Background: Chronic periodontitis is an inflammatory disease that affects the supporting tissues of the teeth and it’s common among adults. Smoking is an important risk factor for periodontitis induces alveolar bone loss. Alkaline phosphatase enzyme is involved in the destruction of the human periodontium. It is produced by many cells such as polymorphonuclear leukocytes, osteoblasts, macrophages and fibroblasts within the area of the periodontium and gingival crevice. Osteocalcin is one of the most abundant matrix proteins found in bones and the only matrix protein synthesized exclusively there. Smaller Osteocalcin fragments are found in areas of bone remodeling and are actually degradation products of the bone matrix.The purpose of this study was to evaluatethe effect of smoking on the salivary alkaline phosphatase and Osteocalcin in subjects with chronic periodontitis compared to control subjects. Materials and Methods: Five ml of unstimulated whole saliva samples and full-mouth clinical periodontal recordings (plaque index, gingival index, bleeding on probing, probing pocket depth and clinical attachment level) were obtained from study groups (25 light smokers and 33 non-smokerssubjects, both with chronic periodontitis) and control groups (8 light smokers and 13 non-smokers subjects, both with healthy periodontium). All subjects were systemically healthy males, with age range (30-50) years. Salivary Alkaline phosphatase and Osteocalcin levels were determined by Colorimetric and Enzyme-linked Immunosorbent Assays, respectively. Results: Smoker chronic periodontitis patients revealed non-significant differences in clinical periodontal parameters with non-smoker counterparts (P˃o.o5) in terms of Plaque index, Probing pocket depth and Clinical attachment loss, with slight increase in plaque index value in smoker chronic periodontitis group(1.42±0.46) than non-smoker chronic periodontitis group, while there were highly significant differences in terms of Gingival index and Bleeding on probing(P ≤ 0.01).Osteocalcin levels were lower in smoker chronic periodontitis group (0.13±0.20) than non-smoker chronic periodontitis group (1.09±2.26) with significant difference (0.05 ≥ P > 0.01). Mean of Alkaline phosphatase level was lower in smoker chronic periodontitis (11.14±4.53) than non-smoker chronic periodontitis (11.45±4.17) with a non-significant difference, while there was a significant difference inAlkaline phosphatase concentrations between smoker and non-smoker control groups.There were non-significant differences between smoker chronic periodontitis and smoker control groups in terms of Osteocalcin and Alkaline phosphatase concentrations. There were non-significant differences between non-smoker chronic periodontitis and non-smoker control groups in terms of Osteocalcin and Alkaline phosphatase concentrations. Conclusion: Within the limits of this study, it may be suggested that suppression of salivary Osteocalcin levels by smoking and slight increase in alkaline phosphatase in smokers groups, may explain the deleterious effects of smoking on periodontal health status.
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
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreIn this paper, Bayes estimators of Poisson distribution have been derived by using two loss functions: the squared error loss function and the proposed exponential loss function in this study, based on different priors classified as the two different informative prior distributions represented by erlang and inverse levy prior distributions and non-informative prior for the shape parameter of Poisson distribution. The maximum likelihood estimator (MLE) of the Poisson distribution has also been derived. A simulation study has been fulfilled to compare the accuracy of the Bayes estimates with the corresponding maximum likelihood estimate (MLE) of the Poisson distribution based on the root mean squared error (RMSE) for different cases of the
... Show MoreTillage appearance device is mechanical, electric-electronic design, getting Patent from the Central Organization for Standardization and Quality Control – Industrial Property Department - Ministry of Planning – The Republic of IRAQ under number Patent 3876 in 20 / 4 / 2014, calculates the number of clods per area by Tillage appearance device, This is done through the generation electrical impulses are sent to the controlled accurate calculates number clods required space and shows the result on the screen in order to see the tillage view per area. Three factor used in these experiment, first factor represents forward speed of tractor three levels (3.5, 4.5, and 5.5 km/h), second factor represent soil moisture content at two levels (14
... Show MoreDeveloping smart city planning requires integrating various techniques, including geospatial techniques, building information models (BIM), information and communication technology (ICT), and artificial intelligence, for instance, three-dimensional (3D) building models, in enabling smart city applications. This study aims to comprehensively analyze the role and significance of geospatial techniques in smart city planning and implementation. The literature review encompasses (74) studies from diverse databases, examining relevant solutions and prototypes related to smart city planning. The focus highlights the requirements and preparation of geospatial techniques to support the transition to a smart city. The paper explores various aspects,
... Show MoreAmong a collection of leafhoppers from Erbil Province in Kurdistan/Iraq, a new species of the genus Arboridia Zakhvatkin, 1946 was designated and described here as a new species to the science. The erection of this species was mainly built on the external characters included the male genitalia. Sites and dates of collections so as the host-plants were verified.
In this work, metal oxide nanostructures, mainly copper oxide (CuO), nickel oxide (NiO), titanium dioxide (TiO2), and multilayer structure, were synthesized by the DC reactive magnetron sputtering technique. The effect of deposition time on the spectroscopic characteristics, as well as on the nanoparticle size, was determined. A long deposition time allows more metal atoms sputtered from the target to bond to oxygen atoms and form CuO, NiO, or TiO2 molecules deposited as thin films on glass substrates. The structural characteristics of the final samples showed high structural purity as no other compounds than CuO, NiO, and TiO2 were found in the final samples. Also, the prepared multilayer structures did not show new compounds other than th
... Show MoreThe CuInSe2 (CIS) nanocrystals are synthesized by arrested precipitation from molecular precursors are added to a hot solvent with organic cap- ping ligands to control nanocrystal formation and growth. CIS thin films deposited onto glass substrate by spray - coating, then selenized in Ar- atmosphere to form CIS thin films. PVs were made with power conversion efficiencies of 0.631% as -deposited and 0.846% after selenization, for Mo coated, under AM 1.5 illumination. X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis it is evident that CIS have the chalcopyrite structure as the major phase with a preferred orientation along (112) direction and the atomic ratio of Cu : In : Se in the nanocrystals is nearly 1 : 1 : 2
The taxonomy of Ficus L., 1753 species is confusing because of the intense morphological variability and the ambiguity of the taxa. This study handled 36 macro-morphological characteristics to clarify the taxonomic identity of the taxa. The study revealed that Ficus is represented in the Egyptian gardens with forty-one taxa; 33 species, 4 subspecies and 4 varieties, and classified into five subgenera: Ficus Corner, 1960; Terega Raf., 1838; Sycomorus Raf., 1838; Synoecia (Miq.) Miq., 1867, and Spherosuke Raf.,1838; out of them seven were misidentified. Amongst, four new Ficus taxa were recently introduced to Egypt namely: F. lingua subsp. lingua Warb. ex De Wild. & T. Durand, 1901; F. pumila L., 1753; F. rumphii Blume, 1825, and F. su
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