Pharmaceuticals are widely distributed in different applications and also released into the environment. Adsorption of Ciprofloxacin HCl (CIPH) on Porcelinaite was studied at ambient conditions. The adsorption isotherms can be well described using the Freundlich and Temkin equations. The pH of the solution influences significantly the adsorption capacity of Porcelinaite, the adsorption of CIPH increased from the initial pH 1.3 and then decreased over the pH rang of 3.8-9. The adsorption is sensitive to the change in ionic Strength, which indicate that electrostatic attraction is a significant mechanism for sorption process. The enthalpy change (∆H) for the adsorption of CIPH onto Porcelinaite signifies an endothermic adsorption. The ∆G value is negative at all studied temperatures, inferring that, the adsorption of CIPH onto porcelinaite will follow a spontaneous trend. The ∆G value decreased when the temperature increased from 15 oC to 37.5 oC, suggesting increase in adsorption of CIPH with increasing temperature. The positive value of ∆S reflects the affinity of porcelinaite towards drug and also suggests increased randomness at the solid-solution interface.
In this research, CNRs have been synthesized using pyrolysis of plastic waste(pp) at 1000 ° C for one hour in a closed reactor made from stainless steel, using magnesium oxide (MgO) as a catalyst. The resultant carbon nano rods were purified and characterized using energy dispersive X-ray spectroscopy (EDX), X-ray powder diffraction (XRD). The surface characteristics of carbon rods were observed with the Field emission scanning electron microscopy (FESEM). The carbon was evenly spread and had the highest concentration from SEM-EDX characterization. The results of XRD and FESEM have shown that carbon Nano rods (CNRs) were present in Nano figures, synthesized at 1000 ° C and with pyrolysis temperature 400° C. One of t
... Show MoreCopper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the
... Show MoreObjective: Using green chemistry, an effective, inexpensive, and environmentally safe method, sulfur nanoparticles with specific properties can be prepared and used in nanotechnology. This research aimed to prepare sulfur nanoparticles from chilli pepper extract and determine their effectiveness against colon cancer. Method: Chilli pepper extract obtained from local markets was treated with aqueous sodium thiosulfate (Na2S2O7.5H2O). After mixing, it was continuously stirred, heated, and filtered. NaBH4 was then added, resulting in a yellow precipitate. The precipitate was centrifuged, purified, and dried at 250°C. Results: Standardised tests such as UV-Vis, XRD, SEM, TEM, AFM, and EDX were used, resulting in sulfur nanoparticles with an av
... Show MoreThe effluent quality improvement being discharged from wastewater treatment plants is essential to maintain an environment and healthy water resources. This study was carried out to evaluate the possibility of intermittent slow sand filtration as a promising tertiary treatment method for the sequencing batch reactor (SBR) effluent. Laboratory scale slow sand filter (SSF) of 1.5 UC and 0.1 m/h filtration rate, was used to study the process performance. It was found that SSF IS very efficient in oxidizing organic matter with COD removal efficiency up to 95%, also it is capable of removing considerable amounts of phosphate with 76% and turbidity with 87% removal efficiencies. Slow sand filter efficiently reduced the mass of suspended
... Show MoreThis paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF
... Show MoreDespite the global economic downturn, online e-commerce, especially the sale of counterfeit goods, continues to witness a rise in sales, and one of the important players in e-commerce is the owners of e-commerce auction sites. Although they do not have a direct role in trademark infringement, they still consider them indirectly responsible (secondary liability) for infringing on their trademarks. Thus, many cases have been filed by the owners of the original trademarks (which have been infringed by persons who have sold some of the goods and products that are imitating their marks through some electronic auctions) against the owners of those auctions. In view of the international character of the Internet, in different countries, and despit
... Show MoreFace recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni
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