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 aerugi

ne,؛Stability constants were determined for complexes of amino acids : L-leuc tryptophane and Aspartic acid with thorium (IV ) and uranyle ( U02++) ions at ؛ serine

Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysi

The article examines metaphors as one of the fundamental means used by D. Rubina when writing the novel “Parsley Syndrome” to form images of dolls as equal heroes of the work. The author of the article continues research related to the work of Dina Ilinichna Rubina, a representative of modern Russian prose.

A simple and novel method was developed by combination of dispersive liquid-liquid microextraction with UV spectrophotometry for the preconcentartion and determination of trace amount of malathion. The presented method is based on using a small volume of ethylenechloride as the extraction solvent was dissolved in ethanol as the dispersive solvent, then the binary solution was rapidly injected by a syringe into the water sample containing malathion. The important parameters, such the type and volume of extraction solvent and disperser solvent, the effect of extraction time and rate, the effect of salt addition and reaction conditions were studied. At the optimum conditions, the calibration graph was linear in the range of 2-100 ng mL-1 of ma

A dispersive liquid-liquid microextraction combines with UV-V is spectrophotometry for the preconcentration and determination of Mefenamic acid in pharmaceutical preparation was developed and introduced. The proposed method is based on the formation of charge transfer complexation between mefenamic acid and chloranil as an n-electron donor and a p-acceptor, respectively to form a violet chromogen complex measured at 542 nm. The important parameters affecting the efficiency of DLLME were evaluated and optimized. Under the optimum conditions, the calibration graphs of standard and drug, were ranged 0.03-10 µg mL-1. The limits of detection, quantification and Sandell's sensitivity were calculated. Good recoveries of MAF Std. and drug at 0.05,

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

The study included the extraction of volatile oil from Mentha piperita which was 1.3 % in the leaves and flowers . Volatile oil of the Mentha piperita leaves had special aromatic odour, pale yellow color, slightly pungent taste . The specific gravity and refractive index were (0.9794) and ( 1.464) respectively. The inhibition activity of the Mentha piperita Volatile oil extracts were studied on some pathogenic microorganisms like Staphylococcus aureus, Salmonella typhi, Escherichia coli, Proteus sp, and Klebsiella pneumoniae . The result showed that the volatile oil had an inhibition effect on the growth of all microorganisms, and it gave the higher inhibition effect on the growth of S. aureus in which the inhibition zone reached to 2