Undoped and Al-doped CdO thin films have been prepared by vacuum thermal evaporation on glass substrate at room temperature for various Al doping ratios (0.5, 1 and 2)wt.% . The films are characterized by XRD and AFM surface morphology properties. XRD analysis showed that CdO:Al films are highly polycrystalline and exhibit cubic crystal structure of lattice constant averaged to 0.4696 nm with (111) preferred orientation. However, intensity of all peaks rapidly decreases which indicates that the crystallinity decreases with the increase of Al dopant. The grain size decreases with Al content (from 60.81 to 48.03 nm). SEM and AFM were applied to study the morphology and to estimate the surface roughness of the obtained films. All films were homogeneous and smooth, with a characteristic spherical grain size depending on Al content. The (RMS) roughness of the films increases with the increase of Al dopant. The improvement of the structural and surface morphology properties of Al-doped CdO has potential applications for different optoelectronic device applications.
Three hundred and sixty different samples were collected from different sources, including wound, burn, nasal, and oral swabs from several hospitals in Baghdad. A number of 150 (53%) Staphylococcus aureus samples were isolated and identified among a total of 283 samples. Then, the spread of the Toxic Shock Syndrome Toxin-1 gene (tsst-1) was investigated in β-lactamase resistant S. aureus. According to the source of samples, the distribution of S. aureus isolates was found to be significantly higher (p < 0.01) in wound samples as compared to other sources. According to the age, a highly significant distribution (p < 0.01) was recorded in the age group of 15-30 years,
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This research includes the synthesis of some new N-Aroyl-N \ -Aryl thiourea derivatives namely: N-benzoyl-N \ -(p-aminophenyl) thiourea (STU1), N-benzoyl-N \ -(thiazole) thiourea (STU2), N-acetyl-N ` -(dibenzyl) thiourea (STU3). The series substituted thiourea derivatives were prepared from reaction of acids with thionyl chloride then treating the resulted with potassium thiocyanate to affored the corresponding N-Aroyl isothiocyanates which direct reaction with primary and secondary aryl amines, The purity of the synthesized compounds were checked by measuring the melting point and Thin Layer Chromatography (TLC) and their structure, were identified by spectral methods [FTIR,1H-NMR and 13C-NMR].These compounds were investigated as a
... Show MoreRetreatment Efficacy of Continuous Rotation Versus Reciprocation Kinematic Movements in Removing Gutta-Percha with Calcium Silicate-Based Sealer: SEM Study, Raghad Noori Nawaf*, Ra
Water has a great self-generating capacity that can neutralize the polluting interventions carried out by humans. However, if human activities continue this uncontrolled and unsustainable exploitation of this resource, this regenerating capacity shall fail and it will be jeopardized definitively. Shatt Al-Arab River in South of Iraq. It has an active role in providing water for irrigation, industry, domestic use and a commercial gateway to Iraq. in the last five years Shatt Al-Arab suffered from a rise in pollutants due to the severe decline in sewage networks, irregular networks and pesticide products, as well as the outputs of factories and companies that find their way to water sources and lead to a widespread collapse of water quality.
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The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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