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Demonstrates the simple but effective application of a standard finite element program (PAFEC), and the associated geometric modelling code (PIGS), to the improvement of the design of an engineering component. The technique adopted involves augmenting material around zones of high stress and removing material in zones of low stress. This evolutionary procedure is related to the behaviour of bones in animals. The essentially two‐step procedure involves; finite element analysis of the preliminary component design using PAFEC; and, definition of a new geometry using PIGS, with selected stress contours giving an indication of the new shape. The technique, which proceeds iteratively, was first tested successfully on some classical academic optimisation problems. Its subsequent application to the industrial problem of a twin chamber pressurised extruded aluminium section, the primary component of an air drying system, resulted in material savings of up to 50 per cent and an associated drop in the maximum von Mises stress of 45 per cent. While this method does not determine the optimal structural form, it does generate substantial improvements in terms of material usage and reduced maximum stresses. It has the advantage that it can be used by any competent engineer with a working knowledge of the strength of materials, finite elements and structural form.

It is well-known that Beatrice Ensor, who founded the New Education Fellowship (NEF) in 1921, was a Theosophist and that from 1915 the Theosophical Fraternity in Education she established laid the foundations for the NEF. However, little research has been performed on the Fraternity itself. The travels of Theosophists, texts, money and ideas between Auckland, India and London from the late nineteenth century offer insights into “New Education” networking in the British Commonwealth more broadly. The paper aims to discuss these issues.

This paper draws on archival documents from the Adyar Library and Research Centre, International Theosophical Society (TS) headquarters, Chennai, India; the archive at the headquarters of the New Zealand Section of the TS, Epsom, Auckland; the NEF files at the archive of the London Institute of Education; papers past digital newspaper archive.

New Zealand’s first affiliated NEF group was set up by the principal of the Vasanta Gardens Theosophical School, Epsom, in 1933. She was also involved in the New Zealand Section of the Theosophical Fraternity, which held conferences from 1917 to 1927. New Zealand’s Fraternity and Theosophical Education Trust had close links with their counterparts in England and India. The setting up of New Zealand’s first NEF group was enabled by networks created between Theosophists in New Zealand, India and England from the late nineteenth century.

The contribution of Theosophists to the new education movement has received little attention internationally. Theosophical educational theory and Theosophists’ contributions to New Zealand Education have not previously been studied. Combining transnational historiography with critical geography, this case study of networks between New Zealand, Adyar (India) and London lays groundwork for a wider “spatial history” of Theosophy and new education.

The purpose of this paper is to propose a new scheme for obtaining acceptable solutions for problems of continuum topology optimization of structures, regarding the distribution and limitation of discretization errors by considering h-adaptivity.

The new scheme encompasses, simultaneously, the solution of the optimization problem considering a solid isotropic microstructure with penalization (SIMP) and the application of the h-adaptive finite element method. An analysis of discretization errors is carried out using an a posteriori error estimator based on both the recovery and the abrupt variation of material properties. The estimate of new element sizes is computed by a new h-adaptive technique named “Isotropic Error Density Recovery”, which is based on the construction of the strain energy error density function together with the analytical solution of an optimization problem at the element level.

Two-dimensional numerical examples, regarding minimization of the structure compliance and constraint over the material volume, demonstrate the capacity of the methodology in controlling and equidistributing discretization errors, as well as obtaining a great definition of the void–material interface, thanks to the h-adaptivity, when compared with results obtained by other methods based on microstructure.

This paper presents a new technique to design a mesh made with isotropic triangular finite elements. Furthermore, this technique is applied to continuum topology optimization problems using a new iterative scheme to obtain solutions with controlled discretization errors, measured in terms of the energy norm, and a great resolution of the material boundary. Regarding the computational cost in terms of degrees of freedom, the present scheme provides approximations with considerable less error if compared to the optimization process on fixed meshes.

This paper aims to investigate the performance of estimators of the bid-ask spread in a wide range of circumstances and sampling frequencies. The bid-ask spread is important for many reasons. Because spread data are not always available, many methods have been suggested for estimating the spread. Existing papers focus on the performance of the estimators either under ideal conditions or in real data. The gap between ideal conditions and the properties of real data are usually ignored. The consistency of the estimates across various sampling frequencies is also ignored.

The estimators and the possible errors are analysed theoretically. Then we perform simulation experiments, reporting the bias, standard deviation and root mean square estimation error of each estimator. More specifically, we assess the effects of the following factors on the performance of the estimators: the magnitude of the spread relative to returns volatility, randomly varying of spreads, the autocorrelation of mid-price returns and mid-price changes caused by trade directions and feedback trading.

The best estimates come from using the highest frequency of data available. The relative performance of estimators can vary quite markedly with the sampling frequency. In small samples, the standard deviation can be more important to the estimation error than bias; in large samples, the opposite tends to be true.

There is a conspicuous lack of simulation evidence on the comparative performance of different estimators of the spread under the less than ideal conditions that are typical of real-world data. This paper aims to fill this gap.

To present an approach to parameterization based shape optimization of statically loaded structures and to propose its practical implementation.

In order to establish a convenient shape parameterization, the design element technique is employed. A rational Bézier body is used to serve as the design element. The design element is used to retrieve the nodal geometrical data of finite elements (FEs). Their field geometrical data are obtained using the FE own internal functions. For practical implementation it is proposed to establish the optimization cycle by two separately running processes. The data exchange is established by using self‐descriptive and platform‐independent XML conforming data files.

The proposed approach offers an unified approach to shape optimization of skeletal, as well as continuous structures. Structural shape may be varied smoothly with a relative small set of design variables. The employment of a gradient‐based optimization algorithm assures computational efficiency.

The aspects of FE mesh deterioration are not considered in this work. This would be necessary if for the actual problem at hand major and excessively non‐uniform shape changes of the FE mesh are expected.

A useful source of information for someone who is planning to develop a general or special‐purpose integrated structural analysis and shape optimization software.

The paper offers a rather simple, but quite powerful approach to structural shape optimization together with practical hints for its computational implementation.

Controversy has long swirled over the claim that Donald Trump's base has deeply rooted authoritarian tendencies, but Trump himself seems to have few doubts. Asked whether his stated wish to be dictator “on day one” of second term in office would repel voters, Trump said “I think a lot of people like it.” It is one of his invariable talking points that 74 million voters supported him in 2020, and he remains the unrivaled leader of the Republican Party, even as his rhetoric escalates to levels that cautious observers now routinely call fascistic.

Is Trump right that many people “like” his talk of dictatorship? If so, what does that mean empirically? Part of the answer to these questions was apparent early, in the results of the 2016 American National Election Study (ANES), which included survey questions that we had proposed which we drew from the aptly-named “Right-Wing Authoritarianism” scale. Posed to voters in 2012–2013 and again in 2016, those questions elicited striking responses.

In this chapter, we revisit those responses. We begin by exploring Trump's escalating anti-democratic rhetoric in the light of themes drawn from Max Weber and Theodor W. Adorno. We follow this with the text of the 2017 conference paper in which we first reported that 75% of Trump's voters supported him enthusiastically, mainly because they shared his prejudices, not because they were hurting economically. They hoped to “get rid” of troublemakers and “crush evil.” That wish, as we show in our conclusion, remains central to Trump's appeal.

This chapter examines the existence of dynamic herding behavior by Tunisian investors in the Tunisia stock market during the revolution period of 2011–2013. The sample covers all Tunindex daily returns as a proxy for the Tunisia stock exchange index over the period 2007–2018. The author modifies the cross-sectional absolute deviation model to include all market conditions (bull and bear markets) and the geopolitical crisis effect corresponding to the Tunisian Jasmine revolution during 2011–2013, and show that herding is indeed not present in the Tunisia stock market including during its turmoil periods. These findings imply that the Tunisian emerging financial market became more vulnerable to adverse herding behavior after the revolution. There is also a clear implication for capitalist firms and angel investors in Tunisia that adverse herding behavior tends to exist on days of higher uncertainty and information asymmetry.