Background: Mouth breathing can lead to introduce cold, dry unprepared air that insults the tissue of oral cavity, nasopharynx and lung, leading in turn to pathological changes in oronasal cavity, nasopharyngeal and other respiratory tissue, mouth breathing associated with nasal obstruction may lead to many health problems, in particular oral health problems such as inflammation of gingiva, oral dryness, change in oral environment that may decrease pH, salivary flow rate and increase bacteria and dental caries.Aims of the present study were to assess the oral health condition among mouth breather associated with nasal obstruction, including dental caries, oral cleanliness and gingival health condition as well as to evaluate the changes in salivary physical characteristics and salivary mutans streptococci counts, and their relation to oral variables in comparison to a control group. Materials and Methods: Thirty patients with mouth breathing associated with nasal obstruction (15 females and 15 males) were selected as a study group with an age range (18-22) years old, all subjects were examined by ENT specialist to confirm mouth breathing. A 30 gender and age matched healthy looking subjects without nasal obstruction were selected as control. The diagnosis and recording of dental caries was according to severity of dental caries lesion through the application of D1_4MFS(Manji et al., 1989). Plaque index of (Silness and Loe, 1964) was used for plaque assessment; gingival index of (Loe and Silness, 1963) was used for gingival health condition assessment. Stimulated salivary samples were collected according to (Tenovuo and Lagerlof, 1996) and the following variables were recorded: microbiological analysis included the salivary counts of mutans streptococci, salivary flow rate, salivary pH (potential of hydrogen) and then measurement of salivary viscosity by using Ostwald's viscometer. Results: Results of the present study showed that the mouth breathing group had statistically highly significant, higher plaque and gingival indices than nose breathing group (P<0.01) with a positive highly significant correlation between them in mouth breathing and nose breathing groups (r=0.56, r= 0.64, respectively).The salivary flow rate was lower among mouth breathing with highly significant difference than nose breathing (P<0.01), also salivary pH was lower among mouth breathing but with significant differencecompare to nose breathing (P<0.05); statistically a negative highly significant correlation was recorded among mouth breathing group between salivary flow rate with gingival index (r= -0.56). It has been found that salivary viscosity was not statistically significant difference between mouth breathing group and nose breathing group. The salivary viscosity was found to be inversely significantly correlated with salivary flow rate among mouth breathing group (r= -0.38). While it was positively not significantly correlated with plaque index, gingival index and counts of mutans streptococci among mouth breathing group. Data analysis of the present study showed that salivary mutans streptococci counts among mouth breathing group were higher than that among nose breathing group, difference was statistically highly significant (P<0.01). Conclusion: Mouth breathing associated with nasal obstruction may have an effect on oral health status, leading to an increase in periodontal disease and changes in dental caries.
In this paper an improved weighted 0-1 knapsack method (WKM) is proposed to optimize the resource allocation process when the sum of items' weight exceeds the knapsack total capacity .The improved method depends on a modified weight for each item to ensure the allocation of the required resources for all the involved items. The results of the improved WKM are compared to the traditional 0-1 Knapsack Problem (KP). The proposed method dominates on the other one in term of the total optimal solution value of the knapsack .
The question about the existence of correlation between the parameters A and m of the Paris function is re-examined theoretically for brittle material such as alumina ceramic (Al2O3) with different grain size. Investigation about existence of the exponential function which fit a good approximation to the majority of experimental data of crack velocity versus stress intensity factor diagram. The rate theory of crack growth was applied for data of alumina ceramics samples in region I and making use of the values of the exponential function parameters the crack growth rate theory parameters were estimated.
This research aims to choose the appropriate probability distribution to the reliability analysis for an item through collected data for operating and stoppage time of the case study.
Appropriate choice for .probability distribution is when the data look to be on or close the form fitting line for probability plot and test the data for goodness of fit .
Minitab’s 17 software was used for this purpose after arranging collected data and setting it in the the program.
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... Show MoreTraumatic Brain Injury (TBI) is still considered a worldwide leading cause of mortality and morbidity. Within the last decades, different modalities were used to assess severity and outcome including Glasgow Coma Scale (GCS), imaging modalities, and even genetic polymorphism, however, determining the prognosis of TBI victims is still challenging requiring the emerging of more accurate and more applicable tools to surrogate other old modalities
In this study, effects of shisha smoking on some blood components were evaluated in (120) male adult mice. The animals were divided into four groups according to smoke types (cigarette, shisha, cigarette +shisha) in addition to control groups which exposed to fresh air only. A special inhalation chamber designed locally has been used to expose the animals. Exposed to cigarette smoke was done for 5 min/day while exposed to shisha smoke for 15 min /day /7days/weeks for 4,8,12 weeks. Blood samples were collected to evaluate some hematological variables. The results showed that RBC, WBC count, Hb, PCV, differential leukocyte (Lymphocyte, Monocyte, Neutrphils) were significantly high (P≤0.001) in groups which exposed to shisha smoke as comp
... Show MoreIn this study, we propose a suitable solution for a non-linear system of ordinary differential equations (ODE) of the first order with the initial value problems (IVP) that contains multi variables and multi-parameters with missing real data. To solve the mentioned system, a new modified numerical simulation method is created for the first time which is called Mean Latin Hypercube Runge-Kutta (MLHRK). This method can be obtained by combining the Runge-Kutta (RK) method with the statistical simulation procedure which is the Latin Hypercube Sampling (LHS) method. The present work is applied to the influenza epidemic model in Australia in 1919 for a previous study. The comparison between the numerical and numerical simulation res
... Show MoreExposure of reinforced concrete buildings to an accidental fire may result in cracking and loss in the bearing capacity of their major components, columns, beams, and slabs. It is a challenge for structural engineers to develop efficient retrofitting techniques that enable RC slabs to restore their structural integrity, after being exposed to intense fires for a long period of time. Experimental
investigation was carried out on twenty one slab specimens made of self compacting concrete, eighteen of them are retrofitted with CFRP sheets after burning and loading till failure while three of them (which represent control specimens) are retrofitted with CFRP sheet after loading till failure without burning. All slabs had been tested in a
Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
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