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Penn World Tables (PWT) data on output measured at international prices are the data most frequently used in cross‐country growth regressions. These data are subject to revision, and the amendments can be substantial for a minority of countries, although negligible for most. The purpose of this paper is to investigate the effect of data revisions on research results using the data.

Using Hanushek and Kimko's analysis of the relationship between growth and schooling quality and Sala‐i‐Martin's tests of model selection, the authors investigate how much the results of cross‐country growth regressions vary if the most recent vintage (6.2) of PWT data is used, rather than the previous vintage (6.1).

The variation is substantial enough to imply significant differences in research results using different vintages of the PWT data.

The results reinforce the case for examining the sensitivity of growth regressions to outliers, which may be subject to subsequent data revision that might substantially affect the conclusions.

Previous research has identified significant revisions between successive vintages of PWT growth data, but has implied that this is not likely to affect the results of cross‐country growth regressions based on long‐run averages rather than on annual data. The findings suggest that this is not necessarily the case.

In the introduction to Beyond Bombshells, Jeffrey A Brown lists examples of blockbuster films with leading female heroines and proclaims that they have ‘challenged the assumption that action movies are a strictly male domain’ (2015, p. 6). His examples include, but are not limited to, the Kill Bill films (2003, 2005), The Hunger Games (2012), Brave (2012) and Snow White and the Huntsman (2012), all of which demonstrate the rise in popularity of the woman-led action film. However, these films also demonstrate a reluctance of the action film to detach itself from masculinity. Despite their female leads, these action films still foreground masculinity. The films have darker colour palettes and their female leads tend to have masculine coded traits and hobbies, suggesting that women can succeed within this genre only by distancing themselves from femininity.

This chapter analyses the subversion of the genre conventions of action by exploring the use of feminine objects in director Cathy Yan's Birds of Prey: And the Fantabulous Emancipation of One Harley Quinn (2020). Written and directed by women, Birds of Prey is a notable turn in the action genre as it makes use of feminine objects (hair ties, glitter, fashion, jewellery) within action sequences that don't just allow a female presence within the action, but centre feminine power. By relocating femininity and masculinity to objects rather than bodies, new ways of understanding how genre conventions are not fixed but fluid are opened up for further exploration.

The purpose of this paper is to propose a robust method to estimate the parameters of Jiles‐Atherton model of ferromagnetic hysteresis by fitting the model to symmetrical hysteresis loops. The performance of the method is evaluated by both theoretical and experimental data.

Jiles‐Atherton model with five parameters describes the hysteretic behaviour of ferromagnetic materials. To calculate the model parameters, the most common data displaying the hysteresis features are the hysteresis loops stimulated by symmetrical steady state excitations, e.g. sinusoidal sources. Using the characteristic equations at specific points on these hysteresis loops, the Jiles‐Atherton model parameters can be determined by curve fitting and numerical optimized iteration.

Practicality and robustness were not well considered by the conventional parameter estimation method: the initial curve starting from demagnetization is not always available and a direct iterative algorithm to solve the characteristic equations is sensitive to the initial values of the iteration and the evaluation order of the equations because of two main reasons. The first one is that the basic equation group has non‐unique solutions, which is caused by the nonlinearity of the characteristic equations and the fact that there are more unknown quantities (i.e. five model parameters) than the equations available; the second reason is the multimodal feature of the problem, which means that there are many local minima for the iteration algorithm to be trapped in. So curve fitting around the loop tips is proposed before numerical iteration. The goal is to make the initial values, particularly saturation magnetization M_s, not far away from the desired solution to increase the possibility of converging to a physical result. The optimized iterative method with the enhanced ability to avoid local minima and find global roots is then applied to obtain the model parameters.

The proposed method overcomes the difficulties of the other techniques which assume zero remanence. It is also robust as it is guaranteed to converge to physical solutions. The method can facilitate further development and it formed the preliminary basis of our earlier work, where the variation of the Jiles‐Atherton model parameters with different magnetic field strengths was investigated and applied to the simulation of transformer inrush current.

Non-oriented electrical steel presents anisotropic behaviour. Modelling such anisotropic behaviour has become a necessity for accurate design of electrical machines. The main aim of this study is to model the magnetic anisotropy in the non-oriented electrical steel sheet of grade M400-50A using a phenomenological hysteresis model.

The well-known phenomenological vector Jiles–Atherton hysteresis model is modified to correctly model the typical anisotropic behaviour of the non-oriented electrical steel sheet, which is not described correctly by the original vector Jiles–Atherton model. The modification to the vector model is implemented through the anhysteretic magnetization. Instead of the commonly used classical Langevin function, the authors introduced 2D bi-cubic spline to represent the anhysteretic magnetization for modelling the magnetic anisotropy.

The proposed model is found to yield good agreement with the measurement data. Comparisons are done between the original vector model and the proposed model. Another comparison is also made between the results obtained considering two different modifications to the anhysteretic magnetization.

The paper presents an original method to model the anhysteretic magnetization based on projections of the anhysteretic magnetization in the principal axis, and apply such modification to the vector Jiles–Atherton model to account for the magnetic anisotropy. The replacement of the classical Langevin function with the spline resulted in better fitting. The proposed model could be used in the numerical analysis of magnetic field in an electrical application.

Improperly fitted parameters for the Jiles–Atherton (JA) hysteresis model can lead to non-physical hysteresis loops when ferromagnetic materials are simulated. This can be remedied by including a proper physical constraint in the parameter-fitting optimization algorithm. This paper aims to implement the constraint in the meta-heuristic simulated annealing (SA) optimization and Nelder–Mead simplex (NMS) algorithms to find JA model parameters that yield a physical hysteresis loop. The quasi-static B(H)-characteristics of a non-oriented (NO) silicon steel sheet are simulated, using existing measurements from a single sheet tester. Hysteresis loops received from the JA model under modified logistic function and piecewise cubic spline fitted to the average M(H) curve are compared against the measured minor and major hysteresis loops.

A physical constraint takes into account the anhysteretic susceptibility at the origin. This helps in the optimization decision-making, whether to accept or reject randomly generated parameters at a given iteration step. A combination of global and local heuristic optimization methods is used to determine the parameters of the JA hysteresis model. First, the SA method is applied and after that the NMS method is used in the process.

The implementation of a physical constraint improves the robustness of the parameter fitting and leads to more physical hysteresis loops. Modeling the anhysteretic magnetization by a spline fitted to the average of a measured major hysteresis loop provides a significantly better fit with the data than using analytical functions for the purpose. The results show that a modified logistic function can be considered a suitable anhysteretic (analytical) function for the NO silicon steel used in this paper. At high magnitude excitations, the average M(H) curve yields the proper fitting with the measured hysteresis loop. However, the parameters valid for the major hysteresis loop do not produce proper fitting for minor hysteresis loops.

The physical constraint is added in the SA and NMS optimization algorithms. The optimization algorithms are taken from the GNU Scientific Library, which is available from the GNU project. The methods described in this paper can be applied to estimate the physical parameters of the JA hysteresis model, particularly for the unidirectional alternating B(H) characteristics of NO silicon steel.