Background: University dental students perceived a higher level of stress prior to the final exam associated with raised salivary alpha-amylase 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 disorders. The aim of this study was to evaluation level of salivary alpha-amylase in stressor students with temporomandibular disorders and the relation between the marker in relation to temporomandibular disorders 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 aged 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 alpha-amylase was used to measure those variable and a Helkimo anamnestic and clinical dysfunction scoring for temporomandibular disorders. Results: The group of participants with stress and temporomandibular disorders showed significantly higher levels of salivary alpha-amylase than the control group, the salivary alpha-amylase has statistically non-significant correlation with Helkimo anamnestic categories (Di-I mild, Di-II moderate and Di-III severe. Salivary alpha-amylase levels show non-significant and weak association with two categories of clinical dysfunction criteria in Helkimo index system, which are Muscle pain and temporomandibular joint pain on palpation. Conclusion: This study concluded that University students perceived a high level of stress before the final examination. Salivary alpha-amylase is now 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 TMD.
This paper considers a new Double Integral transform called Double Sumudu-Elzaki transform DSET. The combining of the DSET with a semi-analytical method, namely the variational iteration method DSETVIM, to arrive numerical solution of nonlinear PDEs of Fractional Order derivatives. The proposed dual method property decreases the number of calculations required, so combining these two methods leads to calculating the solution's speed. The suggested technique is tested on four problems. The results demonstrated that solving these types of equations using the DSETVIM was more advantageous and efficient
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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Pollutants generation is strongly dependant on the firing temperature and reaction rates of the gaseous reactants in the gas turbine combustion chamber. An experimental study is conducted on a two-shaft T200D micro-gas turbine engine in order to evaluate the impact of injecting ethanol directly into the compressor inlet air on the exhaust emissions. The study is carried out in constant speed and constant load engine tests. Generally, the results showed that when ethanol was added in a concentration of 20% by volume of fuel flow; NOx emission was reduced by the half, while CO and UHC emissions were almost doubled with respect to their levels when burning conventional LPG fuel alone.
CD40 is a type 1 transmembrane protein composed of 277 amino acids, and it belongs to the tumor necrosis factor receptor (TNFR) superfamily. It is expressed in a variety of cell types, including normal B cells, macrophages, dendritic cells, and endothelial cells, as a costimulatory molecule. This study aims to summarize the CD40 polymorphism effect and its susceptibility to immune-related disorders. The CD40 gene polymorphisms showed a significant association with different immune-related disorders and act as a risk factor for increased susceptibility to these diseases.
This paper considers a new Double Integral transform called Double Sumudu-Elzaki transform DSET. The combining of the DSET with a semi-analytical method, namely the variational iteration method DSETVIM, to arrive numerical solution of nonlinear PDEs of Fractional Order derivatives. The proposed dual method property decreases the number of calculations required, so combining these two methods leads to calculating the solution's speed. The suggested technique is tested on four problems. The results demonstrated that solving these types of equations using the DSETVIM was more advantageous and efficient
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This paper presents comprehensive analysis and investigation for 1550nm and 1310nm ring optical modulators employing an electro-optic polymer infiltrated silicon-plasmonic hybrid phase shifter. The paper falls into two parts which introduce a theoretical modeling framework and performance assessment of these advanced modulators, respectively. In this part, analytical expressions are derived to characterize the coupling effect in the hybrid phase shifter, transmission function of the modulator, and modulator performance parameters. The results can be used as a guideline to design compact and wideband optical modulators using plasmonic technology
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