Polypyrrole/silver (PPy/Ag) nanocomposites was synthesized via a chemical oxidative method. The AFM analysis is performed to study the surface roughness, morphology and size distribution of the PPy particles and PPy-ag nanocomposites. The results indicated that as the concentration of Ag in the nanocomposite increases, the roughness also increases. The size of nanoparticles was also evaluated and found in the range of 15 nm to 125 nm. The PPy/Ag nanocomposites exhibited an effectiveness against Gram-negative Escherichia coli showing an inhibition zone of 4mm and displayed poor efficacy against Gram-positive Staphylococcus aureus. Based on given adequate antibacterial characteristics of PPy/Ag nanocomposites, it can be identified as a pro

Polypyrrole/silver (PPy/Ag) nanocomposites was synthesized via a chemical oxidative method. The AFM analysis is performed to study the surface roughness, morphology and size distribution of the PPy particles and PPy-ag nanocomposites. The results indicated that as the concentration of Ag in the nanocomposite increases, the roughness also increases. The size of nanoparticles was also evaluated and found in the range of 15 nm to 125 nm. The PPy/Ag nanocomposites exhibited an effectiveness against Gram-negative Escherichia coli showing an inhibition zone of 4mm and displayed poor efficacy against Gram-positive Staphylococcus aureus. Based on given adequate antibacterial characteristics of PPy/Ag nanocomposites, it can be identified as

Treatment of a high strength acidic industrial wastewater was attempted by activated carbon
adsorption to evaluate the feasibility of yielding effluents of reusable qualities. The experimental
methods which were employed in this investigation included batch and column studies. The
former was used to evaluate the rate and equilibrium of carbon adsorption, while the latter was
used to determine treatment efficiencies and performance characteristics. Fixed bed and expanded
bed adsorbers were constructed in the column studies. In this study, the adsorption behavior of acetic acid onto activated carbon was examined as a function of the concentration of the adsorbate, contact time and adsorbent dosage. The adsorption data was mo

The trichomes and chemical composition of three species of the genus Salvia wild-grown (Salvia lanigera, Salvia spinosa) and cultured (Salvia officinalis) were studied in the Anbar governate, the chemical components of the stem and leaves were studied by Gas chromatography–mass spectrometry(GC-MS), in addition to studying the trichomes of the epidermis in the stem and leaves (upper and lower epidermis) by Light microscope. Important differences appeared to us in the chemical study, where it was found that some compounds were found in species without others, which gives them taxonomic importance, also, the trichomes were important in distinguishing the studied species, the species S. spinosa was distinguished by the presence of gla

In this paper, preliminary test Shrinkage estimator have been considered for estimating the shape parameter α of pareto distribution when the scale parameter equal to the smallest loss and when a prior estimate α0 of α is available as initial value from the past experiences or from quaintance cases. The proposed estimator is shown to have a smaller mean squared error in a region around α0 when comparison with usual and existing estimators.

The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the tradit

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor