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The purpose of this paper is to visualize the collaboration network among regions in library science (LS) in China. Using various methods and tools of social network analysis and geographical visualization, results were obtained, showing the structure and patterns of research collaborations in topological and geographical views, as well as the geographical distributions of contribution.

The sample includes all studies published in the top journal in library science in China from 2006 to 2015. First, co-occurrence data representing collaborations among regions was extracted from author affiliations. Second, the topological network of collaboration was generated by applying social network analysis tools and descriptive statistics, network indicators of the collaboration network and research communities were calculated. Third, the topological network was projected into a geographical map with corresponding coordinates and distances using geographical tools. Finally, the topological network maps and the geographical maps were produced for visualization.

The levels of contribution are very unbalanced between regions, and overall research collaboration is low. Beijing, Hubei and several other areas are central and significant regions in China; other regions are mostly connected with central ones through direct collaborations. Research collaborations in LS research in China are mostly distributed in the east and south of China, being centralized in the “Beijing–Hubei–Shanghai” triangle zone, as well as within the triangle’s extending zones. Finally, there are three distinct research communities that connect closely within themselves and loosely between them. The Beijing community is relatively centralized in geography, while other communities are scattered.

This study applied various methods and tools of social network analysis and geographical mapping analysis to reveal the collaboration structure and patterns among regions in LS research in China. Visualized maps in topological and geographical views help shed new light on research efforts.

The shape of a product plays a crucial role in shaping consumer behavior. Despite the voluminous research on factors influencing consumers’ shape preferences, there remains a limited understanding of how the busy mindset, a mentality increasingly emphasized by marketing campaigns, works. This study aims to fill this gap by exploring the relationship between a busy mindset and the preference for angular-shaped versus circular-shaped products and brand logos.

This research consists of seven experimental studies using various shape stimuli, distinct manipulations of busy mindset, different assessments of shape preference and samples drawn from multiple countries.

The findings reveal that a busy mindset leads to a preference for angular shapes over circular ones by amplifying the need for uniqueness. In addition, these effects are attenuated when products are scarce.

This research represents one of the pioneering efforts to study the role of a busy mindset on consumers’ aesthetic preferences. Beyond yielding insights for practitioners into visual marketing, this research contributes to the theories on the busy mindset and shape preference.

The advent of derivatives and structured products has coincided with a proliferation of fixed income models used to analyze hedging, pricing, forecasting, and estimation for the term structure of interest rates. This article evaluates five models Ho‐Lee (HL); Black‐Derman‐Toy (BDT); Vasicek; Cox‐Ingersoll‐Ross (CIR); and Heath‐Jarrow‐Morton (HJM) (see Exhibit 1) that are currently used by structured finance practitioners. We suggest which models are most appropriate for assets with different time horizons, interest rate sensitivities and cashflow properties. The authors link model selection to structured financial instruments with the singular focus on the trade‐off between model precision/complexity and calculation costs.

The purpose of this paper is to generate grinding trajectory of unknown model parts simply and efficiently. In this paper, a method of grinding trajectory generation of hybrid robot based on Cartesian space direct teaching technology is proposed.

This method first realizes the direct teaching of hybrid robot based on 3Dconnexion SpaceMouse (3DMouse) sensor, and the full path points of the robot are recorded in the teaching process. To reduce the jitter and make the speed control more freely when dragging the robot, the sensor data is processed by Kalman filter, and a variable admittance control model is established. And the joint constraint processing is given during teaching. After that, the path points are modified and fitted into double B-splines, and the speed planning is performed to generate the final grinding trajectory.

Experiment verifies the feasibility of using direct teaching technology in Cartesian space to generate grinding trajectory of unknown model parts. By fitting all the teaching points into cubic B-spline, the smoothness of the grinding trajectory is improved.

The whole method is verified by the self-developed TriMule-600 hybrid robot, and it can also be applied to other industrial robots.

The main contribution of this paper is to realize the direct teaching and trajectory generation of the hybrid robot in Cartesian space, which provides an effective new method for the robot to generate grinding trajectory of unknown model parts.

The purpose of this paper is to accurately obtain the deformation of a hybrid robot and rapidly enable real-time compensation in friction stir welding (FSW). In this paper, a prediction algorithm based on the back-propagation neural network (BPNN) optimized by the adaptive genetic algorithm (GA) is presented.

Via the algorithm, the deformations of a five-degree-of-freedom (5-DOF) hybrid robot TriMule800 at a limited number of positions are taken as the training set. The current position of the robot and the axial force it is subjected to are used as the input; the deformation of the robot is taken as the output to construct a BPNN; and an adaptive GA is adopted to optimize the weights and thresholds of the BPNN.

This algorithm can quickly predict the deformation of a robot at any point in the workspace. In this study, a force-deformation experiment bench is built, and the experiment proves that the correspondence between the simulated and actual deformations is as high as 98%; therefore, the simulation data can be used as the actual deformation. Finally, 40 sets of data are taken as examples for the prediction, the errors of predicted and simulated deformations are calculated and the accuracy of the prediction algorithm is verified.

The entire algorithm is verified by the laboratory-developed 5-DOF hybrid robot, and it can be applied to other hybrid robots as well.

Robots have been widely used in FSW. Traditional series robots cannot bear the large axial force during welding, and the deformation of the robot will affect the machining quality. In some research studies, hybrid robots have been used in FSW. However, the deformation of a hybrid robot in thick-plate welding applications cannot be ignored. Presently, there is no research on the deformation of hybrid robots in FSW, let alone the analysis and prediction of their deformation. This research provides a feasible methodology for analysing the deformation and compensation of hybrid robots in FSW. This makes it possible to calculate the deformation of the hybrid robot in FSW without external sensors.

Copper matrix composites are widely used in high-voltage switches, electrified railways and other electric friction fields. The purpose of this study is to improve its wear resistance and investigate the effect of hybrid carbon nanotubes (CNTs) and titanium diboride (TiB₂) particles reinforced copper matrix composites on electrical wear performance.

CNTs and TiB₂ particles were introduced into copper matrix simultaneously by powder metallurgy combined with electroless copper plating. Electrical wear performance of the composites was studied on self-made pin on disk electrical wear tester.

The results show that the friction coefficient and wear rate of (1CNTs–4TiB₂)/Cu composite are respectively reduced by 40% and 25.3%, compared with single TiB₂/Cu composites. The micron-sized TiB₂ particles can hinder the plastic deformation of composites, and bear part of the load to weaken the wear rate of composites. CNTs with the self-lubricating property can form lubricating layer to reduce the friction coefficient of composites.

This work can provide a design method for further improving the wear properties of TiB₂/Cu composites.

This paper aims to study the synergistic lubrication effects of Sn–Ag–Cu and MXene–Ti₃C₂ to improve the tribological properties of M50 bearing steel with microporous channels.

M50 matrix self-lubricating composites (MMSC) were designed and prepared by filling Sn–Ag–Cu and MXene–Ti₃C₂ in the microporous channels of M50 bearing steel. The tribology performance testing of as-prepared samples was executed with a multifunction tribometer. The optimum hole size and lubricant content, as well as self-lubricating mechanism of MMSC, were studied.

The tribological properties of MMSC are strongly dependent on the synergistic lubrication effect of MXene–Ti₃C₂ and Sn–Ag–Cu. When the hole size of microchannel is 1 mm and the content of MXene–Ti₃C₂ in mixed lubricant is 4 wt.%, MMSC shows the lowest friction coefficient and wear rate. The Sn–Ag–Cu and MXene–Ti₃C₂ are extruded from the microporous channels and spread to the friction interface, and a relatively complete lubricating film is formed at the friction interface. Meanwhile, the synergistic lubrication of Sn–Ag–Cu and MXene–Ti₃C₂ can improve the stability of the lubricating film, thus the excellent tribological property of MMSC is obtained.

The results help in deep understanding of the synergistic lubrication effects of Sn–Ag–Cu and MXene–Ti₃C₂ on the tribological properties of M50 bearing steel. This work also provides a useful reference for the tribological design of mechanical components by combining surface texture with solid lubrication.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0381/

This study aims to comprehensively analyze the intersection of technology management and innovation management amidst the fourth industrial revolution, uncovering evolving trends and influential contributors.

Using the Bibliometrix R-package, this pioneering research conducts a bibliometric analysis to delve into innovation and technology management literature, quantifying scholarly output and identifying thematic breakthroughs.

The study reveals quantitative insights into the progression of innovation and technology management research, offering guidance on evolving trends, thematic breakthroughs and influential contributors.

The findings offer valuable insights for practitioners and managers, guiding them through emerging trends and recommending a dual focus on fundamental principles and emerging areas for strategic decision-making.

By fostering active engagement with evolving trends, this research contributes to the ongoing technology and innovation management discourse, potentially leading to societal benefits and advancements.

This study pioneers an in-depth bibliometric analysis at the intersection of innovation and technology management, offering unique insights and quantitative assessments of scholarly output and thematic trends, thus adding significant value to the existing literature.

Previous research has advanced in two-stage construction project productivity (CPP) evaluation by integrating site efficiency (SE) in the delivery and utilisation effectiveness (UE) in the post-delivery stages. The literature has separately addressed the factors affecting these three constructs. However, the interrelationships among them are rarely discussed together. This study aims to systematically identify the influencing factors of CPP, SE and UE and disentangle interrelationships among the three constructs.

The paper first reviews the literature about the two-stage project productivity evaluation framework for government construction projects. Then this paper proposes hypotheses regarding the relationships between the three constructs and identifies influencing factors associated with the constructs. Based on questionnaire survey from over 200 government construction project professionals in China, the structural equation modelling is adopted to validate the hypotheses.

The paper provides empirical insights that CPP can be directly influenced by UE to a large extent but indirectly impacted by SE through its effects on UE. The findings indicate that CPP is not a simple sum of SE and UE, and consequently reveals the complex, non-linear and indirect relationships between SE and CPP.

Future research should further extend the timeframe boundary to merge the pre-delivery stage (e.g. design and planning), findings of which may propose a more generalised understanding and reduce the bias resulting from pre-delivery activities.

This paper contributes to construction facility management literature by explaining the mediating role of UE on the relationship between SE and CPP. Therefore, this paper offers practitioners an integrated management logic in strategically combining project and facility management into government project management.

Strain sensors have been widely used to measure the strain of the structure. However, the ordinary sensing elements are not suitable for measuring large deformation on an irregular surface, which limits their applications. Recently, flexible sensors have attracted extensive interest because they can overcome the shortage of the ordinary sensing elements. The paper aims to discuss this issue.

In this paper, the whole measurement process of strain sensing behavior and the dimension design of fle3xible strain sensing system use the macroscopic measurement method of material tensile test to accurately measure the resistance change with strain. Afterwards, combining electrical components, the flexible strain sensors are produced for two biomedical applications: the wearable data-collecting gloves and rehabilitation training system.

The results show that the developed conductive fabric can exhibit high sensitivity, large workable strain range (>50 percent) under simple and repeated tension and good stability. Both applications demonstrate that the polypyrrole-coated fabric sensor can successfully measure the large and repeat strain, capture the motion of body and display corresponding information almost in real time.

The limitation lies in the lack of a holistic strain sensing mechanism study, and the lack of a corresponding theoretical model to explain the experimental results.