This research deals with and which was entitled: relationship between psychological time and elements of filming expression (one-day event filmsas an example). It is about the relationship of psychological time (internal) with the elements of filming expression and how the time affected when using these elements in terms of its deceleration or acceleration. In particular, this research focus on elements that slow down time or stops it when using these elements. As one day time is short and heavy at the time of spectators in terms of the large number of film events which makes the viewer runs out of breath to understand the nature of those events and then identify the causes and consequences, as they occur in a short time (one day time) a
... Show MoreThree cultivars of the crop Almash (Green Indian VC6089A10, Green Indian VC6173B1319, and Black Indian Gold Star) were tested in a field experiment during the 2022 growing season in Ramadi, Anbar province, to determine the impact of spraying levels of zinc (0, 25, and 50) mg Zn L-1 and manganese (0, 30, and 60) mg Mn L-1 on some growth characteristics. The experiment was conducted using a randomized complete block design (RCBD) with three replicates, with each treatment being tested in a separate split plot. The study found that there were statistically significant differences between zinc levels, with the level giving 50 mg Zn L-1
The current study included the separation of three alkaloid compounds from Anastatica Hierochuntica and studied the effect of the these compounds on cancerous cells , specifically liver cancer it was found that compound number one is the most influential or inhibiting at 50 percent followed by compound number three when using concentration of 400 μg/mL.
Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
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