APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR PREDICTING pH IN SEAWATER ALONG GAZA BEACH

Coastal water issues are gaining worldwide attention because of their impact on health and other environmental problems. This article is concerned with the comparison between artificial neural networks and statistical methods to predict the degree of acidity (pH) in the coastal waters along the Gaza beach. Multilayer perceptron (MLP) and radial basis function (RBF) neural networks are trained and developed with reference to three parameters (water temperature, wind velocity, and turbidity) to predict the level of pH in the seawater. Both networks were developed using the combination of the data collected from nine sites over a period of 4 years, including 294 samples for training and 90 samples for testing the performance of models. The results show that the MLP and RBF models have good ability to predict the pH level. Each network's performance was tested with different sets of data, and the results show satisfactory performance. Results of the developed networks were compared with the statistical regression method and found that the predictions of neural networks are better than the conventional methods. Predictions result show that artificial neural networks approach have good ability for the modeling of pH level in the coastal waters along Gaza beach. It is hoped that neural networks will prove to be a promising alternative to traditional methods used and can contribute in the improvement of the quality of seawater.     

A High Performance of ENi–P Coatings on Mechanical and Tribological Properties with Influence of Bath pH on AZ91 Magnesium Alloy

Electroless nickel–phosphorus (ENi–P) coating was carried out on AZ91 magnesium alloy substrates by varying the bath solutions pH. The ENi–P coating process was carried out with sodium hydroxide as the pH adjuster. The effect of bath pH values on surface characteristics and wear resistance properties were investigated after deposition on AZ91 magnesium alloy substrates. Three suitable bath compositions with different pH were prepared for coating the substrates. Encouraging results for ENi–P deposit were obtained when the bath pH value was maintained at 6.5. A smooth and uniform microstructure was observed in the deposit obtained from bath B (6.5 pH). It also enhanced the microhardness and wettability, while the surface roughness of the ENi–P deposit reduced considerably, thereby resulting in better wear resistance and also preventing regular or early failures, and improving service life.     

Electrical transport properties of Eu2Ti2O7 single crystal

The electrical conductivity, thermoelectric power and dielectric constant of Eu₂Ti₂O₇ single crystal have been studied in the temperature range 300–1000 K. Eu₂Ti₂O₇ is found to be a n-type semiconductor with energy band gap of 2.5 eV. The compound exhibits an extrinsic nature upto 700 K and intrinsic nature above 700 K. Thermoelectric power decreases with temperature in the region 300–700 K whereas it increases with temperature in the region 700–1000 K. Dielectric constant increases with temperature in the entire temperature range studied with a discontinuity atT 700 K.     

Inhibitive effect of FA derivatives on mild steel corrosion in the presence of formic acid

The influence of selected long-chain FA hydrazides and thiosemicarbazides on the corrosion inhibition of mild steel in the presence of 20% formic acid was studied. The inhibition efficiency of these compounds varied with concentration, temperature, and immersion time. All the FA derivatives in the formic acid solution followed Temkin's adsorption isotherm. The activation energies and free energies of adsorption of all the hydrazides and thiosemicarbazides also were calculated. Potentiodynamic polarization studies indicated that all the tested compounds were of mixed type. Electrochemical impedance spectroscopy was also used to investigate the mechanism of corrosion inhibition.     

Fire Behavior of Alternate Building Materials—Part I—RMP

Polymers are fast replacing the conventional building materials, mainly because of their scarcity and attractive properties. However, users are hesitant to accept these alternate building materials as the polymers are considered to be associated with fire hazards. Red mud plastics (RMP) is one such polymer which is finding acceptance albeit slowly. Fire behaviour of RMP is discussed and compared with some conventional materials with a view to present it as a viable alternate.     

Removal of lead, cadmium, zinc, and copper from industrial wastewater by carbon developed from walnut, hazelnut, almond, pistachio shell, and apricot stone

In this work, adsorption of copper (Cu), zinc (Zn), lead (Pb), and cadmium (Cd) that exist in industrial wastewater onto the carbon produced from nutshells of walnut, hazelnut, pistachio, almond, and apricot stone has been investigated. All the agricultural shell or stone used were ground, sieved to a defined size range, and carbonized in an oven. Time and temperature of heating were optimized at 15 min and 800 degrees C, respectively, to reach maximum removal efficiency. Removal efficiency was optimized regarding to the initial pH, flow rate, and dose of adsorbent. The maximum removal occurred at pH 6-10, flow rate of 3 mL/min, and 0.1g of the adsorbent. Capacity of carbon sources for removing cations will be considerably decreased in the following times of passing through them. Results showed that the cations studied significantly can be removed by the carbon sources. Efficiency of carbon to remove the cations from real wastewater produced by copper industries was also studied. Finding showed that not only these cations can be removed considerably by the carbon sources noted above, but also removing efficiency are much more in the real samples. These results were in adoption to those obtained by standard mixture synthetic wastewater.