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.
Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff
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This paper presents calculat,ion of thermal conductivity (K) of palm
leaf experimentally using Lee s disc method to be used as thermal
insulator. The therma l conducti vity is found to be equal to (k=0.03W/mK)
indicating that palm l eaf is a good thermal insulator com pared to the other insulators. The effect of the thermal insulator thickness on temperature di lTt::rence, heat transfer coefficient, thermal conductance, thermal resistance, thermal insulation are in vestigated in this paper. It was found that
... Show MoreRivest Cipher 4 (RC4) is an efficient stream cipher that is commonly used in internet protocols. However, there are several flaws in the key scheduling algorithm (KSA) of RC4. The contribution of this paper is to overcome some of these weaknesses by proposing a new version of KSA coined as modified KSA . In the initial state of the array is suggested to contain random values instead of the identity permutation. Moreover, the permutation of the array is modified to depend on the key value itself. The proposed performance is assessed in terms of cipher secrecy, randomness test and time under a set of experiments with variable key size and different plaintext size. The results show that the RC4 with improves the randomness and secrecy with
... Show MoreIn this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N
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This paper explores VANET topics: architecture, characteristics, security, routing protocols, applications, simulators, and 5G integration. We update, edit, and summarize some of the published data as we analyze each notion. For ease of comprehension and clarity, we give part of the data as tables and figures. This survey also raises issues for potential future research topics, such as how to integrate VANET with a 5G cellular network and how to use trust mechanisms to enhance security, scalability, effectiveness, and other VANET features and services. In short, this review may aid academics and developers in choosing the key VANET characteristics for their objectives in a single document.
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Understanding the compatibility between spider silk and conducting materials is essential to advance the use of spider silk in electronic applications. Spider silk is tough, but becomes soft when exposed to water. Here we report a strong affinity of amine-functionalised multi-walled carbon nanotubes for spider silk, with coating assisted by a water and mechanical shear method. The nanotubes adhere uniformly and bond to the silk fibre surface to produce tough, custom-shaped, flexible and electrically conducting fibres after drying and contraction. The conductivity of coated silk fibres is reversibly sensitive to strain and humidity, leading to proof-of-concept sensor and actuator demonstrations.
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