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About 70% of all aircraft accidents are caused by human–machine interaction, thus identifying and quantifying performance shaping factors is a significant challenge in the study of human reliability. An information flow field model of human–machine interaction is put forward to help better pinpoint the factors influencing performance and to make up for the lack of a model of information flow and feedback processes in the aircraft cockpit. To enhance the efficacy of the human–machine interaction, this paper aims to examine the important coupling factors in the system using the findings of the simulation.

The performance-shaping factors were retrieved from the model, which was created to thoroughly describe the information flow. The coupling degree between the performance shaping factors was calculated, and simulation and sensitivity analysis are based on system dynamics.

The results show that the efficacy of human–computer interaction is significantly influenced by individual important factors and coupling factors. To decrease the frequency of accidents after seven hours, attention should be paid to these factors.

The novelty of this work lies in proposing a theoretical model of cockpit information flow and using system dynamics to analyse the effect of the factors in the human–machine loop on human–machine efficacy.

The purpose of this paper is to conveniently and accurately design partial knitting knitted fabrics based on matrix transformation.

Using mathematical modeling, the pattern diagram block matrix and process design matrix of partial knitting knitted fabrics are established, and the process knitting diagram with parameter information is generated. Based on the establishment of the mathematical model of the process knitting diagram, a loop deformation method based on three-dimensional (3D) coordinate point matrix transformation is proposed.

The matrix transformation method can provide a suitable deformed loop mode for partial knitting knitted fabrics and helps to generate a 3D modeling diagram conveniently.

This paper proposed a method of design and modeling of partial knitting knitted fabric based on matrix transformation. Taking the 3D modeling effect of conventional partial knitting as an example to test the modeling method, the results show that after matrix transformation, the loop model can realize the rapid transformation and calculation of the coordinates of the control point and generate a 3D modeling diagram.

This paper aims to propose a structural sizing approach of an unmanned aerial vehicle (UAV) wing that takes into account the aeroelasticity effects through a fluid–structure interaction analysis.

The sizing approach proposed in this study is an iterative process, each iteration of which consists of two sub-loops, a multidisciplinary analysis (MDA) loop followed by a structural optimization loop. The MDA loop seeks the aeroelastic equilibrium between aerodynamic forces and structural displacements using a fixed-point iteration scheme. Once the equilibrium is reached, the converged pressure loads are used for the structural optimization, which aims to find the structural thicknesses that minimize the wing weight under failure criteria. The two sub-loops are run sequentially in an iterative process until the mass is converged. The analysis models are implemented in open-source software, namely, PANUKL for aerodynamics and MYSTRAN for structures, while the whole process is automated with Python and integrated in the open-source optimization framework OpenMDAO.

The approach was applied to the design of the Predator MQ-1 wing. The results of the MDAs show the convergence of the wing deformations to the flight shape after few iterations. At the end of the aeroelastic sizing loop, the result is a structurally sized wing with minimal weight considering the aeroelasticity effects.

The approach proposed takes into account the wing aero-structural coupling effects while sizing its structure instead of a fixed load distribution. In addition, the approach is fully based on open-source codes, which are freely available for public use and can be fully reproducible.

The accurate modeling of magnetic hysteresis in electrical steels is important in several electrical and electronic applications. Numerical models have long been known that can correctly reproduce some typical behaviours of these magnetic materials. Among these, the model proposed by Jiles and Atherton must certainly be mentioned. This model is intuitive and fairly easy to implement and identify with relatively few experimental data. Also, for this reason, it has been extensively studied in different formulations. The developments and numerical tests made on this hysteresis model have indicated that it is able to accurately reproduce symmetrical cycles, especially the major loop, but often it fails to reproduce non-symmetrical cycles. This paper aims to show the positive aspects and highlight the defects of the different formulations in predicting the minor loops of electrical steels excited by non-sinusoidal currents.

The different formulations are applied to different electrical steels, and the data coming from the simulations are compared with those measured experimentally. The direct and inverse Jiles–Atherton models, including the introduction of the dissipative factor approach, are presented, and their limitations are proposed and validated using the measurements of three non-grain-oriented materials. Only the measured major loop is used to identify the parameters of the Jiles–Atherton model. Furthermore, the direct and inverse Jiles–Atherton models were used to simulate the minor loops as well as the hysteresis cycles with direct component (DC) bias excitation. Finally, the simulation results are discussed and compared to measurements for each study case.

The paper indicates that both the direct and the inverse Jiles–Atherton model formulations provide a good agreement with the experimental data for the major loop representation; nevertheless, both models can not accurately predict the minor loops even when the modification approaches proposed in the literature were implemented.

The Jiles–Atherton model and its modifications are widely discussed in the literature; however, some limitations of the model and its modification in the case of the distorted current waveform are not completely highlighted. Furthermore, this paper contains an original discussion on the accuracy of the prediction of minor loops from distorted current waveforms, including DC bias.

This paper aims to look at the implementation of project-funded research governance and its potential to induce organisational learning on responsible research and innovation (RRI). This paper analysed what types of organisational learning and change can take place within organisations of an Europe-funded project and to what extent. This paper examined whether and how change occurs and how it is shaped and co-produced with other orderings.

The paper is based on materials and evidence collected while working on the internal evaluation of a Horizon 2020-funded project. Analysis of the results of the mixed methods evaluation design was used to characterise occurrences of organisational learning and change.

The authors identified different forms of learning (single-loop learning, double-loop learning, reflexive and reflective learning and situational learning). The extent of learning that could lead to long-lasting organisational change was limited. This was due to the project-based and organisational design, the key-based definition of RRI and the indeterminacy of what constitutes learning and change – both at the level of funding and performing the project. For organisational change to occur, the authors argue for governance mechanisms based on reflexive learning that consider a range of structural conditions and measures.

Organisational learning plays an important role in change processes, which has so far been given too little consideration concerning the governance and implementation of RRI through project-based funding. The authors argue for a restructuring of governance and funding mechanisms to create more space for reflexivity and learning.

This study aims to endeavor to shed light on the underlying causal mechanisms behind the failure of startups by examining the failure process in such organizations. To achieve this goal, the study conducted a comprehensive review of the literature on the definition of failure and its various dimensions, resulting in the compilation of a comprehensive list of causes of startup failure. Subsequently, the failure process was analyzed using a behavioral strategy approach that encompasses rationality, plasticity and shaping, as well as the growth approach of startups based on dialectic, teleology and evolution theories.

The proposed research methodology was a case study using process tracing, with the sample being a failed platform in the ride-hailing technology sector. The causal mechanism was further explicated through the combined application of the behavioral strategy approach and interpretive structural modeling analysis.

The findings of the study suggest that the failure of startups is a result of interlinked causes and effects, and growth in these organizations is driven by dialectic, teleology and evolution theories.

The outcomes of the research can assist startups in formulating an effective strategy to deliver the right value proposition to the market, thereby reducing the chances of failure.

Studies have shown that higher education institutions (HEIs) need to achieve deep organizational learning to develop and implement long-term strategies for responding to the climate crisis. This study aims to analyze the sustainability efforts of HEIs, in particular those who use the sustainability tracking, assessment and rating system (STARS), to ascertain what type of organizational learning is being achieved.

This paper does this by analyzing perceptions of learning amongst this group of HEIs. More specifically, it analyzes survey data regarding perceptions of types and system levels of organizational learning achieved by 116 HEIs in the USA that currently use or have used STARS in the past. The approach also aims to develop a macro view of the relationships between practicing campus sustainability, using sustainability reporting tools and learning as an organization.

An examination of the practice of campus sustainability and its relationship to organizational learning reveals that the use of sustainability reporting promotes broad learning, but deep learning at the level of the organization is seldom achieved.

Given the success of using sustainability reporting tools to diffuse knowledge and foster broad learning, this paper argues that such tools should incorporate more metrics relative to soft organizational characteristics of HEIs to shift organizational cultures and foster deeper organizational learning.

This work constitutes one of the few studies analyzing empirical data on campus sustainability, sustainability reporting and organizational learning for a large number of HEIs.

Effective safety supervision plays a crucial role in ensuring safe production within coal mines. Conventional coal mine safety supervision (CMSS) in China has suffered from the problems of power-seeking, excessive resource consumption and poor timeliness. This paper aims to explore the Internet+ CMSS mode being emerged in China.

The evolution of CMSS systems underwent comprehensive scrutiny through a blend of qualitative and quantitative approaches. First, evolutionary game theory was used to analyze the necessity of incorporating Internet+ technology. Second, a system dynamics model of Internet+ CMSS was crafted, encompassing a system flow diagram and equations for various variables. The model was subsequently simulated by taking the W coal mine in Shanxi Province as a representative case study.

It was revealed that the expected safety profit from the Internet+ mode is 296.03% more than that from the conventional mode. The precise dissemination of law enforcement information was identified as a pivotal approach through which the Internet+ platform served as a conduit to foster synergistic collaboration among diverse elements within the system.

The outcomes of this study not only raise awareness about the potential of Internet+ technology in safety supervision but also establish a vital theoretical foundation for enhancing the efficacy of the Internet+ CMSS mode. The significance of these findings extends to fostering the wholesome and sustainable progress of the coal mining industry.

This research stands out as one of the limited studies that delve into the influence of Internet+ technology on CMSS. Building upon the pivotal approach identified, to the best of authors’ knowledge, a novel “multi-blind” working mechanism for Internet+ CMSS is introduced for the first time.

The purpose of this paper is that the modular mobile robots reformed the multimachine joint mode to achieve obstacle-crossing, climbing and other multifunctional inspection in unstructured environment under the connection of the cone–hole docking mechanism.

An arc-shaped docking cone head with a posture-maintaining spring and two arc-shaped connecting rods that formed a ring round hole were designed to achieve large tolerance docking. Before active locking, the coordination between structures was used to achieve passive locking, which mitigated the docking impact of modular robots in unstructured environment. Using the locking ring composed of the two arc-shaped connecting rods, open-loop and closed-loop motion characteristics were obtained through the mutual motion of the connecting rod and the sliding block to achieve active locking, which not only ensured high precision docking, but also achieved super docking stability.

The cone–hole docking mechanism had the docking tolerance performance of position deviation of 6mm and pitch deviation of 8° to achieve docking of six degrees of freedom (6-DOF), which had a load capacity of 230 N to achieve super docking stability. Under the connection of the cone–hole docking mechanism, the modular mobile robots reformed the multimachine joint mode to achieve obstacle-crossing, climbing and other multifunctional inspection in unstructured environment.

Based on mechanical analysis of universal models, a cone–hole docking mechanism combining active and passive functions, six-dimensional constraints could be implemented, was proposed in this paper. The characteristics of the posture-maintaining spring in the cone docking head and the compression spring at the two ends of two arc-shaped connecting rods were used to achieve docking with large tolerance. Passive locking and active locking modules were designed, mitigating impact load and the locking did not require power to maintain, which not only ensured high precision docking, but also achieved super docking stability.

This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we conducted an analysis spanning 1958 to 2023, sourcing data from Scopus. This research focuses on key terms such as cybernetics, cybernetics systems, complex adaptive systems, viable system models (VSM), agent-based modeling, feedback loops and complexity systems.

The analysis leveraged R Studio’s biblioshiny function to perform bibliometric mapping. Keyword searches were conducted within titles, abstracts and keywords, targeting terms central to cybernetics. The timespan, 1958–2023, provides a comprehensive overview of the evolution of cybernetics-related literature. The data were extracted from Scopus to ensure a robust and widely recognized source.

The results revealed a rich and interconnected global research network in cybernetics. The word cloud analysis highlights prominent terms such as “agent-based modeling,” “complex adaptive systems,” “feedback loop,” “viable system model” and “cybernetics.” Notably, the journal Kybernetes has emerged as a focal point, with significant citations, solidifying its position as a key source within the cybernetics research domain. The bibliometric map provides visual clarity regarding the relationships between various concepts and their evolution over time.

This study contributes original insights by employing advanced bibliometric techniques in R Studio to map the cybernetics research landscape. The comprehensive analysis sheds light on the evolution of key concepts and the global collaborative networks shaping cybernetics research. The identification of influential sources, such as Kybernetes, adds value to researchers seeking to navigate and contribute to the dynamic field of cybernetics. Furthermore, this study highlights that cybernetics not only provides a useful framework for understanding and managing major economic shocks but also offers perspectives for understanding phenomena in various fields such as economics, medicine, environmental sciences and climate change.