Environmentally friendly copper oxide nanoparticles (CuO NPs) were prepared with a green synthesis route via Anchusa strigosa L.  Flowers extract. These nanoparticles were further characterized by FTIR, XRD and SEM techniques. Removing of Gongo red from water was applied successfully by using synthesized CuO NPs which used as an adsorbent material. It was validated that the CuO NPs eliminate Congo red by means of adsorption, and the best efficiency of adsorption was gained at pH (3). The maximum adsorption capacity of CuO NPs for Congo red was observed at (35) mg/g. The equilibrium information for adsorption have been outfitted to the Langmuir, Freundlich, Temkin and Halsey adsorption isot

The investigation of determining solutions for the Diophantine equation  over the Gaussian integer ring for the specific case of  is discussed. The discussion includes various preliminary results later used to build the resolvent theory of the Diophantine equation studied. Our findings show the existence of infinitely many solutions. Since the analytical method used here is based on simple algebraic properties, it can be easily generalized to study the behavior and the conditions for the existence of solutions to other Diophantine equations, allowing a deeper understanding, even when no general solution is known.

Biologically active natural compounds are molecules produced by plants or plant-related microbes, such as endophytes. Many of these metabolites have a wide range of antimicrobial activities and other pharmaceutical properties. This study aimed to evaluate (in vitro) the antifungal activities of the secondary metabolites obtained from Paecilomyces sp. against the pathogenic fungus Rhizoctonia solani. The endophytic fungus Paecilomyces was isolated from Moringa oleifera leaves and cultured on potato dextrose broth for the production of the fungal metabolites. The activity of Paecilomyces filtrate against the radial growth of Rhizoctonia solani was tested by mixing the filtrate with potato dextrose agar medium at concentrations of 15%,

     Background subtraction is the dominant approach in the domain of moving object detection. Lots of research has been done to design or improve background subtraction models. However, there are a few well-known and state-of-the-art models that can be applied as a benchmark. Generally, these models are applied to different dataset benchmarks. Most of the time, choosing an appropriate dataset is challenging due to the lack of dataset availability and the tedious process of creating ground-truth frames for the sake of quantitative evaluation. Therefore, in this article, we collected local video scenes of a street and river taken by a stationary camera, focusing on dynamic background challenges. We presented a new technique for creati