Antibiotics play an important role in disease treatment; however, they are also a threat to public health and the ecosystem. Therefore, a bimetallic CuCo-ZIFs catalyst was manufactured through the ultrasonic-assisted solvothermal method to activate H2O2 towards the removal of tetracycline (TC) in an aqueous environment, a polluting broad-spectrum antibiotic model. PXRD, SEM, TEM, EDX, TGA, FT-IR, and BET analyses indicated that CuCo-ZIFs cubic crystals were successfully synthesized with high crystallinity, large specific surface area, and ideal thermal stability. Factors affecting the TC removal were investigated, including CuCo-ZIFs dosage, H2O2 concentration, treatment time, initial TC concentration, and reaction temperature. The results showed that the CuCo-ZIFs/H2O2 catalytic system was capable of effectively handling TC, with about 93.9% of TC removed in the presence of 0.3 g.L-1 CuCo-ZIFs, 0.01 mol.L-1 H2O2 at room temperature within 30 min. Conclusively, this study contributes to expanding the application potential of bimetallic CuCo-ZIFs materials to eliminate antibiotic residues in an aqueous environment and inspire research on environmental improvement.

In Viet Nam's current traffic conditions, congestion and jams—especially at intersections during peak hours—present major challenges. Traditional traffic light systems, which rely on fixed timing principles, often fail to manage traffic flow efficiently, particularly when vehicle density varies significantly across different directions. This research aims to develop an intelligent traffic light system where the signal timings automatically adjust based on the vehicle density at intersections. The study uses an object recognition algorithm to identify, classify, and count vehicles. The data was then fed into a fuzzy logic model to calculate the optimal signal timings. Experimental results demonstrate an accuracy of approximately 88% in vehicle detection. The fuzzy logic model and the programmable logic controller were able to effectively compute reasonable signal timings based on real-time vehicle density. Future developments include expanding the system's functionalities, creating a user-friendly interface, and developing a management application for mobile devices.