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.
This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.
The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying
... Show MoreThis paper investigates the experimental response of composite reinforced concrete with GFRP and steel I-sections under limited cycles of repeated load. The practical work included testing four beams. A reference beam, two composite beams with pultruded GFRP I-sections, and a composite beam with a steel I-beam were subjected to repeated loading. The repeated loading test started by loading gradually up to a maximum of 75% of the ultimate static failure load for five loading and unloading cycles. After that, the specimens were reloaded gradually until failure. All test specimens were tested under a three-point load. Experimental results showed that the ductility index increased for the composite beams relative to the refe
... Show MoreTwitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat
... Show MoreHypothesis CO2 geological storage (CGS) involves different mechanisms which can store millions of tonnes of CO2 per year in depleted hydrocarbon reservoirs and deep saline aquifers. But their storage capacity is influenced by the presence of different carboxylic compounds in the reservoir. These molecules strongly affect the water wetness of the rock, which has a dramatic impact on storage capacities and containment security. However, precise understanding of how these carboxylic acids influence the rock’s CO2-wettability is lacking. Experiments We thus systematically analysed these relationships as a function of pressure, temperature, storage depth and organic acid concentrations. A particular focus was on identifying organic acid conce
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