The design of this paper is to find the possible correlation of Epstein Barr virus infection ina group of Iraqi women with cervical carcinoma though detection of Latent Membrane Protein 1 (LMP1) in these cervical tissues. Paraffinized blocks of two groups were included. The first sample of 30 cervical carcinomatous tissues and 15 biopsies from an apparently normal cervical tissues. All the samples were sectioned on a positive charged slides with 4 mm – thickness then submitted for immunohistochemical (IHC) staining to detect viral LMP1 expression. Sixty three percentage (19 out of 30) of the studies group showed positive overexpression as shown in with a significant association of the expression with cervical cancer with a significant ass

Increased epidemic when Akbari in his book Explanation in the expression of the Koran

مشكلة البحث:

يبقى الفن ولا زال في جميع حالات التعاقب البشري ومراحل التطور الانساني الاكثر انطلاقة وتميزاً في التعبير عن واقع الانسان وعن مشاعره وانفعالاته وافكاره ذات الصلة بتأثيرات البيئة المحيطة به.

والفن ولاسيما (الرسم) يمثل وسيلة من وسائل التعبير الفني بل يكاد يكون الرسم وسيلة الانسان الاولى التي عبر فيها بخطوط مرئية عن مجالات حياته وعلاقته بالبيئة التي عاش فيها، ويقينا

<span>As a result of numerous applications and low installation costs, wireless sensor networks (WSNs) have expanded excessively. The main concern in the WSN environment is to lower energy consumption amidst nodes while preserving an acceptable level of service quality. Using multi-mobile sinks to reduce the nodes' energy consumption have been considered as an efficient strategy. In such networks, the dynamic network topology created by the sinks mobility makes it a challenging task to deliver the data to the sinks. Thus, in order to provide efficient data dissemination, the sensor nodes will have to readjust the routes to the current position of the mobile sinks. The route re-adjustment process could result in a significant m

<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

Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

Internet paths sharing the same congested link can be identified using several shared congestion detection techniques. The new detection technique which is proposed in this paper depends on the previous novel technique (delay correlation with wavelet denoising (DCW) with new denoising method called Discrete Multiwavelet Transform (DMWT) as signal denoising to separate between queuing delay caused by network congestion and delay caused by various other delay variations. The new detection technique provides faster convergence (3 to 5 seconds less than previous novel technique) while using fewer probe packets approximately half numbers than the previous novel technique, so it will reduce the overload on the network caused by probe packets.

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

In this work, a simple and new method is proposed to simultaneously improve the physical layer security and the transmission performance of the optical orthogonal frequency division multiplexing system, by combining orthogonal frequency division multiplexing technique with chaotic theory principles. In the system, a 2-D chaotic map is employed. The introduced system replaces complex operations such as matrix multiplication with simple operations such as multiplexing and inverting. The system performance in terms of bit error rate (BER) and peak to average ratio (PAPR) is enhanced. The system is simulated using Optisystem15 with a MATLAB2016 and for different constellations. The simulation results showed that the  BE