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The design of electrical machines includes the computation of several requirements and, in general, the improvement of one requirement implies in a degradation of another one: this is a typical multi‐objective scenario. The paper focuses on the multi‐optimization analysis of a special switched reluctance motor.

Two design requirements were analyzed: the average torque and the ripple torque. The electromagnetic field computation was performed by the finite element method and the torque was computed by the Coulomb's Virtual Work for several positions. This allows us to calculate the average torque and the ripple torque. Three different methods were used to obtain the Pareto set: a min‐max approach, the non‐dominated sorting genetic algorithm (NSGA) and the strength Pareto evolutionary algorithm (SPEA). In order to save the computation time, the objective functions (the average torque and the ripple torque) were replaced with surrogate functions. Kriging models were used as surrogate functions.

The evolutionary methods (NSGA and SPEA) have a similar performance. The min‐max has not the same performance. It could have the same performance only if some unconstrained optimization problems are solved before the multi‐objective optimization. The maximum relative deviation between the approximated function (Kriging model) and the same value calculated by the finite element method was equal to 0.8 percent for the average torque and 1.2 percent for the ripple torque. The ripple torque, considered as the difference between the maximum and the minimum values in the 0‐90° region, has reduced while its frequency has doubled. This last characteristic provides a better mechanical stability for the driven load because its inertia softens the ripple effects at the double the frequency. The optimized prototype presents higher torques in the region θ<0° and this allows the electronic drive to switch in a broader range rendering the motor operation more flexible.

The use of surrogate functions save the computation time with high accuracy. This is very important on the design of electrical machines, a typical multi‐objective scenario. Evolutionary methods seem to be well suited to solve this class of problem.

Vaping has become a prominent public health problem that has impacted young adults. The purpose of this study is to empirically examine the effects of different intrinsic and extrinsic motivations on young adults’ realization of excessive vaping and their intention to quit vaping.

A survey was used to collect data from 232 young vapers (primarily Generation Z and Millennials) to test the hypothesized relationships using a covariance-based structural equation model.

The findings of this study suggest that “realization of excessive vaping” is negatively associated with “sensation seeking” and positively associated with “deal proneness,” “environmental cues” and “negative repercussion.” The “intention to quit vaping” is negatively associated with “marketing cues” and positively associated with “alternative to smoking” and “environmental cues.” Finally, the “realization of excessive vaping” is positively associated with “intention to quit vaping.”

This study takes a two-dimensional approach to understand the complex motivations behind a relatively new addictive behavior – vaping. It contributes to the literature of addictive behavior, social cognitive theory and theory of planned behavior. Further, it has important implications for public policy and the marketing of addictive products to youths.

This study aims to present a novel framework of “communication-led behavioral intention” in an effort to aid in the process of planning and coordinating social marketing campaigns on difficult subjects that go against social conventions, including the proper postnatal nutrition practices.

The study followed a quasi-experimental research design. Health communications (public service announcements) were shown to the women aged 18–65 years and responses were collected using a quantitative questionnaire. Structural equation modeling with exploratory and confirmatory factor analyses was used to investigate the linkage between the factors that influence breastfeeding outcomes.

A strong positive impact of contextual communication was confirmed empirically on the behavioral intention to follow and recommend exclusive breastfeeding. Three communication-specific factors – “content quality,” “message clarity” and “belief in message” – were found to play a pivotal role in inducing the “behavioral intention.” These relationships were found to be mediated by “empathy” which is an emotional state experienced out of the respondent’s ability to sense the thoughts and feelings of the characters in the communication.

This study is one of the few attempts on measuring breastfeeding outcomes using theoretical constructs. The framework suggested in the study has a lot of potential in assisting practitioners and researchers to develop effective interventions on complex topics that challenge social norms. Further, this paper offers important insights on the women with limited decision-making capacity on breastfeeding and child care.