Federacja Rosyjska wobec Arabskiej Wiosny

The article presents Russia’s reaction to the unrests in the Arab world which took place in 2011. Apparently, Russian Federation is one of the key actors in international relations, ergo analyzing so important events like the Arab Spring, Moscow’s reaction should be taken into account. The North Africa and Middle East are essential in global geopolitics, so Russian Federation had to take appropriate steps. Its reaction was determined by both internal and external factors. Russia’s Arab Spring strategy had to consider kind and scale of Russian interests in each Arab country dealing with unrests. Moreover, relations between Moscow and Washington also were highly important. These two elements, connected with Russian limited means, made it hard to develop right and clear strategy. In addition, Russian establishment had some justified fears about spreading to Russia and former Soviet republics in Central Asia. The following article comprises two parts. The first one is dedicated to the review of Russian reaction and activities towards revolts in the following Arab states: Tunisia, Egypt, Bahrain, Yemen, Libya and Syria. It contains Moscow diplomacy activities and statements of Russian political leaders and diplomats. Russian position and interests in the region of the North Africa and Middle East are explained in the second part of this article. After a short, historical outline, the author explained the role of the Arab world in Russian foreign policy and relation between its reaction to the Arab Spring and its political and economic interests

Estimation of COVID-19 infections in Iraqi governorates using generalized moments method in spatial autoregressive model

At the end of 2019, a new type of virus that infects the human respiratory system was discovered in China, and it was briefly called COVID-19. In March 2020, the world Health Organization (WHO) declared Corona Virus a global pandemic. The Corona Virus is transmitted through air or through contact. The possibility of infection increases in the area or areas neighboring to the area that witnessed a community spread of the virus or when individuals return from that affected area to their areas of residence. Given the limited studies on the impact of affected neighboring areas or countries, this study focused on using the spatial autoregression model, one of the econometric models. Model parameters have been estimated using the Generalized Moment Method (GMM) which has the ability to correct the Endogeneity that occurs by the spatial regression variable as well as due to the endogenous variables. The results showed that the number of infections (Yn) of Corona epidemic increases as there are infections in the surrounding areas and vice versa. This confirms the impact of spatial neighborhood on the spread of infections among neighboring governorates

Synthesis and Characterization of New heterocyclic Polyacrylamides from Derivatives 2-Aminobenzothiazole

The present work involved preparation of new hetro cyclic polyacrylamides (1-9) using reaction of polyacryloyl chloride with 2-aminobenzothiazole which prepeard by thiocyanogen method in the presence of a suitable solvent and amount tri ethyl amine (Et3N) with heating. The structure confirmation of polymers were proved using FT-IR,1H-NMR,C13NMR and UV spectroscopy.Other physical properties including softening and melting points, and solubility of the polymers were also measured

Synthesis and Characterization of New Polyimide by Curing Poly Acryloyl Chloride with Different Amides

The present work involved preparation of new substituted and unsubstituted and poly imides (1-17) using reaction of acryloyl chloride with different amides (aliphatic ,aromatic) in the presence of a suitable solvent and amount tri ethyl amine (Et3N) with heating – the structure confirmation of all polymers were proved using FT-IR,1H-NMR,C13NMR and UV spectroscopy ,thermal analysis (TG) for some polymers confirmed their thermal stabilities . Other physical properties including softening and melting points, PH and solubility of the polymers were also measure

A comparative study between shrinkage methods (ridge-lasso) using simulation

The general linear model is widely used in many scientific fields, especially biological ones. The Ordinary Least Squares (OLS) estimators for the coefficients of the general linear model are characterized by good specifications symbolized by the acronym BLUE (Best Linear Unbiased Estimator), provided that the basic assumptions for building the model under study are met. The failure to achieve one of the basic assumptions or hypotheses required to build the model can lead to the emergence of estimators with low bias and high variance, which results in poor performance in both prediction and explanation of the model in question. The hypothesis that there are no multiple linear relationships between the explanatory variables is considered one of the leading hypotheses on which the model is based. Thus, the emergence of this problem leads to misleading results and high (Wide) confidence limits for the estimators associated with those variables due to problems characterizing the model. Shrinkage methods are considered one of the most effective and preferable ways to eliminate the multicollinearity problem. These methods are based on addressing the multicollinearity problems by reducing the variance of estimators in the model. Ridge and Lasso methods represent the most and most common of these methods of shrinkage. The simulation was carried out for different sample sizes (40, 120, 200) and some variables (P=30, 60) in the first and second experiments arbitrarily and at the level of low, medium, and high correlation coefficients (0.2, 0.5, 0.8). When (p=30, 60) Lasso method has the smallest (MSE) than the Ridge method. The Lasso method proved its efficiency by obtaining the least MSE. Optimal Penalty parameter (λ) chosen from Cross-Validation through minimizing (MSE) of prediction. We see a rapid increase for (MSE) for both (Ridge-Lasso) where the top axis indicates the number of model variables, and when the correlation between variables increases and sample size too, we can see the (MSE) values increase in the Ridge method than the Lasso method. A ridge method gives greater efficiency when the sample size is more significant than variables (

A new shrinkage method for higher dimensions regression model to remedy of multicollinearity problem

This research seeks to present new method of shrinking variables to select some basic variables from large data sets. This new shrinkage estimator is a modification of (Ridge and Adaptive Lasso) shrinkage regression method in the presence of the mixing parameter that was calculated in the Elastic-Net. The Proposed estimator is called (Improved Mixed Shrinkage Estimator (IMSHE)) to handle the problem of multicollinearity. In practice, it is difficult to achieve the required accuracy and efficiency when dealing with a big data set, especially in the case of multicollinearity problem between the explanatory variables. By using Basic shrinkage methods (Lasso, Adaptive Lasso and Elastic Net) and comparing their results with the New shrinkage method (IMSH) was applied to a set of obesity -related data containing (52) variables for a sample of (112) observations. All shrinkage methods have also been compared for efficiency through Mean Square Error (MSE) criterion and Cross Validation Parameter (CVP). The results showed that the best shrinking parameter among the four methods (Lasso, Adaptive Lasso, Elastic Net and IMSH) was for the IMSH shrinkage method, as it corresponds to the lowest (MSE) based on the cross-validation parameter test (CVP). The new proposed method IMSH achieved the optimal shrinking parameter (λ = 0.6932827) according to the (CVP) test, that leads to have minimum value of mean square error (MSE) equal (0.2576002). The results showed when the value of the regularization parameter increases, the value of the shrinkage parameter decreases to become equal to zero, so the ideal number of variables after shrinkage is (p=6)

Metabolic Disturbances of Phosphate in Metabolic Syndrome

Background: Metabolic syndrome MS a cluster of disorders comprising obesity (central and abdominal), dyslipidaemias, glucose intolerance, insulin resistance (or hyperinsulinaemia) and hypertension – is highly predictive of type 2 diabetes mellitus and cardiovascular disease. It should be emphasized that the metabolic syndrome is a syndrome and not a disease. The aim of this study is to evaluate the levels of serum phosphate in different levels in subjects with metabolic syndrome MS and Correlation between serum phosphate levels with metabolic syndrome components. The study was carried out at the National diabetes Center (NDC) /AL-Mustansiryia University ,the period from (Desmber.2011 – May 2012) One hundred forty (140) Iraqi individuals enrolled in the study (100 subject diagnosed as having metabolic syndrome and 40 as control group). The diagnosis of metabolic syndrome was based on Adult Treatment Panel III guidelines. The results of the serum phosphate concentrations in both groups showed that subjects with metabolic syndrome had significantly lower phosphate concentrations 1.52 mg/dl compared with that of control 2.29 mg/dl P?0.0001. The clinical significance of these electrolyte disturbances, as one of the diagnostic criteria of metabolic syndrome. In addition this electrolyte imbalance may have a role in prevention and or treatment of the metabolic syndrome

Improvements of programing methods for finding reference lines on X-ray images

The paper gives an overview of the algorithms developed to obtain reference lines and angles on X-ray images. These geometrical characteristics are used in the medical analysis of human joints. We propose the algorithm’s modifications based on the analysis of numerous X-ray images.These modifications allowed obtaining a great increase in calculation speed and the improvement of final results quality given by the corresponding application. They also lead to a significant reduction of manual tuning of the program, arising only in the rare cases when the properties of given images differ significantly from the mean ones.The authors are grateful to the experts from Iraq – Al-Abayechi Sinan Adnan (Medicine Iraqi Board of Orthopedic Surgery) and Bassam Faleh Hassan (Medicine Arabic Board of Diagnostic Radiology) who attracted the attention to this investigation. They provided us with X-ray materials, gave important advice connected with the implementation and discussed the obtained results

DNA Polymorphism of Gaucher Disease in Iraqi Patients

Gaucher disease is the autosomally recessively inherited deficiency of the lysosomal enzyme glucocerebrosidase. Increasing storage of glucocerebrosides leads to a multisystem disease, the prevalence of which is about 1 : 40,000 in central Europe and up to 1 : 2,000 in some other countries (e. g. Israel). The acute and chronic neuronopathic forms of the disease (formerly defined as Gaucher types 2 and 3) account for only 5 to 10% of all Gaucher patients in Central Europe and Germany and are thus less frequent than the nonneuronopathic disease (formerly defined as Gaucher type 1). Gaucher's disease is usually associated with splenoand hepatomegaly, fatigue, skeletal complications, and several corresponding hematological and laboratory abnormalities. In 5 to 10% of the patients there are also central nervous symptoms such as myoclonic seizures, oculomotoric apraxia and a slight mental retardation. Recent epidemiological data indicate that only 10 to 20% of all Gaucher patients are correctly diagnosed (and treated) in Germany. The diagnosis today can be done in all patients by noninvasive methods, i. e. determination of the glucocerebrosidase activity in peripheral leukocytes and of the genetic defect, in this research the PCR technique was used to analyze the mutation in glucocerebrosidases gene (G ---C). Key words: Gaucher disease (GD), lysosomal storage disorder (LSD),lysosomal enzyme glucocerebrosidase, PCR, Mutation