Background: Since the periodontal disease Index of Ramfjord (Ramfjord index) can potentially shorten the examination time by almost half, many studies evaluated Ramfjord teeth in predicting full-mouth periodontal status of an adult population. The aim of this study was to evaluate the benefit of Ramfjord teeth in predicting the full-mouth clinical attachment level of an adult population in patients attending the college of dentistry- Baghdad University. Materials and methods: The study participants were 100 patients with age range from 30-60 years old which represent group zero. The patients were divided into three main groups according to the age of the patients. Group I and group II each of them composed of 30 patients while group III composed of 40 patients. In the first time clinical attachment level (CAL) was measured from the full mouth (FM) and then from the Ramfjord teeth (RT) (teeth number: 16, 21, 24, 36, 41, 44) in all groups. Clinical attachment level (CAL) was measured in millimeters using periodontal probe. Results: The difference in the mean clinical attachment level measured from the full mouth (FM) and Ramfjord teeth (RT) by using paired t - test was non significant in all the groups. Also in all groups the correlation coefficient as well as beta coefficient was high. Conclusion: The high agreement between Ramfjord teeth and full mouth CAL confirm the epidemiological validity of Ramfjord teeth to represent the full mouth.
A many risk challenge in (settings hospital) are multi- bacteria are antibiotic-resistant. Some type strains that ability adhesion surface-attached bio-film census. Fifteen MRSA isolates were considered as high biofilm producers Moreover all MRSA isolates; M3, M5, M7 and M11 produced biofilms but the thickest biofilm seen M7strain. The MIC values of N. sativa oil against clinical isolates of MRSA were between (0.25, 0.5, 0.75, 1.0) μg/ml While MRSAcin (50, 75, 100, 125) µg\ ml. All biofilms treated with MRSAcin and Nigella sativa developed a presence of live cells after cultured on plate agar with inhibition zone between MIC (18 – 15) and (14- 11)mm respectively.Yet, results showed that MRSA supernatant developed a inhibitory ef
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Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75
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The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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