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The effect of adding single walled carbon nanotube with different concentrations on mechanical properties of heat cure acrylic denture base material
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Background: The most widely used material for fabrication of denture base is poly methyl methacrylate, despite its popularity, the main problems associated with it as a denture base material are poor strength particularly under fatigue failure inside the patient mouth, impact failure outside the patient mouth, which are the main causes for fracture of denture, several studies was done to increase mechanical properties of denture base. The present study was conducted to evaluate and compare the effect of addition single walled carbon nanotubes in different concentrations to polymethyl methacrylate on some mechanical properties (surface hardness, surface roughness, impact strength and transverse strength). Materials and methods: Forty eight samples were prepared for pilot study divided into four groups according to the concentrations of singled walled carbon nanotubes ( 0%, 0.5%, 1% & 1.5%) added to heat cure acrylic resin , each group was divided into four subgroups according to the tests conducted (Surface hardness , surface roughness, impact strength and transverse strength) and the results obtained were evaluated to determine the concentration of singled walled carbon nanotubes (SWCNTS) that improve the mechanical properties of heat cure acrylic resin to be used to complete our study, so another 80 samples were made divided into two main groups (0% SWCNTS as control group) and (1.5% SWCNTS test group) and all the tests were done again. Results: Impact strength and transverse strength were significantly increased after adding 1.5% SWCNTS While surface hardness was significantly decreased and surface roughness was non-significantly affected when compared with control group. Conclusions: Impact strength and transverse strength of hot cure acrylic resin reinforced with 1.5% SWCNTS were greatly increased.

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Publication Date
Tue Mar 08 2022
Journal Name
Chemical Biology & Drug Design
SARS‐CoV‐2 and its variants of concern including Omicron: A never ending pandemic
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Abstract<p>The ongoing COVID‐19 pandemic caused by SARS‐CoV‐2 is associated with high morbidity and mortality. This zoonotic virus has emerged in Wuhan of China in December 2019 from bats and pangolins probably and continuing the human‐to‐human transmission globally since last two years. As there is no efficient approved treatment, a number of vaccines were developed at an unprecedented speed to counter the pandemic. Moreover, vaccine hesitancy is observed that may be another possible reason for this never ending pandemic. In the meantime, several variants and mutations were identified and causing multiple waves globally. Now the safety and efficacy of these vaccines are debatable and recommended to d</p> ... Show More
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Publication Date
Sun Aug 20 2023
Journal Name
Baghdad Science Journal
Biosynthesis, Characterization, Adsorption and Antimicrobial studies of Manganese oxide Nanoparticles Using Punica Granatum Extract
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Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75

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Publication Date
Mon Apr 01 2024
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Classification of grapevine leaves images using VGG-16 and VGG-19 deep learning nets
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The 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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Publication Date
Fri Dec 01 2023
Journal Name
Case Studies In Chemical And Environmental Engineering
Kinetic modeling of a solar photo-electro-Fenton process for treating petroleum refinery wastewater
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Publication Date
Fri Jan 01 2016
Journal Name
Diabetic Foot &amp; Ankle
Risk factors for occurrence and recurrence of diabetic foot ulcers among Iraqi diabetic patients
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Publication Date
Sun Jun 12 2022
Journal Name
Sensors
Recent Advances in Bipedal Walking Robots: Review of Gait, Drive, Sensors and Control Systems
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Currently, there is an intensive development of bipedal walking robots. The most known solutions are based on the use of the principles of human gait created in nature during evolution. Modernbipedal robots are also based on the locomotion manners of birds. This review presents the current state of the art of bipedal walking robots based on natural bipedal movements (human and bird) as well as on innovative synthetic solutions. Firstly, an overview of the scientific analysis of human gait is provided as a basis for the design of bipedal robots. The full human gait cycle that consists of two main phases is analysed and the attention is paid to the problem of balance and stability, especially in the single support phase when the biped

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Publication Date
Thu Dec 06 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation and Characterization of Bromocriptine Mesylate as Liquid Self-Nano Emulsifying Drug Delivery System
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Bromocriptine mesylate is a semisynthetic ergot alkaloid derivative with potent dopaminergic activity, used in the treatment of pituitary tumors, Parkinson's disease (PD), hyperprolactinaemia, neuroleptic malignant syndrome, and type 2 diabetes ,the oral bioavailability is  approximately 6%, therefore aim  its  prepare and evaluate bromocriptine mesylate  as liquid self nano emulsifying drug delivery system to enhance its solubility , dissolution and stability . Solubility study was made in different vehicles to select the best excipients for dissolving bromocriptine mesylate. Pseudo-ternary phase diagrams were constructed at 1:1, 2:1, 3:1 and 4:1 ratios of surfactant and co-surfactant, four formulations were pre

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Publication Date
Thu Dec 14 2023
Journal Name
Iete Journal Of Research
Performance Enhancement of VLC-NOMA Employing Beamforming Function based vehicle-to-multivehicle Communication system
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Evaluation of ANFIS and Regression Techniques in Estimating Soil Compression Index for Cohesive soils
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Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regre

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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Simulation and Experimental Investigation of Performance and Flow Behavior for Steam Ejector Refrigeration System
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The ejector refrigeration system is a desirable choice to reduce energy consumption. A Computational Fluid Dynamics CFD simulation using the ANSYS package was performed to investigate the flow inside the ejector and determine the performance of a small-scale steam ejector. The experimental results showed that at the nozzle throat diameter of 2.6 mm and the evaporator temperature of 10oC, increasing boiler temperature from 110oC to 140oC decreases the entrainment ratio by 66.25%. At the boiler temperature of 120oC, increasing the evaporator temperature from 7.5 to 15 oC increases the entrainment ratio by 65.57%. While at the boiler temperature of 120oC and

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