Background: University dental students perceived a higher level of stress prior to the final exam associated with raised salivary cortisol levels which could be considered as a useful noninvasive biomarker for measuring acute stress. Using a Helkimo anamnestic and clinical dysfunction scoring for temporomandibular disorders can give a better insight about the association of this marker and temporomandibular joint disorders. The aim of this study was to evaluation level of salivary cortisol in stressor students with temporomandibular disorder and the relation between this marker in relation to temporomandibular disorder severity. This might give a better understanding to the role of psychological stress as an etiological factor for developing temporomandibular joint problems. Materials and methods: A total eighty participants age between 20 to 24 were recruited for this study. The participants were University dental students under graduate students at final examination period who were examined and gave saliva samples in final examination period. Salivary assay kits as cortisol was used to measure those variables and a Helkimo anamnestic and clinical dysfunction scoring for TMD. Results: The group of participants with stress and temporomandibular disorder showed significantly higher levels of salivary cortisol than the control group, the salivary cortisol has statistically significant correlation with Helkimo anamnestic categories (Di-I mild, Di-II moderate and Di-III severe. Salivary cortisol levels show significant but weak association with two categories of clinical dysfunction criteria in Helkimo index system, which are Muscle pain and TMJ pain on palpation. Conclusion: This study demonstrated that University students perceived a high level of stress before the final examination. Salivary cortisol is the stress biomarker that is most often used to measure acute stress. Helkimo anamnestic and clinical dysfunction scoring criteria for still the pioneer for measuring a temporomandibular disorder.
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.
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
... Show MoreThe new compounds of pyrazolines were synthesized from the reaction of different acid hydrazide with ethylacetoacetate and ethanol under reflux. These compounds were obtained from many sequence reactions. The 4-acetyl-5-methyl-2,4-dihydro-3H-pyrazol-3-one compounds synthesized from the reaction of 5-methyl-2,4-dihydro-3H-pyrazol-3-one with acetyl chloride in calcium hydroxide and 1,4-dioxane. Finaly, Schiff bases were prepared via condensation reaction of products of mono- and tri ketone derivatives[IV]a, b with phenyl hydrazines as presented in (Scheme 1, 2). The synthesized compounds were identification by using FTIR, NMR and Mass spectroscopy (of some of them).
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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