Background: the aim of this study was to evaluate the effect of different surface acids treatments (37%phospjoric acid, 5%hydrofluoric acid, 1.23 acidulated phosphate fluoride) of feldspathic ceramic VITA 3D MASTER , and the effect of thermocycling on shear bond strength using a ceramic repair kit (ivoclar/vivadent). Material and Methods: sixty Nickel-Chromium metal base plates were prepared(9mm diameter,3mm depth) using lost wax technique, 2mm thick layer of ceramic(VITA 3D MASTER) fused to metal plates, all specimens were embedded in acrylic resin blocks except their examined surfaces and divided into 3 main groups 20 specimens each, Grp A: treatment with 37%phosphoric acid for 2 mins, Grp B: etching with 5% hydrofluoric acid for 2mins,

The gas sensing properties of Co3O4and Co3O4:Y nano structures were investigated. The films were synthesized using the hydrothermal method on a seeded layer. The XRD, SEM analysis and gas sensing properties were investigated for Co3O4and Co3O4:Y thin films. XRD analysis shows that all films are polycrystalline in nature, having a cubic structure, and the crystallite size is (11.7)nm for cobalt oxide and (9.3)nm for the Co3O4:10%Y. The SEM analysis of thin films obviously indicates that Co3O4possesses a nanosphere-like structure and a flower-like structure for Co3O4:Y.The sensitivity, response time and recovery time to a H2S reducing gas were tested at different operating

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on