As Alkaloids known for their pharmaceutical importance; this research included the extraction of crude alkaloids of three plants (Zingiber officinale Roscoe., Thymus vulgaris L. and Acacia arabica L.) and evaluate their activity as coagulant agent by using three degraded concentrations of each plant extract and tested them on lab mice through the observation of the variations in bleeding time (BT), clotting time (CT) and platelet count. The results revealed differences in the percentage of alkaloids in the plants under the study; Z. officinale extract was the higher one followed by T. vulgaris and A. arabica respectively. Z. officinale extract was also the most effective plant as coagulant factor than other two plants as it decreased both BT and CT and increased platelets count more than what T. vulgaris and A. arabica affected on blood characters mentioned before. This makes crude alkaloids extract of Z. officinale dry rhizomes is the best plant product therapeutically and commercially.
Evaluation of the activity of crude alkaloids extracts of Zingiber officinale Roscoe, Thymus vulgaris L. and Acacia arabica L. as coagulant agent in lab mice.
alkaloids
coagulant agent
bleeding time
clotting time
platelets count.
Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
Boosting E-learner’s Motivation through Identifying his/her Emotional States
Agent
Distance-learning
Emotional states
GMM
Motivation
SDT
Voice analysis
The main objective of e-learning platforms is to offer a high quality instructing, training and educational services. This purpose would never be achieved without taking the students' motivation into consideration. Examining the voice, we can decide the emotional states of the learners after we apply the famous theory of psychologist SDT (Self Determination Theory). This article will investigate certain difficulties and challenges which face e-learner: the problem of leaving their courses and the student's isolation.
Utilizing Gussian blending model (GMM) so as to tackle and to solve the problems of classification, we can determine the learning abnormal status for e-learner. Our framework is going to increase the students’ moti
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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
