The petroleum system of Halfaya oil field shows that the hydrocarbon generation of these Formations such as Sha′uiba and Nahr Umr are immature and have generated few oil TR ≤ 50% which are neglected as compared to Formations below them which are very rich source rock. The Formations of Yamama, Ratawi and Sulaiy are mature with TR ≤ 100%. Other Formations such as Sargelu ,Najma,Zubair and Gotnia are with very high maturity with TR ≥ 100% and completely generated hydrocarbon and depleted after hydrocarbon are expelled and migrate to reservoir rock of structure traps and this study indicates that the major seals of Upper Jurassic are Gotnia and Allan Formations and of Middle Miocene is LowerFars fatha Formation.

A new 4-thiazolidinone, substitutedbenzylidene-thiazolidinone and tetrazole were synthesized from thiosemicarbazone and hydrazone. The thiosemicarbazone was prepared by the reaction of thiosemicarbazide with aldehyde derivative from L-ascorbic acid in absolute ethanol using glacial acetic acid as a catalyst. 1, 3-thiazolidin-4-ones were synthesized from the condensation of thiosemicarbazones with chloroacetic acid in presence of anhydrous sodium acetate. A 1, 3- thiazolidine-4-one was reaction with several 4-substitutedaldehydes to produce new derivatives with a double bond at the position-5 of the 4-thiazolidinone ring. While the tetrazole compounds were synthesized by 1, 3-cycloaddition reaction of sodium azide and hydrazone compounds in

Atopic dermatitis (atopic eczema), is a common familial chronic inflammatory skin disease, determined by xerosis, itching, scaly and erythematous skin lesions, and high serum levels of IgE. Between 10 to 20% of children and 1 to 3% of adults worldwide affected by it and has negative medical and social effect on patients and their families. To evaluate the effectiveness of Phytosterol Fraction of Chenopodium Murale on induced atopic dermatitis (AD) of mice; Forty mice were included in the study, divided in to four groups (10 mice/group): apparently healthy, induced AD without treatment, induced AD treated with Tacrolimus 0.1% ointment, and induced AD treated with Phytosterol Fraction of Chenopodium Murale cream 3% topica

In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r

Medical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform w

Magnetic  Resonance  Imaging  (MRI)  is  one  of  the  most important diagnostic tool. There are many methods to segment the

tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment   the   brain   with   high   precision.   In   this   project,   the unsupervised  classification methods have been used in order to detect the tumor  disease from MRI images.    These metho