Head Canting in Paintings: An Historical Study

Head canting, a lateral shift of the head toward the shoulder axis, was examined in 1498 figures in the complete works of 11 painters from the XIV to the XX century: Martini, van Eyck Hubert and Jan, Holbein, Carracci, Velazquez, Rembrandt, Degas, Cèzanne, Klimt, and Modigliani. All figures (up to 9 in any one painting) that were not in complete profile and that were not depicted bowing or shifting their bodies were selected for analysis. Our analysis found a higher frequency (49%) of head canting in paintings than previously reported in naturalistic settings. Head canting was significantly higher in female figures than male figures. If a figure's head was facing laterally, head canting was more likely to be to the contralateral side. Head canting was lower in older figures than in children, youths, and adults. The highest level of head canting was seen in religious and mythological figures. Head canting was lower in figures of artists and professionals and virtually absent in depictions of nobles. Figures in pose were depicted with less head canting than those in natural settings. Head canting was lower in figures gazing toward the observer. Single-figure portraits head canted less than subjects in multiple-figure paintings. Author analysis revealed that head canting was pronounced in painters of religious subjects and in modern painters, whereas its degree was reduced in official portrait painters. These results are discussed in terms of dominance theory.     

Using Expert Models in Human Reliability Analysis—A Dependence Assessment Method Based on Fuzzy Logic

In human reliability analysis (HRA), dependence analysis refers to assessing the influence of the failure of the operators to perform one task on the failure probabilities of subsequent tasks. A commonly used approach is the technique for human error rate prediction (THERP). The assessment of the dependence level in THERP is a highly subjective judgment based on general rules for the influence of five main factors. A frequently used alternative method extends the THERP model with decision trees. Such trees should increase the repeatability of the assessments but they simplify the relationships among the factors and the dependence level. Moreover, the basis for these simplifications and the resulting tree is difficult to trace. The aim of this work is a method for dependence assessment in HRA that captures the rules used by experts to assess dependence levels and incorporates this knowledge into an algorithm and software tool to be used by HRA analysts. A fuzzy expert system (FES) underlies the method. The method and the associated expert elicitation process are demonstrated with a working model. The expert rules are elicited systematically and converted into a traceable, explicit, and computable model. Anchor situations are provided as guidance for the HRA analyst's judgment of the input factors. The expert model and the FES‐based dependence assessment method make the expert rules accessible to the analyst in a usable and repeatable way, with an explicit and traceable basis.     

A Critical Discussion and Practical Recommendations on Some Issues Relevant to the Nonprobabilistic Treatment of Uncertainty in Engineering Risk Assessment

Models for the assessment of the risk of complex engineering systems are affected by uncertainties due to the randomness of several phenomena involved and the incomplete knowledge about some of the characteristics of the system. The objective of this article is to provide operative guidelines to handle some conceptual and technical issues related to the treatment of uncertainty in risk assessment for engineering practice. In particular, the following issues are addressed: (1) quantitative modeling and representation of uncertainty coherently with the information available on the system of interest; (2) propagation of the uncertainty from the input(s) to the output(s) of the system model; (3) (Bayesian) updating as new information on the system becomes available; and (4) modeling and representation of dependences among the input variables and parameters of the system model. Different approaches and methods are recommended for efficiently tackling each of issues (1)?(4) above; the tools considered are derived from both classical probability theory as well as alternative, nonfully probabilistic uncertainty representation frameworks (e.g., possibility theory). The recommendations drawn are supported by the results obtained in illustrative applications of literature.     

Tests for noninferiority trials with binomial endpoints: A guide to modern and quasi‐exact methods for biomedical researchers

Applied statisticians and pharmaceutical researchers are frequently involved in the design and analysis of clinical trials where at least one of the outcomes is binary. Treatments are judged by the probability of a positive binary response. A typical example is the noninferiority trial, where it is tested whether a new experimental treatment is practically not inferior to an active comparator with a prespecified margin δ. Except for the special case of δ = 0, no exact conditional test is available although approximate conditional methods (also called second‐order methods) can be applied. However, in some situations, the approximation can be poor and the logical argument for approximate conditioning is not compelling. The alternative is to consider an unconditional approach. Standard methods like the pooled z‐test are already unconditional although approximate. In this article, we review and illustrate unconditional methods with a heavy emphasis on modern methods that can deliver exact, or near exact, results. For noninferiority trials based on either rate difference or rate ratio, our recommendation is to use the so‐called E‐procedure, based on either the score or likelihood ratio statistic. This test is effectively exact, computationally efficient, and respects monotonicity constraints in practice. We support our assertions with a numerical study, and we illustrate the concepts developed in theory with a clinical example in pulmonary oncology; R code to conduct all these analyses is available from the authors.     

Do ambiguity avoidance and the comparative ignorance hypothesis depend on people’s affective reactions?

Previous work has showed that people are averse to ambiguity and prefer to bet on known probabilities over unknown probabilities. There is also evidence that ambiguity aversion is stronger in comparative contexts rather than in non-comparative contexts. In the present paper we suggest that ambiguity aversion depends on people’s affective reactions and therefore the effect is more evident in comparative contexts because the comparison between the clear and ambiguous alternatives leads to more positive affective reactions toward the former rather than the latter. The present study extends the previous findings while, at the same time, supporting the “comparative ignorance hypothesis”.     

A class of dynamic piecewise exponential models with random time grid

A novel fully Bayesian approach for modeling survival data with explanatory variables using the Piecewise Exponential Model (PEM) with random time grid is proposed. We consider a class of correlated Gamma prior distributions for the failure rates. Such prior specification is obtained via the dynamic generalized modeling approach jointly with a random time grid for the PEM. A product distribution is considered for modeling the prior uncertainty about the random time grid, turning possible the use of the structure of the Product Partition Model (PPM) to handle the problem. A unifying notation for the construction of the likelihood function of the PEM, suitable for both static and dynamic modeling approaches, is considered. Procedures to evaluate the performance of the proposed model are provided. Two case studies are presented in order to exemplify the methodology. For comparison purposes, the data sets are also fitted using the dynamic model with fixed time grid established in the literature. The results show the superiority of the proposed model.     

Italian Social Enterprises at the Crossroads: Their Role in the Evolution of the Welfare State

This paper investigates the relationship between the emergence of social enterprises (SEs) and the historical development of the Italian welfare state. Our research offers a comprehensive overview of the internal and external influences that shaped the constitutive relations between the welfare state and SEs. A qualitative methodology based on semi-structured interviews and focus groups has been adopted. This study suggests that two interconnected dynamics—the emergence of new social needs being answered by private organisations and the increased prominence of third sector actors during the privatisation of the welfare state—shaped the co-evolution of the welfare state and SEs in Italy. The study also suggests that the emergence and evolution of Social Enterprises in the years leading up to 2001 was mainly a bottom-up phenomena stemming from the actions of citizens setting up private organisations (often cooperatives) to answer to social problems created by new social needs and the structural reform of the welfare state. After 2001 especially with the new law on SEs in 2016, the evolution of SEs seems to have been increasingly influenced by the surrounding ecosystem of actors and supranational policy discourses rather than SEs themselves.     

Probability and Possibility‐Based Representations of Uncertainty in Fault Tree Analysis

Expert knowledge is an important source of input to risk analysis. In practice, experts might be reluctant to characterize their knowledge and the related (epistemic) uncertainty using precise probabilities. The theory of possibility allows for imprecision in probability assignments. The associated possibilistic representation of epistemic uncertainty can be combined with, and transformed into, a probabilistic representation; in this article, we show this with reference to a simple fault tree analysis. We apply an integrated (hybrid) probabilistic‐possibilistic computational framework for the joint propagation of the epistemic uncertainty on the values of the (limiting relative frequency) probabilities of the basic events of the fault tree, and we use possibility‐probability (probability‐possibility) transformations for propagating the epistemic uncertainty within purely probabilistic and possibilistic settings. The results of the different approaches (hybrid, probabilistic, and possibilistic) are compared with respect to the representation of uncertainty about the top event (limiting relative frequency) probability. Both the rationale underpinning the approaches and the computational efforts they require are critically examined. We conclude that the approaches relevant in a given setting depend on the purpose of the risk analysis, and that further research is required to make the possibilistic approaches operational in a risk analysis context.     

Stock Exchange Markets in Hong Kong: Structure and Main Problems

With reference to a previous analysis of the characteristics and morphology of the stock markets of Mainland China (Shanghai and Shenzhen), the study aims at completing the overview of the main Asian stock exchanges (excluding Japan), by examining the Hong Kong stock exchange. After a review of the main literature, the paper considers the historical-legislative process that has defined the current organizational-functional structure of the market. The analysis also shows the main statistical data of the market (number of listed companies, trading volume, performance of the main indices, etc.). For every considered phenomenon, the study suggests plausible explanations. The paper also provides further considerations about the main issues of the market, through a comparison with the stock exchanges of Mainland China.     

Italian Adult Gambling Behavior: At Risk and Problem Gambler Profiles

The present study examined adult gambling behaviours from a local perspective in order to assess the adult at risk and problem gambler’s profile stratified by genre and by different forms of game. 4773 Italian adults from 18 to 94 years old were administered a survey to assess socio-cultural information related to gambling behaviour and the SOGS to evaluate gambling behaviour severity. Logistic regression evidenced that both at risk and problem gamblers are associated with male gender, players that use to play to more than one game, gambling with strategy-based games. People with a gambler father or both parents who used to gamble were significantly more associated with problem gambling behaviour than participants with non-gambler parents. These results present adult profiles of at risk and problem providing a more clear understanding about the relationships between gambling behavior severity and type of gambling.