Quantitative risk assessments are an integral part of risk-informed regulation of current and future nuclear plants in the U.S. The Bayesian approach to treatment of uncertainty, in which both stochastic and epistemic uncertainties are represented with precise probability distributions, is the standard approach to modelling uncertainties in such quantitative risk assessments. However, there are...

The results in this paper add useful tools to the theory of sets of desirable gambles, a growing toolbox for reasoning with partial probability assessments. We investigate how to combine a number of marginal coherent sets of desirable gambles into a joint set using the properties of epistemic irrelevance and independence. We provide formulas for the smallest such joint, called their independent...

Human brain organoids provide a remarkable opportunity to model prenatal human biology in vitro by recapitulating features of utero molecular, cellular and systems biology. An ethical concern peculiar is whether they are or could become capable supporting sentience through the experience pain pleasure and/or consciousness, including higher cognitive abilities such as self-awareness. Identifying...

This paper discusses Numerical Probabilistic Analysis (NPA) for problems under aleatory and epistemic uncertainty. The basis of NPA are numerical operations on probability density functions of the random values and probabilistic extensions. The numerical operations of the histogram arithmetic constitute the major component of NPA. The concepts of natural, probabilistic and histogram extensions ...

5 Many practical methods and different approaches have been proposed to assess Multi-State Systems (MSS) 6 reliability measures. The universal generating function (UGF) method, introduced in 1986, is known to be a very 7 efficient way of evaluating the availability of different types of MSSs. In this paper, we propose an extension 8 of the UGF method considering epistemic uncertainties. This ex...