Background: Rheumatoid arthritis is a chronic destructive inflammatory disease associated with destruction of joint connective tissues and bones, affecting 0.5%–1% of the population worldwide reporting higher prevalence of periodontitis among rheumatoid arthritis patients. The purpose of this study is to estimate level of salivary C-reactive protein in relation to the occurrence and severity of the periodontal disease and other oral parameters among group of patients with rheumatoid arthritis Material and methods: Fifty women patients with rheumatoid arthritis; twenty five on Methotrexate treatment and twenty five on combination treatment of Methotrexate and Etanercept selected as study groups with an age range (30-40) years old and twenty five gender, age and Body Mass Index matched healthy looking persons were selected as control. The diagnosis and recording of periodontal condition recorded through the application of community periodontal index according to WHO1997.Collection of unstimulated salivary samples was carried out under standard conditions, in addition to estimation of salivary C-reactive protein. Results: Regarding count of sextants with community periodontal index, median count of sextant with CPI-score 0 was highest among controls (2) and lowest among both rheumatoid arthritis cases (0).The median count of sextant with CPI-score 3 was lowest among controls (0) and highest among both RA cases (2) and the difference observed in median count of sextant with CPI-score 3 between three groups was statistically significant (p< 0.01).The mean rank of salivary C-reactive protein was highest among controls 39.7mg/L However, the difference was not significant between three groups (P>0.05). Conclusion: The results of the current research revealed that periodontal diseases were higher among rheumatoid arthritis patients without impact of both treatments on periodontal health without significant role of salivary C-reactive protein clinically in assessment of disease activity.
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In this article, we developed a new loss function, as the simplification of linear exponential loss function (LINEX) by weighting LINEX function. We derive a scale parameter, reliability and the hazard functions in accordance with upper record values of the Lomax distribution (LD). To study a small sample behavior performance of the proposed loss function using a Monte Carlo simulation, we make a comparison among maximum likelihood estimator, Bayesian estimator by means of LINEX loss function and Bayesian estimator using square error loss (SE) function. The consequences have shown that a modified method is the finest for valuing a scale parameter, reliability and hazard functions.
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تم استخدام خرائط ضبط الجودة الإحصائية لتقييم جودة الخدمة التعليمية في جامعة الباحة، ويهدف هذا البحث إلى استخدام خرائط ضبط الجودة الإحصائية لقياس مستوى الجودة وفجوة الجودة بين توقعات الطلبة وإدراكاتهم لمستوى الخدمة الذي تقدمه جامعة الباحة. حيث تم اختيار عينة من 200 طالب وطالبة عشوائيا باستخدام العشوائية العنقودية من 4 كليات خلال الفترة 01 – 30/2015م، وجمعت البيانات من خلال استبيان جودة الخدمة الذي يقيس ت
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Background: Marginal adaptation is critical for long – term success of crown and bridge restoration. Computer aided design / computer aided manufacture (CAD/ CAM) system is gaining more importance in the fabrication of dental restoration. Objective: The aim of this study is to evaluate the effect of crystallization firing on the vertical marginal gap of IPS. emax CAD crowns which fabricated with two different CAD/CAM systems .Materials and Methods: Twenty IPS e.max CAD crowns were fabricated. We had two major groups (A, B) (10 crowns for each group) according to the CAD/CAM system being used: Group A: fabricated with Imes - Icore CAD/CAM system; Group B: fabricated with In Lab Sirona CAD/CAM system. Each group was subdivided into two s
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme
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