The launch of the EU’s Eastern Partnership in 2009 intended to signal a new, elevated level of EU engagement with its Eastern neighborhood. Yet there remain several long-simmering and potentially destabilizing conflicts in the region, with which EU engagement thus far has been sporadic at best. The Union’s use of its Common Security and Defense Policy (CSDP) in the region and to help solve these disputes has been particularly ad hoc and inconsistent, wracked by inter-institutional incoherence and undermined by Member States’ inability to agree on a broad strategic vision for engagement with the area.

The three CSDP missions deployed to the region thus far have all suffered from this incoherence to various extents. In particu

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −

   The technology of reducing dimensions and choosing variables are very important topics in statistical analysis to multivariate. When two or more of the predictor variables are linked in the complete or incomplete regression relationships, a problem of multicollinearity are occurred which consist of the breach of one basic assumptions of the ordinary least squares method with incorrect estimates results.

 There are several methods proposed to address this problem, including the partial least squares (PLS), used to reduce dimensional regression analysis. By using linear transformations that convert a set of variables associated with a high link to a set of new independent variables and unr

Background: Breast cancer is the commonest type of malignancy among women worldwide and in Iraq. Tru-cut needle biopsy technique provides adequate tissue for histopathological diagnosis of suspected breast lumps and assessment of hormonal receptors (estrogen, progesterone and HER2neu) prior to surgical operation.
Objectives: To assess estrogen, progesterone andHER2neu expression using breast cancer tissue specimens obtained by tru-cut biopsy, to correlate the findings with clinicopathological parameters of known prognostic significance in breast cancer patients.
Patients and Methods: This prospective study was held within the Main Referral Center for Early Detection of Breast Tumors/Medical City Teachi

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

This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

Background: Rheumatoid arthritis (RA) disease activity plays a central role in causing disability both directly and via indirect effects mediated through joint damage. Evaluation of RA disease activity is therefore important to predict the outcome and effectiveness of therapeutic interventions during follow-up. Clinical disease activity index (CDAI) is new simple tool for measurement of disease activity.
Objectives: To assess validity and reliability of CDAI in comparison to disease activity score-28 joints (DAS28) in Iraqi patients with active RA.
Patients and Methods: Sixty nine Iraqi RA patients were included in this study. All patients were fulfilling the ACR classification criteria and active. Full history was taken and comple

The research took the spatial autoregressive model: SAR and spatial error model: SEM  in an attempt to provide practical evidence that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial and that includes all of the spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. The spatial analysis had been applied to Iraq Household Socio-Economic Survey: IHS

Colorectal cancer is the world's 3^rd most frequent malignant neoplasm and the 4^th most common cancer in Iraq. Leptin and Adiponectin are two major Adipocytokines produced by adipose cells that have opposite effects on the formation of colorectal tumors. Leptin induces tumor growth and metastasis, whereas Adiponectin inhibits it. 1,25-Dihydroxyvitamin D controls and limits cancer cell proliferation, differentiation, and survival. Vitamin C deficiency, on the other hand, has been regularly detected in cancer tissues and has potent anti-cancer properties. The purpose of this study was to look at the biochemical role of circulatory Adipocytokine levels (Adiponectin and Leptin) as well as the anti-cancer potentials of Vi