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The purpose of this paper is to prepare structural colors of fabrics coated with Silver/Zinc Oxide (Ag/ZnO) composite films by magnetron sputtering and analyze the relationship between the colors and the thickness of Zinc Oxide (ZnO) film in Ag/ZnO composite film and the photocatalytic property of the fabrics coated with Ag/ZnO composite film.

Ag/ZnO composite films deposited on polyester fabrics were prepared by magnetron sputtering technology. The structural colors of textiles coated with Ag/ZnO composite films and the relationship between the colors and Ag/ZnO composite films were analyzed, and the photocatalytic property of Ag/ZnO composite films was also discussed.

The results indicated that the colors varied with the thicknesses of the ZnO film in Ag/ZnO composite films. The reactive sputtering time of ZnO film was 5, 8, 10 and 14 min, respectively, and the colors of the corresponding fabrics were purple, blue, blue-green and yellow. Meanwhile, the polyester fabrics coated with Ag/ZnO composite films showed the excellent photocatalytic properties, and silver (Ag) films deposited under the ZnO films in Ag/ZnO composite films could also improve the photocatalytic activities of ZnO films, and the formaldehyde degradation rates was 77.5%, which was higher than the 69.9% for the fabrics coated only with the ZnO film.

The polyester fabrics coated with Ag/ZnO composite films not only created various structural colors using change the thicknesses of the ZnO film, but also achieved the multifuctionality, which will have a broad application prospect in textile fields.

Structural color is more brilliant in color, more resistant to sunshine and will not fade away with time, and more environmental friendly than traditional dyes and pigments. The purpose of this paper is to prepare structural colors of fabrics coated with Ag/TiO₂ composite films by magnetron sputtering, and analyze the relationship between the colors and the thicknesses of TiO₂ films in Ag/TiO₂ composite films.

Preparation of Ag/TiO₂ composite films by magnetron sputtering and their deposition on textiles were investigated. The chemical compositions and surface morphology of Ag/TiO₂ composite films were examined by X-ray photoelectron spectroscopy and scanning electron microscopy, and the structural color of fabric coated with Ag/TiO₂ composite film was also analyzed.

Ag/TiO₂ composite films deposited on textile substrate exhibited structural colors, and the bright colors could be adjusted and controlled by the thickness of TiO₂ thin films in Ag/TiO₂ composite films without any dyes or pigments. By comparing the results of theoretical calculation and experimental results, it was found that the creation of structural colors by the experiment was coincident to the colors by theoretical calculation according to the film interference principle. There was a linear relationship between the thickness of TiO₂ film and the wavelength of the structural color.

Compared to traditional coloration by dyes or pigments, the coloration of textile by structural color from Ag/TiO₂ composite films prepared by magnetron sputtering was very environmental friendly and simple without water consuming, time consuming and tedious work. Structural colors have great potential applications in textiles in place of traditional dyes and pigments. Furthermore, the textiles coated with Ag/TiO₂ composite films have good electrical, optical and magnetic properties, and can be used in apparel, home furnishings and industrial fabrics.

An organization’s ability to successfully manage intellectual capital is determined by the actions of its employees to prevent or minimize information security incidents. To prevent more data breaches to intellectual capital, organizations must provide regular cybersecurity awareness training for all personnel. The purpose of this paper is to investigate the effect of different evidence-based cybersecurity training methods on employees’ cybersecurity risk perception and self-reported behavior.

The study participants were randomly assigned into four groups (i.e. malware report, malware videos, both malware report and malware videos and no interventions) to assess the effects of cybersecurity training on their perceptions of vulnerability, severity, self-efficacy, security intention as well as their self-reported cybersecurity behaviors.

The results show that evidence-based malware report is a relatively better training method in affecting employees’ intentions of engaging in recommended cybersecurity behaviors comparing with the other training methods used in this study. A closer analysis suggests whether the training method contains self-relevant information could make a difference to the training effects.

This paper reports an in-depth investigation on how different evidence-based cybersecurity training methods impact employees’ perceptions of susceptibility, severity, self-efficacy, security intention as well as on their self-reported cybersecurity behaviors.

This study aims to propose an unsupervised learning model to evaluate the credibility of disaster-related Twitter data and present a performance comparison with commonly used supervised machine learning models.

First historical tweets on two recent hurricane events are collected via Twitter API. Then a credibility scoring system is implemented in which the tweet features are analyzed to give a credibility score and credibility label to the tweet. After that, supervised machine learning classification is implemented using various classification algorithms and their performances are compared.

The proposed unsupervised learning model could enhance the emergency response by providing a fast way to determine the credibility of disaster-related tweets. Additionally, the comparison of the supervised classification models reveals that the Random Forest classifier performs significantly better than the SVM and Logistic Regression classifiers in classifying the credibility of disaster-related tweets.

In this paper, an unsupervised 10-point scoring model is proposed to evaluate the tweets’ credibility based on the user-based and content-based features. This technique could be used to evaluate the credibility of disaster-related tweets on future hurricanes and would have the potential to enhance emergency response during critical events. The comparative study of different supervised learning methods has revealed effective supervised learning methods for evaluating the credibility of Tweeter data.

An exact multiple‐level dynamic substructure technique was developed by a combination of WYD algorithm and static multiple‐level substructuring technique. This method is essentially different from the traditional mode component synthesis. The eigenvalues and eigenvectors created by the method are the eigenpairs for the whole structure and not for the components of structure. On the other hand, the dynamic response by using mode superposition can also be implemented in substructure level. This algorithm actually is an exact substructuring technique which means that substructuring itself did not introduce any additional error except the round‐off when a structure was split into some arbitrary subdomains and the error of WYD or mode superposition themselves. It is no longer necessary to assume any connective condition on the interface between substructures. This method makes the capacity of dynamic analysis of a structural analysis program unlimited. It is especially attractive for the programs on microcomputers. Of course, the method leads to a frequent I/O for a subsequent search of the files from each substructure. It is time consuming compared to the mode component synthesis. But the potential still exists to improve the efficiency by using parallel computation on concurrent computers. In this paper the theory and procedure of the algorithm are presented.

Technology innovation in enterprises is a powerful driver of national competitiveness and sustainable corporate development. At the same time, the regional innovation policy mix serves as a core factor at the macro level, guiding and influencing enterprise technology innovation. Therefore, this paper addresses a critical question in innovation studies: the impact of the regional innovation policy mix complexity on enterprise technology innovation. Additionally, we also investigated the internal mechanisms and boundary conditions within this framework.

A dual-mode network model of local government-regional innovation policy is developed to capture the complexity of the regional innovation policy mix. The complexity index is calculated iteratively using the R language. The paper employs quantitative and empirical analysis, drawing on a sample of 622 regional innovation-related policy documents from 31 Chinese provinces (municipalities and autonomous regions).

The results reveal an inverted U-shaped relationship between policy mix complexity and enterprise technological innovation. The analysis further shows that university-industry cooperation intensity mediates this relationship, while regional knowledge absorptive capability moderates the impact of regional innovation policy mix complexity on enterprise technological innovation.

This paper highlights the influence of regional innovation policy mix complexity on enterprise technological innovation and underscores the role of university-industry cooperation intensity and regional knowledge absorptive capability. The findings offer valuable insights into the dynamics of enterprise innovation and inform effective government policy governance for fostering innovation.

This paper aims to explore and review the potential of robotic rehabilitation as a treatment approach for Alzheimer’s disease (AD) and its impact on the health and quality of life of AD patients.

The present discourse endeavors to provide a comprehensive overview of extant scholarly inquiries that have examined the salience of inhibitory mechanisms vis-à-vis robotic interventions and their impact on patients with AD. Specifically, this review aims to explicate the contemporary state of affairs in this realm by furnishing a detailed explication of ongoing research endeavors. With the objective of elucidating the significance of inhibitory processes in robotic therapies for individuals with AD, this analysis offers a critical appraisal of extant literature that probes the intersection of cognitive mechanisms and assistive technologies. Through a meticulous analysis of diverse scholarly contributions, this review advances a nuanced understanding of the intricate interplay between inhibitory processes and robotic interventions in the context of AD.

According to the review papers, it appears that implementing robot-assisted rehabilitation can serve as a pragmatic and effective solution for enhancing the well-being and overall quality of life of patients and families engaged with AD. Besides, this new feature in the robotic area is anticipated to have a critical role in the success of this innovative approach.

Due to the nascent nature of this cutting-edge technology and the constrained configuration of the mechanized entity in question, further protracted analysis is imperative to ascertain the advantages and drawbacks of robotic rehabilitation vis-à-vis individuals afflicted with Alzheimer’s ailment.

The potential for robots to serve as indispensable assets in the provision of care for individuals afflicted with AD is significant; however, their efficacy and appropriateness for utilization by caregivers of AD patients must be subjected to further rigorous scrutiny.

This paper reviews the current robotic method and compares the current state of the art for the AD patient.

In this paper, the purpose of research is to verify good thermal performance of heat pipe receiver.

Mathematical model was set up, numerical calculation method was offered. Calculation results were compared with experimental results, with those of NASA project, and those of the basis heat receiver.

Simulation results show that heat pipe receiver involving heat pipe has the performance of perfect heat transfer and ideal identical temperature, the axial temperature difference of heat pipe is small, PCM canisters situated in different places of heat pipe can melt simultaneously and uniformly. At the same time, normal operation of wick ensures the uniformity of heat pipe circumference temperature, thus heat pipe receiver avoids phenomena of thermal spot. In addition, heat pipe receiver has axial and radial performance of ideal identical temperature, all PCM canisters can freeze simultaneously at the end of eclipse periods, and freeze fully at last, so heat pipe receiver avoids thermal ratcheting.

The research in this paper can be used to design heat pipe receiver.

The purpose of the paper was to assess the functional properties vegetable gourds & the validated health claims so as to help the future researchers to locate the gaps. However, emphasizing on the scientifically available reports was required to make information available in a nutshell to the health-conscious consumers, as well as the researcher from the area of functional foods and nutrition.

The paper is a mini-review of scientific findings in different studies on gourd vegetables. The approach to information collection was finding the research gaps and potential areas for future work with a nutritional perspective.

Ash gourd, bitter gourd and bottle gourd have been extensively studied, and several health benefits and functional components have been reported, while ridge gourd, snake gourd and pointed gourd have been sparsely studied for their therapeutic benefits and the validation thereof; hence, there lies a scope for researchers.

The scarcity of scientific reports compared to the traditional usage and folkloric beliefs was a limitation.

Understanding the nutritional potential of gourd vegetables from scientific reports may influence both the work areas and consumers in the appropriate direction.

Environmental, social and governance (ESG) greenwashing is a form of social responsibility response that appears compliant but is substantively oppositional. As an abnormal social behavior, existing research has rarely focused on the deep-seated strategic logic behind ESG greenwashing. Business strategy emerges as the linchpin for companies undertaking a series of decision-making actions. Consequently, this research seeks to provide new insights into the strategic drivers behind corporate greenwashing and the role of institutional investors in mitigating these practices.

The research utilizes empirical analysis based on data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2010 to 2022. ESG performance data is sourced from the Bloomberg ESG Disclosure Ratings and Thomson Reuters’ Asset4 database. Business strategy is assessed using six key indicators. The study employs institutional theory as the analytical framework, examining the impact of business strategy on ESG greenwashing and investigating the internal mechanisms driving these behaviors.

The study finds that compared with defender strategies, prospector strategies are more likely to lead to ESG greenwashing behavior. Specifically, aggressive business strategies tend to facilitate corporate ESG greenwashing. Mechanism analysis indicates that, compared to defenders, prospectors induce ESG greenwashing by increasing information asymmetry (reputation effect) and being constrained by financing limitations (profit-seeking effect). From an external governance perspective, this study finds that institutional investor ownership can mitigate the impact of business strategy on ESG greenwashing. Furthermore, additional research confirms that in heavily polluting industries, the positive effect of business strategy on ESG greenwashing is more pronounced, whereas implementing the Environmental Protection Tax Law curtails the impact of business strategy on ESG greenwashing.

This study analyzes the role of business strategy in ESG greenwashing, particularly in the context of emerging economies such as China, contributing uniquely to the literature on corporate decision-making and green management. The research extends the application of institutional theory to the field of corporate environmental strategy and introduces the concepts of reputation and profit-seeking effects, offering fresh perspectives on understanding ESG greenwashing behavior. It also provides empirical evidence of the governance role of institutional investors in addressing managerial opportunism related to ESG greenwashing, enriching the existing theoretical framework. Finally, the study highlights the need to establish stronger institutional and managerial mechanisms to effectively tackle corporate greenwashing, offering valuable insights for future research and practice.