Our goal in this research, some new nucleoside analogues was synthesized. Starting from ?-D glucose which was converted to per acetylated ?-D gluco pyronoside then converted to active from(1-Bromo Sugar (2) as a sugar moiety.The base moiety 2-substituted benzimidazole was prepared from condensation of phenylene diamine with different aromatic aldehydes, which were subjected to amino alkylation via Mannich reaction forming new nucleobase derivatives. Condensation of nucleobase with bromo sugar through nucleophilic substitution of anomeric carbon with nitrogen forming new protected nucleoside analogues then hydrolyzed with sodium methoxide in methanol to obtain our target, the free nucleoside analogues. All prepared compound were identified b

Corona virus sickness has become a big public health issue in 2019. Because of its contact-transparent characteristics, it is rapidly spreading. The use of a face mask is among the most efficient methods for preventing the transmission of the Covid-19 virus. Wearing the face mask alone can cut the chance of catching the virus by over 70\%. Consequently, World Health Organization (WHO) advised wearing masks in crowded places as precautionary measures. Because of the incorrect use of facial masks, illnesses have spread rapidly in some locations. To solve this challenge, we needed a reliable mask monitoring system. Numerous government entities are attempting to make wearing a face mask mandatory; this process can be facilitated by using face m

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

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

Scrophularia. striata from Scrophulariacea family has been used in Iranian folk medicine for the treatment of infectious diseases. In this study we evaluated the synergistic effect of S. striata   hydroalcoholic extract (SSE) and commercially available antibiotics against P. aeroginosa and Methicillin- resistant Staphylococcus aureus (MRSA). The resazurin-based microdilution method was used to determine the minimum inhibitory concentration (MIC) values of plan extract and standard antibiotics. The interaction between standard antibiotics and SSE was evaluated by using checkerboard method. The results of this study revealed that SSE enhance the antibacterial activity of antibiotics. The combin

In this work, we focused on studying 1,4-naphthoquinones and their derivatives, and knowing the methods of preparing them using different auxiliary agents and forming derivatives containing heterocyclic rings, active groups and saturated rings containing heterogeneous elements . In addition, due to their strong antibacterial, antifungal and anticancer activity, 1,4-naphthoquinone compounds biological importance and are considered a source of various pharmaceutical compounds.

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

The present study deals with the synthesis of four different azo-azomethine derivatives; this is done by two steps; the first step is diazotization of sulfonamides (sulfanilamide, sulfacetamide, sulfamethoxazole, and sulfadiazine) separately, followed by the second step; the coupling reaction of diazotized compounds with isatin bis-Schiff base named 3-((4-nitrobenzylidene) hydrazono)indolin-2-one. The later one (bis-Schiff base) was synthesized by the reaction of 3-hydrazono-indolin-2-one with p-nitrobenzaldehyde. The chemical structures of newly synthesized compounds were approved on the basis of their FTIR, 1H-NMR, and CHNS elemental analysis data results. The synthesized azo compounds were tested in vitro for their antimicrobial potentia

Levan is an exopolysaccharide produced by various microorganisms and has a variety of applications. In this research, the aim was to demonstrate the biological activity of levan which produced from B. phenoliresistens KX139300. These were done via study the antioxidant, anti-inflammatory, anticancer and antileishmanial activities in vitro. The antioxidant levan was shown 80.9% activity at 1250 µg/mL concentration. The efficient anti-inflammatory activity of 88% protein inhibition was noticed with levan concentration at 35 µg/mL. The cytotoxic activity of levan at 2500 µg/mL concentration showed a maximum cytotoxic effect on L20B cell line and promastigotes of Leishmani tropica. Levan has dose-dependent anticancer and antileishmanial acti