Forty – two elderly hypothyroidism patients and forty – two apparently healthy as control groups , divided to (21) male (M) and (21) female (F) also (21) control male C(M) and (21) control female C(F) aged > 60 years, were tested for the presence of thyroid peroxidase autoantibody (TPo – Ab) and thyroglobulin auto antibody (Tg – Ab) , also for Se and Zn levels in their sera . The results revealed a significant increase in (TPO – Ab) and (Tg – Ab) for group (M) and (F) compared to control group , also a siginificant increase in TPo – Ab and Tg – Ab for (F) compared to (M) was found. A significant decrease in Se and Zn level for (M) and (F) compared to control group, while no significant difference between (M) and (F). In conc

The researcher aims to  detect the emotive equanimity in kindergartens teachers,also to uncover the anxiousness in children of kindergartens,then to detect the relationship between them,then to choose the simple random way which is about(180) teachers and children,when the twore searchers made two tools to measure the emotive equanimity and the anxiety for both teachers and children,statistical methods had been used include:(pearsons correlation coefficient,t-test for one sample,t-test for two independent samples are individuals).the researcher led to multiple results:

1-the teacher has an emotive equanimity.

2-children has no anxiousness.

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.

        In this paper, the Magnetohydrodynamic (MHD) for Williamson fluid with varying temperature and concentration in an inclined channel with variable viscosity has been examined. The perturbation technique in terms of the Weissenberg number  to obtain explicit forms for the velocity field has been used. All the solutions of physical parameters of the Darcy parameter , Reynolds number , Peclet number  and Magnetic parameter  are discussed under the different values as shown in plots.