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Innovation is the fundamental driving force for the long-term sustainable development of an economy. After four decades of rapid economic growth, China is facing crises related to a demographic structure of “aging before getting rich,” industrial overcapacity of low-end products and environmental and resources constraints. This paper aims to discuss these issues.

Based on logical analysis and recapitulation of previous empirical research, this study presents the conclusion.

Scientific and technological innovation, as strategic support to improve social productivity and overall national strength, must be placed at the center of the country’s overall development.

The development model that preys upon cheap resources for extensive growth is unsustainable. Thus, the country needs an urgent strategic switch to drive its economic growth through research and development innovation and original technological advancement.

The coupling process between the loading mechanism and the tank car mouth is a crucial step in the tank car loading process. The purpose of this paper is to design a method to accurately measure the pose of the tanker car.

The collected image is first subjected to a gray enhancement operation, and the black parts of the image are extracted using Otsu’s threshold segmentation and morphological processing. The edge pixels are then filtered to remove outliers and noise, and the remaining effective points are used to fit the contour information of the tank car mouth. Using the successfully extracted contour information, the pose information of the tank car mouth in the camera coordinate system is obtained by establishing a binocular projection elliptical cone model, and the pixel position of the real circle center is obtained through the projection section. Finally, the binocular triangulation method is used to determine the position information of the tank car mouth in space.

Experimental results have shown that this method for measuring the position and orientation of the tank car mouth is highly accurate and can meet the requirements for industrial loading accuracy.

A method for extracting the contours of various types of complex tanker mouth is proposed. This method can accurately extract the contour of the tanker mouth when the contour is occluded or disturbed. Based on the binocular elliptic conical model and perspective projection theory, an innovative method for measuring the pose of the tanker mouth is proposed, and according to the space characteristics of the tanker mouth itself, the ambiguity of understanding is removed. This provides a new idea for the automatic loading of ash tank cars.

The purpose of this paper is to study the corrosion behaviors of X70 steel under direct current (DC) interference at 0-1,200 A/m² in simulated soil solution.

The Tafel polarization curves of X70 steel under DC interference were tested using electrochemical method, the corrosion rate was calculated using weight-loss method and the change in steel surface was analyzed by optical microscopy.

The results showed that E-I polarization curves under 200-1,200 A/m² interference were linear; with an increase in the DC density, the corrosion potential of X70 steel shifted positively, solution pH after the weight-loss tests increased and corrosion rate increased linearly. A mathematical relationship between polarization resistance Rp and current density was established. Corrosion morphology indicated that pitting corrosion and crevice corrosion occurred on the X70 steel under DC interference in simulated soil solution.

All tests were conducted at a relative higher DC density (200-1,200 A/m²). The linear fitting method is proposed to fit data of Tafel polarization curves under DC interference. This study provides guidelines for safe operation of X70 steel pipelines.

Rotating machinery is a crucial component of large equipment, and detecting faults in it accurately is critical for reliable operation. Although fault diagnosis methods based on deep learning have been significantly developed, the existing methods model spatial and temporal features separately and then weigh them, resulting in the decoupling of spatiotemporal features.

The authors propose a spatiotemporal long short-term memory (ST-LSTM) method for fault diagnosis of rotating machinery. The authors collected vibration signals from real rolling bearing and gearing test rigs for verification.

Through these two experiments, the authors demonstrate that machine learning methods still have advantages on small-scale data sets, but our proposed method exhibits a significant advantage due to the simultaneous modeling of the time domain and space domain. These results indicate the potential of the interactive spatiotemporal modeling method for fault diagnosis of rotating machinery.

The authors propose a ST-LSTM method for fault diagnosis of rotating machinery. The authors collected vibration signals from real rolling bearing and gearing test rigs for verification.

The purpose of this paper is to propose a new hybrid algorithm, named improved plant growth simulation algorithm and genetic hybrid algorithm (PGSA-GA), for solving structural optimization problems.

PGSA-GA is based on PGSA and three improved strategies, namely, elitist strategy of morphactin concentration calculation, strategy of intelligent variable step size and strategy of initial growth point selection based on GA. After a detailed formulation and explanation of its implementation, PGSA-GA is verified using the examples of typical truss and single-layer lattice shell.

Improved PGSA-GA was implemented and optimization was carried out for two typical optimization problems; then, a comparison was made between the PGSA-GA and other methods. The results show that the method proposed in the paper has the advantages of high efficiency and rapid convergence, which enable it to be used for the optimization of various types of steel structures.

Through the examples of typical truss and single-layer lattice shell, it shows that the optimization efficiency and effect of PGSA-GA are better than those of other algorithms and methods, such as GA, secondary optimization method, etc. The results show that PGSA-GA is quite suitable for structural optimization.

Wear failure happens frequently in rubber seal of high-speed rotating shaft because of the dry friction. Some traditional lubrication methods are not effective because of the restrictions on the relative high speed, temperature and others. This paper aims to present a new method of lubrication with gas film for the rotation shaft seal based on the contact design.

To obtain the generation condition of gas film and good effect of lubrication in the contact gap between the shaft and its seal, a series of micro-spiral grooves are designed on the contact surface of rubber seal so as to obtain a continuous dynamic pressure difference.

The result is that the distribution of the gas film in the micro-gap is continuous under the design of the spiral grooves and the contact with eccentricity because of the deformation of rubber seal, which is verified through the simulation calculation and experiment test. It is confirmed that the lubrication method with gas film through designing micro-spiral grooves on the contact surface is effective, and can achieve self-adaptive air lubrication for the high-speed shaft under the premise of the reliable sealing.

The method of gas film lubrication is realized through designing a microstructure of spiral grooves on the rubber surface to change the contact status, which can form a mechanism of adaptive lubrication to reduce the dry friction automatically in the contact gap. For the cross-scale difference between the rubber seal and gas film, a new modeling method is presented by building the mapping relation for the split blocks and repairing technique with integrated computer engineering and manufacturing, to reduce the possibility of nonconvergence and improve the efficiency and accuracy of calculation.

This paper aims to systematically demonstrate a methodology to determine the relative and absolute encapsulation efficiencies (α_Re and α_Ab) for thermally- and chemically-robust inorganic pigments, typically like ZrSiO₄-based pigments, thereby enhancing their coloring performance.

The authors designed a route, surplus alkali-decomposition and subsequently strong-acid dissolution (SAD2) to completely decompose three classic zircon pigments (Pr–ZrSiO₄, Fe₂O₃@ZrSiO₄ and CdS@ZrSiO₄) into clear solutions and preferably used inductively coupled plasma-optical emission spectrometry (ICP-OES) to determine the concentrations of host elements and chromophores, thereby deriving the numeric data and interrelation of α_Re and α_Ab.

Zircon pigments can be thoroughly decomposed into some dissoluble zirconate–silicate resultants by SAD2 at a ratio of the fluxing agent to pigment over 6. ICP-OES is proved more suitable than some other quantification techniques in deriving the compositional concentrations, thereby the values of α_Re and α_Ab, and their transformation coefficient K_RA, which maintains stably within 0.8–0.9 in Fe₂O₃@ZrSiO₄ and CdS@ZrSiO₄ and is slightly reduced to 0.67–0.85 in Pr–ZrSiO₄.

The SAD2 method and encapsulation efficiencies are well applicable for both zircon pigments and the other pigmental or non-pigmental inhomogeneous systems in characterizing their accurate composition.

The authors herein first proposed strict definitions for the relative and absolute encapsulation efficiencies for inorganic pigments, developed a relatively stringent methodology to determine their accurate values and interrelation.

To develop the theory and application of the grey prediction model, this investigation constructs a novel discrete grey Riccati model termed DGRM(1,1).

By examining a special kind of Riccati difference equation and the structure of the conventional discrete grey model (DGM), we advance a novel DGRM, and the model's prediction effect is evaluated by two numerical examples and an application case and compared with that of other conventional grey models.

The average relative simulation error of DGRM(1,1) does not change if the model is built after the original sequence has been transformed by a multiplier, and the new model is suitable to predict monotonically increasing, monotonically decreasing and unimodal sequences.

DGRM(1,1) is utilized to forecast the development cost of a small plane owned by the Aviation Industry Corporation of China (AVIC) with an original data sequence from 2006 to 2013. The outcomes indicate that DGRM(1,1) exhibits high precision and potential in development cost prediction.

Combining the Riccati difference equation with the conventional DGM, the author advances a new grey model that is suitable to predict three kinds of data series with different changing trends.

Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.

This study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.

The results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.

This study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.

Unlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.

The purpose of this paper is to investigate the role of acquirer's earnings quality on the choice of payment method in mergers and acquisitions (M&A).

The paper applies a simultaneous equations model to address the concern of endogeneity between earnings quality and payment method in corporate acquisitions. In addition, a propensity score matching model is used for robustness purpose.

Previous studies imply that short‐term accruals have a significant impact on the choice of payment method in M&A. In this study, This paper shows that acquisition financing is not significantly affected by short‐term earnings quality once control variables are considered. Instead, this paper finds that it is the long‐term earnings quality of the acquirer that matters. Acquiring firms with poor (good) long‐term earnings quality prefer lower (higher) cash payment in acquisitions. Their results are robust to different definitions of earnings quality.

Researchers should consider the effect of long‐term earnings quality in their future investigations.

Investors should be aware of this issue when evaluating corporate mergers.

This is the first study to examine the impact of long‐term quality of earnings on the choice of payment method in M&A.