Background: Periodontitis is an inflammatory disease that affects the supporting tissues of the teeth; Smoking is an important risk factor for periodontitis induces alveolar bone loss and cause an imbalance between bone resorption and bone deposition. The purpose of this study is to detect and compare the presence of incipient periodontitis among young smokers and non-smokers by measuring the distance between cement-enamel junction and alveolar crest (CEJ-Ac) using Cone Beam Computed Tomography (CBCT). Material and methods: The total sample composed of fifty two participants, thirty one smokers and twenty one non-smokers (age range 14-22 years). Periodontal parameters: plaque index (PLI), gingival index (GI) were recorded for all teeth except the third molar while the radiographic analysis using CBCT was recorded on the Ramfjord teeth, the unit of measurement was from cement-enamel junction to alveolar crest distance (CEJ-Ac distance) per site in millimeters. Results: The results obtained were a non significant difference for PLI, a significant difference of mean of GI between young smokers and non smokers. There was a highly significant difference in the general mean of CEJ-Ac distance between both groups. There was a significant difference between maxillary and mandibular teeth, a non significant difference between right and left sides among young smokers and non smokers. Conclusion: The CBCT device plays an important role in detection the incipient form of periodontitis among young smokers and non-smokers, so we concluded that there is a highly significant difference in the general mean CEJ-Ac distance between young smokers and non smokers with increase distance in the maxillary teeth than that in the mandibular teeth.
equality between man and woman
Among Islamic law
International conventions and agreements
(4)
(7)
In this study, the volatile compounds found in lemon trees infested and uninfested with Planococcus citri (Risso) (Hemiptera: Pseudococcidae) were investigated. In addition, the interest of the predator Cryptolaemus montrouzieri (Coleoptera: Coccinellidae) and the parasitoid Leptomastix dactylopii (Hymenoptera: Encyrtidae) in lemon trees infested and uninfested with P. citri and some volatile compounds was investigated. According to the results obtained, most of the volatile compounds obtained from mealybug-infested lemon trees showed changes compared to healthy lemon trees. Since volatile compounds play an important role in attracting pests and natural enemies, linalyl acetate was selected as the compound showing the highest amount of chan
... Show More
Plagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and
... Show More
(33)
(10)
The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.
Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.
The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple
... Show More
The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz
... Show More
(8)
(2)
HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023
(8)
For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.