The ground state proton, neutron and matter densities of exotic ¹¹Be and ¹⁵C nuclei are studied by means of the TFSM and BCM. In TFSM, the calculations are based on using different model spaces for the core and the valence (halo) neutron. Besides single particle harmonic oscillator wave functions are employed with two different size parameters  B_c and B_v.  In BCM, the halo nucleus is considered as a composite projectile consisting of core and valence clusters bounded in a state of relative motion. The internal densities of the clusters are described by single particle Gaussian wave functions.

 Elastic electron scattering proton f

<span lang="EN-GB">This paper highlights the barriers that have led to a delay in the implementation of E-Health services in Iraq. A new framework is proposed to improve the E-Health sector using a SECI model which describes how explicit and tacit knowledge is generated, transferred, and recreated in organizations through main stages (socialization, externalization, combination and internalization). Class association rules (CARs) is integrated to mine the SECI model by extracting related rules which correspond to the medical advice. The proposed framework (SECICAR) can be done through a web portal to assemble healthcare professionals, patients in one environment. SECICAR will be applied to the hypertension community to show th

This paper describes the digital chaotic signal with ship map design. The robust digital implementation eliminates the variation tolerance and electronics noise problems common in analog chaotic circuits. Generation of good non-repeatable and nonpredictable random sequences is of increasing importance in security applications. The use of 1-D chaotic signal to mask useful information and to mask it unrecognizable by the receiver is a field of research in full expansion. The piece-wise 1-D map such as ship map is used for this paper. The main advantages of chaos are the increased security of the transmission and ease of generation of a great number of distinct sequences. As consequence, the number of users in the systems can be increased. Rec

Plant extracts occupied a big place in diseases treatment and preserving human health because, they contain many active substances that can be exploited in the field of pharmaceutical manufacturing from natural materials. Therefore, this study was conducted to evaluate the effect of different concentrations of plant extracts for each of Nigella sativa, Alliumsativum and Allium cepa against the fungal growth of Candida albicans that cause many skin diseases and infections to humans as well as Trichophyton mentagrophytes, which affects the hair, skin and nails. These two fungi have been isolated and diagnosed from people who have skin infection. Both fungal isolates were treated with extracts of Nigella sativa, Alliumsativum and Allium cepa

Heavy metals especially lead (Pb), cadmium (Cd), chromium (Cr) and copper (Cu) are noxious pollutants with immense health hazards on living organisms, these pollutants enter aquatic environment in Iraq mainly Tigris and Euphrates rivers via waste water came from different anthropological activities, This study investigated capacity of dried and ground root of water hyacinth (Eichhornia crassipes) in removing the heavy metals from their aqueous solutions. Effects of initial concentrations of the heavy metals and pH of their aqueous solutions were studied. Results of this study revealed excellent biosorption capacity of water hyacinth root in general, removal of Pb was the highest and Cr was lowest. The results showed that the Pb, Cu and C

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.