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Ultra-high molecular weight polyethylene (UHMWPE) has an excellent performance and application value; however, as a tribological material, its main drawback is its poor performance under dry friction, impacting its ability to work in high-speed dry friction conditions. Modification of UHMWPE can be carried out to overcome these issues. A significant number of inorganic materials have been used to modify UHMWPE and provide it with good tribological performance. However, thus far, there has been no systematic investigation into the methodology of modifying UHMWPE. The authors take a quantitative approach to determine the structure tribo-ability relationship and basic principles of screening of inorganic compounds suited to modify UHMWPE.

The tribological properties of modified UHMWPE using a series of inorganic additives have been qualitatively studied by the authors’ research group previously. In this study, basic quantitative structure tribo-ability relationships (QSTRs) of inorganic additives for modifying UHMWPE were studied to predict tribological properties. A set of 15 inorganic compounds and their tribological data were used to study the predictive capability of QSTR towards inorganic additives properties.

The results show that the anti-wear and friction-reducing properties of these inorganic compounds correlate with the calculated parameters of entropy and dipole moment. Increased entropy and smaller dipole moment can effectively improve the anti-wear and friction-reducing ability of inorganic compounds as UHMWPE additives. Additives with larger molecular weight, lower hardness and lower melting and boiling points provide good tribological properties for UHMWPE. For inorganic compounds to act as UHMWPE additives, the chemical bond should be less covalent and have more ionic character.

Only 15 inorganic compounds and their tribological data were used to study the predictive capability of QSTR towards inorganic additives properties. If the samples number is more than 30, the other QSTR methodology can be used to study the modified UHMWPE, and the models finding can be more precise.

A QSTR model for modified UHMWPE has been studied systematically. While the results are not more precise and detailed, the model provides a new way to explore the modified UHMWPE characteristics and to reveal new insight into the friction and wear process.

Because the method of studying tribological materials is entirely different from others, the authors want to present the works and discuss it with colleagues.

The paper presents a new method to study the modified UHMWPE. A QSTR is used to study the tribology capability of compounds from calculated structure descriptors. This study uses the Hartree–Fock ab initio method to establish a QSTR prediction model to estimate the ability of 15 inorganic compounds to act as anti-wear and friction-reducing additives for UHMWPE.

Social presence (SP), which refers to individuals’ perception of others being engaged as “real people” in the same situation, is a crucial component in technology-rich learning environments (TREs). This study aims to identify major learning design, antecedents and outcomes of SP within TREs, and identify common findings from the past two decades.

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses review principles and a qualitative analysis of selected articles, a final review of 72 studies that met inclusion criteria was obtained. Key information, including education level, discipline, sample size, study type and measurements, was extracted and studies were further analyzed and synthesized based on design features and learning modes.

The study identifies five crucial factors for instructional design to foster SP in TREs: technology affordances, multimedia features, social factors, instructional principles, learner characteristics and learning management systems. The authors compare two learning modes across three dimensions and identify popular technologies used in studies related to SP over the past two decades. Practical recommendations are provided for educators and educational technology developers to enhance SP within technology-rich learning environments.

This research contributes to the discourse on online learning and computer-supported communication, particularly in the post-COVID-19 era. By examining factors influencing SP and providing implications for instruction and educational technology development, this study offers evidence-based support to educators for engaging learners and fostering authentic learning experiences through adaptive selection of educational technologies.

Because of short life cycle and fluctuating greatly in total sales volumes (TSV), it is difficult to accumulate enough sales data and mine an attribute set reflecting the common needs of all consumers for a kind of experiential product with short life cycle (EPSLC). Methods for predicting TSV of long-life-cycle products may not be suitable for EPSLC. Furthermore, point prediction cannot obtain satisfactory prediction results because information available before production is inadequate. Thus, this paper aims at proposing and verifying a novel interval prediction method (IPM).

Because interval prediction may satisfy requirements of preproduction investment decision-making, interval prediction was adopted, and then the prediction difficult was converted into a classification problem. The classification was designed by comparing similarities in attribute relationship patterns between a new EPSLC and existing product groups. The product introduction may be written or obtained before production and thus was designed as primary source information. IPM was verified by using data of crime movies released in China from 2013 to 2017.

The IPM is valid, which uses product introduction as input, classifies existing products into three groups with different TSV intervals, mines attribute relationship patterns using content and association analyses and compares similarities in attribute relationship patterns – to predict TSV interval of a new EPSLC before production.

Different from other studies, the IPM uses product introduction to mine attribute relationship patterns and compares similarities in attribute relationship patterns to predict the interval values. It has a strong applicability in data content and structure and may realize rolling prediction.

The purpose of this paper is to analyze the unbalanced magnetic pull (UMP) of the rotor of traction motor and the influence of the UMP on thermal characteristics of traction motor bearing.

The unbalanced magnetic pull on the rotor with different eccentricity was calculated by Fourier series expansion method. A bearing thermal analysis finite element model considering both the vibration of high-speed train caused by track irregularity and the UMP of traction motor rotor was established. The validity of the model is verified by experimental data obtained from a service high-speed train.

The results show that thermal failure of bearing subassemblies most likely occurs at contact area between the inner ring and rollers. The UMP of rotor of traction motor has a significant effect on the temperature of the inner ring and roller of the bearing. When the eccentricity is 10%, the temperature can even be increased by about 12°C. Therefore, the UMP of rotor of traction motor must be considered in thermal analysis of traction motor bearing.

In the thermal analysis of the bearing of the traction motor of high-speed train, the UMP of the rotor of the traction motor is considered for the first time

This paper aims to study the application of reinforcement learning (RL) in the control of an output-constrained flapping-wing micro aerial vehicle (FWMAV) with system uncertainty.

A six-degrees-of-freedom hummingbird model is used without consideration of the inertial effects of the wings. A RL algorithm based on actor–critic framework is applied, which consists of an actor network with unknown policy gradient and a critic network with unknown value function. Considering the good performance of neural network (NN) in fitting nonlinearity and its optimum characteristics, an actor–critic NN optimization algorithm is designed, in which the actor and critic NNs are used to generate a policy and approximate the cost functions, respectively. In addition, to ensure the safe and stable flight of the FWMAV, a barrier Lyapunov function is used to make the flight states constrained in predefined regions. Based on the Lyapunov stability theory, the stability of the system is analyzed, and finally, the feasibility of RL in the control of a FWMAV is verified through simulation.

The proposed RL control scheme works well in ensuring the trajectory tracking of the FWMAV in the presence of output constraint and system uncertainty.

A novel RL algorithm based on actor–critic framework is applied to the control of a FWMAV with system uncertainty. For the stable and safe flight of the FWMAV, the output constraint problem is considered and solved by barrier Lyapunov function-based control.

To fabricate high performance parts, this paper aims to systematically study the pores characteristics and their formation mechanisms in selective laser melting (SLM) AlSi10Mg.

Cubes of 10 × 10 × 5 mm were manufactured in different laser power, scan speed and scan space. Optical microscope (OM) and scanning electron microscopes (SEM) were used to observe morphology of pores.

Round or irregular pores were found in SLMed AlSi10Mg parts. All the round pores have smooth inner walls and locate in the melt pool. The formation mechanisms of the round pores are contributed to the evaporation of elements in the melt pool, H₂O, high laser energy input and hollow powder. Irregular pores have rough inner walls. Big scan space, unevenness of the upper surface, large layer thickness, spatter and oxide are the main reasons of generating irregular pores which outside the melt pool. Instability of keyhole leads to the irregular pores locate in the bottom of keyhole mode melt pool.

Relationship between pores and melt pool were studied systematically for the first time. Researches of pores characteristics and their formation mechanisms in SLMed AlSi10Mg would be a valuable reference for researchers to obtain an important insight into and control the defect in SLMed Al alloy.

This paper aims to study a retailer’s decision on the price and inventory when facing strategic consumer behavior and demand uncertainty. Price protection is a kind of rebate that the retailer provides to consumers when the price drops during the selling season. The research investigates whether price protection can bring the retailer advantages. This paper compares price protection’s impact with price commitment. In addition, the paper studies the price protection’s impacts on supplier of the supply chain.

In this model, there are three alternative strategies for retailer: no price protection policy, full price protection policy and partial price protection policy. The selling season is divided into two periods: regular period and sale period. In the regular period, the products are sold at a regular price. In the sale one, the products are sold at a lower price. By adopting rational expectations equilibrium, this paper analyzes retailer’s optimal price and order quantity under each policy and compares optimal decisions and maximum profits of three policies.

This paper finds that the price protection has a positive influence on the retailer. Strategic consumers are induced to purchase at the regular period. It can simultaneously increase retailer’s profit and reduce inventory risk. Meantime, full price protection is chosen as the optimal policy. By comparing full price protection’s impacts with price commitment, full price protection is considered as the most profitable strategy, while price commitment can bring lower inventory risk. In addition, the profit of supplier would decrease because of price protection.

This research provides a new method to address the negative effects of strategic consumer behavior. It also brings some managerial insights to some retailers, especially online ones, on whether to adopt price protection.

During high demand for the virtualized resources in cloud environment, efficient task scheduling achieves the desired performance criteria by balancing the load in the system.

It is a task scheduling approach used for load balancing in cloud environment. Task scheduling in such an environment is used for the task execution on a suitable resource by considering some parameters and constraints to achieve performance.

The presented mechanism is an extension of the previous proposed work quality of service (QoS)-enabled join minimum loaded queue (JMLQ) (Sharma et al., 2019c). The proposed approach has been tested in the CloudSim simulator, and the results show that the proposed approach achieves better results in comparison to QoS-enabled JMLQ and its other variants in the cloud environment.

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This study aims to develop a measurement scale of tourism-led rural gentrification from the perspective of rural residents.

The procedure for developing the measurement scale included a thorough review of related literature on tourism-led rural gentrification and multiple stages of qualitative and quantitative investigations. A total of 1,080 rural residents in Huzhou and Huangshan participated in the project. The semi-structured interviews and questionnaire were applied to collect the data. This study analyzed the data with the methodologies of exploratory factor analysis, confirmatory factor analysis and structural equation modeling.

The measurement scale developed in this study included seven dimensions: Accelerated Ecological Awareness, Individual Behavior, Rural Economic Development, Enhanced Living Standards, Talents and Demographic Changes, Human and Cultural Shift and Cohesive Community.

This measurement scale was developed and validated in China and may not be relevant in other contexts. The scale focuses on tourism-led rural gentrification only from the perspective of rural residents. The findings broaden the knowledge on tourism-led rural gentrification by researching the topic from the point of view of rural residents.

For policymakers and tourism enterprises, this study provides a valuable index for a full understanding of tourism-led rural gentrification. For investors, the research offers insights for priority investments to advance tourism development in rural regions.

This study is one of the few attempts to empirically measure tourism-led rural gentrification. The results improve on the knowledge about tourism-led rural gentrification in China.

本研究的主要目的是从居民视角开发和验证旅游引导的乡村绅士化测量量表。

开发和验证旅游引导的乡村绅士化测量量表主要包含两方面的工作：旅游引导的乡村绅士化相关文献梳理; 多阶段的定量和定性研究。本研究共邀请1080位研究对象参与调研, 并通过深度半结构访谈和调查问卷收集数据, 使用EFA、CFA和SEM等研究方法研究结果。

本研究开发和验证的测量量表包括7个维度：文明素养感知、经济发展感知、生活水平感知、发展环境感知、社会风尚感知、人居环境感知和社区秩序感知。

本研究基于中国背景开发和验证了旅游引导的乡村绅士化测量量表, 未验证该量表在其他国家或地区的普适性, 且仅从居民视角展开研究。我们的研究结果丰富了旅游引导的乡村绅士化内容。

对于政策制定者和旅游企业来说, 本研究为他们充分了解旅游引导的乡村绅士化提供了参考; 对投资者来说, 本研究为投资者投资提供了有价值的借鉴和参考。

本研究是测量旅游引导的乡村绅士化的重要尝试, 丰富了对中国旅游引导的乡村绅士化的认识。

旅游引导的乡村绅士化 居民感知 量表开发 量表验证

文章类型： 研究型论文

El objetivo principal del presente estudio es desarrollar y validar una escala de medición de gentrificación rural impulsada por el turismo desde la perspectiva de los residentes.

El desarrollo y la validación de la presente escala de medición consistió en dos tareas principales: un examen de la literatura relacionada con la gentrificación rural impulsada por el turismo; y múltiples etapas de investigación cuantitativa y cualitativa. Para este estudio, se invitó a un total de 1080 sujetos para participar de esta investigación, los datos se obtuvieron mediante entrevistas y cuestionarios semiestructurados en profundidad, y los resultados se han analizado mediante EFA, CFA y SEM.

La escala de medición desarrollada y validada en este estudio consta de 7 dimensiones: percepción de alfabetismo civilizacional, percepción de desarrollo económico, percepción de nivel de vida, percepción de entorno de desarrollo, percepción de costumbres sociales, percepción de asentamiento humano y percepción de orden comunitario.

Este estudio desarrolló y validó la escala de medición basada en un contexto chino, pero no se pudo generalizar la escala de medición en otros países o regiones. Esta investigación solo analiza el fenómeno de gentrificación rural impulsada por el turismo desde la perspectiva de los residentes. Nuestros resultados contribuyen a mejorar el contenido de la gentrificación rural impulsada por el turismo.

Para los responsables políticos y las empresas de turismo, la presente investigación constituye una referencia para que comprendan plenamente la gentrificación rural impulsada por el turismo; para los inversores, constituye una valiosa referencia de inversión.

Este estudio es un importante intento para medir la gentrificación rural impulsada por el turismo y contribuye a enriquecer la comprensión de la gentrificación rural impulsada por el turismo de China.

Gentrificación rural impulsada por el turismo, Percepción de los residents, Desarrollo de la escala, Validación de la escala

Trabajo de investigación

The 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.

This work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.

The research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.

The finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.