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 mask detection software based on AI and image processing techniques. For face detection, helmet detection, and mask detection, the approaches mentioned in the article utilize Machine learning, Deep learning, and many other approaches. It will be simple to distinguish between persons having masks and those who are not having masks using all of these ways. The effectiveness of mask detectors must be improved immediately. In this article, we will explain the techniques for face mask detection with a literature review and drawbacks for each technique.
This study aimed to investigate the prevalence of intestinal helminth infections in humans and detect Toxocara spp. in cats, with a focus on assessing the impact of age and gender on infection rates. Traditional diagnostic methods have historically limited the accurate identification of helminth infections in humans. Analysis of 450 human stool samples revealed an overall helminth infection rate of 5.7% using conventional techniques. The specific infection rates were 0.4% for Strongyloides stercoralis, 0.6% for Schistosoma mansoni, 1.7% for Hymenolepis nana, and 2.8% for Ascaris lumbricoides. Notably, no infections were recorded in the 30–39 and ≥40-year age groups, while the highest infection rate (16.3%, P≤0.01) was observed in indi
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The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats. This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat
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Aqueous root extract has been used to examine the green production of silver nanoparticles (AgNPs) by reducing the Ag+ ions in a silver nitrate solution. UV-Vis spectroscopy, X-ray diffraction, field emission scanning electron microscopy, and Fourier transform infrared spectroscopy (FTIR) were used to analyze the produced AgNPs. The AgNPs that were created had a maximum absorbance at 416 nm, were spherical in form, polydispersed in nature, and were 685 nm in size.The AgNPs demonstrated antibacterial efficacy against Escherichia coli and Staphylococcus. The dengue vector Aedes aegypti's second instar larvae were very susceptible to the AgNPs' powerful larvicidal action.
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After the year 2003 terrorist attacks knock Baghdad city capital of Iraq using bomb explosion various, shook the nation, and made public resident of Baghdad aware of the need for better ways to protect occupants, assets, and buildings cause the terrorist gangs adopt style burst of blast to injury vulnerability a wider range form, and many structures will suffer damage from air blast when the overpressure concomitant the blast wave, (i.e., the excess over the atmospheric pressure 14.7 pounds per square inch at standard sea level conditions are about one-half pound per square inch or more(
to attainment injury. Then, the distance to which this overpressure level will extend depends primarily on the energy yield (§1.20) of the burst of
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This study was conducted to evaluate the efficacy of different techniques for extraction and purification of Tomato yellow leaf curl virus (TYLCV). An isolate of the virus free of possible contamination with other viruses infecting the same host and transmitted by the same vector Bemisia tabaci Genn. was obtained. This was realized by indicator plants and incubation period in the vector. Results obtained revealed that the virus infect Nicotiana glutinosa without visible symptoms, while Nicotiana tabaccum var. White Burley was not susceptible to the virus. The incubation period of the virus in the vector was found to be 21 hrs. These results indicate that the virus is TYLCV. Results showed that Butanol was more effective in clarification the
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KE Sharquie, AA Noaimi, HA Al-Mudaris, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 4
Background: The marginal seal is essential for sealant success because penetration of bacteria under the sealant might allow caries onset or progression. The aim of the present study was to estimate and compare the microleakage of pit and fissure sealant after various methods of occlusal surface preparation. Materials and methods: Thirty non-carious premolars extracted for orthodontic reasons were equally divided into three groups. In group one, occlusal fissures were opened with round carbide bur, in group two, occlusal surfaces of the teeth were cleaned with a dry pointed bristle brush and samples of group three were cleaned with a slurry of fine flour of pumice in water using rubber cup. Then fissures of all teeth were etched using 35% p
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