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The paper proposed a fast procedure for solving the reliability-based robust design optimization (RBRDO) by modifying the RBRDO formulation and transforming it into a series of RBRDO subproblems. Then for each subproblem, the objective function, constraint function and reliability index are approximated using Taylor series expansion, and their approximate forms depend on the deterministic design vector rather than the random vector and the uncertain estimation in the inner loop of RBRDO can be avoided. In this way, it can greatly reduce the evaluation number of performance function. Lastly, the trust region method is used to manage the above sequential RBRDO subproblems for convergence.

As is known, RBRDO is nested optimization, where the outer loop updates the design vector and the inner loop estimate the uncertainties. When solving the RBRDO, a large evaluation number of performance functions are needed. Aiming at this issue, the paper proposed a fast integrated procedure for solving the RBRDO by reducing the evaluation number for the performance functions. First, it transforms the original RBRDO problem into a series of RBRDO subproblems. In each subproblem, the objective function, constraint function and reliability index caused are approximated using simple explicit functions that solely depend on the deterministic design vector rather than the random vector. In this way, the need for extensive sampling simulation in the inner loop is greatly reduced. As a result, the evaluation number for performance functions is significantly reduced, leading to a substantial reduction in computation cost. The trust region method is then employed to handle the sequential RBRDO subproblems, ensuring convergence to the optimal solutions. Finally, the engineering test and the application are presented to illustrate the effectiveness and efficiency of the proposed methods.

The paper proposes a fast procedure of solving the RBRDO can greatly reduce the evaluation number of performance function within the RBRDO and the computation cost can be saved greatly, which makes it suitable for engineering applications.

The standard deviation of the original objective function of the RBRDO is replaced by the mean and the reliability index of the original objective function, which are further approximated by using Taylor series expansion and their approximate forms depend on the deterministic design vector rather than the random vector. Moreover, the constraint functions are also approximated by using Taylor series expansion. In this way, the uncertainty estimation of the performance functions (i.e. the mean of the objective function, the constraint functions) and the reliability index of the objective function are avoided within the inner loop of the RBRDO.

This study aims to investigate the influence of CEO’s only-child status on corporate social responsibility (CSR) practices. It seeks to extend the understanding of upper echelon theory by examining unexplored CEO characteristics and their impact on CSR decisions.

The paper uses manually collected CEO family information and Chinese Stock and Market Accounting Research data as a basis to examine the influence of CEOs’ early-life experiences on their engagement in CSR activities. The study applies attachment security theory from developmental psychology and uses upper echelon theory, particularly focusing on CEOs’ only-child status. A comparative analysis of philanthropic donations between CEOs who are only children and those who have siblings is conducted. The study also examines the moderating effects of corporate slack resources and CEO shareholdings.

Preliminary findings suggest that CEOs who are only children are more likely to engage in CSR compared to their counterparts with siblings. However, the difference in donation amounts between the two groups tends to attenuate with decreased slack resources and increased CEO shareholdings.

To the best of the authors’ knowledge, this research represents the first attempt to investigate being the only child in one’s family and the CSR-related decision of CEOs, which extends the upper echelon theory by introducing the family science theory into the management domain.

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

A new approach to gesture recognition using wearable devices.

This study has a broad application prospect in the field of human–computer interaction.

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.

Computer-supported collaborative learning (CSCL) is widely used in different levels of education across disciplines and domains. Researchers in the field have proposed various conceptual frameworks toward a comprehensive understanding of CSCL. However, as the definition of CSCL is varied and contextualized, it is critical to develop a shared understanding of collaboration and common definitions for the metrics that are used. The purpose of this research is to present a synthesis that focuses explicitly on the types and features of coding schemes that are used as analytic tools for CSCL.

This research collected coding schemes from researchers with diverse backgrounds who participated in a series of workshops on collaborative learning and adaptive support in CSCL, as well as coding schemes from recent volumes of the International Journal of Computer-Supported Collaborative learning (ijCSCL). Each original coding scheme was reviewed to generate an empirically grounded framework that reflects collaborative learning models.

The analysis generated 13 categories, which were further classified into three domains: cognitive, social and integrated. Most coding schemes contained categories in the cognitive and integrated domains.

This synthesized coding scheme could be used as a toolkit for researchers to pay attention to the multiple and complex dimensions of collaborative learning and for developing a shared language of collaborative learning.

By analyzing a set of coding schemes, the authors highlight what CSCL researchers find important by making these implicit understandings of collaborative learning visible and by proposing a common language for researchers across disciplines to communicate by referencing a synthesized framework.

This paper aims to present a model of collaborative inquiry play: rule-based imaginary situations that provide challenging problems and support agentic multiplayer interactions (c.f., Vygotsky, 1967; Salen and Zimmerman, 2003). Drawing on problem-based learning (PBL, Hmelo-Silver, 2004), this paper provides a design case to articulate the relationship between the design goals and the game-based learning environment.

Drawing on conjecture mapping (Sandoval, 2014), this paper presents an iterative development of the conjecture map for crystal island: ecojourneys and highlights the development of the story and tools in crystal island: ecojourneys, an immersive game based on PBL pedagogy. By articulating this development, the authors highlight the affordances and constraints of designing for collaborative inquiry play and address challenges in supporting learner agency.

The PBL inquiry process served as the foundation of collaborative inquiry play. Attending to the rules of inquiry fostered student agency, and in turn, playful engagement in the game-based learning environment. Agency however meant holding students accountable to actions undertaken, especially as it pertained to generating group-based explanations and reflecting on productive collaboration. Moreover, socially shared regulation of learning and systems thinking concepts (i.e. phenomenon, mechanisms, and components) must also be externalized in representations and interactions in the game such that students have the agency to decide on their learning paths.

This paper presents the model of collaborative inquiry play and highlights how to support player agency and design content-rich play environments which are not always completely open.

The purpose of this paper is to review the development of the processed feed industry in China through the lens of one of its most successful and earliest entrants, the Hope Group's “New Hope” enterprise. With the feed industry in China now facing a transition phase, the paper looks at the root causes of the problems facing China's feed industry, analyzes the transition strategy undertaken by New Hope and others, and discusses the opportunities for industry growth in the world's most populous country, where urbanization and standards of living are still on the rise and per capita use of feeds is still low by world standards (e.g. one‐fifth of that in the USA). The case also addresses the potential industry impact of mandates outlined in China's Twelfth Five‐Year Plan, such as the imperative to modernize agriculture and improve peasants’ economic well‐being.

The paper draws on expert knowledge of the CEO of New Hope Group's sister agribusiness company, West Hope Group, as well as New Hope Group annual reports and global economic data.

The study reveals future challenges to China's processed feed industry as being price of labor, raw materials, and energy rises; companies undergoing integration; and established companies shifting from product marketing to service marketing models.

This paper is useful for academics interested in industry perspectives, policymakers, practitioners, and business people considering investment in China.

How China's processed feed and breeding industries modernize will impact the economic well‐being of each link in the nation's agribusiness chain (from small producers to conglomerates), the cost and quality of animal‐based proteins, and the world's “food vs. fuel” conflicts.

The paper offers a rare insider's look at one of China's largest private companies and a global player in agribusiness.

In 2013, Chinese president Xi Jinping proposed the concept of “One Belt and One Road” economic cooperation. “The Belt and Road Initiative (B&R)” is the short of “The Silk Road Economic Belt” and the “21st-century Maritime Silk Road,” which has got a series of remarkable achievements and worldwide attentions in past five years such as Asian Infrastructure Investment Bank, China–Pakistan Economic Corridor, B&R Forum for International Cooperation, etc. Especially, cross-border EC has greatly strengthened the trade links between countries along the way, which is a rare chance for Chinese Export-oriented Cross-border EC’s rapid growth. Thus, the authors take DHgate.com as a typical example to do a big data analysis. This chapter analyzes vast data from 2013 to 2017 about seven kinds of commodities including Fashion accessories, Jewelry, Sports & Outdoors, Security & Surveillances, Car accessories, Watches, and Hair & Styling by using data mining related software and algorithms. The authors do some monthly sale charts and find a few counter-intuitive but useful conclusions such as by taking association analysis, the study shows that sports products and jewelry products have strong association rules. In addition, for potential products (such as Fashion accessories and Jewelry), although their sales have a certain shock, the overall selling line keep rising. It is possible to put forward some practical suggestions for Chinese Export-oriented Cross-border EC that actively respond to the One Belt One Road Initiative based on these analysis results.

Institutional actors are critical allies for grassroots movements, but few studies have examined their effects and variations within the non-democratic context. This chapter argues that while institutional allies are heavily constrained and unlikely to give open endorsement to grassroot activists, some institutional activists indirectly facilitate movement mobilization and favorable outcomes in the process of advancing their own political agendas. Drawing upon in-depth interviews conducted in 2008 and 2012, I illustrate this argument by examining the Anti-PX Movement – a landmark grassroots environmental movement against a chemical plant – in Xiamen, China. I find that the environmental institutional actors were constrained and divided, yet some still fostered opportunities for movement mobilization and in turn exploited the opportunity created by the protesters to pursue their policy interests, thus facilitating positive movement outcomes. As long as the claims are not politically subversive to the authoritarian rule, this type of tacit and tactical interaction between institutional activists within the state and grassroot activists on the street is conducive to promoting progressive policy changes.