EXTRACTION AND BIOACTIVITY EVALUATION OF ANTIOXIDANT COMPONENTS FROM TEUCRIUM STOCKSIANUM BIOSS COLLECTED FROM UAE

Recently, the industry of Natural Bioactive Compounds (NBAC) is expanding dramatically due to its high medical potentials. High bioactivity of natural extracts from a wide range of plants is evident from the reported literature. For instance, NBACs show antibacterial, antifungal, antimicrobial, anti-inflammatory, anticancer and antioxidant activities. Teucrium stocksianum Boiss. from the Lamiaceae family is a known herb in the traditional medicine in United Arab Emirates. Multiple bioactivities of T. stocksianum were recorded such as anti-inflammation, analgesia, antioxidation, anticancer, antinociception and antimicrobial bioactivity. In this thesis, the extraction of NBACs from T. stocksianum was studied with Microwave-assisted extraction using Deep eutectic solvent (MAE-DES). The resultant yield of extraction and antioxidant capacity were compared with the results of Ultrasound-assisted extraction with water, Hydrodistillation and Soxhlet with four different solvents (methanol, ethanol, Diethyl ether and n-hexane). MAE-DES showed higher results in term of yield (54.18%) and antioxidant bioactivity (21.67 mg Trolox equivalent/g dry weight). The effects of operating parameters for MAE-DES method on the total antioxidant capacity of extracts and the yield of extraction were investigated. Four independent variables, solid–liquid ratio (1:10, 1:30, and 1:50 ratio of raw material to DES, w/v), microwave power (220, 400, and 800 W), microwave time (60, 120, and 180 s), and DES concentration (30%, 50%, and 70%)—were used, and the optimized conditions were found to be 1:50, 400 W, 180 s and 30%

ANTICOLON CANCER ACTIVITY OF ARISTOLOCHIA ROTUNDA ROOT EXTRACT

Colon cancer is the third leading cause of cancer death worldwide and the first cause of cancer death in the UAE. While the conventional cancer therapy options like chemotherapy, radiation, and surgery are effective in the treatment of most cancers, they exhibit precarious side effects that can endanger the life of the patient. The present study explores the potential anticancer effect of Aristolochia rotunda root extract against human colorectal cancer cells. The root extract exhibited strong anti-proliferative activity in a concentration- and time-dependent manner against human colorectal cancer cell lines. A. rotunda root extract also inhibited colony growth and induced cell cycle arrest. Annexin V staining revealed the induction of apoptosis in treated colon cancer cell lines. These finding provide the basis for the therapeutic potential of A. rotunda in the treatment of colon cancer

Comparison of the 2005 growth charts for Saudi children and adolescents to the 2000 CDC growth charts

Background and objectives: The 2000 CDC growth charts for the United States, a revision of the National Center for Health Statistics/World Health Organization (NCHS/WHO) growth charts, were released in 2002 to replace the NCHS/WHO charts. We evaluated the differences between the CDC growth charts and the Saudi 2005 reference to determine the implications of using the 2000 CDC growth charts in Saudi children and adolescents. Subjects and methods: The Saudi reference was based on a cross-sectional representative sample of the Saudi population of healthy children and adolescents from birth to 19 years of age. Measurements of the length/ stature, weight and head circumference were performed according to expert recommendations. The CDC charts from birth to 20 years were based on a cross-sectional representative national sample from five sources collected between 1963 and 1994. The data from the CDC study including the 3rd, 5th, 50th, 95th, and 97th percentiles were plotted against the corresponding percentiles on the Saudi charts for the weight for age, height for age, weight for height for children from 0 to 36 months and weight for age, stature for age and body mass index for children 2 to 19 years of age. Results: There were major differences between the two growth charts. The main findings were the upward shift of the lower percentiles of the CDC curves and the overlap or downward shift of the upper percentiles, especially for weight, weight for height, and BMI. Conclusions: The use of the 2000 CDC growth charts for Saudi children and adolescents increases the prevalence of undernutrition, stunting, and wasting, potentially leading to unnecessary referrals, investigations and parental anxiety. The increased prevalence of overweight and obesity is alarming and needs further investigation

Undispensed Prescriptions due to Drug Unavailability at a Teaching Hospital in Saudi Arabia

Purpose: To describe the extent of undispensed prescriptions as a result of drug unavailability in a tertiary health facility in Saudi Arabia Methods: This study was conducted prospectively in a large teaching hospital over a 6 months period from May to October of 2005 and tracked 14 commonly prescribed drugs. The bimonthly drug requisition forms and the amount supplied by medical supply department (MSD) were collected and reviewed. Results: Total number of prescriptions issued for the drugs under examination was 29113. 26551 prescriptions were dispensed while the remaining 2562 (9%) were undispensed due to drug unavailability. The difference between quantity of drugs requested by the pharmacy and quantity issued from MSD was 47-52%. Conclusion: Mismatch between drug demand and supply in the facility studied is the main cause of shortage.Keywords: Drug prescriptions, inventory management, hospital pharmac

The continuous intention to use e-learning, from two different perspectives

During the recent vast growth of digitalization, e-learning methods have become the most influential phenomenon at higher educational institutions. E-learning adoption has proved able to shift educational circumstances from the traditional face-to-face teaching environment to a flexible and sharable type of education. An online survey was conducted, consisting of 30 teachers and 342 students in one of the universities in the United Arab Emirates. The results show that teachers’ and students’ perceived technology self-efficacy (TSE), ease of use (PEOU), and usefulness (PU) are the main factors directly affecting the continuous intention to use technology. Instructors’ technological pedagogical content knowledge (TPACK) and perceived organizational support (POS) positively affect the intention to use the technology, whereas students’ controlled motivation (CTRLM) has a greater influence on their intention to use the technology, due to the type of intrinsic and extrinsic motivation that they have and which they can develop throughout the process of learning. The findings support the given hypotheses. In addition, they provide empirical evidence of a relationship between perceived organizational support and perceived pedagogical content knowledge. In fact, they are considered the key factors that support the use of technology continuously

Topology-Aware Vulnerability Mitigation Worms

In very dynamic Information and Communication Technology (ICT) infrastructures, with rapidly growing applications, malicious intrusions have become very sophisticated, effective, and fast. Industries have suffered billions of US dollars losses due only to malicious worm outbreaks. Several calls have been issued by governments and industries to the research community to propose innovative solutions that would help prevent malicious breaches, especially with enterprise networks becoming more complex, large, and volatile. In this thesis we approach self-replicating, self-propagating, and self-contained network programs (i.e. worms) as vulnerability mitigation mechanisms to eliminate threats to networks. These programs provide distinctive features, including: Short distance communication with network nodes, intermittent network node vulnerability probing, and network topology discovery. Such features become necessary, especially for networks with frequent node association and disassociation, dynamically connected links, and where hosts concurrently run multiple operating systems. We propose -- to the best of our knowledge -- the first computer worm that utilize the second layer of the OSI model (Data Link Layer) as its main propagation medium. We name our defensive worm Seawave, a controlled interactive, self-replicating, self-propagating, and self-contained vulnerability mitigation mechanism. We develop, experiment, and evaluate Seawave under different simulation environments that mimic to a large extent enterprise networks. We also propose a threat analysis model to help identify weaknesses, strengths, and threats within and towards our vulnerability mitigation mechanism, followed by a mathematical propagation model to observe Seawave's performance under large scale enterprise networks. We also preliminary propose another vulnerability mitigation worm that utilizes the Link Layer Discovery Protocol (LLDP) for its propagation, along with an evaluation of its performance. In addition, we describe a preliminary taxonomy that rediscovers the relationship between different types of self-replicating programs (i.e. viruses, worms, and botnets) and redefines these programs based on their properties. The taxonomy provides a classification that can be easily applied within the industry and the research community and paves the way for a promising research direction that would consider the defensive side of self-replicating programs

Investigating a theoretical framework for e-learning technology acceptance

E-learning has gained recognition and fame in delivering and distributing educational resources, and the same has become possible with the occurrence of Internet and Web technologies. The research seeks to determine the factors that influence students' acceptance of E-learning and to find out the way these factors determine the students' intention to employ E-learning. A theoretical framework was developed based on the technology acceptance model (TAM). To obtain information from the 270 university students who utilized the E-learning system, a questionnaire was formulated. The results revealed that “social influence, perceived enjoyment, self-efficacy, perceived usefulness, and perceived ease of use” are the strongest and most important predictors in the intention of and students towards E-learning systems. The outcomes offer practical implications for practitioners, lawmakers, and developers in effective E-learning systems implementation to improve ongoing interests and activities of university students in a virtual E-learning atmosphere, valuable recommendations for E-learning practices are given by the research findings, and these may turn out to be as guidelines for the efficient design of E-learning systems

The Reality of E- Learning at the Mutah University from the Viewpoint of Students

This study aimed to identify the reality of e-learning at Mutah University from the perspective of students. The researchers adopted descriptive and analytical method to highlight the concepts related to the subject of study. Moreover, analysis and  extrapolation of the results have resorted researchers to choose a simple random sample  which are in total  (335) from the number of students of science and humanity college in the fourth year. To achieve the objectives ,the study designed a questionnaire included (22) paragraphs to gather preliminary information from the study sample in order to collect and analyze data and test hypotheses. However, the study found that the arithmetic mean of the estimates of the study sample (students) on the axes of the questionnaire (use; positives, negatives; obstacles) was as high as the study showed in the presence of statistically significant differences between the mean scores of students around the axis of Use and the positives and negatives depending on the variable specialization as results of the study showed a lack of statistically significant differences between the mean scores of students around the axis of obstacles

A systematic review of text classification research based on deep learning models in Arabic language

Classifying or categorizing texts is the process by which documents are classified into groups by subject, title, author, etc. This paper undertakes a systematic review of the latest research in the field of the classification of Arabic texts. Several machine learning techniques can be used for text classification, but we have focused only on the recent trend of neural network algorithms. In this paper, the concept of classifying texts and classification processes are reviewed. Deep learning techniques in classification and its type are discussed in this paper as well. Neural networks of various types, namely, RNN, CNN, FFNN, and LSTM, are identified as the subject of study. Through systematic study, 12 research papers related to the field of the classification of Arabic texts using neural networks are obtained: for each paper the methodology for each type of neural network and the accuracy ration for each type is determined. The evaluation criteria used in the algorithms of different neural network types and how they play a large role in the highly accurate classification of Arabic texts are discussed. Our results provide some findings regarding how deep learning models can be used to improve text classification research in Arabic language