Adsorption capacity of a waste biomass, date stones, for phenolic compounds such as phenol (Ph) and p-nitro phenol (PNPh) was investigated. The characteristics of such waste biomass were determined and found to have a surface area and iodine number of 495.71 m²/g and 475.88 mg/g, respectively. The effects of temperature, initial sorbate concentration, and contact time on the adsorption process were studied. Experimental equilibrium data for adsorption of Ph and PNPh on date stones were analyzed by the Langmuir, Freundlich and Sips isotherm models. The results show that the best fit was achieved with the Sips isotherm equation with maximum adsorption capacities of 147.09 and 179.62 mg/g for Ph and PNPh, respectively. The kinetic data wer

The simulation of passively Q-switching is four non – linear first order differential equations. The optimization of passively Q-switching simulation was carried out using the constrained Rosenbrock technique. The maximization option in this technique was utilized to the fourth equation as an objective function; the parameters, γa, γc and β as were dealt with as decision variables. A FORTRAN program was written to determine the optimum values of the decision variables through the simulation of the four coupled equations, for ruby laser Q–switched by Dy +2: CaF2.For different Dy +2:CaF2 molecules number, the values of decision variables was predicted using our written program. The relaxation time of Dy +2: CaF2, used with ruby was

This article introduces a novel procedure to detect an approximate solution to Fredholm fractional integro-differential equations with linear type (LFFIDE) defined using Caputo fractional derivative. The new procedure approximates the solution using three types of polynomials: Laguerre polynomials, Hermite polynomials, and Legendre polynomials, thereafter transforming the problem into a linear programming problem. The approximate solutions are compared using testing examples to examine the efficiency of the suggested approach. Also, a comparison with the other methods using the same polynomials illustrates The effectiveness and consistency of the proposed technique. Finally, the error analysis of the proposed technique and convergent are di

    Synthesis of 2-mercaptobenzothiazole (A₁) is performed from the reaction of  o-aminothiophenol and carbon disulfide CS₂ in ethanol under basic condition. Compound (A₁)  is reacted with chloro acetyl chloride to give compound (A₂). Hydrazide acid compound (A₃) is obtained from the reaction of compound (A₂) with  hydrazine hydrate in ethanol under reflux in the presence of glacial acetic acid .The reaction of hydrazide acid compound (A₃) with ethyl acetoacetate gives pyrazole compound (A₄). The new hydrazone  compound (A₅) was prepared from the reaction of compound (A₃) with  benzaldehyde. Reaction of compound

Mefenamic acid (MA) is one of the non-steroidal anti-inflammatory drugs, it is widely used probably due to having both anti-inflammatory and analgesic activity, the main side effects of mefenamic acid include gastrointestinal tract (GIT) disturbance mainly diarrhea, peptic ulceration, and gastric bleeding. The analgesic effects of NSAIDs are probably linked to COX-2 inhibition, while COX-1 inhibition is the major cause of this classic adverse effects. Introduction of thiazolidinone may lead to the increase in the bulkiness leads to the preferential inhibition of COX-2 rather than COX-1 enzyme. The study aimed to synthesize derivatives of mefenamic acid with more potency and to decrease the drug's potential side effects, new series of 4-t

It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in

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