Twenty bacterial isolates were identified as Staphylococcus aureus collected from wounds and catheters related infections. A capsulated S. aureus isolate was chosen after performing serum soft agar test, for this study Neutropenic mice were challenged with capsulated S. aureus ,and the effect of G-CSF with or without moxifloxacin was studied. The results indicated that the addition of G-CSF to moxifloxacin therapy have a synergistic effect in the killing of the bacteria, while when each G-CSF and moxifloxacin were used seperately have a similar effect on bacterial killing. It was found that the moxifloxacin has the same activity as G_CSF but is less costly than the latter one.

Background:Amino acid disorders are a major group of inborn error metabolism (IEM) with variable clinical presentation; its diagnosis constitutes a real challenge in a community with high consanguinity rate and no systematic newborn screening.

Objectives: to provide data about amino acid disorders detected in high-risk Iraqi children by using quantitative amino acid fluorescent high performance liquid chromatography (HPLC) analysis.

Type of the study: Cross-sectional study.

Methods: a descriptive cross sectional study from 1st February to 1st December 2014, at Neurological ward and clinic of the Children Welfare teaching Hospital, in Baghdad - Ira

 Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved.  In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)

Composite materials are widely used in the engineered assets as aerospace structures, marine and air navigation owing to their high strength/weight ratios. Detection and identification of damage in the composite structures are considered as an important part of monitoring and repairing of structural systems during the service to avoid instantaneous failure. Effective cost and reliability are essential during the process of detecting. The Lamb wave method is an effective and sensitive technique to tiny damage and can be applied for structural health monitoring using low energy sensors; it can provide good information about the condition of the structure during its operation by analyzing the propagation of the wave in the

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate

This study presents, for the first time, an innovative Jet Plasma-assisted technique for the green synthesis of TiO₂@Ag core–shell nanoparticles using chard leaf extract as a natural reducing and stabilizing agent. The Jet Plasma provides a highly energetic environment that accelerates nucleation and core–shell formation at low temperatures without toxic precursors. The synthesized nanoparticles exhibited uniform and stable structures, as confirmed by comprehensive characterization techniques including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), ultraviolet–visible (UV–Vis) spectroscopy, transmission electron microscopy (TEM), and zeta potential analysis. XRD patterns confirmed the crystalline anatase

 Humanity is confronted with a growing array of environmental challenges that demand immediate attention and cannot be disregarded. One of the issues the world faces is air pollution, which presents a significant risk to both the environment and human well-being. The capitalist system has a great impact on the exacerbation of air pollution and environmental deterioration. This impact is reflected in Caryl Churchill’s post-apocalyptic play Not Not Not Not Not Enough Oxygen (1971). The play presents a futuristic scenario in which humanity faces grave consequences due to the polluting practices of capitalism and the unsustainable exploitation of natural resources. It depicts a future in which environmental degradation drives people