Background: Chronic periodontitis is an inflammatory disease of tissues supporting the teeth. Salivary compositions have been most intensely studied as a potential marker for periodontal disease. In this study, analysis of saliva provides a simple and non-invasive method of evaluating the role of salivary IgA (s-IgA) levels in periodontal disease by detecting the level of (s-IgA) in patients with chronic periodontitis smokers and non smokers patients and correlate the mean (s-IgA) levels with clinical periodontal parameters Plaque index (PLI) gingival index (GI), probing pocket depth (PPD) and clinical attachment level (CAL). Materials and Methods: The study samples consists of (15) patients with chronic periodontitis who were non smokers (Group I) and (15) patients with chronic periodontitis who were smokers (Group II) of both gender with an age ranged (35-45) years were the periodontal parameters used in this study (PLI, GI, PPD and CAL), unstimulated salivary sample were collected from all subjects and the levels of salivary IgA (s-IgA) in each sample were analyzed for each group by using enzyme-linked immunosorbent assay (ELISA) technique. A statistical analysis was done by using excel 2013. Results: There was a significant difference with high mean level in the clinical periodontal parameters in smokers group compared to non smokers with chronic periodontitis (PLI, PPD and CAL) except GI which showed no significant difference between the same groups. The biochemical finding showed significant difference with low mean level for (s-IgA) in smokers group compared to non smokers. Conclusion: The findings in this study showed that the concentrations of salivary IgA might be used as an indicator for periodontal disease progression in smokers with chronic periodontitis as a resultant to the effect of smoking which lowering the concentration of the salivary IgA and subsequent reducing of the host’s defense lead to increase in the progression of periodontal disease.
NS-2 is a tool to simulate networks and events that occur per packet sequentially based on time and are widely used in the research field. NS-2 comes with NAM (Network Animator) that produces a visual representation it also supports several simulation protocols. The network can be tested end-to-end. This test includes data transmission, delay, jitter, packet-loss ratio and throughput. The Performance Analysis simulates a virtual network and tests for transport layer protocols at the same time with variable data and analyzes simulation results based on the network simulator NS-2.
In this work, an analytical approximation solution is presented, as well as a comparison of the Variational Iteration Adomian Decomposition Method (VIADM) and the Modified Sumudu Transform Adomian Decomposition Method (M STADM), both of which are capable of solving nonlinear partial differential equations (NPDEs) such as nonhomogeneous Kertewege-de Vries (kdv) problems and the nonlinear Klein-Gordon. The results demonstrate the solution’s dependability and excellent accuracy.
Abstract
The model of financial reporting in Iraq Based on a specific set of accounting objectives & concepts, which require the application of the historical cost valuation approach due to the nature of the objectives of financial reporting in Iraq, established under the unified accounting system , which focuses on serving the needs of the state because it the most influential user in setting accounting objectives and concepts, which stems mainly from the nature of the economic system in Iraq, which focuses on the public sector versus the private sector as well as the nature of the ownership business that focuses on partnership versus corpor
... Show MoreIn this paper, the concept of Jordan triple higher -homomorphisms on prime
rings is introduced. A result of Herstein is extended on this concept from the ring into the prime ring . We prove that every Jordan triple higher -homomorphism of ring into prime ring is either triple higher -homomorphism or triple higher -anti-homomorphism of into .
The image caption is the process of adding an explicit, coherent description to the contents of the image. This is done by using the latest deep learning techniques, which include computer vision and natural language processing, to understand the contents of the image and give it an appropriate caption. Multiple datasets suitable for many applications have been proposed. The biggest challenge for researchers with natural language processing is that the datasets are incompatible with all languages. The researchers worked on translating the most famous English data sets with Google Translate to understand the content of the images in their mother tongue. In this paper, the proposed review aims to enhance the understanding o
... Show MoreThe efforts in designing and developing lightweight cryptography (LWC) started a decade ago. Many scholarly studies in literature report the enhancement of conventional cryptographic algorithms and the development of new algorithms. This significant number of studies resulted in the rise of many review studies on LWC in IoT. Due to the vast number of review studies on LWC in IoT, it is not known what the studies cover and how extensive the review studies are. Therefore, this article aimed to bridge the gap in the review studies by conducting a systematic scoping study. It analyzed the existing review articles on LWC in IoT to discover the extensiveness of the reviews and the topics covered. The results of the study suggested that many re
... Show MoreRecognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on u
... Show MoreThere has been a great deal of research into the considerable challenge of managing of traffic at road junctions; its application to vehicular ad hoc network (VANET) has proved to be of great interest in the developed world. Dynamic topology is one of the vital challenges facing VANET; as a result, routing of packets to their destination successfully and efficiently is a non-simplistic undertaking. This paper presents a MDORA, an efficient and uncomplicated algorithm enabling intelligent wireless vehicular communications. MDORA is a robust routing algorithm that facilitates reliable routing through communication between vehicles. As a position-based routing technique, the MDORA algorithm, vehicles' precise locations are used to establish th
... Show More