Abstract : Silicone elastomer is widely used as the material of choice for fabricating maxillofacial prosthesis. However, silicone properties are far from ideal; low tear strength, low tensile strength and insufficient elasticity are the most undesirable properties. The purpose of this study was to evaluate the effect of addition of nano SiO2filler on tear strength, tensile strength, elongation at break, hardness and color of Cosmesil M-511 HTV maxillofacial silicone elastomer. Nano SiO2was added to the silicone base in concentrations of 4%, 5% and 6% by weight. Silicone with 0% nano filler served as a control. Tear test was done according to ISO 34-1. Tensile and elongation test was done according to ISO 37. Shore A hardness test was done

In the present research, the electrical properties which included the ac-conductivity (σac), loss tangent of dielectric (tan δ) and real dielectric constant (ε’) are studied for nano polycarbonate in different pressures and frequencies as a function of temperature these properties were studied at selective temperature gradients which are (RT-50-100-150-250)°C. The results of the study showed that the values of dielectric constant and dissipation factor increase with increasing pressure and temperature and decreases by increasing frequency. And the results of electrical conductivity showed that it increases with increasing temperature, pressure and frequency.

Background: tooth debonding was one of the major reasons for denture repair. With the use of recently introduced thermoplastic denture base materials the problem of tooth debonding increased due to the nature of the bond between these materials and the acrylic teeth. This study was aimed to assess the bond of the acrylic teeth to conventional heat cure acrylic resin and to thermoplastic resin denture base material and methods to enhance it. Materials and methods: acrylic resin teeth were bonded to heat cure acrylic resin with and without wetting the ridge laps of the teeth with monomer and acrylic teeth with prefabricated retentive holes, unmodified and modified, in their ridge laps were processed with Valplast thermoplastic resin denture b

The choice of binary Pseudonoise (PN) sequences with specific properties, having long period high complexity, randomness, minimum cross and auto- correlation which are essential for some communication systems. In this research a nonlinear PN generator is introduced . It consists of a combination of basic components like Linear Feedback Shift Register (LFSR), ?-element which is a type of RxR crossbar switches. The period and complexity of a sequence which are generated by the proposed generator are computed and the randomness properties of these sequences are measured by well-known randomness tests.

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

Sub-threshold operation has received a lot of attention in limited performance applications.However, energy optimization of sub-threshold circuits should be performed with the concern of the performance limitation of such circuit. In this paper, a dual size design is proposed for energy minimization of sub-threshold CMOS circuits. The optimal downsizing factor is determined and assigned for some gates on the off-critical paths to minimize the energy at the maximum allowable performance. This assignment is performed using the proposed slack based genetic algorithm which is a heuristic-mixed evolutionary algorithm. Some gates are heuristically assigned to the original and the downsized design based on their slack time determined by static tim