ABSTRACT The role of specific amino acids namely cysteine, methionine, threonine and asparagine in the protection provided by vamin solution against B-lactam inhibition to E. coli was evaluated in vitro. In minimal medium, Cells were treated with 32 ug/ml of penicillin G, carbencillin, hostacillin, cloxacillin and cephalotin in the presence of specific amino acid supplementations. Deletion of specific amino acids from the media abolished the protection provided by vamin. Threonine was essential for the protection of cells against all tested antibiotics, while cysteine was essential for protection against carbencillin and cephalotin Deletion of methionine or asparagine abolished the protec- tion against carbencillin and to a less extent ce

The role of specific amino acids namely cysteine, methionine, threonine and asparagine in the protection provided by vamin solution against B-lactam inhibition to E. coli was evaluated in vitro In minimal medium, cells were treated with 32 ug/ml of penicillin G, carbenciLlin, hostacillin, cloxacillin and cephalotin in the presence of specific amino acid supplementation. Deletion of specific amino acids from the media abolished the protection provided by vamin. Threonine was essential for the protection of cells against all tested antibiotics, while cysteine was essential for protection against carbencillin and sephalotin. Deletion of methionine or asparagine abolished the protection against carbencillin and to a less extent cephalotin.

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

One of the important units in Sharq Dijla Water Treatment Plant (WTP) first and second extensions are the alum solution preparation and dosing unit. The existing operation of this unit accomplished manually starting from unloading the powder alum in the preparation basin and ending by controlling the alum dosage addition through the dosing pumps to the flash mix chambers. Because of the modern trend of monitoring and control the automatic operation of WTPs due to the great benefits that could be gain from optimum equipment operation, reducing the operating costs and human errors. This study deals with how to transform the conventional operation to an automatic monitoring and controlling system depending on a Programmable

In this study, manganese dioxide (MnO₂) nanoparticles (NPs) were synthesized via the hydrothermal method and utilized for the adsorption of Janus green dye (JG) from aqueous solutions. The effects of MnO₂ NPs on kinetics and diffusion were also analyzed. The synthesized NPs were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FT-IR), with XRD confirming the nanoparticle size of 6.23 nm. The adsorption kinetics were investigated using three models: pseudo-first-order (PFO), pseudo-second-order (PSO), and the intraparticle diffusion model. The PSO model provided the best fit (R² = 0.999), indicating that the adsorpti