Background and Objectives: Wound healing is a complex process with overlapping phases haemostasis, inflammation, proliferation and maturation/matrix remodeling. Each phase of wound healing requires different management strategies, and inappropriate treatment can delay wound healing. The aim of the present study was to evaluate the efficacy of topical application of calmodulin as a significant augmentation of the granulation tissue production process of wound healing and to express of genes CaMKK2, MaP2K6 and CXCR4 at site of wound defect, that have versatile effects on the body and they belong to Ca/camodulin related genes. Material and Methods: In this study thirty albino male rats, weighting (300-400) gram, aged (6-8) months, wil

Background: Wound healing is a complex dynamical interaction between various cell types, the extracellular matrix, cytokines, and growth factors. osteoponetin is a substance that acts as an anti-inflammatory. Aims of study: The study was designed to identify the role of local exogenous applications of osteopontin on wound healing (in cheek skin). Materials and methods: Thirty adult male albino rats weighting an average of (250-300gm) used in this study, incisional wounds were made in the skin of the cheek of rat and they were divided into the following groups: A-Control group: 15 rats treated with 1µ l of normal saline B-Experimental groups: 15 rats treated with topical application of 1µl osteopontin. The scarification of animals we

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

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing