In this work the study mainly investigated the inhibition behavior, and the adsorption properties of different concentrations of an aqueous extraction of thyme plant range (5-20) ppm at the temperature range (288-318) K for corrosion of dental amalgam in artificial saliva, by applying electrochemical method. The result showed good inhibitive action for all thyme extract concentration with slight decreases by increasing temperature. The physisorption for thyme extract compound on the surface of dental amalgam obeys Langmuir isotherm. The kinetic parameter for corrosion process and thermodynamic data for adsorption process has been calculated.

      This research describes a straightforward procedure for extracting the pigment of Methylene Blue (MB) dye from aqueous solutions by utilizing a low-cost, safe, natural, and national source. Batch adsorption experiments were carried out to determine contact time, adsorbent dose, and the starting concentration of the adsorbate. For the analysis, a UV spectrophotometer was employed. Dye adsorption equilibrium was obtained after 120 minutes of contact time. Temkin, Langmuir, and Freundlich isotherm adsorption were used at solution concentrations of (3, 4, 6, and 8) mg/l. Adsorption data is used to predict the pseudo first and pseudo second order kinetic equations, Elovich kinetic models, and intra-particle diffusion using pseudo f

Different concentrations prepared 2,4,8,16,32 ppt from flow water to Shatt-Alarab
by adding Chlorella vulgares and Navicual busiedtii as alone for each
concentration. The results showed that the concentrations of salinity reduced to 0,
1.78, 9.45, 15 ppt after 10 days, with removed percentage 100, 100, 77.75, 40.93,
37.12 % respectively for Chlorella vulgares the cell numbers of Chlorella vulgares
reached to 58.123, 60.123, 69.712, 37.234, 30.546 ×104/ml comparing with the
control 55.652 ×104/ml while the absorbability of salinity reached to 0.378, 0.391,
0.489, 0.231, and 0.192 nm comparing with 0.342 as control. The external cell wall
of Chlorella vulgares was swelling at 32 ppt. the removal percentage of sali

This study investigated the applicability of iron oxide (Fe₂O₃) nanoparticles for the removal of cadmium metal from sewage water by using batch scale experiments. The iron oxide nanoparticles of 27.7nm were synthesized using a biological method and characterized by Atomic Force Microscope (AFM).  The Box-Wilson design was used to conduct experiments with three parameters such as pH (2-6), time of adsorption (6-120min) and adsorbent dosage (5-25mg/L). The best conditions occurred at pH: 5.5; contact time: 95.8 min; and iron oxide nanoparticle dosage: 20.77 mg/L for maximum cadmium removal of (96.9%).

In this paper, two types of iron oxide nanomaterial (Fe3O4) and nanocomposite (T-Fe3O4) were created from the bio-waste mass of tangerine peel. These two materials were utilized for adsorption tests to remove cefixime (CFX) from an aqueous solution. Before the adsorption application, both adsorbents have been characterized by various characterizations such as XRD, FTIR, VSM, TEM, and FESEM. The mesoporous nano-crystalline structure of Fe3O4 and T-Fe3O4 nanocomposite with less than 100-nm diameter is confirmed. The adsorption of the obtained adsorbents was evaluated for CFX removal by adjusting several operation parameters to optimize the removal. The optimal conditions for CFX removal were found to be an initial concentration of 40 and 50 m

In this research local wheat peel was used as an adsorbent surface for removal of Azure B (AB) dye from the aqueous solution. The adsorption process was performed at different experimental parameters, equilibrium time, temperature, ionic strength and solution pH. The isotherms of adsorption are of H-type as compared with Giles curves and the adsorption data were coincide with Freundlich equation. The adsorption kinetic data were analyzed using pseudo- first and second order kinetic models. The effect of temperature was studied and the amount of dye adsorbed was found to increase with the increasing of temperature from 25 to 50 oC. The values of thermodynamic functions like enthalpy and entropy have been estimated. The quantity of adso

The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio

The ability of pulverized walnut-shell to remove oil from aqueous solutions has been studied. It involves two-phase process which consists of using walnut-shell as a filtering bed for the accumulation and adsorption of oil onto its surface. Up to 96% oil removal from synthetic wastewater samples was achieved while tests results showed that 75% of oil can be removed from the actual wastewater discharged from Al- Duara refinery in the south of Baghdad.

     In the present investigation, the synthesis of copper nanoparticles from green tea was attempted and investigated for its capacity to adsorb drugs (Ciprofloxacin). The copper nanoparticles (Cu-NPs) were characterized by different techniques of analysis such as scanning electron microscopy (SEM) images, atomic force microscope (AFM),  blumenauer-emmer-teller (BET), fourier transform infrared (FTIR) spectroscopy, and zeta potentials techniques. Cu-NPs lie in the mesoporous material category with a diameter in the range of 2-50 nm. The aqueous solution was investigated for the removal of ciprofloxacin (CIP) with green tea-synthesized Cu-NPs. The results showed that ciprofloxacin efficiency depe

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD