The creation and characterisation of biodegradable blend films based on chitosan and polyvinyl alcohol for application in a range of packaging is described. The compatibility between the chitosan and PVA polymers was good. Composite films had a compact and homogeneous structure, according to the morphology analysis. The mechanical test result of PVA/CH at concentrations 5% showed, that The higher values of TS recorded in sample (p1, with 40 MPa) while the lower values appeared in sample (p9, with 22.09 MPa), the TS decreased gradually as the amount of PVA increased in blend film. While the blend film of pure Chitosan exhibits a poor mechanical strength which makes it a poor candidate for packaging but Blending CH with PVA together improved

Background: The ideal maxillofacial prosthesis should have fine and thin boundaries that bindwith the surrounding facial structures and possess high tear strength.This study aims to determinethe best percentages of nanofiller (TiO2) and intrinsic pigment (silicone functional intrinsic) thatcould be mixed in as additives to improve the tear strength of Cosmesil M511 andVST50F siliconeelastomers with the least effect on their hardness.Materials and Methods: In this in vitro experimental study, a total of 80 samples, 40 for eachelastomer, were fabricated. Each elastomer sample was split into two equal groups to test for tearstrength and Shore A hardness. Each group consisted of 20 samples, including 10 control sampleswithout additives and 10 e

The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

Vancomycin Staphylococcus aureus (VRSA) is a strain of S. aureus that is considered the main cause of bacterial skin and soft tissue infections. It has acquired resistance to vancomycin and represents a therapeutic challenge. The current study aimed to compare the possible therapeutic effects of VRSA bacteriocin (VRSAcin) on the treatment of skin infection in mice with those of an antibiotic (linezolid). The results showed that of the fifty swabs obtained from human skin wounds. One isolate was selected for VRSAcin extraction depending on its antibiotic resistance using an antibiotic susceptibility test.An agar well diffusion test was used to determine bacteriocin’s antibacterial activity, as well as its a minimum inhibitory concentration

Background: Although bleaching is typically considered a safe procedure, various investigations have found minor negative effects and changes in mineral composition. The aim was to Evaluate and compare the efficacy of using Nanohydroxyapatite serum on surface microhardness of enamel surface before and after bleaching with chemically cured Boost bleaching. Material and methods: ten sound human permanent upper and lower premolar teeth were used and their roots were removed 2 mm apically to the cementoenamel junction, the crowns were sectioned mesiodistally into two halves buccal and lingual/palatal, the buccal surface was further subdivided into two halves. The samples were embeded in an acrylic resin, resulting in 30 specimens divide

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet