Adaptive optimization of natural coagulants using hybrid machine learning approach for sustainable water treatment.

The efficiency optimization methods for natural coagulants are often restricted due to non-scientific trial-and-error approaches. They are inaccurate in predicting the complex interactions of jet mixing parameters, coagulant dosage, and environmental conditions. To overcome these obstacles, this research paper proposes advanced hybrid models in machine learning to enhance flocculation efficiency.

Aggressive condylar resorption.

This article describes the clinical and radiographic findings in a patient with unilateral aggressive condylar resorption that was diagnosed as osteoarthritis. We present a comprehensive documentation of the clinical manifestations, the appearance on conventional and advanced imaging, and the histopathologic findings. We discuss the systematic approach to develop a differential diagnosis, with specific emphasis on osteoarthritis and idiopathic condylar resorption.