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Insulated Metal Substrates (IMS) have been used in the automotive industry for a number of years. The popularity of this technology is due to the good thermal conductivity of the thin insulation material, which is more effective than convection cooling, and the high temperature performance of the adhesive used for under‐bonnet applications. This paper describes how IMS circuits can be designed and manufactured with two or more layers without using the traditional plating processes.

Computational thinking (CT) is widely considered to be an important component of teaching generalizable computer science skills to all students in a range of learning environments, including robotics. However, despite advances in the design of robotics curricula that can teach CT, actual enactment in classrooms may often fail to reach this target. This study aims to understand whether the various instructional goals teachers’ hold when using these curricula may offer one potential explanation for disparities in outcomes.

In this study, the authors examine results from N = 206 middle-school students’ pre- and post-tests of CT, attitudinal surveys and surveys of their teacher’s instructional goals to determine if student attitudes and learning gains in CT are related to the instructional goals their teachers endorsed while implementing a shared robotics programming curriculum.

The findings provide evidence that despite using the same curriculum, students showed differential learning gains on the CT assessment when in classrooms with teachers who rated CT as a more important instructional goal; these effects were particularly strong for women. Students in classroom with teachers who rated CT more highly also showed greater maintenance of positive attitudes toward programming.

While there is a growing body of literature regarding curricular interventions that provide CT learning opportunities, this study provides a critical insight into the role that teachers may play as a potential support or barrier to the success of these curricula. Implications for the design of professional development and teacher educative materials that attend to teachers’ instructional goals are discussed.

This review arises from a series of multidisciplinary Franco‐British workshops which were supported by a grant from the Economic and Social Research Council (ESRC) and the Agence Nationale de la Recherche (ANR). More than 30 participants from a range of institutions and agencies were involved in compiling the material in this review (Appendix I). The workshops offered an opportunity to exchange ideas from research on the relationships between migration, health and well‐being in Britain and France. In the following discussion we compare and contrast experiences in the two countries, with the aim of assessing the importance of international, national and local contexts, in their various cultural, social and political dimensions, for the relationships of interest. Drawing on these ideas, we suggest the definition of a future international research agenda.

The growing use of internet communication technology has led to increased economic growth across the world, and this chapter seeks to assess the case of Czechia. The study also examines the changing employment distribution in the labour market with the growing influence of information and communication technology (ICT). The multiple indicators and multiple causes model as well as changes in employment or earnings shares of occupations are used for the analysis. The findings show that increased use of ICT contributes to growth in GDP and employment. It also shows that ICT has contributed to rising labour and factor productivity through increased innovation. There is also increased demand for highly educated labour leading to growth in employment in high skill occupations, while the share of low and middle skill occupations declines. The situation, however, does not indicate job polarisation in the labour market and total employment is still increasing. The study also finds that investment and use of ICT has led to progressive development in the human development index of the Czech Republic and a decline in the gender inequality index.

Economies and societies are not digitally isolated. Digital technologies are widely recognised as key drivers of information dissemination, knowledge sharing, income and employment. Digital technologies also influence the interlinkages of digitalisation, gender and labour market outcomes. Digital technologies impact every sphere of day-to-day life. It impacts ways of communication, trade and business; influences networking abilities; shapes societal norms, attitudes and behaviours. It is hence argued that digital technologies may have crucial implications for women's participation in the workforce.

Gender equality and increasing women's workforce participation is an important goal under the United Nations Sustainable Development Goals (SDGs). Research indicates that women are mainly involved in agricultural work, blue-collar formal work, while collar formal work, and entrepreneurship. Digital technologies significantly impact the ways of working in all these sectors. Consequently, it is argued that digital technologies influence women's participation across all such types of work.

This chapter aims at unravelling the linkages between digital technologies and women's workforce participation. To this end, the influences of digital technologies on women's participation in agricultural work, blue-collar formal work, white-collar formal work and entrepreneurship are discussed. The implications and impacts of the use of broadband, internet and mobile technologies are also discussed. This chapter also includes important theories of women's workforce participation and discusses them in light of digitalisation.

This paper aims to develop a novel grey Bernoulli model with memory characteristics, which is designed to dynamically choose the optimal memory kernel function and the length of memory dependence period, ultimately enhancing the model's predictive accuracy.

This paper enhances the traditional grey Bernoulli model by introducing memory-dependent derivatives, resulting in a novel memory-dependent derivative grey model. Additionally, fractional-order accumulation is employed for preprocessing the original data. The length of the memory dependence period for memory-dependent derivatives is determined through grey correlation analysis. Furthermore, the whale optimization algorithm is utilized to optimize the cumulative order, power index and memory kernel function index of the model, enabling adaptability to diverse scenarios.

The selection of appropriate memory kernel functions and memory dependency lengths will improve model prediction performance. The model can adaptively select the memory kernel function and memory dependence length, and the performance of the model is better than other comparison models.

The model presented in this article has some limitations. The grey model is itself suitable for small sample data, and memory-dependent derivatives mainly consider the memory effect on a fixed length. Therefore, this model is mainly applicable to data prediction with short-term memory effect and has certain limitations on time series of long-term memory.

In practical systems, memory effects typically exhibit a decaying pattern, which is effectively characterized by the memory kernel function. The model in this study skillfully determines the appropriate kernel functions and memory dependency lengths to capture these memory effects, enhancing its alignment with real-world scenarios.

Based on the memory-dependent derivative method, a memory-dependent derivative grey Bernoulli model that more accurately reflects the actual memory effect is constructed and applied to power generation forecasting in China, South Korea and India.

The purpose of this paper is to rank the factors associated with smoking according to their relative effect on the tendency to smoke.

A probit procedure and ordinary least squares methods are used to analyze factors that affect the probability of being a smoker and factors that affect smoking intensity, as measured by the number of cigarettes smoked per day.

The paper finds that a relative risk (RR) of smoking is highest for Arab males, especially those with only 11‐12 years of schooling, married with more than five children or unmarried, while it is lowest for Arab females, especially those married with two to four children, or less than eight years of schooling.

The findings indicate that certain characteristics are associated with much larger RR. Mainly, it is found that the RR of smoking is highest for Arab males who work 1‐20 weekly hours, have 11‐12 years of schooling, with more than five children or are unmarried, while it is lowest for married Arab females with two to four children, with less than eight years of schooling, who work 21‐30 hours a week.

F. Taylor Ostrander had three courses from Melchior Palyi at the University of Chicago during the 1933–1934 academic year: Economics 332 on monetary theory; 333 on business cycle theory; and 334 on the European banking system. Fellow students included Albert G. Hart, later a leading monetary economist, and Rose Director, sister of Aaron Director and later wife of Milton Friedman.

This study aimed to explore the antecedents of small- and medium-sized enterprises (SMEs) internationalization and to compare the different resources required to enter different geographical regions. This study adds to the discussion on internationalization from a resource-based view (RBV) and a focus on dynamic capability, especially the linkage with resources such as digital capability, domestic industrial networks and the business-to-business (B2B) model.

This study used secondary data collected by an SME association in 2020, using a logistic regression model to examine the hypotheses. The respondents were selected according to stratified random sampling.

Digital capability and the B2B model significantly and positively affect the likelihood of internationalization by SMEs, while domestic industrial networks were negatively correlated with this process. In addition, Taiwanese SMEs with high digital capability tend to expand to North America, Europe, Southeast Asia, Northeast Asia, Oceania and the Middle East. Smaller firms tend to develop in Southeast Asia, whereas larger firms opt to establish business in Oceania.

A research limitation is the generalizability of the sample. Findings could be enhanced if future studies include more industries and draw comparisons among different industries or countries. Future studies could explore digital entrepreneurship from a global perspective.

Managers need to emphasize better the development of digital capabilities and skills for SMEs. With limited financial resources and workforce, SMEs can strengthen the competence in international markets by adopting a suitable business model. When SMEs join an association to expand SMEs foreign networks, the study suggests that SMEs carefully evaluate the characteristics of each industrial association first, given that some associations are domestic-oriented. As for public policymakers, a project grant can be used to provide digital capability training for SME employees and owners or promote building a B2B model when internationalizing.

The authors' findings fill the research gaps in RBVs of internationalization, especially in linking resources such as digital capability, domestic industrial networks and the B2B model. The outcomes of this research serve as a reference not only to policymakers for improving the current SME ecosystem, but also to business practitioners positioning themselves in this system.