In the resent years, there is a robust scientific interest in discovery of new anti-septic and anti-oxidant naturally products with no/or limited side effects. The current study aimed to investigate the protective role of the quercetin on inflammations induced by lipopolysaccharide (LPS) in male mice A number of criteria included i.e. liver and spleen index and IL-6 and IL1-β cytokines level in spleen homogenate were considered. Sixty male mice (8-9 week age) was divided into six groups and treated for 5 days as the following: the first group represented control, the second and third group were injected with 5, 10 mg/kg b.w doses of quercetin respectively. While the fourth and fifth groups were co-treatment with (5, 10 mg/kg b.w.) intraper

The aim of the present study is to investigate whether or not xanthine oxidase (XO)–derived reactive oxygen species (ROS) may play a role in the pathogenesis of alloxan (ALX)–induced diabetes in rats using the specific XO inhibitor and hydroxyl radical scavenger, allopurinol

The involvement of oxidative stress in ALX – diabetes was assessed by the measurement of plasma and various tissues lipid peroxides levels ( using thiobarbituric acid ( TBA ) reactive substances ). Furthermore, the ability of allopurinol to influence these and other biochemical parameters, including plasma and urine ketones levels were also investigated in diabetic rats.

Rats were divided into four groups: control, untreated diabe

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

     By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb

<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Image quality has been estimated and predicted using the signal to noise ratio (SNR). The purpose of this study is to investigate the relationships between body mass index (BMI) and SNR measurements in PET imaging using patient studies with liver cancer. Three groups of 59 patients (24 males and 35 females) were divided according to BMI. After intravenous injection of 0.1 mCi of 18F-FDG per kilogram of body weight, PET emission scans were acquired for (1, 1.5, and 3) min/bed position according to the weight of patient. Because liver is an organ of homogenous metabolism, five region of interest (ROI) were made at the same location, five successive slices of the PET/CT scans to determine the mean uptake (signal) values and its standard deviat

Laser cleaning of materials’ surfaces implies the removal of deposited pollutants without affecting the material. Nanosecond Nd:YAG pulsed laser, operating at 1064 nm and 532nm, was utilized. Different laser intensities and number of pulses were used on metallic and non-metallic surfaces under O2 and Ar environments to remove metal oxide and crust. Cleaning efficiency was studied by optical microscope. The results indicated the superiority of 1064 nm over the 532 nm wavelength without any detectable damage to materials’ surfaces. Marble cleaned in Oxygen gas environment was better than in Ar gas.