Separation of Trigonelline, the major alkaloid in fenugreek seeds, is difficult because the extract of these seeds usually contains Trigonelline, choline, mucilage, and steroidal saponins, in addition to some other substances. This study amis to isolate the quaternary ammonium alkaloid (Trigonelline) and choline from fenugreek seeds (Trigonella-foenum graecum L.) which have similar physiochemical properties by modifying of the classical method. Seeds were defatted and then extracted with methanol. The presence of alkaloids was detected by using Mayer's and Dragendorff's reagents. In this work, trigonilline was isolated with traces of choline by subsequent processes of purification using analytical and preparative TLC techniques.
... Show MoreIn this effort, we define a new class of fractional analytic functions containing functional parameters in the open unit disk. By employing this class, we introduce two types of fractional operators, differential and integral. The fractional differential operator is considered to be in the sense of Ruscheweyh differential operator, while the fractional integral operator is in the sense of Noor integral. The boundedness and compactness in a complex Banach space are discussed. Other studies are illustrated in the sequel.
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The Audit evedances represent the reconciliation tools between the Financial data shown on financial statements, and the level of satisfaction level of the Auditor about these statements. According that, the Auditor try to achieve the highest quantity of These evidances, and the most satisfactive of it…, but that will be so hard sometimes, when the internal controlling system is not good, and when the Auditor had some satisfied evidences, but not sharp… So, this research comes to inspect the relation between the quantity, and the level of satisfaction, and argument to prove that evidences gives. This research assumes that getting enough evidences leads to reduce faults, improves the auditing operation, and avoids risks. The research
... Show MorePresent investigation aimed to study plasma BNP hormone estimation as predictor of brain stroke and neurocognitive in relative with other limitations in CKD patient. The case control experimental study was conducted on CKD patient at Yarmuk Hospital at Baghdad Province, Iraq from February to April 2020. The results showed that there were significant variances (P< 0.05) between CKD patients and control group, there was significant increase in BNP hormone and cystatin-C levels at patient, while ihematological parameters were significantly decreased. The parameters of lipid profile were significantly increased (P<0.05). The result revealed that there was relationship between BNP hormone level and CKD. This support that BNP level is related wit
... Show MoreBackground: Depression is a state of low mood and aversion to activity, it can affect a person's thoughts, behavior and sense of well-being. It can affect oral health and lead to an increased risk of dental caries. Dental caries is the most common oral infectious diseases that stresses the immune system and causes changes in cellular and molecular components of peripheral blood and C-Reactive Protein is one of these components, considered a key biomarker of inflammation. This study was conducted to assess the effect of depression status on dental caries among 17 years old secondary school female students in relation to salivary C-Reactive Protein. Materials and Methods: A cross sectional study was carried and the whole sample composed of
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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