The 8 - mixing ratios of 7 - transitions from levels of 26 Mg populated in 23 Na (a, py)26Mg reaction are calculated using a2 — ratio method for the first time in the case of two mixed y - transitions from the same initial level. The results obtained have been compared with 8 - values determined by other methods. The comparison shows that the agreement is excellent. This confirms the validity of this method in calculating the 6 - values of such 7 - transitions.

        يمر عالمنا المعاصر اليوم بمرحلة من التطور والتغيير السريعين لم يسبق له أن مر بهما فـي تاريخ البشرية ، ويشمل مظاهر الحياة  الأنسانية  والأقتصادية والعلمية والتربويـة والنفسية وغير ذلك . وتختلف سرعة هذا التغيير من مجتمع الـى مجتمع آخر , وأدى هذا الى تراكم كميات كبيرة من المعلومات .

         لقد أكد الكثير مـن التربويين أن التطور التكنولوجي فـي ال

ان الهدف من البحث الحالي هو تقويم كتاب الفيزياء للصف الرابع العلمي وفق معايير تصميم وانتاج الانفوجرافيك ومن اجل تحقيق هذا الهدف تم اختيار المنهج الوصفي(تحليل المحتوى) وحدد مجتمع البحث بكتاب الفيزياء للمرحلة الاعدادية الرابع العلمي, المقررة للعام الدراسي 2020-2019 ـ اما عينة البحث فكانت جميع الرسوم والاشكال والمخططات المتضمنة في هذا الكتاب. تم اعداد اداة التحليل المتمثلة بقائمة معايير تصميم وانتاج الانفوجرافيك

           The current study aims to show the importance of plant products as mosquitocides against Culex quinquefasciatus. Castor oil Nanoemulsions were subedit in various ratios including castor oil, ethanol, tween 80, and deionized water by using ultrasonication. Thermodynamic, centrifugation, PH, assay which improved that the formula  of 10 ml  of castor  oil, ethanol  5ml, tween 80 (14 ml) and deionized water 71ml was more stable than other formulas. The stable formula of castor oil nanoemulsion was characterized by transmission electron microscopy (TEM) and dynamic light scattering (DLS). Nanoemulsion droplets were spherical in shape and were found to have a Z-average diameter of 87.4nm. A concentration of ca

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

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

Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To