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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.

This chapter demonstrates how the reception, adaption and development of gender studies in Brazil and subsequent law reform have created a new theoretical field of feminist criminology with a Southern approach. During the 1980s, Brazilian literature discussed gender violence according to three theories: male domination (Chauí), patriarchal domination (Saffioti) and relational violence (Gregori). Gender theories were introduced and developed during the 1990s. Decolonial studies stressed the deeper intersection of gender with race, social class and other vectors of discrimination, which increases the vulnerability of minority women, particularly black and indigenous women. The increase in gender studies supported political feminist advocacy to promote law reform, such as the Maria da Penha Law, the criminalisation of femicide, reforms related to sexual violence and women in prison. Feminist criminology has both criticised law and used it to promote gender equality on society. Judicial practices indicate the conservative resistance of the juridical field to assimilating gender debates and feminist critical theories as a whole.

Data providers have been increasingly publishing content as linked data (LD) on the Web. This process includes guidelines (i.e. good practices) to publish, share, and connect data on the Web. Several people in different areas, for instance, sciences, medicine, governments and so on, use these practices to publish data. The LD community has been proposing many practices to aid the publication of data on the Web. However, discovering these practices is a costly and time-consuming task, considering the practices that are produced by the literature. Moreover, the community still lacks a comprehensive understanding of how these practices are used for publishing LD. Thus, the purpose of this paper is to investigate and better understand how best practices support the publication of LD as well as identifying to what extent they have been applied to this field.

The authors conducted a systematic literature review to identify the primary studies that propose best practices to address the publication of LD, following a predefined review protocol. The authors then identified the motivations for recommending best practices for publishing LD and looked for evidence of the benefits of using such practices. The authors also examined the data formats and areas addressed by the studies as well as the institutions that have been publishing LD.

In summary, the main findings of this work are: there is empirical evidence of the benefits of using best practices for publishing LD, especially for defining standard practices, integrability and uniformity of LD; most of the studies used RDF as data format; there are many areas interested in dissemination data in a connected way; and there is a great variety of institutions that have published data on the Web.

The results presented in this systematic review can be very useful to the semantic web and LD community, since it gathers pieces of evidence from the primary studies included in the review, forming a body of knowledge regarding the use best practices for publishing LD pointing out interesting opportunities for future research.