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This paper aims to propose two parallel two-step finite element algorithms based on fully overlapping domain decomposition for solving the 2D/3D time-dependent natural convection problem.

The first-order implicit Euler formula and second-order Crank–Nicolson formula are used to time discretization respectively. Each processor of the algorithms computes a stabilized solution in its own global composite mesh in parallel. These algorithms compute a nonlinear system for the velocity, pressure and temperature based on a lower-order element pair (P₁b-P₁-P₁) and solve a linear approximation based on a higher-order element pair (P₂-P₁-P₂) on the same mesh, which shows that the new algorithms have the same convergence rate as the two-step finite element methods. What is more, the stability analysis of the proposed algorithms is derived. Finally, numerical experiments are presented to demonstrate the efficacy and accuracy of the proposed algorithms.

Finally, numerical experiments are presented to demonstrate the efficacy and accuracy of the proposed algorithms.

The novel parallel two-step algorithms for incompressible natural convection problem are proposed. The rigorous analysis of the stability is given for the proposed parallel two-step algorithms. Extensive 2D/3D numerical tests demonstrate that the parallel two-step algorithms can deal with the incompressible natural convection problem for high Rayleigh number well.

The purpose of this paper is to propose a local parallel finite element algorithm based on fully overlapping domain decomposition technique to solve the incompressible magnetohydrodynamic equations.

The algorithm uses a lower-order element pair to compute an initial approximation by the Oseen-type iteration and uses a higher-order element pair to solve a linear system in each processor.

Besides, the convergence analysis of local parallel finite element algorithm is given. Finally, numerical experiments are presented to verify the efficiency of the proposed algorithm.

Compared with the numerical solution of the common two-step method, this method is easy to realize and can produce a more accurate solution. And, this approach is executed in parallel, so it saves a lot of computational time.

This paper aims to proposes and analyzes a novel recovery-based posteriori error estimator for the stationary natural-convection problem based on penalized finite element method.

The optimal error estimates of the penalty FEM are established by using the lower-order finite element pair P₁-P₀-P₁ which does not satisfy the discrete inf-sup condition. Besides, a new recovery type posteriori estimator in view of the gradient recovery and superconvergent theory to deal with the discontinuity of the gradient of numerical solution.

The stability, accuracy and efficiency of the proposed method are confirmed by several numerical investigations.

The provided reliability and efficiency analysis is shown that the true error can be effectively bounded by the recovery-based error estimator.

The purpose of this paper is to evaluate the influence of nutritional information on menu choices in a higher educational setting using a menu designed by the students themselves.

Based on USDA healthy eating standards, a menu comprising seven healthy and seven unhealthy meal options were presented, once unlabeled as control (n=214) and once labeled with healthy and non-healthy nutrient icons as an intervention test menu (n=212).

Findings demonstrate that despite a positive observed trend, there were no significant differences between healthy selection of labeled and unlabeled dishes (p=0.16).

Providing nutritional information in student cafeterias may be challenging but helpful. However, more strategies need to be developed with student input to provide nutrition data on menus in an informative, comprehensive, yet friendly way that encourages healthy eating in campus foodservices.

No labeling system or legislation can control choices made by individuals, so the responsibility for a healthy selection must always remain personal. However, consumers should have input on menus as they have a stake in the outcome of the products.

This novel study tested a student-designed menu to assess whether user input can influence food choice.

X-ray pulsar navigation (XPNAV) is an autonomous celestial navigation technology for deep space missions. The error in the pulse time of arrival used in pulsar navigation is large for various practical reasons and thus greatly reduces the navigation accuracy of spacecraft near the Earth and in deep space. This paper aims to propose a novel method based on ranging information that improves the performance of XPNAV.

This method replaces one pulsar observation with a satellite observation. The ranging information is the difference between the absolute distance of the satellite relative to the spacecraft and the estimated distance of the satellite relative to the spacecraft. The proposed method improves the accuracy of XPNAV by combining the ranging information with the observation data of two pulsars.

The simulation results show that the proposed method greatly improves the XPNAV accuracy by 70% compared with the conventional navigation method that combines the observations of three pulsars. This research also shows that a larger angle between the orbital plane of the satellite and that of the spacecraft provides higher navigation accuracy. In addition, a greater orbital altitude difference implies higher navigation accuracy. The position error and ranging error of the satellite have approximately linear relationships with the navigation accuracy.

The novelty of this study is that the satellite ranging information is integrated into the pulsar navigation by using mathematical geometry.

This study aims to obtain the speed and angle during safe and comfortable standing of elderly people. With the advancement of society, it is becoming increasingly difficult for the elderly to sit-to-stand (STS) independently and comfortably in a safe and comfortable manner. Safety is essentially a prerequisite for the elderly to achieve a comfortable STS. The speed, angle and power of the STS process can all affect safe STS. From the standpoint of health-care delivery and administration, comfortable STS can be realized easily by addressing the safety issues during STS.

This paper summarizes the research progress on speed and angle during safe and comfortable standing of older people. The authors analyzed the speed and angle of the STS using the Vicon optical gait acquisition system and plantar pressure sensor to find the appropriate angle and speed thresholds.

The center of gravity movement is a prerequisite for the elderly to achieve a comfortable STS. The authors found that the standing speed during the STS process should not be higher than 103.8 mm/s so that the elderly can stand comfortably and safely (safe and dangerous speeds are 72.8 mm/s and 125.2 mm/s). The limitations of waist angle, waist angle speed and the acceleration are also obtained.

This paper analyzes and summarizes the research status of speed and angle during safe and comfortable standing of elderly people, which is essentially a prerequisite for the elderly to achieve a comfortable STS. These results can lay the foundation for the development of assistive devices and related technologies that meet the needs of older adults.

Artificial intelligence (AI) and big data analysis may further enhance the automated and smart features of tourism and hospitality services. However, it also poses new challenges to human resource management. This study aims to explore the direct and indirect effects of employees’ AI perception on career resilience and informal learning as well as the mediating effect of career resilience.

This paper proposed a theoretical model of AI perception, career resilience and informal learning with perceived AI as the antecedent variable, career resilience as the mediate variable and informal learning as the endogenous variable. Targeting the employees working with AI, a total of 472 valid data were collected. Data were analyzed using structural equation modeling with AMOS software.

Findings indicated that employees’ perception of AI positively contributes to career resilience and informal learning. Apart from the direct effect on informal learning, career resilience also mediates the relationship between AI perception and informal learning.

Research findings provide both theoretical and practical implications by revealing the impact of AI perception on employees’ career development, leaning activities, explaining how AI transforms the nature of work and career development and shedding lights on human resource management in the tourism and hospitality field.

本文提出了人工智能感知为前因变量、职业弹性为中介变量、非正式学习为内生变量的理论模型。以旅游业AI工作环境中的员工为研究对象, 本课题共收集了472份来自中国的有效数据, 并通过结构方程建模（SEM）来进行相关模型检验。

人工智能和大数据分析可能会使旅游和酒店服务更加自动化和智能化, 但这也对人力资源管理提出了新的挑战。本研究旨在探讨员工对人工智能（AI）的感知对职业弹性和非正式学习的直接和间接影响, 以及职业弹性的中介作用。

研究结果显示, 员工对人工智能的感知对职业弹性和非正式学习有积极影响。除了对非正式学习的直接影响外, 职业弹性在人工智能 (A I) 感知和非正式学习之间起中介作用。

本研究在以下几个方面具有重要的理论和实践意义：解释了人工智能感知对员工职业发展和学习行为的影响, 以及它是如何改变工作性质和员工职业发展的; 研究发现对旅游和酒店行业的人力资源管理具有实践指导意义。

La IA y el análisis de big data pueden potenciar aún más las características automatizadas e inteligentes de los servicios de turismo y hostelería. Sin embargo, también plantea nuevos retos a la gestión de los recursos humanos. Este estudio pretende explorar los efectos directos e indirectos de la percepción de la IA por parte de los empleados sobre la resiliencia profesional y el aprendizaje informal, así como el efecto mediador de la resiliencia profesional.

En este trabajo se propone un modelo teórico de percepción de la IA, resiliencia profesional y aprendizaje informal con la IA percibida como variable antecedente, la resiliencia profesional como variable mediadora y el aprendizaje informal como variable endógena. Dirigidos a los empleados que trabajan con IA, se recogieron un total de 472 datos válidos. Los datos se analizaron mediante un modelo de ecuaciones estructurales (SEM) con el software AMOS.

Los Resultados indicaron que la percepción de la IA por parte de los empleados contribuye positivamente a la resiliencia profesional y al aprendizaje informal. Aparte del efecto directo sobre el aprendizaje informal, la resiliencia profesional también media en la relación entre la percepción de la IA y el aprendizaje informal.

Los Resultados de la investigación proporcionan implicaciones tanto teóricas como prácticas al revelar el impacto de la percepción de la IA en el desarrollo profesional de los empleados, las actividades de aprendizaje, explicar cómo la IA transforma la naturaleza del trabajo y el desarrollo profesional, y arrojar luz sobre la gestión de los recursos humanos en el ámbito del turismo y la hostelería.

The purpose of this paper is to explore some specific, current social phenomena in China that may influence consumers’ ethical beliefs and practices, focusing on how some top-down, social and political changes could shape consumer behavior that needs to be understood in the Chinese context.

Extensive literature was critically reviewed to explore recent macro-societal reforms in China and their impact on consumers’ (un)ethical practices.

The authors lay out how China, a government-led society, underwent a series of political reforms resulting in demographic shifts that differentiate it from its western, industrialized counterparts. The authors connect these societal changes with Chinese characteristics to consumers’ ethical evaluations, forming a new angle to understand consumer ethics in China. The authors also draw on two empirical examples to illustrate the argument.

While consumer ethics are often explained by either cultural factors or individual variations, the authors discuss how one’s ethical practice is shaped by one’s social position, which is a product of national-level public policy. The discussions have ramifications for the study of consumers’ social class and ethical practices because they take into account the elusive social positions and ambiguous social class consciousness of the Chinese population that have resulted from social mobility. The discussions may give practitioners a better understanding of the ethical rationale behind consumers’ changing lifestyles especially in the Chinese context.

This study aims to use the theory of third places to understand how different kinds of social interactions in small hospitality businesses, such as restaurants and cafes, can enhance senior customers’ experiences and alleviate their loneliness.

The target population of this study were Hong Kong residents of age 60 or older. The sampling frame comprised respondents who visited a Cha Chaan Teng (i.e. a Hong Kong-style tea restaurant) more than once a year. The authors distributed 500 questionnaires and collected 411 valid responses in 2016. They used structural equation modeling for data analysis.

The results show that social interactions (service manner and need identification) with employees and other customers have a positive effect on senior customers’ experiences, while the service manner of employees reduces senior customers’ loneliness.

This study demonstrates the respective contributions of social interactions with employees and those with other customers to enhancing senior customers’ experiences and alleviating their loneliness. This study’s findings may provide a foundation for future research into the relationships between social interactions, customer experience and loneliness in third places (that are, informal public places that offer individuals opportunities to escape from home and the workplace and to enjoy voluntary conversation, entertainment and gatherings). Further, this study also demonstrates the specific role and importance of the hospitality industry in addressing a contemporary social problem in the form of seniors’ loneliness.

The purpose of this paper is to introduce error ellipse into the bootstrap method to improve the reliability of small samples and the credibility of the S-N curve.

Based on the bootstrap method and the reliability of the original samples, two error ellipse models are proposed. The error ellipse model reasonably predicts that the discrete law of expanded virtual samples obeys two-dimensional normal distribution.

By comparing parameters obtained by the bootstrap method, improved bootstrap method (normal distribution) and error ellipse methods, it is found that the error ellipse method achieves the expansion of sampling range and shortens the confidence interval, which improves the accuracy of the estimation of parameters with small samples. Through case analysis, it is proved that the tangent error ellipse method is feasible, and the series of S-N curves is reasonable by the tangent error ellipse method.

The error ellipse methods can lay a technical foundation for life prediction of products and have a progressive significance for the quality evaluation of products.