Background: With the start of the current century, increased the interest in the role of the adipose tissue derived substances that named adipokines in the inflammatory diseases of the human being including the inflammatory periodontal disease, but scientific evidences were not clearly demonstrate the association between these adipokines and periodontal pathologies. Materials and Methods: Forty two subjects male only with normal body mass index were selected for the study with an age ranged (30-39 years). Samples were divided into three groups of 14 subjects in each group based on clinical periodontal parameters; clinically healthy gingiva (group I), gingivitis group (group II) and chronic periodontitis patients group (group III), from whom saliva and serum samples were collected for estimating the levels of leptin and resistin using Enzyme-Linked Immuno Sorbent Assay (ELISA). Results: The results showed that the serum level of leptin and resistin were significantly higher in chronic periodontitis patient (9.81 ng/ml, 6.55 ng/ml) respectively as compared to gingivitis and healthy control groups (leptin; 8.10 ng/ml, ng/ml, resistin; 5.85 ng/ml, 5.45 ng/ml) respectively. On the other hand the level of leptin in saliva of patients with chronic periodontitis (0.17 ng/ml) was significantly lower than that of its salivary levels in gingivitis and healthy control groups (0.21 ng/ml, 0.29 ng/ml) respectively. Whereas, salivary resistin levels was significantly higher in chronic periodontitis patient(14.45 ng/ml) when compared to the gingivitis group (11.59 ng/ml) and the health control group (6.43 ng/ml). Conclusions: Concomitant raise in serum leptin, serum resistin and salivary resistin, while a sensible reduction in salivary leptin with conversion from periodontal health state to periodontal disease state. These finding may draw a suggestion on the role of leptin and resistin in the relation between periodontal disease and the systemic health since the increase in their level were associated with a various systemic pathologies.
The aim of this paper is to design a PID controller based on an on-line tuning bat optimization algorithm for the step-down DC/DC buck converter system which is used in the battery operation of the mobile applications. In this paper, the bat optimization algorithm has been utilized to obtain the optimal parameters of the PID controller as a simple and fast on-line tuning technique to get the best control action for the system. The simulation results using (Matlab Package) show the robustness and the effectiveness of the proposed control system in terms of obtaining a suitable voltage control action as a smooth and unsaturated state of the buck converter input voltage of ( ) volt that will stabilize the buck converter sys
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KE Sharquie, AA Noaimi, SD Hameed, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 15
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Due to the continuous development in society and the multiplicity of customers' desires and their keeping pace with this development and their search for the quality and durability of the commodity that provides them with the best performance and that meets their needs and desires, all this has led to the consideration of quality as one of the competitive advantages that many industrial companies compete for and which are of interest to customers and are looking for. The research problem showed that the Diyala State Company for Electrical Industries relies on some simple methods and personal experience to monitor the quality of products and does not adopt scientific methods and modern programs. The aim of this research is to desi
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In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we
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Recently emerging pandemic SARS CoV-2 conquered our world since December 2019. Continuous efforts have been done to find out effective immunization and precise treatment stetratigies A way from therapeutic options that were tried in SARS CoV-2, an increased attention is directed to predict natural products and mainly phytochemicals as collaborative measures for this crisis. In this review, most of the mentioned compounds specially flavonoids (biacalin, hesperidin, quercetin, luteolin,, and phenolic (resveratrol, curcumin, and theaflavin) exert their effect through interfering with the action of one or more of this proteins (spike protein, papain like protease, 3 chymotrypsin like cysteine protease, and RNA dependent RNA
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
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