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

Aim: This abstract aims to highlight the critical nature of climate change as a pressing challenge facing humanity in the 21st century. It underscores the severe consequences it poses to essential facets of human existence, including water and energy resources, agricultural production, and the broader environmental systems. Method: The abstract primarily utilizes a descriptive approach to emphasize the impact of climate change on the Middle East, particularly the Arab region. It relies on a review of existing knowledge and data related to climate change and its effects on ecosystems and drought patterns. Results: The abstract outlines the direct and indirect repercussions of climate change on human life and the environment. It draws atten

Sol-gel method was use to prepare Ag-SiO2 nanoparticles. Crystal structure of the nanocomposite was investigated by means of X-ray diffraction patterns while the color intensity was evaluated by spectrophotometry. The morphology analysis using atomic force microscopy showed that the average grain sizes were in range (68.96-75.81 nm) for all samples. The characterization of Ag-SiO2 nanoparticles were investigated by using Scanning Electron Microscopy (SEM). Ag-SiO2 NPs are highly stable and have significant effect on both Gram positive and negative bacteria. Antibacterial properties of the nanocomposite were tested with the use of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacteria. The results have shown antibacteri

Background: Entamoeba histolytica is the causative agent of amoebic dysentery and hepatic abscesses. Despite the efficacy of metronidazole in alleviating infectious diseases, the global dissemination of drug-resistant parasites raises the possibility that Punica granatum could serve as an effective natural alternative treatment. Objective: To evaluate the effect of P. granatum methanolic and aqueous extracts of various parts against E. histolytica trophozoites in an in vitro setting. Methods: Various concentrations (0.14, 0.7, 1.4, and 2.8 mg/ml) of P. granatum extracts of the flowers, leafs, peels, and seeds were chosen for this purpose. A culture medium containing 0.05x106/ml E. histolytica trophozoites was treated with different

The aim of the study was extraction of arial part of Euphorbia cyathophora constituents with methanol and evaluate its effect on mitotic index and total chromosomal aberration bone marrow cell and spleen cell in mice  200 gm of E. cyathophora fine powder was defatted then extracted by cold maceration 80% ethanol for seven days. The extract was filtered and dried in a rotary evaporator then the dried extract was suspended with water and consecutively extracted using chloroform, ethyl acetate for each. The aqueous layer was then mixed with 100ml methanol. These fractions are dried under reduced pressure to obtain the dry extract. Twenty-four Albino mice were used for the experiment. The animals were divided into four groups: Gr

The microbend sensor is designed to experience a light loss when force is applied to the sensor. The periodic microbends cause propagating light to couple into higher order modes, the existing higher order modes become unguided modes. Three models of deform cells are fabricated at (3, 5, 8) mm pitchand tested by using MMF and laser source at 850 nm. The maximum output power of (8, 5, 3)mm model is (3, 2.7, 2.55)nW respectively at applied force 5N and the minimum value is (1.9, 1.65, 1.5)nW respectively at 60N.The strain is calculated at different microbend cells ,and the best sensitivity of this sensor for cell 8mm is equal to 0.6nW/N.

This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.