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.
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
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The flexible joint robot manipulators provide various benefits, but also present many control challenges such as nonlinearities, strong coupling, vibration, etc. This paper proposes optimal second order integral sliding mode control (OSOISMC) for a single link flexible joint manipulator to achieve robust and smooth performance. Firstly, the integral sliding mode control is designed, which consists of a linear quadratic regulator (LQR) as a nominal control, and switching control. This control guarantees the system robustness for the entire process. Then, a nonsingularterminal sliding surface is added to give a second order integral sliding mode control (SOISMC), which reduces chartering effect and gives the finite time convergence as well. S
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This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o
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The present paper attempts to detect the level of (COVID-19) pandemic panic attacks among university students, according to gender and stage variables.
To achieve this objective, the present paper adopts the scale set up by (Fathallah et al., 2021), which has been applied electronically to a previous cross-cultural sample consisting of (2285) participants from Arab countries, including Iraq. The scale includes, in its final form, (69) optional items distributed on (6) dimensions: physical symptoms (13) items, psychological and emotional symptoms (12) items, cognitive and mental symptoms (11) items, social symptoms (8) items, general symptoms (13) items and daily living practices (12) items
... Show MoreNowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order PIaDb (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of
... Show MoreCancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei
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This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,
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