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

Electro coagulation treatment was used for zinc removal from electroplating wastewater of the State Company for Electrical Industries . This wastewater, here consists zinc ions with maximum concentration in solution of 90 ppm .

The parameters that influenced the wastewater treatment are: current density in the range  1-1.4 mA/cm2, pH  in the range 5-10, temperature in the range 25-45°C and time in the range 10-180 minute.

The research is a laboratory experimental type using batch system for electrical process with direct current. The cell comprised of aluminum electrode as anode and stainless steel electrode as cathode. Thirty experiments and one hundred fifty sample lab tests were carried out in this research

This study utilized low-cost agricultural waste (molasses production waste powder) to extract copper ions from aqueous solutions. The present investigation explored a range of factors that influence the adsorption process, including temperature, pH, ionic strength, contact time, quantity of adsorbent, and particle size. Spectrophotometric analysis was used to determine the solution's absorbance both before and after the adsorption procedure. The Langmuir and Freundlich adsorption models were used to match the equilibrium data. The Freundlich model was determined to be the best isotherm model using the linear regression coefficient R2=0.9868. Thermodynamic parameters, including enthalpy, entropy, and Gibbs free energy, were calculate

   In the present work, tetracycline (TC) was removed from a simulated wastewater through a new photo-anodic oxidation process with a rotating graphite cylinder anode. The effects of current density, pH, rotation speed, and NaCl addition were evaluated. The results confirmed that increasing the current density results in improving the removal of TC. However, increasing the current density beyond 5 mA/cm2 had little effect on TC removal. Results revealed that TC removal using photoanodic oxidation can be achieved at high performance with an initial pH of 5. Increasing or decreasing pH beyond this value has a negative effect on TC removal. Increasing rotation speed gave better performance for TC removal due to the increase in mass t

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

Abstract : A research was conducted to study the process parameters affecting hexavalent chromium Cr (VI) (carcinogenic compound) the removal percentage from the electrical industries company waste water that contain 88 mg/l of Cr (VI) concentration by adsorption onto tea wastes. Synthetic water with 88 mg/l Cr (VI) concentration was used. Several operation parameters affecting Cr (VI) removal efficiency were investigated, such as pH, initial Cr (VI) concentration, stirring time and tea wastes dose. The experimental results reveal that maximum Cr (VI) removal reached up to 94.26% at pH of 2, stirring time of 180 minute, tea wastes do