This work comprises the synthesis of new thioxanthone derivatives containing C-substituted thioxanthone. To obtain these derivatives, the o-mercapto benzoic acid was chosen as the starting material, which was reacted with dry benzene in sulfuric acid (98 %) to produce the thioxanthone (1). The 2,7-(disulfonyl phosphine imine) thioxanthone (4-8) were prepared from reaction of compound (1) with chlorosulfonic acid gave 2,7-(disulfonyl chloride) thioxanthone (2). Treatment of (2) with sodium azide to produce 2,7-(disulfonyl azide) thioxanthone (3). Condensation of (3) with phosphorus compounds afforded compounds (4-8). The 2,7-(disulfonamide) thioxanthone (9-21) was obtained when co

Dual-species biofilms of Pseudomonas aeruginosa and Staphylococcus aureus generate difficult-to-treat illnesses. Nutrition stress in biofilms affects physiology, microbial metabolism, and species interactions, impacting bacteria growth and survival. Furthermore, the function of alginate, which is encoded by the algD gene, in the production of biofilms has been established. The present study aimed at investigating the impact of starvation on algD gene expression in single-species biofilm of P. aeruginosa and dual-species biofilms of P. aeruginosa and S. aureus from hospital sewage. A total of six P. aeruginosa and six S. aureus isolates were obtained from the microbiology laboratory at the Department of Biology, College of Science, Universit

composition,depiction,antibacterial,antioxidant,and cytotoxicity activities studies of a new nano-sized binuclear metal(||) schiff base complexes

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I