Polymer electrolytes were prepared using the solution cast technology. Under some conditions, the electrolyte content of polymers was analyzed in constant percent of PVA/PVP (50:50), ethylene carbonate (EC), and propylene carbonate (PC) (1:1) with different proportions of potassium iodide (KI) (10, 20, 30, 40, 50 wt%) and iodine (I₂) = 10 wt% of salt. Fourier Transmission Infrared (FTIR) studies confirmed the complex formation of polymer blends. Electrical conductivity was calculated with an impedance analyzer in the frequency range 50 Hz–1MHz and in the temperature range 293–343 K. The highest electrical conductivity value of 5.3 × 10^-3 (S/cm) was observed for electrolytes with 50 wt% KI concentration at room

In this research two series of the new derivatives of Trimethoprim and paracetamol drugs have been prepared which known as a high medicinal effectiveness. Series (A) is including the interaction of diazonium salt of trimethoprim and coupling with some substituted phenol compounds (2-amino phenol, 3-ethyl phenol, 1-naphthol, 2-nitro phenol, Salbutamol). Series (B) is including the interaction coupling alkali solution of paracetamol with diazonium salt of some substituted aniline compounds (Benzedine, 2, 3-di chloro aniline, Trimethoprim, Anilinium chloride, 2-nitro- 4-chloro aniline).Chemical structures of all synthesized compounds were confirmed by UV-visible and FTIR spectroscopy.

Azadirachtin is a naturally occurring substance that belongs to an organic molecule class which is called tetranortriterpenoids. It is on of the most powerful plant derived insecticides known, its structure is similar to insect hormones called ecdysoncs (Molting Hormone), which control the process of metamorphosis. Azadirachtin has been isolated from fruits of Melia azedarach L. The structure of this compound was determined by spectral studies (IR spectra and GC Mass spectra) and denitrified by then layer chromotochraphy (TLC).

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

The need to constantly and consistently improve the quality and quantity of the educational system is essential. E-learning has emerged from the rapid cycle of change and the expansion of new technologies. Advances in information technology have increased network bandwidth, data access speed, and reduced data storage costs. In recent years, the implementation of cloud computing in educational settings has garnered the interest of major companies, leading to substantial investments in this area. Cloud computing improves engineering education by providing an environment that can be accessed from anywhere and allowing access to educational resources on demand. Cloud computing is a term used to describe the provision of hosting services