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Awkward positional problems in robotics could be solved by flexible drives, an inventor claims.

There are intense current debates about the place of belief systems in a secular society, and also whether the mechanistic approach to mental health care is sufficient for human beings. This paper aims to describe the Birmingham and Solihull Mental Health Foundation NHS Trust (BSMHFT) spirituality and mental health research programme within that context.

The research studies are placed within a discourse of current debates, but also within the specific context of the city of Birmingham. Birmingham is England's second city to London, and is an increasingly multi‐ethnic and multi‐cultural environment.

Those who use mental health services increasingly state that they wish to have the spiritual dimension of their lives attended to by professionals. The BSMHFT project reinforces this message and demonstrates the merits of close working with faith communities and engaging with staff in their understanding of spirituality.

The research by Professor Koenig et al. in the USA has demonstrated the physical and mental health benefits of belonging to a supportive faith community. The BSMHFT project is a rare UK example of research in this area and comes at a time of intense debate in England over the nature of society.

In the context of the current financial crisis, this paper aims to examine values and spirituality in the modern workplace.

Using contemporary examples and examining recent literature on spirituality and loneliness, the paper considers the concept of loneliness and argues that this may stem from an over‐preoccupation with the workplace and employment‐based achievement, at the expense of having rounded lives as human beings.

It is demonstrated that, over the last decade at least, the levels of stress in life and work have risen noticeably. In this context, leaders need even more to be forgers of a sense of meaning and purpose in the workplace and engage the hearts and minds of staff towards improved outcomes.

The current financial crisis is also a major spiritual crisis. Now there seems to be a growing gap between leaders and the led, and an increase in what the author terms “soul‐less leadership”, which fails to engage and motivate and inspire. The author calls on leaders in this crisis of capitalism to work and engage with staff in health and social care, so that those serving at the frontline feel‐valued and supported, developed and engaged in a common purpose.

The study aims to shed light on the historical and contemporary trends of biodiversity accounting literature, while simultaneously offering insights into the future of research in this sector. The paper also aims to raise awareness among accounting researchers about their role in preserving biodiversity and informing improvements in policy and practice in this area.

The Bibliometrix R-package is used to carry out an algorithmic historiography. The reference publication year spectroscopy (RPYS) methodology is implemented. It is a unique approach to bibliometric analysis that allows researchers to identify and examine historical patterns in scientific literature.

The work provides a distinct and comprehensive discussion of the four distinct periods demarcating the progression of scientific discourse regarding biodiversity accounting. These periods are identified as Origins (1767–1864), Awareness (1865–1961), Consolidation (1962–1995) and Acceleration (1996–2021). The study offers an insightful analysis of the main thematic advancements, interpretative paradigm shifts and theoretical developments that occurred during these periods.

The paper offers a significant contribution to the existing academic debate on the prospects for accounting scholars to concentrate their research efforts on biodiversity and thereby promote advancements in policy and practice in this sector.

The article represents the first example of using an algorithmic historiography approach to examine the corpus of literature dealing with biodiversity accounting. The value of this study comes from the fusion of historical methodology and perspective. To the best of the authors’ knowledge, this is also the first scientific investigation applying RPYS in the accounting sector.

In public management research, the focus in the public value debate has been on public administration organizations’ broader societal outcomes. Public value describes how public administrations form a vital part of the social context in which people develop and grow. However, there has not yet been an analysis of how public administration contributes to happiness in society.

In this study, we empirically analyze the relationship between people’s happiness and the public value of public administration. Our approach is based on a unique Swiss survey dataset comprising 870 individuals.

We find a positive relationship between public administration’s public value and happiness. We also find preliminary evidence with a moderation analysis that the relationship between a value-creating public administration sector and self-reported happiness is stronger for public administration employees.

While correlation studies cannot claim causal explanations and common method bias may additionally limit any research in social science, we took a number of measures to mitigate related problem. We tested our model in two samples and took both several procedural techniques and a survey design minimizing common method bias.

The paper discusses implications for public sector performance measurement for public management and practitioners.

This study calls for a more positive view on the multiple functions public administration performs for society. After an era of critical voices, our study helps reclaim public administration as a positive force for society at large in times of grand challenges, such as climate crisis, demographics and digitization.

This study has highlighted the importance between public administration’s public value and happiness in Swiss public service organizations. The study also showed that an employment in the public administration contributes to the happiness of individuals and beyond to society.

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.

Owing to the excellent performance, giant magnetostrictive materials (GMMs) are widely used in many engineering fields. The dynamic Jiles–Atherton (J-A) model, derived from physical mechanism, is often used to describe the hysteresis characteristics of GMM. However, this model, despite cited by many different literature studies, seems not to possess unique expressions, which may cause great trouble to the subsequent application. This paper aims to provide the rational expressions of the dynamic J-A model and propose a numerical computation scheme to obtain the model results with high accuracy and fast speed.

This paper analyzes different published papers and provides a reasonable form of the dynamic J-A model based on functional properties and physical explanations. Then, a numerical computation scheme, combining the Newton method and the explicit Adams method, is designed to solve the modified model. In addition, the error source and transmission path of the numerical solution are investigated, and the influence of model parameters on the calculation error is explored. Finally, some attempts are made to study the influence of numerical scheme parameters on the accuracy and time of the computation process. Subsequently, an optimization procedure is proposed.

A rational form of the dynamic J-A model is concluded in this paper. Using the proposed numerical calculation scheme, the maximum calculation error, while computing the modified model, can remain below 2 A/m under different model parameter combinations, and the computation time is always less than 0.5 s. After optimization, the calculation speed can be enhanced with the computation accuracy guaranteed.

To the best of the authors’ knowledge, this paper is the first one trying to provide a rational form of the dynamic J-A model among different citations. No other research studies focus on designing a detailed computation scheme targeting the fast and accurate calculation of this model as well. And the performance of the proposed calculation method is validated in different conditions.

The purpose of this paper is to propose a chaotic optimization method for identifying the parameters of the Jiles–Atherton (J-A) hysteresis model.

The J-A model has five parameters which are assigned with physical meaning and whose determination is demanding. To determine these parameters, the fitness function, which represents the difference between the measured and the modeled hysteresis loop, is formed. Optimal parameter values are the values that minimize the fitness function.

The parameters of J-A model for three magnetic materials are determined. The model with the optimal parameters is validated using measured data and comparison with particle swarm optimization algorithm, genetic algorithm, pattern search and simulated annealing algorithm. The results show that the proposed method provides better agreement between measured and modeled hysteresis loop than other methods used for comparison. The proposed method is also suitable for simultaneous optimization of multiple hysteresis loops.

Chaotic optimization method is implemented for the first time for J-A model parameter identification. Numerical comparisons with results obtained with other optimization algorithms demonstrate that this method is a suitable alternative in parameters identification of J-A hysteresis model. Furthermore, this method is easy to implement and set up.

The accurate modeling of magnetic hysteresis in electrical steels is important in several electrical and electronic applications. Numerical models have long been known that can correctly reproduce some typical behaviours of these magnetic materials. Among these, the model proposed by Jiles and Atherton must certainly be mentioned. This model is intuitive and fairly easy to implement and identify with relatively few experimental data. Also, for this reason, it has been extensively studied in different formulations. The developments and numerical tests made on this hysteresis model have indicated that it is able to accurately reproduce symmetrical cycles, especially the major loop, but often it fails to reproduce non-symmetrical cycles. This paper aims to show the positive aspects and highlight the defects of the different formulations in predicting the minor loops of electrical steels excited by non-sinusoidal currents.

The different formulations are applied to different electrical steels, and the data coming from the simulations are compared with those measured experimentally. The direct and inverse Jiles–Atherton models, including the introduction of the dissipative factor approach, are presented, and their limitations are proposed and validated using the measurements of three non-grain-oriented materials. Only the measured major loop is used to identify the parameters of the Jiles–Atherton model. Furthermore, the direct and inverse Jiles–Atherton models were used to simulate the minor loops as well as the hysteresis cycles with direct component (DC) bias excitation. Finally, the simulation results are discussed and compared to measurements for each study case.

The paper indicates that both the direct and the inverse Jiles–Atherton model formulations provide a good agreement with the experimental data for the major loop representation; nevertheless, both models can not accurately predict the minor loops even when the modification approaches proposed in the literature were implemented.

The Jiles–Atherton model and its modifications are widely discussed in the literature; however, some limitations of the model and its modification in the case of the distorted current waveform are not completely highlighted. Furthermore, this paper contains an original discussion on the accuracy of the prediction of minor loops from distorted current waveforms, including DC bias.

The purpose of this study is to model the global dynamic hysteresis properties with an improved Jiles–Atherton (J-A) model through a unified set of parameters.

First, the waveform scaling parameters β, λ_k and λ_c are used to improve the calculation accuracy of hysteresis loops at low magnetic flux density. Second, the Riemann–Liouville (R-L) type fractional derivatives technique is applied to modified static inverse J-A model to compute the dynamic magnetic field considering the skin effect in wideband frequency magnetization conditions.

The proposed model is identified and verified by modeling the hysteresis loops whose maximum magnetic flux densities vary from 0.3 to 1.4 T up to 800 Hz using B30P105 electrical steel. Compared with the conventional J-A model, the global simulation ability of the proposed dynamic model is much improved.

Accurate modeling of the hysteresis properties of electrical steels is essential for analyzing the loss behavior of electrical equipment in finite element analysis (FEA). Nevertheless, the existing inverse Jiles–Atherton (J-A) model can only guarantee the simulation accuracy with higher magnetic flux densities, which cannot guarantee the analysis requirements of considering both low magnetic flux density and high magnetic flux density in FEA. This paper modifies the dynamic J-A model by introducing waveform scaling parameters and the R-L fractional derivative to improve the hysteresis loops’ simulation accuracy from low to high magnetic flux densities with the same set of parameters in a wide frequency range.