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1. Reliability estimation for one-shot devices under cyclic accelerated life-testing

Author:Zhu,Xiaojun;Liu,Kai;He,Mu;Balakrishnan,N.

Source:Reliability Engineering and System Safety,2021,Vol.212

Abstract:A one-shot device, like an automobile airbag, is a product or an equipment that can be used only once. Better quality and longer lifetime of one-shot devices nowadays increase the cost of life test experiment under normal operating condition. Cyclic stress test, adopted in life-testing experiments by increasing stress levels to induce more failures, has been used to investigate the reliability analysis of one-shot devices based on Coffin–Manson principle. However, the Coffin–Manson model only considers temperature change in each cycle. Moreover, it assumes that the reliability is independent of the cycling frequency, which may not be a realistic assumption in practice. Birnbaum–Saunders distribution, originally developed to model fatigue failure under cyclic loading, has been used widely to model lifetime data. As the Norris–Landzberg model is proposed for modeling fatigue life due to cyclic temperature fluctuation, it is used in this work together with Birnbaum–Saunders distribution for modeling lifetimes of one-shot devices under accelerated life-tests with different cyclic temperature fluctuations. It contains the Coffin–Manson model as a special case. Inferential methods for model parameters, reliability and mean lifetime are developed in this paper. Simulation study and model discrimination are carried out to evaluate the performance of the proposed model and inferential methods. Finally, an example is presented to illustrate the model and the inferential results developed here.
2. ASYMPTOTICS FOR SYSTEMIC RISK WITH DEPENDENT HEAVY-TAILED LOSSES

Author:Liu, JJ;Yang, Y

Source:ASTIN BULLETIN,2021,Vol.51

Abstract:Systemic risk (SR) is considered as the risk of collapse of an entire system, which has played a significant role in explaining the recent financial turmoils from the insurance and financial industries. We consider the asymptotic behavior of the SR for portfolio losses in the model allowing for heavy-tailed primary losses, which are equipped with a wide type of dependence structure. This risk model provides an ideal framework for addressing both heavy-tailedness and dependence. As some extensions, several simulation experiments are conducted, where an insurance application of the asymptotic characterization to the determination and approximation of related SR capital has been proposed, based on the SR measure.
3. On the Kesten-Type Inequality for Randomly Weighted Sums With Applications to an Operational Risk Model

Author:Gong, YS;Yang, Y;Liu, JJ

Source:FILOMAT,2021,Vol.35

Abstract:This paper considers the randomly weighted sums generated by some dependent subexponential primary random variables and some arbitrarily dependent random weights. To study the randomly weighted sums with infinitely many terms, we establish a Kesten-type upper bound for their tail probabilities in presence of subexponential primary random variables and under a certain dependence among them. Our result extends the study of Chen [5] to the dependent case. As applications, we derive some asymptotic formulas for the tail probability and the Value-at-Risk of total aggregate loss in a multivariate operational risk cell model.
4. STEM-ing the Tide: The Influence of the First Year of College on the STEM Gender Gap

Author:Liu,Jiajun;Barnhardt,Cassie L.

Source:Journal of College Student Development,2021,Vol.62

Abstract:Prior research points to the first year of college as a critical time in selecting a college major. Considering the number of studies focusing on the STEM gender gap, surprisingly little research has examined gender differences and the influence of the first college year on the STEM major selection. Using data from the Wabash National Study of Liberal Arts Education, this study examined how women and men compared in STEM college major selection and whether the effects of academic competence, first-year career preferences, life values, and related student experiences influenced their decision in different ways. After controlling a variety of influences, results suggested that women were significantly less likely to be enrolled in a STEM major in the fourth year of college compared to men. Additionally, there were substantial differences between women and men in how various first-year influences shaped the STEM major decision. Findings from this study provide important implications for maximizing women’s participation in STEM fields during the first college year.
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