Background: Dental caries is a disease occurs in the world in both developed and developing countries, it is still widespread among children and it can be controlled but not eliminated , most of tooth loss occurs due to dental caries and its complications. The aim of this study was to estimate the occurrence, and severity of dental caries and treatment needs among kindergarten children in Al-Basrah governorate. Materials and methods: The sample consisted of 1000 kindergarten children at age of 4-5 years old (445 boys and 555 girls) from urban areas in Al-Basrah city. Diagnosis and recording of dental caries and treatment needs were done according to the criteria of WHO (1987). Results: The percentage of dental caries was (80.8%) of the tota

Background: Knowledge is considered to be essential for developing healthy practices and preventing the main oral diseases. In some developing countries, women were at higher risk to develop these diseases. This study was conducted to evaluate women’s dental knowledge and practices through a specific questionnaire and the relationship with patient’s educational level and the number of their children. Subjects and method: Women, aged from 25-35 years old, were selected to participate in the current study. They were attending dental clinics in the teaching hospital of Baghdad University. Each participant was instructed to answer questionnaire sheet which is previously prepared in Arabic language by the authors. The total numb

Abstract: Recombinant human bone morphogenetic protein-2 (rhBMP-2) and platelet-rich fibrin (PRF) bioactive materials have been used to enhance healing and improve dental implant stability. This study aimed to compare the effect of rhBMP-2 and PRF bioactive materials on dental implant stability at different intervals and to evaluate the correlation of implant length and diameter with implant stability. Two bioactive materials were compared to evaluate their effect on dental implant stability. A total of 32 patients (102 dental implants) were divided into 3 groups: 24 dental implants with bone morphogenetic protein (BMP), 27 dental implants with PRF, and 51 dental implants without BMP or PRF (control group). Data were statistically analyzed

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

Nanoparticles of Pb_1-xCd_xS within the composition of 0≤x≤1 were prepared from the reaction of aqueous solution of cadmium acetate, lead acetate, thiourea, and NaOH by chemical co-precipitation. The prepared samples were characterized by UV-Vis spectroscopy(in the range 300-1100nm) to study the optical properties, AFM and SEM to check the surface morphology(Roughness average and shape) and the particle size. XRD technique was used to determine the crystalline structure, XRD technique was used to determine the purity of the phase and the crystalline structure, The crystalline size average of the nanoparticles have been found to be 20.7, 15.48, 11.9, 11.8, and 13.65 nm for PbS, Pb_0.75Cd_0.25S,

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In