Over the past few decades, the health benefits are under threat as many commonly used antibiotics have become less and less effective against certain illnesses not only because many of them produce toxic reactions but also due to the emergence of drug-resistant bacteria. The clinical use of a combination of antibiotic therapy for Pseudomonas aeruginosa infections is probably more effective than monotherapy. The present study aims to estimate the antibacterial and antibiofilm activity of Conocarpus erectus leaves extracts against multi-drug resistant P. aeruginosa isolated from different hospitals in Baghdad city. One hundred fifty different clinical specimens were collected from patients from September 2021 to January 2022. All samples were cultured on specific and differential media, only 83 isolates were able to grow on cetrimide agar and at 42˚C, and then the VITEK 2 compact system was dependent to complete the identification. The results showed that the high resistance of the isolates was to the two antibiotics Ceftriaxone and Amoxicillin-Clavulanic acid with a percentage of (92.7%) and (89.2%) respectively, followed by Trimethoprim with a resistance rate of (79.5%). Ten isolates with multi-drug resistance are selected to evaluate the antibacterial activity of plant extracts and the combination between Conocarpus erectus extract and antibiotics. Maceration and Soxhlet apparatus were used to prepare the methanolic and aqueous extracts. The results of the radical scavenging ability showed that the methanolic and aqueous extracts (96.44 and 94.13%) in 10 mg/ml respectively, were more than the artificial antioxidant (BHT) which was 93.11% and the approach with the vitamin C which was 97.20%. The results of the total phenolic content were observed at 51.58 and 65.60 mg/g in 5 mg/ml for the aqueous and methanolic extracts respectively. The antibacterial activity of C. erectus leaves extracts showed that the methanolic extract was more effective than the aqueous extract at a concentration of 100 mg/ml. The results of the minimal inhibitory concentration (MIC) of the methanolic extract against P. aeruginosa were between 8-32 mg\ml. While the MIC values of the aqueous extract were 128-256 mg\ml. The synergistic activity between C. erectus methanolic extract and antibiotics against multidrug-resistant P. aeruginosa was assessed using the checkerboard analysis technique. The methanolic extract showed a synergistic effect with Cefepime against six isolates (FICI: ≤0.5), and an additive effect against four isolates (FICI: (≥ 0.5–1.0). Furthermore, a synergistic effect with Ceftriaxone against seven isolates and additive interaction was found against three isolates.
The research aims to analyze the television advertisement to monitor the indirect and underlying meanings behind the apparent significance in Zain’s “Ya Baghdad” Advertisement through sociological analysis, in accordance with the cultural analysis of Hofstede’s ‘Model of Cultural Dimensions’. Our choice of such a model in practical application over other models that may have provided more dimensions is due to its ability and verification in explaining cultural diversity and additionally the size of data and studies on the cultural dimension. This study’s aim is to verify the validity, stability and significance of this model before being adopted by Hofstede as a measurement tool. This model was used in order to analyze the rel
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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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Net pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.
This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.
The Mishrif formation was
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In this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.
Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
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This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.
The aim of this research is to recognize the tasks undertaken by the headmasters of intermediate schools concerning time- administration, in accordance to the viewpoints of the headmasters of intermediate schools in the Administration of Education of Al-Karkh the Third. The sample of this research consists of (60) headmasters and &n
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