This study offers numerical simulation results using the ABAQUS/CAE version 2019 finite element computer application to examine the performance, and residual strength of eight recycle aggregate RC one-way slabs. Six strengthened by NSM CFRP plates were presented to study the impact of several parameters on their structural behavior. The experimental results of four selected slabs under monotonic load, plus one slab under repeated load, were validated numerically. Then the numerical analysis was extended to different parameters investigation, such as the impact of added CFRP length on ultimate load capacity and load-deflection response and the impact of concrete compressive strength value on the structural performance of slabs. This article aims to provide a numerical model for simulating the nonlinear behavior of such slabs, including a trustworthy finite element model approach and constitutive material models. In aspects of load-deflection and cracking patterns, comparisons between computational and experimental models are provided, and a reasonable fit is demonstrated. The average ratio of numerical model ultimate load and deflections to experimentally tested slabs were 0.992 and 0.913, respectively. As a result, finite element analysis may be regarded as a preferred and trustworthy approach for simulating the non-linear behavior of one-way slabs (strengthened or not) in terms of complexity, difficulty, time savings, human effort, and money.
Polyhydroxyalkanoates (PHAs) have gained much attention as biodegradable polymers, many efforts are being made to minimize the cost of PHAs by finding cheap carbon source depending on the type of microorganism and fermentation conditions. The aims of this study were to evaluate the effects of different glucose concentrations and other important conditions on the PHA production by Bacillus cereus isolated from soil. Polyhydroxyalkanoates PHAs accumulated by soil microorganisms were examined by screening the isolated bacteria using Sudan B Black and Nile Blue staining process. A Gram positive strain was identified using the 16s rRNA gene, deposited in the NCBI GenBank sequence database. Different growth conditions (favorite glucose concentrat
... Show MoreBackground: Recurrent aphthous ulceration (RAU) is an inflammatory condition of unknown etiology characterized by painful recurrent (single or multiple) ulcerations of the oral mucosa. It is one of the most common and poorly understood mucosal disorders. It occurs more frequently in times of stress. Local and systemic conditions, genetic, immunologic, microbial factors, and oxidative stress may play a role in the pathogenesis of RAU. The objective of this study was to evaluate the free radical metabolism and antioxidant activity of RAU patients treated by lavender or flax oil paint.
Materials and Methods: Sixty-six RAU patients were enroll
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... Show MoreBackground: Poly (methylmethacrylate) is not ideal in every aspect and has disadvantages such as insufficient surface hardness, increase water sorption and poor impact resistance and the latter being the primary cause of fracture of denture base resins. The aim of this study was to evaluate the effect of addition of silanized nano- hydroxyapatite (HA) on some properties of heat cured acrylic denture base material. Materials and methods: HA nano particles were first silanized with ï§MPS (tri methacryloxypropyletrimethoxy silane coupling agent) then ultrasonicated with methylmethacrylate (monomer) to disperse agglomerated nano particles and mixed with polymer. 2% by wt of HA nano particles was selected as the best concentration that add
... Show MoreIn this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every
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