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Brand storytelling is an effective marketing tool. However, when choosing whether to tell more or tell less, it remains unclear which of these two narrative styles is most effective. This study aims to examine whether blank-leaving(less) leads to favourable brand attitudes and compares its effects on consumers’ story immersion, to non-blank-leaving(more).

Two experiments were conducted to test the hypotheses. In Study 1, a single-factorial design was used with 252 participants assigned at random to one of two narrative conditions: blank-leaving or non-blank-leaving. Study 2 replicated Study 1 and investigated the moderating role of implicit mindsets.

The results show that a blank-leaving narrative style increases favourable brand attitudes. Consumers present deeper immersion in the brand story that uses blank-leaving, as compared to non-blank-leaving, leading to a more favourable brand attitude. Furthermore, this effect is stronger for individuals with growth mindsets.

Telling the brand story using a blank-leaving narrative style is more effective in catching consumers’ attention than non-blank-leaving. In particular, a blank-leaving narrative is a good approach for targeting consumers who have a growth mindset.

To the best of the authors’ knowledge, this research is the first to investigate and compare the effects of blank-leaving and non-blank-leaving narrative styles on brand attitudes in the context of storytelling marketing.

Recent spacecraft attitude control systems tend to use wireless communication for cost-saving and distributed mission purposes while encountering limited communication resources and data exposure issues. This paper aims to study the attitude control problem with low communication frequency under the sampled-data.

The authors propose constructive control system structures based on quantization and event-triggered methods for intra-spacecraft and multi-spacecraft systems, and they also provide potential solutions to shield the control system's data security. The proposed control architectures can effectively save communication resources for both intra-spacecraft and multi-spacecraft systems.

The proposed control architectures no longer require sensors with trigger-ing mechanism and can achieve distributed control schemes. This paper also provides proposals of employing the public key encryption to secure the data in control-loop, which is transmitted by the event-triggered control mechanism.

Spacecraft attempts to use wireless communication, yet the attitude control system does not follow up promptly to accommodate these variations. Compared with existing approaches, the proposed control structures can save communication resources of control-loop in multi-sections effectively, and systematically, by rationally configuring the location of quantization and event-triggered mechanisms.

This paper presents several new control schemes and a necessary condition for the employment of encryption algorithms for control systems based on event-based communication.

This paper aims to address the spacecraft attitude regulation problem in the presence of extrinsic disturbances and actuator faults.

Based on adaptive backstepping design technique, a new concise adaptive dual-mode control scheme is proposed, which can either use the fault information detected by fault diagnosis mechanisms or switch to the fault-unknown mode when the fault diagnosis information is non-existent for control signal generation. These two modes share an adaptive mechanism that reduces the complexity of the algorithm.

The new fault-tolerant attitude control algorithm can accommodate both modes with and without fault diagnosis mechanisms.

The proposed algorithm in this paper can be applied to both cases when the attitude control system is equipped with or without fault diagnosis capability. This also enhances the robustness of attitude control algorithm. This study performs numerical simulations and verifies that the algorithm could effectively adapt to both modes.

The coupling impact of hybrid uncertain errors on the machine precision is complex, as a result of which the designing method with multiple independent error sources under uncertainties remains a challenge. For the purpose of precision improvement, this paper focuses on the robot design and aims to present an assembly precision design method based on uncertain hybrid tolerance allocation (UHTA), to improve the positioning precision of the mechanized robot, as well as realize high precision positioning within the workspace.

The fundamentals of the parallel mechanism are introduced first to implement concept design of a 3-R(4S) &3-SS parallel robot. The kinematic modeling of the robot is carried out, and the performance indexes of the robot are calculated via Jacobian matrix, on the basis of which, the 3D spatial overall workspace can be quantified and visualized, under the constraints of limited rod, to avoid the singular position. The error of the robot is described, and a probabilistic error model is hereby developed to classify the hybrid error sensitivity of each independent uncertain error source by Monte Carlo stochastic method. Most innovatively, a methodology called UHTA is proposed to optimize the robot precision, and the tolerance allocation approach is conducted to reduce the overall error amplitude and improve the robotized positioning precision, on the premise of not increasing assembly cost.

The proposed approach is validated by digital simulation of medical puncture robot. The experiment highlights the mathematical findings that the horizontal plane positioning error of the parallel robotic mechanism can be effectively reduced after using UHTA, and the average precision can be improved by up to 39.54%.

The originality lies in UHTA-based precision design method for parallel robots. The proposed method has widely expanding application scenarios in industrial robots, biomedical robots and other assembly automation fields.

This study aims to explore the cross-level effect of the top management team (TMT) on group ambidextrous innovation and to analyze the mediating role of group behavioral integration and the moderating effect of group expertise heterogeneity.

We conducted a multi-source and multi-stage survey. We collected valid data from 43 companies in China, resulting in 141 samples from 43 TMTs and 462 valid responses from 111 organizational groups. The proposed theoretical model and hypotheses were tested using structural equation modeling.

The study findings demonstrated that TMT behavioral integration was positively related to group behavioral integration. Group behavioral integration mediates the relationship between TMT behavioral integration and these two types of innovations. Furthermore, we found that group expertise heterogeneity magnified the positive effect of group behavioral integration on exploratory innovation.

This study reveals the cross-level effects of TMT behavioral integration on other organizational groups and enriches the existing literature on TMT behavioral integration and ambidextrous innovation.

This paper explores how the existence of a second-hand market can affect remanufacturing decisions for durable goods in the presence of patent protection.

The authors construct a dynamic decision model between a durable goods original manufacturer and a durable goods remanufacturer considering the characteristics of the multi-cycle uses of new durable goods and remanufactured durable goods.

The results show that (1) the second-hand market compresses the cost space of a durable goods original manufacturer and a remanufacturer; (2) when the second-hand market exists, the optimal pricing of new durable goods is reduced, the optimal pricing of remanufactured durable goods is increased and the patent cost of each unit of durable goods increases and (3) the presence of the second-hand market will increase the original manufacturer's and remanufacturer's profits.

The research conclusion has certain reference value for the production strategy selection of each enterprise in the process of patented product remanufacturing and the government's fiscal policy formulation at each stage of the remanufacturing industry's development.

The purpose of this paper is to investigate the attitude cooperation control of multi-spacecraft with in-continuous communication.

A decentralized state-irrelevant event-triggered control policy is proposed to reduce control updating frequency and further achieve in-continuous communication by introducing a self-triggered mechanism.

Each spacecraft transmits data independently, without the requirement for the whole system to communicate simultaneously. The local predictions and self-triggered mechanism avoid continuous monitoring of the triggering condition.

This investigation is suitable for small Euler angle conditions.

The control policy based on event-triggered communication can provide potential solutions for saving communication resources.

This investigation uses event- and self-triggered policy to achieve in-communication for the multi-spacecraft system.

The purpose of this paper is to design an adaptive nonlinear controller for a nonlinear system of integrated guidance and control.

A nonlinear integrated guidance and control approach is applied to a homing, tail-controlled air vehicle. Adaptive backstepping controller technique is used to deal with the problem, and the Lyapanov theory is used in the stability analysis of the nonlinear system. A nonlinear model of normal force coefficient is obtained from an existing nonlinear model of lift coefficient which was validated by open loop response. The simulation was performed in the pitch plane to prove the benefits of the proposed scheme; however, it can be readily extended to all the three axes.

Monte Carlo simulations indicate that using nonlinear adaptive backstepping formulation meaningfully improves the performance of the system, while it ensures stability of a nonlinear system.

The proposed method could be used to obtain better performance of hit to kill accuracy without the expense of control effort.

A nonlinear adaptive backstepping controller for nonlinear aerodynamic air vehicle is designed and guaranteed to be stable which is a novel-based approach to the integrated guidance and control. This method makes noticeable performance improvement, and it can be used with hit to kill accuracy.

Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news semantics and establish connections between stocks is deemed essential and viable.

This study presents a knowledge-driven framework for predicting stock prices. The framework integrates relevant stocks with the semantic and emotional characteristics of textual data. The authors construct a stock knowledge graph (SKG) to extract pertinent stock information and use a knowledge graph representation model to capture both the relevant stock features and the semantic features of news articles. Additionally, the authors consider the emotional characteristics of news and investor comments, drawing insights from behavioral finance theory. The authors examined the effectiveness of these features using the combined deep learning model CNN+LSTM+Attention.

Experimental results demonstrate that the knowledge-driven combined feature model exhibits significantly improved predictive accuracy compared to single-feature models.

The study highlights the value of the SKG in uncovering potential correlations among stocks. Moreover, the knowledge-driven multi-feature fusion stock forecasting model enhances the prediction of stock trends for well-known enterprises, providing valuable guidance for investor decision-making.