Synthetic anti-TB drugs are being used to treat tuberculosis (TB) as they are effective, however, they are accompanied by many side effects. The disease has remained largely uncured till date. The use of plant extracts or phytochemicals along with the anti-TB drugs is a very attractive strategy to make the treatment more effective as phytochemicals have no side-effects, are much less toxic than synthetic anti-TB drugs, are safe to use and most importantly, do not produce resistant strains as opposed to synthetic anti-TB drugs. Approximately 420,000 plant species have been identified globally and among them only a few have been explored for their therapeutic potential. Traditional medicine in different parts of the world has employed crude extracts of several plant species to cure tuberculosis. Several anti-TB phytochemicals have been found in plants that are identified to have therapeutic qualities. These phytochemicals are majorly glycosides, flavonoids, triterpenes, phenolic compounds, alkaloids, flavonoids, diterpenoid, lipids, tannins, sterols etc. by nature. They are either antimycobacterial or act synergistically with anti-TB drugs and reduce their adverse effects. Phytochemicals ameliorate the symptoms either by reducing the oxidative stress in the afflicted tissues or by regulating the inflammatory response. Hence, plant derived molecules have great potential to be used for the alternative treatment strategy for TB in future.
This current study aims to:
1st: The recognizing of Alexithymia level for 6th grade students (Study Specimen) through the next Zero Hypothesis:1. There are no statistically significant differences at (0.05) level between the arithmetic mean of the specimen degrees as a whole and the central assumption for the scale of the lack in emotions expression
2. There are no statistically significant differences at (0.05) level between the arithmetic mean of the male students specimen and the arithmetic meanc of the female students specimen for the scale of Alexithymia.
2nd: ldentification the level of the emotional intelligence among 6th grade students (Study Specimen) through the next Zero Hypothesis:
1) There are no statistically si
Formation evaluation is a critical process in the petroleum industry that involves assessing the petrophysical properties and hydrocarbon potential of subsurface rock formations. This study focuses on evaluating the Mauddad Formation in the Bai Hassan oil field by analyzing data obtained from well logs and core samples. Four wells were specifically chosen for this study (BH-102, BH-16, BH-86, and BH-93). The main objectives of this study were to identify the lithology of the Mauddud Formation and estimate key petrophysical properties such as shale volume, porosity, water saturation, and permeability. The Mauddud Formation primarily consists of limestone and dolomite, with some anhydrites present. It is classified as a clean for
... Show MoreWireless control networks (WCNs), based on distributed control systems of wireless sensor and actuator networks, integrate four technologies: control, computer network and wireless communications. Electrostatic precipitator (ESP) in cement plants reduces the emissions from rotary kiln by 99.8% approximately. It is an important thing to change the existing systems (wireline) to wireless because of dusty and hazardous environments. In this paper, we designed a wireless control system for ESP using Truetime 2 beta 6 simulator, depending on the mathematical model that have been built using identification toolbox of Matlab v7.1.1. We also study the effect ofusing wireless network on performance and stability of the closed l
... Show MoreIn this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.
In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f
... Show MoreAn intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men
... Show MoreWith the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
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