Combining different treatment strategies successively or simultaneously has become recommended to achieve high purification standards for the treated discharged water. The current work focused on combining electrocoagulation, ion-exchange, and ultrasonication treatment approaches for the simultaneous removal of copper, nickel, and zinc ions from water. The removal of the three studied ions was significantly enhanced by increasing the power density (4–10 mA/cm2) and NaCl salt concentration (0.5–1.5 g/L) at a natural solution pH. The simultaneous removal of these metal ions at 4 mA/cm2 and 1 g NaCl/L was highly improved by introducing 1 g/L of mordenite zeolite as an ion-exchanger. A remarkable removal of heavy metals was reported, as the initial concentration of each metal decreased from approximately 50 ppm to 1.19 for nickel, 3.06 for zinc, and less than 1 ppm for copper. In contrast, ultrasonication did not show any improvement in the treatment process. The extended Langmuir isotherm model convincingly described the experimental data; the Temkin and Dubinin-Radushkevich isotherm models have proven that the removal processes were physical and exothermic. Finally, the pseudo-second-order kinetics model appropriately explained the kinetics of the process with correlation coefficients of 0.9337 and 0.9016, respectively.
An agricultural waste (walnut shell) was undertaken to remove Cu(II) from aqueous solutions in batch and continuous fluidized bed processes. Walnut shell was found to be effective in batch reaching 75.55% at 20 and 200 rpm, when pH of the solution adjusted to 7. The equilibrium was achieved after 6 h of contacting time. The maximum uptake was 11.94mg/g. The isotherm models indicated that the highest determination coefficient belongs to Langmuir model. Cu (II) uptake process in kinetic rate model followed the pseudo-second-order with determination coefficient of 0.9972. More than 95% of the Cu(II) were adsorbed on the walnut shells within 6 h at optimum agitation speed of 800 rpm. The main functional groups responsible for biosorption of
... Show MoreElectrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel. Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig
... Show MoreObjective: Dental caries is a chronic infectious disease that is prevalent worldwide in all age groups. Numerous attempts have been made to develop conservative approaches to halt caries progression and restore enamel defects. This study aimed to investigate the effect of applying grape seed extract and chicken eggshell extract on the microhardness of demineralized enamel in permanent teeth. Methods: Forty-eight sound upper first premolars were used. Following demineralization with the demineralizing solution for 96 hours, they were distributed into four groups consistent with the treatment agent used: group A was treated with casein phosphopeptide amorphous calcium phosphate (as a control group), group B was treated with grape se
... Show MoreBackground: Salvia officinalis is a plant belong to
Labiatae family .The common name of Salvia is sage
which mean save. The leaves of Salvia have special
oil which is effective against filamentous fungi and
yeasts such as Candida albicans which is the
causative agent of vaginal candidiasis in women
Methods. Cultures from 50 swabs of Candida
albicans isolated from vagina of 70 patient women
who complains from vaginal problems, their ages
(24-43) years from Central City Hospital during
Febreoury 2009 to April 2009 were cultured on
Sabouraud Dextrose Agar (SDA) .Nystatin was used
as positive reference standard to determine the
sensitivity of this fungus . and less this concentration
there was no min
Hydrogen sulfide removal catalyst was prepared chemically by precipitation of zinc bicarbonate at a controlled pH. The physical and chemical catalyst characterization properties were investigated. The catalyst was tested for its activity in adsorption of H2S using a plant that generates the H2S from naphtha hydrodesulphurization and a unit for the adsorption of H2S. The results comparison between the prepared and commercial catalysts revealed that the chemical method can be used to prepare the catalyst with a very good activity.
It has observed that the hydrogen sulfide removal over zinc oxide catalyst follows first order reaction kinetics with activation energy of 19.26 kJ/mole and enthalpy and e
... Show MoreThis paper aims to find new analytical closed-forms to the solutions of the nonhomogeneous functional differential equations of the nth order with finite and constants delays and various initial delay conditions in terms of elementary functions using Laplace transform method. As well as, the definition of dynamical systems for ordinary differential equations is used to introduce the definition of dynamical systems for delay differential equations which contain multiple delays with a discussion of their dynamical properties: The exponential stability and strong stability
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for