In this study, a packed bed was used to remove pathogenic bacteria from synthetic contaminated water. Two types of packing material substrates, sand and zeolite, were used. These substrates were coated with silver nanoparticles (AgNPs), which were prepared by decomposition of Ag ions from AgNO3 solution. The prepared coated packings were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy and transmission electron microscopy. The packed column consisted of a PVC cylinder of 2 cm diameter and 20 cm in length. The column was packed with silver nanoparticlecoated substrates (sand or zeolite) at a depth of 10 cm. Four types of bacteria were studied: Escherichia coli, Shigella dysenteriae, Pseudomonas aeruginosa and Vibrio cholera. The parameters studied were feed inlet flow rate (1.5, 2, 3 and 4 L/h) and AgNO3 concentration (0.02, 0.04, 0.07 and 0.1 mM), which were used to coat the packing substrates. The best results for removal efficiency of bacteria were obtained at the feed flow rate of 1.5 L/h with AgNO3 concentration 0.1 mM. Likewise, the percent of bacterial removal from contaminated water was found to be 99% for V. cholera, 93.7% for E. coli, 85% for S. dysenteriae and 77.5% for P. aeruginosa
The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th
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Abstract: Colloidal gold nanoparticles (ringworm Palm or in the form of paper willow) have been prepared from HAuCl4 containing aqueous solution by hot chemical reduction method. The colloidal gold nanoparticles were characterized by SEM, EDX, and UV-VIS absorption spectroscopy. It was found that the variation of reduction time from boiling point affects the size of the nanoparticles and also in chemical reduction approach the size of nanoparticles can be controlled by varying the amount of variation the volume of reductant material with respect to the volume of HAuCL4.
In this work, the possibility of utilizing osmosis phenomenon to produce energy as a type of the renewable energy using Thin Film Composite Ultra Low Pressure membrane TFC-ULP was studied. Where by forward osmosis water passes through the membrane toward the concentrated brine solution, this will lead to raise the head of the high brine solution. This developed static head may be used to produce energy. The aim of the present work is to study the static head developed and the flux on the high brine water solution side when using forward and reverse osmosis membranes for an initial concentration range from 35-300 g/l for each type of membrane used at room temperature and pressure conditions, and finally calculating the maximum possible po
... Show MoreAn oxidative polymerization approach was used to create polyaniline (PANI) and Fe2O3 /PANI nanoparticle combination. Various characterization approaches were used to investigate the structural, morphological, and Fe2O3 /PANI nanoparticle structures. The findings support the synthesis of polycrystalline nanoparticle PANI and Fe2O3 /PANI spherical nanoparticle composites. Gram-positive bacteria are tested for antibacterial activity. Various quantities of Nanoparticles of PANI and Fe2O3 /PANI nanoparticle composites were used to test Staph-aureus and gram-negative bacteria, E-coli, and candida species. PANI has antibacterial properties against all microo
... Show MoreBackground: This research describes the methodology used for the preparation of selenium nanoparticles from Pseudomonas aeruginosa and their administration to lambs for lipid profile checking, administration of selenium nanoparticles as a medication in lambs results in hypolipidemia. Aim: The study aimed to investigate the potential of selenium nanoparticles in improving lipid profiles in lambs. Methods: Healthy lambs (n=10) of similar age and weight were selected for the study. The animals were housed in individual pens with free access to water and a standard diet. The lambs were randomly divided into two groups: the control group (n=5) and the treatment group (n=5). The control group received a standard diet, while the treatme
... Show MoreGiardia lamblia is one of most common protozoan cause diarrheas, and the most health problem in development countries worldwide. Our work aimed to assess activity and toxicity of metronidazole loaded silver nanoparticles in treatment of acute giardiasis in mice. After inoculated mice with Giardia cysts in a dose of 105 cyst for acute infection, treatments were given for eight days. Number Giardia cysts in stool were discovered. Toxicity nanoparticles was estimated by Measurement oxidative stress markers (GSH) and (MDA) in liver, kidney tissue homogenate. The results showed single therapy was better effect by silver nanoparticles, highest percentages of reduction in number of cysts Giardia lamblia of infected mice treated with silver nanopar
... Show MoreAccurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct