Assessment of water resources carrying capacity (WRCC) is of great significance for understanding the status of regional water resources, promoting the coordinated development of water resources with environmental, social and economic development, and promoting sustainable development. This study focuses on the Longdong Loess Plateau region and utilized panel data spanning from 2010 to 2020, established a three-dimensional evaluation index system encompassing water resources, economic, and ecological dimensions, uses the entropy-weighted TOPSIS model coupled with global spatial autocorrelation analysis (Global Moran’s I) and the hot spot analysis (Getis-Ord Gi* index) method to comprehensively evaluate the spatial distribution of the WRCC in the study region. It can provide scientific basis and theoretical support for decision-making on sustainable development strategies in the Longdong Loess Plateau region and other regions of the world.From 2010 to 2020, the overall WRCC of the Longdong Loess Plateau area show some fluctuations but maintained overall growth. The WRCC in each county and district predominantly fell within level III (normal) and level IV (good). The spatial distribution of the WRCC in each county and district is featured by clustering pattern, with neighboring counties displaying similar values, resulting in a spatial distribution pattern characterized by high carrying capacity in the south and low carrying capacity in the north. Based on these findings, our study puts forth several recommendations for enhancing the WRCC in the Longdong Loess Plateau area.

The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant interest in modern agriculture. The appeal of AI arises from its ability to rapidly and precisely analyze extensive and complex information, allowing farmers and agricultural experts to quickly identify plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant attention in the world of agriculture and agronomy. By harnessing the power of AI to identify and diagnose plant diseases, it is expected that farmers and agricultural experts will have improved capabilities to tackle the challenges posed by these diseases. This will lead to increased effectiveness and efficiency, ultimately resulting in higher agricultural productivity and reduced losses caused by plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has resulted in significant benefits in the field of agriculture. By using AI technology, farmers and agricultural professionals can quickly and accurately identify illnesses affecting their crops. This allows for the prompt adoption of appropriate preventative and corrective actions, therefore reducing losses caused by plant diseases.

Institutions of higher learning are crucial to sustainability. They play a crucial role in preparing the next generation of leaders who will successfully execute the Sustainable Development Goals of the United Nation. This research therefore intends to present a preliminary conceptual approach in examining how industrial revolution 4.0 (I.R. 4.0) technologies, and lean practices affect sustainability in South Africa’s Higher Education Institutions (HEIs). The study shall employ survey questionnaire to collect data from the employees of the institutions. This preliminary study reveals that hybrid IR 4.0 technologies and lean practices as enablers of sustainability has not gained enough attention in the HEIs. Existing literature show the important role plays by performance variance of lean practices to improve sustainable performance when deployed from industry to education sector. The report validates the HEI’s future course, which has been incorporating new technology into its services processes recently. Using the created items, researchers may utilize empirical analysis to look into the combined effects of lean practices and IR 4.0 technologies on sustainability in HEIs. The following conclusions may be drawn: HEIs are essential for the application of sustainability principles; curriculum focused on sustainability and culture change are critical for attitude development; and the political climate and stakeholder interests impact the implementation of sustainability.

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.

In this study, the entropy weight method, the α convergence model, the absolute β convergence model and the conditional β convergence model are used to evaluate the 31 provinces’ innovative potential in China from 2011 to 2022. It is found that the innovative potential in nationwide China and in various regions are all increasing year by year, and the innovative potential in the eastern region is obviously better than that in the central region and western region. No matter considering the influence of external factors or not, the gap of innovative potential among provinces in different regions will gradually expand over time, with the largest gap among provinces in the eastern region, followed by the central region and the smallest in the western region. The conclusion of this study is instructive to enhance the innovative potential of China and promote the balanced development of regional innovative potential in China.

The rise of digital communication technologies has significantly changed how people participate in social protests. Digital platforms—such as social media—have enabled individuals to organize and mobilize protests on a global scale. As a result, there has been a growing interest in understanding the role of digital communication in social protests. This manuscript provides a comprehensive bibliometric analysis of the evolution of research on digital communication and social protests from 2008 to 2022. The study employs bibliometric methodology to analyze a sample of 260 research articles extracted from the SCOPUS core collection. The findings indicate a significant increase in scholarly investigations about digital communication and its role in social protest movements during the past decade. The number of publications on this topic has increased significantly since 2012—peaking in 2022—indicating a heightened interest following COVID-19. The United States, United Kingdom, and Spain are the leading countries in publication output on this topic. The analysis underlines scholars employing a range of theoretical perspectives—including social movement theory, network theory, and media studies—to identify the relationship between digital communication and social protests. Social media platforms—X (Twitter), Facebook, and YouTube—are the most frequently studied and utilized digital communication tools engaged in social protests. The study concludes by identifying emerging topics relating to social movements, political communication, and protest, thereby suggesting gaps and opportunities for future research.