Risk assessment for handling hazardous substances within the European industry: Available methodologies and research streams

After the Seveso disaster occurred more than 40 years ago, there has been an increasing awareness of the potential impacts that similar accident events can occur in a wide range of process establishments, where the handling and production of hazardous substances pose a real threat to society and the environment. In these industrial sites denominated “Seveso sites,” the urgent need for an effective strategy emerged markedly to handle hazardous activities and to ensure safe conditions. Since then, the main challenging research issues have focused on how to prevent such accident events and how to mitigate their consequences leading to the development of many risk assessment methodologies. In recent years, researchers and practitioners have tried to provide useful overviews of the existing risk assessment methodologies proposing several reviews. However, these reviews are not exhaustive because they are either dated or focus only on one specific topic (e.g., liquefied natural gas, domino effect, etc.). This work aims to overcome the limitations of the current reviews by providing an up-to-date and comprehensive overview of the risk assessment methodologies for handling hazardous substances within the European industry. In particular, we have focused on the current techniques for hazards and accident scenarios identification, as well as probability and consequence analyses for both onshore and offshore installations. Thus, we have identified the research streams that have characterized the activities of researchers and practitioners over the years, and we have then presented and discussed the different risk assessment methodologies available concerning the research stream that they belong to.     

Legalization and human capital accumulation

This paper presents new evidence regarding the effects of legalization on the training of immigrants who were granted legal status through the US Immigration Reform and Control Act (IRCA) of 1986. Our findings point to a large increase in the immigrants’ incidence of training relative to comparable groups of natives following legalization. While training gains are higher for males, wage gains are higher for females. We also show that an important part of these changes in labor market outcomes occurs through occupation changes by newly legalized immigrants.     

Contextual Variation in Stereotype Content: An Investigation of Children's Central Tendency and Group Variability Judgements

Drawing upon self‐categorization theory, we predicted that the content of children's stereotypes concerning the gender ingroup would be contextually variable. Two studies are reported, each looking at five‐, seven‐, and 10‐year‐old children's stereotypes of the gender in‐group in two different contexts. Study 1 examined judgements of the perceived central tendency of the in‐group on specified dimensions. Study 2 addressed judgements of perceived variability within the gender in‐group on the same dimensions. Overall multivariate analysis of the data indicated that central tendency judgements were influenced by the context in which a group is considered, but that group variability judgements were not. Individual‐level analyses showed that the most typical pattern of response over the two conditions, in both Studies 1 and 2, was for children to provide consistent rather than varying judgements. However, in Study 1 (but not Study 2 ), among those children who changed their judgements, the nature of change was precisely as predicted by self‐categorization theory.     

Ambiguity Aversion,Robustness, and the Variational Representation of Preferences

We characterize, in the Anscombe–Aumann framework, the preferences for which there are a utility functionu on outcomes and an ambiguity indexc on the set of probabilities on the states of the world such that, for all acts f and g, . The function u represents the decision maker's risk attitudes, while the index c captures his ambiguity attitudes. These preferences include the multiple priors preferences of Gilboa and Schmeidler and the multiplier preferences of Hansen and Sargent. This provides a rigorous decision‐theoretic foundation for the latter model, which has been widely used in macroeconomics and finance.     

Brief Communications: Gender Differences in Gambling Progression

The authors compared 39 women and 38 men entering an outpatient treatment program for pathological gambling. They were diagnosed according to DSM-IV and selected by SOGS, followed by a semi-structured interview for demography and progression of the gambling behavior prior to treatment. Women were more often single (59% vs. 26%; p = .005) and started gambling significantly later than men (34.2 vs. 20.4 years; p < .001). The progression of the disorder was more than 2 times faster in women than in men. There was no difference in the age of seeking treatment (44.7 vs. 42.3 years). Findings from this study resemble gender differences in other addictions—in particular the faster progression among women—challenge pharmacodynamic hypotheses for this phenomenon, and suggest gender into account when devising treatment strategies for pathological gambling.     

Diverging patterns of interaction around news on social media: insularity and partisanship during the 2018 Italian election campaign

ABSTRACT

The paper considers how social media ecologies are affecting partisan engagement around political news and online attention economies by investigating the case of the 2018 Italian general election. By analyzing Twitter and Facebook interactions around political news in the lead-up to the election, we shed light on levels of insularity characterizing sources preferred by different partisan communities and investigate how specific patterns of active attention emerge around different sources and around stories proposing different framing of specific political actors. Our findings indicate that, on Twitter, sources mainly shared by supporters of populist parties (the Five Star Movement and the League) are characterized by higher levels of insularity compared to those shared by supporters of other parties. We also find that, on Facebook, news items published by highly insular sources receive a higher number of shares per comment. Finally, our analyses show that news presenting a positive framing of the Five Star Movement – the unique ‘cyber party’ in the system – receives a higher number of shares per comment compared to items presenting the Movement in a negative light, while the opposite is true for stories on all other political parties.     

Biopharmaceutical and chemical firms’ R&D disclosure,and cost of equity: The impact of the regulatory regime

Based on the proprietary costs theory, this paper aims to survey whether the regulatory regime (mandatory versus voluntary) of research and development (R&D) narrative disclosures impacts, by the means of a reduced information asymmetry, on the cost of equity capital. In order to construct a disclosure index to investigate the extent and the comprehensiveness of R&D information, the methodology adopted was the content analysis of 77 biopharmaceutical and chemical listed companies’ management reports from eight Western European countries across the period 2005–2009. Hence, we obtained an (unbalanced) panel data of 309 observations. The cost of capital has subsequently been regressed on the disclosure index. Results confirm a larger amount of R&D disclosures whereas information is more regulated, but they do not confirm an inverse relation with the cost of capital.     

Spatial Distribution of Social Inequality in the Metropolitan District of Quito,Ecuador

Social Indicators Research - Exploring the spatial variation of regional social inequality allows the design of public policies; therefore, this study analyzes this phenomenon in the Metropolitan...     

Algebraic Markov Bases and MCMC for Two-Way Contingency Tables

ABSTRACT.  The Diaconis–Sturmfels algorithm is a method for sampling from conditional distributions, based on the algebraic theory of toric ideals. This algorithm is applied to categorical data analysis through the notion of Markov basis. An application of this algorithm is a non-parametric Monte Carlo approach to the goodness of fit tests for contingency tables. In this paper, we characterize or compute the Markov bases for some log-linear models for two-way contingency tables using techniques from Computational Commutative Algebra, namely Gröbner bases. This applies to a large set of cases including independence, quasi-independence, symmetry, quasi-symmetry. Three examples of quasi-symmetry and quasi-independence from Fingleton ( Models of category counts , Cambridge University Press, Cambridge, 1984) and Agresti ( An Introduction to categorical data analysis , Wiley, New York, 1996) illustrate the practical applicability and the relevance of this algebraic methodology.