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Objective To investigate whether acupuncture with benefiting the kidney and consolidating the essence could improve the hot flash and the quality of life of breast cancer patients with endocrine therapy. Methods From December 2019 to December 2020, 40 patients with hormone receptor positive breast cancer diagnosed in Jiangsu Provincial Hospital of Chinese Medicine were included, and all the patients had hot flashes after endocrine therapy. The patients were divided into treatment group and control group by random number table method (n=20, each) . The treatment group received acupuncture for benefiting the kidney and consolidating the essence for 10 weeks and self-regulation, while the control group received self-regulation only. The scores of hot flashes, frequency of hot flashes, and quality of life assessment scale (FACT-B) were evaluated before and the 5th and 10th weeks of treatment. Results In the treatment group, the number of hot flashes and the hot flashes fraction at 5 and 10 weeks of acupuncture treatment were significantly lower compared with those before treatment (P＜0.05) . In the control group, the treatment did not change significantly by 5 weeks (P＞0.05) and decreased significantly by 10 weeks (P＜0.05) . The number of hot flashes and the hot flush fraction in the treatment group at 5th and 10th week of treatment were significantly lower than those in the control group (P＜0.05) . The physical, emotional, add-on status, social family and functional status scores in FACT-B were significantly improved in the treatment group at 10th week of acupuncture (P＜0.05) , but did not change in the control group after treatment (P＞0.05) , and the scores improved significantly in the treatment group compared with those in the control group (P＜0.05) . Conclusion Acupuncture with benefiting the kidney and consolidating the essence for 10 weeks can significantly improve the frequency and severity of hot flashes in patients undergoing endocrine therapy for breast cancer, as well as improve the quality of patient survival.

In order to estimate the mechanical components′ response reliability under interference of dynamic correlative stress-strength, the Copula function and random process theory were introduced to establish dynamic reliability model. Due to the complexity of random integral, the random process degenerates into random variable, and then the reliability at a fixed time was calculated based on the discretization thought. Furthermore, the function fitting optimization method was adopted to make the reliability value continuous. At the same time, according to model complexity and fitting residual, the optimal reliability function fitting method was selected. Finally, the typical verified example indicates the effectiveness and feasibility of this method.

ABSTRACT Accelerated life test (ALT) is a generally feasible and effective approach for evaluating the reliability of highly reliable products at normal operating conditions. This paper considers the reliability assessment for a dual constant‐stress ALT with Type‐II censoring for the Weibull distribution with constant shape parameter and a log‐linear link between the scale parameter and the stress factors. We derive the maximum likelihood estimates, weighted least squares estimates using a certain random variable transformation, and a combined maximum likelihood‐least squares estimates for the unknown parameters. In addition, we construct confidence intervals for the parameters of interest using both asymptotic theory and parametric bootstrap technique. Finally, simulation studies and an illustrative example are presented to demonstrate the effectiveness and feasibility of the proposed methods. [ABSTRACT FROM AUTHOR]

Accelerated life test provides a feasible and effective way to rapidly derive lifetime information by exposing products to higher-than-normal operating conditions. However, most of the previous research on accelerated life test has focused on the application of a single stress factor and a traditional censoring scheme. This article considers the reliability inference for a dual constant-stress accelerated life test model with exponential distribution and progressively Type-II censoring. Point estimates for model parameters are provided using maximum likelihood estimation and the weighted least squares method based on random variable transformation. In addition, we construct asymptotic confidence intervals, approximate confidence intervals, and bootstrap confidence intervals for the parameters of interest. Finally, extensive simulation studies and an illustrative example are presented to investigate the performance of the proposed methods. [ABSTRACT FROM AUTHOR]

As cytoplasmic protein complexes that are pivotal for innate immunity, inflammasomes act primarily through the detection of pathogen‐ or danger‐associated molecular patterns. Nucleotide oligomerisation domain‐like receptor family and caspase activation recruitment domain‐containing protein 4 (NLRC4) inflammasomes identify and eliminate intracellular pathogens, a process contingent on the ligand‐recognition capabilities of neuronal apoptosis inhibitory proteins (NAIPs). Upon detection of specific molecules indicative of intracellular infection, NAIPs discern distinct pathogenic components and subsequently transmit signals to NLRC4, thus initiating their activation and triggering an inflammatory response. However, the mechanisms underlying NLRC4 inflammasome remain unclear. In this study, we elucidated the critical role of ATG16L2 in activating the NLRC4 inflammasome. ATG16L2‐deficient macrophages exhibited reduced NLRC4 inflammasome activation, characterised by decreased oligomerisation of apoptosis‐associated speck‐like protein containing a CARD and attenuated cleavage of Pro‐caspase‐1, Pro‐IL‐1β and gasdermin D. Co‐immunoprecipitation assays revealed an interaction between ATG16L2 and NAIPs. Furthermore, ATG16L2 enhanced the association between NAIPs and NLRC4 by binding to NAIPs. For ATG16L2‐knockout mice infected with Salmonella typhimurium, pathogen clearance and survival rates markedly decreased. Collectively, our findings suggest that ATG16L2 is a significant modulator of the innate immune system, influencing the activity of the NLRC4 inflammasome and the host's defensive response to intracellular pathogens. [ABSTRACT FROM AUTHOR]

Aiming at the life data information of multiple types of testing sources for the same product, a mixed base distribution constructed to achieve three-source data fusion, and at the same time, the overall distribution density function of the life data source was estimated. And the iterative formula of the maximum likelihood estimation of each unknown parameter in the parameter vectors of the mixed basis distribution density function was obtained based on the EM algorithm. At the same time, the estimated value of each parameter was given by using the sample weighted by Bootstrap method, the density function analysis of the mixed basis distribution was determined, and the product reliability analysis was completed. The calculation example verified the feasibility and effectiveness of this type of model.

In order to solve the reliability evaluation of small samples for the high reliability, long-life products and to improve the accuracy of reliability evaluation, the Bayesian reliability evaluation model of multiple information source data fusion was carried out. First, a set of data as the initial prior information of another information source in this model was selected, by using the posterior density according to Bayesian estimation. Then, it as the prior distribution of the next information source was used. Through iteration, the joint posterior density and reliability index data of multi-source heterogeneous data are obtained, and the corresponding reliability analysis is completed. Finally, a simulation example verifies the rationality and effectiveness of the model.

The two dependent competing risks are soft failure due to aging degradation and fragmentation caused by shocks and hard failure due to spring breakage caused by the same shock process. Considering the complexity of the product itself and the instability of the working environment, this study proposed a generalized reliability model for systems experiencing dependent competing failure processes (DCFPs) of degradation and random shocks, which considered two kinds of DCFP: (1) shock process could affect soft failure thresholds; (2) degradation process could affect hard failure thresholds. In case (1), we considered the effect that a cumulative number of shocks above a certain magnitude could have on the change in the soft failure threshold. In case (2), we considered not only the shock process's impact on the soft failure threshold but also the total degradation (including continuous degradation and sudden degradation caused by shock) on the hard failure threshold. The model captures the features that the shocks experienced by the system affect the degradation process, accelerating the system degradation and causing soft failures; the degradation process of the system affects the shock process, making the system more susceptible to failure from external shocks. Finally, an example using micro‐electro‐mechanical systems devices illustrates the effectiveness of the proposed approach with sensitivity analysis. [ABSTRACT FROM AUTHOR]

In the reliability assessment of products,this paper tried to make full use of a small amount of field data under natural storage, which might break through the restriction of using single pseudo-sample data in accelerated tests. The comprehensive reliability evaluation model,fusing exponential and Weibull natural storage field data and accelerated storage sample data,was built based on the integrating of relative entropy and the least square method. Simulation results indicate that the method can fuse two sources of information effectively,and when the amount of field data is small,the assessment of model is robust.

In the case of no-fault data,the failure probability combined with the Bayesian theory to study the confidence limit analysis to correct the unilateral confidence reliability evaluation. Based on the Weibull distribution,the distribution curve method was adopted to analyze,and the hierarchical priors distribution was constructed to give the comprehensive E-Bayes estimation of the failure probability,and the estimated value of distribution parameters were obtained by combining the least square method. According to the statistical property of the parameters,the pivot quantity of the confidence interval is constructed,and the interval estimation and reliability confidence lower limit of the Weibull distribution characteristic parameters are given.Taking the classical bearing test as an example,this method was compared with the calculation results of other methods,which proves the rationality and feasibility of this method in evaluating confidence reliability.

In order to realize the rapid reliability evaluation of long-life and high reliability products at a normal stress level, the reliability statistical model of Arrhenius—Weibull was established, by using the Weibull distributions products with the consistent failure mechanism and a log-linear acceleration life test model between characteristic life and stress level. The minimum variance of the product median lifetime estimate at normal stress level as optimum object was considered, the number and quantity of test stress level, samples allocation proporation and censoring time at each stress level are determined as design variables, put forward a reliability optimum scheme of time-censoring constant-stress ALT（CSALT） for weibull distributions. The Fisher Information Matrix is obtained for constructing asymptotic confidence intervals for the model parameters. As the example analysis shows that the reliability optimum scheme of CSALT is effective.

Rotating machinery is an important and easily damaged component in large-scale equipment. Under the coupling action of system components, the occurrence rate of compound faults is very high, which seriously endangers equipment safety. The vibration signals of the damaged rotating machine include equipment operation vibration information, periodic impacts, environmental noise, and even accidental impacts. To effectively extract multi-fault features from compound fault signals, a multi-period pulse detection indicator called harmonic spectrum correlation kurtosis (HSCK) is proposed in this paper. Based on this, an adaptive matching extraction strategy for multiple fault features is proposed. By introducing variational mode decomposition, an adaptive plane paving method for signal components is designed, and an enhanced cyclic frequency estimation method is proposed to pre-determine the fault characteristic frequency as a prior parameter of HSCK, so as to obtain the optimal center frequency and bandwidth of multiple resonance bands. The implementation of this strategy can obtain more periodic pulse information with a high signal-to-noise ratio. Simulation results show that the strategy is accurate and effective. The data of wheel-bearing compound fault and bearing multi-element compound fault indicate that the proposed strategy can be used for compound fault diagnosis of rotating machinery. [ABSTRACT FROM AUTHOR]

This paper investigated reliability modeling for systems subject to dependent competing risks considering that variation of the failure threshold is not considered in most studies on competing failure reliability. Firstly, the variation of degradation quantity under shocks was analyzed, and the variation of the threshold was considered on this basis. Secondly, the cumulative degradation under the influence of the random shock process was analyzed. The attractive property of Copula functions is symmetry. Then, a linear Wiener process model was applied to model performance degradation failure, and a multi-performance degradation correlated-competition model based on a Copula function was constructed, which considered the correlated competition between multi-performance degradation failures. Lastly, a micromotor system was used to analyze the applicability of the proposed model for bivariate instances, demonstrating the rationality and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

To inference the reliability of product at normal stress conditions, accelerated life test (ALT) is usually used to obtain failure information rapidly. However, most of the researches on ALT are focused on the statistical inference with single stress, which makes it difficult to gain accurate reliability through applying ALT method in single stress case. In this article, statistical inference is considered on dual constant-stress accelerated life test (DCSALT) model for the Weibull distribution with Type-I censored data. On the assumption that the Weibull distribution has constant shape parameter, and a log-linear acceleration model between its scale parameter and the test stress level combination. Using the profile maximum likelihood estimation (PMLE) method to estimate the unknown parameters in DCSALT model for Weibull distribution, and this process is completed by Newton-Raphson algorithm. Moreover, the observed information matrix is obtained in order to construct asymptotic confidence intervals of the unknown parameters. Finally, the numerical study is presented to illustrate the effectiveness of the maximum likelihood estimators (MLEs). [ABSTRACT FROM AUTHOR]

Since minimum correlated generalized Lp/Lq deconvolution (MCG-Lp/Lq-D) cannot simultaneously have a good sensing ability to repetitive fault impulses and a strong robustness to noise when processing low SNR signals, a new deconvolution method, minimum improved correlated generalized Lp/Lq deconvolution (MICG-Lp/Lq-D), is proposed in this article. The proposed method is designed based on a novel norm, the improved correlated generalized Lp/Lq (ICG-Lp/Lq) norm. The ICG-Lp/Lq norm not only has the low-order statistics form that is similar to the correlated generalized Lp/Lq (CG-Lp/Lq) norm used in MCG-Lp/Lq-D, but also has the high shift-order signal correlation construction similar to the correlated kurtosis (CK) norm used in maximum correlated kurtosis deconvolution (MCKD). This guarantees that the proposed norm is robust enough to strong noise and can improve its sensing ability for repetitive impulses simultaneously. This feature of the ICG-Lp/Lq norm ensures that MICG-Lp/Lq-D can suppress outliers and extract weak impacts when processing low SNR signals. Simulated and experimental case studies verify the performance of the proposed method. The results indicate that the proposed method is robust enough to strong noise and very sensitive to repetitive impulses simultaneously, which indeed overcomes the aforementioned defects of MCG-Lp/Lq-D. Therefore, MICG-Lp/Lq-D can be considered a promising tool for detecting repetitive impulses. [ABSTRACT FROM AUTHOR]

In order to evaluate the reliability of high reliability and long life products under normal stress conditions effectively and quickly, a confidence reliability evaluation model of dual constant-stress accelerated life lest (DCSALT) for Weibull distribution product is proposed. Firstly, the generalized Eyring-Weibull reliability model is established by using the accelerated life test (ALT) technology. In this model, it is assumed that the Weibull distribution has constant shape parameter and a log-linear relation between its scale parameter and each stress level combination. Secondly, a maximum likelihood estimation (MLE) method for DCSALT with fixed time censoring of the Weibull distribution, the Fisher information matrix related to the likelihood function, and the asymptotic covariance matrix of the model parameters is presented. Furthermore, the asymptotic confidence intervals of the model parameters and some reliability indexes are constructed. Finally, the simulation example demonstrates the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

This article develops reliability models for systems subject to two dependent competing failure processes, considering the correlation between additional damage size on degradation in soft failure process and stress magnitude of shock load in hard failure process, both of which are caused by the same kth random shock. The generalized correlative reliability assessment model based on copulas is proposed, which is then extended to three different shock patterns: (1) δ‐shock, (2) m‐shock, and (3) m‐run shocks. There are some statistical works to be introduced in reliability modeling, including data separation of total degradation amount, inferring the distribution of amount of aging continuous degradation at time t, and fitting copula to the specific correlation. The developed reliability models are demonstrated for an application example of a micro‐electro‐mechanical system. [ABSTRACT FROM AUTHOR]