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The purpose of this research on the control of three-axis aero-dynamic pendulum with disturbance is to facilitate the applications of equipment with similar pendulum structure in intelligent manufacturing and robot.

The controller proposed in this paper is mainly implemented in the following ways. First, the kinematic model of the three-axis aero-dynamic pendulum is derived in state space form to construct the predictive model. Then, according to the predictive model and objective function, the control problem can be expressed a quadratic programming (QP) problem. The optimal solution of the QP problem at each sampling time is the value of control variable.

The trajectory tracking and point stability tests performed on the 3D space with different disturbances are validated and the results show the effectiveness of the proposed control strategy.

This paper proposes a nonlinear unstable three-axis aero-dynamic pendulum with less power devices. Meanwhile, the trajectory tracking and point stability problem of the pendulum system is investigated with the model predictive control strategy.

Micro ultra-thin tubes have important implications in aerospace, nuclear energy and other fields. In microassembly process, these parts are characterized by following reasons: the small size can easily lead to damage when gripping, even for low intensity and the parts are mainly affected by the instability of light source, for vision-based systems, the visual information about ultra-thin tubes is difficult to gather and the contact state is hard to monitor.

The paper presents a new method to adjust the position deviations based on contact forces during microassembly processes. Specific research is such that the assembly model was established based both on mechanic calculation and numerical simulation; the assembly task was carried out on an in-house microassembly system with coaxial alignment function (MSCA), the contact statements were controlled based on force sensor feedback signals and the model of the relationship between contact force and assembly deviations was established. Through a comparative study, the results of experiment and simulation differ by less than 11 per cent, validating the accuracy and feasibility of the method.

The model of assembly force and position deviations of micro ultra-thin tubes based on MSCA has been built. Besides, the assembly force threshold, and the assembly process parameters have been obtained.

The assembly process parameters obtained from experiments can be applied in the precision assembly and provide theoretical guidance and technical support to the precision assembly of the multi-scale parts.

This study aims to provide a timely review of hospitality and tourism live streaming (HTLS) research, aiming to understand the intellectual foundation in the past and identify opportunities for future research.

This study collected 56 papers from journals in the Social Science Citation Index database or the Australian Business Deans Council journal quality list and adopted a hybrid systematic literature review combining bibliometric analysis and the theory-context-characteristics-method framework-based approach. Additionally, a cross-tabulation analysis was conducted to compare the research on two specific forms of HTLS – tourism e-commerce live streaming (TEcLS) and travel live streaming.

The study found that the current research lacks in-depth theoretical insights, focuses on China as the national context and viewers as the research subject, mainly uses online surveys and lacks first-order knowledge. Moreover, it identified five research themes, including the impact of HTLS on viewer behavior, purchase behavior in HTLS and introduction of HTLS, within which eight categories of research constructs, such as viewer-related, streamer-related and relationship-related, are applied.

In terms of research, the study reveals various gaps in the existing literature and provides potential research directions to advance the field. As for practice, it offers valuable strategies for practitioners to optimize their marketing efforts using HTLS.

This study provides an up-to-date review of the HTLS field through a systematic and reproducible method. It offers critical discussions and suggestions for academic research and industry practices.

The preferable concentration of titanium carbide was optimized and added as an additive to the micro-arc oxidation electrolyte to produce a high corrosion-resistant coating on D16T aluminum alloy.

Ceramic coatings were deposited on D16T aluminum alloy by plasma electrolytic oxidation in alkaline silicate electrolytes with micron titanium carbide particle suspending at different concentrations. Influences of additive concentration on morphology, elemental and phase composition and corrosion resistance of doped PEO coatings were evaluated by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD) and electrochemical methods, respectively.

Results revealed that suspending titanium carbide additives incorporated into ceramic coatings through discharging channels and chemically transformed into amorphous stage. The content of titanium in the doped coatings increased with the increasing concentration of suspending micron additive. Compared with the coating without particle addition, the corrosion resistance of the coating produced in 8 g/L titanium carbide suspension increased more than 20 times. The result indicated that the incorporation of titanium into the PEO coatings formed on the D16T aluminum alloy could effectively improve the corrosion resistance.

The mechanism of corporation of TiC and the mechanism of improving the corrosion resistance of the coating were proposed.

This study aims to present a holistic synopsis of the current scientific structure of inbound tourism research and suggest further research directions.

A 30-year bibliometric analysis was conducted using the Web of Science Core Collection database through CiteSpace, covering 568 Social Sciences Citation Index articles.

This study systematically identifies the evolution of scientific structures and emerging research trends in the inbound tourism field. The findings show that: co-authorship patterns reveal a trend of international cooperation; the evolution of research themes is consistent with the development of the macro-environment and inbound tourism industry, the most recent focus being on sustainable development of destinations; varied multivariate data analysis methods dominate current empirical analysis; there exist three major research dimensions in the inbound tourism field; and unilateral political factors in destinations and bilateral linkage factors affecting inbound tourism demand have aroused research interest increasingly.

This study helps scholars and practitioners understand the current issues and needs of the inbound tourism industry and develops a future research agenda to promote the industry’s continuous development.

This study is the first attempt to provide insights into the theoretical development of inbound tourism over the past three decades from the perspective of a knowledge-based platform and further facilitate sustainable development of the industry.

本篇论文旨在全面地梳理入境旅游研究的整体知识架构, 进而提出未来研究方向。

本篇论文基于文献计量法, 运用CiteSpace对从Web of Science Core Collection数据库中检索得到的30年间568篇社会科学引文索引文献进行分析。

本篇论文系统地梳理了入境旅游领域知识架构的演化和新兴研究趋势, 填补了现有研究空白。结果揭示：（1）作者协作模式展现出国际化合作趋势; （2）入境旅游领域研究主题的演化趋势与宏观环境和国际旅游的发展阶段相吻合, 并且目的地可持续发展的研究成为热点; （3）目前实证分析主要采用各种多元数据分析方法; （4）入境旅游领域的研究可以归纳为三个主要研究方向; （5）单边政治因素和国家双边联系因素对入境旅游需求的影响逐渐成为近年研究热点。

本篇论文提出了未来研究方向, 有助于学界和业界人士掌握入境旅游产业的现状和需要, 从而推动该产业的可持续发展。

本篇论文首次从知识平台视角出发, 揭示了过去三十年间入境旅游的理论发展情况。

关键词 入境旅游, 文献计量法, 知识架构, 知识平台, 未来研究方向, CiteSpace

文章类型 ：研究型论文

El objetivo de este estudio es presentar una sinopsis holística de la actual estructura científica de la investigación turística entrante y sugerir nuevas direcciones de investigación.

Se condujo un análisis bibliométrico de 30 años utilizando la base de datos de recopilación de datos de la red de ciencias básicas a través de CiteSpace, que abarcó 568 artículos del Índice de Citación de Ciencias Sociales.

Este estudio identifica sistemáticamente la evolución de estructuras científicas y las tendencias de investigación emergentes en el campo del turismo entrante. Las conclusiones muestran que: i) las pautas de coautoría han revelado una tendencia a la cooperación internacional; ii) la evolución de los temas de investigación es coherente con el desarrollo del macro-entorno y de la industria del turismo entrante, centrándose más recientemente en el desarrollo sostenible de los destinos; iii) los diversos métodos de análisis de datos multivariados predominan en el análisis empírico actual; iv) existen tres grandes dimensiones de investigación en el ámbito del turismo entrante; y v) los factores políticos unilaterales en los destinos y los factores de vinculación bilateral que afectan a la demanda turística entrante han despertado un interés cada vez mayor a la investigación.

Este estudio ayuda a los académicos y los profesionales a entender problemas y necesidades actuales de la industria turística entrante y desarrollar una futura guía de investigación para fomentar el desarrollo continuo de la industria.

Este estudio es el primer intento de proporcionar información sobre el desarrollo teórico del turismo entrante en las últimas tres décadas, desde la perspectiva de la plataforma basada en un conocimiento y facilitar aún más el desarrollo sostenible de la industria.

Turismo entrante, Bibliométrica, Estructura científica, Plataforma basada en el conocimiento, Agenda de investigación futura, CiteSpace

Revisión bibliográfica

Forecasting outpatient volume during a significant security crisis can provide reasonable decision-making references for hospital managers to prevent sudden outbreaks and dispatch medical resources on time. Based on the background of standard hospital operation and Coronavirus disease (COVID-19) periods, this paper constructs a hybrid grey model to forecast the outpatient volume to provide foresight decision support for hospital decision-makers.

This paper proposes an improved hybrid grey model for two stages. In the non-COVID-19 stage, the Aquila Optimizer (AO) is selected to optimize the modeling parameters. Fourier correction is applied to revise the stochastic disturbance. In the COVID-19 stage, this model adds the COVID-19 impact factor to improve the grey model forecasting results based on the dummy variables. The cycle of the dummy variables modifies the COVID-19 factor.

This paper tests the hybrid grey model on a large Chinese hospital in Jiangsu. The fitting MAPE is 2.48%, and the RMSE is 16463.69 in the training group. The test MAPE is 1.91%, and the RMSE is 9354.93 in the test group. The results of both groups are better than those of the comparative models.

The two-stage hybrid grey model can solve traditional hospitals' seasonal outpatient volume forecasting and provide future policy formulation references for sudden large-scale epidemics.

Due to recent technological advances, the retail industry has changed significantly. This paper examines a novel unmanned retail mode-unattended convenience store to identify the possible operational problems and develop appropriate managerial recommendations.

A data-driven two-stage epsilon-based measure (EBM) data envelopment analysis (DEA) method was developed to evaluate operational performance data from 33 unattended convenience stores and assess the impacts on efficiency of the internal factors, and a Tobit regression analysis was employed to examine the external environment.

It was found that the overall economic performances were relatively low and fluctuated significantly; however, the social performances were slightly higher. The out-of-stock rate was found to have a negative impact on efficiency, and regional characteristics were found to have significant effects on performance.

This study sought to identify current operational problems with unattended convenience stores to provide managerial insights. The cross-sectional assessment suggested that to achieve better performance, particular attention needed to be paid to store locations and surrounding store environments.

First, this paper establishes a novel theoretical framework to evaluate the economic and social operational performances at unattended convenience stores. Second, it contributes to research on unattended convenience stores and the unmanned retail industry and offers significant guidance on detecting operational deficiencies and improving future performances.

The purpose of this study is to make a prediction of China's energy consumption structure from the perspective of compositional data and construct a novel grey model for forecasting compositional data.

Due to the existing grey prediction model based on compositional data cannot effectively excavate the evolution law of correlation dimension sequence of compositional data. Thus, the adaptive discrete grey prediction model with innovation term based on compositional data is proposed to forecast the integral structure of China's energy consumption. The prediction results from the new model are then compared with three existing approaches and the comparison results indicate that the proposed model generally outperforms existing methods. A further prediction of China's energy consumption structure is conducted into a future horizon from 2021 to 2035 by using the model.

China's energy structure will change significantly in the medium and long term and China's energy consumption structure can reach the long-term goal. Besides, the proposed model can better mine and predict the development trend of single time series after the transformation of compositional data.

The paper considers the dynamic change of grey action quantity, the characteristics of compositional data and the impact of new information about the system itself on the current system development trend and proposes a novel adaptive discrete grey prediction model with innovation term based on compositional data, which fills the gap in previous studies.

An ideal method for predicting the fatigue life of spherical thrust elastomeric bearings has not been reported, thus far. This paper aims to present a method for predicting the fatigue life of laminated rubber spherical thrust elastomeric bearings.

First, the mechanical properties of standard rubber samples were tested; the axial stiffness, cocking stiffness, torsional stiffness and fatigue life of several full-size spherical thrust elastomeric bearings were tested. Then, the stiffness results were calculated using the neo-Hookean, Mooney–Rivlin and Yoeh models. Using a modified Mooney–Rivlin constitutive model, this paper proposes an improved method for fatigue life prediction, which considers the laminated characteristics of a spherical thrust elastomeric bearing and loads of multiple multi-axle conditions.

The Mooney–Rivlin model could accurately describe the stiffness characteristics of the spherical thrust elastomeric bearings. A comparative analysis of experimental results shows that the model can effectively predict the life of a spherical thrust elastomeric bearing within its range of use and the prediction error is within 20%.

The fatigue parameters of elastomeric bearings under multiaxial loads were fitted and corrected using experimental data and an accurate and effective multiaxial fatigue-life prediction expression was obtained. Finally, the software was redeveloped to improve the flexibility and efficiency of modeling and calculation.

This study aims to predict China's carbon emission intensity and put forward a set of policy recommendations for further development of a low-carbon economy in China.

In this paper, the Interaction Effect Grey Power Model of N Variables (IEGPM(1,N)) is developed, and the Dragonfly algorithm (DA) is used to select the best power index for the model. Specific model construction methods and rigorous mathematical proofs are given. In order to verify the applicability and validity, this paper compares the model with the traditional grey model and simulates the carbon emission intensity of China from 2014 to 2021. In addition, the new model is used to predict the carbon emission intensity of China from 2022 to 2025, which can provide a reference for the 14th Five-Year Plan to develop a scientific emission reduction path.

The results show that if the Chinese government does not take effective policy measures in the future, carbon emission intensity will not achieve the set goals. The IEGPM(1,N) model also provides reliable results and works well in simulation and prediction.

The paper considers the nonlinear and interactive effect of input variables in the system's behavior and proposes an improved grey multivariable model, which fills the gap in previous studies.