Background: Obesity represents a clear and
present danger to the health of children and
adolescents. Its prevalence among American
youth has doubled in the past 3 decades, and
there are now more overweight and obese
adults in the United States than adults of
normal weight.
Objectives of the study:
1- Finding whether screen watching among
adolescents has an effect on increasing
prevalence overweight and obesity.
2- The effect of other variables like physical
activity, eating in front of screen, eating under
stress on obesity and overweight among the
subjects sample.
Patients &Methods: During 3 months period a
cross sectional survey was conducted on 4
high schools at Baghdad with total

A sensitivity-turbidimetric method at (0-180^o) was used for detⁿ. of mebeverine in drugs by two solar cell and six source  with C.F.I.A.. The method was based on the formation  of  ion pair for the pinkish banana color  precipitate by the reaction of Mebeverine hydrochloride with Phosphotungstic acid. Turbidity was measured via the reflection of incident light that collides on the surface particles of   precipitated at 0-180^o. All variables were optimized. The linearity ranged of Mebeverine hydrochloride was 0.05-12.5mmol.L^-1, the L.D. (S/N= 3)(3S_B) was 521.92 ng/sample depending on dilution for the minimum concentration , with correlation coefficient r = 0.9966while was R.S.D%

This study aimed to clarify the importance of ecological taxation in achieving sustainable development, by analyzing a set of economic measures such as taxes, taxes levied by the legislation in the field of ecology, to fight against pollution.       And we tried to evaluate this initiative in Algeria. The results of the study showed that economic measures of ecological taxation contribute to achieving sustainable development, and Although Algeria has adopted a series of ecological tax mechanisms, it is far from keeping pace with developments in this area. 

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

KE Sharquie, AA Al-Nuaimy, FA Al-Shimary, Saudi medical journal, 2005 - Cited by 20