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According to human capital theory, companies derive economic value from the knowledge, skills and abilities (KSAs) of their employees. Research conducted by strategic human resource management has focused on how investment in human capital can create a competitive advantage for an organization. The purpose of the paper is, therefore, to investigate how the choice of different human capital acquisition strategies – “make or buy” – can influence employee attitudes and behavior.

This study explores the relationship between internal and external human capital strategies and employee’s attitudes and behavior in Taiwan's IC (integrated circuit) design industry. The cross-sectional dataset derives from a sample of 49 human resource departments and 497 employees from 25 different IC design companies.

The findings indicate that the decisions made on human capital strategies have an important influence on employee’s attitude and behavior. The results also show that a climate of trust and perceived organizational support is a cross-level mechanism for both human capital strategy and employees' attitudes and behavior.

There has been little research on the cross-level analysis of human capital acquisition strategies that can influence employee’s attitudes and behavior. This study verified that internal and external human capital strategies do affect employees' individual perceptions of organizational support via the organizational-level climate of trust, which in turn influences employees' attitudes and behavior. This cross-level mechanism indeed will facilitate new insights into the nature of strategic human resource management.

As a kind of NP-hard combinatorial optimization problem, pipe routing design (PRD) is applied widely in modern industries. In the offshore oil and gas industry, a semi-submersible production platform is an important equipment for oil exploitation and production. PRD is one of the most key parts of the design of semi-submersible platform. This study aims to present an improved ant colony algorithm (IACO) to address PRD for the oil and gas treatment system when designing a semi-submersible production platform.

First, to simplify PRD problem, a novel mathematical model is built according to real constraints and rules. Then, IACO, which combines modified heuristic function, mutation mechanism and dynamical parameter mechanism, is introduced.

Based on a set of specific instances, experiments are carried out, and the experimental results show that the performance of IACO is better than that of two variants of ACO, especially in terms of the convergence speed and swarm diversity. Finally, IACO is used to solve PRD for the oil and gas treatment system of semi-submersible production platform. The simulation results, which include nine pipe paths, demonstrate the practicality and high-efficiency of IACO.

The main contribution of this study is the development of method for solving PRD of a semi-submersible production platform based on the novel mathematical model and the proposed IACO.

The aim of this paper is to solve the problem of low accuracy of traditional fatigue crack growth (FCG) prediction methods.

The GMSVR model was proposed by combining the grey modeling (GM) and the support vector regression (SVR). Meanwhile, the GMSVR model parameter optimal selection method based on the artificial bee colony (ABC) algorithm was presented. The FCG prediction of 7075 aluminum alloy under different conditions were taken as the study objects, and the performance of the genetic algorithm, the particle swarm optimization algorithm, the n-fold cross validation and the ABC algorithm were compared and analyzed.

The results show that the speed of the ABC algorithm is the fastest and the accuracy of the ABC algorithm is the highest too. The prediction performances of the GM (1, 1) model, the SVR model and the GMSVR model were compared, the results show that the GMSVR model has the best prediction ability, it can improve the FCG prediction accuracy of 7075 aluminum alloy greatly.

A new prediction model is proposed for FCG combined the non-equidistant grey model and the SVR model. Aiming at the problem of the model parameters are difficult to select, the GMSVR model parameter optimization method based on the ABC algorithm was presented. the results show that the GMSVR model has better prediction ability, which increase the FCG prediction accuracy of 7075 aluminum alloy greatly.

The edge of diesel engine crankshaft main bearing is more likely to fail in its real working condition. This paper aims to study the bearing failure mechanism by finding the relationship between bearing lubrication characteristics and its working condition.

This work builds the mixed lubrication model of crankshaft bearing to analyze the cause of bearing abnormal wear, and the finite difference method was used to solving the average Reynolds equation. During the analysis, journal misaligned angle, external load and roughness are considered.

The result shows that the wear of the diesel engine crankshaft bearing happens in engine startup phase and the bottom of the bearing are more prone to be excessively worn. Under the influence of journal misalignment, bearing asperity contact load and speed range of mixed lubrication will increase markedly. The edge of the bearing will be excessively worn. The effect of misalignment on bearing lubrication performance varies under different shaft rotation speed.

The former research studies on crankshaft bearing either just focused on its lubrication characteristics or interested in its failure types (wear, adhere, cavitation). This paper studies the relationship between bearing failure mechanism and lubrication performance.

Teacher education programmes are critical in developing pre-service teachers’ competencies during the apprenticeship phase (Lim et al., 2010), whereas there is evidence indicating that teacher education programmes depend on curriculum leadership (Robinson et al., 2008). The purpose of this paper is to explore the ways in which curriculum leaders enact their curriculum leadership to enhance teacher education programmes in a context of a normal university in Mainland China.

In this paper, three groups of curriculum leaders, from university, faculty and classroom level, respectively, are interviewed.

This study highlights the significance of curriculum leadership in teacher education programmes enhancement in China, particularly the significant impacts from curriculum leaders’ involvement on the programme processes of planning, implementation and evaluation.

Implications for research include a conceptualization of curriculum leadership in teacher education and pre-service teachers’ training in China, and a theoretical integration of curriculum leadership and the enhancement of teacher education programmes.

Implications for practice regard to restructuring curriculum leadership system and informing curriculum leadership practices, not only in Asian countries, but might be able to shed light on the curriculum leadership development in a range of educational contexts either similar to or different from that of Mainland China. This study thus would contribute to several areas of research.

Digital twin (DT) is an emerging technology that enables sophisticated interaction between physical objects and their virtual replicas. Although DT has recently gained significant attraction in both industry and academia, there is no systematic understanding of DT from its development history to its different concepts and applications in disparate disciplines. The majority of DT literature focuses on the conceptual development of DT frameworks for a specific implementation area. Hence, this paper provides a state-of-the-art review of DT history, different definitions and models, and six types of key enabling technologies. The review also provides a comprehensive survey of DT applications from two perspectives: (1) applications in four product-lifecycle phases, i.e. product design, manufacturing, operation and maintenance, and recycling and (2) applications in four categorized engineering fields, including aerospace engineering, tunneling and underground engineering, wind engineering and Internet of things (IoT) applications. DT frameworks, characteristic components, key technologies and specific applications are extracted for each DT category in this paper. A comprehensive survey of the DT references reveals the following findings: (1) The majority of existing DT models only involve one-way data transfer from physical entities to virtual models and (2) There is a lack of consideration of the environmental coupling, which results in the inaccurate representation of the virtual components in existing DT models. Thus, this paper highlights the role of environmental factor in DT enabling technologies and in categorized engineering applications. In addition, the review discusses the key challenges and provides future work for constructing DTs of complex engineering systems.

The purpose of this paper is to investigate the consequences of two strategies of coordinating the online procurement capability and the online channel management capability on competitive performance.

A research model is presented to examine the performance impacts of these two coordination strategies, namely the balancing strategy (achieving a close match relationship) and the complementing strategy (maintaining the synergy effect), and tested using firm-level data collected from 196 manufacturing firms in China. Garen's two-stage econometric technique was used to identify the impacts of two coordination strategies on competitive performance.

Our study discusses and compares two different coordination strategies of mitigating the operational tensions across processes and deploying resource configurations for improving competitive performance. Our results show that while the balancing strategy can mitigate the risks resulted, the complementing strategy does not create synergistic effects on the focal firms' competitive performance.

The results extend our understanding of the nature of B2B digital process coordination both in IS management and supply chain operations.

This paper aims to introduce a high-temperature grease design method assisted by back propagation neural network (BPNN) and verify its application value.

First, the grease data sets were built by sorting out the base data of greases in a large number of literatures and textbooks. Second, the BPNN model was built, trained and tested. Then, the optimized BPNN model was used to search the unknown data space and find the composition of greases with excellent high-temperature performance. Finally, a grease was prepared according to the selected composition predicted by the model and the high-temperature physicochemical performance, high-temperature stability and tribological properties under different friction conditions were investigated.

Through high temperature tribology experiments, thermal gravimetric analysis and differential scanning calorimetry experiments, it is proved that the high temperature grease prepared based on BPNN has good high-temperature performance.

To the best of the authors’ knowledge, a new method of designing and exploring high-temperature greases is successfully proposed, which is useful and important for the industrial applications.

Babbitt bush is easy to cause severe adhesive wear due to unexpected journal fall. This paper aims to improve wear resistance of Babbitt bush.

A soft/hard hybrid surface mircoprofile of Babbitt alloy/steel was fabricated by a technology of laser texture combined with hot-pressing. The friction and wear performances of bare steel (steel-h), Babbitt bush on steel (steel-s) and Babbitt filled in dimples of steel (steel-hs) were conducted on a ball-on-disc tester under dry and lubricated conditions.

The results showed that wettability of steel-hs was enhanced by forming soft/hard hybrid surface. Compared with steel-s, the stability of friction coefficient curve of steel-hs was improved without increasing coefficient friction. The wear resistance of steel-hs was remarkably enhanced under dry and lubricated conditions.

The originality of this paper is as following: to improve the tribological properties and to prolong service life of steel-s, soft/hard hybrid surface of Babbitt filled in dimples of steel substrate was successfully fabricated by laser texturing combined with hot-pressing. This paper showed that the lipophilicity of steel-hs was best among those of steel-s and steel-h. Babbitt alloy as a soft filler on dimples of steel substrate improved anti-wear of steel-s remarkably. It provides a new way to fabricate Babbitt as bushing on steel substrate.

Copper-graphite (Cu/C) is a type of seal material that has been widely used in liquid rocket engines and with normal metal pairs, has a high wear rate under liquid oxygen lubrication. In this study, bearing steel disks were subjected to a high-temperature oxidization and phosphating progress to create an oxidized tricresyl phosphating film (OTCP) film, using tricresyl phosphate (TCP) as the phosphating solvent. It is hoped that the surface wear rate and friction coefficient can be reduced by this method.

This study aim to form an anti-wear film on the surface of bearing steel, which can significantly improve the lubrication performance of Cu/C and bearing steel. The surfaces of bearing steel disks were dried to remove surface water and then put on a heating plate with a magnetic stirrer and a blue glazed oxide film obtained by heating the disks in the air at 200°C for 1 h. To create the OTCP film, bearing steel disks with a blue glazed oxide film were cleaned ultrasonically three times in ethanol and then placed in baths of TCP. After heating for 2 h at 120°C, excess TCP liquid was removed from the disks using ethanol, leaving an OTCP film on the disk surface.

It was found that steel coated with an OTCP film demonstrated better tribological performance (lower coefficient of fiction and wear rate) when pairing with Cu/C than either oxidized or untreated bearing steel. Additional chemical reactions occur when the oxide disk is immersed in TCP and the FePO₄ film is formed after heating. Additionally, the OTCP film coated steel displayed good corrosion resistance, as confirmed by electrochemical corrosion tests. This finding demonstrates the potential for this process in the aerospace industry.

The preparation of OTCP films via high-temperature oxidization and phosphating of bearing steel was demonstrated, with the tribological properties of the OTCP film being investigated alongside those of the original surface and an oxidized film surface. The fabrication of OTCP films is easily scaled up and exhibits significant advantages as a new technology for applications in mechanical contact seal lubrication.