Background: Periodontitis and type 2 diabetes mellitus are both considered as a chronic disease that affect many people and have an interrelationship in their pathogenesis. Objective: The aim is to evaluate the salivary levels of interleukin-17 (IL-17) and galectin-3 in patients with periodontitis and type-2 diabetes mellitus. Materials and Methods: The samples were gathered from 13 healthy (control group) and 75 patients split into 3 groups, 25 patients with type 2 diabetes mellitus and healthy periodontium (T2DM group), 25 patients with generalized periodontitis (P group), and 25 patients with generalized periodontitis and type 2 diabetes mellitus (P-T2DM group). Clinical periodontal parameters were documented. The concentration of IL-17

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

Lagrange series and the Bessel function are two classical methods that were created by series expanding from Taylor series. In this paper, the purpose of those two methods was to find the values of the eccentric anomaly for one period (0–360)°. The Matlab program is used to apply the results, the input parameters were eccentricity (0–1), mean anomaly (0–360)°, and finally the parameter W (1–13). The program does not need a tolerance to obtain a precise value for eccentric anomaly like other iterative and non-iterative methods to stop the program; it will stop after completing the required period from 0° to 360° for a body that is determined by the solver. The output will be the final value of the eccentric anomaly. Furthermore,

Elevated C-Reactive Protein (CRP) level in serum is a risk factor for type 2 diabetes ,this relationship is likely to be the cause it means elevated CRP leads to T2D in future . Our objective was to examine CRP in male Type 2 Diabetes(T2D) patients in different age ,we studied 120 male subjects divided to two groups according to their age. First group A age (31 - 40) year old ,60 person )30 control & 30 T2D patients(,3 person for each same age: second group B age (41 – 50) years old ,60 person )30 control & 30 T2D patients(,3 person for each same age. We examined blood sugar ,cholesterol and CRP in each group. and we toke the mean of samples in the same age in each data in all the 4 groups. Our data shows that CRP

Background: Various studies conducted in many parts of the world suggest that there is lack of public awareness and knowledge of various aspects related to diabetes. With proper education, awareness, earlier detection and better care, many complications and co-morbidities can be reduced in diabetic population.Objectives: to evaluate the level of awareness of diabetes mellitus type 2 patients regarding their disease and its' complications.Methods: Cross – sectional survey was conducted during November and December 2011, in the Medical centers of Al Baladiat, Mustansyria and Zuafranya, including 145 type 2 diabetic patients (58.6 % males, 41.4% females) who were subjected to self–structured questionnaires regarding different aspects of

The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.

Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models