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The purpose of this paper is to propose two linear solid-shell finite elements, a six-node prismatic element denoted SHB6-EXP and an eight-node hexahedral element denoted SHB8PS-EXP, for the three-dimensional modeling of thin structures in the context of explicit dynamic analysis.

These two linear solid-shell elements are formulated based on a purely three-dimensional (3D) approach, with displacements as the only degrees of freedom. To prevent various locking phenomena, a reduced-integration scheme is used along with the assumed-strain method. The resulting formulations are computationally efficient, as only a single layer of elements with an arbitrary number of through-thickness integration points is required to model 3D thin structures.

Via the VUEL user-element subroutines, the performance of these elements is assessed through a set of selective and representative dynamic elastoplastic benchmark tests, impact-type problems and deep drawing processes involving complex non-linear loading paths, anisotropic plasticity and double-sided contact. The obtained numerical results demonstrate good performance of the SHB-EXP elements in the modeling of 3D thin structures, with only a single element layer and few integration points in the thickness direction.

The extension of the SHB-EXP solid-shell formulations to large-strain anisotropic plasticity enlarges their application range to a wide variety of dynamic elastoplastic problems and sheet metal forming simulations. All simulation results reveal that the numerical strategy adopted in this paper can efficiently prevent the various locking phenomena that commonly occur in the 3D modeling of thin structural problems.

An appropriate equivalent model is the key to the effective analysis of the system and structure in which permanent magnet takes part. At present, there are several equivalent models for calculating the interacting magnetic force between permanent magnets including magnetizing current, magnetic charge and magnetic dipole–dipole model. How to choose the most appropriate and efficient model still needs further discussion.

This paper chooses cuboid, cylindrical and spherical permanent magnets as calculating objects to investigate the detailed calculation procedures based on three equivalent models, magnetizing current, magnetic charge and magnetic dipole–dipole model. By comparing the accuracies of those models with experiment measurement, the applicability of three equivalent models for describing permanent magnets with different shapes is analyzed.

Similar calculation accuracies of the equivalent magnetizing current model and magnetic charge model are verified by comparison between simulation and experiment results. However, the magnetic dipole–dipole model can only accurately calculate for spherical magnet instead of other nonellipsoid magnets, because dipole model cannot describe the specific characteristics of magnet's shape, only sphere can be treated as the topological form of a dipole, namely a filled dot.

This work provides reference basis for choosing a proper model to calculate magnetic force in the design of electromechanical structures with permanent magnets. The applicability of different equivalent models describing permanent magnets with different shapes is discussed and the equivalence between the models is also analyzed.

Accompanying the casino liberalization in Macau has been the massive increase in the importation of migrant workers to drive the labour-intensive, service-oriented economic growth there. Nevertheless, the employment of migrant workers has become an intensely contentious issue. The traditional pluralist approach to migration policy has highlighted a mismatch between restrictive policy pronouncements and actual expansive outcomes. This mismatch has resonated strongly in Macau, where the number of migrant workers skyrocketed in the last decade in spite of repeated guarantees from the government of the adoption of a protectionist labour policy. The pluralist approach has attributed the mismatch to strong constituencies supporting more immigration. The purpose of this paper is to dispute this and maintain that the Macau Government is a capitalist state committed to increasing labour importation to facilitate wealth accumulation.

The paper uses a qualitative approach based on extensive research of news and media reports, facilitated by a close observation of political developments.

The Macau Government started, in 2005, to talk about reforming its labour importation programme by adding a migrant worker levy, a ratio mechanism and a six-month waiting period. This paper investigates how the capitalist state navigated the reform process by promising changes and building consent with the working classes. The author maintains that “a game of protection” has been constructed and played to secure the consent of the local working classes for the migrant worker programme.

Very little literature is available that has studied the changes made to the migrant worker system in Macau. This paper will help to close this gap.

A detailed description will be provided of all the classification algorithms that have been widely used in the domain of medical science. The foundation will be laid by giving a comprehensive overview pertaining to the background and history of the classification algorithms. This will be followed by an extensive discussion regarding various techniques of classification algorithm in machine learning (ML) hence concluding with their relevant applications in data analysis in medical science and health care. To begin with, the initials of this chapter will deal with the basic fundamentals required for a profound understanding of the classification techniques in ML which will comprise of the underlying differences between Unsupervised and Supervised Learning followed by the basic terminologies of classification and its history. Further, it will include the types of classification algorithms ranging from linear classifiers like Logistic Regression, Naïve Bayes to Nearest Neighbour, Support Vector Machine, Tree-based Classifiers, and Neural Networks, and their respective mathematics. Ensemble algorithms such as Majority Voting, Boosting, Bagging, Stacking will also be discussed at great length along with their relevant applications. Furthermore, this chapter will also incorporate comprehensive elucidation regarding the areas of application of such classification algorithms in the field of biomedicine and health care and their contribution to decision-making systems and predictive analysis. To conclude, this chapter will devote highly in the field of research and development as it will provide a thorough insight to the classification algorithms and their relevant applications used in the cases of the healthcare development sector.

What is behavioral economics? This chapter explores a mismatch between what is included in the field of behavioral economics and some of the most visible Austrian critiques of behavioral economics. While paternalism, nudging, and a focus on irrationalities and biases are a big part of modern behavioral economics, the portrayal of the field of behavioral economics as being focused predominately upon those areas leaves a swath of low-hanging fruit that would be beneficial for Austrian scholars to consume and use in their own work.

Minimising makespan aims to achieve high utilisation of equipment and resources by getting all jobs out quickly. This is an important scheduling criterion, especially for automated systems, because of the high investment cost. The problem, however, becomes complex when many parts and machines are involved. This is because different parts may require different numbers of operations, and there are many possible schedules. For small problems, a mathematical programming model for minimising makespan is formulated. For large problems, a sequencing algorithm based on decomposition and pairwise comparison is proposed. The idea of “total overlapping time” in the sequencing algorithm is introduced to determine the solution of each sub‐schedule. It maximises the number of jobs working at different machines at the same time, while satisfying the parts’ operation precedence and machine constraints. The differences between this method and the traditional graphical method are discussed. The sequencing algorithm significantly reduces the number of schedules for consideration and hence, the computational power required.

Strategy scholars have long argued that breakthrough innovation is generated by recombining knowledge from distant domains. Even if firms have the ability to access and absorb knowledge from distant domains, however, they may fail to pay attention to such knowledge because it is seemingly irrelevant to their tasks. We draw attention to this problem of knowledge relevance and develop a theoretical model to illuminate how ideas from seemingly irrelevant (i.e., peripheral) domains can generate breakthrough innovation through the cognitive process of analogical reasoning, as well as the conditions under which this is more likely to occur. We situate our theoretical model in the context of teams in order to develop insight into the microfoundations of knowledge recombination within firms. Our model reveals paradoxical requirements for teams that help to explain why breakthrough innovation is so difficult.