Background: Marginal adaptation is critical for long – term success of crown and bridge restoration. Computer aided design / computer aided manufacture (CAD/ CAM) system is gaining more importance in the fabrication of dental restoration. Objective: The aim of this study is to evaluate the effect of crystallization firing on the vertical marginal gap of IPS. emax CAD crowns which fabricated with two different CAD/CAM systems .Materials and Methods: Twenty IPS e.max CAD crowns were fabricated. We had two major groups (A, B) (10 crowns for each group) according to the CAD/CAM system being used: Group A: fabricated with Imes - Icore CAD/CAM system; Group B: fabricated with In Lab Sirona CAD/CAM system. Each group was subdivided into two s

The research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.

      The impregnation method is used in test sample preparation, using molding by pressure presses.

      All samples were exposure to (Co⁶⁰) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.

      The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad

In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes