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Engineering components/structures with geometric discontinuities normally bear complex and variable loads, which lead to a multiaxial and random/variable amplitude stress/strain state. Hence, this study aims how to effectively evaluate the multiaxial random/variable amplitude fatigue life.

Recent studies on critical plane method under multiaxial random/variable amplitude loading are reviewed, and the computational framework is clearly presented in this paper.

Some basic concepts and latest achievements in multiaxial random/variable amplitude fatigue analysis are introduced. This review summarizes the research status of four main aspects of multiaxial fatigue under random/variable amplitude loadings, namely multiaxial fatigue criterion, method for critical plane determination, cycle counting method and damage accumulation criterion. Particularly, the latest achievements of multiaxial random/variable amplitude fatigue using critical plane methods are classified and highlighted.

This review attempts to provide references for further research on multiaxial random/variable amplitude fatigue and to promote the development of multiaxial fatigue from experimental research to practical engineering application.

Improving the diversity of recommendation information has become one of the latest research hotspots to solve information cocoons. Aiming to achieve both high accuracy and diversity of recommender system, a hybrid method has been proposed in this paper. This study aims to discuss the aforementioned method.

This paper integrates latent Dirichlet allocation (LDA) model and locality-sensitive hashing (LSH) algorithm to design topic recommendation system. To measure the effectiveness of the method, this paper builds three-level categories of journal paper abstracts on the Web of Science platform as experimental data.

(1) The results illustrate that the diversity of recommended items has been significantly enhanced by leveraging hashing function to overcome information cocoons. (2) Integrating topic model and hashing algorithm, the diversity of recommender systems could be achieved without losing the accuracy of recommender systems in a certain degree of refined topic levels.

The hybrid recommendation algorithm developed in this paper can overcome the dilemma of high accuracy and low diversity. The method could ameliorate the recommendation in business and service industries to address the problems of information overload and information cocoons.

The purpose of this paper is to introduce the modeling and implementation of a novel multimode amphibious robot, which is used for patrol and beach garbage cleaning in the land–water transition zone.

Starting from the design idea of multimode motion, the robot innovatively integrates the guiding fin and wheel together, is driven by the same motor and can achieve multimodal motion such as land, water surface and underwater with only six actuated degrees of freedom. The robot dispenses with the transmission mechanism by directly connecting the servo motor with a reducer to the actuator, so it has the characteristics of simplifying the structure and reducing the quality. And to the best of the authors' knowledge, the design of the robot can be considered the minimal configuration of amphibious robots with the same locomotion capabilities.

Based on the classical assumptions of underwater dynamics analysis, this paper uses basic airfoil theory to analyze the dynamics of the robot’s horizontal and vertical motions and establishes its simplified dynamics model. Also, the underwater motion of the robot is simulated, and the results are in good agreement with the existing research results. Finally, to verify the feasibility of the robot, a prototype is implemented and fully evaluated by experiments. Experimental results show that the robot can reach the maximum speed of 2.5 m/s and 0.3 m/s on land and underwater, respectively, proving the effectiveness of the robot.

The robot has higher work efficiency with the powerful multimode motion, and its simplified structure makes it more stable while costing less.

In recent years, online public opinion reversal incidents have been occurring frequently, which has increased the complexity of the evolution of online public opinion, and they have become a difficult issue for public opinion management and control. It is of great significance to explore the regularity of online public opinion reversal.

Combined with the grey characteristics of online public opinion information, a grey graphical evaluation review technique (G-GERT) network model is constructed based on kernel and grey degree, and the frequency, probability and time of online public opinion reversal nodes are calculated using C-marking method and Z-marking method.

Throughout the online public opinion reversal events, there are all repeated outbreak nodes occurring, so the authors regard the repeated occurrence of outbreak nodes as reversal. According to the average frequency, probability and time of repeated outbreak nodes in the G-GERT network model, the authors predict the corresponding key information of reversal. It can simulate the evolution process of public opinion events accurately.

The G-GERT network model based on kernel and grey degree reveals the regulation of public opinion reversal, predicts the frequency, probability and time of reversal nodes, which are the most concerned and difficult issues for decision-makers. The model provides the decision basis and reference for government decision-making departments.

This chapter focuses on the Chinese cross-border merger and acquisition (M&A) amid the rising trend of multinational companies from emerging economies. Based on a systematic review of published papers in top international business/strategy/organization journals on Chinese overseas M&A, we offer a tentative multilevel framework to consolidate the past achievement, consider contemporary debates, so as to direct future research efforts. We suggest that Chinese overseas M&A research should emphasize on a process perspective ranging from pre-acquisition to post-acquisition. In addition, qualitative research and methodological pluralism should be embraced to achieve this goal due to the nature of this emerging field of Chinese cross-border M&A. By allocating the extant literature into the multilevel framework, we articulate the demand and identify several potential topics for scholarly inquiry in the future in order to gain a nuanced understanding of this important phenomenon of Chinese cross-border M&A for both China and the rest of the world.

This paper points out new directions for the deepening and broadening of the institution-based view, by drawing on three streams of research with which I have been involved recently: (1) outward foreign direct investment from emerging economies, (2) bankruptcy laws and entrepreneurship development, and (3) institution-based research focusing on Africa. Such deepening has been accomplished by enhancing our institution-based understanding of foreign direct investment with a focus on emerging multinationals, while broadening has been done both substantively by probing into the impact of bankruptcy laws on entrepreneurship development around the world and geographically by calling for enhanced research attention on Africa via an institution-based lens.

Self-report questionnaires are the predominant method used in human resource management (HRM) research to assess employees’ work-related psychological constructs (e.g., processes, states, and attributes). However, this method is associated with significant shortcomings, including the introduction of self-serving bias and common method variance when used exclusively. In this chapter, the authors challenge the assumption that individuals themselves are the only accurate source of the self-focused information collected in HRM research. Instead, the authors propose that other-ratings – ratings of a target individual that are provided by a workplace observer, such as a coworker, supervisor, or subordinate – can accurately assess commonly measured work-related psychological constructs. The authors begin by explaining the advantages of other-ratings for HRM research and practice, reviewing the history of other-ratings and how they emerged in the personality and person-perception literature, and outlining how they have been used in HRM research to date. Then, the authors build upon Funder’s (1995) realistic accuracy model to develop a theoretical argument detailing why workplace others should be able to accurately judge how another employee thinks and feels about work. Next, the authors highlight existing evidence in the literature on the accuracy of other-ratings and present the results of a preliminary meta-analysis on the ability of other-ratings to predict self-ratings of work-related psychological constructs. Finally, the authors discuss potential moderators of other-rating accuracy and reflect on a number of practical considerations for researchers looking to use other-ratings in their own work. The authors intend for this chapter to meaningfully contribute to the larger conversation on HRM research methods. Other-ratings are a simple, yet powerful, addition to the methodological toolkit of HRM researchers that can increase flexibility in research design and improve the overall quality of research.