Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

New hydrazone derivatives of Fenoprofen were synthesized and evaluated for their anti-inflammatory activity by means of egg white induced paw edema method. All the synthesized target compounds were characterized by FT-IR spectroscopy, 1HNMR analysis and by measure of their physical properties. The synthesis of the target compounds(H1-H4) was accomplished by multistep reaction procedures. The synthesized target compounds were show activity in reducing paw edema thickness and their anti-inflammatory effect was comparable to that of the standard (Fenoprofen) except for compound H3 which show anti-inflammatory activity higher than Fenoprofen.

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

Sumatriptan(ST) is a selective agonist at serotonin 5-HTI receptors, as well as 5-HT1B/1D subtypes. It is effective for acute migraine attacks, but has a short half  life (about 2 hours) and low oral bioavailability (15%). The purpose of this study was to develop and optimize nasal mucoadhesive in-situ gel(IG) of ST to enhance nasal residence time for migraine management. Cold method was used to prepare different formulas of  ST nasal IG, using thermosensitive polymers (poloxamer 407  alone or with poloxamer 188) with a mucoadhesive polymer hyaluronic acid (HA) which were examined for gelation temperature and gelation time, pH, drug content, gel strength, spreadability, muc