Local scour, a complex phenomenon in river flows around piers with movable beds, can damage bridge piers during high floods. Predicting scour depth accurately is vital for safety and economic reasons, especially for large bridges. This study using hydraulic flume laboratory experiments compared diamond, square, and elliptical pier models of different sizes under steady clear-water conditions considering different flow rates and discharge levels to identify the most efficient shape with less local scour. Local scour, a complex phenomenon in three-dimensional flow around piers in rivers with movable beds, can lead to detrimental effects on bridge piers due to high flood velocities. Accurate prediction of scour depth is crucial for economic and safety reasons, especially for large bridges with complex piers. Hydraulic engineers are keen on forecasting the equilibrium scour depth. To achieve this, laboratory testing compared diamond, square, and elliptical pier models under steady clear-water conditions to identify the most efficient pier shape with less local scour. This research provides valuable insights for optimizing pier design to enhance bridge stability and resilience against scour-induced risks. A variety of configurations, including different sizes and shapes of piers were experimented with in the flume using diamond, square, and elliptical shapes. The test results showed that the local scour depth around elliptical piers was around 29.16% less, and around diamond piers, it was approximately 16.05% less compared to the scour depth observed around square piers with the same dimensions. The researchers also observed distinct patterns of scouring around different pier shapes. Specifically, the square-shaped piers displayed the highest level of scouring depth, that is, 48 mm, followed by the diamond-shaped pier which experienced a scouring depth of 48 mm while the elliptical-shaped piers experienced the least amount of scouring depth, that is, 34 mm. The test results also demonstrated that pier size significantly influences scouring, with an increase in pier size from 3 × 3 cm2 to 5 × 5 cm2 leading to a rise in scour depth by 26.04%. Moreover, this study findings also elucidated that an increase in flow results in an increase of in scouring depth i.e., elevating the discharge from 0.0026 cumecs to 0.0029 cumecs led to a 28.13% increase in scouring depth for the identical pier size. These findings provide valuable insights into the hydraulic behavior of various pier shapes and can aid in the optimization of bridge design and hydraulic engineering practices. The investigations further revealed that local scouring is sensitive not only to pier dimensions but also to other critical parameters, including flow rate, time of exposure, and the size of a pier.

This bibliometric review evaluates the research progress and knowledge structure regarding the impact of supporting facilities on halal tourism development. Using the Scopus database and bibliometric analysis with the “bibliometrix” package in R, the study covers the period from 2016 to 2023. The search, employing keywords like “halal tourism,” “facilities,” “infrastructure,” and “local support,” identified 26 relevant publications. The findings highlight a limited body of research, with the Journal of Islamic Marketing being the most active publisher in this area, contributing six articles. Indonesia emerges as a leading contributor to halal tourism research, driven by its significant Muslim population and the economic potential of this niche market. Key facilities, such as mosques, musholla, and high-quality halal food options, are identified as crucial factors influencing Muslim travelers’ destination choices. This review provides a comprehensive overview of the current research landscape on supporting facilities in halal tourism and highlights opportunities for future investigation to further enrich the field.

China-Africa economic integration generally looks lucid, as evidenced by rising bilateral trade, as well as Chinese FDI, aid, and debt financing for infrastructure development in Africa. The engagement, however, appears to be strategically channeled to benefit China’s resource endowment strategy. First, Chinese FDI in Africa is primarily resource-seeking, with minimum manufacturing value addition. Second, China has successfully replicated the Angola model in other resource-rich African countries, and most infrastructure loans-for-natural resources barter deals are said to be undervalued. There is also a resource-backed loan arrangement in place, in which default Chinese loans are repaid in natural resources. Third, while China claims that its financial aid is critical to Africa’s growth and development processes, a significant portion of the aid is spent on non-development projects such as building parliaments and government buildings. This lend credence to the notion that China uses aid to gain diplomatic recognition from African leaders, with resource-rich and/or institutionally unstable countries being the most targeted. The preceding arguments support why Africa’s exports to China dominate other China’s financial flows to Africa, and consist mainly of natural resources. Accordingly, this study aims to forecast China-Africa economic integration through the lens of China’s demand for natural resources and Africa’s demand for capital, both of which are reflected in Africa’s exports to China. The study used a MODWT-ARIMA hybrid forecasting technique to account for the short period of available China-Africa bilateral trade dataset (1992–2021), and found that Africa’s exports to China are likely to decline from US$ 119.20 billion in 2022 to US$ 13.68 billion in 2026 on average. This finding coincides with a period in which Chinese demand for Africa’s natural resources is expected to decline.

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.

The development of the maize agribusiness system is highly dependent on the role of social capital in facilitating interaction among actors in the chain of activities ranging from the provision of farm supplies to marketing. Therefore, this research aimed to characterize the key elements of social capital specifically bonding, bridging, and linking, as well as to demonstrate their respective roles. Data were collected from farmers and non-farmers actors engaged in various activities in the maize agribusiness system. The data obtained were processed using ATLAS Ti, applying open, axial, and selective coding techniques. The results showed the roles played by bonding, bridging, and linking social capital in the interaction between farmers and multiple actors in activities such as providing farm supplies, farming production, harvesting, post-harvest, and marketing. The combination of these social capital forms acted as the glue and wires that facilitated access to resources, collective decision-making, and reduced transaction costs. These results have theoretical implications, suggesting that bonding, bridging, and linking should be combined with the appropriate role composition for each activity in the agribusiness system.

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.