In this work, ZnO quantum dots (Q.dots) and nanorods were prepared. ZnO quantum dots were prepared by self-assembly method of zinc acetate solution with KOH solution, while ZnO nanorods were prepared by hydrothermal method of zinc nitrate hexahydrate Zn (NO3)2.6H2O with hexamethy lenetetramin (HMT) C6H12N4. The optical , structural and spectroscopic properties of the product quantum dot were studied. The results show the dependence of the optical properties on the crystal dimension and the formation of the trap states in the energy band gap. The deep levels emission was studied for n-ZnO and p-ZnO. The preparation ZnO nanorods show semiconductor behavior of p-type, which is a difficult process by doping because native defects.
A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa
Critical buckling and natural frequencies behavior of laminated composite thin plates subjected to in-plane uniform load is obtained using classical laminated plate theory (CLPT). Analytical investigation is presented using Ritz- method for eigenvalue problems of buckling load solutions for laminated symmetric and anti-symmetric, angle and cross ply composite plate with different elastic supports along its edges. Equation of motion of the plate was derived using principle of virtual work and solved using modified Fourier displacement function that satisfies general edge conditions. Various numerical investigation were studied to exhibit a convergence and accuracy of the present solution for considering some design parameters such as edge
... Show MoreA simple, precise, and sensitive spectrophotometric method has been established for the analysis of doxycycline. The method includes direct charge transfer complexation of doxycycline withp-Bromanil in acetonitrileto form a colored complex. The intensely colored product formed was quantified based on the absorption band at 377 nm under optimum condition. Beer’s law is obeyed in the concentration range of 1–50 μg.mL-1 with molar absorptivity of 1.5725x104 L.mol-1.cm-1, Sandell's sensitivity index (0.0283) μg.cm-2, detection limit of 0.1064 μg.mL-1, quantification limit 0.3224 μg.mL-1 and association constant of the formed complex (0.75x103). The developed method could find application in routine quality control of doxycycline and has
... Show MoreBackground: Characterization of the ovarian masses preoperatively is important to inform the surgeon about the possible management strategies. MRI may be of great help in identifying malignant lesion before surgery. Diffusion Weighted Imaging (DWI) is a sensitive method for changes in proton of water mobility caused by pathological alteration of tissue cellularity, cellular membrane integrity, extracellular space perfusion, and fluid viscosity.
Objective: to study the diagnostic accuracy of DWI in differentiation between benign and malignant ovarian masses.
Type of the study:Cross-sectional study.
Methods: this study included 53with complex
... Show MoreKE Sharquie, HM Al-Hamamy, AA Noaimi, IA Al-Shawi, Journal of the Saudi Society of Dermatology & Dermatologic Surgery, 2011 - Cited by 9
The present study was aimed to find out the role of humoral immunity in the pathogenesis of psoriasis. Complements C3, C4 and immunoglobulin IgE .The study included 55 Iraqi patients with psoriasis 30 (15 females ,15 males) were untreated with any drugs. The other patient group consisted of 25 (9 female and 16 male) treated with a biological treatment (infliximab) ,and 30 (13 males ,12 females) healthy control group. Blood sample were withdrawn (5) ml of venous blood for both patients and members of the control ,to conduct the Immunological tests to determine the quantitative for each of total IgE by using (ELISA) and C3,C4 by Single Radial Immunodiffuse (SIRD). The results showed significant increase in the level of probability (P <0.0
... Show MoreThe aim of this work was to estimate the concentrations of natural and artificial nuclides in some fertilized and unfertilized plant samples. These samples were collected and prepared in a petri dish for the measurements using gamma spectroscopy. The average values of 238U, 232Th, 40K, and 137Cs for the unfertilized plant samples were (11.964 ± 3.226, 8.273 ± 2.639, 402.436 ± 18.099, and 2.761 ± 1.613) respectively, and for the fertilized plant samples were (30.434 ± 5.282, 22.584 ± 4.620, 711.332 ± 25.806, and 6.986 ± 2.542) respectively. The average values of radiological hazard indices, Raeq, D, D for 137Cs, (AEDE)in, (AEDE)out, Iγ, Hin, and Hout for the unfertilized plant samples were (54.782 ± 7.216, 27.306, 0.469, 0.
... Show MoreOsteoblast and osteoclast activity is disrupted in post-menopausal osteoporosis. Thus, to fully address this imbalance, therapies should reduce bone resorption and promote bone formation. Dietary factors such as phyto-oestrogens and Zn have beneficial effects on osteoblast and osteoclast activity. However, the effect of combinations of these factors has not been widely studied. We therefore examined the effect of coumestrol, daidzein and genistein in the presence or absence of zinc sulphate (Zn) on osteoclast and osteoblast activity. Osteoclast differentiation and bone resorption were significantly reduced by coumestrol (10- 7 m), daidzein (10- 5 m) and genistein (10- 7 m); and this direct anti-osteoclastic action was unaffected by Zn (10-
... Show MoreThe successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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