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In an integrated circuit (IC) substrate, more fillers, including talcum powder and aluminium hydroxide, are added, which leads to much higher rigidity and hardness compared with a traditional printed circuit board. However, the micro drilling of IC substrates is harder. This paper aims to test the drilling process of IC substrates to improve the drilling process and the micro hole quality.

Substrate drilling by a micro drill with 0.11-mm diameter was used under several drilling conditions. The influence of drilling conditions on the drilling process was observed. Drilling forces, drill wear and micro hole quality were also studied.

The deformation circle around holes, hole location accuracy, bugle hole and burrs were the major defects of micro holes that were observed during the drilling of the substrate. Reducing the drilling force and drill wear was the effective way to improve hole quality.

The technology and manufacturing of IC substrates has been little investigated. Research data on drilling IC substrates is lacking. The micro hole quality directly affects the reliability of IC substrates. Thus, improving the drilling technology of IC substrates is very important.

Compared with the traditional printed circuit board (PCB) drilling process, the technology of drilling IC substrate is facing more problems, such as much smaller hole diameter, more intensive hole space, thinner sheet and more complicated materials are drilled in process. Moreover, the base material of IC substrate is different from traditional PCB, more kinds of fillers added in IC substrate which make the drill worn seriously during drilling process. Micro-drills wear and micro holes quality are the most important questions when drilling IC substrate so far. Wear morphology of micro-drill, holes wall roughness and hole location accuracy are researched in this paper. The influence factors of micro-drills wear and micro holes quality are also studied in this drilling process. The paper aims to discuss these issues.

Two drills with same structure and different diameter are used to drill different stacks of IC substrate and drill different holes in this paper. There are four experiments made and the drilling parameters including spindle speed (n), feed rate (v_f) and retraction speed (v_r) are recommended by drill manufacturing company. Wear morphologies of drill are observed, holes wall roughness (R_max) and holes location accuracy (C_pk) are measured in this paper. Analyzing the main factors influence on drill wear, holes wall roughness and holes location accuracy through these experiments.

The micro-drills of IC substrate wear more severely compared with other material of PCB through the experimental results in this paper. Drill diameter has influence on micro-drill wear when drilling IC substrate, the smaller of drill is, the more severely of micro-drill wears. Drill diameter affect the holes wall roughness too, the holes wall roughness of larger holes is better than smaller one in a certain range. The drilled holes number also has influence on micro-drills wear, holes wall roughness and holes location accuracy. The more drilled holes, the seriously of micro-drills wear, and the worn drill would destroy the hole quality. Therefore, the more drilled holes lead the bad holes wall roughness and holes location accuracy in this paper. In addition, stacks of IC substrate affect much on the holes location accuracy, the more stacks, the worse holes location accuracy.

Chinese Mainland is obviously lagging behind in technology and manufacturer of IC substrate which is incompatible with the nation circumstances. There is few research of drilling IC substrate in China and research data are lacking so far. It is most necessary to improve the technology level of drilling IC substrate in China. In order to reduce the wear of micro-drills and improve the quality of micro-holes, many experimental tests about drilling IC substrate are researched in this paper.

This purpose of this paper is to propose a recommendation approach for information retrieval.

Relevant results are presented on the basis of a novel data structure named FPT‐tree, which is used to get common interests. Then, data is trained by using a partial back‐propagation neural network. The learning is guided by users' click behaviors.

Experimental results have shown the effectiveness of the approach.

The approach attempts to integrate metric of interests (e.g., click behavior, ranking) into the strategy of the recommendation system. Relevant results are first presented on the basis of a novel data structure named FPT‐tree, and then, those results are trained through a partial back‐propagation neural network. The learning is guided by users' click behaviors.

This study investigates the direct influence of ambidextrous leadership on employees’ innovation behaviour, the mediating role of innovative self-efficacy and harmonious work passion, and the moderating role of Zhong-Yong thinking.

The authors conducted a series of questionnaire surveys to collect data in three time periods and from multiple sources; 332 supervisor–subordinate matched samples were obtained. The hypothesised relationships were tested using structural equation modelling and ProClin.

Ambidextrous leadership is positively associated with employees’ innovation behaviour, while innovative self-efficacy and harmonious work passion play mediating roles. The analysis further confirms that innovative self-efficacy and harmonious work passion play a chained double-mediating role between ambidextrous leadership and employees’ innovation behaviour, while Zhong-Yong thinking plays moderating roles between ambidextrous leadership and innovative self-efficacy and between ambidextrous leadership and harmonious work passion.

This study demonstrates the influence of ambidextrous leadership on employees’ innovation behaviour, specifically the role of ambidextrous leadership, and extends the relationship’s theoretical foundation. It is also expected to provide inspiration and serve as a reference for local Chinese management.

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.

Zhong-yong thinking is a code of conduct of the Chinese people. The purpose of this study is to explore the relationship among Zhong-yong thinking, social capital, knowledge sharing behavior, and employee survival ability.

Zhong-yong thinking including multi-thinking, integration and harmony, taking a case study of private enterprise in Guangxi of China. Based on the literature, the establishment of the theoretical model and hierarchical regression analysis are explored.

The multi-thinking, integration and harmony of Zhong-yong thinking have a significant positive effect on social capital and employee survival ability. In addition, employee survival ability is positively affected by social capital. Moreover, knowledge sharing behavior has a positive moderating between the multi-thinking dimension of Zhong-yong thinking and social capital, and the remaining dimensions have no moderating effect. Knowledge sharing behavior has no moderating effect on the relationship between social capital and employee survival ability.

Zhong-yong thinking and social capital are actively affecting employee survival ability. Therefore, companies need to work harder to improve their employees' Zhong-yong thinking and social capital.

The paper extends Zhong-yong thinking, social capital and employee survival ability literature to fill gaps in how China people require to both access employee survival ability. The policy value of the work is in suggesting ways to facilitate employee survival ability of China.

Distribution of long-haul goods could be managed via multimodal transportation networks where decision-maker has to consider these factors including the uncertainty of transportation time and cost, the timetable limitation of selected modes and the storage cost incurred in advance or delay arriving of the goods. Considering the above factors comprehensively, this paper establishes a multimodal multi-objective route optimization model which aims to minimize total transportation duration and cost. This study could be used as a reference for decision-maker to transportation plans.

Monte Carlo (MC) simulation is introduced to deal with transportation uncertainty and the NSGA-II algorithm with an external archival elite retention strategy is designed. An efficient transformation method based on data-drive to overcome the high time-consuming problem brought by MC simulation. Other contribution of this study is developed a scheme risk assessment method for the non-absolutely optimal Pareto frontier solution set obtained by the NSGA-II algorithm.

Numerical examples verify the effectiveness of the proposed algorithm as it is able to find a high-quality solution and the risk assessment method proposed in this paper can provide support for the route decision.

The impact of timetable on transportation duration is analyzed and making a detailed description in the mathematical model. The uncertain transportation duration and cost are represented by random number that obeys a certain distribution and designed NSGA-II with MC simulation to solve the proposed problem. The data-driven strategy is adopted to reduce the computational time caused by the combination of evolutionary algorithm and MC simulation. The elite retention strategy with external archiving is created to improve the quality of solutions. A risk assessment approach is proposed for the solution scheme and in the numerical simulation experiment.

The business world today is witnessing ever-growing disruption. This study highlights corporate social responsibility (CSR) as an effective strategy for firms in disrupted industries to consider in order to differentiate themselves and to increase their chance of survival facing disruption.

In this study, the authors test the hypotheses using a multilevel modeling (MLM) design to capture the group and intergroup effects at the industry level and at the firm level. The empirical analysis is based on a panel sample of 1,193 firms over the 10-year period from 2010 to 2019.

The empirical analysis indicates that CSR has a positive impact on corporate financial stability and the effect is especially significant for firms in disrupted industries. Further investigation suggests that this positive effect largely runs through traits of the social pillar, such as human rights, employee relations, customer protection, product responsibility and community impact. The results are robust after controlling for other firm-specific characteristics and after addressing endogeneity concerns.

This study examines whether, and through which channel, CSR helps enhance corporate financial stability and mitigate bankruptcy risk in disrupted industries. To the best of the authors' knowledge, this study is the first attempt to explore the use of CSR as an effective strategic response to disruption. Further analysis indicates that the social capital built through CSR plays an important role in helping enhance corporate financial stability.

The purpose of this study is to explore the determinants of teachers’ continuance intention concerning cloud services.

This study uses a cloud service, namely, Google Sites, to support teacher collaboration and further develop a research model to explore the determinants of their continued usage intention.

The findings reveal that continued intention to use the cloud services is primarily determined by their attitude towards using it; attitude towards using is affected by perceived ease of use and perceived usefulness; and perceived ease of use is influenced by facilitating conditions, while perceived usefulness is influenced by social influence.

This study determines that teachers intend to continue using cloud services once training in using such services has been provided and if they hear favourable opinions from others.

The paper enables us to better understand factors affecting teachers' continuance intention toward cloud services.