Background: Dental casts come into direct contact with impression materials and other items that are contaminated by saliva and blood from a patient's mouth, leaving the casts susceptible to cross-contamination. The disinfectant solutions of the impression materials cause various adverse reactions. Therefore, disinfection of dental casts may be effective in preventing cross infection. This study was carried out to evaluate the surface hardness, dimensional accuracy, reproduction of details and surface porosity of type III, type IV and type IV extra hard dental stone after immersion in and spray by using SOLO and Sodium hypochlorite disinfectant solutions. Materials and methods: 240 Stone samples were prepared in rubber rings, A total of 60

Background: Dental casts come into direct contact with impression materials and other items that are contaminated by saliva and blood from a patient's mouth, leaving the casts susceptible to cross-contamination. The disinfectant solutions of the impression materials cause various adverse reactions. Therefore, disinfection of dental casts may be effective in preventing cross infection. This study was carried out to evaluate the surface hardness, dimensional accuracy, reproduction of details and surface porosity of type III, type IV and type IV extra hard dental stone after immersion in and spray by using SOLO and Sodium hypochlorite disinfectant solutions. Materials and methods: 240 Stone samples were prepared in rubber rings, A total of 60

Dental casts come into direct contact with impression materials and other items that are contaminated by saliva and blood from a patient's mouth, leaving the casts susceptible to cross-contamination. The disinfectant solutions of the impression materials cause various adverse reactions. Therefore, disinfection of dental casts may be effective in preventing cross infection. This study was carried out to evaluate the surface hardness, dimensional accuracy, reproduction of details and surface porosity of type III, type IV and type IV extra hard dental stone after immersion in and spray by using SOLO and Sodium hypochlorite disinfectant solutions. Materials and methods: 240 Stone samples were prepared in rubber rings, A total of 60 test block w

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

This study aims to evaluate the influence of the air abrasion of dentin on the shear bond strength of lithium disilicate using three different types of luting cements. Sixty cylindrical specimens were milled from lithium disilicate CAD/CAM blocks (IPSe.max CAD). Sixty sound human maxillary premolar teeth were decoronated to the level of peripheral dentin, then randomly divided into three groups according to the type of luting cement used for the cementation of the lithium disilicate specimens (n = 20); Group A: Glass ionomer cement (Riva Self- Cure); Group B: Adhesive resin cement (Rely X Ultimate); Group C: Self-adhesive resin cement (Rely X U200). Each group was then further subdivided into two subgroups (n=10); Subgroups AI, BI, and CI,

In this article, the nonlinear problem of Jeffery-Hamel flow has been solved analytically and numerically by using reliable iterative and numerical methods. The approximate solutions obtained by using the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM). The obtained solutions are discussed numerically, in comparison with other numerical solutions obtained from the fourth order Runge-Kutta (RK4), Euler and previous analytic methods available in literature. In addition, the convergence of the proposed methods is given based on the Banach fixed point theorem. The results reveal that the presented methods are reliable, effective and applicable to solve other nonlinear problems.

An analytical model in the form of a hyperbolic function has been suggested for the axial potential distribution of an electrostatic einzel lens. With the aid of this hyperbolic model the relative optical parameters have been computed and investigated in detail as a function of the electrodes voltage ratio for various trajectories of an accelerated charged-particles beam. The electrodes voltage ratio covered a wide range where the lens may be operated at accelerating and decelerating modes. The results have shown that the proposed hyperbolic field has the advantages of producing low aberrations under various magnification conditions and operational modes. The electrodes profile and their three-dimensional diagram have been determined whi

The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o