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The paper aims to accurately measure the key motion parameters, such as velocity, azimuth and pitch angle, of the small flying object with a non-uniform curve trajectory. It proposes a measurement method and its calculation model of non-uniform curve trajectory using a photoelectric sensor array.

First, the basic composition of the measurement system and mechanism of photoelectric sensor array are described, respectively. Second, a non-uniform curve mathematical measurement model is constructed differently from the traditional linear trajectory, taking into account the influence of gravity and air resistance. Third, the measurement error of the system is analyzed through numerical simulation. Finally, the accuracy and feasibility of the approach are verified by live-ammunition experiments.

The results show that the systematic error of the hitting point coordinates can be reduced by 9% compared to the traditional linear measurement model. Consequently, this method can meet the higher measurement requirement for the key motion parameters of the small flying object under the non-uniform curve trajectory. Research limitations/implications (if applicable)- although the approach itself is generalizable, the method is unable to detect the motion parameters of multiple small flying objects.

Although the approach itself is generalizable, the method is unable to detect the motion parameters of the multiple small flying objects.

It is evident that the proposed non-uniform curve measurement model is more precise in quantifying the essential characteristics of the small flying object, particularly in consideration of the environmental conditions.

The precise measurement of the key motion parameters of the small flying object can facilitate the enhancement of the protective performance of protective materials.

A novel approach to measurement is proposed, which differs from the conventional uniform trajectory model. To this end, the space construction of the photoelectric sensor array is optimized. The number of the sensors is revised.

Blockchain technology (BCT) is considered a promising tool to improve the productivity of construction project management. Existing research has studied its potential costs and benefits for the construction industry. However, the potential costs and benefits of BCT failed to be compared as actual costs and benefits of specific applications for stakeholders. To fill this gap, this study seeks to analyze the cost-effectiveness of BCT-based applications in construction project management.

This study is conducted with a customized systematic literature review based on transaction cost theory to enable qualitative comparison. With a deliberately designed structure confining extraneous variables, the costs and benefits of BCT-based applications are identified and compared. The inherent dependent relations of processes and the evolution relations of functions are identified. The cost-effectiveness of blockchain adoption is then analyzed.

Seven functions and six challenges are identified within five processes. The result suggests all identified functions are cost-effective except for manual instruction (coding smart contracts manually). The smart contracts require explicit definition and logic to be effective. However, the construction projects essentially require the institution to be flexible due to unpredictability. The adoption of smart contracts and corresponding additional requirements can increase the transaction cost of bounded rationality.

As manual instruction is fundamental to realize other functions, and its advanced substitute relies on its broad adoption, its cost-effectiveness must be improved for applications to be acceptable to stakeholders. The establishment of a universal smart contract model and a universal, legitimate and efficient database structure are recommended to minimize the cost and maximize the effect of applications.

This study contributes to the knowledge by providing a comprehensive analysis of BCT adoption’s cost-effectiveness in construction project management. The adopted review structure can be extended to analyze the qualitative benefits and challenges of management automation in the early stages.

This study aimed to uncover the characteristics of both misinformation and refutations as well as the associations between different aspects of misinformation and corresponding ways of rebutting it.

Leveraging Hovland's persuasion theory as a research lens and taking data from two Chinese refutation platforms, we characterized the topics of COVID-19-related misinformation and refutations, misinformation communicator, persuasion strategies of misinformation, refutation communicators and refutation strategies based on content analysis. Then, logistic regressions were undertaken to examine how the characteristics of misinformation and refutation strategies interacted.

The investigation into the association between misinformation and refutations found that distinct refutation strategies are favored when debunking particular types of misinformation and by various kinds of refutation communicators. In addition, several patterns of persuasion strategies were identified.

This study had theoretical and practical implications. It emphasized how misinformation and refutations interacted from the perspective of Hovland's persuasion theory, extending the scope of the existing literature and expanding the classical theory to a new research scenario. In addition, several patterns of persuasion strategies used in misinformation and refutation were detected, which may contribute to the refutation practice and help people become immune to misinformation.

This research is among the first to analyze the relationships between misinformation and refutation strategies. Second, we investigated the persuasion strategies of misinformation and refutations, contributing to the concerning literature. Third, elaborating on Hovland’s persuasion theory, this study proposed a comprehensive framework for analyzing the misinformation and refutations in China during the COVID-19 pandemic.

Graded honeycombs are materials that exhibit better energy absorption performance compared to uniform honeycombs without adding additional weight. This paper introduces a novel modularized graded honeycomb into a commercial crash box to improve its crashworthiness.

A modularized graded honeycomb is inserted into a commercial crash box to develop a novel crash box. Finite element analyses are conducted to investigate the crashworthiness. Pareto cumulative influence analysis is conducted to rank the effects of design parameters on crashworthiness. A surrogate model-based multi-objective optimization is carried out to improve energy absorption while limiting the impact peak force. An optimal Pareto solution set is obtained.

Modularized honeycomb-filled crash box outperforms that of its corresponding uniform honeycomb-filled crash box and empty crash box in resisting impact. Pareto cumulative influence analysis reveals that for most crashworthiness indicators, cell-wall thicknesses of crash box tube contribute the most, followed by average relative density and graded coefficient of modularized honeycomb (MH). Graded coefficient contributes nearly 10% on mean force and maximum displacement, but it has insignificant influence on peak force and weight. Optimization results show that the optimal designs can not only absorb more energy but also limit the peak force compared with those of uniform honeycomb-filled crash box.

This paper fills a MH into a commercial crash box to propose a novel crash box and demonstrates the positive impact of modularized design on crashworthiness compared with that of uniform honeycomb-filled crash box. Moreover, modularizing honeycomb does not change the weight of the filler, and thus, the novel crash box would benefit development of crash box with lightweight and excellent energy absorption capacity.

This study aims to explore the traditional plant dyeing of Xinjiang Atlas silk fabrics, providing references for the comprehensive utilization of plant dyes in intangible cultural heritage.

The focus of this study is on dyeing experiments of Atlas silk fabrics using safflower extracts, constrained by regional resources. Safflower dry flowers grown in Xinjiang were selected, rinsed with pure water and rubbed. Yellow pigments were removed by adding edible white vinegar. Red pigments from safflower were extracted using an alkaline solution prepared with Populus euphratica ash, a special product of Xinjiang. The extraction rate was analyzed under varying material-to-liquor ratios, pH values, times and temperatures. Direct dyeing process experiments were conducted to obtain different colorimetric L, a, b and K/S values for comparison. Samples with good color development were selected to test the impact of dyeing immersions on color development, and their color fastness, UV protection and antibacterial effects were verified.

The dyeing experiments on silk fabrics confirmed their UV protection capabilities and antibacterial properties, demonstrating effectiveness against E. coli and Staphylococcus aureus. As a major producer of safflower, Xinjiang underscores the significance of safflower as an essential plant dyes on the Silk Road. This study reveals its market potential and suitability for use in the plant dyeing process of Atlas silk, producing vibrant red and pink colors.

The experiments indicated that after removing yellow pigments, the highest extraction rate of red pigment from safflower was achieved at a pH value of 10–11, a temperature of 30°C and an extraction time of 40 min. The best bright red color effect with strong color fastness was obtained with a material-to-liquor ratio of 1:20, a temperature of 40°C and three immersions. The best light pink color effect with strong color fastness was a material-to-liquor ratio of 1:80, a temperature of 30°C and two immersions.

Purpose: This study quantitatively assesses the impact of ESG profile on equity value and risk, as well as identifies potential differences occurring in different sectors, based on the data of the Nasdaq Nordic market.

Methodology: To reach this purpose, (i) the stock return and volatility analysis is being conducted (using the methods of paired sample t-test, correlation, etc.), and (ii) panel data models with constant, fixed and random effects are being constructed. The analysis is based not only on the company’s ESG performance but also on a cross-sectoral approach.

Findings: The results revealed that although ESG factors appeared to have a significant impact in most of the constructed models, the impact of these factors varies depending on the sector.

Implications: This research provides a comprehensive and comparative approach to the importance of the ESG profile for investment performance and therefore can be useful both for impact investors making investment decisions in dynamic global financial markets and for companies developing or reforming their ESG strategies.

Limitations: Due to the problem of data availability, the cross-sectoral comparison was performed based on the limited number of sectors. In addition, the limited availability of ESG data in the analysed market did not allow the use of additional methods to assess the impact of ESG.

Future Research: Expanding the data sample and assessing the impact of a company’s ESG profile not only in different sectors but also in different phases of the economic cycle might be the direction for future research.

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

This paper takes the manufacturing cluster supply chain as the research object and explores the evaluation and enhancement strategy of manufacturing cluster supply chain synergy. The purpose of this study was to (1) analyze the mechanism of manufacturing cluster supply chain synergy; (2) construct manufacturing cluster supply chain synergy evaluation model; (3) algorithm realization of manufacturing cluster supply chain synergy evaluation and (4) propose manufacturing cluster-based supply chain synergy enhancement strategy.

Breaking through the limitations of traditional manufacturing cluster supply chain synergy evaluation, we take horizontal synergy and vertical synergy as coupled synergy subsystems, use the complex system synergy model to explore the horizontal synergy between core enterprises and cluster enterprises and the vertical synergy of supply chain enterprises and use the coupling coordination model to construct the coupled synergy evaluation model of manufacturing cluster supply chain, which is an innovation of the evaluation perspective of previous cluster supply chain synergy and also an enrichment and supplementation of the evaluation methodology. This is not only the innovation of the evaluation perspective but also the enrichment and supplementation of the evaluation method.

Using Python software to conduct empirical analysis on the evaluation model, the research shows that the horizontal and vertical synergies of the manufacturing cluster supply chain interact with each other and jointly affect the coupling synergy. On this basis, targeted strategies are proposed to enhance the synergy of the manufacturing cluster supply chain.

This study takes manufacturers, suppliers and sellers in the three-level supply chain as the research object and does not consider the synergistic evaluation between distributors and consumers in the supply chain, which can be further explored in this direction in the future.

Advanced manufacturing clusters, as the main force of manufacturing development, and the synergistic development of supply chain are one of the important driving forces for the high-quality development of China’s manufacturing industry. As a new type of network organization coupling industrial clusters and supply chains, cluster supply chain is conducive not only to improving the competitiveness of cluster supply chains but also to upgrading cluster supply chains through horizontal synergy within the cluster and vertical synergy in the supply chain.

Research can help accelerate the transformation and upgrading of clustered supply chains in the manufacturing industry, promote high-quality development of the manufacturing industry and accelerate the rise of the global value chain position of the manufacturing industry.

(1) Innovation of research perspective. Starting from two perspectives of horizontal synergy and vertical synergy, we take a core enterprise in the cluster supply chain as the starting point, horizontally explore the main enterprises of the cluster as the research object of horizontal synergy, vertically explore the upstream and downstream enterprises of the supply chain as the research object of vertical synergy and explore the coupling synergy of cluster supply chain as two subsystems, which provides new perspectives of evaluation of the degree of synergy and synergy evaluation. (2) Innovation of research content. Nine manufacturing clusters are selected as research samples, and through data collection and model analysis, it is verified that the evaluation model and implementation algorithm designed in this paper have strong practicability, which not only provides methodological reference for the evaluation of manufacturing cluster-type supply chain synergy but also reduces the loss caused by the instability of clusters and supply chains and then provides a theoretical basis for improving the overall performance of cluster-type supply chains.

The proliferation of health misinformation on social media has increasingly engaged scholarly interest. This research examines the determinants influencing users’ proactive correction of health misinformation, a crucial strategy in combatting health misbeliefs. Grounded in the elaboration likelihood model (ELM), this research investigates how factors including issue involvement, information literacy and active social media use impact health misinformation recognition and intention to correct it.

A total of 413 social media users finished a national online questionnaire. SPSS 26.0, AMOS 21.0 and PROCESS Macro 4.1 were used to address the research hypotheses and questions.

Results indicated that issue involvement and information literacy both contribute to health misinformation correction intention (HMCI), while misinformation recognition acts as a mediator between information literacy and HMCI. Moreover, active social media use moderated the influence of information literacy on HMCI.

This study not only extends the ELM into the research domain of correcting health misinformation on social media but also enriches the perspective of individual fact-checking intention research by incorporating dimensions of users’ motivation, capability and behavioral patterns.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0505

This paper evaluates the level of the digital economy in Chinese cities based on digital industrialization and industrial digitalization. The research focuses on the effects of spatial mechanism of the urban digital economy on the quality of firms’ exported products.

The authors use the principal component analysis method to evaluate the level of China’s urban digital economy, and spatial metrology to measure the spatial effects of the digital economy on product quality.

The findings suggest that the urban digital economy can expand the quality of firms’ exports. The digital economy has spatial dependence, spatial spillover and spatial heterogeneity on product quality. At the same time, the spatial effect has a significant nonlinear effect and threshold effect. Further decomposition shows that industrial digitalization is the core factor of enterprises’ export products quality, and the micro-mechanism of this impact is mainly manifested in optimization of resource allocation.

The innovation of this paper is reflected explicitly in exploring the quality upgrading of export products from the background of the digital economy, providing a reference for the improvement of China’s export trade competitiveness and the cultivation of a trade power. The authors studied two different mechanisms (specialization division of labor and optimization of resource allocation) to explain the spatial imbalance of export product quality to provide empirical support for enterprises and government departments to formulate quality upgrading policies accurately.