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Explore how the degree of humanization affects user misconduct, and provide effective misconduct prevention measures for the wide application of artificial intelligence in the future.

Based on the “Uncanny Valley theory”, three experiments were conducted to explore the relationship between the degree of humanization of service machines and user misbehavior, and to analyze the mediating role of cognitive resistance and the moderating role of social class.

There is a U-shaped relationship between the degree of humanization of service machines and user misbehavior; Social class not only regulates the main effect of anthropomorphism on misbehavior, but also regulates the intermediary effect of anthropomorphism on cognitive resistance, thus affecting misbehavior.

The design of the service robot can be from the user’s point of view, combined with the user’s social class, match different user types, and provide the same preferences as the user’s humanoid service robot.

This study is an important reference value for enterprises and governments to provide intelligent services in public places. It can prevent the robot from being vandalized and also provide users with a comfortable human-computer interaction experience, expanding the positive effects of providing smart services by government and enterprises.

This study avoids and reduces users' misbehavior towards intelligent service robots, improves users' satisfaction in using service robots, and avoids service robots being damaged, resulting in waste of government, enterprise and social resources.

From the perspective of product factors to identify the inducing factors of improper behavior, from the perspective of social class of users to analyze the moderating effect of humanization degree and user improper behavior.

The purpose of this paper is to provide the high-pass (HP) negative group delay (NGD) circuit based (RL) network. Synthesis and experimental investigation of HP-NGD circuit are developed.

The research work methodology is organized in three phases. The definition of the HP-NGD ideal specifications is introduced. The synthesis method allowing to determine the RL elements is developed. The validation results are discussed with comparison between the calculated model, simulation and measurement.

This paper shows a validation of the HP-NGD theory with responses confirming NGD optimal frequency, value and attenuation of about (9 kHz, −1.12 µs, −1.64 dB) and (21 kHz, −0.92 µs, −4.81 dB) are measured. The tested circuits have experimented NGD cut-off frequencies around 5 and 11.7 kHz.

The validity of the HP-NGD topology depends on the coil self-inductance resonance. The HP-NGD effect is susceptible to be penalized by the parasitic elements of the self.

The NGD circuit is usefully exploited in the electronic and communication system to reduce the undesired delay effect context. The NGD can be used to compensate the delay in any electronic devices and system.

Applications based on the NGD technology will be helpful in the communication, transportation and security research fields by reducing the delay inherent to any electronic circuit.

The originality of the paper concerns the synthesis formulations of the RL elements in function of the expected HP-NGD optimal frequency, value and attenuation. In addition, an original measurement technique of HP-NGD is also introduced.

This study explores identity signaling used by an emerging class of knowledge celebrities in China – Knowledge Wanghong – who sell knowledge products on online platforms. Because identity signaling may involve constructing unique online identities and controlling over product-related and seller-related characteristics, the purpose of this study is two-fold: (1) to uncover different online identities of knowledge celebrities; and (2) to examine the extent to which the online identity type is associated with their product-related characteristics, seller-related characteristics and sales performance.

A unique data set was collected from a Chinese leading pay-for-knowledge platform – Zhihu – which featured the online profiles of tens of thousands of knowledge celebrities. Online identity types were derived from their self-edited content using Latent Dirichlet Allocation (LDA) topic modeling. Thereafter, their product-related characteristics, seller-related characteristics and respective sales performance were analyzed across different identity types using analysis of variance (ANOVA) and multiple-group linear regression.

Knowledge celebrities are clustered into four distinctive online identities: Mentor, Broker, Storyteller and Geek. Product-related characteristics, sell-related characteristics and sales performance varied across four different identities. Additionally, the online identity type moderated the relationships among their product-related characteristics, sell-related characteristics and sales performance.

As emerging-phenomenon-based research, this study extends related literature by using the notion of identity signaling to analyze a peculiar group of online celebrities who are setting an important trend in the pay-for-knowledge model in China.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

The purpose of this paper is to study numerically the rheological properties of fiber suspensions flowing through turbulent pipe flows.

The work presented in this paper is derived the fluctuating equation for fiber orientation distribution function (FODF) in turbulent flows and solved using the method of characteristics. The FODF is predicted numerically. The numerical results of root-mean-square velocities generated by kinetic simulation sweeping model and are compared with the experimental data.

The fiber orientation distribution becomes wider with increasing Re. The components of the fourth-order orientation tensor increase with the increase of Re, and also increase along the radial direction and reach the maximum at the center line. The first normal stress difference is much less than the shear stress. For different Re the shear stress increases rapidly in the region far from the pipe center, and reaches its maximums at center, while the first normal stress difference decreases rapidly in the region far from the pipe center, and reaches its minimum at center finally.

By solving numerically the equation in a turbulent pipe flow with Reynolds number ranging from 2,500 to 1,000, the authors obtain the mean FODF which is in agreement with the experimental one qualitatively. Then the shear stress and first normal stress difference of suspensions are calculated based on the mean FODF.

The former residences of historical figures are typical landscape elements of historic districts, which are characterised by the styles of these residences and spiritual historical figures cultures. The purpose of this paper is to determine how the former residences respond once the historical figures living there have passed.

The history of human culture and progression of urban construction – which are submerged in societal transformation – is recorded for old Beijing city. Narrative space theory is used and methods such as a content analysis, map overlay and the Geographic Information System are employed to analyse the selected 300 former residences of historical figures in old Beijing city.

The results are as follows: the political setting played a key role in the evolution process, three political narrative areas in the inner city and one cultural narrative area in the outer city form the narrative spatial structure of the former residences of historical figures, “government construction” and “resident construction” are the main reasons for the loss and destruction of narrative spaces and ordinary life is an important channel for showcasing the history of former residences. The narrative spaces of these residences carry double histories, namely, the development of human history and of city construction.

Different from former studies that focus on the preservation of the single historical building, this study explores the integral logic of historic buildings in the whole city through narrative space theory to get a combination of culture and space.

The literature review aims to facilitate a broader understanding of on-demand service platform operations management and proposes potential research directions for scholars.

This study searches four databases for relevant literature on on-demand service platform operations management and selects 72 papers for this review. According to the research context, the literature can be divided into research on “a single platform” and research on “multiple platforms”. According to the research methods, the literature can be classified into “Mathematical Models”, “Empirical Studies”, “Multiple Methods” and “Literature Review”. Through comparative analysis, we identify research gaps and propose five future research agendas.

This paper proposes five research agendas for future research on on-demand service platform operations management. First, research can be done to combine classic research problems in the field of operations management with platform characteristics. Second, both the dynamic and steady-state issues of on-demand service platforms can be further explored. Third, research employing mathematical models and empirical analysis simultaneously can be more fruitful. Fourth, more research efforts on the various interactions among two or more platforms can be pursued. Last but not least, it is worthwhile to examine new models and paths that have emerged during the latest development of the platform economy.

Through categorizing the literature into two research contexts as well as classifying it according to four research methods, this article clearly shows the research progresses made so far in on-demand service platform operations management and provides future research directions.

In as much as it is contested, the Belt and Road Initiative (BRI) is also unexplored, underdiscussed, and, as a result, misunderstood. Frequently viewed through the lens of international relations and global economy, the diverse dimensions of collaboration, including business and research-industry clusters, that BRI enhances, tend to be excluded from the analysis. In a similar manner, the role of the Arab Peninsula in the grand strategy underpinning BRI and its implementation is rarely discussed. BRI is a forward-oriented initiative, an attempt to reap benefits of developments and circumstances that are only nascent. This bears two potent implications. First, as China attempts to influence the context in which it operates, it is subject to change itself; the Chinese business sector evolution attests to that. Second, some of China’s not so obvious partners of today, including those in the Arab Peninsula, are about to turn into key interlocutors of tomorrow. BRI taps into opportunities thus created. This chapter elaborates on these issues and, against this backdrop, outlines how the remaining chapters included in this volume add to this discussion.