Introduction: This study was performed to compare the effect of Fractional CO2 laser or Q switched Nd:YAG laser of surface treatment on the shear bond strength of zirconia-porcelain interface. Methods: Fractional CO2 laser at 30 W, 2 ms, time interval 1 ms, distance between spots 0.3 mm, and number of scans is (4) or Q switched Nd:YAG laser at 30 J/mm2 and 10 Hz were used to assess the shear bond strength of zirconia to porcelain. Pre-sintered zirconia specimens were divided into three groups (n = 10) according to the surface treatment technique used: (a) untreated (Control) group; (b) CO2 group; (c) Nd:YAG group. All samples were then sintered and veneered with porcelain according to the manufacturer’s instructions. Surface morph

Background: For decades, the use of naturally accessible materials in treating human disease has been widespread. The goal of this study was to determine the anti-fungal effectiveness /of the lemongrass essential oil (LGEO) versus Candida albicans (C. albicans) adhesion to polymethylmethacrylate (PMMA) materials. Material and methods: LGEO's anti-fungal activity was tested against C. albicans adhesion using the following concentration of LGEO in PMMA monomer (2.5 vol. %, 5 vol. % LGEO) selected from the pilot study as the best two effective concentrations. A total of 40 specimens were fabricated for the candida adherence test and were subdivided into four equal groups: negative control 0 vol. % addition, experimental with 2.5 vol. % and

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

Biologically active natural compounds are molecules produced by plants or plant-related microbes, such as endophytes. Many of these metabolites have a wide range of antimicrobial activities and other pharmaceutical properties. This study aimed to evaluate (in vitro) the antifungal activities of the secondary metabolites obtained from Paecilomyces sp. against the pathogenic fungus Rhizoctonia solani. The endophytic fungus Paecilomyces was isolated from Moringa oleifera leaves and cultured on potato dextrose broth for the production of the fungal metabolites. The activity of Paecilomyces filtrate against the radial growth of Rhizoctonia solani was tested by mixing the filtrate with potato dextrose agar medium at concentrations of 15%,

Biologically active natural compounds are molecules produced by plants or plant-related microbes, such as endophytes. Many of these metabolites have a wide range of antimicrobial activities and other pharmaceutical properties. This study aimed to evaluate (in vitro) the antifungal activities of the secondary metabolites obtained from Paecilomyces sp. against the pathogenic fungus Rhizoctonia solani. The endophytic fungus Paecilomyces was isolated from Moringa oleifera leaves and cultured on potato dextrose broth for the production of the fungal metabolites. The activity of Paecilomyces filtrate against the radial growth of Rhizoctonia solani was tested by mixing the filtrate with potato dextrose agar medium at concentrations of 15%,