This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.

This review paper delves into the intricate landscape of the digital economy, focusing on the multifaceted interplay between innovation, competition, and consumer dynamics. It investigates the transformative impact of digital technologies on market structures and consumer behaviors, spanning areas such as e-commerce, online publishing, taxation, and big data challenges. By analyzing network effects, market concentration, and the influence of key players like Google and Amazon, this study draws on insights from previous research. Furthermore, it examines evolving regulations with an emphasis on consumer protection, competition law, and privacy concerns. Through a comprehensive exploration of the digital ecosystem, this paper offers a nuanced understanding of how businesses, consumers, and policymakers navigate the complexities of the digital marketplace.

The prospects of digital infrastructure in promoting rural economic growth and development are by and large immense. The paper found that rural development is considerably important for economic development and for achievement of sustainable livelihoods that increases people’s ability to achieve good health and wellbeing that enable the achievement of sustainable development. The paper found that digital imbalance and digital illiteracy in the rural areas hinder implementation of digital infrastructure to lead to rural economic growth. Digital infrastructure is the source of economic opportunities that enables local people in the rural areas to be more creative in achieving development success. It enables them to have a unique sense of place and fashioning of vibrant economic and financial opportunities that ensure the achievement of sustainable rural economic development. However, the paper found that the application of digital infrastructure to South Africa’s rural areas in the bid to promote rural economic growth has been hindered by factors like the digital divide, financial constraints, digital illiteracy and the failure to own a smart phone. These factors hinder digital infrastructure from leading to sustainable rural economic development and growth. The paper used secondary data gathered from existing literature. The use of qualitative research methodology and document and content analysis techniques became vital in the process of collecting and analyzing collected data.

The Three Kingdoms period of ancient China (208-280 AD) refers to the period  between Eastern Han (25–220 AD) and Jin dynasties (266–420), during which China was divided into Shu (221-263 AD), Wei  (220-266 AD) and Wu (222-280 AD) kingdoms, and then united as Jin dynasty. This paper constructs the quarterly series of alliance structures between the Three Kingdoms. By collecting and analyzing a total of two hundred and eighty-nine quarterly observations, the paper shows that the three most frequent alliance structures are ρ0: 1) the finest partition or no-alliance structure with 192 partitions; 2) Three partitions with Shu-Jin alliance and Wu singletion with 57 partions; 3) Wei-Wu alliance and one singletion Shu with 12 partions. It also shows that the observed changes in alliance structures were the consequence of a total of fifteen major battles fought by the three kingdoms. Such results serve as a contribution to the studies of applied game theory, alliance study, and the economic and military histories in ancient China.

With the implementation of the rural revitalization strategy, rural wisdom pension gradually becomes an important direction for the development of rural society. The purpose of this paper is to study the optimization path of rural smart pension in the context of rural revitalization. By analyzing the definition, development status and dilemma of rural wisdom pension, key factors for optimizing rural wisdom pension are proposed, and the paths for enhancing rural wisdom pension are discussed. The research results show that strengthening infrastructure construction, improving service quality, and promoting information technology application are the key paths to realize rural smart aging. This study provides theoretical guidance and policy recommendations for the implementation of rural smart aging.

The proposed research work encompasses implications for infrastructure particularly the cybersecurity as an essential in soft infrastructure, and policy making particularly on secure access management of infrastructure governance. In this study, we introduce a novel parameter focusing on the timestamp duration of password entry, enhancing the algorithm titled EPSBalgorithmv01 with seven parameters. The proposed parameter incorporates an analysis of the historical time spent by users entering their passwords, employing ARIMA for processing. To assess the efficacy of the updated algorithm, we developed a simulator and employed a multi-experimental approach. The evaluation utilized a test dataset comprising 617 authentic records from 111 individuals within a selected company spanning from 2017 to 2022. Our findings reveal significant advancements in EPSBalgorithmv01 compared to its predecessor namely EPSBalgorithmv00. While EPSBalgorithmv00 struggled with a recognition rate of 28.00% and a precision of 71.171, EPSBalgorithmv01 exhibited a recognition rate of 17% with a precision of 82.882%. Despite a decrease in recognition rate, EPSBalgorithmv01 demonstrates a notable improvement of approximately 14% over EPSBalgorithmv00.