Objective: The antimicrobial efficacy of three disinfection solutions: 5.25% sodium hypochlorite (NaOCl), 2% chlorhexidine (CHX) and Listerine mouthwash were investigated as routine chair-side gutta-percha (GP) disinfection reagents. Design: four groups of gutta percha points were contaminated with E. faecalis bacteria then disinfected by immersion in different solutions (5.25% sodium hypochlorite, 2% chlorhexidine gluconate, Listerine mouth wash and distilled water as control) after 1 and 7 days culturing periods. The antibacterial efficacy of these disinfection solutions was evaluated by using colonies per units (CPU) Methods: Forty GP cones (F3 Dentsply) were sterilized with ethylene oxide gas before immersed contamination within broth media containing E. faecalis for 20 min. Cones then divided them equally into four groups (n = 10) based on the treated disinfection solution, whilst one group received no disinfection treatment (control group). Each cone was then immersed into broth media within separated Eppendorf tubes for 3 min before 100 μl was taken to be cultured in an agar plate for 24h. The remaining broth media tubes were incubated for 7 days at 37℃ before taking another 100 μl to be cultured in new agar plates. CPU for E. faecalis growth were calculated for the two period cultured plates: immediately after GP disinfection (day 0) and after 7 days incubation. Results: All groups except control showed low E. faecalis colonies growth. The colony-forming units (CFU) of E. faecalis on day 0 was zero growth in NaOCl and CHX disinfected groups and much higher (14) within Listerine group. On day 7, only NaOCl group still have complete inhibition for E. faecalis colonies growth. CHX antimicrobial potency was decreased with time, while CFU for Listerine group decreased after 7 days incubation. Conclusion: The NaOCl was the best disinfection for gutta-percha cones, followed by CHX and Listerine mouthwash
This study synthesized nanocomposite photocatalyst materials from a mixture of Cu2O nanoparticles, ZnO nanoparticles, and graphene oxide (GO) through coprecipitation and hydrothermal methods. This study aims to determine the optimum composition of Cu2O/ZnO/GO nanocomposites in degrading methylene blue. The nanocomposite was synthesized in two steps: 1 the synthesis of Cu2O and ZnO nanoparticles through the coprecipitation method and the preparation of GO through the modified Hummer method. 2 The preparation of Cu2O and ZnO nanoparticles mixtures with GO through the hydrothermal method to form Cu2O/ZnO/GO nanocomposites. The adsorption-photocatalysis process of methylene blue
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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A study were conducted to examinate the effect of organic and aqueous (Hot, Cold) Extracts from leaves of Duranta repens on the growth and activities of the following types of Bacteria:- Staphylococcus aureus,Streptococcus pyogens ,Escherichia coli,Klebsilla pneumonia, in addition to the yeast Candida albicans and the fungi Aspergullis niger ,Aspergulls flavus.The result showed that gram Positive Bacteria is more sensitive to the extracts than gram negative bacteria with Minimum inhibitory concentration (MIC) value (50,25,50,100)% and Minimum Bactericidal Concentration (MBC) value (100,50,200,100)% for all types Bacteria respectively . The most active extract against A.niger ,A,flavus was cold and hot aqueous extract from the leaves with d
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Particulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in
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This research is a study of the difficulties of learning the Arabic language that faces Arabic language learners in the Kurdistan Region, by revealing its types and forms, which can be classified into two categories:
The first type has difficulties related to the educational system, the source of which is the Arabic language itself, the Arabic teacher or the learner studying the Arabic language or the educational curriculum, i.e. educational materials, or the educational process, i.e. the method used in teaching.
The second type: general difficulties related to the political aspect, the source of which is the policy of the Kurdistan Regional Government in marginalizing the Arabic language and replacing the forefront of th
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Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant
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