It was found that Pkvtomyza horticola Goureau infested 36 plants belonging to 11 families of
dicotyledons. only two of which belong to Monocotyledons. Most of plants species are from
compositae and Cruciferae families.

Traditional folk medicine is applied in the treatment of diversity chronic and acute conditions all over the worlds.  This study was carried out to assess the capability of aqueous beetle cocoon extract (Lorinus maculates F.) commonly known as (Tihan) in stimulating immune  response. Adult mice (5 in each group) were divided into two groups: the first one orally administered with 150 mg/kg and the second group received normal saline as a control group for 14 days. Bone marrow and spleen were proceed for mitotic index and phagocytosis estimated. The results showed a significant increase in mitotic index and phagocytosis in treaded mice in comparing with the negative control. These results concluded that Tihan has a

Background and Aim: due to the rapid growth of data communication and multimedia system applications, security becomes a critical issue in the communication and storage of images. This study aims to improve encryption and decryption for various types of images by decreasing time consumption and strengthening security. Methodology: An algorithm is proposed for encrypting images based on the Carlisle Adams and Stafford Tavares CAST block cipher algorithm with 3D and 2D logistic maps. A chaotic function that increases the randomness in the encrypted data and images, thereby breaking the relation sequence through the encryption procedure, is introduced. The time is decreased by using three secure and private S-Boxes rather than using si

An experimental study was conducted to evaluate the effect of AL-coholic extract alkaloid of Cordia myxa leafs in fourth larval stage of lesser grain borer Rhyzopertha dominica. Using alkaline extracts of 8%, the study has been shown clear effect increased in mortality rate for fourth larval stage 93.3% and degressed to 66.6% at 4% concentrate to 13.3% with control treatment .Ahigher percentage of pupal mortality 16.6% at 4% concentrate has been observed, while no natural emergence carried out at concentrates of 4.6% comparing with control treatment of 86.66%, at the same time percentage of deformation has been increased to 16.66% at 4% of extracts and degressed to 6.66% at 6% while no deformation have been shown with control treatment .

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

Background: Diabetes mellitus (DM) accompanied with an increase in the death rate and represents a significant public health challenge. It is the cause of other disorders and infection in many body organs. Hence, it is important to study the possible changes in the immunological components in the serum of diabetic patients which are not well understood. In this work, serum C3, C4, IgA, IgG, and IgM were estimated in the patients with insulin dependent diabetes mellitus (IDDM) and compared with healthy persons. Patients and Methods: Twenty-one insulin dependent diabetic patients in addition to twenty-four healthy persons as control group were participated in this study. Serum C3, C4, IgA, IgG, and IgM were measured by using immunodiffusio

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c