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Based on affective events theory, this research attempted to investigate how negative gossip about organizational change drives employees to experience negative emotions and direct their aggression toward customers.

We conducted a scenario-based experiment (Study 1) and a multiwave field survey (Study 2) to test our hypotheses.

The results show that (1) negative emotions mediate the relationship between change-related negative gossip and displaced aggression toward customers; (2) perceived organizational constraints strengthen the relationship between change-related negative gossip and negative emotions; (3) future work self-salience weakens the relationship between change-related negative gossip and negative emotions; and (4) change-related negative gossip has a strengthened (weakened) indirect effect on displaced aggression via negative emotions when employees have high perceived organizational constraints (future work self-salience).

The study expands research on organizational change and displaced aggression and provides practical implications for managing organizational change.

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.

This paper aims to provide a secure and efficient pairing protocol for two devices. Due to the large amount of data involving sensitive information transmitted in Internet of Things (IoT) devices, generating a secure shared key between smart devices for secure data sharing becomes essential. However, existing smart devices pairing schemes require longer pairing time and are difficult to resist attacks caused by context, as the secure channel is established based on restricted entropy from physical context.

This paper proposes a fuzzy smart IoT device pairing protocol via speak to microphone, FS2M. In FS2M, the device pairing is realized from the speaking audio of humans in the environment around the devices, which is easily implemented in the vast majority of Internet products. Specifically, to protect the privacy of secret keys and improve efficiency, this paper presents a single-round pairing protocol by adopting a recently published asymmetric fuzzy encapsulation mechanism (AFEM), which allows devices with similar environmental fingerprints to successfully negotiate the shared key. To instantiate AFEM, this paper presents a construction algorithm, the AFEM-ECC, based on elliptic curve cryptography.

This paper analyzes the security of the FS2M and its pairing efficiency with extensive experiments. The results show that the proposed protocol can achieve a secure device pairing between two IoT devices with high efficiency.

In FS2M, a novel cryptographic primitive (i.e., AFEM-ECC) are designed for IoT device pairing by using a new context-environment (i.e., human voice) . The experimental results show that FS2M has a good performance in both communication cost (i.e., 130 KB) and running time (i.e., 10 S).

This paper aims to address the safety concerns of path-planning algorithms in dynamic obstacle warehouse environments. It proposes a method that uses improved artificial potential fields (IAPF) as expert knowledge for an improved deep deterministic policy gradient (IDDPG) and designs a hierarchical strategy for robots through obstacle detection methods.

The IAPF algorithm is used as the expert experience of reinforcement learning (RL) to reduce the useless exploration in the early stage of RL training. A strategy-switching mechanism is introduced during training to adapt to various scenarios and overcome challenges related to sparse rewards. Sensor inputs, including light detection and ranging data, are integrated to detect obstacles around waypoints, guiding the robot toward the target point.

Simulation experiments demonstrate that the integrated use of IDDPG and the IAPF method significantly enhances the safety and training efficiency of path planning for mobile robots.

This method enhances safety by applying safety domain judgment rules to improve APF’s security and designing an obstacle detection method for better danger anticipation. It also boosts training efficiency through using IAPF as expert experience for DDPG and the classification storage and sampling design for the RL experience pool. Additionally, adjustments to the actor network’s update frequency expedite convergence.

Iron deficiency anemia (IDA) is the most common form of anemia in the world, affecting children, women and the elderly, while also being a common comorbidity in several medical conditions. Several studies have suggested a possible association between IDA and neurological dysfunction. Epilepsy, one of the common neurological disorders, has an unknown association with IDA. This pa per aims to investigate whether there is a causal relationship between IDA and epilepsy using a two-sample Mendelian randomization (MR) design.

This paper obtained summary data on IDA and epilepsy from the FinnGen consortium. Genetic variants significantly associated with IDA were used as instrumental variables (IVs). Epilepsy, focal epilepsy and generalized epilepsy were the outcomes. This paper used inverse variance weighted (IVW) as the primary estimate, and other MR methods were used as supplementary measures. Sensitivity analysis was also performed to assess heterogeneity and pleiotropy.

IVW estimates genetically predicted a causal relationship between IDA and the risk of epilepsy [odds ratio (OR), 1.15; 95% confidence interval (95% CI), 1.05–1.26; p = 0.002] and focal epilepsy (OR, 1.978, 95% CI, 1.58–2.48, p ≤ 0.0001), while no significant causal relationship was found with generalized epilepsy (OR, 1.1, 95% CI, 0.94–1.3, p = 0.24). There was no evidence of horizontal pleiotropy and heterogeneity in the sensitivity analysis.

This two-sample MR study found that IDA has a negative effect on the development of epilepsy. Clinical control of IDA may be helpful in the prevention of epilepsy. There is a need for further studies to explain the underlying mechanisms of this association.

Metaverse is one of the technologies that has the most promise for the future. However, there is less discussion about teaching using the metaverse. It is possible that most of the educators are ignorant of the metaverse’s features and its potential uses. The objective of this chapter is to define the metaverse precisely and discusses the various applications, characteristics, and challenges of metaverse in Education. This chapter explores the pioneering efforts in leveraging the metaverse for educational purposes, highlighting key examples and their impact on the learning experience. The possible applications of metaverse and research encounters in context to education are further reviewed and then explained and included the Artificial Intelligence (AI) functions in the world of metaverse along with learning based on metaverse. Researchers in the domains of educational technology and computer science shall advance an inclusive insight of the metaverse and its potential applications in education using various metaverse techniques like gamified learning, virtual learning, etc. Also, the metaverse role in education starting from the perception of AI has been covered.

Wheeled robots have been widely used in People’s Daily life. Accurate positioning is the premise of autonomous navigation. In this paper, an optimization-based visual-inertial-wheel odometer tightly coupled system is proposed, which solves the problem of failure of visual inertia initialization due to unobservable scale.The aim of this paper is to achieve robust localization of visually challenging scenes.

During system initialization, the wheel odometer measurement and visual-inertial odometry (VIO) fusion are initialized using maximum a posteriori (MAP). Aiming at the visual challenge scene, a fusion method of wheel odometer and inertial measurement unit (IMU) measurement is proposed, which can still be robust initialization in the scene without visual features. To solve the problem of low track accuracy caused by cumulative errors of VIO, the local and global positioning accuracy is improved by integrating wheel odometer data. The system is validated on a public data set.

The results show that our system performs well in visual challenge scenarios, can achieve robust initialization with high efficiency and improves the state estimation accuracy of wheeled robots.

To realize robust initialization of wheeled robot, wheel odometer measurement and vision-inertia fusion are initialized using MAP. Aiming at the visual challenge scene, a fusion method of wheel odometer and IMU measurement is proposed. To improve the accuracy of state estimation of wheeled robot, wheel encoder measurement and plane constraint information are added to local and global BA, so as to achieve refined scale estimation.

In this article, the authors try to determine why and under what conditions consumers intend to buy green and what the consequences are. Relying on theories of reasoned action and theory of planned behaviour (TPB), the authors offer that the green purchase intention (GPI) is impressed by environmental and personality components. Provide statements about the determinants and key implications of such market identification.

This study aims to provide a new perspective on the impact of mortality threats on consumer behavior through the lens of brand anthropomorphism. It examines the mediating effects of control and connectedness motives and the moderating effects of brand roles on the relationship between mediators and brand attitudes.

A preliminary study explored the relationship between pandemic-induced mortality threats and attitudes toward anthropomorphized brands. Study 1 investigated the underlying mechanism, and Study 2 examined the moderating effects of servant or partner roles. Study 3 confirmed the mortality threat effect on anthropomorphic brand attitudes in the absence of the pandemic.

The study revealed that mortality threats enhanced the desire for control and connectedness, which strengthened attitudes toward anthropomorphized brands. The results also indicated matching effects between the motivations for anthropomorphism and brand roles.

This research offers novel insights into the effects of pandemic-induced mortality threats and mortality threats in non-pandemic contexts on anthropomorphic motives. It highlights the influence of these psychological needs on consumer responses to brand roles and provides insights for brand management during a crisis.

In this chapter, we describe the importance of good governance in the metaverse. It offers unlimited opportunities and presents unique governance challenges. First, we describe the concept of good governance and its relevance to the metaverse. We emphasize that the speed of metaverse adoption depends upon the presence or absence of effective governance. Recognizing the metaverse as the next iteration of the internet, we present significant governance issues. Some issues such as interoperability, security, safety, privacy, law, and digital inequality are critical governance issues in the metaverse. Next, we explore the diverse governance frameworks to ensure the implementation of policies and regulations. These frameworks include decentralized governance, cross-sector collaboration, and standards-based governance. We also describe the best practices which are essential for good governance. To materialize the concepts and principles discussed, we present a compelling case study centered on Decentraland. This insightful exploration dissects a decentralized autonomous organization (DAO)-based governance structure, offering valuable insights into the intricacies and stages of governance proposals. We acknowledge both the merits and potential drawbacks inherent to this approach. This chapter aims to offer an all-encompassing view of metaverse governance, essentially serving as a comprehensive roadmap for traversing the multifaceted landscape of this digital frontier.