The positivity scale: Concurrent and factorial validity across late childhood and early adolescence

Despite the well-established protective functions of positivity (i.e., a dispositional selfevaluative tendency to view oneself, life, and future under a positive outlook) from middle adolescence to old age, its reliable assessment and contribution to a proper psychological functioning have received little attention during previous developmental phases. In this article, we aimed to evaluate the psychometric properties and construct validity of the eight-item Positivity Scale (P Scale; Caprara et al., 2012) during late childhood and early adolescence in a sample of British students (N = 742; 48% boys) from both primary (M age = 10.75, SD = 0.52) and secondary schools (M age = 13.38 years, SD = 0.94). First, results from confirmatory factor analysis (CFA) attested to the plausibility of the hypothesized 1-factor structure of the P Scale in a revised CFA model including the correlation between the residuals of two items similar in their wording. Next, we found evidence for strong (scalar) measurement invariance of the P Scale across late childhood and early adolescence as well as for its concurrent validity as indicated by expected relations of positivity to indicators of adjustment (i.e., prosocial behavior) and maladjustment (i.e., externalizing and internalizing problems). Overall, these findings support the concurrent and factorial validity of the P Scale as a short self-report instrument to measure children's tendency to view their experience from a positive stance. We discuss the implications of our results for improving the wording of the items composing P Scale as well as for understanding the dispositional mechanisms conducive to psychological health and wellbeing across late childhood and early adolescence

Conspiracy beliefs, regulatory self-efficacy and compliance with COVID-19 health-related behaviors: The mediating role of moral disengagement

Although recent studies on the 2019 coronavirus disease (COVID-19) have highlighted the negative effects of moral disengagement on intentions to comply with COVID-19 containment measures, little is known about the mediating role of moral disengagement in the relationship between regulatory self-efficacy in complying with the containment measures, beliefs in conspiracy theories and compliance with COVID-19 health-related behaviors. Data were collected from 1164 young adults (women, N = 796; 68.4%; mean age 25.60 ± 4.40 years) who completed an online survey from 15th May to 22nd June 2021. Results of the multi-group path analyses indicated that higher beliefs in conspiracy theories were associated with lower compliance with COVID-19 health-related behaviors, whereas higher self-efficacy beliefs in complying with the containment measures were associated with higher compliance with COVID-19 health-related behaviors. Moral disengagement significantly mediated the associations between beliefs in conspiracy theories, regulatory self-efficacy, and compliance with COVID-19 health-related behaviors. Finally, the tested model was gender-invariant. Findings suggest that public health authorities and social care professionals should promote interventions aimed at improving regulatory self-efficacy, emphasizing the moral significance of respecting or ignoring the recommended COVID-19 measures (e.g., physical distance in public), and enhancing people's concern for the potential harms of their immoral actions

Novel Multi‐Vehicle Motion‐Based Model of Trolleybus Grids towards Smarter Urban Mobility

Trolleybus systems are resurfacing as a steppingstone to carbon-neutral urban transport. With an eye on smart city evolution, the study and simulation of a proper monitoring system for trolleybus infrastructures will be essential. This paper merges the authors’ engineering knowledge and sources available in the literature on designing and modeling catenary-based electric traction networks and performs a critical review of them to lay the foundations for proposing possible optimal alternatives. A novel multi-vehicle motion-based model of the DC catenary system is then devised and simulated in Matlab-Simulink, which could prove useful in predicting possible technical obstacles arising from the next-future introduction of smart electric traction grids, inevitably featuring greater morphological intricacy. The modularity property characterizing the created model allows an accurate, detailed, and flexible simulation of sophisticated catenary systems. By means of graphical and numerical results illustrating the behavior of the main electrical line parameters, the presented approach demonstrates today’s obsolescence of conventional design methods used so far. The trolleybus network of the city of Bologna was chosen as a case study

Efficient management of industrial electric vehicles by means of static and dynamic wireless power transfer systems

Industrial companies are moving toward the electrification of equipment and processes, in line with the broader energy transition taking place across the economy. Particularly, the energy efficiency and, consequently, the reduction of environmental pollution of intralogistics activities have become a competitive element and are now an actual research and development objective. A wireless power transfer is a contactless electrical energy transmission technology based on the magnetic coupling between coils installable under the ground level and a coil mounted under the vehicle floor, and it represents an excellent solution to decrease the demand for batteries by reducing vehicle downtimes during the recharge. This work aims to define a methodology to determine the optimal positioning of wireless charging units across the warehouse, both for static and dynamic recharging. To this aim, firstly, a mathematical model of the warehouse is proposed to describe transfers and storage/retrieval operations executed by the forklifts. Then, an integer linear programming problem is applied to find the best possible layout of the charging infrastructures. The optimal solution respects the energetic requirements given by the customer and minimizes the overall system cost. The proposed approach was applied to optimize the installation in a real-size warehouse of a tire manufacturing company. Several scenarios were computer generated through discrete event simulation in order to test the optimizer in different warehouse conditions. The obtained results show that integrated dynamic and static WPT systems ensure a constant state of charge of the electric vehicles during their operations

Catenary-Powered Electric Traction Network Modeling: A Data-Driven Analysis for Trolleybus System Simulation

In the context of smart cities, direct current overhead contact lines, usually adopted to power urban transportation systems such as trolleybuses, tramways, metros, and railways, can serve as a backbone to connect different modern emerging technologies. Among these, in-motion charging (IMC) trolleybuses with on-board batteries are expected to be very impactful on the DC network’s power flow and may require specific voltage and current control. These factors motivate the development of a simulation tool able to emulate these devices’ absorption and their effect on the supply infrastructure. The main innovative value of the work is to improve a simulation model of a trolleybus grid through a data-driven approach by using measurements of voltage and current output from a traction substation. The measurements are essential for understanding the behavior of vehicle weight variation throughout the day. Thanks to this information, a characterization of the current draw by conventional trolleybuses and IMC trolleybuses is then provided for each trolleybus route in a specific power section of the Bologna trolleybus system. By integrating the variation in vehicle weight within the model, a simulation of a possible daily operation of a trolleybus feeding section has been performed, obtaining a 7% error between the daily energy calculated from the simulation and that obtained through measurements. This analysis demonstrates the feasibility of the adopted simulation tool, which can also be used to evaluate additional hypothetical trolleybus operation scenarios. One of these possible scenarios considers IMC vehicles, and it is also evaluated in this paper

Smart Charging for Electric Car-Sharing Fleets Based on Charging Duration Forecasting and Planning

Electric car-sharing (ECS) is an increasingly popular service in many European cities. The management of an ECS fleet is more complex than its thermal engine counterpart due to the longer ”refueling“ time and the limited autonomy of the vehicles. To ensure adequate autonomy, the ECS provider needs high-capacity charging hubs located in urban areas where available peak power is often limited by the system power rating. Lastly, electric vehicle (EV) charging is typically entrusted to operators who retrieve discharged EVs in the city and connect them to the charging hub. The timing of the whole charging process may strongly differ among the vehicles due to their different states of charge on arrival at the hub. This makes it difficult to plan the charging events and leads to non-optimal exploitation of charging points. This paper provides a smart charging (SC) method that aims to support the ECS operators’ activity by optimizing the charging points’ utilization. The proposed SC promotes charging duration management by differently allocating powers among vehicles as a function of their state of charge and the desired end-of-charge time. The proposed method has been evaluated by considering a real case study. The results showed the ability to decrease charging points downtime by 71.5% on average with better exploitation of the available contracted power and an increase of 18.8% in the average number of EVs processed per day

Facing the Pandemic in Italy: Personality Profiles and Their Associations With Adaptive and Maladaptive Outcomes

The negative impact of the COVID-19 pandemic on individuals’ psychosocial functioning was widely attested during the last year. However, the extent to which individual differences are associated with adaptive and maladaptive outcomes during quarantine in Italy remains largely unexplored. Using a person-oriented approach, the present study explored the association of personality profiles, based on three broad individual dispositions (i.e., positivity, irritability, and hostile rumination) and two self-efficacy beliefs in the emotional area (i.e., expressing positive emotions and regulating anger emotion), with adaptive and maladaptive outcomes during the first Italian lockdown (March–June 2020). In doing so, we focused also on how different age groups (i.e., young adults and adults) differently faced the pandemic. The study was conducted through an online survey from May to June 2020 and included 1341 participants living in Italy, divided into two groups: 737 young adults aged 18–35 and 604 adults aged 36–60 years old. Latent Profile Analysis identified three personality profiles: resilient, vulnerable, and moderate. A subsequent path analysis model showed that the resilient profile was positively associated with prosocial behavior as an indicator of adaptive outcome, and negatively associated with three maladaptive outcomes: interpersonal aggression, depressive symptoms, and anxiety problems. Contrarily, the vulnerable profile resulted negatively associated with prosocial behavior and positively associated with the three maladaptive outcomes. Finally, regarding age group differences, young adults belonging to the vulnerable profile showed a greater association especially with interpersonal aggression, depression, and anxiety problems, as compared to adults belonging to the same profile. Overall, the results of the present study highlighted the importance to analyze individual functioning during an isolation period by using a person-oriented approach. Findings evidenced the existence of three different profiles (i.e., Resilient, Vulnerable, and Moderate) and subsequent path analysis revealed, especially for the vulnerable profile and young adults, a greater maladaptive consequence of the quarantine. The practical implications will be discussed

Uncertainty Quantification for SAE J2954 Compliant Static Wireless Charge Components

The present work aims at quantifying how, and how much, the uncertainties on the components and material parameters of a wireless power transfer (WPT) system for the static charge of electric vehicles affect the overall efficiency and functionality of the final produced device. With the aim of considering the perspective of a possible industrial developer, the parameters selected for the uncertainty quantification are chosen to be the capacitance values of the compensation capacitors and the electromagnetic material parameters used for the construction of the magnetic structure of a WPT system, i.e. the parameters of the elements to be purchased. The analysis is based on a standard system among the ones provided by the current SAE J2954 recommended practice

Smartphone and social network addiction in early adolescents: The role of self-regulatory self-efficacy in a pilot school-based intervention

Background: Youths' online problematic behaviors, such as smartphone or social network sites (SNS) addiction, gained increasing attention nowadays, due to their impact on concurrent and later adjustment, such as emotional and/or behavioral problems, academic impairments, or relational issues. Aims: This study aims to evaluate the effectiveness of a pilot school-based intervention to contrast online addictive behaviors while fostering adolescents' self-regulative abilities. Materials & Methods: The intervention started in January 2022 in an Italian junior high school located in Rome, and consisted of four meetings with students. A total sample of 462 15-year-old adolescents (Mage = 15.2; SD = 0.50; 41% females; Ncontrol = 214; Nintervention = 248) was considered. Within the latent difference score framework, we examined short-term changes from the pre-to-the-postintervention levels of SNS and smartphone addiction, and self-regulatory self-efficacy (SRSE) beliefs as a possible booster of the intervention's effectiveness. Results: Results showed a significant decrease in both online addictions (SNS and smartphone addiction), controlling for age, gender, sexual orientation, and socioeconomic status, because of the short-term efficacy of the project. The buffering effect of SRSE beliefs was further supported. Conclusion: These findings emphasized the usefulness of promoting youths' self-regulative beliefs to contrast problematic tendencies, according to a Positive Youth Development perspective which focused on resources rather than only on the prevention of negative outcomes for youths' adjustment

Analysis of dynamic wireless power transfer systems based on behavioral modeling of mutual inductance

This paper proposes a system-level approach suitable to analyze the performance of a dynamic Wireless Power Transfer System (WPTS) for electric vehicles, accounting for the uncertainty in the vehicle trajectory. The key-point of the approach is the use of an analytical behavioral model that relates mutual inductance between the coil pair to their relative positions along the actual vehicle trajectory. The behavioral model is derived from a limited training data set of simulations, by using a multi-objective genetic programming algorithm, and is validated against experimental data, taken from a real dynamic WPTS. This approach avoids the massive use of computationally expensive 3D finite element simulations, that would be required if this analysis were performed by means of look-up tables. This analytical model is here embedded into a system-level circuital model of the entire WPTS, thus allowing a fast and accurate analysis of the sensitivity of the performance as the actual vehicle trajectory deviates from the nominal one. The system-level analysis is eventually performed to assess the sensitivity of the power and efficiency of the WPTS to the vehicle misalignment from the nominal trajectory during the dynamic charging process