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The purpose of this paper is to investigate how R&D originality functions in an open innovation process after the introduction of knowledge spillovers (KSs).

To examine the research framework, the authors use hierarchical regression based on questionnaire data from 211 emerging enterprises in China.

Consistent with the proposed framework, the authors find that the KS effect mediates the positive relationship between openness and innovation performance. In addition, R&D originality weakens the impact of the KS effect on innovation performance.

One limitation is that the questionnaire survey the authors choose for data collection has some natural defects; furthermore, the testing method and research framework need to be improved.

Several implications of the findings for managerial practices are discussed.

First, the research expands the existing theoretical construct by introducing the KS effect into the open innovation process; second, the authors reveal the negative impact of R&D originality on the open innovation process.

Legged robots are inevitably to interact with the environment while they are moving. This paper aims to properly handle these interactions. It works to actively control the joint torques of a hydraulic-actuated leg prototype and achieve compliant motion of the leg.

This work focuses on the modelling and controlling of a hydraulic-actuated robot leg prototype. First, the design and kinematics of the leg prototype is introduced. Then the linearlized model for the hydraulic actuator is built, and a model-based leg joint torque controller is presented. Furthermore, the virtual model controller is implemented on the prototype leg to achieve active compliance of the leg. Effectiveness of the controllers are validated through the experiments on the physical platform as well as the results from simulations.

The hydraulic joint torque controller presented in this paper shows good torque tracking performance. And the actively compliant leg successfully emulates the performance of virtual passive components under dynamic situations.

The main contribution of this paper is that it proposed a model-based active compliance controller for the hydraulic-actuated robot leg. It will be helpful for those robots that aim to achieve versatile and safe motions.

Previous studies have mostly discussed the impact of environmental policy on enterprise innovation, but the discussion on how turbulence in environmental policy may affect firms' green innovation has been insufficient. This paper explores the effect of environmental policy uncertainty on corporate green innovation in the turnover of environmental protection officials (EPOT) context.

The authors manually collected the data on the EPOT of 280 Chinese prefecture-level cities, and used the Poisson regression model to conduct empirical analyses based on the panel data of 1472 Chinese listed manufacturing firms from 2008 to 2017.

The results show that environmental policy uncertainty leads firms to reduce their green patent applications only for green invention patent applications. Such an effect is more pronounced in non-state-owned enterprises (non-SOEs). In addition, when the new directors of the Ecology and Environmental Bureau take office through promotions or are no more than 55 years old, the negative effect is more obvious, but there is no significant difference regardless of whether new directors have worked in environmental protection departments.

First, this paper supplements the research on the antecedents of corporate green innovation from the perspective of environmental policy uncertainty and extends the applications of real options theory. Second, this paper expands the research on the government–business relationship from the EPOT perspective.

This paper aims to present an evaluation method for energy-absorption characteristics of thin-walled composite structures with random uncertain parameters.

The mechanical properties of T700/3234 are obtained by material performance tests and energy-absorption results are obtained by quasi-static crushing tests of thin-walled composite circular tubes. The indicators of triggering specific load (TSL) and specific energy absorption (SEA) are introduced and calculated to determine the energy-absorption characteristics and validate the probability finite element analysis model. The uncertainty in the parameters contain the machining tolerance for the thickness and inner diameter of composite circular tubes and are associated with the composite material system. The Plackett–Burman method is used to choose the measurement parameters. Then, the response surface method is used to build a second-order function of random uncertain parameters versus TSL/SEA, and the Monte Carlo method is finally used to obtain the probabilities of TSL and SEA.

The finite element models can accurately simulate the initial peak load, load-displacement curve and SEA value. The random uncertain parameter method can be used to evaluate the energy-absorption characteristics of thin-walled composite circular tubes.

The presented evaluation method for energy-absorption characteristics of thin-walled composite structures is an approach that considers uncertain parameters to increase the simulation accuracy and decrease the computational burden.

This methodology considers uncertain parameters in evaluating the energy-absorption characteristics of thin-walled composite structures, and this methodology can be applied to other thin-walled composite structures.

This study aims to evaluate the thermal performance of sodium alginate (SA) aerogel attached to nano SiO₂ and its radiative cooling effect on firefighting clothing without environmental pollution.

SA/SiO₂ aerogel with refractory heat insulation and enhanced radiative cooling performance was fabricated by freeze-drying method, which can be used in firefighting clothing. The microstructure, chemical composition, thermal stability, and thermal emissivity were analyzed using Fourier transform infrared spectroscopy, scanning electron microscopy, thermogravimetric analyzer and infrared emissivity measurement instrument. The radiative cooling effect of aerogel was studied using thermal infrared imager and thermocouple.

When the addition of SiO₂ is 25% of SA, the prepared aerogel has excellent heat insulation and a high radiative cooling effect. Under a clear sky, the temperature of SA/SiO₂ aerogel is 9.4°C lower than that of pure SA aerogel and 22.1°C lower than that of the simulated environment. In addition, aerogel has more exceptional heat insulation effect than other common fabrics in the heat insulation performance test.

SA/SiO₂ aerogel has passive radiative cooling function, which can efficaciously economize global energy, and it is paramount to environment-friendly cooling.

This method could pave the way for high-performance cooling materials designed for firefighting clothing to keep maintain the wearing comfort of firefighters.

SA/SiO₂ aerogel used in firefighting clothing can release heat to the low-temperature outer space in the form of thermal radiation to achieve its own cooling purpose, without additional energy supply.

Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.

This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.

Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.

A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.

The purpose of this study is to forecast the development performance of important economies in a smart city using mixed-frequency data.

This study introduces reverse unrestricted mixed-data sampling (RUMIDAS) to support vector regression (SVR) to develop a novel RUMIDAS-SVR model. The RUMIDAS-SVR model was estimated using a quadratic programming problem. The authors then use the novel RUMIDAS-SVR model to forecast the development performance of all high-tech listed companies, an important sector of the economy reflecting the potential and dynamism of urban economic development in Shanghai using the mixed-frequency consumer price index (CPI) producer price index (PPI), and consumer confidence index (CCI) as predictors.

The empirical results show that the established RUMIDAS-SVR is superior to the competing models with regard to mean absolute error (MAE) and root-mean-squared error (RMSE) and multi-source macroeconomic predictors contribute to the development performance forecast of important economies.

Smart city policy makers should create a favourable macroeconomic environment, such as controlling inflation or stabilising prices for companies within the city, and companies within the important city economic sectors should take initiative to shoulder their responsibility to support the construction of the smart city.

This study contributes to smart city monitoring by proposing and developing a new model, RUMIDAS-SVR, to help the construction of smart cities. It also empirically provides strategic insights for smart city stakeholders.

For the developing countries involving in the Belt and Road Initiative (BRI) with China as the main source of foreign development investment (FDI) and development as the top priority, it appears to attract more and more attention on how to make the best use of China’s outward foreign development investment. However, the contradictory evidence in the previous studies of FDI spillover effect and the remarkable time-lag feature of spillovers motivate us to analyze the mechanism of FDI spillover effect. The paper aims to discuss this issue.

The mechanism of FDI spillovers and the unavoidable lag effect in this process are empirically analyzed. Based on the panel data from the Belt and Road developing countries (BRDCs) and China’s direct investments (CDIs) from 2003 to 2017, the authors establish a panel vector autoregressive model, employing impulse response function and variance decomposition analysis, together with Granger causality test.

Results suggest a dynamic interactive causality mechanism. First, CDI promotes the economic growth of BRDCs through technical efficiency, human capital and institutional transition with combined lags of five, nine and eight years. Second, improvements in the technical efficiency and institutional quality promote economic growth by facilitating the human capital with integrated delays of six and eight years. Third, China’s investment directly affects the economic growth of BRDCs, with a time lag of six years. The average time lag is about eight years.

Based on the analysis on the mechanism and time lag of FDI spillovers, the authors have shown that many previous articles using one-year lagged FDI to examine the spillover effect have systematic biases, which contributes to the research on the FDI spillover mechanism. It provides new views for host countries on how to make more effective use of FDI, especially for BRDCs using CDIs.

In confronting the challenge of climate change and progressing towards dual carbon goals, China is actively implementing low-carbon city pilot policy. This paper aims to focus on the potential impact of this policy on enterprise green governance, aiming to promote the reduction and balance of carbon emissions.

Based on the panel data of China's large-scale industrial enterprises from 2007 to 2013, this paper uses the Difference-in-differences (DID) method to study the impact and path mechanism of the implementation of low-carbon city pilot policy on enterprise green governance. Heterogeneity analysis is used to compare the effects of low-carbon city pilot policy in different regions, different enterprises and different industries.

The low-carbon pilot can indeed effectively enhance corporate green governance, a conclusion that still holds after a series of robustness tests. The low-carbon city pilot policy mainly enhances enterprise green governance through two paths: an industrial structure upgrade and enterprise energy consumption, and it improves green governance by reducing enterprise energy consumption through industrial structure upgrade. The impact of low-carbon city pilot policy on enterprise green governance shows significant differences across different regions, different enterprises and different industries.

This paper examines the impact of low-carbon city pilot policy on enterprise green governance. However, due to availability of data, there are still some limitations to be further tackled. The parallel trend test in this paper shows that the pilot policy has a significant positive effect on the green governance of enterprises. However, due to serious lack of data in some years, the authors only selected the enterprise data of a shorter period as our experimental data, which leads the results to still have certain deficiencies. For the verification of the impact mechanism, the conclusions obtained in this paper are relatively limited. Although all the mechanism tests are passed, the reliability of the results still needs to be further tested through future data samples. In addition, as the pilot policy of low-carbon cities is still in progress, the policy can be tracked and analysed in the future as more data are disclosed, and further research can be carried out through dimensional expansion.

Low-carbon city pilot policy plays an important role in inducing the green governance of enterprises. Therefore, policy makers can continue to strengthen the construction of low-carbon city pilots by refining pilot experience, building typical cases, actively promoting pilot policy experience, expanding pilot scope and enhancing the implementation efficiency of pilot policy nationwide, which will contribute to the optimization and upgrading of the regional industrial structure at the urban level and will provide experience and reference for the synergistic implementation plan of pollution reduction and carbon reduction.

The impact of the low-carbon city pilot policy on enterprise green governance not only exists in two separate paths of urban industrial upgrading and enterprise energy consumption but also exists in a chain transmission path from macro to micro. The authors find that the effect value of each influence path is different, and there is an obvious leading influence path for the role of enterprise green governance. Therefore, in the process of implementing a low-carbon city pilot policy, policies should be designed specifically for different mechanisms. Moreover, complementing and coordinating several paths should be advocated to give full play to the green governance effect of enterprises brought by different paths and to further expand the scope of industries and enterprises where policies play a role.

To the best of the authors’ knowledge, for the first time, this paper connects macro mechanisms with micro mechanisms, discovering a macro-to-micro transmission mechanism in the process of low-carbon city pilot policy affecting enterprise green governance. That is, the low-carbon city pilot policy can facilitate industrial structure upgrading, resulting in reduced enterprise energy consumption, ultimately enhancing enterprise green governance.

The behavior of joints has a significant effect on the stability of water conveyance tunnel. The purpose of this paper is to study the contact and friction at the joint of the tunneling segment lining and establish its contact friction model. At the same time, the stress and deformation characteristics at the joint of the segment under hydrostatic load are analyzed.

In this study, the contact and friction in a bolted joint are examined using shear testing. The feasibility of the proposed model is verified by a numerical simulation of tests and a theoretical analysis. Accordingly, the effect of joints on the lining is explored under internal hydrostatic loading.

The results show that the openings of tunnel segments in joints gradually expand from the positions of the inner and outer edges to the location of the bolt. Moreover, the stress concentration zone is formed at the bolt. Under hydraulic loading, the opening displacement at the joint increases as the water pressure increases; nevertheless, it does not exceed engineering requirements. When the water pressure of the tunnel lining joint reaches 0.5 MPa, the opening of the joint slowly increases. When the water pressure exceeds 0.7 MPa, the opening of the joint rapidly and significantly increases.

Contact and friction in a bolted joint were examined using shear testing. A cohesive zone model of bolted joints was proposed based on test results. The influence of joint behavior on the stability of water conveyance tunnel was studied.