The present study is concerned with studying the effect of aquatic plant Hydrella vorticellata with the concentration of 10 and 20 gm/2 K gm soil on percentage and growth rate of germinating seeds of Hordeum vulgare and Vicia faba. More overs, the quantitative amount of NPK in both tested plants and Hydrella vorticellata, are estimated as an organic fertilizer. It has also been find the total number of root cells, the number of dividing cells, and stages of mitosis. The study reveales, that there are no significant differences between the concentration of hydrella used in germination percentage, growth rate, wet and dry weight. While there are differences in the plants containing NPK. The number of cells dividing stages and number of divid

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

Copper with different concentrations doped with zinc oxide nanoparticles were prepared from a mixture of zinc acetate and copper acetate with sodium hydroxide in aqueous solution. The structure of the prepared samples was done by X-ray diffraction, atomic force microscopy (AFM) and UV-VIS absorption spectrophotometer. Debye-Scherer formula was used to calculate the size of the prepared samples. The band gap of the nanoparticle ZnO was determined by using UV-VIS optical spectroscopy.

Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

Recording two species of larval cestodes Callitetrarhynchus gracilis and Callitetrarhynchus sp. (Cestoda: Trypanorhyncha) parasitic in body cavity of two carangid fishes (Carangoides malabaricus and Megalaspis cordyla) from north west Arab Gulf, Iraq, is described. The species Callitetrarhynchus sp. was recorded for the first time in Iraq in carangid fishes. Also, two fish species (C. malabaricus and M. cordyla) are considered as new hosts for C. gracilis and Callitetrarhynchus sp. in the Arab Gulf. The cestodes were sent to Prof. Dr. Harry W. Palm, Department of Fisheries Biology, Institute Zoo Morphology, Germany for confirmation of the identification.