Sharing of emotional memories with a listener: differences between adolescents and emerging adults

Research demonstrated a strong influence of personal narratives on emotions linked to memories. However, few studies considered shared narratives and the role of listener’s behavior, especially in adolescence and emerging adulthood. This paper aims to explore the impact of listening attitude on emotions related to memories in adolescents and emerging adults. A total of 157 participants were asked to choose a memory: in the experimental conditions (Attentive Listening, AL vs. Detached Listening, DL), they narrated it to a listener, in the Control Group, they internally reflected about it. Emotions linked to memory at the first time, to narrative/reflection, and to memory after 15 days were measured, as well as the perception of listener’s behavior. Results showed that participants perceived the differences of the listening, although adolescents perceived less listener’s detached stance. Moreover, among adolescents, positive emotions increased after narrative for both experimental conditions, instead, among emerging adults, only AL condition participants increased their positive emotions. Moreover, adults maintained the positive effects of narrative also after 15 days. Authors discussed the role of an empathic context and the adolescent egocentrism in shared narratives about personal memories.     

Geoadditive modeling for extreme rainfall data

Extreme value models and techniques are widely applied in environmental studies to define protection systems against the effects of extreme levels of environmental processes. Regarding the matter related to the climate science, a certain importance is covered by the implication of changes in the hydrological cycle. Among all hydrologic processes, rainfall is a very important variable as it is strongly related to flood risk assessment and mitigation, as well as to water resources availability and drought identification. We implement here a geoadditive model for extremes assuming that the observations follow a generalized extreme value distribution with spatially dependent location. The analyzed territory is the catchment area of the Arno River in Tuscany in Central Italy.     

Social services and deviation from the Bismarckian model in Italy: the absence of a nationwide trend of change

This article analyses the processes of deviation from the Bismarckian welfare model in Italy, with a focus on social assistance. The sector was reformed in 2000, with new service provision functions being assigned to local institutions and the affirmation of a universalistic principle of access. However, an analysis of social expenditure data and a review of the process of implementation of the reform demonstrate that many local governments have been unable to enact the innovation and that a homogeneous nationwide trend of deviation from the Bismarckian tradition is absent. This absence is explained by looking both at the local institutional arrangements that have historically characterized the different Italian territories and at the present relationships among national, regional, and local governments.     

A Quality Risk Management Model Approach for Cell Therapy Manufacturing

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell‐based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator‐introduced variations, and affected by heterogeneity of the processed organs/tissues and lot‐dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell‐based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo‐quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.     

Optimal use of two auxiliary variables in double sampling

Double sampling scheme is used when cheap auxiliary variables may be measured to improve the estimation of a finite population parameter. Several estimators for population mean, ratio of means and variance are available, when two dependent samples are drawn. However, there are few proposals for the case of independent samples. In this paper both cases of dependent and independent samples are dealt with. A general approach for estimating a finite population parameter is given, showing that all the proposed estimators are particular cases of the same general class. The minimum variance bound for any estimator in this class is provided (at the first order of approximation). Furthermore, an optimal estimator which reaches this minimum is found.     

Adjusting Stepwise p-Values in Generalized Linear Models

Stepwise methods for variable selection are frequently used to determine the predictors of an outcome in generalized linear models. Although it is widely used within the scientific community, it is well known that the tests on the explained deviance of the selected model are biased. This arises from the fact that the traditional test statistics upon which these methods are based were intended for testing pre-specified hypotheses; instead, the tested model is selected through a data-driven procedure. A multiplicity problem therefore arises. In this work, we define and discuss a nonparametric procedure to adjust the p-value of the selected model of any stepwise selection method. The unbiasedness and consistency of the method is also proved. A simulation study shows the validity of this procedure. Theoretical differences with previous works in the same field are also discussed.     

A Gender Lens on Quality of Life: The Role of Sense of Community,Perceived Social Support,Self-Reported Health and Income

Quality of life (QoL) refers to a subjective evaluation that is embedded in a cultural, social and environmental context. It is a multidimensional concept and its assessment covers four domains: physical health, psychological health, social relationships, and environment. Although many studies report on QoL, literature rarely addressed the question of the QoL predictors from a gender perspective. Present study aimed at investigating gender differences in the determinants of QoL. Specifically, gender was considered as a moderator in the relationship between predictors of QoL (i.e. socio-demographic characteristics, perceived health, income, social support and sense of community) and each dimension of QoL. 654 Italian adults participated in the study. Results show that men outscore women on the physical, the psychological and the environmental domains of QoL. Considering determinants of QoL, sense of community and self-reported health operate in a similar fashion for both genders. On the contrary, social support is more predictive for women’s QoL, whereas the income level is more significant for men’s QoL. Implications are discussed.     

Multi-phase sampling under cost constraints

Multi-phase sampling (M-PhS) scheme is useful when the interest is in the estimation of the population mean of an expensive variable strictly connected with other cheaper (auxiliary) variables. The MSE is an accuracy measure of an estimator. Usually it decreases as the sample size increases. In practice the sample size cannot become arbitrarily large for possible cost constraints. From a practical point of view it would be useful to know the sample sizes which guarantee the best accuracy of the estimates for fixed costs. These “optimum” sample sizes can be, in some cases, computable but not admissible. In other cases, they can be neither admissible nor computable. The main goal of this paper is to propose a solution for both these situations. It will be clear that in both situations the solution is to consider a M-PhS scheme with one or more phases less.     

Newborns' Perceptual Categorization for Closed and Open Geometric Forms

This study explored newborns' ability to perceive perceptual similarities between different exemplars of 2 broad classes of simple shapes: closed and open geometric forms. Three experiments were carried out using a visual paired‐comparison task. Evidence showed that, after familiarization either to closed‐shaped or to open‐shaped forms, newborns manifested a novelty preference for a novel‐category rather than for a familiar‐category exemplar (Experiment 1). This result could not be explained either as a consequence of the newborns' inability to discriminate between instances of the same category of simple geometric forms (Experiment 2), or as a consequence of a spontaneous preference for the novel‐category exemplars (Experiment 3). Overall, findings revealed that newborns are able to form broad categories of distinguishable geometric shapes by relying on the shapes' perceptual similarity.     

Mutual-Fund Benchmarking and Market Bubbles: A Behavioral Approach

Dynamics of equity risk premium is not directly measurable on the market. Numerous studies and empirical research analyse its volatility also considering the time span, concluding that the dynamics of equity risk premium over time is inversely proportional to the economic cycle. This study analyses the passive role that, implicitly, would place institutional investors in such a context. In reality, savings management is delegated to a small number of professional operators (institutional investors), as opposed to pure theoretical models in which every person can act directly on the market thus ensuring unlimited price elasticity. Institutional investors should be rational and completely informed so that they can assume an anticyclical position on the market. Thus, supply and demand should quickly smooth over emerging price pressures and avoid price bubbles. We analyse one possible explanation for this situation not to occur, namely, that professionals suffer from operational limits that prevent them from doing their job in the best possible way. Using empirical evidence from the Italian Stock Exchange (Comit Index), we conclude that three factors reduce the freedom of institutional investors to manage their portfolios – the market target size, the fund structure, and the benchmarking – and discuss some implications for each of them.