An electrolytic process for the removal of Zn(II) from aqueous solution using a parallel amalgamated copper screens cathode operated in the flow through mode is proposed. The current-potential curves recorded at a rotating amalgamated copper disc electrode were used to determine diffusion coefficient of Zn(II). The performance of electrolytic reactor was investigated by using different flow rates at initial zinc ion concentration(48 mg/L). Taking into account the residential Zn(II) concentration, the best results were obtained for cathode potential of (-1.35 V vs. SCE) at flow rate (320 L/h). Zinc ion concentration was found to decrease from 48 mg/L to 1 mg/L during 120 min. of electrolysis. The experimental data are well correlate

In this research, the removal of cadmium (Cd) from simulated wastewater was investigated by using a fixed bed bio-electrochemical reactor. The effects of the main controlling factors on the performance of the removal process such as applied cell voltage, initial Cd concentration, pH of the catholyte, and the mesh number of the cathode were investigated. The results showed that the applied cell voltage had the main impact on the removal efficiency of cadmium where increasing the applied voltage led to higher removal efficiency. Meanwhile increasing the applied voltage was found to be given lower current efficiency and higher energy consumption.  No significant effect of initial Cd concentration on the removal efficiency of cadmium b

In this paper, the ability of using corn leaves as low-cost natural biowaste adsorbent material for the removal of Indigo Carmen (IC) dye was studied. Batch mode system was used to study several parameters such as, contact time (4 days), concentration of dye (10-50) ppm, adsorbent dosage (0.05-0.25) gram, pH (2-12) and temperature (30-60) ^oC. The corn leaf was characterized by Fourier-transform infrared spectroscopy device before and after the adsorption process of the IC dye and scanning electron microscope device was used to find the morphology of the adsorbent material. The experimental data was imputing with several isotherms where it fits with Freundlich (R² = 0.9

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

Background: Atrioventricular nodal reentrant tachycardia (AVNRT) is the commonest regular supraventricular tachyarrhythmia. Ablation in the area of slow pathway (SP) has been successfully implemented in every day clinical electrophysiological practice for more than 20 years. Although the procedure is generally regarded as effective and safe, data on long-term effects and predictors of success or failure are incomplete.

Extended calculations for sputtering yield through bombed Nickel – target by Xenon ions plasma are accomplished. The calculations include changing the input parameters: the energy of xenon ions plasma, the hit target angle of nickel target, thickness of the nickel target layer, and the slight change in the surface binding energy of Nickel. The program TRIM is used to accomplish these calculations. The results show that the sputtering yields directly dependent on these parameters. The change in angles of incidence plasma ions and energy leads to a significant change in the sputtering yields. On the other hand, the sputtering yields ore highly affected by changing target width and surface binding energy at fixed ion parameters.