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Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail transit passengers during the epidemic. The purpose of this paper is to efficiently monitor the flow of rail passengers, the first method is to regulate the flow of passengers by means of a coordinated connection between the stations of the railway line; the second method is to objectively distribute the inbound traffic quotas between stations to achieve the aim of accurate and reasonable control according to the actual number of people entering the station.

This paper analyzes the rules of rail transit passenger flow and updates the passenger flow prediction model in time according to the characteristics of passenger flow during the epidemic to solve the above-mentioned problems. Big data system analysis restores and refines the time and space distribution of the finely expected passenger flow and the train service plan of each route. Get information on the passenger travel chain from arriving, boarding, transferring, getting off and leaving, as well as the full load rate of each train.

A series of digital flow control models, based on the time and space composition of passengers on trains with congested sections, has been designed and developed to scientifically calculate the number of passengers entering the station and provide an operational basis for operating companies to accurately control flow.

This study can analyze the section where the highest full load occurs, the composition of passengers in this section and when and where passengers board the train, based on the measured train full load rate data. Then, this paper combines the full load rate control index to perform reverse deduction to calculate the inbound volume time-sharing indicators of each station and redistribute the time-sharing indicators for each station according to the actual situation of the inbound volume of each line during the epidemic. Finally, form the specified full load rate index digital time-sharing passenger flow control scheme.

This paper is supposed to provide a critical review of current research progress on thermal management in grinding of superalloys, and future directions and challenges. By understanding the current progress and identifying the developing directions, thermal management can be achieved in the grinding of superalloys to significantly improve the grinding quality and efficiency.

The relevant literature is collected from Web of Science, Scopus, CNKI, Google scholar, etc. A total of 185 literature is analyzed, and the findings in the literature are systematically summarized. In this case, the current development and future trends of thermal management in grinding of superalloys can be concluded.

The recent developments in grinding superalloys, demands, challenges and solutions are analyzed. The theoretical basis of thermal management in grinding, the grinding heat partition analysis, is also summarized. The novel methods and technologies for thermal management are developed and reviewed, i.e. new grinding technologies and parameter optimization, super abrasive grinding wheel technologies, improved lubrication, highly efficient coolant delivery and enhanced heat transfer by passive thermal devices. Finally, the future trends and challenges are identified.

Superalloys have excellent physical and mechanical properties, e.g. high thermal stability, and good high-temperature strength. The superalloys have been broadly applied in the aerospace, energy and automobile industries. Grinding is one of the most important precision machining technologies for superalloy parts. Owing to the mechanical and physical properties of superalloys, during grinding processes, forces are large and a massive heat is generated. Consequently, the improvement of grinding quality and efficiency is limited. It is important to conduct thermal management in the grinding of superalloys to decrease grinding forces and heat generation. The grinding heat is also dissipated in time by enhanced heat transfer methods. Therefore, it is necessary and valuable to holistically review the current situation of thermal management in grinding of superalloys and also provide the development trends and challenges.

Francois Quesnay, known as the “Confucius of Europe”, was profoundly influenced by traditional Chinese culture to form his thoughts, which contained strong Chinese characteristics. This paper aims to examine economic thought of Francois Quesnay from the perspective of the construction of socialist political economics with Chinese characteristics.

Moreover, his thoughts also profoundly influenced subsequent economists, such as Adam Smith and Karl Marx. It can be said that Francois Quesnay was at the intersection of Chinese, Western and Marxist thought systems, so it is quite important to examine his thoughts critically and conduct source-tracing in China.

Hence, in the process of constructing and developing socialist political economy with Chinese characteristics, there is an urgent need to focus on exploring the value of excellent traditional Chinese culture at the theoretical level and combining the development and dissemination of the history of thoughts and the historical position of Chinese reality to realize the innovation and development of socialist political economy with Chinese characteristics.

Meanwhile, while absorbing nutrition from excellent traditional Chinese culture, it is necessary to establish scientific coordinates rather than use the discourse systems and paradigms of Western economics to interpret ancient Chinese economic thoughts. It is necessary to adhere to, inherit and develop Marxist political economy and absorb nutrition from Chinese excellent traditional culture to construct socialist political economy with Chinese characteristics.

This study aims to explore how manufacturing firms master customer lock-in through value creation by servitization innovation strategies from the perspective of asset specificity.

A multiple case study with triangulation fashion is adopted to identify servitization innovation strategies. Several manufacturing firms were investigated, which are distributed in different positions of the value chain. Content analysis and abductive approaches are adopted to analyze the data. Moreover, an in-depth interview and participatory observation were conducted to refine the analysis results.

This study identified four different focusing points of servitization operations. Based on these, the paper further induces an innovative servitization strategy matrix of customer lock-in, concerning communion, intellectual, existential and insubstantial strategies. Furthermore, a conceptual model of customer lock-in by servitization innovation from the perspective of asset specificity is elaborated. It is suggested that companies can use tangible or intangible resources by sharing or storing operations to create servitization value.

This study theoretically proposes a conceptual model to extend servitization innovation as an intangible asset and adopt the new perspective of asset specificity to illustrate the value creation in servitization to generate customer lock-in.

This study explored how the Singaporean government responded to the Covid-19 pandemic crisis from early January 2020 to the end of May of the same year. It evaluated the capability of Singapore's leadership management in a crisis during the peak and ravaging period of the Covid-19 pandemic.

The study utilised a systematic design analysis approach, analysing Singaporean cases on the Covid-19 crisis using a systematic and narrative approach to underscore the country's response to the pandemic attack from January 2020 to May 2020.

Against the backdrop of Singapore's peculiar political system of government dominated by the ruling People's Action Party (PAP) and culture of bureaucracy, the government has increasingly executed several control measures, including strict travel bans, contact tracing, the circuit breaker–lockdown, mask-wearing, social distancing orders as well as financial support to businesses and employees from top to the bottom in the country. However, the treatment and health issues of the migrant workers in the dormitories continue to be the major concern among academics and scholars. At the same time, policy inadequacies truncate the excellent measure of Singapore's response to Covid-19. The case point review concluded that the mortality rate in Singapore remains low compared to other nations of the world. Singapore's case points unveil fundamental learning that an excellent leadership-driven harmonised strategic model is essential for crisis management in any society. The finding of the analysis demonstrated that Singapore adopted a contingency and value-based leadership model to advance good governance and tackle the spread of the deadly coronavirus in its country.

The study has demonstrated a profound analysis that has not been conducted hitherto. Investigation of the Singapore case point is not a popular analysis among Nigerian scholars. Therefore, from Nigeria's perspective, the study has showcased the good and the wrong sides of a coin in Singapore's leadership and power dynamic in crisis management.

Food supply chain (FSC) in Greece is dominated by small and medium-sized enterprises (SMEs), who face several challenges in adopting green practices. The purpose of this paper is to identify the key drivers and barriers influencing the environmental performance of SMEs within the Greek dairy supply chain (SC).

Descriptive research methodology attempts to prioritize the drivers and barriers for improving the environmental sustainability performance. Analytical hierarchy process and sensitivity analysis are used to understand the complex nature of the influencing factors.

The analysis identifies five barriers and six drivers for the implementation of green practices within the dairy SC. While external drivers significantly influence the market structure and logistics network, government, competitors and customers are the driving factors for improving environmental performance.

The study contributes to filling the literature gap on key factors influencing the implementation of green practices within the FSC. The identified influential factors will contribute toward building a framework for improving sustainability performance within the Greek dairy SC.

The study is expected to benefit the Greek and European SMEs by driving their environmental practices within the perishable SC network.

The paper provides directions for researchers, practitioners and policy makers in understanding the challenges for implementing green practices in the dairy SC. The holistic approach followed in this paper is a building block for a conceptual framework on implementing environmental sustainability within the FSC. Apart from contributing to the current literature by extending the research horizon to SMEs’ green adoption capability, this study also provides better understanding of the pivotal role of internal and external key factors in influencing sustainability performance.

While the Olympic Games are always under the spotlight, the Paralympic Games are somehow ignored. This paper aims to invite the general public to think about the para-athletes and the differential treatments they received.

Among the participating countries, many of them were unable to win a single Olympic or Paralympic medal. When the dependent variable is left-censored, ordinary least squares regression is asymptotically biased downwards. In the literature, researchers typically employ the maximum likelihood Tobit model to take care of the censoring problem. However, some researchers argue that the Hurdle model has an advantage over the Tobit model in identifying the determinants of winning Olympic medals. Following their wisdom, this paper employs both the Tobit and Hurdle models in analysis.

The empirical evidence gathered in this paper suggests that population size, host status and average years of schooling are the big three socio-economic determinants when it comes to winning medals at the Paralympic Games and Olympic Games. The findings support the hypothesis that sports talent is randomly distributed and a large country has a higher chance to have talented athletes or para-athletes winning the Olympic medals. The strong host advantage also showed up in the following Paralympics but was not so strong at the next Olympics.

This paper not only examines the relationship between various social, economic and political factors in determining the success of a nation in the Paralympic Games but also attempts to identify possible non-traditional determinants.

This study aims to use regression Least-Square Support Vector Machine (LS-SVM) as a probabilistic model to determine the factor of safety (FS) and probability of failure (PF) of anisotropic soil slopes.

This research uses machine learning (ML) techniques to predict soil slope failure. Due to the lack of analytical solutions for measuring FS and PF, it is more convenient to use surrogate models like probabilistic modeling, which is suitable for performing repetitive calculations to compute the effect of uncertainty on the anisotropic soil slope stability. The study first uses the Limit Equilibrium Method (LEM) based on a probabilistic evaluation over the Latin Hypercube Sampling (LHS) technique for two anisotropic soil slope profiles to assess FS and PF. Then, using one of the supervised methods of ML named LS-SVM, the outcomes (FS and PF) were compared to evaluate the efficiency of the LS-SVM method in predicting the stability of such complex soil slope profiles.

This method increases the computational performance of low-probability analysis significantly. The compared results by FS-PF plots show that the proposed method is valuable for analyzing complex slopes under different probabilistic distributions. Accordingly, to obtain a precise estimate of slope stability, all layers must be included in the probabilistic modeling in the LS-SVM method.

Combining LS-SVM and LEM offers a unique and innovative approach to address the anisotropic behavior of soil slope stability analysis. The initiative part of this paper is to evaluate the stability of an anisotropic soil slope based on one ML method, the Least-Square Support Vector Machine (LS-SVM). The soil slope is defined as complex because there are uncertainties in the slope profile characteristics transformed to LS-SVM. Consequently, several input parameters are effective in finding FS and PF as output parameters.

This paper aims to contribute to understanding Brazilian fashion consumer behavior. The subsequent research question is formulated as follows: How are the consumers purchasing new clothes and disposing of used ones, and how is their awareness of sustainable fashion consumption and disposal of used clothes?

An online questionnaire was sent to nearly one thousand e-mails. A database was formed with 182 complete answers to 13 questions concerning consumer behavior toward sustainability, especially clothing acquisition, use and disposal. A multimethod approach was used to analyze the initial attributes, applying descriptive statistics, cluster analysis and data mining.

This survey obtained valuable answers from Brazilian fashion consumers grouped into four clusters. Age and yearly income were more critical in determining the clusters. Only four attributes were chosen by the algorithm to build the trees (age, annual income, yearly spending on clothes and how long the clothes are worn). The consumer's profile may help the fashion industry redirect investments in sustainability. The most critical factor leading to the sustainability of clothing fashion was the duration of the clothes. The study dealt with a limited sample size that was not representative of Brazil's broader population. Despite numerous attempts to seek responses through e-mail, the participant pool was predominantly composed of highly educated individuals.

This assessment of Brazilian consumer behavior toward sustainability and fashion presents essential knowledge to understand the relationships among variables affecting the purchase and discharge of clothes.

The purpose of this research is to identify major barriers to the implementation of reverse logistics (RL). Also, the study addresses best practices among reuse, remanufacture, recycling, refurbishment and repair as alternatives for RL processes.

This study targets supply chain management experts for their opinions regarding the identification of critical barriers and alternatives for RL implementation. Their opinions were extracted through a Web questionnaire based on 14 criteria with 5 alternatives. The tools of multi-criteria decision-making are used for analysis, i.e. fuzzy VIKOR and fuzzy TOPSIS.

The results indicate that lack of recognition of competitive advantage to be gained through RL practice is the most critical barrier to RL implementation. The least barrier or major facilitator for RL is “supportive initiative for end-of-life products.” The top-ranked alternative in this study is reuse followed by remanufacturing. The least important alternative is “repair” in the case of Pakistan. These alternatives are ranked based on “q values” derived through fuzzy VIKOR.

The results of this study can only be generalized for the manufacturing sector of Pakistan during the period of the study.

The findings of this study will assist managers in deploying the best practices concerning RL.

Fuzzy VIKOR and fuzzy TOPSIS have not been applied to RL alternatives in previous research.