Universities play a key role in university-industry-government interactions and are important in innovation ecosystem studies. Universities are also expected to engage with industries and governments and contribute to economic development. In the age of artificial intelligence (AI), governments have introduced relevant policies regarding the AI-enabled innovation ecosystem in universities. Previous studies have not focused on the provision of a dynamic capabilities perspective on such an ecosystem based on policy analysis. This research work takes China as a case and provides a framework of AI-enabled dynamic capabilities to guide how universities should manage this based on China’s AI policy analysis. Drawing on two main concepts, which are the innovation ecosystem and dynamic capabilities, we analyzed the importance of the AI-enabled innovation ecosystem in universities with governance regulations, shedding light on the theoretical framework that is simultaneously analytical and normative, practical, and policy-relevant. We conducted a text analysis of policy instruments to illustrate the specificities of the AI innovation ecosystem in China’s universities. This allowed us to address the complexity of emerging environments of innovation and draw meaningful conclusions. The results show the broad adoption of AI in a favorable context, where talents and governance are boosting the advance of such an ecosystem in China’s universities.

The wealth of nations depends on the quality of their infrastructure. Often, however, infrastructure suffers from ineffective investments and poor maintenance. Proposed solutions, such as New Public Management or Public-Private Partnerships (PPPs) tend to develop into Politicians-Private Partnerships as politicians collude with private firms to exploit present and future tax-payers. Therefore, it is necessary to give citizens better control over collective decision making. While there is a significant economic literature on empowering citizens via decentralization and direct democratic institutions, the role of electoral rules has thus far been rather neglected. An interesting case in point is Switzerland, which is well known for its high-quality infrastructure, extensive decentralization, and direct democracy. However, this paper argues that there is an additional and previously neglected institution that moves Swiss politicians away from client politics towards better serving public interest: Switzerland’s unique electoral institutions which effectively combine proportional elections with multi-seat majority elections. We explain how these institutions work, how they enhance the relationships between citizens and public and private entities, and we argue that they could be implemented in other countries.

Japan’s investment in the domestic construction industry has fallen to less than half its peak in 1992. Given the country’s declining population, Japanese construction companies must go global to remain profitable. To what extent the Japanese government and Japanese companies can contribute to meeting the growing infrastructure needs in the region is unclear as Japanese companies have long been operating primarily in Japan. The Japanese government has in recent years passed a series of new laws that encourage private sector participation in financing, building and operating public infrastructure. Through involvement in such public projects, Japanese companies have developed the skills and technologies to build a variety of infrastructures that are resilient to natural disasters and adaptable to various geographical conditions and social and economic development. But the major challenge for Japanese companies is to transform their business model drastically from one that relies on the domestic market to one that contributes to the social and economic development of third countries.

In the domains of geological study, natural resource exploitation, geological hazards, sustainable development, and environmental management, lithological mapping holds significant importance. Conventional approaches to lithological mapping sometimes entail considerable effort and difficulties, especially in geographically isolated or inaccessible regions. Incorporating geological surveys and satellite data is a powerful approach that can be effectively employed for lithological mapping. During this process, contemporary RS-enhancing methodologies demonstrate a remarkable proficiency in identifying complex patterns and attributes within the data, hence facilitating the classification of diverse lithological entities. The primary objective of this study is to ascertain the lithological units present in the western section of the Sohag region. This objective will be achieved by integrating Landsat ETM⁺ satellite imagery and field observations. To achieve our objectives, we employed many methodologies, including the true and false color composition (FCC&TCC), the minimal noise fraction (MNF), principal component analysis (PCA), decoration stretch (DS), and independent component analysis (ICA). Our findings from the field investigation and the data presented offer compelling evidence that the distinct lithological units can be effectively distinguished. A recently introduced geology map has been incorporated within the research area. The sequence of formations depicted in this map is as follows: Thebes, Drunka, Katkut, Abu Retag, Issawia, Armant, Qena, Abbassia, and Dandara. Implementing this integrated technique enhances our comprehension of geological units and their impacts on urban development in the area. Based on the new geologic map of the study area, geologists can improve urban development in the regions by detecting building materials “aggregates”. This underscores the significance and potential of our research in the context of urban development.

Artificial intelligence (AI) has rapidly evolved, transforming industries and addressing societal challenges across sectors such as healthcare and education. This study provides a state-of-the-art overview of AI research up to 2023 through a bibliometric analysis of the 50 most influential papers, identified using Scopus citation metrics. The selected works, averaging 74 citations each, encompass original research, reviews, and editorials, demonstrating a diversity of impactful contributions. Over 300 contributing authors and significant international collaboration highlight AI’s global and multidisciplinary nature. Our analysis reveals that research is concentrated in core journals, as described by Bradford’s Law, with leading contributions from institutions in the United States, China, Canada, the United Kingdom, and Australia. Trends in authorship underscore the growing role of generative AI systems in advancing knowledge dissemination. The findings illustrate AI’s transformative potential in practical applications, such as enabling early disease detection and precision medicine in healthcare and fostering adaptive learning systems and accessibility in education. By examining the dynamics of collaboration, geographic productivity, and institutional influence, this study sheds light on the innovation drivers shaping the AI field. The results emphasize the need for responsible AI development to maximize societal benefits and mitigate risks. This research provides an evidence-based understanding of AI’s progress and sets the stage for future advancements. It aims to inform stakeholders and contribute to the ongoing scientific discourse, offering insights into AI’s impact at a time of unprecedented global interest and investment.

Gold nanoparticles (AuNPs) have been known to possess exceptional electric, biochemical, and optical characteristics and are ‘the topic of discussion’ these days, especially relating to the field of biomedicine. Several plants, bacteria, and fungi have been utilized for the generation of AuNPs, besides other physical and chemical methods. While some studies have been reported with gold nanoparticles, less are aimed at fungi and its optimization factors. These parameters can allow us to design AuNPs of our choice depending on the use. The present review focuses on and inspects AuNPs with green synthesis through fungus optimization parameters followed by applications, aiming specifically at their antibacterial activity. Their antibacterial characteristics can open new doors for the pharmaceutical industry in the future.