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There is a dearth of empirical research examining the influence of various facets of sustainable banking on the environmental sustainability performance (SP) of banks in developing economies like Bangladesh. This study looks at how green banking practices (GBPs), green finance (GF) and corporate social responsibility (CSR) practices affect SP in both direct and indirect ways.

The research framework of this study was designed based on legitimacy theory to examine the direct and indirect impacts of GBP on environmental SP through GF and CSR practices. Based on a structured questionnaire and convenience sampling, the data were collected from banking institutions to investigate the association among the study variables. Subsequently, the obtained data were evaluated using a well-established structural equation modeling (SEM) approach via SmartPls 4.0 software.

The empirical findings reveal that GBP has a significant direct impact on GF, CSR practices and the banks' SP. Further, the findings show that GF has a direct and significant impact on CSR practices and SP. Likewise, CSR practices have a direct and significant influence on the SP of banks. Additionally, among indirect effects, both CSR practices and GF mediate the association between GBP and SP, whereas GF also has an indirect effect on the relationship between GBP and CSR practices. Surprisingly, the findings demonstrate that CSR practices do not have an indirect effect on the association between GF and SP. Hence, the greater the bank's involvement in green banking activities, the greater the influence of green financing and CSR practices on environmental sustainability.

This study adds to the growing body of research in the areas of sustainable banking and environmental sustainability literature by evaluating the link between GBP, CSR practices, GF and SP. Besides, this is a ground-breaking study that examines both direct and indirect effects of different aspects of sustainable banking (GBP, GF and CSR practices) on the SP of the banking industry in an emerging country like Bangladesh. On the theoretical level, it adds to the application and expansion of legitimacy theory in the sphere of banking and finance. It provides new insights into the dynamics of green banking, GF and CSR practices within the framework of legitimacy theory. Hence, the current study offers significant suggestions to managers, academicians and researchers on how to advance the sustainability of the banking industry by adopting green banking, GF and CSR practices.

This paper aims to explore the influencing factors of public perceived efficacy of emergency infrastructure projects based on the triadic interactive determinism, and analyze the relationship among these factors.

Based on the triadic interactive determinism, we explored the factors influencing public perceived efficacy of emergency infrastructure project and empirically verified the relationship among these factors and perceived efficacy by using data drawn from a questionnaire survey of 491 residents near Leishenshan Hospital, Jiangxia District, Wuhan, China.

Prior experience, emotional response, personal expectation, public trust, context message and interactivity level, namely behavior, individual and environment, affect the perceived efficacy of public emergency infrastructure projects.

The results offer an insight into public perceived efficacy of emergency infrastructure project from the perspective of antecedents in a triadic reciprocal determinism, which provides a reference basis for the sustainable development of the emergency infrastructure projects. This study also suggests valuable practical implications to government departments to improve the quality of administrative decision-making effectively.

Although existing studies have found some influencing factors of public perceived efficacy in general infrastructure, there is still a lack of systematic carding and quantitative description of influencing factors of public perceived efficacy of emergency infrastructure projects. This study bridges this gap by exploring the determinants and their influencing relationship of public perceived efficacy especially for emergency infrastructure projects.

This paper aims to optimize cable-stayed force in asymmetric one-tower cable-stayed bridge formation using an improved particle swarm algorithm. It compares results with the traditional unconstrained minimum bending energy method.

This paper proposes an improved particle swarm algorithm to optimize cable-stayed force in bridge formation. It formulates a quadratic programming mathematical model considering the sum of bending energies of the main girder and bridge tower as the objective function. Constraints include displacements, stresses, cable-stayed force, and uniformity. The algorithm is applied to optimize the formation of an asymmetrical single-tower cable-stayed bridge, combining it with the finite element method.

The study’s findings reveal significant improvements over the minimum bending energy method. Results show that the structural displacement and internal force are within constraints, the maximum bending moment of the main girder decreases, resulting in smoother linear shape and more even internal force distribution. Additionally, the tower top offset decreases, and the bending moment change at the tower-beam junction is reduced. Moreover, diagonal cable force and cable force increase uniformly with cable length growth.

The improved particle swarm algorithm offers simplicity, effectiveness, and practicality in optimizing bridge-forming cable-staying force. It eliminates the need for arbitrary manual cable adjustments seen in traditional methods and effectively addresses the optimization challenge in asymmetric cable-stayed bridges.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

This chapter examines the ‘embodied turn’ in the study of traditional Chinese sports and identifies issues within this area of research. It introduces new interpretative perspectives and approaches within the framework of bodily sociology to elucidate the link between locally-informed sports practices and the formation of socialized individuals. The chapter categorises the current research into three main themes: self-giving, the creation of bodily value and the construction of national identity through sports. It then integrates these themes with the findings of embodied sociology. The chapter compiles and analyzes the existing literature on traditional Chinese sports culture from both Chinese and international scholars, offering insights into the status, rationale and challenges of bodily sociological research. By contextualising the concept of the embodied turn in traditional Chinese sports culture – through concepts such as self-givenness, self-techniques, the generation of value and the creation of collective memory – the chapter discusses the impact of bodily sociology on cultural research. The chapter advocates for further bodily sociological studies of Chinese sports culture, which could enhance the understanding of Chinese studies among Western scholars and contribute to a genuine embodied turn in this field of study. Providing one of the initial explorations of embodied studies in traditional Chinese sports, the chapter reveals a transition from broad cultural interpretations and symbolic, structuralist sociology to a phenomenological approach in sports cultural studies. It posits that the bodily sociology approach is beneficial for sports studies although current research has not yet fully realized the embodied turn.

Fine-tuning pre-trained language models (PLMs), e.g. SciBERT, generally require large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in the scientific domain. However, obtaining fine-tuning data for scientific NLP tasks is still challenging and expensive. In this paper, the authors propose the mix prompt tuning (MPT), which is a semi-supervised method aiming to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks.

Specifically, the proposed method provides multi-perspective representations by combining manually designed prompt templates with automatically learned continuous prompt templates to help the given academic function recognition task take full advantage of knowledge in PLMs. Based on these prompt templates and the fine-tuned PLM, a large number of pseudo labels are assigned to the unlabelled examples. Finally, the authors further fine-tune the PLM using the pseudo training set. The authors evaluate the method on three academic function recognition tasks of different granularity including the citation function, the abstract sentence function and the keyword function, with data sets from the computer science domain and the biomedical domain.

Extensive experiments demonstrate the effectiveness of the method and statistically significant improvements against strong baselines. In particular, it achieves an average increase of 5% in Macro-F1 score compared with fine-tuning, and 6% in Macro-F1 score compared with other semi-supervised methods under low-resource settings.

In addition, MPT is a general method that can be easily applied to other low-resource scientific classification tasks.

The purpose of this study was to examine the relationship between environmental pressure, green logistics strategy (GLS) and sustainability performance as well as the moderating role of competitive intensity in the relationship between environmental pressure and GLS in the context of the Ghanaian Manufacturing firms.

The study included a thorough review of the literature and an empirical questionnaire-based data collection with responses from 220 participant manufacturing firms in Ghana. The data collected was statistically analysed using the PLS-SEM software.

The findings of the study indicated that environmental pressure positively influences the implementation of GLS. Again, it was revealed that there is a significant relationship between GLS and sustainability performance. Likewise, the study also found that environmental pressure significantly influences sustainability performance. Also, competitive intensity was found to moderate the relationship between environmental pressure and GLS.

This study gives insight into GLS and sustainability performance and also suggested that when managers in manufacturing industries adopt green practices as a result of environmental pressure, sustainability performance will be achieved. The geographic scope of the study area and time constraints were some of the research's limitations.

Although there have been studies carried out on the subject of green logistics, this study is the first of its kind to examine the relationship between environmental pressure, GLS and sustainability performance within the context of developing economies such as Ghana. Also, this study shows how intense competition in the market can moderate the adoption of GLS.

During the forming process, aluminum alloy sheets develop various types of textures and are subjected to cyclic loading as structural components, resulting in fatigue damage. This study aims to develop polycrystalline models with different orientation distributions and incorporate suitable fatigue indicator parameters to investigate the effect of orientation distribution on the mechanical properties of Al-7.02Mg-1.78Zn alloys under cyclic loading.

In this study, a two-dimensional polycrystalline model with 150 equiaxed grains was constructed based on optical microscope images. Subsequently, six different orientation distributions were assigned to this model. The fatigue indicator parameter of strain energy dissipation is utilized to analyze the stress response and fatigue crack driving force in polycrystalline models with different orientation distributions subjected to cyclic loading.

The study found that orientation distribution significantly influences fatigue crack initiation. Orientation distributions with a larger average Schmid factor exhibit reduced stress response and lower fatigue indicator parameters. Locations with a larger average Schmid factor experience greater plastic deformation and present a higher risk for fatigue crack initiation. RVE with a single orientation undergoes more rotation to reach cyclic steady state under cyclic loading due to the ease of deformation transfer.

Currently, there are no reports in the literature on the calculation of fatigue crack initiation for Al-Mg-Zn alloys using the crystal plasticity finite element method. This study presents a novel strategy for simulating the response of Al-7.02Mg-1.78Zn materials with different orientation distributions under symmetric strain cyclic loading, providing valuable references for future research.

The inclusion of esports as an official event in the Hangzhou Asian Games is an important step towards the institutionalisation of esports. The significance of this event marks that Asia once again takes a lead in the global esportisation. This chapter investigates a series of history events in the inclusion process of esports into the comprehensive Games in Asia using process sociology and actor network theory (ANT). This study will analyse the type characteristics of esports events in Hangzhou Asian Games, whilst examining how key stakeholders' interact and balance in the network composed of international sports organisations, host of the event, emerging esports organisations and esports game companies. The chapter also examines the functions of global game industrial economic geography, local cultural politics, esports geopolitics and Olympic values in esports sportization, aiming to reveal the implications of esports inclusion in the Asian Games on the debate of whether esports meets the criteria to be classified as a ‘sport’ and its enlightenment of digital strategy to the inclusion esports in the Olympics.

This paper focuses on the last-mile logistics (LML) operations in fulfilling online grocery orders and the related sustainability considerations in sparsely populated areas like Australia. It aims to examine how online groceries in sparsely populated areas can benefit from online business. Specifically, this study seeks to investigate whether a centralized order fulfillment approach is better than the existing approach which fulfills online orders from local grocery stores.

A multi-method approach is employed to conduct a high level of cost and emission analysis between the existing and the proposed approaches to illustrate the ratios between the two approaches in terms of cost and carbon emissions. Mathematical models are developed with support from the literature. The model is empirically validated with a case study of grocery distribution in the city of Gold Coast, Australia.

It finds that the centralized order fulfillment approach in sparsely populated areas can achieve LML sustainability with low cost, high efficiency and less double handling. Meanwhile, the separation of in-store and online retailing processes improves the in-store shopping experience and online shopping visibility, jointly improves customer satisfaction, and consequently achieves a positive effect on long-term sustainability. Additionally, the possibility of automating order picking and dispatching at a central place can make the processes more efficient and help build more sustainable grocery retailing supply chains by using more environmentally friendly systems.

This paper offers analytical and empirical insights into the sustainability of multi-channel grocery retailing supply chains. The high-level model developed first incorporates the concept of online shopping adoption rates and can serve as a decision-making tool for practitioners to improve supply chain sustainability in LML.