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Even though following the laws of nature to construct harmonious nature–human interactions has long been one of the most influential philosophies in Chinese history, nature-based solutions (NBS), an innovative concept referring to the sustainable utilization of nature in solving various social and environmental challenges facing contemporary societies, can hardly be found in research papers and practices in Chinese context until very recently. Yet, some NBS features, and also NBS thinking, have already been successfully embedded within many environmental management decisions and practices, which are commonly characterized by (1) prioritization of nature preservation/restoration to economic activities and (2) functionalization of nature as a countermeasure to environmental and/or social issues. This chapter will present a comprehensive overview of the Beijing Afforestation Scheme, an exemplar case of NBS in the Chinese context. Starting from a description of Beijing and this massive afforestation project, it delineates major characteristics of this NBS, signified by (1) a shift from outcome-driven to integrated ecological resilience, (2) a change from recreating tree rows to restoring natural boreal forest, and (3) an evolution from top-down to adaptive and inclusive governance. Lastly, lessons learnt and future challenges are discussed.

In this chapter, we will review the history, deregulation, policy reforms, and airline consolidations and mergers of the Chinese airline industry. The measurement of airline competition in China’s domestic market will also be discussed. Although air deregulation is still ongoing, the Chinese airline industry has become a market-driven business subject to some mild regulations. Then, we will review the impressive development of the high-speed rail (HSR) network in China and its effects on the domestic civil aviation market. In general, previous studies have found that the introduction of HSR services has a significant negative impact on airfare and air travel demand in China. The rapidly expanding network of HSR has important policy implications for Chinese airlines.

The purpose of this paper is to explore the influence of organizational culture (OC) on talent management (TM) by a case study of a real estate company.

The method of case study is adopted in the present study.

The authors present four propositions. The first is OC has an effect on TM. The second is a new conceptual model of TM. The third is a 4-P pattern to identify and develop the talent. The fourth is to adopt both the spiritual and material satisfactions that retain the talent.

The primary limitation of this study is embedded in the case study method, which is not sufficient to represent the totality. The other limitation is that the issue of cohesion and team efficacy of talents is not considered. This study argues the relationship between OC and TM and expands the existing TM and OC theory. The effect of professional idealism is emphasized on in the process of TM. Talent can be retained firmly within the organization through the methods of rebuilding and strengthening OC.

A conceptual model of TM, 4-P pattern of evaluation and the operational mean to retain the talent is introduced.

This study aims to investigate the role of aluminium (Al) in marine environment and the corrosion mechanism of galvalume coatings by conducting accelerated experiments and data analysis.

Samples were subjected to accelerated corrosion for 136 days via salt spray tests to simulate the natural conditions of marine environment and consequently accelerate the experiments. Subsequently, the samples were examined using various test methods, such as EDS, scanning electron microscopy (SEM), X-ray diffraction (XRD) and electrochemical impedance spectroscopy (EIS), and the obtained data were analysed.

Galvalume coatings comprised interdigitated zinc (Zn)-rich and dendritic Al-rich phases. Corrosion was observed to begin with a Zn-rich phase. The primary components of the corrosion product film were Al₂O₃ and Zn₅(OH)₈Cl₂·H₂O. It was confirmed that the role of Al was to form a dense protective film, thereby successfully blocking the entry of corrosive media and protecting the iron substrate.

This study provides a clearer understanding of the corrosion mechanism and kinetics of galvalume coatings in a simulated marine environment. In addition, the role of Al, which is rarely mentioned in the literature, was investigated.

This paper employs nationwide, large-scale field survey data to provide the first empirical evidence on the impact of human educational capital on the acquisition of health entitlement among Chinese migrant workers. The findings of this study hold significant practical implications for the formulation of policies aimed at improving the health protection of migrant workers, as well as for socioeconomic policies during China's transitional period.

Using the IVProbit model, this research examines how human educational capital influences the attainment of health entitlement among migrant workers in China by analyzing the impact and mechanism of education on health entitlement. The study is based on the China Migrants Dynamic Survey (CMDS) data from 2018, which include 100,177 observations.

For migrant workers in China, higher levels of education have a significant positive effect on the acquisition of health entitlements, including medical insurance, health records and health education. The positive impact of human educational capital on health entitlements is more significant for non-provincial cities and young-generation migrant workers. The results also show that human educational capital can influence the acquisition of health entitlements through mediators such as financial status, social integration and health status.

This study represents the first empirical attempt to evaluate the influence of human educational capital on the access of migrant workers in China to health rights and interests. Additionally, the study develops a theoretical framework to examine how the impact of human educational capital varies across migrant workers with different characteristics and their access to health entitlements.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

This study aims to use eye-tracking technology to conduct an empirical study about online learning process analysis, thus aiming to understand the attentional preferences and learning paths in online learners.

With eye movement tracking and data analysing technology, the Tobii X120 eye-tracking instrument, Tobii studio and online learning platform are used to record and visualise data of eye moving and learning steps during the real task-based online learning processes of 14 online learners. According to Barbara A. Soloman’s learning style classification framework, these learners’ learning style was presented in four dimensions. Based on data of eye moving, leaning style and operation in online course, the correlation about learners’ preferences of learning content, online learning paths and learning style were analysed based on according data.

The paper provides empirical insights about how change is brought about during online learning. It is found that there is no significant difference in attention preference between the students with the difference on the learning style of visual-verbal, although each person has a different attention preference on the learning content.

The limitation of this study is that only one common type of video learning process is studied. The learning process of various types of instructional videos in online learning will be done in future research.

In this study, eye-movement tracking technology is used to understand students’ learning path and learning preference in the online learning process, which is helpful to optimise the online learning process and improve the efficiency of online learning.

This research findings have been approved by relevant experts and have won the first prize in the school-level competition of South China Normal University in China.

In this study, the technology of psychology (eye-tracking technology) is introduced into the study of real task-based online learning process in the subject of educational technology, realising the integration of multi-disciplinary research techniques and methods.

Inland shipping has been extensively recognised as a sustainable, efficient and good alternative to rail and road modes of transportation. In recent years, various authorities and academic researchers have advocated shifting from road to other sustainable modes like inland waterway transport (IWT) or rail transport. Academic work on modernisation and technological innovations to enhance the effectiveness and efficiency of waterborne transportation is becoming apparent as a growing body of literature caused by the need to achieve a sustainable transport system. Thus, it became apparent to explore the research trends on IWT.

A systematic and structured literature review study was employed in this paper to identify the challenges and concepts in modernising inland waterways for freight transportation. The review analysed 94 articles published in 54 journals from six well-known databases between 2010 and 2022.

The key findings of this review are that despite various challenges confronting the sector, there have been successful cases of technological advancement in the industry. The main interest among scholars is improving technical and economic performance, digitalisation, and safety and environmental issues. The review revealed that most of the literature is fragmented despite growing interest from practitioners and academic scholars. Academic research to address the strategic objectives, including strengthening competitiveness (shipbuilding, hydrodynamics, incorporating artificial intelligence into the decision-making process, adopting blockchain technology to ensure transparency and security in the transactions, new technologies for fleets adaptation to climate change, more effective handling, maintenance and rehabilitation technologies), matching growth and changing trade patterns (intermodal solutions and new logistics approaches) are major causes of concerns.

By employing the approach of reviewing previously available literature on IWT review papers, this review complements the existing body of literature in the field of IWT by providing in a single paper a consolidation of recent state-of-the-art research on technological developments and challenges for inland waterways freight transport in the intermodal supply chain that can act as a single resource to keep researchers up to date with the most recent advancements in research in the domain of inland waterway freight transport. Additionally, this review identified gaps in the literature that may inspire new research themes in the field of IWT.

Selective laser melting (SLM) is a major additive manufacturing (AM) process in which laser beams are used as the heat source to melt and deposit metals in a layerwise fashion to enable the construction of components of arbitrary complexity. The purpose of this paper is to develop a framework for accurate and fast prediction of the temperature distribution during the SLM process.

A fast computation tool is proposed for thermal analysis of the SLM process. It is based on the finite volume method (FVM) and the quiet element method to allow the development of customized functionalities at the source level. The results obtained from the proposed FVM approach are compared against those obtained from the finite element method (FEM) using a well-established commercial software, in terms of accuracy and efficiency.

The results show that for simulating the SLM deposition of a cubic block with 81,000, 189,000 and 297,000 cells, the computation takes about 767, 3,041 and 7,054 min, respectively, with the FEM approach; while 174, 679 and 1,630 min with the FVM code. This represents a speedup of around 4.4x. Meanwhile, the average temperature difference between the two is below 6%, indicating good agreement between them.

The thermal field for the multi-track and multi-layer SLM process is for the first time computed by the FVM approach. This pioneering work on comparing FVM and FEM for SLM applications implies that a fast and simple computing tool for thermal analysis of the SLM process is within the reach, and it delivers comparable accuracy with significantly higher computational efficiency. The research results lay the foundation for a potentially cost-effective tool for investigating the fundamental microstructure evolution, and also optimizing the process parameters in the SLM process.