In this work, the effect of different particle size on the nonlinear optical properties of silver nanoparticles in de-ionized water was studied. The experimental observation of the far field diffraction patterns by CCD camera in two and three dimensions. The maximum change of nonlinear refractive index and the relative phase shift were calculated. The self-defocusing technique was used with a continuous-wave radiation from DPSS Blue laser .The wavelength is 473 nm with an output power of 270 mW. All the Ag colloids samples containing the sizes 15, 30, 50, and 70 nm of silver nanoparticles used in the study were chemically prepared. It was found that the nonlinear refractive index is a particle size dependent and of the order of 10-7 cm2/W, while its maximum change is in the order of 10-4. The phase shift increased from 8π up to 14π with particle size increment. The increase in the particle size of the Ag nanoparticles leads to increasing the number of rings and to the material possessing more nonlinearity with the nonlinear refractive index increment.
In the current study, synthesis and characterization of silver nanoparticles (AgNPs) before and after functionalization with ampicillin antibiotic and their application as anti-pathogenic agents towards bacteria were investigated. AgNPs were synthesized by a green method from AgNO3 solution with glucose subjected to microwave radiation. Characterization of the nanoparticles was conducted using UV-Vis spectroscopy, scanning electron microscopy (SEM), zeta potential determination and Fourier transform infrared (FTIR) spectroscopy. From SEM analysis, the typical silver nanoparticle particle size was found to be 30 nm and Zeta potential measurements gave information about particle stability. Analysis of FTIR patterns and UV-VIS spectroscopy con
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The kinetic of atropine pertraction from seeds of Datura Metel Linn plant was studied. Diisopropyl ether, n-hexane and n-heptane were used as membranes for atropine recovery. The effect of speed of agitation and time in the range of 200-300 rpm and 0-3.5h, respectively were studied using the proposed membranes. The pertraction experiments were carried outs in a batch laboratory unit. The liquid-liquid pertraction was found to be very suitable for atropine recovery from its liquid extracts of Datura Metel seeds. A high purity (94-96%) can be obtained in the receiver phase. The pertraction process was found to be very selective for atropine recovery with diisopropyl ether membrane. As the speed of agitation increases the efficiency of pertrac
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Solid dispersion is an attractive tool of pharmaceutical technology used to improve the physical properties of drugs. Among these properties is to enhance the solubility of the drugs.
Rebamipide is a poorly soluble drug of class IV of biopharmaceutical classification system (BCS).
Rebamipide is used as potent antiulcer, mucoprotective drug, by stimulating the generation of prostoglandine enhanced mucosal protection.
Rebamipide was formulated as a solid dispersion using different polymers such as pluronic F-127, PEG6000, PVP K30, and TPGS by using different preparation methods solvent evaporation, fusion, and kneading methods.
It was seen that rebamipide was successfully dispersed in a homogenous solid dispersion matrix by sol
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Metal oxide nanoparticles, including iron oxide, are highly considered as one of the most important species of nanomaterials in a varied range of applications due to their optical, magnetic, and electrical properties. Iron oxides are common compounds, extensive in nature, and easily synthesized in the laboratory. In this paper, iron oxide nanoparticles were prepared by co-precipitation of (Fe+2) and (Fe+3) ions, using iron (II and III) sulfate as precursor material and NH4OH solution as solvent at 90°C. After the synthesis of iron oxide particles, it was characterized using X-ray diffraction (XRD), infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). These tests confirmed the obtaining o
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Abstract:
Objective: To self-evaluate the effect of SBAR (Situation, Background, Assessment, and Recommendation) educational program on nurse and midwives practices in maternal health report documentation accuracy.
Methods: A quasi- experimental design was carried with the application of pre- post test for nurses and midwives’ knowledge and practices regarding SBAR communication tool. The study was held in Al-Elwia maternity teaching hospital, Al –Karckh maternity hospital and Al-Yarmouk teaching Hospital. purposive sample as it was convenient with inclusion criteria consisted of (84) nurse and midwives. The questionnaire comprised of demographic data, nurses- midwives practices of SBAR using (5) level Likert scale for assessme
بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته
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The present study include a new developed method of analysis for determination of drug Spironolaction (SP) in some Pharmaceuticals by Spectrofluorometric method. Spironolaction was determined under optimal experimental condition that follows :- The excitation spectrum was (l=351 nm), the emmetion spectrum was (l=518 nm), pH=1, the suitable temperature for reaction 60oC and the optimal time less than (3) minute. The analysis and rang statistical data was:-Linear dynamic rang (1-10) ?g.ml-1, the detection limit (D.L = 0.023 ?g.ml-1), Molar absorptivity (? = 29875 liter mole-1 cm-1), Relative standard deviation (%RSD = 0.78), (%Erel = 3.3) and recovery (Rec = 96.6) percentage. Determination of Spironolactone was accomplished by two methods
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
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