Pseudomonas aeruginosa is an opportunistic pathogen responsible for serious infections. At least three different exopolysaccharides, alginate, polysaccharide synthesis locus (Psl), and pellicle exopolysaccharide (Pel) make up the biofilm matrix in P. aeruginosa . The effect of temperature on the biofilm formation and gene expression was examined by microtiter plate and real-time quantitative polymerase chain reaction (qRT-PCR). To be able to determine the effect of temperature on biofilm formation and gene expression of P. aeruginosa, 303 clinical and environmental samples were collected. Pseudomonas aeruginosa was isolated from 61 (20.1%) and 48 (15.8%) of the clinical and e

The current study included the collection of 175 samples (blood-urea) of patients suffering from rheumatism, collected from Baghdad Teaching Hospital (Educational Laboratory), Al-Kindy Teaching Hospital, Al-Imamian Al-Kadhimya in Medical City in Baghdad at different duration between 2016/10/1-2017/2/1. The bacterial growth results showed that 80% of urea samples positive for bacterial culture, while the rate of samples did not show any bacterial grow this 20%. The isolation subjugates to morphological, microscopically and biochemical tests, as also diagnosis by Api system. The most frequent bacterial pathogenic is E. coli which appeared highly rate (41.97)% followed by E. cloacae (21.25)%, P. aeruginosa (12.5)%, Salmonella (10)% and the pro

            Rheumatoid arthritis (RA) is a systematic autoimmune disorder with chronic inflammation changes of unknown etiology. Various synovial inflammatory and proliferative alterations may contribute to the cartilaginous tissues and invasive bony tissues, leading to destructive joints and malformed bones. This disease is mostly due to infective microorganisms or genetic susceptibility causing immune system disturbances through triggering both T-cells and B-cells. Furthermore, different immune cells may secret cytokines, which are responsible for some RA pathogenesis activity. From ninety individuals, serum sample was collected; thirty of them were normal and sixty cases were patients with RA attended a privet medical clin

AN Adil A, F Basman M, 2009

Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

Objectives of the study: The main objective of the study is to assess the prevalence of hypertension among
cardiac diseases patients and to fiend out relation ship between hypertension and cardiovascular diseases.
Methodology: A descriptive study, using interviewer and questionnaire technique was conducted on cardiac
diseases inpatients of clinic unite at Kirkuk and Azady hospitals from 17th ,June ,2012 to 1st, March , 2013.
Non – probability (purposive) sample of (148) adult patients, (81) females and (67) males with heart disease are
selected from inpatients of clinic unite at Kirkuk and Azady hospitals at kirkuk city. Questionnaire was
developed to assess the items which are related to heart disease patient's (Dise

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve