The research aims to study the effect of adding (Li2O) to an alkaline glaze containing (K2O, Na2O). Although all the alkaline oxides have common properties, each oxide has something that distinguishes it. The molecular weight of (Li2O) is two times less than that of (Na2O) and three times that of (K2O). Therefore, it is added in small proportions. In addition, it is a very strong flux, so it is not used alone, but rather replaces a part of other alkaline oxides. It was added to an alkali glass that matured at a temperature of 980CO in proportions (2.0,1.4,1.2,0.8,0.4%) instead of (Na2O), using lithium carbonate (Li2CO3) as an oxide source. The glazes mixtures were applied to a white pottery body, and the samples were fired and cooled acc

The kinetics of nickel removal from aqueous solutions using a bio-electrochemical reactor with a packed bed rotating cylinder cathode was investigated. The effects of applied voltage, initial nickel concentration, the rotation speed of the cathode, and pH on the reaction rate constant (k) were studied. The results showed that the cathodic deposition occurred under mass transfer control for all values of the applied voltage used in this research. Accordingly, the relationship between concentration and time can be represented by a first-order equation. The rate constant was found to be dependent on the applied voltage, initial nickel concentration, pH, and rotation speed. It was increased as the applied voltage increased and decreased as t

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of