A new mathematical model in weibull proportional hazards regression using GABA_A

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting Time-To-Failure (TTF) and the probability of failure in future time are essential. In traditional reliability models, the lifetime of assets is estimated using failure time data. However, in most real-life situations and applications, the lifetime of assets is influenced by different risk factors, which are called covariates. These covariates change stochastically and may influence and/or indicate the failure time. Research shows that many statistical models have been developed to estimate the hazard of assets or individuals with covariates. This paper is a state-of-the-art review of the existing literature on these covariate models in both the reliability and biomedical fields. One of the major purposes of this expository paper is to synthesize these models from biomedical fields. For example, Neurotransmitters can have both toxic and trophic functions in addition to their role in neural signaling. Surprisingly, chronic blockade of GABA_A receptor activity for 5–8 d in vitro enhanced survival, suggesting that GABAA receptor overactivation may be neurotoxic. Potentiating GABA_A receptor activity by chronic treatment with the endogenous neurosteroid. Other potentiators of GABA_A receptors, including benzodiazepines, mimicked the cell loss, suggesting that potentiating endogenous GAB_A activity is sufficient to produce neuronal death. Neurosteroidtreated neurons had lower resting intracellular calcium levels than control cells and produced smaller calcium rises in response to depolarizing challenges. The results may have implications for the mechanisms of programmed cell death in the developing CNS as well as implications for the long-term consequences of chronic GABAmimetic drug use during development.