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This study aims to the three major problems of low cleaning efficiency, high labor intensity and difficult to evaluate the cleaning effect for manual insulators cleaning in ultra high voltage (UHV) converter station, the purpose of this paper is to propose a basic configuration of UHV vertical insulator cleaning robot with multi-freedom-degree mechanical arm system on mobile airborne platform and its innovation cleaning operation motion planning.

The main factors affecting the insulators cleaning effect in the operation process have been analyzed. Because of the complex coupling relationship between the influencing factors and the insulators cleaning effect, it is difficult to establish its analytical mathematical model. Combining the non-linear mapping and approximation characteristics of back propagation (BP) neural network, the insulator cleaning effect evaluation can be abstracted as a non-linear approximation process from actual cleaning effect to ideal cleaning effect. An evaluation method of robot insulator cleaning effect based on BP neural network has been proposed.

Through the BP neural network training, the robot cleaning control parameters can be obtained and used in the robot online operation control, so that the better cleaning effect can be also obtained. Finally, a physical prototype of UHV vertical insulator cleaning robot has been developed, and the effectiveness and engineering practicability of the proposed robot configuration, cleaning effect evaluation method are all verified by simulation experiments and field operation experiments. At the same time, this method has the remarkable characteristics of sound versatility, strong adaptability, easy expansion and popularization.

An UHV vertical insulator cleaning robot operation system platform with multi-arm system on airborne platform has been proposed. Through the coordinated movement of the manipulator each joint, the manipulator can be positioned to the insulator strings, and the insulator can be cleaned by two pairs high-pressure nozzles located at the double manipulator. The influence factors of robot insulator cleaning effect have been analyzed. The BP neural network model of insulator cleaning effect evaluation has been established. The evaluation method of robot insulator cleaning effect based on BP neural network has also been proposed, and the corresponding evaluation result can be obtained through the network training. Through the system integration design, the robot physical prototype has been developed. For the evaluation of other operation effects of power system, the validity and engineering practicability of the robot mechanism, motion planning and the method for evaluating the effect of robot insulator cleaning have been verified by simulation and field operation experiments.

In the long-term network operation, the power distribution network will be subjected to the effects of ultra-high voltage, strong electromagnetic interference and harsh natural environment on the power system, which will lead to the occurrence of different faults in the distribution network and directly affect the normal operation of the power grid.

The purpose of this study is to solve the problems of labor intensity, high risk and low efficiency of distribution network manual maintenance operation, this paper proposed a new configuration of the live working robot for distribution network maintenance, the robot is equipped with dual working arms through the mobile platform, which can realize the coordination movement, the autonomous reorganization and replacement of the end tools, respectively, so as the robot power distribution maintenance function such as stripping, trimming, wiring and the operation control problem of the distribution network-robot with small arms and in small operation space can be realized.

To effective elimination or reduce the adverse effects of the internal forces in the closed chain between the working object and manipulator under the typical task of the 10 kV distribution network, this paper has established the robot coordinated control dynamics model in the closed-chain between the dual-working object and proposed the dynamic distribution method of closed-chain internal force and the effectiveness has been proved by simulation experiments and 10 kV field operation.

The force-position hybrid control can realize the mutual compensation of force and position so as to effectively reduce the internal force in the closed chain. Finally, the engineering practicality of the method is verified by field operation experiment, the effective implementation of this control method greatly improves the robot working efficiency and the operation reliability, the promotion and application of the control method have great theoretical and practical value and maintenance management system, so as to achieve automation of electric.

Drawing on the upper echelons theory, this study focuses on how top management team (TMT) heterogeneity affects breakthrough innovations and examines how strategic decision-making logic (including causation and effectuation) moderates the relationship between TMT heterogeneity and breakthrough innovation.

By conducting an empirical test of 227 sample firms in China, the authors applied linear hierarchical regression analysis to test the hypotheses on the TMT heterogeneityinnovation relationship and the moderating roles of causation and effectuation.

The empirical tests show that TMT heterogeneity positively affects breakthrough innovation, and both causation and effectuation positively moderate the positive relationship between TMT heterogeneity and breakthrough innovation. In addition, effectuation has a stronger moderating effect on the positive correlation between TMT heterogeneity and breakthrough innovation than causation.

This study extends the upper echelons theory to explain how the characteristics of TMTs affect firm innovation. Specifically, the authors explore the TMT heterogeneity–breakthrough innovation relationship from the perspectives of information processing and core competence and reveal the boundary condition of strategic decision-making logic in the correlation between TMT heterogeneity and breakthrough innovation. In this vein, the authors contribute to the literature by untangling the internal mechanisms between TMT heterogeneity and breakthrough innovation and extending the discussion on effectuation theory from the entrepreneurship domain to the innovation field. Furthermore, the research findings can provide helpful implications for TMTs to manage breakthrough innovation effectively.

Direct additive manufacturing of ceramics (DAMC) is a highly promising ceramics preparation technology because of its simple process and rapid response capability, but the cracking issue prevents its industrial application. The purpose of this paper is to propose aluminum titanate (Al₂TiO₅) with low coefficient of thermal expansion (CTE) to suppress cracks during the DAMC.

Al₂O₃/Al₂TiO₅ (A/AT) composite ceramic samples with different compositions were in-situ synthesized from Al₂O₃/TiO₂ (A/T) powder in a directed laser deposition (DLD) process. The relationship between the content of TiO₂ and cracking characteristics of fabricated sample was discussed. Phase composition, microstructure and properties of the fabricated samples were also investigated.

The results of this paper show that the doping of TiO₂ can obtain Al₂TiO₅ synthesized in situ by reaction with Al₂O₃ and effectively suppress cracks during DAMC. When the content of TiO₂ reaches 30 wt.per cent, cracks hardly occur even under conditions of slow deposition. Crack-free structures such as vane, cone and pyramid were successfully prepared, with a maximum cross-sectional dimension of 30 mm and maximum length of 150 mm. A continuous matrix phase formed of the low CTE of Al₂TiO₅ is the major cause of crack suppression. The dispersed distribution of a-Al₂O₃ columnar dendrites has the effect of increasing the strength of the matrix. Under current process conditions, the prepared sample with 10 wt.per cent TiO₂ has micro-hardness of 21.05 GPa and flexural strength of 170 MPa.

This paper provides a new method and inspiration for direct additive manufacturing of large-sized crack-free ceramics, which has the potential to promote practical application of the technology.

This paper aims to identify a variety of binary system solders by alloying, and relevantly derive multiple system Pb-free solders from the former, attempting to replace the high temperature Sn-Pb solder.

The basis of the paper is the synthesis of previous studies. In terms of some binary high temperature solder alloys, such as Au-20Sn, Bi-2.5Ag, Sn-5Sb, Au-12.5Ge, Zn-6Al and Zn-Sn, taking the alloy phase diagram as the starting point, the melting characteristics, microstructure, mechanical properties, wetting ability and reliability of solder joint are analysed and the prospect is consequently indicated.

Based on the analysis of the six groups of Pb-free solders, the present binary system solder alloys, from the perspective of melting properties, mechanical properties, soldering or reliability of solder joint, rarely meet the comprehensive requirements of replacing the high-temperature Sn-Pb solder. It is assumed to be a solution that multiple-system Pb-free solders derive from a variety of binary system solders by means of alloying. The future development of high temperature Pb-free solder may focus on some factors such as physical properties, mechanical properties, processing, reliability of solder joint, environmental performance and expense.

The paper concentrates on the issue of Pb-free solders at high temperature. From a specific perspective of binary system solders, the presently available Pb-free solders are suggested from the starting point of the alloy phase diagram and the prospect of alternatives of Sn-Pb solders at high temperature are indicated.

The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and workforce automation. This shift has sparked a considerable amount of public discussion. This study aims to explore the online public's sentiment toward remote work amid the pandemic.

Based on justice theory, this paper examines user-generated content on social media platforms, particularly Twitter, to gain insight into public opinion and discourse surrounding remote work during the COVID-19 pandemic. Employing content analysis techniques such as sentiment analysis, text clustering and evolutionary analysis, this study aims to identify prevalent topics, temporal patterns and instances of sentiment polarization in tweets.

Results show that people with positive opinions focus mainly on personal interests, while others focus on the interests of the company and society; people's subjectivities are higher when they express extremely negative or extremely positive emotions. Distributive justice and interactional justice are distinguishable with a high degree of differentiation in the cluster map.

Previous research has inadequately addressed public apprehensions about remote work during emergencies, particularly from a justice-based perspective. This study seeks to fill this gap by examining how justice theory can shed light on the public's views regarding corporate policy-making during emergencies. The results of this study provide valuable insights and guidance for managing public opinion during such events.

Social media, especially microblog, has become one of the most popular platforms for public opinion dissemination. However, so far few studies have been conducted to explore information dissemination under the mobile environment. This paper aims to introduce the approach to analyze the public opinion information dissemination in mobile social networks.

This paper chooses “network attack” as the research topic and extracts 23,567 relevant messages from Sina Microblogs to study the structure of nodes for public opinion dissemination and the characteristics of propagation paths on mobile internet. Public opinion dissemination is compared on both mobile and non-mobile terminals.

The results reveal the characteristics of public opinion dissemination in mobile environment and identify three patterns of information propagation path. This study concludes that public opinion on mobile internet propagates more widely and efficiently and generates more impact than that on the non-mobile internet.

The methods used in this study can be useful for the government and other organizations to analyze and identify problems in online information dissemination.

This paper explores the mechanism of public opinion dissemination on mobile internet in China and further investigates how to improve public opinion management through a case study related to “network attack.”

The rope-climbing robot that can cling to a rope for locomotion has been a popular piece of equipment for some overhead applications due to its high flexibility. In view of problems left by existing rope-climbing robots, this paper aims to propose a new-style rope-climbing robot named Finger-wheeled mechanism robot (FWMR)-II to improve their performance.

FWMR-II adopts a modular and link-type mechanical structure. With the finger-wheeled mechanism (FWM) module, the robot can achieve smooth and quick locomotion and good capability of obstacle-crossing on the rope and with the link module based on a spatial parallel mechanism, the robot adaptability for rope environments is improved further. The kinematic models that can present configurations of the FWM module and link module of the robot are established and for typical states of the obstacle-crossing process, the geometric definitions and constraints that can present the robot position relative to the rope are established. The simulation is performed with the optimization calculating method to obtain the robot adaptability for rope environments and the experiment is also conducted with the developed prototype to verify the robot performance.

From the simulation results, the adaptability for rope environments of FWMR-II are obtained and the advantage of FWMR-II compared with FWMR-I is also proved. The experiment results give a further verification for the robot design and analysis work.

The robot proposed in this study can be used for inspection of power transmission lines, inspection and delivery in mine and some other overhead applications.

An ingenious modular link-type robot is proposed to improve existing rope-climbing robots and the method established in this study is worthy of reference for obstacle-crossing analysis of other rope-climbing robots.

The purpose of this study is to empirically explore the connection between transformational leadership (TL) and organizational effectiveness (OE). Also, the paper looks at the mediating impact of employee innovative behaviour (EIB) and the moderating effect of knowledge sharing (KS) on the aforementioned association.

The respondents included 410 bank employees from North India. The mediating effect of EIB and moderating effect of KS was explored by plug-in for SPSS, PROCESS Macro (Hayes).

The investigation demonstrated that there exists a significant relationship between the constructs under examination. Further, it was seen that EIB mediated and KS moderated the connection between TL and OE.

Looking at the associations among TL, KS, EIB and OE can have significant implications for organizations. The considered framework as proposed can be used to outline organizational practices, to frame organizational policies and to build a pool of innovative employees who will in turn enhance OE.

The general comprehension of the associations among TL, KS, EIB and OE is insufficient in existing literature. This examination expands on past studies by examining the mediating role of the EIB and moderating role of KS between TL and OE. The present work is one of the rare attempts to investigate this nested association in the Indian context.

In recent years, there has been a growing interest in the potential of data analytics to enhance project delivery. Yet many argue that its application in projects is still lagging behind other disciplines. This paper aims to provide a review of the current use of data analytics in project delivery encompassing both academic research and practice to accelerate current understanding and use this to formulate questions and goals for future research.

We propose to achieve the research aim through the creation of a systematic review of the status of data analytics in project delivery. Fusing the methodology of integrative literature review with a recently established practice to include both white and grey literature amounts to an approach tailored to the state of the domain. It serves to delineate a research agenda informed by current developments in both academic research and industrial practice.

The literature review reveals a dearth of work in both academic research and practice relating to data analytics in project delivery and characterises this situation as having “more gap than knowledge.” Some work does exist in the application of machine learning to predicting project delivery though this is restricted to disparate, single context studies that do not reach extendible findings on algorithm selection or key predictive characteristics. Grey literature addresses the potential benefits of data analytics in project delivery but in a manner reliant on “thought-experiments” and devoid of empirical examples.

Based on the review we articulate a research agenda to create knowledge fundamental to the effective use of data analytics in project delivery. This is structured around the functional framework devised by this investigation and highlights both organisational and data analytic challenges. Specifically, we express this structure in the form of an “onion-skin” model for conceptual structuring of data analytics in projects. We conclude with a discussion about if and how today’s project studies research community can respond to the totality of these challenges. This paper provides a blueprint for a bridge connecting data analytics and project management.