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The tactile sensor with array structure normally has the defects of existing nondetection zone, complex and nonstretchable structure. It is difficult to seamlessly attach to the surface of the robot. For this reason, this paper proposes a method to prepare nonarray structure tactile sensor directly on the surface of the robot by spraying process.

Based on the principle of gradient potential distribution, the potential fields are constructed in two different directions over the conductive film in time-sharing. The potentials at touching position in the two directions are detected to determine the coordinate of the touching point. The designed tactile sensor based on this principle consists of only three layers. Its bottom layer is designed as a weak conductive film made of graphite coating and used to construct the potential field. It can be sprayed either on PET substrate or directly on robot surface.

The radial basis function neural network is used for remodeling the potential distribution, which can effectively solve the problem of nonlinear potential distribution caused by irregular sensor shape, and uneven conductivity at different points of the spraying coating. The simulation and experimental results show that the principle of the proposed tactile sensor used for touching position detection is feasible to be applied to complex surfaces of the robot.

This paper proposed a nonarray customizable tactile sensor based on the spraying process. The sensor has a simple structure, and only five lead wires are needed to realize the coordinate detection of the touch position.

The purpose of this paper is to explore the combined influence of exchange quality (i.e. leader-member exchange or LMX, and coworker exchange or CWX) and organizational identity on the relationship between authoritarian leadership and employee innovation based on social cognition theory and social exchange theory.

The authors used mediation analysis, moderation analysis and bootstrapping method to test the proposed model with data from 286 supervisor-subordinate dyads in China, covering manufacturing and Internet companies. This study also used the time-lag design, and the questionnaires were collected by means of multi-source and multiphase.

The results indicate that authoritarian leadership can positively influence employee innovation behavior, and organizational identity mediates this relationship. Both LMX and CWX can significantly moderate the relationship between authoritarian leadership and organizational identity, while the moderating effect is the opposite. To be specific, CWX has appositive effect, while LMX has a negative effect. Furthermore, the indirect effect of authoritarian leadership on employee innovation behavior via organizational identity is also moderated by LMX.

At present, scholars have not yet reached a consensus on the relationship between authoritarian leadership and employee innovation behavior. Based on social cognition theory and social exchange theory, this study incorporates organizational identity and exchange quality into the research model to explore this lack of consensus. By verifying the research model, this study offers original views on when and how authoritarian leadership and exchange quality affect employee innovation behavior, which enriches the current research on employee innovation and the effectiveness of authoritarian leadership in different cultural contexts.

Imitation learning is a powerful tool for planning the trajectory of robotic end-effectors in Cartesian space. Present methods can adapt the trajectory to the obstacle; however, the solutions may not always satisfy users, whereas it is hard for a nonexpert user to teach the robot to avoid obstacles in time as he/she wishes through demonstrations. This paper aims to address the above problem by proposing an approach that combines human supervision with the kernelized movement primitives (KMP) model.

This approach first extracts the reference database used to train KMP from demonstrations by using Gaussian mixture model and Gaussian mixture regression. Subsequently, KMP is used to modulate the trajectory of robotic end-effectors in real time based on feedback from its interaction with humans to avoid obstacles, which benefits from a novel reference database update strategy. The user can test different obstacle avoidance trajectories in the current task until a satisfactory solution is found.

Experiments performed with the KUKA cobot for obstacle avoidance show that this approach can adapt the trajectories of the robotic end-effector to the user’s wishes in real time, including trajectories that the robot has already passed and has not yet passed. Simulation comparisons also show that it exhibits better performance than KMP with the original reference database update strategy.

An interactive learning approach based on KMP is proposed and verified, which not only enables users to plan the trajectory of robotic end-effectors for obstacle avoidance more conveniently and efficiently but also provides an effective idea for accomplishing interactive learning tasks under constraints.

This paper aims to report a flexible position-sensitive sensor that can be applied as large-area electronic skin over the stiff media.

The sensor uses a whole piezoresistive film as a touch sensing area. By alternately constructing two uniform electric fields with orthogonal directions in the piezoresistive film, the local changes in conductivity caused by touch can be projected to the boundary along the equipotential line under the constraint of electric field. Based on the change of boundary potential in the two uniform electric fields, it can be easy to determine the position of the contact area in the piezoresistive film.

Experiment results show the proposed tactile sensor is capable of detecting the contact position and classifying the contact force in real-time based on the changes of the potential differences on the boundary of the sensor.

The application example of using the sensor sample as a controller in shooting game is presented in this paper. It shows that the sensor has excellent touch sensing performance.

In this paper, a position-sensitive electronic skin is proposed. The experiment results show that the sensor has great application prospects in the field of interactive tactile sensing.

The aim of the research is to achieve a robot skin which is easy to use, and can detect both position and force interacted between robot and environments.

The new type of robot skin proposed in this paper includes two functional modules – contact position sensor and contact force sensor. The contact position sensor module is based on the resistor divider principle, which consists of two perpendicular conductive fiber layers and insulated dot spacer between them. The contact force sensor module is based on capacitance change theory, which consists of two soft conductive plates and a viscoelastic layer between them. By combining the two modules, the soft robot skin was designed.

Simulation and experiment results demonstrate that the proposed robot skin design is feasible and effective enough to sense contact position and contact force simultaneously.

This robot skin is low-cost and easy to make and use, which provides safety solutions for most of the robot.

For the first time, an integrated robot skin which can get contact position and force information simultaneously is designed. Unlike general tactile sensor matrices, this robot skin has only six leads. Furthermore, the number of leads does not increase with the enlarging of sensor area. Soft and simple structure of the robot skin makes it possible to cover any region of the robot body.

This paper aims to empirically investigate the impact of the carbon intensity constraint policy (CICP) on green innovation.

This study takes the implementation of the CICP as a quasi-natural experiment and uses a quasi–difference-in-difference method to investigate the impact of the CICP on firm green innovation from a microeconomic perspective.

The CICP significantly limits the quality of firms’ green innovation. Among the range of green patents, the CICP distorts only patents related to CO₂ emissions. The inhibitory effect is more pronounced in non-state-owned enterprises and heavily polluting firms. R&D investment and green investor are identified as the main mechanism.

These findings provide evidence for the influence of the CICP on firm green innovation, which can guide policymakers in China and other emerging economies that prioritize carbon intensity constraint targets and the improvement of relevant auxiliary measures.

Governments and firms should have a comprehensive understanding of environmental policies and corporate behavior and need to mitigate the negative impact through a combination of measures.

This study contributes to the literature by providing additional empirical evidence regarding the two opposing sides of the ongoing debate on the positive or negative effects of CICP. It also provides new evidence on the policy effect of the CICP on firm green innovation, together with its mechanisms and heterogeneous influences.

The purpose of this paper is to study the influence of calcium sulfate whiskers (CSWs) on the thermodynamic properties and shape memory properties of epoxy/cyanate ester shape memory composites.

To improve the mechanical properties of shape memory cyanate ester (CE)/epoxy polymer (EP) resin, high performance CSWs were used to reinforce the thermo-induced shape memory CE/EP composites and the shape memory CSW/CE/EP composites were prepared by molding. The effect of CSW on the mechanical properties and shape memory behavior of shape memory CE/EP composites was investigated.

After CSW filled the shape memory CE/EP composites, the bending strength of the composites is greatly improved. When the content of CSW is 5 Wt.%, the bending strength of the composite is 107 MPa and the bending strength is increased by 29 per cent compared with bulk CE/EP resin. The glass transition temperature and storage modulus of the composites were improved in CE/EP resin curing system. However, when the content of CSW is more than 10 Wt.%, clusters are easily formed between whiskers and the voids between whiskers and matrix increase, which will lead to the decrease of mechanical properties of composites. The results of shape memory test show that the shape memory recovery time of the composites decreases with the decrease of CSW content at the same temperature. In addition, the shape recovery ratio of the composites decreased slightly with the increase of the number of thermo-induced shape memory cycles.

A simple way for fabricating thermo-activated SMP composites has been developed by using CSW.

The outcome of this study will help to fabricate the SMP composites with high mechanical properties and the shape memory CSW/CE/EP composites are expected to be used in space deployable structures.

In any time and space and under any circumstance, we find peasants are never passive actors in their livelihoods and rural development. Instead, they always create space for manoeuvre in order to make changes. This chapter analyses the innovative actions taken by the majority of rural inhabitants in rural areas during the overwhelming modernization process, so as to affirm that peasants are the main actors of rural development. It is they who have shaped the transformation of rural societies and the history. Through the analysis, this chapter concludes that rural development is not an objective, a blueprint nor a design. It is not the to-be-developed rear field in modernization. It is not the babysitter for cities, nor a rehearsal place for bureaucrats to testify their random thoughts. Rural development is what peasants do. The path they have chosen reveals scenery so different from modernization. If we regard development as a social change, or a cross with influential meanings, we could understand rural development as peasants’ victories over their predicament. Villages accommodate not only peasants, but without peasants villages would surely vanish. In this sense, the most important part in rural development or rural change is peasants – their conditions and their feelings.

The purpose of this paper is to propose novel attitudinal prioritization and correlated aggregating methods for multiple attribute group decision making (MAGDM) with triangular intuitionistic fuzzy Choquet integral.

Based on the continuous ordered weighted average (COWA) operator, the triangular fuzzy COWA (TF-COWA) operator is defined, and then a novel attitudinal expected score function for triangular intuitionistic fuzzy numbers (TIFNs) is investigated. The novelty of this function is that it allows the prioritization of TIFNs by taking account of the expert’s attitudinal character. When the ranking order of TIFNs is determined, the triangular intuitionistic fuzzy correlated geometric (TIFCG) operator and the induced TIFCG (I-TIFCG) operator are developed.

Their use is twofold: first, the TIFCG operator is used to aggregate the correlative attribute value; and second, the I-TIFCG operator is designed to aggregate the preferences of experts with some degree of inter-dependent. Then, a TIFCG and I-TIFCG operators-based approach is presented for correlative MAGDM problems. Finally, the propose method is applied to select investment projects.

Based on the TIFCG and I-TIFCG operators, this paper proposes a novel correlated aggregating methods for MAGDM with triangular intuitionistic fuzzy Choquet integral. This method helps to solve the correlated attribute (criteria) relationship. Furthermore, by the attitudinal expected score functions of TIFNs, the propose method can reflect decision maker’s risk attitude in the final decision result.

In contrast to existing studies, this paper aims to propose that digital transformation does not depend on a single condition; rather, it depends on the interaction between internal and external factors of a firm. Therefore, the aim of this paper is to examine the effect of a combination of internal and external factors on a firm's digital transformation intention.

An empirical analysis on a sample of 112 Chinese small- and medium-sized firms was conducted by applying smart-PLS and fuzzy set qualitative comparative analysis (fsQCA).

The results of smart PLS show that external pressures (institutional and market pressures) and human capital have a positive impact on corporate digital transformation intentions. From a combination perspective, the results of the fsQCA show that there are five causal conditions that lead to high digital transformation intention. In contrast to the net effect, the results of fsQCA show that different combinations of states of internal (human capital, organizational culture and technological capital) and external elements (institutional and market pressures) of the firm are likely to stimulate digital transformation intention.

This study provides empirically based insights into firms' digital transformation intentions and advances the current understanding of the drivers and inhibitors of digital transformation. Unlike most current research, which tends to focus on the net effect of factors influencing the digital transformation of enterprises, this study focuses on identifying the core elements influencing enterprises' digital transformation intention, especially the joint effect of different factors, both internal and external to the enterprise. The combined SEM and fsQCA findings of this paper not only enrich the existing theories on digital transformation but also have high value in guiding the digital transformation of firms.