Seroprevalence of Hepatitis B and C in Coronary Artery Disease Patients in Urmia, Northwest of Iran

Background: Coronary artery disease (CAD) is one of the main causes of death all over the world. Predisposing factors comprise some infectious etiologies with systemic effects such as the hepatitis C virus and HBV-infection might be related to CAD from chronic inflammation process. The relationships between hepatitis B and C virus (HBV and HCV) infections and CAD considered a noticeable health problem. In the present study, we evaluated the seropositivity of HCV and HBV in CAD patients from the Iranian population. Materials and Methods: We conducted a cohort study including 192 CAD subjects. To identify HCV and HBV -infected subjects, a serologic examination comprising Hepatitis B surface antigen (HBsAg) and anti-HCV antibodies (HCV-Ab) tests performed by ELISA method. Also, we examined the biochemical blood parameters such as lipid profile, glycemic parameters, and blood inflammatory factor (C-reactive protein). Results: We identified a very low percent of HBV-infected cases (1.04%). All examined CAD patients indicate the HCV Ab-negative results. The HBV-infected subject had not, hyperlipidemia, and diabetes. HBV infection was not related to the increased risk of CAD. Also, CAD risk factors were not associated with the prevalence of HBV and HCV. Conclusion: According to the results, HCV and HBV infections had very low prevalence in examined subjects and there was not any association between CAD and prevalence of HCV and HBV infections

Development of a hybrid system of artificial neural networks and artificial bee colony algorithm for prediction and modeling of customer choice in the market

With the increasing growth of technology and the emergence of various industries, numerous manufacturers have entered this field. In today's world, sellers and manufacturers find themselves among a vast number of competitors. Therefore, they need to adopt a variety of policies and strategies for their own survival and profitability. Companies should identify their customers’ needs and adopt their own policies based on customers’ purchase behaviors. To this end, attempts have been made to identify the customer choice model since the past decades. These models aim at modeling and predicting customer choice among several brands. Traditional models were of interest for many years and these methods were frequently used with the advent of artificial intelligence and machine learning systems. They could demonstrate very good results. In this study, it has been attempted to present a new method for the modeling and prediction of customer choice in the market using the combination of artificial intelligence and data mining. Indeed, the new model is to be applied in helping managers with decision-making. Hence, probabilistic neural networks have been combined with artificial bee colony algorithm.  The proposed model was tested in a real market and its efficiency and accuracy were finally compared with those of other models, including neural network trained with back-propagation, probabilistic neural networks, and the neural networks trained with genetic algorithm. The results reveal that the hybrid model shows better performance than the other models.Keywords: Consumer Choice Model, Data Mining, Artificial Intelligence, modeling, predicting, probabilistic neural network, artificial bee colony algorith

On soft σ-algebras

The concept of soft sets, which was first introduced by Molodstov, is a new method to deal with uncertainty. In this work, we generalize probability theory to soft probability theory. We first introduce a soft σ-algebra as a collection of soft sets over an initial universe set X with a fixed set of parameters E and show the soft σ-algebra is a parameterized family of σ-algebras over X, then present some of its properties. Finally, we discuss on the soft probability space

TWO-EPOCH OPTIMAL DESIGN OF DISPLACEMENT MONITORING NETWORKS

In the traditional method of optimal design of displacement monitoring networks a higher precision, √2 times better than the desired accuracy of displacements, is considered for the net points in such a way that the accuracy of the detected displacements meets the desired one. However, in this paper, we develop an alternative method by considering the total number of observations in two epochs without such a simple assumption and we call it two-epoch optimisation. This method is developed based on the Gauss-Helmert adjustment model and the variances of the observations are estimated instead of the weights to optimise the observation plan. This method can deliver the same results as the traditional one, but with less required observations in each epoch

Effectiveness of Solution-Focused Group Therapy on the Resiliency of Patients with Multiple Sclerosis (MS) in Tehran

The current research was conducted with the aim of determining the effectiveness of solution-focused group therapy in resiliency of patients with MS. The current research methodology is experimental with pretest-posttest, one-month follow up and control group. The population includes 60 patients covered by Iran MS Society during 2012-2013, among which 30 patients were chosen and by the use of random sampling they were put into two groups of experimental (15 individuals) and control (15 patients) group. Then the experimental group received 8 sessions of solution-focused therapy, while no intervention was conducted on the control group. Tools being used in this research include: Resilience Questionnaire (RQ), and the training package of solution-focused group therapy. Research data were analyzed through MANOOVA test and ANOVA test with repeated measures. Comparing the dimensions of resilience (self-confidence, personal view, flexibility, organized, problem-solving, interpersonal competence, having social relationship, active) by the use of Covariance analysis after eliminating the effect of pretest showed that experimental intervention is generally effective on the resiliency. Results of ANOVA test with repeated measures also showed that the effects of therapy have stayed at the follow-up level