The expanding of the medically important diseases created by multidrug-resistant Acinetobacter baumannii warrants the evolve a new methodology for prevention includes vaccination and treatment. Totally of forty-five clinical isolates identified as A.baumannii were obtained from hospitalized patients from three hospital in Baghdad City during the period from February 2016 to August 2016. Followed by diagnosing using different methods. Every strain was tested for susceptibility testing also some important virulence factorswere detected. Two isolates were chosen for the immunization and vaccine model, the first one remittent for most antibiotics except one are too virulence (strong) and the second is less virulent and resistance (weak).Enzyme-linked immunosorbent assaywas used for assessments of Toll like receptor 4,and Toll like receptor 2 concentrations in mouse serum at 14, 21 and 28 days of immunization. Results proved that the strong isolate showed resistance to all antibiotics except one and positive to all virulence factors except one, while the weak isolate resistance to Ceftriaxone, Cefotaxime, positive to tow virulence factors. Mice were intramuscular inoculated with strong and weak isolate. There are high significant differences when using strong A.baumannii strong in the level of TLR4 and there was not an important variation among the use of strong and weak isolation in the level of TLR2.Finaly,the yield refers to the TLR4 plays a key role in innate sensing with multidrug resistance isolate immunization, whereas TLR 2 shows it gives the same level of stimulation during immunization with both strains but lesser concentration than TLR4, so the inactivated with MDR isolate has a potential for development as a candidate vaccine for strong protection against MDR isolate infections.
This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe
... Show MoreOptimizing the Access Point (AP) deployment is of great importance in wireless applications owing the requirement to provide efficient and cost-effective communication. Highly targeted by many researchers and academic industries, Quality of Service (QOS) is an important primary parameter and objective in mind along with AP placement and overall publishing cost. This study proposes and investigates a multi-level optimization algorithm based on Binary Particle Swarm Optimization (BPSO). It aims to an optimal multi-floor AP placement with effective coverage that makes it more capable of supporting QOS and cost effectiveness. Five pairs (coverage, AP placement) of weights, signal threshol
An efficient modification and a novel technique combining the homotopy concept with Adomian decomposition method (ADM) to obtain an accurate analytical solution for Riccati matrix delay differential equation (RMDDE) is introduced in this paper . Both methods are very efficient and effective. The whole integral part of ADM is used instead of the integral part of homotopy technique. The major feature in current technique gives us a large convergence region of iterative approximate solutions .The results acquired by this technique give better approximations for a larger region as well as previously. Finally, the results conducted via suggesting an efficient and easy technique, and may be addressed to other non-linear problems.
The increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot
... Show MoreThe covid-19 pandemic sweeping the world and has rendered a large proportion of the workforce as they are unable to commute to work. This has resulted in employees and employers seeking alternative work arrangements, including the software industry. Then comes the need for the global market and international presence of many companies to implement the global virtual teams (GVTs). GVTs members are gradually engaged in globalized business environments across space, time and organizational boundaries via information and communication technologies. Despite the advancement of technology, the project managers are still facing many challenges in communication. Hense, to become a successful project manager still a big challenge for them. This study
... Show MoreThe study aims to indicate the role of the agricultural initiative in building agricultural development, mediated by activation of the role of internal and external audit on agricultural initiative projects, for the purpose of meeting the challenges of abuses on agricultural land and lack of water used in agriculture and proportions of high poverty, which led to the rural people of the migration to the city and leave agriculture and livestock, and that of the main conclusions reached by the researcher. When comparing the work of the external auditing agencies (the Federal Office of Financial Supervision) on the initiative of agricultural projects with internal audit services in the Directorate of Agriculture and branches of the Agricultu
... Show MoreBACKGROUND: Keratoconus is a progressive non inflammatory bilateral (usually asymmetric) ectatic corneal disease characterized by paraxial stromal thinning ,weakening that lead to corneal surface distortion ,vision loss primarily from irregular astigmatism and myopia and secondly from corneal scar. OBJECTIVE: To evaluate visual and refractive outcomes after intracorneal continuous ring (ICCR) implantation combined with intrapocket corneal collagen cross linking in patient with keratoconus. Setting: Eye Specialty Private Hospital, Baghdad, Iraq. METHODS: This study assessed the results of implantation of Myoring ICCR combined with CXL in 40 eyes with KC. Outcome measures include UDVA,CDVA(spectacle correction),refraction, complications and s
... Show MoreThis work presents the construction of a test apparatus for air-conditioning application that is flexible in changing a scaled down adsorbent bed modules. To improve the heat and mass transfer performance of the adsorbent bed, a finned-tube of the adsorbent bed heat exchanger was used. The results show that the specific cooling power (SCP) and the coefficient of performance (COP) are 163 W/kg and 0.16, respectively, when the cycle time is 40 min, the hot water temperature is 90oC, the cooling water temperature is 30oC and the evaporative water temperature is 11.4oC.
The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), T
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