Osteoporosis in men: a case report

Osteoporosis in men is frequently not considered, underdiagnosed and often undertreated. In contrast with osteoporosis occurring in women, the genesis is frequently secondary (30-60%) with a complex diagnostic approach. A careful anamnesis and physical examination associated with laboratory and instrumental evaluation are necessary for an accurate diagnosis. The clinical case presented concerns a 70-year-old man with negative family history for osteoporosis and a personal history of depression, HBV carrier, and chronic obstructive pulmonary disease (COPD) in a heavy ex-smoker with history of alcoholism. The comprehensive geriatric evaluation allowed us to diagnose a multifactorially secondary osteoporosis associated to osteomalacia probably generated by the combination of alcohol abuse with consequent severe malnutrition, heavy smoking and COPD, physical inactivity and rapid weight loss

The value of visual inspections for emergency management of bridges under seismic hazard

One of the major problems in the aftermath of an earthquake is the management of the emergency inspection operations. Traffic restriction, including limited emergency operations or bridge closure due to safety concerns, may be issued to keep an appropriate level of safety. Visual inspections may be conducted to provide useful information on the damage state of the bridge and support the decision of imposing traffic restriction up to the complete closure of the bridge, or for allowing the immediate use of safe bridges after the event. The cost related to the inspection shall be at least balanced by the uncertainty reduction provided by the inspection data and the benefit is higher when the costs associated with taking a wrong management decision are high, but may be negligible if this is not the case. Practical tools and methods to forecast this benefit before collecting the information exist in classical decision theory, but are seldom applied by engineers. In this paper a framework based on the concept of Value of Information (VoI) from the pre-posterior Bayesian decision analysis is adopted and applied to the case study of a two span reinforced concrete bridge

On Decision Support for Sustainability and Resilience of Infrastructure Systems

An overview of selected contributions across the different sciences to sustainability and resilience research is provided and discussed. A general frame-work for supporting decisions for sustainable and resilient design and management of societal infrastructures is then proposed taking basis in Bayesian decision analysis and probabilistic systems performance modelling. A principal example for decision support at regulatory level is presented for a coupled system comprised of infrastructure, social, hazard and environmental subsystems. The infrastructure systems is modelled as multi-component Daniels system generating benefits over time after deduction of potential losses due to disturbance events. The societal system is represented in terms of the preparedness level with respect to respond, reorganize and rehabilitate functionality after disturbances and the environmental system is represented in terms of local and global scale constraints concerning acceptable emissions

The benefit of permanent monitoring for seismic emergency management

In this paper, a framework based on Value of Information (VoI) theory from pre-posterior Bayesian decision analysis is applied to the case of post-earthquake emergency management of traffic restrictions for a bridge. The decision context is the following: the operator of a bridge is concerned about the use of the structure in post-earthquake scenarios and wishes to know if it is worth to install a Structural Health Monitoring (SHM) system which gives information about the state of the bridge. The possible choices about traffic restrictions after the seismic event are Open or Close the bridge. The benefit of SHM is computed based on VoI and the influence of significant variables involved in the decisional framework is investigated

On the Probabilistic Characterization of Robustness and Resilience

Over the last decade significant research efforts have been devoted to the probabilistic modeling and analysis of system characteristics. Especially performance characteristics of systems subjected to random disturbances, such as robustness and resilience have been in the focus of these efforts and significant insights have been gained. However, as much of the undertaken research and developments aim to fulfill the particular needs of specific application areas and/or societal sectors somewhat diverging perspectives and approaches have emerged. In the present paper we take basis in recent developments in the modeling of robustness and resilience in the research areas of natural disaster risk management, socio-ecological systems and social systems and we propose a generic decision analysis framework for the modeling and analysis of systems across application areas. The proposed framework extends the concept of direct and indirect consequences and associated risks in probabilistic systems modeling formulated by the Joint Committee on Structural Safety (JCSS) to facilitate the modeling and analysis of resilience in addition to robustness and vulnerability. Moreover, based on recent insights in the modeling of robustness, a quantification of resilience is formulated utilizing a scenario based systems benefit modeling where resilience failure is associated with exhaustion of the capital accumulated by the system of time. The proposed framework and modeling concepts are illustrated with basis in a simple interlinked system model comprised by an infrastructure system, a governance system, a regulatory system and a geo-hazards system. It is shown how the robustness and the resilience of the interlinked system may be modeled and quantified, how robustness and resilience are influenced by the stochastic dependency structure of the disturbance events and corresponding resistances, how robustness and resilience depends on the capacity of the social system to plan for and respond to disturbances over time and how robustness and resilience interrelate

Resilience of systems by value of information and SHM

Critical infrastructure systems such as energy provision and distribution systems, transport systems and the built environment in general are subject to and sensitive to deterioration processes. Structural Health Monitoring (SHM) strategies have been increasingly employed as a means to detect deterioration, facilitate timely and efficient interventions – and thereby to enhance resilience of critical infrastructure. However, in specific situations, it is generally not obvious if and to what degree different SHM strategies are efficient and sufficient for enhancing the resilience of critical infrastructure systems. In response to this challenge, the present contribution puts forwards a novel approach, taking basis in the concept of value of information analysis from Bayesian pre-posterior decision. Utilizing a principal model framework we show how the proposed approach is implemented with due consideration of the resilience governing characteristics and interdependencies between infrastructure systems, social/organisational systems, regulatory systems, ecological systems as well as anthropological and geological hazard systems