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In a first of its kind, this paper tries to explore the long-run relationship between investors' sentiment and selected industries' returns over the period January 2010 to December 2021.

The paper uses 23 market and macroeconomic proxies to measure investor sentiment. Principal component analysis has been used to create sentiment sub-indices that represent investor sentiment. The autoregressive distributed lag (ARDL) model and other sophisticated econometric techniques such as the unit root test, the cumulative sum (CUSUM) stability test, regression, etc. have been used to achieve the objectives of the study.

The authors find that there is a significant relationship between sentiment sub-indices and industries' returns over the period of study. Market and economic variables, market ratios, advance-decline ratio, high-low index, price-to-book value ratio and liquidity in the economy are some of the significant sub-indices explaining industries' returns.

The study has relevant implications for retail investors, policy-makers and other decision-makers in the Indian stock market. Results are helpful for the investor in improving their decision-making and identifying those sentiment sub-indices and the variables therein that are relevant in explaining the return of a particular industry.

The study contributes to the existing literature by exploring the relationship between sentiment and industries' returns in the Indian stock market and by identifying relevant sentiment sub-indices. Also, the study supports the investors' irrationality, which arises due to a plethora of behavioral biases as enshrined in classical finance.

This study aims to research the development trend, research status, research results and existing problems of the steel–concrete composite joint of railway long-span hybrid girder cable-stayed bridge.

Based on the investigation and analysis of the development history, structure form, structural parameters, stress characteristics, shear connector stress state, force transmission mechanism, and fatigue performance, aiming at the steel–concrete composite joint of railway long-span hybrid girder cable-stayed bridge, the development trend, research status, research results and existing problems are expounded.

The shear-compression composite joint has become the main form in practice, featuring shortened length and simplified structure. The length of composite joints between 1.5 and 3.0 m has no significant effect on the stress and force transmission laws of the main girder. The reasonable thickness of the bearing plate is 40–70 mm. The calculation theory and simplified calculation formula of the overall bearing capacity, the nonuniformity and distribution laws of the shear connector, the force transferring ratio of steel and concrete components, the fatigue failure mechanism and structural parameters effects are the focus of the research study.

This study puts forward some suggestions and prospects for the structural design and theoretical research of the steel–concrete composite joint of railway long-span hybrid girder cable-stayed bridge.

This research explores the intricate dynamics of national interests realised through Japan's official development assistance (ODA) to China. It aims to deepen the understanding of these mechanisms, detailing the extent to which Japan has accomplished its national interests.

The paper applies the role theory and narrative analysis to elucidate Japan's national role conception and its categories of national interests with regards to its ODA policy. It utilises both qualitative and quantitative methods to examine the success rate in achieving Japan's diplomatic objectives and how those interests have manifested over time.

The findings suggest a mixed outcome. Whilst Japan's ODA to China has helped in expanding trade and fostering mutual understanding and cooperation, it has been less successful in promoting democratic governance in China or effectively counterbalancing China's regional power. Hence, the realisation of national interests through ODA is a complex process contingent upon numerous factors.

This study stands out for its multifaceted approach in examining Japan's ODA policy towards China, integrating both quantitative and qualitative methodologies and applying the role theory in the context of international development aid. It fills a significant gap in the literature by analysing the interplay between national interests and foreign aid, providing nuanced insights into the successes and challenges of Japan's pursuit of its diplomatic objectives. The study's findings have important implications for understanding the complexity of international aid dynamics and can inform future policy decisions in the realm of international relations and foreign aid.

Outsourcing of logistics has great importance in disaster relief. Aid agencies spend several billion US dollars every year on logistics services. However, the concept of outsourcing has not been established adequately in literature on humanitarian logistics, leading to a fragmented view of the practice. This paper provides a holistic perspective of the concept by constructing a conceptual framework to analyze both practice and research of outsourcing in humanitarian operations. Based on this analysis, we explore future trends and identify research gaps.

The paper is based on a structured review of academic literature, a two-round Delphi study with 31 experts from aid agencies and a complementary full-day focus group with twelve experts from aid agencies and logistics service providers.

The paper systemizes the current practice of outsourcing in humanitarian logistics according to a conceptual framework of five dimensions: subject, object, partner, design and context. In addition, it reveals ten probable developments of the practice over the next years. Finally, it describes eight important research gaps and presents a research agenda for the field.

The literature review considered peer-reviewed academic papers. Practitioner papers could provide additional insights into the practice. Moreover, the Delphi study focused on the perspective of aid agencies. Capturing the views of logistics service providers in more detail would be a valuable addition.

The paper establishes the academic basis for the important practice of outsourcing in humanitarian logistics. It highlights essential research gaps and, thereby, opens up the field for future research.

The recent innovations of Industry 4.0 have made it possible to easily collect data related to a production environment. In this context, information about industrial equipment – gathered by proper sensors – can be profitably used for supporting predictive maintenance (PdM) through the application of data-driven analytics based on artificial intelligence (AI) techniques. Although deep learning (DL) approaches have proven to be a quite effective solutions to the problem, one of the open research challenges remains – the design of PdM methods that are computationally efficient, and most importantly, applicable in real-world internet of things (IoT) scenarios, where they are required to be executable directly on the limited devices’ hardware.

In this paper, the authors propose a DL approach for PdM task, which is based on a particular and very efficient architecture. The major novelty behind the proposed framework is to leverage a multi-head attention (MHA) mechanism to obtain both high results in terms of remaining useful life (RUL) estimation and low memory model storage requirements, providing the basis for a possible implementation directly on the equipment hardware.

The achieved experimental results on the NASA dataset show how the authors’ approach outperforms in terms of effectiveness and efficiency the majority of the most diffused state-of-the-art techniques.

A comparison of the spatial and temporal complexity with a typical long-short term memory (LSTM) model and the state-of-the-art approaches was also done on the NASA dataset. Despite the authors’ approach achieving similar effectiveness results with respect to other approaches, it has a significantly smaller number of parameters, a smaller storage volume and lower training time.

The proposed approach aims to find a compromise between effectiveness and efficiency, which is crucial in the industrial domain in which it is important to maximize the link between performance attained and resources allocated. The overall accuracy performances are also on par with the finest methods described in the literature.

The proposed approach allows satisfying the requirements of modern embedded AI applications (reliability, low power consumption, etc.), finding a compromise between efficiency and effectiveness.

This paper examines the different features of China's economic development in different stages of economic globalization. The study finds that the investment- and export-based growth model drove China's high-speed economic growth between 2000 and 2007, which came into existence around 2000 when China plugged into the global production network.

This paper also finds that China slowed down to the New Normal because of the disruption to the socio-economic underpinnings of this growth model. As China adapts to and steers the New Normal, supply-side structural reforms can channel excess capacity to the construction of underground pipe networks in rural areas of central China and fix capital while advance rural revitalization.

At the same time, enterprises must strive to build a key component development platform for key component innovation and the standard-setting power in global manufacturing.

The establishment of a domestic production network integrating the integrated innovation-driven core enterprises and modular producers at different levels can satisfy the dynamic demand structure of China in which standardized demands and personalized demands coexist.