230 stool samples were collected from 2 state homes for (males and females) to investigate
the infection of different intestinal parasites (pathogenic and non-pathogenic).
The infection rate was higher among males 15.7% than females 6%, these rates were
increased when concentration method was employed up to 54.8% for males and 8.7% for
females significantly.
Most infected orphans were found to harbor single parasite followed by double, triple
parasites.
The highest rate of infection was found among young age group (1-5) years old, while
the older age groups got lowest rates.
Of helminthes, the commonest parasite was Hymenolepis nana 5.7% and of protozoa, the
commonest intestinal parasite was Giardia lamblia
The determination of river pollution impact on the performance of water treatment plants is achieved by two main objectives. The first is to study raw and treated water qualities and comparing them with standards and the second is to evaluate the treatment plants efficiency. The analyzed data were those water quality parameters in relation to physical, chemical and bacteriological characteristics for river water and produced water by seven water treatment plants located on Tigris River passing through Baghdad City.
The results of this study indicated that all raw water characteristic are within the surface water standards established by Iraqi and USA criteria except Bacterial Counts.
Tigris River water is of good quality to be trea
Acuaria skrjabini Ozerskaya, 1926 and Dispharynx nasuta (Rudolphi, 1819) Stiles and Hassall, 1920, were found embedded in the mucosa of the gizzards of 26.97% of house sparrows, Passer domesticus biblicus collected in Baghdad City. Their morphometric and meristic features were expressed and compared with that reported in other studies.
One hundred thirty seven Staphylococcus spp. isolates were isolated form one hundred fifty clinical specimens which were collected from several hospitals at Al-Sulaimaniya city. Seventy two Staphylococcus aureus isolates, 28 Staphylococcus epidermidis isolates and 37 isolates related to other coagulase negative staphylocci (S. chromogenes, S. lugdunensis, S. cohnii, S. saprophyticus, S. hominis, and S. haemolyticus constituted 3.60%, 2.20%, 2.90%, 2.90%, 6.60%, and 8.80%, respectively). Burn specimens represented the highest (P< 0.05) reservoir for S. aureus and S. epidermidis isolates. Staphylococci developed variable susceptibility to 4 antibiotics (cefoxitin; 30 μg, oxacillin; 1μg, methicillin; 5μg, and cefotaxime; 30 μg). Neve
... Show MoreObjective :To evaluate elderly's environmental practices concerning fall prevention at governmental elderly care homes in Baghdad city. Methodology: A quazi- Experimental study was carried out in governmental elderly care homes at Baghdad city, during the period 1st, June 2014 to 30th November, 2014 , selected a purposive " Non – probability " sample of (40) elderly men and women aged (60) years old and over who were resident in governmental elderly care homes " Al Ceelakh and Al Sader elderly care homes", the data was collected through the use of constructed questionnaire that consist of (23) items,
Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreCodes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
... Show MoreThis paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere
... Show More