Aim: To evaluate the wettability and microhardness of Zirconium (ZrO2) dental material when coated with different concentrations of Faujasite. Materials and methods: 30 circular disks produced from ZrO2, then each group is classified into 10 control groups, 10 coated groups with 3% Faujasite, and 10 coated groups with 7% faujasite by electro-spun tool to study variable properties in hardness and water contact angle of implant materials. Results: This study stated the high hardness in 7% of faujasite concentration for ZrO2, in addition, the contact angle decreased gradually until reach 0 ᵒ in 7% concentration of faujasite with ZrO2 Conclusion: Water contact angle (WCA) declined till disappeared in (7% wt.) of faujasite coated with the Z

The conception and experimental assessment of a removable friction-based shear connector (FBSC) for precast steel-concrete composite bridges is presented. The FBSC uses pre-tensioned high-strength steel bolts that pass through countersunk holes drilled on the top flange of the steel beam. Pre-tensioning of the bolts provides the FBSC with significant frictional resistance that essentially prevents relative slip displacement of the concrete slab with respect to the steel beam under service loading. The countersunk holes are grouted to prevent sudden slip of the FBSC when friction resistance is exceeded. Moreover, the FBSC promotes accelerated bridge construction by fully exploiting prefabrication, does not raise issues relevant to precast co

This work analyzes the effectiveness of an artificial intelligence (AI) community- building workshop designed for high school teachers and it focuses on contemporary issues related to AI concepts and applications. A group of high school teachers from local education districts attended a one-day AI hands-on workshop at our university. The workshop included several AI-related topics and hands-on examples and exercises aiming to introduce AI concepts and tools relevant to pre-college education. The participating teachers were expected to become a part of a collaborative network created to design, develop, and implement novel AI learning modules for high school students. Initial and a post-training surveys have been used to measure the

Magnesium hydroxide was used as flame inhibitor to increased flame resistance for tires .Magnesium hydroxide was adding with (5%,10%) weight percents to rubber master batch of tire and then exposed the resulting material to a flame generated from gas torch with (10 mm) exposure distance . Method of measuring the surface temperature opposite to the flame was used to determine the heat transferred through tire material. The results were obtained shows enhanced flame resistance for tire by added magnesium hydroxide and this resistance increased by increasing hydroxide Percentage .

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re