The shape dimensions and characteristics of pollen grains and seeds have importance in distinguish among species. Therefore, the present study included morphological characteristics of pollen grains and seeds for eight species belonging to eight genera of the family Brassicaceae and these species are: Alliaria petiolata (M.Bieb) Cavara et Grand, Aubrieta parviflora Boiss, Cardamine hirsuta L., Crambe orientalis L., Eromobium aegyptiacum (Spreng.) Schweinf.et Asch.ex Boiss., Parlatoria cakiloidea Boiss., Sterigmostemum sulphureum (Banksetsol.) Bornm. Neotorularia torulosa (Desf.) Hedge & J. Leonard. The pollen grains were studied in morphological and full measurements were taken, the study showed that the majority of the pollen grai

Background: The symptoms of Parkinson's disease (PD) can lead to problems in movement and coordination that lead to difficulty in maintaining well oral cleaning which can then negatively affect dental status of those Patients. The aim of present study: To evaluate prosthetic status in relation to weight status and occupation by age and gender among Parkinson's disease Patients in Baghdad-Iraq. Methods: The sample consisted of 104 patients with Parkinson disease attended to the Neurosciences Hospital in Baghdad city / Iraq, aged 60-79 years Prosthetic Status was recorded according to WHO(1997). Weight status was recorded according to Trowbridge 1988 and occupation was recorded according to Erikson and Goldthorpe (1992) and Ganzeboom et al (

   The subject of the organizational Ambidexterity of the vital Topics through which it seeks organizations to provide mentalities renewable for their members and maintain its survival and continuity according to different organizational methods of access for strategic success.     The research aims to demonstrate the impact of organizational Ambidexterity in achieving strategic success in the National bank of Iraq, and the questionnaire was prepared as a tool for collecting data and information through sample  survey of (16) managers and heads of departments , The results were analyzed by using the statistical program (SPSS) in calculating  mean, standard deviation, percent and test (f), coefficie

This study aimed to statement jet stream and its impact in the anti-cyclone affecting the climate of Iraq. Through the use of simple correlation coefficient ( Pearson ) that there is a very strong relationship between high- Siberian and both of the jet stream especially during the winter or over the stations of North . Therefore we, observe the relationship be significant in most of the winter months , spring and autumn . Statistically significant , but are different between station and another station , while the study come to another Anti-ciyclon have a real ,significant and statistically relationship corrclation . But this relationship is less than which found in are much less it with the Siberian high , it depends on the type of stat

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

This work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species. This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.