Four metal complexes mixed ligand of 2-aminophenol (2-AP) and tributylphosphine (PBu3) were produced in aqueous ethanol with (1:2:2) (M:2-AP:PBu3). The prepared complexes were identified by using flame atomic absorption, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. In addition antibacterial activity of the two ligands and mixed ligand complexes oboist three species of bacteria were also examined. The ligands and their complexes show good bacterial activities. From the obtained data the octahedral geometry was suggested for all prepared complexes. Keywords: Mixed ligand complexes, spectral studies, 2-aminophenol, tributylphosphine.

The problem of soil contamination is increased recently due to increasing the industrial wastes such as petroleum hydrocarbon, organic solvents, and heavy metals as well as maximizing the use of agricultural fertilizers. During this period, wide development of data collection methods, using remote sensing techniques in the field of soil and environment applications appear and state the suitable technique for remediation. This study deals with the application of remote sensing techniques in geoenvironmental engineering through a field spectral reflectance measurements at nine spots of naturally hydrocarbons contaminated soil in Al-Daura Refinery Company site which is located to the south west of Baghdad using radiometer device to get stan

This study was aimed to extract the effective material from the dry nests of termites and detect its antibacterial activity against some pathogenic bacterial isolates and inhibit synthesis of its biofilm. Termites dry nests were collected and the effective material was extracted then the antibacterial activity was detected using the disc diffusion assay. Results were showed that the extract have antibacterial material from the Termites dry nests, this extract showed antibacterial activity against Gram positive bacteria (Staphylococcus aureus) at (21.5mm) and Gram negative bacteria ( Enterobacter sp. and Pseudomonas aeruginosa) at (26 mm and 20 mm) respectively by inhibiting their growth, as well as its effect on biofilm production o

          The research deal with three variables of exceptional importance to organization business firms. These variables are emotional intelligence, transformational leadership, and organizational performance. The aim of this research is to determine the effect of emotional intelligence and transformational leadership on organizational performance at the banking sector, which is represented by Al-Rafidain Bank. The problem of the research is expressed by many questions related with the nature of the interrelationships and effects among research’s variables. The researcher has depended upon the descriptions - analytical approach. on a random sample of (80 ) managers

Arbuscular mycorrhizal fungi and sulphur foam added either at direct seeding or at transplanting decreased the effects of nematode (Meloidogyne javanica) on eggplant growth, and improved plant health. Experiments were conducted to study the possible interactions between the Mycorrhizal fungi (Glomus mossae and Gigaspora spp.) and sulphur foam to control M. javanica on eggplant at seed or seedling stage. Experiment at seed stage treated with Mycorrhiza or sulphur foam alone or together stimulated the growth and reduced Nematode infestation significantly. Treated plant at seedling stage increased plant growth and reduced the number of galls /gm of root system. The interaction between Mycorrhiza and sulpher foam treatments was not significant

Introduction: Infection control or hospital-acquired infections are the major concern of the health care system and agencies. Critical care nurses are on the first-line contact with the patients, so on, they are most vulnerable to acquired infections. It is really important to regularly check their knowledge and practices concerning infection control. Objectives: The study aims to identify the impact of years’ experience on nurses’ knowledge and practices concerning infection control in three hospitals and center (Baghdad teaching hospital, Ibn Al-Nafees hospital, and Ibn al-Bitar center) Methodology: Cross-sectional study was conducted, the study starting from 4th of July 2020 to 13th of November 2020. Non-probability (purposive) sampl

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow