The Internet has added another dimension to public relations in institutions and organisations, as it provided tools and communication channels, especially social networking sites, which provided information and data on public relations for the institution through these websites. In addition to its communication with its audience, and the audience's interaction with it, so our research tagged (the effectiveness of public relations of the Sunni Endowment Diwan through social networking sites): An analytical study of the official Facebook page of the Diwan that addresses the knowledge and monitoring of the contents of the official Facebook page that public relations adopt in providing information, data, and activities of the Sunni End

Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off permeab

The problem of water scarcity is becoming common in many parts of the world, to overcome part of this problem proper management of water and an efficient irrigation system are needed.  Irrigation with a buried vertical ceramic pipe is known as a very effective in the management of irrigation water.  The two- dimensional transient flow of water from a buried vertical ceramic pipe through homogenous porous media is simulated numerically using the HYDRUS/2D software.  Different values of pipe lengths and hydraulic conductivity were selected.  In addition, different values of initial volumetric soil water content were assumed in this simulation as initial conditions.  Different value

Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off

Cryptosporidiosis is mainly cause a persistent diarrhea in immune compromised patients, BALB/c mice have been suppressed by dexamethasone, tissue Th1, Th2 and Th17 cytokines concentrations in the ileum were significantly diminished in both infected and immunosuppressed mice. Level of IFN-g, TNF-a, IL-12, IL-6, IL-17A was increased in level, IL-4 didn’t increases, in both ileal and spleen tissue. Levels of above cytokines were examined in spleen in order to follow the proliferation of CD4+ T-cell during C. parvum infection.

Background: The adenomatoid odontogenic tumor is a relatively rare benign epithelial odontogenic tumor. It contains both epithelial and mesenchymal components. Few cases presented as an extrafollicular lesion or involve the mandible or associated with other odontogenic lesions. This paper represents a rare case of an extrafollicular AOT. Case presentation: A 24-year-old female had a painless swelling on the right side of the lower jaw since one-month duration. Intraorally there was a well defined fluctuant-blue swelling in the right alveolar premolar region measuring 1×2 cm obliterating the right lower buccal vestibule. Grade II mobility in the vital 44 and 45 teeth were observed. Panoramic radiographs showed a well-defined pear shaped

<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le