The researcher concluded that it consists of several types of structures, where the intellectual structure related to the choice of the idea, its treatment, its effect, the choice of the topic, the way ideas are addressed and presented in the film, and then the dramatic structure of the film's characters, the formulation of its events, its dramatic composition, its temporal arrangement, the identification of the parties to the conflict and their management, then these are formulated. Visions and ideas through the visual and audio signal systems, which work to highlight the stylistic features in the character of the film director.

         This research deals with the audio part of the cinematic film, which is the sound and its elements inside the space of the cinema picture. It also deals with the psychological side of the sound and the effects made by the sound on the audience through the carefully studied use of the film maker in employing the sound and the picture. For the importance of this element, most of the directors were aware of the seriousness that sound causes to the cinematography, and consequently working as a whole such as the  indications, meanings, symbols, metaphors ,transitions…etc. The research included the methodological framework which consists of the research problem, in which the researcher ma

Let R be a ring with 1 and W is a left Module over R. A Submodule D of an R-Module W is small in W(D ≪ W) if whenever a Submodule V of W s.t W = D + V then V = W. A proper Submodule Y of an R-Module W is semismall in W(Y ≪_S W) if Y = 0 or Y/F ≪ W/F ∀ nonzero Submodules F of Y. A Submodule U of an R-Module E is essentially semismall(U ≪es E), if for every non zero semismall Submodule V of E, V∩U ≠ 0. An R-Module E is essentially semismall quasi-Dedekind(ESSQD) if Hom(E/W, E) = 0 ∀ W ≪es E. A ring R is ESSQD if R is an ESSQD R-Module. An R-Module E is a scalar R-Module if, ∀ , ∃ s.t V(e) = ze ∀ . In this paper, we study the relationship between ESSQD Modules with scalar and multiplication Modules. We show that

Background: Multiple sclerosis is a chronic heterogeneous demyelinating axonal and inflammatory disease involving the Central Nervous System [CNS] white matter with a possibility of gray matter involvement in which the insulating covers of nerve cells in the brain and spinal cord are damaged. This damage disrupts the ability of parts of the nervous system to communicate, resulting in a wide range of signs and symptoms. Cerebral venous insufficiency theory was raised as a possible etiology for the disease at 2008 by Zamboni an Italian cardiothoracic surgeon. This theory was defeated by Multiple Sclerosis[ MS] researchers and scientists who thought that the disease is an autoimmune rather than vascular.

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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

A novel analytical method is developed for the determination of azithromycin. The method utilizes continuous flow injection analysis to enhance the chemiluminescence system of luminol, H2O2, and Cr(III). The method demonstrated a linear dynamic range of 0.001–100 mmol L-1 with a high correlation coefficient (r) of 0.9978, and 0.001–150 mmol L-1 with a correlation coefficient (r) of 0.9769 for the chemiluminescence emission versus azithromycin concentration. The limit of detection (L.O.D.) of the method was found to be 18.725 ng.50 µL−1 based on the stepwise dilution method for the lowest concentration within the linear dynamic range of the calibration graph. The relative standard deviation (R.S.D. %) for n = 6 was less than 1.2%