Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.     

On Optimality of Bayesian Wavelet Estimators

Abstract.  We investigate the asymptotic optimality of several Bayesian wavelet estimators, namely, posterior mean, posterior median and Bayes Factor, where the prior imposed on wavelet coefficients is a mixture of a mass function at zero and a Gaussian density. We show that in terms of the mean squared error, for the properly chosen hyperparameters of the prior, all the three resulting Bayesian wavelet estimators achieve optimal minimax rates within any prescribed Besov space     for p  ≥ 2. For 1 ≤  p  < 2, the Bayes Factor is still optimal for (2 s +2)/(2 s +1) ≤  p  < 2 and always outperforms the posterior mean and the posterior median that can achieve only the best possible rates for linear estimators in this case.     

Group therapists' countertransference reactions to multiple deaths from aids

Group therapists for those with HIV Related Diseases are becoming the “professional” survivors of this world-wide epidemic. From their experiences we may learn a great deal more about the effects of multiple deaths on mental health care professionals. As therapists they are constantly eliciting and listening to the fears, hopes, agonies and terrors of those with this disease. They become the bereaved. Witnesses to the deaths of many of their group members, they struggle with a wide range of emotional responses while at the same time assisting surviving group members in their struggle to live with these deaths. Mourning reactions and countertransference phenomena are in abundance as these therapists grapple with these group processes. This article identifies and examines these therapists' responses by focusing on clinical illustrations drawn from their bi-weekly supervision sessions.     

Developing Age-Friendly Cities: Case Studies From Brussels and Manchester and Implications for Policy and Practice

Developing environments responsive to the aspirations of older people has become a major concern for social and public policy. Policies and programs directed at achieving “age-friendly” communities are considered to require a wide range of interventions, including actions at the level of the social and physical environment. This article compares the age-friendly approaches of two European cities, Brussels and Manchester, with a particular focus on policies and initiatives that promote active aging in an urban context. The article examines, first, the demographic, social, and multicultural contexts of Brussels and Manchester; second, the way in which both cities became members of the World Health Organization Global Network of Age-Friendly Cities and Communities; third, similarities and differences in the age-friendly approaches and actions adopted by both cities; and fourth, opportunities and barriers to the implementation of age-friendly policies. The article concludes by discussing the key elements and resources needed to develop age-friendly cities.