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Extant research on the crowding-out effects of government subsidies on the positive role of firm innovation resources or activity remains limited. This paper aims to investigate the crowding-out effects of subsidies on the utilization of technological capabilities and also the contingency mechanisms of market-oriented economy based on the resource-based view (RBV), given the co-existence of the subsidies and technological capabilities for firm innovation in transitional economy.

This paper used panel data of 115 Chinese high-tech firms from 2002 to 2010. Fixed-effects model was used to test several hypotheses.

This paper empirically demonstrates that the subsidies crowd out the utilization of firms’ technological capabilities for invention outcomes in the near-term. Furthermore, this paper finds that the crowding-out effects are weaker when firms have high export intensity or are located in provinces with high market-oriented systems.

The findings of this paper apply to Chinese firms. Future research could test their generalizability to different samples and other transitional economies.

This paper highlights the crowding-out effects of the subsidies, revealing that high-tech firms should balance the direct effects and crowding-out effects of the subsidies.

This paper highlights the neglected interactions between the subsidies and technological capabilities based on RBV and provides a more nuanced understanding of the crowding-out effects of the subsidies in transitional economy.

In the brain imaging based on electrical impedance tomography, it is sometimes not able to attach 16 electrodes due to space restriction caused by craniotomy. As a result of this, the number of boundary measurements decreases, and spatial resolution of reconstructed conductivity distribution is reduced. The purpose of this study is to enhance reconstruction quality in cases of limited measurement.

A new data expansion method based on the shallow convolutional neural network is proposed. An eight-electrode model is built from which fewer boundary measurements can be obtained. To improve the imaging quality, shallow convolutional neural network is constructed which maps limited voltage data of the 8-electrode model to expanded voltage data of a quasi-16-electrode model. The predicted data is compared with the quasi-16-electrode data. Besides, image reconstruction based on L1 regularization method is conducted.

The results show that the predicted data generally coincides with the quasi-16-electrode data. It is found that images reconstructed with the data of eight-electrode model are the poorest. Nevertheless, imaging results when the limited data is expanded by the proposed method show large improvement, and there is a minor difference with the images recovered with the quasi-16-electrode data. Also, the impact of noise is studied, which shows that the proposed method is robust to noise.

To enhance reconstruction quality in the case of limited measurement, a new data expansion method based on the shallow convolutional neural network is proposed. Both simulation work and phantom experiments have demonstrated that high-quality images of cerebral hemorrhage and cerebral ischemia can be obtained when the limited measurement is expanded by the proposed method.

Electronic word of mouth (eWOM) is a digital marketing method that has been considered by some companies as an effective and efficient approach to enhance social learning and the environment for the customers. A social media user could benefit from gaining information from other users to aid their decision-making process. Instagram is an example of a social media platform that could be utilized for the application of eWOM. It could serve as a source of quality, credible and detailed information, and a channel to increase customer interactions and trust. This study aims to determine the effects of eWOM information generated through Instagram on patients’ intention to join the in vitro fertilization (IVF) programs. By adopting the information acceptance model (IACM) theory, several parameters were evaluated: information quality, credibility, usefulness, adoption, attitude toward information, and purchase intention. The structural equation modeling (SEM) was used to analyze as many as 200 respondents of Morula IVF Jakarta and were active Instagram users. The results showed that the adoption of information and attitude toward information had considerably influenced patients’ intentions to join the IVF programs. Such circumstances might have occurred as a result of the increase in information exchange about IVF, through the discussions and sharing of experiences by patients on Instagram. Furthermore, information usefulness was demonstrated to affect information adoption and was influenced by the credibility of information and attitudes toward information. Nonetheless, one variable which did not display any effects on the usefulness of information was the quality of information. In summary, the characteristics of eWOM information that were conveyed on Instagram could affect the intention of patients in joining the IVF program.

It is suggested that, to be successful, innovation teams should be small and consist of people with key expertise who want to participate and develop new solutions within their organisations. When it comes to conducting innovation work, I suggest shared leadership may be a factor influencing success. In this chapter, a theoretical framework is presented on the shared leadership of innovation teams. The key to establishing shared leadership in innovation teams is to plan for it as the team is created, not after the team has already been formed, as this may result in various problems in the intended innovation project. The proposed framework details key aspects to consider; some of which are related to external factors such as management and resources, and some to internal factors such as the team’s size, competencies, and their ability to develop norms and ways of working together. The proposed framework is applicable for managers, innovation leaders, and team members, and contributes to previous research on shared leadership and innovation leadership. Further research on the proposed framework is suggested.

With significant changes in the aviation industry, various airport–airline arrangements have been formed to achieve alternative objectives. However, no consensus has been reached on such arrangements’ economic effects and the associated optimal public policy. This chapter aims to provide an interpretive review of the common types of airport–airline arrangements, the different modeling approaches used and key conclusions reached by recent studies. Our review suggests that airport–airline arrangements can take diverse forms and have been widely used in the industry. They may allow the airport and its airlines to internalize demand externality, increase traffic volume, reduce airport investment risks and costs, promote capacity investment, enhance service quality, or simply are a response to the competition from other airport–airline chains. On the other hand, such vertical arrangements, especially for those exclusively between airports and selected airlines, could lead to collusive outcomes at the expenses of non-participating organizations. The effects of such arrangements are also significantly influenced by the contract type, market structure and bargaining power between the airport and airline sectors. While case by case investigations are often needed for important economic decisions, we recommend policy-makers to promote competition in the airline and airport segments whenever possible, and demand more transparency or regulatory reporting of such arrangements. Policy debates and economic studies should be carried out first, before intrusive regulations are introduced.

Surgical robot systems have been used in single-port laparoscopy (SPL) surgery to improve patient outcomes. This study aims to develop a vision robot system for SPL surgery to effectively improve the visualization of surgical robot systems for relatively complex surgical procedures.

In this paper, a new master-slave magnetic anchoring vision robotic system for SPL surgery was proposed. A lighting distribution analysis for the imaging unit of the vision robot was carried out to guarantee illumination uniformity in the workspace during SPL surgery. Moreover, cleaning force for the lens of the camera was measured to assess safety for an abdominal wall, and performance assessment of the system was performed.

Extensive experimental results for illumination, control, cleaning force and functionality test have indicated that the proposed system has an excellent performance in providing the visual feedback.

The main contribution of this paper lies in the development of a magnetic anchoring vision robot system that successfully improves the ability of cleaning the lens and avoiding the blind area in a field of view.

The grasping task of robots in dense cluttered scenes from a single-view has not been solved perfectly, and there is still a problem of low grasping success rate. This study aims to propose an end-to-end grasp generation method to solve this problem.

A new grasp representation method is proposed, which cleverly uses the normal vector of the table surface to derive the grasp baseline vectors, and maps the grasps to the pointed points (PP), so that there is no need to add orthogonal constraints between vectors when using a neural network to predict rotation matrixes of grasps.

Experimental results show that the proposed method is beneficial to the training of the neural network, and the model trained on synthetic data set can also have high grasping success rate and completion rate in real-world tasks.

The main contribution of this paper is that the authors propose a new grasp representation method, which maps the 6-DoF grasps to a PP and an angle related to the tabletop normal vector, thereby eliminating the need to add orthogonal constraints between vectors when directly predicting grasps using neural networks. The proposed method can generate hundreds of grasps covering the whole surface in about 0.3 s. The experimental results show that the proposed method has obvious superiority compared with other methods.

The purpose of this paper is to propose a novel jump control method based on Two Mass Spring Damp Inverted Pendulum (TMS-DIP) model, which makes the third generation of hydraulic driven wheel-legged robot prototype (WLR-3P) achieve stable jumping.

First, according to the configuration of the WLR, a TMS-DIP model is proposed to simplify the dynamic model of the robot. Then the jumping process is divided into four stages: thrust, ascent, descent and compression, and each stage is modeled and solved independently based on TMS-DIP model. Through WLR-3P kinematics, the trajectory of the upper and lower centroids of the TMS-DIP model can be mapped to the joint space of the robot. The corresponding control strategies are proposed for jumping height, landing buffer, jumping attitude and robotic balance, so as to realize the stable jump control of the WLR.

The TMS-DIP model proposed in this paper can simplify the WLR dynamic model and provide a simple and effective tool for the jumping trajectory planning of the robot. The proposed approach is suitable for hydraulic WLR jumping control. The performance of the proposed wheel-legged jump method was verified by experiments on WLR-3P.

This work provides an effective model (TMS-DIP) for the jump control of WLR-3P. The results showed that the number of landing shock (twice) and the pitch angle fluctuation range (0.44 rad) of center of mass of the jump control method based on TMS-DIP model are smaller than those based on spring-loaded inverted pendulum model. Therefore, the TMS-DIP model makes the jumping process of WLR more stable and gentler.

This paper aims to present a pipeline to progressively deal with the online external parameter calibration and estimator initialization of the Stereo-inertial measurement unit (IMU) system, which does not require any prior information and is suitable for system initialization in a variety of environments.

Before calibration and initialization, a modified stereo tracking method is adopted to obtain a motion pose, which provides prerequisites for the next three steps. Firstly, the authors align the pose obtained with the IMU measurements and linearly calculate the rough external parameters and gravity vector to provide initial values for the next optimization. Secondly, the authors fix the pose obtained by the vision and restore the external and inertial parameters of the system by optimizing the pre-integration of the IMU. Thirdly, the result of the previous step is used to perform visual-inertial joint optimization to further refine the external and inertial parameters.

The results of public data set experiments and actual experiments show that this method has better accuracy and robustness compared with the state of-the-art.

This method improves the accuracy of external parameters calibration and initialization and prevents the system from falling into a local minimum. Different from the traditional method of solving inertial navigation parameters separately, in this paper, all inertial navigation parameters are solved at one time, and the results of the previous step are used as the seed for the next optimization, and gradually solve the external inertial navigation parameters from coarse to fine, which avoids falling into a local minimum, reduces the number of iterations during optimization and improves the efficiency of the system.

Majority of the existing direct slicing methods have generated precise slicing contours from different surface representations, they do not carry any interior information. Whereas, heterogeneous solids are highly preferable for designing and manufacturing sophisticated models. To directly slice heterogeneous solids for additive manufacturing (AM), this study aims to present an algorithm using octree-based subdivision and trivariate T-splines.

This paper presents a direct slicing algorithm for heterogeneous solids using T-splines, which can be applied to AM based on the fused deposition modeling (FDM) technology. First, trivariate T-splines are constructed using a harmonic field with the gradient direction aligning with the slicing direction. An octree-based subdivision algorithm is then used to directly generate the sliced layers with heterogeneous materials. For FDM-based AM applications, the heterogeneous materials of each sliced layer are discretized into a finite number of partitions. Finally, boundary contours of each separated partition are extracted and paired according to the rules of CuraEngine to generate the scan path for FDM machines equipped with multi-nozzles.

The experimental results demonstrate that the proposed algorithm is effective and reliable, especially for solid objects with multiple materials, which could maintain the model integrity throughout the process from the original representation to the final product in AM.

Directly slicing heterogeneous solid using trivariate T-splines will be a powerful supplement to current technologies in AM.