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This paper compares four external technology acquisition channels' (foreign technology transfer, exporting, inter-industry R&D spillover and domestic technology transfer) contributions to Chinese high-tech enterprises' innovation in the moderating role of absorptive capacity (AC).

Using technological catch-up theory and China Statistics Yearbook on High Technology Industry, this research investigates 16 Chinese high-tech industries from 2004 to 2015 via negative binomial regression.

The results show that indigenous knowledge transfer improves foreign-funded enterprises' (FFEs) innovation, while transnational knowledge transfer is the main channel for state-owned enterprises' (SOEs) technology acquisition. AC strengthens the positive relationship between transnational knowledge transfer and innovation in SOEs and improves FFEs' innovation and exported tacit knowledge absorption.

This study contributes to the literature on external technology acquisition (ETA) and innovation by examining the different mechanism of ETA instead of isolated strategy considering the AC and ownership structure of Chinese high-tech enterprises, which enrich the technological catch-up theory.

This paper aims to present a dynamic reliability model of scraper chains based on the fretting wear process and propose a reasonable structural optimization method.

First, the dynamic tension of the scraper chain is modeled by considering the polygon effect of the scraper conveyor. Then, the numerical wear model of the scraper chain is established based on the tangential and radial fretting wear modes. The scraper chain wear process is introduced based on the diameter wear rate. Furthermore, the time-dependent reliability of scraper chains based on the fretting wear process is addressed by the third-moment saddlepoint approximation (TMSA) method. Finally, the scraper chain is optimized based on the reliability optimization design theory.

There is a correlation between the wear and the dynamic tension of the scraper conveyor. The unit sliding distance of fretting wear is affected by the dynamic tension of the scraper conveyor. The reliability estimation of the scraper chain with incomplete probability information is achieved by using the TMSA for the method needs only the first three statistical moments of the state variable. From the perspective of the chain drive system, the reliability-based optimal design of the scraper chain can effectively extend its service life and reduce its linear density.

The innovation of the work is that the physical model of the scraper chain wear is established based on the dynamic analysis of the scraper conveyor. And based on the physical model of wear, the time-dependent reliability and optimal design of scraper chains are carried out.

This paper mainly aims to deal with the problems of uncertainties including modelling errors, unknown dynamics and disturbances caused by load mutation in control of permanent magnet synchronous motor (PMSM).

This paper proposes an enhanced speed sensorless vector control method based on an active disturbance rejection controller (ADRC) for a PMSM. First, a state space model of the PMSM is obtained for the field orientation control strategy. Second, a sliding mode observer (SMO) based on back electromotive force (EMF) is introduced to replace the encode to estimate the rotor flux position angle and speed. Third, an infinite impulse response (IIR) filter is introduced to eliminate high frequency noise mixed in the output of the sliding mode observer. In addition, a speed control method based on an extended state observer (ESO) is proposed to estimate and compensate for the total disturbances. Finally, an experimental set-up is built to verify the effectiveness and superiority of the proposed ADRC-based control method.

The comparative experimental results show that the proposed speed sensorless control method with the IIR filter can achieve excellent robustness and speed tracking performance for PMSM system.

An enhanced sensorless control method based on active disturbance rejection controller is designed to realize high precision control of the PMSM; the IIR filter is used to attenuate the chattering problem of traditional SMO; this method simplifies the system and saves the total cost due to the speed sensorless technology.

The use of sensorless can reduce costs and be more beneficial to actual industrial application.

The proposed enhanced speed sensorless vector control method based on an ADRC with the IIR filter enriches the control method of PMSM. It can ameliorate system robustness and achieve excellent speed tracking performance.

This paper aims to investigate whether a complementary effect exists between government R&D subsidies (GRSs) and intellectual property rights (IPR) protection on innovation performance in the pharmaceutical manufacturing industry in China. This paper also attempts to understand whether this complementary effect is significantly different across China’s eastern, central and western regions.

The study sample comprised 28 provinces involved in the pharmaceutical manufacturing industry in China from 2003 to 2014. Ordinary least squares was used to test the complementary effects of GRSs and IPR protection on innovation performance. The seemingly unrelated estimation test was also applied to ascertain whether differences existed between the eastern and western regions.

A complementary effect between GRSs and IPR protection in terms of improving the innovation of pharmaceutical manufacturers was found to exist only in eastern and western regions. There was no significant difference in the complementary effect between GRSs and IPR protection in terms of improving innovation among the three regions. Without considering the interaction effect of GRSs and IPR protection, the GRSs were negatively associated with innovation in the eastern region, but positively related to the innovation in central region.

This study contributes to the literature on government policies and innovation by incorporating the interaction effect of GRSs and IPR protection on innovation in the context of a high-tech industry (pharmaceutical manufacturing) in an emerging economy (China). It also explores the internal differences in the influence of this complementary effect on innovation in an emerging economy, enriching the institution-based view.

This paper aims to improve the scene sense of a virtual scene, the welding model of a virtual reality system of riser automatic equipment was constructed using Unity3D and UG software, which mainly included a welding car, welding guide rail, welding power supply, virtual camera and other equipment and the model was rendered.

The human-computer interaction page and simulation test of the system was produced using the user interface GUI system for creating a human-computer interaction scene. The operator could capture the welding status of the physical equipment accurately and in real-time so the virtual reality technology was very suitable for the remote monitoring operation integrated with the welding system.

Human-computer interaction design and collision detection were realized. In addition, the system simulation experiment was accomplished. With the continuous improvement and development of virtual reality technology real-time virtual simulation and monitoring, technology will become the main development trend.

Based on virtual reality, the monitoring system can capture the operation status of physical welding equipment in real-time and accurately, which is very suitable for remote monitoring operation integrated with the welding system and also conducive to improving the monitoring level of the welding process.

This technology is time-saving and money-saving, for the operators do not have to be in a real welding environment and therefore they can get away from dangerous places. Consequently, it can avoid unnecessary injuries and problems.

This technology can replace people to enter the dangerous and extreme environment to carry out welding operation, so it becomes the most effective means of nuclear power plant maintenance, space structure construction and marine engineering construction. In addition, it is time-saving and money-saving.

With the rapid development of virtual reality technology in recent years, it is a new research direction to apply virtual reality technology to the remote welding operation. This technology is different from the traditional way of welding for the operators can stay away from the welding scene especially some dangerous places.

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.

Content analysis is a methodology that has been used in many academic disciplines as a means to extract quantitative measures from textual information. The purpose of this paper is to document the use of content analysis in the supply chain literature. The authors also discuss opportunities for future research.

The authors conduct a literature review of 13 leading supply chain journals to assess the state of the content analysis-based literature and identify opportunities for future research. Additionally, the authors provide a general schema for and illustration of the use of content analysis.

The findings suggest that content analysis for quantitative studies and hypothesis testing purposes has rarely been used in the supply chain discipline. The research also suggests that in order to fully realize the potential of content analysis, future content analysis research should conduct more hypothesis testing, employ diverse data sets, utilize state-of-the-art content analysis software programs, and leverage multi-method research designs.

The current research synthesizes the use of content analysis methods in the supply chain domain and promotes the need to capitalize on the advantages offered by this research methodology. The paper also presents several topics for future research that can benefit from the content analysis method.

Improving a startup’s ability to obtain funding is critical to the survival of the organization. Although existing studies have observed various biases in investment decisions, few have studied the neural mechanisms behind such behavioral observations. We propose to apply cutting-edge neuroscientific techniques to uncover the neural processes engaged during pitches by entrepreneurs to investors and to use this new knowledge to identify strategy artifacts promoting pitch success. We hypothesize that pitches are dynamically shaped by covert cognitive, emotional, and social processes, which are in turn influenced by tactical approach (story-telling vs dry facts), physical context (online vs in-person), and demographics (gender, ethnicity). The role of inter-brain synchrony (i.e., correlation of cortical activity between brains) – within the startup team or between the entrepreneurs and investors – in pitch outcomes remains unknown. By uncovering the covert processes that mediate pitch outcomes, we provide an evidence-based, scientific approach to improving pitch success.

The purpose of this paper is to analyze the variation of temperature field, pressure field and deformation of hydrostatic thrust bearing under different working conditions, so as to provide a theoretical basis for improving accuracy and reliability.

In this study, the double rectangular hydrostatic bearing of type Q1-224 was selected as the research object, and the simulation was carried out according to different working conditions, and the obtained data were summarized regularly.

It is found that the overall temperature of hydrostatic bearing increases with the increase of speed and load, and the increase in load will result in a larger pressure distribution which first increases and then decreases with the speed. The deformation trend of the deformation field is found, and it is found that the force deformation is larger than the thermal deformation at low rotational speed, and the thermal deformation is larger than the force deformation at high rotational speed.

In this study, the fluid-structure coupling method of conjugate heat transfer is applied to study the whole hydrostatic bearing. Most of the previous studies only studied the oil film and considered the influence of the convective heat transfer between the hydrostatic bearing and the air in heat transfer, which is rarely seen in the previous research literature.

The set-union knapsack problem is one of the most significant generalizations of the Non-deterministic Polynomial (NP)-hard 0-1 knapsack problem in combinatorial optimization, which has rich application scenarios. Although some researchers performed effective algorithms on normal-sized instances, the authors found these methods deteriorated rapidly as the scale became larger. Therefore, the authors design an efficient yet effective algorithm to solve this large-scale optimization problem, making it applicable to real-world cases under the era of big data.

The authors develop three targeted strategies and adjust them into the adaptive tabu search framework. Specifically, the dynamic item scoring tries to select proper items into the knapsack dynamically to enhance the intensification, while the age-guided perturbation places more emphasis on the diversification of the algorithm. The lightweight neighborhood updating simplifies the neighborhood operators to reduce the algorithm complexity distinctly as well as maintains potential solutions. The authors conduct comparative experiments against currently best solvers to show the performance of the proposed algorithm.

Statistical experiments show that the proposed algorithm can find 18 out of 24 better solutions than other algorithms. For the remaining six instances on which the competitor also achieves the same solutions, ours performs more stably due to its narrow gap between best and mean value. Besides, the convergence time is also verified efficiency against other algorithms.

The authors present the first implementation of heuristic algorithm for solving large-scale set-union knapsack problem and achieve the best results. Also, the authors provide the benchmarks on the website for the first time.