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The purpose of this paper is to investigate the two-dimensional stagnation-point flow, heat and mass transfer of an incompressible upper-convected Oldroyd-B MHD nanofluid over a stretching surface with convective heat transfer boundary condition in the presence of thermal radiation, Brownian motion, thermophoresis and chemical reaction. The process of heat and mass transfer based on Cattaneo–Christov double-diffusion model is studied, which can characterize the features of thermal and concentration relaxations factors.

The governing equations are developed and similarly transformed into a set of ordinary differential equations, which are solved by a newly approximate analytical method combining the double-parameter transformation expansion method with the base function method (DPTEM-BF).

An interesting phenomenon can be found that all the velocity profiles first enhance up to a maximal value and then gradually drop to the value of the stagnation parameter, which indicates the viscoelastic memory characteristic of Oldroyd-B fluid. Moreover, it is revealed that the thickness of the thermal and mass boundary layer is increasing with larger values of thermal and concentration relaxation parameters, which indicates that Cattaneo–Christov double-diffusion model restricts the heat and mass transfer comparing with classical Fourier’s law and Fick’s law.

This paper focuses on stagnation-point flow, heat and mass transfer combining the constitutive relation of upper-convected Oldroyd-B fluid and Cattaneo–Christov double diffusion model.

Trust has emerged as a crucial research topic in the sharing economy. However, scholarship on trust in sharing accommodation remains limited. By using stakeholder theory, this study aims to provide a systematic framework for integrating trust among multiple stakeholders and identify potential knowledge gaps and future research directions for trust in sharing accommodation.

The authors select papers using a combination of multiple keywords from EBSCOhost and Web of Science. The analysis includes 172 journal papers published between 2011 and 2021. The authors conduct a systematic review through thematic content analysis, and each paper is analyzed using manual coding.

The analysis shows that key stakeholders for trust building in sharing accommodation include consumers, hosts, platforms, residents and governments, with most studies focusing on the consumer perspective. The study integrates various trust antecedents and outcomes from the above multistakeholder. Second, this study summarizes the most commonly used theories, and more diversified theories could be applied to future research. Third, this study finds that most studies use quantitative methods, and researchers should introduce more integrated methodologies such as machine learning on a large scale. Furthermore, the current research disciplinary paradigm should be extended to multidisciplinary and interdisciplinary approaches to promote innovation in trust research. Finally, the COVID-19 pandemic has brought both challenges and opportunities to industry as well as researchers, and more institutional rather than commercial perspectives need to be addressed.

The study contributes to the trust and the sharing economy literature by providing a systematic framework for integrating trust from multistakeholder perspectives. The study also points out several future research directions by combining micro and macro multistakeholder perspectives, identifying more diversified theories and methodologies and specifying multidisciplinary and interdisciplinary approaches.

The study advances knowledge by providing a systematic framework for integrating trust among multiple stakeholders and proposing future research directions for trust in sharing accommodation.

This study aims to examine the use of the metaverse in tourism and hospitality to comprehend better how the technology might shape customer journey management, especially relative to information provision, experiences and customer benefits.

This explanatory research used a two-stage approach of media analysis and practitioner interviews to analyse the interactions among tourism information provision, customer experiences and customer benefits in the metaverse. It conceptualized and mapped the consumer journey of the emerging metaverse experience, focusing on the ideas and practices of metaverse design pioneers in tourism and hospitality.

Based on the media analysis and interviews with 27 designers, the metaverse – information – experiences – benefits (MIEB) model was proposed, containing three parts (information characteristics, customer experiences and customer benefits) and 31 supporting items grouped into nine components.

One of the unique contributions of this research is the MIEB model for applying the metaverse in customer journey management (pre-, during- and post-trip). The findings contribute to the current literature with this model based on the practical perspectives of metaverse designers and provide insights on how to incorporate the MIEB model in applying the metaverse in tourism and hospitality management. The findings also address existing literature gaps of insufficient research on metaverse management and design through all stages of the customer travel journey and by paying attention to stakeholders’ viewpoints, including the media and designers of metaverse applications. Engaging in semi-structured interviews with pioneers of the metaverse to gain insights into the design of tourism experiences was also different from other metaverse tourism research, although this is not claimed as a significant point of innovation.

This study aims to develop a finite element method based co-simulation platform for the numerical analysis of motor drive system. With the rising requirement of industry, the comprehensive design of motor drive systems has attracted increasing attentions. An accurate model, which considers the coupling between motor and its drive system, is vital for the analysis and design of motor drive system.

Considering the coupling relationship between motor and its drive system, a flexible and extensible co-simulation platform of motor drive system is developed with the C++ language and finite element machine model to carry out the comprehensive analysis of motor drive system. The control system simulation program developed with C++ language adopts the same discrete form as the single-chip microcomputer and can simulate the interrupt mechanism, making the simulation closer to the actual control system. With the finite element analysis results of current step, the winding input voltage of next step is calculated by the executable program of control system and is fed into the finite element analysis, forming the two-way coupling analysis of drive system.

Preliminary studies, such as calculation of machine core losses fed by inverters, and control parameters optimization, are conducted with this platform, which shows the flexibility and expansibility of this platform.

The power inverter circuit along with the controller is modeled using the C++ language, and embedded into the finite element machine model to achieve more realistic motor drive system simulation and complex functions.

The purpose of this paper is to generate grinding trajectory of unknown model parts simply and efficiently. In this paper, a method of grinding trajectory generation of hybrid robot based on Cartesian space direct teaching technology is proposed.

This method first realizes the direct teaching of hybrid robot based on 3Dconnexion SpaceMouse (3DMouse) sensor, and the full path points of the robot are recorded in the teaching process. To reduce the jitter and make the speed control more freely when dragging the robot, the sensor data is processed by Kalman filter, and a variable admittance control model is established. And the joint constraint processing is given during teaching. After that, the path points are modified and fitted into double B-splines, and the speed planning is performed to generate the final grinding trajectory.

Experiment verifies the feasibility of using direct teaching technology in Cartesian space to generate grinding trajectory of unknown model parts. By fitting all the teaching points into cubic B-spline, the smoothness of the grinding trajectory is improved.

The whole method is verified by the self-developed TriMule-600 hybrid robot, and it can also be applied to other industrial robots.

The main contribution of this paper is to realize the direct teaching and trajectory generation of the hybrid robot in Cartesian space, which provides an effective new method for the robot to generate grinding trajectory of unknown model parts.

Evaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.

The researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.

Using the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.

Considering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.

This study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.

The present study provides a comprehensive review of the advancements in five active heating modes for cold-proof clothing as of 2021. It aims to evaluate the current state of research for each heating mode and identify their limitations. Further, the study provides insights into the optimization of intelligent temperature control algorithms and design considerations for intelligent cold-proof clothing.

This article presents a classification of active heating systems based on five different heating principles: electric heating system, solar heating system, phase-change material (PCM) heating system, chemical heating system and fluid/air heating system. The systems are analyzed and evaluated in terms of heating principle, research advancement, scientific challenges and application potential in the field of cold-proof clothing.

The rational utilization of active heating modes enhances the thermal efficiency of cold-proof clothing, resulting in enhanced cold-resistance and reduced volume and weight. Despite progress in the development of the five prevalent heating modes, particularly with regard to the improvement and advancement of heating materials, the current integration of heating systems with cold-proof clothing is limited to the torso and limbs, lacking consideration of the thermal physiological requirements of the human body. Additionally, the heating modes of each system tend to be uniform and lack differentiation to meet the varying cold protection needs of various body parts.

The effective application of multiple heating modes helps the human body to maintain a constant body temperature and thermal equilibrium in a cold environment. The research of heating mode is the basis for realizing the temperature control of cold-proof clothing and provides an effective guarantee for the future development of the intelligent algorithms for temperature control of non-uniform heating of body segments.

The integration of multiple heating modes ensures the maintenance of a constant body temperature and thermal balance for the wearer in cold environments. The research of heating modes forms the foundation for the temperature regulation of cold-proof clothing and lays the groundwork for the development of intelligent algorithms for non-uniform heating control of different body segments.

The present article systematically reviews five active heating modes suitable for use in cold-proof clothing and offers guidance for the selection of heating systems in future smart cold-proof clothing. Furthermore, the findings of this research provide a basis for future research on non-uniform heating modes that are aligned with the thermal physiological needs of the human body, thus contributing to the development of cold-proof clothing that is better suited to meet the thermal needs of the human body.

This study presents a fuzzy synthetic evaluation of the challenges of smart city realisation in developing countries, using Nigeria as a case study. By defining and delineating the problems faced by the country, more viable directions to attaining smart city development can be achieved.

The study adopted a post-positivist philosophical stance with a deductive approach. A structured questionnaire was used to gather data from built environment professionals involved in the delivery of Nigerian public infrastructures. Six dimensions of the challenges of smart cities were identified from literature and explored. They are governance, economic, social, technological, environmental and legal issues. Data gathered were analysed using Cronbach alpha test for reliability, Shapiro-Wilks test for normality, Kruskal-Wallis H-test for consistency and fuzzy synthetic evaluation test for the synthetic evaluation of the challenges of smart city attainment.

The findings revealed that all six assessed dimensions have a significant impact on the attainment of smart cities in Nigeria. More specifically, issues relating to environmental, technological, social and legal challenges are more prominent.

The fuzzy synthetic approach adopted provides a clear, practical insight on the issues that need to be addressed before the smart city development can be attained within developing countries.