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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.

Given that a prerequisite for COVID-19 transmission is the interaction between individuals, it is reasonable to suspect that transportation networks may have contributed to the spread of COVID-19. This study uses the air transportation network to quantify the risk of COVID-19 spread in the United States. The proposed model is applied at the county level and identifies the risk of importing COVID-19-infected passengers into a given county. We also undertake an examination of the factors influencing the spread of COVID-19 in relation to air travel. Utilizing an extensive dataset encompassing various socioeconomic, demographic, and healthcare-related variables, our results indicate a positive relationship between these factors and the relative risk of COVID-19 spread, highlighting the pronounced impact of population density, air travel volume, and larger household sizes on increasing travel-related risk. Conversely, greater healthcare capacity, particularly in terms of hospital and intensive care unit (ICU) beds, is associated with reduced risk. We provide estimates of expected relative risk for each county and a ranking that can be useful for informing public health policies to stem the spread of the virus by devoting resources such as screening and enhanced travel protocols to airports located in at-risk counties.

With the global market for advanced technology-driven customer service set to soar, understanding the complicated relationship between advanced technology and customer purchase behaviour is paramount. While prior research has touched upon the impact of technology on purchase processes in some aspects, this study investigates the specific features of advanced technology that shape customer purchase intention in greater depth. By investigating when and under what conditions customers choose advanced technology-based purchases, this research sheds light on the evolving landscape of consumer decision-making and it seeks to quantify the transformative power of advanced technology in driving customer purchase intentions.

This study explores technology trends and challenges in the liner shipping industry through the lens of blockchain technology, addressing gaps in the literature with a comprehensive analysis. By examining blockchain applications in shipping and port contexts, the research fills a significant void, covering trend identification, legal considerations, and implementation challenges. This study extends to examining links between current blockchain projects, revealing trends and challenges in technology applications. The conclusion synthesizes implications and future trajectories of this transformative technology within the broader context of Industry 4.0, positioning this research at the forefront of advancements in maritime technology and supply chain management (SCM).

The governance of our towns and cities requires an approach that connects people with nature and places. Digital technology can be the glue that does this, if it serves the needs of the various stakeholders, including urban communities. It means identifying the potential connections across people, digital, and place themes, examining successful approaches, and exploring some of the current practice (or lack of it) in spatial planning and smart cities. This can be considered using a range of Internet of Things (IoT) technologies with other methodologies which combine the use of socioeconomic and environmental data about the urban environment. This ambient domain sensing can provide the ecological and other data to show how digital connectivity is addressing the placemaking challenges alongside providing implications for urban governance and communities.

A manufacturer with complex end-products can play the “hub firm” role in its supplier network and manage the relationship among its suppliers, but it mostly does not know how to manage suppliers’ coopetitive relationship for improving its innovation. This study aims to investigate the influence of horizontal supplier–supplier (S-S) competition and cooperation in the supplier network on the quantity and quality of manufacturer’s innovation, to unravel the manufacturers’ coopetitive strategic sourcing.

The study conducts negative binomial regression using the data from 130 listed Japanese manufacturers and their first-tier supplier networks as the analysis unit.

The results indicate that both S-S competition and cooperation have inverted U-shaped effects on manufacturers’ innovation. As to the interplay of S-S competition and cooperation in driving manufacturers’ innovation, the one weakens the other’s inverted U-shaped role. It also shows that simultaneously maintaining moderate cooperation and competition among suppliers is a good choice for manufacturer innovation, and when there is high S-S competition, motivating high cooperation among suppliers is also a way to enhance manufacturers’ innovation. All of the effects are more significant and robust on the innovation quality than the innovation quantity.

This study contributes to linking the dyadic analysis of vertical relationships to the network analysis of horizontal S-S relations and exploring the under-researched interplay between competition and cooperation in driving the ego firm’s innovation. It provides insights to manufacturers’ policymakers on how to strategically manage their supplier networks and S-S coopetition to improve their innovation performance.

The success of online health communities (OHCs) depends on maintaining long-term relationships with physicians and preventing churn. Even so, the reasons for physician churn are poorly understood. In this study, an empirical model was proposed from a social influence perspective to explore the effects of online social influence and offline social influence on physician churn, as well as the moderating effect of their online returns.

The empirical data of 4,145 physicians from a Chinese OHC, and probit regression models were employed to verify the proposed theoretical model.

The results suggest that physicians' churn intention is influenced by online and offline social influences, and the offline social influence is more powerful. Physicians' reputational and economic returns could weaken the effect of online social influence on churn intention. However, physicians' economic returns could strengthen the effect of offline social influence on churn intention.

This research study is the first attempt to explore physician churn and divides the social influence into online and offline social influences according to the source of social relationship. The findings contribute to the literature on e-Health, user churn and social influence and provide management implications for OHC managers.

The purpose of this study is to evaluate the tea stem natural dye was extracted from tea stem waste and applied to dyeing silk fiber, after which the properties of dyed samples were tested and analyzed.

The dyeing process was optimized using the response surface methodology (RSM) approach. Dyeing temperature, pH and time were chosen as variables and the color difference value as a response. The properties of dyed samples were tested and analyzed.

The optimized dyeing process was as follows: dyeing temperature 70°C, pH 3.5 and time 110 min. The K/S and color difference value of silk fiber dyed with the optimal process dye enzymatic oxidation with laccase was 1.4 and 27.8, respectively. The silk fiber dyed has excellent color fastness, antioxidant and antibacterial property, which greatly increases the added value of the dyed products. Furthermore, the optimized dyeing process did not significantly affect the strength properties and handle of the silk fiber.

Researchers have not used statistical analysis to optimize the process of dyeing process of silk fiber by tea stem natural dye enzymatic oxidation with laccase using response surface methodology. Additionally, this dyeing process was a low-temperature dyeing process, which not only saves energy consumption and reduces silk fiber damage but also obtains superbly dyeing results and biological functional properties, achieve the effects of waste utilization and clean dyeing.

This paper aims to develop a flexible manufacturing method for multimaterial sand molds to realize efficient additive manufacturing of multimaterial sand molds.

To study the influence of multimaterial sand laying process parameters on the quality of powder bed and optimize the design of multimaterial sand laying device. Numerical simulation and X-ray Computed Tomography are used to study the penetration behavior and curing morphology of resin in different sand particles.

The surface roughness and porosity of the multimaterial powder bed that meet the requirements of sand-based additive manufacturing can be obtained under the optimal printing process, that is, the sanding speed of 140.0 mm/s and sanding roller diameter of 15.0 mm. The resin penetration process of the multimaterial sand molds shows a pattern of transverse expansion and longitudinal penetration. In terms of the resin curing morphology, the maximum thickness of the resin film layer of zircon sand reaches 30.5 ± 1.0 µm, which has the best tensile property, followed by silica sand and the thinnest resin film layer of chromite sand.

In this work, a highly flexible integrated combined sand-laying device suitable for multimaterial sand-laying tests is developed, which can obtain a multimaterial powder bed that meets the needs of sand additive manufacturing. Subsequent casting print tests also verify that the program can meet the needs of multimaterial sand mold additive manufacturing.

In the context of green development in China, the circumstance in which Environmental, Social and Governance (ESG) ratings function has changed. As an important external governance mechanism of sustainable development, ESG ratings can also be a two-edged sword for the implementation of carbon emission reduction. This research examines the connection of ESG ratings and corporate carbon emission reduction in the context of green development. This present study postulates that the impact of ESG ratings on carbon emission reduction performance in the context of green development is inverted U-shaped.

To obtain empirical evidence for the hypotheses proposed, this study makes an empirical test based on the two-way fixed effects model. The data is taken from listed Chinese manufacturing firms between 2012 and 2021.

The study reveals that there is a significant inverted U-shape relationship between ESG ratings and carbon emission reduction performance in the context of green development. Managerial myopic behaviour plays a positive moderating role in the above relationship. In addition, it makes the inflection point of inverted U-shaped curve move to left. Heterogeneity analyses show that the above inverted U-shaped relationship is more significant for firms that don’t hire CEO with environmental protection background or big four accounting firms.

In the background of green development, this study helps to understand dual influence of ESG ratings on corporate carbon emission reduction deeply. It is beneficial to guide enterprises to utilize ESG ratings mechanism reasonably, thus enhancing the effectiveness of carbon emission reduction. This study provides decision-making reference for government to accelerate low-carbon transformation in microcosmic field.