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This study aims to explore the impact mechanism of the degree of innovation failure on breakthrough innovation in Chinese listed companies, and examines the moderating effect of the company’s own knowledge-based capabilities.

Based on organizational learning theory and using the innovation failure data of invention patents from Chinese A-share listed companies on the main board from 2003 to 2017 as research samples, this study constructs and examines a comprehensive framework and its impact on breakthrough innovation regarding “what kind of innovation failure will promote breakthrough innovation”, focusing on innovation failure, enterprise knowledge base, and breakthrough innovation.

Empirical research has found a U-shaped relationship between innovation failure and breakthrough innovation. In other words, both a low level of failure and an extremely high level of failure can significantly promote breakthrough innovation in enterprises. Furthermore, when the depth of enterprise knowledge is high, it further strengthens the non-linear relationship between innovation failure and breakthrough innovation.

The research results enrich the study of the failure predicament and breakthrough innovation of Chinese technology innovation enterprises, revealing effective paths for Chinese technology innovation enterprises to get rid of the passive situation of innovation failure, and providing theoretical support and practical reference for “breaking new ground and achieving breakthrough innovation”.

Under the repeated action of the construction load, opening deformation and disturbed deformation occurred at the precast box culvert joints of the shield tunnel. The objective of this paper is to investigate the effect of construction vehicle loading on the mechanical deformation characteristics of the internal structure of a large-diameter shield tunnel during the entire construction period.

The structural response of the prefabricated internal structure under heavy construction vehicle loads at four different construction stages (prefabricated box culvert installation, curved lining cast-in-place, lane slab installation and pavement structure casting) was analyzed through field tests and ABAQUS (finite element analysis software) numerical simulation.

Heavy construction vehicles can cause significant mechanical impacts on the internal structure, as the construction phase progresses, the integrity of the internal structure with the tunnel section increases. The vertical and horizontal deformation of the internal structure is significantly reduced, and the overall stress level of the internal structure is reduced. The bolts connecting the precast box culvert have the maximum stress at the initial stage of construction, as the construction proceeds the stress distribution among the bolts gradually becomes uniform.

This study can provide a reference for the design model, theoretical analysis and construction technology of the internal structure during the construction of large-diameter tunnel projects.

In recent years, organizations have progressively adopted electronic performance monitoring (EPM) to obtain accurate employee performance data and improve management efficiency in response to the growing complexity of the work environment. However, existing research has primarily focused on examining the effect of EPM on employee behaviors within established job designs, neglecting the consequential role of EPM in shaping employees’ bottom-up job redesign (i.e. job crafting). This study aims to explore whether and how EPM affects employee job crafting.

To test proposed hypotheses, we conducted two time-lagged surveys across different cultural contexts and a scenario experiment on an online platform in China.

The results revealed the negative indirect relationship between EPM and employee job crafting via role breadth self-efficacy. This indirect relationship was moderated by constructive supervisor feedback and job complexity, with the above relationships being weak (versus strong) when constructive supervisor feedback was high (versus low) or job complexity was low (versus high).

The results have crucial implications for organizational practices, suggesting that managers should provide constructive feedback to break the trade-off between EPM and job crafting. Additionally, managers may need to give employees with high job complexity more autonomy rather than intense monitoring.

This study is the first to clarify the effect of EPM on employee job crafting. As job crafting captures the important value of employees in organizational job design, our effort helps to enrich the understanding of EPM effectiveness.

This paper aims to identify the factors that are constraining technological innovation to support the development of coalbed methane in China.

The analysis applies ideas relating to national and sector systems of innovation to explain why China’s strategies to support research and technological innovation have failed to stimulate the desired progress in coalbed methane production. It also provides a counter-example of the USA that implemented a number of measures in the 1970s that proved very effective.

The deficiencies of China’s research and development strategies in support of coalbed methane development reflect the national and sectoral systems of innovation. They are exacerbated by the structure of the national oil and gas industry. Key constraints include the excessively top-down management of the national R&D agenda, insufficient support for basic research, limited collaboration networks between companies, research institutes and universities and weak mechanisms for diffusion of knowledge. The success of the USA was based on entirely different systems for innovation and in quite a different industrial setting.

The originality of this analysis lies in placing the challenges facing research and innovation for China’s coalbed methane development in the context of the national and sectoral systems for innovation and comparing with the approach and success of the USA.

The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.

Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.

Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.

This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.

The continuous impact of the pandemic and the downturn of the global economy have brought new challenges to the tourism industry. In this context, effectively attracting consumers and improving user stickiness are the top priorities of tourism platform companies. This study explores the impact of ethical concerns raised by new issues under the multi-governance environment on user stickiness. Based on the trust theory, the authors provide solutions for tourism platforms.

This study adopted a quantitative approach, gathering survey data via an online platform. A total of 400 participants were investigated, and 356 valid questionnaires were returned, with a recovery rate of 89%. Questionnaires that did not meet the inclusion criteria were excluded, leaving 298 valid responses.

Studies have found that consumers' ethical concerns about platform companies are key factors affecting user stickiness, and among these, consumer trust plays a mediating role. They have found that corporate social responsibility (CSR) behaviours help alleviate ethical concerns and improve trust in enterprises. At the same time, enterprises should properly control the number of platform collaborators, and excessive platform cooperation negatively moderates the impact of consumer ethical concerns on competence-based trust.

This study complements the deficiency of previous research with regard to ethical concerns in a multi-governance environment. These findings indicate that subject diversity exacerbates the negative impact of ethical concerns on consumer trust; however, CSR alleviates the impact of ethical concerns on consumer trust.

The purpose of this paper is to numerically and experimentally evaluate the effect of the protection net icing on the inlet performance of helicopter engines.

The ice shapes of the protection net at different times are first simulated by a two-dimensional (2D) icing calculation, then the porous media parameters are calculated based on the 2D ice shapes. Afterward, three-dimensional flow fields of the engine inlet with the iced net are simulated using the porous media model instead of the real protection net. The transient pressure losses of the iced protection net are calculated and tested through an icing wind tunnel test rig under different icing conditions.

Overall, the numerical results and experimental data show a good agreement. The effects of several control parameters, such as liquid water contents (LWC), water droplet diameters and airflow velocities on the pressure loss of the protection net during the icing process are analyzed in a systematic manner. The results indicate that the pressure loss increases with the increase of the LWC at the same icing time. The same trend occurs when the water droplet diameter and the airflow velocity increase.

A new method to predict the pressure loss of the iced protection net is proposed. A series of tests in an icing wind tunnel are performed to obtain the ice shapes and pressure loss of protection net during the icing process.

To save the economic cost and improve the performance of enterprises, this study aims to synthesize high performance immobilized penicillin G acylase (PGA) carriers with fast reaction speed, high recovery rate of enzyme activity and good reusability through corresponding theoretical guidance and experimental exploration.

A diblock resin was synthesized by reversible addition-fragmentation chain transfer polymerization method using N, N-diethylacrylamide (DEA) and β-hydroxyethyl methacrylate (HEMA) as functional monomers poly(N, N-diethylacrylamide)-b-poly(β-hydroxyethyl methacrylate) (PDEA-b-PHEMA) was obtained, and the effect of the ratio of DEA and HEMA on the activity of PGA was investigated, and the appropriate block ratio of DEA and HEMA was obtained. After that, the competitive rate of HEMA and glycidyl methacrylate (GMA) under the carrier preparation conditions was investigated. Based on the above work, a thermosensitive resin carrier PDEA-b-PHEMA-b-P(HEMA-co-GMA) with different target distances was synthesized, and the chemical structures and molecular weight of copolymers were investigated by hydrogen NMR (¹H NMR).

The lower critical solution temperature of the resin support decreases with the increase of the monomer HEMA in the random copolymerization; the catalytic performance study indicated that the response rate of the immobilized PGA is fast, and the recovery rate of the enzyme activity of the immobilized PGA varies with the distance between the targets. When the molar ratio of HEMA to GMA in the resin block is 8.15:1 [i.e. resin PDEA100-b-PHEMA10-b-P(HEMA65-co-GMA8)], the activity recovery rate of immobilized PGA can reach 50.51%, which was 15.49% higher than that of pure GMA immobilized PGA.

This contribution provides a novel carrier for immobilizing PGA. Under the optimal molar ratio, the enzyme activity recovery could be up to 50.51%, which was 15.49% higher than that of PGA immobilized on the carrier with nonregulated distance between two immobilization sites.

Most of the existing ground filtering algorithms are based on the Cartesian coordinate system, which is not compatible with the working principle of mobile light detection and ranging and difficult to obtain good filtering accuracy. The purpose of this paper is to improve the accuracy of ground filtering by making full use of the order information between the point and the point in the spherical coordinate.

First, the cloth simulation (CS) algorithm is modified into a sorting algorithm for scattered point clouds to obtain the adjacent relationship of the point clouds and to generate a matrix containing the adjacent information of the point cloud. Then, according to the adjacent information of the points, a projection distance comparison and local slope analysis are simultaneously performed. These results are integrated to process the point cloud details further and the algorithm is finally used to filter a point cloud in a scene from the KITTI data set.

The results show that the accuracy of KITTI point cloud sorting is 96.3% and the kappa coefficient of the ground filtering result is 0.7978. Compared with other algorithms applied to the same scene, the proposed algorithm has higher processing accuracy.

Steps of the algorithm are parallel computing, which saves time owing to the small amount of computation. In addition, the generality of the algorithm is improved and it could be used for different data sets from urban streets. However, due to the lack of point clouds from the field environment with labeled ground points, the filtering result of this algorithm in the field environment needs further study.

In this study, the point cloud neighboring information was obtained by a modified CS algorithm. The ground filtering algorithm distinguish ground points and off-ground points according to the flatness, continuity and minimality of ground points in point cloud data. In addition, it has little effect on the algorithm results if thresholds were changed.

This method will become a new development trend in subgrade structure design for high speed railways.

This paper summarizes the structural types and design methods of subgrade bed for high speed railways in China, Japan, France, Germany, the United States and other countries based on the study and analysis of existing literature and combined with the research results and practices of high speed railway subgrade engineering at home and abroad.

It is found that in foreign countries, the layered reinforced structure is generally adopted for the subgrade bed of high speed railways, and the unified double-layer or multi-layer structure is adopted for the surface layer of subgrade bed, while the simple structure is adopted in China; in foreign countries, different inspection parameters are adopted to evaluate the compaction state of fillers according to their respective understanding and practice, while in China, compaction coefficient, subsoil coefficient and dynamic deformation modulus are adopted for such evaluation; in foreign countries, the subgrade top deformation control method, the subgrade bottom deformation control method, the subsurface fill strength control method are mainly adopted in subgrade bed structure design of high speed railways, while in China, dynamic deformation control of subgrade surface and dynamic strain control of subgrade bed bottom layer is adopted in the design. However, the cumulative deformation of subgrade caused by train cyclic vibration load is not considered in the existing design methods.

This paper introduces a new subgrade structure design method based on whole-process dynamics analysis that meets subgrade functional requirements and is established on the basis of the existing research at home and abroad on prediction methods for cumulative deformation of subgrade soil.