Back ground: The innervations of the pineal
gland from the superior cervical ganglion have
shown some form of a chromatolysis reaction.
Objective:
1-Tracing the innervations of the pineal gland by
removing the target tissue (the pineal gland in
this study) i.e. (pinealoctomy) and removal of the
superior cervical ganglion i.e. (ganglionectomy).
2- The localization and total number of the
neurons which project into the rat pineal gland
3-The effect of pinealoctomy on the SCG after a
different time interval.
Methods: Twenty five albino rats were used in
this study, Pinealoctomy was done, then after a
different time interval ganglionectomy was done,
in order to study the Chromatolysis in their cel

The search aims to find out the most important requirements for the success of marshes investment and maximize the expected returns of investment was marked by a problem find aquestion for availability requirements necessary for the success of marshes investment has a research community owners decision in the province Maysan the most important conclusions to the search is that the investment great importance in support of the economy and raising the cultural and social level, there is no investment successful but only with configure the investment environment appropriate economic, social, cultural, political, and security ways. the most important recommendations are working on the provision of the investment environment appropria

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The paper deals with the study of the sciences of the Qur’an according to the interpreter, Ayatollah Sayyid Mahmoud al-Talaqani, a religious jihadist figure from Iran. He is the author of the exegesis (Ishraq from Al-Quran), which consists of six parts, which he wrote inside the prisons of the Shah and in exile. Mr. Al-Talaqani agreed with some of the commentators in his positions on the sciences of the Qur’an, and some of them disagreed with others.

An Auto Crop method is used for detection and extraction signature, logo and stamp from the document image. This method improves the performance of security system based on signature, logo and stamp images as well as it is extracted images from the original document image and keeping the content information of cropped images. An Auto Crop method reduces the time cost associated with document contents recognition. This method consists of preprocessing, feature extraction and classification. The HSL color space is used to extract color features from cropped image. The k-Nearest Neighbors (KNN) classifier is used for classification. 

  In the present paper, Arabic Character Recognition  Edge detection method based on contour and connected components  is proposed. First stage contour extraction feature is introduced to tackle the Arabic characters edge detection problem, where the aim is to extract the edge information presented in the Arabic characters, since it is crucial to understand the character content.         The second stage connected components appling for the same characters to find edge detection. The proposed approach exploits a number of connected components, which move on the character by character intensity values, to establish matrix, which represents the edge information at each pixel location .

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to   record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth,

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or