A total of 54 out of 67 (80.59%) of burn wound swab showed growth of one, or two, or three bacterial pathogens. Pseudomonas aeruginosa was the commonest pathogen, isolated in 48.14% of swab samples, followed by Klebsiella pneumoniae (31.48%), Staphylococcus aureus (27.77%), Acinetobacter baumanii (14.81%), Escherichia coli (7.40%), and Citrobacter freundii, Providencia stuartii, Enterobacter cloacae, with 1.85% isolation percentage for each. All bacterial isolates were tested against 19 antibiotics, and showed multi-drug resistance to 10 antibiotics, or more. The most effective antibiotics were the fifth-generation cephalosporin, ceftobiprole, and and antibiotic combinations, as Ceftazidime / clavulanic acid, and Cefoperazone /sulbactam, an

The insulation system of a machine coil includes several layers made of materials with different characteristics. The effective insulation design of machine coils, especially in the machine end winding, depends upon an accurate model of the stress grading system. This paper proposes a modeling approach to predict the transient overvoltage, electric field, and heat generation in machine coils with a stress grading system, considering the variation of physical properties in the insulation layers. A non-uniform line model is used to divide the coil in different segments based on material properties and lengths: overhang, stress grading and slot. The cascaded connection of chain matrices is used to connect segments for the representation of the

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

In this study, the potential of adsorption of amoxicillin antibiotic (AMOX) from aqueous solutions using prepared activated carbon (AC) was studied. The used AC was prepared from an inexpensive and available precursor (sunflower seed hulls (SSH)) and activated by potassium hydroxide (KOH). The prepared AC was examined for its ability to remove AMOX from aqueous contaminated solutions and characterized with the aid of N2 -adsorption/desorption isotherm Brunauer–Emmett– Teller, scanning electron microscopy, energy-dispersive X-ray spectroscopy and Fourier-transform infrared. Zeta potential of the prepared activated carbon from sunflower seed hulls (SSHAC) were studied in relation to AMOX adsorption. The physical and chemical propert

This article explores the role of talk shows in setting the public's agenda regarding political mobilization in Iraq. The researcher designed a questionnaire that contains both closed and open-ended questions to allow respondents to express their opinions more freely.

 The researcher chose a phased purposive sample consisting of 294 respondents. The data was then subjected to analysis and verification using the Statistical Package for the Social Sciences (SPSS).

Eye loss may be caused as a result of eye trauma, accidents, or malignant tumors, which leads the patient to undergo surgery to remove the damaged parts. This research examines the potential of computer vision represented by Structure from Motion (SfM) photogrammetry in fabricating the orbital prosthesis as a noninvasive and low-cost technique. A low-cost camera was used to collect the data towards extracting the dense 3D data of the patient facial features following Structure from Motion-Multi View Stereo (SfM-MVS) algorithms. To restore the defective orbital, a Reverse Engineering (RE) based approach has been applied using the similarity RE algorithms based on the opposite healthy eye to rehabilitate the defected orbital precisely