In a trend towards digital continuity, model-based systems engineering is becoming widely adopted for the design of complex systems, supporting system development from the very first stages. A narrow panel of methods and tools are available on the market; they offer different scopes and approaches, are more or less intuitive to follow, and are sometimes supported by tools. Among them, the Architecture Analysis & Design Integrated Approach (ARCADIA) is becoming popular and is gradually spreading in different industrial fields to model a wide variety of systems at different stages of their development and from different points of view. It is implemented using an open-source tool called Capella. Few feedback on its use in industrial settings have been published, while other feedback remains confidential. The goal of this paper is to analyze the interests and limitations of ARCADIA/Capella. To reach this goal, we experimented with ARCADIA/Capella in several projects and chose one to explain how the method and tool proceeded. In addition, we conducted a survey to obtain industrial feedback. As a result, the paper gives an overview of the relevance of ARCADIA/Capella in projects and of its usefulness, effectiveness, and adaptability in modeling different types of systems. It also provides some perspectives for the evolution of the method and the tool according to industrial feedback.

During the outbreak of the COVID-19 (2019 coronavirus disease), misinformation related to the virus spread rapidly online and have led to serious difficulties in controlling the disease. The term infodemic is coined to outline the bad effect from the extensive dissemination of misinformation during the outbreak. With regards to this phenomenon, the World Health Organization emphasized the need to fight against infodemic and asked all countries not only to make efforts in slowing down the spread of the COVID-19 but also in countering the risk caused by infodemic. Due to its negative impact, this paper analyzes infodemic on Chinese social media at the initial stage of the COVID-19 outbreak and presents a 4P framework standing for the four features of Chinese infodemic: Prevention Attention, Problem Orientation, Patterns Interaction and Points Globalization. Furthermore, a selective review of existing datasets in the neural networks domain is synthesized based on the 4P framework. Finally, research directions, including recommendations, about constructing a large-scale dataset for Chinese infodemic automatic detection are proposed.

With the growing economic pressure, one lever for companies to be competitive is to efficiently monitor projects. To this goal, the different processes involved in the project must be carefully supervised and the project manager needs to be well-informed on their state and progress to take the best decisions thanks to accurate performances of indicators, process, and project. Another key factor of successful decision-making in engineering projects beyond taking into account information from the project manager on the project management (PM) is to consider information from the systems engineer on the product development. This paper proposes a process to monitor engineering projects relying on a set of project performance indicators that integrate the views of both project manager and systems engineer. This process includes three main activities: 1) defining project performance indicators related to the processes described by international guides and standards; 2) valuating and weighting these indicators by consulting project managers and systems engineers; and 3) constructing a hierarchical framework of indexes to support project monitoring. This proposal thus refers to the practices described in PM and systems engineering norms and improves them by involving project managers and systems engineers into decision-making, with the goal to take more coherent decisions.

Nowadays, because of the increasing complexity of systems and projects, more and more people focus on the systems of systems. At the same time, Systems Engineering and Project Management are considered as two independent activities during the development of systems of systems, but many inconsistencies appear between Systems Engineering and Project Management teams during engineering projects although their relationships is needed to be integrated as they get involved in large scale systems of systems. For the most part, these inconsistencies are due to a not close enough coordination and sometimes a lack of communication. As a result, there is a great need for international companies to understand the standards or guides from both domains to better integrate them and enhance their chances of success. Although numerous Systems Engineering and Project Management standards or guides have been published to help people get better organized and improve the quality of products or services, a lot of their projects still fail due to the poor integration of both domains. At the same time, the number of small and medium enterprises has quickly increased because the social division of labor is becoming more and more meticulous with the rapid development of the science and technology. The ability for small and medium enterprises to analyze and apply the Systems Engineering and Project Management standards or guides is not the same as for international companies, due to their limited resources. So the aim of this paper is to select two references from the most frequently used standards or guides in Systems Engineering and Project Management domains, the ISO/IEC 15288 and the PMBoK, and to illustrate how to help the systems engineers and project managers to compare and align the references from both domains quickly and effectively.

This study examines the regional co-funding network as a novel framework for advancing high-quality fundamental research amid systemic reforms in science funding. Based on provincial joint funding data from Mainland China retrieved via the WoS-SCIE and SSCI databases (2013–2022), an interprovincial co-funding network was constructed. Social network analysis, kernel density estimation, and fixed-effects regression analysis were employed to explore the evolution of regional location advantages and their impact on technological innovation. The findings reveal that the co-funding network has become increasingly balanced over time, significantly enhancing the location-based innovation advantages of individual provinces and strengthening the network’s overall capacity to foster innovation. This improved equilibrium has positively influenced regional scientific output, demonstrating that a province’s position within the co-funding network—particularly its individual location advantage—plays a pivotal role in advancing technological progress. However, persistent disparities in regional collaboration and development remain, underscoring the need for more coordinated strategies to address uneven growth dynamics. By introducing the co-funding network as an analytical lens, this study uncovers the hidden channels of resource synergy and their influence on regional innovation. The results provide actionable insights for optimizing co-funding mechanisms and enhancing interprovincial collaboration to maximize innovation potential in China.