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

Objective: Geographic differences in clinical and pathological aspects of ameloblastoma have been suggested, therefore the purpose of this study was to analyze cases of ameloblastoma in terms of clinical and radiographic manifestations, histopathological types, treatment modalities and recurrence rate and compare them with reports from other parts of the world. Methods: The medical reports of patients diagnosed with ameloblastoma were reviewed and the data concerning the age, gender, chief complaint, the anatomical site of the lesion, radiographic appearance, histopathological diagnosis, treatment approach and recurrence were retrieved. Surgical treatment consisted of either enucleation with curettage and peripheral ostectomy or resection;

Biosorption is an effective method to remove toxic metals from wastewaters. In this study biosorption of lead and chromium ions from solution was studied using Citrobacter freundii and Citrobacter kosari isolated from industrial wastewater. The experimental results showed that optimum grwoth temperature for both bacteria is 30oC and the optimum pH is 7 &6 for C. freundii and C. kosari respectively. While the optimum incubation period to remove Pb and Cr for C. freundii and C. kosari is 4 days and 3days respectively. Also the biosorption of Pb and Cr in mixed culture of bacteria and mixed culture of Pb and Cr was investigated. Result indicate that uptake of Cr and Pb for C.freundii, C. kosari and in mixes culture of both bacteria is 58%, 53%

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

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 aim of this study is to evaluating the antibacterial activity of Laurus nobilis leaves extract in hospital environment isolates. Maceration and Soxhlet apparatus were used to prepare aqueous and methanolic extracts. The total phenolic content and high-performance liquid chromatography (HPLC) were conducted to determine the active compounds in the extracts. The results showed that the methanolic and aqueous extracts contain four flavonoids derivatives (kaempferol, luteolin, quercetin and Rutin) were identified on the basis of matching retention time with the standards. The total phenolic contents were 56.81 and 81.56 mg/g in 50 mg/ml, in aqueous and methanolic extracts respectively. The antibacterial activity of Laurus nobilis leaves ext

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

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