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The purpose of this paper is to investigate how Chinese firms’ innovation is related to their perceived incentives and pressures from the transitioning institutional environment.

A sample of 166 manufacturing firms located in Guangdong Province (China) is analyzed using binomial and moderated multiple regression models.

The results show that institutional incentives are more effective in promoting incremental innovations than radical ones, whereas institutional pressures are more pronounced in facilitating radical innovations than incremental ones. In addition, the interaction between the two divergent institutional forces is negatively related to innovation performance.

The findings inform managers and policy makers in institutional transition environments to consider and balance the effects of institutional forces. Firms should match the institutional incentives and pressures with their own innovation objectives in terms of incremental or radical goals, and take caution to deal with the divergent institutional directions, so as to avoid the negative interaction effects. Policy makers should take a systems approach when considering the incentive-based and/or command-and-control designs of innovation policies and regulations.

The study contributes to existing literature on institutions and innovation by disentangling incentive and pressure effects of institutions, regulation and innovation policies, as well as the combined and interaction effects intrinsic within institutional mixes.

The innovation process demands an interaction between environment agents, knowledge generators and policies of incentive for innovation and not only development by companies. Universities have gradually become the core of the knowledge production system and, therefore, their role regarding innovation has become more important and diversified. This study is aimed at identifying the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.

This study is aimed at identifying, based on a systematic literature review, the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.

The analysis of the 72 selected articles enabled identifying 15 mechanisms of U–I collaboration, proposing a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process.

In this paper, the authors screened nearly 1,500 papers and analyzed in detail 86 papers addressing U–I collaboration, mechanisms of U–I collaboration and operationalization steps of the U–I collaboration process. This paper provides a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process. This research contributes to both theory and practice by highlighting managerial aspects and stimulating academic research on such timely topic.

This paper throws light on some of the nature of artificial intelligence (AI) development, which will serve as a starter for helping to advance its development.

This work reveals the evolutions and trends of AI from four dimensions: research, output, influence and competition through leveraging academic knowledge graph with 130,750 AI scholars and 43,746 scholarly articles.

The authors unearth that the “research convergence” phenomenon becomes more evident in current AI research for scholars' highly similar research interests in different regions. The authors notice that Pareto's principle applies to AI scholars' outputs, and the outputs have been increasing at an explosive rate in the past two decades. The authors discover that top works dominate the AI academia, for they attracted considerable attention. Finally, the authors delve into AI competition, which accelerates technology development, talent flow, and collaboration.

The work aims to throw light on the nature of AI development, which will serve as a starter for helping to advance its development. The work will help us to have a more comprehensive and profound understanding of the evolutions and trends, which bridge the gap between literature research and AI development as well as enlighten the way the authors promote AI development and its strategy formulation.

Significant amount of harmonics and inter-harmonics are being injected into the power system because of the increasing use of power electronics and large non-liner loads. Therefore, analyzing their contents in real time is necessary.

The frequency and phase of an electric power harmonic or inter-harmonic can be estimated by using the discrete spectrum energy center of symmetric windows, the amplitude calculation of an electric power harmonic or inter-harmonic can be calculated by using the Pasival theorem, and their relative estimation error is only decided by the distribution of windows’ energy in the frequency domain, which equals the proportion of the spectrum energy occupied in the side lobe to the whole.

The results of the digital simulation and experimental tests show that the method proposed in this paper has the same measurement precision as and more advantages in computational complexity and burden over other methods, which are based on multipoint interpolation or interpolation polynomial windowed.

The method is very suitable to be used to real-time measurement in a single chip DSP micro-processor.

Online product ratings play an important role in the decision-making process of consumers, which are not only sources of information used by consumers to understand the function and quality of a product or service but also sources of information used to find desirable products. The purpose of this paper is to develop a decision-based method for supporting the purchase decisions of consumers based on not only the online product ratings but also the actual product attributes.

First, two types of utility values are designed to measure the preference of the consumer based on either online ratings or actual product attributes. Then, the traditional TOPSIS method is adopted to achieve a comprehensive value by integrating the two types of utility values so that all of the alternative products can be ranked. Further, a product selection support system prototype is designed and developed to support the purchase decisions of consumers.

To help consumers select desirable products efficiently, it is necessary to develop a product selection method based on the online ratings of alternative products and consumer expectations.

The research shows that the proposed method can not only support consumers’ purchase decisions based on a large number of online product ratings but also help manufacturers to find out consumers’ demands or requirements on products so as to facilitate the design of new products or the improvement of products. On the basis of the proposed method, the developed system prototype is helpful for consumers to select desirable products.

To support the purchase decisions of consumers, a new decision-based method for selecting desirable online products is proposed.

The purpose of this paper is to numerically study the influence of wall conduction on the heat transfer of supercritical n-decane in the active regenerative cooling channels.

A horizontally placed rectangular pipe with a solid zone and another one without a solid zone were used. A drastic variation of thermo-physical properties was emphatically addressed. After the verification of mesh and turbulence models comparing with the experimental results, a mesh number of 4.5 M and the low Reynolds number SST k-ω turbulence model were chosen. The solution of the governing equations and the acquisition of the numerical results were executed by the commercial software FLUENT 2020 R1.

The numerical results indicate that there is a heat transfer deterioration (HTD) potential for the upper wall, lower wall and sidewall with the decrease of mass flux. Due to wall conduction, the distribution of the fluid temperature at spanwise-normal planes becomes uniform and this feature also takes advantage of the relatively uniform transverse velocity. For the streamwise-normal planes, the low fluid temperature appears close to the upper wall at the region near the sidewall and vice versa for the region near the centre. Undoubtedly, the secondary flow at the cross-section plays a crucial role in this process and the relatively cool mainstream is affected by the vortices.

This study warns that the wall conduction must be considered in the practical design and thermal optimization due to the sensibility of thermo-physical properties to the heat flux. The secondary flow caused by the buoyancy force (gravity) plays a significant role in the supercritical heat transfer and mixed convection heat transfer should be further studied.

When a vehicle passes through a long highway tunnel, the smoke it discharges accumulates in the tunnel. High smoke concentration has an important influence on the driver’s health and driving safety. The use of numerous jet fans to diffuse the smoke causes excessive energy consumption, so it is of significant practical value to design suitable tunnel ventilation.

The study is based on the continuum hypothesis, incompressible hypothesis, steady flow hypothesis and similar hypothesis of gas in a long highway tunnel. These hypotheses calculate the gas emissions and wind demand in a long highway tunnel given the deployment of the jet fan program.

This program selects each of the two 1120-type jet machine group and sets up 13 groups; each group has an interval of 184.5 m in the end. The analysis of air test results when the tunnel is in operation shows that CO and smoke concentrations meet the design requirements, which can provide reference for a similar engineering design later.

At present, a highway tunnel is recognized at home and abroad by means of clearance of longitudinal ventilation, which is 2,000 m. In view of this, this paper is based on the theory of longitudinal jet ventilation of a highway tunnel, whose length is more than 2,000 m, to calculate the ventilation and apply it to a tunnel’s ventilation design.

Talent development has become an important policy given prominence by the Macao government since Fernando Chui became its Chief Executive. The purpose of this paper is to review human resources and talent development policies in Macao and discuss the difficulties and challenges that they pose.

Using Macao as a case study the paper indicates the difficulties and challenges experienced by emerging markets in fostering talent development for the sustainability of their local economies.

This paper finds that, as an emerging market, Macao has to solve and overcome its institutional deficiencies (namely, by the establishment of both a professional registration regime and the means to gather metadata to enable predictions of the talents needed for the local economy and their potential scale) so as to please stakeholders. Only then can it truly introduce talent development schemes and programs.

There have been very few studies on Macao’s talent development initiative. This paper tries to fill this gap in the existing understanding of talent development.

This study aims to assess the use of variational quantum imaginary time evolution for solving partial differential equations using real-amplitude ansätze with full circular entangling layers. A graphical mapping technique for encoding impulse functions is also proposed.

The Smoluchowski equation, including the Derjaguin–Landau–Verwey–Overbeek potential energy, is solved to simulate colloidal deposition on a planar wall. The performance of different types of entangling layers and over-parameterization is evaluated.

Colloidal transport can be modelled adequately with variational quantum simulations. Full circular entangling layers with real-amplitude ansätze lead to higher-fidelity solutions. In most cases, the proposed graphical mapping technique requires only a single bit-flip with a parametric gate. Over-parameterization is necessary to satisfy certain physical boundary conditions, and higher-order time-stepping reduces norm errors.

Variational quantum simulation can solve partial differential equations using near-term quantum devices. The proposed graphical mapping technique could potentially aid quantum simulations for certain applications.

This study shows a concrete application of variational quantum simulation methods in solving practically relevant partial differential equations. It also provides insight into the performance of different types of entangling layers and over-parameterization. The proposed graphical mapping technique could be valuable for quantum simulation implementations. The findings contribute to the growing body of research on using variational quantum simulations for solving partial differential equations.