This study included the isolation and diagnosis of Pseudomonas aeruginosa from cases of burns samples. 100 samples were collected from resident patients at Al-Kindi Teaching Hospital, who suffer from different types of burns. Pseudomonas aeruginosa was isolated and diagnosed with 39% of the total samples. The cold and hot aqueous and alcoholic extract of flaxseeds oil was prepared and its inhibitory efficacy has been studied on the growth of isolated Pseudomonas aeruginosa. It is revealed that both extracts of flaxseeds oil had a high inhibitory effect on Pseudomonas aeruginosa growth. The Minimum Inhibitory Concentration (MIC) of flaxseed oil on the studied bacteria was also estimated, which was 25 mg/ml. In conclusion, the efficacy of flaxseed oil was estimated in vitro and it was found that the extract of flaxseeds had an effective impact in the healing and recovery of wounds in the Balb/c white mice induced by using P. aeruginosa for eight days
Copper 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
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This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.
Buckling analysis of a laminated composite thin plate with different boundary conditions subjected to in-plane uniform load are studied depending on classical laminated plate theory; analytically using (Rayleigh-Ritz method). Equation of motion of the plates was derived using the principle of virtual work and solved using modified Fourier displacement function that satisfies general edge conditions. The eigenvalue problem generated by using Ritz method, the set of linear algebraic equations can be solved using MATLAB for symmetric and anti-symmetric, cross and angle-ply laminated plate considering some design parameters such as aspect ratios, number of layers, lamination type and orthotropic ratio. The results obtained g
... Show MoreObjective(s): To assess the burden of mothers` care for child with colostomy and find out relationships between child and mother socio-demographic data with mothers` burden. Methodology: a descriptive study was conducted from 1 August 2013 to 1 September 2014. The sample consisted of 100 children and their mothers at Baghdad Teaching hospital in Baghdad city. A questionnaire was prepared based on the previous literature review, meeting mothers of children with colostomy, and the Zarit Burden Interview scale. Data has collected through the application of questionnaire and interview techniques. Results: T
Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p
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