Varying levels of anomie in Europe: a multilevel analysis based on multidimensional IRT models

Recent years have seen increased attention paid to monitoring social anomie and its dependency on micro- and macro-factors. In this paper, we endorse the theorisation of social anomie as a complex, multidimensional and multilevel phenomenon. To ensure a rigorous measurement of the varying levels of social anomie in the European countries, the current study relies on a multilevel multidimensional item response theory model which explicitly accounts for the presence of a non-ignorable missing data mechanism. This unified approach makes it possible to specify an analytical model of links between anomie features and their determinants and to explore how the latent traits of interest are influenced by individual-level factors, as well as by country-level indicators. Additionally, to avoid misleading inferential conclusions, the proposed model takes into account the respondent’s omitting behaviour, assuming that the missingness mechanism is driven by a latent propensity to respond. Data used in this study have been collected in the 2010 wave of the European Social Survey. To reduce the computational complexities, a Bayesian specification of the MIRT model is provided and the parameter model estimates are obtained through MCMC algorithms.     

Evidence for multiple strategies in choice under risk

This paper describes an experimental study that yields evidence for the coexistence of two decision strategies of choice under risk. Under the first strategy, choices are made based on aspiration levels – a heuristic that simplifies risky decisions. Under the second strategy, which can be used when aspiration levels are not determinative, choices are made based on preferences for positive skewness. Our model fitting confirms the efficacy of a two-pronged approach that can marshal either strategy depending on specific features of the risky prospects under consideration.     

Green remnants are hotspots for bat activity in a large Brazilian urban area

Urbanization tends to remove or isolate green areas into fragments or restrict them to narrow corridors inserted in a matrix of buildings. Nevertheless, urban green areas may act as refuges for fauna and bats are among the animals able to use such habitats. Using bioacoustics we investigated the influence of green areas on the activity of insectivorous bats in the metropolitan area of Recife, a conurbation of 4 million people in the Atlantic forest of Northeastern Brazil. Bat activity was statistically higher in green areas, based on calls (t?=?2.5298, p?=?0.0165), but not on feeding buzzes (t?=?1.8132, p?=?0.0817) or social calls (t?=??1.5551, p?=?0.1329). Several species were able to persist in an urban matrix and calls were classified into 16 sonotypes, belonging to five families (Emballonuridae, Molossidae, Noctilionidae, Phyllostomidae and Vespertilionidae). However, activity was significantly more associated with areas with vegetation, indicating that green remnants are hotspots for bat activity. Our results indicate that most insectivorous bats have a biased use of the urban landscape and the maintenance of urban green areas is essential to preserve them and the environmental services they provide.     

IEA/WHO toolkit for WMSDs prevention: criteria and practical tools for a step by step approach

When studying WMSDs, several determinants and their interrelationship are considered as relevant. Hence the necessity of an "holistic" approach to prevention, especially when preparing technical rules and strategic plans. There is a strong request, from OSH agencies and operators, for developing "simple" tools for risk assessment and management. In this context WHO asked IEA to develop a "Toolkit for WMSD prevention". The paper presents one of the main contribution to this WHO project, focused on selecting tools at different level for hazard identification, risk estimation and management. Proposals are based on two essential criteria: Acting on a step-by-step approach; Taking into account the presence of multiple influencing factors. The proposals consider: A Basic Step devoted to hazard identification by operative "key-enter" questions, that can be operated also by non-experts. A First Step, (quick assessment), for identifying 3 possible conditions: acceptable; high risk present; more detailed analysis (via tools presented at second step) necessary. This step can be operated by non-experts with only some specific training. A Second Step, where recognized (i.e. from international standards or guidelines) tools for risk estimation are used. This step can be operated only by persons with some specific training.     

Higher Moments and Prediction‐Based Estimation for the COGARCH(1,1) Model

COGARCH models are continuous time versions of the well‐known GARCH models of financial returns. The first aim of this paper is to show how the method of prediction‐based estimating functions can be applied to draw statistical inference from observations of a COGARCH(1,1) model if the higher‐order structure of the process is clarified. A second aim of the paper is to provide recursive expressions for the joint moments of any fixed order of the process. Asymptotic results are given, and a simulation study shows that the method of prediction‐based estimating function outperforms the other available estimation methods.     

An Adaptive Simulation Framework for the Exploration of Extreme and Unexpected Events in Dynamic Engineered Systems

The end states reached by an engineered system during an accident scenario depend not only on the sequences of the events composing the scenario, but also on their timing and magnitudes. Including these additional features within an overarching framework can render the analysis infeasible in practical cases, due to the high dimension of the system state‐space and the computational effort correspondingly needed to explore the possible system evolutions in search of the interesting (and very rare) ones of failure. To tackle this hurdle, in this article we introduce a framework for efficiently probing the space of event sequences of a dynamic system by means of a guided Monte Carlo simulation. Such framework is semi‐automatic and allows embedding the analyst's prior knowledge about the system and his/her objectives of analysis. Specifically, the framework allows adaptively and intelligently allocating the simulation efforts preferably on those sequences leading to outcomes of interest for the objectives of the analysis, e.g., typically those that are more safety‐critical (and/or rare). The emerging diversification in the filling of the state‐space by the preference‐guided exploration allows also the retrieval of critical system features, which can be useful to analysts and designers for taking appropriate means of prevention and mitigation of dangerous and/or unexpected consequences. A dynamic system for gas transmission is considered as a case study to demonstrate the application of the method.     

Assessing Climate Change Impacts on Wildfire Exposure in Mediterranean Areas

We used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period 1981–2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981–2010, 2011–2040, and 2041–2070). Overall, the wildfire simulations showed very slight changes in flame length, while other outputs such as burn probability and fire size increased significantly in the second future period (2041–2070), especially in the southern portion of the study area. The projected changes fuel moisture could result in a lengthening of the fire season for the entire study area. This work represents the first application in Europe of a methodology based on high resolution (250 m) landscape wildfire modeling to assess potential impacts of climate changes on wildfire exposure at a national scale. The findings can provide information and support in wildfire management planning and fire risk mitigation activities.     

Concerns,Challenges, and Directions of Development for the Issue of Representing Uncertainty in Risk Assessment

In the analysis of the risk associated to rare events that may lead to catastrophic consequences with large uncertainty, it is questionable that the knowledge and information available for the analysis can be reflected properly by probabilities. Approaches other than purely probabilistic have been suggested, for example, using interval probabilities, possibilistic measures, or qualitative methods. In this article, we look into the problem and identify a number of issues that are foundational for its treatment. The foundational issues addressed reflect on the position that “probability is perfect” and take into open consideration the need for an extended framework for risk assessment that reflects the separation that practically exists between analyst and decisionmaker.     

An Unbalance Adjustment Method for Development Indicators

This paper analyzes some aggregation aspects of the procedure for constructing a composite index on a multidimensional socio-economic phenomenon such as development, the main focus being on the unbalance among individual dimensions. First a theoretical framework is set up for the unbalance adjustment of the index. Then an aggregation function is proposed that takes unbalance among development dimensions into account; a separate index is also introduced that measures the unbalance itself. Finally the dataset of the Index of African Governance for the year 2007 is used to test this method and compare it against the weighted arithmetic mean of variables with relation to the measured values of unbalance, yielding significantly different results for ratings and rankings, which in addition show negative correlations with the unbalance adjustment values. The changes ensuing from the adjustment are commented for some countries.     

Uncertainty Analysis in Fault Tree Models with Dependent Basic Events

In general, two types of dependence need to be considered when estimating the probability of the top event (TE) of a fault tree (FT): “objective” dependence between the (random) occurrences of different basic events (BEs) in the FT and “state‐of‐knowledge” (epistemic) dependence between estimates of the epistemically uncertain probabilities of some BEs of the FT model. In this article, we study the effects on the TE probability of objective and epistemic dependences. The well‐known Frèchet bounds and the distribution envelope determination (DEnv) method are used to model all kinds of (possibly unknown) objective and epistemic dependences, respectively. For exemplification, the analyses are carried out on a FT with six BEs. Results show that both types of dependence significantly affect the TE probability; however, the effects of epistemic dependence are likely to be overwhelmed by those of objective dependence (if present).