Silver nanoparticles (AgNPs) are of potential interest because of their effective antibacterial and antiviral activities. Capping agents are used for exhibiting a better antibacterial activity than uncapped Ag NPs. There are very few reports that have shown the usage of AgNPs for in-vivo antibacterial therapy. Citrate-capped silver nanoparticles were synthesized chemically by citrate reduction method; the size of Cit-AgNPs was determined by an atomic force microscope (AFM) and was between 15-90 nm. Acinetobacter baumannii (A. baumannii) isolates were the only sensitive species to Cit-AgNPs. MICs and MBC of Cit-AgNPs were determined by using A. baumannii. The results showed an additive effect of Cit-AgNPs. Four mice groups were infected with a sub-lethal dose of A. baumannii intraperitoneally, IP. The single daily dose of Cit-AgNPs and imipenem plus Cit-AgNPs combination were administered IP. Imipenem and phosphate buffer saline (PBS) was used as positive control and negative control, respectively. Interestingly, only the PBS-treated group showed growth of A. baumannii in the liver and spleen of sacrificed mice. Histopathologically, Cit-AgNPs showed antibacterial activity and had an additive effect when combined with imipenem in vivo and in vitro. Moreover, the Cit-AgNPs showed dose-dependent activity and the organs differed in the illumination of the toxicity effect of Cit-AgNPs even after high dose administration. In conclusion, Cit-capped AgNPs had antibacterial activity against multiple drug resistant (MDR) A. baumannii but not against K. pneumoniae and E. coli. Cit-capped AgNPs increased the inhibition zone of imipenem in …
In the era of the digital economy, public organizations need to consolidation the capabilities of entrepreneurial alertness to reduce the risks of sudden transformations and changes, and to find effective mechanisms to discover and invest in environmental opportunities proactively, as this concern has become a knowledge gap in public sector institutions, the current research aims to identify the role of digital competence in influencing on entrepreneurial alertness in the Central Bank of Iraq (CBI), the descriptive analytical approach was used as a research method to describe and analyze the main research variables. digital competence as an explanatory variable includes three dimensions: digital infrastructure, digital integration, and d
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia
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This study was undertaken to diagnose routine settling problems within a third-party oil and gas companies’ Mono-Ethylene Glycol (MEG) regeneration system. Two primary issues were identified including; a) low particle size (<40 μm) resulting in poor settlement within high viscosity MEG solution and b) exposure to hydrocarbon condensate causing modification of particle surface properties through oil-wetting of the particle surface. Analysis of oil-wetted quartz and iron carbonate (FeCO₃) settlement behavior found a greater tendency to remain suspended in the solution and be removed in the rich MEG effluent stream or to strongly float and accumulate at the liquid-vapor interface in comparison to naturally water-wetted particles. As su
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The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.
In this study, the use of non-thermal plasma theory to remove toxic gases emitted from a vehicle was experimentally investigated. A non-thermal plasma reactor was constructed in the form of a cylindrical tube made of Pyrex glass. Two stainless steel rods were placed inside the tube to generate electric discharge and plasma condition, by connecting with a high voltage power supply (up to 40 kV). The reactor was used to remove the contaminants of a 1.25-liter 4-cylinder engine at ambient conditions. Several tests have been carried out for a ranging speed from 750 to 4,500 rpm of the engine and varying voltages from 0 to 32 kV. The gases entering the reactor were examined by a gas analyzer and the gases concentration ratio
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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