL is derived. Finally,the degradation data of aero-turbofan engines are used to verify the correctness and advantages of the method.
基金Key Research and Development projects in Jiangxi Province,No.20223BBG71010National Natural Science Foundation of China,No.81960058.
文摘BACKGROUND Heart failure(HF),an end-stage manifestation of various cardiac diseases,poses an enormous economic and health burden on society.Vericiguat may be an effective drug in the treatment of HF.AIM To explore by meta-analysis the efficacy and safety of Vericiguat in treating chronic heart failure.METHODS Databases,including PubMed,EMBASE,Web of Science,and Cochrane Library,were searched to collect all published randomized controlled trials(RCTs)on Vericiguat treatment of chronic heart failure from the earliest electronic records to those published in March 2023.Two investigators independently screened the literature according to inclusion and exclusion criteria,evaluated the quality of the studies,and extracted valid data before conducting a meta-analysis using RevMan5.4.RESULTS Four RCTs with 5919 patients were included,and the meta-analysis showed that treatment with 10 mg Vericiguat reduced the incidence of the primary endpoint(a composite of cardiovascular mortality and first heart-failure-related hospital-ization)in patients with chronic heart failure compared to placebo[relative risk(RR)=0.91,95%confidence interval(CI):0.85–0.98,P=0.01],and reduced the incidence of heart-failure-related hospitalization(RR=0.92,95%CI:0.84–1.00,P=0.05).However,for the incidence of cardiovascular and all-cause death,there were no significant differences between the Vericiguat and placebo groups.In addition,the two groups did not show significant differences in blood pressure,heart rate,and Kansas Cardiomyopathy Questionnaire physical limitation score.In terms of safety,10 mg Vericiguat did not increase the risk of adverse effects in patients with chronic heart failure.Vericiguat may increase the risk of symp-tomatic hypotension(RR=1.17,95%CI:0.98–1.39,P=0.08)and syncope(RR=1.18,95%CI:0.90–1.55,P=0.24),but not significantly.CONCLUSION Vericiguat(10 mg)was more effective than placebo in treating patients with chronic heart failure and had a better safety profile.
基金the National Department Public Benefit Research Foundation(200807007)the National Basic Research Program of China(973 Program under grant 2011CB505106)+3 种基金the International Science and Technology Cooperation of China(2008DFA30610)the National“Twelfth Five-Year”Plan for Science and Technology Support(2012BAI29B07)the Foundation of Beijing University of Chinese Medicine Basic Scientific Research Business Expenses(2011-CXTD-06)the National Science Foundation of China(30902020 and 81173463).
文摘Objective:The purpose of this study was to assess the efficacy and safety of Chinese herbal medicine(CHM)in the treatment of chronic heart failure(CHF)patients according to syndrome differentiation.Methods:In this multicenter,randomized,double-blind,placebo-controlled clinical trial,a total of 220 CHF patients were assigned to receive CHM or placebo granules without decoction according to syndrome differentiation in addition to their standard western treatment for 4 weeks.The change in the left ventricular ejection fraction(LVEF)was the primary outcome,and the changes in the TCM syndrome scores(TCM-SS)and New York Heart Association functional classification(NYHA-FC)were the secondary outcomes.
基金Taif University Researchers Supporting Project Number(TURSP-2020/73)Taif University,Taif,Saudi Arabia.
文摘Heart failure is now widely spread throughout the world.Heart disease affects approximately 48%of the population.It is too expensive and also difficult to cure the disease.This research paper represents machine learning models to predict heart failure.The fundamental concept is to compare the correctness of various Machine Learning(ML)algorithms and boost algorithms to improve models’accuracy for prediction.Some supervised algorithms like K-Nearest Neighbor(KNN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF),Logistic Regression(LR)are considered to achieve the best results.Some boosting algorithms like Extreme Gradient Boosting(XGBoost)and Cat-Boost are also used to improve the prediction using Artificial Neural Networks(ANN).This research also focuses on data visualization to identify patterns,trends,and outliers in a massive data set.Python and Scikit-learns are used for ML.Tensor Flow and Keras,along with Python,are used for ANN model train-ing.The DT and RF algorithms achieved the highest accuracy of 95%among the classifiers.Meanwhile,KNN obtained a second height accuracy of 93.33%.XGBoost had a gratified accuracy of 91.67%,SVM,CATBoost,and ANN had an accuracy of 90%,and LR had 88.33%accuracy.
基金supported by the Natural Science Foundation of Hebei Province,China(Grant Nos.F2012203179 and F2014203239)
文摘Nodes in the wireless sensor networks （WSNs） are prone to failure due to energy depletion and poor environment, which could have a negative impact on the normal operation of the network. In order to solve this problem, in this paper, we build a fault-tolerant topology which can effectively tolerate energy depletion and random failure. Firstly, a comprehensive failure model about energy depletion and random failure is established. Then an improved evolution model is presented to generate a fault-tolerant topology, and the degree distribution of the topology can be adjusted. Finally, the relation between the degree distribution and the topological fault tolerance is analyzed, and the optimal value of evolution model parameter is obtained. Then the target fault-tolerant topology which can effectively tolerate energy depletion and random failure is obtained. The performances of the new fault tolerant topology are verified by simulation experiments. The results show that the new fault tolerant topology effectively prolongs the network lifetime and has strong fault tolerance.
基金Supported by Sichuan Outstanding Young Science Project Funding(No.2020JDJQ0051)the National Natural Science Foundation of China(Nos.82174517 and 81973966)。
文摘Objective To investigate the immediate effects of electro-acupuncture(EA)on endometrial blood flow among recurrent implantation failure(RIF)patients.Methods Eighty RIF patients,enrolled from March 2022 to December 2022,were randomly allocated into either the EA group(40 cases)or the waiting-list(WL)group(40 cases)by using a random number table.The EA group underwent acupuncture at points of Shenting(GV 24),Baihui(GV 4),Benshen(GB 13),bilateral Zigong(EX-CA 1),Huangshu(KI 16),Sanyinjiao(SP 6)and Xuehai(SP10),and electric acupuncture apparatus was connected to EX-CA 1,KI 16,SP 6,and SP 10 with disperse-dense waves at 4/20 Hz frequencies for 30 min after transvaginal ultrasound,while the WL group received no intervention.The primary outcome measured was the endometrial volume blood flow.The secondary outcomes included the bilateral uterine artery index,endometrial volume,endometrial blood flow type,vascular distribution index(VI^(MV))for endometrial and ovary,clinical pregnancy rate,and embryo implantation rate.Results In the EA group,there was a notable decrease in the bilateral pulsatility index and a significant improvement in the endometrial blood flow type post-EA(P<0.05).Both the endometrial blood flow type and VI^(MV) for the endometrium and right ovary were markedly higher in the EA group compared to the WL group post-treatment(P<0.05).Conversely,no significant disparities were observed in vascular index,flow index,vascular blood flow index,uterine arterial blood flow indices,endometrial volume,clinical pregnancy rate and embryo implantation rate between the two groups after treatment(P>0.05).Besides,no adverse events related to EA were observed.Conclusions EA can promptly ameliorate VI^(MV) for the endometrial and right ovary,and endometrial blood flow type.Future randomized controlled trials are warranted to investigate the long-term effects of EA on blood flow of RIF patients and its implications for pregnancy outcomes.(Trial registration No.ChiCTR2200057377).
基金Projects(50479071, 40672191) supported by the National Natural Science Foundation of ChinaProject(SKLZ0801) supported by the Independent Research Key Project of State Key Laboratory of Geomechanics and Geotechnical EngineeringProject(SKLQ001) supported by the Independent Research Frontier Exploring Project of State Key Laboratory of Geomechanics and Geotechnical Engineering
文摘A modified discontinuous deformation analysis (DDA) algorithm was proposed to simulate the failure behavior of jointed rock. In the proposed algorithm, by using the Monte-Carlo technique, random joint network was generated in the domain of interest. Based on the joint network, the triangular DDA block system was automatically generated by adopting the advanced front method. In the process of generating blocks, numerous artificial joints came into being, and once the stress states at some artificial joints satisfy the failure criterion given beforehand, artificial joints will turn into real joints. In this way, the whole fragmentation process of rock mass can be replicated. The algorithm logic was described in detail, and several numerical examples were carried out to obtain some insight into the failure behavior of rock mass containing random joints. From the numerical results, it can be found that the crack initiates from the crack tip, the growth direction of the crack depends upon the loading and constraint conditions, and the proposed method can reproduce some complicated phenomena in the whole process of rock failure.
文摘BACKGROUND Microvascular tissue reconstruction is a well-established,commonly used technique for a wide variety of the tissue defects.However,flap failure is associated with an additional hospital stay,medical cost burden,and mental stress.Therefore,understanding of the risk factors associated with this event is of utmost importance.AIM To develop machine learning-based predictive models for flap failure to identify the potential factors and screen out high-risk patients.METHODS Using the data set of 946 consecutive patients,who underwent microvascular tissue reconstruction of free flap reconstruction for head and neck,breast,back,and extremity,we established three machine learning models including random forest classifier,support vector machine,and gradient boosting.Model performances were evaluated by the indicators such as area under the curve of receiver operating characteristic curve,accuracy,precision,recall,and F1 score.A multivariable regression analysis was performed for the most critical variables in the random forest model.RESULTS Post-surgery,the flap failure event occurred in 34 patients(3.6%).The machine learning models based on various preoperative and intraoperative variables were successfully developed.Among them,the random forest classifier reached the best performance in receiver operating characteristic curve,with an area under the curve score of 0.770 in the test set.The top 10 variables in the random forest were age,body mass index,ischemia time,smoking,diabetes,experience,prior chemotherapy,hypertension,insulin,and obesity.Interestingly,only age,body mass index, and ischemic time were statistically associated with the outcomes.CONCLUSIONMachine learning-based algorithms, especially the random forest classifier, were very important incategorizing patients at high risk of flap failure. The occurrence of flap failure was a multifactordrivenevent and was identified with numerous factors that warrant further investigation.Importantly, the successful application of machine learning models may help the clinician indecision-making, understanding the underlying pathologic mechanisms of the disease, andimproving the long-term outcome of patients.
文摘The problem of production control for a hybrid manufacturing/remanufacturing system under uncertainty is analyzed. Two sources of uncertainty are considered: machines are subject to random breakdowns and repairs, and demand level is modeled as a diffusion type stochastic process. Contrary to most of studies where the demand level is considered constant and fewer results where the demand is modeled as a Poisson process with few discrete levels and exponentially distributed switching time, the demand is modeled here as a diffusion type process. In particular Wiener and Ornstein-Uhlenbeck processes for cumulative demands are analyzed. We formulate the stochastic control problem and develop optimality conditions for it in the form of Hamilton-Jacobi-Bellman (HJB) partial differential equations (PDEs). We demonstrate that HJB equations are of the second order contrary to the case of constant demand rate (corresponding to the average demand in our case), where HJB equations are linear PDEs. We apply the Kushner-type finite difference scheme and the policy improvement procedure to solve HJB equations numerically and show that the optimal production policy is of hedging-point type for both demand models we have introduced, similarly to the known case of a constant demand. Obtained results allow to compute numerically the optimal production policy in hybrid manufacturing/ remanufacturing systems taking into account the demand variability, and also show that Kushner-type discrete scheme can be successfully applied for solving underlying second order HJB equations.
基金the financial support from National Natural Science Foundation of China(No.52078086)Program of Distinguished Young Scholars,Natural Science Foundation of Chongqing,China(No.cstc2020jcyj-jq0087)+1 种基金China Scholarship Council,China(CSC No.201906050237)Innovation Group Science Foundation of the Natural Science Foundation of Chongqing,China(Grant No.cstc2020jcyj-cxttX0003).
文摘Anisotropic spatial variability of soil properties is frequently encountered in geotechnical engineering practice due to the complex depositional process.To quantitatively evaluate the response of slope failure related to anisotropic spatial variability of soil properties and reveal the underlying influence of anisotropic spatial variability of soil properties on the slope reliability,this study integrates the random finite difference method(RFDM)into a probabilistic assessment framework and adopts general spatial variability and a cohesive-frictional soil slope example for illustration.A parametric analysis is carried out to investigate the influence of general anisotropic spatial variability of soil properties on slope failure probability and failure characteristics.The results show that the directional angles of scales of fluctuation of general anisotropic spatial variability significantly affect the slope failure probability.The dominant failure mode is the intermediate type in most cases of general anisotropic spatial variability,which is distinguished from the shallow failure mode occurring in the homogenous state.Overestimation of cross-correlation between c and u(qc;u),scales of fluctuation(dmax and dmin)in general anisotropic spatially variable soils significantly influences the average slip mass volumes of deep and multi-slip failure mode.Compared with transverse anisotropic spatial variability,general anisotropic spatial variability significantly ampli-fies the effects of qc;u,dmax and dmin on slope reliability.
基金A part of the project supported financially by the National Natural Science Foundation of China
文摘On the basis of Miner's linear cumulative damage theorem, random variables are introduced to evaluate objectively the fatigue damage of a semi-submerged platform structure and a method is presented to analyze the fatigue reliability of the structure in its design life. The reliability of the method is verified through numerical examples and some conclusions are drawn, which have certain guiding and reference value for design and inspection.
文摘Functional failure mode of commercial deep sub-micron static random access memory（SRAM） induced by total dose irradiation is experimentally analyzed and verified by circuit simulation. We extensively characterize the functional failure mode of the device by testing its electrical parameters and function with test patterns covering different functional failure modes. Experimental results reveal that the functional failure mode of the device is a temporary function interruption caused by peripheral circuits being sensitive to the standby current rising. By including radiation-induced threshold shift and off-state leakage current in memory cell transistors, we simulate the influence of radiation on the functionality of the memory cell. Simulation results reveal that the memory cell is tolerant to irradiation due to its high stability, which agrees with our experimental result.
文摘A probability based model of block failure capacity of pile foundation in clay soil under axial load is developed. The model was based on the first order second moment method. Instead of using point variability, the soil inherent variability is modelled as random field model. Based on this model, a reliability based factor of safety for designing pile group foundation, taking into account bock failure mechanism, is proposed. Furthermore, using simplified lognormal model, the relationship between the factor of safety used in design practice and target reliability may be derived explicitly.
文摘In this paper, the inference for the Burr-X model under progressively first-failure censoring scheme is discussed. Based on this new censoring were the number of units removed at each failure time has a discrete binomial distribution. The maximum likelihood, Bootstrap and Bayes estimates for the Burr-X distribution are obtained. The Bayes estimators are obtained using both the symmetric and asymmetric loss functions. Approximate confidence interval and highest posterior density interval (HPDI) are discussed. A numerical example is provided to illustrate the proposed estimation methods developed here. The maximum likelihood and the different Bayes estimates are compared via a Monte Carlo simulation study.
