Background: A Catheter-associated with candidiasis infection is the most common nosocomial infection and the objective of this work is to isolate and identify Candida species from catheterized patients by ordinary culture and PCR.Objective:To study the isolation and identification of Candida species from catheterized patients by culture media and polymerase chain reaction(PCR).Methods: One hundred and thirty five Candida species isolates were obtained from urine culture of catheterized specimens from male and female patients , During the period between October 2011 to April 2012 , attending AL-Ramadi general teaching Hospital. A quantitative urine culture for isolation and identification of Candida species was. The isolation of Candida s

This Study was conducted to investigate vaginitis in women who live in Baghdad City. Results Revealed that Candida spp. were the causal agent of 38.5% of symptomatic cases the yeasts Candidaalbicans, C.glabrata, C.tropicalis, C.parapsilosis and C.krusei were isolated with the percentage of 38.1, 9.1, 3.9, 2.6, 1.3 respectively also there were 18% of women in control group carrying Candida spp. The direct smear method were not efficient because the percentage of infection was 17.5% comparing with the culture method the sensitivity of direct smear method was 45.5% The percentage of WBC to Epithelial cells was less than one in 76.6% of women.

The records of Primary Health Care Centres (Al-Risafa section of Baghdad) were inspected for communicable diseases during the period January-April 2006. There were 8622 recorded cases (the diagnosis was based on a clinical examination and laboratory findings), which were distributed as 4782 (55.5%), 1430 (16.6%), 1604 (18.6%) and 806 (9.3%) for Sadar city, Risafa, A'adhamyiah and Mada'in, respectively. The highest frequency was reported for chicken pox (42.7%), followed by mumps and typhoid fever (20 and 13.7%, respectively), while diphtheria and cholera were not recorded. These three most frequent diseases were further analyzed, and their distribution showed a significant difference (P ? 0.001). April was the month of the highest recorded

    Twenty-two of the Starling Sturnus vulgaris Linnaeus, 1758 were collected in Baghdad city during the period from January to September, 2014, and examined for endoparasites. Ten (45.45%) were found infected with either the cestode Passerilepis crenata (Goeze, 1782) (31.81%) or the nematode Dispharynx nasuta (Rudolphi, 1819) (13.63 %). Morphometric and meristic features for these worms were expressed. D. nasuta is recorded here for the first time from S. vulgaris for Iraq.

This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi

Surface water flow samples were collected with distances downstream over Saqlawiya main drain whose stretch of about 24.5 km. The drain travels through different land use pattern, before, flowing into Tigris River. Eight sampling points were carefully
selected downstream the channel during dry season. The examined water parameters were pH, NH3, NO3, PO= 4, BOD5, COD, TDS, S.S, Cl-, SO= 4, Na+ , Ca+2, Mg+2, and Oil and Grease. Descriptive and inferential methods through finding the best curve fit correlation were employed in the study to test the strength of the association between water chemical characteristics and distance downstream the channel. A comparison of the values of chemical parameters at the Al-Saqlawiya Drain-Tigris Riv

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

The study seeks to identify e-governance requirements in human resources management, which are (administrative requirements, technical, human, financial, and security) which is a new style differs from the traditional management pattern, where work depends on multiple forms and methods of Tools, (e. g. computers and various electronic software), by relying on powerful information systems that help to make management decisions as quickly and less effortless and less expensive to keep up with the tremendous technological advancements in the field of information and communication technology revolution.

 The sample included 132 Person who constitute a position (Director General, assistant Director General, section managers and d