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2 results

  • 15 - Bayesian Network for Reliability Assessment and Updating

  • Armen Der Kiureghian, University of California, Berkeley
  • Book:
    Structural and System Reliability
    Published online:
    13 January 2022
    Print publication:
    13 January 2022, pp 523-571

  • Summary

    Chapter 15 describes the use of the Bayesian network (BN) methodology for reliability assessment and updating of structural and infrastructure systems. A brief review of the BN as a graphical representation of random variables and an efficient framework for encoding their joint distribution and its updating upon observations is presented. D-separation rules describing the flow of information within the network upon observation of random variables are described and methods are presented for discretizing continuous random variables, thus allowing the use of efficient algorithms applicable to BNs with discrete nodes. Efficient BN models for components, systems, random fields, and seismic hazard are developed. For time- or space-variant problems, the dynamic Bayesian network is introduced. This model is used in conjunction with structural reliability methods (FORM, SORM, simulation) to develop enhanced BNs to solve reliability problems for structures under time-varying loads. Detailed examples are presented, including post-earthquake risk assessment of a spatially distributed infrastructure system and reliability assessment of a deteriorating structure under stochastic loads. The chapter concludes with a discussion of the potential of the BN as a tool for near-real-time risk assessment and decision support for constructed facilities, and the need for further research and development to realize this potential.

  • Executive function and other cognitive deficits are distal risk factors of generalized anxiety disorder 9 years later

  • Nur Hani Zainal, Michelle G. Newman
  • Journal:
    Psychological Medicine / Volume 48 / Issue 12 / September 2018
    Published online by Cambridge University Press:
    11 December 2017, pp. 2045-2053
  • Objective

    The cognitive model (Hirsch & Mathews, 2012) and attentional control theory (Eysenck & Derakshan, 2011) postulate that compromised executive function (EF) and other cognitive constructs are negatively linked to increased excessive and uncontrollable worry, the core symptom of generalized anxiety disorder (GAD). However, the prospective link between neuropsychological constructs and GAD are not well understood.

    Methods

    A nationally representative sample of 2605 community-dwelling adults whose average age was 55.20 (s.d. = 11.41, range 33–84; 56.31% females) participated at baseline and 9-year follow-up. Baseline neuropsychological function and symptoms were measured using the Brief Test of Adult Cognition by Telephone and Composite International Diagnostic Interview – Short Form. Multivariate Poisson and negative binomial regression analyses were conducted with 11 baseline covariates entered simultaneously: age, gender, years of formal education, perceived control, hypertension/diabetes, body mass index, exercise status, as well as GAD severity, panic disorder severity, and depression severity. Those with baseline GAD were also removed.

    Results

    Lower Time 1 composite global cognition z-score independently predicted higher Time 2 GAD severity and diagnosis [odds ratio (OR) 0.60, 95% confidence interval (CI) 0.40–0.89, p = 0.01]. Poor inhibition, set-shifting, working memory (WM) updating, inductive reasoning, and global cognition sequentially forecasted heightened GAD. However, processing speed, verbal WM, verbal fluency, and episodic memory did not predict future GAD.

    Conclusion

    Global cognition, inductive reasoning, inhibition, set-shifting, and WM updating EF impairments may be distal risk factors for elevated GAD nearly a decade later.