This study was conducted on species composition, morphology, ecological characteristics, biotope distribution, ecological groups, biodiversity indicators and zoogeography of leeches and gastropods distributed in the lower Ak-Buura River. According to the results, it was found that 7 species of leeches belonging to 4 families and 6 genera and 10 species of fresh-water gastropods belonging to 3 families and 6 genera live in the lower Ak-Buura River. In the river, it was observed that leeches are mainly distributed in muddy biotopes, and gastropods are widespread in muddy, stony and sandy biotopes with a lot of plants. Biodiversity indices of leeches and gastropods in the Ak-Buura River were analyzed using the Shannon index. As a result, it

Background: Cystatin C is recently considered to be a good predictor of cardiovascular morbidity and mortality in patients with coronary artery disease (CAD)Objectives: Correlation between cystatin and ischemic heart disease.Methods :One hundred forty patients (140) with ischemic heart disease admitted to thin study at Baghdad teaching hospital from the period June. 2011 to Jan. 2012. Those patients was categorized into three groups.Group (A): patients with ischemic heart failure.Group (B): Patients with myocardial infarction.Group (C) patients with unstable angina.All these groups were in comparison to fifty (50) healthy controls. Fasting serum citation (C) were measured in all patients and control in addition to all other routine inves

From 144 specimens of tonsillitis which were collected from patient, (children of 3 -12 year olds) there were 70 isolates beta hemolytic and 28 isolates were identified as S. pyogenes. Sensitivity of S. pyogenes isolates to antibiotics was tested, all isolates were sensitive to amoxicillin and cephaloxia while higher resistant were to erythromycin. One isolate whiche was 100 A had a stable characteristics and produce pyrogenic toxin was chosen for study and it was purified and characterized from the cell free supernatant of S. pyrogenes strain.

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Abstract:

One of the important things provided by fuzzy model is to identify the membership functions. In the fuzzy reliability applications with failure functions of the kind who cares that deals with positive variables .There are many types of membership functions studied by many researchers, including triangular membership function, trapezoidal membership function and bell-shaped membership function. In I research we used beta function. Based on this paper study classical method to obtain estimation fuzzy reliability function for both series and parallel systems.

The research aims to evaluate the suppliers at Diyala general electric industries company conducted in an environment of uncertainty and fuzzy where there is no particular system followed by the company, and also aims to use the problem of traveling salesman problem in the process of transporting raw materials from suppliers to the company in a fuzzy environment. Therefore, a system based on mathematical methods and quantity was developed to evaluate the suppliers. Fuzzy inference system (FIS) and fuzzy set theory were used to solve this problem through (Matlab) and the problem of the traveling salesman in two stages was also solved by the first stage of eliminating the fuzzing of the environment using the rank function method, w

Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t